WorldWideScience

Sample records for wind parameter estimates

  1. Modeling and Parameter Estimation of a Small Wind Generation System

    Directory of Open Access Journals (Sweden)

    Carlos A. Ramírez Gómez

    2013-11-01

    Full Text Available The modeling and parameter estimation of a small wind generation system is presented in this paper. The system consists of a wind turbine, a permanent magnet synchronous generator, a three phase rectifier, and a direct current load. In order to estimate the parameters wind speed data are registered in a weather station located in the Fraternidad Campus at ITM. Wind speed data were applied to a reference model programed with PSIM software. From that simulation, variables were registered to estimate the parameters. The wind generation system model together with the estimated parameters is an excellent representation of the detailed model, but the estimated model offers a higher flexibility than the programed model in PSIM software.

  2. Wind Climate Parameters for Wind Turbine Fatigue Load Assessment

    DEFF Research Database (Denmark)

    Toft, Henrik Stensgaard; Svenningsen, Lasse; Moser, Wolfgang

    2016-01-01

    Site-specific assessment of wind turbine design requires verification that the individual wind turbine components can survive the site-specific wind climate. The wind turbine design standard, IEC 61400-1 (third edition), describes how this should be done using a simplified, equivalent wind climate...... climate required by the current design standard by comparing damage equivalent fatigue loads estimated based on wind climate parameters for each 10 min time-series with fatigue loads estimated based on the equivalent wind climate parameters. Wind measurements from Boulder, CO, in the United States...

  3. Reliability Estimation of Parameters of Helical Wind Turbine with Vertical Axis

    Directory of Open Access Journals (Sweden)

    Adela-Eliza Dumitrascu

    2015-01-01

    Full Text Available Due to the prolonged use of wind turbines they must be characterized by high reliability. This can be achieved through a rigorous design, appropriate simulation and testing, and proper construction. The reliability prediction and analysis of these systems will lead to identifying the critical components, increasing the operating time, minimizing failure rate, and minimizing maintenance costs. To estimate the produced energy by the wind turbine, an evaluation approach based on the Monte Carlo simulation model is developed which enables us to estimate the probability of minimum and maximum parameters. In our simulation process we used triangular distributions. The analysis of simulation results has been focused on the interpretation of the relative frequency histograms and cumulative distribution curve (ogive diagram, which indicates the probability of obtaining the daily or annual energy output depending on wind speed. The experimental researches consist in estimation of the reliability and unreliability functions and hazard rate of the helical vertical axis wind turbine designed and patented to climatic conditions for Romanian regions. Also, the variation of power produced for different wind speeds, the Weibull distribution of wind probability, and the power generated were determined. The analysis of experimental results indicates that this type of wind turbine is efficient at low wind speed.

  4. Reliability Estimation of Parameters of Helical Wind Turbine with Vertical Axis.

    Science.gov (United States)

    Dumitrascu, Adela-Eliza; Lepadatescu, Badea; Dumitrascu, Dorin-Ion; Nedelcu, Anisor; Ciobanu, Doina Valentina

    2015-01-01

    Due to the prolonged use of wind turbines they must be characterized by high reliability. This can be achieved through a rigorous design, appropriate simulation and testing, and proper construction. The reliability prediction and analysis of these systems will lead to identifying the critical components, increasing the operating time, minimizing failure rate, and minimizing maintenance costs. To estimate the produced energy by the wind turbine, an evaluation approach based on the Monte Carlo simulation model is developed which enables us to estimate the probability of minimum and maximum parameters. In our simulation process we used triangular distributions. The analysis of simulation results has been focused on the interpretation of the relative frequency histograms and cumulative distribution curve (ogive diagram), which indicates the probability of obtaining the daily or annual energy output depending on wind speed. The experimental researches consist in estimation of the reliability and unreliability functions and hazard rate of the helical vertical axis wind turbine designed and patented to climatic conditions for Romanian regions. Also, the variation of power produced for different wind speeds, the Weibull distribution of wind probability, and the power generated were determined. The analysis of experimental results indicates that this type of wind turbine is efficient at low wind speed.

  5. Assessing different parameters estimation methods of Weibull distribution to compute wind power density

    International Nuclear Information System (INIS)

    Mohammadi, Kasra; Alavi, Omid; Mostafaeipour, Ali; Goudarzi, Navid; Jalilvand, Mahdi

    2016-01-01

    Highlights: • Effectiveness of six numerical methods is evaluated to determine wind power density. • More appropriate method for computing the daily wind power density is estimated. • Four windy stations located in the south part of Alberta, Canada namely is investigated. • The more appropriate parameters estimation method was not identical among all examined stations. - Abstract: In this study, the effectiveness of six numerical methods is evaluated to determine the shape (k) and scale (c) parameters of Weibull distribution function for the purpose of calculating the wind power density. The selected methods are graphical method (GP), empirical method of Justus (EMJ), empirical method of Lysen (EML), energy pattern factor method (EPF), maximum likelihood method (ML) and modified maximum likelihood method (MML). The purpose of this study is to identify the more appropriate method for computing the wind power density in four stations distributed in Alberta province of Canada namely Edmonton City Center Awos, Grande Prairie A, Lethbridge A and Waterton Park Gate. To provide a complete analysis, the evaluations are performed on both daily and monthly scales. The results indicate that the precision of computed wind power density values change when different parameters estimation methods are used to determine the k and c parameters. Four methods of EMJ, EML, EPF and ML present very favorable efficiency while the GP method shows weak ability for all stations. However, it is found that the more effective method is not similar among stations owing to the difference in the wind characteristics.

  6. Hierarchical parameter estimation of DFIG and drive train system in a wind turbine generator

    Institute of Scientific and Technical Information of China (English)

    Xueping PAN; Ping JU; Feng WU; Yuqing JIN

    2017-01-01

    A new hierarchical parameter estimation method for doubly fed induction generator (DFIG) and drive train system in a wind turbine generator (WTG) is proposed in this paper.Firstly,the parameters of the DFIG and the drive train are estimated locally under different types of disturbances.Secondly,a coordination estimation method is further applied to identify the parameters of the DFIG and the drive train simultaneously with the purpose of attaining the global optimal estimation results.The main benefit of the proposed scheme is the improved estimation accuracy.Estimation results confirm the applicability of the proposed estimation technique.

  7. Extreme wind estimate for Hornsea wind farm

    DEFF Research Database (Denmark)

    Larsén, Xiaoli Guo

    The purpose of this study is to provide estimation of the 50-year winds of 10 min and 1-s gust value at hub height of 100 m, as well as the design parameter shear exponent for the Hornsea offshore wind farm. The turbulence intensity required for estimating the gust value is estimated using two...... approaches. One is through the measurements from the wind Doppler lidar, WindCube, which implies serious uncertainty, and the other one is through similarity theory for the atmospheric surface layer where the hub height is likely to belong to during strong storms. The turbulence intensity for storm wind...... strength is taken as 0.1. The shear exponents at several heights were calculated from the measurements. The values at 100 m are less than the limit given by IEC standard for all sectors. The 50-year winds have been calculated from various global reanalysis and analysis products as well as mesoscale models...

  8. Wind Resource Estimation using QuikSCAT Ocean Surface Winds

    DEFF Research Database (Denmark)

    Xu, Qing; Zhang, Guosheng; Cheng, Yongcun

    2011-01-01

    In this study, the offshore wind resources in the East China Sea and South China Sea were estimated from over ten years of QuikSCAT scatterometer wind products. Since the errors of these products are larger close to the coast due to the land contamination of radar backscatter signal...... and the complexity of air-sea interaction processes, an empirical relationship that adjusts QuikSCAT winds in coastal waters was first proposed based on vessel measurements. Then the shape and scale parameters of Weibull function are determined for wind resource estimation. The wind roses are also plotted. Results...

  9. Evaluation of wind power production prospective and Weibull parameter estimation methods for Babaurband, Sindh Pakistan

    International Nuclear Information System (INIS)

    Khahro, Shahnawaz Farhan; Tabbassum, Kavita; Soomro, Amir Mahmood; Dong, Lei; Liao, Xiaozhong

    2014-01-01

    Highlights: • Weibull scale and shape parameters are calculated using 5 numerical methods. • Yearly mean wind speed is 6.712 m/s at 80 m height with highest in May 9.595 m/s. • Yearly mean WPD is 310 W/m 2 and available energy density is 2716 kWh/m 2 at 80 m height. • Probability of higher wind speeds is more in spring and summer than in autumn and winter. • Estimated cost of per kWh of electricity from wind is calculated as 0.0263 US$/kWh. - Abstract: Pakistan is currently experiencing an acute shortage of energy and urgently needs new sources of affordable energy that could alleviate the misery of the energy starved masses. At present the government is increasing not only the conventional energy sources like hydel and thermal but also focusing on the immense potential of renewable energy sources like; solar, wind, biogas, waste-to-energy etc. The recent economic crisis worldwide, global warming and climate change have also emphasized the need for utilizing economic feasible energy sources having lowest carbon emissions. Wind energy, with its sustainability and low environmental impact, is highly prominent. The aim of this paper is to explore the wind power production prospective of one of the sites in south region of Pakistan. It is worth mentioning here that this type of detailed analysis is hardly done for any location in Pakistan. Wind power densities and frequency distributions of wind speed at four different altitudes along with estimated wind power expected to be generated through commercial wind turbines is calculated. Analysis and comparison of 5 numerical methods is presented in this paper to determine the Weibull scale and shape parameters for the available wind data. The yearly mean wind speed of the considered site is 6.712 m/s and has power density of 310 W/m 2 at 80 m height with high power density during April to August (highest in May with wind speed 9.595 m/s and power density 732 W/m 2 ). Economic evaluation, to exemplify feasibility

  10. Weibull Distribution for Estimating the Parameters and Application of Hilbert Transform in case of a Low Wind Speed at Kolaghat

    Directory of Open Access Journals (Sweden)

    P Bhattacharya

    2016-09-01

    Full Text Available The wind resource varies with of the day and the season of the year and even some extent from year to year. Wind energy has inherent variances and hence it has been expressed by distribution functions. In this paper, we present some methods for estimating Weibull parameters in case of a low wind speed characterization, namely, shape parameter (k, scale parameter (c and characterize the discrete wind data sample by the discrete Hilbert transform. We know that the Weibull distribution is an important distribution especially for reliability and maintainability analysis. The suitable values for both shape parameter and scale parameters of Weibull distribution are important for selecting locations of installing wind turbine generators. The scale parameter of Weibull distribution also important to determine whether a wind farm is good or not. Thereafter the use of discrete Hilbert transform (DHT for wind speed characterization provides a new era of using DHT besides its application in digital signal processing. Basically in this paper, discrete Hilbert transform has been applied to characterize the wind sample data measured on College of Engineering and Management, Kolaghat, East Midnapore, India in January 2011.

  11. Mathematical Model to estimate the wind power using four-parameter Burr distribution

    Science.gov (United States)

    Liu, Sanming; Wang, Zhijie; Pan, Zhaoxu

    2018-03-01

    When the real probability of wind speed in the same position needs to be described, the four-parameter Burr distribution is more suitable than other distributions. This paper introduces its important properties and characteristics. Also, the application of the four-parameter Burr distribution in wind speed prediction is discussed, and the expression of probability distribution of output power of wind turbine is deduced.

  12. On-Line Flutter Prediction Tool for Wind Tunnel Flutter Testing using Parameter Varying Estimation Methodology, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — ZONA Technology, Inc. (ZONA) proposes to develop an on-line flutter prediction tool for wind tunnel model using the parameter varying estimation (PVE) technique to...

  13. Aerodynamic Parameters of High Performance Aircraft Estimated from Wind Tunnel and Flight Test Data

    Science.gov (United States)

    Klein, Vladislav; Murphy, Patrick C.

    1998-01-01

    A concept of system identification applied to high performance aircraft is introduced followed by a discussion on the identification methodology. Special emphasis is given to model postulation using time invariant and time dependent aerodynamic parameters, model structure determination and parameter estimation using ordinary least squares an mixed estimation methods, At the same time problems of data collinearity detection and its assessment are discussed. These parts of methodology are demonstrated in examples using flight data of the X-29A and X-31A aircraft. In the third example wind tunnel oscillatory data of the F-16XL model are used. A strong dependence of these data on frequency led to the development of models with unsteady aerodynamic terms in the form of indicial functions. The paper is completed by concluding remarks.

  14. Fault Detection of Wind Turbines with Uncertain Parameters

    DEFF Research Database (Denmark)

    Tabatabaeipour, Seyed Mojtaba; Odgaard, Peter Fogh; Bak, Thomas

    2012-01-01

    on the torque coefficient. High noise on the wind speed measurement, nonlinearities in the aerodynamic torque and uncertainties on the parameters make fault detection a challenging problem. We use an effective wind speed estimator to reduce the noise on the wind speed measurements. A set-membership approach...... is detected. For representation of these sets we use zonotopes and for modeling of uncertainties we use matrix zonotopes, which yields a computationally efficient algorithm. The method is applied to the wind turbine benchmark problem without and with uncertainties. The result demonstrates the effectiveness...

  15. Wind Speed Preview Measurement and Estimation for Feedforward Control of Wind Turbines

    Science.gov (United States)

    Simley, Eric J.

    Wind turbines typically rely on feedback controllers to maximize power capture in below-rated conditions and regulate rotor speed during above-rated operation. However, measurements of the approaching wind provided by Light Detection and Ranging (lidar) can be used as part of a preview-based, or feedforward, control system in order to improve rotor speed regulation and reduce structural loads. But the effectiveness of preview-based control depends on how accurately lidar can measure the wind that will interact with the turbine. In this thesis, lidar measurement error is determined using a statistical frequency-domain wind field model including wind evolution, or the change in turbulent wind speeds between the time they are measured and when they reach the turbine. Parameters of the National Renewable Energy Laboratory (NREL) 5-MW reference turbine model are used to determine measurement error for a hub-mounted circularly-scanning lidar scenario, based on commercially-available technology, designed to estimate rotor effective uniform and shear wind speed components. By combining the wind field model, lidar model, and turbine parameters, the optimal lidar scan radius and preview distance that yield the minimum mean square measurement error, as well as the resulting minimum achievable error, are found for a variety of wind conditions. With optimized scan scenarios, it is found that relatively low measurement error can be achieved, but the attainable measurement error largely depends on the wind conditions. In addition, the impact of the induction zone, the region upstream of the turbine where the approaching wind speeds are reduced, as well as turbine yaw error on measurement quality is analyzed. In order to minimize the mean square measurement error, an optimal measurement prefilter is employed, which depends on statistics of the correlation between the preview measurements and the wind that interacts with the turbine. However, because the wind speeds encountered by

  16. Wind resource estimation and siting of wind turbines

    DEFF Research Database (Denmark)

    Lundtang Petersen, Erik; Mortensen, N.G.; Landberg, L.

    1994-01-01

    Detailed knowledge of the characteristics of the natural wind is necessary for the design, planning and operational aspect of wind energy systems. Here, we shall only be concerned with those meteorological aspects of wind energy planning that are termed wind resource estimation. The estimation...... of the wind resource ranges from the overall estimation of the mean energy content of the wind over a large area - called regional assessment - to the prediction of the average yearly energy production of a specific wind turbine at a specific location - called siting. A regional assessment will most often...... lead to a so-called wind atlas. A precise prediction of the wind speed at a given site is essential because for aerodynamic reasons the power output of a wind turbine is proportional to the third power of the wind speed, hence even small errors in prediction of wind speed may result in large deviations...

  17. Prototype bucket foundation for wind turbines - natural frequency estimation

    Energy Technology Data Exchange (ETDEWEB)

    Ibsen, Lars Bo; Liingaard, M.

    2006-12-15

    The first full scale prototype bucket foundation for wind turbines has been installed in October 2002 at Aalborg University offshore test facility in Frederikshavn, Denmark. The suction caisson and the wind turbine have been equipped with an online monitoring system, consisting of 15 accelerometers and a real-time data-acquisition system. The report concerns the in service performance of the wind turbine, with focus on estimation of the natural frequencies of the structure/foundation. The natural frequencies are initially estimated by means of experimental Output-only Modal analysis. The experimental estimates are then compared with numerical simulations of the suction caisson foundation and the wind turbine. The numerical model consists of a finite element section for the wind turbine tower and nacelle. The soil-structure interaction of the soil-foundation section is modelled by lumped-parameter models capable of simulating dynamic frequency dependent behaviour of the structure-foundation system. (au)

  18. Estimation of Typhoon Wind Hazard Curves for Nuclear Sites

    Energy Technology Data Exchange (ETDEWEB)

    Choun, Young-Sun; Kim, Min-Kyu [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

    2016-10-15

    The intensity of such typhoons, which can influence the Korean Peninsula, is on an increasing trend owing to a rapid change of climate of the Northwest Pacific Ocean. Therefore, nuclear facilities should be prepared against future super-typhoons. Currently, the U.S. Nuclear Regulatory Commission requires that a new NPP should be designed to endure the design-basis hurricane wind speeds corresponding to an annual exceedance frequency of 10{sup -7} (return period of 10 million years). A typical technique used to estimate typhoon wind speeds is based on a sampling of the key parameters of typhoon wind models from the distribution functions fitting statistical distributions to the observation data. Thus, the estimated wind speeds for long return periods include an unavoidable uncertainty owing to a limited observation. This study estimates the typhoon wind speeds for nuclear sites using a Monte Carlo simulation, and derives wind hazard curves using a logic-tree framework to reduce the epistemic uncertainty. Typhoon wind speeds were estimated for different return periods through a Monte-Carlo simulation using the typhoon observation data, and the wind hazard curves were derived using a logic-tree framework for three nuclear sites. The hazard curves for the simulated and probable maximum winds were obtained. The mean hazard curves for the simulated and probable maximum winds can be used for the design and risk assessment of an NPP.

  19. Improving Wind Predictions in the Marine Atmospheric Boundary Layer through Parameter Estimation in a Single-Column Model

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Jared A.; Hacker, Joshua P.; Delle Monache, Luca; Kosović, Branko; Clifton, Andrew; Vandenberghe, Francois; Rodrigo, Javier Sanz

    2016-12-14

    A current barrier to greater deployment of offshore wind turbines is the poor quality of numerical weather prediction model wind and turbulence forecasts over open ocean. The bulk of development for atmospheric boundary layer (ABL) parameterization schemes has focused on land, partly due to a scarcity of observations over ocean. The 100-m FINO1 tower in the North Sea is one of the few sources worldwide of atmospheric profile observations from the sea surface to turbine hub height. These observations are crucial to developing a better understanding and modeling of physical processes in the marine ABL. In this study, we use the WRF single column model (SCM), coupled with an ensemble Kalman filter from the Data Assimilation Research Testbed (DART), to create 100-member ensembles at the FINO1 location. The goal of this study is to determine the extent to which model parameter estimation can improve offshore wind forecasts.

  20. Offshore wind resource estimation for wind energy

    DEFF Research Database (Denmark)

    Hasager, Charlotte Bay; Badger, Merete; Mouche, A.

    2010-01-01

    Satellite remote sensing from active and passive microwave instruments is used to estimate the offshore wind resource in the Northern European Seas in the EU-Norsewind project. The satellite data include 8 years of Envisat ASAR, 10 years of QuikSCAT, and 23 years of SSM/I. The satellite observati......Satellite remote sensing from active and passive microwave instruments is used to estimate the offshore wind resource in the Northern European Seas in the EU-Norsewind project. The satellite data include 8 years of Envisat ASAR, 10 years of QuikSCAT, and 23 years of SSM/I. The satellite...... observations are compared to selected offshore meteorological masts in the Baltic Sea and North Sea. The overall aim of the Norsewind project is a state-of-the-art wind atlas at 100 m height. The satellite winds are all valid at 10 m above sea level. Extrapolation to higher heights is a challenge. Mesoscale...... modeling of the winds at hub height will be compared to data from wind lidars observing at 100 m above sea level. Plans are also to compare mesoscale model results and satellite-based estimates of the offshore wind resource....

  1. Estimation of monthly wind power outputs of WECS with limited record period using artificial neural networks

    International Nuclear Information System (INIS)

    Tu, Yi-Long; Chang, Tsang-Jung; Chen, Cheng-Lung; Chang, Yu-Jung

    2012-01-01

    Highlights: ► ANN with short record training data is used to estimate power outputs in an existing station. ► The suitable numbers/parameters of input neurons for ANN are presented. ► Current wind speeds and previous power outputs are the most important input neurons. ► Choosing suitable input parameters is more important than choosing multiple parameters. - Abstract: For the brand new wind power industry, online recordings of wind power data are always in a relatively limited period. The aim of the study is to investigate the suitable numbers/parameters of input neurons for artificial neural networks under a short record of measured data. Measured wind speeds, wind directions (yaw angles) and power outputs with 10-min resolution at an existing wind power station, located at Jhongtun, Taiwan, are integrated to form three types of input neuron numbers and sixteen cases of input neurons. The first-10 days of each month in 2006 are used for data training to simulate the following 20-day power generation of the same month. The performance of various input neuron cases is evaluated. The simulated results show that using the first 10-day training data with adequate input neurons can estimate energy outputs well except the weak wind regime (May, June, and July). Among the input neuron parameters used, current wind speeds V(t) and previous power outputs P(t − 1) are the most important. Individually using one of them into input neurons can only provide satisfactory estimation. However, simultaneously using these two parameters into input neurons can give the best estimation. Thus, choosing suitable input parameters is more important than choosing multiple parameters.

  2. A Parameter Selection Method for Wind Turbine Health Management through SCADA Data

    Directory of Open Access Journals (Sweden)

    Mian Du

    2017-02-01

    Full Text Available Wind turbine anomaly or failure detection using machine learning techniques through supervisory control and data acquisition (SCADA system is drawing wide attention from academic and industry While parameter selection is important for modelling a wind turbine’s condition, only a few papers have been published focusing on this issue and in those papers interconnections among sub-components in a wind turbine are used to address this problem. However, merely the interconnections for decision making sometimes is too general to provide a parameter list considering the differences of each SCADA dataset. In this paper, a method is proposed to provide more detailed suggestions on parameter selection based on mutual information. First, the copula is proven to be capable of simplifying the estimation of mutual information. Then an empirical copulabased mutual information estimation method (ECMI is introduced for application. After that, a real SCADA dataset is adopted to test the method, and the results show the effectiveness of the ECMI in providing parameter selection suggestions when physical knowledge is not accurate enough.

  3. Wind distribution and capacity factor estimation for wind turbines in the coastal region of South Africa

    International Nuclear Information System (INIS)

    Ayodele, T.R.; Jimoh, A.A.; Munda, J.L.; Agee, J.T.

    2012-01-01

    Highlights: ► We evaluate capacity factor of some commercially available wind turbines. ► Wind speed in the sites studied can best be modelled using Weibull distribution. ► Site WM05 has the highest wind power potential while site WM02 has the lowest. ► More wind power can be harnessed during the day period compared to the night. ► Turbine K seems to be the best turbine for the coastal region of South Africa. - Abstract: The operating curve parameters of a wind turbine should match the local wind regime optimally to ensure maximum exploitation of available energy in a mass of moving air. This paper provides estimates of the capacity factor of 20 commercially available wind turbines, based on the local wind characteristics of ten different sites located in the Western Cape region of South Africa. Ten-min average time series wind-speed data for a period of 1 year are used for the study. First, the wind distribution that best models the local wind regime of the sites is determined. This is based on root mean square error (RMSE) and coefficient of determination (R 2 ) which are used to test goodness of fit. First, annual, seasonal, diurnal and peak period-capacity factor are estimated analytically. Then, the influence of turbine power curve parameters on the capacity factor is investigated. Some of the key results show that the wind distribution of the entire site can best be modelled statistically using the Weibull distribution. Site WM05 (Napier) presents the highest capacity factor for all the turbines. This indicates that this site has the highest wind power potential of all the available sites. Site WM02 (Calvinia) has the lowest capacity factor i.e. lowest wind power potential. This paper can assist in the planning and development of large-scale wind power-generating sites in South Africa.

  4. Assessment of Wind Parameter Sensitivity on Extreme and Fatigue Wind Turbine Loads

    Energy Technology Data Exchange (ETDEWEB)

    Robertson, Amy N [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Sethuraman, Latha [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Jonkman, Jason [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Quick, Julian [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

    2018-01-12

    Wind turbines are designed using a set of simulations to ascertain the structural loads that the turbine could encounter. While mean hub-height wind speed is considered to vary, other wind parameters such as turbulence spectra, sheer, veer, spatial coherence, and component correlation are fixed or conditional values that, in reality, could have different characteristics at different sites and have a significant effect on the resulting loads. This paper therefore seeks to assess the sensitivity of different wind parameters on the resulting ultimate and fatigue loads on the turbine during normal operational conditions. Eighteen different wind parameters are screened using an Elementary Effects approach with radial points. As expected, the results show a high sensitivity of the loads to the turbulence standard deviation in the primary wind direction, but the sensitivity to wind shear is often much greater. To a lesser extent, other wind parameters that drive loads include the coherence in the primary wind direction and veer.

  5. Fatigue Damage Estimation and Data-based Control for Wind Turbines

    DEFF Research Database (Denmark)

    Barradas Berglind, Jose de Jesus; Wisniewski, Rafal; Soltani, Mohsen

    2015-01-01

    based on hysteresis operators, which can be used in control loops. The authors propose a data-based model predictive control (MPC) strategy that incorporates an online fatigue estimation method through the objective function, where the ultimate goal in mind is to reduce the fatigue damage of the wind......The focus of this work is on fatigue estimation and data-based controller design for wind turbines. The main purpose is to include a model of the fatigue damage of the wind turbine components in the controller design and synthesis process. This study addresses an online fatigue estimation method...... turbine components. The outcome is an adaptive or self-tuning MPC strategy for wind turbine fatigue damage reduction, which relies on parameter identification on previous measurement data. The results of the proposed strategy are compared with a baseline model predictive controller....

  6. Influence of the Determination Methods of K and C Parameters on the Ability of Weibull Distribution to Suitably Estimate Wind Potential and Electric Energy

    Directory of Open Access Journals (Sweden)

    Ruben M. Mouangue

    2014-05-01

    Full Text Available The modeling of the wind speed distribution is of great importance for the assessment of wind energy potential and the performance of wind energy conversion system. In this paper, the choice of two determination methods of Weibull parameters shows theirs influences on the Weibull distribution performances. Because of important calm winds on the site of Ngaoundere airport, we characterize the wind potential using the approach of Weibull distribution with parameters which are determined by the modified maximum likelihood method. This approach is compared to the Weibull distribution with parameters which are determined by the maximum likelihood method and the hybrid distribution which is recommended for wind potential assessment of sites having nonzero probability of calm. Using data provided by the ASECNA Weather Service (Agency for the Safety of Air Navigation in Africa and Madagascar, we evaluate the goodness of fit of the various fitted distributions to the wind speed data using the Q – Q plots, the Pearson’s coefficient of correlation, the mean wind speed, the mean square error, the energy density and its relative error. It appears from the results that the accuracy of the Weibull distribution with parameters which are determined by the modified maximum likelihood method is higher than others. Then, this approach is used to estimate the monthly and annual energy productions of the site of the Ngaoundere airport. The most energy contribution is made in March with 255.7 MWh. It also appears from the results that a wind turbine generator installed on this particular site could not work for at least a half of the time because of higher frequency of calm. For this kind of sites, the modified maximum likelihood method proposed by Seguro and Lambert in 2000 is one of the best methods which can be used to determinate the Weibull parameters.

  7. Characteristics for wind energy and wind turbines by considering vertical wind shear

    Institute of Scientific and Technical Information of China (English)

    郑玉巧; 赵荣珍

    2015-01-01

    The probability distributions of wind speeds and the availability of wind turbines were investigated by considering the vertical wind shear. Based on the wind speed data at the standard height observed at a wind farm, the power-law process was used to simulate the wind speeds at a hub height of 60 m. The Weibull and Rayleigh distributions were chosen to express the wind speeds at two different heights. The parameters in the model were estimated via the least square (LS) method and the maximum likelihood estimation (MLE) method, respectively. An adjusted MLE approach was also presented for parameter estimation. The main indices of wind energy characteristics were calculated based on observational wind speed data. A case study based on the data of Hexi area, Gansu Province of China was given. The results show that MLE method generally outperforms LS method for parameter estimation, and Weibull distribution is more appropriate to describe the wind speed at the hub height.

  8. Mooring Line Damping Estimation for a Floating Wind Turbine

    Directory of Open Access Journals (Sweden)

    Dongsheng Qiao

    2014-01-01

    Full Text Available The dynamic responses of mooring line serve important functions in the station keeping of a floating wind turbine (FWT. Mooring line damping significantly influences the global motions of a FWT. This study investigates the estimation of mooring line damping on the basis of the National Renewable Energy Laboratory 5 MW offshore wind turbine model that is mounted on the ITI Energy barge. A numerical estimation method is derived from the energy absorption of a mooring line resulting from FWT motion. The method is validated by performing a 1/80 scale model test. Different parameter changes are analyzed for mooring line damping induced by horizontal and vertical motions. These parameters include excitation amplitude, excitation period, and drag coefficient. Results suggest that mooring line damping must be carefully considered in the FWT design.

  9. Mooring line damping estimation for a floating wind turbine.

    Science.gov (United States)

    Qiao, Dongsheng; Ou, Jinping

    2014-01-01

    The dynamic responses of mooring line serve important functions in the station keeping of a floating wind turbine (FWT). Mooring line damping significantly influences the global motions of a FWT. This study investigates the estimation of mooring line damping on the basis of the National Renewable Energy Laboratory 5 MW offshore wind turbine model that is mounted on the ITI Energy barge. A numerical estimation method is derived from the energy absorption of a mooring line resulting from FWT motion. The method is validated by performing a 1/80 scale model test. Different parameter changes are analyzed for mooring line damping induced by horizontal and vertical motions. These parameters include excitation amplitude, excitation period, and drag coefficient. Results suggest that mooring line damping must be carefully considered in the FWT design.

  10. Estimation of effective wind speed

    Science.gov (United States)

    Østergaard, K. Z.; Brath, P.; Stoustrup, J.

    2007-07-01

    The wind speed has a huge impact on the dynamic response of wind turbine. Because of this, many control algorithms use a measure of the wind speed to increase performance, e.g. by gain scheduling and feed forward. Unfortunately, no accurate measurement of the effective wind speed is online available from direct measurements, which means that it must be estimated in order to make such control methods applicable in practice. In this paper a new method is presented for the estimation of the effective wind speed. First, the rotor speed and aerodynamic torque are estimated by a combined state and input observer. These two variables combined with the measured pitch angle is then used to calculate the effective wind speed by an inversion of a static aerodynamic model.

  11. PERFORMANCE ANALYSIS OF METHODS FOR ESTIMATING WEIBULL PARAMETERS FOR WIND SPEED DISTRIBUTION IN THE DISTRICT OF MAROUA

    Directory of Open Access Journals (Sweden)

    D. Kidmo Kaoga

    2015-07-01

    Full Text Available In this study, five numerical Weibull distribution methods, namely, the maximum likelihood method, the modified maximum likelihood method (MLM, the energy pattern factor method (EPF, the graphical method (GM, and the empirical method (EM were explored using hourly synoptic data collected from 1985 to 2013 in the district of Maroua in Cameroon. The performance analysis revealed that the MLM was the most accurate model followed by the EPF and the GM. Furthermore, the comparison between the wind speed standard deviation predicted by the proposed models and the measured data showed that the MLM has a smaller relative error of -3.33% on average compared to -11.67% on average for the EPF and -8.86% on average for the GM. As a result, the MLM was precisely recommended to estimate the scale and shape parameters for an accurate and efficient wind energy potential evaluation.

  12. PERFORMANCE ANALYSIS OF METHODS FOR ESTIMATING WEIBULL PARAMETERS FOR WIND SPEED DISTRIBUTION IN THE DISTRICT OF MAROUA

    Directory of Open Access Journals (Sweden)

    D. Kidmo Kaoga

    2014-12-01

    Full Text Available In this study, five numerical Weibull distribution methods, namely, the maximum likelihood method, the modified maximum likelihood method (MLM, the energy pattern factor method (EPF, the graphical method (GM, and the empirical method (EM were explored using hourly synoptic data collected from 1985 to 2013 in the district of Maroua in Cameroon. The performance analysis revealed that the MLM was the most accurate model followed by the EPF and the GM. Furthermore, the comparison between the wind speed standard deviation predicted by the proposed models and the measured data showed that the MLM has a smaller relative error of -3.33% on average compared to -11.67% on average for the EPF and -8.86% on average for the GM. As a result, the MLM was precisely recommended to estimate the scale and shape parameters for an accurate and efficient wind energy potential evaluation.

  13. Assessment of Wind Parameter Sensitivity on Ultimate and Fatigue Wind Turbine Loads: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Robertson, Amy N [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Sethuraman, Latha [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Jonkman, Jason [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Quick, Julian [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

    2018-02-13

    Wind turbines are designed using a set of simulations to ascertain the structural loads that the turbine could encounter. While mean hub-height wind speed is considered to vary, other wind parameters such as turbulence spectra, sheer, veer, spatial coherence, and component correlation are fixed or conditional values that, in reality, could have different characteristics at different sites and have a significant effect on the resulting loads. This paper therefore seeks to assess the sensitivity of different wind parameters on the resulting ultimate and fatigue loads on the turbine during normal operational conditions. Eighteen different wind parameters are screened using an Elementary Effects approach with radial points. As expected, the results show a high sensitivity of the loads to the turbulence standard deviation in the primary wind direction, but the sensitivity to wind shear is often much greater. To a lesser extent, other wind parameters that drive loads include the coherence in the primary wind direction and veer.

  14. An Approach to Determine the Weibull Parameters and Wind Power Analysis of Saint Martin’s Island, Bangladesh

    Directory of Open Access Journals (Sweden)

    Islam Khandaker Dahirul

    2016-01-01

    Full Text Available This paper explores wind speed distribution using Weibull probability distribution and Rayleigh distribution methods that are proven to provide accurate and efficient estimation of energy output in terms of wind energy conversion systems. Two parameters of Weibull (shape and scale parameters k and c respectively and scale parameter of Rayleigh distribution have been determined based on hourly time-series wind speed data recorded from October 2014 to October 2015 at Saint Martin’s island, Bangladesh. This research has been carried out to examine three numerical methods namely Graphical Method (GM, Empirical Method (EM, Energy Pattern Factor method (EPF to estimate Weibull parameters. Also, Rayleigh distribution method has been analyzed throughout the study. The results in the research revealed that the Graphical method followed by Empirical method and Energy Pattern Factor method were the most accurate and efficient way for determining the value of k and c to approximate wind speed distribution in terms of estimating power error. Rayleigh distribution gives the most power error in the research. Potential for wind energy development in Saint Martin’s island, Bangladesh as found from the data analysis has been explained in this paper.

  15. Stellar and wind parameters of massive stars from spectral analysis

    Science.gov (United States)

    Araya, Ignacio; Curé, Michel

    2017-11-01

    The only way to deduce information from stars is to decode the radiation it emits in an appropriate way. Spectroscopy can solve this and derive many properties of stars. In this work we seek to derive simultaneously the stellar and wind characteristics of a wide range of massive stars. Our stellar properties encompass the effective temperature, the surface gravity, the stellar radius, the micro-turbulence velocity, the rotational velocity and the Si abundance. For wind properties we consider the mass-loss rate, the terminal velocity and the line-force parameters α, k and δ (from the line-driven wind theory). To model the data we use the radiative transport code Fastwind considering the newest hydrodynamical solutions derived with Hydwind code, which needs stellar and line-force parameters to obtain a wind solution. A grid of spectral models of massive stars is created and together with the observed spectra their physical properties are determined through spectral line fittings. These fittings provide an estimation about the line-force parameters, whose theoretical calculations are extremely complex. Furthermore, we expect to confirm that the hydrodynamical solutions obtained with a value of δ slightly larger than ~ 0.25, called δ-slow solutions, describe quite reliable the radiation line-driven winds of A and late B supergiant stars and at the same time explain disagreements between observational data and theoretical models for the Wind-Momentum Luminosity Relationship (WLR).

  16. Wind power error estimation in resource assessments.

    Directory of Open Access Journals (Sweden)

    Osvaldo Rodríguez

    Full Text Available Estimating the power output is one of the elements that determine the techno-economic feasibility of a renewable project. At present, there is a need to develop reliable methods that achieve this goal, thereby contributing to wind power penetration. In this study, we propose a method for wind power error estimation based on the wind speed measurement error, probability density function, and wind turbine power curves. This method uses the actual wind speed data without prior statistical treatment based on 28 wind turbine power curves, which were fitted by Lagrange's method, to calculate the estimate wind power output and the corresponding error propagation. We found that wind speed percentage errors of 10% were propagated into the power output estimates, thereby yielding an error of 5%. The proposed error propagation complements the traditional power resource assessments. The wind power estimation error also allows us to estimate intervals for the power production leveled cost or the investment time return. The implementation of this method increases the reliability of techno-economic resource assessment studies.

  17. Wind power error estimation in resource assessments.

    Science.gov (United States)

    Rodríguez, Osvaldo; Del Río, Jesús A; Jaramillo, Oscar A; Martínez, Manuel

    2015-01-01

    Estimating the power output is one of the elements that determine the techno-economic feasibility of a renewable project. At present, there is a need to develop reliable methods that achieve this goal, thereby contributing to wind power penetration. In this study, we propose a method for wind power error estimation based on the wind speed measurement error, probability density function, and wind turbine power curves. This method uses the actual wind speed data without prior statistical treatment based on 28 wind turbine power curves, which were fitted by Lagrange's method, to calculate the estimate wind power output and the corresponding error propagation. We found that wind speed percentage errors of 10% were propagated into the power output estimates, thereby yielding an error of 5%. The proposed error propagation complements the traditional power resource assessments. The wind power estimation error also allows us to estimate intervals for the power production leveled cost or the investment time return. The implementation of this method increases the reliability of techno-economic resource assessment studies.

  18. Estimating random transverse velocities in the fast solar wind from EISCAT Interplanetary Scintillation measurements

    Directory of Open Access Journals (Sweden)

    A. Canals

    2002-09-01

    Full Text Available Interplanetary scintillation measurements can yield estimates of a large number of solar wind parameters, including bulk flow speed, variation in bulk velocity along the observing path through the solar wind and random variation in transverse velocity. This last parameter is of particular interest, as it can indicate the flux of low-frequency Alfvén waves, and the dissipation of these waves has been proposed as an acceleration mechanism for the fast solar wind. Analysis of IPS data is, however, a significantly unresolved problem and a variety of a priori assumptions must be made in interpreting the data. Furthermore, the results may be affected by the physical structure of the radio source and by variations in the solar wind along the scintillation ray path. We have used observations of simple point-like radio sources made with EISCAT between 1994 and 1998 to obtain estimates of random transverse velocity in the fast solar wind. The results obtained with various a priori assumptions made in the analysis are compared, and we hope thereby to be able to provide some indication of the reliability of our estimates of random transverse velocity and the variation of this parameter with distance from the Sun.Key words. Interplanetary physics (MHD waves and turbulence; solar wind plasma; instruments and techniques

  19. Estimating random transverse velocities in the fast solar wind from EISCAT Interplanetary Scintillation measurements

    Directory of Open Access Journals (Sweden)

    A. Canals

    Full Text Available Interplanetary scintillation measurements can yield estimates of a large number of solar wind parameters, including bulk flow speed, variation in bulk velocity along the observing path through the solar wind and random variation in transverse velocity. This last parameter is of particular interest, as it can indicate the flux of low-frequency Alfvén waves, and the dissipation of these waves has been proposed as an acceleration mechanism for the fast solar wind. Analysis of IPS data is, however, a significantly unresolved problem and a variety of a priori assumptions must be made in interpreting the data. Furthermore, the results may be affected by the physical structure of the radio source and by variations in the solar wind along the scintillation ray path. We have used observations of simple point-like radio sources made with EISCAT between 1994 and 1998 to obtain estimates of random transverse velocity in the fast solar wind. The results obtained with various a priori assumptions made in the analysis are compared, and we hope thereby to be able to provide some indication of the reliability of our estimates of random transverse velocity and the variation of this parameter with distance from the Sun.

    Key words. Interplanetary physics (MHD waves and turbulence; solar wind plasma; instruments and techniques

  20. Improved diagnostic model for estimating wind energy

    Energy Technology Data Exchange (ETDEWEB)

    Endlich, R.M.; Lee, J.D.

    1983-03-01

    Because wind data are available only at scattered locations, a quantitative method is needed to estimate the wind resource at specific sites where wind energy generation may be economically feasible. This report describes a computer model that makes such estimates. The model uses standard weather reports and terrain heights in deriving wind estimates; the method of computation has been changed from what has been used previously. The performance of the current model is compared with that of the earlier version at three sites; estimates of wind energy at four new sites are also presented.

  1. Estimating Wind and Wave Induced Forces On a Floating Wind Turbine

    DEFF Research Database (Denmark)

    Henriksen, Lars Christian; Natarajan, Anand; Kim, Taeseong

    2013-01-01

    -principles derived state space model of the floating wind turbine. The ability to estimate aero- and hydrodynamic states could prove crucial for the performance of model-based control methods applied on floating wind turbines. Furthermore, two types of water kinematics have been compared two determine whether......In this work, the basic model for a spar buoy floating wind turbine [1], used by an extended Kalman filter, is presented and results concerning wind speed and wave force estimations are shown. The wind speed and aerodynamic forces are estimated using an extended Kalman filter based on a first...... or not linear and nonlinear water kinematics lead to significantly different loads....

  2. Wind Farm Decentralized Dynamic Modeling With Parameters

    DEFF Research Database (Denmark)

    Soltani, Mohsen; Shakeri, Sayyed Mojtaba; Grunnet, Jacob Deleuran

    2010-01-01

    Development of dynamic wind flow models for wind farms is part of the research in European research FP7 project AEOLUS. The objective of this report is to provide decentralized dynamic wind flow models with parameters. The report presents a structure for decentralized flow models with inputs from...... local models. The results of this report are especially useful, but not limited, to design a decentralized wind farm controller, since in centralized controller design one can also use the model and update it in a central computing node.......Development of dynamic wind flow models for wind farms is part of the research in European research FP7 project AEOLUS. The objective of this report is to provide decentralized dynamic wind flow models with parameters. The report presents a structure for decentralized flow models with inputs from...

  3. Condition Parameter Modeling for Anomaly Detection in Wind Turbines

    Directory of Open Access Journals (Sweden)

    Yonglong Yan

    2014-05-01

    Full Text Available Data collected from the supervisory control and data acquisition (SCADA system, used widely in wind farms to obtain operational and condition information about wind turbines (WTs, is of important significance for anomaly detection in wind turbines. The paper presents a novel model for wind turbine anomaly detection mainly based on SCADA data and a back-propagation neural network (BPNN for automatic selection of the condition parameters. The SCADA data sets are determined through analysis of the cumulative probability distribution of wind speed and the relationship between output power and wind speed. The automatic BPNN-based parameter selection is for reduction of redundant parameters for anomaly detection in wind turbines. Through investigation of cases of WT faults, the validity of the automatic parameter selection-based model for WT anomaly detection is verified.

  4. Parameter Estimation

    DEFF Research Database (Denmark)

    Sales-Cruz, Mauricio; Heitzig, Martina; Cameron, Ian

    2011-01-01

    of optimisation techniques coupled with dynamic solution of the underlying model. Linear and nonlinear approaches to parameter estimation are investigated. There is also the application of maximum likelihood principles in the estimation of parameters, as well as the use of orthogonal collocation to generate a set......In this chapter the importance of parameter estimation in model development is illustrated through various applications related to reaction systems. In particular, rate constants in a reaction system are obtained through parameter estimation methods. These approaches often require the application...... of algebraic equations as the basis for parameter estimation.These approaches are illustrated using estimations of kinetic constants from reaction system models....

  5. Determining the parameters of Weibull function to estimate the wind power potential in conditions of limited source meteorological data

    Science.gov (United States)

    Fetisova, Yu. A.; Ermolenko, B. V.; Ermolenko, G. V.; Kiseleva, S. V.

    2017-04-01

    We studied the information basis for the assessment of wind power potential on the territory of Russia. We described the methodology to determine the parameters of the Weibull function, which reflects the density of distribution of probabilities of wind flow speeds at a defined basic height above the surface of the earth using the available data on the average speed at this height and its repetition by gradations. The application of the least square method for determining these parameters, unlike the use of graphical methods, allows performing a statistical assessment of the results of approximation of empirical histograms by the Weibull formula. On the basis of the computer-aided analysis of the statistical data, it was shown that, at a fixed point where the wind speed changes at different heights, the range of parameter variation of the Weibull distribution curve is relatively small, the sensitivity of the function to parameter changes is quite low, and the influence of changes on the shape of speed distribution curves is negligible. Taking this into consideration, we proposed and mathematically verified the methodology of determining the speed parameters of the Weibull function at other heights using the parameter computations for this function at a basic height, which is known or defined by the average speed of wind flow, or the roughness coefficient of the geological substrate. We gave examples of practical application of the suggested methodology in the development of the Atlas of Renewable Energy Resources in Russia in conditions of deficiency of source meteorological data. The proposed methodology, to some extent, may solve the problem related to the lack of information on the vertical profile of repeatability of the wind flow speeds in the presence of a wide assortment of wind turbines with different ranges of wind-wheel axis heights and various performance characteristics in the global market; as a result, this methodology can become a powerful tool for

  6. An Improved Global Wind Resource Estimate for Integrated Assessment Models: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Eurek, Kelly [National Renewable Energy Lab. (NREL), Golden, CO (United States); Sullivan, Patrick [National Renewable Energy Lab. (NREL), Golden, CO (United States); Gleason, Michael [National Renewable Energy Lab. (NREL), Golden, CO (United States); Hettinger, Dylan [National Renewable Energy Lab. (NREL), Golden, CO (United States); Heimiller, Donna [National Renewable Energy Lab. (NREL), Golden, CO (United States); Lopez, Anthony [National Renewable Energy Lab. (NREL), Golden, CO (United States)

    2017-02-01

    This paper summarizes initial steps to improving the robustness and accuracy of global renewable resource and techno-economic assessments for use in integrated assessment models. We outline a method to construct country-level wind resource supply curves, delineated by resource quality and other parameters. Using mesoscale reanalysis data, we generate estimates for wind quality, both terrestrial and offshore, across the globe. Because not all land or water area is suitable for development, appropriate database layers provide exclusions to reduce the total resource to its technical potential. We expand upon estimates from related studies by: using a globally consistent data source of uniquely detailed wind speed characterizations; assuming a non-constant coefficient of performance for adjusting power curves for altitude; categorizing the distance from resource sites to the electric power grid; and characterizing offshore exclusions on the basis of sea ice concentrations. The product, then, is technical potential by country, classified by resource quality as determined by net capacity factor. Additional classifications dimensions are available, including distance to transmission networks for terrestrial wind and distance to shore and water depth for offshore. We estimate the total global wind generation potential of 560 PWh for terrestrial wind with 90% of resource classified as low-to-mid quality, and 315 PWh for offshore wind with 67% classified as mid-to-high quality. These estimates are based on 3.5 MW composite wind turbines with 90 m hub heights, 0.95 availability, 90% array efficiency, and 5 MW/km2 deployment density in non-excluded areas. We compare the underlying technical assumption and results with other global assessments.

  7. Optimum Operational Parameters for Yawed Wind Turbines

    Directory of Open Access Journals (Sweden)

    David A. Peters

    2011-01-01

    Full Text Available A set of systematical optimum operational parameters for wind turbines under various wind directions is derived by using combined momentum-energy and blade-element-energy concepts. The derivations are solved numerically by fixing some parameters at practical values. Then, the interactions between the produced power and the influential factors of it are generated in the figures. It is shown that the maximum power produced is strongly affected by the wind direction, the tip speed, the pitch angle of the rotor, and the drag coefficient, which are specifically indicated by figures. It also turns out that the maximum power can take place at two different optimum tip speeds in some cases. The equations derived herein can also be used in the modeling of tethered wind turbines which can keep aloft and deliver energy.

  8. Study on Parameters Modeling of Wind Turbines Using SCADA Data

    Directory of Open Access Journals (Sweden)

    Yonglong YAN

    2014-08-01

    Full Text Available Taking the advantage of the current massive monitoring data from Supervisory Control and Data Acquisition (SCADA system of wind farm, it is of important significance for anomaly detection, early warning and fault diagnosis to build the data model of state parameters of wind turbines (WTs. The operational conditions and the relationships between the state parameters of wind turbines are complex. It is difficult to establish the model of state parameter accurately, and the modeling method of state parameters of wind turbines considering parameter selection is proposed. Firstly, by analyzing the characteristic of SCADA data, a reasonable range of data and monitoring parameters are chosen. Secondly, neural network algorithm is adapted, and the selection method of input parameters in the model is presented. Generator bearing temperature and cooling air temperature are regarded as target parameters, and the two models are built and input parameters of the models are selected, respectively. Finally, the parameter selection method in this paper and the method using genetic algorithm-partial least square (GA-PLS are analyzed comparatively, and the results show that the proposed methods are correct and effective. Furthermore, the modeling of two parameters illustrate that the method in this paper can applied to other state parameters of wind turbines.

  9. Estimating near-shore wind resources

    DEFF Research Database (Denmark)

    Floors, Rogier Ralph; Hahmann, Andrea N.; Peña, Alfredo

    An evaluation and sensitivity study using the WRF mesoscale model to estimate the wind in a coastal area is performed using a unique data set consisting of scanning, profiling and floating lidars. The ability of the WRF model to represent the wind speed was evaluated by running the model for a four...... grid spacings were performed for each of the two schemes. An evaluation of the wind profile using vertical profilers revealed small differences in modelled mean wind speed between the different set-ups, with the YSU scheme predicting slightly higher mean wind speeds. Larger differences between...... the different simulations were observed when comparing the root-mean-square error (RMSE) between modelled and measured wind, with the ERA interim-based simulations having the lowest errors. The simulations with finer horizontal grid spacing had a larger MSE. Horizontal transects of mean wind speed across...

  10. Wind direction dependent vertical wind shear and surface roughness parameter in two different coastal environments

    International Nuclear Information System (INIS)

    Bagavathsingh, A.; Srinivas, C.V.; Baskaran, R.; Venkatraman, B.; Sardar Maran, P.

    2016-01-01

    Atmospheric boundary layer parameters and surface layer parameterizations are important prerequisites for air pollution dispersion analysis. The turbulent flow characteristics vary at coastal and inland sites where the nuclear facilities are situated. Many pollution sources and their dispersion occur within the roughness sub layer in the lower atmosphere. In this study analysis of wind direction dependence vertical wind shear, surface roughness lengths and surface layer wind condition has been carried out at a coastal and the urban coastal site for the different wind flow regime. The differential response of the near coastal and inland urban site SBL parameters (wind shear, roughness length, etc) was examined as a function of wind direction

  11. Wind speed estimation using multilayer perceptron

    International Nuclear Information System (INIS)

    Velo, Ramón; López, Paz; Maseda, Francisco

    2014-01-01

    Highlights: • We present a method for determining the average wind speed using neural networks. • We use data from that site in the short term and data from other nearby stations. • The inputs used in the ANN were wind speed and direction data from a station. • The method allows knowing the wind speed without topographical data. - Abstract: Wind speed knowledge is prerequisite in the siting of wind turbines. In consequence the wind energy use requires meticulous and specified knowledge of the wind characteristics at a location. This paper presents a method for determining the annual average wind speed at a complex terrain site by using neural networks, when only short term data are available for that site. This information is useful for preliminary calculations of the wind resource at a remote area having only a short time period of wind measurements measurement in a site. Artificial neural networks are useful for implementing non-linear process variables over time, and therefore are a useful tool for estimating the wind speed. The neural network used is multilayer perceptron with three layers and the supervised learning algorithm used is backpropagation. The inputs used in the neural network were wind speed and direction data from a single station, and the training patterns used correspond to sixty days data. The results obtained by simulating the annual average wind speed at the selected site based on data from nearby stations with correlation coefficients above 0.5 were satisfactory, compared with actual values. Reliable estimations were obtained, with errors below 6%

  12. Estimations of Kappa parameter using quasi-thermal noise spectroscopy: Applications on Wind spacecraft

    Science.gov (United States)

    Martinović, M.

    2017-12-01

    Quasi-thermal noise (QTN) spectroscopy is an accurate technique for in situ measurements of electron density and temperature in space plasmas. The QTN spectrum has a characteristic noise peak just above the plasma frequency produced by electron quasi-thermal fluctuations, which allows a very accurate measurement of the electron density. The size and shape of the peak are determined by suprathermal electrons. Since this nonthermal electron population is well described by a generalized Lorentzian - Kappa velocity distribution, it is possible to determinate the distribution properties in the solar wind from a measured spectrum. In this work, we discuss some basic properties of the QTN spectrum dependence of the Kappa distribution parameters - total electron density, temperature and the Kappa index, giving an overview on how instrument characteristics and environment conditions affect quality of the measurements. Further on, we aim to apply the method to Wind Thermal Noise Receiver (TNR) measurements. However, the spectra observed by this instrument usually contain contributions from nonthermal phenomena, like ion acoustic waves below, or galactic noise above the plasma frequency. This is why, besides comparison of the theory with observations, work with Wind data requires development of a sophisticated algorithm that distinguish parts of the spectra that are dominated by the QTN, and therefore can be used in our study. Postulates of this algorithm, as well as major results of its implementation, are also presented.

  13. Wind-Climate Estimation Based on Mesoscale and Microscale Modeling: Statistical-Dynamical Downscaling for Wind Energy Applications

    DEFF Research Database (Denmark)

    Badger, Jake; Frank, Helmut; Hahmann, Andrea N.

    2014-01-01

    This paper demonstrates that a statistical dynamical method can be used to accurately estimate the wind climate at a wind farm site. In particular, postprocessing of mesoscale model output allows an efficient calculation of the local wind climate required for wind resource estimation at a wind...

  14. Estimation of Aircraft Nonlinear Unsteady Parameters From Wind Tunnel Data

    Science.gov (United States)

    Klein, Vladislav; Murphy, Patrick C.

    1998-01-01

    Aerodynamic equations were formulated for an aircraft in one-degree-of-freedom large amplitude motion about each of its body axes. The model formulation based on indicial functions separated the resulting aerodynamic forces and moments into static terms, purely rotary terms and unsteady terms. Model identification from experimental data combined stepwise regression and maximum likelihood estimation in a two-stage optimization algorithm that can identify the unsteady term and rotary term if necessary. The identification scheme was applied to oscillatory data in two examples. The model identified from experimental data fit the data well, however, some parameters were estimated with limited accuracy. The resulting model was a good predictor for oscillatory and ramp input data.

  15. WIND TURBINE OPERATION PARAMETER CHARACTERISTICS AT A GIVEN WIND SPEED

    Directory of Open Access Journals (Sweden)

    Zdzisław Kamiński

    2014-06-01

    Full Text Available This paper discusses the results of the CFD simulation of the flow around Vertical Axis Wind Turbine rotor. The examined rotor was designed following patent application no. 402214. The turbine operation is characterised by parameters, such as opening angle of blades, power, torque, rotational velocity at a given wind velocity. Those parameters have an impact on the performance of entire assembly. The distribution of forces acting on the working surfaces in the turbine can change, depending on the angle of rotor rotation. Moreover, the resultant force derived from the force acting on the oncoming and leaving blades should be as high as possible. Accordingly, those parameters were individually simulated over time for each blade in three complete rotations. The attempts to improve the performance of the entire system resulted in a new research trend to improve the performance of working turbine rotor blades.

  16. Geometry of solar corona expansion and solar wind parameters

    International Nuclear Information System (INIS)

    Krajnev, M.B.

    1980-01-01

    The character of the parameter chanqe of solar wind plasma in the region of the Earth orbit is studied. The main regularities in the parametep behaviour of solar wind (plasma velocity and density) are qualitatively explained in the framework of a model according to which solar corona expansion stronqly differs from radial expansion, that is: the solar wind current lines are focused towards helioequator during the period of low solar activity with gradual transfer to radial expansion during the years of high solar activity. It is shown that the geometry of the solar wind current tubes and its change with the solar activity cycle can not serve an explanation of the observed change of the solar wind parameters

  17. Multi-Response Parameter Interval Sensitivity and Optimization for the Composite Tape Winding Process

    Science.gov (United States)

    Yu, Tao; Kang, Chao; Zhao, Pan

    2018-01-01

    The composite tape winding process, which utilizes a tape winding machine and prepreg tapes, provides a promising way to improve the quality of composite products. Nevertheless, the process parameters of composite tape winding have crucial effects on the tensile strength and void content, which are closely related to the performances of the winding products. In this article, two different object values of winding products, including mechanical performance (tensile strength) and a physical property (void content), were respectively calculated. Thereafter, the paper presents an integrated methodology by combining multi-parameter relative sensitivity analysis and single-parameter sensitivity analysis to obtain the optimal intervals of the composite tape winding process. First, the global multi-parameter sensitivity analysis method was applied to investigate the sensitivity of each parameter in the tape winding processing. Then, the local single-parameter sensitivity analysis method was employed to calculate the sensitivity of a single parameter within the corresponding range. Finally, the stability and instability ranges of each parameter were distinguished. Meanwhile, the authors optimized the process parameter ranges and provided comprehensive optimized intervals of the winding parameters. The verification test validated that the optimized intervals of the process parameters were reliable and stable for winding products manufacturing. PMID:29385048

  18. Estimating wind frequency limits for natural ventilation at remote sites

    International Nuclear Information System (INIS)

    Su, B.; Aynsley, R.

    2006-01-01

    Detailed wind data are collected at a limited number of sites, usually at airports. When a building is sited remote from the nearest wind data collection site, estimating wind frequency is more complex. The techniques involved come from the discipline of wind engineering. Where there is a relatively flat terrain between the wind data-recording site and the building site, simple computations can be made to account for the wind velocities over intervening terrain roughness. Where significant topographic features such as hills or mountains are present between the wind data-recording site and the building site, then boundary layer wind tunnel studies will be necessary to determine the influence of such features on wind speed and direction. Rough estimates can be calculated using factors used in some wind loading codes. When buildings are to be designed to take advantage of the energy efficiency offered by natural ventilation, it is important to estimate the actual potential for such ventilation. The natural ventilation potential can be estimated in terms of the percentage of time when wind exceeds some minimum value. For buildings near airports this is a relatively simple procedure. Such estimates are important as they also indicate the likely percentage of time when fans or other energy consuming devices will be needed to maintain indoor thermal comfort. This paper identifies the wind engineering techniques that can be used for such estimates and gives examples of such calculations

  19. Modelling wind speed parameters for computer generation of wind speed in Flanders. A case study using small wind turbines in an urban environment

    Energy Technology Data Exchange (ETDEWEB)

    Gay, Michael; Dessel, Michel van [Lessius Mechelen, Campus De Nayer (Belgium). Dept. of Applied Engineering; Driesen, Johan [Leuven Univ. (Belgium). Dept. of Electrical Engineering / ESAT

    2012-07-01

    The calculation of wind energy parameters is made for small wind turbines on moderate height in a suburban environment. After using the measured data, the same parameters were calculated using first order Markov chain computer generated data. Some characteristics of the wind and the wind power were preserved using Markov, other were not. (orig.)

  20. Estimating the Wind Resource in Uttarakhand: Comparison of Dynamic Downscaling with Doppler Lidar Wind Measurements

    Energy Technology Data Exchange (ETDEWEB)

    Lundquist, J. K. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Pukayastha, A. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Martin, C. [Univ. of Colorado, Boulder, CO (United States); Newsom, R. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

    2014-03-01

    Previous estimates of the wind resources in Uttarakhand, India, suggest minimal wind resources in this region. To explore whether or not the complex terrain in fact provides localized regions of wind resource, the authors of this study employed a dynamic down scaling method with the Weather Research and Forecasting model, providing detailed estimates of winds at approximately 1 km resolution in the finest nested simulation.

  1. Determination of performance parameters of vertical axis wind turbines in wind tunnel

    Directory of Open Access Journals (Sweden)

    Nguyen Van Bang

    2017-01-01

    Full Text Available The paper deals with the determination of the performance parameters of a small vertical axis wind turbines (VAWT, which operate by the utilization of drag forces acting on the blades of the turbine. The performance was evaluated by investigating the electrical power output and torque moment of the wind machine. Measurements were performed on the full-scale model and the experimental data are assessed and compared to other types of wind turbines, with respect to its purpose.

  2. Fault Detection of Wind Turbines with Uncertain Parameters: A Set-Membership Approach

    Directory of Open Access Journals (Sweden)

    Thomas Bak

    2012-07-01

    Full Text Available In this paper a set-membership approach for fault detection of a benchmark wind turbine is proposed. The benchmark represents relevant fault scenarios in the control system, including sensor, actuator and system faults. In addition we also consider parameter uncertainties and uncertainties on the torque coefficient. High noise on the wind speed measurement, nonlinearities in the aerodynamic torque and uncertainties on the parameters make fault detection a challenging problem. We use an effective wind speed estimator to reduce the noise on the wind speed measurements. A set-membership approach is used generate a set that contains all states consistent with the past measurements and the given model of the wind turbine including uncertainties and noise. This set represents all possible states the system can be in if not faulty. If the current measurement is not consistent with this set, a fault is detected. For representation of these sets we use zonotopes and for modeling of uncertainties we use matrix zonotopes, which yields a computationally efficient algorithm. The method is applied to the wind turbine benchmark problem without and with uncertainties. The result demonstrates the effectiveness of the proposed method compared to other proposed methods applied to the same problem. An advantage of the proposed method is that there is no need for threshold design, and it does not produce positive false alarms. In the case where uncertainty on the torque lookup table is introduced, some faults are not detectable. Previous research has not addressed this uncertainty. The method proposed here requires equal or less detection time than previous results.

  3. DC Link Current Estimation in Wind-Double Feed Induction Generator Power Conditioning System

    Directory of Open Access Journals (Sweden)

    MARIAN GAICEANU

    2010-12-01

    Full Text Available In this paper the implementation of the DC link current estimator in power conditioning system of the variable speed wind turbine is shown. The wind turbine is connected to double feed induction generator (DFIG. The variable electrical energy parameters delivered by DFIG are fitted with the electrical grid parameters through back-to-back power converter. The bidirectional AC-AC power converter covers a wide speed range from subsynchronous to supersynchronous speeds. The modern control of back-to-back power converter involves power balance concept, therefore its load power should be known in any instant. By using the power balance control, the DC link voltage variation at the load changes can be reduced. In this paper the load power is estimated from the dc link, indirectly, through a second order DC link current estimator. The load current estimator is based on the DC link voltage and on the dc link input current of the rotor side converter. This method presents certain advantages instead of using measured method, which requires a low pass filter: no time delay, the feedforward current component has no ripple, no additional hardware, and more fast control response. Through the numerical simulation the performances of the proposed DC link output current estimator scheme are demonstrated.

  4. Mode extraction on wind turbine blades via phase-based video motion estimation

    Science.gov (United States)

    Sarrafi, Aral; Poozesh, Peyman; Niezrecki, Christopher; Mao, Zhu

    2017-04-01

    In recent years, image processing techniques are being applied more often for structural dynamics identification, characterization, and structural health monitoring. Although as a non-contact and full-field measurement method, image processing still has a long way to go to outperform other conventional sensing instruments (i.e. accelerometers, strain gauges, laser vibrometers, etc.,). However, the technologies associated with image processing are developing rapidly and gaining more attention in a variety of engineering applications including structural dynamics identification and modal analysis. Among numerous motion estimation and image-processing methods, phase-based video motion estimation is considered as one of the most efficient methods regarding computation consumption and noise robustness. In this paper, phase-based video motion estimation is adopted for structural dynamics characterization on a 2.3-meter long Skystream wind turbine blade, and the modal parameters (natural frequencies, operating deflection shapes) are extracted. Phase-based video processing adopted in this paper provides reliable full-field 2-D motion information, which is beneficial for manufacturing certification and model updating at the design stage. The phase-based video motion estimation approach is demonstrated through processing data on a full-scale commercial structure (i.e. a wind turbine blade) with complex geometry and properties, and the results obtained have a good correlation with the modal parameters extracted from accelerometer measurements, especially for the first four bending modes, which have significant importance in blade characterization.

  5. An improvement of wind velocity estimation from radar Doppler spectra in the upper mesosphere

    Directory of Open Access Journals (Sweden)

    S. Takeda

    2001-08-01

    Full Text Available We have developed a new parameter estimation method for Doppler wind spectra in the mesosphere observed with an MST radar such as the MU radar in the DBS (Doppler Beam Swinging mode. Off-line incoherent integration of the Doppler spectra is carried out with a new algorithm excluding contamination by strong meteor echoes. At the same time, initial values on a least square fitting of the Gaussian function are derived using a larger number of integration of the spectra for a longer time and for multiple heights. As a result, a significant improvement has been achieved with the probability of a successful fitting and parameter estimation above 80 km. The top height for the wind estimation has been improved to around 95 km. A comparison between the MU radar and the High Resolution Doppler Imager (HRDI on the UARS satellite is shown and the capability of the new method for a validation of a future satellite mission is suggested.Key words. Meteorology and atmospheric dynamics (middle atmosphere dynamics – Radio science (remote sensing; signal processing

  6. Estimating bat and bird mortality occurring at wind energy turbines from covariates and carcass searches using mixture models.

    Science.gov (United States)

    Korner-Nievergelt, Fränzi; Brinkmann, Robert; Niermann, Ivo; Behr, Oliver

    2013-01-01

    Environmental impacts of wind energy facilities increasingly cause concern, a central issue being bats and birds killed by rotor blades. Two approaches have been employed to assess collision rates: carcass searches and surveys of animals prone to collisions. Carcass searches can provide an estimate for the actual number of animals being killed but they offer little information on the relation between collision rates and, for example, weather parameters due to the time of death not being precisely known. In contrast, a density index of animals exposed to collision is sufficient to analyse the parameters influencing the collision rate. However, quantification of the collision rate from animal density indices (e.g. acoustic bat activity or bird migration traffic rates) remains difficult. We combine carcass search data with animal density indices in a mixture model to investigate collision rates. In a simulation study we show that the collision rates estimated by our model were at least as precise as conventional estimates based solely on carcass search data. Furthermore, if certain conditions are met, the model can be used to predict the collision rate from density indices alone, without data from carcass searches. This can reduce the time and effort required to estimate collision rates. We applied the model to bat carcass search data obtained at 30 wind turbines in 15 wind facilities in Germany. We used acoustic bat activity and wind speed as predictors for the collision rate. The model estimates correlated well with conventional estimators. Our model can be used to predict the average collision rate. It enables an analysis of the effect of parameters such as rotor diameter or turbine type on the collision rate. The model can also be used in turbine-specific curtailment algorithms that predict the collision rate and reduce this rate with a minimal loss of energy production.

  7. Estimating bat and bird mortality occurring at wind energy turbines from covariates and carcass searches using mixture models.

    Directory of Open Access Journals (Sweden)

    Fränzi Korner-Nievergelt

    Full Text Available Environmental impacts of wind energy facilities increasingly cause concern, a central issue being bats and birds killed by rotor blades. Two approaches have been employed to assess collision rates: carcass searches and surveys of animals prone to collisions. Carcass searches can provide an estimate for the actual number of animals being killed but they offer little information on the relation between collision rates and, for example, weather parameters due to the time of death not being precisely known. In contrast, a density index of animals exposed to collision is sufficient to analyse the parameters influencing the collision rate. However, quantification of the collision rate from animal density indices (e.g. acoustic bat activity or bird migration traffic rates remains difficult. We combine carcass search data with animal density indices in a mixture model to investigate collision rates. In a simulation study we show that the collision rates estimated by our model were at least as precise as conventional estimates based solely on carcass search data. Furthermore, if certain conditions are met, the model can be used to predict the collision rate from density indices alone, without data from carcass searches. This can reduce the time and effort required to estimate collision rates. We applied the model to bat carcass search data obtained at 30 wind turbines in 15 wind facilities in Germany. We used acoustic bat activity and wind speed as predictors for the collision rate. The model estimates correlated well with conventional estimators. Our model can be used to predict the average collision rate. It enables an analysis of the effect of parameters such as rotor diameter or turbine type on the collision rate. The model can also be used in turbine-specific curtailment algorithms that predict the collision rate and reduce this rate with a minimal loss of energy production.

  8. Short-Term Wind Speed Forecasting Using the Data Processing Approach and the Support Vector Machine Model Optimized by the Improved Cuckoo Search Parameter Estimation Algorithm

    Directory of Open Access Journals (Sweden)

    Chen Wang

    2016-01-01

    Full Text Available Power systems could be at risk when the power-grid collapse accident occurs. As a clean and renewable resource, wind energy plays an increasingly vital role in reducing air pollution and wind power generation becomes an important way to produce electrical power. Therefore, accurate wind power and wind speed forecasting are in need. In this research, a novel short-term wind speed forecasting portfolio has been proposed using the following three procedures: (I data preprocessing: apart from the regular normalization preprocessing, the data are preprocessed through empirical model decomposition (EMD, which reduces the effect of noise on the wind speed data; (II artificially intelligent parameter optimization introduction: the unknown parameters in the support vector machine (SVM model are optimized by the cuckoo search (CS algorithm; (III parameter optimization approach modification: an improved parameter optimization approach, called the SDCS model, based on the CS algorithm and the steepest descent (SD method is proposed. The comparison results show that the simple and effective portfolio EMD-SDCS-SVM produces promising predictions and has better performance than the individual forecasting components, with very small root mean squared errors and mean absolute percentage errors.

  9. Shear and Turbulence Estimates for Calculation of Wind Turbine Loads and Responses Under Hurricane Strength Winds

    Science.gov (United States)

    Kosovic, B.; Bryan, G. H.; Haupt, S. E.

    2012-12-01

    Schwartz et al. (2010) recently reported that the total gross energy-generating offshore wind resource in the United States in waters less than 30m deep is approximately 1000 GW. Estimated offshore generating capacity is thus equivalent to the current generating capacity in the United States. Offshore wind power can therefore play important role in electricity production in the United States. However, most of this resource is located along the East Coast of the United States and in the Gulf of Mexico, areas frequently affected by tropical cyclones including hurricanes. Hurricane strength winds, associated shear and turbulence can affect performance and structural integrity of wind turbines. In a recent study Rose et al. (2012) attempted to estimate the risk to offshore wind turbines from hurricane strength winds over a lifetime of a wind farm (i.e. 20 years). According to Rose et al. turbine tower buckling has been observed in typhoons. They concluded that there is "substantial risk that Category 3 and higher hurricanes can destroy half or more of the turbines at some locations." More robust designs including appropriate controls can mitigate the risk of wind turbine damage. To develop such designs good estimates of turbine loads under hurricane strength winds are essential. We use output from a large-eddy simulation of a hurricane to estimate shear and turbulence intensity over first couple of hundred meters above sea surface. We compute power spectra of three velocity components at several distances from the eye of the hurricane. Based on these spectra analytical spectral forms are developed and included in TurbSim, a stochastic inflow turbulence code developed by the National Renewable Energy Laboratory (NREL, http://wind.nrel.gov/designcodes/preprocessors/turbsim/). TurbSim provides a numerical simulation including bursts of coherent turbulence associated with organized turbulent structures. It can generate realistic flow conditions that an operating turbine

  10. Robust and Fault-Tolerant Linear Parameter-Varying Control of Wind Turbines

    DEFF Research Database (Denmark)

    Sloth, Christoffer; Esbensen, Thomas; Stoustrup, Jakob

    2011-01-01

    High performance and reliability are required for wind turbines to be competitive within the energy market. To capture their nonlinear behavior, wind turbines are often modeled using parameter-varying models. In this paper we design and compare multiple linear parameter-varying (LPV) controllers,...

  11. Estimation of wind and solar resources in Mali

    Energy Technology Data Exchange (ETDEWEB)

    Badger, J.; Kamissoko, F.; Olander Rasmussen, M.; Larsen, Soeren; Guidon, N.; Boye Hansen, L.; Dewilde, L.; Alhousseini, M.; Noergaard, P.; Nygaard, I.

    2012-11-15

    The wind resource has been estimated for all of Mali at 7.5 km resolution using the KAMM/WAsP numerical wind atlas methodology. Three domains were used to cover entire country and three sets of wind classes used to capture change in large scale forcing over country. The final output includes generalized climate statistics for any location in Mali, giving wind direction and wind speed distribution. The modelled generalized climate statistics can be used directly in the WAsP software. The preliminary results show a wind resource, which is relatively low, but which under certain conditions may be economically feasible, i.e. at favourably exposed sites, giving enhanced winds, and where practical utilization is possible, given consideration to grid connection or replacement or augmentation of diesel-based electricity systems. The solar energy resource for Mali was assessed for the period between July 2008 and June 2011 using a remote sensing based estimate of the down-welling surface shortwave flux. The remote sensing estimates were adjusted on a month-by-month basis to account for seasonal differences between the remote sensing estimates and in situ data. Calibration was found to improve the coefficient of determination as well as decreasing the mean error both for the calibration and validation data. Compared to the results presented in the ''Renewable energy resources in Mali - preliminary mapping''-report that showed a tendency for underestimation compared to data from the NASA PPOWER/SSE database, the presented results show a very good agreement with the in situ data (after calibration) with no significant bias. Unfortunately, the NASA-database only contains data up until 2005, so a similar comparison could not be done for the time period analyzed in this study, although the agreement with the historic NASA data is still useful as reference. (LN)

  12. Voyager microwave scintillation measurements of solar wind plasma parameters

    International Nuclear Information System (INIS)

    Martin, J.M.

    1985-01-01

    During the solar conjunctions of Voyager 1 and 2 spacecraft in August 1979, September 1980, and November 1982, temporal variations of intensity and frequency of the dual-wavelength (3.6 and 13 cm) radio transmissions from the spacecraft were observed and subsequently analyzed to infer characteristics of the solar wind plasma flow. Measurements of the temporal wave structure function were used to estimate the spectral index of the power law spatial spectrum of irregularities. Theoretical-intensity scintillation spectra were compared with measured intensity spectra to obtain least-squares estimates of (1) mean velocity, (2) random velocity, (3) axial ratio, and (4) electron density standard deviation. Uncertainties in parameter estimates were calculated by standard propagation of errors techniques. Mean velocity and electron density standard deviations in 1979-1980 show little dependence on solar latitude. Density standard deviation estimates were 3-10% of the background mean density and mean velocity estimates ranged from approx.200 km/s inside 17 solar radii to approx.300 km/s at 25 solar radii. 1982 density standard deviation estimates increased rapidly with latitude near 45 0 N, then sharply decreased north of that latitude, indicating the existence of a polar region of reduced fluctuations surrounded by a thin cone of strong density irregularities

  13. Study on wind turbine for Yamagata wind energy institute. Comparison of the actual and estimate values for electric power; Yamagata furyoku hatsudensho no fusha ni tsuite. Hatsudenryo yosoku to jissekichi no hikaku

    Energy Technology Data Exchange (ETDEWEB)

    Nagai, H [Nihon University, Tokyo (Japan); Kojima, T [Yamagata Wind Energy Institute, Yamagata (Japan)

    1996-10-27

    For two 400kW wind turbines erected in Jan. 1996 of Yamagata Wind Energy Institute, their estimated power output was compared with actual output for 7 months. AMeDAS data in 1985-94 were totaled every month to use as basic data. The altitude and surface roughness model necessary for WAsP analysis recommended by NEDO`s wind condition close inspection manual were prepared using 1/25,000 maps and aerial photographs. The obstacle model for estimating wind conditions at height of the wind turbine was prepared using the data obtained by field survey. Mean wind velocity and latent energy were determined by statistical analysis of wind velocity occurrence relative frequencies and Weibull distribution parameters. The power output of 717,700kWh was obtained for 7 months, which is equivalent to 88.5% of the estimated output of 810,730kWh for the same period. It was clarified from obtained characteristic wind conditions at the site that the wind power generation is promising at the site not only in winter but also in summer. Although the test period was too short, this method was effective as analytical method of output estimation in the planning stage of wind turbines. 3 refs., 8 figs., 4 tabs.

  14. Estimation of the uncertainty in wind power forecasting

    International Nuclear Information System (INIS)

    Pinson, P.

    2006-03-01

    WIND POWER experiences a tremendous development of its installed capacities in Europe. Though, the intermittence of wind generation causes difficulties in the management of power systems. Also, in the context of the deregulation of electricity markets, wind energy is penalized by its intermittent nature. It is recognized today that the forecasting of wind power for horizons up to 2/3-day ahead eases the integration of wind generation. Wind power forecasts are traditionally provided in the form of point predictions, which correspond to the most-likely power production for a given horizon. That sole information is not sufficient for developing optimal management or trading strategies. Therefore, we investigate on possible ways for estimating the uncertainty of wind power forecasts. The characteristics of the prediction uncertainty are described by a thorough study of the performance of some of the state-of-the-art approaches, and by underlining the influence of some variables e.g. level of predicted power on distributions of prediction errors. Then, a generic method for the estimation of prediction intervals is introduced. This statistical method is non-parametric and utilizes fuzzy logic concepts for integrating expertise on the prediction uncertainty characteristics. By estimating several prediction intervals at once, one obtains predictive distributions of wind power output. The proposed method is evaluated in terms of its reliability, sharpness and resolution. In parallel, we explore the potential use of ensemble predictions for skill forecasting. Wind power ensemble forecasts are obtained either by converting meteorological ensembles (from ECMWF and NCEP) to power or by applying a poor man's temporal approach. A proposal for the definition of prediction risk indices is given, reflecting the disagreement between ensemble members over a set of successive look-ahead times. Such prediction risk indices may comprise a more comprehensive signal on the expected level

  15. Structured Linear Parameter Varying Control of Wind Turbines

    DEFF Research Database (Denmark)

    Adegas, Fabiano Daher; Sloth, Christoffer; Stoustrup, Jakob

    2012-01-01

    High performance and reliability are required for wind turbines to be competitive within the energy market. To capture their nonlinear behavior, wind turbines are often modeled using parameter-varying models. In this chapter, a framework for modelling and controller design of wind turbines is pre...... in the controller synthesis are solved by an iterative LMI-based algorithm. The resulting controllers can also be easily implemented in practice due to low data storage and simple math operations. The performance of the LPV controllers is assessed by nonlinear simulations results....

  16. Reassessing Wind Potential Estimates for India: Economic and Policy Implications

    Energy Technology Data Exchange (ETDEWEB)

    Phadke, Amol; Bharvirkar, Ranjit; Khangura, Jagmeet

    2011-09-15

    We assess developable on-shore wind potential in India at three different hub-heights and under two sensitivity scenarios – one with no farmland included, the other with all farmland included. Under the “no farmland included” case, the total wind potential in India ranges from 748 GW at 80m hub-height to 976 GW at 120m hub-height. Under the “all farmland included” case, the potential with a minimum capacity factor of 20 percent ranges from 984 GW to 1,549 GW. High quality wind energy sites, at 80m hub-height with a minimum capacity factor of 25 percent, have a potential between 253 GW (no farmland included) and 306 GW (all farmland included). Our estimates are more than 15 times the current official estimate of wind energy potential in India (estimated at 50m hub height) and are about one tenth of the official estimate of the wind energy potential in the US.

  17. Estimation of the Possible Power of a Wind Farm

    DEFF Research Database (Denmark)

    Mirzaei, Mahmood; Göçmen Bozkurt, Tuhfe; Giebel, Gregor

    2014-01-01

    the possible power calculated based on the estimated effective wind speed of a down regulated wind farm (the industry standard) is compared against the calculated possible power based on the algorithm presented in the paper. The latter takes into account the eect of the wakes of down regulated turbines......It seems possible to increase competitiveness of wind power plants by offering grid services (also called ancillary services) and enter the wind power plants into the ancillary market. One of the ancillary services is called reserve power, the differential capacity between the generated power...... and the available power in the farm. The total amount of energy that a wind farm can potentially generate is called possible power. It is very important for a wind farm owner to have a relatively accurate estimate of the possible power of the wind farm in order to be able to trade the reserve power. In this paper...

  18. Fatigue-Damage Estimation and Control for Wind Turbines

    OpenAIRE

    Barradas Berglind, Jose de Jesus

    2015-01-01

    How can fatigue-damage for control of wind turbines be represented? Fatigue-damage is indeed a crucial factor in structures such as wind turbines that are exposed to turbulent and rapidly changing wind flow conditions. This is relevant both in their design stage and during the control of their operation. Accordingly, the most recognized methods of fatigue-damage estimation are discussed in this thesis.In wind energy conversion systems there is an intrinsic trade-off between power generation m...

  19. Estimation of wind stress using dual-frequency TOPEX data

    Science.gov (United States)

    Elfouhaily, Tanos; Vandemark, Douglas; Gourrion, Jéro‸me; Chapron, Bertrand

    1998-10-01

    The TOPEX/POSEIDON satellite carries the first dual-frequency radar altimeter. Monofrequency (Ku-band) algorithms are presently used to retrieve surface wind speed from the altimeter's radar cross-section measurement (σ0Ku). These algorithms work reasonably well, but it is also known that altimeter wind estimates can be contaminated by residual effects, such as sea state, embedded in the σ0Ku measurement. Investigating the potential benefit of using two frequencies for wind retrieval, it is shown that a simple evaluation of TOPEX data yields previously unavailable information, particularly for high and low wind speeds. As the wind speed increases, the dual-frequency data provides a measurement more directly linked to the short-scale surface roughness, which in turn is associated with the local surface wind stress. Using a global TOPEX σ0° data set and TOPEX's significant wave height (Hs) estimate as a surrogate for the sea state's degree of development, it is also shown that differences between the two TOPEX σ0 measurements strongly evidence nonlocal sea state signature. A composite scattering theory is used to show how the dual-frequency data can provide an improved friction velocity model, especially for winds above 7 m/s. A wind speed conversion is included using a sea state dependent drag coefficient fed with TOPEX Hs data. Two colocated TOPEX-buoy data sets (from the National Data Buoy Center (NDBC) and the Structure des Echanges Mer-Atmosphre, Proprietes des Heterogeneites Oceaniques: Recherche Expérimentale (SEMAPHORE) campaign) are employed to test the new wind speed algorithm. A measurable improvement in wind speed estimation is obtained when compared to the monofrequency Witter and Chelton [1991] model.

  20. Fatigue-Damage Estimation and Control for Wind Turbines

    DEFF Research Database (Denmark)

    Barradas Berglind, Jose de Jesus

    How can fatigue-damage for control of wind turbines be represented? Fatigue-damage is indeed a crucial factor in structures such as wind turbines that are exposed to turbulent and rapidly changing wind flow conditions. This is relevant both in their design stage and during the control......, the inclusion of fatigue-damage within feedback control loops is of special interest. Four strategies in total are proposed in this work: three for the wind turbine level and one for the wind farm level. On one hand, the three strategies in the turbine level are based on hysteresis operators and strive......-damage estimation in wind turbine components, to the mixed objective operation of wind energy conversion systems, and to the synthesis of control strategies that include hysteresis operators....

  1. Optomechanical parameter estimation

    International Nuclear Information System (INIS)

    Ang, Shan Zheng; Tsang, Mankei; Harris, Glen I; Bowen, Warwick P

    2013-01-01

    We propose a statistical framework for the problem of parameter estimation from a noisy optomechanical system. The Cramér–Rao lower bound on the estimation errors in the long-time limit is derived and compared with the errors of radiometer and expectation–maximization (EM) algorithms in the estimation of the force noise power. When applied to experimental data, the EM estimator is found to have the lowest error and follow the Cramér–Rao bound most closely. Our analytic results are envisioned to be valuable to optomechanical experiment design, while the EM algorithm, with its ability to estimate most of the system parameters, is envisioned to be useful for optomechanical sensing, atomic magnetometry and fundamental tests of quantum mechanics. (paper)

  2. Wind Loads on Ships and Offshore Structures Estimated by CFD

    DEFF Research Database (Denmark)

    Aage, Christian; Hvid, S.L.; Hughes, P.H.

    1997-01-01

    Wind loads on ships and offshore structures could until recently be determined only by model tests, or by statistical methods based on model tests. By the development of Computational Fluid Dynamics or CFD there is now a realistic computational alternative available. In this paper, wind loads...... on a seagoing ferry and on a semisubmersible offshore platform have been estimated by CFD. The results have been compared with wind tunnel model tests and, for the ferry, a few full-scale measurements, and good agreement is obtained. The CFD method offers the possibility of a computational estimate of scale...... effects related to wind tunnel model testing. An example of such an estimate on the ferry is discussed. Due to the time involved in generating the computational mesh and in computing the solution, the CFD method is not at the moment economically competitive to routine wind tunnel model testing....

  3. Tuning of the PI Controller Parameters of a PMSG Wind Turbine to Improve Control Performance under Various Wind Speeds

    Directory of Open Access Journals (Sweden)

    Yun-Su Kim

    2015-02-01

    Full Text Available This paper presents a method to seek the PI controller parameters of a PMSG wind turbine to improve control performance. Since operating conditions vary with the wind speed, therefore the PI controller parameters should be determined as a function of the wind speed. Small-signal modeling of a PMSG WT is implemented to analyze the stability under various operating conditions and with eigenvalues obtained from the small-signal model of the PMSG WT, which are coordinated by adjusting the PI controller parameters. The parameters to be tuned are chosen by investigating participation factors of state variables, which simplifies the problem by reducing the number of parameters to be tuned. The process of adjusting these PI controller parameters is carried out using particle swarm optimization (PSO. To characterize the improvements in the control method due to the PSO method of tuning the PI controller parameters, the PMSG WT is modeled using the MATLAB/SimPowerSystems libraries with the obtained PI controller parameters.

  4. Estimation of turbulence intensity using rotor effective wind speed in Lillgrund and Horns Rev-I offshore wind farms

    DEFF Research Database (Denmark)

    Gögmen, Tuhfe; Giebel, Gregor

    2016-01-01

    varies over the extent of the wind farm. This paper describes a method to estimate the TI at individual turbine locations by using the rotor effective wind speed calculated via high frequency turbine data. The method is applied to Lillgrund and Horns Rev-I offshore wind farms and the results are compared...... with TI derived from the meteorological mast, nacelle mounted anemometer on the turbines and estimation based on the standard deviation of power. The results show that the proposed TI estimation method is in the best agreement with the meteorological mast. Therefore, the rotor effective wind speed...... is shown to be applicable for the TI assessment in real-time wind farm calculations under different operational conditions. Furthermore, the TI in the wake is seen to follow the same trend with the estimated wake deficit which enables to quantify the turbulence in terms of the wake loss locally inside...

  5. determination of weibull parameters and analysis of wind power

    African Journals Online (AJOL)

    HOD

    shape parameter (k) and the scale factor(c) were obtained to be 6.7 m/s and 4.3 m/s, 0.91 MW and 0.25 MW, K~ 5.4 and. 2.1, and c ... China, the forecast is not different as the report of the ..... Distribution for Wind Energy Analysis”, J. Wind Eng.

  6. Empirical investigation on using wind speed volatility to estimate the operation probability and power output of wind turbines

    International Nuclear Information System (INIS)

    Liu, Heping; Shi, Jing; Qu, Xiuli

    2013-01-01

    Highlights: ► Ten-minute wind speed and power generation data of an offshore wind turbine are used. ► An ARMA–GARCH-M model is built to simultaneously forecast wind speed mean and volatility. ► The operation probability and expected power output of the wind turbine are predicted. ► The integrated approach produces more accurate wind power forecasting than other conventional methods. - Abstract: In this paper, we introduce a quantitative methodology that performs the interval estimation of wind speed, calculates the operation probability of wind turbine, and forecasts the wind power output. The technological advantage of this methodology stems from the empowered capability of mean and volatility forecasting of wind speed. Based on the real wind speed and corresponding wind power output data from an offshore wind turbine, this methodology is applied to build an ARMA–GARCH-M model for wind speed forecasting, and then to compute the operation probability and the expected power output of the wind turbine. The results show that the developed methodology is effective, the obtained interval estimation of wind speed is reliable, and the forecasted operation probability and expected wind power output of the wind turbine are accurate

  7. Assessment of Wind Datasets for Estimating Offshore Wind Energy along the Central California Coast

    Science.gov (United States)

    Wang, Y. H.; Walter, R. K.; Ruttenberg, B.; White, C.

    2017-12-01

    Offshore renewable energy along the central California coastline has gained significant interest in recent years. We present a comprehensive analysis of near-surface wind datasets available in this region to facilitate future estimates of wind power generation potential. The analyses are based on local NDBC buoys, satellite-based measurements (QuickSCAT and CCMP V2.0), reanalysis products (NARR and MERRA), and a regional climate model (WRF). There are substantial differences in the diurnal signal during different months among the various products (i.e., satellite-based, reanalysis, and modeled) relative to the local buoys. Moreover, the datasets tended to underestimate wind speed under light wind conditions and overestimate under strong wind conditions. In addition to point-to-point comparisons against local buoys, the spatial variations of bias and error in both the reanalysis products and WRF model data in this region were compared against satellite-based measurements. NARR's bias and root-mean-square-error were generally small in the study domain and decreased with distance from coastlines. Although its smaller spatial resolution is likely to be insufficient to reveal local effects, the small bias and error in near-surface winds, as well as the availability of wind data at the proposed turbine hub heights, suggests that NARR is an ideal candidate for use in offshore wind energy production estimates along the central California coast. The framework utilized here could be applied in other site-specific regions where offshore renewable energy is being considered.

  8. Wind Plant Preconstruction Energy Estimates. Current Practice and Opportunities

    Energy Technology Data Exchange (ETDEWEB)

    Clifton, Andrew [National Renewable Energy Lab. (NREL), Golden, CO (United States); Smith, Aaron [National Renewable Energy Lab. (NREL), Golden, CO (United States); Fields, Michael [National Renewable Energy Lab. (NREL), Golden, CO (United States)

    2016-04-19

    Understanding the amount of energy that will be harvested by a wind power plant each year and the variability of that energy is essential to assessing and potentially improving the financial viability of that power plant. The preconstruction energy estimate process predicts the amount of energy--with uncertainty estimates--that a wind power plant will deliver to the point of revenue. This report describes the preconstruction energy estimate process from a technical perspective and seeks to provide insight into the financial implications associated with each step.

  9. Calculation of Wind Speeds for Return Period Using Weibull Parameter: A Case Study of Hanbit NPP Area

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Jongk Uk; Lee, Kwan Hee; Kim, Sung Il; Yook, Dae Sik; Ahn, Sang Myeon [KINS, Daejeon (Korea, Republic of)

    2016-05-15

    Evaluation of the meteorological characteristics at the nuclear power plant and in the surrounding area should be performed in determining the site suitability for safe operation of the nuclear power plant. Under unexpected emergency condition, knowledge of meteorological information on the site area is important to provide the basis for estimating environmental impacts resulting from radioactive materials released in gaseous effluents during the accident condition. In the meteorological information, wind speed and direction are the important meteorological factors for examination of the safety analysis in the nuclear power plant area. Wind characteristics was analyzed on Hanbit NPP area. It was found that the Weibull parameters k and c vary 2.56 to 4.77 and 4.53 to 6.79 for directional wind speed distribution, respectively. Maximum wind frequency was NE and minimum was NNW.

  10. Estimation of Transformer Parameters and Loss Analysis for High Voltage Capacitor Charging Application

    DEFF Research Database (Denmark)

    Thummala, Prasanth; Schneider, Henrik; Ouyang, Ziwei

    2013-01-01

    In a bi-directional DC-DC converter for capacitive charging application, the losses associated with the transformer makes it a critical component. In order to calculate the transformer losses, its parameters such as AC resistance, leakage inductance and self capacitance of the high voltage (HV......) winding has to be estimated accurately. This paper analyzes the following losses of bi-directional flyback converter namely switching loss, conduction loss, gate drive loss, transformer core loss, and snubber loss, etc. Iterative analysis of transformer parameters viz., AC resistance, leakage inductance...

  11. Profitability of locations for wind energy utilization. Investigation of the significant influence parameters

    International Nuclear Information System (INIS)

    Wallasch, Anna-Kathrin; Rehfeldt, Knud

    2012-04-01

    The jurisdiction for the designation of sites for wind energy requires that sufficient space was procured within the created sites for wind energy to achieve an exclusionary effect in the rest of the plan area of wind energy. This means that the designated areas must allow the economic operation of wind turbines. It is often not easy to adequately determine and assess the suitability of an area. The project economics of wind energy projects is dependent on the individual case, and there is no general guideline for estimating the decision of municipalities. In the case of allegations of so-called ''prevention plan'' against communities in which seemingly unsuitable areas have been identified the dispute is usually settled by court. This represents a considerable effort. At this point, the present investigation shall begin to prepare and carry out more detailed studies on the economics of wind energy sites, which can be used for orientation in the evaluation of possible identified areas for wind energy. For this purpose, the results of the power generation costs of wind energy projects from the Scientific accompanying report wind energy for EEG Progress Report will first used and collectively evaluated, what conclusions can be obtained based on these results for the profitability of locations. Based on the database, which was developed as part of the scientific opinion accompanying wind energy for EEG Progress Report, then a sensitivity analysis is carried out with regard to individual parameters of the economics of wind energy projects. This means individual factors within the sample locations are varied and analyzes the impact on the project economics. Thus, statements about can be taken, how limits for individual factors can be defined in terms of project economics. [de

  12. Applications of wind generation for power system frequency control, inter-area oscillations damping and parameter identification

    Science.gov (United States)

    Wilches-Bernal, Felipe

    of the WTG while the second controller manipulates the reactive power control of the WTG using the current magnitude as the feedback signal. Finally, the dissertation proposes a parameter identification method for identifying and verifying the reactive power control parameters of WTGs. Using voltage and current measurements of a wind unit as an input, the proposed method estimates an optimal set of parameters such that the output current of a standalone WTG model better approximates the measured signal. Because WTG are nonlinear systems, the identification method is solved by a Gauss-Newton iteration used to calculate the solution of a nonlinear least-squares problem. The effectiveness of the proposed method is illustrated using a set of simulated data and actual PMU recordings.

  13. Tuning of the PI Controller Parameters of a PMSG Wind Turbine to Improve Control Performance under Various Wind Speeds

    OpenAIRE

    Yun-Su Kim; Il-Yop Chung; Seung-Il Moon

    2015-01-01

    This paper presents a method to seek the PI controller parameters of a PMSG wind turbine to improve control performance. Since operating conditions vary with the wind speed, therefore the PI controller parameters should be determined as a function of the wind speed. Small-signal modeling of a PMSG WT is implemented to analyze the stability under various operating conditions and with eigenvalues obtained from the small-signal model of the PMSG WT, which are coordinated by adjusting the PI con...

  14. Applied parameter estimation for chemical engineers

    CERN Document Server

    Englezos, Peter

    2000-01-01

    Formulation of the parameter estimation problem; computation of parameters in linear models-linear regression; Gauss-Newton method for algebraic models; other nonlinear regression methods for algebraic models; Gauss-Newton method for ordinary differential equation (ODE) models; shortcut estimation methods for ODE models; practical guidelines for algorithm implementation; constrained parameter estimation; Gauss-Newton method for partial differential equation (PDE) models; statistical inferences; design of experiments; recursive parameter estimation; parameter estimation in nonlinear thermodynam

  15. Wind gust estimation by combining numerical weather prediction model and statistical post-processing

    Science.gov (United States)

    Patlakas, Platon; Drakaki, Eleni; Galanis, George; Spyrou, Christos; Kallos, George

    2017-04-01

    The continuous rise of off-shore and near-shore activities as well as the development of structures, such as wind farms and various offshore platforms, requires the employment of state-of-the-art risk assessment techniques. Such analysis is used to set the safety standards and can be characterized as a climatologically oriented approach. Nevertheless, a reliable operational support is also needed in order to minimize cost drawbacks and human danger during the construction and the functioning stage as well as during maintenance activities. One of the most important parameters for this kind of analysis is the wind speed intensity and variability. A critical measure associated with this variability is the presence and magnitude of wind gusts as estimated in the reference level of 10m. The latter can be attributed to different processes that vary among boundary-layer turbulence, convection activities, mountain waves and wake phenomena. The purpose of this work is the development of a wind gust forecasting methodology combining a Numerical Weather Prediction model and a dynamical statistical tool based on Kalman filtering. To this end, the parameterization of Wind Gust Estimate method was implemented to function within the framework of the atmospheric model SKIRON/Dust. The new modeling tool combines the atmospheric model with a statistical local adaptation methodology based on Kalman filters. This has been tested over the offshore west coastline of the United States. The main purpose is to provide a useful tool for wind analysis and prediction and applications related to offshore wind energy (power prediction, operation and maintenance). The results have been evaluated by using observational data from the NOAA's buoy network. As it was found, the predicted output shows a good behavior that is further improved after the local adjustment post-process.

  16. Improved Estimates of Thermodynamic Parameters

    Science.gov (United States)

    Lawson, D. D.

    1982-01-01

    Techniques refined for estimating heat of vaporization and other parameters from molecular structure. Using parabolic equation with three adjustable parameters, heat of vaporization can be used to estimate boiling point, and vice versa. Boiling points and vapor pressures for some nonpolar liquids were estimated by improved method and compared with previously reported values. Technique for estimating thermodynamic parameters should make it easier for engineers to choose among candidate heat-exchange fluids for thermochemical cycles.

  17. Application of microwave radiometer and wind profiler data in the estimation of wind gust associated with intense convective weather

    International Nuclear Information System (INIS)

    Chan, P W; Wong, K H

    2008-01-01

    Estimates of the wind gusts associated with intense convective weather could be obtained using empirical relationships such as GUSTEX based on radiosonde measurements. However, such data are only available a couple of times a day and may not reflect the rapidly changing atmospheric condition in spring and summer times. The feasibility of combining the thermodynamic profiles from a ground-based microwave radiometer and wind profiles given by radar wind profilers in the continuous estimation of wind gusts is studied in this paper. Based on the results of a 4-month trial of a microwave radiometer in Hong Kong in 2004, the estimated and the actual gusts are reasonably well correlated. It is also found that the wind gusts so estimated provide better indications of the strength of squalls compared with those based on radiosonde measurements and with a lead time of about one hour

  18. Potential of neuro-fuzzy methodology to estimate noise level of wind turbines

    Science.gov (United States)

    Nikolić, Vlastimir; Petković, Dalibor; Por, Lip Yee; Shamshirband, Shahaboddin; Zamani, Mazdak; Ćojbašić, Žarko; Motamedi, Shervin

    2016-01-01

    Wind turbines noise effect became large problem because of increasing of wind farms numbers since renewable energy becomes the most influential energy sources. However, wind turbine noise generation and propagation is not understandable in all aspects. Mechanical noise of wind turbines can be ignored since aerodynamic noise of wind turbine blades is the main source of the noise generation. Numerical simulations of the noise effects of the wind turbine can be very challenging task. Therefore in this article soft computing method is used to evaluate noise level of wind turbines. The main goal of the study is to estimate wind turbine noise in regard of wind speed at different heights and for different sound frequency. Adaptive neuro-fuzzy inference system (ANFIS) is used to estimate the wind turbine noise levels.

  19. Mixture distributions of wind speed in the UAE

    Science.gov (United States)

    Shin, J.; Ouarda, T.; Lee, T. S.

    2013-12-01

    Wind speed probability distribution is commonly used to estimate potential wind energy. The 2-parameter Weibull distribution has been most widely used to characterize the distribution of wind speed. However, it is unable to properly model wind speed regimes when wind speed distribution presents bimodal and kurtotic shapes. Several studies have concluded that the Weibull distribution should not be used for frequency analysis of wind speed without investigation of wind speed distribution. Due to these mixture distributional characteristics of wind speed data, the application of mixture distributions should be further investigated in the frequency analysis of wind speed. A number of studies have investigated the potential wind energy in different parts of the Arabian Peninsula. Mixture distributional characteristics of wind speed were detected from some of these studies. Nevertheless, mixture distributions have not been employed for wind speed modeling in the Arabian Peninsula. In order to improve our understanding of wind energy potential in Arabian Peninsula, mixture distributions should be tested for the frequency analysis of wind speed. The aim of the current study is to assess the suitability of mixture distributions for the frequency analysis of wind speed in the UAE. Hourly mean wind speed data at 10-m height from 7 stations were used in the current study. The Weibull and Kappa distributions were employed as representatives of the conventional non-mixture distributions. 10 mixture distributions are used and constructed by mixing four probability distributions such as Normal, Gamma, Weibull and Extreme value type-one (EV-1) distributions. Three parameter estimation methods such as Expectation Maximization algorithm, Least Squares method and Meta-Heuristic Maximum Likelihood (MHML) method were employed to estimate the parameters of the mixture distributions. In order to compare the goodness-of-fit of tested distributions and parameter estimation methods for

  20. Estimating the Probability of Wind Ramping Events: A Data-driven Approach

    OpenAIRE

    Wang, Cheng; Wei, Wei; Wang, Jianhui; Qiu, Feng

    2016-01-01

    This letter proposes a data-driven method for estimating the probability of wind ramping events without exploiting the exact probability distribution function (PDF) of wind power. Actual wind data validates the proposed method.

  1. Lifetime estimation for the power semiconductors considering mission profiles in wind power converter

    DEFF Research Database (Denmark)

    Ma, Ke; Liserre, Marco; Blaabjerg, Frede

    2013-01-01

    for the reliability improvement and also for cost reduction of wind power technology. Unfortunately, the existing lifetime estimation methods for the power electronic converter are not yet suitable in the wind power application, because the comprehensive mission profiles are not well specified and included......As a key component in the wind turbine system, power electronic converter and its power semiconductors suffer from adverse power loadings related to environment, and are proven to have certain failure rates. Therefore, correct lifetime estimation of wind power converter is crucial...... estimation, more detailed information for the reliability performance of wind power converter can be obtained....

  2. Frequency-Domain Maximum-Likelihood Estimation of High-Voltage Pulse Transformer Model Parameters

    CERN Document Server

    Aguglia, D; Martins, C.D.A.

    2014-01-01

    This paper presents an offline frequency-domain nonlinear and stochastic identification method for equivalent model parameter estimation of high-voltage pulse transformers. Such kinds of transformers are widely used in the pulsed-power domain, and the difficulty in deriving pulsed-power converter optimal control strategies is directly linked to the accuracy of the equivalent circuit parameters. These components require models which take into account electric fields energies represented by stray capacitance in the equivalent circuit. These capacitive elements must be accurately identified, since they greatly influence the general converter performances. A nonlinear frequency-based identification method, based on maximum-likelihood estimation, is presented, and a sensitivity analysis of the best experimental test to be considered is carried out. The procedure takes into account magnetic saturation and skin effects occurring in the windings during the frequency tests. The presented method is validated by experim...

  3. Comparison of several measure-correlate-predict models using support vector regression techniques to estimate wind power densities. A case study

    International Nuclear Information System (INIS)

    Díaz, Santiago; Carta, José A.; Matías, José M.

    2017-01-01

    Highlights: • Eight measure-correlate-predict (MCP) models used to estimate the wind power densities (WPDs) at a target site are compared. • Support vector regressions are used as the main prediction techniques in the proposed MCPs. • The most precise MCP uses two sub-models which predict wind speed and air density in an unlinked manner. • The most precise model allows to construct a bivariable (wind speed and air density) WPD probability density function. • MCP models trained to minimise wind speed prediction error do not minimise WPD prediction error. - Abstract: The long-term annual mean wind power density (WPD) is an important indicator of wind as a power source which is usually included in regional wind resource maps as useful prior information to identify potentially attractive sites for the installation of wind projects. In this paper, a comparison is made of eight proposed Measure-Correlate-Predict (MCP) models to estimate the WPDs at a target site. Seven of these models use the Support Vector Regression (SVR) and the eighth the Multiple Linear Regression (MLR) technique, which serves as a basis to compare the performance of the other models. In addition, a wrapper technique with 10-fold cross-validation has been used to select the optimal set of input features for the SVR and MLR models. Some of the eight models were trained to directly estimate the mean hourly WPDs at a target site. Others, however, were firstly trained to estimate the parameters on which the WPD depends (i.e. wind speed and air density) and then, using these parameters, the target site mean hourly WPDs. The explanatory features considered are different combinations of the mean hourly wind speeds, wind directions and air densities recorded in 2014 at ten weather stations in the Canary Archipelago (Spain). The conclusions that can be drawn from the study undertaken include the argument that the most accurate method for the long-term estimation of WPDs requires the execution of a

  4. Lumped-Parameter Models for Wind-Turbine Footings on Layered Ground

    DEFF Research Database (Denmark)

    Andersen, Lars; Liingaard, Morten

    2007-01-01

    The design of modern wind turbines is typically based on lifetime analyses using aeroelastic codes. In this regard, the impedance of the foundations must be described accurately without increasing the overall size of the computational model significantly. This may be obtained by the fitting...... of a lumped-parameter model to the results of a rigorous model or experimental results. In this paper, guidelines are given for the formulation of such lumped-parameter models and examples are given in which the models are utilised for the analysis of a wind turbine supported by a surface footing on a layered...

  5. Estimating the true energy value of a wind farm

    International Nuclear Information System (INIS)

    Bass, J.

    1995-01-01

    To assess the true energy yield of a wind farm taking into account real-world effects such as control losses in individual turbines, losses in the distribution network and wake and topographic effects, this report from the Energy Technology Support Unit, has developed a more appropriate methodology for making economic assessments of wind farm projects. Simulations of wind turbines are used to enable control losses to be quantified, and long term performance data from wind turbines in operational United Kingdom wind farms adds to the accuracy of assessment. A model has also been used to estimate performance of a power distribution system for a wind farm, to enable losses associated with wind turbine, wind speed and various distribution layouts to be predicted. Data on wake effects are drawn from a separate study. All these are drawn into an economic simulation model which predicts a wind farm's likely achievement of its target energy yield, thus demonstrating the risk factors involved. (UK)

  6. Effects of normal and extreme turbulence spectral parameters on wind turbine loads

    DEFF Research Database (Denmark)

    Dimitrov, Nikolay Krasimirov; Natarajan, Anand; Mann, Jakob

    2017-01-01

    the recommended values in the IEC 61400-1 Ed.3 that is used for wind turbine design. The present paper investigates the impact of Mann turbulence model parameter variations on the design loads envelope for 5 MW and 10 MW reference wind turbines. Specific focus is made on the blade root loads, tower top moments...... of design loads is investigated with a focus on the commonly used Mann turbulence model. Quantification of the Mann model parameters is made through wind measurements acquired from the Høvsøre site. The parameters of the Mann model fitted to site specific observations can differ significantly from...... and tower base loads under normal turbulence and extreme turbulence, whereby the change in operating extreme and fatigue design loads obtained through turbulence model parameter variations is compared with corresponding variations obtained from random seeds of turbulence. The investigations quantify...

  7. Model-based Estimation of Gas Leakage for Fluid Power Accumulators in Wind Turbines

    DEFF Research Database (Denmark)

    Liniger, Jesper; Pedersen, Henrik Clemmensen; N. Soltani, Mohsen

    2017-01-01

    for accumulators, namely gas leakage. The method utilizes an Extended Kalman Filter for joint state and parameter estimation with special attention to limiting the use of sensors to those commonly used in wind turbines. The precision of the method is investigated on an experimental setup which allows for operation...... of the accumulator similar to the conditions in a turbine. The results show that gas leakage is indeed detectable during start-up of the turbine and robust behavior is achieved in a multi-fault environment where both gas and external fluid leakage occur simultaneously. The estimation precision is shown...... to be sensitive to initial conditions for the gas temperature and volume....

  8. Synoptic maps of solar wind parameters from in situ spacecraft observations

    Science.gov (United States)

    Gazis, P. R.

    1995-01-01

    Solar wind observations from the Interplanetary Monitoring Platform-8 (IMP-8) and Pioneer Venus Orbiter (PVO) spacecraft from 1982 until 1988 are combined to construct synoptic maps of solar wind parameters near 1 AU. Each map consists of 6 months of hourly averaged solar wind data, binned by heliographic latitude and Carrington longitude and projected back to the Sun. These maps show the structure and time evolution of solar wind streams near 1 AU in the heliographic latitudes of +/- 7.25 deg and provide and explicit picture of several phenomena, such as gradients, changes in the inclination of the heliospheric current sheet, and the relative positions of various structures in the inner heliosphere, that is difficult to obtain from single-spacecraft observations. The stream structure varied significantly during the last solar cycle. Between 1982 and early 1985, solar wind parameters did not depend strongly on heliographic latitude. During the last solar minimum, the solar wind developed significant latitudinal structure, and high-speed streams were excluded from the vicinity of the solar equator. The interplanetary magnetic field was strongly correlated with the coronal field, and the current sheet tended to coincide with the coronal neutral line. The solar wind speed showed the expected correlations with temperature, interplanetary magnetic field, and distance from the current sheet. The solar wind speed was anticorrelated with density, but the regions of highest density occurred east of the heliospheric current sheet and the regions of lowest solar wind speed. This is consistent with compression at the leading edge of high-speed streams.

  9. Use of Bayesian networks classifiers for long-term mean wind turbine energy output estimation at a potential wind energy conversion site

    Energy Technology Data Exchange (ETDEWEB)

    Carta, Jose A. [Department of Mechanical Engineering, University of Las Palmas de Gran Canaria, Campus de Tafira s/n, 35017 Las Palmas de Gran Canaria, Canary Islands (Spain); Velazquez, Sergio [Department of Electronics and Automatics Engineering, University of Las Palmas de Gran Canaria, Campus de Tafira s/n, 35017 Las Palmas de Gran Canaria, Canary Islands (Spain); Matias, J.M. [Department of Statistics, University of Vigo, Lagoas Marcosende, 36200 Vigo (Spain)

    2011-02-15

    Due to the interannual variability of wind speed a feasibility analysis for the installation of a Wind Energy Conversion System at a particular site requires estimation of the long-term mean wind turbine energy output. A method is proposed in this paper which, based on probabilistic Bayesian networks (BNs), enables estimation of the long-term mean wind speed histogram for a site where few measurements of the wind resource are available. For this purpose, the proposed method allows the use of multiple reference stations with a long history of wind speed and wind direction measurements. That is to say, the model that is proposed in this paper is able to involve and make use of regional information about the wind resource. With the estimated long-term wind speed histogram and the power curve of a wind turbine it is possible to use the method of bins to determine the long-term mean energy output for that wind turbine. The intelligent system employed, the knowledgebase of which is a joint probability function of all the model variables, uses efficient calculation techniques for conditional probabilities to perform the reasoning. This enables automatic model learning and inference to be performed efficiently based on the available evidence. The proposed model is applied in this paper to wind speeds and wind directions recorded at four weather stations located in the Canary Islands (Spain). Ten years of mean hourly wind speed and direction data are available for these stations. One of the conclusions reached is that the BN with three reference stations gave fewer errors between the real and estimated long-term mean wind turbine energy output than when using two measure-correlate-predict algorithms which were evaluated and which use a linear regression between the candidate station and one reference station. (author)

  10. Use of Bayesian networks classifiers for long-term mean wind turbine energy output estimation at a potential wind energy conversion site

    International Nuclear Information System (INIS)

    Carta, Jose A.; Velazquez, Sergio; Matias, J.M.

    2011-01-01

    Due to the interannual variability of wind speed a feasibility analysis for the installation of a Wind Energy Conversion System at a particular site requires estimation of the long-term mean wind turbine energy output. A method is proposed in this paper which, based on probabilistic Bayesian networks (BNs), enables estimation of the long-term mean wind speed histogram for a site where few measurements of the wind resource are available. For this purpose, the proposed method allows the use of multiple reference stations with a long history of wind speed and wind direction measurements. That is to say, the model that is proposed in this paper is able to involve and make use of regional information about the wind resource. With the estimated long-term wind speed histogram and the power curve of a wind turbine it is possible to use the method of bins to determine the long-term mean energy output for that wind turbine. The intelligent system employed, the knowledgebase of which is a joint probability function of all the model variables, uses efficient calculation techniques for conditional probabilities to perform the reasoning. This enables automatic model learning and inference to be performed efficiently based on the available evidence. The proposed model is applied in this paper to wind speeds and wind directions recorded at four weather stations located in the Canary Islands (Spain). Ten years of mean hourly wind speed and direction data are available for these stations. One of the conclusions reached is that the BN with three reference stations gave fewer errors between the real and estimated long-term mean wind turbine energy output than when using two measure-correlate-predict algorithms which were evaluated and which use a linear regression between the candidate station and one reference station.

  11. Estimation of uncertainty of wind energy predictions with application to weather routing and wind power generation

    CERN Document Server

    Zastrau, David

    2017-01-01

    Wind drives in combination with weather routing can lower the fuel consumption of cargo ships significantly. For this reason, the author describes a mathematical method based on quantile regression for a probabilistic estimate of the wind propulsion force on a ship route.

  12. Hurricane Wind Speed Estimation Using WindSat 6 and 10 GHz Brightness Temperatures

    Directory of Open Access Journals (Sweden)

    Lei Zhang

    2016-08-01

    Full Text Available The realistic and accurate estimation of hurricane intensity is highly desired in many scientific and operational applications. With the advance of passive microwave polarimetry, an alternative opportunity for retrieving wind speed in hurricanes has become available. A wind speed retrieval algorithm for wind speeds above 20 m/s in hurricanes has been developed by using the 6.8 and 10.7 GHz vertically and horizontally polarized brightness temperatures of WindSat. The WindSat measurements for 15 category 4 and category 5 hurricanes from 2003 to 2010 and the corresponding H*wind analysis data are used to develop and validate the retrieval model. In addition, the retrieved wind speeds are also compared to the Remote Sensing Systems (RSS global all-weather product and stepped-frequency microwave radiometer (SFMR measurements. The statistical results show that the mean bias and the overall root-mean-square (RMS difference of the retrieved wind speeds with respect to the H*wind analysis data are 0.04 and 2.75 m/s, respectively, which provides an encouraging result for retrieving hurricane wind speeds over the ocean surface. The retrieved wind speeds show good agreement with the SFMR measurements. Two case studies demonstrate that the mean bias and RMS difference are 0.79 m/s and 1.79 m/s for hurricane Rita-1 and 0.63 m/s and 2.38 m/s for hurricane Rita-2, respectively. In general, the wind speed retrieval accuracy of the new model in hurricanes ranges from 2.0 m/s in light rain to 3.9 m/s in heavy rain.

  13. Study on the product estimation of small wind turbines; Kogata fusha no hatsudenryo yosoku ni kansuru kenkyu

    Energy Technology Data Exchange (ETDEWEB)

    Matsuzawa, K.; Kimura, Y.; Ushiyama, I. [Ashikaga Institute of Technology, Tochigi (Japan); Nagai, H. [Nihon Univ., Chiba (Japan). Coll. of Industrial Technology

    1998-09-01

    In order to clarify problems involved in application of Weibull probability distribution used for estimation of power production by a large wind turbine to a small wind turbine, and solutions thereof, the estimated results are compared with the observed ones. The conventional estimation method, when applied to a small wind turbine, tends to overestimate production of power, because of overestimated production in a high wind velocity range which occurs less frequently. Estimation of power produced by a wind turbine is based on working wind velocity range, determined from the furling mechanism for the power generation characteristics of the wind turbine concerned. In the case of a small wind turbine, on the other hand, better estimates are obtained from the working wind velocity range in which Weibull wind velocity distribution is used to determine probability of occurrence. For wind turbines working at low to medium wind velocities, such as Savonius wind turbine, the estimates are in fairly good agreement with the observed results, by which is meant that the conventional estimation method aided by Weibull distribution can be directly applicable to small wind turbines. 4 refs., 3 figs., 3 tabs.

  14. Estimation of cost and value of energy from wind turbines

    International Nuclear Information System (INIS)

    Tande, J.O.; Fransden, S.

    1995-01-01

    The International Energy Agency expert group on recommended practices for wind turbine testing and evaluation is finalizing a second edition of the E stimation of cost of energy from wind energy conversion systems . This paper summarizes those recommendations. Further, the value of wind energy in terms of the associated savings is discussed, and a case study is undertaken to illustrate wind energy cost/benefit analyses. The paper concludes that while the recommended practices on cost estimation may be useful in connection with wind energy feasibility studies there is still a need for further international agreement upon guidelines on how to assess wind energy benefits. (author)

  15. Scour depth estimation using an equation based on wind tunnel experiments

    Directory of Open Access Journals (Sweden)

    Tsutsui Takayuki

    2016-01-01

    Full Text Available Scour is the result of degradation and aggradation by wind or moving fluid in the front and back of a pole standing in sand, respectively, and is often observed at the bottom of bridge piers in rivers. In this study, we propose a method of estimating the scour depth around a cylindrical structure standing in sand. The relationships among the depth of the scour, the aspect ratio of the structure (= height/diameter, the fluid velocity, and the sand properties (particle size and density were determined experimentally using a wind tunnel. The experiments were carried out under clear-water scour conditions. In the experiments, the aspect ratio of the cylindrical structure, the fluid velocity, and the sand particle size were varied systematically. The diameters of the structure were 20, 40, and 60 mm, and the aspect ratio was varied from 0.25 to 3.0. Sand particles of four sizes (200, 275, 475, and 600 μm were used in the experiment, and the velocity was varied from 4 to 11 m/s. The depth and radius of the scour were measured. As a result, we have developed an equation for estimating the scour depth that uses the aspect ratio, fluid velocity, and sand particle size as parameters.

  16. Parameter estimation in plasmonic QED

    Science.gov (United States)

    Jahromi, H. Rangani

    2018-03-01

    We address the problem of parameter estimation in the presence of plasmonic modes manipulating emitted light via the localized surface plasmons in a plasmonic waveguide at the nanoscale. The emitter that we discuss is the nitrogen vacancy centre (NVC) in diamond modelled as a qubit. Our goal is to estimate the β factor measuring the fraction of emitted energy captured by waveguide surface plasmons. The best strategy to obtain the most accurate estimation of the parameter, in terms of the initial state of the probes and different control parameters, is investigated. In particular, for two-qubit estimation, it is found although we may achieve the best estimation at initial instants by using the maximally entangled initial states, at long times, the optimal estimation occurs when the initial state of the probes is a product one. We also find that decreasing the interqubit distance or increasing the propagation length of the plasmons improve the precision of the estimation. Moreover, decrease of spontaneous emission rate of the NVCs retards the quantum Fisher information (QFI) reduction and therefore the vanishing of the QFI, measuring the precision of the estimation, is delayed. In addition, if the phase parameter of the initial state of the two NVCs is equal to πrad, the best estimation with the two-qubit system is achieved when initially the NVCs are maximally entangled. Besides, the one-qubit estimation has been also analysed in detail. Especially, we show that, using a two-qubit probe, at any arbitrary time, enhances considerably the precision of estimation in comparison with one-qubit estimation.

  17. Parameter Estimation in Continuous Time Domain

    Directory of Open Access Journals (Sweden)

    Gabriela M. ATANASIU

    2016-12-01

    Full Text Available This paper will aim to presents the applications of a continuous-time parameter estimation method for estimating structural parameters of a real bridge structure. For the purpose of illustrating this method two case studies of a bridge pile located in a highly seismic risk area are considered, for which the structural parameters for the mass, damping and stiffness are estimated. The estimation process is followed by the validation of the analytical results and comparison with them to the measurement data. Further benefits and applications for the continuous-time parameter estimation method in civil engineering are presented in the final part of this paper.

  18. A novel application of artificial neural network for wind speed estimation

    Science.gov (United States)

    Fang, Da; Wang, Jianzhou

    2017-05-01

    Providing accurate multi-steps wind speed estimation models has increasing significance, because of the important technical and economic impacts of wind speed on power grid security and environment benefits. In this study, the combined strategies for wind speed forecasting are proposed based on an intelligent data processing system using artificial neural network (ANN). Generalized regression neural network and Elman neural network are employed to form two hybrid models. The approach employs one of ANN to model the samples achieving data denoising and assimilation and apply the other to predict wind speed using the pre-processed samples. The proposed method is demonstrated in terms of the predicting improvements of the hybrid models compared with single ANN and the typical forecasting method. To give sufficient cases for the study, four observation sites with monthly average wind speed of four given years in Western China were used to test the models. Multiple evaluation methods demonstrated that the proposed method provides a promising alternative technique in monthly average wind speed estimation.

  19. Lifetime estimation for the power semiconductors considering mission profiles in wind power converter

    OpenAIRE

    Ma, Ke; Liserre, Marco; Blaabjerg, Frede

    2013-01-01

    As a key component in the wind turbine system, power electronic converter and its power semiconductors suffer from adverse power loadings related to environment, and are proven to have certain failure rates. Therefore, correct lifetime estimation of wind power converter is crucial for the reliability improvement and also for cost reduction of wind power technology. Unfortunately, the existing lifetime estimation methods for the power electronic converter are not yet suitable in the wind power...

  20. Model-Based Estimation of Collision Risks of Predatory Birds with Wind Turbines

    Directory of Open Access Journals (Sweden)

    Marcus Eichhorn

    2012-06-01

    Full Text Available The expansion of renewable energies, such as wind power, is a promising way of mitigating climate change. Because of the risk of collision with rotor blades, wind turbines have negative effects on local bird populations, particularly on raptors such as the Red Kite (Milvus milvus. Appropriate assessment tools for these effects have been lacking. To close this gap, we have developed an agent-based, spatially explicit model that simulates the foraging behavior of the Red Kite around its aerie in a landscape consisting of different land-use types. We determined the collision risk of the Red Kite with the turbine as a function of the distance between the wind turbine and the aerie and other parameters. The impact function comprises the synergistic effects of species-specific foraging behavior and landscape structure. The collision risk declines exponentially with increasing distance. The strength of this decline depends on the raptor's foraging behavior, its ability to avoid wind turbines, and the mean wind speed in the region. The collision risks, which are estimated by the simulation model, are in the range of values observed in the field. The derived impact function shows that the collision risk can be described as an aggregated function of distance between the wind turbine and the raptor's aerie. This allows an easy and rapid assessment of the ecological impacts of (existing or planned wind turbines in relation to their spatial location. Furthermore, it implies that minimum buffer zones for different landscapes can be determined in a defensible way. This modeling approach can be extended to other bird species with central-place foraging behavior. It provides a helpful tool for landscape planning aimed at minimizing the impacts of wind power on biodiversity.

  1. ESTIMATION ACCURACY OF EXPONENTIAL DISTRIBUTION PARAMETERS

    Directory of Open Access Journals (Sweden)

    muhammad zahid rashid

    2011-04-01

    Full Text Available The exponential distribution is commonly used to model the behavior of units that have a constant failure rate. The two-parameter exponential distribution provides a simple but nevertheless useful model for the analysis of lifetimes, especially when investigating reliability of technical equipment.This paper is concerned with estimation of parameters of the two parameter (location and scale exponential distribution. We used the least squares method (LSM, relative least squares method (RELS, ridge regression method (RR,  moment estimators (ME, modified moment estimators (MME, maximum likelihood estimators (MLE and modified maximum likelihood estimators (MMLE. We used the mean square error MSE, and total deviation TD, as measurement for the comparison between these methods. We determined the best method for estimation using different values for the parameters and different sample sizes

  2. Coronal mass ejections and disturbances in solar wind plasma parameters in relation with geomagnetic storms

    International Nuclear Information System (INIS)

    Verma, P L; Singh, Puspraj; Singh, Preetam

    2014-01-01

    Coronal Mass Ejections (CMEs) are the drastic solar events in which huge amount of solar plasma materials are ejected into the heliosphere from the sun and are mainly responsible to generate large disturbances in solar wind plasma parameters and geomagnetic storms in geomagnetic field. We have studied geomagnetic storms, (Dst ≤-75 nT) observed during the period of 1997-2007 with Coronal Mass Ejections and disturbances in solar wind plasma parameters (solar wind temperature, velocity, density and interplanetary magnetic field) .We have inferred that most of the geomagnetic storms are associated with halo and partial halo Coronal Mass Ejections (CMEs).The association rate of halo and partial halo coronal mass ejections are found 72.37 % and 27.63 % respectively. Further we have concluded that geomagnetic storms are closely associated with the disturbances in solar wind plasma parameters. We have determined positive co-relation between magnitudes of geomagnetic storms and magnitude of jump in solar wind plasma temperature, jump in solar wind plasma density, jump in solar wind plasma velocity and jump in average interplanetary magnetic field with co-relation co-efficient 0 .35 between magnitude of geomagnetic storms and magnitude of jump in solar wind plasma temperature, 0.19 between magnitude of geomagnetic storms and magnitude of jump in solar wind density, 0.34 between magnitude of geomagnetic storms and magnitude of jump in solar wind plasma velocity, 0.66 between magnitude of geomagnetic storms and magnitude of jump in average interplanetary magnetic field respectively. We have concluded that geomagnetic storms are mainly caused by Coronal Mass Ejections and disturbances in solar wind plasma parameters that they generate.

  3. High-speed solar wind flow parameters at 1 AU

    International Nuclear Information System (INIS)

    Feldman, W.C.; Asbridge, J.R.; Bame, S.J.; Gosling, J.T.

    1976-01-01

    To develop a set of constraints for theories of solar wind high-speed streams, a detailed study was made of the fastest streams observed at 1 AU during the time period spanning March 1971 through July 1974. Streams were accepted for study only if (1) the maximum speed exceeded 650 km s -1 ; (2) effects of stream-stream dynamical interaction on the flow parameters could be safely separated from the intrinsic characteristics of the high-speed regions; (3) the full width at half maximum (FWHM) of the stream when mapped back to 20 solar radii by using a constant speed approximation was greater than 45degree in Carrington longitude; and (4) there were no obvious solar-activity-induced contaminating effects. Nineteen streams during this time interval satisfied these criteria. Average parameters at 1 AU for those portions of these streams above V=650 km s -1 are given.Not only is it not presently known why electrons are significantly cooler than the protons within high-speed regions, but also observed particle fluxes and convected energy fluxes for speed greater than 650 km s -1 are substantially larger than those values predicted by any of the existing theories of solar wind high-speed streams. More work is therefore needed in refining present solar wind models to see whether suitable modifications and/or combinations of existing theories based on reasonable coronal conditions can accommodate the above high-speed flow parameters

  4. The use of energy pattern factor (EPF) in estimating wind power ...

    African Journals Online (AJOL)

    The Energy Pattern Factor (EPF) method is a less computational method of estimating the available wind power density of an area and wind speed variation account for the energy power density throughout a given period. Using the Average daily wind speed data for an 11 year period (2004-2014) obtained from the ...

  5. Bayesian Parameter Estimation for Heavy-Duty Vehicles

    Energy Technology Data Exchange (ETDEWEB)

    Miller, Eric; Konan, Arnaud; Duran, Adam

    2017-03-28

    Accurate vehicle parameters are valuable for design, modeling, and reporting. Estimating vehicle parameters can be a very time-consuming process requiring tightly-controlled experimentation. This work describes a method to estimate vehicle parameters such as mass, coefficient of drag/frontal area, and rolling resistance using data logged during standard vehicle operation. The method uses Monte Carlo to generate parameter sets which is fed to a variant of the road load equation. Modeled road load is then compared to measured load to evaluate the probability of the parameter set. Acceptance of a proposed parameter set is determined using the probability ratio to the current state, so that the chain history will give a distribution of parameter sets. Compared to a single value, a distribution of possible values provides information on the quality of estimates and the range of possible parameter values. The method is demonstrated by estimating dynamometer parameters. Results confirm the method's ability to estimate reasonable parameter sets, and indicates an opportunity to increase the certainty of estimates through careful selection or generation of the test drive cycle.

  6. Statistical analysis of wind speed using two-parameter Weibull distribution in Alaçatı region

    International Nuclear Information System (INIS)

    Ozay, Can; Celiktas, Melih Soner

    2016-01-01

    Highlights: • Wind speed & direction data from September 2008 to March 2014 has been analyzed. • Mean wind speed for the whole data set has been found to be 8.11 m/s. • Highest wind speed is observed in July with a monthly mean value of 9.10 m/s. • Wind speed with the most energy has been calculated as 12.77 m/s. • Observed data has been fit to a Weibull distribution and k &c parameters have been calculated as 2.05 and 9.16. - Abstract: Weibull Statistical Distribution is a common method for analyzing wind speed measurements and determining wind energy potential. Weibull probability density function can be used to forecast wind speed, wind density and wind energy potential. In this study a two-parameter Weibull statistical distribution is used to analyze the wind characteristics of Alaçatı region, located in Çeşme, İzmir. The data used in the density function are acquired from a wind measurement station in Alaçatı. Measurements were gathered on three different heights respectively 70, 50 and 30 m between 10 min intervals for five and half years. As a result of this study; wind speed frequency distribution, wind direction trends, mean wind speed, and the shape and the scale (k&c) Weibull parameters have been calculated for the region. Mean wind speed for the entirety of the data set is found to be 8.11 m/s. k&c parameters are found as 2.05 and 9.16 in relative order. Wind direction analysis along with a wind rose graph for the region is also provided with the study. Analysis suggests that higher wind speeds which range from 6–12 m/s are prevalent between the sectors 340–360°. Lower wind speeds, from 3 to 6 m/s occur between sectors 10–29°. Results of this study contribute to the general knowledge about the regions wind energy potential and can be used as a source for investors and academics.

  7. Effective wind speed estimation: Comparison between Kalman Filter and Takagi-Sugeno observer techniques.

    Science.gov (United States)

    Gauterin, Eckhard; Kammerer, Philipp; Kühn, Martin; Schulte, Horst

    2016-05-01

    Advanced model-based control of wind turbines requires knowledge of the states and the wind speed. This paper benchmarks a nonlinear Takagi-Sugeno observer for wind speed estimation with enhanced Kalman Filter techniques: The performance and robustness towards model-structure uncertainties of the Takagi-Sugeno observer, a Linear, Extended and Unscented Kalman Filter are assessed. Hence the Takagi-Sugeno observer and enhanced Kalman Filter techniques are compared based on reduced-order models of a reference wind turbine with different modelling details. The objective is the systematic comparison with different design assumptions and requirements and the numerical evaluation of the reconstruction quality of the wind speed. Exemplified by a feedforward loop employing the reconstructed wind speed, the benefit of wind speed estimation within wind turbine control is illustrated. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

  8. Wind Resource Assessment in Abadan Airport in Iran

    Directory of Open Access Journals (Sweden)

    Mojtaba Nedaei

    2012-11-01

    Full Text Available Renewable energies have potential for supplying of relatively clean and mostly local energy. Wind energy generation is expected to increase in the near future and has experienced dramatic growth over the past decade in many countries. Wind speed is the most important parameter in the design and study of wind energy conversion systems. Probability density functions such as Weibull and Rayleigh are often used in wind speed and wind energy analyses. This paper presents an assessment of wind energy at three heights during near two years based on Weibull distribution function in Abadan Airport. Extrapolation of the 10 m and 40 m data, using the power law, has been used to determine the wind speed at height of 80 m. According to the results wind speed at 80 m height in Abadan is ranged from 5.8 m/s in Nov to 8.5 m/s in Jun with average value of 7.15 m/s. In this study, different parameters such as Weibull parameters, diurnal and monthly wind speeds, cumulative distribution and turbulence intensity have been estimated and analyzed. In addition Energy production of different wind turbines at different heights was estimated. The results show that the studied site has good potential for Installation of large and commercial wind turbines at height of 80 m or higher. Keywords: Abadan, Iran, wind energy, wind resource, wind turbine, Weibull

  9. Possible Power Estimation of Down-Regulated Offshore Wind Power Plants

    DEFF Research Database (Denmark)

    Gögmen, Tuhfe

    The penetration of offshore wind power is continuously increasing in the Northern European grids. To assure safety in the operation of the power system, wind power plants are required to provide ancillary services, including reserve power attained through down-regulating the wind farm from its...... power plant. The developed procedure, the PossPOW algorithm, can also be used in the wind farm control as it yields a real-time wind farm power curve. The modern wind turbines have a possible power signal at the turbine level and the current state of the art is to aggregate those signals to achieve...... the wind farm scale production capacity. However the summation of these individual signals is simply an over-estimation for the wind power plant, due to reduced wake losses during curtailment. The determination of the possible power with the PossPOW algorithm works as follows: firstly the second...

  10. Gearbox Fatigue Load Estimation for Condition Monitoring of Wind Turbines

    DEFF Research Database (Denmark)

    Perisic, Nevena; Pedersen, Bo Juul; Kirkegaard, Poul Henning

    2012-01-01

    control and data acquisition (SCADA) system. Estimated loads can be further used for prediction of remaining operating lifetime of turbine components, detection of high stress level or fault detection. An augmented Kalman filter is chosen as the fatigue load estimator because its characteristics well suit......The focus of the paper is on a design of a fatigue load estimator for predictive condition monitoring systems (CMS) of wind turbines. In order to avoid high-price measurement equipment required for direct load measuring, an indirect approach is suggested using only measurements from supervisory...... for the real time application. This paper presents results of the estimation of the gearbox fatigue load, often called shaft torque, using simulated data of wind turbine. Noise sensitivity of the algorithm is investigated by assuming different levels of measurement noise. Shaft torque estimations are compared...

  11. The problem of the second wind turbine – a note on a common but flawed wind power estimation method

    Directory of Open Access Journals (Sweden)

    A. Kleidon

    2012-06-01

    Full Text Available Several recent wind power estimates suggest that this renewable energy resource can meet all of the current and future global energy demand with little impact on the atmosphere. These estimates are calculated using observed wind speeds in combination with specifications of wind turbine size and density to quantify the extractable wind power. However, this approach neglects the effects of momentum extraction by the turbines on the atmospheric flow that would have effects outside the turbine wake. Here we show with a simple momentum balance model of the atmospheric boundary layer that this common methodology to derive wind power potentials requires unrealistically high increases in the generation of kinetic energy by the atmosphere. This increase by an order of magnitude is needed to ensure momentum conservation in the atmospheric boundary layer. In the context of this simple model, we then compare the effect of three different assumptions regarding the boundary conditions at the top of the boundary layer, with prescribed hub height velocity, momentum transport, or kinetic energy transfer into the boundary layer. We then use simulations with an atmospheric general circulation model that explicitly simulate generation of kinetic energy with momentum conservation. These simulations show that the assumption of prescribed momentum import into the atmospheric boundary layer yields the most realistic behavior of the simple model, while the assumption of prescribed hub height velocity can clearly be disregarded. We also show that the assumptions yield similar estimates for extracted wind power when less than 10% of the kinetic energy flux in the boundary layer is extracted by the turbines. We conclude that the common method significantly overestimates wind power potentials by an order of magnitude in the limit of high wind power extraction. Ultimately, environmental constraints set the upper limit on wind power potential at larger scales rather than

  12. Modal Parameter Identification of New Design of Vertical Axis Wind Turbine

    DEFF Research Database (Denmark)

    Chougule, Prasad; Nielsen, Søren R.K.

    2013-01-01

    Vertical axis wind turbines have lower power efficiency than the horizontal axis wind turbines. However vertical axis wind turbines are proven to be economical and noise free on smaller scale. A new design of three bladed vertical axis wind turbine by using two airfoils in construction of each...... blade has been proposed to improve power efficiency. The purpose of two airfoils in blade design of vertical axis wind turbine is to create high lift which in turns gives higher power output. In such case the structural parameter identification is important to understand the system behavior due to its...... first kind of design before experimental analysis. Therefore a study is carried out to determine the natural frequency to avoid unstable state of the system due to rotational frequency of rotor. The present paper outlines a conceptual design of vertical axis wind turbine and a modal analysis by using...

  13. Estimating Planetary Boundary Layer Heights from NOAA Profiler Network Wind Profiler Data

    Science.gov (United States)

    Molod, Andrea M.; Salmun, H.; Dempsey, M

    2015-01-01

    An algorithm was developed to estimate planetary boundary layer (PBL) heights from hourly archived wind profiler data from the NOAA Profiler Network (NPN) sites located throughout the central United States. Unlike previous studies, the present algorithm has been applied to a long record of publicly available wind profiler signal backscatter data. Under clear conditions, summertime averaged hourly time series of PBL heights compare well with Richardson-number based estimates at the few NPN stations with hourly temperature measurements. Comparisons with clear sky reanalysis based estimates show that the wind profiler PBL heights are lower by approximately 250-500 m. The geographical distribution of daily maximum PBL heights corresponds well with the expected distribution based on patterns of surface temperature and soil moisture. Wind profiler PBL heights were also estimated under mostly cloudy conditions, and are generally higher than both the Richardson number based and reanalysis PBL heights, resulting in a smaller clear-cloudy condition difference. The algorithm presented here was shown to provide a reliable summertime climatology of daytime hourly PBL heights throughout the central United States.

  14. Artificial neural network approach to spatial estimation of wind velocity data

    International Nuclear Information System (INIS)

    Oztopal, Ahmet

    2006-01-01

    In any regional wind energy assessment, equal wind velocity or energy lines provide a common basis for meaningful interpretations that furnish essential information for proper design purposes. In order to achieve regional variation descriptions, there are methods of optimum interpolation with classical weighting functions or variogram methods in Kriging methodology. Generally, the weighting functions are logically and geometrically deduced in a deterministic manner, and hence, they are imaginary first approximations for regional variability assessments, such as wind velocity. Geometrical weighting functions are necessary for regional estimation of the regional variable at a location with no measurement, which is referred to as the pivot station from the measurements of a set of surrounding stations. In this paper, weighting factors of surrounding stations necessary for the prediction of a pivot station are presented by an artificial neural network (ANN) technique. The wind speed prediction results are compared with measured values at a pivot station. Daily wind velocity measurements in the Marmara region from 1993 to 1997 are considered for application of the ANN methodology. The model is more appropriate for winter period daily wind velocities, which are significant for energy generation in the study area. Trigonometric point cumulative semivariogram (TPCSV) approach results are compared with the ANN estimations for the same set of data by considering the correlation coefficient (R). Under and over estimation problems in objective analysis can be avoided by the ANN approach

  15. CYGNSS Surface Wind Observations and Surface Flux Estimates within Low-Latitude Extratropical Cyclones

    Science.gov (United States)

    Crespo, J.; Posselt, D. J.

    2017-12-01

    The Cyclone Global Navigation Satellite System (CYGNSS), launched in December 2016, aims to improve estimates of surface wind speeds over the tropical oceans. While CYGNSS's core mission is to provide better estimates of surface winds within the core of tropical cyclones, previous research has shown that the constellation, with its orbital inclination of 35°, also has the ability to observe numerous extratropical cyclones that form in the lower latitudes. Along with its high spatial and temporal resolution, CYGNSS can provide new insights into how extratropical cyclones develop and evolve, especially in the presence of thick clouds and precipitation. We will demonstrate this by presenting case studies of multiple extratropical cyclones observed by CYGNSS early on in its mission in both Northern and Southern Hemispheres. By using the improved estimates of surface wind speeds from CYGNSS, we can obtain better estimates of surface latent and sensible heat fluxes within and around extratropical cyclones. Surface heat fluxes, driven by surface winds and strong vertical gradients of water vapor and temperature, play a key role in marine cyclogenesis as they increase instability within the boundary layer and may contribute to extreme marine cyclogenesis. In the past, it has been difficult to estimate surface heat fluxes from space borne instruments, as these fluxes cannot be observed directly from space, and deficiencies in spatial coverage and attenuation from clouds and precipitation lead to inaccurate estimates of surface flux components, such as surface wind speeds. While CYGNSS only contributes estimates of surface wind speeds, we can combine this data with other reanalysis and satellite data to provide improved estimates of surface sensible and latent heat fluxes within and around extratropical cyclones and throughout the entire CYGNSS mission.

  16. Bayesian Predictive Models for Rayleigh Wind Speed

    DEFF Research Database (Denmark)

    Shahirinia, Amir; Hajizadeh, Amin; Yu, David C

    2017-01-01

    predictive model of the wind speed aggregates the non-homogeneous distributions into a single continuous distribution. Therefore, the result is able to capture the variation among the probability distributions of the wind speeds at the turbines’ locations in a wind farm. More specifically, instead of using...... a wind speed distribution whose parameters are known or estimated, the parameters are considered as random whose variations are according to probability distributions. The Bayesian predictive model for a Rayleigh which only has a single model scale parameter has been proposed. Also closed-form posterior...... and predictive inferences under different reasonable choices of prior distribution in sensitivity analysis have been presented....

  17. Airborne Doppler Wind Lidar Post Data Processing Software DAPS-LV

    Science.gov (United States)

    Beyon, Jeffrey Y. (Inventor); Koch, Grady J. (Inventor); Kavaya, Michael J. (Inventor)

    2015-01-01

    Systems, methods, and devices of the present invention enable post processing of airborne Doppler wind LIDAR data. In an embodiment, airborne Doppler wind LIDAR data software written in LabVIEW may be provided and may run two versions of different airborne wind profiling algorithms. A first algorithm may be the Airborne Wind Profiling Algorithm for Doppler Wind LIDAR ("APOLO") using airborne wind LIDAR data from two orthogonal directions to estimate wind parameters, and a second algorithm may be a five direction based method using pseudo inverse functions to estimate wind parameters. The various embodiments may enable wind profiles to be compared using different algorithms, may enable wind profile data for long haul color displays to be generated, may display long haul color displays, and/or may enable archiving of data at user-selectable altitudes over a long observation period for data distribution and population.

  18. Estimation of the wind turbine yaw error by support vector machines

    DEFF Research Database (Denmark)

    Sheibat-Othman, Nida; Othman, Sami; Tayari, Raoaa

    2015-01-01

    Wind turbine yaw error information is of high importance in controlling wind turbine power and structural load. Normally used wind vanes are imprecise. In this work, the estimation of yaw error in wind turbines is studied using support vector machines for regression (SVR). As the methodology...... is data-based, simulated data from a high fidelity aero-elastic model is used for learning. The model simulates a variable speed horizontal-axis wind turbine composed of three blades and a full converter. Both partial load (blade angles fixed at 0 deg) and full load zones (active pitch actuators...

  19. Estimating generation costs for wind power production in France

    International Nuclear Information System (INIS)

    Benazet, J.F.; Probert, E.J.

    1997-01-01

    Wind power is being exploited in several European countries as one of a possible number of sources of renewable energy. However, in France there is a heavy reliance on nuclear and hydro-electric power and the potential of wind power as part of the energy mix has been virtually ignored. One of the reasons advanced for the under utilisation of this technology is that it is financially unattractive. In this paper the contribution which wind power could potentially make to overall power production levels in France is examined. A cost estimate model is developed which derives electricity generation costs and determines realistic levels of production for the future. The model automatically determines the associated number of wind turbines required and the geographical areas in which they should be located. (author)

  20. Multi-objective optimization in quantum parameter estimation

    Science.gov (United States)

    Gong, BeiLi; Cui, Wei

    2018-04-01

    We investigate quantum parameter estimation based on linear and Kerr-type nonlinear controls in an open quantum system, and consider the dissipation rate as an unknown parameter. We show that while the precision of parameter estimation is improved, it usually introduces a significant deformation to the system state. Moreover, we propose a multi-objective model to optimize the two conflicting objectives: (1) maximizing the Fisher information, improving the parameter estimation precision, and (2) minimizing the deformation of the system state, which maintains its fidelity. Finally, simulations of a simplified ɛ-constrained model demonstrate the feasibility of the Hamiltonian control in improving the precision of the quantum parameter estimation.

  1. Probability Distributions for Cyclone Key Parameters and Cyclonic Wind Speed for the East Coast of Indian Region

    Directory of Open Access Journals (Sweden)

    Pradeep K. Goyal

    2011-09-01

    Full Text Available This paper presents a study conducted on the probabilistic distribution of key cyclone parameters and the cyclonic wind speed by analyzing the cyclone track records obtained from India meteorological department for east coast region of India. The dataset of historical landfalling storm tracks in India from 1975–2007 with latitude /longitude and landfall locations are used to map the cyclone tracks in a region of study. The statistical tests were performed to find a best fit distribution to the track data for each cyclone parameter. These parameters include central pressure difference, the radius of maximum wind speed, the translation velocity, track angle with site and are used to generate digital simulated cyclones using wind field simulation techniques. For this, different sets of values for all the cyclone key parameters are generated randomly from their probability distributions. Using these simulated values of the cyclone key parameters, the distribution of wind velocity at a particular site is obtained. The same distribution of wind velocity at the site is also obtained from actual track records and using the distributions of the cyclone key parameters as published in the literature. The simulated distribution is compared with the wind speed distributions obtained from actual track records. The findings are useful in cyclone disaster mitigation.

  2. Influences of some parameters on the performance of a small vertical axis wind turbine

    Directory of Open Access Journals (Sweden)

    Dumitrache Alexandru

    2016-01-01

    Full Text Available The effects of various parameters on the performance of a straight bladed vertical axis wind turbine, using the vortex model, have been numerically investigated. A vortex model has been used to evaluate the performance of a vertical axis wind turbine, by means of aerodynamic characteristics of different airfoils for Reynolds numbers between 105 and 106. Parameters such as the thickness and the camber of the blade airfoil, the solidity, the type of blade profile, the number of blades and the pitch angle, which influence the power coefficient, CP, and the start-up regime. This study can be used in the designing an optimal vertical axis wind turbine in a specific location, when the prevailed wind regime is known.

  3. Modeling wind speed and wind power distributions in Rwanda

    Energy Technology Data Exchange (ETDEWEB)

    Safari, Bonfils [Department of Physics, National University of Rwanda, P.O. Box 117, Huye District, South Province (Rwanda)

    2011-02-15

    Utilization of wind energy as an alternative energy source may offer many environmental and economical advantages compared to fossil fuels based energy sources polluting the lower layer atmosphere. Wind energy as other forms of alternative energy may offer the promise of meeting energy demand in the direct, grid connected modes as well as stand alone and remote applications. Wind speed is the most significant parameter of the wind energy. Hence, an accurate determination of probability distribution of wind speed values is very important in estimating wind speed energy potential over a region. In the present study, parameters of five probability density distribution functions such as Weibull, Rayleigh, lognormal, normal and gamma were calculated in the light of long term hourly observed data at four meteorological stations in Rwanda for the period of the year with fairly useful wind energy potential (monthly hourly mean wind speed anti v{>=}2 m s{sup -1}). In order to select good fitting probability density distribution functions, graphical comparisons to the empirical distributions were made. In addition, RMSE and MBE have been computed for each distribution and magnitudes of errors were compared. Residuals of theoretical distributions were visually analyzed graphically. Finally, a selection of three good fitting distributions to the empirical distribution of wind speed measured data was performed with the aid of a {chi}{sup 2} goodness-of-fit test for each station. (author)

  4. Statistical study of chorus wave distributions in the inner magnetosphere using Ae and solar wind parameters

    Science.gov (United States)

    Aryan, Homayon; Yearby, Keith; Balikhin, Michael; Agapitov, Oleksiy; Krasnoselskikh, Vladimir; Boynton, Richard

    2014-08-01

    Energetic electrons within the Earth's radiation belts represent a serious hazard to geostationary satellites. The interactions of electrons with chorus waves play an important role in both the acceleration and loss of radiation belt electrons. The common approach is to present model wave distributions in the inner magnetosphere under different values of geomagnetic activity as expressed by the geomagnetic indices. However, it has been shown that only around 50% of geomagnetic storms increase flux of relativistic electrons at geostationary orbit while 20% causes a decrease and the remaining 30% has relatively no effect. This emphasizes the importance of including solar wind parameters such as bulk velocity (V), density (n), flow pressure (P), and the vertical interplanetary magnetic field component (Bz) that are known to be predominately effective in the control of high energy fluxes at the geostationary orbit. Therefore, in the present study the set of parameters of the wave distributions is expanded to include the solar wind parameters in addition to the geomagnetic activity. The present study examines almost 4 years (1 January 2004 to 29 September 2007) of Spatio-Temporal Analysis of Field Fluctuation data from Double Star TC1 combined with geomagnetic indices and solar wind parameters from OMNI database in order to present a comprehensive model of wave magnetic field intensities for the chorus waves as a function of magnetic local time, L shell (L), magnetic latitude (λm), geomagnetic activity, and solar wind parameters. Generally, the results indicate that the intensity of chorus emission is not only dependent upon geomagnetic activity but also dependent on solar wind parameters with velocity and southward interplanetary magnetic field Bs (Bz < 0), evidently the most influential solar wind parameters. The largest peak chorus intensities in the order of 50 pT are observed during active conditions, high solar wind velocities, low solar wind densities, high

  5. Two methods for estimating limits to large-scale wind power generation.

    Science.gov (United States)

    Miller, Lee M; Brunsell, Nathaniel A; Mechem, David B; Gans, Fabian; Monaghan, Andrew J; Vautard, Robert; Keith, David W; Kleidon, Axel

    2015-09-08

    Wind turbines remove kinetic energy from the atmospheric flow, which reduces wind speeds and limits generation rates of large wind farms. These interactions can be approximated using a vertical kinetic energy (VKE) flux method, which predicts that the maximum power generation potential is 26% of the instantaneous downward transport of kinetic energy using the preturbine climatology. We compare the energy flux method to the Weather Research and Forecasting (WRF) regional atmospheric model equipped with a wind turbine parameterization over a 10(5) km2 region in the central United States. The WRF simulations yield a maximum generation of 1.1 We⋅m(-2), whereas the VKE method predicts the time series while underestimating the maximum generation rate by about 50%. Because VKE derives the generation limit from the preturbine climatology, potential changes in the vertical kinetic energy flux from the free atmosphere are not considered. Such changes are important at night when WRF estimates are about twice the VKE value because wind turbines interact with the decoupled nocturnal low-level jet in this region. Daytime estimates agree better to 20% because the wind turbines induce comparatively small changes to the downward kinetic energy flux. This combination of downward transport limits and wind speed reductions explains why large-scale wind power generation in windy regions is limited to about 1 We⋅m(-2), with VKE capturing this combination in a comparatively simple way.

  6. Spatial Distribution of Estimated Wind-Power Royalties in West Texas

    Directory of Open Access Journals (Sweden)

    Christian Brannstrom

    2015-12-01

    Full Text Available Wind-power development in the U.S. occurs primarily on private land, producing royalties for landowners through private contracts with wind-farm operators. Texas, the U.S. leader in wind-power production with well-documented support for wind power, has virtually all of its ~12 GW of wind capacity sited on private lands. Determining the spatial distribution of royalty payments from wind energy is a crucial first step to understanding how renewable power may alter land-based livelihoods of some landowners, and, as a result, possibly encourage land-use changes. We located ~1700 wind turbines (~2.7 GW on 241 landholdings in Nolan and Taylor counties, Texas, a major wind-development region. We estimated total royalties to be ~$11.5 million per year, with mean annual royalty received per landowner per year of $47,879 but with significant differences among quintiles and between two sub-regions. Unequal distribution of royalties results from land-tenure patterns established before wind-power development because of a “property advantage,” defined as the pre-existing land-tenure patterns that benefit the fraction of rural landowners who receive wind turbines. A “royalty paradox” describes the observation that royalties flow to a small fraction of landowners even though support for wind power exceeds 70 percent.

  7. Aerodynamic parameters of across-wind self-limiting vibration for square sections after lock-in in smooth flow

    Science.gov (United States)

    Wu, Jong-Cheng; Chang, Feng-Jung

    2011-08-01

    The paper aims to identify the across-wind aerodynamic parameters of two-dimensional square section structures after the lock-in stage from the response measurements of wind tunnel tests under smooth wind flow conditions. Firstly, a conceivable self-limiting model was selected from the existent literature and the revisit of the analytical solution shows that the aerodynamic parameters (linear and nonlinear aerodynamic dampings Y1 and ɛ, and aerodynamic stiffness Y2) are not only functions of the section shape and reduced wind velocity but also dependent on both the mass ratio ( mr) and structural damping ratio ( ξ) independently, rather than on the Scruton number as a whole. Secondly, the growth-to-resonance (GTR) method was adopted for identifying the aerodynamic parameters of four different square section models (DN1, DN2, DN3 and DN4) by varying the density ranging from 226 to 409 kg/m 3. To improve the accuracy of the results, numerical optimization of the curve-fitting for experimental and analytical response in time domain was performed to finalize the results. The experimental results of the across-wind self-limiting steady-state amplitudes after lock-in stage versus the reduced wind velocity show that, except the tail part of the DN1 case slightly decreases indicating a pure vortex-induced lock-in persists, the DN2, DN3 and DN4 cases have a trend of monotonically increasing with the reduced wind velocity, which shows an asymptotic combination with the galloping behavior. Due to such a combination effect, all three aerodynamic parameters decrease as the reduced wind velocity increases and asymptotically approaches to a constant at the high branch. In the DN1 case, the parameters Y1 and Y2 decrease as the reduced wind velocity increases while the parameter ɛ slightly reverses in the tail part. The 3-dimensional surface plot of the Y1, ɛ and Y2 curves further show that, excluding the DN1 case, the parameters in the DN2, DN3 and DN4 cases almost follow a

  8. The distribution of waves in the inner magnetosphere as a function of solar wind parameters

    Science.gov (United States)

    Aryan, Homayon; Balikhin, Michael A.; Agapitov, Oleksiy; Krasnoselskikh, Vladimir; Yearby, Keith

    Energetic electrons within the Earth’s radiation belts represent a serious hazard to geostationary satellites. The interactions of electrons with chorus waves play an important role in both the acceleration and loss of radiation belt electrons. Studies of the evolution of energetic electron fluxes rely heavily on numerical codes in order to model energy and pitch angle diffusion due to electron interaction with plasma waves in the frame of quasilinear approximation. Application of these codes requires knowledge of statistical wave models to present wave distributions in the magnetosphere. A number of such models are based on CRESS, Cluster, THEMIS and other mission data. These models present wave distributions as a function of L-shell, magnetic local time, magnetic latitude and geomagnetic activity expressed by geomagnetic indices (Kp or Ae). However, it has been shown by G. Reeves and co-authors that only 50% of geomagnetic storms increase flux of relativistic electrons at GEO while 20% cause a decrease. This emphasizes the importance of including solar wind parameters in addition to geomagnetic indices. The present study examines almost four years (01, January, 2004 to 29, September, 2007) of STAFF (Spatio-Temporal Analysis of Field Fluctuation) data from Double Star TC1 combined with geomagnetic indices and solar wind parameters from OMNI database in order to present a comprehensive model of chorus wave intensities as a function of L-shell, magnetic local time, magnetic latitude, geomagnetic indices and solar wind parameters. The results show that chorus emission is not only sub-storm dependent but also dependent upon solar wind parameters with solar wind velocity evidently the most influential solar wind parameter. The largest peak intensities are observed for lower band chorus during active conditions, high solar wind velocity, low density and high pressure.

  9. A large-eddy simulation based power estimation capability for wind farms over complex terrain

    Science.gov (United States)

    Senocak, I.; Sandusky, M.; Deleon, R.

    2017-12-01

    There has been an increasing interest in predicting wind fields over complex terrain at the micro-scale for resource assessment, turbine siting, and power forecasting. These capabilities are made possible by advancements in computational speed from a new generation of computing hardware, numerical methods and physics modelling. The micro-scale wind prediction model presented in this work is based on the large-eddy simulation paradigm with surface-stress parameterization. The complex terrain is represented using an immersed-boundary method that takes into account the parameterization of the surface stresses. Governing equations of incompressible fluid flow are solved using a projection method with second-order accurate schemes in space and time. We use actuator disk models with rotation to simulate the influence of turbines on the wind field. Data regarding power production from individual turbines are mostly restricted because of proprietary nature of the wind energy business. Most studies report percentage drop of power relative to power from the first row. There have been different approaches to predict power production. Some studies simply report available wind power in the upstream, some studies estimate power production using power curves available from turbine manufacturers, and some studies estimate power as torque multiplied by rotational speed. In the present work, we propose a black-box approach that considers a control volume around a turbine and estimate the power extracted from the turbine based on the conservation of energy principle. We applied our wind power prediction capability to wind farms over flat terrain such as the wind farm over Mower County, Minnesota and the Horns Rev offshore wind farm in Denmark. The results from these simulations are in good agreement with published data. We also estimate power production from a hypothetical wind farm in complex terrain region and identify potential zones suitable for wind power production.

  10. On parameter estimation in deformable models

    DEFF Research Database (Denmark)

    Fisker, Rune; Carstensen, Jens Michael

    1998-01-01

    Deformable templates have been intensively studied in image analysis through the last decade, but despite its significance the estimation of model parameters has received little attention. We present a method for supervised and unsupervised model parameter estimation using a general Bayesian form...

  11. Prototype bucket foundation for wind turbines

    DEFF Research Database (Denmark)

    Ibsen, Lars Bo; Liingaard, Morten

    The first full scale prototype bucket foundation for wind turbines has been installed in October 2002 at Aalborg University offshore test facility in Frederikshavn, Denmark. The suction caisson and the wind turbine have been equipped with an online monitoring system, consisting of 15 accelerometers...... and a real-time data-acquisition system. The report concerns the in service performance of the wind turbine, with focus on estimation of the natural frequencies of the structure/foundation. The natural frequencies are initially estimated by means of experimental Output-only Modal analysis. The experimental...... estimates are then compared with numerical simulations of the suction caisson foundation and the wind turbine. The numerical model consists of a finite element section for the wind turbine tower and nacelle. The soil-structure interaction of the soil-foundation section is modelled by lumped-parameter models...

  12. State of the art on wind resource estimation

    Energy Technology Data Exchange (ETDEWEB)

    Maribo Pedersen, B.

    1998-12-31

    With the increasing number of wind resource estimation studies carried out for regions, countries and even larger areas all over the world, the IEA finds that the time has come to stop and take stock of the various methods used in these studies. The IEA would therefore like to propose an Experts Meeting on wind resource estimation. The Experts Meeting should describe the models and databases used in the various studies. It should shed light on the strengths and shortcomings of the models and answer questions like: where and under what circumstances should a specific model be used? what is the expected accuracy of the estimate of the model? and what is the applicability? When addressing databases the main goal will be to identify the content and scope of these. Further, the quality, availability and reliability of the databases must also be recognised. In the various studies of wind resources the models and databases have been combined in different ways. A final goal of the Experts Meeting is to see whether it is possible to develop systems of methods which would depend on the available input. These systems of methods should be able to address the simple case (level 0) of a region with barely no data, to the complex case of a region with all available measurements: surface observations, radio soundings, satellite observations and so on. The outcome of the meeting should be an inventory of available models as well as databases and a map of already studied regions. (au)

  13. Estimation of wake propagation behind the rotors of wind-powered generators

    DEFF Research Database (Denmark)

    Naumov, I. V.; Mikkelsen, Robert Flemming; Okulov, Valery

    2016-01-01

    . It is shown that the recovery of velocity of incident flow is faster than has been previously defined in the models of calculating the impact of wind electric power plants on the regional climate changes. Thus, existing wind loss calculated on the model of wake behind the wind-powered generator, adjusted......The objectives of this work are to develop the experimental model of wake behind the wind-power generator rotor to estimate its propagation distance and the impact on the average and pulsation characteristics of incident flow with the possibility of further use of these data in the calculation...... models of wind and climate changes in the regions and to determine the optimal operation of wind turbines. For experimental modeling, the laboratory model of wind-powered generator with a horizontal axis was used that operated as wind turbine in optimal mode. The kinematic characteristics of flow...

  14. Application of spreadsheet to estimate infiltration parameters

    Directory of Open Access Journals (Sweden)

    Mohammad Zakwan

    2016-09-01

    Full Text Available Infiltration is the process of flow of water into the ground through the soil surface. Soil water although contributes a negligible fraction of total water present on earth surface, but is of utmost importance for plant life. Estimation of infiltration rates is of paramount importance for estimation of effective rainfall, groundwater recharge, and designing of irrigation systems. Numerous infiltration models are in use for estimation of infiltration rates. The conventional graphical approach for estimation of infiltration parameters often fails to estimate the infiltration parameters precisely. The generalised reduced gradient (GRG solver is reported to be a powerful tool for estimating parameters of nonlinear equations and it has, therefore, been implemented to estimate the infiltration parameters in the present paper. Field data of infiltration rate available in literature for sandy loam soils of Umuahia, Nigeria were used to evaluate the performance of GRG solver. A comparative study of graphical method and GRG solver shows that the performance of GRG solver is better than that of conventional graphical method for estimation of infiltration rates. Further, the performance of Kostiakov model has been found to be better than the Horton and Philip's model in most of the cases based on both the approaches of parameter estimation.

  15. Parameter Estimation of Partial Differential Equation Models.

    Science.gov (United States)

    Xun, Xiaolei; Cao, Jiguo; Mallick, Bani; Carroll, Raymond J; Maity, Arnab

    2013-01-01

    Partial differential equation (PDE) models are commonly used to model complex dynamic systems in applied sciences such as biology and finance. The forms of these PDE models are usually proposed by experts based on their prior knowledge and understanding of the dynamic system. Parameters in PDE models often have interesting scientific interpretations, but their values are often unknown, and need to be estimated from the measurements of the dynamic system in the present of measurement errors. Most PDEs used in practice have no analytic solutions, and can only be solved with numerical methods. Currently, methods for estimating PDE parameters require repeatedly solving PDEs numerically under thousands of candidate parameter values, and thus the computational load is high. In this article, we propose two methods to estimate parameters in PDE models: a parameter cascading method and a Bayesian approach. In both methods, the underlying dynamic process modeled with the PDE model is represented via basis function expansion. For the parameter cascading method, we develop two nested levels of optimization to estimate the PDE parameters. For the Bayesian method, we develop a joint model for data and the PDE, and develop a novel hierarchical model allowing us to employ Markov chain Monte Carlo (MCMC) techniques to make posterior inference. Simulation studies show that the Bayesian method and parameter cascading method are comparable, and both outperform other available methods in terms of estimation accuracy. The two methods are demonstrated by estimating parameters in a PDE model from LIDAR data.

  16. [Estimation of the effect derived from wind erosion of soil and dust emission in Tianjin suburbs on the central district based on WEPS model].

    Science.gov (United States)

    Chen, Li; Han, Ting-Ting; Li, Tao; Ji, Ya-Qin; Bai, Zhi-Peng; Wang, Bin

    2012-07-01

    Due to the lack of a prediction model for current wind erosion in China and the slow development for such models, this study aims to predict the wind erosion of soil and the dust emission and develop a prediction model for wind erosion in Tianjin by investigating the structure, parameter systems and the relationships among the parameter systems of the prediction models for wind erosion in typical areas, using the U.S. wind erosion prediction system (WEPS) as reference. Based on the remote sensing technique and the test data, a parameter system was established for the prediction model of wind erosion and dust emission, and a model was developed that was suitable for the prediction of wind erosion and dust emission in Tianjin. Tianjin was divided into 11 080 blocks with a resolution of 1 x 1 km2, among which 7 778 dust emitting blocks were selected. The parameters of the blocks were localized, including longitude, latitude, elevation and direction, etc.. The database files of blocks were localized, including wind file, climate file, soil file and management file. The weps. run file was edited. Based on Microsoft Visualstudio 2008, secondary development was done using C + + language, and the dust fluxes of 7 778 blocks were estimated, including creep and saltation fluxes, suspension fluxes and PM10 fluxes. Based on the parameters of wind tunnel experiments in Inner Mongolia, the soil measurement data and climate data in suburbs of Tianjin, the wind erosion module, wind erosion fluxes, dust emission release modulus and dust release fluxes were calculated for the four seasons and the whole year in suburbs of Tianjin. In 2009, the total creep and saltation fluxes, suspension fluxes and PM10 fluxes in the suburbs of Tianjin were 2.54 x 10(6) t, 1.25 x 10(7) t and 9.04 x 10(5) t, respectively, among which, the parts pointing to the central district were 5.61 x 10(5) t, 2.89 x 10(6) t and 2.03 x 10(5) t, respectively.

  17. Statistical Evaluation of the Identified Structural Parameters of an idling Offshore Wind Turbine

    International Nuclear Information System (INIS)

    Kramers, Hendrik C.; Van der Valk, Paul L.C.; Van Wingerden, Jan-Willem

    2016-01-01

    With the increased need for renewable energy, new offshore wind farms are being developed at an unprecedented scale. However, as the costs of offshore wind energy are still too high, design optimization and new innovations are required for lowering its cost. The design of modern day offshore wind turbines relies on numerical models for estimating ultimate and fatigue loads of the turbines. The dynamic behavior and the resulting structural loading of the turbines is determined for a large part by its structural properties, such as the natural frequencies and damping ratios. Hence, it is important to obtain accurate estimates of these modal properties. For this purpose stochastic subspace identification (SSI), in combination with clustering and statistical evaluation methods, is used to obtain the variance of the identified modal properties of an installed 3.6MW offshore wind turbine in idling conditions. It is found that one is able to obtain confidence intervals for the means of eigenfrequencies and damping ratios of the fore-aft and side-side modes of the wind turbine. (paper)

  18. Parameter sensitivity and uncertainty analysis for a storm surge and wave model

    Directory of Open Access Journals (Sweden)

    L. A. Bastidas

    2016-09-01

    Full Text Available Development and simulation of synthetic hurricane tracks is a common methodology used to estimate hurricane hazards in the absence of empirical coastal surge and wave observations. Such methods typically rely on numerical models to translate stochastically generated hurricane wind and pressure forcing into coastal surge and wave estimates. The model output uncertainty associated with selection of appropriate model parameters must therefore be addressed. The computational overburden of probabilistic surge hazard estimates is exacerbated by the high dimensionality of numerical surge and wave models. We present a model parameter sensitivity analysis of the Delft3D model for the simulation of hazards posed by Hurricane Bob (1991 utilizing three theoretical wind distributions (NWS23, modified Rankine, and Holland. The sensitive model parameters (of 11 total considered include wind drag, the depth-induced breaking γB, and the bottom roughness. Several parameters show no sensitivity (threshold depth, eddy viscosity, wave triad parameters, and depth-induced breaking αB and can therefore be excluded to reduce the computational overburden of probabilistic surge hazard estimates. The sensitive model parameters also demonstrate a large number of interactions between parameters and a nonlinear model response. While model outputs showed sensitivity to several parameters, the ability of these parameters to act as tuning parameters for calibration is somewhat limited as proper model calibration is strongly reliant on accurate wind and pressure forcing data. A comparison of the model performance with forcings from the different wind models is also presented.

  19. PERFORMANCE ANALYSIS OF METHODS FOR ESTIMATING ...

    African Journals Online (AJOL)

    2014-12-31

    Dec 31, 2014 ... speed is the most significant parameter of the wind energy. ... wind-powered generators and applied to estimate potential power output at various ...... Wind and Solar Power Systems, U.S. Merchant Marine Academy Kings.

  20. Objective estimation of tropical cyclone innercore surface wind structure using infrared satellite images

    Science.gov (United States)

    Zhang, Changjiang; Dai, Lijie; Ma, Leiming; Qian, Jinfang; Yang, Bo

    2017-10-01

    An objective technique is presented for estimating tropical cyclone (TC) innercore two-dimensional (2-D) surface wind field structure using infrared satellite imagery and machine learning. For a TC with eye, the eye contour is first segmented by a geodesic active contour model, based on which the eye circumference is obtained as the TC eye size. A mathematical model is then established between the eye size and the radius of maximum wind obtained from the past official TC report to derive the 2-D surface wind field within the TC eye. Meanwhile, the composite information about the latitude of TC center, surface maximum wind speed, TC age, and critical wind radii of 34- and 50-kt winds can be combined to build another mathematical model for deriving the innercore wind structure. After that, least squares support vector machine (LSSVM), radial basis function neural network (RBFNN), and linear regression are introduced, respectively, in the two mathematical models, which are then tested with sensitivity experiments on real TC cases. Verification shows that the innercore 2-D surface wind field structure estimated by LSSVM is better than that of RBFNN and linear regression.

  1. Power Curve Estimation With Multivariate Environmental Factors for Inland and Offshore Wind Farms

    KAUST Repository

    Lee, Giwhyun

    2015-04-22

    In the wind industry, a power curve refers to the functional relationship between the power output generated by a wind turbine and the wind speed at the time of power generation. Power curves are used in practice for a number of important tasks including predicting wind power production and assessing a turbine’s energy production efficiency. Nevertheless, actual wind power data indicate that the power output is affected by more than just wind speed. Several other environmental factors, such as wind direction, air density, humidity, turbulence intensity, and wind shears, have potential impact. Yet, in industry practice, as well as in the literature, current power curve models primarily consider wind speed and, sometimes, wind speed and direction. We propose an additive multivariate kernel method that can include the aforementioned environmental factors as a new power curve model. Our model provides, conditional on a given environmental condition, both the point estimation and density estimation of power output. It is able to capture the nonlinear relationships between environmental factors and the wind power output, as well as the high-order interaction effects among some of the environmental factors. Using operational data associated with four turbines in an inland wind farm and two turbines in an offshore wind farm, we demonstrate the improvement achieved by our kernel method.

  2. Precision Parameter Estimation and Machine Learning

    Science.gov (United States)

    Wandelt, Benjamin D.

    2008-12-01

    I discuss the strategy of ``Acceleration by Parallel Precomputation and Learning'' (AP-PLe) that can vastly accelerate parameter estimation in high-dimensional parameter spaces and costly likelihood functions, using trivially parallel computing to speed up sequential exploration of parameter space. This strategy combines the power of distributed computing with machine learning and Markov-Chain Monte Carlo techniques efficiently to explore a likelihood function, posterior distribution or χ2-surface. This strategy is particularly successful in cases where computing the likelihood is costly and the number of parameters is moderate or large. We apply this technique to two central problems in cosmology: the solution of the cosmological parameter estimation problem with sufficient accuracy for the Planck data using PICo; and the detailed calculation of cosmological helium and hydrogen recombination with RICO. Since the APPLe approach is designed to be able to use massively parallel resources to speed up problems that are inherently serial, we can bring the power of distributed computing to bear on parameter estimation problems. We have demonstrated this with the CosmologyatHome project.

  3. Adaptive neuro-fuzzy optimization of wind farm project net profit

    International Nuclear Information System (INIS)

    Shamshirband, Shahaboddin; Petković, Dalibor; Ćojbašić, Žarko; Nikolić, Vlastimir; Anuar, Nor Badrul; Mohd Shuib, Nor Liyana; Mat Kiah, Miss Laiha; Akib, Shatirah

    2014-01-01

    Highlights: • Analyzing of wind farm project investment. • Net present value (NPV) maximization of the wind farm project. • Adaptive neuro-fuzzy (ANFIS) optimization of the number of wind turbines to maximize NPV. • The impact of the variation in the wind farm parameters. • Adaptive neuro fuzzy application. - Abstract: A wind power plant which consists of a group of wind turbines at a specific location is also known as wind farm. To maximize the wind farm net profit, the number of turbines installed in the wind farm should be different in depend on wind farm project investment parameters. In this paper, in order to achieve the maximal net profit of a wind farm, an intelligent optimization scheme based on the adaptive neuro-fuzzy inference system (ANFIS) is applied. As the net profit measures, net present value (NPV) and interest rate of return (IRR) are used. The NPV and IRR are two of the most important criteria for project investment estimating. The general approach in determining the accept/reject/stay in different decision for a project via NPV and IRR is to treat the cash flows as known with certainty. However, even small deviations from the predetermined values may easily invalidate the decision. In the proposed model the ANFIS estimator adjusts the number of turbines installed in the wind farm, for operating at the highest net profit point. The performance of proposed optimizer is confirmed by simulation results. Some outstanding properties of this new estimator are online implementation capability, structural simplicity and its robustness against any changes in wind farm parameters. Based on the simulation results, the effectiveness of the proposed optimization strategy is verified

  4. Analysis of the wind data and estimation of the resultant air concentration rates

    International Nuclear Information System (INIS)

    Hu, Shze Jer; Katagiri, Hiroshi; Kobayashi, Hideo

    1988-09-01

    Statistical analyses and comparisons of the meteorological wind data obtained by the propeller and supersonic anemometers for the year of 1987 in the Japan Atomic Energy Research Institute, Tokai, were performed. For wind speeds less than 1 m/s, the propeller readings are generally 0.5 m/s less than those of the supersonic readings. The resultant average air concentration and ground level γ exposure rates due to the radioactive releases for the normal operation of a nuclear plant are over-estimated when calculated using the propeller wind data. As supersonic anemometer can give accurate wind speed to as low as 0.01 m/s, it should be used to measure the low wind speed. The difference in the average air concentrations and γ exposure rates calculated using the two different sets of wind data, is due to the influence of low wind speeds at calm. If the number at calm is large, actual low wind speeds and wind directions should be used in the statistical analysis of atmospheric dispersion to give a more accurate and realistic estimation of the air concentrations and γ exposure rates due to the normal operation of a nuclear plant. (author). 4 refs, 3 figs, 9 tabs

  5. Total cost estimates for large-scale wind scenarios in UK

    International Nuclear Information System (INIS)

    Dale, Lewis; Milborrow, David; Slark, Richard; Strbac, Goran

    2004-01-01

    The recent UK Energy White Paper suggested that the Government should aim to secure 20% of electricity from renewable sources by 2020. A number of estimates of the extra cost of such a commitment have been made, but these have not necessarily included all the relevant cost components. This analysis sets out to identify these and to calculate the extra cost to the electricity consumer, assuming all the renewable electricity is sourced from wind energy. This enables one of the more controversial issues--the implications of wind intermittency--to be addressed. The basis of the assumptions associated with generating costs, extra balancing costs and distribution and transmission system reinforcement costs are all clearly identified and the total costs of a '20% wind' scenario are compared with a scenario where a similar amount of energy is generated by gas-fired plant. This enables the extra costs of the renewables scenario to be determined. The central estimate of the extra costs to electricity consumers is just over 0.3 p/kW h in current prices (around 5% extra on average domestic unit prices). Sensitivity analyses examine the implications of differing assumptions. The extra cost would rise if the capital costs of wind generation fall slower than anticipated, but would fall if gas prices rise more rapidly than has been assumed, or if wind plant are more productive. Even if it is assumed that wind has no capacity displacement value, the added cost to the electricity consumer rises by less than 0.1 p/kW h. It is concluded that there does not appear to be any technical reason why a substantial proportion of the country's electricity requirements could not be delivered by wind

  6. Reionization history and CMB parameter estimation

    International Nuclear Information System (INIS)

    Dizgah, Azadeh Moradinezhad; Kinney, William H.; Gnedin, Nickolay Y.

    2013-01-01

    We study how uncertainty in the reionization history of the universe affects estimates of other cosmological parameters from the Cosmic Microwave Background. We analyze WMAP7 data and synthetic Planck-quality data generated using a realistic scenario for the reionization history of the universe obtained from high-resolution numerical simulation. We perform parameter estimation using a simple sudden reionization approximation, and using the Principal Component Analysis (PCA) technique proposed by Mortonson and Hu. We reach two main conclusions: (1) Adopting a simple sudden reionization model does not introduce measurable bias into values for other parameters, indicating that detailed modeling of reionization is not necessary for the purpose of parameter estimation from future CMB data sets such as Planck. (2) PCA analysis does not allow accurate reconstruction of the actual reionization history of the universe in a realistic case

  7. Reionization history and CMB parameter estimation

    Energy Technology Data Exchange (ETDEWEB)

    Dizgah, Azadeh Moradinezhad; Gnedin, Nickolay Y.; Kinney, William H.

    2013-05-01

    We study how uncertainty in the reionization history of the universe affects estimates of other cosmological parameters from the Cosmic Microwave Background. We analyze WMAP7 data and synthetic Planck-quality data generated using a realistic scenario for the reionization history of the universe obtained from high-resolution numerical simulation. We perform parameter estimation using a simple sudden reionization approximation, and using the Principal Component Analysis (PCA) technique proposed by Mortonson and Hu. We reach two main conclusions: (1) Adopting a simple sudden reionization model does not introduce measurable bias into values for other parameters, indicating that detailed modeling of reionization is not necessary for the purpose of parameter estimation from future CMB data sets such as Planck. (2) PCA analysis does not allow accurate reconstruction of the actual reionization history of the universe in a realistic case.

  8. Comparing avian and bat fatality rate estimates among North American wind energy projects

    Energy Technology Data Exchange (ETDEWEB)

    Smallwood, Shawn

    2011-07-01

    Full text: Wind energy development has expanded rapidly, and so have concerns over bird and bat impacts caused by wind turbines. To assess and compare impacts due to collisions, investigators use a common metric, fatalities/MW/year, but estimates of fatality rates have come from various wind turbine models, tower heights, environments, fatality search methods, and analytical methods. To improve comparability and asses large-scale impacts, I applied a common set of assumptions and methods to data in fatality monitoring reports to estimate fatality rates of birds and bats at 71 wind projects across North America (52 outside the Altamont Pass Wind Resource Area, APWRA). The data were from wind turbines of 27 sizes (range 0.04-3.00 MW) and 28 tower heights (range 18.5-90 m), and searched at 40 periodic intervals (range 1-90 days) and out to 20 distances from turbines (range 30-126 m). Estimates spanned the years 1982 to 2010, and involved 1-1,345 turbines per unique combination of project, turbine size, tower height, and search methodology. I adjusted fatality rates for search detection rates averaged from 425 detection trials, and for scavenger removal rates based on 413 removal trials. I also adjusted fatality rates for turbine tower height and maximum search radius, based on logistic functions fit to cumulative counts of carcasses that were detected at 1-m distance intervals from the turbine. For each tower height, I estimated the distance at which cumulative carcass counts reached an asymptote, and for each project I calculated the proportion of fatalities likely not found due to the maximum search radius being short of the model-predicted distance asymptote. I used the same estimator in all cases. I estimated mean fatalities/MW/year among North American wind projects at 12.6 bats (80% CI: 8.1-17.1) and 11.1 birds (80% CI: 9.5-12.7), including 1.6 raptors (80% CI: 1.3-2.0), and excluding the Altamont Pass I estimated fatality rates at 17.2 bats (80% CI: 9

  9. Are estimates of wind characteristics based on measurements with Pitot tubes and GNSS receivers mounted on consumer-grade unmanned aerial vehicles applicable in meteorological studies?

    Science.gov (United States)

    Niedzielski, Tomasz; Skjøth, Carsten; Werner, Małgorzata; Spallek, Waldemar; Witek, Matylda; Sawiński, Tymoteusz; Drzeniecka-Osiadacz, Anetta; Korzystka-Muskała, Magdalena; Muskała, Piotr; Modzel, Piotr; Guzikowski, Jakub; Kryza, Maciej

    2017-09-01

    The objective of this paper is to empirically show that estimates of wind speed and wind direction based on measurements carried out using the Pitot tubes and GNSS receivers, mounted on consumer-grade unmanned aerial vehicles (UAVs), may accurately approximate true wind parameters. The motivation for the study is that a growing number of commercial and scientific UAV operations may soon become a new source of data on wind speed and wind direction, with unprecedented spatial and temporal resolution. The feasibility study was carried out within an isolated mountain meadow of Polana Izerska located in the Izera Mountains (SW Poland) during an experiment which aimed to compare wind characteristics measured by several instruments: three UAVs (swinglet CAM, eBee, Maja) equipped with the Pitot tubes and GNSS receivers, wind speed and direction meters mounted at 2.5 and 10 m (mast), conventional weather station and vertical sodar. The three UAVs performed seven missions along spiral-like trajectories, most reaching 130 m above take-off location. The estimates of wind speed and wind direction were found to agree between UAVs. The time series of wind speed measured at 10 m were extrapolated to flight altitudes recorded at a given time so that a comparison was made feasible. It was found that the wind speed estimates provided by the UAVs on a basis of the Pitot tube/GNSS data are in agreement with measurements carried out using dedicated meteorological instruments. The discrepancies were recorded in the first and last phases of UAV flights.

  10. Parameter Estimation of Partial Differential Equation Models

    KAUST Repository

    Xun, Xiaolei

    2013-09-01

    Partial differential equation (PDE) models are commonly used to model complex dynamic systems in applied sciences such as biology and finance. The forms of these PDE models are usually proposed by experts based on their prior knowledge and understanding of the dynamic system. Parameters in PDE models often have interesting scientific interpretations, but their values are often unknown and need to be estimated from the measurements of the dynamic system in the presence of measurement errors. Most PDEs used in practice have no analytic solutions, and can only be solved with numerical methods. Currently, methods for estimating PDE parameters require repeatedly solving PDEs numerically under thousands of candidate parameter values, and thus the computational load is high. In this article, we propose two methods to estimate parameters in PDE models: a parameter cascading method and a Bayesian approach. In both methods, the underlying dynamic process modeled with the PDE model is represented via basis function expansion. For the parameter cascading method, we develop two nested levels of optimization to estimate the PDE parameters. For the Bayesian method, we develop a joint model for data and the PDE and develop a novel hierarchical model allowing us to employ Markov chain Monte Carlo (MCMC) techniques to make posterior inference. Simulation studies show that the Bayesian method and parameter cascading method are comparable, and both outperform other available methods in terms of estimation accuracy. The two methods are demonstrated by estimating parameters in a PDE model from long-range infrared light detection and ranging data. Supplementary materials for this article are available online. © 2013 American Statistical Association.

  11. Optimum Parameters of a Tuned Liquid Column Damper in a Wind Turbine Subject to Stochastic Load

    Science.gov (United States)

    Alkmim, M. H.; de Morais, M. V. G.; Fabro, A. T.

    2017-12-01

    Parameter optimization for tuned liquid column dampers (TLCD), a class of passive structural control, have been previously proposed in the literature for reducing vibration in wind turbines, and several other applications. However, most of the available work consider the wind excitation as either a deterministic harmonic load or random load with white noise spectra. In this paper, a global direct search optimization algorithm to reduce vibration of a tuned liquid column damper (TLCD), a class of passive structural control device, is presented. The objective is to find optimized parameters for the TLCD under stochastic load from different wind power spectral density. A verification is made considering the analytical solution of undamped primary system under white noise excitation by comparing with result from the literature. Finally, it is shown that different wind profiles can significantly affect the optimum TLCD parameters.

  12. Parameter Estimation for Thurstone Choice Models

    Energy Technology Data Exchange (ETDEWEB)

    Vojnovic, Milan [London School of Economics (United Kingdom); Yun, Seyoung [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2017-04-24

    We consider the estimation accuracy of individual strength parameters of a Thurstone choice model when each input observation consists of a choice of one item from a set of two or more items (so called top-1 lists). This model accommodates the well-known choice models such as the Luce choice model for comparison sets of two or more items and the Bradley-Terry model for pair comparisons. We provide a tight characterization of the mean squared error of the maximum likelihood parameter estimator. We also provide similar characterizations for parameter estimators defined by a rank-breaking method, which amounts to deducing one or more pair comparisons from a comparison of two or more items, assuming independence of these pair comparisons, and maximizing a likelihood function derived under these assumptions. We also consider a related binary classification problem where each individual parameter takes value from a set of two possible values and the goal is to correctly classify all items within a prescribed classification error. The results of this paper shed light on how the parameter estimation accuracy depends on given Thurstone choice model and the structure of comparison sets. In particular, we found that for unbiased input comparison sets of a given cardinality, when in expectation each comparison set of given cardinality occurs the same number of times, for a broad class of Thurstone choice models, the mean squared error decreases with the cardinality of comparison sets, but only marginally according to a diminishing returns relation. On the other hand, we found that there exist Thurstone choice models for which the mean squared error of the maximum likelihood parameter estimator can decrease much faster with the cardinality of comparison sets. We report empirical evaluation of some claims and key parameters revealed by theory using both synthetic and real-world input data from some popular sport competitions and online labor platforms.

  13. Spectral tensor parameters for wind turbine load modeling from forested and agricultural landscapes

    DEFF Research Database (Denmark)

    Chougule, Abhijit S.; Mann, Jakob; Segalini, A.

    2015-01-01

    A velocity spectral tensor model was evaluated from the single-point measurements of wind speed. The model contains three parameters representing the dissipation rate of specific turbulent kinetic energy, a turbulence length scale and the turbulence anisotropy. Sonic anemometer measurements taken...... was better than that of the cross-wind component. No significant difference was found between the performance of the model at the forested and the agricultural areas. © 2014 The Authors. Wind Energy published by John Wiley & Sons, Ltd....

  14. Wind farm production estimates

    DEFF Research Database (Denmark)

    Larsen, Torben J.; Larsen, Gunner Chr.; Aagaard Madsen, Helge

    2012-01-01

    In this paper, the Dynamic Wake Meandering (DWM) model is applied for simulation of wind farm production. In addition to the numerical simulations, measured data have been analyzed in order to provide the basis for a full-scale verification of the model performance. The basic idea behind the DWMm......In this paper, the Dynamic Wake Meandering (DWM) model is applied for simulation of wind farm production. In addition to the numerical simulations, measured data have been analyzed in order to provide the basis for a full-scale verification of the model performance. The basic idea behind...... the DWMmodel is to model the in- stationary wind farm flow characteristics by considering wind turbine wakes as passive tracers continuously emitted from the wind farm turbines each with a downstream transport pro- cess dictated by large scale turbulent eddies (lateral and ver- tical transportation; i.......e. meandering) and Taylor advection. For the present purpose, the DWM model has been im- plemented in the aeroelastic code HAWC2 [1], and the per- formance of the resulting model complex is mainly verified by comparing simulated and measured loads for the Dutch off-shore Egmond aan Zee wind farm [2]. This farm...

  15. A new Bayesian recursive technique for parameter estimation

    Science.gov (United States)

    Kaheil, Yasir H.; Gill, M. Kashif; McKee, Mac; Bastidas, Luis

    2006-08-01

    The performance of any model depends on how well its associated parameters are estimated. In the current application, a localized Bayesian recursive estimation (LOBARE) approach is devised for parameter estimation. The LOBARE methodology is an extension of the Bayesian recursive estimation (BARE) method. It is applied in this paper on two different types of models: an artificial intelligence (AI) model in the form of a support vector machine (SVM) application for forecasting soil moisture and a conceptual rainfall-runoff (CRR) model represented by the Sacramento soil moisture accounting (SAC-SMA) model. Support vector machines, based on statistical learning theory (SLT), represent the modeling task as a quadratic optimization problem and have already been used in various applications in hydrology. They require estimation of three parameters. SAC-SMA is a very well known model that estimates runoff. It has a 13-dimensional parameter space. In the LOBARE approach presented here, Bayesian inference is used in an iterative fashion to estimate the parameter space that will most likely enclose a best parameter set. This is done by narrowing the sampling space through updating the "parent" bounds based on their fitness. These bounds are actually the parameter sets that were selected by BARE runs on subspaces of the initial parameter space. The new approach results in faster convergence toward the optimal parameter set using minimum training/calibration data and fewer sets of parameter values. The efficacy of the localized methodology is also compared with the previously used BARE algorithm.

  16. Estimating return periods of extreme values from relatively short time series of winds

    Science.gov (United States)

    Jonasson, Kristjan; Agustsson, Halfdan; Rognvaldsson, Olafur; Arfeuille, Gilles

    2013-04-01

    An important factor for determining the prospect of individual wind farm sites is the frequency of extreme winds at hub height. Here, extreme winds are defined as the value of the highest 10 minutes averaged wind speed with a 50 year return period, i.e. annual exceeding probability of 2% (Rodrigo, 2010). A frequently applied method to estimate winds in the lowest few hundred meters above ground is to extrapolate observed 10-meter winds logarithmically to higher altitudes. Recent study by Drechsel et al. (2012) showed however that this methodology is not as accurate as interpolating simulated results from the global ECMWF numerical weather prediction (NWP) model to the desired height. Observations of persistent low level jets near Colima in SW-Mexico also show that the logarithmic approach can give highly inaccurate results for some regions (Arfeuille et al., 2012). To address these shortcomings of limited, and/or poorly representative, observations and extrapolations of winds one can use NWP models to dynamically scale down relatively coarse resolution atmospheric analysis. In the case of limited computing resources one has typically to make a compromise between spatial resolution and the duration of the simulated period, both of which can limit the quality of the wind farm siting. A common method to estimate maximum winds is to fit an extreme value distribution (e.g. Gumbel, gev or Pareto) to the maximum values of each year of available data, or the tail of these values. If data are only available for a short period, e.g. 10 or 15 years, then this will give a rather inaccurate estimate. It is possible to deal with this problem by utilizing monthly or weekly maxima, but this introduces new problems: seasonal variation, autocorrelation of neighboring values, and increased discrepancy between data and fitted distribution. We introduce a new method to estimate return periods of extreme values of winds at hub height from relatively short time series of winds, simulated

  17. Ranking as parameter estimation

    Czech Academy of Sciences Publication Activity Database

    Kárný, Miroslav; Guy, Tatiana Valentine

    2009-01-01

    Roč. 4, č. 2 (2009), s. 142-158 ISSN 1745-7645 R&D Projects: GA MŠk 2C06001; GA AV ČR 1ET100750401; GA MŠk 1M0572 Institutional research plan: CEZ:AV0Z10750506 Keywords : ranking * Bayesian estimation * negotiation * modelling Subject RIV: BB - Applied Statistics, Operational Research http://library.utia.cas.cz/separaty/2009/AS/karny- ranking as parameter estimation.pdf

  18. Failure Probability Estimation of Wind Turbines by Enhanced Monte Carlo

    DEFF Research Database (Denmark)

    Sichani, Mahdi Teimouri; Nielsen, Søren R.K.; Naess, Arvid

    2012-01-01

    This paper discusses the estimation of the failure probability of wind turbines required by codes of practice for designing them. The Standard Monte Carlo (SMC) simulations may be used for this reason conceptually as an alternative to the popular Peaks-Over-Threshold (POT) method. However......, estimation of very low failure probabilities with SMC simulations leads to unacceptably high computational costs. In this study, an Enhanced Monte Carlo (EMC) method is proposed that overcomes this obstacle. The method has advantages over both POT and SMC in terms of its low computational cost and accuracy...... is controlled by the pitch controller. This provides a fair framework for comparison of the behavior and failure event of the wind turbine with emphasis on the effect of the pitch controller. The Enhanced Monte Carlo method is then applied to the model and the failure probabilities of the model are estimated...

  19. Wind inflow observation from load harmonics

    OpenAIRE

    Marta, Bertelè; Bottasso, Carlo L.; Cacciola, Stefano; Fabiano Daher Adegas,; Sara, Delport

    2017-01-01

    The wind field leaves its fingerprint on the rotor response. This fact can be exploited by using the rotor as a sensor: by looking at the rotor response, in the present case in terms of blade loads, one may infer the wind characteristics. This paper describes a wind state observer that estimates four wind parameters, namely the vertical and horizontal shears and the yaw and upflow misalignment angles, from out-of-plane and in-plane blade bending moments. The resulting observ...

  20. Study of the fractal dimension of the wind and its relationships with turbulent and stability parameters

    Science.gov (United States)

    Tijera, Manuel; Maqueda, Gregorio; Cano, José L.; López, Pilar; Yagüe, Carlos

    2010-05-01

    The wind velocity series of the atmospheric turbulent flow in the planetary boundary layer (PBL), in spite of being highly erratic, present a self-similarity structure (Frisch, 1995; Peitgen et., 2004; Falkovich et., 2006). So, the wind velocity can be seen as a fractal magnitude. We calculate the fractal dimension (Komolgorov capacity or box-counting dimension) of the wind perturbation series (u' = u- ) in the physical spaces (namely velocity-time). It has been studied the time evolution of the fractal dimension along different days and at three levels above the ground (5.8 m, 13.5 m, 32 m). The data analysed was recorded in the experimental campaign SABLES-98 (Cuxart et al., 2000) at the Research Centre for the Lower Atmosphere (CIBA) located in Valladolid (Spain). In this work the u, v and w components of wind velocity series have been measured by sonic anemometers (20 Hz sampling rate). The fractal dimension versus the integral length scales of the mean wind series have been studied, as well as the influence of different turbulent parameters. A method for estimating these integral scales is developed using the normalized autocorrelation function and a Gaussian fit. Finally, it will be analysed the variation of the fractal dimension versus stability parameters (as Richardson number) in order to explain some of the dominant features which are likely immersed in the fractal nature of these turbulent flows. References - Cuxart J, Yagüe C, Morales G, Terradellas E, Orbe J, Calvo J, Fernández A, Soler MR, Infante C, Buenestado P, Espinalt A, Joergensen HE, Rees JM, Vilá J, Redondo JM, Cantalapiedra IR and Conangla L (2000) Stable atmospheric boundary-layer experiment in Spain (SABLES98): a report. Boundary- Layer Meteorol 96:337-370 - Falkovich G and Kattepalli R. Sreenivasan (2006) Lessons from Hidrodynamic Turbulence. Physics Today 59: 43-49 - Frisch U (1995) Turbulence the legacy of A.N. Kolmogorov Cambridge University Press 269pp - Peitgen H, Jürgens H and

  1. Statistical characterization of roughness uncertainty and impact on wind resource estimation

    Directory of Open Access Journals (Sweden)

    M. Kelly

    2017-04-01

    Full Text Available In this work we relate uncertainty in background roughness length (z0 to uncertainty in wind speeds, where the latter are predicted at a wind farm location based on wind statistics observed at a different site. Sensitivity of predicted winds to roughness is derived analytically for the industry-standard European Wind Atlas method, which is based on the geostrophic drag law. We statistically consider roughness and its corresponding uncertainty, in terms of both z0 derived from measured wind speeds as well as that chosen in practice by wind engineers. We show the combined effect of roughness uncertainty arising from differing wind-observation and turbine-prediction sites; this is done for the case of roughness bias as well as for the general case. For estimation of uncertainty in annual energy production (AEP, we also develop a generalized analytical turbine power curve, from which we derive a relation between mean wind speed and AEP. Following our developments, we provide guidance on approximate roughness uncertainty magnitudes to be expected in industry practice, and we also find that sites with larger background roughness incur relatively larger uncertainties.

  2. Determining magnetospheric ULF wave activity from external drivers using the most influential solar wind parameters

    Science.gov (United States)

    Bentley, S.; Watt, C.; Owens, M. J.

    2017-12-01

    Ultra-low frequency (ULF) waves in the magnetosphere are involved in the energisation and transport of radiation belt particles and are predominantly driven by the external solar wind. By systematically examining the instantaneous relative contribution of non-derived solar wind parameters and accounting for their interdependencies using fifteen years of ground-based measurements (CANOPUS) at a single frequency and magnetic latitude, we conclude that the dominant causal parameters for ground-based ULF wave power are solar wind speed v, interplanetary magnetic field component Bz and summed power in number density perturbations δNp. We suggest that these correspond to driving by the Kelvin-Helmholtz instability, flux transfer events and direct perturbations from solar wind structures sweeping past. We will also extend our analysis to a stochastic wave model at multiple magnetic latitudes that will be used in future to predict background ULF wave power across the radiation belts in different magnetic local time sectors, and to examine the relative contribution of the parameters v, Bz and var(Np) in these sectors.

  3. Cosmological parameter estimation using Particle Swarm Optimization

    Science.gov (United States)

    Prasad, J.; Souradeep, T.

    2014-03-01

    Constraining parameters of a theoretical model from observational data is an important exercise in cosmology. There are many theoretically motivated models, which demand greater number of cosmological parameters than the standard model of cosmology uses, and make the problem of parameter estimation challenging. It is a common practice to employ Bayesian formalism for parameter estimation for which, in general, likelihood surface is probed. For the standard cosmological model with six parameters, likelihood surface is quite smooth and does not have local maxima, and sampling based methods like Markov Chain Monte Carlo (MCMC) method are quite successful. However, when there are a large number of parameters or the likelihood surface is not smooth, other methods may be more effective. In this paper, we have demonstrated application of another method inspired from artificial intelligence, called Particle Swarm Optimization (PSO) for estimating cosmological parameters from Cosmic Microwave Background (CMB) data taken from the WMAP satellite.

  4. Cosmological parameter estimation using Particle Swarm Optimization

    International Nuclear Information System (INIS)

    Prasad, J; Souradeep, T

    2014-01-01

    Constraining parameters of a theoretical model from observational data is an important exercise in cosmology. There are many theoretically motivated models, which demand greater number of cosmological parameters than the standard model of cosmology uses, and make the problem of parameter estimation challenging. It is a common practice to employ Bayesian formalism for parameter estimation for which, in general, likelihood surface is probed. For the standard cosmological model with six parameters, likelihood surface is quite smooth and does not have local maxima, and sampling based methods like Markov Chain Monte Carlo (MCMC) method are quite successful. However, when there are a large number of parameters or the likelihood surface is not smooth, other methods may be more effective. In this paper, we have demonstrated application of another method inspired from artificial intelligence, called Particle Swarm Optimization (PSO) for estimating cosmological parameters from Cosmic Microwave Background (CMB) data taken from the WMAP satellite

  5. Statistics of Parameter Estimates: A Concrete Example

    KAUST Repository

    Aguilar, Oscar

    2015-01-01

    © 2015 Society for Industrial and Applied Mathematics. Most mathematical models include parameters that need to be determined from measurements. The estimated values of these parameters and their uncertainties depend on assumptions made about noise levels, models, or prior knowledge. But what can we say about the validity of such estimates, and the influence of these assumptions? This paper is concerned with methods to address these questions, and for didactic purposes it is written in the context of a concrete nonlinear parameter estimation problem. We will use the results of a physical experiment conducted by Allmaras et al. at Texas A&M University [M. Allmaras et al., SIAM Rev., 55 (2013), pp. 149-167] to illustrate the importance of validation procedures for statistical parameter estimation. We describe statistical methods and data analysis tools to check the choices of likelihood and prior distributions, and provide examples of how to compare Bayesian results with those obtained by non-Bayesian methods based on different types of assumptions. We explain how different statistical methods can be used in complementary ways to improve the understanding of parameter estimates and their uncertainties.

  6. Highly reliable wind-rolling triboelectric nanogenerator operating in a wide wind speed range

    Science.gov (United States)

    Yong, Hyungseok; Chung, Jihoon; Choi, Dukhyun; Jung, Daewoong; Cho, Minhaeng; Lee, Sangmin

    2016-01-01

    Triboelectric nanogenerators are aspiring energy harvesting methods that generate electricity from the triboelectric effect and electrostatic induction. This study demonstrates the harvesting of wind energy by a wind-rolling triboelectric nanogenerator (WR-TENG). The WR-TENG generates electricity from wind as a lightweight dielectric sphere rotates along the vortex whistle substrate. Increasing the kinetic energy of a dielectric converted from the wind energy is a key factor in fabricating an efficient WR-TENG. Computation fluid dynamics (CFD) analysis is introduced to estimate the precise movements of wind flow and to create a vortex flow by adjusting the parameters of the vortex whistle shape to optimize the design parameters to increase the kinetic energy conversion rate. WR-TENG can be utilized as both a self-powered wind velocity sensor and a wind energy harvester. A single unit of WR-TENG produces open-circuit voltage of 11.2 V and closed-circuit current of 1.86 μA. Additionally, findings reveal that the electrical power is enhanced through multiple electrode patterns in a single device and by increasing the number of dielectric spheres inside WR-TENG. The wind-rolling TENG is a novel approach for a sustainable wind-driven TENG that is sensitive and reliable to wind flows to harvest wasted wind energy in the near future. PMID:27653976

  7. Analysis and estimation of transient stability for a grid-connected wind turbine with induction generator

    DEFF Research Database (Denmark)

    Li, H.; Zhao, B.; Yang, C.

    2011-01-01

    based on normal form theory is proposed. The transient models of the wind turbine generation system including the flexible drive train model are derived based on the direct transient stability estimation method. A method of critical clearing time (CCT) calculation is developed for the transient......Increasing levels of wind energy in modern electrical power system is initiating a need for accurate analysis and estimation of transient stability of wind turbine generation systems. This paper investigates the transient behaviors and possible direct methods for transient stability evaluation...... of a grid-connected wind turbine with squirrel cage induction generator (SCIG). Firstly, by using an equivalent lump mass method, a three-mass wind turbine equivalent model is proposed considering both the blades and the shaft flexibility of the wind turbine drive train system. Combined with the detailed...

  8. Spatial and temporal patterns of global onshore wind speed distribution

    International Nuclear Information System (INIS)

    Zhou, Yuyu; Smith, Steven J

    2013-01-01

    Wind power, a renewable energy source, can play an important role in electrical energy generation. Information regarding wind energy potential is important both for energy related modeling and for decision-making in the policy community. While wind speed datasets with high spatial and temporal resolution are often ultimately used for detailed planning, simpler assumptions are often used in analysis work. An accurate representation of the wind speed frequency distribution is needed in order to properly characterize wind energy potential. Using a power density method, this study estimated global variation in wind parameters as fitted to a Weibull density function using NCEP/climate forecast system reanalysis (CFSR) data over land areas. The Weibull distribution performs well in fitting the time series wind speed data at most locations according to R 2 , root mean square error, and power density error. The wind speed frequency distribution, as represented by the Weibull k parameter, exhibits a large amount of spatial variation, a regionally varying amount of seasonal variation, and relatively low decadal variation. We also analyzed the potential error in wind power estimation when a commonly assumed Rayleigh distribution (Weibull k = 2) is used. We find that the assumption of the same Weibull parameter across large regions can result in non-negligible errors. While large-scale wind speed data are often presented in the form of mean wind speeds, these results highlight the need to also provide information on the wind speed frequency distribution. (letter)

  9. Understanding the Role of Wind in Reducing the Surface Mass Balance Estimates over East Antarctica

    Science.gov (United States)

    Das, I.; Scambos, T. A.; Koenig, L.; Creyts, T. T.; Bell, R. E.; van den Broeke, M. R.; Lenaerts, J.; Paden, J. D.

    2014-12-01

    Accurate quantification of surface snow-accumulation over Antarctica is important for mass balance estimates and climate studies based on ice core records. An improved estimate of surface mass balance must include the significant role near-surface wind plays in the sublimation and redistribution of snow across Antarctica. We have developed an empirical model based on airborne radar and lidar observations, and modeled surface mass balance and wind fields to produce a continent-wide prediction of wind-scour zones over Antarctica. These zones have zero to negative surface mass balance, are located over locally steep ice sheet areas (>0.002) and controlled by bedrock topography. The near-surface winds accelerate over these zones, eroding and sublimating the surface snow. This scouring results in numerous localized regions (≤ 200 km2) with reduced surface accumulation. Each year, tens of gigatons of snow on the Antarctic ice sheet are ablated by persistent near-surface katabatic winds over these wind-scour zones. Large uncertainties remain in the surface mass balance estimates over East Antarctica as climate models do not adequately represent the small-scale physical processes that lead to mass loss through sublimation or redistribution over the wind-scour zones. In this study, we integrate Operation IceBridge's snow radar over the Recovery Ice Stream with a series of ice core dielectric and depth-density profiles for improved surface mass balance estimates that reflect the mass loss over the wind-scour zones. Accurate surface mass balance estimates from snow radars require spatially variable depth-density profiles. Using an ensemble of firn cores, MODIS-derived surface snow grain size, modeled accumulation rates and surface temperatures from RACMO2, we assemble spatially variable depth-density profiles and use our mapping of snow density variations to estimate layer mass and net accumulation rates from snow radar layer data. Our study improves the quantification of

  10. Wind turbine power coefficient estimation by soft computing methodologies: Comparative study

    International Nuclear Information System (INIS)

    Shamshirband, Shahaboddin; Petković, Dalibor; Saboohi, Hadi; Anuar, Nor Badrul; Inayat, Irum; Akib, Shatirah; Ćojbašić, Žarko; Nikolić, Vlastimir; Mat Kiah, Miss Laiha; Gani, Abdullah

    2014-01-01

    Highlights: • Variable speed operation of wind turbine to increase power generation. • Changeability and fluctuation of wind has to be accounted. • To build an effective prediction model of wind turbine power coefficient. • The impact of the variation in the blade pitch angle and tip speed ratio. • Support vector regression methodology application as predictive methodology. - Abstract: Wind energy has become a large contender of traditional fossil fuel energy, particularly with the successful operation of multi-megawatt sized wind turbines. However, reasonable wind speed is not adequately sustainable everywhere to build an economical wind farm. In wind energy conversion systems, one of the operational problems is the changeability and fluctuation of wind. In most cases, wind speed can vacillate rapidly. Hence, quality of produced energy becomes an important problem in wind energy conversion plants. Several control techniques have been applied to improve the quality of power generated from wind turbines. In this study, the polynomial and radial basis function (RBF) are applied as the kernel function of support vector regression (SVR) to estimate optimal power coefficient value of the wind turbines. Instead of minimizing the observed training error, SVR p oly and SVR r bf attempt to minimize the generalization error bound so as to achieve generalized performance. The experimental results show that an improvement in predictive accuracy and capability of generalization can be achieved by the SVR approach in compare to other soft computing methodologies

  11. Wind effect on PV module temperature: Analysis of different techniques for an accurate estimation.

    Science.gov (United States)

    Schwingshackl, Clemens; Petitta, Marcello; Ernst Wagner, Jochen; Belluardo, Giorgio; Moser, David; Castelli, Mariapina; Zebisch, Marc; Tetzlaff, Anke

    2013-04-01

    In this abstract a study on the influence of wind to model the PV module temperature is presented. This study is carried out in the framework of the PV-Alps INTERREG project in which the potential of different photovoltaic technologies is analysed for alpine regions. The PV module temperature depends on different parameters, such as ambient temperature, irradiance, wind speed and PV technology [1]. In most models, a very simple approach is used, where the PV module temperature is calculated from NOCT (nominal operating cell temperature), ambient temperature and irradiance alone [2]. In this study the influence of wind speed on the PV module temperature was investigated. First, different approaches suggested by various authors were tested [1], [2], [3], [4], [5]. For our analysis, temperature, irradiance and wind data from a PV test facility at the airport Bolzano (South Tyrol, Italy) from the EURAC Institute of Renewable Energies were used. The PV module temperature was calculated with different models and compared to the measured PV module temperature at the single panels. The best results were achieved with the approach suggested by Skoplaki et al. [1]. Preliminary results indicate that for all PV technologies which were tested (monocrystalline, amorphous, microcrystalline and polycrystalline silicon and cadmium telluride), modelled and measured PV module temperatures show a higher agreement (RMSE about 3-4 K) compared to standard approaches in which wind is not considered. For further investigation the in-situ measured wind velocities were replaced with wind data from numerical weather forecast models (ECMWF, reanalysis fields). Our results show that the PV module temperature calculated with wind data from ECMWF is still in very good agreement with the measured one (R² > 0.9 for all technologies). Compared to the previous analysis, we find comparable mean values and an increasing standard deviation. These results open a promising approach for PV module

  12. Estimating Soil Hydraulic Parameters using Gradient Based Approach

    Science.gov (United States)

    Rai, P. K.; Tripathi, S.

    2017-12-01

    The conventional way of estimating parameters of a differential equation is to minimize the error between the observations and their estimates. The estimates are produced from forward solution (numerical or analytical) of differential equation assuming a set of parameters. Parameter estimation using the conventional approach requires high computational cost, setting-up of initial and boundary conditions, and formation of difference equations in case the forward solution is obtained numerically. Gaussian process based approaches like Gaussian Process Ordinary Differential Equation (GPODE) and Adaptive Gradient Matching (AGM) have been developed to estimate the parameters of Ordinary Differential Equations without explicitly solving them. Claims have been made that these approaches can straightforwardly be extended to Partial Differential Equations; however, it has been never demonstrated. This study extends AGM approach to PDEs and applies it for estimating parameters of Richards equation. Unlike the conventional approach, the AGM approach does not require setting-up of initial and boundary conditions explicitly, which is often difficult in real world application of Richards equation. The developed methodology was applied to synthetic soil moisture data. It was seen that the proposed methodology can estimate the soil hydraulic parameters correctly and can be a potential alternative to the conventional method.

  13. State Estimation-based Transmission line parameter identification

    Directory of Open Access Journals (Sweden)

    Fredy Andrés Olarte Dussán

    2010-01-01

    Full Text Available This article presents two state-estimation-based algorithms for identifying transmission line parameters. The identification technique used simultaneous state-parameter estimation on an artificial power system composed of several copies of the same transmission line, using measurements at different points in time. The first algorithm used active and reactive power measurements at both ends of the line. The second method used synchronised phasor voltage and current measurements at both ends. The algorithms were tested in simulated conditions on the 30-node IEEE test system. All line parameters for this system were estimated with errors below 1%.

  14. HF Radar Observations of Current, Wave and Wind Parameters in the South Australian Gulf

    Science.gov (United States)

    Middleditch, A.; Cosoli, S.

    2016-12-01

    The Australian Coastal Ocean Radar Network (ACORN) has been measuring metocean parameters from an array of HF radar systems since 2007. Current, wave and wind measurements from a WERA phased-array radar system in the South Australian Gulf are evaluated using current meter, wave buoy and weather station data over a 12-month period. The spatial and temporal scales of the radar deployment have been configured for the measurement of surface currents from the first order backscatter spectra. Quality control procedures are applied to the radar currents that relate to the geometric configurations, statistical properties, and diagnostic variables provided by the analysis software. Wave measurements are obtained through an iterative inversion algorithm that provides an estimate of the directional frequency spectrum. The standard static configurations and data sampling strategies are not optimised for waves and so additional signal processing steps need to be implemented in order to provide reliable estimates. These techniques are currently only applied in offline mode but a real-time approach is in development. Improvements in the quality of extracted wave data are found through increased averaging of the raw radar data but the impact of temporal non-stationarity and spatial inhomogeneities in the WERA measurement region needs to be taken into account. Validations of wind direction data from a weather station on Neptune Island show the potential of using HF radar to combat the spread of bushfires in South Australia.

  15. Thermal Loading and Lifetime Estimation for Power Device Considering Mission Profiles in Wind Power Converter

    DEFF Research Database (Denmark)

    Ma, Ke; Liserre, Marco; Blaabjerg, Frede

    2015-01-01

    for the reliability improvement and also for cost reduction of wind power technology. Unfortunately, the existing lifetime estimation methods for the power electronic converter are not yet suitable in the wind power application, because the comprehensive mission profiles are not well specified and included......As a key component in the wind turbine system, the power electronic converter and its power semiconductors suffer from complicated power loadings related to environment, and are proven to have high failure rates. Therefore, correct lifetime estimation of wind power converter is crucial...... devices, more detailed information of the lifetime-related performance in wind power converter can be obtained. Some experimental results are also included to validate the thermal behavior of power device under different mission profiles....

  16. Kinetic parameter estimation from attenuated SPECT projection measurements

    International Nuclear Information System (INIS)

    Reutter, B.W.; Gullberg, G.T.

    1998-01-01

    Conventional analysis of dynamically acquired nuclear medicine data involves fitting kinetic models to time-activity curves generated from regions of interest defined on a temporal sequence of reconstructed images. However, images reconstructed from the inconsistent projections of a time-varying distribution of radiopharmaceutical acquired by a rotating SPECT system can contain artifacts that lead to biases in the estimated kinetic parameters. To overcome this problem the authors investigated the estimation of kinetic parameters directly from projection data by modeling the data acquisition process. To accomplish this it was necessary to parametrize the spatial and temporal distribution of the radiopharmaceutical within the SPECT field of view. In a simulated transverse slice, kinetic parameters were estimated for simple one compartment models for three myocardial regions of interest, as well as for the liver. Myocardial uptake and washout parameters estimated by conventional analysis of noiseless simulated data had biases ranging between 1--63%. Parameters estimated directly from the noiseless projection data were unbiased as expected, since the model used for fitting was faithful to the simulation. Predicted uncertainties (standard deviations) of the parameters obtained for 500,000 detected events ranged between 2--31% for the myocardial uptake parameters and 2--23% for the myocardial washout parameters

  17. A Deeper Understanding of Stability in the Solar Wind: Applying Nyquist's Instability Criterion to Wind Faraday Cup Data

    Science.gov (United States)

    Alterman, B. L.; Klein, K. G.; Verscharen, D.; Stevens, M. L.; Kasper, J. C.

    2017-12-01

    Long duration, in situ data sets enable large-scale statistical analysis of free-energy-driven instabilities in the solar wind. The plasma beta and temperature anisotropy plane provides a well-defined parameter space in which a single-fluid plasma's stability can be represented. Because this reduced parameter space can only represent instability thresholds due to the free energy of one ion species - typically the bulk protons - the true impact of instabilities on the solar wind is under estimated. Nyquist's instability criterion allows us to systematically account for other sources of free energy including beams, drifts, and additional temperature anisotropies. Utilizing over 20 years of Wind Faraday cup and magnetic field observations, we have resolved the bulk parameters for three ion populations: the bulk protons, beam protons, and alpha particles. Applying Nyquist's criterion, we calculate the number of linearly growing modes supported by each spectrum and provide a more nuanced consideration of solar wind stability. Using collisional age measurements, we predict the stability of the solar wind close to the sun. Accounting for the free-energy from the three most common ion populations in the solar wind, our approach provides a more complete characterization of solar wind stability.

  18. Robust Parameter and Signal Estimation in Induction Motors

    DEFF Research Database (Denmark)

    Børsting, H.

    This thesis deals with theories and methods for robust parameter and signal estimation in induction motors. The project originates in industrial interests concerning sensor-less control of electrical drives. During the work, some general problems concerning estimation of signals and parameters...... in nonlinear systems, have been exposed. The main objectives of this project are: - analysis and application of theories and methods for robust estimation of parameters in a model structure, obtained from knowledge of the physics of the induction motor. - analysis and application of theories and methods...... for robust estimation of the rotor speed and driving torque of the induction motor based only on measurements of stator voltages and currents. Only contimuous-time models have been used, which means that physical related signals and parameters are estimated directly and not indirectly by some discrete...

  19. Reliability/Cost Evaluation on Power System connected with Wind Power for the Reserve Estimation

    DEFF Research Database (Denmark)

    Lee, Go-Eun; Cha, Seung-Tae; Shin, Je-Seok

    2012-01-01

    Wind power is ideally a renewable energy with no fuel cost, but has a risk to reduce reliability of the whole system because of uncertainty of the output. If the reserve of the system is increased, the reliability of the system may be improved. However, the cost would be increased. Therefore...... the reserve needs to be estimated considering the trade-off between reliability and economic aspects. This paper suggests a methodology to estimate the appropriate reserve, when wind power is connected to the power system. As a case study, when wind power is connected to power system of Korea, the effects...

  20. Standard Errors of Estimated Latent Variable Scores with Estimated Structural Parameters

    Science.gov (United States)

    Hoshino, Takahiro; Shigemasu, Kazuo

    2008-01-01

    The authors propose a concise formula to evaluate the standard error of the estimated latent variable score when the true values of the structural parameters are not known and must be estimated. The formula can be applied to factor scores in factor analysis or ability parameters in item response theory, without bootstrap or Markov chain Monte…

  1. Estimating the maritime component of aerosol optical depth and its dependency on surface wind speed using satellite data

    Directory of Open Access Journals (Sweden)

    Y. Lehahn

    2010-07-01

    Full Text Available Six years (2003–2008 of satellite measurements of aerosol parameters from the Moderate Resolution Imaging Spectroradiometer (MODIS and surface wind speeds from Quick Scatterometer (QuikSCAT, the Advanced Microwave Scanning Radiometer (AMSR-E, and the Special Sensor Microwave Imager (SSM/I, are used to provide a comprehensive perspective on the link between surface wind speed and marine aerosol optical depth over tropical and subtropical oceanic regions. A systematic comparison between the satellite derived fields in these regions allows to: (i separate the relative contribution of wind-induced marine aerosol to the aerosol optical depth; (ii extract an empirical linear equation linking coarse marine aerosol optical depth and wind intensity; and (iii identify a time scale for correlating marine aerosol optical depth and surface wind speed. The contribution of wind induced marine aerosol to aerosol optical depth is found to be dominated by the coarse mode elements. When wind intensity exceeds 4 m/s, coarse marine aerosol optical depth is linearly correlated with the surface wind speed, with a remarkably consistent slope of 0.009±0.002 s/m. A detailed time scale analysis shows that the linear correlation between the fields is well kept within a 12 h time frame, while sharply decreasing when the time lag between measurements is longer. The background aerosol optical depth, associated with aerosols that are not produced in-situ through wind driven processes, can be used for estimating the contributions of terrestrial and biogenic marine aerosol to over-ocean satellite retrievals of aerosol optical depth.

  2. Underwater Acoustic Measurements to Estimate Wind and Rainfall in the Mediterranean Sea

    Directory of Open Access Journals (Sweden)

    Sara Pensieri

    2015-01-01

    Full Text Available Oceanic ambient noise measurements can be analyzed to obtain qualitative and quantitative information about wind and rainfall phenomena over the ocean filling the existing gap of reliable meteorological observations at sea. The Ligurian Sea Acoustic Experiment was designed to collect long-term synergistic observations from a passive acoustic recorder and surface sensors (i.e., buoy mounted rain gauge and anemometer and weather radar to support error analysis of rainfall rate and wind speed quantification techniques developed in past studies. The study period included combination of high and low wind and rainfall episodes and two storm events that caused two floods in the vicinity of La Spezia and in the city of Genoa in 2011. The availability of high resolution in situ meteorological data allows improving data processing technique to detect and especially to provide effective estimates of wind and rainfall at sea. Results show a very good correspondence between estimates provided by passive acoustic recorder algorithm and in situ observations for both rainfall and wind phenomena and demonstrate the potential of using measurements provided by passive acoustic instruments in open sea for early warning of approaching coastal storms, which for the Mediterranean coastal areas constitutes one of the main causes of recurrent floods.

  3. Large-scale wind power integration and wholesale electricity trading benefits: Estimation via an ex post approach

    International Nuclear Information System (INIS)

    Gil, Hugo A.; Gomez-Quiles, Catalina; Riquelme, Jesus

    2012-01-01

    The integration of large-scale wind power has brought about a series of challenges to the power industry, but at the same time a number of benefits are being realized. Among those, the ability of wind power to cause a decline in the electricity market prices has been recognized. In quantifying this effect, some models used in recent years are based on simulations of the market supply-side and the price clearing process. The accuracy of the estimates depend on the quality of the input data, the veracity of the adopted scenarios and the rigorousness of the solution technique. In this work, a series of econometric techniques based on actual ex post wind power and electricity price data are implemented for the estimation of the impact of region-wide wind power integration on the local electricity market clearing prices and the trading savings that stem from this effect. The model is applied to the case of Spain, where the estimated savings are compared against actual credit and bonus expenses to ratepayers. The implications and extent of these results for current and future renewable energy policy-making are discussed. - Highlights: ► Wholesale electricity market trading benefits by wind power are quantified. ► Actual wind power forecast-based bids and electricity price data from Spain are used. ► Different econometric tools are used and compared for improved estimation accuracy. ► Estimated benefits outweigh current credit overhead paid to wind farms in Spain. ► An economically efficient benefit surplus allocation framework is proposed.

  4. Seasonal, annual and inter-annual features of turbulence parameters over the tropical station Pune (18°32' N, 73°51' E observed with UHF wind profiler

    Directory of Open Access Journals (Sweden)

    N. Singh

    2008-11-01

    Full Text Available The present study is specifically focused on the seasonal, annual and inter-annual variations of the refractive index structure parameter (Cn2 using three years of radar observations. Energy dissipation rates (ε during different seasons for a particular year are also computed over a tropical station, Pune. Doppler spectral width measurements made by the Wind Profiler, under various atmospheric conditions, are utilized to estimate the turbulence parameters. The refractive index structure parameter varies from 10−17.5 to 10−13 m−2/3 under clear air to precipitation conditions in the height region of 1.05 to 10.35 km. During the monsoon months, observed Cn2 values are up to 1–2 orders of magnitude higher than those during pre-monsoon and post-monsoon seasons. Spectral width correction for various non-turbulent spectral broadenings such as beam broadening and shear broadening are made in the observed spectral width for reliable estimation of ε under non-precipitating conditions. It is found that in the lower tropospheric height region, values of ε are in the range of 10−6 to 10−3 m2 s−3. In summer and monsoon seasons the observed values of ε are larger than those in post-monsoon and winter seasons in the lower troposphere. A comparison of Cn2 observed with the wind profiler and that estimated using Radio Sonde/Radio Wind (RS/RW data of nearby Met station Chikalthana has been made for the month of July 2003.

  5. First Passage Probability Estimation of Wind Turbines by Markov Chain Monte Carlo

    DEFF Research Database (Denmark)

    Sichani, Mahdi Teimouri; Nielsen, Søren R.K.

    2013-01-01

    Markov Chain Monte Carlo simulation has received considerable attention within the past decade as reportedly one of the most powerful techniques for the first passage probability estimation of dynamic systems. A very popular method in this direction capable of estimating probability of rare events...... of the method by modifying the conditional sampler. In this paper, applicability of the original SS is compared to the recently introduced modifications of the method on a wind turbine model. The model incorporates a PID pitch controller which aims at keeping the rotational speed of the wind turbine rotor equal...... to its nominal value. Finally Monte Carlo simulations are performed which allow assessment of the accuracy of the first passage probability estimation by the SS methods....

  6. Examining the utility of satellite-based wind sheltering estimates for lake hydrodynamic modeling

    Science.gov (United States)

    Van Den Hoek, Jamon; Read, Jordan S.; Winslow, Luke A.; Montesano, Paul; Markfort, Corey D.

    2015-01-01

    Satellite-based measurements of vegetation canopy structure have been in common use for the last decade but have never been used to estimate canopy's impact on wind sheltering of individual lakes. Wind sheltering is caused by slower winds in the wake of topography and shoreline obstacles (e.g. forest canopy) and influences heat loss and the flux of wind-driven mixing energy into lakes, which control lake temperatures and indirectly structure lake ecosystem processes, including carbon cycling and thermal habitat partitioning. Lakeshore wind sheltering has often been parameterized by lake surface area but such empirical relationships are only based on forested lakeshores and overlook the contributions of local land cover and terrain to wind sheltering. This study is the first to examine the utility of satellite imagery-derived broad-scale estimates of wind sheltering across a diversity of land covers. Using 30 m spatial resolution ASTER GDEM2 elevation data, the mean sheltering height, hs, being the combination of local topographic rise and canopy height above the lake surface, is calculated within 100 m-wide buffers surrounding 76,000 lakes in the U.S. state of Wisconsin. Uncertainty of GDEM2-derived hs was compared to SRTM-, high-resolution G-LiHT lidar-, and ICESat-derived estimates of hs, respective influences of land cover type and buffer width on hsare examined; and the effect of including satellite-based hs on the accuracy of a statewide lake hydrodynamic model was discussed. Though GDEM2 hs uncertainty was comparable to or better than other satellite-based measures of hs, its higher spatial resolution and broader spatial coverage allowed more lakes to be included in modeling efforts. GDEM2 was shown to offer superior utility for estimating hs compared to other satellite-derived data, but was limited by its consistent underestimation of hs, inability to detect within-buffer hs variability, and differing accuracy across land cover types. Nonetheless

  7. Presentation of a stochastic model estimating the wind energy contribution in remote island electrical networks

    International Nuclear Information System (INIS)

    Kaldellis, J.K.; Kapsali, M.; Tiligadas, D.

    2012-01-01

    Highlights: ► This study estimates the maximum wind energy contribution to an isolated micro-grid. ► An integrated computational tool is developed on the basis of stochastic analysis. ► The probability distribution of the wind energy surplus and deficit is estimated. ► The results indicate that a strict penetration limit is imposed to wind energy. -- Abstract: The electrification in remote islands whose electricity distribution network is not connected to the mainland’s grid is mostly based on Autonomous Power Stations (APSs) that are usually characterized by a considerably high electricity production cost, while at the same time the contribution of Renewable Energy Sources (RES) in these regions accounts for less than 10% of the total electricity generation. This actually results from the fact that despite the excellent wind potential of most of these islands, the wind energy contribution is significantly restricted from limits imposed to protect the remote electrical grids from possible instability problems, due to the stochastic wind speed behavior and the variable electricity consumption. On the basis of probability distribution of the load demand of a representative Greek island and the corresponding data related to the available wind potential, the present study estimates the maximum – acceptable by the local grid – wind energy contribution. For that reason, an integrated computational algorithm has been developed from first principles, based on a stochastic analysis. According to the results obtained, it becomes evident that with the current wind turbine technology, wind energy cannot play a key role in coping with the electrification problems encountered in many Greek island regions, excluding however the case of introducing bulk energy storage systems that may provide considerable recovery of the remarkable wind energy rejections expected.

  8. Wind inflow observation from load harmonics

    Directory of Open Access Journals (Sweden)

    M. Bertelè

    2017-12-01

    Full Text Available The wind field leaves its fingerprint on the rotor response. This fact can be exploited by using the rotor as a sensor: by looking at the rotor response, in the present case in terms of blade loads, one may infer the wind characteristics. This paper describes a wind state observer that estimates four wind parameters, namely the vertical and horizontal shears and the yaw and upflow misalignment angles, from out-of-plane and in-plane blade bending moments. The resulting observer provides on-rotor wind inflow characteristics that can be exploited for wind turbine and wind farm control. The proposed formulation is evaluated through extensive numerical simulations in turbulent and nonturbulent wind conditions using a high-fidelity aeroservoelastic model of a multi-MW wind turbine.

  9. Estimates of Sputter Yields of Solar-Wind Heavy Ions of Lunar Regolith Materials

    Science.gov (United States)

    Barghouty, Abdulmasser F.; Adams, James H., Jr.

    2008-01-01

    At energies of approximately 1 keV/amu, solar-wind protons and heavy ions interact with the lunar surface materials via a number of microscopic interactions that include sputtering. Solar-wind induced sputtering is a main mechanism by which the composition of the topmost layers of the lunar surface can change, dynamically and preferentially. This work concentrates on sputtering induced by solar-wind heavy ions. Sputtering associated with slow (speeds the electrons speed in its first Bohr orbit) and highly charged ions are known to include both kinetic and potential sputtering. Potential sputtering enjoys some unique characteristics that makes it of special interest to lunar science and exploration. Unlike the yield from kinetic sputtering where simulation and approximation schemes exist, the yield from potential sputtering is not as easy to estimate. This work will present a preliminary numerical scheme designed to estimate potential sputtering yields from reactions relevant to this aspect of solar-wind lunar-surface coupling.

  10. Parameter estimation and inverse problems

    CERN Document Server

    Aster, Richard C; Thurber, Clifford H

    2005-01-01

    Parameter Estimation and Inverse Problems primarily serves as a textbook for advanced undergraduate and introductory graduate courses. Class notes have been developed and reside on the World Wide Web for faciliting use and feedback by teaching colleagues. The authors'' treatment promotes an understanding of fundamental and practical issus associated with parameter fitting and inverse problems including basic theory of inverse problems, statistical issues, computational issues, and an understanding of how to analyze the success and limitations of solutions to these probles. The text is also a practical resource for general students and professional researchers, where techniques and concepts can be readily picked up on a chapter-by-chapter basis.Parameter Estimation and Inverse Problems is structured around a course at New Mexico Tech and is designed to be accessible to typical graduate students in the physical sciences who may not have an extensive mathematical background. It is accompanied by a Web site that...

  11. Estimation of the high-spatial-resolution variability in extreme wind speeds for forestry applications

    Directory of Open Access Journals (Sweden)

    A. Venäläinen

    2017-07-01

    Full Text Available The bioeconomy has an increasing role to play in climate change mitigation and the sustainable development of national economies. In Finland, a forested country, over 50 % of the current bioeconomy relies on the sustainable management and utilization of forest resources. Wind storms are a major risk that forests are exposed to and high-spatial-resolution analysis of the most vulnerable locations can produce risk assessment of forest management planning. In this paper, we examine the feasibility of the wind multiplier approach for downscaling of maximum wind speed, using 20 m spatial resolution CORINE land-use dataset and high-resolution digital elevation data. A coarse spatial resolution estimate of the 10-year return level of maximum wind speed was obtained from the ERA-Interim reanalyzed data. Using a geospatial re-mapping technique the data were downscaled to 26 meteorological station locations to represent very diverse environments. Applying a comparison, we find that the downscaled 10-year return levels represent 66 % of the observed variation among the stations examined. In addition, the spatial variation in wind-multiplier-downscaled 10-year return level wind was compared with the WAsP model-simulated wind. The heterogeneous test area was situated in northern Finland, and it was found that the major features of the spatial variation were similar, but in some locations, there were relatively large differences. The results indicate that the wind multiplier method offers a pragmatic and computationally feasible tool for identifying at a high spatial resolution those locations with the highest forest wind damage risks. It can also be used to provide the necessary wind climate information for wind damage risk model calculations, thus making it possible to estimate the probability of predicted threshold wind speeds for wind damage and consequently the probability (and amount of wind damage for certain forest stand configurations.

  12. Pollen parameters estimates of genetic variability among newly ...

    African Journals Online (AJOL)

    Pollen parameters estimates of genetic variability among newly selected Nigerian roselle (Hibiscus sabdariffa L.) genotypes. ... Estimates of some pollen parameters where used to assess the genetic diversity among ... HOW TO USE AJOL.

  13. A Comparative Study of Distribution System Parameter Estimation Methods

    Energy Technology Data Exchange (ETDEWEB)

    Sun, Yannan; Williams, Tess L.; Gourisetti, Sri Nikhil Gup

    2016-07-17

    In this paper, we compare two parameter estimation methods for distribution systems: residual sensitivity analysis and state-vector augmentation with a Kalman filter. These two methods were originally proposed for transmission systems, and are still the most commonly used methods for parameter estimation. Distribution systems have much lower measurement redundancy than transmission systems. Therefore, estimating parameters is much more difficult. To increase the robustness of parameter estimation, the two methods are applied with combined measurement snapshots (measurement sets taken at different points in time), so that the redundancy for computing the parameter values is increased. The advantages and disadvantages of both methods are discussed. The results of this paper show that state-vector augmentation is a better approach for parameter estimation in distribution systems. Simulation studies are done on a modified version of IEEE 13-Node Test Feeder with varying levels of measurement noise and non-zero error in the other system model parameters.

  14. Applicability of Synthetic Aperture Radar Wind Retrievals on Offshore Wind Resources Assessment in Hangzhou Bay, China

    DEFF Research Database (Denmark)

    Chang, Rui; Zhu, Rong; Badger, Merete

    2014-01-01

    In view of the high cost and sparse spatial resolution of offshore meteorological observations, ocean winds retrieved from satellites are valuable in offshore wind resource assessment as a supplement to in situ measurements. This study examines satellite synthetic aperture radar (SAR) images from...... ENVISAT advanced SAR (ASAR) for mapping wind resources with high spatial resolution. Around 181 collected pairs of wind data from SAR wind maps and from 13 meteorological stations in Hangzhou Bay are compared. The statistical results comparing in situ wind speed and SAR-based wind speed show a standard...... density functions are compared at one meteorological station. The SAR-based results appear not to estimate the mean wind speed, Weibull scale and shape parameters and wind power density from the full in situ data set so well due to the lower number of satellite samples. Distributions calculated from...

  15. On the equivalence of the solar wind coupling parameter ε and the magnetospheric energy output parameter UT during intense geomagnetic storms

    International Nuclear Information System (INIS)

    Gonzalez, W.D.; Gonzalez, A.L.C.; Tsurutani, B.T.

    1990-01-01

    For intervals with intense geomagnetic activity it is shown that the solar wind coupling parameter ε and the magnetospheric output parameter U T are equivalent and that ranges of values of ε can be set up in terms of values of the ring current-time constant τ. (author)

  16. Multi-Parameter Estimation for Orthorhombic Media

    KAUST Repository

    Masmoudi, Nabil

    2015-08-19

    Building reliable anisotropy models is crucial in seismic modeling, imaging and full waveform inversion. However, estimating anisotropy parameters is often hampered by the trade off between inhomogeneity and anisotropy. For instance, one way to estimate the anisotropy parameters is to relate them analytically to traveltimes, which is challenging in inhomogeneous media. Using perturbation theory, we develop travel-time approximations for orthorhombic media as explicit functions of the anellipticity parameters η1, η2 and a parameter Δγ in inhomogeneous background media. Specifically, our expansion assumes inhomogeneous ellipsoidal anisotropic background model, which can be obtained from well information and stacking velocity analysis. This approach has two main advantages: in one hand, it provides a computationally efficient tool to solve the orthorhombic eikonal equation, on the other hand, it provides a mechanism to scan for the best fitting anisotropy parameters without the need for repetitive modeling of traveltimes, because the coefficients of the traveltime expansion are independent of the perturbed parameters. Furthermore, the coefficients of the traveltime expansion provide insights on the sensitivity of the traveltime with respect to the perturbed parameters. We show the accuracy of the traveltime approximations as well as an approach for multi-parameter scanning in orthorhombic media.

  17. Multi-Parameter Estimation for Orthorhombic Media

    KAUST Repository

    Masmoudi, Nabil; Alkhalifah, Tariq Ali

    2015-01-01

    Building reliable anisotropy models is crucial in seismic modeling, imaging and full waveform inversion. However, estimating anisotropy parameters is often hampered by the trade off between inhomogeneity and anisotropy. For instance, one way to estimate the anisotropy parameters is to relate them analytically to traveltimes, which is challenging in inhomogeneous media. Using perturbation theory, we develop travel-time approximations for orthorhombic media as explicit functions of the anellipticity parameters η1, η2 and a parameter Δγ in inhomogeneous background media. Specifically, our expansion assumes inhomogeneous ellipsoidal anisotropic background model, which can be obtained from well information and stacking velocity analysis. This approach has two main advantages: in one hand, it provides a computationally efficient tool to solve the orthorhombic eikonal equation, on the other hand, it provides a mechanism to scan for the best fitting anisotropy parameters without the need for repetitive modeling of traveltimes, because the coefficients of the traveltime expansion are independent of the perturbed parameters. Furthermore, the coefficients of the traveltime expansion provide insights on the sensitivity of the traveltime with respect to the perturbed parameters. We show the accuracy of the traveltime approximations as well as an approach for multi-parameter scanning in orthorhombic media.

  18. Method for Estimating Evaporative Potential (IM/CLO) from ASTM Standard Single Wind Velocity Measures

    Science.gov (United States)

    2016-08-10

    IM/CLO) FROM ASTM STANDARD SINGLE WIND VELOCITY MEASURES DISCLAIMER The opinions or assertions contained herein are the private views of the...USARIEM TECHNICAL REPORT T16-14 METHOD FOR ESTIMATING EVAPORATIVE POTENTIAL (IM/CLO) FROM ASTM STANDARD SINGLE WIND VELOCITY... ASTM STANDARD SINGLE WIND VELOCITY MEASURES Adam W. Potter Biophysics and Biomedical Modeling Division U.S. Army Research Institute of Environmental

  19. Maximum wind radius estimated by the 50 kt radius: improvement of storm surge forecasting over the western North Pacific

    Science.gov (United States)

    Takagi, Hiroshi; Wu, Wenjie

    2016-03-01

    Even though the maximum wind radius (Rmax) is an important parameter in determining the intensity and size of tropical cyclones, it has been overlooked in previous storm surge studies. This study reviews the existing estimation methods for Rmax based on central pressure or maximum wind speed. These over- or underestimate Rmax because of substantial variations in the data, although an average radius can be estimated with moderate accuracy. As an alternative, we propose an Rmax estimation method based on the radius of the 50 kt wind (R50). Data obtained by a meteorological station network in the Japanese archipelago during the passage of strong typhoons, together with the JMA typhoon best track data for 1990-2013, enabled us to derive the following simple equation, Rmax = 0.23 R50. Application to a recent strong typhoon, the 2015 Typhoon Goni, confirms that the equation provides a good estimation of Rmax, particularly when the central pressure became considerably low. Although this new method substantially improves the estimation of Rmax compared to the existing models, estimation errors are unavoidable because of fundamental uncertainties regarding the typhoon's structure or insufficient number of available typhoon data. In fact, a numerical simulation for the 2013 Typhoon Haiyan as well as 2015 Typhoon Goni demonstrates a substantial difference in the storm surge height for different Rmax. Therefore, the variability of Rmax should be taken into account in storm surge simulations (e.g., Rmax = 0.15 R50-0.35 R50), independently of the model used, to minimize the risk of over- or underestimating storm surges. The proposed method is expected to increase the predictability of major storm surges and to contribute to disaster risk management, particularly in the western North Pacific, including countries such as Japan, China, Taiwan, the Philippines, and Vietnam.

  20. Adaptive Disturbance Tracking Theory with State Estimation and State Feedback for Region II Control of Large Wind Turbines

    Science.gov (United States)

    Balas, Mark J.; Thapa Magar, Kaman S.; Frost, Susan A.

    2013-01-01

    A theory called Adaptive Disturbance Tracking Control (ADTC) is introduced and used to track the Tip Speed Ratio (TSR) of 5 MW Horizontal Axis Wind Turbine (HAWT). Since ADTC theory requires wind speed information, a wind disturbance generator model is combined with lower order plant model to estimate the wind speed as well as partial states of the wind turbine. In this paper, we present a proof of stability and convergence of ADTC theory with lower order estimator and show that the state feedback can be adaptive.

  1. Variation of Magnetic Field (By , Bz) Polarity and Statistical Analysis of Solar Wind Parameters during the Magnetic Storm Period

    OpenAIRE

    Ga-Hee Moon

    2011-01-01

    It is generally believed that the occurrence of a magnetic storm depends upon the solar wind conditions, particularly the southward interplanetary magnetic field (IMF) component. To understand the relationship between solar wind parameters and magnetic storms, variations in magnetic field polarity and solar wind parameters during magnetic storms are examined. A total of 156 storms during the period of 1997~2003 are used. According to the interplanetary driver, magnetic storms are ...

  2. Parameter and State Estimator for State Space Models

    Directory of Open Access Journals (Sweden)

    Ruifeng Ding

    2014-01-01

    Full Text Available This paper proposes a parameter and state estimator for canonical state space systems from measured input-output data. The key is to solve the system state from the state equation and to substitute it into the output equation, eliminating the state variables, and the resulting equation contains only the system inputs and outputs, and to derive a least squares parameter identification algorithm. Furthermore, the system states are computed from the estimated parameters and the input-output data. Convergence analysis using the martingale convergence theorem indicates that the parameter estimates converge to their true values. Finally, an illustrative example is provided to show that the proposed algorithm is effective.

  3. Comparison of interplanetary CME arrival times and solar wind parameters based on the WSA-ENLIL model with three cone types and observations

    Science.gov (United States)

    Jang, Soojeong; Moon, Y.-J.; Lee, Jae-Ok; Na, Hyeonock

    2014-09-01

    We have made a comparison between coronal mass ejection (CME)-associated shock propagations based on the Wang-Sheeley-Arge (WSA)-ENLIL model using three cone types and in situ observations. For this we use 28 full-halo CMEs, whose cone parameters are determined and their corresponding interplanetary shocks were observed at the Earth, from 2001 to 2002. We consider three different cone types (an asymmetric cone model, an ice cream cone model, and an elliptical cone model) to determine 3-D CME cone parameters (radial velocity, angular width, and source location), which are the input values of the WSA-ENLIL model. The mean absolute error of the CME-associated shock travel times for the WSA-ENLIL model using the ice-cream cone model is 9.9 h, which is about 1 h smaller than those of the other models. We compare the peak values and profiles of solar wind parameters (speed and density) with in situ observations. We find that the root-mean-square errors of solar wind peak speed and density for the ice cream and asymmetric cone model are about 190 km/s and 24/cm3, respectively. We estimate the cross correlations between the models and observations within the time lag of ± 2 days from the shock travel time. The correlation coefficients between the solar wind speeds from the WSA-ENLIL model using three cone types and in situ observations are approximately 0.7, which is larger than those of solar wind density (cc ˜0.6). Our preliminary investigations show that the ice cream cone model seems to be better than the other cone models in terms of the input parameters of the WSA-ENLIL model.

  4. Accounting for unsearched areas in estimating wind turbine-caused fatality

    Science.gov (United States)

    Huso, Manuela M.P.; Dalthorp, Dan

    2014-01-01

    With wind energy production expanding rapidly, concerns about turbine-induced bird and bat fatality have grown and the demand for accurate estimation of fatality is increasing. Estimation typically involves counting carcasses observed below turbines and adjusting counts by estimated detection probabilities. Three primary sources of imperfect detection are 1) carcasses fall into unsearched areas, 2) carcasses are removed or destroyed before sampling, and 3) carcasses present in the searched area are missed by observers. Search plots large enough to comprise 100% of turbine-induced fatality are expensive to search and may nonetheless contain areas unsearchable because of dangerous terrain or impenetrable brush. We evaluated models relating carcass density to distance from the turbine to estimate the proportion of carcasses expected to fall in searched areas and evaluated the statistical cost of restricting searches to areas near turbines where carcass density is highest and search conditions optimal. We compared 5 estimators differing in assumptions about the relationship of carcass density to distance from the turbine. We tested them on 6 different carcass dispersion scenarios at each of 3 sites under 2 different search regimes. We found that even simple distance-based carcass-density models were more effective at reducing bias than was a 5-fold expansion of the search area. Estimators incorporating fitted rather than assumed models were least biased, even under restricted searches. Accurate estimates of fatality at wind-power facilities will allow critical comparisons of rates among turbines, sites, and regions and contribute to our understanding of the potential environmental impact of this technology.

  5. Estimation of Separation Buffers for Wind-Prediction Error in an Airborne Separation Assistance System

    Science.gov (United States)

    Consiglio, Maria C.; Hoadley, Sherwood T.; Allen, B. Danette

    2009-01-01

    Wind prediction errors are known to affect the performance of automated air traffic management tools that rely on aircraft trajectory predictions. In particular, automated separation assurance tools, planned as part of the NextGen concept of operations, must be designed to account and compensate for the impact of wind prediction errors and other system uncertainties. In this paper we describe a high fidelity batch simulation study designed to estimate the separation distance required to compensate for the effects of wind-prediction errors throughout increasing traffic density on an airborne separation assistance system. These experimental runs are part of the Safety Performance of Airborne Separation experiment suite that examines the safety implications of prediction errors and system uncertainties on airborne separation assurance systems. In this experiment, wind-prediction errors were varied between zero and forty knots while traffic density was increased several times current traffic levels. In order to accurately measure the full unmitigated impact of wind-prediction errors, no uncertainty buffers were added to the separation minima. The goal of the study was to measure the impact of wind-prediction errors in order to estimate the additional separation buffers necessary to preserve separation and to provide a baseline for future analyses. Buffer estimations from this study will be used and verified in upcoming safety evaluation experiments under similar simulation conditions. Results suggest that the strategic airborne separation functions exercised in this experiment can sustain wind prediction errors up to 40kts at current day air traffic density with no additional separation distance buffer and at eight times the current day with no more than a 60% increase in separation distance buffer.

  6. Parameter Estimation in Stochastic Grey-Box Models

    DEFF Research Database (Denmark)

    Kristensen, Niels Rode; Madsen, Henrik; Jørgensen, Sten Bay

    2004-01-01

    An efficient and flexible parameter estimation scheme for grey-box models in the sense of discretely, partially observed Ito stochastic differential equations with measurement noise is presented along with a corresponding software implementation. The estimation scheme is based on the extended...... Kalman filter and features maximum likelihood as well as maximum a posteriori estimation on multiple independent data sets, including irregularly sampled data sets and data sets with occasional outliers and missing observations. The software implementation is compared to an existing software tool...... and proves to have better performance both in terms of quality of estimates for nonlinear systems with significant diffusion and in terms of reproducibility. In particular, the new tool provides more accurate and more consistent estimates of the parameters of the diffusion term....

  7. The estimation of early health effects for different combinations of release parameters and meteorological data

    International Nuclear Information System (INIS)

    Jeong, Jong Tae; Jung, Won Dea

    2001-01-01

    Variations in the number of early health effects resulting from the severe accidents of the YGN 3 and 4 nuclear power plants were examined for different combinations of release parameters and meteorological data. The release parameters and meteorological data were selected in combination to define a limited number of basic spectra characterized by release height, heat content, release time, warning time, wind speed, rainfall rate, and atmospheric stability class. Variant seasonal spectra were also defined in order to estimate the potential significance of seasonal variations as a factor determining the incidence or number of early health effects. The results show that there are large differences in consequences from spectrum to spectrum, although an equal amount and mix of radioactive material is released to the atmosphere in each case. Also, there are large differences in the estimated number of health effects from season to season due to distinct seasonal variations in meteorological combinations in Korea. Therefore, it is necessary to consider seasonal characteristics in developing optimum emergency response strategies

  8. Kinetic parameter estimation from SPECT cone-beam projection measurements

    International Nuclear Information System (INIS)

    Huesman, Ronald H.; Reutter, Bryan W.; Zeng, G. Larry; Gullberg, Grant T.

    1998-01-01

    Kinetic parameters are commonly estimated from dynamically acquired nuclear medicine data by first reconstructing a dynamic sequence of images and subsequently fitting the parameters to time-activity curves generated from regions of interest overlaid upon the image sequence. Biased estimates can result from images reconstructed using inconsistent projections of a time-varying distribution of radiopharmaceutical acquired by a rotating SPECT system. If the SPECT data are acquired using cone-beam collimators wherein the gantry rotates so that the focal point of the collimators always remains in a plane, additional biases can arise from images reconstructed using insufficient, as well as truncated, projection samples. To overcome these problems we have investigated the estimation of kinetic parameters directly from SPECT cone-beam projection data by modelling the data acquisition process. To accomplish this it was necessary to parametrize the spatial and temporal distribution of the radiopharmaceutical within the SPECT field of view. In a simulated chest image volume, kinetic parameters were estimated for simple one-compartment models for four myocardial regions of interest. Myocardial uptake and washout parameters estimated by conventional analysis of noiseless simulated cone-beam data had biases ranging between 3-26% and 0-28%, respectively. Parameters estimated directly from the noiseless projection data were unbiased as expected, since the model used for fitting was faithful to the simulation. Statistical uncertainties of parameter estimates for 10 000 000 events ranged between 0.2-9% for the uptake parameters and between 0.3-6% for the washout parameters. (author)

  9. Off-Shore wind potential estimation along the coast of Chile by using scatterometer and Reanalysis data

    Directory of Open Access Journals (Sweden)

    C. Mattar

    2014-06-01

    Full Text Available This work presents the first offshore wind potential estimation over the coast of Chile using long term data series from “QuikSCAT (V04 wind vectors” and ERA-interim’s wind product between 1999-2009 and 1979-2012, respectively. Weibull and Rayleigh’s distribution were used to adjust the data series from the study period to find the probability density function, mean wind speed, maximum and minimum from each data series adjusted per pixel. Power generation and a capacity factor were estimated for the whole scene using three wind turbine models corresponding to 3.6, 5.0 and 8.0 MW. The images obtained from the data processing were grouped into three different wind power zones named (A located up north, (B in the center and (C down south-center. The mean capacity factors are higher than 20%, moreover B and C areas have an average of 36%. This work shows the high wind power potential to generate electricity by using wind off-shore technologies along the coast of Chile.

  10. Global sensitivity analysis in wind energy assessment

    Science.gov (United States)

    Tsvetkova, O.; Ouarda, T. B.

    2012-12-01

    Wind energy is one of the most promising renewable energy sources. Nevertheless, it is not yet a common source of energy, although there is enough wind potential to supply world's energy demand. One of the most prominent obstacles on the way of employing wind energy is the uncertainty associated with wind energy assessment. Global sensitivity analysis (SA) studies how the variation of input parameters in an abstract model effects the variation of the variable of interest or the output variable. It also provides ways to calculate explicit measures of importance of input variables (first order and total effect sensitivity indices) in regard to influence on the variation of the output variable. Two methods of determining the above mentioned indices were applied and compared: the brute force method and the best practice estimation procedure In this study a methodology for conducting global SA of wind energy assessment at a planning stage is proposed. Three sampling strategies which are a part of SA procedure were compared: sampling based on Sobol' sequences (SBSS), Latin hypercube sampling (LHS) and pseudo-random sampling (PRS). A case study of Masdar City, a showcase of sustainable living in the UAE, is used to exemplify application of the proposed methodology. Sources of uncertainty in wind energy assessment are very diverse. In the case study the following were identified as uncertain input parameters: the Weibull shape parameter, the Weibull scale parameter, availability of a wind turbine, lifetime of a turbine, air density, electrical losses, blade losses, ineffective time losses. Ineffective time losses are defined as losses during the time when the actual wind speed is lower than the cut-in speed or higher than the cut-out speed. The output variable in the case study is the lifetime energy production. Most influential factors for lifetime energy production are identified with the ranking of the total effect sensitivity indices. The results of the present

  11. Traveltime approximations and parameter estimation for orthorhombic media

    KAUST Repository

    Masmoudi, Nabil

    2016-05-30

    Building anisotropy models is necessary for seismic modeling and imaging. However, anisotropy estimation is challenging due to the trade-off between inhomogeneity and anisotropy. Luckily, we can estimate the anisotropy parameters Building anisotropy models is necessary for seismic modeling and imaging. However, anisotropy estimation is challenging due to the trade-off between inhomogeneity and anisotropy. Luckily, we can estimate the anisotropy parameters if we relate them analytically to traveltimes. Using perturbation theory, we have developed traveltime approximations for orthorhombic media as explicit functions of the anellipticity parameters η1, η2, and Δχ in inhomogeneous background media. The parameter Δχ is related to Tsvankin-Thomsen notation and ensures easier computation of traveltimes in the background model. Specifically, our expansion assumes an inhomogeneous ellipsoidal anisotropic background model, which can be obtained from well information and stacking velocity analysis. We have used the Shanks transform to enhance the accuracy of the formulas. A homogeneous medium simplification of the traveltime expansion provided a nonhyperbolic moveout description of the traveltime that was more accurate than other derived approximations. Moreover, the formulation provides a computationally efficient tool to solve the eikonal equation of an orthorhombic medium, without any constraints on the background model complexity. Although, the expansion is based on the factorized representation of the perturbation parameters, smooth variations of these parameters (represented as effective values) provides reasonable results. Thus, this formulation provides a mechanism to estimate the three effective parameters η1, η2, and Δχ. We have derived Dix-type formulas for orthorhombic medium to convert the effective parameters to their interval values.

  12. Parameter Estimation of Nonlinear Models in Forestry.

    OpenAIRE

    Fekedulegn, Desta; Mac Siúrtáin, Máirtín Pádraig; Colbert, Jim J.

    1999-01-01

    Partial derivatives of the negative exponential, monomolecular, Mitcherlich, Gompertz, logistic, Chapman-Richards, von Bertalanffy, Weibull and the Richard’s nonlinear growth models are presented. The application of these partial derivatives in estimating the model parameters is illustrated. The parameters are estimated using the Marquardt iterative method of nonlinear regression relating top height to age of Norway spruce (Picea abies L.) from the Bowmont Norway Spruce Thinnin...

  13. Weibull Wind-Speed Distribution Parameters Derived from a Combination of Wind-Lidar and Tall-Mast Measurements Over Land, Coastal and Marine Sites

    DEFF Research Database (Denmark)

    Gryning, Sven-Erik; Floors, Rogier Ralph; Peña, Alfredo

    2016-01-01

    Wind-speed observations from tall towers are used in combination with observations up to 600 m in altitude from a Doppler wind lidar to study the long-term conditions over suburban (Hamburg), rural coastal (Høvsøre) and marine (FINO3) sites. The variability in the wind field among the sites is ex...... of the vertical profile of the shape parameter fits well with observations over land, coastal regions and over the sea. An applied model for the dependence of the reversal height on the surface roughness is in good agreement with the observations over land....

  14. Nonlinear Parameter Estimation in Microbiological Degradation Systems and Statistic Test for Common Estimation

    DEFF Research Database (Denmark)

    Sommer, Helle Mølgaard; Holst, Helle; Spliid, Henrik

    1995-01-01

    Three identical microbiological experiments were carried out and analysed in order to examine the variability of the parameter estimates. The microbiological system consisted of a substrate (toluene) and a biomass (pure culture) mixed together in an aquifer medium. The degradation of the substrate...... and the growth of the biomass are described by the Monod model consisting of two nonlinear coupled first-order differential equations. The objective of this study was to estimate the kinetic parameters in the Monod model and to test whether the parameters from the three identical experiments have the same values....... Estimation of the parameters was obtained using an iterative maximum likelihood method and the test used was an approximative likelihood ratio test. The test showed that the three sets of parameters were identical only on a 4% alpha level....

  15. Parameter estimation in X-ray astronomy

    International Nuclear Information System (INIS)

    Lampton, M.; Margon, B.; Bowyer, S.

    1976-01-01

    The problems of model classification and parameter estimation are examined, with the objective of establishing the statistical reliability of inferences drawn from X-ray observations. For testing the validities of classes of models, the procedure based on minimizing the chi 2 statistic is recommended; it provides a rejection criterion at any desired significance level. Once a class of models has been accepted, a related procedure based on the increase of chi 2 gives a confidence region for the values of the model's adjustable parameters. The procedure allows the confidence level to be chosen exactly, even for highly nonlinear models. Numerical experiments confirm the validity of the prescribed technique.The chi 2 /sub min/+1 error estimation method is evaluated and found unsuitable when several parameter ranges are to be derived, because it substantially underestimates their joint errors. The ratio of variances method, while formally correct, gives parameter confidence regions which are more variable than necessary

  16. A Novel Nonlinear Parameter Estimation Method of Soft Tissues

    Directory of Open Access Journals (Sweden)

    Qianqian Tong

    2017-12-01

    Full Text Available The elastic parameters of soft tissues are important for medical diagnosis and virtual surgery simulation. In this study, we propose a novel nonlinear parameter estimation method for soft tissues. Firstly, an in-house data acquisition platform was used to obtain external forces and their corresponding deformation values. To provide highly precise data for estimating nonlinear parameters, the measured forces were corrected using the constructed weighted combination forecasting model based on a support vector machine (WCFM_SVM. Secondly, a tetrahedral finite element parameter estimation model was established to describe the physical characteristics of soft tissues, using the substitution parameters of Young’s modulus and Poisson’s ratio to avoid solving complicated nonlinear problems. To improve the robustness of our model and avoid poor local minima, the initial parameters solved by a linear finite element model were introduced into the parameter estimation model. Finally, a self-adapting Levenberg–Marquardt (LM algorithm was presented, which is capable of adaptively adjusting iterative parameters to solve the established parameter estimation model. The maximum absolute error of our WCFM_SVM model was less than 0.03 Newton, resulting in more accurate forces in comparison with other correction models tested. The maximum absolute error between the calculated and measured nodal displacements was less than 1.5 mm, demonstrating that our nonlinear parameters are precise.

  17. Estimates for the parameters of the heavy quark expansion

    Energy Technology Data Exchange (ETDEWEB)

    Heinonen, Johannes; Mannel, Thomas [Universitaet Siegen (Germany)

    2015-07-01

    We give improved estimates for the non-perturbative parameters appearing in the heavy quark expansion for inclusive decays. While the parameters appearing in low orders of this expansion can be extracted from data, the number of parameters in higher orders proliferates strongly, making a determination of these parameters from data impossible. Thus, one has to rely on theoretical estimates which may be obtained from an insertion of intermediate states. We refine this method and attempt to estimate the uncertainties of this approach.

  18. On multivariate imputation and forecasting of decadal wind speed missing data.

    Science.gov (United States)

    Wesonga, Ronald

    2015-01-01

    This paper demonstrates the application of multiple imputations by chained equations and time series forecasting of wind speed data. The study was motivated by the high prevalence of missing wind speed historic data. Findings based on the fully conditional specification under multiple imputations by chained equations, provided reliable wind speed missing data imputations. Further, the forecasting model shows, the smoothing parameter, alpha (0.014) close to zero, confirming that recent past observations are more suitable for use to forecast wind speeds. The maximum decadal wind speed for Entebbe International Airport was estimated to be 17.6 metres per second at a 0.05 level of significance with a bound on the error of estimation of 10.8 metres per second. The large bound on the error of estimations confirms the dynamic tendencies of wind speed at the airport under study.

  19. On robust parameter estimation in brain-computer interfacing

    Science.gov (United States)

    Samek, Wojciech; Nakajima, Shinichi; Kawanabe, Motoaki; Müller, Klaus-Robert

    2017-12-01

    Objective. The reliable estimation of parameters such as mean or covariance matrix from noisy and high-dimensional observations is a prerequisite for successful application of signal processing and machine learning algorithms in brain-computer interfacing (BCI). This challenging task becomes significantly more difficult if the data set contains outliers, e.g. due to subject movements, eye blinks or loose electrodes, as they may heavily bias the estimation and the subsequent statistical analysis. Although various robust estimators have been developed to tackle the outlier problem, they ignore important structural information in the data and thus may not be optimal. Typical structural elements in BCI data are the trials consisting of a few hundred EEG samples and indicating the start and end of a task. Approach. This work discusses the parameter estimation problem in BCI and introduces a novel hierarchical view on robustness which naturally comprises different types of outlierness occurring in structured data. Furthermore, the class of minimum divergence estimators is reviewed and a robust mean and covariance estimator for structured data is derived and evaluated with simulations and on a benchmark data set. Main results. The results show that state-of-the-art BCI algorithms benefit from robustly estimated parameters. Significance. Since parameter estimation is an integral part of various machine learning algorithms, the presented techniques are applicable to many problems beyond BCI.

  20. Probabilistic Design of Wind Turbines

    DEFF Research Database (Denmark)

    Sørensen, John Dalsgaard; Toft, H.S.

    2010-01-01

    Probabilistic design of wind turbines requires definition of the structural elements to be included in the probabilistic basis: e.g., blades, tower, foundation; identification of important failure modes; careful stochastic modeling of the uncertain parameters; recommendations for target reliability....... It is described how uncertainties in wind turbine design related to computational models, statistical data from test specimens, results from a few full-scale tests and from prototype wind turbines can be accounted for using the Maximum Likelihood Method and a Bayesian approach. Assessment of the optimal...... reliability level by cost-benefit optimization is illustrated by an offshore wind turbine example. Uncertainty modeling is illustrated by an example where physical, statistical and model uncertainties are estimated....

  1. Wind Plant Performance Prediction (WP3) Project

    Energy Technology Data Exchange (ETDEWEB)

    Craig, Anna [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

    2018-01-26

    The methods for analysis of operational wind plant data are highly variable across the wind industry, leading to high uncertainties in the validation and bias-correction of preconstruction energy estimation methods. Lack of credibility in the preconstruction energy estimates leads to significant impacts on project financing and therefore the final levelized cost of energy for the plant. In this work, the variation in the evaluation of a wind plant's operational energy production as a result of variations in the processing methods applied to the operational data is examined. Preliminary results indicate that selection of the filters applied to the data and the filter parameters can have significant impacts in the final computed assessment metrics.

  2. Estimating the wake deflection downstream of a wind turbine in different atmospheric stabilities: an LES study

    Directory of Open Access Journals (Sweden)

    L. Vollmer

    2016-09-01

    Full Text Available An intentional yaw misalignment of wind turbines is currently discussed as one possibility to increase the overall energy yield of wind farms. The idea behind this control is to decrease wake losses of downstream turbines by altering the wake trajectory of the controlled upwind turbines. For an application of such an operational control, precise knowledge about the inflow wind conditions, the magnitude of wake deflection by a yawed turbine and the propagation of the wake is crucial. The dependency of the wake deflection on the ambient wind conditions as well as the uncertainty of its trajectory are not sufficiently covered in current wind farm control models. In this study we analyze multiple sources that contribute to the uncertainty of the estimation of the wake deflection downstream of yawed wind turbines in different ambient wind conditions. We find that the wake shapes and the magnitude of deflection differ in the three evaluated atmospheric boundary layers of neutral, stable and unstable thermal stability. Uncertainty in the wake deflection estimation increases for smaller temporal averaging intervals. We also consider the choice of the method to define the wake center as a source of uncertainty as it modifies the result. The variance of the wake deflection estimation increases with decreasing atmospheric stability. Control of the wake position in a highly convective environment is therefore not recommended.

  3. A simulation of water pollution model parameter estimation

    Science.gov (United States)

    Kibler, J. F.

    1976-01-01

    A parameter estimation procedure for a water pollution transport model is elaborated. A two-dimensional instantaneous-release shear-diffusion model serves as representative of a simple transport process. Pollution concentration levels are arrived at via modeling of a remote-sensing system. The remote-sensed data are simulated by adding Gaussian noise to the concentration level values generated via the transport model. Model parameters are estimated from the simulated data using a least-squares batch processor. Resolution, sensor array size, and number and location of sensor readings can be found from the accuracies of the parameter estimates.

  4. Correlation of Magnetic Fields with Solar Wind Plasma Parameters at 1AU

    Science.gov (United States)

    Shen, F.

    2017-12-01

    The physical parameters of the solar wind observed in-situ near 1AU have been studied for several decades, and relationships between them, such as the positive correlation between the solar wind plasma temperature T and velocity V, and the negative correlation between density N and velocity V, are well known. However, the magnetic field intensity does not appear to be well correlated with any individual plasma parameter. In this paper, we discuss previously under-reported correlations between B and the combined plasma parameters √NV2 as well as between B and √NT. These two correlations are strong during the periods of corotating interaction regions and high speed streams, moderate during intervals of slow solar wind, and rather poor during the passage of interplanetary coronal mass ejections. The results indicate that the magnetic pressure in the solar wind is well correlated both with the plasma dynamic pressure and the thermal pressure. Then, we employ a 3D MHD model to simulate the formation of the relationships between the magnetic strength B and √NV2 as well as √NT observed at 1AU. The inner boundary condition is derived by empirical models, with the magnetic field and density are optional. Five kinds of boundary conditions at the inner boundary of heliosphere are tested. In the cases that the magnetic field is related to speed at the inner boundary, the correlation coefficients between B and √NV2 as well as between B and √NT are even higher than that in the observational results. At 1AU the simulated radial magnetic field shows little latitude dependence, which matches the observation of Ulysses. Most of the modeled characters in these cases are closer to observation than others. This inner boundary condition may more accurately characterize Sun's magnetic influence on the heliosphere. The new input may be able to improve the simulation of CME propagation in the inner heliosphere and the space weather forecasting.

  5. Estimation of Poisson-Dirichlet Parameters with Monotone Missing Data

    Directory of Open Access Journals (Sweden)

    Xueqin Zhou

    2017-01-01

    Full Text Available This article considers the estimation of the unknown numerical parameters and the density of the base measure in a Poisson-Dirichlet process prior with grouped monotone missing data. The numerical parameters are estimated by the method of maximum likelihood estimates and the density function is estimated by kernel method. A set of simulations was conducted, which shows that the estimates perform well.

  6. Probabilistic multiobjective wind-thermal economic emission dispatch based on point estimated method

    International Nuclear Information System (INIS)

    Azizipanah-Abarghooee, Rasoul; Niknam, Taher; Roosta, Alireza; Malekpour, Ahmad Reza; Zare, Mohsen

    2012-01-01

    In this paper, wind power generators are being incorporated in the multiobjective economic emission dispatch problem which minimizes wind-thermal electrical energy cost and emissions produced by fossil-fueled power plants, simultaneously. Large integration of wind energy sources necessitates an efficient model to cope with uncertainty arising from random wind variation. Hence, a multiobjective stochastic search algorithm based on 2m point estimated method is implemented to analyze the probabilistic wind-thermal economic emission dispatch problem considering both overestimation and underestimation of available wind power. 2m point estimated method handles the system uncertainties and renders the probability density function of desired variables efficiently. Moreover, a new population-based optimization algorithm called modified teaching-learning algorithm is proposed to determine the set of non-dominated optimal solutions. During the simulation, the set of non-dominated solutions are kept in an external memory (repository). Also, a fuzzy-based clustering technique is implemented to control the size of the repository. In order to select the best compromise solution from the repository, a niching mechanism is utilized such that the population will move toward a smaller search space in the Pareto-optimal front. In order to show the efficiency and feasibility of the proposed framework, three different test systems are represented as case studies. -- Highlights: ► WPGs are being incorporated in the multiobjective economic emission dispatch problem. ► 2m PEM handles the system uncertainties. ► A MTLBO is proposed to determine the set of non-dominated (Pareto) optimal solutions. ► A fuzzy-based clustering technique is implemented to control the size of the repository.

  7. Representivity of wind measurements for design wind speed estimations

    CSIR Research Space (South Africa)

    Goliger, Adam M

    2013-07-01

    Full Text Available of instrumentation sited according to World Meteorological Organization (WMO) requirements. With the advent of automatic weather station technology several decades ago, wind measurements have become much more cost-effective. While previously wind measurements were...

  8. Simplified rotor load models and fatigue damage estimates for offshore wind turbines.

    Science.gov (United States)

    Muskulus, M

    2015-02-28

    The aim of rotor load models is to characterize and generate the thrust loads acting on an offshore wind turbine. Ideally, the rotor simulation can be replaced by time series from a model with a few parameters and state variables only. Such models are used extensively in control system design and, as a potentially new application area, structural optimization of support structures. Different rotor load models are here evaluated for a jacket support structure in terms of fatigue lifetimes of relevant structural variables. All models were found to be lacking in accuracy, with differences of more than 20% in fatigue load estimates. The most accurate models were the use of an effective thrust coefficient determined from a regression analysis of dynamic thrust loads, and a novel stochastic model in state-space form. The stochastic model explicitly models the quasi-periodic components obtained from rotational sampling of turbulent fluctuations. Its state variables follow a mean-reverting Ornstein-Uhlenbeck process. Although promising, more work is needed on how to determine the parameters of the stochastic model and before accurate lifetime predictions can be obtained without comprehensive rotor simulations. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

  9. Stochastic Modeling of Long-Term and Extreme Value Estimation of Wind and Sea Conditions for Probabilistic Reliability Assessments of Wave Energy Devices

    DEFF Research Database (Denmark)

    Ambühl, Simon; Kofoed, Jens Peter; Sørensen, John Dalsgaard

    2014-01-01

    Wave energy power plants are expected to become one of the major future contribution to the sustainable electricity production. Optimal design of wave energy power plants is associated with modeling of physical, statistical, measurement and model uncertainties. This paper presents stochastic models...... for the significant wave height, the mean zero-crossing wave period and the wind speed for long-term and extreme estimations. The long-term estimation focuses on annual statistical distributions, the inter-annual variation of distribution parameters and the statistical uncertainty due to limited amount of data...

  10. Dependence of Weibull distribution parameters on the CNR threshold i wind lidar data

    DEFF Research Database (Denmark)

    Gryning, Sven-Erik; Batchvarova, Ekaterina; Floors, Rogier Ralph

    2015-01-01

    in the boundary layer. Observations from tall towers in combination with observations from a lidar of wind speed up to 600 m are used to study the long-term variability of the wind profile over sub-urban, rural, coastal and marine areas. The variability is expressed in terms of the shape parameter in the Weibull...... over land, both terms are about equally important in the coastal area where the height of the reversal height is low and in the marine conditions, the second term dominates....

  11. The use of wind tunnel facilities to estimate hydrodynamic data

    Science.gov (United States)

    Hoffmann, Kristoffer; Tophøj Rasmussen, Johannes; Hansen, Svend Ole; Reiso, Marit; Isaksen, Bjørn; Egeberg Aasland, Tale

    2016-03-01

    Experimental laboratory testing of vortex-induced structural oscillations in flowing water is an expensive and time-consuming procedure, and the testing of high Reynolds number flow regimes is complicated due to the requirement of either a large-scale or high-speed facility. In most cases, Reynolds number scaling effects are unavoidable, and these uncertainties have to be accounted for, usually by means of empirical rules-of-thumb. Instead of performing traditional hydrodynamic measurements, wind tunnel testing in an appropriately designed experimental setup may provide an alternative and much simpler and cheaper framework for estimating the structural behavior under water current and wave loading. Furthermore, the fluid velocities that can be obtained in a wind tunnel are substantially higher than in a water testing facility, thus decreasing the uncertainty from scaling effects. In a series of measurements, wind tunnel testing has been used to investigate the static response characteristics of a circular and a rectangular section model. Motivated by the wish to estimate the vortex-induced in-line vibration characteristics of a neutrally buoyant submerged marine structure, additional measurements on extremely lightweight, helium-filled circular section models were conducted in a dynamic setup. During the experiment campaign, the mass of the model was varied in order to investigate how the mass ratio influences the vibration amplitude. The results show good agreement with both aerodynamic and hydrodynamic experimental results documented in the literature.

  12. Parameter estimation in stochastic differential equations

    CERN Document Server

    Bishwal, Jaya P N

    2008-01-01

    Parameter estimation in stochastic differential equations and stochastic partial differential equations is the science, art and technology of modelling complex phenomena and making beautiful decisions. The subject has attracted researchers from several areas of mathematics and other related fields like economics and finance. This volume presents the estimation of the unknown parameters in the corresponding continuous models based on continuous and discrete observations and examines extensively maximum likelihood, minimum contrast and Bayesian methods. Useful because of the current availability of high frequency data is the study of refined asymptotic properties of several estimators when the observation time length is large and the observation time interval is small. Also space time white noise driven models, useful for spatial data, and more sophisticated non-Markovian and non-semimartingale models like fractional diffusions that model the long memory phenomena are examined in this volume.

  13. Statistical study of waves distribution in the inner magnetosphere using geomagnetic indices and solar wind parameters

    Science.gov (United States)

    Aryan, H.; Yearby, K.; Balikhin, M. A.; Krasnoselskikh, V.; Agapitov, O. V.

    2013-12-01

    The interaction of gyroresonant wave particles with chorus waves largely determine the dynamics of the Earth's radiation belts that effects the acceleration and loss of radiation belt electrons. The common approach is to present model waves distribution in the inner magnetosphere under different values of geomagnetic activity as expressed by the geomagnetic indices. However it is known that solar wind parameters such as bulk velocity (V) and density (n) are more effective in the control of high energy fluxes at the geostationary orbit. Therefore in the present study the set of parameters of the wave distribution is expanded to include the solar wind parameters in addition to the geomagnetic indices. The present study examines almost four years (01, January, 2004 to 29, September, 2007) of Cluster STAFF-SA, Double Star TC1 and OMNI data in order to present a combined model of wave magnetic field intensities for the chorus waves as a function of magnetic local time (MLT), L-shell (L*), geomagnetic activity, and solar wind velocity and density. Generally, the largest wave intensities are observed during average solar wind velocities (3006cm-3. On the other hand the wave intensity is lower and limited between 06:00 to 18:00 MLT for V700kms-1.

  14. Analysis of a Kalman filter based method for on-line estimation of atmospheric dispersion parameters using radiation monitoring data

    DEFF Research Database (Denmark)

    Drews, Martin; Lauritzen, Bent; Madsen, Henrik

    2005-01-01

    A Kalman filter method is discussed for on-line estimation of radioactive release and atmospheric dispersion from a time series of off-site radiation monitoring data. The method is based on a state space approach, where a stochastic system equation describes the dynamics of the plume model...... parameters, and the observables are linked to the state variables through a static measurement equation. The method is analysed for three simple state space models using experimental data obtained at a nuclear research reactor. Compared to direct measurements of the atmospheric dispersion, the Kalman filter...... estimates are found to agree well with the measured parameters, provided that the radiation measurements are spread out in the cross-wind direction. For less optimal detector placement it proves difficult to distinguish variations in the source term and plume height; yet the Kalman filter yields consistent...

  15. How to fool cosmic microwave background parameter estimation

    International Nuclear Information System (INIS)

    Kinney, William H.

    2001-01-01

    With the release of the data from the Boomerang and MAXIMA-1 balloon flights, estimates of cosmological parameters based on the cosmic microwave background (CMB) have reached unprecedented precision. In this paper I show that it is possible for these estimates to be substantially biased by features in the primordial density power spectrum. I construct primordial power spectra which mimic to within cosmic variance errors the effect of changing parameters such as the baryon density and neutrino mass, meaning that even an ideal measurement would be unable to resolve the degeneracy. Complementary measurements are necessary to resolve this ambiguity in parameter estimation efforts based on CMB temperature fluctuations alone

  16. Summary of the DREAM8 Parameter Estimation Challenge: Toward Parameter Identification for Whole-Cell Models.

    Directory of Open Access Journals (Sweden)

    Jonathan R Karr

    2015-05-01

    Full Text Available Whole-cell models that explicitly represent all cellular components at the molecular level have the potential to predict phenotype from genotype. However, even for simple bacteria, whole-cell models will contain thousands of parameters, many of which are poorly characterized or unknown. New algorithms are needed to estimate these parameters and enable researchers to build increasingly comprehensive models. We organized the Dialogue for Reverse Engineering Assessments and Methods (DREAM 8 Whole-Cell Parameter Estimation Challenge to develop new parameter estimation algorithms for whole-cell models. We asked participants to identify a subset of parameters of a whole-cell model given the model's structure and in silico "experimental" data. Here we describe the challenge, the best performing methods, and new insights into the identifiability of whole-cell models. We also describe several valuable lessons we learned toward improving future challenges. Going forward, we believe that collaborative efforts supported by inexpensive cloud computing have the potential to solve whole-cell model parameter estimation.

  17. Statistical Properties of Geomagnetic Activity Indices and Solar Wind Parameters

    Directory of Open Access Journals (Sweden)

    Jung-Hee Kim

    2014-06-01

    Full Text Available As the prediction of geomagnetic storms is becoming an important and practical problem, conditions in the Earth’s magnetosphere have been studied rigorously in terms of those in the interplanetary space. Another approach to space weather forecast is to deal with it as a probabilistic geomagnetic storm forecasting problem. In this study, we carry out detailed statistical analysis of solar wind parameters and geomagnetic indices examining the dependence of the distribution on the solar cycle and annual variations. Our main findings are as follows: (1 The distribution of parameters obtained via the superimposed epoch method follows the Gaussian distribution. (2 When solar activity is at its maximum the mean value of the distribution is shifted to the direction indicating the intense environment. Furthermore, the width of the distribution becomes wider at its maximum than at its minimum so that more extreme case can be expected. (3 The distribution of some certain heliospheric parameters is less sensitive to the phase of the solar cycle and annual variations. (4 The distribution of the eastward component of the interplanetary electric field BV and the solar wind driving function BV2, however, appears to be all dependent on the solar maximum/minimum, the descending/ascending phases of the solar cycle and the equinoxes/solstices. (5 The distribution of the AE index and the Dst index shares statistical features closely with BV and BV2 compared with other heliospheric parameters. In this sense, BV and BV2 are more robust proxies of the geomagnetic storm. We conclude by pointing out that our results allow us to step forward in providing the occurrence probability of geomagnetic storms for space weather and physical modeling.

  18. Sensitivity of Turbine-Height Wind Speeds to Parameters in Planetary Boundary-Layer and Surface-Layer Schemes in the Weather Research and Forecasting Model

    Science.gov (United States)

    Yang, Ben; Qian, Yun; Berg, Larry K.; Ma, Po-Lun; Wharton, Sonia; Bulaevskaya, Vera; Yan, Huiping; Hou, Zhangshuan; Shaw, William J.

    2017-01-01

    We evaluate the sensitivity of simulated turbine-height wind speeds to 26 parameters within the Mellor-Yamada-Nakanishi-Niino (MYNN) planetary boundary-layer scheme and MM5 surface-layer scheme of the Weather Research and Forecasting model over an area of complex terrain. An efficient sampling algorithm and generalized linear model are used to explore the multiple-dimensional parameter space and quantify the parametric sensitivity of simulated turbine-height wind speeds. The results indicate that most of the variability in the ensemble simulations is due to parameters related to the dissipation of turbulent kinetic energy (TKE), Prandtl number, turbulent length scales, surface roughness, and the von Kármán constant. The parameter associated with the TKE dissipation rate is found to be most important, and a larger dissipation rate produces larger hub-height wind speeds. A larger Prandtl number results in smaller nighttime wind speeds. Increasing surface roughness reduces the frequencies of both extremely weak and strong airflows, implying a reduction in the variability of wind speed. All of the above parameters significantly affect the vertical profiles of wind speed and the magnitude of wind shear. The relative contributions of individual parameters are found to be dependent on both the terrain slope and atmospheric stability.

  19. Parameter Estimation for Improving Association Indicators in Binary Logistic Regression

    Directory of Open Access Journals (Sweden)

    Mahdi Bashiri

    2012-02-01

    Full Text Available The aim of this paper is estimation of Binary logistic regression parameters for maximizing the log-likelihood function with improved association indicators. In this paper the parameter estimation steps have been explained and then measures of association have been introduced and their calculations have been analyzed. Moreover a new related indicators based on membership degree level have been expressed. Indeed association measures demonstrate the number of success responses occurred in front of failure in certain number of Bernoulli independent experiments. In parameter estimation, existing indicators values is not sensitive to the parameter values, whereas the proposed indicators are sensitive to the estimated parameters during the iterative procedure. Therefore, proposing a new association indicator of binary logistic regression with more sensitivity to the estimated parameters in maximizing the log- likelihood in iterative procedure is innovation of this study.

  20. Evaluation of global onshore wind energy potential and generation costs.

    Science.gov (United States)

    Zhou, Yuyu; Luckow, Patrick; Smith, Steven J; Clarke, Leon

    2012-07-17

    In this study, we develop an updated global estimate of onshore wind energy potential using reanalysis wind speed data, along with updated wind turbine technology performance, land suitability factors, cost assumptions, and explicit consideration of transmission distance in the calculation of transmission costs. We find that wind has the potential to supply a significant portion of the world energy needs, although this potential varies substantially by region and with assumptions such as on what types of land can be used to site wind farms. Total global economic wind potential under central assumptions, that is, intermediate between optimistic and pessimistic, is estimated to be approximately 119.5 petawatt hours per year (13.6 TW) at less than 9 cents/kWh. A sensitivity analysis of eight key parameters is presented. Wind potential is sensitive to a number of input parameters, particularly wind speed (varying by -70% to +450% at less than 9 cents/kWh), land suitability (by -55% to +25%), turbine density (by -60% to +80%), and cost and financing options (by -20% to +200%), many of which have important policy implications. As a result of sensitivities studied here we suggest that further research intended to inform wind supply curve development focus not purely on physical science, such as better resolved wind maps, but also on these less well-defined factors, such as land-suitability, that will also have an impact on the long-term role of wind power.

  1. A high resolution global wind atlas - improving estimation of world wind resources

    DEFF Research Database (Denmark)

    Badger, Jake; Ejsing Jørgensen, Hans

    2011-01-01

    to population centres, electrical transmission grids, terrain types, and protected land areas are important parts of the resource assessment downstream of the generation of wind climate statistics. Related to these issues of integration are the temporal characteristics and spatial correlation of the wind...... resources. These aspects will also be addressed by the Global Wind Atlas. The Global Wind Atlas, through a transparent methodology, will provide a unified, high resolution, and public domain dataset of wind energy resources for the whole world. The wind atlas data will be the most appropriate wind resource...

  2. Estimation of light transport parameters in biological media using ...

    Indian Academy of Sciences (India)

    Estimation of light transport parameters in biological media using coherent backscattering ... backscattered light for estimating the light transport parameters of biological media has been investigated. ... Pramana – Journal of Physics | News.

  3. Statistics of Parameter Estimates: A Concrete Example

    KAUST Repository

    Aguilar, Oscar; Allmaras, Moritz; Bangerth, Wolfgang; Tenorio, Luis

    2015-01-01

    © 2015 Society for Industrial and Applied Mathematics. Most mathematical models include parameters that need to be determined from measurements. The estimated values of these parameters and their uncertainties depend on assumptions made about noise

  4. Parameter Estimation of Partial Differential Equation Models

    KAUST Repository

    Xun, Xiaolei; Cao, Jiguo; Mallick, Bani; Maity, Arnab; Carroll, Raymond J.

    2013-01-01

    PDEs used in practice have no analytic solutions, and can only be solved with numerical methods. Currently, methods for estimating PDE parameters require repeatedly solving PDEs numerically under thousands of candidate parameter values, and thus

  5. Stochastic Parameter Estimation of Non-Linear Systems Using Only Higher Order Spectra of the Measured Response

    Science.gov (United States)

    Vasta, M.; Roberts, J. B.

    1998-06-01

    Methods for using fourth order spectral quantities to estimate the unknown parameters in non-linear, randomly excited dynamic systems are developed. Attention is focused on the case where only the response is measurable and the excitation is unmeasurable and known only in terms of a stochastic process model. The approach is illustrated through application to a non-linear oscillator with both non-linear damping and stiffness and with excitation modelled as a stationary Gaussian white noise process. The methods have applications in studies of the response of structures to random environmental loads, such as wind and ocean wave forces.

  6. Lightning Attachment Estimation to Wind Turbines by Utilizing Lightning Location Systems

    DEFF Research Database (Denmark)

    Vogel, Stephan; Holbøll, Joachim; Lopez, Javier

    2016-01-01

    three different wind power plant locations are analyzed and the impact of varying data qualities is evaluated regarding the ability to detect upward lightning. This work provides a variety of background information which is relevant to the exposure assessment of wind turbine and includes practical......The goal of a lightning exposure assessment is to identify the number, type and characteristics of lightning discharges to a certain structure. There are various Lightning Location System (LLS) technologies available, each of them are characterized by individual performance characteristics....... In this work, these technologies are reviewed and evaluated in order to obtain an estimation of which technologies are eligible to perform a lightning assessment to wind turbines. The results indicate that ground-based mid-range low frequency (LF) LLS systems are most qualified since they combine a wide...

  7. Estimating annoyance to calculated wind turbine shadow flicker is improved when variables associated with wind turbine noise exposure are considered.

    Science.gov (United States)

    Voicescu, Sonia A; Michaud, David S; Feder, Katya; Marro, Leonora; Than, John; Guay, Mireille; Denning, Allison; Bower, Tara; van den Berg, Frits; Broner, Norm; Lavigne, Eric

    2016-03-01

    The Community Noise and Health Study conducted by Health Canada included randomly selected participants aged 18-79 yrs (606 males, 632 females, response rate 78.9%), living between 0.25 and 11.22 km from operational wind turbines. Annoyance to wind turbine noise (WTN) and other features, including shadow flicker (SF) was assessed. The current analysis reports on the degree to which estimating high annoyance to wind turbine shadow flicker (HAWTSF) was improved when variables known to be related to WTN exposure were also considered. As SF exposure increased [calculated as maximum minutes per day (SFm)], HAWTSF increased from 3.8% at 0 ≤ SFm wind turbine-related features, concern for physical safety, and noise sensitivity. Reported dizziness was also retained in the final model at p = 0.0581. Study findings add to the growing science base in this area and may be helpful in identifying factors associated with community reactions to SF exposure from wind turbines.

  8. Parameter identification of JONSWAP spectrum acquired by airborne LIDAR

    Science.gov (United States)

    Yu, Yang; Pei, Hailong; Xu, Chengzhong

    2017-12-01

    In this study, we developed the first linear Joint North Sea Wave Project (JONSWAP) spectrum (JS), which involves a transformation from the JS solution to the natural logarithmic scale. This transformation is convenient for defining the least squares function in terms of the scale and shape parameters. We identified these two wind-dependent parameters to better understand the wind effect on surface waves. Due to its efficiency and high-resolution, we employed the airborne Light Detection and Ranging (LIDAR) system for our measurements. Due to the lack of actual data, we simulated ocean waves in the MATLAB environment, which can be easily translated into industrial programming language. We utilized the Longuet-Higgin (LH) random-phase method to generate the time series of wave records and used the fast Fourier transform (FFT) technique to compute the power spectra density. After validating these procedures, we identified the JS parameters by minimizing the mean-square error of the target spectrum to that of the estimated spectrum obtained by FFT. We determined that the estimation error is relative to the amount of available wave record data. Finally, we found the inverse computation of wind factors (wind speed and wind fetch length) to be robust and sufficiently precise for wave forecasting.

  9. Long-period variations of wind parameters in the mesopause region and the solar cycle dependence

    International Nuclear Information System (INIS)

    Greisiger, K.M.; Schminder, R.; Kuerschner, D.

    1987-01-01

    The solar cycle dependence of wind parameters below 100 km on the basis of long term continuous ionospheric drift measurements in the low frequency range is discussed. For the meridional prevailing wind no significant variation was found. The same comparison as for winter was done for summer where the previous investigations gave no correlation. Now the radar meteor wind measurement values, too, showed a significant negative correlation of the zonal prevailing wind with solar activity for the years 1976 to 1983. The ionospheric drift measurement results of Collm have the same tendency but a larger dispersion due to the lower accuracy of the harmonic analysis because of the shorter daily measuring interval in summer. Continuous wind observations in the upper mesopause region over more than 20 years revealed distinct long term variations, the origin of which cannot be explained with the present knowledge

  10. Solar wind parameters responsible for the plasma injection into the magnetospheric ring current region

    International Nuclear Information System (INIS)

    Bobrov, M.S.

    1977-01-01

    Solar wind effect on the magnetospheric ring-current region has been considered. The correlations with solar wind parameters of the magnitude qsub(o) proportional to the total energy of particles being injected into the magnetospheric ring-current region per one hour are studied statistically and by comparison of time variations. The data on 8 sporadic geomagnetic storms of various intensity, from moderate to very severe one, are used. It is found that qsub(o) correlates not only with the magnitude and the direction of the solar-wind magnetic field component normal to the ecliptic plane, Bsub(z), but also with the variability, sigmasub(B), of the total magnetic-field strength vector. The solar-wind flux velocity ν influences the average storm intensity but the time variations of ν during any individual storm do not correlate with those of qsub(o)

  11. Kalman filter data assimilation: targeting observations and parameter estimation.

    Science.gov (United States)

    Bellsky, Thomas; Kostelich, Eric J; Mahalov, Alex

    2014-06-01

    This paper studies the effect of targeted observations on state and parameter estimates determined with Kalman filter data assimilation (DA) techniques. We first provide an analytical result demonstrating that targeting observations within the Kalman filter for a linear model can significantly reduce state estimation error as opposed to fixed or randomly located observations. We next conduct observing system simulation experiments for a chaotic model of meteorological interest, where we demonstrate that the local ensemble transform Kalman filter (LETKF) with targeted observations based on largest ensemble variance is skillful in providing more accurate state estimates than the LETKF with randomly located observations. Additionally, we find that a hybrid ensemble Kalman filter parameter estimation method accurately updates model parameters within the targeted observation context to further improve state estimation.

  12. Kalman filter data assimilation: Targeting observations and parameter estimation

    International Nuclear Information System (INIS)

    Bellsky, Thomas; Kostelich, Eric J.; Mahalov, Alex

    2014-01-01

    This paper studies the effect of targeted observations on state and parameter estimates determined with Kalman filter data assimilation (DA) techniques. We first provide an analytical result demonstrating that targeting observations within the Kalman filter for a linear model can significantly reduce state estimation error as opposed to fixed or randomly located observations. We next conduct observing system simulation experiments for a chaotic model of meteorological interest, where we demonstrate that the local ensemble transform Kalman filter (LETKF) with targeted observations based on largest ensemble variance is skillful in providing more accurate state estimates than the LETKF with randomly located observations. Additionally, we find that a hybrid ensemble Kalman filter parameter estimation method accurately updates model parameters within the targeted observation context to further improve state estimation

  13. Aeroservoelasticity of wind turbines

    Energy Technology Data Exchange (ETDEWEB)

    Skovmose Kallesoee, B.

    2007-12-14

    This thesis deals with the fundamental aeroelastic interaction between structural motion, Pitch action and control for a wind turbine blade. As wind turbines become larger, the interaction between pitch action, blade motion, aerodynamic forces, and control become even more important to understand and address. The main contribution of this thesis is the development of an aeroelastic blade model which on the one hand includes the important effects of steady state blade deformation, gravity and pitch action, and on the other it is transparent, suitable for analytical analysis and parameter studies, and furthermore linear and therefore suitable for control design. The development of the primary aeroelastic blade model is divided into four steps: 1) Nonlinear partial differential equations (PDEs) of structural blade motion are derived together with equations of pitch action and rotor speed; the individual terms in these equations are discussed and given physical interpretations; 2) Steady state blade deformation and induced velocities are computed by combining the PDEs with a steady state aerodynamic model; 3) Aeroelastic modes of motion are computed by combining the linearized PDEs with a linear unsteady aerodynamic model; this model is used to analyze how blade deformation effects the modes of motion; and 4) the linear aeroelastic blade model is derived by a modal expansion of the linearized PDEs combined with a linear unsteady aerodynamic model. The aeroelastic blade model has many similarities to a 2D blade section model, and it can be used instead of this in many applications, giving a transparent connection to a real wind turbine blade. In this work the aeroelastic blade model is used to analyze interaction between pitch action, blade motion and wind speed variations. Furthermore the model is used to develop a state estimator for estimating the wind speed and wind shear, and to suggest a load reducing controller. The state estimator estimates the wind shear very

  14. On probabilistic forecasting of wind power time-series

    DEFF Research Database (Denmark)

    Pinson, Pierre

    power dynamics. In both cases, the model parameters are adaptively and recursively estimated, time-adaptativity being the result of exponential forgetting of past observations. The probabilistic forecasting methodology is applied at the Horns Rev wind farm in Denmark, for 10-minute ahead probabilistic...... forecasting of wind power generation. Probabilistic forecasts generated from the proposed methodology clearly have higher skill than those obtained from a classical Gaussian assumption about wind power predictive densities. Corresponding point forecasts also exhibit significantly lower error criteria....

  15. Wind Noise Reduction using Non-negative Sparse Coding

    DEFF Research Database (Denmark)

    Schmidt, Mikkel N.; Larsen, Jan; Hsiao, Fu-Tien

    2007-01-01

    We introduce a new speaker independent method for reducing wind noise in single-channel recordings of noisy speech. The method is based on non-negative sparse coding and relies on a wind noise dictionary which is estimated from an isolated noise recording. We estimate the parameters of the model ...... and discuss their sensitivity. We then compare the algorithm with the classical spectral subtraction method and the Qualcomm-ICSI-OGI noise reduction method. We optimize the sound quality in terms of signal-to-noise ratio and provide results on a noisy speech recognition task....

  16. Canadian Estimate of Bird Mortality Due to Collisions and Direct Habitat Loss Associated with Wind Turbine Developments

    Directory of Open Access Journals (Sweden)

    J. Ryan. Zimmerling

    2013-12-01

    Full Text Available We estimated impacts on birds from the development and operation of wind turbines in Canada considering both mortality due to collisions and loss of nesting habitat. We estimated collision mortality using data from carcass searches for 43 wind farms, incorporating correction factors for scavenger removal, searcher efficiency, and carcasses that fell beyond the area searched. On average, 8.2 ± 1.4 birds (95% C.I. were killed per turbine per year at these sites, although the numbers at individual wind farms varied from 0 - 26.9 birds per turbine per year. Based on 2955 installed turbines (the number installed in Canada by December 2011, an estimated 23,300 birds (95% C.I. 20,000 - 28,300 would be killed from collisions with turbines each year. We estimated direct habitat loss based on data from 32 wind farms in Canada. On average, total habitat loss per turbine was 1.23 ha, which corresponds to an estimated total habitat loss due to wind farms nationwide of 3635 ha. Based on published estimates of nest density, this could represent habitat for ~5700 nests of all species. Assuming nearby habitats are saturated, and 2 adults displaced per nest site, effects of direct habitat loss are less than that of direct mortality. Installed wind capacity is growing rapidly, and is predicted to increase more than 10-fold over the next 10-15 years, which could lead to direct mortality of approximately 233,000 birds / year, and displacement of 57,000 pairs. Despite concerns about the impacts of biased correction factors on the accuracy of mortality estimates, these values are likely much lower than those from collisions with some other anthropogenic sources such as windows, vehicles, or towers, or habitat loss due to many other forms of development. Species composition data suggest that < 0.2% of the population of any species is currently affected by mortality or displacement from wind turbine development. Therefore, population level impacts are unlikely

  17. Estimation of parameter sensitivities for stochastic reaction networks

    KAUST Repository

    Gupta, Ankit

    2016-01-07

    Quantification of the effects of parameter uncertainty is an important and challenging problem in Systems Biology. We consider this problem in the context of stochastic models of biochemical reaction networks where the dynamics is described as a continuous-time Markov chain whose states represent the molecular counts of various species. For such models, effects of parameter uncertainty are often quantified by estimating the infinitesimal sensitivities of some observables with respect to model parameters. The aim of this talk is to present a holistic approach towards this problem of estimating parameter sensitivities for stochastic reaction networks. Our approach is based on a generic formula which allows us to construct efficient estimators for parameter sensitivity using simulations of the underlying model. We will discuss how novel simulation techniques, such as tau-leaping approximations, multi-level methods etc. can be easily integrated with our approach and how one can deal with stiff reaction networks where reactions span multiple time-scales. We will demonstrate the efficiency and applicability of our approach using many examples from the biological literature.

  18. On the estimation of wind comfort in a building environment by micro-scale simulation

    Directory of Open Access Journals (Sweden)

    Günter Gross

    2014-06-01

    Full Text Available A three-dimensional micro-scale model is used to study some aspects of wind comfort in a built-up area. The equations for calculating the mean wind have been extended by a Markov approach for short-term wind fluctuations. The model components have been successfully verified against wind tunnel measurements and observations of a field experiment. The simulated time series are used to estimate wind comfort measures. It turns out that the frequency of exceedance of prescribed thresholds depends strongly on the specification of the gust duration time. It was also possible to calculate the spatial distribution of a gust factor g$g$ depending on local wind characteristics. The simulated range is much broader than a value of g=3–3.5$g=3\\text{--}3.5$ commonly used for wind comfort assessments. Again, the order of magnitude and the bandwidth of g$g$ depends strongly on the definition of a gust.

  19. Spectral Analysis of Geomagnetic Activity Indices and Solar Wind Parameters

    Directory of Open Access Journals (Sweden)

    Jung-Hee Kim

    2014-06-01

    Full Text Available Solar variability is widely known to affect the interplanetary space and in turn the Earth’s electromagnetical environment on the basis of common periodicities in the solar and geomagnetic activity indices. The goal of this study is twofold. Firstly, we attempt to associate modes by comparing a temporal behavior of the power of geomagnetic activity parameters since it is barely sufficient searching for common peaks with a similar periodicity in order to causally correlate geomagnetic activity parameters. As a result of the wavelet transform analysis we are able to obtain information on the temporal behavior of the power in the velocity of the solar wind, the number density of protons in the solar wind, the AE index, the Dst index, the interplanetary magnetic field, B and its three components of the GSM coordinate system, BX, BY, BZ. Secondly, we also attempt to search for any signatures of influence on the space environment near the Earth by inner planets orbiting around the Sun. Our main findings are as follows: (1 Parameters we have investigated show periodicities of ~ 27 days, ~ 13.5 days, ~ 9 days. (2 The peaks in the power spectrum of BZ appear to be split due to an unknown agent. (3 For some modes powers are not present all the time and intervals showing high powers do not always coincide. (4 Noticeable peaks do not emerge at those frequencies corresponding to the synodic and/or sidereal periods of Mercury and Venus, which leads us to conclude that the Earth’s space environment is not subject to the shadow of the inner planets as suggested earlier.

  20. Load Estimation from Modal Parameters

    DEFF Research Database (Denmark)

    Aenlle, Manuel López; Brincker, Rune; Fernández, Pelayo Fernández

    2007-01-01

    In Natural Input Modal Analysis the modal parameters are estimated just from the responses while the loading is not recorded. However, engineers are sometimes interested in knowing some features of the loading acting on a structure. In this paper, a procedure to determine the loading from a FRF m...

  1. Evaluation of the impact of adjusting the angle of the axis of a wind turbine rotor relative to the flow of air stream on operating parameters of a wind turbine model

    Directory of Open Access Journals (Sweden)

    Gumuła Stanisław

    2017-01-01

    Full Text Available The aim of this study was to determine the effect of regulation of an axis of a wind turbine rotor to the direction of wind on the volume of energy produced by wind turbines. A role of an optimal setting of the blades of the wind turbine rotor was specified, as well. According to the measurements, changes in the tilt angle of the axis of the wind turbine rotor in relation to the air stream flow direction cause changes in the use of wind energy. The publication explores the effects of the operating conditions of wind turbines on the possibility of using wind energy. A range of factors affect the operation of the wind turbine, and thus the volume of energy produced by the plant. The impact of design parameters of wind power plant, climatic factors or associated with the location seismic challenges can be shown from among them. One of the parameters has proved to be change settings of the rotor axis in relation to direction of flow of the air stream. Studies have shown that the accurate determination of the optimum angle of the axis of the rotor with respect to flow of air stream strongly influences the characteristics of the wind turbine.

  2. A variational approach to parameter estimation in ordinary differential equations

    Directory of Open Access Journals (Sweden)

    Kaschek Daniel

    2012-08-01

    Full Text Available Abstract Background Ordinary differential equations are widely-used in the field of systems biology and chemical engineering to model chemical reaction networks. Numerous techniques have been developed to estimate parameters like rate constants, initial conditions or steady state concentrations from time-resolved data. In contrast to this countable set of parameters, the estimation of entire courses of network components corresponds to an innumerable set of parameters. Results The approach presented in this work is able to deal with course estimation for extrinsic system inputs or intrinsic reactants, both not being constrained by the reaction network itself. Our method is based on variational calculus which is carried out analytically to derive an augmented system of differential equations including the unconstrained components as ordinary state variables. Finally, conventional parameter estimation is applied to the augmented system resulting in a combined estimation of courses and parameters. Conclusions The combined estimation approach takes the uncertainty in input courses correctly into account. This leads to precise parameter estimates and correct confidence intervals. In particular this implies that small motifs of large reaction networks can be analysed independently of the rest. By the use of variational methods, elements from control theory and statistics are combined allowing for future transfer of methods between the two fields.

  3. A variational approach to parameter estimation in ordinary differential equations.

    Science.gov (United States)

    Kaschek, Daniel; Timmer, Jens

    2012-08-14

    Ordinary differential equations are widely-used in the field of systems biology and chemical engineering to model chemical reaction networks. Numerous techniques have been developed to estimate parameters like rate constants, initial conditions or steady state concentrations from time-resolved data. In contrast to this countable set of parameters, the estimation of entire courses of network components corresponds to an innumerable set of parameters. The approach presented in this work is able to deal with course estimation for extrinsic system inputs or intrinsic reactants, both not being constrained by the reaction network itself. Our method is based on variational calculus which is carried out analytically to derive an augmented system of differential equations including the unconstrained components as ordinary state variables. Finally, conventional parameter estimation is applied to the augmented system resulting in a combined estimation of courses and parameters. The combined estimation approach takes the uncertainty in input courses correctly into account. This leads to precise parameter estimates and correct confidence intervals. In particular this implies that small motifs of large reaction networks can be analysed independently of the rest. By the use of variational methods, elements from control theory and statistics are combined allowing for future transfer of methods between the two fields.

  4. Parameter estimation in stochastic rainfall-runoff models

    DEFF Research Database (Denmark)

    Jonsdottir, Harpa; Madsen, Henrik; Palsson, Olafur Petur

    2006-01-01

    A parameter estimation method for stochastic rainfall-runoff models is presented. The model considered in the paper is a conceptual stochastic model, formulated in continuous-discrete state space form. The model is small and a fully automatic optimization is, therefore, possible for estimating all...... the parameter values are optimal for simulation or prediction. The data originates from Iceland and the model is designed for Icelandic conditions, including a snow routine for mountainous areas. The model demands only two input data series, precipitation and temperature and one output data series...

  5. Blade Bearing Friction Estimation of Operating Wind Turbines

    DEFF Research Database (Denmark)

    Perisic, Nevena; Pedersen, Bo Juul; Kirkegaard, Poul Henning

    2012-01-01

    Blade root bearing on a wind turbine (WTG) enables pitching of blades for power control and rotor braking and is a WTG critical component. As the size of modern WTGs is constantly increasing, this leads to relatively less rigid bearings, more sensitive to deformations, thus WTG operational...... reliability can be increased by continuous monitoring of blade bearing. High blade bearing friction is undesirable, as it may be associated with excessive heating of the surfaces, damage and/or inefficient operation. Thus, continuous observation of bearing friction level is crucial for blade bearing health...... monitoring systems. A novel algorithm for online monitoring of bearing friction level is developed combining physical knowledge about pitch system dynamics with state estimator, i.e. observer theory and signal processing assuming realistic sensor availability. Results show estimation of bearing friction...

  6. NORSEWInD satellite wind climatology

    DEFF Research Database (Denmark)

    Hasager, Charlotte Bay; Badger, Merete; Mouche, Alexis

    The EU-NORSEWInD project www.norsewind.eu has taken place from August 2008 to July 2012 (4 years). NORSEWInD is short for Northern Seas Wind Index database. In the project ocean surface wind observations from space have been retrieved, processed and analysed. The overall aim of the work...... is to provide new offshore wind climatology map for the entire area of interest based on satellite remote sensing. This has been based on Synthetic Aperture Radar (SAR) from Envisat ASAR using 9000 scenes re-processed with ECMWF wind direction and CMOD-IFR. The number of overlapping samples range from 450...... in the Irish Sea to more than 1200 in most of the Baltic Sea. Wind resource statistics include maps at 2 km spatial resolution of mean wind speed, Weibull A and k, and energy density at 10 m above sea level. Uncertainty estimates on the number of available samples for each of the four parameters are presented...

  7. Effect of solar wind plasma parameters on space weather

    International Nuclear Information System (INIS)

    Rathore, Balveer S.; Gupta, Dinesh C.; Kaushik, Subhash C.

    2015-01-01

    Today's challenge for space weather research is to quantitatively predict the dynamics of the magnetosphere from measured solar wind and interplanetary magnetic field (IMF) conditions. Correlative studies between geomagnetic storms (GMSs) and the various interplanetary (IP) field/plasma parameters have been performed to search for the causes of geomagnetic activity and develop models for predicting the occurrence of GMSs, which are important for space weather predictions. We find a possible relation between GMSs and solar wind and IMF parameters in three different situations and also derived the linear relation for all parameters in three situations. On the basis of the present statistical study, we develop an empirical model. With the help of this model, we can predict all categories of GMSs. This model is based on the following fact: the total IMF B total can be used to trigger an alarm for GMSs, when sudden changes in total magnetic field B total occur. This is the first alarm condition for a storm's arrival. It is observed in the present study that the southward B z component of the IMF is an important factor for describing GMSs. A result of the paper is that the magnitude of B z is maximum neither during the initial phase (at the instant of the IP shock) nor during the main phase (at the instant of Disturbance storm time (Dst) minimum). It is seen in this study that there is a time delay between the maximum value of southward B z and the Dst minimum, and this time delay can be used in the prediction of the intensity of a magnetic storm two-three hours before the main phase of a GMS. A linear relation has been derived between the maximum value of the southward component of B z and the Dst, which is Dst = (−0.06) + (7.65) B z +t. Some auxiliary conditions should be fulfilled with this, for example the speed of the solar wind should, on average, be 350 km s −1 to 750 km s −1 , plasma β should be low and, most importantly, plasma temperature

  8. Wind speed reductions by large-scale wind turbine deployments lower turbine efficiencies and set low wind power potentials

    Science.gov (United States)

    Miller, Lee; Kleidon, Axel

    2017-04-01

    Wind turbines generate electricity by removing kinetic energy from the atmosphere. Large numbers of wind turbines are likely to reduce wind speeds, which lowers estimates of electricity generation from what would be presumed from unaffected conditions. Here, we test how well wind power potentials that account for this effect can be estimated without explicitly simulating atmospheric dynamics. We first use simulations with an atmospheric general circulation model (GCM) that explicitly simulates the effects of wind turbines to derive wind power limits (GCM estimate), and compare them to a simple approach derived from the climatological conditions without turbines [vertical kinetic energy (VKE) estimate]. On land, we find strong agreement between the VKE and GCM estimates with respect to electricity generation rates (0.32 and 0.37 We m-2) and wind speed reductions by 42 and 44%. Over ocean, the GCM estimate is about twice the VKE estimate (0.59 and 0.29 We m-2) and yet with comparable wind speed reductions (50 and 42%). We then show that this bias can be corrected by modifying the downward momentum flux to the surface. Thus, large-scale limits to wind power can be derived from climatological conditions without explicitly simulating atmospheric dynamics. Consistent with the GCM simulations, the approach estimates that only comparatively few land areas are suitable to generate more than 1 We m-2 of electricity and that larger deployment scales are likely to reduce the expected electricity generation rate of each turbine. We conclude that these atmospheric effects are relevant for planning the future expansion of wind power.

  9. Approximate effect of parameter pseudonoise intensity on rate of convergence for EKF parameter estimators. [Extended Kalman Filter

    Science.gov (United States)

    Hill, Bryon K.; Walker, Bruce K.

    1991-01-01

    When using parameter estimation methods based on extended Kalman filter (EKF) theory, it is common practice to assume that the unknown parameter values behave like a random process, such as a random walk, in order to guarantee their identifiability by the filter. The present work is the result of an ongoing effort to quantitatively describe the effect that the assumption of a fictitious noise (called pseudonoise) driving the unknown parameter values has on the parameter estimate convergence rate in filter-based parameter estimators. The initial approach is to examine a first-order system described by one state variable with one parameter to be estimated. The intent is to derive analytical results for this simple system that might offer insight into the effect of the pseudonoise assumption for more complex systems. Such results would make it possible to predict the estimator error convergence behavior as a function of the assumed pseudonoise intensity, and this leads to the natural application of the results to the design of filter-based parameter estimators. The results obtained show that the analytical description of the convergence behavior is very difficult.

  10. Neglect Of Parameter Estimation Uncertainty Can Significantly Overestimate Structural Reliability

    Directory of Open Access Journals (Sweden)

    Rózsás Árpád

    2015-12-01

    Full Text Available Parameter estimation uncertainty is often neglected in reliability studies, i.e. point estimates of distribution parameters are used for representative fractiles, and in probabilistic models. A numerical example examines the effect of this uncertainty on structural reliability using Bayesian statistics. The study reveals that the neglect of parameter estimation uncertainty might lead to an order of magnitude underestimation of failure probability.

  11. Modelling Wind for Wind Farm Layout Optimization Using Joint Distribution of Wind Speed and Wind Direction

    OpenAIRE

    Ju Feng; Wen Zhong Shen

    2015-01-01

    Reliable wind modelling is of crucial importance for wind farm development. The common practice of using sector-wise Weibull distributions has been found inappropriate for wind farm layout optimization. In this study, we propose a simple and easily implementable method to construct joint distributions of wind speed and wind direction, which is based on the parameters of sector-wise Weibull distributions and interpolations between direction sectors. It is applied to the wind measurement data a...

  12. Operation and Equivalent Loads of Wind Turbines in Large Wind Farms

    Science.gov (United States)

    Andersen, Soren Juhl; Sorensen, Jens Norkaer; Mikkelsen, Robert Flemming

    2017-11-01

    Wind farms continue to grow in size and as the technology matures, the design of wind farms move towards including dynamic effects besides merely annual power production estimates. The unsteady operation of wind turbines in large wind farms has been modelled with EllipSys3D(Michelsen, 1992, and Sørensen, 1995) for a number of different scenarios using a fully coupled large eddy simulations(LES) and aero-elastic framework. The turbines are represented in the flow fields using the actuator line method(Sørensen and Shen, 2002), where the aerodynamic forces and deflections are derived from an aero-elastic code, Flex5(Øye, 1996). The simulations constitute a database of full turbine operation in terms of both production and loads for various wind speeds, turbulence intensities, and turbine spacings. The operating conditions are examined in terms of averaged power production and thrust force, as well as 10min equivalent flapwise bending, yaw, and tilt moment loads. The analyses focus on how the performance and loads change throughout a given farm as well as comparing how various input parameters affect the operation and loads of the wind turbines during different scenarios. COMWIND(Grant 2104-09- 067216/DSF), Nordic Consortium on Optimization and Control of Wind Farms, Eurotech Greentech Wind project, Winds2Loads, and CCA LES. Ressources Granted on SNIC and JESS. The Vestas NM80 turbine has been used.

  13. Parameter estimation of variable-parameter nonlinear Muskingum model using excel solver

    Science.gov (United States)

    Kang, Ling; Zhou, Liwei

    2018-02-01

    Abstract . The Muskingum model is an effective flood routing technology in hydrology and water resources Engineering. With the development of optimization technology, more and more variable-parameter Muskingum models were presented to improve effectiveness of the Muskingum model in recent decades. A variable-parameter nonlinear Muskingum model (NVPNLMM) was proposed in this paper. According to the results of two real and frequently-used case studies by various models, the NVPNLMM could obtain better values of evaluation criteria, which are used to describe the superiority of the estimated outflows and compare the accuracies of flood routing using various models, and the optimal estimated outflows by the NVPNLMM were closer to the observed outflows than the ones by other models.

  14. Inflation and cosmological parameter estimation

    Energy Technology Data Exchange (ETDEWEB)

    Hamann, J.

    2007-05-15

    In this work, we focus on two aspects of cosmological data analysis: inference of parameter values and the search for new effects in the inflationary sector. Constraints on cosmological parameters are commonly derived under the assumption of a minimal model. We point out that this procedure systematically underestimates errors and possibly biases estimates, due to overly restrictive assumptions. In a more conservative approach, we analyse cosmological data using a more general eleven-parameter model. We find that regions of the parameter space that were previously thought ruled out are still compatible with the data; the bounds on individual parameters are relaxed by up to a factor of two, compared to the results for the minimal six-parameter model. Moreover, we analyse a class of inflation models, in which the slow roll conditions are briefly violated, due to a step in the potential. We show that the presence of a step generically leads to an oscillating spectrum and perform a fit to CMB and galaxy clustering data. We do not find conclusive evidence for a step in the potential and derive strong bounds on quantities that parameterise the step. (orig.)

  15. Wind climate estimation using WRF model output: method and model sensitivities over the sea

    DEFF Research Database (Denmark)

    Hahmann, Andrea N.; Vincent, Claire Louise; Peña, Alfredo

    2015-01-01

    setup parameters. The results of the year-long sensitivity simulations show that the long-term mean wind speed simulated by the WRF model offshore in the region studied is quite insensitive to the global reanalysis, the number of vertical levels, and the horizontal resolution of the sea surface...... temperature used as lower boundary conditions. Also, the strength and form (grid vs spectral) of the nudging is quite irrelevant for the mean wind speed at 100 m. Large sensitivity is found to the choice of boundary layer parametrization, and to the length of the period that is discarded as spin-up to produce...... a wind climatology. It is found that the spin-up period for the boundary layer winds is likely larger than 12 h over land and could affect the wind climatology for points offshore for quite a distance downstream from the coast....

  16. Exploratory Study for Continuous-time Parameter Estimation of Ankle Dynamics

    Science.gov (United States)

    Kukreja, Sunil L.; Boyle, Richard D.

    2014-01-01

    Recently, a parallel pathway model to describe ankle dynamics was proposed. This model provides a relationship between ankle angle and net ankle torque as the sum of a linear and nonlinear contribution. A technique to identify parameters of this model in discrete-time has been developed. However, these parameters are a nonlinear combination of the continuous-time physiology, making insight into the underlying physiology impossible. The stable and accurate estimation of continuous-time parameters is critical for accurate disease modeling, clinical diagnosis, robotic control strategies, development of optimal exercise protocols for longterm space exploration, sports medicine, etc. This paper explores the development of a system identification technique to estimate the continuous-time parameters of ankle dynamics. The effectiveness of this approach is assessed via simulation of a continuous-time model of ankle dynamics with typical parameters found in clinical studies. The results show that although this technique improves estimates, it does not provide robust estimates of continuous-time parameters of ankle dynamics. Due to this we conclude that alternative modeling strategies and more advanced estimation techniques be considered for future work.

  17. A parameter tree approach to estimating system sensitivities to parameter sets

    International Nuclear Information System (INIS)

    Jarzemba, M.S.; Sagar, B.

    2000-01-01

    A post-processing technique for determining relative system sensitivity to groups of parameters and system components is presented. It is assumed that an appropriate parametric model is used to simulate system behavior using Monte Carlo techniques and that a set of realizations of system output(s) is available. The objective of our technique is to analyze the input vectors and the corresponding output vectors (that is, post-process the results) to estimate the relative sensitivity of the output to input parameters (taken singly and as a group) and thereby rank them. This technique is different from the design of experimental techniques in that a partitioning of the parameter space is not required before the simulation. A tree structure (which looks similar to an event tree) is developed to better explain the technique. Each limb of the tree represents a particular combination of parameters or a combination of system components. For convenience and to distinguish it from the event tree, we call it the parameter tree. To construct the parameter tree, the samples of input parameter values are treated as either a '+' or a '-' based on whether or not the sampled parameter value is greater than or less than a specified branching criterion (e.g., mean, median, percentile of the population). The corresponding system outputs are also segregated into similar bins. Partitioning the first parameter into a '+' or a '-' bin creates the first level of the tree containing two branches. At the next level, realizations associated with each first-level branch are further partitioned into two bins using the branching criteria on the second parameter and so on until the tree is fully populated. Relative sensitivities are then inferred from the number of samples associated with each branch of the tree. The parameter tree approach is illustrated by applying it to a number of preliminary simulations of the proposed high-level radioactive waste repository at Yucca Mountain, NV. Using a

  18. Medical Meteorology: the Relationship between Meteorological Parameters (Humidity, Rainfall, Wind, and Temperature and Brucellosis in Zanjan Province

    Directory of Open Access Journals (Sweden)

    Yousefali Abedini

    2016-06-01

    Full Text Available Background: Brucellosis (Malta fever is a major contagious zoonotic disease, with economic and public health importance. Methods To assess the effect of meteorological (temperature, rainfall, humidity, and wind and climate parameters on incidence of brucellosis, brucellosis distribution and meteorological zoning maps of Zanjan Province were prepared using Inverse Distance Weighting (IDW and Kriging technique in Arc GIS medium. Zoning maps of mean temperature, rainfall, humidity, and wind were compared to brucellosis distribution maps. Results: Correlation test showed no relationship between the mean number of patients with brucellosis and any of the four meteorological parameters. Conclusion: It seems that in Zanjan province there is no correlation between brucellosis and meteorological parameters.

  19. Statistics-Based Compression of Global Wind Fields

    KAUST Repository

    Jeong, Jaehong

    2017-02-07

    Wind has the potential to make a significant contribution to future energy resources. Locating the sources of this renewable energy on a global scale is however extremely challenging, given the difficulty to store very large data sets generated by modern computer models. We propose a statistical model that aims at reproducing the data-generating mechanism of an ensemble of runs via a Stochastic Generator (SG) of global annual wind data. We introduce an evolutionary spectrum approach with spatially varying parameters based on large-scale geographical descriptors such as altitude to better account for different regimes across the Earth\\'s orography. We consider a multi-step conditional likelihood approach to estimate the parameters that explicitly accounts for nonstationary features while also balancing memory storage and distributed computation. We apply the proposed model to more than 18 million points of yearly global wind speed. The proposed SG requires orders of magnitude less storage for generating surrogate ensemble members from wind than does creating additional wind fields from the climate model, even if an effective lossy data compression algorithm is applied to the simulation output.

  20. Statistics-Based Compression of Global Wind Fields

    KAUST Repository

    Jeong, Jaehong; Castruccio, Stefano; Crippa, Paola; Genton, Marc G.

    2017-01-01

    Wind has the potential to make a significant contribution to future energy resources. Locating the sources of this renewable energy on a global scale is however extremely challenging, given the difficulty to store very large data sets generated by modern computer models. We propose a statistical model that aims at reproducing the data-generating mechanism of an ensemble of runs via a Stochastic Generator (SG) of global annual wind data. We introduce an evolutionary spectrum approach with spatially varying parameters based on large-scale geographical descriptors such as altitude to better account for different regimes across the Earth's orography. We consider a multi-step conditional likelihood approach to estimate the parameters that explicitly accounts for nonstationary features while also balancing memory storage and distributed computation. We apply the proposed model to more than 18 million points of yearly global wind speed. The proposed SG requires orders of magnitude less storage for generating surrogate ensemble members from wind than does creating additional wind fields from the climate model, even if an effective lossy data compression algorithm is applied to the simulation output.

  1. Online State Space Model Parameter Estimation in Synchronous Machines

    Directory of Open Access Journals (Sweden)

    Z. Gallehdari

    2014-06-01

    The suggested approach is evaluated for a sample synchronous machine model. Estimated parameters are tested for different inputs at different operating conditions. The effect of noise is also considered in this study. Simulation results show that the proposed approach provides good accuracy for parameter estimation.

  2. Unifying parameter estimation and the Deutsch-Jozsa algorithm for continuous variables

    International Nuclear Information System (INIS)

    Zwierz, Marcin; Perez-Delgado, Carlos A.; Kok, Pieter

    2010-01-01

    We reveal a close relationship between quantum metrology and the Deutsch-Jozsa algorithm on continuous-variable quantum systems. We develop a general procedure, characterized by two parameters, that unifies parameter estimation and the Deutsch-Jozsa algorithm. Depending on which parameter we keep constant, the procedure implements either the parameter-estimation protocol or the Deutsch-Jozsa algorithm. The parameter-estimation part of the procedure attains the Heisenberg limit and is therefore optimal. Due to the use of approximate normalizable continuous-variable eigenstates, the Deutsch-Jozsa algorithm is probabilistic. The procedure estimates a value of an unknown parameter and solves the Deutsch-Jozsa problem without the use of any entanglement.

  3. Impacts of Different Types of Measurements on Estimating Unsaturatedflow Parameters

    Science.gov (United States)

    Shi, L.

    2015-12-01

    This study evaluates the value of different types of measurements for estimating soil hydraulic parameters. A numerical method based on ensemble Kalman filter (EnKF) is presented to solely or jointly assimilate point-scale soil water head data, point-scale soil water content data, surface soil water content data and groundwater level data. This study investigates the performance of EnKF under different types of data, the potential worth contained in these data, and the factors that may affect estimation accuracy. Results show that for all types of data, smaller measurements errors lead to faster convergence to the true values. Higher accuracy measurements are required to improve the parameter estimation if a large number of unknown parameters need to be identified simultaneously. The data worth implied by the surface soil water content data and groundwater level data is prone to corruption by a deviated initial guess. Surface soil moisture data are capable of identifying soil hydraulic parameters for the top layers, but exert less or no influence on deeper layers especially when estimating multiple parameters simultaneously. Groundwater level is one type of valuable information to infer the soil hydraulic parameters. However, based on the approach used in this study, the estimates from groundwater level data may suffer severe degradation if a large number of parameters must be identified. Combined use of two or more types of data is helpful to improve the parameter estimation.

  4. Accelerated maximum likelihood parameter estimation for stochastic biochemical systems

    Directory of Open Access Journals (Sweden)

    Daigle Bernie J

    2012-05-01

    Full Text Available Abstract Background A prerequisite for the mechanistic simulation of a biochemical system is detailed knowledge of its kinetic parameters. Despite recent experimental advances, the estimation of unknown parameter values from observed data is still a bottleneck for obtaining accurate simulation results. Many methods exist for parameter estimation in deterministic biochemical systems; methods for discrete stochastic systems are less well developed. Given the probabilistic nature of stochastic biochemical models, a natural approach is to choose parameter values that maximize the probability of the observed data with respect to the unknown parameters, a.k.a. the maximum likelihood parameter estimates (MLEs. MLE computation for all but the simplest models requires the simulation of many system trajectories that are consistent with experimental data. For models with unknown parameters, this presents a computational challenge, as the generation of consistent trajectories can be an extremely rare occurrence. Results We have developed Monte Carlo Expectation-Maximization with Modified Cross-Entropy Method (MCEM2: an accelerated method for calculating MLEs that combines advances in rare event simulation with a computationally efficient version of the Monte Carlo expectation-maximization (MCEM algorithm. Our method requires no prior knowledge regarding parameter values, and it automatically provides a multivariate parameter uncertainty estimate. We applied the method to five stochastic systems of increasing complexity, progressing from an analytically tractable pure-birth model to a computationally demanding model of yeast-polarization. Our results demonstrate that MCEM2 substantially accelerates MLE computation on all tested models when compared to a stand-alone version of MCEM. Additionally, we show how our method identifies parameter values for certain classes of models more accurately than two recently proposed computationally efficient methods

  5. Fine tuning support vector machines for short-term wind speed forecasting

    International Nuclear Information System (INIS)

    Zhou Junyi; Shi Jing; Li Gong

    2011-01-01

    Research highlights: → A systematic approach to tuning SVM models for wind speed prediction is proposed. → Multiple kernel functions and a wide range of tuning parameters are evaluated, and optimal parameters for each kernel function are obtained. → It is found that the forecasting performance of SVM is closely related to the dynamic characteristics of wind speed. → Under the optimal combination of parameters, different kernels give comparable forecasting accuracy. -- Abstract: Accurate forecasting of wind speed is critical to the effective harvesting of wind energy and the integration of wind power into the existing electric power grid. Least-squares support vector machines (LS-SVM), a powerful technique that is widely applied in a variety of classification and function estimation problems, carries great potential for the application of short-term wind speed forecasting. In this case, tuning the model parameters for optimal forecasting accuracy is a fundamental issue. This paper, for the first time, presents a systematic study on fine tuning of LS-SVM model parameters for one-step ahead wind speed forecasting. Three SVM kernels, namely linear, Gaussian, and polynomial kernels, are implemented. The SVM parameters considered include the training sample size, SVM order, regularization parameter, and kernel parameters. The results show that (1) the performance of LS-SVM is closely related to the dynamic characteristics of wind speed; (2) all parameters investigated greatly affect the performance of LS-SVM models; (3) under the optimal combination of parameters after fine tuning, the three kernels give comparable forecasting accuracy; (4) the performance of linear kernel is worse than the other two kernels when the training sample size or SVM order is small. In addition, LS-SVMs are compared against the persistence approach, and it is found that they can outperform the persistence model in the majority of cases.

  6. Postprocessing MPEG based on estimated quantization parameters

    DEFF Research Database (Denmark)

    Forchhammer, Søren

    2009-01-01

    the case where the coded stream is not accessible, or from an architectural point of view not desirable to use, and instead estimate some of the MPEG stream parameters based on the decoded sequence. The I-frames are detected and the quantization parameters are estimated from the coded stream and used...... in the postprocessing. We focus on deringing and present a scheme which aims at suppressing ringing artifacts, while maintaining the sharpness of the texture. The goal is to improve the visual quality, so perceptual blur and ringing metrics are used in addition to PSNR evaluation. The performance of the new `pure......' postprocessing compares favorable to a reference postprocessing filter which has access to the quantization parameters not only for I-frames but also on P and B-frames....

  7. A comprehensive measure of the energy resource: Wind power potential (WPP)

    International Nuclear Information System (INIS)

    Zhang, Jie; Chowdhury, Souma; Messac, Achille

    2014-01-01

    Highlights: • A more comprehensive metric is developed to accurately assess the quality of wind resources at a site. • WPP exploits the joint distribution of wind speed and direction, and yields more credible estimates. • WPP investigates the effect of wind distribution on the optimal net power generation of a farm. • The results show that WPD and WPP follow different trends. - Abstract: Currently, the quality of available wind energy at a site is assessed using wind power density (WPD). This paper proposes to use a more comprehensive metric: the wind power potential (WPP). While the former accounts for only wind speed information, the latter exploits the joint distribution of wind speed and wind direction and yields more credible estimates. The WPP investigates the effect of wind velocity distribution on the optimal net power generation of a farm. A joint distribution of wind speed and direction is used to characterize the stochastic variation of wind conditions. Two joint distribution methods are adopted in this paper: bivariate normal distribution and anisotropic lognormal method. The net power generation for a particular farmland size and installed capacity is maximized for different distributions of wind speed and wind direction, using the Unrestricted Wind Farm Layout Optimization (UWFLO) framework. A response surface is constructed to represent the computed maximum wind farm capacity factor as a function of the parameters of the wind distribution. Two different response surface methods are adopted in this paper: (i) the adaptive hybrid functions (AHF), and (ii) the quadratic response surface method (QRSM). Toward this end, for any farm site, we can (i) estimate the parameters of the joint distribution using recorded wind data (for bivariate normal or anisotropic lognormal distributions) and (ii) predict the maximum capacity factor for a specified farm size and capacity using this response surface. The WPP metric is illustrated using recorded wind

  8. Identifyability measures to select the parameters to be estimated in a solid-state fermentation distributed parameter model.

    Science.gov (United States)

    da Silveira, Christian L; Mazutti, Marcio A; Salau, Nina P G

    2016-07-08

    Process modeling can lead to of advantages such as helping in process control, reducing process costs and product quality improvement. This work proposes a solid-state fermentation distributed parameter model composed by seven differential equations with seventeen parameters to represent the process. Also, parameters estimation with a parameters identifyability analysis (PIA) is performed to build an accurate model with optimum parameters. Statistical tests were made to verify the model accuracy with the estimated parameters considering different assumptions. The results have shown that the model assuming substrate inhibition better represents the process. It was also shown that eight from the seventeen original model parameters were nonidentifiable and better results were obtained with the removal of these parameters from the estimation procedure. Therefore, PIA can be useful to estimation procedure, since it may reduce the number of parameters that can be evaluated. Further, PIA improved the model results, showing to be an important procedure to be taken. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:905-917, 2016. © 2016 American Institute of Chemical Engineers.

  9. Estimating wind-turbine-caused bird and bat fatality when zero carcasses are observed

    Science.gov (United States)

    Huso, Manuela M.P.; Dalthorp, Daniel; Dail, David; Madsen, Lisa

    2015-01-01

    Many wind-power facilities in the United States have established effective monitoring programs to determine turbine-caused fatality rates of birds and bats, but estimating the number of fatalities of rare species poses special difficulties. The loss of even small numbers of individuals may adversely affect fragile populations, but typically, few (if any) carcasses are observed during monitoring. If monitoring design results in only a small proportion of carcasses detected, then finding zero carcasses may give little assurance that the number of actual fatalities is small. Fatality monitoring at wind-power facilities commonly involves conducting experiments to estimate the probability (g) an individual will be observed, accounting for the possibilities that it falls in an unsearched area, is scavenged prior to detection, or remains undetected even when present. When g  ~0.45. Further, we develop extensions for temporal replication that can inform prior distributions of M and methods for combining information across several areas or time periods. We apply the method to data collected at a wind-power facility where scheduled searches yielded X = 0 raptor carcasses

  10. Estimating wind-turbine-caused bird and bat fatality when zero carcasses are observed.

    Science.gov (United States)

    Huso, Manuela M P; Dalthorp, Dan; Dail, David; Madsen, Lisa

    2015-07-01

    Many wind-power facilities in the United States have established effective monitoring programs to determine turbine-caused fatality rates of birds and bats, but estimating the number of fatalities of rare species poses special difficulties. The loss of even small numbers of individuals may adversely affect fragile populations, but typically, few (if any) carcasses are observed during monitoring. If monitoring design results in only a small proportion of carcasses detected, then finding zero carcasses may give little assurance that the number of actual fatalities is small. Fatality monitoring at wind-power facilities commonly involves conducting experiments to estimate the probability (g) an individual will be observed, accounting for the possibilities that it falls in an unsearched area, is scavenged prior to detection, or remains undetected even when present. When g -0.45. Further, we develop extensions for temporal replication that can inform prior distributions of M and methods for combining information across several areas or time periods. We apply the method to data collected at a wind-power facility where scheduled searches yielded X = 0 raptor carcasses.

  11. Composite likelihood estimation of demographic parameters

    Directory of Open Access Journals (Sweden)

    Garrigan Daniel

    2009-11-01

    Full Text Available Abstract Background Most existing likelihood-based methods for fitting historical demographic models to DNA sequence polymorphism data to do not scale feasibly up to the level of whole-genome data sets. Computational economies can be achieved by incorporating two forms of pseudo-likelihood: composite and approximate likelihood methods. Composite likelihood enables scaling up to large data sets because it takes the product of marginal likelihoods as an estimator of the likelihood of the complete data set. This approach is especially useful when a large number of genomic regions constitutes the data set. Additionally, approximate likelihood methods can reduce the dimensionality of the data by summarizing the information in the original data by either a sufficient statistic, or a set of statistics. Both composite and approximate likelihood methods hold promise for analyzing large data sets or for use in situations where the underlying demographic model is complex and has many parameters. This paper considers a simple demographic model of allopatric divergence between two populations, in which one of the population is hypothesized to have experienced a founder event, or population bottleneck. A large resequencing data set from human populations is summarized by the joint frequency spectrum, which is a matrix of the genomic frequency spectrum of derived base frequencies in two populations. A Bayesian Metropolis-coupled Markov chain Monte Carlo (MCMCMC method for parameter estimation is developed that uses both composite and likelihood methods and is applied to the three different pairwise combinations of the human population resequence data. The accuracy of the method is also tested on data sets sampled from a simulated population model with known parameters. Results The Bayesian MCMCMC method also estimates the ratio of effective population size for the X chromosome versus that of the autosomes. The method is shown to estimate, with reasonable

  12. Estimation of the mid-century Etesians wind pattern from EURO-CORDEX models

    Science.gov (United States)

    Dafka, Stella; Toreti, Andrea; Luterbacher, Juerg; Zanis, Prodromos; Tyrlis, Evangelos; Xoplaki, Elena

    2017-04-01

    The Etesians are one of the major and most prominent wind system, prevailing over the Aegean Sea during summer and early autumn. Here, projections of changes in 30-year (2021-2050) wind speeds relative to 1971-2000, under the 8.5 and 4.5 Representative Concentration Pathways, have been produced for Etesians. Future changes in the number of Etesian days and the associated large scale dynamics are also considered. We analyze seven simulations from three EURO-CORDEX regional climate models at a 12 km grid resolution. Both scenarios indicate that in most RCMs daily wind speeds are projected to increase by 1-1.5m/s over the Aegean Sea, suggesting that the current estimate of wind power potential for Aegean Sea will be increased with the greenhouse gas forcing in the coming decades (2021-2050). Wind direction at 10-m as well as the number of Etesian days have shown to undergo minor changes. The projected changes in sea level pressure and geopotential height anomalies at 500 hPa have a large spread among the seven simulations with a disperse tendency of strengthening of the ridge over the Balkans.

  13. Parameter estimation for an expanding universe

    Directory of Open Access Journals (Sweden)

    Jieci Wang

    2015-03-01

    Full Text Available We study the parameter estimation for excitations of Dirac fields in the expanding Robertson–Walker universe. We employ quantum metrology techniques to demonstrate the possibility for high precision estimation for the volume rate of the expanding universe. We show that the optimal precision of the estimation depends sensitively on the dimensionless mass m˜ and dimensionless momentum k˜ of the Dirac particles. The optimal precision for the ratio estimation peaks at some finite dimensionless mass m˜ and momentum k˜. We find that the precision of the estimation can be improved by choosing the probe state as an eigenvector of the hamiltonian. This occurs because the largest quantum Fisher information is obtained by performing projective measurements implemented by the projectors onto the eigenvectors of specific probe states.

  14. Method for Estimating the Parameters of LFM Radar Signal

    Directory of Open Access Journals (Sweden)

    Tan Chuan-Zhang

    2017-01-01

    Full Text Available In order to obtain reliable estimate of parameters, it is very important to protect the integrality of linear frequency modulation (LFM signal. Therefore, in the practical LFM radar signal processing, the length of data frame is often greater than the pulse width (PW of signal. In this condition, estimating the parameters by fractional Fourier transform (FrFT will cause the signal to noise ratio (SNR decrease. Aiming at this problem, we multiply the data frame by a Gaussian window to improve the SNR. Besides, for a further improvement of parameters estimation precision, a novel algorithm is derived via Lagrange interpolation polynomial, and we enhance the algorithm by a logarithmic transformation. Simulation results demonstrate that the derived algorithm significantly reduces the estimation errors of chirp-rate and initial frequency.

  15. Estimation of the ability to use a mass of air from a moving vehicle in wind turbine propulsion

    Directory of Open Access Journals (Sweden)

    Adam BAWORSKI

    2015-09-01

    Full Text Available This work presents division and classification of wind turbines according to the location of the axis of rotation and generated power. The work introduces applications of the wind turbines in electric energy generation with their direct development. The paper discusses indicators and exploitation parameters that characterize particular types of wind rotators. Dimension and construction factors, as well as work parameters, have been analyzed in order to choose the optimal rotator in the road infrastructure application. The aim of the analysis was to conduct further investigation to restore a mass of air from passing vehicles.

  16. Photovoltaic-wind hybrid autonomous generation systems in Mongolia

    Energy Technology Data Exchange (ETDEWEB)

    Dei, Tsutomu; Ushiyama, Izumi

    2005-01-01

    Two hybrid stand-alone (autonomous) power systems, each with wind and PV generation, were studied as installed at health clinics in semi-desert and mountainous region in Mongolia. Meteorological and system operation parameters, including power output and the consumption of the system, were generally monitored by sophisticated monitoring. However, where wind and solar site information was lacking, justifiable estimates were made. The results show that there is a seasonal complementary relationship between wind and solar irradiation in Tarot Sum. The users understood the necessity of Demand Side Management of isolated wind-PV generation system through technology transfer seminars and actually executed DSM at both sites. (author)

  17. Assumptions of the primordial spectrum and cosmological parameter estimation

    International Nuclear Information System (INIS)

    Shafieloo, Arman; Souradeep, Tarun

    2011-01-01

    The observables of the perturbed universe, cosmic microwave background (CMB) anisotropy and large structures depend on a set of cosmological parameters, as well as the assumed nature of primordial perturbations. In particular, the shape of the primordial power spectrum (PPS) is, at best, a well-motivated assumption. It is known that the assumed functional form of the PPS in cosmological parameter estimation can affect the best-fit-parameters and their relative confidence limits. In this paper, we demonstrate that a specific assumed form actually drives the best-fit parameters into distinct basins of likelihood in the space of cosmological parameters where the likelihood resists improvement via modifications to the PPS. The regions where considerably better likelihoods are obtained allowing free-form PPS lie outside these basins. In the absence of a preferred model of inflation, this raises a concern that current cosmological parameter estimates are strongly prejudiced by the assumed form of PPS. Our results strongly motivate approaches toward simultaneous estimation of the cosmological parameters and the shape of the primordial spectrum from upcoming cosmological data. It is equally important for theorists to keep an open mind towards early universe scenarios that produce features in the PPS. (paper)

  18. Bayesian estimation of Weibull distribution parameters

    International Nuclear Information System (INIS)

    Bacha, M.; Celeux, G.; Idee, E.; Lannoy, A.; Vasseur, D.

    1994-11-01

    In this paper, we expose SEM (Stochastic Expectation Maximization) and WLB-SIR (Weighted Likelihood Bootstrap - Sampling Importance Re-sampling) methods which are used to estimate Weibull distribution parameters when data are very censored. The second method is based on Bayesian inference and allow to take into account available prior informations on parameters. An application of this method, with real data provided by nuclear power plants operation feedback analysis has been realized. (authors). 8 refs., 2 figs., 2 tabs

  19. A Modified Penalty Parameter Approach for Optimal Estimation of UH with Simultaneous Estimation of Infiltration Parameters

    Science.gov (United States)

    Bhattacharjya, Rajib Kumar

    2018-05-01

    The unit hydrograph and the infiltration parameters of a watershed can be obtained from observed rainfall-runoff data by using inverse optimization technique. This is a two-stage optimization problem. In the first stage, the infiltration parameters are obtained and the unit hydrograph ordinates are estimated in the second stage. In order to combine this two-stage method into a single stage one, a modified penalty parameter approach is proposed for converting the constrained optimization problem to an unconstrained one. The proposed approach is designed in such a way that the model initially obtains the infiltration parameters and then searches the optimal unit hydrograph ordinates. The optimization model is solved using Genetic Algorithms. A reduction factor is used in the penalty parameter approach so that the obtained optimal infiltration parameters are not destroyed during subsequent generation of genetic algorithms, required for searching optimal unit hydrograph ordinates. The performance of the proposed methodology is evaluated by using two example problems. The evaluation shows that the model is superior, simple in concept and also has the potential for field application.

  20. Experimental and analytical determination of stability parameters for a balloon tethered in a wind

    Science.gov (United States)

    Redd, L. T.; Bennett, R. M.; Bland, S. R.

    1973-01-01

    Experimental and analytical techniques for determining stability parameters for a balloon tethered in a steady wind are described. These techniques are applied to a particular 7.64-meter-long balloon, and the results are presented. The stability parameters of interest appear as coefficients in linearized stability equations and are derived from the various forces and moments acting on the balloon. In several cases the results from the experimental and analytical techniques are compared and suggestions are given as to which techniques are the most practical means of determining values for the stability parameters.

  1. Improved Offshore Wind Resource Assessment in Global Climate Stabilization Scenarios

    Energy Technology Data Exchange (ETDEWEB)

    Arent, D.; Sullivan, P.; Heimiller, D.; Lopez, A.; Eurek, K.; Badger, J.; Jorgensen, H. E.; Kelly, M.; Clarke, L.; Luckow, P.

    2012-10-01

    This paper introduces a technique for digesting geospatial wind-speed data into areally defined -- country-level, in this case -- wind resource supply curves. We combined gridded wind-vector data for ocean areas with bathymetry maps, country exclusive economic zones, wind turbine power curves, and other datasets and relevant parameters to build supply curves that estimate a country's offshore wind resource defined by resource quality, depth, and distance-from-shore. We include a single set of supply curves -- for a particular assumption set -- and study some implications of including it in a global energy model. We also discuss the importance of downscaling gridded wind vector data to capturing the full resource potential, especially over land areas with complex terrain. This paper includes motivation and background for a statistical downscaling methodology to account for terrain effects with a low computational burden. Finally, we use this forum to sketch a framework for building synthetic electric networks to estimate transmission accessibility of renewable resource sites in remote areas.

  2. SCoPE: an efficient method of Cosmological Parameter Estimation

    International Nuclear Information System (INIS)

    Das, Santanu; Souradeep, Tarun

    2014-01-01

    Markov Chain Monte Carlo (MCMC) sampler is widely used for cosmological parameter estimation from CMB and other data. However, due to the intrinsic serial nature of the MCMC sampler, convergence is often very slow. Here we present a fast and independently written Monte Carlo method for cosmological parameter estimation named as Slick Cosmological Parameter Estimator (SCoPE), that employs delayed rejection to increase the acceptance rate of a chain, and pre-fetching that helps an individual chain to run on parallel CPUs. An inter-chain covariance update is also incorporated to prevent clustering of the chains allowing faster and better mixing of the chains. We use an adaptive method for covariance calculation to calculate and update the covariance automatically as the chains progress. Our analysis shows that the acceptance probability of each step in SCoPE is more than 95% and the convergence of the chains are faster. Using SCoPE, we carry out some cosmological parameter estimations with different cosmological models using WMAP-9 and Planck results. One of the current research interests in cosmology is quantifying the nature of dark energy. We analyze the cosmological parameters from two illustrative commonly used parameterisations of dark energy models. We also asses primordial helium fraction in the universe can be constrained by the present CMB data from WMAP-9 and Planck. The results from our MCMC analysis on the one hand helps us to understand the workability of the SCoPE better, on the other hand it provides a completely independent estimation of cosmological parameters from WMAP-9 and Planck data

  3. Bayesian parameter estimation in probabilistic risk assessment

    International Nuclear Information System (INIS)

    Siu, Nathan O.; Kelly, Dana L.

    1998-01-01

    Bayesian statistical methods are widely used in probabilistic risk assessment (PRA) because of their ability to provide useful estimates of model parameters when data are sparse and because the subjective probability framework, from which these methods are derived, is a natural framework to address the decision problems motivating PRA. This paper presents a tutorial on Bayesian parameter estimation especially relevant to PRA. It summarizes the philosophy behind these methods, approaches for constructing likelihood functions and prior distributions, some simple but realistic examples, and a variety of cautions and lessons regarding practical applications. References are also provided for more in-depth coverage of various topics

  4. Estimate of Hurricane Wind Speed from AMSR-E Low-Frequency Channel Brightness Temperature Data

    Directory of Open Access Journals (Sweden)

    Lei Zhang

    2018-01-01

    Full Text Available Two new parameters (W6H and W6V were defined that represent brightness temperature increments for different low-frequency channels due to ocean wind. We developed a new wind speed retrieval model inside hurricanes based on W6H and W6V using brightness temperature data from AMSR-E. The AMSR-E observations of 12 category 3–5 hurricanes from 2003 to 2011 and corresponding data from the H*wind analysis system were used to develop and validate the AMSR-E wind speed retrieval model. The results show that the mean bias and the overall root-mean-square (RMS difference of the AMSR-E retrieved wind speeds with respect to H*wind (HRD Real-time Hurricane Wind Analysis System analysis data were −0.01 m/s and 2.66 m/s, respectively. One case study showed that W6H and W6V were less sensitive to rain than the observed AMSR-E C-band and X-band brightness temperature data. The AMSR-E retrieval model was further validated by comparing the retrieved wind speeds against stepped-frequency microwave radiometer (SFMR measurements. The comparison showed an RMS difference of 3.41 m/s and a mean bias of 0.49 m/s.

  5. Iterative methods for distributed parameter estimation in parabolic PDE

    Energy Technology Data Exchange (ETDEWEB)

    Vogel, C.R. [Montana State Univ., Bozeman, MT (United States); Wade, J.G. [Bowling Green State Univ., OH (United States)

    1994-12-31

    The goal of the work presented is the development of effective iterative techniques for large-scale inverse or parameter estimation problems. In this extended abstract, a detailed description of the mathematical framework in which the authors view these problem is presented, followed by an outline of the ideas and algorithms developed. Distributed parameter estimation problems often arise in mathematical modeling with partial differential equations. They can be viewed as inverse problems; the `forward problem` is that of using the fully specified model to predict the behavior of the system. The inverse or parameter estimation problem is: given the form of the model and some observed data from the system being modeled, determine the unknown parameters of the model. These problems are of great practical and mathematical interest, and the development of efficient computational algorithms is an active area of study.

  6. Dispersion under low wind speed conditions using Gaussian Plume approach

    International Nuclear Information System (INIS)

    Rakesh, P.T.; Srinivas, C.V.; Baskaran, R.; Venkatesan, R.; Venkatraman, B.

    2018-01-01

    For radioactive dose computation due to atmospheric releases, dispersion models are essential requirement. For this purpose, Gaussian plume model (GPM) is used in the short range and advanced particle dispersion models are used in all ranges. In dispersion models, other than wind speed the most influential parameter which determines the fate of the pollutant is the turbulence diffusivity. In GPM the diffusivity is represented using empirical approach. Studies show that under low wind speed conditions, the existing diffusivity relationships are not adequate in estimating the diffusion. An important phenomenon that occurs during the low wind speed is the meandering motions. It is found that under meandering motions the extent of plume dispersion is more than the estimated value using conventional GPM and particle transport models. In this work a set of new turbulence parameters for the horizontal diffusion of the plume is suggested and using them in GPM, the plume is simulated and is compared against observation available from Hanford tracer release experiment

  7. Wind resource assessment: A three year experience

    Energy Technology Data Exchange (ETDEWEB)

    Al-Abbadi, N.M.; Alawaji, S.H.; Eugenio, N.N. [Energy Research Institute (ERI), Riyadh (Saudi Arabia)

    1997-12-31

    This paper presents the results of data collected from three different sites located in the central, northern and eastern region of Saudi Arabia. Each site is geographically and climatologically different from the others. Statistical moments and frequency distributions were generated for the wind speed and direction parameters to analyse the wind energy characteristics and its availability. The results of these statistical operations present the wind power and energy density estimates of the three sites. The data analysis presented a prospect of wind energy conversion and utilization. The annual extractable energy density is 488, 890, 599 kWh/m{sup 2} for the central, northern and eastern sites respectively. Also, the paper demonstrates the lessons learned from operating wind assessment stations installed in remote areas having different environmental characteristics.

  8. Preliminary study of long-term wind characteristics of the Mexican Yucatan Peninsula

    International Nuclear Information System (INIS)

    Soler-Bientz, Rolando; Watson, Simon; Infield, David

    2009-01-01

    Mexico's Yucatan Peninsula is one of the most promising areas for wind energy development within the Latin American region but no comprehensive assessment of wind resource has been previously published. This research presents a preliminary analysis of the meteorological parameters relevant to the wind resource in order to find patterns in their long-term behaviour and to establish a foundation for subsequent research into the wind power potential of the Yucatan Peninsula. Three meteorological stations with data measured for a period between 10 and 20 years were used in this study. The monthly trends of ambient temperature, atmospheric pressure and wind speed data were identified and are discussed. The directional behaviour of the winds, their frequency distributions and the related Weibull parameters are presented. Wind power densities for the study sites have been estimated and have been shown to be relatively low (wind power class 1), though a larger number of suitable sites needs to be studied before a definitive resource evaluation can be reported.

  9. Literature review of models for estimating soil erosion and deposition from wind stresses on uranium-mill-tailings covers

    International Nuclear Information System (INIS)

    Bander, T.J.

    1982-11-01

    Pacific Northwest Laboratory (PNL) is investigating the use of a rock armoring blanket (riprap) to mitigate wind and water erosion of an earthen radon-suppression cover applied to uranium-mill tailings. The mechanics of wind erosion, as well as of soil deposition, are discussed in this report. Several wind erosion models are reviewed to determine if they can be used to estimate the erosion of soil from a mill-tailings cover. One model, developed by W.S. Chepil, contains the most-important factors that describe variables that influence wind erosion. Particular features of other models are also discussed, as well as the application of Chepil's model to a particular tailings pile. For this particular tailings pile, the estimated erosion was almost one inch per year for an unprotected tailings soil surface. Wide variability in the deposition velocity and lack of adequate deposition models preclude reliable estimates of the rate at which airborne particles are deposited

  10. Literature review of models for estimating soil erosion and deposition from wind stresses on uranium-mill-tailings covers

    Energy Technology Data Exchange (ETDEWEB)

    Bander, T.J.

    1982-11-01

    Pacific Northwest Laboratory (PNL) is investigating the use of a rock armoring blanket (riprap) to mitigate wind and water erosion of an earthen radon-suppression cover applied to uranium-mill tailings. The mechanics of wind erosion, as well as of soil deposition, are discussed in this report. Several wind erosion models are reviewed to determine if they can be used to estimate the erosion of soil from a mill-tailings cover. One model, developed by W.S. Chepil, contains the most-important factors that describe variables that influence wind erosion. Particular features of other models are also discussed, as well as the application of Chepil's model to a particular tailings pile. For this particular tailings pile, the estimated erosion was almost one inch per year for an unprotected tailings soil surface. Wide variability in the deposition velocity and lack of adequate deposition models preclude reliable estimates of the rate at which airborne particles are deposited.

  11. A distributed approach for parameters estimation in System Biology models

    International Nuclear Information System (INIS)

    Mosca, E.; Merelli, I.; Alfieri, R.; Milanesi, L.

    2009-01-01

    Due to the lack of experimental measurements, biological variability and experimental errors, the value of many parameters of the systems biology mathematical models is yet unknown or uncertain. A possible computational solution is the parameter estimation, that is the identification of the parameter values that determine the best model fitting respect to experimental data. We have developed an environment to distribute each run of the parameter estimation algorithm on a different computational resource. The key feature of the implementation is a relational database that allows the user to swap the candidate solutions among the working nodes during the computations. The comparison of the distributed implementation with the parallel one showed that the presented approach enables a faster and better parameter estimation of systems biology models.

  12. Estimation of pharmacokinetic parameters from non-compartmental variables using Microsoft Excel.

    Science.gov (United States)

    Dansirikul, Chantaratsamon; Choi, Malcolm; Duffull, Stephen B

    2005-06-01

    This study was conducted to develop a method, termed 'back analysis (BA)', for converting non-compartmental variables to compartment model dependent pharmacokinetic parameters for both one- and two-compartment models. A Microsoft Excel spreadsheet was implemented with the use of Solver and visual basic functions. The performance of the BA method in estimating pharmacokinetic parameter values was evaluated by comparing the parameter values obtained to a standard modelling software program, NONMEM, using simulated data. The results show that the BA method was reasonably precise and provided low bias in estimating fixed and random effect parameters for both one- and two-compartment models. The pharmacokinetic parameters estimated from the BA method were similar to those of NONMEM estimation.

  13. Model-based fault detection for generator cooling system in wind turbines using SCADA data

    DEFF Research Database (Denmark)

    Borchersen, Anders Bech; Kinnaert, Michel

    2016-01-01

    In this work, an early fault detection system for the generator cooling of wind turbines is presented and tested. It relies on a hybrid model of the cooling system. The parameters of the generator model are estimated by an extended Kalman filter. The estimated parameters are then processed by an ...

  14. Parameter Estimates in Differential Equation Models for Chemical Kinetics

    Science.gov (United States)

    Winkel, Brian

    2011-01-01

    We discuss the need for devoting time in differential equations courses to modelling and the completion of the modelling process with efforts to estimate the parameters in the models using data. We estimate the parameters present in several differential equation models of chemical reactions of order n, where n = 0, 1, 2, and apply more general…

  15. Estimating physiological skin parameters from hyperspectral signatures

    Science.gov (United States)

    Vyas, Saurabh; Banerjee, Amit; Burlina, Philippe

    2013-05-01

    We describe an approach for estimating human skin parameters, such as melanosome concentration, collagen concentration, oxygen saturation, and blood volume, using hyperspectral radiometric measurements (signatures) obtained from in vivo skin. We use a computational model based on Kubelka-Munk theory and the Fresnel equations. This model forward maps the skin parameters to a corresponding multiband reflectance spectra. Machine-learning-based regression is used to generate the inverse map, and hence estimate skin parameters from hyperspectral signatures. We test our methods using synthetic and in vivo skin signatures obtained in the visible through the short wave infrared domains from 24 patients of both genders and Caucasian, Asian, and African American ethnicities. Performance validation shows promising results: good agreement with the ground truth and well-established physiological precepts. These methods have potential use in the characterization of skin abnormalities and in minimally-invasive prescreening of malignant skin cancers.

  16. Real-time approaches to the estimation of local wind velocity for a fixed-wing unmanned air vehicle

    International Nuclear Information System (INIS)

    Chan, W L; Lee, C S; Hsiao, F B

    2011-01-01

    Three real-time approaches to estimating local wind velocity for a fixed-wing unmanned air vehicle are presented in this study. All three methods work around the navigation equations with added wind components. The first approach calculates the local wind speed by substituting the ground speed and ascent rate data given by the Global Positioning System (GPS) into the navigation equations. The second and third approaches utilize the extended Kalman filter (EKF) and the unscented Kalman filter (UKF), respectively. The results show that, despite the nonlinearity of the navigation equations, the EKF performance is proven to be on a par with the UKF. A time-varying noise estimation method based on the Wiener filter is also discussed. Results are compared with the average wind speed measured on the ground. All three approaches are proven to be reliable with stated advantages and disadvantages

  17. Wind noise under a pine tree canopy.

    Science.gov (United States)

    Raspet, Richard; Webster, Jeremy

    2015-02-01

    It is well known that infrasonic wind noise levels are lower for arrays placed in forests and under vegetation than for those in open areas. In this research, the wind noise levels, turbulence spectra, and wind velocity profiles are measured in a pine forest. A prediction of the wind noise spectra from the measured meteorological parameters is developed based on recent research on wind noise above a flat plane. The resulting wind noise spectrum is the sum of the low frequency wind noise generated by the turbulence-shear interaction near and above the tops of the trees and higher frequency wind noise generated by the turbulence-turbulence interaction near the ground within the tree layer. The convection velocity of the low frequency wind noise corresponds to the wind speed above the trees while the measurements showed that the wind noise generated by the turbulence-turbulence interaction is near stationary and is generated by the slow moving turbulence adjacent to the ground. Comparison of the predicted wind noise spectrum with the measured wind noise spectrum shows good agreement for four measurement sets. The prediction can be applied to meteorological estimates to predict the wind noise under other pine forests.

  18. A software for parameter estimation in dynamic models

    Directory of Open Access Journals (Sweden)

    M. Yuceer

    2008-12-01

    Full Text Available A common problem in dynamic systems is to determine parameters in an equation used to represent experimental data. The goal is to determine the values of model parameters that provide the best fit to measured data, generally based on some type of least squares or maximum likelihood criterion. In the most general case, this requires the solution of a nonlinear and frequently non-convex optimization problem. Some of the available software lack in generality, while others do not provide ease of use. A user-interactive parameter estimation software was needed for identifying kinetic parameters. In this work we developed an integration based optimization approach to provide a solution to such problems. For easy implementation of the technique, a parameter estimation software (PARES has been developed in MATLAB environment. When tested with extensive example problems from literature, the suggested approach is proven to provide good agreement between predicted and observed data within relatively less computing time and iterations.

  19. Nonlinear adaptive control system design with asymptotically stable parameter estimation error

    Science.gov (United States)

    Mishkov, Rumen; Darmonski, Stanislav

    2018-01-01

    The paper presents a new general method for nonlinear adaptive system design with asymptotic stability of the parameter estimation error. The advantages of the approach include asymptotic unknown parameter estimation without persistent excitation and capability to directly control the estimates transient response time. The method proposed modifies the basic parameter estimation dynamics designed via a known nonlinear adaptive control approach. The modification is based on the generalised prediction error, a priori constraints with a hierarchical parameter projection algorithm, and the stable data accumulation concepts. The data accumulation principle is the main tool for achieving asymptotic unknown parameter estimation. It relies on the parametric identifiability system property introduced. Necessary and sufficient conditions for exponential stability of the data accumulation dynamics are derived. The approach is applied in a nonlinear adaptive speed tracking vector control of a three-phase induction motor.

  20. CTER—Rapid estimation of CTF parameters with error assessment

    Energy Technology Data Exchange (ETDEWEB)

    Penczek, Pawel A., E-mail: Pawel.A.Penczek@uth.tmc.edu [Department of Biochemistry and Molecular Biology, The University of Texas Medical School, 6431 Fannin MSB 6.220, Houston, TX 77054 (United States); Fang, Jia [Department of Biochemistry and Molecular Biology, The University of Texas Medical School, 6431 Fannin MSB 6.220, Houston, TX 77054 (United States); Li, Xueming; Cheng, Yifan [The Keck Advanced Microscopy Laboratory, Department of Biochemistry and Biophysics, University of California, San Francisco, CA 94158 (United States); Loerke, Justus; Spahn, Christian M.T. [Institut für Medizinische Physik und Biophysik, Charité – Universitätsmedizin Berlin, Charitéplatz 1, 10117 Berlin (Germany)

    2014-05-01

    In structural electron microscopy, the accurate estimation of the Contrast Transfer Function (CTF) parameters, particularly defocus and astigmatism, is of utmost importance for both initial evaluation of micrograph quality and for subsequent structure determination. Due to increases in the rate of data collection on modern microscopes equipped with new generation cameras, it is also important that the CTF estimation can be done rapidly and with minimal user intervention. Finally, in order to minimize the necessity for manual screening of the micrographs by a user it is necessary to provide an assessment of the errors of fitted parameters values. In this work we introduce CTER, a CTF parameters estimation method distinguished by its computational efficiency. The efficiency of the method makes it suitable for high-throughput EM data collection, and enables the use of a statistical resampling technique, bootstrap, that yields standard deviations of estimated defocus and astigmatism amplitude and angle, thus facilitating the automation of the process of screening out inferior micrograph data. Furthermore, CTER also outputs the spatial frequency limit imposed by reciprocal space aliasing of the discrete form of the CTF and the finite window size. We demonstrate the efficiency and accuracy of CTER using a data set collected on a 300 kV Tecnai Polara (FEI) using the K2 Summit DED camera in super-resolution counting mode. Using CTER we obtained a structure of the 80S ribosome whose large subunit had a resolution of 4.03 Å without, and 3.85 Å with, inclusion of astigmatism parameters. - Highlights: • We describe methodology for estimation of CTF parameters with error assessment. • Error estimates provide means for automated elimination of inferior micrographs. • High computational efficiency allows real-time monitoring of EM data quality. • Accurate CTF estimation yields structure of the 80S human ribosome at 3.85 Å.

  1. Wind Energy Development in India and a Methodology for Evaluating Performance of Wind Farm Clusters

    Directory of Open Access Journals (Sweden)

    Sanjeev H. Kulkarni

    2016-01-01

    Full Text Available With maturity of advanced technologies and urgent requirement for maintaining a healthy environment with reasonable price, India is moving towards a trend of generating electricity from renewable resources. Wind energy production, with its relatively safer and positive environmental characteristics, has evolved from a marginal activity into a multibillion dollar industry today. Wind energy power plants, also known as wind farms, comprise multiple wind turbines. Though there are several wind-mill clusters producing energy in different geographical locations across the world, evaluating their performance is a complex task and is an important focus for stakeholders. In this work an attempt is made to estimate the performance of wind clusters employing a multicriteria approach. Multiple factors that affect wind farm operations are analyzed by taking experts opinions, and a performance ranking of the wind farms is generated. The weights of the selection criteria are determined by pairwise comparison matrices of the Analytic Hierarchy Process (AHP. The proposed methodology evaluates wind farm performance based on technical, economic, environmental, and sociological indicators. Both qualitative and quantitative parameters were considered. Empirical data were collected through questionnaire from the selected wind farms of Belagavi district in the Indian State of Karnataka. This proposed methodology is a useful tool for cluster analysis.

  2. A Response Surface-Based Cost Model for Wind Farm Design

    International Nuclear Information System (INIS)

    Zhang Jie; Chowdhury, Souma; Messac, Achille; Castillo, Luciano

    2012-01-01

    A Response Surface-Based Wind Farm Cost (RS-WFC) model is developed for the engineering planning of wind farms. The RS-WFC model is developed using Extended Radial Basis Functions (E-RBF) for onshore wind farms in the U.S. This model is then used to explore the influences of different design and economic parameters, including number of turbines, rotor diameter and labor cost, on the cost of a wind farm. The RS-WFC model is composed of three components that estimate the effects of engineering and economic factors on (i) the installation cost, (ii) the annual Operation and Maintenance (O and M) cost, and (iii) the total annual cost of a wind farm. The accuracy of the cost model is favorably established through comparison with pertinent commercial data. The final RS-WFC model provided interesting insights into cost variation with respect to critical engineering and economic parameters. In addition, a newly developed analytical wind farm engineering model is used to determine the power generated by the farm, and the subsequent Cost of Energy (COE). This COE is optimized for a unidirectional uniform “incoming wind speed” scenario using Particle Swarm Optimization (PSO). We found that the COE could be appreciably minimized through layout optimization, thereby yielding significant cost savings. - Highlights: ► We present a Response Surface-Based Wind Farm Cost (RS-WFC) model for wind farm design. ► The model could estimate installation cost, Operation and Maintenance cost, and total annual cost of a wind farm. ► The Cost of Energy is optimized using Particle Swarm Optimization. ► Layout optimization could yield significant cost savings.

  3. Novel Method for 5G Systems NLOS Channels Parameter Estimation

    Directory of Open Access Journals (Sweden)

    Vladeta Milenkovic

    2017-01-01

    Full Text Available For the development of new 5G systems to operate in mm bands, there is a need for accurate radio propagation modelling at these bands. In this paper novel approach for NLOS channels parameter estimation will be presented. Estimation will be performed based on LCR performance measure, which will enable us to estimate propagation parameters in real time and to avoid weaknesses of ML and moment method estimation approaches.

  4. THE COMPARATIVE ANALYSIS OF TWO DIFFERENT STATISTICAL DISTRIBUTIONS USED TO ESTIMATE THE WIND ENERGY POTENTIAL

    Directory of Open Access Journals (Sweden)

    Mehmet KURBAN

    2007-01-01

    Full Text Available In this paper, the wind energy potential of the region is analyzed with Weibull and Reyleigh statistical distribution functions by using the wind speed data measured per 15 seconds in July, August, September, and October of 2005 at 10 m height of 30-m observation pole in the wind observation station constructed in the coverage of the scientific research project titled "The Construction of Hybrid (Wind-Solar Power Plant Model by Determining the Wind and Solar Potential in the Iki Eylul Campus of A.U." supported by Anadolu University. The Maximum likelihood method is used for finding the parameters of these distributions. The conclusion of the analysis for the months taken represents that the Weibull distribution models the wind speeds better than the Rayleigh distribution. Furthermore, the error rate in the monthly values of power density computed by using the Weibull distribution is smaller than the values by Rayleigh distribution.

  5. A compound structure of ELM based on feature selection and parameter optimization using hybrid backtracking search algorithm for wind speed forecasting

    International Nuclear Information System (INIS)

    Zhang, Chu; Zhou, Jianzhong; Li, Chaoshun; Fu, Wenlong; Peng, Tian

    2017-01-01

    Highlights: • A novel hybrid approach is proposed for wind speed forecasting. • The variational mode decomposition (VMD) is optimized to decompose the original wind speed series. • The input matrix and parameters of ELM are optimized simultaneously by using a hybrid BSA. • Results show that OVMD-HBSA-ELM achieves better performance in terms of prediction accuracy. - Abstract: Reliable wind speed forecasting is essential for wind power integration in wind power generation system. The purpose of paper is to develop a novel hybrid model for short-term wind speed forecasting and demonstrates its efficiency. In the proposed model, a compound structure of extreme learning machine (ELM) based on feature selection and parameter optimization using hybrid backtracking search algorithm (HBSA) is employed as the predictor. The real-valued BSA (RBSA) is exploited to search for the optimal combination of weights and bias of ELM while the binary-valued BSA (BBSA) is exploited as a feature selection method applying on the candidate inputs predefined by partial autocorrelation function (PACF) values to reconstruct the input-matrix. Due to the volatility and randomness of wind speed signal, an optimized variational mode decomposition (OVMD) is employed to eliminate the redundant noises. The parameters of the proposed OVMD are determined according to the center frequencies of the decomposed modes and the residual evaluation index (REI). The wind speed signal is decomposed into a few modes via OVMD. The aggregation of the forecasting results of these modes constructs the final forecasting result of the proposed model. The proposed hybrid model has been applied on the mean half-hour wind speed observation data from two wind farms in Inner Mongolia, China and 10-min wind speed data from the Sotavento Galicia wind farm are studied as an additional case. Parallel experiments have been designed to compare with the proposed model. Results obtained from this study indicate that the

  6. A diagnostic model to estimate winds and small-scale drag from Mars Observer PMIRR data

    Science.gov (United States)

    Barnes, J. R.

    1993-01-01

    Theoretical and modeling studies indicate that small-scale drag due to breaking gravity waves is likely to be of considerable importance for the circulation in the middle atmospheric region (approximately 40-100 km altitude) on Mars. Recent earth-based spectroscopic observations have provided evidence for the existence of circulation features, in particular, a warm winter polar region, associated with gravity wave drag. Since the Mars Observer PMIRR experiment will obtain temperature profiles extending from the surface up to about 80 km altitude, it will be extensively sampling middle atmospheric regions in which gravity wave drag may play a dominant role. Estimating the drag then becomes crucial to the estimation of the atmospheric winds from the PMIRR-observed temperatures. An interative diagnostic model based upon one previously developed and tested with earth satellite temperature data will be applied to the PMIRR measurements to produce estimates of the small-scale zonal drag and three-dimensional wind fields in the Mars middle atmosphere. This model is based on the primitive equations, and can allow for time dependence (the time tendencies used may be based upon those computed in a Fast Fourier Mapping procedure). The small-scale zonal drag is estimated as the residual in the zonal momentum equation; the horizontal winds having first been estimated from the meridional momentum equation and the continuity equation. The scheme estimates the vertical motions from the thermodynamic equation, and thus needs estimates of the diabatic heating based upon the observed temperatures. The latter will be generated using a radiative model. It is hoped that the diagnostic scheme will be able to produce good estimates of the zonal gravity wave drag in the Mars middle atmosphere, estimates that can then be used in other diagnostic or assimilation efforts, as well as more theoretical studies.

  7. The impact of in-canopy wind profile formulations on heat flux estimation in an open orchard using the remote sensing-based two-source model

    Directory of Open Access Journals (Sweden)

    C. Cammalleri

    2010-12-01

    Full Text Available For open orchard and vineyard canopies containing significant fractions of exposed soil (>50%, typical of Mediterranean agricultural regions, the energy balance of the vegetation elements is strongly influenced by heat exchange with the bare soil/substrate. For these agricultural systems a "two-source" approach, where radiation and turbulent exchange between the soil and canopy elements are explicitly modelled, appears to be the only suitable methodology for reliably assessing energy fluxes. In strongly clumped canopies, the effective wind speed profile inside and below the canopy layer can strongly influence the partitioning of energy fluxes between the soil and vegetation components. To assess the impact of in-canopy wind profile on model flux estimates, an analysis of three different formulations is presented, including algorithms from Goudriaan (1977, Massman (1987 and Lalic et al. (2003. The in-canopy wind profile formulations are applied to the thermal-based two-source energy balance (TSEB model developed by Norman et al. (1995 and modified by Kustas and Norman (1999. High resolution airborne remote sensing images, collected over an agricultural area located in the western part of Sicily (Italy comprised primarily of vineyards, olive and citrus orchards, are used to derive all the input parameters needed to apply the TSEB. The images were acquired from June to October 2008 and include a relatively wide range of meteorological and soil moisture conditions. A preliminary sensitivity analysis of the three wind profile algorithms highlights the dependence of wind speed just above the soil/substrate to leaf area index and canopy height over the typical range of canopy properties encountered in these agricultural areas. It is found that differences among the models in wind just above the soil surface are most significant under sparse and medium fractional cover conditions (15–50%. The TSEB model heat flux estimates are compared with micro

  8. European Wind Atlas and Wind Resource Research in Denmark

    DEFF Research Database (Denmark)

    Mortensen, Niels Gylling

    to estimate the actual wind climate at any specific site and height within this region. The Danish and European Wind Atlases are examples of how the wind atlas methodology can be employed to estimate the wind resource potential for a country or a sub-continent. Recently, the methodology has also been used...... - from wind measurements at prospective sites to wind tunnel simulations and advanced flow modelling. Among these approaches, the wind atlas methodology - developed at Ris0 National Laboratory over the last 25 years - has gained widespread recognition and is presently considered by many as the industry......-standard tool for wind resource assessment and siting of wind turbines. The PC-implementation of the methodology, the Wind Atlas Analysis and Application Program (WAsP), has been applied in more than 70 countries and territories world-wide. The wind atlas methodology is based on physical descriptions and models...

  9. Application of isotopic information for estimating parameters in Philip infiltration model

    Directory of Open Access Journals (Sweden)

    Tao Wang

    2016-10-01

    Full Text Available Minimizing parameter uncertainty is crucial in the application of hydrologic models. Isotopic information in various hydrologic components of the water cycle can expand our knowledge of the dynamics of water flow in the system, provide additional information for parameter estimation, and improve parameter identifiability. This study combined the Philip infiltration model with an isotopic mixing model using an isotopic mass balance approach for estimating parameters in the Philip infiltration model. Two approaches to parameter estimation were compared: (a using isotopic information to determine the soil water transmission and then hydrologic information to estimate the soil sorptivity, and (b using hydrologic information to determine the soil water transmission and the soil sorptivity. Results of parameter estimation were verified through a rainfall infiltration experiment in a laboratory under rainfall with constant isotopic compositions and uniform initial soil water content conditions. Experimental results showed that approach (a, using isotopic and hydrologic information, estimated the soil water transmission in the Philip infiltration model in a manner that matched measured values well. The results of parameter estimation of approach (a were better than those of approach (b. It was also found that the analytical precision of hydrogen and oxygen stable isotopes had a significant effect on parameter estimation using isotopic information.

  10. A Novel Methodology for Estimating State-Of-Charge of Li-Ion Batteries Using Advanced Parameters Estimation

    Directory of Open Access Journals (Sweden)

    Ibrahim M. Safwat

    2017-11-01

    Full Text Available State-of-charge (SOC estimations of Li-ion batteries have been the focus of many research studies in previous years. Many articles discussed the dynamic model’s parameters estimation of the Li-ion battery, where the fixed forgetting factor recursive least square estimation methodology is employed. However, the change rate of each parameter to reach the true value is not taken into consideration, which may tend to poor estimation. This article discusses this issue, and proposes two solutions to solve it. The first solution is the usage of a variable forgetting factor instead of a fixed one, while the second solution is defining a vector of forgetting factors, which means one factor for each parameter. After parameters estimation, a new idea is proposed to estimate state-of-charge (SOC of the Li-ion battery based on Newton’s method. Also, the error percentage and computational cost are discussed and compared with that of nonlinear Kalman filters. This methodology is applied on a 36 V 30 A Li-ion pack to validate this idea.

  11. Applicability of Synthetic Aperture Radar Wind Retrievals on Offshore Wind Resources Assessment in Hangzhou Bay, China

    Directory of Open Access Journals (Sweden)

    Rui Chang

    2014-05-01

    Full Text Available In view of the high cost and sparse spatial resolution of offshore meteorological observations, ocean winds retrieved from satellites are valuable in offshore wind resource assessment as a supplement to in situ measurements. This study examines satellite synthetic aperture radar (SAR images from ENVISAT advanced SAR (ASAR for mapping wind resources with high spatial resolution. Around 181 collected pairs of wind data from SAR wind maps and from 13 meteorological stations in Hangzhou Bay are compared. The statistical results comparing in situ wind speed and SAR-based wind speed show a standard deviation (SD of 1.99 m/s and correlation coefficient of R = 0.67. The model wind directions, which are used as input for the SAR wind speed retrieval, show a high correlation coefficient (R = 0.89 but a large standard deviation (SD = 42.3° compared to in situ observations. The Weibull probability density functions are compared at one meteorological station. The SAR-based results appear not to estimate the mean wind speed, Weibull scale and shape parameters and wind power density from the full in situ data set so well due to the lower number of satellite samples. Distributions calculated from the concurrent 81 SAR and in situ samples agree well.

  12. On the estimation of water pure compound parameters in association theories

    DEFF Research Database (Denmark)

    Grenner, Andreas; Kontogeorgis, Georgios; Michelsen, Michael Locht

    2007-01-01

    Determination of the appropriate number of association sites and estimation of parameters for association (SAFT-type) theories is not a trivial matter. Building further on a recently published manuscript by Clark et al., this work investigates aspects of the parameter estimation for water using t...... different association theories. Their performance for various properties as well as against the results presented earlier is demonstrated.......Determination of the appropriate number of association sites and estimation of parameters for association (SAFT-type) theories is not a trivial matter. Building further on a recently published manuscript by Clark et al., this work investigates aspects of the parameter estimation for water using two...

  13. Reliability Estimation with Uncertainties Consideration for High Power IGBTs in 2.3 MW Wind Turbine Converter System

    DEFF Research Database (Denmark)

    Kostandyan, Erik; Ma, Ke

    2012-01-01

    This paper investigates the lifetime of high power IGBTs (insulated gate bipolar transistors) used in large wind turbine applications. Since the IGBTs are critical components in a wind turbine power converter, it is of great importance to assess their reliability in the design phase of the turbine....... Minimum, maximum and average junction temperatures profiles for the grid side IGBTs are estimated at each wind speed input values. The selected failure mechanism is the crack propagation in solder joint under the silicon die. Based on junction temperature profiles and physics of failure model......, the probabilistic and determinist damage models are presented with estimated fatigue lives. Reliably levels were assessed by means of First Order Reliability Method taking into account uncertainties....

  14. Estimation of Rotor Effective Wind Speed: A Comparison

    DEFF Research Database (Denmark)

    Soltani, Mohsen; Knudsen, Torben; Svenstrup, Mikael

    2013-01-01

    Modern wind turbine controllers use wind speed information to improve power production and reduce loads on the turbine components. The turbine top wind speed measurement is unfortunately imprecise and not a good representative of the rotor effective wind speed. Consequently, many different model...... aero-servo-elastic turbine simulations and real turbine field experiments in different wind scenarios....

  15. Parameter Estimation for a Computable General Equilibrium Model

    DEFF Research Database (Denmark)

    Arndt, Channing; Robinson, Sherman; Tarp, Finn

    We introduce a maximum entropy approach to parameter estimation for computable general equilibrium (CGE) models. The approach applies information theory to estimating a system of nonlinear simultaneous equations. It has a number of advantages. First, it imposes all general equilibrium constraints...

  16. Modular Estimation Strategy of Vehicle Dynamic Parameters for Motion Control Applications

    Directory of Open Access Journals (Sweden)

    Rawash Mustafa

    2018-01-01

    Full Text Available The presence of motion control or active safety systems in vehicles have become increasingly important for improving vehicle performance and handling and negotiating dangerous driving situations. The performance of such systems would be improved if combined with knowledge of vehicle dynamic parameters. Since some of these parameters are difficult to measure, due to technical or economic reasons, estimation of those parameters might be the only practical alternative. In this paper, an estimation strategy of important vehicle dynamic parameters, pertaining to motion control applications, is presented. The estimation strategy is of a modular structure such that each module is concerned with estimating a single vehicle parameter. Parameters estimated include: longitudinal, lateral, and vertical tire forces – longitudinal velocity – vehicle mass. The advantage of this strategy is its independence of tire parameters or wear, road surface condition, and vehicle mass variation. Also, because of its modular structure, each module could be later updated or exchanged for a more effective one. Results from simulations on a 14-DOF vehicle model are provided here to validate the strategy and show its robustness and accuracy.

  17. Estimation of object motion parameters from noisy images.

    Science.gov (United States)

    Broida, T J; Chellappa, R

    1986-01-01

    An approach is presented for the estimation of object motion parameters based on a sequence of noisy images. The problem considered is that of a rigid body undergoing unknown rotational and translational motion. The measurement data consists of a sequence of noisy image coordinates of two or more object correspondence points. By modeling the object dynamics as a function of time, estimates of the model parameters (including motion parameters) can be extracted from the data using recursive and/or batch techniques. This permits a desired degree of smoothing to be achieved through the use of an arbitrarily large number of images. Some assumptions regarding object structure are presently made. Results are presented for a recursive estimation procedure: the case considered here is that of a sequence of one dimensional images of a two dimensional object. Thus, the object moves in one transverse dimension, and in depth, preserving the fundamental ambiguity of the central projection image model (loss of depth information). An iterated extended Kalman filter is used for the recursive solution. Noise levels of 5-10 percent of the object image size are used. Approximate Cramer-Rao lower bounds are derived for the model parameter estimates as a function of object trajectory and noise level. This approach may be of use in situations where it is difficult to resolve large numbers of object match points, but relatively long sequences of images (10 to 20 or more) are available.

  18. State and parameter estimation in biotechnical batch reactors

    NARCIS (Netherlands)

    Keesman, K.J.

    2000-01-01

    In this paper the problem of state and parameter estimation in biotechnical batch reactors is considered. Models describing the biotechnical process behaviour are usually nonlinear with time-varying parameters. Hence, the resulting large dimensions of the augmented state vector, roughly > 7, in

  19. Parameter Estimation of Damped Compound Pendulum Using Bat Algorithm

    Directory of Open Access Journals (Sweden)

    Saad Mohd Sazli

    2016-01-01

    Full Text Available In this study, the parameter identification of the damped compound pendulum system is proposed using one of the most promising nature inspired algorithms which is Bat Algorithm (BA. The procedure used to achieve the parameter identification of the experimental system consists of input-output data collection, ARX model order selection and parameter estimation using bat algorithm (BA method. PRBS signal is used as an input signal to regulate the motor speed. Whereas, the output signal is taken from position sensor. Both, input and output data is used to estimate the parameter of the autoregressive with exogenous input (ARX model. The performance of the model is validated using mean squares error (MSE between the actual and predicted output responses of the models. Finally, comparative study is conducted between BA and the conventional estimation method (i.e. Least Square. Based on the results obtained, MSE produce from Bat Algorithm (BA is outperformed the Least Square (LS method.

  20. Numerical Estimation of Fatigue Life of Wind Turbines due to Shadow Effect

    DEFF Research Database (Denmark)

    Thoft-Christensen, Palle; Pedersen, Ronnie; Nielsen, Søren R.K.

    2009-01-01

    The influence of tower design on damage accumulation in up-wind turbine blades during tower passage is discussed. The fatigue life of a blade is estimated for a tripod tower configuration and a standard mono-tower. The blade stresses are determined from a dynamic mechanical model with a delay...

  1. Global parameter estimation for thermodynamic models of transcriptional regulation.

    Science.gov (United States)

    Suleimenov, Yerzhan; Ay, Ahmet; Samee, Md Abul Hassan; Dresch, Jacqueline M; Sinha, Saurabh; Arnosti, David N

    2013-07-15

    Deciphering the mechanisms involved in gene regulation holds the key to understanding the control of central biological processes, including human disease, population variation, and the evolution of morphological innovations. New experimental techniques including whole genome sequencing and transcriptome analysis have enabled comprehensive modeling approaches to study gene regulation. In many cases, it is useful to be able to assign biological significance to the inferred model parameters, but such interpretation should take into account features that affect these parameters, including model construction and sensitivity, the type of fitness calculation, and the effectiveness of parameter estimation. This last point is often neglected, as estimation methods are often selected for historical reasons or for computational ease. Here, we compare the performance of two parameter estimation techniques broadly representative of local and global approaches, namely, a quasi-Newton/Nelder-Mead simplex (QN/NMS) method and a covariance matrix adaptation-evolutionary strategy (CMA-ES) method. The estimation methods were applied to a set of thermodynamic models of gene transcription applied to regulatory elements active in the Drosophila embryo. Measuring overall fit, the global CMA-ES method performed significantly better than the local QN/NMS method on high quality data sets, but this difference was negligible on lower quality data sets with increased noise or on data sets simplified by stringent thresholding. Our results suggest that the choice of parameter estimation technique for evaluation of gene expression models depends both on quality of data, the nature of the models [again, remains to be established] and the aims of the modeling effort. Copyright © 2013 Elsevier Inc. All rights reserved.

  2. Uncertainty estimation of core safety parameters using cross-correlations of covariance matrix

    International Nuclear Information System (INIS)

    Yamamoto, A.; Yasue, Y.; Endo, T.; Kodama, Y.; Ohoka, Y.; Tatsumi, M.

    2012-01-01

    An uncertainty estimation method for core safety parameters, for which measurement values are not obtained, is proposed. We empirically recognize the correlations among the prediction errors among core safety parameters, e.g., a correlation between the control rod worth and assembly relative power of corresponding position. Correlations of uncertainties among core safety parameters are theoretically estimated using the covariance of cross sections and sensitivity coefficients for core parameters. The estimated correlations among core safety parameters are verified through the direct Monte-Carlo sampling method. Once the correlation of uncertainties among core safety parameters is known, we can estimate the uncertainty of a safety parameter for which measurement value is not obtained. Furthermore, the correlations can be also used for the reduction of uncertainties of core safety parameters. (authors)

  3. Parameter Estimation for a Computable General Equilibrium Model

    DEFF Research Database (Denmark)

    Arndt, Channing; Robinson, Sherman; Tarp, Finn

    2002-01-01

    We introduce a maximum entropy approach to parameter estimation for computable general equilibrium (CGE) models. The approach applies information theory to estimating a system of non-linear simultaneous equations. It has a number of advantages. First, it imposes all general equilibrium constraints...

  4. Heuristic and probabilistic wind power availability estimation procedures: Improved tools for technology and site selection

    Energy Technology Data Exchange (ETDEWEB)

    Nigim, K.A. [University of Waterloo, Waterloo, Ont. (Canada). Department of Electrical and Computer Engineering; Parker, Paul [University of Waterloo, Waterloo, Ont. (Canada). Department of Geography, Environmental Studies

    2007-04-15

    The paper describes two investigative procedures to estimate wind power from measured wind velocities. Wind velocity data are manipulated to visualize the site potential by investigating the probable wind power availability and its capacity to meet a targeted demand. The first procedure is an availability procedure that looks at the wind characteristics and its probable energy capturing profile. This profile of wind enables the probable maximum operating wind velocity profile for a selected wind turbine design to be predicted. The structured procedures allow for a consequent adjustment, sorting and grouping of the measured wind velocity data taken at different time intervals and hub heights. The second procedure is the adequacy procedure that investigates the probable degree of availability and the application consequences. Both procedures are programmed using MathCAD symbolic mathematical software. The math tool is used to generate a visual interpolation of the data as well as numerical results from extensive data sets that exceed the capacity of conventional spreadsheet tools. Two sites located in Southern Ontario, Canada are investigated using the procedures. Successful implementation of the procedures supports informed decision making where a hill site is shown to have much higher wind potential than that measured at the local airport. The process is suitable for a wide spectrum of users who are considering the energy potential for either a grid-tied or off-grid wind energy system. (author)

  5. Bias-Corrected Estimation of Noncentrality Parameters of Covariance Structure Models

    Science.gov (United States)

    Raykov, Tenko

    2005-01-01

    A bias-corrected estimator of noncentrality parameters of covariance structure models is discussed. The approach represents an application of the bootstrap methodology for purposes of bias correction, and utilizes the relation between average of resample conventional noncentrality parameter estimates and their sample counterpart. The…

  6. A comment on "Novel scavenger removal trials increase wind turbine-caused avian fatality estimates"

    Science.gov (United States)

    Huso, Manuela M.P.; Erickson, Wallace P.

    2013-01-01

    In a recent paper, Smallwood et al. (2010) conducted a study to compare their “novel” approach to conducting carcass removal trials with what they term the “conventional” approach and to evaluate the effects of the different methods on estimated avian fatality at a wind power facility in California. A quick glance at Table 3 that succinctly summarizes their results and provides estimated fatality rates and 80% confidence intervals calculated using the 2 methods reveals a surprising result. The confidence intervals of all of their estimates and most of the conventional estimates extend below 0. These results imply that wind turbines may have the capacity to create live birds. But a more likely interpretation is that a serious error occurred in the calculation of either the average fatality rate or its standard error or both. Further evaluation of their methods reveals that the scientific basis for concluding that “many estimates of scavenger removal rates prior to [their] study were likely biased low due to scavenger swamping” and “previously reported estimates of avian fatality rates … should be adjusted upwards” was not evident in their analysis and results. Their comparison to conventional approaches was not applicable, their statistical models were questionable, and the conclusions they drew were unsupported.

  7. Optimal design criteria - prediction vs. parameter estimation

    Science.gov (United States)

    Waldl, Helmut

    2014-05-01

    G-optimality is a popular design criterion for optimal prediction, it tries to minimize the kriging variance over the whole design region. A G-optimal design minimizes the maximum variance of all predicted values. If we use kriging methods for prediction it is self-evident to use the kriging variance as a measure of uncertainty for the estimates. Though the computation of the kriging variance and even more the computation of the empirical kriging variance is computationally very costly and finding the maximum kriging variance in high-dimensional regions can be time demanding such that we cannot really find the G-optimal design with nowadays available computer equipment in practice. We cannot always avoid this problem by using space-filling designs because small designs that minimize the empirical kriging variance are often non-space-filling. D-optimality is the design criterion related to parameter estimation. A D-optimal design maximizes the determinant of the information matrix of the estimates. D-optimality in terms of trend parameter estimation and D-optimality in terms of covariance parameter estimation yield basically different designs. The Pareto frontier of these two competing determinant criteria corresponds with designs that perform well under both criteria. Under certain conditions searching the G-optimal design on the above Pareto frontier yields almost as good results as searching the G-optimal design in the whole design region. In doing so the maximum of the empirical kriging variance has to be computed only a few times though. The method is demonstrated by means of a computer simulation experiment based on data provided by the Belgian institute Management Unit of the North Sea Mathematical Models (MUMM) that describe the evolution of inorganic and organic carbon and nutrients, phytoplankton, bacteria and zooplankton in the Southern Bight of the North Sea.

  8. Maximum profile likelihood estimation of differential equation parameters through model based smoothing state estimates.

    Science.gov (United States)

    Campbell, D A; Chkrebtii, O

    2013-12-01

    Statistical inference for biochemical models often faces a variety of characteristic challenges. In this paper we examine state and parameter estimation for the JAK-STAT intracellular signalling mechanism, which exemplifies the implementation intricacies common in many biochemical inference problems. We introduce an extension to the Generalized Smoothing approach for estimating delay differential equation models, addressing selection of complexity parameters, choice of the basis system, and appropriate optimization strategies. Motivated by the JAK-STAT system, we further extend the generalized smoothing approach to consider a nonlinear observation process with additional unknown parameters, and highlight how the approach handles unobserved states and unevenly spaced observations. The methodology developed is generally applicable to problems of estimation for differential equation models with delays, unobserved states, nonlinear observation processes, and partially observed histories. Crown Copyright © 2013. Published by Elsevier Inc. All rights reserved.

  9. Parameter estimation of Lorenz chaotic system using a hybrid swarm intelligence algorithm

    International Nuclear Information System (INIS)

    Lazzús, Juan A.; Rivera, Marco; López-Caraballo, Carlos H.

    2016-01-01

    A novel hybrid swarm intelligence algorithm for chaotic system parameter estimation is present. For this purpose, the parameters estimation on Lorenz systems is formulated as a multidimensional problem, and a hybrid approach based on particle swarm optimization with ant colony optimization (PSO–ACO) is implemented to solve this problem. Firstly, the performance of the proposed PSO–ACO algorithm is tested on a set of three representative benchmark functions, and the impact of the parameter settings on PSO–ACO efficiency is studied. Secondly, the parameter estimation is converted into an optimization problem on a three-dimensional Lorenz system. Numerical simulations on Lorenz model and comparisons with results obtained by other algorithms showed that PSO–ACO is a very powerful tool for parameter estimation with high accuracy and low deviations. - Highlights: • PSO–ACO combined particle swarm optimization with ant colony optimization. • This study is the first research of PSO–ACO to estimate parameters of chaotic systems. • PSO–ACO algorithm can identify the parameters of the three-dimensional Lorenz system with low deviations. • PSO–ACO is a very powerful tool for the parameter estimation on other chaotic system.

  10. Parameter estimation of Lorenz chaotic system using a hybrid swarm intelligence algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Lazzús, Juan A., E-mail: jlazzus@dfuls.cl; Rivera, Marco; López-Caraballo, Carlos H.

    2016-03-11

    A novel hybrid swarm intelligence algorithm for chaotic system parameter estimation is present. For this purpose, the parameters estimation on Lorenz systems is formulated as a multidimensional problem, and a hybrid approach based on particle swarm optimization with ant colony optimization (PSO–ACO) is implemented to solve this problem. Firstly, the performance of the proposed PSO–ACO algorithm is tested on a set of three representative benchmark functions, and the impact of the parameter settings on PSO–ACO efficiency is studied. Secondly, the parameter estimation is converted into an optimization problem on a three-dimensional Lorenz system. Numerical simulations on Lorenz model and comparisons with results obtained by other algorithms showed that PSO–ACO is a very powerful tool for parameter estimation with high accuracy and low deviations. - Highlights: • PSO–ACO combined particle swarm optimization with ant colony optimization. • This study is the first research of PSO–ACO to estimate parameters of chaotic systems. • PSO–ACO algorithm can identify the parameters of the three-dimensional Lorenz system with low deviations. • PSO–ACO is a very powerful tool for the parameter estimation on other chaotic system.

  11. Comparative study of speed estimators with highly noisy measurement signals for Wind Energy Generation Systems

    Energy Technology Data Exchange (ETDEWEB)

    Carranza, O. [Escuela Superior de Computo, Instituto Politecnico Nacional, Av. Juan de Dios Batiz S/N, Col. Lindavista, Del. Gustavo A. Madero 7738, D.F. (Mexico); Figueres, E.; Garcera, G. [Grupo de Sistemas Electronicos Industriales, Departamento de Ingenieria Electronica, Universidad Politecnica de Valencia, Camino de Vera S/N, 7F, 46020 Valencia (Spain); Gonzalez, L.G. [Departamento de Ingenieria Electronica, Universidad de los Andes, Merida (Venezuela)

    2011-03-15

    This paper presents a comparative study of several speed estimators to implement a sensorless speed control loop in Wind Energy Generation Systems driven by power factor correction three-phase boost rectifiers. This rectifier topology reduces the low frequency harmonics contents of the generator currents and, consequently, the generator power factor approaches unity whereas undesired vibrations of the mechanical system decrease. For implementation of the speed estimators, the compared techniques start from the measurement of electrical variables like currents and voltages, which contain low frequency harmonics of the fundamental frequency of the wind generator, as well as switching frequency components due to the boost rectifier. In this noisy environment it has been analyzed the performance of the following estimation techniques: Synchronous Reference Frame Phase Locked Loop, speed reconstruction by measuring the dc current and voltage of the rectifier and speed estimation by means of both an Extended Kalman Filter and a Linear Kalman Filter. (author)

  12. Reliability analysis for wind turbines with incomplete failure data collected from after the date of initial installation

    International Nuclear Information System (INIS)

    Guo Haitao; Watson, Simon; Tavner, Peter; Xiang Jiangping

    2009-01-01

    Reliability has an impact on wind energy project costs and benefits. Both life test data and field failure data can be used for reliability analysis. In wind energy industry, wind farm operators have greater interest in recording wind turbine operating data. However, field failure data may be tainted or incomplete, and therefore it needs a more general mathematical model and algorithms to solve the model. The aim of this paper is to provide a solution to this problem. A three-parameter Weibull failure rate function is discussed for wind turbines and the parameters are estimated by maximum likelihood and least squares. Two populations of German and Danish wind turbines are analyzed. The traditional Weibull failure rate function is also employed for comparison. Analysis shows that the three-parameter Weibull function can obtain more accuracy on reliability growth of wind turbines. This work will be helpful in the understanding of the reliability growth of wind energy systems as wind energy technologies evolving. The proposed three-parameter Weibull function is also applicable to the life test of the components that have been used for a period of time, not only in wind energy but also in other industries

  13. Maximum-likelihood estimation of the hyperbolic parameters from grouped observations

    DEFF Research Database (Denmark)

    Jensen, Jens Ledet

    1988-01-01

    a least-squares problem. The second procedure Hypesti first approaches the maximum-likelihood estimate by iterating in the profile-log likelihood function for the scale parameter. Close to the maximum of the likelihood function, the estimation is brought to an end by iteration, using all four parameters...

  14. Dual ant colony operational modal analysis parameter estimation method

    Science.gov (United States)

    Sitarz, Piotr; Powałka, Bartosz

    2018-01-01

    Operational Modal Analysis (OMA) is a common technique used to examine the dynamic properties of a system. Contrary to experimental modal analysis, the input signal is generated in object ambient environment. Operational modal analysis mainly aims at determining the number of pole pairs and at estimating modal parameters. Many methods are used for parameter identification. Some methods operate in time while others in frequency domain. The former use correlation functions, the latter - spectral density functions. However, while some methods require the user to select poles from a stabilisation diagram, others try to automate the selection process. Dual ant colony operational modal analysis parameter estimation method (DAC-OMA) presents a new approach to the problem, avoiding issues involved in the stabilisation diagram. The presented algorithm is fully automated. It uses deterministic methods to define the interval of estimated parameters, thus reducing the problem to optimisation task which is conducted with dedicated software based on ant colony optimisation algorithm. The combination of deterministic methods restricting parameter intervals and artificial intelligence yields very good results, also for closely spaced modes and significantly varied mode shapes within one measurement point.

  15. Reducing storage of global wind ensembles with stochastic generators

    KAUST Repository

    Jeong, Jaehong

    2018-03-09

    Wind has the potential to make a significant contribution to future energy resources. Locating the sources of this renewable energy on a global scale is however extremely challenging, given the difficulty to store very large data sets generated by modern computer models. We propose a statistical model that aims at reproducing the data-generating mechanism of an ensemble of runs via a Stochastic Generator (SG) of global annual wind data. We introduce an evolutionary spectrum approach with spatially varying parameters based on large-scale geographical descriptors such as altitude to better account for different regimes across the Earth’s orography. We consider a multi-step conditional likelihood approach to estimate the parameters that explicitly accounts for nonstationary features while also balancing memory storage and distributed computation. We apply the proposed model to more than 18 million points of yearly global wind speed. The proposed SG requires orders of magnitude less storage for generating surrogate ensemble members from wind than does creating additional wind fields from the climate model, even if an effective lossy data compression algorithm is applied to the simulation output.

  16. Reducing storage of global wind ensembles with stochastic generators

    KAUST Repository

    Jeong, Jaehong; Castruccio, Stefano; Crippa, Paola; Genton, Marc G.

    2018-01-01

    Wind has the potential to make a significant contribution to future energy resources. Locating the sources of this renewable energy on a global scale is however extremely challenging, given the difficulty to store very large data sets generated by modern computer models. We propose a statistical model that aims at reproducing the data-generating mechanism of an ensemble of runs via a Stochastic Generator (SG) of global annual wind data. We introduce an evolutionary spectrum approach with spatially varying parameters based on large-scale geographical descriptors such as altitude to better account for different regimes across the Earth’s orography. We consider a multi-step conditional likelihood approach to estimate the parameters that explicitly accounts for nonstationary features while also balancing memory storage and distributed computation. We apply the proposed model to more than 18 million points of yearly global wind speed. The proposed SG requires orders of magnitude less storage for generating surrogate ensemble members from wind than does creating additional wind fields from the climate model, even if an effective lossy data compression algorithm is applied to the simulation output.

  17. Dst Prediction Based on Solar Wind Parameters

    Directory of Open Access Journals (Sweden)

    Yoon-Kyung Park

    2009-12-01

    Full Text Available We reevaluate the Burton equation (Burton et al. 1975 of predicting Dst index using high quality hourly solar wind data supplied by the ACE satellite for the period from 1998 to 2006. Sixty magnetic storms with monotonously decreasing main phase are selected. In order to determine the injection term (Q and the decay time (tau of the equation, we examine the relationships between Dst* and VB_s, Delta Dst* and VB_s, and Delta Dst* and Dst* during the magnetic storms. For this analysis, we take into account one hour of the propagation time from the ACE satellite to the magnetopause, and a half hour of the response time of the magnetosphere/ring current to the solar wind forcing. The injection term is found to be Q({nT}/h=-3.56VB_s for VB_s>0.5mV/m and Q({nT}/h=0 for VB_s leq0.5mV/m. The tau (hour is estimated as 0.060 Dst* + 16.65 for Dst*>-175nT and 6.15 hours for Dst* leq -175nT. Based on these empirical relationships, we predict the 60 magnetic storms and find that the correlation coefficient between the observed and predicted Dst* is 0.88. To evaluate the performance of our prediction scheme, the 60 magnetic storms are predicted again using the models by Burton et al. (1975 and O'Brien & McPherron (2000a. The correlation coefficients thus obtained are 0.85, the same value for both of the two models. In this respect, our model is slightly improved over the other two models as far as the correlation coefficients is concerned. Particularly our model does a better job than the other two models in predicting intense magnetic storms (Dst* lesssim -200nT.

  18. Cosmological parameter estimation using particle swarm optimization

    Science.gov (United States)

    Prasad, Jayanti; Souradeep, Tarun

    2012-06-01

    Constraining theoretical models, which are represented by a set of parameters, using observational data is an important exercise in cosmology. In Bayesian framework this is done by finding the probability distribution of parameters which best fits to the observational data using sampling based methods like Markov chain Monte Carlo (MCMC). It has been argued that MCMC may not be the best option in certain problems in which the target function (likelihood) poses local maxima or have very high dimensionality. Apart from this, there may be examples in which we are mainly interested to find the point in the parameter space at which the probability distribution has the largest value. In this situation the problem of parameter estimation becomes an optimization problem. In the present work we show that particle swarm optimization (PSO), which is an artificial intelligence inspired population based search procedure, can also be used for cosmological parameter estimation. Using PSO we were able to recover the best-fit Λ cold dark matter (LCDM) model parameters from the WMAP seven year data without using any prior guess value or any other property of the probability distribution of parameters like standard deviation, as is common in MCMC. We also report the results of an exercise in which we consider a binned primordial power spectrum (to increase the dimensionality of problem) and find that a power spectrum with features gives lower chi square than the standard power law. Since PSO does not sample the likelihood surface in a fair way, we follow a fitting procedure to find the spread of likelihood function around the best-fit point.

  19. Environmental indicators for the wind power generation in Mato Grosso do Sul; Indicadores ambientais para a geracao de energia eolica em Mato Grosso do Sul

    Energy Technology Data Exchange (ETDEWEB)

    Souza, Amaury de; Fernandes, Widinei Alves; Pavao, Hamilton Germano; Lastoria, Giancarlo; Gabas, Sandra Garcia; Paranhos Filho, Antonio Conceicao; Zampieri, Alexandra [Universidade Federal de Mato Grosso do Sul (UFRGS), Campo Grande, MS (Brazil). Centro de Ciencias Exatas e Tecnologia], E-mails: amaury.de@uol.com.br, wafer@hotmail.com, pavao@dfi.ufms.br, g.lastoria@.ufms.br; sandragabas@ufms.br, antonio.paranhos@pq.cnpq.br, alexandrazampieri@gmail.com

    2011-10-15

    In this study, we used data of wind speed, from Universal Records anemograph Fuess, 10 m high, from 19 meteorological stations belonging to the National Institute of Meteorology (INMET), from January 2008 to December 2010. The research objective was to determine the wind power in selected stations. To do so, estimated the parameters of the Weibull distribution, by which it calculated the wind power. The least squares method applied to the frequency distribution of wind speed is a good option for calculating the parameters of Weibull distribution and the estimated parameters c and k, represent satisfactorily, the monthly frequencies of wind speed in the locations studied. The methods in the characterization of wind power in the state of Mato Grosso do Sul, according to the spatial and temporal variability of daily average wind speeds and classification of wind speeds, using the agglomerative Wards at the discretion of inertia, allowed to obtain three homogeneous groups in the study area and the regions that showed higher average daily wind speed was the area of Campo Grande and Sete Quedas. (author)

  20. Wind-wave modelling aspects within complicate topography

    Directory of Open Access Journals (Sweden)

    S. Christopoulos

    Full Text Available Wave forecasting aspects for basins with complicate geomorphology, such as the Aegean Sea, are investigated through an intercomparison study. The efficiency of the available wind models (ECMWF, UKMO to reproduce wind patterns over special basins, as well as three wave models incorporating different physics and characteristics (WAM, AUT, WACCAS, are tested for selected storm cases representing the typical wind situations over the basin. From the wave results, discussed in terms of time-series and statistical parameters, the crucial role is pointed out of the wind resolution and the reliability of the different wave models to estimate the wave climate in such a basin. The necessary grid resolution is also tested, while for a specific test case (December 1991 ERS-1 satellite data are compared with those of the model.

  1. Estimating RASATI scores using acoustical parameters

    International Nuclear Information System (INIS)

    Agüero, P D; Tulli, J C; Moscardi, G; Gonzalez, E L; Uriz, A J

    2011-01-01

    Acoustical analysis of speech using computers has reached an important development in the latest years. The subjective evaluation of a clinician is complemented with an objective measure of relevant parameters of voice. Praat, MDVP (Multi Dimensional Voice Program) and SAV (Software for Voice Analysis) are some examples of software for speech analysis. This paper describes an approach to estimate the subjective characteristics of RASATI scale given objective acoustical parameters. Two approaches were used: linear regression with non-negativity constraints, and neural networks. The experiments show that such approach gives correct evaluations with ±1 error in 80% of the cases.

  2. Simultaneous Parameters Identifiability and Estimation of an E. coli Metabolic Network Model

    Directory of Open Access Journals (Sweden)

    Kese Pontes Freitas Alberton

    2015-01-01

    Full Text Available This work proposes a procedure for simultaneous parameters identifiability and estimation in metabolic networks in order to overcome difficulties associated with lack of experimental data and large number of parameters, a common scenario in the modeling of such systems. As case study, the complex real problem of parameters identifiability of the Escherichia coli K-12 W3110 dynamic model was investigated, composed by 18 differential ordinary equations and 35 kinetic rates, containing 125 parameters. With the procedure, model fit was improved for most of the measured metabolites, achieving 58 parameters estimated, including 5 unknown initial conditions. The results indicate that simultaneous parameters identifiability and estimation approach in metabolic networks is appealing, since model fit to the most of measured metabolites was possible even when important measures of intracellular metabolites and good initial estimates of parameters are not available.

  3. Southern Ocean carbon-wind stress feedback

    Science.gov (United States)

    Bronselaer, Ben; Zanna, Laure; Munday, David R.; Lowe, Jason

    2018-02-01

    The Southern Ocean is the largest sink of anthropogenic carbon in the present-day climate. Here, Southern Ocean pCO2 and its dependence on wind forcing are investigated using an equilibrium mixed layer carbon budget. This budget is used to derive an expression for Southern Ocean pCO2 sensitivity to wind stress. Southern Ocean pCO2 is found to vary as the square root of area-mean wind stress, arising from the dominance of vertical mixing over other processes such as lateral Ekman transport. The expression for pCO2 is validated using idealised coarse-resolution ocean numerical experiments. Additionally, we show that increased (decreased) stratification through surface warming reduces (increases) the sensitivity of the Southern Ocean pCO2 to wind stress. The scaling is then used to estimate the wind-stress induced changes of atmospheric pCO_2 in CMIP5 models using only a handful of parameters. The scaling is further used to model the anthropogenic carbon sink, showing a long-term reversal of the Southern Ocean sink for large wind stress strength.

  4. Electric solar wind sail mass budget model

    Directory of Open Access Journals (Sweden)

    P. Janhunen

    2013-02-01

    Full Text Available The electric solar wind sail (E-sail is a new type of propellantless propulsion system for Solar System transportation, which uses the natural solar wind to produce spacecraft propulsion. The E-sail consists of thin centrifugally stretched tethers that are kept charged by an onboard electron gun and, as such, experience Coulomb drag through the high-speed solar wind plasma stream. This paper discusses a mass breakdown and a performance model for an E-sail spacecraft that hosts a mission-specific payload of prescribed mass. In particular, the model is able to estimate the total spacecraft mass and its propulsive acceleration as a function of various design parameters such as the number of tethers and their length. A number of subsystem masses are calculated assuming existing or near-term E-sail technology. In light of the obtained performance estimates, an E-sail represents a promising propulsion system for a variety of transportation needs in the Solar System.

  5. Kalman filter estimation of RLC parameters for UMP transmission line

    Directory of Open Access Journals (Sweden)

    Mohd Amin Siti Nur Aishah

    2018-01-01

    Full Text Available This paper present the development of Kalman filter that allows evaluation in the estimation of resistance (R, inductance (L, and capacitance (C values for Universiti Malaysia Pahang (UMP short transmission line. To overcome the weaknesses of existing system such as power losses in the transmission line, Kalman Filter can be a better solution to estimate the parameters. The aim of this paper is to estimate RLC values by using Kalman filter that in the end can increase the system efficiency in UMP. In this research, matlab simulink model is developed to analyse the UMP short transmission line by considering different noise conditions to reprint certain unknown parameters which are difficult to predict. The data is then used for comparison purposes between calculated and estimated values. The results have illustrated that the Kalman Filter estimate accurately the RLC parameters with less error. The comparison of accuracy between Kalman Filter and Least Square method is also presented to evaluate their performances.

  6. Wind energy potential assessment of Cameroon's coastal regions for the installation of an onshore wind farm.

    Science.gov (United States)

    Arreyndip, Nkongho Ayuketang; Joseph, Ebobenow; David, Afungchui

    2016-11-01

    For the future installation of a wind farm in Cameroon, the wind energy potentials of three of Cameroon's coastal cities (Kribi, Douala and Limbe) are assessed using NASA average monthly wind data for 31 years (1983-2013) and compared through Weibull statistics. The Weibull parameters are estimated by the method of maximum likelihood, the mean power densities, the maximum energy carrying wind speeds and the most probable wind speeds are also calculated and compared over these three cities. Finally, the cumulative wind speed distributions over the wet and dry seasons are also analyzed. The results show that the shape and scale parameters for Kribi, Douala and Limbe are 2.9 and 2.8, 3.9 and 1.8 and 3.08 and 2.58, respectively. The mean power densities through Weibull analysis for Kribi, Douala and Limbe are 33.7 W/m2, 8.0 W/m2 and 25.42 W/m2, respectively. Kribi's most probable wind speed and maximum energy carrying wind speed was found to be 2.42 m/s and 3.35 m/s, 2.27 m/s and 3.03 m/s for Limbe and 1.67 m/s and 2.0 m/s for Douala, respectively. Analysis of the wind speed and hence power distribution over the wet and dry seasons shows that in the wet season, August is the windiest month for Douala and Limbe while September is the windiest month for Kribi while in the dry season, March is the windiest month for Douala and Limbe while February is the windiest month for Kribi. In terms of mean power density, most probable wind speed and wind speed carrying maximum energy, Kribi shows to be the best site for the installation of a wind farm. Generally, the wind speeds at all three locations seem quite low, average wind speeds of all the three studied locations fall below 4.0m/s which is far below the cut-in wind speed of many modern wind turbines. However we recommend the use of low cut-in speed wind turbines like the Savonius for stand alone low energy needs.

  7. Iterative importance sampling algorithms for parameter estimation

    OpenAIRE

    Morzfeld, Matthias; Day, Marcus S.; Grout, Ray W.; Pau, George Shu Heng; Finsterle, Stefan A.; Bell, John B.

    2016-01-01

    In parameter estimation problems one computes a posterior distribution over uncertain parameters defined jointly by a prior distribution, a model, and noisy data. Markov Chain Monte Carlo (MCMC) is often used for the numerical solution of such problems. An alternative to MCMC is importance sampling, which can exhibit near perfect scaling with the number of cores on high performance computing systems because samples are drawn independently. However, finding a suitable proposal distribution is ...

  8. Uncertainties in the Item Parameter Estimates and Robust Automated Test Assembly

    Science.gov (United States)

    Veldkamp, Bernard P.; Matteucci, Mariagiulia; de Jong, Martijn G.

    2013-01-01

    Item response theory parameters have to be estimated, and because of the estimation process, they do have uncertainty in them. In most large-scale testing programs, the parameters are stored in item banks, and automated test assembly algorithms are applied to assemble operational test forms. These algorithms treat item parameters as fixed values,…

  9. Parameter estimation in nonlinear models for pesticide degradation

    International Nuclear Information System (INIS)

    Richter, O.; Pestemer, W.; Bunte, D.; Diekkrueger, B.

    1991-01-01

    A wide class of environmental transfer models is formulated as ordinary or partial differential equations. With the availability of fast computers, the numerical solution of large systems became feasible. The main difficulty in performing a realistic and convincing simulation of the fate of a substance in the biosphere is not the implementation of numerical techniques but rather the incomplete data basis for parameter estimation. Parameter estimation is a synonym for statistical and numerical procedures to derive reasonable numerical values for model parameters from data. The classical method is the familiar linear regression technique which dates back to the 18th century. Because it is easy to handle, linear regression has long been established as a convenient tool for analysing relationships. However, the wide use of linear regression has led to an overemphasis of linear relationships. In nature, most relationships are nonlinear and linearization often gives a poor approximation of reality. Furthermore, pure regression models are not capable to map the dynamics of a process. Therefore, realistic models involve the evolution in time (and space). This leads in a natural way to the formulation of differential equations. To establish the link between data and dynamical models, numerical advanced parameter identification methods have been developed in recent years. This paper demonstrates the application of these techniques to estimation problems in the field of pesticide dynamics. (7 refs., 5 figs., 2 tabs.)

  10. Simple method for quick estimation of aquifer hydrogeological parameters

    Science.gov (United States)

    Ma, C.; Li, Y. Y.

    2017-08-01

    Development of simple and accurate methods to determine the aquifer hydrogeological parameters was of importance for groundwater resources assessment and management. Aiming at the present issue of estimating aquifer parameters based on some data of the unsteady pumping test, a fitting function of Theis well function was proposed using fitting optimization method and then a unitary linear regression equation was established. The aquifer parameters could be obtained by solving coefficients of the regression equation. The application of the proposed method was illustrated, using two published data sets. By the error statistics and analysis on the pumping drawdown, it showed that the method proposed in this paper yielded quick and accurate estimates of the aquifer parameters. The proposed method could reliably identify the aquifer parameters from long distance observed drawdowns and early drawdowns. It was hoped that the proposed method in this paper would be helpful for practicing hydrogeologists and hydrologists.

  11. Compressive Parameter Estimation for Sparse Translation-Invariant Signals Using Polar Interpolation

    DEFF Research Database (Denmark)

    Fyhn, Karsten; Duarte, Marco F.; Jensen, Søren Holdt

    2015-01-01

    We propose new compressive parameter estimation algorithms that make use of polar interpolation to improve the estimator precision. Our work extends previous approaches involving polar interpolation for compressive parameter estimation in two aspects: (i) we extend the formulation from real non...... to attain good estimation precision and keep the computational complexity low. Our numerical experiments show that the proposed algorithms outperform existing approaches that either leverage polynomial interpolation or are based on a conversion to a frequency-estimation problem followed by a super...... interpolation increases the estimation precision....

  12. Estimation of Parameters in Mean-Reverting Stochastic Systems

    Directory of Open Access Journals (Sweden)

    Tianhai Tian

    2014-01-01

    Full Text Available Stochastic differential equation (SDE is a very important mathematical tool to describe complex systems in which noise plays an important role. SDE models have been widely used to study the dynamic properties of various nonlinear systems in biology, engineering, finance, and economics, as well as physical sciences. Since a SDE can generate unlimited numbers of trajectories, it is difficult to estimate model parameters based on experimental observations which may represent only one trajectory of the stochastic model. Although substantial research efforts have been made to develop effective methods, it is still a challenge to infer unknown parameters in SDE models from observations that may have large variations. Using an interest rate model as a test problem, in this work we use the Bayesian inference and Markov Chain Monte Carlo method to estimate unknown parameters in SDE models.

  13. Statistical distributions applications and parameter estimates

    CERN Document Server

    Thomopoulos, Nick T

    2017-01-01

    This book gives a description of the group of statistical distributions that have ample application to studies in statistics and probability.  Understanding statistical distributions is fundamental for researchers in almost all disciplines.  The informed researcher will select the statistical distribution that best fits the data in the study at hand.  Some of the distributions are well known to the general researcher and are in use in a wide variety of ways.  Other useful distributions are less understood and are not in common use.  The book describes when and how to apply each of the distributions in research studies, with a goal to identify the distribution that best applies to the study.  The distributions are for continuous, discrete, and bivariate random variables.  In most studies, the parameter values are not known a priori, and sample data is needed to estimate parameter values.  In other scenarios, no sample data is available, and the researcher seeks some insight that allows the estimate of ...

  14. Analysis and control of the compaction force in the composite prepreg tape winding process for rocket motor nozzles

    Directory of Open Access Journals (Sweden)

    Xiaodong He

    2017-04-01

    Full Text Available In the process of composite prepreg tape winding, the compaction force could influence the quality of winding products. According to the analysis and experiments, during the winding process of a rocket motor nozzle aft exit cone with a winding angle, there would be an error between the deposition speed of tape layers and the feeding speed of the compaction roller, which could influence the compaction force. Both a lack of compaction and overcompaction related to the feeding of the compaction roller could result in defects of winding nozzles. Thus, a flexible winding system has been developed for rocket motor nozzle winding. In the system, feeding of the compaction roller could be adjusted in real time to achieve an invariable compaction force. According to experiments, the force deformation model of the winding tape is a time-varying system. Thus, a forgetting factor recursive least square based parameter estimation proportional-integral-differential (PID controller has been developed, which could estimate the time-varying parameter and control the compaction force by adjusting the feeding of the compaction roller during the winding process. According to the experimental results, a winding nozzle with fewer voids and a smooth surface could be wounded by the invariable compaction force in the flexible winding system.

  15. Uncertainty estimation of core safety parameters using cross-correlations of covariance matrix

    International Nuclear Information System (INIS)

    Yamamoto, Akio; Yasue, Yoshihiro; Endo, Tomohiro; Kodama, Yasuhiro; Ohoka, Yasunori; Tatsumi, Masahiro

    2013-01-01

    An uncertainty reduction method for core safety parameters, for which measurement values are not obtained, is proposed. We empirically recognize that there exist some correlations among the prediction errors of core safety parameters, e.g., a correlation between the control rod worth and the assembly relative power at corresponding position. Correlations of errors among core safety parameters are theoretically estimated using the covariance of cross sections and sensitivity coefficients of core parameters. The estimated correlations of errors among core safety parameters are verified through the direct Monte Carlo sampling method. Once the correlation of errors among core safety parameters is known, we can estimate the uncertainty of a safety parameter for which measurement value is not obtained. (author)

  16. Adaptive distributed parameter and input estimation in linear parabolic PDEs

    KAUST Repository

    Mechhoud, Sarra

    2016-01-01

    In this paper, we discuss the on-line estimation of distributed source term, diffusion, and reaction coefficients of a linear parabolic partial differential equation using both distributed and interior-point measurements. First, new sufficient identifiability conditions of the input and the parameter simultaneous estimation are stated. Then, by means of Lyapunov-based design, an adaptive estimator is derived in the infinite-dimensional framework. It consists of a state observer and gradient-based parameter and input adaptation laws. The parameter convergence depends on the plant signal richness assumption, whereas the state convergence is established using a Lyapunov approach. The results of the paper are illustrated by simulation on tokamak plasma heat transport model using simulated data.

  17. Robust estimation of hydrological model parameters

    Directory of Open Access Journals (Sweden)

    A. Bárdossy

    2008-11-01

    Full Text Available The estimation of hydrological model parameters is a challenging task. With increasing capacity of computational power several complex optimization algorithms have emerged, but none of the algorithms gives a unique and very best parameter vector. The parameters of fitted hydrological models depend upon the input data. The quality of input data cannot be assured as there may be measurement errors for both input and state variables. In this study a methodology has been developed to find a set of robust parameter vectors for a hydrological model. To see the effect of observational error on parameters, stochastically generated synthetic measurement errors were applied to observed discharge and temperature data. With this modified data, the model was calibrated and the effect of measurement errors on parameters was analysed. It was found that the measurement errors have a significant effect on the best performing parameter vector. The erroneous data led to very different optimal parameter vectors. To overcome this problem and to find a set of robust parameter vectors, a geometrical approach based on Tukey's half space depth was used. The depth of the set of N randomly generated parameters was calculated with respect to the set with the best model performance (Nash-Sutclife efficiency was used for this study for each parameter vector. Based on the depth of parameter vectors, one can find a set of robust parameter vectors. The results show that the parameters chosen according to the above criteria have low sensitivity and perform well when transfered to a different time period. The method is demonstrated on the upper Neckar catchment in Germany. The conceptual HBV model was used for this study.

  18. Wind turbine state estimation

    DEFF Research Database (Denmark)

    Knudsen, Torben

    2014-01-01

    Dynamic inflow is an effect which is normally not included in the models used for wind turbine control design. Therefore, potential improvement from including this effect exists. The objective in this project is to improve the methods previously developed for this and especially to verify the res...

  19. Economics of a small wind pump system based on estimated petrol and diesel cost savings from use in Northern Nigeria

    OpenAIRE

    Ejieji, C. J.; Olayaki-Luqman, M.

    2013-01-01

    Eleven years of daily wind records were analyzed for the estimation of available wind energy for water pumping at three selected locations in Northern Nigeria, namely Jos, Kano and Sokoto. This formed the basis for investigating the economics of the use of an imported small wind pump under a deregulated energy market environment.  The estimated available energy for water pumping at the installation height of 9m was 190 kwh/m2/yr for Jos, 225 kwh/m2/yr for Kano and 348 kwh/m2/yr for Sokot...

  20. Results of large scale wind climatologically estimations

    Directory of Open Access Journals (Sweden)

    Andrea Kircsi

    2008-05-01

    Full Text Available The aim of this article is to describe theparticular field of climatology which analyzes airmovement characteristics regarding utilization of windfor energy generation. The article describes features ofwind energy potential available in Hungary compared towind conditions in other areas of the northern quartersphere in order to assist the wind energy use developmentin Hungary. Information on wind climate gives a solidbasis for financial and economic decisions ofstakeholders in the field of wind energy utilization.

  1. Targeted estimation of nuisance parameters to obtain valid statistical inference.

    Science.gov (United States)

    van der Laan, Mark J

    2014-01-01

    In order to obtain concrete results, we focus on estimation of the treatment specific mean, controlling for all measured baseline covariates, based on observing independent and identically distributed copies of a random variable consisting of baseline covariates, a subsequently assigned binary treatment, and a final outcome. The statistical model only assumes possible restrictions on the conditional distribution of treatment, given the covariates, the so-called propensity score. Estimators of the treatment specific mean involve estimation of the propensity score and/or estimation of the conditional mean of the outcome, given the treatment and covariates. In order to make these estimators asymptotically unbiased at any data distribution in the statistical model, it is essential to use data-adaptive estimators of these nuisance parameters such as ensemble learning, and specifically super-learning. Because such estimators involve optimal trade-off of bias and variance w.r.t. the infinite dimensional nuisance parameter itself, they result in a sub-optimal bias/variance trade-off for the resulting real-valued estimator of the estimand. We demonstrate that additional targeting of the estimators of these nuisance parameters guarantees that this bias for the estimand is second order and thereby allows us to prove theorems that establish asymptotic linearity of the estimator of the treatment specific mean under regularity conditions. These insights result in novel targeted minimum loss-based estimators (TMLEs) that use ensemble learning with additional targeted bias reduction to construct estimators of the nuisance parameters. In particular, we construct collaborative TMLEs (C-TMLEs) with known influence curve allowing for statistical inference, even though these C-TMLEs involve variable selection for the propensity score based on a criterion that measures how effective the resulting fit of the propensity score is in removing bias for the estimand. As a particular special

  2. Analysis on Designed Wind Speed of Wind Power Generator Based on Wind Source Estimation%基于风资源评估的风电机组设计风速分析

    Institute of Scientific and Technical Information of China (English)

    华荣芹; 张新燕; 胡立锦

    2014-01-01

    Taking topography and wind source of one wind area in Xinjiang as study object,this paper analyzes basic data of the historic wind source.By calculating and analyzing main parameters such as wind energy density,wind direction frequen-cy,direction distribution of wind energy density,yearly change of wind speed,turbulence intensity and yearly generating ca-pacity,it optimizes and ensures designed wind speed and power of the wind power generator in favor of this area.By exem-plification,it analyzes impact of wake flow and points out problems to be noted for model selection and configuration for the wind power generator.%以新疆某风区的地形、风资源情况为研究对象,分析其历史风资源基础数据。通过计算、分析风能密度、风向频率及风能密度的方向分布、风速年变化、湍流强度、年发电量等主要参数,优化和确定有利于该地区的风力机设计风速和功率。通过例证分析了尾流的影响,指出进行风力发电机组选型和配置时应注意的问题。

  3. Offshore wind investments – Realism about cost developments is necessary

    International Nuclear Information System (INIS)

    Schwanitz, Valeria Jana; Wierling, August

    2016-01-01

    Data available from the recent boom in European offshore wind investments contradict widely held expectations about a decline in costs per kW. Our review shows that scenario projections for investment costs are systematically flawed by over-optimistic assumptions. Contrasting offshore wind technology with onshore wind and nuclear power, we argue that offshore wind could be a candidate for negative learning since a trend towards more complex OWP (offshore wind parks) exists and uncertainty remains high. We estimate technical uncertainty and input cost uncertainty to calculate whether investments in offshore wind technology are profitable today. Applying a real option model to two reference plants using empirically derived parameter values, we allow for sunk cost and the possibility to abandon the investment. We find that for a large parameter range, investments are not profitable, even with substantial support such as feed-in tariffs under the German Energy Act. Therefore, policy incentives for building larger and more complex offshore wind parks bear a high risk to fail in their aim of bringing down investment costs. Policies that instead incentivize the optimization of offshore wind technology – in particular by increasing the load factor and material efficiency and bringing down decommissioning costs – are more sustainable. - Highlights: • We review offshore wind power investments. • Contrary to expectations costs increase. • It is unlikely to see a turn in the near future as complexity is growing. • We deploy an empirically based real option model. • Investments are not profitable across a large parameter range.

  4. Maximum Wind Power Tracking of Doubly Fed Wind Turbine System Based on Adaptive Gain Second-Order Sliding Mode

    Directory of Open Access Journals (Sweden)

    Hongchang Sun

    2018-01-01

    Full Text Available This paper proposes an adaptive gain second-order sliding mode control strategy to track optimal electromagnetic torque and regulate reactive power of doubly fed wind turbine system. Firstly, wind turbine aerodynamic characteristics and doubly fed induction generator (DFIG modeling are presented. Then, electromagnetic torque error and reactive power error are chosen as sliding variables, and fixed gain super-twisting sliding mode control scheme is designed. Considering that uncertainty upper bound is unknown and is hard to be estimated in actual doubly fed wind turbine system, a gain scheduled law is proposed to compel control parameters variation according to uncertainty upper bound real-time. Adaptive gain second-order sliding mode rotor voltage control method is constructed in detail and finite time stability of doubly fed wind turbine control system is strictly proved. The superiority and robustness of the proposed control scheme are finally evaluated on a 1.5 MW DFIG wind turbine system.

  5. minimum variance estimation of yield parameters of rubber tree

    African Journals Online (AJOL)

    2013-03-01

    Mar 1, 2013 ... It is our opinion that Kalman filter is a robust estimator of the ... Kalman filter, parameter estimation, rubber clones, Chow failure test, autocorrelation, STAMP, data ...... Mills, T.C. Modelling Current Temperature Trends.

  6. Parameter Estimation of Multiple Frequency-Hopping Signals with Two Sensors

    Directory of Open Access Journals (Sweden)

    Le Zuo

    2018-04-01

    Full Text Available This paper essentially focuses on parameter estimation of multiple wideband emitting sources with time-varying frequencies, such as two-dimensional (2-D direction of arrival (DOA and signal sorting, with a low-cost circular synthetic array (CSA consisting of only two rotating sensors. Our basic idea is to decompose the received data, which is a superimposition of phase measurements from multiple sources into separated groups and separately estimate the DOA associated with each source. Motivated by joint parameter estimation, we propose to adopt the expectation maximization (EM algorithm in this paper; our method involves two steps, namely, the expectation-step (E-step and the maximization (M-step. In the E-step, the correspondence of each signal with its emitting source is found. Then, in the M-step, the maximum-likelihood (ML estimates of the DOA parameters are obtained. These two steps are iteratively and alternatively executed to jointly determine the DOAs and sort multiple signals. Closed-form DOA estimation formulae are developed by ML estimation based on phase data, which also realize an optimal estimation. Directional ambiguity is also addressed by another ML estimation method based on received complex responses. The Cramer-Rao lower bound is derived for understanding the estimation accuracy and performance comparison. The verification of the proposed method is demonstrated with simulations.

  7. Automatic smoothing parameter selection in GAMLSS with an application to centile estimation.

    Science.gov (United States)

    Rigby, Robert A; Stasinopoulos, Dimitrios M

    2014-08-01

    A method for automatic selection of the smoothing parameters in a generalised additive model for location, scale and shape (GAMLSS) model is introduced. The method uses a P-spline representation of the smoothing terms to express them as random effect terms with an internal (or local) maximum likelihood estimation on the predictor scale of each distribution parameter to estimate its smoothing parameters. This provides a fast method for estimating multiple smoothing parameters. The method is applied to centile estimation where all four parameters of a distribution for the response variable are modelled as smooth functions of a transformed explanatory variable x This allows smooth modelling of the location, scale, skewness and kurtosis parameters of the response variable distribution as functions of x. © The Author(s) 2013 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

  8. Estimation of G-renewal process parameters as an ill-posed inverse problem

    International Nuclear Information System (INIS)

    Krivtsov, V.; Yevkin, O.

    2013-01-01

    Statistical estimation of G-renewal process parameters is an important estimation problem, which has been considered by many authors. We view this problem from the standpoint of a mathematically ill-posed, inverse problem (the solution is not unique and/or is sensitive to statistical error) and propose a regularization approach specifically suited to the G-renewal process. Regardless of the estimation method, the respective objective function usually involves parameters of the underlying life-time distribution and simultaneously the restoration parameter. In this paper, we propose to regularize the problem by decoupling the estimation of the aforementioned parameters. Using a simulation study, we show that the resulting estimation/extrapolation accuracy of the proposed method is considerably higher than that of the existing methods

  9. Joint Multi-Fiber NODDI Parameter Estimation and Tractography using the Unscented Information Filter

    Directory of Open Access Journals (Sweden)

    Yogesh eRathi

    2016-04-01

    Full Text Available Tracing white matter fiber bundles is an integral part of analyzing brain connectivity. An accurate estimate of the underlying tissue parameters is also paramount in several neuroscience applications. In this work, we propose to use a joint fiber model estimation and tractography algorithm that uses the NODDI (neurite orientation dispersion diffusion imaging model to estimate fiber orientation dispersion consistently and smoothly along the fiber tracts along with estimating the intracellular and extracellular volume fractions from the diffusion signal. While the NODDI model has been used in earlier works to estimate the microstructural parameters at each voxel independently, for the first time, we propose to integrate it into a tractography framework. We extend this framework to estimate the NODDI parameters for two crossing fibers, which is imperative to trace fiber bundles through crossings as well as to estimate the microstructural parameters for each fiber bundle separately. We propose to use the unscented information filter (UIF to accurately estimate the model parameters and perform tractography. The proposed approach has significant computational performance improvements as well as numerical robustness over the unscented Kalman filter (UKF. Our method not only estimates the confidence in the estimated parameters via the covariance matrix, but also provides the Fisher-information matrix of the state variables (model parameters, which can be quite useful to measure model complexity. Results from in-vivo human brain data sets demonstrate the ability of our algorithm to trace through crossing fiber regions, while estimating orientation dispersion and other biophysical model parameters in a consistent manner along the tracts.

  10. Parameter study of electric power production in wind farms - experiments using two model scale wind turbines

    OpenAIRE

    Ceccotti, Clio

    2015-01-01

    Wind farms are widely developed even if several unsolved problems need to be faced. The rotor-wake interaction involves different physical phenomena, not yet fully understood, directly affecting the overall wind farm power production. Numerical models and engineering rules have always been used to design wind farm layout but a spread between power predictions and results is verified. In this context wind energy research assumes a "back to basic" approach, by means of wind tunne...

  11. Estimation of octanol/water partition coefficients using LSER parameters

    Science.gov (United States)

    Luehrs, Dean C.; Hickey, James P.; Godbole, Kalpana A.; Rogers, Tony N.

    1998-01-01

    The logarithms of octanol/water partition coefficients, logKow, were regressed against the linear solvation energy relationship (LSER) parameters for a training set of 981 diverse organic chemicals. The standard deviation for logKow was 0.49. The regression equation was then used to estimate logKow for a test of 146 chemicals which included pesticides and other diverse polyfunctional compounds. Thus the octanol/water partition coefficient may be estimated by LSER parameters without elaborate software but only moderate accuracy should be expected.

  12. Analysis of wind energy generation possibilities with various rotor types at disadvantageous wind condition zones

    Science.gov (United States)

    Bieniek, Andrzej

    2017-10-01

    The paper describe possibilities of energy generation using various rotor types but especially with multi-blade wind engine operates in the areas with unfavourable wind condition. The paper presents also wind energy conversion estimation results presented based on proposed solution of multi-blade wind turbine of outer diameter of 4 m. Based on the wind distribution histogram from the disadvantage wind condition zones (city of Basel) and taking into account design and estimated operating indexes of the considered wind engine rotor an annual energy generation was estimated. Also theoretical energy generation using various types of wind turbines operates at disadvantage wind conditions zones were estimated and compared. The conducted analysis shows that introduction of multi-blade wind rotor instead of the most popular 3- blades or vertical axis rotors results of about 5% better energy generation. Simultaneously there are energy production also at very disadvantages wind condition at wind speed lower then 4 m s-1. Based on considered construction of multi-blade wind engine the rise of rotor mounting height from 10 to 30 m results with more then 300 % better results in terms of electric energy generation.

  13. Analysis of wind energy generation possibilities with various rotor types at disadvantageous wind condition zones

    Directory of Open Access Journals (Sweden)

    Bieniek Andrzej

    2017-01-01

    Full Text Available The paper describe possibilities of energy generation using various rotor types but especially with multi-blade wind engine operates in the areas with unfavourable wind condition. The paper presents also wind energy conversion estimation results presented based on proposed solution of multi-blade wind turbine of outer diameter of 4 m. Based on the wind distribution histogram from the disadvantage wind condition zones (city of Basel and taking into account design and estimated operating indexes of the considered wind engine rotor an annual energy generation was estimated. Also theoretical energy generation using various types of wind turbines operates at disadvantage wind conditions zones were estimated and compared. The conducted analysis shows that introduction of multi-blade wind rotor instead of the most popular 3- blades or vertical axis rotors results of about 5% better energy generation. Simultaneously there are energy production also at very disadvantages wind condition at wind speed lower then 4 ms-1. Based on considered construction of multi-blade wind engine the rise of rotor mounting height from 10 to 30 m results with more then 300 % better results in terms of electric energy generation.

  14. MCMC for parameters estimation by bayesian approach

    International Nuclear Information System (INIS)

    Ait Saadi, H.; Ykhlef, F.; Guessoum, A.

    2011-01-01

    This article discusses the parameter estimation for dynamic system by a Bayesian approach associated with Markov Chain Monte Carlo methods (MCMC). The MCMC methods are powerful for approximating complex integrals, simulating joint distributions, and the estimation of marginal posterior distributions, or posterior means. The MetropolisHastings algorithm has been widely used in Bayesian inference to approximate posterior densities. Calibrating the proposal distribution is one of the main issues of MCMC simulation in order to accelerate the convergence.

  15. Estimating model parameters in nonautonomous chaotic systems using synchronization

    International Nuclear Information System (INIS)

    Yang, Xiaoli; Xu, Wei; Sun, Zhongkui

    2007-01-01

    In this Letter, a technique is addressed for estimating unknown model parameters of multivariate, in particular, nonautonomous chaotic systems from time series of state variables. This technique uses an adaptive strategy for tracking unknown parameters in addition to a linear feedback coupling for synchronizing systems, and then some general conditions, by means of the periodic version of the LaSalle invariance principle for differential equations, are analytically derived to ensure precise evaluation of unknown parameters and identical synchronization between the concerned experimental system and its corresponding receiver one. Exemplifies are presented by employing a parametrically excited 4D new oscillator and an additionally excited Ueda oscillator. The results of computer simulations reveal that the technique not only can quickly track the desired parameter values but also can rapidly respond to changes in operating parameters. In addition, the technique can be favorably robust against the effect of noise when the experimental system is corrupted by bounded disturbance and the normalized absolute error of parameter estimation grows almost linearly with the cutoff value of noise strength in simulation

  16. Adaptive distributed parameter and input estimation in linear parabolic PDEs

    KAUST Repository

    Mechhoud, Sarra

    2016-01-01

    First, new sufficient identifiability conditions of the input and the parameter simultaneous estimation are stated. Then, by means of Lyapunov-based design, an adaptive estimator is derived in the infinite-dimensional framework. It consists of a state observer and gradient-based parameter and input adaptation laws. The parameter convergence depends on the plant signal richness assumption, whereas the state convergence is established using a Lyapunov approach. The results of the paper are illustrated by simulation on tokamak plasma heat transport model using simulated data.

  17. Observation of chorus waves by the Van Allen Probes: dependence on solar wind parameters and scale size

    Science.gov (United States)

    Aryan, H.; Sibeck, D. G.; Balikhin, M. A.; Agapitov, O. V.; Kletzing, C.

    2016-12-01

    Highly energetic electrons in the Earth's Van Allen radiation belts can cause serious damage to spacecraft electronic systems, and affect the atmospheric composition if they precipitate into the upper atmosphere. Whistler mode chorus waves have attracted significant attention in recent decades for their crucial role in the acceleration and loss of energetic electrons that ultimately change the dynamics of the radiation belts. The distribution of these waves in the inner magnetosphere is commonly presented as a function of geomagnetic activity. However, geomagnetic indices are non-specific parameters that are compiled from imperfectly covered ground based measurements. The present study uses wave data from the two Van Allen Probes to present the distribution of lower band chorus waves not only as functions of single geomagnetic index and solar wind parameters, but also as functions of combined parameters. Also the current study takes advantage of the unique equatorial orbit of the Van Allen Probes to estimate the average scale size of chorus wave packets, during close separations between the two spacecraft, as a function of radial distance, magnetic latitude, and geomagnetic activity respectively. Results show that the average scale size of chorus wave packets is approximately 1300 - 2300 km. The results also show that the inclusion of combined parameters can provide better representation of the chorus wave distributions in the inner magnetosphere, and therefore can further improve our knowledge of the acceleration and loss of radiation belt electrons.

  18. Parameter estimation and determinability analysis applied to Drosophila gap gene circuits

    Directory of Open Access Journals (Sweden)

    Jaeger Johannes

    2008-09-01

    Full Text Available Abstract Background Mathematical modeling of real-life processes often requires the estimation of unknown parameters. Once the parameters are found by means of optimization, it is important to assess the quality of the parameter estimates, especially if parameter values are used to draw biological conclusions from the model. Results In this paper we describe how the quality of parameter estimates can be analyzed. We apply our methodology to assess parameter determinability for gene circuit models of the gap gene network in early Drosophila embryos. Conclusion Our analysis shows that none of the parameters of the considered model can be determined individually with reasonable accuracy due to correlations between parameters. Therefore, the model cannot be used as a tool to infer quantitative regulatory weights. On the other hand, our results show that it is still possible to draw reliable qualitative conclusions on the regulatory topology of the gene network. Moreover, it improves previous analyses of the same model by allowing us to identify those interactions for which qualitative conclusions are reliable, and those for which they are ambiguous.

  19. Estimation of delays and other parameters in nonlinear functional differential equations

    Science.gov (United States)

    Banks, H. T.; Lamm, P. K. D.

    1983-01-01

    A spline-based approximation scheme for nonlinear nonautonomous delay differential equations is discussed. Convergence results (using dissipative type estimates on the underlying nonlinear operators) are given in the context of parameter estimation problems which include estimation of multiple delays and initial data as well as the usual coefficient-type parameters. A brief summary of some of the related numerical findings is also given.

  20. Nonparametric estimation of location and scale parameters

    KAUST Repository

    Potgieter, C.J.

    2012-12-01

    Two random variables X and Y belong to the same location-scale family if there are constants μ and σ such that Y and μ+σX have the same distribution. In this paper we consider non-parametric estimation of the parameters μ and σ under minimal assumptions regarding the form of the distribution functions of X and Y. We discuss an approach to the estimation problem that is based on asymptotic likelihood considerations. Our results enable us to provide a methodology that can be implemented easily and which yields estimators that are often near optimal when compared to fully parametric methods. We evaluate the performance of the estimators in a series of Monte Carlo simulations. © 2012 Elsevier B.V. All rights reserved.

  1. Bayesian estimation of parameters in a regional hydrological model

    Directory of Open Access Journals (Sweden)

    K. Engeland

    2002-01-01

    Full Text Available This study evaluates the applicability of the distributed, process-oriented Ecomag model for prediction of daily streamflow in ungauged basins. The Ecomag model is applied as a regional model to nine catchments in the NOPEX area, using Bayesian statistics to estimate the posterior distribution of the model parameters conditioned on the observed streamflow. The distribution is calculated by Markov Chain Monte Carlo (MCMC analysis. The Bayesian method requires formulation of a likelihood function for the parameters and three alternative formulations are used. The first is a subjectively chosen objective function that describes the goodness of fit between the simulated and observed streamflow, as defined in the GLUE framework. The second and third formulations are more statistically correct likelihood models that describe the simulation errors. The full statistical likelihood model describes the simulation errors as an AR(1 process, whereas the simple model excludes the auto-regressive part. The statistical parameters depend on the catchments and the hydrological processes and the statistical and the hydrological parameters are estimated simultaneously. The results show that the simple likelihood model gives the most robust parameter estimates. The simulation error may be explained to a large extent by the catchment characteristics and climatic conditions, so it is possible to transfer knowledge about them to ungauged catchments. The statistical models for the simulation errors indicate that structural errors in the model are more important than parameter uncertainties. Keywords: regional hydrological model, model uncertainty, Bayesian analysis, Markov Chain Monte Carlo analysis

  2. Estimation of common cause failure parameters with periodic tests

    Energy Technology Data Exchange (ETDEWEB)

    Barros, Anne [Institut Charles Delaunay - Universite de technologie de Troyes - FRE CNRS 2848, 12, rue Marie Curie - BP 2060 -10010 Troyes cedex (France)], E-mail: anne.barros@utt.fr; Grall, Antoine [Institut Charles Delaunay - Universite de technologie de Troyes - FRE CNRS 2848, 12, rue Marie Curie - BP 2060 -10010 Troyes cedex (France); Vasseur, Dominique [Electricite de France, EDF R and D - Industrial Risk Management Department 1, av. du General de Gaulle- 92141 Clamart (France)

    2009-04-15

    In the specific case of safety systems, CCF parameters estimators for standby components depend on the periodic test schemes. Classically, the testing schemes are either staggered (alternation of tests on redundant components) or non-staggered (all components are tested at the same time). In reality, periodic tests schemes performed on safety components are more complex and combine staggered tests, when the plant is in operation, to non-staggered tests during maintenance and refueling outage periods of the installation. Moreover, the CCF parameters estimators described in the US literature are derived in a consistent way with US Technical Specifications constraints that do not apply on the French Nuclear Power Plants for staggered tests on standby components. Given these issues, the evaluation of CCF parameters from the operating feedback data available within EDF implies the development of methodologies that integrate the testing schemes specificities. This paper aims to formally propose a solution for the estimation of CCF parameters given two distinct difficulties respectively related to a mixed testing scheme and to the consistency with EDF's specific practices inducing systematic non-simultaneity of the observed failures in a staggered testing scheme.

  3. Consistent Parameter and Transfer Function Estimation using Context Free Grammars

    Science.gov (United States)

    Klotz, Daniel; Herrnegger, Mathew; Schulz, Karsten

    2017-04-01

    This contribution presents a method for the inference of transfer functions for rainfall-runoff models. Here, transfer functions are defined as parametrized (functional) relationships between a set of spatial predictors (e.g. elevation, slope or soil texture) and model parameters. They are ultimately used for estimation of consistent, spatially distributed model parameters from a limited amount of lumped global parameters. Additionally, they provide a straightforward method for parameter extrapolation from one set of basins to another and can even be used to derive parameterizations for multi-scale models [see: Samaniego et al., 2010]. Yet, currently an actual knowledge of the transfer functions is often implicitly assumed. As a matter of fact, for most cases these hypothesized transfer functions can rarely be measured and often remain unknown. Therefore, this contribution presents a general method for the concurrent estimation of the structure of transfer functions and their respective (global) parameters. Note, that by consequence an estimation of the distributed parameters of the rainfall-runoff model is also undertaken. The method combines two steps to achieve this. The first generates different possible transfer functions. The second then estimates the respective global transfer function parameters. The structural estimation of the transfer functions is based on the context free grammar concept. Chomsky first introduced context free grammars in linguistics [Chomsky, 1956]. Since then, they have been widely applied in computer science. But, to the knowledge of the authors, they have so far not been used in hydrology. Therefore, the contribution gives an introduction to context free grammars and shows how they can be constructed and used for the structural inference of transfer functions. This is enabled by new methods from evolutionary computation, such as grammatical evolution [O'Neill, 2001], which make it possible to exploit the constructed grammar as a

  4. Wind energy potential assessment of Cameroon’s coastal regions for the installation of an onshore wind farm

    Directory of Open Access Journals (Sweden)

    Nkongho Ayuketang Arreyndip

    2016-11-01

    Full Text Available For the future installation of a wind farm in Cameroon, the wind energy potentials of three of Cameroon’s coastal cities (Kribi, Douala and Limbe are assessed using NASA average monthly wind data for 31 years (1983–2013 and compared through Weibull statistics. The Weibull parameters are estimated by the method of maximum likelihood, the mean power densities, the maximum energy carrying wind speeds and the most probable wind speeds are also calculated and compared over these three cities. Finally, the cumulative wind speed distributions over the wet and dry seasons are also analyzed. The results show that the shape and scale parameters for Kribi, Douala and Limbe are 2.9 and 2.8, 3.9 and 1.8 and 3.08 and 2.58, respectively. The mean power densities through Weibull analysis for Kribi, Douala and Limbe are 33.7 W/m2, 8.0 W/m2 and 25.42 W/m2, respectively. Kribi’s most probable wind speed and maximum energy carrying wind speed was found to be 2.42 m/s and 3.35 m/s, 2.27 m/s and 3.03 m/s for Limbe and 1.67 m/s and 2.0 m/s for Douala, respectively. Analysis of the wind speed and hence power distribution over the wet and dry seasons shows that in the wet season, August is the windiest month for Douala and Limbe while September is the windiest month for Kribi while in the dry season, March is the windiest month for Douala and Limbe while February is the windiest month for Kribi. In terms of mean power density, most probable wind speed and wind speed carrying maximum energy, Kribi shows to be the best site for the installation of a wind farm. Generally, the wind speeds at all three locations seem quite low, average wind speeds of all the three studied locations fall below 4.0m/s which is far below the cut-in wind speed of many modern wind turbines. However we recommend the use of low cut-in speed wind turbines like the Savonius for stand alone low energy needs

  5. Parameter and state estimation in nonlinear dynamical systems

    Science.gov (United States)

    Creveling, Daniel R.

    This thesis is concerned with the problem of state and parameter estimation in nonlinear systems. The need to evaluate unknown parameters in models of nonlinear physical, biophysical and engineering systems occurs throughout the development of phenomenological or reduced models of dynamics. When verifying and validating these models, it is important to incorporate information from observations in an efficient manner. Using the idea of synchronization of nonlinear dynamical systems, this thesis develops a framework for presenting data to a candidate model of a physical process in a way that makes efficient use of the measured data while allowing for estimation of the unknown parameters in the model. The approach presented here builds on existing work that uses synchronization as a tool for parameter estimation. Some critical issues of stability in that work are addressed and a practical framework is developed for overcoming these difficulties. The central issue is the choice of coupling strength between the model and data. If the coupling is too strong, the model will reproduce the measured data regardless of the adequacy of the model or correctness of the parameters. If the coupling is too weak, nonlinearities in the dynamics could lead to complex dynamics rendering any cost function comparing the model to the data inadequate for the determination of model parameters. Two methods are introduced which seek to balance the need for coupling with the desire to allow the model to evolve in its natural manner without coupling. One method, 'balanced' synchronization, adds to the synchronization cost function a requirement that the conditional Lyapunov exponents of the model system, conditioned on being driven by the data, remain negative but small in magnitude. Another method allows the coupling between the data and the model to vary in time according to a specific form of differential equation. The coupling dynamics is damped to allow for a tendency toward zero coupling

  6. New methodologies for calculation of flight parameters on reduced scale wings models in wind tunnel =

    Science.gov (United States)

    Ben Mosbah, Abdallah

    In order to improve the qualities of wind tunnel tests, and the tools used to perform aerodynamic tests on aircraft wings in the wind tunnel, new methodologies were developed and tested on rigid and flexible wings models. A flexible wing concept is consists in replacing a portion (lower and/or upper) of the skin with another flexible portion whose shape can be changed using an actuation system installed inside of the wing. The main purpose of this concept is to improve the aerodynamic performance of the aircraft, and especially to reduce the fuel consumption of the airplane. Numerical and experimental analyses were conducted to develop and test the methodologies proposed in this thesis. To control the flow inside the test sections of the Price-Paidoussis wind tunnel of LARCASE, numerical and experimental analyses were performed. Computational fluid dynamics calculations have been made in order to obtain a database used to develop a new hybrid methodology for wind tunnel calibration. This approach allows controlling the flow in the test section of the Price-Paidoussis wind tunnel. For the fast determination of aerodynamic parameters, new hybrid methodologies were proposed. These methodologies were used to control flight parameters by the calculation of the drag, lift and pitching moment coefficients and by the calculation of the pressure distribution around an airfoil. These aerodynamic coefficients were calculated from the known airflow conditions such as angles of attack, the mach and the Reynolds numbers. In order to modify the shape of the wing skin, electric actuators were installed inside the wing to get the desired shape. These deformations provide optimal profiles according to different flight conditions in order to reduce the fuel consumption. A controller based on neural networks was implemented to obtain desired displacement actuators. A metaheuristic algorithm was used in hybridization with neural networks, and support vector machine approaches and their

  7. Wind waves in the Black Sea: results of a hindcast study

    Science.gov (United States)

    Arkhipkin, V. S.; Gippius, F. N.; Koltermann, K. P.; Surkova, G. V.

    2014-11-01

    In this study we describe the wind wave fields in the Black Sea. The general aims of the work were the estimation of statistical wave parameters and the assessment of interannual and seasonal wave parameter variability. The domain of this study was the entire Black Sea. Wave parameters were calculated by means of the SWAN wave model on a 5 × 5 km rectangular grid. Initial conditions (wind speed and direction) for the period between 1949 and 2010 were derived from the NCEP/NCAR reanalysis. According to our calculations the average significant wave height on the Black Sea does not exceed 0.7 m. Areas of most significant heavy sea are the southwestern and the northeastern parts of the sea as expressed in the spatial distribution of significant wave heights, wave lengths and periods. Besides, long-term annual variations of wave parameters were estimated. Thus, linear trends of the annual total duration of storms and of their quantity are nearly stable over the hindcast period. However, an intensification of storm activity is observed in the 1960s-1970s.

  8. Estimating the impacts of wind power on power systems—summary of IEA Wind collaboration

    Science.gov (United States)

    Holttinen, Hannele

    2008-04-01

    Adding wind power to power systems will have beneficial impacts by reducing the emissions of electricity production and reducing the operational costs of the power system as less fuel is consumed in conventional power plants. Wind power will also have a capacity value to a power system. However, possible negative impacts will have to be assessed to make sure that they will only offset a small part of the benefits and also to ensure the security of the power system operation. An international forum for the exchange of knowledge of power system impacts of wind power has been formed under the IEA Implementing Agreement on Wind Energy. The Task 'Design and Operation of Power Systems with Large Amounts of Wind Power' is analyzing existing case studies from different power systems. There are a multitude of studies completed and ongoing related to the cost of wind integration. However, the results are not easy to compare. This paper describes the general issues of wind power impacts on power systems and presents a comparison of results from ten case studies on increased balancing needs due to wind power.

  9. Estimating the impacts of wind power on power systems-summary of IEA Wind collaboration

    International Nuclear Information System (INIS)

    Holttinen, Hannele

    2008-01-01

    Adding wind power to power systems will have beneficial impacts by reducing the emissions of electricity production and reducing the operational costs of the power system as less fuel is consumed in conventional power plants. Wind power will also have a capacity value to a power system. However, possible negative impacts will have to be assessed to make sure that they will only offset a small part of the benefits and also to ensure the security of the power system operation. An international forum for the exchange of knowledge of power system impacts of wind power has been formed under the IEA Implementing Agreement on Wind Energy. The Task 'Design and Operation of Power Systems with Large Amounts of Wind Power' is analyzing existing case studies from different power systems. There are a multitude of studies completed and ongoing related to the cost of wind integration. However, the results are not easy to compare. This paper describes the general issues of wind power impacts on power systems and presents a comparison of results from ten case studies on increased balancing needs due to wind power

  10. Parameter estimation for lithium ion batteries

    Science.gov (United States)

    Santhanagopalan, Shriram

    With an increase in the demand for lithium based batteries at the rate of about 7% per year, the amount of effort put into improving the performance of these batteries from both experimental and theoretical perspectives is increasing. There exist a number of mathematical models ranging from simple empirical models to complicated physics-based models to describe the processes leading to failure of these cells. The literature is also rife with experimental studies that characterize the various properties of the system in an attempt to improve the performance of lithium ion cells. However, very little has been done to quantify the experimental observations and relate these results to the existing mathematical models. In fact, the best of the physics based models in the literature show as much as 20% discrepancy when compared to experimental data. The reasons for such a big difference include, but are not limited to, numerical complexities involved in extracting parameters from experimental data and inconsistencies in interpreting directly measured values for the parameters. In this work, an attempt has been made to implement simplified models to extract parameter values that accurately characterize the performance of lithium ion cells. The validity of these models under a variety of experimental conditions is verified using a model discrimination procedure. Transport and kinetic properties are estimated using a non-linear estimation procedure. The initial state of charge inside each electrode is also maintained as an unknown parameter, since this value plays a significant role in accurately matching experimental charge/discharge curves with model predictions and is not readily known from experimental data. The second part of the dissertation focuses on parameters that change rapidly with time. For example, in the case of lithium ion batteries used in Hybrid Electric Vehicle (HEV) applications, the prediction of the State of Charge (SOC) of the cell under a variety of

  11. Nonlinear systems time-varying parameter estimation: Application to induction motors

    Energy Technology Data Exchange (ETDEWEB)

    Kenne, Godpromesse [Laboratoire d' Automatique et d' Informatique Appliquee (LAIA), Departement de Genie Electrique, IUT FOTSO Victor, Universite de Dschang, B.P. 134 Bandjoun (Cameroon); Ahmed-Ali, Tarek [Ecole Nationale Superieure des Ingenieurs des Etudes et Techniques d' Armement (ENSIETA), 2 Rue Francois Verny, 29806 Brest Cedex 9 (France); Lamnabhi-Lagarrigue, F. [Laboratoire des Signaux et Systemes (L2S), C.N.R.S-SUPELEC, Universite Paris XI, 3 Rue Joliot Curie, 91192 Gif-sur-Yvette (France); Arzande, Amir [Departement Energie, Ecole Superieure d' Electricite-SUPELEC, 3 Rue Joliot Curie, 91192 Gif-sur-Yvette (France)

    2008-11-15

    In this paper, an algorithm for time-varying parameter estimation for a large class of nonlinear systems is presented. The proof of the convergence of the estimates to their true values is achieved using Lyapunov theories and does not require that the classical persistent excitation condition be satisfied by the input signal. Since the induction motor (IM) is widely used in several industrial sectors, the algorithm developed is potentially useful for adjusting the controller parameters of variable speed drives. The method proposed is simple and easily implementable in real-time. The application of this approach to on-line estimation of the rotor resistance of IM shows a rapidly converging estimate in spite of measurement noise, discretization effects, parameter uncertainties (e.g. inaccuracies on motor inductance values) and modeling inaccuracies. The robustness analysis for this IM application also revealed that the proposed scheme is insensitive to the stator resistance variations within a wide range. The merits of the proposed algorithm in the case of on-line time-varying rotor resistance estimation are demonstrated via experimental results in various operating conditions of the induction motor. The experimental results obtained demonstrate that the application of the proposed algorithm to update on-line the parameters of an adaptive controller (e.g. IM and synchronous machines adaptive control) can improve the efficiency of the industrial process. The other interesting features of the proposed method include fault detection/estimation and adaptive control of IM and synchronous machines. (author)

  12. An Integrated Approach To Offshore Wind Energy Assessment: Great Lakes 3D Wind Experiment

    Energy Technology Data Exchange (ETDEWEB)

    Barthelmie, R. J. [Cornell Univ., Ithaca, NY (United States). Sibley School of Mechanical & Aerospace Engineering; Pryor, S. C. [Cornell Univ., Ithaca, NY (United States). Dept. of Earth and Atmospheric Sciences

    2017-09-18

    This grant supported fundamental research into the characterization of flow parameters of relevance to the wind energy industry focused on offshore and the coastal zone. A major focus of the project was application of the latest generation of remote sensing instrumentation and also integration of measurements and numerical modeling to optimize characterization of time-evolving atmospheric flow parameters in 3-D. Our research developed a new data-constrained Wind Atlas for the Great Lakes, and developed new insights into flow parameters in heterogeneous environments. Four experiments were conducted during the project: At a large operating onshore wind farm in May 2012; At the National Renewable Energy Laboratory National Wind Technology Center (NREL NWTC) during February 2013; At the shoreline of Lake Erie in May 2013; and At the Wind Energy Institute of Canada on Prince Edward Island in May 2015. The experiment we conducted in the coastal zone of Lake Erie indicated very complex flow fields and the frequent presence of upward momentum fluxes and resulting distortion of the wind speed profile at turbine relevant heights due to swells in the Great Lakes. Additionally, our data (and modeling) indicate the frequent presence of low level jets at 600 m height over the Lake and occasions when the wind speed profile across the rotor plane may be impacted by this phenomenon. Experimental data and modeling of the fourth experiment on Prince Edward Island showed that at 10-14 m escarpment adjacent to long-overseas fetch the zone of wind speed decrease before the terrain feature and the increase at (and slightly downwind of) the escarpment is ~3–5% at turbine hub-heights. Additionally, our measurements were used to improve methods to compute the uncertainty in lidar-derived flow properties and to optimize lidar-scanning strategies. For example, on the basis of the experimental data we collected plus those from one of our research partners we advanced a new methodology to

  13. Accuracy and sensitivity analysis on seismic anisotropy parameter estimation

    Science.gov (United States)

    Yan, Fuyong; Han, De-Hua

    2018-04-01

    There is significant uncertainty in measuring the Thomsen’s parameter δ in laboratory even though the dimensions and orientations of the rock samples are known. It is expected that more challenges will be encountered in the estimating of the seismic anisotropy parameters from field seismic data. Based on Monte Carlo simulation of vertical transversely isotropic layer cake model using the database of laboratory anisotropy measurement from the literature, we apply the commonly used quartic non-hyperbolic reflection moveout equation to estimate the seismic anisotropy parameters and test its accuracy and sensitivities to the source-receive offset, vertical interval velocity error and time picking error. The testing results show that the methodology works perfectly for noise-free synthetic data with short spread length. However, this method is extremely sensitive to the time picking error caused by mild random noises, and it requires the spread length to be greater than the depth of the reflection event. The uncertainties increase rapidly for the deeper layers and the estimated anisotropy parameters can be very unreliable for a layer with more than five overlain layers. It is possible that an isotropic formation can be misinterpreted as a strong anisotropic formation. The sensitivity analysis should provide useful guidance on how to group the reflection events and build a suitable geological model for anisotropy parameter inversion.

  14. Estimation of wind speeds inside Super Typhoon Nepartak from AMSR2 low-frequency brightness temperatures

    Science.gov (United States)

    Zhang, Lei; Yin, Xiaobin; Shi, Hanqing; Wang, Zhenzhan; Xu, Qing

    2018-04-01

    Accurate estimations of typhoon-level winds are highly desired over the western Pacific Ocean. A wind speed retrieval algorithm is used to retrieve the wind speeds within Super Typhoon Nepartak (2016) using 6.9- and 10.7-GHz brightness temperatures from the Japanese Advanced Microwave Scanning Radiometer 2 (AMSR2) sensor on board the Global Change Observation Mission-Water 1 (GCOM-W1) satellite. The results show that the retrieved wind speeds clearly represent the intensification process of Super Typhoon Nepartak. A good agreement is found between the retrieved wind speeds and the Soil Moisture Active Passive wind speed product. The mean bias is 0.51 m/s, and the root-mean-square difference is 1.93 m/s between them. The retrieved maximum wind speeds are 59.6 m/s at 04:45 UTC on July 6 and 71.3 m/s at 16:58 UTC on July 6. The two results demonstrate good agreement with the results reported by the China Meteorological Administration and the Joint Typhoon Warning Center. In addition, Feng-Yun 2G (FY-2G) satellite infrared images, Feng-Yun 3C (FY-3C) microwave atmospheric sounder data, and AMSR2 brightness temperature images are also used to describe the development and structure of Super Typhoon Nepartak.

  15. Estimation of Compaction Parameters Based on Soil Classification

    Science.gov (United States)

    Lubis, A. S.; Muis, Z. A.; Hastuty, I. P.; Siregar, I. M.

    2018-02-01

    Factors that must be considered in compaction of the soil works were the type of soil material, field control, maintenance and availability of funds. Those problems then raised the idea of how to estimate the density of the soil with a proper implementation system, fast, and economical. This study aims to estimate the compaction parameter i.e. the maximum dry unit weight (γ dmax) and optimum water content (Wopt) based on soil classification. Each of 30 samples were being tested for its properties index and compaction test. All of the data’s from the laboratory test results, were used to estimate the compaction parameter values by using linear regression and Goswami Model. From the research result, the soil types were A4, A-6, and A-7 according to AASHTO and SC, SC-SM, and CL based on USCS. By linear regression, the equation for estimation of the maximum dry unit weight (γdmax *)=1,862-0,005*FINES- 0,003*LL and estimation of the optimum water content (wopt *)=- 0,607+0,362*FINES+0,161*LL. By Goswami Model (with equation Y=mLogG+k), for estimation of the maximum dry unit weight (γdmax *) with m=-0,376 and k=2,482, for estimation of the optimum water content (wopt *) with m=21,265 and k=-32,421. For both of these equations a 95% confidence interval was obtained.

  16. Optimizing data access for wind farm control over hierarchical communication networks

    DEFF Research Database (Denmark)

    Madsen, Jacob Theilgaard; Findrik, Mislav; Madsen, Tatiana Kozlova

    2016-01-01

    delays and also by the choice of the time instances at which sensor information is accessed. In order to optimize the latter, we introduce an information quality metric and a mathematical model based on Markov chains, which are compared performance-wise to a heuristic approach for finding this parameter......In this paper we investigate a centralized wind farm controller which runs periodically. The controller attempts to reduce the damage a wind turbine sustains during operation by estimating fatigue based on the wind turbine state. The investigation focuses on the impact of information access...

  17. Probabilistic estimation of the constitutive parameters of polymers

    Directory of Open Access Journals (Sweden)

    Siviour C.R.

    2012-08-01

    Full Text Available The Mulliken-Boyce constitutive model predicts the dynamic response of crystalline polymers as a function of strain rate and temperature. This paper describes the Mulliken-Boyce model-based estimation of the constitutive parameters in a Bayesian probabilistic framework. Experimental data from dynamic mechanical analysis and dynamic compression of PVC samples over a wide range of strain rates are analyzed. Both experimental uncertainty and natural variations in the material properties are simultaneously considered as independent and joint distributions; the posterior probability distributions are shown and compared with prior estimates of the material constitutive parameters. Additionally, particular statistical distributions are shown to be effective at capturing the rate and temperature dependence of internal phase transitions in DMA data.

  18. Statistical approach for uncertainty quantification of experimental modal model parameters

    DEFF Research Database (Denmark)

    Luczak, M.; Peeters, B.; Kahsin, M.

    2014-01-01

    Composite materials are widely used in manufacture of aerospace and wind energy structural components. These load carrying structures are subjected to dynamic time-varying loading conditions. Robust structural dynamics identification procedure impose tight constraints on the quality of modal models...... represent different complexity levels ranging from coupon, through sub-component up to fully assembled aerospace and wind energy structural components made of composite materials. The proposed method is demonstrated on two application cases of a small and large wind turbine blade........ This paper aims at a systematic approach for uncertainty quantification of the parameters of the modal models estimated from experimentally obtained data. Statistical analysis of modal parameters is implemented to derive an assessment of the entire modal model uncertainty measure. Investigated structures...

  19. IMPACT STUDY OF ANISOTROPIC OPTICAL FIBERS WINDING WITH DIFFERENT TENSION VALUE ON THE H-PARAMETER INVARIANCE DEGREE

    Directory of Open Access Journals (Sweden)

    A. B. Mukhtubayev

    2015-09-01

    Full Text Available Subject of Research. We have investigated the effect of anisotropic optical fibers winding with an elliptical sheath subjecting to stress on the H-parameter invariance degree. This type of optical fiber is used in the manufacture of fiber loop in fiber-optic gyroscopes. Method of Research. The method of research is based on the application of Michelson polarization scanning interferometer as a measuring device. Superluminescent diode with a central wavelength of 1575 nm and a half-width of the spectrum equal to 45 nm is used as a radiation source. The studies were carried out with anisotropic optical fiber with 50 m long elliptical sheath subjecting to stress. The fiber was wound with one layer turn to turn on the coil with a diameter of 18 cm, which is used in the design of fiber-optic gyroscope. The tension force of the optical fiber was controlled during winding on a special machine. Main Results. It was found that at the increase of tension force from 0.05 N to 0.8 H the value of H-parameter increases from 7×10-6 1/m up to 178×10-6 1/m, respectively; i.e. the coupling coefficient of orthogonal modes in the test fiber is being increased. Thus, it is necessary to consider the longitudinal tension force of fiber in the design and manufacture of the fiber-optic sensors of high accuracy class: the less the fiber winding power, the higher invariance degree of distributed H-parameter. The longitudinal tension force of anisotropic optical fiber with elliptical sheath subjecting to stress equal to 0.2 N is recommended in the process of designing fiber-optic gyroscopes. Practical Relevance. The proposed method of Michelson scanning interferometer is usable in the production process for quality determination of the optical fiber winding: no local defects, value controlling of fiber H-parameter.

  20. Hurricane Wind Vector Estimates from WindSat Polarimetric Radiometer

    National Research Council Canada - National Science Library

    Adams, Ian S; Hennon, Christopther C; Jones, W. L; Ahmad, Khalil

    2005-01-01

    .... In late 2004, the first preliminary oceanic wind vector results were released, and this paper presents the first evaluation of this product for several Atlantic hurricanes during the 2003 season...

  1. Estimating 3D Object Parameters from 2D Grey-Level Images

    NARCIS (Netherlands)

    Houkes, Z.

    2000-01-01

    This thesis describes a general framework for parameter estimation, which is suitable for computer vision applications. The approach described combines 3D modelling, animation and estimation tools to determine parameters of objects in a scene from 2D grey-level images. The animation tool predicts

  2. Effect of wind waves on air-sea gas exchange: proposal of an overall CO2 transfer velocity formula as a function of breaking-wave parameter

    International Nuclear Information System (INIS)

    Zhao, D.; Suzuki, Y.; Komori, S.

    2003-01-01

    A new formula for gas transfer velocity as a function of the breaking-wave parameter is proposed based on correlating gas transfer with whitecap coverage. The new formula for gas transfer across an air-sea interface depends not only on wind speed but also on wind-wave state. At the same wind speed, a higher gas transfer velocity will be obtained for a more developed wind-sea, which is represented by a smaller spectral peak frequency of wind waves. We suggest that the large uncertainties in the traditional relationship of gas transfer velocity with wind speed be ascribed to the neglect of the effect of wind waves. The breaking-wave parameter can be regarded as a Reynolds number that characterizes the intensity of turbulence associated with wind waves in the downward-bursting boundary layer (DBBL). DBBL provides an effective way to exchange gas across the air-sea interface, which might be related to the surface renewal

  3. Estimations of parameters in Pareto reliability model in the presence of masked data

    International Nuclear Information System (INIS)

    Sarhan, Ammar M.

    2003-01-01

    Estimations of parameters included in the individual distributions of the life times of system components in a series system are considered in this paper based on masked system life test data. We consider a series system of two independent components each has a Pareto distributed lifetime. The maximum likelihood and Bayes estimators for the parameters and the values of the reliability of the system's components at a specific time are obtained. Symmetrical triangular prior distributions are assumed for the unknown parameters to be estimated in obtaining the Bayes estimators of these parameters. Large simulation studies are done in order: (i) explain how one can utilize the theoretical results obtained; (ii) compare the maximum likelihood and Bayes estimates obtained of the underlying parameters; and (iii) study the influence of the masking level and the sample size on the accuracy of the estimates obtained

  4. Quasi-Newton methods for parameter estimation in functional differential equations

    Science.gov (United States)

    Brewer, Dennis W.

    1988-01-01

    A state-space approach to parameter estimation in linear functional differential equations is developed using the theory of linear evolution equations. A locally convergent quasi-Newton type algorithm is applied to distributed systems with particular emphasis on parameters that induce unbounded perturbations of the state. The algorithm is computationally implemented on several functional differential equations, including coefficient and delay estimation in linear delay-differential equations.

  5. Estimating Arrhenius parameters using temperature programmed molecular dynamics

    International Nuclear Information System (INIS)

    Imandi, Venkataramana; Chatterjee, Abhijit

    2016-01-01

    Kinetic rates at different temperatures and the associated Arrhenius parameters, whenever Arrhenius law is obeyed, are efficiently estimated by applying maximum likelihood analysis to waiting times collected using the temperature programmed molecular dynamics method. When transitions involving many activated pathways are available in the dataset, their rates may be calculated using the same collection of waiting times. Arrhenius behaviour is ascertained by comparing rates at the sampled temperatures with ones from the Arrhenius expression. Three prototype systems with corrugated energy landscapes, namely, solvated alanine dipeptide, diffusion at the metal-solvent interphase, and lithium diffusion in silicon, are studied to highlight various aspects of the method. The method becomes particularly appealing when the Arrhenius parameters can be used to find rates at low temperatures where transitions are rare. Systematic coarse-graining of states can further extend the time scales accessible to the method. Good estimates for the rate parameters are obtained with 500-1000 waiting times.

  6. Estimating Arrhenius parameters using temperature programmed molecular dynamics

    Energy Technology Data Exchange (ETDEWEB)

    Imandi, Venkataramana; Chatterjee, Abhijit, E-mail: abhijit@che.iitb.ac.in [Department of Chemical Engineering, Indian Institute of Technology Bombay, Mumbai 400076 (India)

    2016-07-21

    Kinetic rates at different temperatures and the associated Arrhenius parameters, whenever Arrhenius law is obeyed, are efficiently estimated by applying maximum likelihood analysis to waiting times collected using the temperature programmed molecular dynamics method. When transitions involving many activated pathways are available in the dataset, their rates may be calculated using the same collection of waiting times. Arrhenius behaviour is ascertained by comparing rates at the sampled temperatures with ones from the Arrhenius expression. Three prototype systems with corrugated energy landscapes, namely, solvated alanine dipeptide, diffusion at the metal-solvent interphase, and lithium diffusion in silicon, are studied to highlight various aspects of the method. The method becomes particularly appealing when the Arrhenius parameters can be used to find rates at low temperatures where transitions are rare. Systematic coarse-graining of states can further extend the time scales accessible to the method. Good estimates for the rate parameters are obtained with 500-1000 waiting times.

  7. Generation of electricity by wind power

    Energy Technology Data Exchange (ETDEWEB)

    Golding, E W

    1976-01-01

    Information on wind power is presented concerning the history of windmills; estimation of the energy obtainable from the wind; wind characteristics and distribution; wind power sites; wind surveys; wind flow over hills; measurement of wind velocity; wind structure and its determination; wind data and energy estimation; testing of wind driven ac generators; wind-driven machines; propeller type windmills; plants for isolated premises and small communities; economy of wind power generation; construction costs for large wind-driven generators; relationship of wind power to other power sources; research and development; and international cooperation.

  8. Using linear time-invariant system theory to estimate kinetic parameters directly from projection measurements

    International Nuclear Information System (INIS)

    Zeng, G.L.; Gullberg, G.T.

    1995-01-01

    It is common practice to estimate kinetic parameters from dynamically acquired tomographic data by first reconstructing a dynamic sequence of three-dimensional reconstructions and then fitting the parameters to time activity curves generated from the time-varying reconstructed images. However, in SPECT, the pharmaceutical distribution can change during the acquisition of a complete tomographic data set, which can bias the estimated kinetic parameters. It is hypothesized that more accurate estimates of the kinetic parameters can be obtained by fitting to the projection measurements instead of the reconstructed time sequence. Estimation from projections requires the knowledge of their relationship between the tissue regions of interest or voxels with particular kinetic parameters and the project measurements, which results in a complicated nonlinear estimation problem with a series of exponential factors with multiplicative coefficients. A technique is presented in this paper where the exponential decay parameters are estimated separately using linear time-invariant system theory. Once the exponential factors are known, the coefficients of the exponentials can be estimated using linear estimation techniques. Computer simulations demonstrate that estimation of the kinetic parameters directly from the projections is more accurate than the estimation from the reconstructed images

  9. Parameter Estimation of Damped Compound Pendulum Differential Evolution Algorithm

    Directory of Open Access Journals (Sweden)

    Saad Mohd Sazli

    2016-01-01

    Full Text Available This paper present the parameter identification of damped compound pendulum using differential evolution algorithm. The procedure used to achieve the parameter identification of the experimental system consisted of input output data collection, ARX model order selection and parameter estimation using conventional method least square (LS and differential evolution (DE algorithm. PRBS signal is used to be input signal to regulate the motor speed. Whereas, the output signal is taken from position sensor. Both, input and output data is used to estimate the parameter of the ARX model. The residual error between the actual and predicted output responses of the models is validated using mean squares error (MSE. Analysis showed that, MSE value for LS is 0.0026 and MSE value for DE is 3.6601×10-5. Based results obtained, it was found that DE have lower MSE than the LS method.

  10. Improved Battery Parameter Estimation Method Considering Operating Scenarios for HEV/EV Applications

    Directory of Open Access Journals (Sweden)

    Jufeng Yang

    2016-12-01

    Full Text Available This paper presents an improved battery parameter estimation method based on typical operating scenarios in hybrid electric vehicles and pure electric vehicles. Compared with the conventional estimation methods, the proposed method takes both the constant-current charging and the dynamic driving scenarios into account, and two separate sets of model parameters are estimated through different parts of the pulse-rest test. The model parameters for the constant-charging scenario are estimated from the data in the pulse-charging periods, while the model parameters for the dynamic driving scenario are estimated from the data in the rest periods, and the length of the fitted dataset is determined by the spectrum analysis of the load current. In addition, the unsaturated phenomenon caused by the long-term resistor-capacitor (RC network is analyzed, and the initial voltage expressions of the RC networks in the fitting functions are improved to ensure a higher model fidelity. Simulation and experiment results validated the feasibility of the developed estimation method.

  11. The noise generated by wind turbines

    International Nuclear Information System (INIS)

    Anon.

    2012-01-01

    Sound propagation damps down with distance and varies according to different parameters like wind direction and temperature. This article begins by recalling the basic physics of sound wave propagation and gives a list of common noises and corresponding decibels. The habitual noise of wind turbines 500 m away is 35 decibels which ranks it between a quiet bedroom (30 decibels) and a calm office (40 decibels). The question about whether wind turbines are a noise nuisance is all the more difficult as the feeling of a nuisance is so objective and personal. Any project of wind turbines requires a thorough study of its estimated acoustic impact. This study is a 3 step approach: first the initial noise environment is measured, secondly the propagation of the sound generated by the wind turbine farm is modelled and adequate mitigation measures are proposed to comply the law. The law stipulates that the increase of noise must be less than 5 db during daylight and less than 3 db during night. (A.C.)

  12. Estimating plume dispersion: a comparison of several sigma schemes

    International Nuclear Information System (INIS)

    Irwin, J.S.

    1983-01-01

    The lateral and vertical Gaussian plume dispersion parameters are estimated and compared with field tracer data collected at 11 sites. The dispersion parameter schemes used in this analysis include Cramer's scheme, suggested for tall stack dispersion estimates, Draxler's scheme, suggested for elevated and surface releases, Pasquill's scheme, suggested for interim use in dispersion estimates, and the Pasquill--Gifford scheme using Turner's technique for assigning stability categories. The schemes suggested by Cramer, Draxler and Pasquill estimate the dispersion parameters using onsite measurements of the vertical and lateral wind-velocity variances at the effective release height. The performances of these schemes in estimating the dispersion parameters are compared with that of the Pasquill--Gifford scheme, using the Prairie Grass and Karlsruhe data. For these two experiments, the estimates of the dispersion parameters using Draxler's scheme correlate better with the measurements than did estimates using the Pasquill--Gifford scheme. Comparison of the dispersion parameter estimates with the measurement suggests that Draxler's scheme for characterizing the dispersion results in the smallest mean fractional error in the estimated dispersion parameters and the smallest variance of the fractional errors

  13. Parameters Estimation of Geographically Weighted Ordinal Logistic Regression (GWOLR) Model

    Science.gov (United States)

    Zuhdi, Shaifudin; Retno Sari Saputro, Dewi; Widyaningsih, Purnami

    2017-06-01

    A regression model is the representation of relationship between independent variable and dependent variable. The dependent variable has categories used in the logistic regression model to calculate odds on. The logistic regression model for dependent variable has levels in the logistics regression model is ordinal. GWOLR model is an ordinal logistic regression model influenced the geographical location of the observation site. Parameters estimation in the model needed to determine the value of a population based on sample. The purpose of this research is to parameters estimation of GWOLR model using R software. Parameter estimation uses the data amount of dengue fever patients in Semarang City. Observation units used are 144 villages in Semarang City. The results of research get GWOLR model locally for each village and to know probability of number dengue fever patient categories.

  14. Effects of Icing on Wind Turbine Fatigue Loads

    International Nuclear Information System (INIS)

    Frohboese, Peter; Anders, Andreas

    2007-01-01

    The external conditions occurring at cold climate sites will affect wind turbines in different ways. The effects of ice accretion on wind turbines and the influence on the turbine fatigue loads are examined. The amount of icing prior to turbine installation needs to be estimated by using standard measurement data and considering the geometry of the proposed turbine. A procedure to calculate the expected ice accretion on wind turbines out of standard measurement data is explained and the results are discussed. Different parameters to describe the accreted ice on the turbine are examined separately in a fatigue load calculation. The results of the fatigue load calculation are discussed and selected cases are presented

  15. Solar-wind predictions for the Parker Solar Probe orbit. Near-Sun extrapolations derived from an empirical solar-wind model based on Helios and OMNI observations

    Science.gov (United States)

    Venzmer, M. S.; Bothmer, V.

    2018-03-01

    heliosphere confined to the ecliptic region is derived, accounting for solar activity and for solar distance through adequate shifts of the lognormal distributions. Finally, the inclusion of SSN predictions and the extrapolation down to PSPs perihelion region enables us to estimate the solar-wind environment for PSPs planned trajectory during its mission duration. Results: The CGAUSS empirical solar-wind model for PSP yields dependencies on solar activity and solar distance for the solar-wind parameters' frequency distributions. The estimated solar-wind median values for PSPs first perihelion in 2018 at a solar distance of 0.16 au are 87 nT, 340 km s-1, 214 cm-3, and 503 000 K. The estimates for PSPs first closest perihelion, occurring in 2024 at 0.046 au (9.86 R⊙), are 943 nT, 290 km s-1, 2951 cm-3, and 1 930 000 K. Since the modeled velocity and temperature values below approximately 20 R⊙appear overestimated in comparison with existing observations, this suggests that PSP will directly measure solar-wind acceleration and heating processes below 20 R⊙ as planned.

  16. Circuit realization, chaos synchronization and estimation of parameters of a hyperchaotic system with unknown parameters

    Directory of Open Access Journals (Sweden)

    A. Elsonbaty

    2014-10-01

    Full Text Available In this article, the adaptive chaos synchronization technique is implemented by an electronic circuit and applied to the hyperchaotic system proposed by Chen et al. We consider the more realistic and practical case where all the parameters of the master system are unknowns. We propose and implement an electronic circuit that performs the estimation of the unknown parameters and the updating of the parameters of the slave system automatically, and hence it achieves the synchronization. To the best of our knowledge, this is the first attempt to implement a circuit that estimates the values of the unknown parameters of chaotic system and achieves synchronization. The proposed circuit has a variety of suitable real applications related to chaos encryption and cryptography. The outputs of the implemented circuits and numerical simulation results are shown to view the performance of the synchronized system and the proposed circuit.

  17. Optimal supplementary frequency controller design using the wind farm frequency model and controller parameters stability region.

    Science.gov (United States)

    Toulabi, Mohammadreza; Bahrami, Shahab; Ranjbar, Ali Mohammad

    2018-03-01

    In most of the existing studies, the frequency response in the variable speed wind turbines (VSWTs) is simply realized by changing the torque set-point via appropriate inputs such as frequency deviations signal. However, effective dynamics and systematic process design have not been comprehensively discussed yet. Accordingly, this paper proposes a proportional-derivative frequency controller and investigates its performance in a wind farm consisting of several VSWTs. A band-pass filter is deployed before the proposed controller to avoid responding to either steady state frequency deviations or high rate of change of frequency. To design the controller, the frequency model of the wind farm is first characterized. The proposed controller is then designed based on the obtained open loop system. The stability region associated with the controller parameters is analytically determined by decomposing the closed-loop system's characteristic polynomial into the odd and even parts. The performance of the proposed controller is evaluated through extensive simulations in MATLAB/Simulink environment in a power system comprising a high penetration of VSWTs equipped with the proposed controller. Finally, based on the obtained feasible area and appropriate objective function, the optimal values associated with the controller parameters are determined using the genetic algorithm (GA). Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

  18. Comparison of sampling techniques for Bayesian parameter estimation

    Science.gov (United States)

    Allison, Rupert; Dunkley, Joanna

    2014-02-01

    The posterior probability distribution for a set of model parameters encodes all that the data have to tell us in the context of a given model; it is the fundamental quantity for Bayesian parameter estimation. In order to infer the posterior probability distribution we have to decide how to explore parameter space. Here we compare three prescriptions for how parameter space is navigated, discussing their relative merits. We consider Metropolis-Hasting sampling, nested sampling and affine-invariant ensemble Markov chain Monte Carlo (MCMC) sampling. We focus on their performance on toy-model Gaussian likelihoods and on a real-world cosmological data set. We outline the sampling algorithms themselves and elaborate on performance diagnostics such as convergence time, scope for parallelization, dimensional scaling, requisite tunings and suitability for non-Gaussian distributions. We find that nested sampling delivers high-fidelity estimates for posterior statistics at low computational cost, and should be adopted in favour of Metropolis-Hastings in many cases. Affine-invariant MCMC is competitive when computing clusters can be utilized for massive parallelization. Affine-invariant MCMC and existing extensions to nested sampling naturally probe multimodal and curving distributions.

  19. Economics of a small wind pump system based on estimated petrol and diesel cost savings from use in Northern Nigeria

    Directory of Open Access Journals (Sweden)

    C. J. Ejieji

    2013-08-01

    Full Text Available Eleven years of daily wind records were analyzed for the estimation of available wind energy for water pumping at three selected locations in Northern Nigeria, namely Jos, Kano and Sokoto. This formed the basis for investigating the economics of the use of an imported small wind pump under a deregulated energy market environment. The estimated available energy for water pumping at the installation height of 9m was 190 kwh/m2/yr for Jos, 225 kwh/m2/yr for Kano and 348 kwh/m2/yr for Sokoto. The monetary value of the available wind energy was considered as saved energy cost. The saved cost was obtained in terms of the unsubsidized cost of the petrol and diesel that an internal combustion engine (ICE would consume to produce energy equivalent to the available wind energy. At the prevailing interest and inflation rates of 21.96 % and 12.1% respectively, and unsubsidized prices of N 131.32/l and N 140.23/l for petrol and diesel respectively, investment in the wind pump was not found to be economically competitive relative to using a pump with ICE prime mover at the three locations unless the cost of the pump was subsidized. For Sokoto, the estimated subsidy for initial cost of the wind pump required for the investment to be competitive relative to the use of a pump driven by a petrol ICE was 16%. Relative to a pump driven by a diesel ICE, the required subsidy was 24%. The corresponding subsidy estimates for Kano were 48 % and 51 % respectively. For Jos, it was 56% relative to the use of a pump driven by a petrol ICE and 60 % relative to that driven by a diesel ICE. Considering the potential environmental and social and environmental benefits however, subsidy support by government for local manufacturing of the pumps was recommended since shipping cost and custom tariff constituted over 36% of the initial cost of the wind pump.

  20. PARAMETER ESTIMATION AND MODEL SELECTION FOR INDOOR ENVIRONMENTS BASED ON SPARSE OBSERVATIONS

    Directory of Open Access Journals (Sweden)

    Y. Dehbi

    2017-09-01

    Full Text Available This paper presents a novel method for the parameter estimation and model selection for the reconstruction of indoor environments based on sparse observations. While most approaches for the reconstruction of indoor models rely on dense observations, we predict scenes of the interior with high accuracy in the absence of indoor measurements. We use a model-based top-down approach and incorporate strong but profound prior knowledge. The latter includes probability density functions for model parameters and sparse observations such as room areas and the building footprint. The floorplan model is characterized by linear and bi-linear relations with discrete and continuous parameters. We focus on the stochastic estimation of model parameters based on a topological model derived by combinatorial reasoning in a first step. A Gauss-Markov model is applied for estimation and simulation of the model parameters. Symmetries are represented and exploited during the estimation process. Background knowledge as well as observations are incorporated in a maximum likelihood estimation and model selection is performed with AIC/BIC. The likelihood is also used for the detection and correction of potential errors in the topological model. Estimation results are presented and discussed.

  1. Parameter Estimation and Model Selection for Indoor Environments Based on Sparse Observations

    Science.gov (United States)

    Dehbi, Y.; Loch-Dehbi, S.; Plümer, L.

    2017-09-01

    This paper presents a novel method for the parameter estimation and model selection for the reconstruction of indoor environments based on sparse observations. While most approaches for the reconstruction of indoor models rely on dense observations, we predict scenes of the interior with high accuracy in the absence of indoor measurements. We use a model-based top-down approach and incorporate strong but profound prior knowledge. The latter includes probability density functions for model parameters and sparse observations such as room areas and the building footprint. The floorplan model is characterized by linear and bi-linear relations with discrete and continuous parameters. We focus on the stochastic estimation of model parameters based on a topological model derived by combinatorial reasoning in a first step. A Gauss-Markov model is applied for estimation and simulation of the model parameters. Symmetries are represented and exploited during the estimation process. Background knowledge as well as observations are incorporated in a maximum likelihood estimation and model selection is performed with AIC/BIC. The likelihood is also used for the detection and correction of potential errors in the topological model. Estimation results are presented and discussed.

  2. Robust bivariate error detection in skewed data with application to historical radiosonde winds

    KAUST Repository

    Sun, Ying

    2017-01-18

    The global historical radiosonde archives date back to the 1920s and contain the only directly observed measurements of temperature, wind, and moisture in the upper atmosphere, but they contain many random errors. Most of the focus on cleaning these large datasets has been on temperatures, but winds are important inputs to climate models and in studies of wind climatology. The bivariate distribution of the wind vector does not have elliptical contours but is skewed and heavy-tailed, so we develop two methods for outlier detection based on the bivariate skew-t (BST) distribution, using either distance-based or contour-based approaches to flag observations as potential outliers. We develop a framework to robustly estimate the parameters of the BST and then show how the tuning parameter to get these estimates is chosen. In simulation, we compare our methods with one based on a bivariate normal distribution and a nonparametric approach based on the bagplot. We then apply all four methods to the winds observed for over 35,000 radiosonde launches at a single station and demonstrate differences in the number of observations flagged across eight pressure levels and through time. In this pilot study, the method based on the BST contours performs very well.

  3. Robust bivariate error detection in skewed data with application to historical radiosonde winds

    KAUST Repository

    Sun, Ying; Hering, Amanda S.; Browning, Joshua M.

    2017-01-01

    The global historical radiosonde archives date back to the 1920s and contain the only directly observed measurements of temperature, wind, and moisture in the upper atmosphere, but they contain many random errors. Most of the focus on cleaning these large datasets has been on temperatures, but winds are important inputs to climate models and in studies of wind climatology. The bivariate distribution of the wind vector does not have elliptical contours but is skewed and heavy-tailed, so we develop two methods for outlier detection based on the bivariate skew-t (BST) distribution, using either distance-based or contour-based approaches to flag observations as potential outliers. We develop a framework to robustly estimate the parameters of the BST and then show how the tuning parameter to get these estimates is chosen. In simulation, we compare our methods with one based on a bivariate normal distribution and a nonparametric approach based on the bagplot. We then apply all four methods to the winds observed for over 35,000 radiosonde launches at a single station and demonstrate differences in the number of observations flagged across eight pressure levels and through time. In this pilot study, the method based on the BST contours performs very well.

  4. An appraisal of wind speed distribution prediction by soft computing methodologies: A comparative study

    International Nuclear Information System (INIS)

    Petković, Dalibor; Shamshirband, Shahaboddin; Anuar, Nor Badrul; Saboohi, Hadi; Abdul Wahab, Ainuddin Wahid; Protić, Milan; Zalnezhad, Erfan; Mirhashemi, Seyed Mohammad Amin

    2014-01-01

    Highlights: • Probabilistic distribution functions of wind speed. • Two parameter Weibull probability distribution. • To build an effective prediction model of distribution of wind speed. • Support vector regression application as probability function for wind speed. - Abstract: The probabilistic distribution of wind speed is among the more significant wind characteristics in examining wind energy potential and the performance of wind energy conversion systems. When the wind speed probability distribution is known, the wind energy distribution can be easily obtained. Therefore, the probability distribution of wind speed is a very important piece of information required in assessing wind energy potential. For this reason, a large number of studies have been established concerning the use of a variety of probability density functions to describe wind speed frequency distributions. Although the two-parameter Weibull distribution comprises a widely used and accepted method, solving the function is very challenging. In this study, the polynomial and radial basis functions (RBF) are applied as the kernel function of support vector regression (SVR) to estimate two parameters of the Weibull distribution function according to previously established analytical methods. Rather than minimizing the observed training error, SVR p oly and SVR r bf attempt to minimize the generalization error bound, so as to achieve generalized performance. According to the experimental results, enhanced predictive accuracy and capability of generalization can be achieved using the SVR approach compared to other soft computing methodologies

  5. A practical approach to parameter estimation applied to model predicting heart rate regulation

    DEFF Research Database (Denmark)

    Olufsen, Mette; Ottesen, Johnny T.

    2013-01-01

    Mathematical models have long been used for prediction of dynamics in biological systems. Recently, several efforts have been made to render these models patient specific. One way to do so is to employ techniques to estimate parameters that enable model based prediction of observed quantities....... Knowledge of variation in parameters within and between groups of subjects have potential to provide insight into biological function. Often it is not possible to estimate all parameters in a given model, in particular if the model is complex and the data is sparse. However, it may be possible to estimate...... a subset of model parameters reducing the complexity of the problem. In this study, we compare three methods that allow identification of parameter subsets that can be estimated given a model and a set of data. These methods will be used to estimate patient specific parameters in a model predicting...

  6. Models for estimating photosynthesis parameters from in situ production profiles

    Science.gov (United States)

    Kovač, Žarko; Platt, Trevor; Sathyendranath, Shubha; Antunović, Suzana

    2017-12-01

    The rate of carbon assimilation in phytoplankton primary production models is mathematically prescribed with photosynthesis irradiance functions, which convert a light flux (energy) into a material flux (carbon). Information on this rate is contained in photosynthesis parameters: the initial slope and the assimilation number. The exactness of parameter values is crucial for precise calculation of primary production. Here we use a model of the daily production profile based on a suite of photosynthesis irradiance functions and extract photosynthesis parameters from in situ measured daily production profiles at the Hawaii Ocean Time-series station Aloha. For each function we recover parameter values, establish parameter distributions and quantify model skill. We observe that the choice of the photosynthesis irradiance function to estimate the photosynthesis parameters affects the magnitudes of parameter values as recovered from in situ profiles. We also tackle the problem of parameter exchange amongst the models and the effect it has on model performance. All models displayed little or no bias prior to parameter exchange, but significant bias following parameter exchange. The best model performance resulted from using optimal parameter values. Model formulation was extended further by accounting for spectral effects and deriving a spectral analytical solution for the daily production profile. The daily production profile was also formulated with time dependent growing biomass governed by a growth equation. The work on parameter recovery was further extended by exploring how to extract photosynthesis parameters from information on watercolumn production. It was demonstrated how to estimate parameter values based on a linearization of the full analytical solution for normalized watercolumn production and from the solution itself, without linearization. The paper complements previous works on photosynthesis irradiance models by analysing the skill and consistency of

  7. A robust methodology for kinetic model parameter estimation for biocatalytic reactions

    DEFF Research Database (Denmark)

    Al-Haque, Naweed; Andrade Santacoloma, Paloma de Gracia; Lima Afonso Neto, Watson

    2012-01-01

    lead to globally optimized parameter values. In this article, a robust methodology to estimate parameters for biocatalytic reaction kinetic expressions is proposed. The methodology determines the parameters in a systematic manner by exploiting the best features of several of the current approaches...... parameters, which are strongly correlated with each other. State-of-the-art methodologies such as nonlinear regression (using progress curves) or graphical analysis (using initial rate data, for example, the Lineweaver-Burke plot, Hanes plot or Dixon plot) often incorporate errors in the estimates and rarely...

  8. Tsunami Prediction and Earthquake Parameters Estimation in the Red Sea

    KAUST Repository

    Sawlan, Zaid A

    2012-12-01

    Tsunami concerns have increased in the world after the 2004 Indian Ocean tsunami and the 2011 Tohoku tsunami. Consequently, tsunami models have been developed rapidly in the last few years. One of the advanced tsunami models is the GeoClaw tsunami model introduced by LeVeque (2011). This model is adaptive and consistent. Because of different sources of uncertainties in the model, observations are needed to improve model prediction through a data assimilation framework. Model inputs are earthquake parameters and topography. This thesis introduces a real-time tsunami forecasting method that combines tsunami model with observations using a hybrid ensemble Kalman filter and ensemble Kalman smoother. The filter is used for state prediction while the smoother operates smoothing to estimate the earthquake parameters. This method reduces the error produced by uncertain inputs. In addition, state-parameter EnKF is implemented to estimate earthquake parameters. Although number of observations is small, estimated parameters generates a better tsunami prediction than the model. Methods and results of prediction experiments in the Red Sea are presented and the prospect of developing an operational tsunami prediction system in the Red Sea is discussed.

  9. Estimating Parameters in Physical Models through Bayesian Inversion: A Complete Example

    KAUST Repository

    Allmaras, Moritz

    2013-02-07

    All mathematical models of real-world phenomena contain parameters that need to be estimated from measurements, either for realistic predictions or simply to understand the characteristics of the model. Bayesian statistics provides a framework for parameter estimation in which uncertainties about models and measurements are translated into uncertainties in estimates of parameters. This paper provides a simple, step-by-step example-starting from a physical experiment and going through all of the mathematics-to explain the use of Bayesian techniques for estimating the coefficients of gravity and air friction in the equations describing a falling body. In the experiment we dropped an object from a known height and recorded the free fall using a video camera. The video recording was analyzed frame by frame to obtain the distance the body had fallen as a function of time, including measures of uncertainty in our data that we describe as probability densities. We explain the decisions behind the various choices of probability distributions and relate them to observed phenomena. Our measured data are then combined with a mathematical model of a falling body to obtain probability densities on the space of parameters we seek to estimate. We interpret these results and discuss sources of errors in our estimation procedure. © 2013 Society for Industrial and Applied Mathematics.

  10. PWR system simulation and parameter estimation with neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Akkurt, Hatice; Colak, Uener E-mail: uc@nuke.hacettepe.edu.tr

    2002-11-01

    A detailed nonlinear model for a typical PWR system has been considered for the development of simulation software. Each component in the system has been represented by appropriate differential equations. The SCILAB software was used for solving nonlinear equations to simulate steady-state and transient operational conditions. Overall system has been constructed by connecting individual components to each other. The validity of models for individual components and overall system has been verified. The system response against given transients have been analyzed. A neural network has been utilized to estimate system parameters during transients. Different transients have been imposed in training and prediction stages with neural networks. Reactor power and system reactivity during the transient event have been predicted by the neural network. Results show that neural networks estimations are in good agreement with the calculated response of the reactor system. The maximum errors are within {+-}0.254% for power and between -0.146 and 0.353% for reactivity prediction cases. Steam generator parameters, pressure and water level, are also successfully predicted by the neural network employed in this study. The noise imposed on the input parameters of the neural network deteriorates the power estimation capability whereas the reactivity estimation capability is not significantly affected.

  11. PWR system simulation and parameter estimation with neural networks

    International Nuclear Information System (INIS)

    Akkurt, Hatice; Colak, Uener

    2002-01-01

    A detailed nonlinear model for a typical PWR system has been considered for the development of simulation software. Each component in the system has been represented by appropriate differential equations. The SCILAB software was used for solving nonlinear equations to simulate steady-state and transient operational conditions. Overall system has been constructed by connecting individual components to each other. The validity of models for individual components and overall system has been verified. The system response against given transients have been analyzed. A neural network has been utilized to estimate system parameters during transients. Different transients have been imposed in training and prediction stages with neural networks. Reactor power and system reactivity during the transient event have been predicted by the neural network. Results show that neural networks estimations are in good agreement with the calculated response of the reactor system. The maximum errors are within ±0.254% for power and between -0.146 and 0.353% for reactivity prediction cases. Steam generator parameters, pressure and water level, are also successfully predicted by the neural network employed in this study. The noise imposed on the input parameters of the neural network deteriorates the power estimation capability whereas the reactivity estimation capability is not significantly affected

  12. Analysis of Wind Data, Calculation of Energy Yield Potential, and Micrositing Application with WAsP

    Directory of Open Access Journals (Sweden)

    Fatih Topaloğlu

    2018-01-01

    Full Text Available The parameters required for building a wind power plant have been calculated using the fuzzy logic method by means of Wind Atlas Analysis and Application Program (WAsP in this study. Overall objectives of the program include analysis of raw data, evaluation of wind and climate, construction of a wind atlas, and estimation of wind power potential. With the analysis performed in the application, the average wind velocity, average power density, energy potential from micrositing, capacity factor, unit cost price, and period of redemption have been calculated, which are needed by the project developer during the decision-making stage and intended to be used as the input unit in the fuzzy logic-based system designed. It is aimed at processing the parameters calculated by the designed fuzzy logic-based decision-making system at the rule base and generating a compatibility factor that will allow for making the final decision in building wind power plants.

  13. Impact of Spatial Resolution on Wind Field Derived Estimates of Air Pressure Depression in the Hurricane Eye

    Directory of Open Access Journals (Sweden)

    Linwood Jones

    2010-03-01

    Full Text Available Measurements of the near surface horizontal wind field in a hurricane with spatial resolution of order 1–10 km are possible using airborne microwave radiometer imagers. An assessment is made of the information content of the measured winds as a function of the spatial resolution of the imager. An existing algorithm is used which estimates the maximum surface air pressure depression in the hurricane eye from the maximum wind speed. High resolution numerical model wind fields from Hurricane Frances 2004 are convolved with various HIRAD antenna spatial filters to observe the impact of the antenna design on the central pressure depression in the eye that can be deduced from it.

  14. Estimation of Ordinary Differential Equation Parameters Using Constrained Local Polynomial Regression.

    Science.gov (United States)

    Ding, A Adam; Wu, Hulin

    2014-10-01

    We propose a new method to use a constrained local polynomial regression to estimate the unknown parameters in ordinary differential equation models with a goal of improving the smoothing-based two-stage pseudo-least squares estimate. The equation constraints are derived from the differential equation model and are incorporated into the local polynomial regression in order to estimate the unknown parameters in the differential equation model. We also derive the asymptotic bias and variance of the proposed estimator. Our simulation studies show that our new estimator is clearly better than the pseudo-least squares estimator in estimation accuracy with a small price of computational cost. An application example on immune cell kinetics and trafficking for influenza infection further illustrates the benefits of the proposed new method.

  15. Nonparametric estimation of location and scale parameters

    KAUST Repository

    Potgieter, C.J.; Lombard, F.

    2012-01-01

    Two random variables X and Y belong to the same location-scale family if there are constants μ and σ such that Y and μ+σX have the same distribution. In this paper we consider non-parametric estimation of the parameters μ and σ under minimal

  16. Sensor Placement for Modal Parameter Subset Estimation

    DEFF Research Database (Denmark)

    Ulriksen, Martin Dalgaard; Bernal, Dionisio; Damkilde, Lars

    2016-01-01

    The present paper proposes an approach for deciding on sensor placements in the context of modal parameter estimation from vibration measurements. The approach is based on placing sensors, of which the amount is determined a priori, such that the minimum Fisher information that the frequency resp...

  17. Research on Radar Micro-Doppler Feature Parameter Estimation of Propeller Aircraft

    Science.gov (United States)

    He, Zhihua; Tao, Feixiang; Duan, Jia; Luo, Jingsheng

    2018-01-01

    The micro-motion modulation effect of the rotated propellers to radar echo can be a steady feature for aircraft target recognition. Thus, micro-Doppler feature parameter estimation is a key to accurate target recognition. In this paper, the radar echo of rotated propellers is modelled and simulated. Based on which, the distribution characteristics of the micro-motion modulation energy in time, frequency and time-frequency domain are analyzed. The micro-motion modulation energy produced by the scattering points of rotating propellers is accumulated using the Inverse-Radon (I-Radon) transform, which can be used to accomplish the estimation of micro-modulation parameter. Finally, it is proved that the proposed parameter estimation method is effective with measured data. The micro-motion parameters of aircraft can be used as the features of radar target recognition.

  18. Long-period variations of wind parameters in the mesopause region and the solar cycle dependence

    International Nuclear Information System (INIS)

    Greisiger, K.M.; Schminder, R.; Kuerschner, D.

    1987-01-01

    A solar dependence of wind parameters below 100 km was found by Sprenger and Schminder on the basis of long-term continuous ionospheric drift measurements. For winter they obtained for the prevailing wind a positive correlation with solar activity and for the amplitude of the semi-diurnal tidal wind a negative correlation. However, after the years 1973-1974 we found a significant negative correlation with solar activity with an indication of a new change after 1983. We conclude that this long-term behaviour points rather to a climatic variation with an internal atmospheric cause than to a direct solar control. Recent satellite data of the solar u.v. radiation and the upper stratospheric ozone have shown that the possible variation of the thermal tidal excitation during the solar cycle amounts to only a few per cent. This is, therefore, insufficient to account for the 40-70% variation of the tidal amplitudes. Some other possibilities of explaining this result are discussed. (author)

  19. Analysis of wind energy generation possibilities with various rotor types at disadvantageous wind condition zones

    OpenAIRE

    Bieniek Andrzej

    2017-01-01

    The paper describe possibilities of energy generation using various rotor types but especially with multi-blade wind engine operates in the areas with unfavourable wind condition. The paper presents also wind energy conversion estimation results presented based on proposed solution of multi-blade wind turbine of outer diameter of 4 m. Based on the wind distribution histogram from the disadvantage wind condition zones (city of Basel) and taking into account design and estimated operating index...

  20. The small amplitude of density turbulence in the inner solar wind

    Directory of Open Access Journals (Sweden)

    S. R. Spangler

    2003-01-01

    Full Text Available Very Long Baseline Interferometer (VLBI observations were made of radio sources close to the Sun, whose lines of sight pass through the inner solar wind (impact parameters 16-26 RE. Power spectra were analyzed of the interferometer phase fluctuations due to the solar wind plasma. These power spectra provide information on the level of plasma density fluctuations on spatial scales of roughly one hundred to several thousand kilometers. By specifying an outer scale to the turbulence spectrum, we can estimate the root-mean-square (rms amplitude of the density fluctuations. The data indicate that the rms fluctuation in density is only about 10% of the mean density. This value is low, and consistent with extrapolated estimates from more distant parts of the solar wind. Physical speculations based on this result are presented.

  1. Parameter estimation and prediction of nonlinear biological systems: some examples

    NARCIS (Netherlands)

    Doeswijk, T.G.; Keesman, K.J.

    2006-01-01

    Rearranging and reparameterizing a discrete-time nonlinear model with polynomial quotient structure in input, output and parameters (xk = f(Z, p)) leads to a model linear in its (new) parameters. As a result, the parameter estimation problem becomes a so-called errors-in-variables problem for which

  2. CTER-rapid estimation of CTF parameters with error assessment.

    Science.gov (United States)

    Penczek, Pawel A; Fang, Jia; Li, Xueming; Cheng, Yifan; Loerke, Justus; Spahn, Christian M T

    2014-05-01

    In structural electron microscopy, the accurate estimation of the Contrast Transfer Function (CTF) parameters, particularly defocus and astigmatism, is of utmost importance for both initial evaluation of micrograph quality and for subsequent structure determination. Due to increases in the rate of data collection on modern microscopes equipped with new generation cameras, it is also important that the CTF estimation can be done rapidly and with minimal user intervention. Finally, in order to minimize the necessity for manual screening of the micrographs by a user it is necessary to provide an assessment of the errors of fitted parameters values. In this work we introduce CTER, a CTF parameters estimation method distinguished by its computational efficiency. The efficiency of the method makes it suitable for high-throughput EM data collection, and enables the use of a statistical resampling technique, bootstrap, that yields standard deviations of estimated defocus and astigmatism amplitude and angle, thus facilitating the automation of the process of screening out inferior micrograph data. Furthermore, CTER also outputs the spatial frequency limit imposed by reciprocal space aliasing of the discrete form of the CTF and the finite window size. We demonstrate the efficiency and accuracy of CTER using a data set collected on a 300kV Tecnai Polara (FEI) using the K2 Summit DED camera in super-resolution counting mode. Using CTER we obtained a structure of the 80S ribosome whose large subunit had a resolution of 4.03Å without, and 3.85Å with, inclusion of astigmatism parameters. Copyright © 2014 Elsevier B.V. All rights reserved.

  3. Influence of measurement errors and estimated parameters on combustion diagnosis

    International Nuclear Information System (INIS)

    Payri, F.; Molina, S.; Martin, J.; Armas, O.

    2006-01-01

    Thermodynamic diagnosis models are valuable tools for the study of Diesel combustion. Inputs required by such models comprise measured mean and instantaneous variables, together with suitable values for adjustable parameters used in different submodels. In the case of measured variables, one may estimate the uncertainty associated with measurement errors; however, the influence of errors in model parameter estimation may not be so easily established on an experimental basis. In this paper, a simulated pressure cycle has been used along with known input parameters, so that any uncertainty in the inputs is avoided. Then, the influence of errors in measured variables and geometric and heat transmission parameters on the results of a diagnosis combustion model for direct injection diesel engines have been studied. This procedure allowed to establish the relative importance of these parameters and to set limits to the maximal errors of the model, accounting for both the maximal expected errors in the input parameters and the sensitivity of the model to those errors

  4. Aircraft parameter estimation ± A tool for development of ...

    Indian Academy of Sciences (India)

    In addition, actuator performance and controller gains may be flight condition dependent. Moreover, this approach may result in open-loop parameter estimates with low accuracy. 6. Aerodynamic databases for high fidelity flight simulators. Estimation of a comprehensive aerodynamic model suitable for a flight simulator is an.

  5. Optimal wind energy penetration in power systems: An approach based on spatial distribution of wind speed

    International Nuclear Information System (INIS)

    Zolfaghari, Saeed; Riahy, Gholam H.; Abedi, Mehrdad; Golshannavaz, Sajjad

    2016-01-01

    Highlights: • Chronological wind speeds at distinct locations of the wind farm are not the same. • Spatial distribution of wind speed affects wind farm’s output power expectation. • Neglecting wind speed’s spatial doubt leads to mistake in wind energy penetration. • Scenario-based method can be used for effective wind capacity penetration level. - Abstract: Contributing in power system expansions, the present study establishes an efficient scheme for optimal integration of wind energy resources. The proposed approach highly concerns the spatial distribution of wind speed at different points of a wind farm. In mathematical statements, a suitable probability distribution function (PDF) is well-designed for representing such uncertainties. In such conditions, it is likely to have dissimilar output powers for individual and identical wind turbines. Thus, the overall aggregated PDF of a wind farm remarkably influences the critical parameters including the expected power and energy, capacity factor, and the reliability metrics such as loss of load expectation (LOLE) and expected energy not supplied (EENS). Furthermore, the proposed approach is deployed for optimal allocation of wind energy in bulk power systems. Hence, two typical test systems are numerically analyzed to interrogate the performance of the proposed approach. The conducted survey discloses an over/underestimation of harvestable wind energy in the case of overlooking spatial distributions. Thus, inaccurate amounts of wind farm’s capacity factor, output power, energy and reliability indices might be estimated. Meanwhile, the number of wind turbines may be misjudged to be installed. However, the proposed approach yields in a fair judgment regarding the overall performance of the wind farm. Consequently, a reliable penetration level of wind energy to the power system is assured. Extra discussions are provided to deeply assess the promising merits of the founded approach.

  6. Estimation of mesospheric vertical winds from a VHF meteor radar at King Sejong Station, Antarctica (62.2S, 58.8W)

    Science.gov (United States)

    Kim, Y.; Lee, C.; Kim, J.; Jee, G.

    2013-12-01

    For the first time, vertical winds near the mesopause region were estimated from radial velocities of meteor echoes detected by a VHF meteor radar at King Sejong Station (KSS) in 2011 and 2012. Since the radar usually detects more than a hundred echoes every hour in an altitude bin of 88 - 92 km, much larger than other radars, we were able to fit measured radial velocities of these echoes with a 6 component model that consists of horizontal winds, spatial gradients of horizontal winds and vertical wind. The conventional method of deriving horizontal winds from meteor echoes utilizes a 2 component model, assuming that vertical winds and spatial gradients of horizontal winds are negligible. We analyzed the radar data obtained for 8400 hours in 2012 and 8100 hours in 2011. We found that daily mean values of vertical winds are mostly within +/- 1 m/s, whereas those of zonal winds are a few tens m/s mostly eastward. The daily mean vertical winds sometimes stay positive or negative for more than 20 days, implying that the atmosphere near the mesopause experiences episodically a large scale low and high pressure environments, respectively, like the tropospheric weather system. By conducting Lomb-normalized periodogram analysis, we also found that the vertical winds have diurnal, semidiurnal and terdiurnal tidal components with about equal significance, in contrast to horizontal winds that show a dominant semidiurnal one. We will discuss about uncertainties of the estimated vertical wind and possible reasons of its tidal and daily variations.

  7. Dynamic Reliability Analysis of Gear Transmission System of Wind Turbine in Consideration of Randomness of Loadings and Parameters

    Directory of Open Access Journals (Sweden)

    Lei Wang

    2014-01-01

    Full Text Available A dynamic model of gear transmission system of wind turbine is built with consideration of randomness of loads and parameters. The dynamic response of the system is obtained using the theory of random sampling and the Runge-Kutta method. According to rain flow counting principle, the dynamic meshing forces are converted into a series of luffing fatigue load spectra. The amplitude and frequency of the equivalent stress are obtained using equivalent method of Geber quadratic curve. Moreover, the dynamic reliability model of components and system is built according to the theory of probability of cumulative fatigue damage. The system reliability with the random variation of parameters is calculated and the influence of random parameters on dynamic reliability of components is analyzed. In the end, the results of the proposed method are compared with that of Monte Carlo method. This paper can be instrumental in the design of wind turbine gear transmission system with more advantageous dynamic reliability.

  8. On the Nature of SEM Estimates of ARMA Parameters.

    Science.gov (United States)

    Hamaker, Ellen L.; Dolan, Conor V.; Molenaar, Peter C. M.

    2002-01-01

    Reexamined the nature of structural equation modeling (SEM) estimates of autoregressive moving average (ARMA) models, replicated the simulation experiments of P. Molenaar, and examined the behavior of the log-likelihood ratio test. Simulation studies indicate that estimates of ARMA parameters observed with SEM software are identical to those…

  9. Small sample GEE estimation of regression parameters for longitudinal data.

    Science.gov (United States)

    Paul, Sudhir; Zhang, Xuemao

    2014-09-28

    Longitudinal (clustered) response data arise in many bio-statistical applications which, in general, cannot be assumed to be independent. Generalized estimating equation (GEE) is a widely used method to estimate marginal regression parameters for correlated responses. The advantage of the GEE is that the estimates of the regression parameters are asymptotically unbiased even if the correlation structure is misspecified, although their small sample properties are not known. In this paper, two bias adjusted GEE estimators of the regression parameters in longitudinal data are obtained when the number of subjects is small. One is based on a bias correction, and the other is based on a bias reduction. Simulations show that the performances of both the bias-corrected methods are similar in terms of bias, efficiency, coverage probability, average coverage length, impact of misspecification of correlation structure, and impact of cluster size on bias correction. Both these methods show superior properties over the GEE estimates for small samples. Further, analysis of data involving a small number of subjects also shows improvement in bias, MSE, standard error, and length of the confidence interval of the estimates by the two bias adjusted methods over the GEE estimates. For small to moderate sample sizes (N ≤50), either of the bias-corrected methods GEEBc and GEEBr can be used. However, the method GEEBc should be preferred over GEEBr, as the former is computationally easier. For large sample sizes, the GEE method can be used. Copyright © 2014 John Wiley & Sons, Ltd.

  10. Parameter estimation techniques and uncertainty in ground water flow model predictions

    International Nuclear Information System (INIS)

    Zimmerman, D.A.; Davis, P.A.

    1990-01-01

    Quantification of uncertainty in predictions of nuclear waste repository performance is a requirement of Nuclear Regulatory Commission regulations governing the licensing of proposed geologic repositories for high-level radioactive waste disposal. One of the major uncertainties in these predictions is in estimating the ground-water travel time of radionuclides migrating from the repository to the accessible environment. The cause of much of this uncertainty has been attributed to a lack of knowledge about the hydrogeologic properties that control the movement of radionuclides through the aquifers. A major reason for this lack of knowledge is the paucity of data that is typically available for characterizing complex ground-water flow systems. Because of this, considerable effort has been put into developing parameter estimation techniques that infer property values in regions where no measurements exist. Currently, no single technique has been shown to be superior or even consistently conservative with respect to predictions of ground-water travel time. This work was undertaken to compare a number of parameter estimation techniques and to evaluate how differences in the parameter estimates and the estimation errors are reflected in the behavior of the flow model predictions. That is, we wished to determine to what degree uncertainties in flow model predictions may be affected simply by the choice of parameter estimation technique used. 3 refs., 2 figs

  11. Genetic Parameter Estimates for Metabolizing Two Common Pharmaceuticals in Swine

    Directory of Open Access Journals (Sweden)

    Jeremy T. Howard

    2018-02-01

    Full Text Available In livestock, the regulation of drugs used to treat livestock has received increased attention and it is currently unknown how much of the phenotypic variation in drug metabolism is due to the genetics of an animal. Therefore, the objective of the study was to determine the amount of phenotypic variation in fenbendazole and flunixin meglumine drug metabolism due to genetics. The population consisted of crossbred female and castrated male nursery pigs (n = 198 that were sired by boars represented by four breeds. The animals were spread across nine batches. Drugs were administered intravenously and blood collected a minimum of 10 times over a 48 h period. Genetic parameters for the parent drug and metabolite concentration within each drug were estimated based on pharmacokinetics (PK parameters or concentrations across time utilizing a random regression model. The PK parameters were estimated using a non-compartmental analysis. The PK model included fixed effects of sex and breed of sire along with random sire and batch effects. The random regression model utilized Legendre polynomials and included a fixed population concentration curve, sex, and breed of sire effects along with a random sire deviation from the population curve and batch effect. The sire effect included the intercept for all models except for the fenbendazole metabolite (i.e., intercept and slope. The mean heritability across PK parameters for the fenbendazole and flunixin meglumine parent drug (metabolite was 0.15 (0.18 and 0.31 (0.40, respectively. For the parent drug (metabolite, the mean heritability across time was 0.27 (0.60 and 0.14 (0.44 for fenbendazole and flunixin meglumine, respectively. The errors surrounding the heritability estimates for the random regression model were smaller compared to estimates obtained from PK parameters. Across both the PK and plasma drug concentration across model, a moderate heritability was estimated. The model that utilized the plasma drug

  12. Genetic Parameter Estimates for Metabolizing Two Common Pharmaceuticals in Swine

    Science.gov (United States)

    Howard, Jeremy T.; Ashwell, Melissa S.; Baynes, Ronald E.; Brooks, James D.; Yeatts, James L.; Maltecca, Christian

    2018-01-01

    In livestock, the regulation of drugs used to treat livestock has received increased attention and it is currently unknown how much of the phenotypic variation in drug metabolism is due to the genetics of an animal. Therefore, the objective of the study was to determine the amount of phenotypic variation in fenbendazole and flunixin meglumine drug metabolism due to genetics. The population consisted of crossbred female and castrated male nursery pigs (n = 198) that were sired by boars represented by four breeds. The animals were spread across nine batches. Drugs were administered intravenously and blood collected a minimum of 10 times over a 48 h period. Genetic parameters for the parent drug and metabolite concentration within each drug were estimated based on pharmacokinetics (PK) parameters or concentrations across time utilizing a random regression model. The PK parameters were estimated using a non-compartmental analysis. The PK model included fixed effects of sex and breed of sire along with random sire and batch effects. The random regression model utilized Legendre polynomials and included a fixed population concentration curve, sex, and breed of sire effects along with a random sire deviation from the population curve and batch effect. The sire effect included the intercept for all models except for the fenbendazole metabolite (i.e., intercept and slope). The mean heritability across PK parameters for the fenbendazole and flunixin meglumine parent drug (metabolite) was 0.15 (0.18) and 0.31 (0.40), respectively. For the parent drug (metabolite), the mean heritability across time was 0.27 (0.60) and 0.14 (0.44) for fenbendazole and flunixin meglumine, respectively. The errors surrounding the heritability estimates for the random regression model were smaller compared to estimates obtained from PK parameters. Across both the PK and plasma drug concentration across model, a moderate heritability was estimated. The model that utilized the plasma drug

  13. Wind power electricity: the bigger the turbine, the greener the electricity?

    Science.gov (United States)

    Caduff, Marloes; Huijbregts, Mark A J; Althaus, Hans-Joerg; Koehler, Annette; Hellweg, Stefanie

    2012-05-01

    Wind energy is a fast-growing and promising renewable energy source. The investment costs of wind turbines have decreased over the years, making wind energy economically competitive to conventionally produced electricity. Size scaling in the form of a power law, experience curves and progress rates are used to estimate the cost development of ever-larger turbines. In life cycle assessment, scaling and progress rates are seldom applied to estimate the environmental impacts of wind energy. This study quantifies whether the trend toward larger turbines affects the environmental profile of the generated electricity. Previously published life cycle inventories were combined with an engineering-based scaling approach as well as European wind power statistics. The results showed that the larger the turbine is, the greener the electricity becomes. This effect was caused by pure size effects of the turbine (micro level) as well as learning and experience with the technology over time (macro level). The environmental progress rate was 86%, indicating that for every cumulative production doubling, the global warming potential per kWh was reduced by 14%. The parameters, hub height and rotor diameter were identified as Environmental Key Performance Indicators that can be used to estimate the environmental impacts for a generic turbine. © 2012 American Chemical Society

  14. Measurement-Based Transmission Line Parameter Estimation with Adaptive Data Selection Scheme

    DEFF Research Database (Denmark)

    Li, Changgang; Zhang, Yaping; Zhang, Hengxu

    2017-01-01

    Accurate parameters of transmission lines are critical for power system operation and control decision making. Transmission line parameter estimation based on measured data is an effective way to enhance the validity of the parameters. This paper proposes a multi-point transmission line parameter...

  15. Automatic estimation of elasticity parameters in breast tissue

    Science.gov (United States)

    Skerl, Katrin; Cochran, Sandy; Evans, Andrew

    2014-03-01

    Shear wave elastography (SWE), a novel ultrasound imaging technique, can provide unique information about cancerous tissue. To estimate elasticity parameters, a region of interest (ROI) is manually positioned over the stiffest part of the shear wave image (SWI). The aim of this work is to estimate the elasticity parameters i.e. mean elasticity, maximal elasticity and standard deviation, fully automatically. Ultrasonic SWI of a breast elastography phantom and breast tissue in vivo were acquired using the Aixplorer system (SuperSonic Imagine, Aix-en-Provence, France). First, the SWI within the ultrasonic B-mode image was detected using MATLAB then the elasticity values were extracted. The ROI was automatically positioned over the stiffest part of the SWI and the elasticity parameters were calculated. Finally all values were saved in a spreadsheet which also contains the patient's study ID. This spreadsheet is easily available for physicians and clinical staff for further evaluation and so increase efficiency. Therewith the efficiency is increased. This algorithm simplifies the handling, especially for the performance and evaluation of clinical trials. The SWE processing method allows physicians easy access to the elasticity parameters of the examinations from their own and other institutions. This reduces clinical time and effort and simplifies evaluation of data in clinical trials. Furthermore, reproducibility will be improved.

  16. The Impact of Variable Wind Shear Coefficients on Risk Reduction of Wind Energy Projects.

    Science.gov (United States)

    Corscadden, Kenneth W; Thomson, Allan; Yoonesi, Behrang; McNutt, Josiah

    2016-01-01

    Estimation of wind speed at proposed hub heights is typically achieved using a wind shear exponent or wind shear coefficient (WSC), variation in wind speed as a function of height. The WSC is subject to temporal variation at low and high frequencies, ranging from diurnal and seasonal variations to disturbance caused by weather patterns; however, in many cases, it is assumed that the WSC remains constant. This assumption creates significant error in resource assessment, increasing uncertainty in projects and potentially significantly impacting the ability to control gird connected wind generators. This paper contributes to the body of knowledge relating to the evaluation and assessment of wind speed, with particular emphasis on the development of techniques to improve the accuracy of estimated wind speed above measurement height. It presents an evaluation of the use of a variable wind shear coefficient methodology based on a distribution of wind shear coefficients which have been implemented in real time. The results indicate that a VWSC provides a more accurate estimate of wind at hub height, ranging from 41% to 4% reduction in root mean squared error (RMSE) between predicted and actual wind speeds when using a variable wind shear coefficient at heights ranging from 33% to 100% above the highest actual wind measurement.

  17. On wake modeling, wind-farm gradients, and AEP predictions at the Anholt wind farm

    Directory of Open Access Journals (Sweden)

    A. Peña

    2018-04-01

    Full Text Available We investigate wake effects at the Anholt offshore wind farm in Denmark, which is a farm experiencing strong horizontal wind-speed gradients because of its size and proximity to land. Mesoscale model simulations are used to study the horizontal wind-speed gradients over the wind farm. From analysis of the mesoscale simulations and supervisory control and data acquisition (SCADA, we show that for westerly flow in particular, there is a clear horizontal wind-speed gradient over the wind farm. We also use the mesoscale simulations to derive the undisturbed inflow conditions that are coupled with three commonly used wake models: two engineering approaches (the Park and G. C. Larsen models and a linearized Reynolds-averaged Navier–Stokes approach (Fuga. The effect of the horizontal wind-speed gradient on annual energy production estimates is not found to be critical compared to estimates from both the average undisturbed wind climate of all turbines' positions and the undisturbed wind climate of a position in the middle of the wind farm. However, annual energy production estimates can largely differ when using wind climates at positions that are strongly influenced by the horizontal wind-speed gradient. When looking at westerly flow wake cases, where the impact of the horizontal wind-speed gradient on the power of the undisturbed turbines is largest, the wake models agree with the SCADA fairly well; when looking at a southerly flow case, where the wake losses are highest, the wake models tend to underestimate the wake loss. With the mesoscale-wake model setup, we are also able to estimate the capacity factor of the wind farm rather well when compared to that derived from the SCADA. Finally, we estimate the uncertainty of the wake models by bootstrapping the SCADA. The models tend to underestimate the wake losses (the median relative model error is 8.75 % and the engineering wake models are as uncertain as Fuga. These results are specific for

  18. Identification of variables for site calibration and power curve assessment in complex terrain. Task 8, a literature survey on theory and practice of parameter identification, specification and estimation (ISE) techniques

    Energy Technology Data Exchange (ETDEWEB)

    Verhoef, J.P.; Leendertse, G.P. [ECN Wind, Petten (Netherlands)

    2001-04-01

    This document presents the literature survey results on Identification, Specification and Estimation (ISE) techniques for variables within the SiteParIden project. Besides an overview of the different general techniques also an overview is given on EU funded wind energy projects where some of these techniques have been applied more specifically. The main problem in applications like power performance assessment and site calibration is to establish an appropriate model for predicting the considered dependent variable with the aid of measured independent (explanatory) variables. In these applications detailed knowledge on what the relevant variables are and how their precise appearance in the model would be is typically missing. Therefore, the identification (of variables) and the specification (of the model relation) are important steps in the model building phase. For the determination of the parameters in the model a reliable variable estimation technique is required. In EU funded wind energy projects the linear regression technique is the most commonly applied tool for the estimation step. The linear regression technique may fail in finding reliable parameter estimates when the model variables are strongly correlated, either due to the experimental set-up or because of their particular appearance in the model. This situation of multicollinearity sometimes results in unrealistic parameter values, e.g. with the wrong algebraic sign. It is concluded that different approaches, like multi-binning can provide a better way of identifying the relevant variables. However further research in these applications is needed and it is recommended that alternative methods (neural networks, singular value decomposition etc.) should also be tested on their usefulness in a succeeding project. Increased interest in complex terrains, as feasible locations for wind farms, has also emphasised the need for adequate models. A common standard procedure to prescribe the statistical

  19. Adaptive Parameter Estimation of Person Recognition Model in a Stochastic Human Tracking Process

    Science.gov (United States)

    Nakanishi, W.; Fuse, T.; Ishikawa, T.

    2015-05-01

    This paper aims at an estimation of parameters of person recognition models using a sequential Bayesian filtering method. In many human tracking method, any parameters of models used for recognize the same person in successive frames are usually set in advance of human tracking process. In real situation these parameters may change according to situation of observation and difficulty level of human position prediction. Thus in this paper we formulate an adaptive parameter estimation using general state space model. Firstly we explain the way to formulate human tracking in general state space model with their components. Then referring to previous researches, we use Bhattacharyya coefficient to formulate observation model of general state space model, which is corresponding to person recognition model. The observation model in this paper is a function of Bhattacharyya coefficient with one unknown parameter. At last we sequentially estimate this parameter in real dataset with some settings. Results showed that sequential parameter estimation was succeeded and were consistent with observation situations such as occlusions.

  20. CosmoSIS: A System for MC Parameter Estimation

    Energy Technology Data Exchange (ETDEWEB)

    Zuntz, Joe [Manchester U.; Paterno, Marc [Fermilab; Jennings, Elise [Chicago U., EFI; Rudd, Douglas [U. Chicago; Manzotti, Alessandro [Chicago U., Astron. Astrophys. Ctr.; Dodelson, Scott [Chicago U., Astron. Astrophys. Ctr.; Bridle, Sarah [Manchester U.; Sehrish, Saba [Fermilab; Kowalkowski, James [Fermilab

    2015-01-01

    Cosmological parameter estimation is entering a new era. Large collaborations need to coordinate high-stakes analyses using multiple methods; furthermore such analyses have grown in complexity due to sophisticated models of cosmology and systematic uncertainties. In this paper we argue that modularity is the key to addressing these challenges: calculations should be broken up into interchangeable modular units with inputs and outputs clearly defined. We present a new framework for cosmological parameter estimation, CosmoSIS, designed to connect together, share, and advance development of inference tools across the community. We describe the modules already available in Cosmo- SIS, including camb, Planck, cosmic shear calculations, and a suite of samplers. We illustrate it using demonstration code that you can run out-of-the-box with the installer available at http://bitbucket.org/joezuntz/cosmosis.