Tidal influence on offshore wind fields and resource predictions[Efficient Development of Offshore Windfarms

Energy Technology Data Exchange (ETDEWEB)

Khan, D. [Entec UK Ltd., Doherty Innovation Centre, Penicuik (United Kingdom); Infield, D. [Loughborough Univ., Centre for Renewable Energy Systems Tecnology, Loughborough (United Kingdom)

2002-03-01

The rise and fall of the sea surface due to tides effectively moves an offshore wind turbine hub through the wind shear profile. This effect is quantified using measured data from 3 offshore UK sites. Statistical evidence of the influence of tide on mean wind speed and turbulence is presented. The implications of this effect for predicting offshore wind resource are outlined. (au)

Influence of orographically steered winds on Mutsu Bay surface currents

Science.gov (United States)

Yamaguchi, Satoshi; Kawamura, Hiroshi

2005-09-01

Effects of spatially dependent sea surface wind field on currents in Mutsu Bay, which is located at the northern end of Japanese Honshu Island, are investigated using winds derived from synthetic aperture radar (SAR) images and a numerical model. A characteristic wind pattern over the bay was evidenced from analysis of 118 SAR images and coincided with in situ observations. Wind is topographically steered with easterly winds entering the bay through the terrestrial gap and stronger wind blowing over the central water toward its mouth. Nearshore winds are weaker due to terrestrial blockages. Using the Princeton Ocean Model, we investigated currents forced by the observed spatially dependent wind field. The predicted current pattern agrees well with available observations. For a uniform wind field of equal magnitude and average direction, the circulation pattern departs from observations demonstrating that vorticity input due to spatially dependent wind stress is essential in generation of the wind-driven current in Mutsu Bay.

How important is getting the land surface energy exchange correct in WRF for wind energy forecasting?

Science.gov (United States)

Wharton, S.; Simpson, M.; Osuna, J. L.; Newman, J. F.; Biraud, S.

2013-12-01

Wind power forecasting is plagued with difficulties in accurately predicting the occurrence and intensity of atmospheric conditions at the heights spanned by industrial-scale turbines (~ 40 to 200 m above ground level). Better simulation of the relevant physics would enable operational practices such as integration of large fractions of wind power into power grids, scheduling maintenance on wind energy facilities, and deciding design criteria based on complex loads for next-generation turbines and siting. Accurately simulating the surface energy processes in numerical models may be critically important for wind energy forecasting as energy exchange at the surface strongly drives atmospheric mixing (i.e., stability) in the lower layers of the planetary boundary layer (PBL), which in turn largely determines wind shear and turbulence at heights found in the turbine rotor-disk. We hypothesize that simulating accurate a surface-atmosphere energy coupling should lead to more accurate predictions of wind speed and turbulence at heights within the turbine rotor-disk. Here, we tested 10 different land surface model configurations in the Weather Research and Forecasting (WRF) model including Noah, Noah-MP, SSiB, Pleim-Xiu, RUC, and others to evaluate (1) the accuracy of simulated surface energy fluxes to flux tower measurements, (2) the accuracy of forecasted wind speeds to observations at rotor-disk heights, and (3) the sensitivity of forecasting hub-height rotor disk wind speed to the choice of land surface model. WRF was run for four, two-week periods covering both summer and winter periods over the Southern Great Plains ARM site in Oklahoma. Continuous measurements of surface energy fluxes and lidar-based wind speed, direction and turbulence were also available. The SGP ARM site provided an ideal location for this evaluation as it centrally located in the wind-rich Great Plains and multi-MW wind farms are rapidly expanding in the area. We found significant differences in

Improved Wind Speed Prediction Using Empirical Mode Decomposition

Directory of Open Access Journals (Sweden)

ZHANG, Y.

2018-05-01

Full Text Available Wind power industry plays an important role in promoting the development of low-carbon economic and energy transformation in the world. However, the randomness and volatility of wind speed series restrict the healthy development of the wind power industry. Accurate wind speed prediction is the key to realize the stability of wind power integration and to guarantee the safe operation of the power system. In this paper, combined with the Empirical Mode Decomposition (EMD, the Radial Basis Function Neural Network (RBF and the Least Square Support Vector Machine (SVM, an improved wind speed prediction model based on Empirical Mode Decomposition (EMD-RBF-LS-SVM is proposed. The prediction result indicates that compared with the traditional prediction model (RBF, LS-SVM, the EMD-RBF-LS-SVM model can weaken the random fluctuation to a certain extent and improve the short-term accuracy of wind speed prediction significantly. In a word, this research will significantly reduce the impact of wind power instability on the power grid, ensure the power grid supply and demand balance, reduce the operating costs in the grid-connected systems, and enhance the market competitiveness of the wind power.

Short-term wind power prediction

DEFF Research Database (Denmark)

Joensen, Alfred K.

2003-01-01

, and to implement these models and methods in an on-line software application. The economical value of having predictions available is also briefly considered. The summary report outlines the background and motivation for developing wind power prediction models. The meteorological theory which is relevant......The present thesis consists of 10 research papers published during the period 1997-2002 together with a summary report. The objective of the work described in the thesis is to develop models and methods for calculation of high accuracy predictions of wind power generated electricity...

Modeling wind adjustment factor and midflame wind speed for Rothermel's surface fire spread model

Science.gov (United States)

Patricia L. Andrews

2012-01-01

Rothermel's surface fire spread model was developed to use a value for the wind speed that affects surface fire, called midflame wind speed. Models have been developed to adjust 20-ft wind speed to midflame wind speed for sheltered and unsheltered surface fuel. In this report, Wind Adjustment Factor (WAF) model equations are given, and the BehavePlus fire modeling...

Skill forecasting from ensemble predictions of wind power

DEFF Research Database (Denmark)

Pinson, Pierre; Nielsen, Henrik Aalborg; Madsen, Henrik

2009-01-01

Optimal management and trading of wind generation calls for the providing of uncertainty estimates along with the commonly provided short-term wind power point predictions. Alternative approaches for the use of probabilistic forecasting are introduced. More precisely, focus is given to prediction...... risk indices aiming to give a comprehensive signal on the expected level of forecast uncertainty. Ensemble predictions of wind generation are used as input. A proposal for the definition of prediction risk indices is given. Such skill forecasts are based on the spread of ensemble forecasts (i.e. a set...... of alternative scenarios for the coming period) for a single prediction horizon or over a took-ahead period. It is shown on the test case of a Danish offshore wind farm how these prediction risk indices may be related to several levels of forecast uncertainty (and potential energy imbalances). Wind power...

Wind prediction in Malaysia using Mycielski-1 approach

Science.gov (United States)

Lee, S. W.; Kok, B. C.; Goh, K. C.; Goh, H. H.

2012-11-01

In this paper, the wind speed prediction in Kudat, Malaysia had been done by using Mycielski-1 approach. There is some improvement in obtaining the random number of Mycielski-1. The wind prediction is important to study a favorable site's wind potential. The prediction is based on 3 years history data provided by Meteorology Department of Malaysia and 1 year data as the reference to check the accuracy of this algorithm. The basic concept of this algorithm is to predict the next value by looking to history data. The result shows the prediction of Mycielski-1 algorithm is promising. The wind speed is predicted in order to obtain the mean power for energy planning.

Forced synchronization of large-scale circulation to increase predictability of surface states

Science.gov (United States)

Shen, Mao-Lin; Keenlyside, Noel; Selten, Frank; Wiegerinck, Wim; Duane, Gregory

2016-04-01

Numerical models are key tools in the projection of the future climate change. The lack of perfect initial condition and perfect knowledge of the laws of physics, as well as inherent chaotic behavior limit predictions. Conceptually, the atmospheric variables can be decomposed into a predictable component (signal) and an unpredictable component (noise). In ensemble prediction the anomaly of ensemble mean is regarded as the signal and the ensemble spread the noise. Naturally the prediction skill will be higher if the signal-to-noise ratio (SNR) is larger in the initial conditions. We run two ensemble experiments in order to explore a way to reduce the SNR of surface winds and temperature. One ensemble experiment is AGCM with prescribing sea surface temperature (SST); the other is AGCM with both prescribing SST and nudging the high-level temperature and winds to ERA-Interim. Each ensemble has 30 members. Larger SNR is expected and found over the tropical ocean in the first experiment because the tropical circulation is associated with the convection and the associated surface wind convergence as these are to a large extent driven by the SST. However, small SNR is found over high latitude ocean and land surface due to the chaotic and non-synchronized atmosphere states. In the second experiment the higher level temperature and winds are forced to be synchronized (nudged to reanalysis) and hence a larger SNR of surface winds and temperature is expected. Furthermore, different nudging coefficients are also tested in order to understand the limitation of both synchronization of large-scale circulation and the surface states. These experiments will be useful for the developing strategies to synchronize the 3-D states of atmospheric models that can be later used to build a super model.

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....

FY 1998 Report on development of large-scale wind power generation systems. Feasibility study on development of new technologies for wind power generation, and study on local wind resource prediction model; 1998 nendo ogata furyoku hatsuden system kaihatsu seika hokokusho. Furyoku hatsuden shingijutsu kaihatsu kanosei chosa (kyokusho fukyo yosoku shuho ni kansuru chosa)

Energy Technology Data Exchange (ETDEWEB)

NONE

1999-03-01

Described herein are the FY 1998 results of the study on local wind resource prediction model. The local wind resource prediction models developed so far apply the solutions based on the existing linear models (WASP and AVENU) for relatively flat terrain. These models are studied for their applicability limits. The study covers wind direction and speed patterns of the surface wind and upper winds at 3 sites in Hokkaido, Fukushima Pref. and Shizuoka Pref. The surface winds are found to be correlated with the upper winds both for wind direction and wind speed in almost all cases. Next, wind resources simulations are carried out for each of the classified weather patterns using the existing models, and the prediction errors are studied. The results show that the prediction accuracy of the existing linear models is highly dependent on inputs of observed data, and that the accuracy tends to decrease for the situations where the upper and surface wind conditions greatly differ from each other, as in the case of a land and sea breeze of thermal origin. It is also confirmed that prediction accuracy is lower on complex terrain than on flat terrain. (NEDO)

Statistical downscaling of historical monthly mean winds over a coastal region of complex terrain. I. Predicting wind speed

Energy Technology Data Exchange (ETDEWEB)

Curry, Charles L. [Canadian Centre for Climate Modelling and Analysis, Environment Canada, University of Victoria, Victoria, BC (Canada); School of Earth and Ocean Sciences, University of Victoria, Victoria, BC (Canada); Kamp, Derek van der [School of Earth and Ocean Sciences, University of Victoria, Victoria, BC (Canada); Pacific Climate Impacts Consortium, University of Victoria, Victoria, BC (Canada); Monahan, Adam H. [School of Earth and Ocean Sciences, University of Victoria, Victoria, BC (Canada)

2012-04-15

Surface wind speed is a key climatic variable of interest in many applications, including assessments of storm-related infrastructure damage and feasibility studies of wind power generation. In this work and a companion paper (van der Kamp et al. 2011), the relationship between local surface wind and large-scale climate variables was studied using multiple regression analysis. The analysis was performed using monthly mean station data from British Columbia, Canada and large-scale climate variables (predictors) from the NCEP-2 reanalysis over the period 1979-2006. Two regression-based methodologies were compared. The first relates the annual cycle of station wind speed to that of the large-scale predictors at the closest grid box to the station. It is shown that the relatively high correlation coefficients obtained with this method are attributable to the dominant influence of region-wide seasonality, and thus contain minimal information about local wind behaviour at the stations. The second method uses interannually varying data for individual months, aggregated into seasons, and is demonstrated to contain intrinsically local information about the surface winds. The dependence of local wind speed upon large-scale predictors over a much larger region surrounding the station was also explored, resulting in 2D maps of spatial correlations. The cross-validated explained variance using the interannual method was highest in autumn and winter, ranging from 30 to 70% at about a dozen stations in the region. Reasons for the limited predictive skill of the regressions and directions for future progress are reviewed. (orig.)

Offshore Wind Energy: Wind and Sea Surface Temperature from Satellite Observations

DEFF Research Database (Denmark)

Karagali, Ioanna

as the entire atmosphere above. Under conditions of light winds and strong solar insolation, warming of the upper oceanic layer may occur. In this PhD study, remote sensing from satellites is used to obtain information for the near-surface ocean wind and the sea surface temperature over the North Sea......, demonstrate that wind information from SAR is more appropriate when small scale local features are of interest, not resolved by scatterometers. Hourly satellite observations of the sea surface temperature, from a thermal infra-red sensor, are used to identify and quantify the daily variability of the sea...

Satellite Remote Sensing of Ocean Winds, Surface Waves and Surface Currents during the Hurricanes

Science.gov (United States)

Zhang, G.; Perrie, W. A.; Liu, G.; Zhang, L.

2017-12-01

Hurricanes over the ocean have been observed by spaceborne aperture radar (SAR) since the first SAR images were available in 1978. SAR has high spatial resolution (about 1 km), relatively large coverage and capability for observations during almost all-weather, day-and-night conditions. In this study, seven C-band RADARSAT-2 dual-polarized (VV and VH) ScanSAR wide images from the Canadian Space Agency (CSA) Hurricane Watch Program in 2017 are collected over five hurricanes: Harvey, Irma, Maria, Nate, and Ophelia. We retrieve the ocean winds by applying our C-band Cross-Polarization Coupled-Parameters Ocean (C-3PO) wind retrieval model [Zhang et al., 2017, IEEE TGRS] to the SAR images. Ocean waves are estimated by applying a relationship based on the fetch- and duration-limited nature of wave growth inside hurricanes [Hwang et al., 2016; 2017, J. Phys. Ocean.]. We estimate the ocean surface currents using the Doppler Shift extracted from VV-polarized SAR images [Kang et al., 2016, IEEE TGRS]. C-3PO model is based on theoretical analysis of ocean surface waves and SAR microwave backscatter. Based on the retrieved ocean winds, we estimate the hurricane center locations, maxima wind speeds, and radii of the five hurricanes by adopting the SHEW model (Symmetric Hurricane Estimates for Wind) by Zhang et al. [2017, IEEE TGRS]. Thus, we investigate possible relations between hurricane structures and intensities, and especially some possible effects of the asymmetrical characteristics on changes in the hurricane intensities, such as the eyewall replacement cycle. The three SAR images of Ophelia include the north coast of Ireland and east coast of Scotland allowing study of ocean surface currents respond to the hurricane. A system of methods capable of observing marine winds, surface waves, and surface currents from satellites is of value, even if these data are only available in near real-time or from SAR-related satellite images. Insight into high resolution ocean winds

Frequency weighted model predictive control of wind turbine

DEFF Research Database (Denmark)

Klauco, Martin; Poulsen, Niels Kjølstad; Mirzaei, Mahmood

2013-01-01

This work is focused on applying frequency weighted model predictive control (FMPC) on three blade horizontal axis wind turbine (HAWT). A wind turbine is a very complex, non-linear system influenced by a stochastic wind speed variation. The reduced dynamics considered in this work are the rotatio...... predictive controller are presented. Statistical comparison between frequency weighted MPC, standard MPC and baseline PI controller is shown as well.......This work is focused on applying frequency weighted model predictive control (FMPC) on three blade horizontal axis wind turbine (HAWT). A wind turbine is a very complex, non-linear system influenced by a stochastic wind speed variation. The reduced dynamics considered in this work...... are the rotational degree of freedom of the rotor and the tower for-aft movement. The MPC design is based on a receding horizon policy and a linearised model of the wind turbine. Due to the change of dynamics according to wind speed, several linearisation points must be considered and the control design adjusted...

One-level modeling for diagnosing surface winds over complex terrain. II - Applicability to short-range forecasting

Science.gov (United States)

Alpert, P.; Getenio, B.; Zak-Rosenthal, R.

1988-01-01

The Alpert and Getenio (1988) modification of the Mass and Dempsey (1985) one-level sigma-surface model was used to study four synoptic events that included two winter cases (a Cyprus low and a Siberian high) and two summer cases. Results of statistical verification showed that the model is not only capable of diagnosing many details of surface mesoscale flow, but might also be useful for various applications which require operative short-range prediction of the diurnal changes of high-resolution surface flow over complex terrain, for example, in locating wildland fires, determining the dispersion of air pollutants, and predicting changes in wind energy or of surface wind for low-level air flights.

Short-Term Wind Speed Prediction Using EEMD-LSSVM Model

Directory of Open Access Journals (Sweden)

Aiqing Kang

2017-01-01

Full Text Available Hybrid Ensemble Empirical Mode Decomposition (EEMD and Least Square Support Vector Machine (LSSVM is proposed to improve short-term wind speed forecasting precision. The EEMD is firstly utilized to decompose the original wind speed time series into a set of subseries. Then the LSSVM models are established to forecast these subseries. Partial autocorrelation function is adopted to analyze the inner relationships between the historical wind speed series in order to determine input variables of LSSVM models for prediction of every subseries. Finally, the superposition principle is employed to sum the predicted values of every subseries as the final wind speed prediction. The performance of hybrid model is evaluated based on six metrics. Compared with LSSVM, Back Propagation Neural Networks (BP, Auto-Regressive Integrated Moving Average (ARIMA, combination of Empirical Mode Decomposition (EMD with LSSVM, and hybrid EEMD with ARIMA models, the wind speed forecasting results show that the proposed hybrid model outperforms these models in terms of six metrics. Furthermore, the scatter diagrams of predicted versus actual wind speed and histograms of prediction errors are presented to verify the superiority of the hybrid model in short-term wind speed prediction.

Predicting the Extreme Loads on a Wind Turbine Considering Uncertainty in Airfoil Data

DEFF Research Database (Denmark)

Abdallah, Imad; Natarajan, Anand; Sørensen, John Dalsgaard

2014-01-01

The sources contributing to uncertainty in a wind turbine blade static airfoil data include wind tunnel testing, CFD calculations, 3D rotational corrections based on CFD or emprircal models, surface roughness corrections, Reynolds number corrections, expansion to the full 360-degree angle of attack...... range, validation by full scale measurements, and geometric distortions of the blade during manufacturing and under loading. In this paper a stochastic model of the static airfoil data is proposed to supplement the prediction of extreme loads effects for large wind turbines. It is shown...... that the uncertainty in airfoil data can have e significant impact on the prediction of extreme loads effects depending on the component, and the correlation along the span of the blade....

The wind power prediction research based on mind evolutionary algorithm

Science.gov (United States)

Zhuang, Ling; Zhao, Xinjian; Ji, Tianming; Miao, Jingwen; Cui, Haina

2018-04-01

When the wind power is connected to the power grid, its characteristics of fluctuation, intermittent and randomness will affect the stability of the power system. The wind power prediction can guarantee the power quality and reduce the operating cost of power system. There were some limitations in several traditional wind power prediction methods. On the basis, the wind power prediction method based on Mind Evolutionary Algorithm (MEA) is put forward and a prediction model is provided. The experimental results demonstrate that MEA performs efficiently in term of the wind power prediction. The MEA method has broad prospect of engineering application.

Aeolian sediment transport on a beach: Surface moisture, wind fetch, and mean transport

Science.gov (United States)

Bauer, B. O.; Davidson-Arnott, R. G. D.; Hesp, P. A.; Namikas, S. L.; Ollerhead, J.; Walker, I. J.

2009-04-01

Temporal and spatial changes in wind speed, wind direction, and moisture content are ubiquitous across sandy coastal beaches. Often these factors interact in unknown ways to create complexity that confounds our ability to model sediment transport at any point across the beach as well as our capacity to predict sediment delivery into the adjacent foredunes. This study was designed to measure wind flow and sediment transport over a beach and foredune at Greenwich Dunes, Prince Edward Island National Park, with the express purpose of addressing these complex interactions. Detailed measurements are reported for one stormy day, October 11, 2004, during which meteorological conditions were highly variable. Wind speed ranged from 4 ms - 1 to over 20 ms - 1 , wind direction was highly oblique varying between 60° and 85° from shore perpendicular, and moisture content of the sand surface ranged from a minimum of about 3% (by mass) to complete saturation depending on precipitation, tidal excursion, and storm surge that progressively inundated the beach. The data indicate that short-term variations (i.e., minutes to hours) in sediment transport across this beach arise predominantly because of short-term changes in wind speed, as is expected, but also because of variations in wind direction, precipitation intensity, and tide level. Even slight increases in wind speed are capable of driving more intense saltation events, but this relationship is mediated by other factors on this characteristically narrow beach. As the angle of wind approach becomes more oblique, the fetch distance increases and allows greater opportunity for the saltation system to evolve toward an equilibrium transport state before reaching the foredunes. Whether the theoretically-predicted maximum rate of transport is ever achieved depends on the character of the sand surface (e.g., grain size, slope, roughness, vegetation, moisture content) and on various attributes of the wind field (e.g., average wind

Surface drag effects on simulated wind fields in high-resolution atmospheric forecast model

Energy Technology Data Exchange (ETDEWEB)

Lim, Kyo Sun; Lim, Jong Myoung; Ji, Young Yong [Environmental Radioactivity Assessment Team,Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of); Shin, Hye Yum [NOAA/Geophysical Fluid Dynamics Laboratory, Princeton (United States); Hong, Jin Kyu [Yonsei University, Seoul (Korea, Republic of)

2017-04-15

It has been reported that the Weather Research and Forecasting (WRF) model generally shows a substantial over prediction bias at low to moderate wind speeds and winds are too geostrophic (Cheng and Steenburgh 2005), which limits the application of WRF model in the area that requires the accurate surface wind estimation such as wind-energy application, air-quality studies, and radioactive-pollutants dispersion studies. The surface drag generated by the subgrid-scale orography is represented by introducing a sink term in the momentum equation in their studies. The purpose of our study is to evaluate the simulated meteorological fields in the high-resolution WRF framework, that includes the parameterization of subgrid-scale orography developed by Mass and Ovens (2010), and enhance the forecast skill of low-level wind fields, which plays an important role in transport and dispersion of air pollutants including radioactive pollutants. The positive bias in 10-m wind speed is significantly alleviated by implementing the subgrid-scale orography parameterization, while other meteorological fields including 10-m wind direction are not changed. Increased variance of subgrid- scale orography enhances the sink of momentum and further reduces the bias in 10-m wind speed.

Observational study of surface wind along a sloping surface over mountainous terrain during winter

Science.gov (United States)

Lee, Young-Hee; Lee, Gyuwon; Joo, Sangwon; Ahn, Kwang-Deuk

2018-03-01

The 2018 Winter Olympic and Paralympic Games will be held in Pyeongchang, Korea, during February and March. We examined the near surface winds and wind gusts along the sloping surface at two outdoor venues in Pyeongchang during February and March using surface wind data. The outdoor venues are located in a complex, mountainous terrain, and hence the near-surface winds form intricate patterns due to the interplay between large-scale and locally forced winds. During February and March, the dominant wind at the ridge level is westerly; however, a significant wind direction change is observed along the sloping surface at the venues. The winds on the sloping surface are also influenced by thermal forcing, showing increased upslope flow during daytime. When neutral air flows over the hill, the windward and leeward flows show a significantly different behavior. A higher correlation of the wind speed between upper- and lower-level stations is shown in the windward region compared with the leeward region. The strong synoptic wind, small width of the ridge, and steep leeward ridge slope angle provide favorable conditions for flow separation at the leeward foot of the ridge. The gust factor increases with decreasing surface elevation and is larger during daytime than nighttime. A significantly large gust factor is also observed in the leeward region.

Using meteorological forecasts in on-line predictions of wind power

DEFF Research Database (Denmark)

Nielsen, Torben Skov; Nielsen, Henrik Aalborg; Madsen, Henrik

1999-01-01

This report describes a model investigation into wind power prediction model as well as a tool for predicting the power production from wind turbines in an area - the Wind Power Prediction Tool (WPPT). The predictions are based on on-line measurements of power production for a selected set...

Calculating the sensitivity of wind turbine loads to wind inputs using response surfaces

International Nuclear Information System (INIS)

Rinker, Jennifer M.

2016-01-01

This paper presents a methodology to calculate wind turbine load sensitivities to turbulence parameters through the use of response surfaces. A response surface is a highdimensional polynomial surface that can be calibrated to any set of input/output data and then used to generate synthetic data at a low computational cost. Sobol sensitivity indices (SIs) can then be calculated with relative ease using the calibrated response surface. The proposed methodology is demonstrated by calculating the total sensitivity of the maximum blade root bending moment of the WindPACT 5 MW reference model to four turbulence input parameters: a reference mean wind speed, a reference turbulence intensity, the Kaimal length scale, and a novel parameter reflecting the nonstationarity present in the inflow turbulence. The input/output data used to calibrate the response surface were generated for a previous project. The fit of the calibrated response surface is evaluated in terms of error between the model and the training data and in terms of the convergence. The Sobol SIs are calculated using the calibrated response surface, and the convergence is examined. The Sobol SIs reveal that, of the four turbulence parameters examined in this paper, the variance caused by the Kaimal length scale and nonstationarity parameter are negligible. Thus, the findings in this paper represent the first systematic evidence that stochastic wind turbine load response statistics can be modeled purely by mean wind wind speed and turbulence intensity. (paper)

Assessment and prediction of wind turbine noise

International Nuclear Information System (INIS)

Lowson, M.V.

1993-01-01

The significance of basic aerodynamic noise sources for wind turbine noise are assessed, using information on the aero-acoustic mechanisms of other rotors, which have been studied in depth for many years. From the analysis, areas of potential improvement in wind turbine noise prediction are defined. Suggestions are made for approaches to wind turbine noise control which separate the noise problems at cut-in from those at rated power. Some of these offer the possibility of noise reduction without unfavourable effects on performance. Based on this analysis, a new model for prediction of wind turbine noise is presented and comparisons made between prediction and experiment. The model is based on well established aeroacoustic theory and published laboratory data for the two principal sources, inflow turbulence and boundary layer trailing edge interaction. The new method gives good agreement with experiment with the case studied so far. Parametric trends and sensitivities for the model are presented. Comparisons with previous prediction methods are also given. A consequence of the new model is to put more emphasis on boundary layer trailing edge interaction as a noise source. There are prospects for reducing noise from this source detail changes to the wind turbine design. (author)

Wind Speed Prediction with Wavelet Time Series Based on Lorenz Disturbance

Directory of Open Access Journals (Sweden)

ZHANG, Y.

2017-08-01

Full Text Available Due to the sustainable and pollution-free characteristics, wind energy has been one of the fastest growing renewable energy sources. However, the intermittent and random fluctuation of wind speed presents many challenges for reliable wind power integration and normal operation of wind farm. Accurate wind speed prediction is the key to ensure the safe operation of power system and to develop wind energy resources. Therefore, this paper has presented a wavelet time series wind speed prediction model based on Lorenz disturbance. Therefore, in this paper, combined with the atmospheric dynamical system, a wavelet-time series improved wind speed prediction model based on Lorenz disturbance is proposed and the wind turbines of different climate types in Spain and China are used to simulate the disturbances of Lorenz equations with different initial values. The prediction results show that the improved model can effectively correct the preliminary prediction of wind speed, improving the prediction. In a word, the research work in this paper will be helpful to arrange the electric power dispatching plan and ensure the normal operation of the wind farm.

Wind speed and direction shears with associated vertical motion during strong surface winds

Science.gov (United States)

Alexander, M. B.; Camp, D. W.

1984-01-01

Strong surface winds recorded at the NASA 150-Meter Ground Winds Tower facility at Kennedy Space Center, Florida, are analyzed to present occurrences representative of wind shear and vertical motion known to be hazardous to the ascent and descent of conventional aircraft and the Space Shuttle. Graphical (percentage frequency distributions) and mathematical (maximum, mean, standard deviation) descriptions of wind speed and direction shears and associated updrafts and downdrafts are included as functions of six vertical layers and one horizontal distance for twenty 5-second intervals of parameters sampled simultaneously at the rate of ten per second during a period of high surface winds.

Short-term wind power prediction based on LSSVM–GSA model

International Nuclear Information System (INIS)

Yuan, Xiaohui; Chen, Chen; Yuan, Yanbin; Huang, Yuehua; Tan, Qingxiong

2015-01-01

Highlights: • A hybrid model is developed for short-term wind power prediction. • The model is based on LSSVM and gravitational search algorithm. • Gravitational search algorithm is used to optimize parameters of LSSVM. • Effect of different kernel function of LSSVM on wind power prediction is discussed. • Comparative studies show that prediction accuracy of wind power is improved. - Abstract: Wind power forecasting can improve the economical and technical integration of wind energy into the existing electricity grid. Due to its intermittency and randomness, it is hard to forecast wind power accurately. For the purpose of utilizing wind power to the utmost extent, it is very important to make an accurate prediction of the output power of a wind farm under the premise of guaranteeing the security and the stability of the operation of the power system. In this paper, a hybrid model (LSSVM–GSA) based on the least squares support vector machine (LSSVM) and gravitational search algorithm (GSA) is proposed to forecast the short-term wind power. As the kernel function and the related parameters of the LSSVM have a great influence on the performance of the prediction model, the paper establishes LSSVM model based on different kernel functions for short-term wind power prediction. And then an optimal kernel function is determined and the parameters of the LSSVM model are optimized by using GSA. Compared with the Back Propagation (BP) neural network and support vector machine (SVM) model, the simulation results show that the hybrid LSSVM–GSA model based on exponential radial basis kernel function and GSA has higher accuracy for short-term wind power prediction. Therefore, the proposed LSSVM–GSA is a better model for short-term wind power prediction

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

Using wind tunnels to predict bird mortality in wind farms: the case of griffon vultures.

Science.gov (United States)

de Lucas, Manuela; Ferrer, Miguel; Janss, Guyonne F E

2012-01-01

Wind farms have shown a spectacular growth during the last 15 years. Avian mortality through collision with moving rotor blades is well-known as one of the main adverse impacts of wind farms. In Spain, the griffon vulture incurs the highest mortality rates in wind farms. As far as we know, this study is the first attempt to predict flight trajectories of birds in order to foresee potentially dangerous areas for wind farm development. We analyse topography and wind flows in relation to flight paths of griffon vultures, using a scaled model of the wind farm area in an aerodynamic wind tunnel, and test the difference between the observed flight paths of griffon vultures and the predominant wind flows. Different wind currents for each wind direction in the aerodynamic model were observed. Simulations of wind flows in a wind tunnel were compared with observed flight paths of griffon vultures. No statistical differences were detected between the observed flight trajectories of griffon vultures and the wind passages observed in our wind tunnel model. A significant correlation was found between dead vultures predicted proportion of vultures crossing those cells according to the aerodynamic model. Griffon vulture flight routes matched the predominant wind flows in the area (i.e. they followed the routes where less flight effort was needed). We suggest using these kinds of simulations to predict flight paths over complex terrains can inform the location of wind turbines and thereby reduce soaring bird mortality.

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

Model Predictive Control with Constraints of a Wind Turbine

DEFF Research Database (Denmark)

Henriksen, Lars Christian; Poulsen, Niels Kjølstad

2007-01-01

Model predictive control of wind turbines offer a more systematic approach of constructing controllers that handle constraints while focusing on the main control objective. In this article several controllers are designed for different wind conditions and appropriate switching conditions ensure a...... an efficient control of the wind turbine over the entire range of wind speeds. Both onshore and floating offshore wind turbines are tested with the controllers.......Model predictive control of wind turbines offer a more systematic approach of constructing controllers that handle constraints while focusing on the main control objective. In this article several controllers are designed for different wind conditions and appropriate switching conditions ensure...

Field and numerical study of wind and surface waves at short fetches

Science.gov (United States)

Baydakov, Georgy; Kuznetsova, Alexandra; Sergeev, Daniil; Papko, Vladislav; Kandaurov, Alexander; Vdovin, Maxim; Troitskaya, Yuliya

2016-04-01

Measurements were carried out in 2012-2015 from May to October in the waters of Gorky Reservoir belonging to the Volga Cascade. The methods of the experiment focus on the study of airflow in the close proximity to the water surface. The sensors were positioned at the oceanographic Froude buoy including five two-component ultrasonic sensors WindSonic by Gill Instruments at different levels (0.1, 0.85, 1.3, 2.27, 5.26 meters above the mean water surface level), one water and three air temperature sensors, and three-channel wire wave gauge. One of wind sensors (0.1 m) was located on the float tracking the waveform for measuring the wind speed in the close proximity to the water surface. Basic parameters of the atmospheric boundary layer (the friction velocity u∗, the wind speed U10 and the drag coefficient CD) were calculated from the measured profiles of wind speed. Parameters were obtained in the range of wind speeds of 1-12 m/s. For wind speeds stronger than 4 m/s CD values were lower than those obtained before (see eg. [1,2]) and those predicted by the bulk parameterization. However, for weak winds (less than 3 m/s) CD values considerably higher than expected ones. The new parameterization of surface drag coefficient was proposed on the basis of the obtained data. The suggested parameterization of drag coefficient CD(U10) was implemented within wind input source terms in WAVEWATCH III [3]. The results of the numerical experiments were compared with the results obtained in the field experiments on the Gorky Reservoir. The use of the new drag coefficient improves the agreement in significant wave heights HS [4]. At the same time, the predicted mean wave periods are overestimated using both built-in source terms and adjusted source terms. We associate it with the necessity of the adjusting of the DIA nonlinearity model in WAVEWATCH III to the conditions of the middle-sized reservoir. Test experiments on the adjusting were carried out. The work was supported by the

Wind speed prediction using statistical regression and neural network

Indian Academy of Sciences (India)

Prediction of wind speed in the atmospheric boundary layer is important for wind energy assess- ment,satellite launching and aviation,etc.There are a few techniques available for wind speed prediction,which require a minimum number of input parameters.Four different statistical techniques,viz.,curve fitting,Auto Regressive ...

Effect of accuracy of wind power prediction on power system operator

Science.gov (United States)

Schlueter, R. A.; Sigari, G.; Costi, T.

1985-01-01

This research project proposed a modified unit commitment that schedules connection and disconnection of generating units in response to load. A modified generation control is also proposed that controls steam units under automatic generation control, fast responding diesels, gas turbines and hydro units under a feedforward control, and wind turbine array output under a closed loop array control. This modified generation control and unit commitment require prediction of trend wind power variation one hour ahead and the prediction of error in this trend wind power prediction one half hour ahead. An improved meter for predicting trend wind speed variation is developed. Methods for accurately simulating the wind array power from a limited number of wind speed prediction records was developed. Finally, two methods for predicting the error in the trend wind power prediction were developed. This research provides a foundation for testing and evaluating the modified unit commitment and generation control that was developed to maintain operating reliability at a greatly reduced overall production cost for utilities with wind generation capacity.

Using wind tunnels to predict bird mortality in wind farms: the case of griffon vultures.

Directory of Open Access Journals (Sweden)

Manuela de Lucas

Full Text Available BACKGROUND: Wind farms have shown a spectacular growth during the last 15 years. Avian mortality through collision with moving rotor blades is well-known as one of the main adverse impacts of wind farms. In Spain, the griffon vulture incurs the highest mortality rates in wind farms. METHODOLOGY/PRINCIPAL FINDINGS: As far as we know, this study is the first attempt to predict flight trajectories of birds in order to foresee potentially dangerous areas for wind farm development. We analyse topography and wind flows in relation to flight paths of griffon vultures, using a scaled model of the wind farm area in an aerodynamic wind tunnel, and test the difference between the observed flight paths of griffon vultures and the predominant wind flows. Different wind currents for each wind direction in the aerodynamic model were observed. Simulations of wind flows in a wind tunnel were compared with observed flight paths of griffon vultures. No statistical differences were detected between the observed flight trajectories of griffon vultures and the wind passages observed in our wind tunnel model. A significant correlation was found between dead vultures predicted proportion of vultures crossing those cells according to the aerodynamic model. CONCLUSIONS: Griffon vulture flight routes matched the predominant wind flows in the area (i.e. they followed the routes where less flight effort was needed. We suggest using these kinds of simulations to predict flight paths over complex terrains can inform the location of wind turbines and thereby reduce soaring bird mortality.

Neural Network Classifiers for Local Wind Prediction.

Science.gov (United States)

Kretzschmar, Ralf; Eckert, Pierre; Cattani, Daniel; Eggimann, Fritz

2004-05-01

This paper evaluates the quality of neural network classifiers for wind speed and wind gust prediction with prediction lead times between +1 and +24 h. The predictions were realized based on local time series and model data. The selection of appropriate input features was initiated by time series analysis and completed by empirical comparison of neural network classifiers trained on several choices of input features. The selected input features involved day time, yearday, features from a single wind observation device at the site of interest, and features derived from model data. The quality of the resulting classifiers was benchmarked against persistence for two different sites in Switzerland. The neural network classifiers exhibited superior quality when compared with persistence judged on a specific performance measure, hit and false-alarm rates.

Model output statistics applied to wind power prediction

Energy Technology Data Exchange (ETDEWEB)

Joensen, A; Giebel, G; Landberg, L [Risoe National Lab., Roskilde (Denmark); Madsen, H; Nielsen, H A [The Technical Univ. of Denmark, Dept. of Mathematical Modelling, Lyngby (Denmark)

1999-03-01

Being able to predict the output of a wind farm online for a day or two in advance has significant advantages for utilities, such as better possibility to schedule fossil fuelled power plants and a better position on electricity spot markets. In this paper prediction methods based on Numerical Weather Prediction (NWP) models are considered. The spatial resolution used in NWP models implies that these predictions are not valid locally at a specific wind farm. Furthermore, due to the non-stationary nature and complexity of the processes in the atmosphere, and occasional changes of NWP models, the deviation between the predicted and the measured wind will be time dependent. If observational data is available, and if the deviation between the predictions and the observations exhibits systematic behavior, this should be corrected for; if statistical methods are used, this approaches is usually referred to as MOS (Model Output Statistics). The influence of atmospheric turbulence intensity, topography, prediction horizon length and auto-correlation of wind speed and power is considered, and to take the time-variations into account, adaptive estimation methods are applied. Three estimation techniques are considered and compared, Extended Kalman Filtering, recursive least squares and a new modified recursive least squares algorithm. (au) EU-JOULE-3. 11 refs.

A model to predict the power output from wind farms

Energy Technology Data Exchange (ETDEWEB)

Landberg, L. [Riso National Lab., Roskilde (Denmark)

1997-12-31

This paper will describe a model that can predict the power output from wind farms. To give examples of input the model is applied to a wind farm in Texas. The predictions are generated from forecasts from the NGM model of NCEP. These predictions are made valid at individual sites (wind farms) by applying a matrix calculated by the sub-models of WASP (Wind Atlas Application and Analysis Program). The actual wind farm production is calculated using the Riso PARK model. Because of the preliminary nature of the results, they will not be given. However, similar results from Europe will be given.

Ocean surface waves in Hurricane Ike (2008) and Superstorm Sandy (2012): Coupled model predictions and observations

Science.gov (United States)

Chen, Shuyi S.; Curcic, Milan

2016-07-01

Forecasting hurricane impacts of extreme winds and flooding requires accurate prediction of hurricane structure and storm-induced ocean surface waves days in advance. The waves are complex, especially near landfall when the hurricane winds and water depth varies significantly and the surface waves refract, shoal and dissipate. In this study, we examine the spatial structure, magnitude, and directional spectrum of hurricane-induced ocean waves using a high resolution, fully coupled atmosphere-wave-ocean model and observations. The coupled model predictions of ocean surface waves in Hurricane Ike (2008) over the Gulf of Mexico and Superstorm Sandy (2012) in the northeastern Atlantic and coastal region are evaluated with the NDBC buoy and satellite altimeter observations. Although there are characteristics that are general to ocean waves in both hurricanes as documented in previous studies, wave fields in Ike and Sandy possess unique properties due mostly to the distinct wind fields and coastal bathymetry in the two storms. Several processes are found to significantly modulate hurricane surface waves near landfall. First, the phase speed and group velocities decrease as the waves become shorter and steeper in shallow water, effectively increasing surface roughness and wind stress. Second, the bottom-induced refraction acts to turn the waves toward the coast, increasing the misalignment between the wind and waves. Third, as the hurricane translates over land, the left side of the storm center is characterized by offshore winds over very short fetch, which opposes incoming swell. Landfalling hurricanes produce broader wave spectra overall than that of the open ocean. The front-left quadrant is most complex, where the combination of windsea, swell propagating against the wind, increasing wind-wave stress, and interaction with the coastal topography requires a fully coupled model to meet these challenges in hurricane wave and surge prediction.

Skill forecasting from different wind power ensemble prediction methods

International Nuclear Information System (INIS)

Pinson, Pierre; Nielsen, Henrik A; Madsen, Henrik; Kariniotakis, George

2007-01-01

This paper presents an investigation on alternative approaches to the providing of uncertainty estimates associated to point predictions of wind generation. Focus is given to skill forecasts in the form of prediction risk indices, aiming at giving a comprehensive signal on the expected level of forecast uncertainty. Ensemble predictions of wind generation are used as input. A proposal for the definition of prediction risk indices is given. Such skill forecasts are based on the dispersion of ensemble members for a single prediction horizon, or over a set of successive look-ahead times. It is shown on the test case of a Danish offshore wind farm how prediction risk indices may be related to several levels of forecast uncertainty (and energy imbalances). Wind power ensemble predictions are derived from the transformation of ECMWF and NCEP ensembles of meteorological variables to power, as well as by a lagged average approach alternative. The ability of risk indices calculated from the various types of ensembles forecasts to resolve among situations with different levels of uncertainty is discussed

Using machine learning to predict wind turbine power output

International Nuclear Information System (INIS)

Clifton, A; Kilcher, L; Lundquist, J K; Fleming, P

2013-01-01

Wind turbine power output is known to be a strong function of wind speed, but is also affected by turbulence and shear. In this work, new aerostructural simulations of a generic 1.5 MW turbine are used to rank atmospheric influences on power output. Most significant is the hub height wind speed, followed by hub height turbulence intensity and then wind speed shear across the rotor disk. These simulation data are used to train regression trees that predict the turbine response for any combination of wind speed, turbulence intensity, and wind shear that might be expected at a turbine site. For a randomly selected atmospheric condition, the accuracy of the regression tree power predictions is three times higher than that from the traditional power curve methodology. The regression tree method can also be applied to turbine test data and used to predict turbine performance at a new site. No new data are required in comparison to the data that are usually collected for a wind resource assessment. Implementing the method requires turbine manufacturers to create a turbine regression tree model from test site data. Such an approach could significantly reduce bias in power predictions that arise because of the different turbulence and shear at the new site, compared to the test site. (letter)

Calculating the sensitivity of wind turbine loads to wind inputs using response surfaces

DEFF Research Database (Denmark)

Rinker, Jennifer M.

2016-01-01

at a low computational cost. Sobol sensitivity indices (SIs) can then be calculated with relative ease using the calibrated response surface. The proposed methodology is demonstrated by calculating the total sensitivity of the maximum blade root bending moment of the WindPACT 5 MW reference model to four......This paper presents a methodology to calculate wind turbine load sensitivities to turbulence parameters through the use of response surfaces. A response surface is a high-dimensional polynomial surface that can be calibrated to any set of input/output data and then used to generate synthetic data...... turbulence input parameters: a reference mean wind speed, a reference turbulence intensity, the Kaimal length scale, and a novel parameter reflecting the nonstationarity present in the inflow turbulence. The input/output data used to calibrate the response surface were generated for a previous project...

Wind power prediction based on genetic neural network

Science.gov (United States)

Zhang, Suhan

2017-04-01

The scale of grid connected wind farms keeps increasing. To ensure the stability of power system operation, make a reasonable scheduling scheme and improve the competitiveness of wind farm in the electricity generation market, it's important to accurately forecast the short-term wind power. To reduce the influence of the nonlinear relationship between the disturbance factor and the wind power, the improved prediction model based on genetic algorithm and neural network method is established. To overcome the shortcomings of long training time of BP neural network and easy to fall into local minimum and improve the accuracy of the neural network, genetic algorithm is adopted to optimize the parameters and topology of neural network. The historical data is used as input to predict short-term wind power. The effectiveness and feasibility of the method is verified by the actual data of a certain wind farm as an example.

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.

Simulation of the Impact of New Ocean Surface Wind Measurements on H*Wind Analyses

Science.gov (United States)

Miller, Timothy; Atlas, Robert; Black, Peter; Chen, Shuyi; Hood, Robbie; Johnson, James; Jones, Linwood; Ruf, Chris; Uhlhorn, Eric

2008-01-01

The H*Wind analysis, a product of the Hurricane Research Division of NOAA's Atlantic Oceanographic and Meteorological Laboratory, brings together wind measurements from a variety of observation platforms into an objective analysis of the distribution of surface wind speeds in a tropical cyclone. This product is designed to improve understanding of the extent and strength of the wind field, and to improve the assessment of hurricane intensity. See http://www.aoml.noaa.gov/hrd/data sub/wind.html. The Hurricane Imaging Radiometer (HIRAD) is a new passive microwave remote sensor for hurricane observations that is currently under development by NASA Marshall Space Flight Center, NOAA Hurricane Research Division, the University of Central Florida and the University of Michigan. HIRAD is being designed to enhance the current real-time airborne ocean surface winds observation capabilities of NOAA and USAF Weather Squadron hurricane hunter aircraft using the operational airbome Stepped Frequency Microwave Radiometer (SFMR). Unlike SFMR, which measures wind speed and rain rate along the ground track directly beneath the aircraft, HIRAD will provide images of the surface wind and rain field over a wide swath (approximately 3 x the aircraft altitude, or approximately 2 km from space). The instrument is described in a separate paper presented at this conference. The present paper describes a set of Observing System Simulation Experiments (OSSEs) in which measurements from the new instrument as well as those from existing instruments (air, surface, and space-based) are simulated from the output of a numerical model from the University of Miami, and those results are used to construct H*Wind analyses. Evaluations will be presented on the relative impact of HIRAD and other instruments on H*Wind analyses, including the use of HIRAD from 2 aircraft altitudes and from a space-based platform.

Benefits for wind energy in electricity markets from using short term wind power prediction tools: a simulation study

International Nuclear Information System (INIS)

Usaola, J.; Ravelo, O.; Gonzalez, G.; Soto, F.; Davila, M.C.; Diaz-Guerra, B.

2004-01-01

One of the characteristics of wind energy, from the grid point of view, is its non-dispatchability, i.e. generation cannot be ordered, hence integration in electrical networks may be difficult. Short-term wind power prediction-tools could make this integration easier, either by their use by the grid System Operator, or by promoting the participation of wind farms in the electricity markets and using prediction tools to make their bids in the market. In this paper, the importance of a short-term wind power-prediction tool for the participation of wind energy systems in electricity markets is studied. Simulations, according to the current Spanish market rules, have been performed to the production of different wind farms, with different degrees of accuracy in the prediction tool. It may be concluded that income from participation in electricity markets is increased using a short-term wind power prediction-tool of average accuracy. This both marginally increases income and also reduces the impact on system operation with the improved forecasts. (author)

Ultra-Short-Term Wind Power Prediction Using a Hybrid Model

Science.gov (United States)

Mohammed, E.; Wang, S.; Yu, J.

2017-05-01

This paper aims to develop and apply a hybrid model of two data analytical methods, multiple linear regressions and least square (MLR&LS), for ultra-short-term wind power prediction (WPP), for example taking, Northeast China electricity demand. The data was obtained from the historical records of wind power from an offshore region, and from a wind farm of the wind power plant in the areas. The WPP achieved in two stages: first, the ratios of wind power were forecasted using the proposed hybrid method, and then the transformation of these ratios of wind power to obtain forecasted values. The hybrid model combines the persistence methods, MLR and LS. The proposed method included two prediction types, multi-point prediction and single-point prediction. WPP is tested by applying different models such as autoregressive moving average (ARMA), autoregressive integrated moving average (ARIMA) and artificial neural network (ANN). By comparing results of the above models, the validity of the proposed hybrid model is confirmed in terms of error and correlation coefficient. Comparison of results confirmed that the proposed method works effectively. Additional, forecasting errors were also computed and compared, to improve understanding of how to depict highly variable WPP and the correlations between actual and predicted wind power.

Probabilistic maximum-value wind prediction for offshore environments

DEFF Research Database (Denmark)

Staid, Andrea; Pinson, Pierre; Guikema, Seth D.

2015-01-01

statistical models to predict the full distribution of the maximum-value wind speeds in a 3 h interval. We take a detailed look at the performance of linear models, generalized additive models and multivariate adaptive regression splines models using meteorological covariates such as gust speed, wind speed......, convective available potential energy, Charnock, mean sea-level pressure and temperature, as given by the European Center for Medium-Range Weather Forecasts forecasts. The models are trained to predict the mean value of maximum wind speed, and the residuals from training the models are used to develop...... the full probabilistic distribution of maximum wind speed. Knowledge of the maximum wind speed for an offshore location within a given period can inform decision-making regarding turbine operations, planned maintenance operations and power grid scheduling in order to improve safety and reliability...

Repetitive model predictive approach to individual pitch control of wind turbines

DEFF Research Database (Denmark)

Adegas, Fabiano Daher; Stoustrup, Jakob; Odgaard, Peter Fogh

2011-01-01

prediction. As a consequence, individual pitch feed-forward control action is generated by the controller, taking ”future” wind disturbance into account. Information about the estimated wind spatial distribution one blade experience can be used in the prediction model to better control the next passing blade......Wind turbines are inherently exposed to nonuniform wind fields with of wind shear, tower shadow, and possible wake contributions. Asymmetrical aerodynamic rotor loads are a consequence of such periodic, repetitive wind disturbances experienced by the blades. A controller may estimate and use...... this peculiar disturbance pattern to better attenuate loads and regulate power by controlling the blade pitch angles individually. A novel model predictive (MPC) approach for individual pitch control of wind turbines is proposed in this paper. A repetitive wind disturbance model is incorporated into the MPC...

Wind Power Plant Prediction by Using Neural Networks: Preprint

Energy Technology Data Exchange (ETDEWEB)

Liu, Z.; Gao, W.; Wan, Y. H.; Muljadi, E.

2012-08-01

This paper introduces a method of short-term wind power prediction for a wind power plant by training neural networks based on historical data of wind speed and wind direction. The model proposed is shown to achieve a high accuracy with respect to the measured data.

Prediction models for wind speed at turbine locations in a wind farm

DEFF Research Database (Denmark)

Knudsen, Torben; Bak, Thomas; Soltani, Mohsen

2011-01-01

In wind farms, individual turbines disturb the wind field by generating wakes that influence other turbines in the farm. From a control point of view, there is an interest in dynamic optimization of the balance between fatigue and production, and an understanding of the relationship between turbines...... on standard turbine measurements such as rotor speed and power produced, an effective wind speed, which represents the wind field averaged over the rotor disc, is derived. The effective wind speed estimator is based on a continuous–discrete extended Kalman filter that takes advantage of nonlinear time varying...... on the result related to effective wind speed, it is possible to predict wind speeds at neighboring turbines, with a separation of over 700 m, up to 1 min ahead reducing the error by 30% compared with a persistence method. The methodological results are demonstrated on data from an off-shore wind farm...

Optimal day-ahead wind-thermal unit commitment considering statistical and predicted features of wind speeds

International Nuclear Information System (INIS)

Sun, Yanan; Dong, Jizhe; Ding, Lijuan

2017-01-01

Highlights: • A day–ahead wind–thermal unit commitment model is presented. • Wind speed transfer matrix is formed to depict the sequential wind features. • Spinning reserve setting considering wind power accuracy and variation is proposed. • Verified study is performed to check the correctness of the program. - Abstract: The increasing penetration of intermittent wind power affects the secure operation of power systems and leads to a requirement of robust and economic generation scheduling. This paper presents an optimal day–ahead wind–thermal generation scheduling method that considers the statistical and predicted features of wind speeds. In this method, the statistical analysis of historical wind data, which represents the local wind regime, is first implemented. Then, according to the statistical results and the predicted wind power, the spinning reserve requirements for the scheduling period are calculated. Based on the calculated spinning reserve requirements, the wind–thermal generation scheduling is finally conducted. To validate the program, a verified study is performed on a test system. Then, numerical studies to demonstrate the effectiveness of the proposed method are conducted.

Simulation of the Impact of New Aircraft- and Satellite-Based Ocean Surface Wind Measurements on H*Wind Analyses and Numerical Forecasts

Science.gov (United States)

Miller, Timothy; Atlas, Robert; Black, Peter; Chen, Shuyi; Hood, Robbie; Johnson, James; Jones, Linwood; Ruf, Chris; Uhlhorn, Eric; Krishnamurti, T. N.;

OW ASCAT Ocean Surface Winds

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Advanced Scatterometer (ASCAT) sensor onboard the EUMETSAT MetOp polar-orbiting satellite provides ocean surface wind observations by means of radar...

Standardizing the performance evaluation of short-term wind prediction models

DEFF Research Database (Denmark)

Madsen, Henrik; Pinson, Pierre; Kariniotakis, G.

2005-01-01

Short-term wind power prediction is a primary requirement for efficient large-scale integration of wind generation in power systems and electricity markets. The choice of an appropriate prediction model among the numerous available models is not trivial, and has to be based on an objective...... evaluation of model performance. This paper proposes a standardized protocol for the evaluation of short-term wind-poser preciction systems. A number of reference prediction models are also described, and their use for performance comparison is analysed. The use of the protocol is demonstrated using results...... from both on-shore and off-shore wind forms. The work was developed in the frame of the Anemos project (EU R&D project) where the protocol has been used to evaluate more than 10 prediction systems....

Using data-driven approach for wind power prediction: A comparative study

International Nuclear Information System (INIS)

Taslimi Renani, Ehsan; Elias, Mohamad Fathi Mohamad; Rahim, Nasrudin Abd.

2016-01-01

Highlights: • Double exponential smoothing is the most accurate model in wind speed prediction. • A two-stage feature selection method is proposed to select most important inputs. • Direct prediction illustrates better accuracy than indirect prediction. • Adaptive neuro fuzzy inference system outperforms data mining algorithms. • Random forest performs the worst compared to other data mining algorithm. - Abstract: Although wind energy is intermittent and stochastic in nature, it is increasingly important in the power generation due to its sustainability and pollution-free. Increased utilization of wind energy sources calls for more robust and efficient prediction models to mitigate uncertainties associated with wind power. This research compares two different approaches in wind power forecasting which are indirect and direct prediction methods. In indirect method, several times series are applied to forecast the wind speed, whereas the logistic function with five parameters is then used to forecast the wind power. In this study, backtracking search algorithm with novel crossover and mutation operators is employed to find the best parameters of five-parameter logistic function. A new feature selection technique, combining the mutual information and neural network is proposed in this paper to extract the most informative features with a maximum relevancy and minimum redundancy. From the comparative study, the results demonstrate that, in the direct prediction approach where the historical weather data are used to predict the wind power generation directly, adaptive neuro fuzzy inference system outperforms five data mining algorithms namely, random forest, M5Rules, k-nearest neighbor, support vector machine and multilayer perceptron. Moreover, it is also found that the mean absolute percentage error of the direct prediction method using adaptive neuro fuzzy inference system is 1.47% which is approximately less than half of the error obtained with the

Increased Surface Wind Speeds Follow Diminishing Arctic Sea Ice

Science.gov (United States)

Mioduszewski, J.; Vavrus, S. J.; Wang, M.; Holland, M. M.; Landrum, L.

2017-12-01

Projections of Arctic sea ice through the end of the 21st century indicate the likelihood of a strong reduction in ice area and thickness in all seasons, leading to a substantial thermodynamic influence on the overlying atmosphere. This is likely to have an effect on winds over the Arctic Basin, due to changes in atmospheric stability and/or baroclinicity. Prior research on future Arctic wind changes is limited and has focused mainly on the practical impacts on wave heights in certain seasons. Here we attempt to identify patterns and likely mechanisms responsible for surface wind changes in all seasons across the Arctic, particularly those associated with sea ice loss in the marginal ice zone. Sea level pressure, near-surface (10 m) and upper-air (850 hPa) wind speeds, and lower-level dynamic and thermodynamic variables from the Community Earth System Model Large Ensemble Project (CESM-LE) were analyzed for the periods 1971-2000 and 2071-2100 to facilitate comparison between a present-day and future climate. Mean near-surface wind speeds over the Arctic Ocean are projected to increase by late century in all seasons but especially during autumn and winter, when they strengthen by up to 50% locally. The most extreme wind speeds in the 90th percentile change even more, increasing in frequency by over 100%. The strengthened winds are closely linked to decreasing lower-tropospheric stability resulting from the loss of sea ice cover and consequent surface warming (locally over 20 ºC warmer in autumn and winter). A muted pattern of these future changes is simulated in CESM-LE historical runs from 1920-2005. The enhanced winds near the surface are mostly collocated with weaker winds above the boundary layer during autumn and winter, implying more vigorous vertical mixing and a drawdown of high-momentum air.The implications of stronger future winds include increased coastal hazards and the potential for a positive feedback with sea ice by generating higher winds and

Building Chinese wind data for Wind Erosion Prediction System using surrogate US data

Science.gov (United States)

Wind erosion is a global problem, especially in arid and semiarid regions of the world, which leads to land degradation and atmosphere pollution. The process-based Wind Erosion Prediction System (WEPS), developed by the USDA, is capable of simulating the windblown soil loss with changing weather and...

Robust Model Predictive Control of a Wind Turbine

DEFF Research Database (Denmark)

Mirzaei, Mahmood; Poulsen, Niels Kjølstad; Niemann, Hans Henrik

2012-01-01

In this work the problem of robust model predictive control (robust MPC) of a wind turbine in the full load region is considered. A minimax robust MPC approach is used to tackle the problem. Nonlinear dynamics of the wind turbine are derived by combining blade element momentum (BEM) theory...... of the uncertain system is employed and a norm-bounded uncertainty model is used to formulate a minimax model predictive control. The resulting optimization problem is simplified by semidefinite relaxation and the controller obtained is applied on a full complexity, high fidelity wind turbine model. Finally...... and first principle modeling of the turbine flexible structure. Thereafter the nonlinear model is linearized using Taylor series expansion around system operating points. Operating points are determined by effective wind speed and an extended Kalman filter (EKF) is employed to estimate this. In addition...

Empirical models for predicting wind potential for wind energy applications in rural locations of Nigeria

Energy Technology Data Exchange (ETDEWEB)

Odo, F.C. [National Centre for Energy Research and Development, University of Nigeria, Nsukka (Nigeria); Department of Physics and Astronomy, University of Nigeria, Nsukka (Nigeria); Akubue, G.U.; Offiah, S.U.; Ugwuoke, P.E. [National Centre for Energy Research and Development, University of Nigeria, Nsukka (Nigeria)

2013-07-01

In this paper, we use the correlation between the average wind speed and ambient temperature to develop models for predicting wind potentials for two Nigerian locations. Assuming that the troposphere is a typical heterogeneous mixture of ideal gases, we find that for the studied locations, wind speed clearly correlates with ambient temperature in a simple polynomial of 3rd degree. The coefficient of determination and root-mean-square error of the models are 0.81; 0.0024 and 0.56; 0.0041, respectively, for Enugu (6.40N; 7.50E) and Owerri (5.50N; 7.00E). These results suggest that the temperature-based model can be used, with acceptable accuracy, in predicting wind potentials needed for preliminary design assessment of wind energy conversion devices for the locations and others with similar meteorological conditions.

Error analysis of short term wind power prediction models

International Nuclear Information System (INIS)

De Giorgi, Maria Grazia; Ficarella, Antonio; Tarantino, Marco

2011-01-01

The integration of wind farms in power networks has become an important problem. This is because the electricity produced cannot be preserved because of the high cost of storage and electricity production must follow market demand. Short-long-range wind forecasting over different lengths/periods of time is becoming an important process for the management of wind farms. Time series modelling of wind speeds is based upon the valid assumption that all the causative factors are implicitly accounted for in the sequence of occurrence of the process itself. Hence time series modelling is equivalent to physical modelling. Auto Regressive Moving Average (ARMA) models, which perform a linear mapping between inputs and outputs, and Artificial Neural Networks (ANNs) and Adaptive Neuro-Fuzzy Inference Systems (ANFIS), which perform a non-linear mapping, provide a robust approach to wind power prediction. In this work, these models are developed in order to forecast power production of a wind farm with three wind turbines, using real load data and comparing different time prediction periods. This comparative analysis takes in the first time, various forecasting methods, time horizons and a deep performance analysis focused upon the normalised mean error and the statistical distribution hereof in order to evaluate error distribution within a narrower curve and therefore forecasting methods whereby it is more improbable to make errors in prediction. (author)

Error analysis of short term wind power prediction models

Energy Technology Data Exchange (ETDEWEB)

De Giorgi, Maria Grazia; Ficarella, Antonio; Tarantino, Marco [Dipartimento di Ingegneria dell' Innovazione, Universita del Salento, Via per Monteroni, 73100 Lecce (Italy)

2011-04-15

The integration of wind farms in power networks has become an important problem. This is because the electricity produced cannot be preserved because of the high cost of storage and electricity production must follow market demand. Short-long-range wind forecasting over different lengths/periods of time is becoming an important process for the management of wind farms. Time series modelling of wind speeds is based upon the valid assumption that all the causative factors are implicitly accounted for in the sequence of occurrence of the process itself. Hence time series modelling is equivalent to physical modelling. Auto Regressive Moving Average (ARMA) models, which perform a linear mapping between inputs and outputs, and Artificial Neural Networks (ANNs) and Adaptive Neuro-Fuzzy Inference Systems (ANFIS), which perform a non-linear mapping, provide a robust approach to wind power prediction. In this work, these models are developed in order to forecast power production of a wind farm with three wind turbines, using real load data and comparing different time prediction periods. This comparative analysis takes in the first time, various forecasting methods, time horizons and a deep performance analysis focused upon the normalised mean error and the statistical distribution hereof in order to evaluate error distribution within a narrower curve and therefore forecasting methods whereby it is more improbable to make errors in prediction. (author)

Short-term prediction method of wind speed series based on fractal interpolation

International Nuclear Information System (INIS)

Xiu, Chunbo; Wang, Tiantian; Tian, Meng; Li, Yanqing; Cheng, Yi

2014-01-01

Highlights: • An improved fractal interpolation prediction method is proposed. • The chaos optimization algorithm is used to obtain the iterated function system. • The fractal extrapolate interpolation prediction of wind speed series is performed. - Abstract: In order to improve the prediction performance of the wind speed series, the rescaled range analysis is used to analyze the fractal characteristics of the wind speed series. An improved fractal interpolation prediction method is proposed to predict the wind speed series whose Hurst exponents are close to 1. An optimization function which is composed of the interpolation error and the constraint items of the vertical scaling factors in the fractal interpolation iterated function system is designed. The chaos optimization algorithm is used to optimize the function to resolve the optimal vertical scaling factors. According to the self-similarity characteristic and the scale invariance, the fractal extrapolate interpolation prediction can be performed by extending the fractal characteristic from internal interval to external interval. Simulation results show that the fractal interpolation prediction method can get better prediction result than others for the wind speed series with the fractal characteristic, and the prediction performance of the proposed method can be improved further because the fractal characteristic of its iterated function system is similar to that of the predicted wind speed series

OW CCMP Ocean Surface Wind

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Cross-Calibrated Multi-Platform (CCMP) Ocean Surface Wind Vector Analyses (Atlas et al., 2011) provide a consistent, gap-free long-term time-series of monthly...

A history of wind erosion prediction models in the United States Department of Agriculture prior to the Wind Erosion Prediction System

Science.gov (United States)

Tatarko, John; Sporcic, Michael A.; Skidmore, Edward L.

2013-09-01

The Great Plains experienced an influx of settlers in the late 1850s-1900. Periodic drought was hard on both settlers and the soil and caused severe wind erosion. The period known as the Dirty Thirties, 1931-1939, produced many severe windstorms, and the resulting dusty sky over Washington, DC helped Hugh Hammond Bennett gain political support for the Soil Conservation Act of 1937 that started the USDA Soil Conservation Service (SCS). Austin W. Zingg and William S. Chepil began wind erosion studies at a USDA laboratory at Kansas State University in 1947. Neil P. Woodruff and Francis H. Siddoway published the first widely used model for wind erosion in 1965, called the Wind Erosion Equation (WEQ). The WEQ was solved using a series of charts and lookup tables. Subsequent improvements to WEQ included monthly magnitudes of the total wind, a computer version of WEQ programmed in FORTRAN, small-grain equivalents for range grasses, tillage systems, effects of residue management, crop row direction, cloddiness, monthly climate factors, and the weather. The SCS and the Natural Resources Conservation Service (NRCS) produced several computer versions of WEQ with the goal of standardizing and simplifying it for field personnel including a standalone version of WEQ was developed in the late 1990s using Microsoft Excel. Although WEQ was a great advancement to the science of prediction and control of wind erosion on cropland, it had many limitations that prevented its use on many lands throughout the United States and the world. In response to these limitations, the USDA developed a process-based model know as the Wind Erosion Prediction System (WEPS). The USDA Agricultural Research Service has taken the lead in developing science and technology for wind erosion prediction.

Surface Currents and Winds at the Delaware Bay Mouth

Energy Technology Data Exchange (ETDEWEB)

Muscarella, P A; Barton, N P; Lipphardt, B L; Veron, D E; Wong, K C; Kirwan, A D

2011-04-06

Knowledge of the circulation of estuaries and adjacent shelf waters has relied on hydrographic measurements, moorings, and local wind observations usually removed from the region of interest. Although these observations are certainly sufficient to identify major characteristics, they lack both spatial resolution and temporal coverage. High resolution synoptic observations are required to identify important coastal processes at smaller scales. Long observation periods are needed to properly sample low-frequency processes that may also be important. The introduction of high-frequency (HF) radar measurements and regional wind models for coastal studies is changing this situation. Here we analyze synoptic, high-resolution surface winds and currents in the Delaware Bay mouth over an eight-month period (October 2007 through May 2008). The surface currents were measured by two high-frequency radars while the surface winds were extracted from a data-assimilating regional wind model. To illustrate the utility of these monitoring tools we focus on two 45-day periods which previously were shown to present contrasting pictures of the circulation. One, the low-outflow period is from 1 October through 14 November 2007; the other is the high-outflow period from 3 March through 16 April 2008. The large-scale characteristics noted by previous workers are clearly corroborated. Specifically the M2 tide dominates the surface currents, and the Delaware Bay outflow plume is clearly evident in the low frequency currents. Several new aspects of the surface circulation were also identified. These include a map of the spatial variability of the M2 tide (validating an earlier model study), persistent low-frequency cross-mouth flow, and a rapid response of the surface currents to a changing wind field. However, strong wind episodes did not persist long enough to set up a sustained Ekman response.

Simulation of the Impact of New Aircraft-and Satellite-based Ocean Surface Wind Measurements on Wind Analyses and Numerical Forecasts

Science.gov (United States)

Miller, TImothy; Atlas, Robert; Black, Peter; Chen, Shuyi; Jones, Linwood; Ruf, Chris; Uhlhorn, Eric; Gamache, John; Amarin, Ruba; El-Nimri, Salem;

An adaptive short-term prediction scheme for wind energy storage management

International Nuclear Information System (INIS)

Blonbou, Ruddy; Monjoly, Stephanie; Dorville, Jean-Francois

2011-01-01

Research highlights: → We develop a real time algorithm for grid-connected wind energy storage management. → The method aims to guarantee, with ±5% error margin, the power sent to the grid. → Dynamic scheduling of energy storage is based on short-term energy prediction. → Accurate predictions reduce the need in storage capacity. -- Abstract: Efficient forecasting scheme that includes some information on the likelihood of the forecast and based on a better knowledge of the wind variations characteristics along with their influence on power output variation is of key importance for the optimal integration of wind energy in island's power system. In the Guadeloupean archipelago (French West-Indies), with a total wind power capacity of 25 MW; wind energy can represent up to 5% of the instantaneous electricity production. At this level, wind energy contribution can be equivalent to the current network primary control reserve, which causes balancing difficult. The share of wind energy is due to grow even further since the objective is set to reach 118 MW by 2020. It is an absolute evidence for the network operator that due to security concerns of the electrical grid, the share of wind generation should not increase unless solutions are found to solve the prediction problem. The University of French West-Indies and Guyana has developed a short-term wind energy prediction scheme that uses artificial neural networks and adaptive learning procedures based on Bayesian approach and Gaussian approximation. This paper reports the results of the evaluation of the proposed approach; the improvement with respect to the simple persistent prediction model was globally good. A discussion on how such a tool combined with energy storage capacity could help to smooth the wind power variation and improve the wind energy penetration rate into island utility network is also proposed.

Development of Wind Farm AEP Prediction Program Considering Directional Wake Effect

Energy Technology Data Exchange (ETDEWEB)

Yang, Kyoungboo; Cho, Kyungho; Huh, Jongchul [Jeju Nat’l Univ., Jeju (Korea, Republic of)

2017-07-15

For accurate AEP prediction in a wind farm, it is necessary to effectively calculate the wind speed reduction and the power loss due to the wake effect in each wind direction. In this study, a computer program for AEP prediction considering directional wake effect was developed. The results of the developed program were compared with the actual AEP of the wind farm and the calculation result of existing commercial software to confirm the accuracy of prediction. The applied equations are identical with those of commercial software based on existing theories, but there is a difference in the calculation process of the detection of the wake effect area in each wind direction. As a result, the developed program predicted to be less than 1% of difference to the actual capacity factor and showed more than 2% of better results compared with the existing commercial software.

CWEX: Crop/wind-energy experiment: Observations of surface-layer, boundary-layer and mesoscale interactions with a wind farm

Science.gov (United States)

Large wind turbines perturb mean and turbulent wind characteristics, which modify fluxes between the vegetated surface and the lower boundary layer. While simulations have suggested that wind farms could create significant changes in surface fluxes of heat, momentum, moisture, and CO2 over hundreds ...

Crop/Wind-energy Experiment (CWEX): Observations of surface-layer, boundary-layer and mesoscale interactions with a wind farm

Science.gov (United States)

Perturbations of mean and turbulent wind characteristics by large wind turbines modify fluxes between the vegetated surface and the lower boundary layer. While simulations have suggested that wind farms could significantly change surface fluxes of heat, momentum, moisture, and CO2 over hundreds of s...

Simulation of an Underwater Acoustic Communication Channel Characterized by Wind-Generated Surface Waves and Bubbles

NARCIS (Netherlands)

Dol, H.S.; Colin, M.E.G.D.; Ainslie, M.A.; Walree, P.A. van; Janmaat, J.

2012-01-01

Sea surface scattering by wind-generated waves and bubbles is regarded to be the main non-platform related cause of the time variability of shallow acoustic communication channels. Simulations for predicting the quality of acoustic communication links in such channels thus require adequate modeling

Role of Surface Energy Exchange for Simulating Wind Turbine Inflow: A Case Study in the Southern Great Plains, USA

Directory of Open Access Journals (Sweden)

Sonia Wharton

2014-12-01

Full Text Available The Weather Research and Forecasting (WRF model is used to investigate choice of land surface model (LSM on the near surface wind profile, including heights reached by multi-megawatt (MW wind turbines. Simulations of wind profiles and surface energy fluxes were made using five LSMs of varying degrees of sophistication in dealing with soil–plant–atmosphere feedbacks for the Department of Energy (DOE Southern Great Plains (SGP Atmospheric Radiation Measurement Program (ARM Central Facility in Oklahoma, USA. Surface flux and wind profile measurements were available for validation. WRF was run for three, two-week periods covering varying canopy and meteorological conditions. The LSMs predicted a wide range of energy flux and wind shear magnitudes even during the cool autumn period when we expected less variability. Simulations of energy fluxes varied in accuracy by model sophistication, whereby LSMs with very simple or no soil–plant–atmosphere feedbacks were the least accurate; however, the most complex models did not consistently produce more accurate results. Errors in wind shear were also sensitive to LSM choice and were partially related to energy flux accuracy. The variability of LSM performance was relatively high suggesting that LSM representation of energy fluxes in WRF remains a large source of model uncertainty for simulating wind turbine inflow conditions.

Observations of C-Band Brightness Temperature and Ocean Surface Wind Speed and Rain Rate in Hurricanes Earl And Karl (2010)

Science.gov (United States)

Miller, Timothy; James, Mark; Roberts, Brent J.; Biswax, Sayak; Uhlhorn, Eric; Black, Peter; Linwood Jones, W.; Johnson, Jimmy; Farrar, Spencer; Sahawneh, Saleem

2012-01-01

Ocean surface emission is affected by: a) Sea surface temperature. b) Wind speed (foam fraction). c) Salinity After production of calibrated Tb fields, geophysical fields wind speed and rain rate (or column) are retrieved. HIRAD utilizes NASA Instrument Incubator Technology: a) Provides unique observations of sea surface wind, temp and rain b) Advances understanding & prediction of hurricane intensity c) Expands Stepped Frequency Microwave Radiometer capabilities d) Uses synthetic thinned array and RFI mitigation technology of Lightweight Rain Radiometer (NASA Instrument Incubator) Passive Microwave C-Band Radiometer with Freq: 4, 5, 6 & 6.6 GHz: a) Version 1: H-pol for ocean wind speed, b) Version 2: dual ]pol for ocean wind vectors. Performance Characteristics: a) Earth Incidence angle: 0deg - 60deg, b) Spatial Resolution: 2-5 km, c) Swath: approx.70 km for 20 km altitude. Observational Goals: WS 10 - >85 m/s RR 5 - > 100 mm/hr.

Blended 6-Hourly Sea Surface Wind Vectors and Wind Stress on a Global 0.25 Degree Grid (1987-2011)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Blended Global Sea Surface Winds products contain ocean surface wind vectors and wind stress on a global 0.25 degree grid, in multiple time resolutions of...

Indian Ocean surface winds from NCMRWF analysis as compared

Indian Academy of Sciences (India)

The quality of the surface wind analysis at the National Centre for Medium Range Weather Forecasts (NCMRWF), New Delhi over the tropical Indian Ocean and its improvement in 2001 are examined by comparing it with in situ buoy measurements and satellite derived surface winds from NASA QuikSCAT satellite (QSCT) ...

WPPT, a tool for on-line wind power prediction

Energy Technology Data Exchange (ETDEWEB)

Skov Nielsen, T. [Dept. of Mathematical Modelling (IMM-DTU), Kgs. Lyngby (Denmark); Madsen, H. [Dept. of Mathematical Modelling (IMM-DTU) Kgs. Lyngby (Denmark); Toefting, J. [Elsam, Fredericia (Denmark)

2004-07-01

This paper dsecribes VPPT (Wind Power Prediction Tool), an application for assessing the future available wind power up to 36 hours ahead in time. WPPT has been installed in the Eltra/Elsam central dispatch center since October 1997. The paper describes the prediction model used, the actual implementation of WPPT as well as the experience gained by the operators in the dispatch center (au)

Effectiveness of WRF wind direction for retrieving coastal sea surface wind from synthetic aperture radar

DEFF Research Database (Denmark)

Takeyama, Yuko; Ohsawa, Teruo; Kozai, Katsutoshi

2013-01-01

Wind direction is required as input to the geophysical model function (GMF) for the retrieval of sea surface wind speed from a synthetic aperture radar (SAR) images. The present study verifies the effectiveness of using the wind direction obtained from the weather research and forecasting model (...

Wind Characteristics of Coastal and Inland Surface Flows

Science.gov (United States)

Subramanian, Chelakara; Lazarus, Steven; Jin, Tetsuya

2015-11-01

Lidar measurements of the winds in the surface layer (up to 80 m) inland and near the beach are studied to better characterize the velocity profile and the effect of roughness. Mean and root-mean-squared profiles of horizontal and vertical wind components are analyzed. The effects of variable time (18, 60 and 600 seconds) averaging on the above profiles are discussed. The validity of common surface layer wind profile models to estimate skin friction drag is assessed in light of these measurements. Other turbulence statistics such as auto- and cross- correlations in spatial and temporal domains are also presented. The help of FIT DMES field measurement crew is acknowledged.

Comparison of the ocean surface vector winds over the Nordic Seas and their application for ocean modeling

Science.gov (United States)

Dukhovskoy, Dmitry; Bourassa, Mark

2017-04-01

Ocean processes in the Nordic Seas and northern North Atlantic are strongly controlled by air-sea heat and momentum fluxes. The predominantly cyclonic, large-scale atmospheric circulation brings the deep ocean layer up to the surface preconditioning the convective sites in the Nordic Seas for deep convection. In winter, intensive cooling and possibly salt flux from newly formed sea ice erodes the near-surface stratification and the mixed layer merges with the deeper domed layer, exposing the very weakly stratified deep water mass to direct interaction with the atmosphere. Surface wind is one of the atmospheric parameters required for estimating momentum and turbulent heat fluxes to the sea ice and ocean surface. In the ocean models forced by atmospheric analysis, errors in surface wind fields result in errors in air-sea heat and momentum fluxes, water mass formation, ocean circulation, as well as volume and heat transport in the straits. The goal of the study is to assess discrepancies across the wind vector fields from reanalysis data sets and scatterometer-derived gridded products over the Nordic Seas and northern North Atlantic and to demonstrate possible implications of these differences for ocean modeling. The analyzed data sets include the reanalysis data from the National Center for Environmental Prediction Reanalysis 2 (NCEPR2), Climate Forecast System Reanalysis (CFSR), Arctic System Reanalysis (ASR) and satellite wind products Cross-Calibrated Multi-Platform (CCMP) wind product version 1.1 and recently released version 2.0, and Remote Sensing Systems QuikSCAT data. Large-scale and mesoscale characteristics of winds are compared at interannual, seasonal, and synoptic timescales. Numerical sensitivity experiments are conducted with a coupled ice-ocean model forced by different wind fields. The sensitivity experiments demonstrate differences in the net surface heat fluxes during storm events. Next, it is hypothesized that discrepancies in the wind vorticity

Wind-induced contaminant transport in near-surface soils with application to radon entry into buildings

Energy Technology Data Exchange (ETDEWEB)

Riley, William Jowett [Univ. of California, Berkeley, CA (United States)

1996-05-01

Indoor air exposures to gaseous contaminants originating in soil can cause large human health risks. To predict and control these exposures, the mechanisms that affect vapor transport in near-surface soils need to be understood. In particular, radon exposure is a concern since average indoor radon concentrations lead to much higher risks than are generally accepted for exposure to other environmental contaminants. This dissertation examines an important component of the indoor radon problem: the impacts of wind on soil-gas and radon transport and entry into buildings. The research includes experimental and modeling studies of wind`s interactions with a building`s superstructure and the resulting soil-gas and radon flows in the surrounding soil. In addition to exploring the effects of steady winds, a novel modeling technique is developed to examine the impacts of fluctuating winds on soil-gas and radon transport.

Short-term prediction of local wind conditions

DEFF Research Database (Denmark)

Landberg, L.

2001-01-01

This paper will describe a system which predicts the expected power output of a number of wind farms. The system is automatic and operates on-line. The paper will quantify the accuracy of the predictions and will also give examples of the performance for specific storm events. An actual...

Surface wind energy trends near Taiwan in winter since 1871

Directory of Open Access Journals (Sweden)

Lei Zhang

2017-01-01

Full Text Available The tropical surface wind speed in boreal winter reaches a maximum near Taiwan. This stable wind resource may be used for future clean energy development. How this surface wind energy source has changed in past 141 years is investigated using the 20th century reanalysis dataset and CMIP5 models. Our observational analysis shows that the surface wind speed experienced a weakening trend in the past 141 years (1871 - 2010. The average decreasing rate is around -1.4 m s-1 per century. The decrease is primarily attributed to the relative sea surface temperature (SST cooling in the subtropical North Pacific, which forces a large-scale low-level anti-cyclonic circulation anomaly in situ and is thus responsible for the southerly trend near Taiwan. The relative SST trend pattern is attributed mainly to the greenhouse gas effect associated with anthropogenic activities. The southerly trend near Taiwan is more pronounced in the boreal winter than in summer. Such seasonal difference is attributed to the reversed seasonal mean wind, which promotes more efficient positive feedback in the boreal winter. The CMIP5 historical run analysis reveals that climate models capture less SST warming and large-scale anti-cyclonic circulation in the subtropical North Pacific, but the simulated weakening trend of the surface wind speed near Taiwan is too small.

Using Wind Tunnels to Predict Bird Mortality in Wind Farms: The Case of Griffon Vultures

OpenAIRE

de Lucas, Manuela; Ferrer, Miguel; Janss, Guyonne F. E.

2012-01-01

Background: Wind farms have shown a spectacular growth during the last 15 years. Avian mortality through collision with moving rotor blades is well-known as one of the main adverse impacts of wind farms. In Spain, the griffon vulture incurs the highest mortality rates in wind farms. Methodology/Principal Findings: As far as we know, this study is the first attempt to predict flight trajectories of birds in order to foresee potentially dangerous areas for wind farm development. We analyse topo...

Load prediction of stall regulated wind turbines

Energy Technology Data Exchange (ETDEWEB)

Bjoerck, A.; Dahlberg, J.Aa. [Aeronautical Research Inst. of Sweden, Bromma (Sweden); Carlen, I. [Chalmers Univ. of Technology, Goeteborg (Sweden). Div. of Marine Structural Engineering; Ganander, H. [Teknikgruppen AB, Sollentua (Sweden)

1996-12-01

Measurements of blade loads on a turbine situated in a small wind farm shows that the highest blade loads occur during operation close to the peak power i.e. when the turbine operates in the stall region. In this study the extensive experimental data base has been utilised to compare loads in selected campaigns with corresponding load predictions. The predictions are based on time domain simulations of the wind turbine structure, performed by the aeroelastic code VIDYN. In the calculations a model were adopted in order to include the effects of dynamic stall. This paper describes the work carried out so far within the project and key results. 5 refs, 10 figs

Selection of References in Wind Turbine Model Predictive Control Design

DEFF Research Database (Denmark)

Odgaard, Peter Fogh; Hovgaard, Tobias

2015-01-01

a model predictive controller for a wind turbine. One of the important aspects for a tracking control problem is how to setup the optimal reference tracking problem, as it might be relevant to track, e.g., the three concurrent references: optimal pitch angle, optimal rotational speed, and optimal power......Lowering the cost of energy is one of the major focus areas in the wind turbine industry. Recent research has indicated that wind turbine controllers based on model predictive control methods can be useful in obtaining this objective. A number of design considerations have to be made when designing....... The importance if the individual references differ depending in particular on the wind speed. In this paper we investigate the performance of a reference tracking model predictive controller with two different setups of the used optimal reference signals. The controllers are evaluated using an industrial high...

Prediction of Wind Energy Resources (PoWER) Users Guide

Science.gov (United States)

2016-01-01

ARL-TR-7573● JAN 2016 US Army Research Laboratory Prediction of Wind Energy Resources (PoWER) User’s Guide by David P Sauter...manufacturer’s or trade names does not constitute an official endorsement or approval of the use thereof. Destroy this report when it is no longer needed. Do...not return it to the originator. ARL-TR-7573 ● JAN 2016 US Army Research Laboratory Prediction of Wind Energy Resources (PoWER

The Role of Surface Energy Exchange for Simulating Wind Inflow: An Evaluation of Multiple Land Surface Models in WRF for the Southern Great Plains Site Field Campaign Report

Energy Technology Data Exchange (ETDEWEB)

Wharton, Sonia [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Simpson, Matthew [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Osuna, Jessica [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Newman, Jennifer [National Renewable Energy Lab. (NREL), Golden, CO (United States); Biraud, Sebastien [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

2016-05-01

The Weather Research and Forecasting (WRF) model is used to investigate choice of land surface model (LSM) on the near-surface wind profile, including heights reached by multi-megawatt wind turbines. Simulations of wind profiles and surface energy fluxes were made using five LSMs of varying degrees of sophistication in dealing with soil-plant-atmosphere feedbacks for the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility’s Southern Great Plains (SGP) Central Facility in Oklahoma. Surface-flux and wind-profile measurements were available for validation. The WRF model was run for three two-week periods during which varying canopy and meteorological conditions existed. The LSMs predicted a wide range of energy-flux and wind-shear magnitudes even during the cool autumn period when we expected less variability. Simulations of energy fluxes varied in accuracy by model sophistication, whereby LSMs with very simple or no soil-plant-atmosphere feedbacks were the least accurate; however, the most complex models did not consistently produce more accurate results. Errors in wind shear also were sensitive to LSM choice and were partially related to the accuracy of energy flux data. The variability of LSM performance was relatively high, suggesting that LSM representation of energy fluxes in the WRF model remains a significant source of uncertainty for simulating wind turbine inflow conditions.

The effect of foam on waves and the aerodynamic roughness of the water surface at high winds

Science.gov (United States)

Troitskaya, Yuliya; Vdovin, Maxim; Sergeev, Daniil; Kandaurov, Alexander

2017-04-01

Air-sea coupling at extreme winds is of special interest now in connection with the problem of explanation of the sea surface drag saturation at the wind speed exceeding 30 m/s. The idea on saturation (and even reduction) of the coefficient of aerodynamic resistance of the sea surface at hurricane wind speed first suggested in [1] on the basis of theoretical analysis of sensitivity of maximum wind speed in a hurricane to the ratio of the enthalpy and momentum exchange coefficients was then confirmed by a number of field (e.g.[2]) and laboratory [3] experiments, which showed that the sea surface drag coefficient was significantly reduced in comparison with the parameterization obtained at moderate to strong wind conditions. The theoretical explanations of the effect of the sea surface drag reduction exploit either peculiarities of the air flow over breaking waves (e.g.[4,5]) or the effect of sea drops and spray on the wind-wave momentum exchange (e.g. [6,7]). Recently an alternative hypothesis was suggested in [8], where the surface drag reduction in hurricanes was explained by the influence of foam covering sea surface on its aerodynamic roughness. This paper describes a series of laboratory experiments in Thermostratified Wind-Wave Tank (TSWiWaT) of IAP directed to investigation of the foam impact on the short-wave part of the surface waves and the momentum exchange in the atmospheric boundary layer at high winds in the range of equivalent 10-m wind speed from 12 to 38 m/s. A special foam generator was designed for these experiments. The air flow parameters were retrieved from measurements of the velocity profiles. The frequency-wavenumber spectra of surface waves were retrieved from the measurements of water surface elevation by the array 3-channel wave gauge. Foam coverage of water surface was controlled by video filming of the water surface. The results of measurements were compared with predictions of the quasi-linear model of atmospheric boundary layer over

The Character of the Solar Wind, Surface Interactions, and Water

Science.gov (United States)

Farrell, William M.

2011-01-01

We discuss the key characteristics of the proton-rich solar wind and describe how it may interact with the lunar surface. We suggest that solar wind can be both a source and loss of water/OH related volatiles, and review models showing both possibilities. Energy from the Sun in the form of radiation and solar wind plasma are in constant interaction with the lunar surface. As such, there is a solar-lunar energy connection, where solar energy and matter are continually bombarding the lunar surface, acting at the largest scale to erode the surface at 0.2 Angstroms per year via ion sputtering [1]. Figure 1 illustrates this dynamically Sun-Moon system.

Surface Winds and Dust Biases in Climate Models

Science.gov (United States)

Evan, A. T.

2018-01-01

An analysis of North African dust from models participating in the Fifth Climate Models Intercomparison Project (CMIP5) suggested that, when forced by observed sea surface temperatures, these models were unable to reproduce any aspects of the observed year-to-year variability in dust from North Africa. Consequently, there would be little reason to have confidence in the models' projections of changes in dust over the 21st century. However, no subsequent study has elucidated the root causes of the disagreement between CMIP5 and observed dust. Here I develop an idealized model of dust emission and then use this model to show that, over North Africa, such biases in CMIP5 models are due to errors in the surface wind fields and not due to the representation of dust emission processes. These results also suggest that because the surface wind field over North Africa is highly spatially autocorrelated, intermodel differences in the spatial structure of dust emission have little effect on the relative change in year-to-year dust emission over the continent. I use these results to show that similar biases in North African dust from the NASA Modern Era Retrospective analysis for Research and Applications (MERRA) version 2 surface wind field biases but that these wind biases were not present in the first version of MERRA.

Predicting annoyance by wind turbine noise

NARCIS (Netherlands)

Janssen, S.A.; Vos, H.; Eisses, A.R.; Pedersen, E.

2010-01-01

While wind turbines have beneficial effects for the environment, they inevitably generate environmental noise. In order to protect residents against unacceptable levels of noise, exposure-response relationships are needed to predict the expected percentage of people annoyed or highly annoyed at a

Model Predictive Control of Wind Turbines using Uncertain LIDAR Measurements

DEFF Research Database (Denmark)

Mirzaei, Mahmood; Soltani, Mohsen; Poulsen, Niels Kjølstad

2013-01-01

, we simplify state prediction for the MPC. Consequently, the control problem of the nonlinear system is simplified into a quadratic programming. We consider uncertainty in the wind propagation time, which is the traveling time of wind from the LIDAR measurement point to the rotor. An algorithm based......The problem of Model predictive control (MPC) of wind turbines using uncertain LIDAR (LIght Detection And Ranging) measurements is considered. A nonlinear dynamical model of the wind turbine is obtained. We linearize the obtained nonlinear model for different operating points, which are determined...... on wind speed estimation and measurements from the LIDAR is devised to find an estimate of the delay and compensate for it before it is used in the controller. Comparisons between the MPC with error compensation, the MPC without error compensation and an MPC with re-linearization at each sample point...

A new ensemble model for short term wind power prediction

DEFF Research Database (Denmark)

Madsen, Henrik; Albu, Razvan-Daniel; Felea, Ioan

2012-01-01

As the objective of this study, a non-linear ensemble system is used to develop a new model for predicting wind speed in short-term time scale. Short-term wind power prediction becomes an extremely important field of research for the energy sector. Regardless of the recent advancements in the re-search...... of prediction models, it was observed that different models have different capabilities and also no single model is suitable under all situations. The idea behind EPS (ensemble prediction systems) is to take advantage of the unique features of each subsystem to detain diverse patterns that exist in the dataset...

Wind-induced contaminant transport in near-surface soils with application to radon entry into buildings

International Nuclear Information System (INIS)

Riley, W.J.

1996-05-01

Indoor air exposures to gaseous contaminants originating in soil can cause large human health risks. To predict and control these exposures, the mechanisms that affect vapor transport in near-surface soils need to be understood. In particular, radon exposure is a concern since average indoor radon concentrations lead to much higher risks than are generally accepted for exposure to other environmental contaminants. This dissertation examines an important component of the indoor radon problem: the impacts of wind on soil-gas and radon transport and entry into buildings. The research includes experimental and modeling studies of wind's interactions with a building's superstructure and the resulting soil-gas and radon flows in the surrounding soil. In addition to exploring the effects of steady winds, a novel modeling technique is developed to examine the impacts of fluctuating winds on soil-gas and radon transport

A new approach to very short term wind speed prediction using k-nearest neighbor classification

International Nuclear Information System (INIS)

Yesilbudak, Mehmet; Sagiroglu, Seref; Colak, Ilhami

2013-01-01

Highlights: ► Wind speed parameter was predicted in an n-tupled inputs using k-NN classification. ► The effects of input parameters, nearest neighbors and distance metrics were analyzed. ► Many useful and reasonable inferences were uncovered using the developed model. - Abstract: Wind energy is an inexhaustible energy source and wind power production has been growing rapidly in recent years. However, wind power has a non-schedulable nature due to wind speed variations. Hence, wind speed prediction is an indispensable requirement for power system operators. This paper predicts wind speed parameter in an n-tupled inputs using k-nearest neighbor (k-NN) classification and analyzes the effects of input parameters, nearest neighbors and distance metrics on wind speed prediction. The k-NN classification model was developed using the object oriented programming techniques and includes Manhattan and Minkowski distance metrics except from Euclidean distance metric on the contrary of literature. The k-NN classification model which uses wind direction, air temperature, atmospheric pressure and relative humidity parameters in a 4-tupled space achieved the best wind speed prediction for k = 5 in the Manhattan distance metric. Differently, the k-NN classification model which uses wind direction, air temperature and atmospheric pressure parameters in a 3-tupled inputs gave the worst wind speed prediction for k = 1 in the Minkowski distance metric

Hourly Wind Speed Interval Prediction in Arid Regions

Science.gov (United States)

Chaouch, M.; Ouarda, T.

2013-12-01

context, probabilistic forecasts might be more relevant than point forecasts for the planner to build scenarios In this paper, we are interested in estimating predictive intervals of the hourly wind speed measures in few cities in United Arab emirates (UAE). More precisely, given a wind speed time series, our target is to forecast the wind speed at any specific hour during the day and provide in addition an interval with the coverage probability 0flexible because it does not need a specification of the model to work with (such as normal distribution or a linear relation). Here, we use a covariable that is correlated to the wind speed. In practice, many possible choices of the covariate are available. In fact, in addition to its historical data, the wind speed is highly correlated to temperature, humidity and wind direction. In this paper a comparison, in terms of Mean Absolute Prediction Errors and Interquartile Range, between those choices will be provided to show which covariates are more suitable to forecast wind speed.

Model Predictive Voltage Control of Wind Power Plants

DEFF Research Database (Denmark)

Zhao, Haoran; Wu, Qiuwei

2018-01-01

the efficacy of the proposed WFVC, two case scenarios were designed: the wind farm is under normal operating conditions and the internal wind power fluctuation is considered; and besides internal power fluctuation, the impact of the external grid on the wind farm is considered.......This chapter proposes an autonomous wind farm voltage controller (WFVC) based on model predictive control (MPC). It also introduces the analytical expressions for the voltage sensitivity to tap positions of a transformer. The chapter then describes the discrete models for the wind turbine...... generators (WTGs) and static var compensators (SVCs)/static var generators (SVGs). Next, it describes the implementation of the on‐load tap changing (OLTC) in the MPC. Furthermore, the chapter examines the cost function as well as the constraints of the MPC‐based WFVC for both control modes. In order to test...

Wind effected redistribution of surface contamination. Progress report, September 1974--August 1975

International Nuclear Information System (INIS)

Amato, A.J.

1975-01-01

Theoretical resuspension ratios were computed through the extension of a one-dimensional model used to simulate the wind effected movement of surface contaminants. The surface movement of contamination associated with inhalable size particles was considered in relation to time, space, wind velocity, distance from the source, soil resuspension ratios, and other variables. A computer program was developed to calculate the wind effected distribution of surface contaminants. (U.S.)

Two Machine Learning Approaches for Short-Term Wind Speed Time-Series Prediction.

Science.gov (United States)

Ak, Ronay; Fink, Olga; Zio, Enrico

2016-08-01

The increasing liberalization of European electricity markets, the growing proportion of intermittent renewable energy being fed into the energy grids, and also new challenges in the patterns of energy consumption (such as electric mobility) require flexible and intelligent power grids capable of providing efficient, reliable, economical, and sustainable energy production and distribution. From the supplier side, particularly, the integration of renewable energy sources (e.g., wind and solar) into the grid imposes an engineering and economic challenge because of the limited ability to control and dispatch these energy sources due to their intermittent characteristics. Time-series prediction of wind speed for wind power production is a particularly important and challenging task, wherein prediction intervals (PIs) are preferable results of the prediction, rather than point estimates, because they provide information on the confidence in the prediction. In this paper, two different machine learning approaches to assess PIs of time-series predictions are considered and compared: 1) multilayer perceptron neural networks trained with a multiobjective genetic algorithm and 2) extreme learning machines combined with the nearest neighbors approach. The proposed approaches are applied for short-term wind speed prediction from a real data set of hourly wind speed measurements for the region of Regina in Saskatchewan, Canada. Both approaches demonstrate good prediction precision and provide complementary advantages with respect to different evaluation criteria.

Artificial intelligence to predict short-term wind speed

Energy Technology Data Exchange (ETDEWEB)

Pinto, Tiago; Soares, Joao; Ramos, Sergio; Vale, Zita [Polytechnic of Porto (Portugal). GECAD - ISEP

2012-07-01

The use of renewable energy is increasing exponentially in many countries due to the introduction of new energy and environmental policies. Thus, the focus on energy and on the environment makes the efficient integration of renewable energy into the electric power system extremely important. Several European countries have been seeing a high penetration of wind power, representing, gradually, a significant penetration on electricity generation. The introduction of wind power in the network power system causes new challenges for the power system operator due to the variability and uncertainty in weather conditions and, consequently, in the wind power generation. As result, the scheduling dispatch has a significantly portion of uncertainty. In order to deal with the uncertainty in wind power and, with that, introduce improvements in the power system operator efficiency, the wind power forecasting may reveal as a useful tool. This paper proposes a data-mining-based methodology to forecast wind speed. This method is based on the use of data mining techniques applied to a real database of historical wind data. The paper includes a case study based on a real database regarding the last three years to predict wind speed at 5 minute intervals. (orig.)

Northerly surface winds over the eastern North Pacific Ocean in spring and summer

Science.gov (United States)

Taylor, S.V.; Cayan, D.R.; Graham, N.E.; Georgakakos, K.P.

2008-01-01

Persistent spring and summer northerly surface winds are the defining climatological feature of the western coast of North America, especially south of the Oregon coast. Northerly surface winds are important for upwelling and a vast array of other biological, oceanic, and atmospheric processes. Intermittence in northerly coastal surface wind is characterized and wind events are quantitatively defined using coastal buoy data south of Cape Mendocino on the northern California coast. The defined wind events are then used as a basis for composites in order to explain the spatial evolution of various atmospheric and oceanic processes. Wind events involve large-scale changes in the three-dimensional atmospheric circulation including the eastern North Pacific subtropical anticyclone and southeast trade winds. Composites of QSCAT satellite scatterometer wind estimates from 1999 to 2005 based on a single coastal buoy indicate that wind events typically last 72-96 h and result in anomalies in surface wind and Ekman pumping that extend over 1000 kin from the west coast of North America. It may be useful to consider ocean circulation and dependent ecosystem dynamics and the distribution of temperature, moisture, and aerosols in the atmospheric boundary layer in the context of wind events defined herein. Copyright 2008 by the American Geophysical Union.

Development and Application of Advanced Weather Prediction Technologies for the Wind Energy Industry (Invited)

Science.gov (United States)

Mahoney, W. P.; Wiener, G.; Liu, Y.; Myers, W.; Johnson, D.

2010-12-01

Wind energy decision makers are required to make critical judgments on a daily basis with regard to energy generation, distribution, demand, storage, and integration. Accurate knowledge of the present and future state of the atmosphere is vital in making these decisions. As wind energy portfolios expand, this forecast problem is taking on new urgency because wind forecast inaccuracies frequently lead to substantial economic losses and constrain the national expansion of renewable energy. Improved weather prediction and precise spatial analysis of small-scale weather events are crucial for renewable energy management. In early 2009, the National Center for Atmospheric Research (NCAR) began a collaborative project with Xcel Energy Services, Inc. to perform research and develop technologies to improve Xcel Energy's ability to increase the amount of wind energy in their generation portfolio. The agreement and scope of work was designed to provide highly detailed, localized wind energy forecasts to enable Xcel Energy to more efficiently integrate electricity generated from wind into the power grid. The wind prediction technologies are designed to help Xcel Energy operators make critical decisions about powering down traditional coal and natural gas-powered plants when sufficient wind energy is predicted. The wind prediction technologies have been designed to cover Xcel Energy wind resources spanning a region from Wisconsin to New Mexico. The goal of the project is not only to improve Xcel Energy’s wind energy prediction capabilities, but also to make technological advancements in wind and wind energy prediction, expand our knowledge of boundary layer meteorology, and share the results across the renewable energy industry. To generate wind energy forecasts, NCAR is incorporating observations of current atmospheric conditions from a variety of sources including satellites, aircraft, weather radars, ground-based weather stations, wind profilers, and even wind sensors on

PREDICTION OF POWER GENERATION OF SMALL SCALE VERTICAL AXIS WIND TURBINE USING FUZZY LOGIC

Directory of Open Access Journals (Sweden)

Altab Hossain

2009-01-01

Full Text Available Renewable energy from the wind turbine has been focused for the alternative source of power generation due to the following advances of the of the wind turbine. Firstly, the wind turbine is highly efficient and eco-friendly. Secondly, the turbine has the ability to response for the changeable power generation based on the wind velocity and structural framework. However, the competitive efficiency of the wind turbine is necessary to successfully alternate the conventional power sources. The most relevant factor which affects the overall efficiency of the wind turbine is the wind velocity and the relative turbine dimensions. Artificial intelligence systems are widely used technology that can learn from examples and are able to deal with non-linear problems. Compared with traditional approach, fuzzy logic approach is more efficient for the representation, manipulation and utilization. Therefore, the primary purpose of this work was to investigate the relationship between wind turbine power generation and wind velocity, and to illustrate how fuzzy expert system might play an important role in prediction of wind turbine power generation. The main purpose of the measurement over the small scaled prototype vertical axis wind turbine for the wind velocity is to predict the performance of full scaled H-type vertical axis wind turbine. Prediction of power generation at the different wind velocities has been tested at the Thermal Laboratory of Faculty of Engineering, Universiti Industri Selangor (UNISEL and results concerning the daily prediction have been obtained.

PREDICTION OF POWER GENERATION OF SMALL SCALE VERTICAL AXIS WIND TURBINE USING FUZZY LOGIC

Directory of Open Access Journals (Sweden)

Altab Md. Hossain

2009-12-01

Full Text Available Renewable energy from the wind turbine has been focused for the alternative source of power generation due to the following advances of the of the wind turbine. Firstly, the wind turbine is highly efficient and eco-friendly. Secondly, the turbine has the ability to response for the changeable power generation based on the wind velocity and structural framework. However, the competitive efficiency of the wind turbine is necessary to successfully alternate the conventional power sources. The most relevant factor which affects the overall efficiency of the wind turbine is the wind velocity and the relative turbine dimensions. Artificial intelligence systems are widely used technology that can learn from examples and are able to deal with non-linear problems. Compared with traditional approach, fuzzy logic approach is more efficient for the representation, manipulation and utilization. Therefore, the primary purpose of this work was to investigate the relationship between wind turbine power generation and wind velocity, and to illustrate how fuzzy expert system might play an important role in prediction of wind turbine power generation. The main purpose of the measurement over the small scaled prototype vertical axis wind turbine for the wind velocity is to predict the performance of full scaled H-type vertical axis wind turbine. Prediction of power generation at the different wind velocities has been tested at the Thermal Laboratory of Faculty of Engineering, Universiti Industri Selangor (UNISEL and results concerning the daily prediction have been obtained.

Low-Frequency Rotation of Surface Winds over Canada

Directory of Open Access Journals (Sweden)

Richard B. Richardson

2012-10-01

Full Text Available Hourly surface observations from the Canadian Weather Energy and Engineering Dataset were analyzed with respect to long-term wind direction drift or rotation. Most of the Canadian landmass, including the High Arctic, exhibits a spatially consistent and remarkably steady anticyclonic rotation of wind direction. The period of anticyclonic rotation recorded at 144 out of 149 Canadian meteostations directly correlated with latitude and ranged from 7 days at Medicine Hat (50°N, 110°W to 25 days at Resolute (75°N, 95°W. Only five locations in the vicinity of the Rocky Mountains and Pacific Coast were found to obey a “negative” (i.e., cyclonic rotation. The observed anticyclonic rotation appears to be a deterministic, virtually ubiquitous, and highly persistent feature of continental surface wind. These findings are directly applicable to probabilistic assessments of airborne pollutants.

Wind Turbine Generator Efficiency Based on Powertrain Combination and Annual Power Generation Prediction

Directory of Open Access Journals (Sweden)

Dongmyung Kim

2018-05-01

Full Text Available Wind turbine generators are eco-friendly generators that produce electric energy using wind energy. In this study, wind turbine generator efficiency is examined using a powertrain combination and annual power generation prediction, by employing an analysis model. Performance testing was conducted in order to analyze the efficiency of a hydraulic pump and a motor, which are key components, and so as to verify the analysis model. The annual wind speed occurrence frequency for the expected installation areas was used to predict the annual power generation of the wind turbine generators. It was found that the parallel combination of the induction motors exhibited a higher efficiency when the wind speed was low and the serial combination showed higher efficiency when wind speed was high. The results of predicting the annual power generation considering the regional characteristics showed that the power generation was the highest when the hydraulic motors were designed in parallel and the induction motors were designed in series.

Wind-Tunnel Investigation of the Aerodynamic Performance of Surface-Modification Cables

Directory of Open Access Journals (Sweden)

Hiroshi Katsuchi

2017-12-01

Full Text Available The wind-induced vibration of stay cables of cable-stayed bridges, which includes rain-wind-induced vibration (RWIV and dry galloping (DG, has been studied for a considerable amount of time. In general, mechanical dampers or surface modification are applied to suppress the vibration. In particular, several types of surface-modification cable, including indentation, longitudinally parallel protuberance, helical fillet, and U-shaped grooving, have been developed. Recently, a new type of aerodynamically stable cable with spiral protuberances was developed. It was confirmed that the cable has a low drag force coefficient, like an indented cable, and that it prevented the formation of water rivulets on the cable surface. In this study, the stability for RWIV of this cable was investigated with various flow angles and protuberance dimensions in a wind-tunnel test. It was found that the spiral protuberance cable is aerodynamically stable against both RWIV and DG for all test wind angles. The effects of the protuberance dimensions were also clarified. Keywords: Rain-wind-induced vibration, Dry galloping, Stay cable, Wind-tunnel test

Research on wind field algorithm of wind lidar based on BP neural network and grey prediction

Science.gov (United States)

Chen, Yong; Chen, Chun-Li; Luo, Xiong; Zhang, Yan; Yang, Ze-hou; Zhou, Jie; Shi, Xiao-ding; Wang, Lei

2018-01-01

This paper uses the BP neural network and grey algorithm to forecast and study radar wind field. In order to reduce the residual error in the wind field prediction which uses BP neural network and grey algorithm, calculating the minimum value of residual error function, adopting the residuals of the gray algorithm trained by BP neural network, using the trained network model to forecast the residual sequence, using the predicted residual error sequence to modify the forecast sequence of the grey algorithm. The test data show that using the grey algorithm modified by BP neural network can effectively reduce the residual value and improve the prediction precision.

Aggregated wind power generation probabilistic forecasting based on particle filter

International Nuclear Information System (INIS)

Li, Pai; Guan, Xiaohong; Wu, Jiang

2015-01-01

Highlights: • A new method for probabilistic forecasting of aggregated wind power generation. • A dynamic system is established based on a numerical weather prediction model. • The new method handles the non-Gaussian and time-varying wind power uncertainties. • Particle filter is applied to forecast predictive densities of wind generation. - Abstract: Probability distribution of aggregated wind power generation in a region is one of important issues for power system daily operation. This paper presents a novel method to forecast the predictive densities of the aggregated wind power generation from several geographically distributed wind farms, considering the non-Gaussian and non-stationary characteristics in wind power uncertainties. Based on a mesoscale numerical weather prediction model, a dynamic system is established to formulate the relationship between the atmospheric and near-surface wind fields of geographically distributed wind farms. A recursively backtracking framework based on the particle filter is applied to estimate the atmospheric state with the near-surface wind power generation measurements, and to forecast the possible samples of the aggregated wind power generation. The predictive densities of the aggregated wind power generation are then estimated based on these predicted samples by a kernel density estimator. In case studies, the new method presented is tested on a 9 wind farms system in Midwestern United States. The testing results that the new method can provide competitive interval forecasts for the aggregated wind power generation with conventional statistical based models, which validates the effectiveness of the new method

Residence time of contaminants released in surface coal mines -- a wind-tunnel study

Energy Technology Data Exchange (ETDEWEB)

Thompson, R.S. [Environmental Protection Agency, Research Triangle Park, NC (United States)

1994-12-31

Surface coal mining operations (blasting, shoveling, loading, trucking, etc.) are sources of airborne particles. The 1990 Clean Air Act Amendments direct the EPA to analyze the accuracy of the Industrial Source Complex model and the AP-42 emission factors, and to make revisions as may be necessary to eliminate any significant over-prediction of air concentration of fugitive particles from surface coal mines. A wind-tunnel study was performed at the US EPA`s Fluid Modeling Facility to investigate dispersion from surface coal mines in support of the dispersion modeling activities. Described here is the portion of the study directed at determining the residence time that material released near the floor of a mine will stay within the mine.

Predictability of surface currents and fronts off the Mississippi Delta

International Nuclear Information System (INIS)

Walker, N.D.; Rouse, L.J.; Wiseman, W.J.

2001-01-01

The dynamic coastal region of the lower Mississippi River was examined under varying conditions of wind, river discharge and circulation patterns of the Gulf of Mexico. Nearly 7,000 deep-sea merchant vessels enter the port complex each year and the area boasts the highest concentration of offshore drilling rigs, rendering the Mississippi delta and adjacent coastal areas vulnerable to risk from oil spills. Satellite imagery has been useful in tracking movements of the Mississippi river plume as recognizable turbidity and temperature fronts are formed where river waters encounter ambient shelf waters. Oil spill modelers often base their predictions of oil movement on the surface wind field and surface currents, but past studies have indicated that this can be overly simplistic in regions affected by river flow because river fronts have significant control over the movement of oil in opposition to prevailing winds. Frontal zones, such as those found where river waters meet oceanic waters, are characterized by strong convergence of surface flow. These frontal zones can provide large and efficient traps or natural booms for spilled oil. In an effort to facilitate cleanup operations, this study made use of the National Ocean and Atmospheric Administration (NOAA) AVHRR satellite imagery of temperature and reflectance to study front locations and their variability in space and time. The main objectives were to quantify surface temperature structure and locations of fronts throughout the year using satellite image data, to map the structure of the Mississippi sediment plume and to assess the forcing factors responsible for its variability over space and time. The final objective was to use in-situ measurements of surface currents together with satellite image data to better understand surface flow in this region of strong and variable currents. It was concluded that the main factors controlling circulation in the Mississippi River outflow region are river discharge and

A study of single multiplicative neuron model with nonlinear filters for hourly wind speed prediction

International Nuclear Information System (INIS)

Wu, Xuedong; Zhu, Zhiyu; Su, Xunliang; Fan, Shaosheng; Du, Zhaoping; Chang, Yanchao; Zeng, Qingjun

2015-01-01

Wind speed prediction is one important methods to guarantee the wind energy integrated into the whole power system smoothly. However, wind power has a non–schedulable nature due to the strong stochastic nature and dynamic uncertainty nature of wind speed. Therefore, wind speed prediction is an indispensable requirement for power system operators. Two new approaches for hourly wind speed prediction are developed in this study by integrating the single multiplicative neuron model and the iterated nonlinear filters for updating the wind speed sequence accurately. In the presented methods, a nonlinear state–space model is first formed based on the single multiplicative neuron model and then the iterated nonlinear filters are employed to perform dynamic state estimation on wind speed sequence with stochastic uncertainty. The suggested approaches are demonstrated using three cases wind speed data and are compared with autoregressive moving average, artificial neural network, kernel ridge regression based residual active learning and single multiplicative neuron model methods. Three types of prediction errors, mean absolute error improvement ratio and running time are employed for different models’ performance comparison. Comparison results from Tables 1–3 indicate that the presented strategies have much better performance for hourly wind speed prediction than other technologies. - Highlights: • Developed two novel hybrid modeling methods for hourly wind speed prediction. • Uncertainty and fluctuations of wind speed can be better explained by novel methods. • Proposed strategies have online adaptive learning ability. • Proposed approaches have shown better performance compared with existed approaches. • Comparison and analysis of two proposed novel models for three cases are provided

Model predictive control of wind energy conversion systems

CERN Document Server

Yaramasu, Venkata Narasimha R

2017-01-01

The authors provide a comprehensive analysis on the model predictive control of power converters employed in a wide variety of variable-speed wind energy conversion systems (WECS). The contents of this book includes an overview of wind energy system configurations, power converters for variable-speed WECS, digital control techniques, MPC, modeling of power converters and wind generators for MPC design. Other topics include the mapping of continuous-time models to discrete-time models by various exact, approximate, and quasi-exact discretization methods, modeling and control of wind turbine grid-side two-level and multilevel voltage source converters. The authors also focus on the MPC of several power converter configurations for full variable-speed permanent magnet synchronous generator based WECS, squirrel-cage induction generator based WECS, and semi-variable-speed doubly fed induction generator based WECS.

Vertical Wind Tunnel for Prediction of Rocket Flight Dynamics

Directory of Open Access Journals (Sweden)

Hoani Bryson

2016-03-01

Full Text Available A customized vertical wind tunnel has been built by the University of Canterbury Rocketry group (UC Rocketry. This wind tunnel has been critical for the success of UC Rocketry as it allows the optimization of avionics and control systems before flight. This paper outlines the construction of the wind tunnel and includes an analysis of flow quality including swirl. A minimal modelling methodology for roll dynamics is developed that can extrapolate wind tunnel behavior at low wind speeds to much higher velocities encountered during flight. The models were shown to capture the roll flight dynamics in two rocket launches with mean roll angle errors varying from 0.26° to 1.5° across the flight data. The identified model parameters showed consistent and predictable variations over both wind tunnel tests and flight, including canard–fin interaction behavior. These results demonstrate that the vertical wind tunnel is an important tool for the modelling and control of sounding rockets.

Complex terrain wind resource estimation with the wind-atlas method: Prediction errors using linearized and nonlinear CFD micro-scale models

DEFF Research Database (Denmark)

Troen, Ib; Bechmann, Andreas; Kelly, Mark C.

2014-01-01

Using the Wind Atlas methodology to predict the average wind speed at one location from measured climatological wind frequency distributions at another nearby location we analyse the relative prediction errors using a linearized flow model (IBZ) and a more physically correct fully non-linear 3D...... flow model (CFD) for a number of sites in very complex terrain (large terrain slopes). We first briefly describe the Wind Atlas methodology as implemented in WAsP and the specifics of the “classical” model setup and the new setup allowing the use of the CFD computation engine. We discuss some known...

Martian Dune Ripples as Indicators of Recent Surface Wind Patterns

Science.gov (United States)

Johnson, M.; Zimbelman, J. R.

2015-12-01

Sand dunes have been shown to preserve the most recent wind patterns in their ripple formations. This investigation continues the manual documentation of ripples on Martian dunes in order to assess surface wind flow. Study sites investigated must have clear HiRISE frames and be able to represent diverse locations across the surface, decided primarily by their spread of latitude and longitude values. Additionally, frames with stereo pairs are preferred because of their ability to create digital terrain models. This will assist in efforts to relate dune slopes and obstacles to ripple patterns. The search and analysis period resulted in 40 study sites with mapped ripples. Lines were drawn perpendicular to ripple crests across three adjacent ripples in order to document both ripple wavelength from line length and inferred wind direction from azimuth. It is not possible to infer a unique wind direction from ripple orientation alone and therefore these inferred directions have a 180 degree ambiguity. Initial results from all study sites support previous observations that the Martian surface has many dune types in areas with adequate sand supply. The complexity of ripple patterns varies greatly across sites as well as within individual sites. Some areas of uniform directionality for hundreds of kilometers suggest a unimodal wind regime while overlapping patterns suggest multiple dominant winds or seasonally varying winds. In most areas, form flow related to dune shape seems to have a large effect on orientation and must be considered along with the dune type. As long as the few steep slip faces on these small dunes are avoided, form flow can be considered the dominant cause of deviation from the regional wind direction. Regional results, wind roses, and comparisons to previous work will be presented for individual sites.

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.

Modeling Solar-Wind Heavy-Ions' Potential Sputtering of Lunar KREEP Surface

Science.gov (United States)

Barghouty, A. F.; Meyer, F. W.; Harris, R. P.; Adams, J. H., Jr.

2012-01-01

Recent laboratory data suggest that potential sputtering may be an important weathering mechanism that can affect the composition of both the lunar surface and its tenuous exosphere; its role and implications, however, remain unclear. Using a relatively simple kinetic model, we will demonstrate that solar-wind heavy ions induced sputtering of KREEP surfaces is critical in establishing the timescale of the overall solar-wind sputtering process of the lunar surface. We will also also show that potential sputtering leads to a more pronounced and significant differentiation between depleted and enriched surface elements. We briefly discuss the impacts of enhanced sputtering on the composition of the regolith and the exosphere, as well as of solar-wind sputtering as a source of hydrogen and water on the moon.

The statistical prediction of offshore winds from land-based data for wind-energy applications

DEFF Research Database (Denmark)

Walmsley, J.L.; Barthelmie, R.J.; Burrows, W.R.

2001-01-01

Land-based meteorological measurements at two locations on the Danish coast are used to predict offshore wind speeds. Offshore wind-speed data are used only for developing the statistical prediction algorithms and for verification. As a first step, the two datasets were separated into nine...... percentile-based bins, with a minimum of 30 data records in each bin. Next, the records were randomly selected with approximately 70% of the data in each bin being used as a training set for development of the prediction algorithms, and the remaining 30% being reserved as a test set for evaluation purposes....... The binning procedure ensured that both training and test sets fairly represented the overall data distribution. To base the conclusions on firmer ground, five permutations of these training and test sets were created. Thus, all calculations were based on five cases, each one representing a different random...

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.

Predictability and Variability of Wave and Wind

DEFF Research Database (Denmark)

Chozas, Julia Fernandez; Kofoed, Jens Peter; Sørensen, Hans Christian

This project covers two fields of study: a) Wave energy predictability and electricity markets. b) Variability of the power output of WECs in diversified systems : diversified renewable systems with wave and offshore wind production. See page 2-4 in the report for a executive summery....

VT Predicted Mean Wind Speed - 70 meter height

Data.gov (United States)

Vermont Center for Geographic Information — (Link to Metadata) Wind speed predictions at 70m are generated by a numerical model that simulates weather conditions over a 15-year period, taking into account...

VT Predicted Mean Wind Power - 50 meter height

Data.gov (United States)

Vermont Center for Geographic Information — (Link to Metadata) Wind power predictions at 50m are generated by a numerical model that simulates weather conditions over a 15-year period, taking into account...

VT Predicted Mean Wind Speed - 30 meter height

Data.gov (United States)

Vermont Center for Geographic Information — (Link to Metadata) Wind speed predictions at 30m are generated by a numerical model that simulates weather conditions over a 15-year period, taking into account...

A new wind power prediction method based on chaotic theory and Bernstein Neural Network

International Nuclear Information System (INIS)

Wang, Cong; Zhang, Hongli; Fan, Wenhui; Fan, Xiaochao

2016-01-01

The accuracy of wind power prediction is important for assessing the security and economy of the system operation when wind power connects to the grids. However, multiple factors cause a long delay and large errors in wind power prediction. Hence, efficient wind power forecasting approaches are still required for practical applications. In this paper, a new wind power forecasting method based on Chaos Theory and Bernstein Neural Network (BNN) is proposed. Firstly, the largest Lyapunov exponent as a judgment for wind power system's chaotic behavior is made. Secondly, Phase Space Reconstruction (PSR) is used to reconstruct the wind power series' phase space. Thirdly, the prediction model is constructed using the Bernstein polynomial and neural network. Finally, the weights and thresholds of the model are optimized by Primal Dual State Transition Algorithm (PDSTA). The practical hourly data of wind power generation in Xinjiang is used to test this forecaster. The proposed forecaster is compared with several current prominent research findings. Analytical results indicate that the forecasting error of PDSTA + BNN is 3.893% for 24 look-ahead hours, and has lower errors obtained compared with the other forecast methods discussed in this paper. The results of all cases studying confirm the validity of the new forecast method. - Highlights: • Lyapunov exponent is used to verify chaotic behavior of wind power series. • Phase Space Reconstruction is used to reconstruct chaotic wind power series. • A new Bernstein Neural Network to predict wind power series is proposed. • Primal dual state transition algorithm is chosen as the training strategy of BNN.

Comparison of the ocean surface vector winds from atmospheric reanalysis and scatterometer-based wind products over the Nordic Seas and the northern North Atlantic and their application for ocean modeling

Science.gov (United States)

Dukhovskoy, Dmitry S.; Bourassa, Mark A.; Petersen, Gudrún Nína; Steffen, John

2017-03-01

Ocean surface vector wind fields from reanalysis data sets and scatterometer-derived gridded products are analyzed over the Nordic Seas and the northern North Atlantic for the time period from 2000 to 2009. The data sets include the National Center for Environmental Prediction Reanalysis 2 (NCEPR2), Climate Forecast System Reanalysis (CFSR), Arctic System Reanalysis (ASR), Cross-Calibrated Multiplatform (CCMP) wind product version 1.1 and recently released version 2.0, and QuikSCAT. The goal of the study is to assess discrepancies across the wind vector fields in the data sets and demonstrate possible implications of these differences for ocean modeling. Large-scale and mesoscale characteristics of winds are compared at interannual, seasonal, and synoptic timescales. A cyclone tracking methodology is developed and applied to the wind fields to compare cyclone characteristics in the data sets. Additionally, the winds are evaluated against observations collected from meteorological buoys deployed in the Iceland and Irminger Seas. The agreement among the wind fields is better for longer time and larger spatial scales. The discrepancies are clearly apparent for synoptic timescales and mesoscales. CCMP, ASR, and CFSR show the closest overall agreement with each other. Substantial biases are found in the NCEPR2 winds. Numerical sensitivity experiments are conducted with a coupled ice-ocean model forced by different wind fields. The experiments demonstrate differences in the net surface heat fluxes during storms. In the experiment forced by NCEPR2 winds, there are discrepancies in the large-scale wind-driven ocean dynamics compared to the other experiments.

Development of a wind farm noise propagation prediction model - project progress to date

International Nuclear Information System (INIS)

Robinson, P.; Bullmore, A.; Bass, J.; Sloth, E.

1998-01-01

This paper describes a twelve month measurement campaign which is part of a European project (CEC Project JOR3-CT95-0051) with the aim to substantially reduce the uncertainties involved in predicting environmentally radiated noise levels from wind farms (1). This will be achieved by comparing noise levels measure at varying distances from single and multiple sources over differing complexities of terrain with those predicted using a number of currently adopted sound propagation models. Specific objectives within the project are to: establish the important parameters controlling the propagation of wind farm noise to the far field; develop a planning tool for predicting wind farm noise emission levels under practically encountered conditions; place confidence limits on the upper and lower bounds of the noise levels predicted, thus enabling developers to quantify the risk whether noise emission from wind farms will cause nuisance to nearby residents. (Author)

Changes in Surface Wind Speed over North America from CMIP5 Model Projections and Implications for Wind Energy

Directory of Open Access Journals (Sweden)

Sujay Kulkarni

2014-01-01

Full Text Available The centennial trends in the surface wind speed over North America are deduced from global climate model simulations in the Climate Model Intercomparison Project—Phase 5 (CMIP5 archive. Using the 21st century simulations under the RCP 8.5 scenario of greenhouse gas emissions, 5–10 percent increases per century in the 10 m wind speed are found over Central and East-Central United States, the Californian Coast, and the South and East Coasts of the USA in winter. In summer, climate models projected decreases in the wind speed ranging from 5 to 10 percent per century over the same coastal regions. These projected changes in the surface wind speed are moderate and imply that the current estimate of wind power potential for North America based on present-day climatology will not be significantly changed by the greenhouse gas forcing in the coming decades.

A methodology for the prediction of offshore wind energy resources

Energy Technology Data Exchange (ETDEWEB)

Watson, S J; Watson, G M [Rutherford Appleton Lab., Oxfordshire (United Kingdom); Holt, R.J. [Univ. of East Anglia, Climatic Research Unit, Norwich (United Kingdom)] Barthelmie, R.J. [Risoe National Lab., Dept. of Wind Energy and Atmospheric Physics, Roskilde (Denmark); Zuylen, E.J. van [Ecofys Energy and Environment, Utrecht (Netherlands)] Cleijne, J.W. [Kema Sustainable, Arnhem (Netherlands)

1999-03-01

There are increasing constraints on the development of wind power on land. Recently, there has been a move to develop wind power offshore, though the amount of measured wind speed data at potential offshore wind farm sites is sparse. We present a novel methodology for the prediction of offshore wind power resources which is being applied to European Union waters. The first stage is to calculate the geostrophic wind from long-term pressure fields over the sea area of interest. Secondly, the geostrophic wind is transformed to the sea level using WA{sup s}P, taking account of near shore topography. Finally, these values are corrected for land/sea climatology (stability) effects using an analytical Coastal discontinuity Model (CDM). These values are further refined using high resolution offshore data at selected sites. The final values are validated against existing offshore datasets. Preliminary results are presented of the geostrophic wind speed validation in European Union waters. (au)

LDV measurement of boundary layer on rotating blade surface in wind tunnel

Science.gov (United States)

Maeda, Takao; Kamada, Yasunari; Murata, Junsuke; Suzuki, Daiki; Kaga, Norimitsu; Kagisaki, Yosuke

2014-12-01

Wind turbines generate electricity due to extracting energy from the wind. The rotor aerodynamics strongly depends on the flow around blade. The surface flow on the rotating blade affects the sectional performance. The wind turbine surface flow has span-wise component due to span-wise change of airfoil section, chord length, twisted angle of blade and centrifugal force on the flow. These span-wise flow changes the boundary layer on the rotating blade and the sectional performance. Hence, the thorough understanding of blade surface flow is important to improve the rotor performance. For the purpose of clarification of the flow behaviour around the rotor blade, the velocity in the boundary layer on rotating blade surface of an experimental HAWT was measured in a wind tunnel. The velocity measurement on the blade surface was carried out by a laser Doppler velocimeter (LDV). As the results of the measurement, characteristics of surface flow are clarified. In optimum tip speed operation, the surface flow on leading edge and r/R=0.3 have large span-wise velocity which reaches 20% of sectional inflow velocity. The surface flow inboard have three dimensional flow patterns. On the other hand, the flow outboard is almost two dimensional in cross sectional plane.

Wind Power Ramp Events Prediction with Hybrid Machine Learning Regression Techniques and Reanalysis Data

Directory of Open Access Journals (Sweden)

Laura Cornejo-Bueno

2017-11-01

Full Text Available Wind Power Ramp Events (WPREs are large fluctuations of wind power in a short time interval, which lead to strong, undesirable variations in the electric power produced by a wind farm. Its accurate prediction is important in the effort of efficiently integrating wind energy in the electric system, without affecting considerably its stability, robustness and resilience. In this paper, we tackle the problem of predicting WPREs by applying Machine Learning (ML regression techniques. Our approach consists of using variables from atmospheric reanalysis data as predictive inputs for the learning machine, which opens the possibility of hybridizing numerical-physical weather models with ML techniques for WPREs prediction in real systems. Specifically, we have explored the feasibility of a number of state-of-the-art ML regression techniques, such as support vector regression, artificial neural networks (multi-layer perceptrons and extreme learning machines and Gaussian processes to solve the problem. Furthermore, the ERA-Interim reanalysis from the European Center for Medium-Range Weather Forecasts is the one used in this paper because of its accuracy and high resolution (in both spatial and temporal domains. Aiming at validating the feasibility of our predicting approach, we have carried out an extensive experimental work using real data from three wind farms in Spain, discussing the performance of the different ML regression tested in this wind power ramp event prediction problem.

A Free Wake Numerical Simulation for Darrieus Vertical Axis Wind Turbine Performance Prediction

Science.gov (United States)

Belu, Radian

2010-11-01

In the last four decades, several aerodynamic prediction models have been formulated for the Darrieus wind turbine performances and characteristics. We can identified two families: stream-tube and vortex. The paper presents a simplified numerical techniques for simulating vertical axis wind turbine flow, based on the lifting line theory and a free vortex wake model, including dynamic stall effects for predicting the performances of a 3-D vertical axis wind turbine. A vortex model is used in which the wake is composed of trailing stream-wise and shedding span-wise vortices, whose strengths are equal to the change in the bound vortex strength as required by the Helmholz and Kelvin theorems. Performance parameters are computed by application of the Biot-Savart law along with the Kutta-Jukowski theorem and a semi-empirical stall model. We tested the developed model with an adaptation of the earlier multiple stream-tube performance prediction model for the Darrieus turbines. Predictions by using our method are shown to compare favorably with existing experimental data and the outputs of other numerical models. The method can predict accurately the local and global performances of a vertical axis wind turbine, and can be used in the design and optimization of wind turbines for built environment applications.

A history of wind erosion prediction models in the United States Department of Agriculture: The Wind Erosion Prediction System (WEPS)

Science.gov (United States)

Development of the Wind Erosion Prediction System (WEPS) was officially inaugurated in 1985 by United States Department of Agriculture-Agricultural Research Service (USDA-ARS) scientists in response to customer requests, particularly those coming from the USDA Soil Conservation Service (SCS), for im...

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.

Stochastic Prediction of Wind Generating Resources Using the Enhanced Ensemble Model for Jeju Island’s Wind Farms in South Korea

OpenAIRE

Deockho Kim; Jin Hur

2017-01-01

Due to the intermittency of wind power generation, it is very hard to manage its system operation and planning. In order to incorporate higher wind power penetrations into power systems that maintain secure and economic power system operation, an accurate and efficient estimation of wind power outputs is needed. In this paper, we propose the stochastic prediction of wind generating resources using an enhanced ensemble model for Jeju Island’s wind farms in South Korea. When selecting the poten...

Aerodynamic performance prediction of Darrieus-type wind turbines

Directory of Open Access Journals (Sweden)

Ion NILĂ

2010-06-01

Full Text Available The prediction of Darrieus wind turbine aerodynamic performances provides the necessarydesign and operational data base related to the wind potential. In this sense it provides the type ofturbine suitable to the area where it is to be installed. Two calculation methods are analyzed for arotor with straight blades. The first one is a global method that allows an assessment of the turbinenominal power by a brief calculation. This method leads to an overestimation of performances. Thesecond is the calculation method of the gust factor and momentum which deals with the pale as beingcomposed of different elements that don’t influence each other. This method, developed based on thetheory of the turbine blades, leads to values close to the statistical data obtained experimentally. Thevalues obtained by the calculation method of gust factor - momentum led to the concept of a Darrieusturbine, which will be tested for different wind values in the INCAS subsonic wind tunnel.

Soil erosion rates from mixed soil and gravel surfaces in a wind tunnel: A preliminary report

International Nuclear Information System (INIS)

Ligotke, M.W.

1988-12-01

Tests of wind erosion were performed in a controlled-environment wind tunnel to support the development of natural-material protective barriers for long-term isolation of radioactive waste. Barrier performance standards currently being developed for internal and external barrier performance are expected to mandate a surface layer that is resistant to wind erosion. The purpose of this study was to initiate a series of tests to determine suitable soil and gravel mixtures for such a barrier and to test worst-case surface layer conditions under the influence of high wind speeds. Six mixed soil and gravel surfaces were prepared, weathered to represent natural wind-blown desert areas, and subjected to controlled wind erosion forces in a wind tunnel. The applied erosive forces, including surface shear forces, were characterized to provide a means of relating wind tunnel results with actual field conditions. Soil particle losses from the surfaces caused by suspension, saltation, and surface creep were monitored by aerosol sample probes and mass balance measurements. 23 refs., 22 figs., 3 tabs

Correaltion of full-scale drag predictions with flight measurements on the C-141A aircraft. Phase 2: Wind tunnel test, analysis, and prediction techniques. Volume 1: Drag predictions, wind tunnel data analysis and correlation

Science.gov (United States)

Macwilkinson, D. G.; Blackerby, W. T.; Paterson, J. H.

1974-01-01

The degree of cruise drag correlation on the C-141A aircraft is determined between predictions based on wind tunnel test data, and flight test results. An analysis of wind tunnel tests on a 0.0275 scale model at Reynolds number up to 3.05 x 1 million/MAC is reported. Model support interference corrections are evaluated through a series of tests, and fully corrected model data are analyzed to provide details on model component interference factors. It is shown that predicted minimum profile drag for the complete configuration agrees within 0.75% of flight test data, using a wind tunnel extrapolation method based on flat plate skin friction and component shape factors. An alternative method of extrapolation, based on computed profile drag from a subsonic viscous theory, results in a prediction four percent lower than flight test data.

CYGNSS Surface Wind Validation and Characteristics in the Maritime Continent

Science.gov (United States)

Asharaf, S.; Waliser, D. E.; Zhang, C.; Wandala, A.

2017-12-01

Surface wind over tropical oceans plays a crucial role in many local/regional weather and climate processes and helps to shape the global climate system. However, there is a lack of consistent high quality observations for surface winds. The newly launched NASA Cyclone Global Navigation Satellite System (CYGNSS) mission provides near surface wind speed over the tropical ocean with sampling that accounts for the diurnal cycle. In the early phase of the mission, validation is a critical task, and over-ocean validation is typically challenging due to a lack of robust validation resources that a cover a variety of environmental conditions. In addition, it can also be challenging to obtain in-situ observation resources and also to extract co-located CYGNSS records for some of the more scientifically interesting regions, such as the Maritime Continent (MC). The MC is regarded as a key tropical driver for the mean global circulation as well as important large-scale circulation variability such as the Madian-Julian Oscillation (MJO). The focus of this project and analysis is to take advantage of local in-situ resources from the MC regions (e.g. volunteer shipping, marine buoys, and the Year of Maritime Continent (YMC) campaign) to quantitatively characterize and validate the CYGNSS derived winds in the MC region and in turn work to unravel the complex multi-scale interactions between the MJO and MC. This presentation will show preliminary results of a comparison between the CYGNSS and the in-situ surface wind measurements focusing on the MC region. Details about the validation methods, uncertainties, and planned work will be discussed in this presentation.

Solar Atmosphere to Earth's Surface: Long Lead Time dB/dt Predictions with the Space Weather Modeling Framework

Science.gov (United States)

Welling, D. T.; Manchester, W.; Savani, N.; Sokolov, I.; van der Holst, B.; Jin, M.; Toth, G.; Liemohn, M. W.; Gombosi, T. I.

2017-12-01

The future of space weather prediction depends on the community's ability to predict L1 values from observations of the solar atmosphere, which can yield hours of lead time. While both empirical and physics-based L1 forecast methods exist, it is not yet known if this nascent capability can translate to skilled dB/dt forecasts at the Earth's surface. This paper shows results for the first forecast-quality, solar-atmosphere-to-Earth's-surface dB/dt predictions. Two methods are used to predict solar wind and IMF conditions at L1 for several real-world coronal mass ejection events. The first method is an empirical and observationally based system to estimate the plasma characteristics. The magnetic field predictions are based on the Bz4Cast system which assumes that the CME has a cylindrical flux rope geometry locally around Earth's trajectory. The remaining plasma parameters of density, temperature and velocity are estimated from white-light coronagraphs via a variety of triangulation methods and forward based modelling. The second is a first-principles-based approach that combines the Eruptive Event Generator using Gibson-Low configuration (EEGGL) model with the Alfven Wave Solar Model (AWSoM). EEGGL specifies parameters for the Gibson-Low flux rope such that it erupts, driving a CME in the coronal model that reproduces coronagraph observations and propagates to 1AU. The resulting solar wind predictions are used to drive the operational Space Weather Modeling Framework (SWMF) for geospace. Following the configuration used by NOAA's Space Weather Prediction Center, this setup couples the BATS-R-US global magnetohydromagnetic model to the Rice Convection Model (RCM) ring current model and a height-integrated ionosphere electrodynamics model. The long lead time predictions of dB/dt are compared to model results that are driven by L1 solar wind observations. Both are compared to real-world observations from surface magnetometers at a variety of geomagnetic latitudes

Distributed Model Predictive Control for Active Power Control of Wind Farm

DEFF Research Database (Denmark)

Zhao, Haoran; Wu, Qiuwei; Rasmussen, Claus Nygaard

2014-01-01

This paper presents the active power control of a wind farm using the Distributed Model Predictive Controller (D- MPC) via dual decomposition. Different from the conventional centralized wind farm control, multiple objectives such as power reference tracking performance and wind turbine load can...... be considered to achieve a trade-off between them. Additionally, D- MPC is based on communication among the subsystems. Through the interaction among the neighboring subsystems, the global optimization could be achieved, which significantly reduces the computation burden. It is suitable for the modern large......-scale wind farm control....

A novel implementation of kNN classifier based on multi-tupled meteorological input data for wind power prediction

International Nuclear Information System (INIS)

Yesilbudak, Mehmet; Sagiroglu, Seref; Colak, Ilhami

2017-01-01

Highlights: • An accurate wind power prediction model is proposed for very short-term horizon. • The k-nearest neighbor classifier is implemented based on the multi-tupled inputs. • The variation of wind power prediction errors is evaluated in various aspects. • Our approach shows the superior prediction performance over the persistence method. - Abstract: With the growing share of wind power production in the electric power grids, many critical challenges to the grid operators have been emerged in terms of the power balance, power quality, voltage support, frequency stability, load scheduling, unit commitment and spinning reserve calculations. To overcome such problems, numerous studies have been conducted to predict the wind power production, but a small number of them have attempted to improve the prediction accuracy by employing the multidimensional meteorological input data. The novelties of this study lie in the proposal of an efficient and easy to implement very short-term wind power prediction model based on the k-nearest neighbor classifier (kNN), in the usage of wind speed, wind direction, barometric pressure and air temperature parameters as the multi-tupled meteorological inputs and in the comparison of wind power prediction results with respect to the persistence reference model. As a result of the achieved patterns, we characterize the variation of wind power prediction errors according to the input tuples, distance measures and neighbor numbers, and uncover the most influential and the most ineffective meteorological parameters on the optimization of wind power prediction results.

The use of real-time off-site observations as a methodology for increasing forecast skill in prediction of large wind power ramps one or more hours ahead of their impact on a wind plant.

Energy Technology Data Exchange (ETDEWEB)

Martin Wilde, Principal Investigator

2012-12-31

ABSTRACT Application of Real-Time Offsite Measurements in Improved Short-Term Wind Ramp Prediction Skill Improved forecasting performance immediately preceding wind ramp events is of preeminent concern to most wind energy companies, system operators, and balancing authorities. The value of near real-time hub height-level wind data and more general meteorological measurements to short-term wind power forecasting is well understood. For some sites, access to onsite measured wind data - even historical - can reduce forecast error in the short-range to medium-range horizons by as much as 50%. Unfortunately, valuable free-stream wind measurements at tall tower are not typically available at most wind plants, thereby forcing wind forecasters to rely upon wind measurements below hub height and/or turbine nacelle anemometry. Free-stream measurements can be appropriately scaled to hub-height levels, using existing empirically-derived relationships that account for surface roughness and turbulence. But there is large uncertainty in these relationships for a given time of day and state of the boundary layer. Alternatively, forecasts can rely entirely on turbine anemometry measurements, though such measurements are themselves subject to wake effects that are not stationary. The void in free-stream hub-height level measurements of wind can be filled by remote sensing (e.g., sodar, lidar, and radar). However, the expense of such equipment may not be sustainable. There is a growing market for traditional anemometry on tall tower networks, maintained by third parties to the forecasting process (i.e., independent of forecasters and the forecast users). This study examines the value of offsite tall-tower data from the WINDataNOW Technology network for short-horizon wind power predictions at a wind farm in northern Montana. The presentation shall describe successful physical and statistical techniques for its application and the practicality of its application in an operational

On Practical tuning of Model Uncertainty in Wind Turbine Model Predictive Control

DEFF Research Database (Denmark)

Odgaard, Peter Fogh; Hovgaard, Tobias

2015-01-01

Model predictive control (MPC) has in previous works been applied on wind turbines with promising results. These results apply linear MPC, i.e., linear models linearized at different operational points depending on the wind speed. The linearized models are derived from a nonlinear first principles...... model of a wind turbine. In this paper, we investigate the impact of this approach on the performance of a wind turbine. In particular, we focus on the most non-linear operational ranges of a wind turbine. The MPC controller is designed for, tested, and evaluated at an industrial high fidelity wind...

Reduction of wind power induced reserve requirements by advanced shortest-term forecasts and prediction intervals

Energy Technology Data Exchange (ETDEWEB)

Dobschinski, Jan; Wessel, Arne; Lange, Bernhard; Bremen, Lueder von [Fraunhofer Institut fuer Windenergie und Energiesystemtechnik (IWES), Kassel (Germany)

2009-07-01

In electricity systems with large penetration of wind power, the limited predictability of the wind power generation leads to an increase in reserve and balancing requirements. At first the present study concentrates on the capability of dynamic day-ahead prediction intervals to reduce the wind power induced reserve and balancing requirements. Alternatively the reduction of large forecast errors of the German wind power generation by using advanced shortest-term predictions has been evaluated in a second approach. With focus on the allocation of minute reserve power the aim is to estimate the maximal remaining uncertainty after trading activities on the intraday market. Finally both approaches were used in a case study concerning the reserve requirements induced by the total German wind power expansion in 2007. (orig.)

Predicting wind shear effects: A study of Minnesota wind data collected at heights up to 70 meters

Energy Technology Data Exchange (ETDEWEB)

Artig, R. [Minnesota Dept. of Public Service, St. Paul, MN (United States)

1997-12-31

The Minnesota Department of Public Service (DPS) collects wind data at carefully selected sites around the state and analyzes the data to determine Minnesota`s wind power potential. DPS recently installed advanced new monitoring equipment at these sites and began to collect wind data at 30, 50, and 70 meters above ground level, with two anemometers at each level. Previously, the Department had not collected data at heights above ground level higher than 30 meters. DPS also, with the U.S. Department of Energy (DOE), installed four sophisticated monitoring sites as part of a Tall Tower Wind Shear Study that is assessing the effects of wind shear on wind power potential. At these sites, wind data are being collected at the 10, 30, 40, 50, 60, and 70 meter heights. This paper presents the preliminary results of the analysis of wind data from all sites. These preliminary results indicate that the traditional 1/7 power law does not effectively predict wind shear in Minnesota, and the result is an underestimation of Minnesota`s wind power potential at higher heights. Using a power factor of 1/5 or 1/4 may be more accurate and provide sound justification for installing wind turbines on taller towers in Minnesota.

A hybrid PSO-ANFIS approach for short-term wind power prediction in Portugal

International Nuclear Information System (INIS)

Pousinho, H.M.I.; Mendes, V.M.F.; Catalao, J.P.S.

2011-01-01

The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Wind power prediction plays a key role in tackling these challenges. The contribution of this paper is to propose a new hybrid approach, combining particle swarm optimization and adaptive-network-based fuzzy inference system, for short-term wind power prediction in Portugal. Significant improvements regarding forecasting accuracy are attainable using the proposed approach, in comparison with the results obtained with five other approaches.

Variation of air--water gas transfer with wind stress and surface viscoelasticity

OpenAIRE

Frew, Nelson M.; Bock, Erik J.; McGillis, Wade R.; Karachintsev, Andrey V.; Hara, Tetsu; Münsterer, Thomas; Jähne, Bernd

1995-01-01

Previous parameterizations of gas transfer velocity have attempted to cast this quantity as a function of wind speed or wind-stress. This study demonstrates that the presence of a surface film is effective at reducing the gas transfer velocity at constant wind-stress. Gas exchange experiments were performed at WHOI and UH using annular wind-wave tanks of different scales. Systematic variations of wind-stress and surfactant concentration (Triton-X-100) were explored to determ...

Multisensor satellite data integration for sea surface wind speed and direction determination

Science.gov (United States)

Glackin, D. L.; Pihos, G. G.; Wheelock, S. L.

1984-01-01

Techniques to integrate meteorological data from various satellite sensors to yield a global measure of sea surface wind speed and direction for input to the Navy's operational weather forecast models were investigated. The sensors were launched or will be launched, specifically the GOES visible and infrared imaging sensor, the Nimbus-7 SMMR, and the DMSP SSM/I instrument. An algorithm for the extrapolation to the sea surface of wind directions as derived from successive GOES cloud images was developed. This wind veering algorithm is relatively simple, accounts for the major physical variables, and seems to represent the best solution that can be found with existing data. An algorithm for the interpolation of the scattered observed data to a common geographical grid was implemented. The algorithm is based on a combination of inverse distance weighting and trend surface fitting, and is suited to combing wind data from disparate sources.

Bayesian based Prognostic Model for Predictive Maintenance of Offshore Wind Farms

DEFF Research Database (Denmark)

Asgarpour, Masoud; Sørensen, John Dalsgaard

2018-01-01

The operation and maintenance costs of offshore wind farms can be significantly reduced if existing corrective actions are performed as efficient as possible and if future corrective actions are avoided by performing sufficient preventive actions. In this paper a prognostic model for degradation...... monitoring, fault prediction and predictive maintenance of offshore wind components is defined. The diagnostic model defined in this paper is based on degradation, remaining useful lifetime and hybrid inspection threshold models. The defined degradation model is based on an exponential distribution...

Bayesian based Prognostic Model for Predictive Maintenance of Offshore Wind Farms

DEFF Research Database (Denmark)

Asgarpour, Masoud; Sørensen, John Dalsgaard

2018-01-01

monitoring, fault prediction and predictive maintenance of offshore wind components is defined. The diagnostic model defined in this paper is based on degradation, remaining useful lifetime and hybrid inspection threshold models. The defined degradation model is based on an exponential distribution......The operation and maintenance costs of offshore wind farms can be significantly reduced if existing corrective actions are performed as efficient as possible and if future corrective actions are avoided by performing sufficient preventive actions. In this paper a prognostic model for degradation...

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.

Coordinated Voltage Control of a Wind Farm based on Model Predictive Control

DEFF Research Database (Denmark)

Zhao, Haoran; Wu, Qiuwei; Guo, Qinglai

2016-01-01

This paper presents an autonomous wind farm voltage controller based on Model Predictive Control (MPC). The reactive power compensation and voltage regulation devices of the wind farm include Static Var Compensators (SVCs), Static Var Generators (SVGs), Wind Turbine Generators (WTGs) and On...... are calculated based on an analytical method to improve the computation efficiency and overcome the convergence problem. Two control modes are designed for both voltage violated and normal operation conditions. A wind farm with 20 wind turbines was used to conduct case studies to verify the proposed coordinated...

Validated Loads Prediction Models for Offshore Wind Turbines for Enhanced Component Reliability

DEFF Research Database (Denmark)

Koukoura, Christina

To improve the reliability of offshore wind turbines, accurate prediction of their response is required. Therefore, validation of models with site measurements is imperative. In the present thesis a 3.6MW pitch regulated-variable speed offshore wind turbine on a monopole foundation is built...... are used for the modification of the sub-structure/foundation design for possible material savings. First, the background of offshore wind engineering, including wind-wave conditions, support structure, blade loading and wind turbine dynamics are presented. Second, a detailed description of the site...

A hybrid PSO-ANFIS approach for short-term wind power prediction in Portugal

Energy Technology Data Exchange (ETDEWEB)

Pousinho, H.M.I. [Department of Electromechanical Engineering, University of Beira Interior, R. Fonte do Lameiro, 6201-001 Covilha (Portugal); Mendes, V.M.F. [Department of Electrical Engineering and Automation, Instituto Superior de Engenharia de Lisboa, R. Conselheiro Emidio Navarro, 1950-062 Lisbon (Portugal); Catalao, J.P.S. [Department of Electromechanical Engineering, University of Beira Interior, R. Fonte do Lameiro, 6201-001 Covilha (Portugal); Center for Innovation in Electrical and Energy Engineering, Instituto Superior Tecnico, Technical University of Lisbon, Av. Rovisco Pais, 1049-001 Lisbon (Portugal)

2011-01-15

The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Wind power prediction plays a key role in tackling these challenges. The contribution of this paper is to propose a new hybrid approach, combining particle swarm optimization and adaptive-network-based fuzzy inference system, for short-term wind power prediction in Portugal. Significant improvements regarding forecasting accuracy are attainable using the proposed approach, in comparison with the results obtained with five other approaches. (author)

Short-term wind speed prediction using an unscented Kalman filter based state-space support vector regression approach

International Nuclear Information System (INIS)

Chen, Kuilin; Yu, Jie

2014-01-01

Highlights: • A novel hybrid modeling method is proposed for short-term wind speed forecasting. • Support vector regression model is constructed to formulate nonlinear state-space framework. • Unscented Kalman filter is adopted to recursively update states under random uncertainty. • The new SVR–UKF approach is compared to several conventional methods for short-term wind speed prediction. • The proposed method demonstrates higher prediction accuracy and reliability. - Abstract: Accurate wind speed forecasting is becoming increasingly important to improve and optimize renewable wind power generation. Particularly, reliable short-term wind speed prediction can enable model predictive control of wind turbines and real-time optimization of wind farm operation. However, this task remains challenging due to the strong stochastic nature and dynamic uncertainty of wind speed. In this study, unscented Kalman filter (UKF) is integrated with support vector regression (SVR) based state-space model in order to precisely update the short-term estimation of wind speed sequence. In the proposed SVR–UKF approach, support vector regression is first employed to formulate a nonlinear state-space model and then unscented Kalman filter is adopted to perform dynamic state estimation recursively on wind sequence with stochastic uncertainty. The novel SVR–UKF method is compared with artificial neural networks (ANNs), SVR, autoregressive (AR) and autoregressive integrated with Kalman filter (AR-Kalman) approaches for predicting short-term wind speed sequences collected from three sites in Massachusetts, USA. The forecasting results indicate that the proposed method has much better performance in both one-step-ahead and multi-step-ahead wind speed predictions than the other approaches across all the locations

An Improved Local Gradient Method for Sea Surface Wind Direction Retrieval from SAR Imagery

Directory of Open Access Journals (Sweden)

Lizhang Zhou

2017-06-01

Full Text Available Sea surface wind affects the fluxes of energy, mass and momentum between the atmosphere and ocean, and therefore regional and global weather and climate. With various satellite microwave sensors, sea surface wind can be measured with large spatial coverage in almost all-weather conditions, day or night. Like any other remote sensing measurements, sea surface wind measurement is also indirect. Therefore, it is important to develop appropriate wind speed and direction retrieval models for different types of microwave instruments. In this paper, a new sea surface wind direction retrieval method from synthetic aperture radar (SAR imagery is developed. In the method, local gradients are computed in frequency domain by combining the operation of smoothing and computing local gradients in one step to simplify the process and avoid the difference approximation. This improved local gradients (ILG method is compared with the traditional two-dimensional fast Fourier transform (2D FFT method and local gradients (LG method, using interpolating wind directions from the European Centre for Medium-Range Weather Forecast (ECMWF reanalysis data and the Cross-Calibrated Multi-Platform (CCMP wind vector product. The sensitivities to the salt-and-pepper noise, the additive noise and the multiplicative noise are analyzed. The ILG method shows a better performance of retrieval wind directions than the other two methods.

Ocean Surface Wind Speed of Hurricane Helene Observed by SAR

DEFF Research Database (Denmark)

Xu, Qing; Cheng, Yongcun; Li, Xiaofeng

2011-01-01

Prediction System (NOGAPS) model, C-band geophysical model functions (GMFs) which describe the normalized radar cross section (NRCS) dependence on the wind speed and the geometry of radar observations (i.e., incidence angle and azimuth angle with respect to wind direction) such as CMOD5 and newly developed......The hurricanes can be detected by many remote sensors, but synthetic aperture radar (SAR) can yield high-resolution (sub-kilometer) and low-level wind information that cannot be seen below the cloud by other sensors. In this paper, an assessment of SAR capability of monitoring high...

Observations of the structure and evolution of surface and flight-level wind asymmetries in Hurricane Rita (2005)

Science.gov (United States)

Rogers, Robert; Uhlhorn, Eric

2008-11-01

Knowledge of the magnitude and distribution of surface winds, including the structure of azimuthal asymmetries in the wind field, are important factors for tropical cyclone forecasting. With its ability to remotely measure surface wind speeds, the stepped frequency microwave radiometer (SFMR) has assumed a prominent role for the operational tropical cyclone forecasting community. An example of this instrument's utility is presented here, where concurrent measurements of aircraft flight-level and SFMR surface winds are used to document the wind field evolution over three days in Hurricane Rita (2005). The amplitude and azimuthal location (phase) of the wavenumber-1 asymmetry in the storm-relative winds varied at both levels over time. The peak was found to the right of storm track at both levels on the first day. By the third day, the peak in flight-level storm-relative winds remained to the right of storm track, but it shifted to left of storm track at the surface, resulting in a 60-degree shift between the surface and flight-level and azimuthal variations in the ratio of surface to flight-level winds. The asymmetric differences between the surface and flight-level maximum wind radii also varied, indicating a vortex whose tilt was increasing.

Observation and modeling of tide- and wind-induced surface currents in Galway Bay

Directory of Open Access Journals (Sweden)

Lei REN

2015-10-01

Full Text Available A high-frequency radar system has been deployed in Galway Bay, a semi-enclosed bay on the west coast of Ireland. The system provides surface currents with fine spatial resolution every hour. Prior to its use for model validation, the accuracy of the radar data was verified through comparison with measurements from acoustic Doppler current profilers (ADCPs and a good correlation between time series of surface current speeds and directions obtained from radar data and ADCP data. Since Galway Bay is located on the coast of the Atlantic Ocean, it is subject to relatively windy conditions, and surface currents are therefore strongly wind-driven. With a view to assimilating the radar data for forecasting purposes, a three-dimensional numerical model of Galway Bay, the Environmental Fluid Dynamics Code (EFDC, was developed based on a terrain-following vertical (sigma coordinate system. This study shows that the performance and accuracy of the numerical model, particularly with regard to tide- and wind-induced surface currents, are sensitive to the vertical layer structure. Results of five models using different layer structures are presented and compared with radar measurements. A variable vertical structure with thin layers at the bottom and the surface and thicker layers in the middle of the water column was found to be the optimal layer structure for reproduction of tide- and wind-induced surface currents. This structure ensures that wind shear can properly propagate from the surface layer to the sub-surface layers, thereby ensuring that wind forcing is not overdamped by tidal forcing. The vertical layer structure affects not only the velocities at the surface layer but also the velocities further down in the water column.

A hybrid measure-correlate-predict method for long-term wind condition assessment

International Nuclear Information System (INIS)

Zhang, Jie; Chowdhury, Souma; Messac, Achille; Hodge, Bri-Mathias

2014-01-01

Highlights: • A hybrid measure-correlate-predict (MCP) methodology with greater accuracy is developed. • Three sets of performance metrics are proposed to evaluate the hybrid MCP method. • Both wind speed and direction are considered in the hybrid MCP method. • The best combination of MCP algorithms is determined. • The developed hybrid MCP method is uniquely helpful for long-term wind resource assessment. - Abstract: This paper develops a hybrid measure-correlate-predict (MCP) strategy to assess long-term wind resource variations at a farm site. The hybrid MCP method uses recorded data from multiple reference stations to estimate long-term wind conditions at a target wind plant site with greater accuracy than is possible with data from a single reference station. The weight of each reference station in the hybrid strategy is determined by the (i) distance and (ii) elevation differences between the target farm site and each reference station. In this case, the wind data is divided into sectors according to the wind direction, and the MCP strategy is implemented for each wind direction sector separately. The applicability of the proposed hybrid strategy is investigated using five MCP methods: (i) the linear regression; (ii) the variance ratio; (iii) the Weibull scale; (iv) the artificial neural networks; and (v) the support vector regression. To implement the hybrid MCP methodology, we use hourly averaged wind data recorded at five stations in the state of Minnesota between 07-01-1996 and 06-30-2004. Three sets of performance metrics are used to evaluate the hybrid MCP method. The first set of metrics analyze the statistical performance, including the mean wind speed, wind speed variance, root mean square error, and mean absolute error. The second set of metrics evaluate the distribution of long-term wind speed; to this end, the Weibull distribution and the Multivariate and Multimodal Wind Distribution models are adopted. The third set of metrics analyze

An optimal design of wind turbine and ship structure based on neuro-response surface method

Directory of Open Access Journals (Sweden)

Jae-Chul Lee

2015-07-01

Full Text Available The geometry of engineering systems affects their performances. For this reason, the shape of engineering systems needs to be optimized in the initial design stage. However, engineering system design problems consist of multi-objective optimization and the performance analysis using commercial code or numerical analysis is generally time-consuming. To solve these problems, many engineers perform the optimization using the approximation model (response surface. The Response Surface Method (RSM is generally used to predict the system performance in engi-neering research field, but RSM presents some prediction errors for highly nonlinear systems. The major objective of this research is to establish an optimal design method for multi-objective problems and confirm its applicability. The proposed process is composed of three parts: definition of geometry, generation of response surface, and optimization process. To reduce the time for performance analysis and minimize the prediction errors, the approximation model is generated using the Backpropagation Artificial Neural Network (BPANN which is considered as Neuro-Response Surface Method (NRSM. The optimization is done for the generated response surface by non-dominated sorting genetic algorithm-II (NSGA-II. Through case studies of marine system and ship structure (substructure of floating offshore wind turbine considering hydrodynamics performances and bulk carrier bottom stiffened panels considering structure performance, we have confirmed the applicability of the proposed method for multi-objective side constraint optimization problems.

An optimal design of wind turbine and ship structure based on neuro-response surface method

Science.gov (United States)

Lee, Jae-Chul; Shin, Sung-Chul; Kim, Soo-Young

2015-07-01

The geometry of engineering systems affects their performances. For this reason, the shape of engineering systems needs to be optimized in the initial design stage. However, engineering system design problems consist of multi-objective optimization and the performance analysis using commercial code or numerical analysis is generally time-consuming. To solve these problems, many engineers perform the optimization using the approximation model (response surface). The Response Surface Method (RSM) is generally used to predict the system performance in engineering research field, but RSM presents some prediction errors for highly nonlinear systems. The major objective of this research is to establish an optimal design method for multi-objective problems and confirm its applicability. The proposed process is composed of three parts: definition of geometry, generation of response surface, and optimization process. To reduce the time for performance analysis and minimize the prediction errors, the approximation model is generated using the Backpropagation Artificial Neural Network (BPANN) which is considered as Neuro-Response Surface Method (NRSM). The optimization is done for the generated response surface by non-dominated sorting genetic algorithm-II (NSGA-II). Through case studies of marine system and ship structure (substructure of floating offshore wind turbine considering hydrodynamics performances and bulk carrier bottom stiffened panels considering structure performance), we have confirmed the applicability of the proposed method for multi-objective side constraint optimization problems.

Global composites of surface wind speeds in tropical cyclones based on a 12 year scatterometer database

Science.gov (United States)

Klotz, Bradley W.; Jiang, Haiyan

2016-10-01

A 12 year global database of rain-corrected satellite scatterometer surface winds for tropical cyclones (TCs) is used to produce composites of TC surface wind speed distributions relative to vertical wind shear and storm motion directions in each TC-prone basin and various TC intensity stages. These composites corroborate ideas presented in earlier studies, where maxima are located right of motion in the Earth-relative framework. The entire TC surface wind asymmetry is down motion left for all basins and for lower strength TCs after removing the motion vector. Relative to the shear direction, the motion-removed composites indicate that the surface wind asymmetry is located down shear left for the outer region of all TCs, but for the inner-core region it varies from left of shear to down shear right for different basin and TC intensity groups. Quantification of the surface wind asymmetric structure in further stratifications is a necessary next step for this scatterometer data set.

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.

Indian Ocean surface winds from NCMRWF analysis as compared to ...

Indian Academy of Sciences (India)

R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22

The quality of the surface wind analysis at the National Centre for Medium Range Weather Fore- casts (NCMRWF), New .... mization of a generalized cost function using the. Spectral ... power from a given location on the sea surface at multiple ...

Wind power application research on the fusion of the determination and ensemble prediction

Science.gov (United States)

Lan, Shi; Lina, Xu; Yuzhu, Hao

2017-07-01

The fused product of wind speed for the wind farm is designed through the use of wind speed products of ensemble prediction from the European Centre for Medium-Range Weather Forecasts (ECMWF) and professional numerical model products on wind power based on Mesoscale Model5 (MM5) and Beijing Rapid Update Cycle (BJ-RUC), which are suitable for short-term wind power forecasting and electric dispatch. The single-valued forecast is formed by calculating the different ensemble statistics of the Bayesian probabilistic forecasting representing the uncertainty of ECMWF ensemble prediction. Using autoregressive integrated moving average (ARIMA) model to improve the time resolution of the single-valued forecast, and based on the Bayesian model averaging (BMA) and the deterministic numerical model prediction, the optimal wind speed forecasting curve and the confidence interval are provided. The result shows that the fusion forecast has made obvious improvement to the accuracy relative to the existing numerical forecasting products. Compared with the 0-24 h existing deterministic forecast in the validation period, the mean absolute error (MAE) is decreased by 24.3 % and the correlation coefficient (R) is increased by 12.5 %. In comparison with the ECMWF ensemble forecast, the MAE is reduced by 11.7 %, and R is increased 14.5 %. Additionally, MAE did not increase with the prolongation of the forecast ahead.

Improving Wind Farm Dispatchability Using Model Predictive Control for Optimal Operation of Grid-Scale Energy Storage

Directory of Open Access Journals (Sweden)

Douglas Halamay

2014-09-01

Full Text Available This paper demonstrates the use of model-based predictive control for energy storage systems to improve the dispatchability of wind power plants. Large-scale wind penetration increases the variability of power flow on the grid, thus increasing reserve requirements. Large energy storage systems collocated with wind farms can improve dispatchability of the wind plant by storing energy during generation over-the-schedule and sourcing energy during generation under-the-schedule, essentially providing on-site reserves. Model predictive control (MPC provides a natural framework for this application. By utilizing an accurate energy storage system model, control actions can be planned in the context of system power and state-of-charge limitations. MPC also enables the inclusion of predicted wind farm performance over a near-term horizon that allows control actions to be planned in anticipation of fast changes, such as wind ramps. This paper demonstrates that model-based predictive control can improve system performance compared with a standard non-predictive, non-model-based control approach. It is also demonstrated that secondary objectives, such as reducing the rate of change of the wind plant output (i.e., ramps, can be considered and successfully implemented within the MPC framework. Specifically, it is shown that scheduling error can be reduced by 81%, reserve requirements can be improved by up to 37%, and the number of ramp events can be reduced by 74%.

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.

Auto-correlation analysis of ocean surface wind vectors

Indian Academy of Sciences (India)

M. Senthilkumar (Newgen Imaging) 1461 1996 Oct 15 13:05:22

time series data of surface winds measured in situ by a deep water buoy in the Indian Ocean has been carried out. ... A case study using the TRMM Microwave Imager (TMI) and ... parameter is essential when the values of the parameter ...

A Gaussian mixture copula model based localized Gaussian process regression approach for long-term wind speed prediction

International Nuclear Information System (INIS)

Yu, Jie; Chen, Kuilin; Mori, Junichi; Rashid, Mudassir M.

2013-01-01

Optimizing wind power generation and controlling the operation of wind turbines to efficiently harness the renewable wind energy is a challenging task due to the intermittency and unpredictable nature of wind speed, which has significant influence on wind power production. A new approach for long-term wind speed forecasting is developed in this study by integrating GMCM (Gaussian mixture copula model) and localized GPR (Gaussian process regression). The time series of wind speed is first classified into multiple non-Gaussian components through the Gaussian mixture copula model and then Bayesian inference strategy is employed to incorporate the various non-Gaussian components using the posterior probabilities. Further, the localized Gaussian process regression models corresponding to different non-Gaussian components are built to characterize the stochastic uncertainty and non-stationary seasonality of the wind speed data. The various localized GPR models are integrated through the posterior probabilities as the weightings so that a global predictive model is developed for the prediction of wind speed. The proposed GMCM–GPR approach is demonstrated using wind speed data from various wind farm locations and compared against the GMCM-based ARIMA (auto-regressive integrated moving average) and SVR (support vector regression) methods. In contrast to GMCM–ARIMA and GMCM–SVR methods, the proposed GMCM–GPR model is able to well characterize the multi-seasonality and uncertainty of wind speed series for accurate long-term prediction. - Highlights: • A novel predictive modeling method is proposed for long-term wind speed forecasting. • Gaussian mixture copula model is estimated to characterize the multi-seasonality. • Localized Gaussian process regression models can deal with the random uncertainty. • Multiple GPR models are integrated through Bayesian inference strategy. • The proposed approach shows higher prediction accuracy and reliability

Comparison of Flight Measured, Predicted and Wind Tunnel Measured Winglet Characteristics on a KC-135 Aircraft

Science.gov (United States)

Dodson, R. O., Jr.

1982-01-01

One of the objectives of the KC-135 Winglet Flight Research and Demonstration Program was to obtain experimental flight test data to verify the theoretical and wind tunnel winglet aerodynamic performance prediction methods. Good agreement between analytic, wind tunnel and flight test performance was obtained when the known differences between the tests and analyses were accounted for. The flight test measured fuel mileage improvements for a 0.78 Mach number was 3.1 percent at 8 x 10(5) pounds W/delta and 5.5 percent at 1.05 x 10(6) pounds W/delta. Correcting the flight measured data for surface pressure differences between wind tunnel and flight resulted in a fuel mileage improvement of 4.4 percent at 8 x 10(5) pounds W/delta and 7.2 percent at 1.05 x 10(6) pounds W/delta. The performance improvement obtained was within the wind tunnel test data obtained from two different wind tunnel models. The buffet boundary data obtained for the baseline configuration was in good agreement with previous established data. Buffet data for the 15 deg cant/-4 deg incidence configuration showed a slight improvement, while the 15 deg cant/-2 deg incidence and 0 deg cant/-4 deg incidence data showed a slight deterioration.

The effects of tropical wind data on the prediction of ultralong waves

Science.gov (United States)

Baker, W. E.

1981-01-01

The influence of tropical wind data on the prediction of planetary waves were studied. Two assimilation experiments were performed, one with and one without FGGE tropical winds. The planetary wave error was then analyzed in 72 h forecasts from the initial conditions provided by the two assimilations.

Application of a ray theory model to the prediction of noise emissions from isolated wind turbines and wind parks

International Nuclear Information System (INIS)

Prospathopoulos, John M.; Voutsinas, Spyros G.

2006-01-01

Various propagation models have been developed to estimate the level of noise near residential areas. Predictions and measurements have proven that proper modelling of the propagation medium is of particular importance. In the present work, calculations are performed using a ray theory methodology. The ray trajectory and transport equations are derived from the linear acoustics equations for a moving medium in three dimensions. Ground and atmospheric absorption, wave refraction and diffraction and atmospheric turbulence are taken into account by introducing appropriate coefficients in the equations. In the case of a wind turbine (W/T) it is assumed that noise is produced by a point source located at the rotor centre. Given the sound power spectrum, the noise spectrum at the receiver is obtained by solving the axisymmetric propagation problem. The procedure consists of (a) finding the eigenrays, (b) calculating the energy losses along the eigenrays and (c) synthesizing the sound pressure level (SPL) by superposing the contributions of the eigenrays. In the case of a wind park the total SPL is calculated by superposing the contributions of all W/Ts. Application is made to five cases of isolated W/Ts in terrains of varying complexity. In flat or even smooth terrain the predictions agree well with the measurements. In complex terrain the predictions can be considered satisfactory, taking into account the assumption of constant wind velocity profile. Application to a wind park shows clearly the influence of the terrain on the wind velocity and consequently on the SPL. (Author)

A Gaussian process regression based hybrid approach for short-term wind speed prediction

International Nuclear Information System (INIS)

Zhang, Chi; Wei, Haikun; Zhao, Xin; Liu, Tianhong; Zhang, Kanjian

2016-01-01

Highlights: • A novel hybrid approach is proposed for short-term wind speed prediction. • This method combines the parametric AR model with the non-parametric GPR model. • The relative importance of different inputs is considered. • Different types of covariance functions are considered and combined. • It can provide both accurate point forecasts and satisfactory prediction intervals. - Abstract: This paper proposes a hybrid model based on autoregressive (AR) model and Gaussian process regression (GPR) for probabilistic wind speed forecasting. In the proposed approach, the AR model is employed to capture the overall structure from wind speed series, and the GPR is adopted to extract the local structure. Additionally, automatic relevance determination (ARD) is used to take into account the relative importance of different inputs, and different types of covariance functions are combined to capture the characteristics of the data. The proposed hybrid model is compared with the persistence model, artificial neural network (ANN), and support vector machine (SVM) for one-step ahead forecasting, using wind speed data collected from three wind farms in China. The forecasting results indicate that the proposed method can not only improve point forecasts compared with other methods, but also generate satisfactory prediction intervals.

Assessment of Wind Turbine Structural Integrity using Response Surface Methodology

DEFF Research Database (Denmark)

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

2016-01-01

Highlights •A new approach to assessment of site specific wind turbine loads is proposed. •The approach can be applied in both fatigue and ultimate limit state. •Two different response surface methodologies have been investigated. •The model uncertainty introduced by the response surfaces...

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

Observation and modeling of tide- and wind-induced surface currents in Galway Bay

Directory of Open Access Journals (Sweden)

Lei Ren

2015-10-01

Full Text Available A high-frequency radar system has been deployed in Galway Bay, a semi-enclosed bay on the west coast of Ireland. The system provides surface currents with fine spatial resolution every hour. Prior to its use for model validation, the accuracy of the radar data was verified through comparison with measurements from acoustic Doppler current profilers (ADCPs and a good correlation between time series of surface current speeds and directions obtained from radar data and ADCP data. Since Galway Bay is located on the coast of the Atlantic Ocean, it is subject to relatively windy conditions, and surface currents are therefore strongly wind-driven. With a view to assimilating the radar data for forecasting purposes, a three-dimensional numerical model of Galway Bay, the Environmental Fluid Dynamics Code (EFDC, was developed based on a terrain-following vertical (sigma coordinate system. This study shows that the performance and accuracy of the numerical model, particularly with regard to tide- and wind-induced surface currents, are sensitive to the vertical layer structure. Results of five models with different layer structures are presented and compared with radar measurements. A variable vertical structure with thin layers at the bottom and the surface and thicker layers in the middle of the water column was found to be the optimal layer structure for reproduction of tide- and wind-induced surface currents. This structure ensures that wind shear can properly propagate from the surface layer to the sub-surface layers, thereby ensuring that wind forcing is not overdamped by tidal forcing. The vertical layer structure affects not only the velocities at the surface layer but also the velocities further down in the water column.

Dynamic Modeling and Very Short-term Prediction of Wind Power Output Using Box-Cox Transformation

Science.gov (United States)

Urata, Kengo; Inoue, Masaki; Murayama, Dai; Adachi, Shuichi

2016-09-01

We propose a statistical modeling method of wind power output for very short-term prediction. The modeling method with a nonlinear model has cascade structure composed of two parts. One is a linear dynamic part that is driven by a Gaussian white noise and described by an autoregressive model. The other is a nonlinear static part that is driven by the output of the linear part. This nonlinear part is designed for output distribution matching: we shape the distribution of the model output to match with that of the wind power output. The constructed model is utilized for one-step ahead prediction of the wind power output. Furthermore, we study the relation between the prediction accuracy and the prediction horizon.

Comparison of four Adaboost algorithm based artificial neural networks in wind speed predictions

International Nuclear Information System (INIS)

Liu, Hui; Tian, Hong-qi; Li, Yan-fei; Zhang, Lei

2015-01-01

Highlights: • Four hybrid algorithms are proposed for the wind speed decomposition. • Adaboost algorithm is adopted to provide a hybrid training framework. • MLP neural networks are built to do the forecasting computation. • Four important network training algorithms are included in the MLP networks. • All the proposed hybrid algorithms are suitable for the wind speed predictions. - Abstract: The technology of wind speed prediction is important to guarantee the safety of wind power utilization. In this paper, four different hybrid methods are proposed for the high-precision multi-step wind speed predictions based on the Adaboost (Adaptive Boosting) algorithm and the MLP (Multilayer Perceptron) neural networks. In the hybrid Adaboost–MLP forecasting architecture, four important algorithms are adopted for the training and modeling of the MLP neural networks, including GD-ALR-BP algorithm, GDM-ALR-BP algorithm, CG-BP-FR algorithm and BFGS algorithm. The aim of the study is to investigate the promoted forecasting percentages of the MLP neural networks by the Adaboost algorithm’ optimization under various training algorithms. The hybrid models in the performance comparison include Adaboost–GD-ALR-BP–MLP, Adaboost–GDM-ALR-BP–MLP, Adaboost–CG-BP-FR–MLP, Adaboost–BFGS–MLP, GD-ALR-BP–MLP, GDM-ALR-BP–MLP, CG-BP-FR–MLP and BFGS–MLP. Two experimental results show that: (1) the proposed hybrid Adaboost–MLP forecasting architecture is effective for the wind speed predictions; (2) the Adaboost algorithm has promoted the forecasting performance of the MLP neural networks considerably; (3) among the proposed Adaboost–MLP forecasting models, the Adaboost–CG-BP-FR–MLP model has the best performance; and (4) the improved percentages of the MLP neural networks by the Adaboost algorithm decrease step by step with the following sequence of training algorithms as: GD-ALR-BP, GDM-ALR-BP, CG-BP-FR and BFGS

Are we near the predictability limit of tropical Indo-Pacific sea surface temperatures?

Science.gov (United States)

Newman, Matthew; Sardeshmukh, Prashant D.

2017-08-01

The predictability of seasonal anomalies worldwide rests largely on the predictability of tropical sea surface temperature (SST) anomalies. Tropical forecast skill is also a key metric of climate models. We find, however, that despite extensive model development, the tropical SST forecast skill of the operational North American Multi-Model Ensemble (NMME) of eight coupled atmosphere-ocean models remains close both regionally and temporally to that of a vastly simpler linear inverse model (LIM) derived from observed covariances of SST, sea surface height, and wind fields. The LIM clearly captures the essence of the predictable SST dynamics. The NMME and LIM skills also closely track and are only slightly lower than the potential skill estimated using the LIM's forecast signal-to-noise ratios. This suggests that the scope for further skill improvement is small in most regions, except in the western equatorial Pacific where the NMME skill is currently much lower than the LIM skill.

Drivers and seasonal predictability of extreme wind speeds in the ECMWF System 4 and a statistical model

Science.gov (United States)

Walz, M. A.; Donat, M.; Leckebusch, G. C.

2017-12-01

As extreme wind speeds are responsible for large socio-economic losses in Europe, a skillful prediction would be of great benefit for disaster prevention as well as for the actuarial community. Here we evaluate patterns of large-scale atmospheric variability and the seasonal predictability of extreme wind speeds (e.g. >95th percentile) in the European domain in the dynamical seasonal forecast system ECMWF System 4, and compare to the predictability based on a statistical prediction model. The dominant patterns of atmospheric variability show distinct differences between reanalysis and ECMWF System 4, with most patterns in System 4 extended downstream in comparison to ERA-Interim. The dissimilar manifestations of the patterns within the two models lead to substantially different drivers associated with the occurrence of extreme winds in the respective model. While the ECMWF System 4 is shown to provide some predictive power over Scandinavia and the eastern Atlantic, only very few grid cells in the European domain have significant correlations for extreme wind speeds in System 4 compared to ERA-Interim. In contrast, a statistical model predicts extreme wind speeds during boreal winter in better agreement with the observations. Our results suggest that System 4 does not seem to capture the potential predictability of extreme winds that exists in the real world, and therefore fails to provide reliable seasonal predictions for lead months 2-4. This is likely related to the unrealistic representation of large-scale patterns of atmospheric variability. Hence our study points to potential improvements of dynamical prediction skill by improving the simulation of large-scale atmospheric dynamics.

Performance and wake predictions of HAWTs in wind farms

Energy Technology Data Exchange (ETDEWEB)

Leclerc, C.; Masson, C.; Paraschivoiu, I. [Ecole Polytechnique, Montreal (Canada)

1997-12-31

The present contribution proposes and describes a promising way towards performance prediction of an arbitrary array of turbines. It is based on the solution of the time-averaged, steady-state, incompressible Navier-Stokes equations with an appropriate turbulence closure model. The turbines are represented by distributions of momentum sources in the Navier-Stokes equations. In this paper, the applicability and viability of the proposed methodology is demonstrated using an axisymmetric implementation. The k-{epsilon} model has been chosen for the closure of the time-averaged, turbulent flow equations and the properties of the incident flow correspond to those of a neutral atmospheric boundary layer. The proposed mathematical model is solved using a Control-Volume Finite Element Method (CVFEM). Detailed results have been obtained using the proposed method for an isolated wind turbine and for two turbines one behind another. In the case of an isolated turbine, accurate wake velocity deficit predictions are obtained and an increase in power due to atmospheric turbulence is found in agreement with measurements. In the case of two turbines, the proposed methodology provides an appropriate modelling of the wind-turbine wake and a realistic prediction of the performance degradation of the downstream turbine.

Initialization of high resolution surface wind simulations using NWS gridded data

Science.gov (United States)

J. Forthofer; K. Shannon; Bret Butler

2010-01-01

WindNinja is a standalone computer model designed to provide the user with simulations of surface wind flow. It is deterministic and steady state. It is currently being modified to allow the user to initialize the flow calculation using National Digital Forecast Database. It essentially allows the user to downscale the coarse scale simulations from meso-scale models to...

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...

Forecasting Electricity Spot Prices Accounting for Wind Power Predictions

DEFF Research Database (Denmark)

Jónsson, Tryggvi; Pinson, Pierre; Nielsen, Henrik Aalborg

2013-01-01

A two-step methodology for forecasting of electricity spot prices is introduced, with focus on the impact of predicted system load and wind power generation. The nonlinear and nonstationary influence of these explanatory variables is accommodated in a first step based on a nonparametric and time...

Experimental High-Resolution Land Surface Prediction System for the Vancouver 2010 Winter Olympic Games

Science.gov (United States)

Belair, S.; Bernier, N.; Tong, L.; Mailhot, J.

2008-05-01

The 2010 Winter Olympic and Paralympic Games will take place in Vancouver, Canada, from 12 to 28 February 2010 and from 12 to 21 March 2010, respectively. In order to provide the best possible guidance achievable with current state-of-the-art science and technology, Environment Canada is currently setting up an experimental numerical prediction system for these special events. This system consists of a 1-km limited-area atmospheric model that will be integrated for 16h, twice a day, with improved microphysics compared with the system currently operational at the Canadian Meteorological Centre. In addition, several new and original tools will be used to adapt and refine predictions near and at the surface. Very high-resolution two-dimensional surface systems, with 100-m and 20-m grid size, will cover the Vancouver Olympic area. Using adaptation methods to improve the forcing from the lower-resolution atmospheric models, these 2D surface models better represent surface processes, and thus lead to better predictions of snow conditions and near-surface air temperature. Based on a similar strategy, a single-point model will be implemented to better predict surface characteristics at each station of an observing network especially installed for the 2010 events. The main advantage of this single-point system is that surface observations are used as forcing for the land surface models, and can even be assimilated (although this is not expected in the first version of this new tool) to improve initial conditions of surface variables such as snow depth and surface temperatures. Another adaptation tool, based on 2D stationnary solutions of a simple dynamical system, will be used to produce near-surface winds on the 100-m grid, coherent with the high- resolution orography. The configuration of the experimental numerical prediction system will be presented at the conference, together with preliminary results for winter 2007-2008.

Model predictive control of a wind turbine modelled in Simpack

International Nuclear Information System (INIS)

Jassmann, U; Matzke, D; Reiter, M; Abel, D; Berroth, J; Schelenz, R; Jacobs, G

2014-01-01

Wind turbines (WT) are steadily growing in size to increase their power production, which also causes increasing loads acting on the turbine's components. At the same time large structures, such as the blades and the tower get more flexible. To minimize this impact, the classical control loops for keeping the power production in an optimum state are more and more extended by load alleviation strategies. These additional control loops can be unified by a multiple-input multiple-output (MIMO) controller to achieve better balancing of tuning parameters. An example for MIMO control, which has been paid more attention to recently by wind industry, is Model Predictive Control (MPC). In a MPC framework a simplified model of the WT is used to predict its controlled outputs. Based on a user-defined cost function an online optimization calculates the optimal control sequence. Thereby MPC can intrinsically incorporate constraints e.g. of actuators. Turbine models used for calculation within the MPC are typically simplified. For testing and verification usually multi body simulations, such as FAST, BLADED or FLEX5 are used to model system dynamics, but they are still limited in the number of degrees of freedom (DOF). Detailed information about load distribution (e.g. inside the gearbox) cannot be provided by such models. In this paper a Model Predictive Controller is presented and tested in a co-simulation with SlMPACK, a multi body system (MBS) simulation framework used for detailed load analysis. The analysis are performed on the basis of the IME6.0 MBS WT model, described in this paper. It is based on the rotor of the NREL 5MW WT and consists of a detailed representation of the drive train. This takes into account a flexible main shaft and its main bearings with a planetary gearbox, where all components are modelled flexible, as well as a supporting flexible main frame. The wind loads are simulated using the NREL AERODYN v13 code which has been implemented as a routine

Model predictive control of a wind turbine modelled in Simpack

Science.gov (United States)

Jassmann, U.; Berroth, J.; Matzke, D.; Schelenz, R.; Reiter, M.; Jacobs, G.; Abel, D.

2014-06-01

Wind turbines (WT) are steadily growing in size to increase their power production, which also causes increasing loads acting on the turbine's components. At the same time large structures, such as the blades and the tower get more flexible. To minimize this impact, the classical control loops for keeping the power production in an optimum state are more and more extended by load alleviation strategies. These additional control loops can be unified by a multiple-input multiple-output (MIMO) controller to achieve better balancing of tuning parameters. An example for MIMO control, which has been paid more attention to recently by wind industry, is Model Predictive Control (MPC). In a MPC framework a simplified model of the WT is used to predict its controlled outputs. Based on a user-defined cost function an online optimization calculates the optimal control sequence. Thereby MPC can intrinsically incorporate constraints e.g. of actuators. Turbine models used for calculation within the MPC are typically simplified. For testing and verification usually multi body simulations, such as FAST, BLADED or FLEX5 are used to model system dynamics, but they are still limited in the number of degrees of freedom (DOF). Detailed information about load distribution (e.g. inside the gearbox) cannot be provided by such models. In this paper a Model Predictive Controller is presented and tested in a co-simulation with SlMPACK, a multi body system (MBS) simulation framework used for detailed load analysis. The analysis are performed on the basis of the IME6.0 MBS WT model, described in this paper. It is based on the rotor of the NREL 5MW WT and consists of a detailed representation of the drive train. This takes into account a flexible main shaft and its main bearings with a planetary gearbox, where all components are modelled flexible, as well as a supporting flexible main frame. The wind loads are simulated using the NREL AERODYN v13 code which has been implemented as a routine to

Predicting geomagnetic storms from solar-wind data using time-delay neural networks

Directory of Open Access Journals (Sweden)

H. Gleisner

1996-07-01

Full Text Available We have used time-delay feed-forward neural networks to compute the geomagnetic-activity index Dst one hour ahead from a temporal sequence of solar-wind data. The input data include solar-wind density n, velocity V and the southward component Bz of the interplanetary magnetic field. Dst is not included in the input data. The networks implement an explicit functional relationship between the solar wind and the geomagnetic disturbance, including both direct and time-delayed non-linear relations. In this study we especially consider the influence of varying the temporal size of the input-data sequence. The networks are trained on data covering 6600 h, and tested on data covering 2100 h. It is found that the initial and main phases of geomagnetic storms are well predicted, almost independent of the length of the input-data sequence. However, to predict the recovery phase, we have to use up to 20 h of solar-wind input data. The recovery phase is mainly governed by the ring-current loss processes, and is very much dependent on the ring-current history, and thus also the solar-wind history. With due consideration of the time history when optimizing the networks, we can reproduce 84% of the Dst variance.

Stochastic Prediction of Wind Generating Resources Using the Enhanced Ensemble Model for Jeju Island’s Wind Farms in South Korea

Directory of Open Access Journals (Sweden)

Deockho Kim

2017-05-01

Full Text Available Due to the intermittency of wind power generation, it is very hard to manage its system operation and planning. In order to incorporate higher wind power penetrations into power systems that maintain secure and economic power system operation, an accurate and efficient estimation of wind power outputs is needed. In this paper, we propose the stochastic prediction of wind generating resources using an enhanced ensemble model for Jeju Island’s wind farms in South Korea. When selecting the potential sites of wind farms, wind speed data at points of interest are not always available. We apply the Kriging method, which is one of spatial interpolation, to estimate wind speed at potential sites. We also consider a wind profile power law to correct wind speed along the turbine height and terrain characteristics. After that, we used estimated wind speed data to calculate wind power output and select the best wind farm sites using a Weibull distribution. Probability density function (PDF or cumulative density function (CDF is used to estimate the probability of wind speed. The wind speed data is classified along the manufacturer’s power curve data. Therefore, the probability of wind speed is also given in accordance with classified values. The average wind power output is estimated in the form of a confidence interval. The empirical data of meteorological towers from Jeju Island in Korea is used to interpolate the wind speed data spatially at potential sites. Finally, we propose the best wind farm site among the four potential wind farm sites.

Time-resolved PIV measurements of the atmospheric boundary layer over wind-driven surface waves

Science.gov (United States)

Markfort, Corey; Stegmeir, Matt

2017-11-01

Complex interactions at the air-water interface result in two-way coupling between wind-driven surface waves and the atmospheric boundary layer (ABL). Turbulence generated at the surface plays an important role in aquatic ecology and biogeochemistry, exchange of gases such as oxygen and carbon dioxide, and it is important for the transfer of energy and controlling evaporation. Energy transferred from the ABL promotes the generation and maintenance of waves. A fraction of the energy is transferred to the surface mixed layer through the generation of turbulence. Energy is also transferred back to the ABL by waves. There is a need to quantify the details of the coupled boundary layers of the air-water system to better understand how turbulence plays a role in the interactions. We employ time-resolved PIV to measure the detailed structure of the air and water boundary layers under varying wind and wave conditions in the newly developed IIHR Boundary-Layer Wind-Wave Tunnel. The facility combines a 30-m long recirculating water channel with an open-return boundary layer wind tunnel. A thick turbulent boundary layer is developed in the 1 m high air channel, over the water surface, allowing for the study of boundary layer turbulence interacting with a wind-driven wave field.

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...

Wind-Wave Effects on Vertical Mixing in Chesapeake Bay, USA: comparing observations to second-moment closure predictions.

Science.gov (United States)

Fisher, A. W.; Sanford, L. P.; Scully, M. E.

2016-12-01

Coherent wave-driven turbulence generated through wave breaking or nonlinear wave-current interactions, e.g. Langmuir turbulence (LT), can significantly enhance the downward transfer of momentum, kinetic energy, and dissolved gases in the oceanic surface layer. There are few observations of these processes in the estuarine or coastal environments, where wind-driven mixing may co-occur with energetic tidal mixing and strong density stratification. This presents a major challenge for evaluating vertical mixing parameterizations used in modeling estuarine and coastal dynamics. We carried out a large, multi-investigator study of wind-driven estuarine dynamics in the middle reaches of Chesapeake Bay, USA, during 2012-2013. The center of the observational array was an instrumented turbulence tower with both atmospheric and marine turbulence sensors as well as rapidly sampled temperature and conductivity sensors. For this paper, we examined the impacts of surface gravity waves on vertical profiles of turbulent mixing and compared our results to second-moment turbulence closure predictions. Wave and turbulence measurements collected from the vertical array of Acoustic Doppler Velocimeters (ADVs) provided direct estimates of the dominant terms in the TKE budget and the surface wave field. Observed dissipation rates, TKE levels, and turbulent length scales are compared to published scaling relations and used in the calculation of second-moment nonequilibrium stability functions. Results indicate that in the surface layer of the estuary, where elevated dissipation is balanced by vertical divergence in TKE flux, existing nonequilibrium stability functions underpredict observed eddy viscosities. The influences of wave breaking and coherent wave-driven turbulence on modeled and observed stability functions will be discussed further in the context of turbulent length scales, TKE and dissipation profiles, and the depth at which the wave-dominated turbulent transport layer

A new class of actuator surface models for wind turbines

Science.gov (United States)

Yang, Xiaolei; Sotiropoulos, Fotis

2018-05-01

Actuator line model has been widely employed in wind turbine simulations. However, the standard actuator line model does not include a model for the turbine nacelle which can significantly impact turbine wake characteristics as shown in the literature. Another disadvantage of the standard actuator line model is that more geometrical features of turbine blades cannot be resolved on a finer mesh. To alleviate these disadvantages of the standard model, we develop a new class of actuator surface models for turbine blades and nacelle to take into account more geometrical details of turbine blades and include the effect of turbine nacelle. In the actuator surface model for blade, the aerodynamic forces calculated using the blade element method are distributed from the surface formed by the foil chords at different radial locations. In the actuator surface model for nacelle, the forces are distributed from the actual nacelle surface with the normal force component computed in the same way as in the direct forcing immersed boundary method and the tangential force component computed using a friction coefficient and a reference velocity of the incoming flow. The actuator surface model for nacelle is evaluated by simulating the flow over periodically placed nacelles. Both the actuator surface simulation and the wall-resolved large-eddy simulation are carried out. The comparison shows that the actuator surface model is able to give acceptable results especially at far wake locations on a very coarse mesh. It is noted that although this model is employed for the turbine nacelle in this work, it is also applicable to other bluff bodies. The capability of the actuator surface model in predicting turbine wakes is assessed by simulating the flow over the MEXICO (Model experiments in Controlled Conditions) turbine and a hydrokinetic turbine.

Wind Power Grid Connected Capacity Prediction Using LSSVM Optimized by the Bat Algorithm

Directory of Open Access Journals (Sweden)

Qunli Wu

2015-12-01

Full Text Available Given the stochastic nature of wind, wind power grid-connected capacity prediction plays an essential role in coping with the challenge of balancing supply and demand. Accurate forecasting methods make enormous contribution to mapping wind power strategy, power dispatching and sustainable development of wind power industry. This study proposes a bat algorithm (BA–least squares support vector machine (LSSVM hybrid model to improve prediction performance. In order to select input of LSSVM effectively, Stationarity, Cointegration and Granger causality tests are conducted to examine the influence of installed capacity with different lags, and partial autocorrelation analysis is employed to investigate the inner relationship of grid-connected capacity. The parameters in LSSVM are optimized by BA to validate the learning ability and generalization of LSSVM. Multiple model sufficiency evaluation methods are utilized. The research results reveal that the accuracy improvement of the present approach can reach about 20% compared to other single or hybrid models.

Enhanced Voltage Control of VSC-HVDC Connected Offshore Wind Farms Based on Model Predictive Control

DEFF Research Database (Denmark)

Guo, Yifei; Gao, Houlei; Wu, Qiuwei

2018-01-01

This paper proposes an enhanced voltage control strategy (EVCS) based on model predictive control (MPC) for voltage source converter based high voltage direct current (VSCHVDC) connected offshore wind farms (OWFs). In the proposed MPC based EVCS, all wind turbine generators (WTGs) as well...... as the wind farm side VSC are optimally coordinated to keep voltages within the feasible range and reduce system power losses. Considering the high ratio of the OWF collector system, the effects of active power outputs of WTGs on voltage control are also taken into consideration. The predictive model of VSC...

Wind tunnel experiments on the effects of tillage ridge features on wind erosion horizontal fluxes

Directory of Open Access Journals (Sweden)

M. Kardous

2005-11-01

Full Text Available In addition to the well-known soil factors which control wind erosion on flat, unridged surfaces, two specific processes affect the susceptibility of tillage ridged surfaces to wind erosion: ridge-induced roughness and ridge- trapping efficiency. In order to parameterize horizontal soil fluxes produced by wind over tillage ridges, eight-ridge configurations composed of sandy soil and exhibiting ridge heights to ridge spacing (RH/RS ratios ranging from 0.18 to 0.38 were experimented in a wind tunnel. These experiments are used to develop a parameterization of the horizontal fluxes over tillage ridged surfaces based only on the geometric characteristics of the ridges. Indeed, the key parameters controlling the horizontal flux, namely the friction velocity, threshold friction velocity and the adjustment coefficient, are derived through specific expressions, from ridge heights (RH and ridge spacing (RS. This parameterization was evaluated by comparing the results of the simulations to an additional experimental data set and to the data set obtained by Hagen and Armbrust (1992. In both cases, predicted and measured values are found to be in a satisfying agreement. This parameterization was used to evaluate the efficiency of ridges in reducing wind erosion. The results show that ridged surfaces, when compared to a loose, unridged soil surface, lead to an important reduction in the horizontal fluxes (exceeding 60%. Moreover, the effect of ridges in trapping particles contributes for more than 90% in the flux reduction while the ridge roughness effect is weak and decreases when the wind velocity increases.

Performance Evaluation of a Modular Design of Wind Tower with Wetted Surfaces

Directory of Open Access Journals (Sweden)

Sajad M.R. Khani

2017-06-01

Full Text Available Wind towers or wind catchers, as passive cooling systems, can provide natural ventilation in buildings located in hot, arid regions. These natural cooling systems can provide thermal comfort for the building inhabitants throughout the warm months. In this paper, a modular design of a wind tower is introduced. The design, called a modular wind tower with wetted surfaces, was investigated experimentally and analytically. To determine the performance of the wind tower, air temperature, relative humidity (RH and air velocity were measured at different points. Measurements were carried out when the wind speed was zero. The experimental results were compared with the analytical ones. The results illustrated that the modular wind tower can decrease the air temperature significantly and increase the relative humidity of airflow into the building. The average differences for air temperature and air relative humidity between ambient air and air exiting from the wind tower were approximately 10 °C and 40%, respectively. The main advantage of the proposed wind tower is that it is a modular design that can reduce the cost of wind tower construction.

Anomalous Arctic surface wind patterns and their impacts on September sea ice minima and trend

Directory of Open Access Journals (Sweden)

Bingyi Wu

2012-05-01

Full Text Available We used monthly mean surface wind data from the National Centers for Environmental Prediction/National Centers for Atmospheric Research (NCEP/NCAR reanalysis dataset during the period 1979–2010 to describe the first two patterns of Arctic surface wind variability by means of the complex vector empirical orthogonal function (CVEOF analysis. The first two patterns respectively account for 31 and 16% of its total anomalous kinetic energy. The leading pattern consists of the two subpatterns: the northern Laptev Sea (NLS pattern and the Arctic dipole (AD pattern. The second pattern contains the northern Kara Sea (NKS pattern and the central Arctic (CA pattern. Over the past two decades, the combined dynamical forcing of the first two patterns has contributed to Arctic September sea ice extent (SIE minima and its declining trend. September SIE minima are mainly associated with the negative phase of the AD pattern and the positive phase of the CA pattern during the summer (July to September season, and both phases coherently show an anomalous anticyclone over the Arctic Ocean. Wind patterns affect September SIE through their frequency and intensity. The negative trend in September SIE over the past two decades is associated with increased frequency and enhanced intensity of the CA pattern during the melting season from April to September. Thus, it cannot be simply attributed to the AD anomaly characterised by the second empirical orthogonal function mode of sea level pressure north of 70°N. The CA pattern exhibited interdecadal variability in the late 1990s, and an anomalous cyclone prevailed before 1997 and was then replaced by an anomalous anticyclone over the Arctic Ocean that is consistent with the rapid decline trend in September SIE. This paper provides an alternative way to identify the dominant patterns of climate variability and investigate their associated Arctic sea ice variability from a dynamical perspective. Indeed, this study

"Rapid Revisit" Measurements of Sea Surface Winds Using CYGNSS

Science.gov (United States)

Park, J.; Johnson, J. T.

2017-12-01

The Cyclone Global Navigation Satellite System (CYGNSS) is a space-borne GNSS-R (GNSS-Reflectometry) mission that launched December 15, 2016 for ocean surface wind speed measurements. CYGNSS includes 8 small satellites in the same LEO orbit, so that the mission provides wind speed products having unprecedented coverage both in time and space to study multi-temporal behaviors of oceanic winds. The nature of CYGNSS coverage results in some locations on Earth experiencing multiple wind speed measurements within a short period of time (a "clump" of observations in time resulting in a "rapid revisit" series of measurements). Such observations could seemingly provide indications of regions experiencing rapid changes in wind speeds, and therefore be of scientific utility. Temporally "clumped" properties of CYGNSS measurements are investigated using early CYGNSS L1/L2 measurements, and the results show that clump durations and spacing vary with latitude. For example, the duration of a clump can extend as long as a few hours at higher latitudes, with gaps between clumps ranging from 6 to as high as 12 hours depending on latitude. Examples are provided to indicate the potential of changes within a clump to produce a "rapid revisit" product for detecting convective activity. Also, we investigate detector design for identifying convective activities. Results from analyses using recent CYGNSS L2 winds will be provided in the presentation.

Measurement of the sea surface wind speed and direction by an airborne microwave radar altimeter

Energy Technology Data Exchange (ETDEWEB)

Nekrassov, A. [GKSS-Forschungszentrum Geesthacht GmbH (Germany). Inst. fuer Hydrophysik

2001-07-01

A pilot needs operational information about wind over sea as well as wave height to provide safety of a hydroplane landing on water. Near-surface wind speed and direction can be obtained with an airborne microwave scatterometer, radar designed for measuring the scatter characteristics of a surface. Mostly narrow-beam antennas are applied for such wind measurement. Unfortunately, a microwave narrow-beam antenna has considerable size that hampers its placing on flying apparatus. In this connection, a possibility to apply a conventional airborne radar altimeter as a scatterometer with a nadir-looking wide-beam antenna in conjunction with Doppler filtering for recovering the wind vector over sea is discussed, and measuring algorithms of sea surface wind speed and direction are proposed. The obtained results can be used for creation of an airborne radar system for operational measurement of the sea roughness characteristics and for safe landing of a hydroplane on water. (orig.)

Discussion of “Prediction intervals for short-term wind farm generation forecasts” and “Combined nonparametric prediction intervals for wind power generation”

DEFF Research Database (Denmark)

Pinson, Pierre; Tastu, Julija

2014-01-01

A new score for the evaluation of interval forecasts, the so-called coverage width-based criterion (CWC), was proposed and utilized.. This score has been used for the tuning (in-sample) and genuine evaluation (out-ofsample) of prediction intervals for various applications, e.g., electric load [1......], electricity prices [2], general purpose prediction [3], and wind power generation [4], [5]. Indeed, two papers by the same authors appearing in the IEEE Transactions On Sustainable Energy employ that score and use it to conclude on the comparative quality of alternative approaches to interval forecasting...

Phase spectral composition of wind generated ocean surface waves

Digital Repository Service at National Institute of Oceanography (India)

Varkey, M.J.

A study of the composition of the phase spectra of wind generated ocean surface waves is carried out using wave records collected employing a ship borne wave recorder. It is found that the raw phase spectral estimates could be fitted by the Uniform...

Adjoint-based model predictive control of wind farms : Beyond the quasi steady-state power maximization

NARCIS (Netherlands)

Vali, M.; Petrović, Vlaho; Boersma, S.; van Wingerden, J.W.; Kuhn, Martin; Dochain, Denis; Henrion, Didier; Peaucelle, Dimitri

2017-01-01

In this paper, we extend our closed-loop optimal control framework for wind farms to minimize wake-induced power losses. We develop an adjoint-based model predictive controller which employs a medium-fidelity 2D dynamic wind farm model. The wind turbine axial induction factors are considered here

Energy Coordinative Optimization of Wind-Storage-Load Microgrids Based on Short-Term Prediction

Directory of Open Access Journals (Sweden)

Changbin Hu

2015-02-01

Full Text Available According to the topological structure of wind-storage-load complementation microgrids, this paper proposes a method for energy coordinative optimization which focuses on improvement of the economic benefits of microgrids in the prediction framework. First of all, the external characteristic mathematical model of distributed generation (DG units including wind turbines and storage batteries are established according to the requirements of the actual constraints. Meanwhile, using the minimum consumption costs from the external grid as the objective function, a grey prediction model with residual modification is introduced to output the predictive wind turbine power and load at specific periods. Second, based on the basic framework of receding horizon optimization, an intelligent genetic algorithm (GA is applied to figure out the optimum solution in the predictive horizon for the complex non-linear coordination control model of microgrids. The optimum results of the GA are compared with the receding solution of mixed integer linear programming (MILP. The obtained results show that the method is a viable approach for energy coordinative optimization of microgrid systems for energy flow and reasonable schedule. The effectiveness and feasibility of the proposed method is verified by examples.

Wind Resource Assessment in Complex Terrain with a High-Resolution Numerical Weather Prediction Model

Science.gov (United States)

Gruber, Karin; Serafin, Stefano; Grubišić, Vanda; Dorninger, Manfred; Zauner, Rudolf; Fink, Martin

2014-05-01

A crucial step in planning new wind farms is the estimation of the amount of wind energy that can be harvested in possible target sites. Wind resource assessment traditionally entails deployment of masts equipped for wind speed measurements at several heights for a reasonably long period of time. Simplified linear models of atmospheric flow are then used for a spatial extrapolation of point measurements to a wide area. While linear models have been successfully applied in the wind resource assessment in plains and offshore, their reliability in complex terrain is generally poor. This represents a major limitation to wind resource assessment in Austria, where high-altitude locations are being considered for new plant sites, given the higher frequency of sustained winds at such sites. The limitations of linear models stem from two key assumptions in their formulation, the neutral stratification and attached boundary-layer flow, both of which often break down in complex terrain. Consequently, an accurate modeling of near-surface flow over mountains requires the adoption of a NWP model with high horizontal and vertical resolution. This study explores the wind potential of a site in Styria in the North-Eastern Alps. The WRF model is used for simulations with a maximum horizontal resolution of 800 m. Three nested computational domains are defined, with the innermost one encompassing a stretch of the relatively broad Enns Valley, flanked by the main crest of the Alps in the south and the Nördliche Kalkalpen of similar height in the north. In addition to the simulation results, we use data from fourteen 10-m wind measurement sites (of which 7 are located within valleys and 5 near mountain tops) and from 2 masts with anemometers at several heights (at hillside locations) in an area of 1600 km2 around the target site. The potential for wind energy production is assessed using the mean wind speed and turbulence intensity at hub height. The capacity factor is also evaluated

Coupled assimilation for an intermediated coupled ENSO prediction model

Science.gov (United States)

Zheng, Fei; Zhu, Jiang

2010-10-01

The value of coupled assimilation is discussed using an intermediate coupled model in which the wind stress is the only atmospheric state which is slavery to model sea surface temperature (SST). In the coupled assimilation analysis, based on the coupled wind-ocean state covariance calculated from the coupled state ensemble, the ocean state is adjusted by assimilating wind data using the ensemble Kalman filter. As revealed by a series of assimilation experiments using simulated observations, the coupled assimilation of wind observations yields better results than the assimilation of SST observations. Specifically, the coupled assimilation of wind observations can help to improve the accuracy of the surface and subsurface currents because the correlation between the wind and ocean currents is stronger than that between SST and ocean currents in the equatorial Pacific. Thus, the coupled assimilation of wind data can decrease the initial condition errors in the surface/subsurface currents that can significantly contribute to SST forecast errors. The value of the coupled assimilation of wind observations is further demonstrated by comparing the prediction skills of three 12-year (1997-2008) hindcast experiments initialized by the ocean-only assimilation scheme that assimilates SST observations, the coupled assimilation scheme that assimilates wind observations, and a nudging scheme that nudges the observed wind stress data, respectively. The prediction skills of two assimilation schemes are significantly better than those of the nudging scheme. The prediction skills of assimilating wind observations are better than assimilating SST observations. Assimilating wind observations for the 2007/2008 La Niña event triggers better predictions, while assimilating SST observations fails to provide an early warning for that event.

Active Power Optimal Control of Wind Turbines with Doubly Fed Inductive Generators Based on Model Predictive Control

Directory of Open Access Journals (Sweden)

Guo Jiuwang

2015-01-01

Full Text Available Because of the randomness and fluctuation of wind energy, as well as the impact of strongly nonlinear characteristic of variable speed constant frequency (VSCF wind power generation system with doubly fed induction generators (DFIG, traditional active power control strategies are difficult to achieve high precision control and the output power of wind turbines is more fluctuated. In order to improve the quality of output electric energy of doubly fed wind turbines, on the basis of analyzing the operating principles and dynamic characteristics of doubly fed wind turbines, this paper proposes a new active power optimal control method of doubly fed wind turbines based on predictive control theory. This method uses state space model of wind turbines, based on the prediction of the future state of wind turbines, moves horizon optimization, and meanwhile, gets the control signals of pitch angle and generator torque. Simulation results show that the proposed control strategies can guarantee the utilization efficiency for wind energy. Simultaneously, they can improve operation stability of wind turbines and the quality of electric energy.

Homogenization of Tianjin monthly near-surface wind speed using RHtestsV4 for 1951-2014

Science.gov (United States)

Si, Peng; Luo, Chuanjun; Liang, Dongpo

2018-05-01

Historical Chinese surface meteorological records provided by the special fund for basic meteorological data from the National Meteorological Information Center (NMIC) were processed to produce accurate wind speed data. Monthly 2-min near-surface wind speeds from 13 observation stations in Tianjin covering 1951-2014 were homogenized using RHtestV4 combined with their metadata. Results indicate that 10 stations had significant breakpoints—77% of the Tianjin stations—suggesting that inhomogeneity was common in the Tianjin wind speed series. Instrument change accounted for most changes, based on the metadata, including changes in type and height, especially for the instrument type. Average positive quantile matching (QM) adjustments were more than negative adjustments at 10 stations; positive biases with a probability density of 0.2 or more were mainly concentrates in the range 0.2 m s-1 to 1.2 m s-1, while the corresponding negative biases were mainly in the range -0.1 to -1.2 m s-1. Here, changes in variances and trends in the monthly mean surface wind speed series at 10 stations before and after adjustment were compared. Climate characteristics of wind speed in Tianjin were more reasonably reflected by the adjusted data; inhomogeneity in wind speed series was largely corrected. Moreover, error analysis reveals that there was a high consistency between the two datasets here and that from the NMIC, with the latter as the reference. The adjusted monthly near-surface wind speed series shows a certain reliability for the period 1951-2014 in Tianjin.

Wind-sea surface temperature-sea ice relationship in the Chukchi-Beaufort Seas during autumn

Science.gov (United States)

Zhang, Jing; Stegall, Steve T.; Zhang, Xiangdong

2018-03-01

Dramatic climate changes, especially the largest sea ice retreat during September and October, in the Chukchi-Beaufort Seas could be a consequence of, and further enhance, complex air-ice-sea interactions. To detect these interaction signals, statistical relationships between surface wind speed, sea surface temperature (SST), and sea ice concentration (SIC) were analyzed. The results show a negative correlation between wind speed and SIC. The relationships between wind speed and SST are complicated by the presence of sea ice, with a negative correlation over open water but a positive correlation in sea ice dominated areas. The examination of spatial structures indicates that wind speed tends to increase when approaching the ice edge from open water and the area fully covered by sea ice. The anomalous downward radiation and thermal advection, as well as their regional distribution, play important roles in shaping these relationships, though wind-driven sub-grid scale boundary layer processes may also have contributions. Considering the feedback loop involved in the wind-SST-SIC relationships, climate model experiments would be required to further untangle the underlying complex physical processes.

Surface wind mixing in the Regional Ocean Modeling System (ROMS)

Science.gov (United States)

Robertson, Robin; Hartlipp, Paul

2017-12-01

Mixing at the ocean surface is key for atmosphere-ocean interactions and the distribution of heat, energy, and gases in the upper ocean. Winds are the primary force for surface mixing. To properly simulate upper ocean dynamics and the flux of these quantities within the upper ocean, models must reproduce mixing in the upper ocean. To evaluate the performance of the Regional Ocean Modeling System (ROMS) in replicating the surface mixing, the results of four different vertical mixing parameterizations were compared against observations, using the surface mixed layer depth, the temperature fields, and observed diffusivities for comparisons. The vertical mixing parameterizations investigated were Mellor- Yamada 2.5 level turbulent closure (MY), Large- McWilliams- Doney Kpp (LMD), Nakanishi- Niino (NN), and the generic length scale (GLS) schemes. This was done for one temperate site in deep water in the Eastern Pacific and three shallow water sites in the Baltic Sea. The model reproduced the surface mixed layer depth reasonably well for all sites; however, the temperature fields were reproduced well for the deep site, but not for the shallow Baltic Sea sites. In the Baltic Sea, the models overmixed the water column after a few days. Vertical temperature diffusivities were higher than those observed and did not show the temporal fluctuations present in the observations. The best performance was by NN and MY; however, MY became unstable in two of the shallow simulations with high winds. The performance of GLS nearly as good as NN and MY. LMD had the poorest performance as it generated temperature diffusivities that were too high and induced too much mixing. Further observational comparisons are needed to evaluate the effects of different stratification and wind conditions and the limitations on the vertical mixing parameterizations.

A New Global Regression Analysis Method for the Prediction of Wind Tunnel Model Weight Corrections

Science.gov (United States)

Ulbrich, Norbert Manfred; Bridge, Thomas M.; Amaya, Max A.

2014-01-01

A new global regression analysis method is discussed that predicts wind tunnel model weight corrections for strain-gage balance loads during a wind tunnel test. The method determines corrections by combining "wind-on" model attitude measurements with least squares estimates of the model weight and center of gravity coordinates that are obtained from "wind-off" data points. The method treats the least squares fit of the model weight separate from the fit of the center of gravity coordinates. Therefore, it performs two fits of "wind- off" data points and uses the least squares estimator of the model weight as an input for the fit of the center of gravity coordinates. Explicit equations for the least squares estimators of the weight and center of gravity coordinates are derived that simplify the implementation of the method in the data system software of a wind tunnel. In addition, recommendations for sets of "wind-off" data points are made that take typical model support system constraints into account. Explicit equations of the confidence intervals on the model weight and center of gravity coordinates and two different error analyses of the model weight prediction are also discussed in the appendices of the paper.

WIND SPEED AND ATMOSPHERIC STABILITY TRENDS FOR SELECTED UNITED STATES SURFACE STATIONS

Energy Technology Data Exchange (ETDEWEB)

Buckley, R; Allen H. Weber, A

2006-11-01

Recently it has been suggested that global warming and a decrease in mean wind speeds over most land masses are related. Decreases in near surface wind speeds have been reported by previous investigators looking at records with time spans of 15 to 30 years. This study focuses on United States (US) surface stations that have little or no location change since the late 1940s or the 1950s--a time range of up to 58 years. Data were selected from 62 stations (24 of which had not changed location) and separated into ten groups for analysis. The group's annual averages of temperature, wind speed, and percentage of Pasquill-Gifford (PG) stability categories were fitted with linear least squares regression lines. The results showed that the temperatures have increased for eight of the ten groups as expected. Wind speeds have decreased for nine of the ten groups. The mean slope of the wind speed trend lines for stations within the coterminous US was -0.77 m s{sup -1} per century. The percentage frequency of occurrence for the neutral (D) PG stability category decreased, while that for the unstable (B) and the stable (F) categories increased in almost all cases except for the group of stations located in Alaska.

Wind tunnel experiments on the effects of tillage ridge features on wind erosion horizontal fluxes

Directory of Open Access Journals (Sweden)

M. Kardous

2005-11-01

Full Text Available In addition to the well-known soil factors which control wind erosion on flat, unridged surfaces, two specific processes affect the susceptibility of tillage ridged surfaces to wind erosion: ridge-induced roughness and ridge- trapping efficiency.

In order to parameterize horizontal soil fluxes produced by wind over tillage ridges, eight-ridge configurations composed of sandy soil and exhibiting ridge heights to ridge spacing (RH/RS ratios ranging from 0.18 to 0.38 were experimented in a wind tunnel. These experiments are used to develop a parameterization of the horizontal fluxes over tillage ridged surfaces based only on the geometric characteristics of the ridges. Indeed, the key parameters controlling the horizontal flux, namely the friction velocity, threshold friction velocity and the adjustment coefficient, are derived through specific expressions, from ridge heights (RH and ridge spacing (RS. This parameterization was evaluated by comparing the results of the simulations to an additional experimental data set and to the data set obtained by Hagen and Armbrust (1992. In both cases, predicted and measured values are found to be in a satisfying agreement.

This parameterization was used to evaluate the efficiency of ridges in reducing wind erosion. The results show that ridged surfaces, when compared to a loose, unridged soil surface, lead to an important reduction in the horizontal fluxes (exceeding 60%. Moreover, the effect of ridges in trapping particles contributes for more than 90% in the flux reduction while the ridge roughness effect is weak and decreases when the wind velocity increases.

CONTROLLING INFLUENCE OF MAGNETIC FIELD ON SOLAR WIND OUTFLOW: AN INVESTIGATION USING CURRENT SHEET SOURCE SURFACE MODEL

Energy Technology Data Exchange (ETDEWEB)

Poduval, B., E-mail: bpoduval@spacescience.org [Space Science Institute, Boulder, CO 80303 (United States)

2016-08-10

This Letter presents the results of an investigation into the controlling influence of large-scale magnetic field of the Sun in determining the solar wind outflow using two magnetostatic coronal models: current sheet source surface (CSSS) and potential field source surface. For this, we made use of the Wang and Sheeley inverse correlation between magnetic flux expansion rate (FTE) and observed solar wind speed (SWS) at 1 au. During the period of study, extended over solar cycle 23 and beginning of solar cycle 24, we found that the coefficients of the fitted quadratic equation representing the FTE–SWS inverse relation exhibited significant temporal variation, implying the changing pattern of the influence of FTE on SWS over time. A particularly noteworthy feature is an anomaly in the behavior of the fitted coefficients during the extended minimum, 2008–2010 (CRs 2073–2092), which is considered due to the particularly complex nature of the solar magnetic field during this period. However, this variation was significant only for the CSSS model, though not a systematic dependence on the phase of the solar cycle. Further, we noticed that the CSSS model demonstrated better solar wind prediction during the period of study, which we attribute to the treatment of volume and sheet currents throughout the corona and the more accurate tracing of footpoint locations resulting from the geometry of the model.

Application of model predictive control for optimal operation of wind turbines

Science.gov (United States)

Yuan, Yuan; Cao, Pei; Tang, J.

2017-04-01

For large-scale wind turbines, reducing maintenance cost is a major challenge. Model predictive control (MPC) is a promising approach to deal with multiple conflicting objectives using the weighed sum approach. In this research, model predictive control method is applied to wind turbine to find an optimal balance between multiple objectives, such as the energy capture, loads on turbine components, and the pitch actuator usage. The actuator constraints are integrated into the objective function at the control design stage. The analysis is carried out in both the partial load region and full load region, and the performances are compared with those of a baseline gain scheduling PID controller. The application of this strategy achieves enhanced balance of component loads, the average power and actuator usages in partial load region.

[Fire behavior of ground surface fuels in Pinus koraiensis and Quercus mongolica mixed forest under no wind and zero slope condition: a prediction with extended Rothermel model].

Science.gov (United States)

Zhang, Ji-Li; Liu, Bo-Fei; Chu, Teng-Fei; Di, Xue-Ying; Jin, Sen

2012-06-01

A laboratory burning experiment was conducted to measure the fire spread speed, residual time, reaction intensity, fireline intensity, and flame length of the ground surface fuels collected from a Korean pine (Pinus koraiensis) and Mongolian oak (Quercus mongolica) mixed stand in Maoer Mountains of Northeast China under the conditions of no wind, zero slope, and different moisture content, load, and mixture ratio of the fuels. The results measured were compared with those predicted by the extended Rothermel model to test the performance of the model, especially for the effects of two different weighting methods on the fire behavior modeling of the mixed fuels. With the prediction of the model, the mean absolute errors of the fire spread speed and reaction intensity of the fuels were 0.04 m X min(-1) and 77 kW X m(-2), their mean relative errors were 16% and 22%, while the mean absolute errors of residual time, fireline intensity and flame length were 15.5 s, 17.3 kW X m(-1), and 9.7 cm, and their mean relative errors were 55.5%, 48.7%, and 24%, respectively, indicating that the predicted values of residual time, fireline intensity, and flame length were lower than the observed ones. These errors could be regarded as the lower limits for the application of the extended Rothermel model in predicting the fire behavior of similar fuel types, and provide valuable information for using the model to predict the fire behavior under the similar field conditions. As a whole, the two different weighting methods did not show significant difference in predicting the fire behavior of the mixed fuels by extended Rothermel model. When the proportion of Korean pine fuels was lower, the predicted values of spread speed and reaction intensity obtained by surface area weighting method and those of fireline intensity and flame length obtained by load weighting method were higher; when the proportion of Korean pine needles was higher, the contrary results were obtained.

Model Predictive Control of Wind Turbines

DEFF Research Database (Denmark)

Henriksen, Lars Christian

Wind turbines play a major role in the transformation from a fossil fuel based energy production to a more sustainable production of energy. Total-cost-of-ownership is an important parameter when investors decide in which energy technology they should place their capital. Modern wind turbines...... the need for maintenance of the wind turbine. Either way, better total-cost-of-ownership for wind turbine operators can be achieved by improved control of the wind turbines. Wind turbine control can be improved in two ways, by improving the model on which the controller bases its design or by improving...

Feature selection in wind speed prediction systems based on a hybrid coral reefs optimization – Extreme learning machine approach

International Nuclear Information System (INIS)

Salcedo-Sanz, S.; Pastor-Sánchez, A.; Prieto, L.; Blanco-Aguilera, A.; García-Herrera, R.

2014-01-01

Highlights: • A novel approach for short-term wind speed prediction is presented. • The system is formed by a coral reefs optimization algorithm and an extreme learning machine. • Feature selection is carried out with the CRO to improve the ELM performance. • The method is tested in real wind farm data in USA, for the period 2007–2008. - Abstract: This paper presents a novel approach for short-term wind speed prediction based on a Coral Reefs Optimization algorithm (CRO) and an Extreme Learning Machine (ELM), using meteorological predictive variables from a physical model (the Weather Research and Forecast model, WRF). The approach is based on a Feature Selection Problem (FSP) carried out with the CRO, that must obtain a reduced number of predictive variables out of the total available from the WRF. This set of features will be the input of an ELM, that finally provides the wind speed prediction. The CRO is a novel bio-inspired approach, based on the simulation of reef formation and coral reproduction, able to obtain excellent results in optimization problems. On the other hand, the ELM is a new paradigm in neural networks’ training, that provides a robust and extremely fast training of the network. Together, these algorithms are able to successfully solve this problem of feature selection in short-term wind speed prediction. Experiments in a real wind farm in the USA show the excellent performance of the CRO–ELM approach in this FSP wind speed prediction problem

Light reflection from a rough liquid surface including wind-wave effects in a scattering atmosphere

International Nuclear Information System (INIS)

Salinas, Santo V.; Liew, S.C.

2007-01-01

Visible and near-IR images of the ocean surface, taken from remote satellites, often contain important information of near-surface or sub-surface processes, which occur on, or over the ocean. Remote measurements of near surface winds, sea surface temperature and salinity, ocean color and underwater bathymetry, all, one way or another, depend on how well we understand sea surface roughness. However, in order to extract useful information from our remote measurements, we need to construct accurate models of the transfer of solar radiation inside the atmosphere as well as, its reflection from the sea surface. To approach this problem, we numerically solve the radiative transfer equation (RTE) by implementing a model for the atmosphere-ocean system. A one-dimensional atmospheric radiation model is solved via the widely known doubling and adding method and the ocean body is treated as a boundary condition to the problem. The ocean surface is modeled as a rough liquid surface which includes wind interaction and wave states, such as wave age. The model can have possible applications to the retrieval of wind and wave states, such as wave age, near a Sun glint region

Bayesian based Prognostic Model for Predictive Maintenance of Offshore Wind Farms

DEFF Research Database (Denmark)

Asgarpour, Masoud

2017-01-01

monitoring, fault detection and predictive maintenance of offshore wind components is defined. The diagnostic model defined in this paper is based on degradation, remaining useful lifetime and hybrid inspection threshold models. The defined degradation model is based on an exponential distribution......The operation and maintenance costs of offshore wind farms can be significantly reduced if existing corrective actions are performed as efficient as possible and if future corrective actions are avoided by performing sufficient preventive actions. In this paper a prognostic model for degradation...

The winds regime of surface in the Colombian coffee area

International Nuclear Information System (INIS)

Orlando Guzman Martinez; Lucia Gomez Gomez

1994-01-01

The characteristics of the address and gust of wind of the surface winds have been studied in 15 stations of the Colombian coffee area. It was found that the relief plays an important paper in the wind circulation so that during the day (7 a.m. - 7 p.m.) these they blow of the low sector toward the mountain and at night (7 p.m. - 7 a.m.) this situation is invested, that which is consistent with the characteristic pattern of circulation valley-mountain of the mountainous regions. For this fact, in most of the analyzed places a single day and night dominant address that it takes the orientation in that it is the respective hydrographic basin. It was not observed that the Alisios winds of the northeast and southeast modify the address settled down by the local circulation (valley-mountain) on the other hand a remarkable increase of the gust of wind was appreciated in July and August in the Florida and Ospina, stations located to the south of the country, as direct consequence of the Alisios of the southeast. The daily gust of wind in most of the studied places is low and it doesn't exceed of the 10 km/h, reason why it can consider that the Colombian coffee area is free of important damages for the action of the wind. Nevertheless, in some stations as Alban, Maracay and Paraguaicito the daily maximum gust of wind can surpass the 30 km/h and in occasions to cause damage mechanic to cultivations of high behavior and not well anchored facilities

Development of ANN Model for Wind Speed Prediction as a Support for Early Warning System

Directory of Open Access Journals (Sweden)

Ivan Marović

2017-01-01

Full Text Available The impact of natural disasters increases every year with more casualties and damage to property and the environment. Therefore, it is important to prevent consequences by implementation of the early warning system (EWS in order to announce the possibility of the harmful phenomena occurrence. In this paper, focus is placed on the implementation of the EWS on the micro location in order to announce possible harmful phenomena occurrence caused by wind. In order to predict such phenomena (wind speed, an artificial neural network (ANN prediction model is developed. The model is developed on the basis of the input data obtained by local meteorological station on the University of Rijeka campus area in the Republic of Croatia. The prediction model is validated and evaluated by visual and common calculation approaches, after which it was found that it is possible to perform very good wind speed prediction for time steps Δt=1 h, Δt=3 h, and Δt=8 h. The developed model is implemented in the EWS as a decision support for improvement of the existing “procedure plan in a case of the emergency caused by stormy wind or hurricane, snow and occurrence of the ice on the University of Rijeka campus.”

How Many Model Evaluations Are Required To Predict The AEP Of A Wind Power Plant?

DEFF Research Database (Denmark)

Murcia Leon, Juan Pablo; Réthoré, Pierre-Elouan; Natarajan, Anand

2015-01-01

(AEP) predictions expensive. The objective of the present paper is to minimize the number of model evaluations required to capture the wind power plant's AEP using stationary wind farm flow models. Polynomial chaos techniques are proposed based on arbitrary Weibull distributed wind speed and Von Misses...... distributed wind direction. The correlation between wind direction and wind speed are captured by defining Weibull-parameters as functions of wind direction. In order to evaluate the accuracy of these methods the expectation and variance of the wind farm power distributions are compared against...... the traditional binning method with trapezoidal and Simpson's integration rules. The wind farm flow model used in this study is the semi-empirical wake model developed by Larsen [1]. Three test cases are studied: a single turbine, a simple and a real offshore wind power plant. A reduced number of model...

Prediction of wind energy distribution in complex terrain using CFD

DEFF Research Database (Denmark)

Xu, Chang; Li, Chenqi; Yang, Jianchuan

2013-01-01

Based on linear models, WAsP software predicts wind energy distribution, with a good accuracy for flat terrain, but with a large error under complicated topography. In this paper, numerical simulations are carried out using the FLUENT software on a mesh generated by the GAMBIT and ARGIS software ...

Assessing Long-Term Wind Conditions by Combining Different Measure-Correlate-Predict Algorithms: Preprint

Energy Technology Data Exchange (ETDEWEB)

Zhang, J.; Chowdhury, S.; Messac, A.; Hodge, B. M.

2013-08-01

This paper significantly advances the hybrid measure-correlate-predict (MCP) methodology, enabling it to account for variations of both wind speed and direction. The advanced hybrid MCP method uses the recorded data of multiple reference stations to estimate the long-term wind condition at a target wind plant site. The results show that the accuracy of the hybrid MCP method is highly sensitive to the combination of the individual MCP algorithms and reference stations. It was also found that the best combination of MCP algorithms varies based on the length of the correlation period.

Model Predictive Control for Load Frequency Control with Wind Turbines

Directory of Open Access Journals (Sweden)

Yi Zhang

2015-01-01

Full Text Available Reliable load frequency (LFC control is crucial to the operation and design of modern electric power systems. Considering the LFC problem of a four-area interconnected power system with wind turbines, this paper presents a distributed model predictive control (DMPC based on coordination scheme. The proposed algorithm solves a series of local optimization problems to minimize a performance objective for each control area. The scheme incorporates the two critical nonlinear constraints, for example, the generation rate constraint (GRC and the valve limit, into convex optimization problems. Furthermore, the algorithm reduces the impact on the randomness and intermittence of wind turbine effectively. A performance comparison between the proposed controller with and that without the participation of the wind turbines is carried out. Good performance is obtained in the presence of power system nonlinearities due to the governors and turbines constraints and load change disturbances.

Wind power forecast error smoothing within a wind farm

International Nuclear Information System (INIS)

Saleck, Nadja; Bremen, Lueder von

2007-01-01

Smoothing of wind power forecast errors is well-known for large areas. Comparable effects within a wind farm are investigated in this paper. A Neural Network was taken to predict the power output of a wind farm in north-western Germany comprising 17 turbines. A comparison was done between an algorithm that fits mean wind and mean power data of the wind farm and a second algorithm that fits wind and power data individually for each turbine. The evaluation of root mean square errors (RMSE) shows that relative small smoothing effects occur. However, it can be shown for this wind farm that individual calculations have the advantage that only a few turbines are needed to give better results than the use of mean data. Furthermore different results occurred if predicted wind speeds are directly fitted to observed wind power or if predicted wind speeds are first fitted to observed wind speeds and then applied to a power curve. The first approach gives slightly better RMSE values, the bias improves considerably

Profiles of Wind and Turbulence in the Coastal Atmospheric Boundary Layer of Lake Erie

KAUST Repository

Wang, H

2014-06-16

Prediction of wind resource in coastal zones is difficult due to the complexity of flow in the coastal atmospheric boundary layer (CABL). A three week campaign was conducted over Lake Erie in May 2013 to investigate wind characteristics and improve model parameterizations in the CABL. Vertical profiles of wind speed up to 200 m were measured onshore and offshore by lidar wind profilers, and horizontal gradients of wind speed by a 3-D scanning lidar. Turbulence data were collected from sonic anemometers deployed onshore and offshore. Numerical simulations were conducted with the Weather Research Forecasting (WRF) model with 2 nested domains down to a resolution of 1-km over the lake. Initial data analyses presented in this paper investigate complex flow patterns across the coast. Acceleration was observed up to 200 m above the surface for flow coming from the land to the water. However, by 7 km off the coast the wind field had not yet reached equilibrium with the new surface (water) conditions. The surface turbulence parameters over the water derived from the sonic data could not predict wind profiles observed by the ZephlR lidar located offshore. Horizontal wind speed gradients near the coast show the influence of atmospheric stability on flow dynamics. Wind profiles retrieved from the 3-D scanning lidar show evidence of nocturnal low level jets (LLJs). The WRF model was able to capture the occurrence of LLJ events, but its performance varied in predicting their intensity, duration, and the location of the jet core.

Intelligent and robust prediction of short term wind power using genetic programming based ensemble of neural networks

International Nuclear Information System (INIS)

Zameer, Aneela; Arshad, Junaid; Khan, Asifullah; Raja, Muhammad Asif Zahoor

2017-01-01

Highlights: • Genetic programming based ensemble of neural networks is employed for short term wind power prediction. • Proposed predictor shows resilience against abrupt changes in weather. • Genetic programming evolves nonlinear mapping between meteorological measures and wind-power. • Proposed approach gives mathematical expressions of wind power to its independent variables. • Proposed model shows relatively accurate and steady wind-power prediction performance. - Abstract: The inherent instability of wind power production leads to critical problems for smooth power generation from wind turbines, which then requires an accurate forecast of wind power. In this study, an effective short term wind power prediction methodology is presented, which uses an intelligent ensemble regressor that comprises Artificial Neural Networks and Genetic Programming. In contrast to existing series based combination of wind power predictors, whereby the error or variation in the leading predictor is propagated down the stream to the next predictors, the proposed intelligent ensemble predictor avoids this shortcoming by introducing Genetical Programming based semi-stochastic combination of neural networks. It is observed that the decision of the individual base regressors may vary due to the frequent and inherent fluctuations in the atmospheric conditions and thus meteorological properties. The novelty of the reported work lies in creating ensemble to generate an intelligent, collective and robust decision space and thereby avoiding large errors due to the sensitivity of the individual wind predictors. The proposed ensemble based regressor, Genetic Programming based ensemble of Artificial Neural Networks, has been implemented and tested on data taken from five different wind farms located in Europe. Obtained numerical results of the proposed model in terms of various error measures are compared with the recent artificial intelligence based strategies to demonstrate the

Global surface wind and flux fields from model assimilation of Seasat data

Science.gov (United States)

Atlas, R.; Busalacchi, A. J.; Kalnay, E.; Bloom, S.; Ghil, M.

1986-01-01

Procedures for dealiasing Seasat data and developing global surface wind and latent and sensible heat flux fields are discussed. Seasat data from September 20, 1978 was dealiased using the Goddard Laboratory for Atmospheres (GLA) analysis/forecast system. The wind data obtained with the objective GLA forecast model are compared to the data subjectively dealiased by Peteherych et al. (1984) and Hoffman (1982, 1984). The GLA procedure is also verified using simulated Seasat data. The areas of high and low heat fluxes and cyclonic and anticyclonic wind stresses detected in the generated fields are analyzed and compared to climatological fields. It is observed that there is good correlation between the time-averaged analyses of wind stress obtained subjectively and objectively, and the monthly mean wind stress and latent fluxes agree with climatological fields and atmospheric and oceanic features.

Wind-Tunnel Investigations of Blunt-Body Drag Reduction Using Forebody Surface Roughness

Science.gov (United States)

Whitmore, Stephen A.; Sprague, Stephanie; Naughton, Jonathan W.; Curry, Robert E. (Technical Monitor)

2001-01-01

This paper presents results of wind-tunnel tests that demonstrate a novel drag reduction technique for blunt-based vehicles. For these tests, the forebody roughness of a blunt-based model was modified using micomachined surface overlays. As forebody roughness increases, boundary layer at the model aft thickens and reduces the shearing effect of external flow on the separated flow behind the base region, resulting in reduced base drag. For vehicle configurations with large base drag, existing data predict that a small increment in forebody friction drag will result in a relatively large decrease in base drag. If the added increment in forebody skin drag is optimized with respect to base drag, reducing the total drag of the configuration is possible. The wind-tunnel tests results conclusively demonstrate the existence of a forebody dragbase drag optimal point. The data demonstrate that the base drag coefficient corresponding to the drag minimum lies between 0.225 and 0.275, referenced to the base area. Most importantly, the data show a drag reduction of approximately 15% when the drag optimum is reached. When this drag reduction is scaled to the X-33 base area, drag savings approaching 45,000 N (10,000 lbf) can be realized.

Numerical Predictions of Wind Turbine Power and Aerodynamic Loads for the NREL Phase II and IV Combined Experiment Rotor

Science.gov (United States)

Duque, Earl P. N.; Johnson, Wayne; vanDam, C. P.; Chao, David D.; Cortes, Regina; Yee, Karen

1999-01-01

Accurate, reliable and robust numerical predictions of wind turbine rotor power remain a challenge to the wind energy industry. The literature reports various methods that compare predictions to experiments. The methods vary from Blade Element Momentum Theory (BEM), Vortex Lattice (VL), to variants of Reynolds-averaged Navier-Stokes (RaNS). The BEM and VL methods consistently show discrepancies in predicting rotor power at higher wind speeds mainly due to inadequacies with inboard stall and stall delay models. The RaNS methodologies show promise in predicting blade stall. However, inaccurate rotor vortex wake convection, boundary layer turbulence modeling and grid resolution has limited their accuracy. In addition, the inherently unsteady stalled flow conditions become computationally expensive for even the best endowed research labs. Although numerical power predictions have been compared to experiment. The availability of good wind turbine data sufficient for code validation experimental data that has been extracted from the IEA Annex XIV download site for the NREL Combined Experiment phase II and phase IV rotor. In addition, the comparisons will show data that has been further reduced into steady wind and zero yaw conditions suitable for comparisons to "steady wind" rotor power predictions. In summary, the paper will present and discuss the capabilities and limitations of the three numerical methods and make available a database of experimental data suitable to help other numerical methods practitioners validate their own work.

Transient power coefficients for a two-blade Savonius wind turbine

Energy Technology Data Exchange (ETDEWEB)

Pope, K.; Naterer, G. [Univ. of Ontario Inst. of Technology, Oshawa, ON (Canada). Faculty of Engineering and Applied Science

2010-07-01

The wind power industry had a 29 percent growth rate in installed capacity in 2008, and technological advances are helping to speed up growth by significantly increasing wind turbine power yields. While the majority of the industry's growth has come from large horizontal axis wind turbine installations, small wind turbines can also be used in a wide variety of applications. This study predicted the transient power coefficient for a Savonius vertical axis wind turbine (VAWT) wind turbine with 2 blades. The turbine's flow field was used to analyze pressure distribution along the rotor blades in relation to the momentum, lift, and drag forces on the rotor surfaces. The integral force balance was used to predict the transient torque and power output of the turbine. The study examined the implications of the addition of a second blade on the model's ability to predict transient power outputs. Computational fluid dynamics (CFD) programs were used to verify that the formulation can be used to accurately predict the transient power coefficients of VAWTs with Savonius blades. 11 refs., 1 tab., 6 figs.

Wind Speed Prediction Using a Univariate ARIMA Model and a Multivariate NARX Model

Directory of Open Access Journals (Sweden)

Erasmo Cadenas

2016-02-01

Full Text Available Two on step ahead wind speed forecasting models were compared. A univariate model was developed using a linear autoregressive integrated moving average (ARIMA. This method’s performance is well studied for a large number of prediction problems. The other is a multivariate model developed using a nonlinear autoregressive exogenous artificial neural network (NARX. This uses the variables: barometric pressure, air temperature, wind direction and solar radiation or relative humidity, as well as delayed wind speed. Both models were developed from two databases from two sites: an hourly average measurements database from La Mata, Oaxaca, Mexico, and a ten minute average measurements database from Metepec, Hidalgo, Mexico. The main objective was to compare the impact of the various meteorological variables on the performance of the multivariate model of wind speed prediction with respect to the high performance univariate linear model. The NARX model gave better results with improvements on the ARIMA model of between 5.5% and 10. 6% for the hourly database and of between 2.3% and 12.8% for the ten minute database for mean absolute error and mean squared error, respectively.

Predictive Surface Complexation Modeling

Energy Technology Data Exchange (ETDEWEB)

Sverjensky, Dimitri A. [Johns Hopkins Univ., Baltimore, MD (United States). Dept. of Earth and Planetary Sciences

2016-11-29

Surface complexation plays an important role in the equilibria and kinetics of processes controlling the compositions of soilwaters and groundwaters, the fate of contaminants in groundwaters, and the subsurface storage of CO₂ and nuclear waste. Over the last several decades, many dozens of individual experimental studies have addressed aspects of surface complexation that have contributed to an increased understanding of its role in natural systems. However, there has been no previous attempt to develop a model of surface complexation that can be used to link all the experimental studies in order to place them on a predictive basis. Overall, my research has successfully integrated the results of the work of many experimentalists published over several decades. For the first time in studies of the geochemistry of the mineral-water interface, a practical predictive capability for modeling has become available. The predictive correlations developed in my research now enable extrapolations of experimental studies to provide estimates of surface chemistry for systems not yet studied experimentally and for natural and anthropogenically perturbed systems.

Protection of surface assets on Mars from wind blown jettisoned spacecraft components

Science.gov (United States)

Paton, Mark

2017-07-01

Jettisoned Entry, Descent and Landing System (EDLS) hardware from landing spacecraft have been observed by orbiting spacecraft, strewn over the Martian surface. Future Mars missions that land spacecraft close to prelanded assets will have to use a landing architecture that somehow minimises the possibility of impacts from these jettisoned EDLS components. Computer modelling is used here to investigate the influence of wind speed and direction on the distribution of EDLS components on the surface. Typical wind speeds encountered in the Martian Planetary Boundary Layer (PBL) were found to be of sufficient strength to blow items having a low ballistic coefficient, i.e. Hypersonic Inflatable Aerodynamic Decelerators (HIADs) or parachutes, onto prelanded assets even when the lander itself touches down several kilometres away. Employing meteorological measurements and careful characterisation of the Martian PBL, e.g. appropriate wind speed probability density functions, may then benefit future spacecraft landings, increase safety and possibly help reduce the delta v budget for Mars landers that rely on aerodynamic decelerators.

A Collision Risk Model to Predict Avian Fatalities at Wind Facilities: An Example Using Golden Eagles, Aquila chrysaetos.

Science.gov (United States)

New, Leslie; Bjerre, Emily; Millsap, Brian; Otto, Mark C; Runge, Michael C

2015-01-01

Wind power is a major candidate in the search for clean, renewable energy. Beyond the technical and economic challenges of wind energy development are environmental issues that may restrict its growth. Avian fatalities due to collisions with rotating turbine blades are a leading concern and there is considerable uncertainty surrounding avian collision risk at wind facilities. This uncertainty is not reflected in many models currently used to predict the avian fatalities that would result from proposed wind developments. We introduce a method to predict fatalities at wind facilities, based on pre-construction monitoring. Our method can directly incorporate uncertainty into the estimates of avian fatalities and can be updated if information on the true number of fatalities becomes available from post-construction carcass monitoring. Our model considers only three parameters: hazardous footprint, bird exposure to turbines and collision probability. By using a Bayesian analytical framework we account for uncertainties in these values, which are then reflected in our predictions and can be reduced through subsequent data collection. The simplicity of our approach makes it accessible to ecologists concerned with the impact of wind development, as well as to managers, policy makers and industry interested in its implementation in real-world decision contexts. We demonstrate the utility of our method by predicting golden eagle (Aquila chrysaetos) fatalities at a wind installation in the United States. Using pre-construction data, we predicted 7.48 eagle fatalities year-1 (95% CI: (1.1, 19.81)). The U.S. Fish and Wildlife Service uses the 80th quantile (11.0 eagle fatalities year-1) in their permitting process to ensure there is only a 20% chance a wind facility exceeds the authorized fatalities. Once data were available from two-years of post-construction monitoring, we updated the fatality estimate to 4.8 eagle fatalities year-1 (95% CI: (1.76, 9.4); 80th quantile, 6

Wind directions predicted from global circulation models and wind directions determined from eolian sandstones of the western United States-A comparison

Science.gov (United States)

Parrish, Judith T.; Peterson, F.

1988-01-01

Wind directions for Middle Pennsylvanian through Jurassic time are predicted from global circulation models for the western United States. These predictions are compared with paleowind directions interpreted from eolian sandstones of Middle Pennsylvanian through Jurassic age. Predicted regional wind directions correspond with at least three-quarters of the paleowind data from the sandstones; the rest of the data may indicate problems with correlation, local effects of paleogeography on winds, and lack of resolution of the circulation models. The data and predictions suggest the following paleoclimatic developments through the time interval studied: predominance of winter subtropical high-pressure circulation in the Late Pennsylvanian; predominance of summer subtropical high-pressure circulation in the Permian; predominance of summer monsoonal circulation in the Triassic and earliest Jurassic; and, during the remainder of the Jurassic, influence of both summer subtropical and summer monsoonal circulation, with the boundary between the two systems over the western United States. This sequence of climatic changes is largely owing to paleogeographic changes, which influenced the buildup and breakdown of the monsoonal circulation, and possibly owing partly to a decrease in the global temperature gradient, which might have lessened the influence of the subtropical high-pressure circulation. The atypical humidity of Triassic time probably resulted from the monsoonal circulation created by the geography of Pangaea. This circulation is predicted to have been at a maximum in the Triassic and was likely to have been powerful enough to draw moisture along the equator from the ocean to the west. ?? 1988.

Predicting hurricane wind damage by claim payout based on Hurricane Ike in Texas

Directory of Open Access Journals (Sweden)

Ji-Myong Kim

2016-09-01

Full Text Available The increasing occurrence of natural disasters and their related damage have led to a growing demand for models that predict financial loss. Although considerable research on the financial losses related to natural disasters has found significant predictors, there has been a lack of comprehensive study that addresses the relationship among vulnerabilities, natural disasters, and the economic losses of individual buildings. This study identifies the vulnerability indicators for hurricanes to establish a metric to predict the related financial loss. We classify hurricane-prone areas by highlighting the spatial distribution of losses and vulnerabilities. This study used a Geographical Information System (GIS to combine and produce spatial data and a multiple regression method to establish a wind damage prediction model. As the dependent variable, we used the value of the Texas Windstorm Insurance Association (TWIA claim payout divided by the appraised values of the buildings to predict real economic loss. As independent variables, we selected a hurricane indicator and built environment vulnerability indicators. The model we developed can be used by government agencies and insurance companies to predict hurricane wind damage.

Wind climate from the regional climate model REMO

DEFF Research Database (Denmark)

Larsén, Xiaoli Guo; Mann, Jakob; Berg, Jacob

2010-01-01

Selected outputs from simulations with the regional climate model REMO from the Max Planck Institute, Hamburg, Germany were studied in connection with wind energy resource assessment. It was found that the mean wind characteristics based on observations from six mid-latitude stations are well...... described by the standard winds derived from the REMO pressure data. The mean wind parameters include the directional wind distribution, directional and omni-directional mean values and Weibull fitting parameters, spectral analysis and interannual variability of the standard winds. It was also found that......, on average, the wind characteristics from REMO are in better agreement with observations than those derived from the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) re-analysis pressure data. The spatial correlation of REMO surface winds in Europe...

Doppler lidar investigation of wind turbine wake characteristics and atmospheric turbulence under different surface roughness.

Science.gov (United States)

Zhai, Xiaochun; Wu, Songhua; Liu, Bingyi

2017-06-12

Four field experiments based on Pulsed Coherent Doppler Lidar with different surface roughness have been carried out in 2013-2015 to study the turbulent wind field in the vicinity of operating wind turbine in the onshore and offshore wind parks. The turbulence characteristics in ambient atmosphere and wake area was analyzed using transverse structure function based on Plane Position Indicator scanning mode. An automatic wake processing procedure was developed to determine the wake velocity deficit by considering the effect of ambient velocity disturbance and wake meandering with the mean wind direction. It is found that the turbine wake obviously enhances the atmospheric turbulence mixing, and the difference in the correlation of turbulence parameters under different surface roughness is significant. The dependence of wake parameters including the wake velocity deficit and wake length on wind velocity and turbulence intensity are analyzed and compared with other studies, which validates the empirical model and simulation of a turbine wake for various atmosphere conditions.

The tropical Atlantic surface wind divergence belt and its effect on clouds

OpenAIRE

Y. Tubul; I. Koren; O. Altaratz

2015-01-01

A well-defined surface wind divergence (SWD) belt with distinct cloud properties forms over the equatorial Atlantic during the boreal summer months. This belt separates the deep convective clouds of the intertropical convergence zone (ITCZ) from the shallow marine stratocumulus cloud decks forming over the cold-water subtropical region of the southern Hadley cell. Using the QuikSCAT-SeaWinds and Aqua-MODIS instruments, we examined the large-scale spatiotemporal ...

Observations of Martian surface winds at the Viking Lander 1 site

International Nuclear Information System (INIS)

Murphy, J.R.; Leovy, C.B.; Tillman, J.E.

1990-01-01

Partial failure of the wind instrumentation on the Viking Lander 1 (VL1) in the Martian subtropics (22.5 degree N) has limited previous analyses of meteorological data for this site. The authors describe a method for reconstructing surface winds using data from the partially failed sensor and present and analyze a time series of wind, pressure, and temperature at the site covering 350 Mars days (sols). At the beginning of the mission during early summer, winds were controlled by regional topography, but they soon underwent a transition to a regime controlled by the Hadley circulation. Diurnal and semidiurnal wind oscillations and synoptic variations have been analyzed and compared with the corresponding variations at the Viking Lander 2 middle latitude site (48 degree N). Diurnal wind oscillations were controlled primarily by regional topography and boundary layer forcing, although a global mode may have been influencing them during two brief episodes. Semidiurnal wind oscillations were controlled by the westward propagating semidiurnal tide from sol 210 onward. Comparison of the synoptic variations at the two sites suggests that the same eastward propagating wave trains were present at both sites, at least following the first 1977 great dust storm, but discordant inferred zonal wave numbers and phase speeds at the two sites cast doubt on the zonal wave numbers deduced from analyses of combined wind and pressure data, particularly at the VL1 site where the signal to noise ratio of the dominant synoptic waves is relatively small

Comparison of new hybrid FEEMD-MLP, FEEMD-ANFIS, Wavelet Packet-MLP and Wavelet Packet-ANFIS for wind speed predictions

International Nuclear Information System (INIS)

Liu, Hui; Tian, Hong-qi; Li, Yan-fei

2015-01-01

Highlights: • Four algorithms [EMD/FEEMD/WD/WPD] are proposed for the wind speed decomposition. • Two new hybrid forecasting algorithms [FEEMD-MLP/ANFIS] are presented. • The contributions of the FEEMD/WPD algorithms are both significant. • The MLP has better forecasting performance than the ANFIS in these cases. • All the proposed hybrid algorithms are suitable for the wind speed predictions. - Abstract: The technology of wind speed prediction is important to guarantee the safety of wind power utilization. Compared to the single algorithms, the hybrid ones always have better performance in the wind speed predictions. In this paper, three most important decomposing algorithms [Wavelet Decomposition – WD/Wavelet Packet Decomposition – WPD/Empirical Mode Decomposition – EMD] and a latest decomposing algorithm [Fast Ensemble Empirical Mode Decomposition – FEEMD] are all adopted to realize the wind speed high-precision predictions with two representative networks [MLP Neural Network/ANFIS Neural Network]. Based on the hybrid forecasting framework, two new wind speed forecasting methods [FEEMD-MLP and FEEMD-ANFIS] are proposed. Additionally, a series of performance comparison is provided, which includes EMD-MLP, FEEMD-MLP, EDM-ANFIS, FEEMD-ANFIS, WD-MLP, WD-ANFIS, WPD-MLP and WPD-ANFIS. The aim of the study is to investigate the decomposing and forecasting performance of the different hybrid models. Two experimental results show that: (1) Due to the inclusion of the decomposing algorithms, the hybrid ANN algorithms have better performance than their corresponding single ANN algorithms; (2) the proposed new FEEMD-MLP hybrid model has the best performance in the three-step predictions while the WPD-MLP hybrid model has the best performance in the one-step predictions; (3) among the decomposing algorithms, the FEEMD and WPD have better performance than the EMD and WD, respectively; (4) in the forecasting neural networks, the MLP has better performance

Health-aware Model Predictive Control of Wind Turbines using Fatigue Prognosis

DEFF Research Database (Denmark)

Sardi, Hector Eloy Sanchez; Escobet, Teressa; Puig, Vicenc

2015-01-01

management module with the control provides a mechanism for the wind turbine to operate safely and optimize the trade-off between components life and energy production. The research presented in this paper explores the integration of model predictive control (MPC) with fatigue-based prognosis approach...

Prediction of windings temperature rise in induction motors supplied with distorted voltage

Energy Technology Data Exchange (ETDEWEB)

Gnacinski, P. [Gdynia Maritime University, Department of Ship Electrical Power Engineering, Morska Street 83, 81-225 Gdynia (Poland)

2008-04-15

One of the features of ship power systems is a different level and intensity of disturbances appearing during routine operation - the rms voltage value and frequency deviation, voltage unbalance and waveform voltage distortion. As a result, marine induction machines are exposed to overheating due to the lowered voltage quality. This paper is devoted to windings temperature rise prediction in marine induction cage machines supplied with distorted voltage, which means real voltage conditions. The proposed method of prediction does not require detailed knowledge of the thermal properties of a machine. Although the method was developed for marine induction motors, it is applicable for industry machines supplied with distorted voltage. It can also be generalized and used for estimation of the steady state windings temperature rise of any electrical machinery in various work conditions. (author)

Prediction of windings temperature rise in induction motors supplied with distorted voltage

International Nuclear Information System (INIS)

Gnacinski, P.

2008-01-01

One of the features of ship power systems is a different level and intensity of disturbances appearing during routine operation - the rms voltage value and frequency deviation, voltage unbalance and waveform voltage distortion. As a result, marine induction machines are exposed to overheating due to the lowered voltage quality. This paper is devoted to windings temperature rise prediction in marine induction cage machines supplied with distorted voltage, which means real voltage conditions. The proposed method of prediction does not require detailed knowledge of the thermal properties of a machine. Although the method was developed for marine induction motors, it is applicable for industry machines supplied with distorted voltage. It can also be generalized and used for estimation of the steady state windings temperature rise of any electrical machinery in various work conditions

Final Report for Project: Impacts of stratification and non-equilibrium winds and waves on hub-height winds

Energy Technology Data Exchange (ETDEWEB)

Patton, Edward G. [Univ. Corporation for Atmospheric Research, Boulder, CO (United States)

2015-07-14

) primarily experienced weakly-unstable conditions, while stability at the ASIT tower (with a larger influence of offshore winds) experiences a mix of both unstable and stable conditions, where the summer months are predominantly stable. Wind-wave misalignment likely explains the large scatter in observed non-dimensional surface roughness under swell-dominated conditions. Andreas et al.’s (2012) relationship between u* and the 10-m wind speed under predicts the increased u* produced by wave-induced pressure drag produced by misaligned winds and waves. Incorporating wave-state (speed and direction) influences in parameterizations improves predictive skill. In a broad sense, these results suggest that one needs information on winds, temperature, and wave state to upscale buoy measurements to hub-height and across the rotor plane. Our parameterization of wave-state influences on surface drag has been submitted for inclusion in the next publicly available release. In combination, our project elucidates the impacts of two important physical processes (non-equilibrium wind/waves and stratification) on the atmosphere within which offshore turbines operate. This knowledge should help guide and inform manufacturers making critical decisions surrounding design criteria of future turbines to be deployed in the coastal zone. Reductions in annually averaged hub height wind speed error using our new wave-state-aware surface layer parameterization are relatively modest. However since wind turbine power production depends on the wind speed cubed, the error in estimated power production is close to 5%; which is significant and can substantially impact wind resource assessment and decision making with regards to the viability of particular location for a wind plant location. For a single 30-hour forecast, significant reductions in wind speed prediction errors can yield substantially improved wind power forecast skill, thereby mitigating costs and/or increasing revenue through improved

Initialization shock in decadal hindcasts due to errors in wind stress over the tropical Pacific

Science.gov (United States)

Pohlmann, Holger; Kröger, Jürgen; Greatbatch, Richard J.; Müller, Wolfgang A.

2017-10-01

Low prediction skill in the tropical Pacific is a common problem in decadal prediction systems, especially for lead years 2-5 which, in many systems, is lower than in uninitialized experiments. On the other hand, the tropical Pacific is of almost worldwide climate relevance through its teleconnections with other tropical and extratropical regions and also of importance for global mean temperature. Understanding the causes of the reduced prediction skill is thus of major interest for decadal climate predictions. We look into the problem of reduced prediction skill by analyzing the Max Planck Institute Earth System Model (MPI-ESM) decadal hindcasts for the fifth phase of the Climate Model Intercomparison Project and performing a sensitivity experiment in which hindcasts are initialized from a model run forced only by surface wind stress. In both systems, sea surface temperature variability in the tropical Pacific is successfully initialized, but most skill is lost at lead years 2-5. Utilizing the sensitivity experiment enables us to pin down the reason for the reduced prediction skill in MPI-ESM to errors in wind stress used for the initialization. A spurious trend in the wind stress forcing displaces the equatorial thermocline in MPI-ESM unrealistically. When the climate model is then switched into its forecast mode, the recovery process triggers artificial El Niño and La Niña events at the surface. Our results demonstrate the importance of realistic wind stress products for the initialization of decadal predictions.

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.

Pesticide volatilization from soil and plant surfaces: Measurements at different scales versus model predictions

Energy Technology Data Exchange (ETDEWEB)

Wolters, A.

2003-07-01

Simulation of pesticide volatilization from plant and soil surfaces as an integral component of pesticide fate models is of utmost importance, especially as part of the PEC (predicted environmental concentrations) models used in the registration procedures for pesticides. Experimentally determined volatilization rates at different scales were compared to model predictions to improve recent approaches included in European registration models. To assess the influence of crucial factors affecting volatilization under well-defined conditions, a laboratory chamber was set-up and validated. Aerodynamic conditions were adjusted to fulfill the requirements of the German guideline on assessing pesticide volatilization for registration purposes. At the semi-field scale, volatilization rates were determined in a wind-tunnel study after soil surface application of pesticides to gleyic cambisol. The following descending order of cumulative volatilization was observed: chlorpyrifos > parathion-methyl > terbuthylazine > fenpropimorph. Parameterization of the models PEARL (pesticide emission assessment at regional and local scales) and PELMO (pesticide leaching model) was performed to mirror the experimental boundary conditions. (orig.)

Effect of phase coupling on surface amplitude distribution of wind waves

Digital Repository Service at National Institute of Oceanography (India)

Varkey, M.J.

Nonlinear features of wind generated surface waves are considered here to be caused by nonrandomness (non-Uniform) in the phase spectrum. Nonrandomness in recorded waves, if present, would be generally obscured within the error level of observations...

Coupling a Mesoscale Numerical Weather Prediction Model with Large-Eddy Simulation for Realistic Wind Plant Aerodynamics Simulations (Poster)

Energy Technology Data Exchange (ETDEWEB)

Draxl, C.; Churchfield, M.; Mirocha, J.; Lee, S.; Lundquist, J.; Michalakes, J.; Moriarty, P.; Purkayastha, A.; Sprague, M.; Vanderwende, B.

2014-06-01

Wind plant aerodynamics are influenced by a combination of microscale and mesoscale phenomena. Incorporating mesoscale atmospheric forcing (e.g., diurnal cycles and frontal passages) into wind plant simulations can lead to a more accurate representation of microscale flows, aerodynamics, and wind turbine/plant performance. Our goal is to couple a numerical weather prediction model that can represent mesoscale flow [specifically the Weather Research and Forecasting model] with a microscale LES model (OpenFOAM) that can predict microscale turbulence and wake losses.

The tropical Atlantic surface wind divergence belt and its effect on clouds

OpenAIRE

Y. Tubul; I. Koren; O. Altaratz

2015-01-01

A well-defined surface wind divergence (SWD) belt with distinct cloud properties forms over the equatorial Atlantic during the boreal summer months. This belt separates the deep convective clouds of the Intertropical Convergence Zone (ITCZ) from the shallow marine stratocumulus cloud decks forming over the cold-water subtropical region of the southern branch of the Hadley cell in the Atlantic. Using the QuikSCAT-SeaWinds and Aqua-MODIS instruments, we examined the large-scal...

Deterministic and probabilistic interval prediction for short-term wind power generation based on variational mode decomposition and machine learning methods

International Nuclear Information System (INIS)

Zhang, Yachao; Liu, Kaipei; Qin, Liang; An, Xueli

2016-01-01

Highlights: • Variational mode decomposition is adopted to process original wind power series. • A novel combined model based on machine learning methods is established. • An improved differential evolution algorithm is proposed for weight adjustment. • Probabilistic interval prediction is performed by quantile regression averaging. - Abstract: Due to the increasingly significant energy crisis nowadays, the exploitation and utilization of new clean energy gains more and more attention. As an important category of renewable energy, wind power generation has become the most rapidly growing renewable energy in China. However, the intermittency and volatility of wind power has restricted the large-scale integration of wind turbines into power systems. High-precision wind power forecasting is an effective measure to alleviate the negative influence of wind power generation on the power systems. In this paper, a novel combined model is proposed to improve the prediction performance for the short-term wind power forecasting. Variational mode decomposition is firstly adopted to handle the instability of the raw wind power series, and the subseries can be reconstructed by measuring sample entropy of the decomposed modes. Then the base models can be established for each subseries respectively. On this basis, the combined model is developed based on the optimal virtual prediction scheme, the weight matrix of which is dynamically adjusted by a self-adaptive multi-strategy differential evolution algorithm. Besides, a probabilistic interval prediction model based on quantile regression averaging and variational mode decomposition-based hybrid models is presented to quantify the potential risks of the wind power series. The simulation results indicate that: (1) the normalized mean absolute errors of the proposed combined model from one-step to three-step forecasting are 4.34%, 6.49% and 7.76%, respectively, which are much lower than those of the base models and the hybrid

Surface Wind Gust Statistics at the Savannah River Site

International Nuclear Information System (INIS)

Weber, A.H.

2001-01-01

The Atmospheric Technologies Group (ATG) of the Savannah River Technology Center (SRTC) collects meteorological data for many purposes at the Savannah River Site (SRS) including weather forecasting. This study focuses on wind gusts and also, to a lesser degree, turbulence intensities that occur in fair weather conditions near the surface over time periods from 1 hour to one week (168 hours)

Combined Active and Reactive Power Control of Wind Farms based on Model Predictive Control

DEFF Research Database (Denmark)

Zhao, Haoran; Wu, Qiuwei; Wang, Jianhui

2017-01-01

This paper proposes a combined wind farm controller based on Model Predictive Control (MPC). Compared with the conventional decoupled active and reactive power control, the proposed control scheme considers the significant impact of active power on voltage variations due to the low X=R ratio...... of wind farm collector systems. The voltage control is improved. Besides, by coordination of active and reactive power, the Var capacity is optimized to prevent potential failures due to Var shortage, especially when the wind farm operates close to its full load. An analytical method is used to calculate...... the sensitivity coefficients to improve the computation efficiency and overcome the convergence problem. Two control modes are designed for both normal and emergency conditions. A wind farm with 20 wind turbines was used to verify the proposed combined control scheme....

Some challenges of wind modelling for modern wind turbines: The Weibull distribution

DEFF Research Database (Denmark)

Gryning, Sven-Erik; Batchvarova, Ekatarina; Floors, Rogier

2012-01-01

Wind power assessments, as well as forecast of wind energy production, are key issues in wind energy and grid related studies. However the hub height of today’s wind turbines is well above the surface layer. Wind profiles studies based on mast data show that the wind profile above the surface layer...

Observations and Predictability of Gap Winds in the Salmon River Canyon of Central Idaho, USA

Directory of Open Access Journals (Sweden)

Natalie S. Wagenbrenner

2018-01-01

Full Text Available This work investigates gap winds in a steep, deep river canyon prone to wildland fire. The driving mechanisms and the potential for forecasting the gap winds are investigated. The onset and strength of the gap winds are found to be correlated to the formation of an along-gap pressure gradient linked to periodic development of a thermal trough in the Pacific Northwest, USA. Numerical simulations are performed using a reanalysis dataset to investigate the ability of numerical weather prediction (NWP to simulate the observed gap wind events, including the timing and flow characteristics within the canyon. The effects of model horizontal grid spacing and terrain representation are considered. The reanalysis simulations suggest that horizontal grid spacings used in operational NWP could be sufficient for simulating the gap flow events given the regional-scale depression in which the Salmon River Canyon is situated. The strength of the events, however, is under-predicted due, at least in part, to terrain smoothing in the model. Routine NWP, however, is found to have mixed results in terms of forecasting the gap wind events, primarily due to problems in simulating the regional sea level pressure system correctly.

Predictive control of a chaotic permanent magnet synchronous generator in a wind turbine system

International Nuclear Information System (INIS)

Messadi, Manal; Mellit, Adel; Kemih, Karim; Ghanes, Malek

2015-01-01

This paper investigates how to address the chaos problem in a permanent magnet synchronous generator (PMSG) in a wind turbine system. Predictive control approach is proposed to suppress chaotic behavior and make operating stable; the advantage of this method is that it can only be applied to one state of the wind turbine system. The use of the genetic algorithms to estimate the optimal parameter values of the wind turbine leads to maximization of the power generation. Moreover, some simulation results are included to visualize the effectiveness and robustness of the proposed method. (paper)

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.

Local inertial oscillations in the surface ocean generated by time-varying winds

Science.gov (United States)

Chen, Shengli; Polton, Jeff A.; Hu, Jianyu; Xing, Jiuxing

2015-12-01

A new relationship is presented to give a review study on the evolution of inertial oscillations in the surface ocean locally generated by time-varying wind stress. The inertial oscillation is expressed as the superposition of a previous oscillation and a newly generated oscillation, which depends upon the time-varying wind stress. This relationship is employed to investigate some idealized wind change events. For a wind series varying temporally with different rates, the induced inertial oscillation is dominated by the wind with the greatest variation. The resonant wind, which rotates anti-cyclonically at the local inertial frequency with time, produces maximal amplitude of inertial oscillations, which grows monotonically. For the wind rotating at non-inertial frequencies, the responses vary periodically, with wind injecting inertial energy when it is in phase with the currents, but removing inertial energy when it is out of phase. The wind rotating anti-cyclonically with time is much more favorable to generate inertial oscillations than the cyclonic rotating wind. The wind with a frequency closer to the inertial frequency generates stronger inertial oscillations. For a diurnal wind, the induced inertial oscillation is dependent on latitude and is most significant at 30 °. This relationship is also applied to examine idealized moving cyclones. The inertial oscillation is much stronger on the right-hand side of the cyclone path than on the left-hand side (in the northern hemisphere). This is due to the wind being anti-cyclonic with time on the right-hand side, but cyclonic on the other side. The inertial oscillation varies with the cyclone translation speed. The optimal translation speed generating the greatest inertial oscillations is 2 m/s at the latitude of 10 ° and gradually increases to 6 m/s at the latitude of 30 °.

Near-Inertial Surface Currents and their influence on Surface Dispersion in the Northeastern Gulf of Mexico near the Deepwater Horizon Oil Spill

Science.gov (United States)

Gough, M.; Reniers, A.; MacMahan, J. H.; Howden, S. D.

2014-12-01

The continental shelf along the northeastern Gulf of Mexico is transected by the critical latitude (30°N) for inertial motions. At this latitude the inertial period is 24 hours and diurnal surface current oscillations can amplify due to resonance with diurnal wind and tidal forcing. Tidal amplitudes are relatively small in this region although K1 tidal currents can be strong over the shelf west of the DeSoto Canyon where the K1 tide propagates onshore as a Sverdrup wave. Other sources of diurnal motions include internal tidal currents, Poincaré waves, and basin resonance. It is therefore very difficult to separate inertial wind-driven motions from other diurnal motions. Spatiotemporal surface currents were measured using hourly 6 km resolution HF radar data collected in June 2010 during the Deepwater Horizon oil spill and July 2012 during the Grand Lagrangian Deployment (GLAD). Surface currents were also measured using GLAD GPS-tracked drifters. NDBC buoy wind data were used to determine wind-forcing, and OSU Tidal Inversion Software (OTIS) were used to predict tidal currents. The relative spatiotemporal influence of diurnal wind and tidal forcing on diurnal surface current oscillations is determined through a series of comparative analyses: phase and amplitude of bandpassed timeseries, wavelet analyses, wind-driven inertial oscillation calculations, and tidal current predictions. The wind-driven inertial ocean response is calculated by applying a simple "slab" model where wind-forcing is allowed to excite a layer of low-density water riding over high density water. The spatial variance of diurnal motions are found to be correlated with satellite turbidity imagery indicating that stratification influences the sea surface inertial response to wind-forcing. Surface dispersion is found to be minimized in regions of high diurnal variance suggesting that mean surface transport is restricted in regions of inertial motions associated with stratification.

Sea surface wind perturbations over the Kashevarov Bank of the Okhotsk Sea. A satellite study

Energy Technology Data Exchange (ETDEWEB)

Tarkhova, T.I.; Permyakov, M.S.; Potalova, E.Yu.; Semykin, V.I. [V.I. Il' ichev Pacific Oceanological Institute of the Far Eastern Branch of Russian Academy of Sciences, Vladivostok (Russian Federation). Lab. of the Ocean and Atmosphere Interaction Studies

2011-07-01

Sea surface wind perturbations over sea surface temperature (SST) cold anomalies over the Kashevarov Bank (KB) of the Okhotsk Sea are analyzed using satellite (AMSR-E and QuikSCAT) data during the summerautumn period of 2006-2009. It is shown, that frequency of cases of wind speed decreasing over a cold spot in August- September reaches up to 67%. In the cold spot center SST cold anomalies reached 10.5 C and wind speed lowered down to {proportional_to}7ms {sup -1} relative its value on the periphery. The wind difference between a periphery and a centre of the cold spot is proportional to SST difference with the correlations 0.5 for daily satellite passes data, 0.66 for 3-day mean data and 0.9 for monthly ones. For all types of data the coefficient of proportionality consists of {proportional_to}0.3 {sup -1} on 1 C. (orig.)

A study on the survey of wind energy resources for potential areas

Energy Technology Data Exchange (ETDEWEB)

Park, Kyung Ho; Kim, Keon Hoon; Yoo, Seung Won; Choi, Chang Joon; Ahn, Jung Jong [Korea Inst. of Energy Research, Taejon (Korea, Republic of)

1995-12-01

Among the wind energy utilization projects, the siting work for wind turbine installation is one of the most important procedure because the wind energy distribution is very different regionally and wind energy density influences greatly to the feasibility of wind energy utilization. So, the potential sites of wind generating in our country must be surveyed and analyzed the feasibility of wind energy utilization. In addition to this, the technique of wind energy prediction considered of the topography, surface roughness and obstacle condition must be established for the reliable analysis of wind energy utilization. The contents carried out in this project are shown below, 1. Determining of the measuring sites of wind data - Wyoulryung-ri, Youngrag-ri, Gapa-ri in Cheju Province - Heul-ri, Gangwon Province. 2. Analysis of wind energy at measuring sites The characteristics of wind energy at the measured sites were analysed. It will be continued to measure the wind data by wind data logger. 3. A study on wind energy prediction technique It was studied how to obtain the topographic map data for using WAsP(WIndAtlas Analysis and Application Program). (author). 21 refs., 59 figs., 19 tabs.

Predicting Ionization Rates from SEP and Solar Wind Proton Precipitation into the Martian Atmosphere

Science.gov (United States)

Jolitz, R.; Dong, C.; Lee, C. O.; Curry, S.; Lillis, R. J.; Brain, D.; Halekas, J. S.; Larson, D. E.; Bougher, S. W.; Jakosky, B. M.

2017-12-01

Precipitating energetic particles ionize planetary atmospheres and increase total electron content. At Mars, the solar wind and solar energetic particles (SEPs) can precipitate directly into the atmosphere because solar wind protons can charge exchange to become neutrals and pass through the magnetosheath, while SEPs are sufficiently energetic to cross the magnetosheath unchanged. In this study we will present predicted ionization rates and resulting electron densities produced by solar wind and SEP proton ionization during nominal solar activity and a CME shock front impact event on May 16 2016. We will use the Atmospheric Scattering of Protons and Energetic Neutrals (ASPEN) model to compare ionization by SEP and solar wind protons currently measured by the SWIA (Solar Wind Ion Analyzer) and SEP instruments aboard the MAVEN spacecraft. Results will help to quantify how the ionosphere responds to extreme solar events during solar minimum.

A prediction model for wind speed ratios at pedestrian level with simplified urban canopies

Science.gov (United States)

Ikegaya, N.; Ikeda, Y.; Hagishima, A.; Razak, A. A.; Tanimoto, J.

2017-02-01

The purpose of this study is to review and improve prediction models for wind speed ratios at pedestrian level with simplified urban canopies. We adopted an extensive database of velocity fields under various conditions for arrays consisting of cubes, slender or flattened rectangles, and rectangles with varying roughness heights. Conclusions are summarized as follows: first, a new geometric parameter is introduced as a function of the plan area index and the aspect ratio so as to express the increase in virtual density that causes wind speed reduction. Second, the estimated wind speed ratios in the range 0.05 coefficients between the wind speeds averaged over the entire region, and the front or side region values are larger than 0.8. In contrast, in areas where the influence of roughness elements is significant, such as behind a building, the wind speeds are weakly correlated.

Torsional Performance of Wind Turbine Blades

DEFF Research Database (Denmark)

Branner, Kim; Berring, Peter; Berggreen, Christian

2007-01-01

The present work investigates how well different finite element modeling techniques can predict bending and torsion behavior of a wind turbine blade. Two shell models are investigated. One model has element offsets and the other has the elements at the mid-thickness surfaces of the model. The las...

How Many Model Evaluations Are Required To Predict The AEP Of A Wind Power Plant?

International Nuclear Information System (INIS)

Murcia, J P; Réthoré, P E; Natarajan, A; Sørensen, J D

2015-01-01

Wind farm flow models have advanced considerably with the use of large eddy simulations (LES) and Reynolds averaged Navier-Stokes (RANS) computations. The main limitation of these techniques is their high computational time requirements; which makes their use for wind farm annual energy production (AEP) predictions expensive. The objective of the present paper is to minimize the number of model evaluations required to capture the wind power plant's AEP using stationary wind farm flow models. Polynomial chaos techniques are proposed based on arbitrary Weibull distributed wind speed and Von Misses distributed wind direction. The correlation between wind direction and wind speed are captured by defining Weibull-parameters as functions of wind direction. In order to evaluate the accuracy of these methods the expectation and variance of the wind farm power distributions are compared against the traditional binning method with trapezoidal and Simpson's integration rules.The wind farm flow model used in this study is the semi-empirical wake model developed by Larsen [1]. Three test cases are studied: a single turbine, a simple and a real offshore wind power plant. A reduced number of model evaluations for a general wind power plant is proposed based on the convergence of the present method for each case. (paper)

Charnock's Roughness Length Model and Non-dimensional Wind Profiles Over the Sea

DEFF Research Database (Denmark)

Pena Diaz, Alfredo; Gryning, Sven-Erik

2008-01-01

An analysis tool for the study of wind speed profiles over the water has been developed. The profiles are analysed using a modified dimensionless wind speed and dimensionless height, assuming that the sea surface roughness can be predicted by Charnock's roughness length model. In this form, the r...

A probability index for surface zonda wind occurrence at Mendoza city through vertical sounding principal components analysis

Science.gov (United States)

Otero, Federico; Norte, Federico; Araneo, Diego

2018-01-01

The aim of this work is to obtain an index for predicting the probability of occurrence of zonda event at surface level from sounding data at Mendoza city, Argentine. To accomplish this goal, surface zonda wind events were previously found with an objective classification method (OCM) only considering the surface station values. Once obtained the dates and the onset time of each event, the prior closest sounding for each event was taken to realize a principal component analysis (PCA) that is used to identify the leading patterns of the vertical structure of the atmosphere previously to a zonda wind event. These components were used to construct the index model. For the PCA an entry matrix of temperature ( T) and dew point temperature (Td) anomalies for the standard levels between 850 and 300 hPa was build. The analysis yielded six significant components with a 94 % of the variance explained and the leading patterns of favorable weather conditions for the development of the phenomenon were obtained. A zonda/non-zonda indicator c can be estimated by a logistic multiple regressions depending on the PCA component loadings, determining a zonda probability index \\widehat{c} calculable from T and Td profiles and it depends on the climatological features of the region. The index showed 74.7 % efficiency. The same analysis was performed by adding surface values of T and Td from Mendoza Aero station increasing the index efficiency to 87.8 %. The results revealed four significantly correlated PCs with a major improvement in differentiating zonda cases and a reducing of the uncertainty interval.

OffWindSolver: Wind farm design tool based on actuator line/actuator disk concept in OpenFoam architecture

Directory of Open Access Journals (Sweden)

Panjwani Balram

2014-01-01

Full Text Available Wind energy is a good alternative to meet the energy requirements in some parts of the world; however the efficiency of wind farm depends on the optimized location of the wind turbines. Therefore a software tool that is capable of predicting the in-situ performance of multiple turbine installations in different operating conditions with reliable accuracy is needed. In present study wind farm layout design tool OffWindSolver is developed within the OpenFoam architecture. Unsteady PisoFoam solver is extended to account for wind turbines, where each turbine is modeled as a sink term in the momentum equation. Turbine modeling is based on actuator line concepts derived from SOWFA code, where each blade of the turbine is represented as a line. The loading on each line/blade of the turbine is estimated using the Blade Element Method (BEM. The inputs for the solver are tabulated airfoil aerodynamic data, dimension and height of the wind turbines, wind magnitude and direction. OffWindSolver is validated for a real wind farm – Lillgrund offshore facility in Sweden/Denmark operated by Vattenfall Vindkraft AB. Because of the scale of the computation, we only examine the effect of wind from one direction at one speed. In the absence of time dependent Marine Atmospheric Boundary Layer (MABL, a log wind profile with surface roughness of 0.04 is used at the inlet. The simulated power production of each turbine is compared to the field data and large-eddy simulation. The overall power of the wind farm is well predicted. The simulation shows the significant decreases of the power for those turbines that were in the wake.

Wind Structure and Wind Loading

DEFF Research Database (Denmark)

Brorsen, Michael

The purpose of this note is to provide a short description of wind, i.e. of the flow in the atmosphere of the Earth and the loading caused by wind on structures. The description comprises: causes to the generation of windhe interaction between wind and the surface of the Earthhe stochastic nature...

Wind erosion in semiarid landscapes: Predictive models and remote sensing methods for the influence of vegetation

Science.gov (United States)

Musick, H. Brad

1993-01-01

The objectives of this research are: to develop and test predictive relations for the quantitative influence of vegetation canopy structure on wind erosion of semiarid rangeland soils, and to develop remote sensing methods for measuring the canopy structural parameters that determine sheltering against wind erosion. The influence of canopy structure on wind erosion will be investigated by means of wind-tunnel and field experiments using structural variables identified by the wind-tunnel and field experiments using model roughness elements to simulate plant canopies. The canopy structural variables identified by the wind-tunnel and field experiments as important in determining vegetative sheltering against wind erosion will then be measured at a number of naturally vegetated field sites and compared with estimates of these variables derived from analysis of remotely sensed data.

Mapping near-surface air temperature, pressure, relative humidity and wind speed over Mainland China with high spatiotemporal resolution

Science.gov (United States)

Li, Tao; Zheng, Xiaogu; Dai, Yongjiu; Yang, Chi; Chen, Zhuoqi; Zhang, Shupeng; Wu, Guocan; Wang, Zhonglei; Huang, Chengcheng; Shen, Yan; Liao, Rongwei

2014-09-01

As part of a joint effort to construct an atmospheric forcing dataset for mainland China with high spatiotemporal resolution, a new approach is proposed to construct gridded near-surface temperature, relative humidity, wind speed and surface pressure with a resolution of 1 km×1 km. The approach comprises two steps: (1) fit a partial thin-plate smoothing spline with orography and reanalysis data as explanatory variables to ground-based observations for estimating a trend surface; (2) apply a simple kriging procedure to the residual for trend surface correction. The proposed approach is applied to observations collected at approximately 700 stations over mainland China. The generated forcing fields are compared with the corresponding components of the National Centers for Environmental Prediction (NCEP) Climate Forecast System Reanalysis dataset and the Princeton meteorological forcing dataset. The comparison shows that, both within the station network and within the resolutions of the two gridded datasets, the interpolation errors of the proposed approach are markedly smaller than the two gridded datasets.

Predictions of local ground geomagnetic field fluctuations during the 7-10 November 2004 events studied with solar wind driven models

Directory of Open Access Journals (Sweden)

P. Wintoft

2005-11-01

Full Text Available The 7-10 November 2004 period contains two events for which the local ground magnetic field was severely disturbed and simultaneously, the solar wind displayed several shocks and negative Bz periods. Using empirical models the 10-min RMS and at Brorfelde (BFE, 11.67° E, 55.63° N, Denmark, are predicted. The models are recurrent neural networks with 10-min solar wind plasma and magnetic field data as inputs. The predictions show a good agreement during 7 November, up until around noon on 8 November, after which the predictions become significantly poorer. The correlations between observed and predicted log RMS is 0.77 during 7-8 November but drops to 0.38 during 9-10 November. For RMS the correlations for the two periods are 0.71 and 0.41, respectively. Studying the solar wind data for other L1-spacecraft (WIND and SOHO it seems that the ACE data have a better agreement to the near-Earth solar wind during the first two days as compared to the last two days. Thus, the accuracy of the predictions depends on the location of the spacecraft and the solar wind flow direction. Another finding, for the events studied here, is that the and models showed a very different dependence on Bz. The model is almost independent of the solar wind magnetic field Bz, except at times when Bz is exceptionally large or when the overall activity is low. On the contrary, the model shows a strong dependence on Bz at all times.

Sea surface wind perturbations over the Kashevarov Bank of the Okhotsk Sea: a satellite study

Directory of Open Access Journals (Sweden)

T. I. Tarkhova

2011-02-01

Full Text Available Sea surface wind perturbations over sea surface temperature (SST cold anomalies over the Kashevarov Bank (KB of the Okhotsk Sea are analyzed using satellite (AMSR-E and QuikSCAT data during the summer-autumn period of 2006–2009. It is shown, that frequency of cases of wind speed decreasing over a cold spot in August–September reaches up to 67%. In the cold spot center SST cold anomalies reached 10.5 °C and wind speed lowered down to ~7 m s−1 relative its value on the periphery. The wind difference between a periphery and a centre of the cold spot is proportional to SST difference with the correlations 0.5 for daily satellite passes data, 0.66 for 3-day mean data and 0.9 for monthly ones. For all types of data the coefficient of proportionality consists of ~0.3 m s−1 on 1 °C.

A preliminary evaluation of short-term thunderstorm forecasting using surface winds at Kennedy Space Center

Science.gov (United States)

Watson, Andrew I.; Holle, Ronald L.; Lopez, Raul E.; Nicholson, James R.

1990-01-01

In 1987 NASA expanded its surface wind network onto the mainland west of Kennedy Space Center, increasing the network area from nearly 800 sq km to over 1600 sq km. Here, the results of this expansion are reported using three years of wind and lightning information collected during June, July, August, and September of 1987, 1988, and 1989. The divergence-lightning relationships and the importance of wind direction are addressed, and the verification is summarized.

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

Potential climatic impacts and reliability of large-scale offshore wind farms

International Nuclear Information System (INIS)

Wang Chien; Prinn, Ronald G

2011-01-01

The vast availability of wind power has fueled substantial interest in this renewable energy source as a potential near-zero greenhouse gas emission technology for meeting future world energy needs while addressing the climate change issue. However, in order to provide even a fraction of the estimated future energy needs, a large-scale deployment of wind turbines (several million) is required. The consequent environmental impacts, and the inherent reliability of such a large-scale usage of intermittent wind power would have to be carefully assessed, in addition to the need to lower the high current unit wind power costs. Our previous study (Wang and Prinn 2010 Atmos. Chem. Phys. 10 2053) using a three-dimensional climate model suggested that a large deployment of wind turbines over land to meet about 10% of predicted world energy needs in 2100 could lead to a significant temperature increase in the lower atmosphere over the installed regions. A global-scale perturbation to the general circulation patterns as well as to the cloud and precipitation distribution was also predicted. In the later study reported here, we conducted a set of six additional model simulations using an improved climate model to further address the potential environmental and intermittency issues of large-scale deployment of offshore wind turbines for differing installation areas and spatial densities. In contrast to the previous land installation results, the offshore wind turbine installations are found to cause a surface cooling over the installed offshore regions. This cooling is due principally to the enhanced latent heat flux from the sea surface to lower atmosphere, driven by an increase in turbulent mixing caused by the wind turbines which was not entirely offset by the concurrent reduction of mean wind kinetic energy. We found that the perturbation of the large-scale deployment of offshore wind turbines to the global climate is relatively small compared to the case of land

Fatigue life prediction and strength degradation of wind turbine rotor blade composites

NARCIS (Netherlands)

Nijssen, R.P.L.

2006-01-01

Wind turbine rotor blades are subjected to a large number of highly variable loads, but life predictions are typically based on constant amplitude fatigue behaviour. Therefore, it is important to determine how service life under variable amplitude fatigue can be estimated from constant amplitude

Doppler Navigation System with a Non-Stabilized Antenna as a Sea-Surface Wind Sensor.

Science.gov (United States)

Nekrasov, Alexey; Khachaturian, Alena; Veremyev, Vladimir; Bogachev, Mikhail

2017-06-09

We propose a concept of the utilization of an aircraft Doppler Navigation System (DNS) as a sea-surface wind sensor complementary to its normal functionality. The DNS with an antenna, which is non-stabilized physically to the local horizontal with x -configured beams, is considered. We consider the wind measurements by the DNS configured in the multi-beam scatterometer mode for a rectilinear flight scenario. The system feasibility and the efficiency of the proposed wind algorithm retrieval are supported by computer simulations. Finally, the associated limitations of the proposed approach are considered.

A tall tower study of Missouri winds

Energy Technology Data Exchange (ETDEWEB)

Fox, Neil I. [Department of Soil, Environmental and Atmospheric Sciences, 332 ABNR Building, University of Missouri, Columbia, MO 65211 (United States)

2011-01-15

This paper summarizes the results of a study of wind speeds observed at heights up to 150 m above ground level around Missouri. This is an amalgamation of four projects that allowed a total of eleven tall communication towers to be instrumented with wind observation equipment across the State of Missouri. This provided an assessment of the wind resource and the characteristics of the seasonal and diurnal cycles of wind in different areas of Missouri at the heights of utility scale wind turbines. Comparisons were also made to wind speeds predicted at these levels from a previously published wind map. The main finding was that the observed winds at each tower were smaller than those presented in the wind map. The discrepancy is most likely to be due to underestimation of the surface roughness and turbulence leading to an overestimation of near-surface wind shear. However, the wind shear, as expressed by the shear parameter was consistently greater than the 'standard' value of 1.4. The reconciliation of these two apparently contradictory findings is that the shear varies with the height at which it is measured. In wind resource assessment, wind shear is usually observed below 50 m and is tacitly assumed to be constant with height when used to extrapolate winds to higher levels. The author advocates the use of the friction velocity as a measure of shear in wind power applications in preference to the shear parameter that is usually used. This is because the shear parameter has a velocity bias that can also manifest as a bias with height or season. As wind power resource assessment is starting to use taller towers than the standard 50 m, intercomparison of site resources and extrapolation to turbine heights can be compromised if the shear parameter is used. (author)

Predictive control strategies for wind turbine system based on permanent magnet synchronous generator.

Science.gov (United States)

Maaoui-Ben Hassine, Ikram; Naouar, Mohamed Wissem; Mrabet-Bellaaj, Najiba

2016-05-01

In this paper, Model Predictive Control and Dead-beat predictive control strategies are proposed for the control of a PMSG based wind energy system. The proposed MPC considers the model of the converter-based system to forecast the possible future behavior of the controlled variables. It allows selecting the voltage vector to be applied that leads to a minimum error by minimizing a predefined cost function. The main features of the MPC are low current THD and robustness against parameters variations. The Dead-beat predictive control is based on the system model to compute the optimum voltage vector that ensures zero-steady state error. The optimum voltage vector is then applied through Space Vector Modulation (SVM) technique. The main advantages of the Dead-beat predictive control are low current THD and constant switching frequency. The proposed control techniques are presented and detailed for the control of back-to-back converter in a wind turbine system based on PMSG. Simulation results (under Matlab-Simulink software environment tool) and experimental results (under developed prototyping platform) are presented in order to show the performances of the considered control strategies. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Dynamic Loads and Wake Prediction for Large Wind Turbines Based on Free Wake Method

Institute of Scientific and Technical Information of China (English)

Cao Jiufa; Wang Tongguang; Long Hui; Ke Shitang; Xu Bofeng

2015-01-01

With large scale wind turbines ,the issue of aerodynamic elastic response is even more significant on dy-namic behaviour of the system .Unsteady free vortex wake method is proposed to calculate the shape of wake and aerodynamic load .Considering the effect of aerodynamic load ,inertial load and gravity load ,the decoupling dy-namic equations are established by using finite element method in conjunction of the modal method and equations are solved numerically by Newmark approach .Finally ,the numerical simulation of a large scale wind turbine is performed through coupling the free vortex wake modelling with structural modelling .The results show that this coupling model can predict the flexible wind turbine dynamic characteristics effectively and efficiently .Under the influence of the gravitational force ,the dynamic response of flapwise direction contributes to the dynamic behavior of edgewise direction under the operational condition of steady wind speed .The difference in dynamic response be-tween the flexible and rigid wind turbines manifests when the aerodynamics/structure coupling effect is of signifi-cance in both wind turbine design and performance calculation .

The new generation of tools for prediction of wind power potential and site selection

DEFF Research Database (Denmark)

Lundtang Petersen, Erik

2012-01-01

, from insufficient input data to deficient physics and resolution in any of the models, model linking issues, insufficient resolution or errors in surface topographical data such as terrain heights, land cover data etc. Therefore it has been decided on a European Union level to launch a project “The New...... European Wind Atlas” aiming at reducing overall uncertainties in determining wind conditions; standing on three legs: A data bank from a series of intensive measuring campaigns; a thorough examination and redesign of the model chain from global, mesoscale to microscale models and the creation of the wind...

An Experimental and Theoretical Investigation of Micropiiting in Wind Turbine Gears and Bearings

Energy Technology Data Exchange (ETDEWEB)

Kahraman, Ahmet

2012-03-28

In this research study, the micro-pitting related contact failures of wind turbine gearbox components were investigated both experimentally and theoretically. On the experimental side, a twin-disk type test machine was used to simulate wind turbine transmission contacts in terms of their kinematic (rolling and sliding speeds), surface roughnesses, material parameters and lubricant conditions. A test matrix that represents the ranges of contact conditions of the wind turbine gear boxes was defined and executed to bring an empirical understanding to the micro-pitting problem in terms of key contact parameters and operating conditions. On the theoretical side, the first deterministic micro-pitting model based on a mixed elastohydrodynamic lubrication formulations and multi-axial near-surface crack initiation model was developed. This physics-based model includes actual instantaneous asperity contacts associated with real surface roughness profiles for predicting the onset of the micro-pit formation. The predictions from the theoretical model were compared to the experimental data for validation of the models. The close agreement between the model and measurements was demonstrated. With this, the proposed model can be deemed suitable for identifying the mechanisms leading to micro-pitting of gear and bearing surfaces of wind turbine gear boxes, including all key material, lubricant and surface engineering aspects of the problem, and providing solutions to these micro-pitting problems.

Predictive control of a chaotic permanent magnet synchronous generator in a wind turbine system

Science.gov (United States)

Manal, Messadi; Adel, Mellit; Karim, Kemih; Malek, Ghanes

2015-01-01

This paper investigates how to address the chaos problem in a permanent magnet synchronous generator (PMSG) in a wind turbine system. Predictive control approach is proposed to suppress chaotic behavior and make operating stable; the advantage of this method is that it can only be applied to one state of the wind turbine system. The use of the genetic algorithms to estimate the optimal parameter values of the wind turbine leads to maximization of the power generation. Moreover, some simulation results are included to visualize the effectiveness and robustness of the proposed method. Project supported by the CMEP-TASSILI Project (Grant No. 14MDU920).

Estimated solar wind-implanted helium-3 distribution on the Moon

Science.gov (United States)

Johnson, J. R.; Swindle, T.D.; Lucey, P.G.

1999-01-01

Among the solar wind-implanted volatiles present in the lunar regolith, 3 He is possibly the most valuable resource because of its potential as a fusion fuel. The abundance of 3 He in the lunar regolith at a given location depends on surface maturity, the amount of solar wind fluence, and titanium content, because ilmenite (FeTiO3) retains helium much better than other major lunar minerals. Surface maturity and TiO2 maps from Clementine multispectral data sets are combined here with a solar wind fluence model to produce a 3He abundance map of the Moon. Comparison of the predicted 3He values to landing site observations shows good correlation. The highest 3He abundances occur in the farside maria (due to greater solar wind fluence received) and in higher TiO2 nearside mare regions.

Model predictive control for wind power gradients

DEFF Research Database (Denmark)

Hovgaard, Tobias Gybel; Boyd, Stephen; Jørgensen, John Bagterp

2015-01-01

We consider the operation of a wind turbine and a connected local battery or other electrical storage device, taking into account varying wind speed, with the goal of maximizing the total energy generated while respecting limits on the time derivative (gradient) of power delivered to the grid. We...... ranges. The system dynamics are quite non-linear, and the constraints and objectives are not convex functions of the control inputs, so the resulting optimal control problem is difficult to solve globally. In this paper, we show that by a novel change of variables, which focuses on power flows, we can...... wind data and modern wind forecasting methods. The simulation results using real wind data demonstrate the ability to reject the disturbances from fast changes in wind speed, ensuring certain power gradients, with an insignificant loss in energy production....

Computer modelling of the UK wind energy resource: UK wind speed data package and user manual

Energy Technology Data Exchange (ETDEWEB)

Burch, S F; Ravenscroft, F

1993-12-31

A software package has been developed for IBM-PC or true compatibles. It is designed to provide easy access to the results of a programme of work to estimate the UK wind energy resource. Mean wind speed maps and quantitative resource estimates were obtained using the NOABL mesoscale (1 km resolution) numerical model for the prediction of wind flow over complex terrain. NOABL was used in conjunction with digitised terrain data and wind data from surface meteorological stations for a ten year period (1975-1984) to provide digital UK maps of mean wind speed at 10m, 25m and 45m above ground level. Also included in the derivation of these maps was the use of the Engineering Science Data Unit (ESDU) method to model the effect on wind speed of the abrupt change in surface roughness that occurs at the coast. With the wind speed software package, the user is able to obtain a display of the modelled wind speed at 10m, 25m and 45m above ground level for any location in the UK. The required co-ordinates are simply supplied by the user, and the package displays the selected wind speed. This user manual summarises the methodology used in the generation of these UK maps and shows computer generated plots of the 25m wind speeds in 200 x 200 km regions covering the whole UK. The uncertainties inherent in the derivation of these maps are also described, and notes given on their practical usage. The present study indicated that 23% of the UK land area had speeds over 6 m/s, with many hill sites having 10m speeds over 10 m/s. It is concluded that these `first order` resource estimates represent a substantial improvement over the presently available `zero order` estimates. (18 figures, 3 tables, 6 references). (author)

Modeling and control design of a stand alone wind energy conversion system based on functional model predictive control

Energy Technology Data Exchange (ETDEWEB)

Kassem, Ahmed M. [Beni-Suef University, Electrical Dept., Beni Suef (Egypt)

2012-09-15

This paper investigates the application of the model predictive control (MPC) approach to control the voltage and frequency of a stand alone wind generation system. This scheme consists of a wind turbine which drives an induction generator feeding an isolated load. A static VAR compensator is connected at the induction generator terminals to regulate the load voltage. The rotor speed, and thereby the load frequency are controlled via adjusting the mechanical power input using the blade pitch-angle. The MPC is used to calculate the optimal control actions including system constraints. To alleviate computational effort and to reduce numerical problems, particularly in large prediction horizon, an exponentially weighted functional model predictive control (FMPC) is employed. Digital simulations have been carried out in order to validate the effectiveness of the proposed scheme. The proposed controller has been tested through step changes in the wind speed and the load impedance. Simulation results show that adequate performance of the proposed wind energy scheme has been achieved. Moreover, this scheme is robust against the parameters variation and eliminates the influence of modeling and measurement errors. (orig.)

Prediction of the wind turbine performance by using BEM with airfoil data extracted from CFD

DEFF Research Database (Denmark)

Yang, Hua; Shen, Wen Zhong; Xu, Haoran

2014-01-01

Blade element momentum (BEM) theory with airfoil data is a widely used technique for prediction of wind turbine aerodynamic performance, but the reliability of the airfoil data is an important factor for the prediction accuracy of aerodynamic loads and power. The airfoil characteristics used in BEM...

Annual and interannual variability of scatterometer ocean surface wind over the South China Sea

DEFF Research Database (Denmark)

Zhang, GS; Xu, Q.; Gong, Z.

2014-01-01

To investigate the annual and interannual variability of ocean surface wind over the South China Sea (SCS), the vector empirical orthogonal function (VEOF) method and the Hilbert-Huang transform (HHT) method were employed to analyze a set of combined satellite scatterometer wind data during.......3% of the total variance and represents the East Asian monsoon features. The second mode of VEOF corresponds to a spring-autumn oscillation which accounts for 8.3% of the total variance. To analyze the interannual variability, the annual signal was removed from the wind data set and the VEOFs of the residuals...

Vibration Analysis and Time Series Prediction for Wind Turbine Gearbox Prognostics

Directory of Open Access Journals (Sweden)

Hossam A. Gabbar

2013-01-01

Full Text Available Premature failure of a gearbox in a wind turbine poses a high risk of increasing the operational and maintenance costs and decreasing the profit margins. Prognostics and health management (PHM techniques are widely used to access the current health condition of the gearbox and project it in future to predict premature failures. This paper proposes such techniques for predicting gearbox health condition index extracted from the vibration signals emanating from the gearbox. The progression of the monitoring index is predicted using two different prediction techniques, adaptive neuro-fuzzy inference system (ANFIS and nonlinear autoregressive model with exogenous inputs (NARX. The proposed prediction techniques are evaluated through sun-spot data-set and applied on vibration based health related monitoring index calculated through psychoacoustic phenomenon. A comparison is given for their prediction accuracy. The results are helpful in understanding the relationship of machine conditions, the corresponding indicating features, the level of damage/degradation, and their progression.

Coastal and rain-induced wind variability depicted by scatterometers

Science.gov (United States)

Portabella, M.; Lin, W.; Stoffelen, A.; Turiel, A.; Verhoef, A.; Verspeek, J.; Ballabrera, J.; Vogelzang, J.

2012-04-01

A detailed knowledge of local wind variability near the shore is very important since it strongly affects the weather and microclimate in coastal regions. Since coastal areas are densely populated and most activity at sea occurs near the shore, sea-surface wind field information is important for a number of applications. In the vicinity of land sea-breeze, wave fetch, katabatic and current effects are more likely than in the open ocean, thus enhancing air-sea interaction. Also very relevant for air-sea interaction are the rain-induced phenomena, such as downbursts and convergence. Relatively cold and dry air is effectively transported to the ocean surface and surface winds are enhanced. In general, both coastal and rain-induced wind variability are poorly resolved by Numerical Weather Prediction (NWP) models. Satellite real aperture radars (i.e., scatterometers) are known to provide accurate mesoscale (25-50 km resolution) sea surface wind field information used in a wide variety of applications. Nowadays, there are two operating scatterometers in orbit, i.e., the C-band Advanced Scatterometer (ASCAT) onboard Metop-A and the Ku-band scatterometer (OSCAT) onboard Oceansat-2. The EUMETSAT Ocean and Sea Ice Satellite Application Facility (OSI SAF) delivers several ASCAT level 2 wind products with 25 km and 12.5 km Wind Vector Cell (WVC) spacing, including a pre-operational coastal wind product as well as an OSCAT level 2 wind product with 50 km spacing in development status. Rain is known to both attenuate and scatter the microwave signal. In addition, there is a "splashing" effect. The roughness of the sea surface is increased because of splashing due to rain drops. The so-called "rain contamination" is larger for Ku-band scatterometer systems than for C-band systems. Moreover, the associated downdrafts lead to variable wind speeds and directions, further complicating the wind retrieval. The C-band ASCAT high resolution wind processing is validated under rainy

Aero-acoustics prediction of a vertical axis wind turbine using Large Eddy Simulation and acoustic analogy

International Nuclear Information System (INIS)

Ghasemian, Masoud; Nejat, Amir

2015-01-01

Operating wind turbines generate tonal and broadband noises affecting the living environment adversely; especially small wind turbines located in the vicinity of human living places. Therefore, it is important to determine the level of noise pollution of such type of wind turbine installation. The current study carries out numerical prediction for aerodynamic noise radiated from an H-Darrieus Vertical Axis Wind Turbine. Incompressible LES (Large Eddy Simulation) is conducted to obtain the instantaneous turbulent flow field. The noise predictions are performed by the Ffowcs Williams and Hawkings (FW–H) acoustic analogy formulation. Simulations are performed for five different tip-speed ratios. First, the mean torque coefficient is compared with the experimental data, and good agreement is observed. Then, the research focuses on the broadband noises of the turbulent boundary layers and the tonal noises due to blade passing frequency. The contribution of the thickness, loading and quadrupole noises are investigated, separately. The results indicate a direct relation between the strength of the radiated noise and the rotational speed. Furthermore, the effect of receiver distance on the OASPL (Overall Sound Pressure Level) is investigated. It is concluded that the OASPL varies with a logarithmic trend with the receiver distance as it was expected. - Highlights: • Large Eddy Simulation has been used to predict the turbulent flow field. • The Ffowcs Williams and Hawkings method was employed to predict radiated noise. • There is a direct relation between the radiated noise and the tip speed ratio. • The quadrupole noises have negligible effect on the tonal noises

Predictions of local ground geomagnetic field fluctuations during the 7-10 November 2004 events studied with solar wind driven models

Directory of Open Access Journals (Sweden)

P. Wintoft

2005-11-01

Full Text Available The 7-10 November 2004 period contains two events for which the local ground magnetic field was severely disturbed and simultaneously, the solar wind displayed several shocks and negative B_z periods. Using empirical models the 10-min RMS and at Brorfelde (BFE, 11.67° E, 55.63° N, Denmark, are predicted. The models are recurrent neural networks with 10-min solar wind plasma and magnetic field data as inputs. The predictions show a good agreement during 7 November, up until around noon on 8 November, after which the predictions become significantly poorer. The correlations between observed and predicted log RMS is 0.77 during 7-8 November but drops to 0.38 during 9-10 November. For RMS the correlations for the two periods are 0.71 and 0.41, respectively. Studying the solar wind data for other L1-spacecraft (WIND and SOHO it seems that the ACE data have a better agreement to the near-Earth solar wind during the first two days as compared to the last two days. Thus, the accuracy of the predictions depends on the location of the spacecraft and the solar wind flow direction. Another finding, for the events studied here, is that the and models showed a very different dependence on B_z. The model is almost independent of the solar wind magnetic field B_z, except at times when B_z is exceptionally large or when the overall activity is low. On the contrary, the model shows a strong dependence on B_z at all times.

A novel hybrid approach for predicting wind farm power production based on wavelet transform, hybrid neural networks and imperialist competitive algorithm

International Nuclear Information System (INIS)

Aghajani, Afshin; Kazemzadeh, Rasool; Ebrahimi, Afshin

2016-01-01

Highlights: • Proposing a novel hybrid method for short-term prediction of wind farms with high accuracy. • Investigating the prediction accuracy for proposed method in comparison with other methods. • Investigating the effect of six types of parameters as input data on predictions. • Comparing results for 6 & 4 types of the input parameters – addition of pressure and air humidity. - Abstract: This paper proposes a novel hybrid approach to forecast electric power production in wind farms. Wavelet transform (WT) is employed to filter input data of wind power, while radial basis function (RBF) neural network is utilized for primary prediction. For better predictions the main forecasting engine is comprised of three multilayer perceptron (MLP) neural networks by different learning algorithms of Levenberg–Marquardt (LM), Broyden–Fletcher–Goldfarb–Shanno (BFGS), and Bayesian regularization (BR). Meta-heuristic technique Imperialist Competitive Algorithm (ICA) is used to optimize neural networks’ weightings in order to escape from local minima. In the forecast process, the real data of wind farms located in the southern part of Alberta, Canada, are used to train and test the proposed model. The data are a complete set of six meteorological and technical characteristics, including wind speed, wind power, wind direction, temperature, pressure, and air humidity. In order to demonstrate the efficiency of the proposed method, it is compared with several other wind power forecast techniques. Results of optimizations indicate the superiority of the proposed method over the other mentioned techniques; and, forecasting error is remarkably reduced. For instance, the average normalized root mean square error (NRMSE) and average mean absolute percentage error (MAPE) are respectively 11% and 14% lower for the proposed method in 1-h-ahead forecasts over a 24-h period with six types of input than those for the best of the compared models.

Predicting Migratory Corridors of White Storks, Ciconia ciconia, to Enhance Sustainable Wind Energy Planning: A Data-Driven Agent-Based Model

Directory of Open Access Journals (Sweden)

Francis Oloo

2018-05-01

Full Text Available White storks (Ciconia ciconia are birds that make annual long-distance migration flights from their breeding grounds in the Northern Hemisphere to the south of Africa. These trips take place in the winter season, when the temperatures in the North fall and food supply drops. White storks, because of their large size, depend on the wind, thermals, and orographic characteristics of the environment in order to minimize their energy expenditure during flight. In particular, the birds adopt a soaring behavior in landscapes where the thermal uplift and orographic updrafts are conducive. By attaining suitable soaring heights, the birds then use the wind characteristics to glide for hundreds of kilometers. It is therefore expected that white storks would prefer landscapes that are characterized by suitable wind and thermal characteristics, which promote the soaring and gliding behaviors. However, these same landscapes are also potential sites for large-scale wind energy generation. In this study, we used the observed data of the white stork movement trajectories to specify a data-driven agent-based model, which simulates flight behavior of the white storks in a dynamic environment. The data on the wind characteristics and thermal uplift are dynamically changed on a daily basis so as to mimic the scenarios that the observed birds experienced during flight. The flight corridors that emerge from the simulated flights are then combined with the predicted surface on the wind energy potential, in order to highlight the potential risk of collision between the migratory white storks and hypothetical wind farms in the locations that are suitable for wind energy developments. This work provides methods that can be adopted to assess the overlap between wind energy potential and migratory corridors of the migration of birds. This can contribute to achieving sustainable trade-offs between wind energy development and conservation of wildlife and, hence, handling the

Pressure integration technique for predicting wind-induced response in high-rise buildings

Directory of Open Access Journals (Sweden)

Aly Mousaad Aly

2013-12-01

Full Text Available This paper presents a procedure for response prediction in high-rise buildings under wind loads. The procedure is illustrated in an application example of a tall building exposed to both cross-wind and along-wind loads. The responses of the building in the lateral directions combined with torsion are estimated simultaneously. Results show good agreement with recent design standards; however, the proposed procedure has the advantages of accounting for complex mode shapes, non-uniform mass distribution, and interference effects from the surrounding. In addition, the technique allows for the contribution of higher modes. For accurate estimation of the acceleration response, it is important to consider not only the first two lateral vibrational modes, but also higher modes. Ignoring the contribution of higher modes may lead to underestimation of the acceleration response; on the other hand, it could result in overestimation of the displacement response. Furthermore, the procedure presented in this study can help decision makers, involved in a tall building design/retrofit to choose among innovative solutions like aerodynamic mitigation, structural member size adjustment, damping enhancement, and/or materials change, with an objective to improve the resiliency and the serviceability under extreme wind actions.

Integrated spatial assessment of wind erosion risk in Hungary

Directory of Open Access Journals (Sweden)

L. Pásztor

2016-11-01

Full Text Available Wind erosion susceptibility of Hungarian soils was mapped on the national level integrating three factors of the complex phenomenon of deflation (physical soil features, wind characteristics, and land use and land cover. Results of wind tunnel experiments on erodibility of representative soil samples were used for the parametrization of a countrywide map of soil texture compiled for the upper 5 cm layer of soil, which resulted in a map representing threshold wind velocity exceedance. Average wind velocity was spatially estimated with 0.5′ resolution using the Meteorological Interpolation based on Surface Homogenised Data Basis (MISH method elaborated for the spatial interpolation of surface meteorological elements. The probability of threshold wind velocity exceedance was determined based on values predicted by the soil texture map at the grid locations. Ratio values were further interpolated to a finer 1 ha resolution using sand and silt content of the uppermost (0–5 cm layer of soil as spatial co-variables. Land cover was also taken into account, excluding areas that are not relevant to wind erosion (forests, water bodies, settlements, etc., to spatially assess the risk of wind erosion. According to the resulting map of wind erosion susceptibility, about 10 % of the total area of Hungary can be identified as susceptible to wind erosion. The map gives more detailed insight into the spatial distribution of wind-affected areas in Hungary compared to previous studies.

Spatial interpolation of fine particulate matter concentrations using the shortest wind-field path distance.

Directory of Open Access Journals (Sweden)

Longxiang Li

Full Text Available Effective assessments of air-pollution exposure depend on the ability to accurately predict pollutant concentrations at unmonitored locations, which can be achieved through spatial interpolation. However, most interpolation approaches currently in use are based on the Euclidean distance, which cannot account for the complex nonlinear features displayed by air-pollution distributions in the wind-field. In this study, an interpolation method based on the shortest path distance is developed to characterize the impact of complex urban wind-field on the distribution of the particulate matter concentration. In this method, the wind-field is incorporated by first interpolating the observed wind-field from a meteorological-station network, then using this continuous wind-field to construct a cost surface based on Gaussian dispersion model and calculating the shortest wind-field path distances between locations, and finally replacing the Euclidean distances typically used in Inverse Distance Weighting (IDW with the shortest wind-field path distances. This proposed methodology is used to generate daily and hourly estimation surfaces for the particulate matter concentration in the urban area of Beijing in May 2013. This study demonstrates that wind-fields can be incorporated into an interpolation framework using the shortest wind-field path distance, which leads to a remarkable improvement in both the prediction accuracy and the visual reproduction of the wind-flow effect, both of which are of great importance for the assessment of the effects of pollutants on human health.

A New Instrument for Testing Wind Erosion by Soil Surface Shape Change

International Nuclear Information System (INIS)

Hai, C.; Yuan, X.; Jiang, H.; Zhou, R.; Wang, J.; Liu, B.; Ye, Y.; Du, P.

2010-01-01

Wind erosion, a primary cause of soil degeneration, is a problem in arid and semiarid areas throughout the world. Many methods are available to study soil erosion, but there is no an effective method for making quantitative measurements in the field. To solve this problem, we have developed a new instrument that can measure the change in the shape of the soil surface, allowing quick quantification of wind erosion. In this paper, the construction and principle of the new instrument are described. Field experiments are carried out using the instrument, and the data are analyzed. The erosion depth is found to vary by 11% compared to the average for measurement areas ranging from 30 x 30 cm 2 to 10 x 10 cm 2 . The results show that the instrument is convenient and reliable for quantitatively measuring wind erosion in the field.

Model Predictive Control of Trailing Edge Flaps on a wind turbine blade

DEFF Research Database (Denmark)

Castaignet, Damien; Poulsen, Niels Kjølstad; Buhl, Thomas

2011-01-01

Trailing Edge Flaps on wind turbine blades have been studied in order to achieve fatigue load reduction on the turbine components. We show in this paper how Model Predictive Control can be used to do frequency weighted control of the trailing edge flaps in order to reduce fatigue damage on the bl...

Development of an Integrated Water and Wind Erosion Model

Science.gov (United States)

Flanagan, D. C.; Ascough, J. C.; Wagner, L. E.; Geter, W. F.

2006-12-01

Prediction technologies for soil erosion by the forces of wind or water have largely been developed independently from one another, especially within the United States. Much of this has been due to the initial creation of equations and models which were empirical in nature (i.e., Universal Soil Loss Equation, Wind Erosion Equation) and based upon separate water erosion or wind erosion plot and field measurements. Additionally, institutional organizations in place typically divided research efforts and funding to unique wind or water erosion research and modeling projects. However, during the past 20 years computer technologies and erosion modeling have progressed to the point where it is now possible to merge physical process-based computer simulation models into an integrated water and wind erosion prediction system. In a physically- based model, many of the processes which must be simulated for wind and water erosion computations are the same, e.g., climate, water balance, runoff, plant growth, etc. Model components which specifically deal with the wind or water detachment, transport and deposition processes are those that must differ, as well as any necessary parameterization of input variables (e.g., adjusted soil erodibilities, critical shear stresses, etc.) for those components. This presentation describes current efforts towards development of a combined wind and water erosion model, based in part upon technologies present in the Water Erosion Prediction Project (WEPP) and the Wind Erosion Prediction System (WEPS) models. Initial efforts during the past two years have resulted in modular modeling components that allow for prediction of infiltration, surface runoff, and water erosion at a hillslope scale within an Object Modeling System. Additional components currently in development include wind detachment at a single field point, continuous water balance, and unified plant growth. Challenges in this project are many, and include adequate field

Trends in significant wave height and surface wind speed in the China Seas between 1988 and 2011

Science.gov (United States)

Zheng, Chongwei; Zhang, Ren; Shi, Weilai; Li, Xin; Chen, Xuan

2017-10-01

Wind and waves are key components of the climate system as they drive air-sea interactions and influence weather systems and atmospheric circulation. In marine environments, understanding surface wind and wave fields and their evolution over time is important for conducting safe and efficient human activities, such as navigation and engineering. This study considers long-term trends in the sea surface wind speed (WS) and significant wave height (SWH) in the China Seas over the period 1988-2011 using the Cross-Calibrated Multi-Platform (CCMP) ocean surface wind product and a 24-year hindcast wave dataset obtained from the WAVEWATCH-III (WW3) wave model forced with CCMP winds. The long-term trends in WS and SWH in the China Seas are analyzed over the past 24 years to provide a reference point from which to assess future climate change and offshore wind and wave energy resource development in the region. Results demonstrate that over the period 1988-2011 in the China Seas: 1) WS and SWH showed a significant increasing trend of 3.38 cm s-1 yr-1 and 1.52 cm yr-1, respectively; 2) there were notable regional differences in the long-term trends of WS and SWH; 3) areas with strong increasing trends were located mainly in the middle of the Tsushima Strait, the northern and southern areas of the Taiwan Strait, and in nearshore regions of the northern South China Sea; and 4) the long-term trend in WS was closely associated with El Niño and a significant increase in the occurrence of gale force winds in the region.

Turbulent Flow Inside and Above a Wind Farm: A Wind-Tunnel Study

Directory of Open Access Journals (Sweden)

Leonardo P. Chamorro

2011-11-01

Full Text Available Wind-tunnel experiments were carried out to better understand boundary layer effects on the flow pattern inside and above a model wind farm under thermally neutral conditions. Cross-wire anemometry was used to characterize the turbulent flow structure at different locations around a 10 by 3 array of model wind turbines aligned with the mean flow and arranged in two different layouts (inter-turbine separation of 5 and 7 rotor diameters in the direction of the mean flow by 4 rotor diameters in its span. Results suggest that the turbulent flow can be characterized in two broad regions. The first, located below the turbine top tip height, has a direct effect on the performance of the turbines. In that region, the turbulent flow statistics appear to reach equilibrium as close as the third to fourth row of wind turbines for both layouts. In the second region, located right above the first one, the flow adjusts slowly. There, two layers can be identified: an internal boundary layer where the flow is affected by both the incoming wind and the wind turbines, and an equilibrium layer, where the flow is fully adjusted to the wind farm. An adjusted logarithmic velocity distribution is observed in the equilibrium layer starting from the sixth row of wind turbines. The effective surface roughness length induced by the wind farm is found to be higher than that predicted by some existing models. Momentum recovery and turbulence intensity are shown to be affected by the wind farm layout. Power spectra show that the signature of the tip vortices, in both streamwise and vertical velocity components, is highly affected by both the relative location in the wind farm and the wind farm layout.

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

High temperature co-axial winding transformers

Science.gov (United States)

Divan, Deepakraj M.; Novotny, Donald W.

1993-01-01

The analysis and design of co-axial winding transformers is presented. The design equations are derived and the different design approaches are discussed. One of the most important features of co-axial winding transformers is the fact that the leakage inductance is well controlled and can be made low. This is not the case in conventional winding transformers. In addition, the power density of co-axial winding transformers is higher than conventional ones. Hence, using co-axial winding transformers in a certain converter topology improves the power density of the converter. The design methodology used in meeting the proposed specifications of the co-axial winding transformer specifications are presented and discussed. The final transformer design was constructed in the lab. Co-axial winding transformers proved to be a good choice for high power density and high frequency applications. They have a more predictable performance compared with conventional transformers. In addition, the leakage inductance of the transformer can be controlled easily to suit a specific application. For space applications, one major concern is the extraction of heat from power apparatus to prevent excessive heating and hence damaging of these units. Because of the vacuum environment, the only way to extract heat is by using a cold plate. One advantage of co-axial winding transformers is that the surface area available to extract heat from is very large compared to conventional transformers. This stems from the unique structure of the co-axial transformer where the whole core surface area is exposed and can be utilized for cooling effectively. This is a crucial issue here since most of the losses are core losses.

Spectral Properties of ENVISAT ASAR and QuikSCAT Surface Winds in the North Sea

DEFF Research Database (Denmark)

Karagali, Ioanna; Larsén, Xiaoli Guo; Badger, Merete

2013-01-01

as an increase in spectral density over similar wavenumber ranges as the spatial resolution increases. The 600-m SAR wind product reveals a range of wavenumbers in which the exchange processes between micro- and meso-scales occur; this range is not captured by the wind products with a resolution of 1.5 km......Spectra derived from ENVISAT Advanced Synthetic Aperture Radar (ASAR) and QuikSCAT near-surface ocean winds are investigated over the North Sea. The two sensors offer a wide range of spatial resolutions, from 600 m to 25 km, with different spatial coverage over the area of interest. This provides...... a unique opportunity to study the impact of the spatial resolution on the spectral properties of the wind over a wide range of length scales. Initially, a sub-domain in the North Sea is chosen, due to the overlap of 87 wind scenes from both sensors. The impact of the spatial resolution is manifested...

Effect of fall wind on wind power generation; Furyoku hatsuden ni okeru dashikaze no koka

Energy Technology Data Exchange (ETDEWEB)

Nagai, H [Nihon University, Tokyo (Japan)

1997-11-25

Wind conditions in Arakawa Town, Niigata Prefecture, were surveyed by anemometers and anemoscopes installed at 3 different points, and the data are analyzed to develop the prediction model for investigating possibility of introduction of wind mills there. Outlined herein is power generated by fall wind by comparing predicted power availability with the actual results. In order to investigate possibility of power generation by fall wind, the wind conditions and power availability are simulated using the observed wind condition data. Predicted wind velocity involves a large error at a point where frequency of prevailing wind direction is high, and direction in which average wind velocity is high coincides with direction in which land is slanted at a high slope. Fall wind occurs locally for geographical reasons. Location of the wind mill must be carefully considered, because it is complex, although potentially gives a larger quantity of power. A wind mill of 400kW can produce power of around 600MWh annually, when it is located at the suited site confirmed by the wind condition analysis results. 6 refs., 5 figs., 6 tabs.

Investigation of wind turbine effects on Evapotranspiration using surface energy balance model based on satellite-derived data

Science.gov (United States)

hassanpour Adeh, E.; Higgins, C. W.

2014-12-01

Wind turbines have been introduced as an energy source that does not require a large expenditure of water. However, recent simulation results indicate that wind turbines increase evaporation rates from the nearby land. In this research the effect of wind energy on irrigated agriculture is determined using a Surface Energy Balance Algorithm (SEBAL) on Landsat data spanning a 30 year interval. The analysis allows the characterization of evapotranspiration (ET) before and after wind turbine installations. The time history of ET from Landsat data will be presented for several major wind farms across the US. These data will be used to determine the impact on water demand due to presence of wind turbines.

Station-keeping control of an unmanned surface vehicle exposed to current and wind disturbances

OpenAIRE

Sarda, Edoardo I.; Qu, Huajin; Bertaska, Ivan R.; von Ellenrieder, Karl D.

2017-01-01

Field trials of a 4 meter long, 180 kilogram, unmanned surface vehicle (USV) have been conducted to evaluate the performance of station-keeping heading and position controllers in an outdoor marine environment disturbed by wind and current. The USV has a twin hull configuration and a custom-designed propulsion system, which consists of two azimuthing thrusters, one for each hull. Nonlinear proportional derivative, backstepping and sliding mode feedback controllers were tested in winds of abou...

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

Representativeness of wind measurements in moderately complex terrain

Science.gov (United States)

van den Bossche, Michael; De Wekker, Stephan F. J.

2018-02-01

We investigated the representativeness of 10-m wind measurements in a 4 km × 2 km area of modest relief by comparing observations at a central site with those at four satellite sites located in the same area. Using a combination of established and new methods to quantify and visualize representativeness, we found significant differences in wind speed and direction between the four satellite sites and the central site. The representativeness of the central site wind measurements depended strongly on surface wind speed and direction, and atmospheric stability. Through closer inspection of the observations at one of the satellite sites, we concluded that terrain-forced flows combined with thermally driven downslope winds caused large biases in wind direction and speed. We used these biases to generate a basic model, showing that terrain-related differences in wind observations can to a large extent be predicted. Such a model is a cost-effective way to enhance an area's wind field determination and to improve the outcome of pollutant dispersion and weather forecasting models.

Determining the bounds of skilful forecast range for probabilistic prediction of system-wide wind power generation

Directory of Open Access Journals (Sweden)

Dirk Cannon

2017-06-01

Full Text Available State-of-the-art wind power forecasts beyond a few hours ahead rely on global numerical weather prediction models to forecast the future large-scale atmospheric state. Often they provide initial and boundary conditions for nested high resolution simulations. In this paper, both upper and lower bounds on forecast range are identified within which global ensemble forecasts provide skilful information for system-wide wind power applications. An upper bound on forecast range is associated with the limit of predictability, beyond which forecasts have no more skill than predictions based on climatological statistics. A lower bound is defined at the lead time beyond which the resolved uncertainty associated with estimating the future large-scale atmospheric state is larger than the unresolved uncertainty associated with estimating the system-wide wind power response to a given large-scale state.The bounds of skilful ensemble forecast range are quantified for three leading global forecast systems. The power system of Great Britain (GB is used as an example because independent verifying data is available from National Grid. The upper bound defined by forecasts of GB-total wind power generation at a specific point in time is found to be 6–8 days. The lower bound is found to be 1.4–2.4 days. Both bounds depend on the global forecast system and vary seasonally. In addition, forecasts of the probability of an extreme power ramp event were found to possess a shorter limit of predictability (4.5–5.5 days. The upper bound on this forecast range can only be extended by improving the global forecast system (outside the control of most users or by changing the metric used in the probability forecast. Improved downscaling and microscale modelling of the wind farm response may act to decrease the lower bound. The potential gain from such improvements have diminishing returns beyond the short-range (out to around 2 days.

Numerical and Observational Investigations of Long-Lived Mcs-Induced Severe Surface Wind Events: the Derecho

Science.gov (United States)

Schmidt, Jerome Michael

This study addresses the production of sustained, straight-line, severe surface winds associated with mesoscale convective systems (MCSs) of extratropical origin otherwise known as derechos. The physical processes which govern the observed derecho characteristics are identified and their possible forcing mechanisms are determined. Detailed observations of two derechos are presented along with simulations using the Colorado State University Regional Atmospheric Modeling System (CSU-RAMS). The observations revealed a derecho environment characterized by strong vertical wind shear through the depth of the troposphere and large values of convective available potential energy (CAPE). The thermodynamic environment of the troposphere in each case had a distinct three-layer structure consisting of: (i) a surface-based stable layer of 1-to-2 km in depth, (ii) an elevated well -mixed layer of 2-4 km in depth, and (iii) an upper tropospheric layer of intermediate stability that extended to the tropopause. Two primary sets of simulations were performed to assess the impact of the observed environmental profiles on the derecho structure, propagation, and longevity. The first set consisted of nested-grid regional-scale simulations initialized from the standard NMC analyses on a domain having relatively coarse horizontal resolution (75 km). The second set of simulations consisted of two and three-dimensional experiments initialized in a horizontally homogeneous environment having a relatively fine horizontal resolution (2 km) and explicit microphysics. The results from these experiments indicate the importance of convectively -induced gravity waves on the MCS structure, propagation, longevity, and severe surface wind development. The sensitivity of the simulated convection and gravity waves to variations in the vertical wind shear and moisture profiles are described. Detailed Doppler radar analyses and 3-D simulations of a severe, bow echo squall line are presented which reveal

The impact of urbanization on wind speed and surface aerodynamic characteristics in Beijing during 1991-2011

Science.gov (United States)

Liu, Junkai; Gao, Zhiqiu; Wang, Linlin; Li, Yubin; Gao, Chloe Y.

2018-06-01

Urbanization has a significant influence on climate and meteorological conditions through altering surface aerodynamic characteristics. Based on observational data collected at 15 levels on a 325 m meteorological tower in Beijing during 1991-2011, changes in wind speed, vertical profile, aerodynamic roughness length (z0), and zero-plane displacement height (zd) were analyzed. Decreasing trends were observed predominantly during this period, especially for levels between 65 and 140 m where the largest decreasing rates often occur. The annual and seasonal (spring, summer, autumn, and winter) mean wind speeds at 15 levels all present decreasing trends with average rates of 0.029, 0.024, 0.023, 0.040, and 0.019 m s-1 a-1, respectively. The decreases in strong wind categories contribute most to the reduction of mean wind speed. Furthermore, in 2005-2011, the diurnal maximum wind speeds at lower levels tend to appear earlier as compared to those in 1991-1997, while the patterns of diurnal cycle between different levels become more similar in these periods. Besides, the phenomena of "kink" in wind profiles are visible in various atmospheric stabilities, and the average height of a kink has increased from about 40 m to nearly 80 m associated with urbanization during 1991-2011. In addition, the results of z0 and zd calculated using the wind profile method vary with wind directions due to surface heterogeneity and that larger values often occur along with southerly winds. Both z0 and zd show increasing trends in different sectors during 1991-2011, and the annual mean z0 and zd have increased from less than 1 m to greater than 2 m, and from less than 10 m to greater than 20 m, respectively.

Comparison of the effectiveness of analytical wake models for wind farm with constant and variable hub heights

International Nuclear Information System (INIS)

Wang, Longyan; Tan, Andy C.C.; Cholette, Michael; Gu, Yuantong

2016-01-01

Highlights: • The effectiveness of three analytical wake models is studied. • The results of the analytical wake models are compared with the CFD simulations. • The results of CFD simulation are verified by comparison to the offshore wind farm observation data. • The onshore wind farm with both constant and different hub height turbines are analyzed. • PARK model is able to predict the total wind farm power production well with tuned surface roughness value. - Abstract: Extensive power losses of wind farm have been witnessed due to the wake interactions between wind turbines. By applying analytical wake models which describe the wind speed deficits in the wake quantitatively, the power losses can be regained to a large extent through wind farm layout optimization, and this has been extensively reported in literature. Nevertheless, the effectiveness of the analytical wake models in predicting the wind farm power production have rarely been studied and compared for wind farm with both constant and variable wind turbine hub heights. In this study, the effectiveness of three different analytical wake models (PARK model, Larsen model and B-P model) is thoroughly compared over a wide range of wake properties. After the validation with the observation data from offshore wind farm, CFD simulations are used to verify the effectiveness of the analytical wake models for an onshore wind farm. The results show that when using the PARK model the surface roughness value (z 0 ) must be carefully tuned to achieve good performance in predicting the wind farm power production. For the other two analytical wake models, their effectiveness varies depending on the situation of wind farm (offshore or onshore) and the wind turbine hub heights (constant or variable). It was found that the results of B-P model agree well with the CFD simulations for offshore wind farm, but not for the onshore wind farm. The Larsen model is more accurate for the wind farm with variable wind turbine

Practical use of offsite atmospheric measurements to enhance profitability of onsite wind prediction

Energy Technology Data Exchange (ETDEWEB)

Collier, Craig [GL Garrad Hassan (Canada)

2011-07-01

This paper presents the use of offsite atmospheric measurements to improve the profitability of onsite wind prediction. There are two common sensitivities used, intraday and interday. Results from US mid-western sites show that the error associated with wind predictions is large but there are possibilities for improvement. Inter- and intraday can be used traditionally to contribute towards NWP bias correction. Intraday alone can be used with machine learning and NWP. These techniques are compared and given in order of ease of use and potential accuracy gains. Some considerations and differences for all three techniques, namely, traditional, data assimilation and machine learning are also detailed. An offsite selection matrix shows how elements like location, geography and telemetry rate in the 3 techniques. The experimental setup for all 3 techniques over a 3-month period is given and the results are presented. It can be concluded that the results from these simple experiments show promise but vary in method and time scale.

Predicting wind-induced vibrations of high-rise buildings using unsteady CFD and modal analysis

KAUST Repository

Zhang, Yue

2015-01-01

This paper investigates the wind-induced vibration of the CAARC standard tall building model, via unsteady Computational Fluid Dynamics (CFD) and a structural modal analysis. In this numerical procedure, the natural unsteady wind in the atmospheric boundary layer is modeled with an artificial inflow turbulence generation method. Then, the turbulent flow is simulated by the second mode of a Zonal Detached-Eddy Simulation, and a conservative quadrature-projection scheme is adopted to transfer unsteady loads from fluid to structural nodes. The aerodynamic damping that represents the fluid-structure interaction mechanism is determined by empirical functions extracted from wind tunnel experiments. Eventually, the flow solutions and the structural responses in terms of mean and root mean square quantities are compared with experimental measurements, over a wide range of reduced velocities. The significance of turbulent inflow conditions and aeroelastic effects is highlighted. The current methodology provides predictions of good accuracy and can be considered as a preliminary design tool to evaluate the unsteady wind effects on tall buildings.

Gain-Scheduled Model Predictive Control of Wind Turbines using Laguerre Functions

DEFF Research Database (Denmark)

Adegas, Fabiano Daher; Wisniewski, Rafal; Larsen, Lars Finn Sloth

2014-01-01

This paper presents a systematic approach to design gain-scheduled predictive controllers for wind turbines. The predictive control law is based on Laguerre functions to parameterize control signals and a parameter-dependent cost function that is analytically determined from turbine data....... These properties facilitate the design of speed controllers by placement of the closed-loop poles (when constraints are not active) and systematic adaptation towards changes in the operating point. Vibration control of undamped modes is achieved by imposing a certain degree of stability to the closed-loop system....... The approach can be utilized to the design of new controllers and to represent existing gain-scheduled controllers as predictive controllers. The numerical example and simulations illustrate the design of a speed controller augmented with active damping of the tower fore-aft displacement....

Distinctive Features of Surface Winds over Indian Ocean Between Strong and Weak Indian Summer Monsoons: Implications With Respect To Regional Rainfall Change in India

Science.gov (United States)

Zheng, Y.; Bourassa, M. A.; Ali, M. M.

2017-12-01

This observational study focuses on characterizing the surface winds in the Arabian Sea (AS), the Bay of Bengal (BoB), and the southern Indian Ocean (SIO) with special reference to the strong and weak Indian summer monsoon rainfall (ISMR) using the latest daily gridded rainfall dataset provided by the Indian Meteorological Department (IMD) and the Cross-Calibrated Multi-Platform (CCMP) gridded wind product version 2.0 produced by Remote Sensing System (RSS) over the overlapped period 1991-2014. The potential links between surface winds and Indian regional rainfall are also examined. Results indicate that the surface wind speeds in AS and BoB during June-August are almost similar during strong ISMRs and weak ISMRs, whereas significant discrepancies are observed during September. By contrast, the surface wind speeds in SIO during June-August are found to be significantly different between strong and weak ISMRs, where they are similar during September. The significant differences in monthly mean surface wind convergence between strong and weak ISMRs are not coherent in space in the three regions. However, the probability density function (PDF) distributions of daily mean area-averaged values are distinctive between strong and weak ISMRs in the three regions. The correlation analysis indicates the area-averaged surface wind speeds in AS and the area-averaged wind convergence in BoB are highly correlated with regional rainfall for both strong and weak ISMRs. The wind convergence in BoB during strong ISMRs is relatively better correlated with regional rainfall than during weak ISMRs. The surface winds in SIO do not greatly affect Indian rainfall in short timescales, however, they will ultimately affect the strength of monsoon circulation by modulating Indian Ocean Dipole (IOD) mode via atmosphere-ocean interactions.

Inhibition of solar wind impingement on Mercury by planetary induction currents

International Nuclear Information System (INIS)

Hood, L.L.; Schubert, G.

1979-01-01

The simple compression of a planetary magnetosphere by varying solar wind stagnation pressure is limited by currents induced in the electrically conducting parts of the planet. This inhibition is especially important for Mercury, since the radius of the electrically conducting iron core is a large fraction of the planetary radius, which in turn is a significant fraction of the subsolar magnetospheric radius b. Previous treatments of solar wind standoff distance variations at Mercury using the terrestrial analogue b 6 assumption have neglected this phenomenon. Using the lowest suggested value of the planetary dipole moment, 2.4 x 10 22 G cm 3 , we estimate that a minimum pressure of approx.38P 0 where P 0 is the external stagnation pressure in the steady state, is required to force the standoff distance down to the subsolar surface of Mercury if the pressure change persists for at least 1 day. This value is 4.3 times that which would be predicted if Mercury had no core, and it is larger than the maximum pressure predicted at Mercury's orbit (approx.25P 0 ) on the basis of hourly averaged solar wind statistics at 1 AU. Thus a direct interaction at any time of solar wind plasma with the surface of Mercury due to external compression effects alone is unlikely for solar wind conditions similar to those at present

North Atlantic atmospheric circulation and surface wind in the Northeast of the Iberian Peninsula: uncertainty and long term downscaled variability

Energy Technology Data Exchange (ETDEWEB)

Garcia-Bustamante, E.; Jimenez, P.A. [CIEMAT, Departamento de Energias Renovables, Madrid (Spain); Universidad Complutense de Madrid, Departamento de Astrofisica y CC. de la Atmosfera, Madrid (Spain); Gonzalez-Rouco, J.F. [Universidad Complutense de Madrid, Departamento de Astrofisica y CC. de la Atmosfera, Madrid (Spain); Navarro, J. [CIEMAT, Departamento de Energias Renovables, Madrid (Spain); Xoplaki, E. [University of Bern, Institute of Geography and Oeschger Centre for Climate Change Research, Bern (Switzerland); Montavez, J.P. [Universidad de Murcia, Departamento de Fisica, Murcia (Spain)

2012-01-15

The variability and predictability of the surface wind field at the regional scale is explored over a complex terrain region in the northeastern Iberian Peninsula by means of a downscaling technique based on Canonical Correlation Analysis. More than a decade of observations (1992-2005) allows for calibrating and validating a statistical method that elicits the main associations between the large scale atmospheric circulation over the North Atlantic and Mediterranean areas and the regional wind field. In an initial step the downscaling model is designed by selecting parameter values from practise. To a large extent, the variability of the wind at monthly timescales is found to be governed by the large scale circulation modulated by the particular orographic features of the area. The sensitivity of the downscaling methodology to the selection of the model parameter values is explored, in a second step, by performing a systematic sampling of the parameters space, avoiding a heuristic selection. This provides a metric for the uncertainty associated with the various possible model configurations. The uncertainties associated with the model configuration are considerably dependent on the spatial variability of the wind. While the sampling of the parameters space in the model set up moderately impact estimations during the calibration period, the regional wind variability is very sensitive to the parameters selection at longer timescales. This fact illustrates that downscaling exercises based on a single configuration of parameters should be interpreted with extreme caution. The downscaling model is used to extend the estimations several centuries to the past using long datasets of sea level pressure, thereby illustrating the large temporal variability of the regional wind field from interannual to multicentennial timescales. The analysis does not evidence long term trends throughout the twentieth century, however anomalous episodes of high/low wind speeds are identified

Short term prediction of the horizontal wind vector within a wake vortex warning system

Energy Technology Data Exchange (ETDEWEB)

Frech, M.; Holzaepfel, F.; Gerz, T. [DLR Deutsches Zentrum fuer Luft- und Raumfahrt e.V., Wessling (Germany). Inst. fuer Physik der Atmosphaere; Konopka, J. [Deutsche Flugsicherung (DFS) GmbH, Langen (Germany)

2000-07-14

A wake vortex warning system (WVWS) has been developed for Frankfurt airport. This airport has two parallel runways which are separated by 518 m, a distance too short to operate them independently because wake vortices may be advected to the adjacent runway. The objective of the WVWS is to enable operation with reduced separation between two aircraft approaching the parallel runways at appropriate wind conditions. The WVWS applies a statistical persistence model to predict the crosswind within a 20 minute period. One of the main problems identified in the old WVWS are discontinuities between successive forecasts. These forecast breakdowns were not acceptable to airtraffic controllers. At least part of the problem was related to the fact that the forecast was solely based on the prediction of crosswind. A new method is developed on the basis of 523 days of sonic anemometer measurements at Frankfurt airport. It is demonstrated that the prediction of the horizontal wind vector avoids these difficulties and significantly improves the system's performance. (orig.)

Wind Power Prediction using Ensembles

DEFF Research Database (Denmark)

Giebel, Gregor; Badger, Jake; Landberg, Lars

2005-01-01

offshore wind farm and the whole Jutland/Funen area. The utilities used these forecasts for maintenance planning, fuel consumption estimates and over-the-weekend trading on the Leipzig power exchange. Othernotable scientific results include the better accuracy of forecasts made up from a simple...... superposition of two NWP provider (in our case, DMI and DWD), an investigation of the merits of a parameterisation of the turbulent kinetic energy within thedelivered wind speed forecasts, and the finding that a “naïve” downscaling of each of the coarse ECMWF ensemble members with higher resolution HIRLAM did...

Using Unsupervised Machine Learning for Outlier Detection in Data to Improve Wind Power Production Prediction

OpenAIRE

Åkerberg, Ludvig

2017-01-01

The expansion of wind power for electrical energy production has increased in recent years and shows no signs of slowing down. This unpredictable source of energy has contributed to destabilization of the electrical grid causing the energy market prices to vary significantly on a daily basis. For energy producers and consumers to make good investments, methods have been developed to make predictions of wind power production. These methods are often based on machine learning were historical we...

Model predictive control of PMSG-based wind turbines for frequency regulation in an isolated grid

DEFF Research Database (Denmark)

Wang, Haixin; Yang, Junyou; Ma, Yiming

2017-01-01

This paper proposes a frequency regulation strategy applied to wind turbine generators (WTGs) in an isolated grid. In order to complement active power shortage caused by sudden load or wind speed change, an improved deloading method is proposed to solve inconsistent regulation capabilities...... in different speed regions and provide WTGs a certain capacity of power reserves. Considering the torque compensation may bring about power oscillation, speed reference of conventional pitch control system should be reset. Moreover, to suppress disturbances of load and wind speed as well as overcome dependence...... on system parameters, a model predictive controller (MPC) of wind farm is designed to generate torque compensation for each deloaded WTG. The key feature of this strategy is that each WTG reacts to grid disturbances in different ways, which depends on generator speeds. Hardware-in-the-loop simulation...

Evolution of rotating stars. III. Predicted surface rotation velocities for stars which conserve total angular momentum