WorldWideScience

Sample records for wind power forecasts

  1. Data mining for wind power forecasting

    OpenAIRE

    Fugon, Lionel; Juban, Jérémie; Kariniotakis, Georges

    2008-01-01

    International audience; Short-term forecasting of wind energy production up to 2-3 days ahead is recognized as a major contribution for reliable large-scale wind power integration. Increasing the value of wind generation through the improvement of prediction systems performance is recognised as one of the priorities in wind energy research needs for the coming years. This paper aims to evaluate Data Mining type of models for wind power forecasting. Models that are examined include neural netw...

  2. A New Reference for Wind Power Forecasting

    DEFF Research Database (Denmark)

    Nielsen, Torben Skov; Joensen, Alfred K.; Madsen, Henrik

    1998-01-01

    In recent years some research towards developing forecasting models for wind power or energy has been carried out. In order to evaluate the prediction ability of these models, the forecasts are usually compared with those of the persistence forecast model. As shown in this article, however...

  3. Forecasting winds over nuclear power plants statistics

    International Nuclear Information System (INIS)

    Marais, Ch.

    1997-01-01

    In the event of an accident at nuclear power plant, it is essential to forecast the wind velocity at the level where the efflux occurs (about 100 m). At present meteorologists refine the wind forecast from the coarse grid of numerical weather prediction (NWP) models. The purpose of this study is to improve the forecasts by developing a statistical adaptation method which corrects the NWP forecasts by using statistical comparisons between wind forecasts and observations. The Multiple Linear Regression method is used here to forecast the 100 m wind at 12 and 24 hours range for three Electricite de France (EDF) sites. It turns out that this approach gives better forecasts than the NWP model alone and is worthy of operational use. (author)

  4. Forecasting volatility of wind power production

    OpenAIRE

    Zhiwei Shen; Matthias Ritter

    2015-01-01

    Abstract: The increasing share of wind energy in the portfolio of energy sources highlights its uncertainties due to changing weather conditions. To account for the uncertainty in predicting wind power production, this article examines the volatility forecasting abilities of different GARCH-type models for wind power production. Moreover, due to characteristic features of the wind power process, such as heteroscedasticity and nonlinearity, we also investigate the use of a Markov regime-switch...

  5. The new IEA Wind Task 36 on Wind Power Forecasting

    DEFF Research Database (Denmark)

    Giebel, Gregor; Cline, Joel; Frank, Helmut

    Wind power forecasts have been used operatively for over 20 years. Despite this fact, there are still several possibilities to improve the forecasts, both from the weather prediction side and from the usage of the forecasts. The new International Energy Agency (IEA) Task on Forecasting for Wind...... Energy tries to organise international collaboration, among national weather centres with an interest and/or large projects on wind forecast improvements (NOAA, DWD, …), operational forecaster and forecast users. The Task is divided in three work packages: Firstly, a collaboration on the improvement...... forecasts, including probabilistic forecasts. This WP will also organise benchmarks, in cooperation with the IEA Task WakeBench. Thirdly, we will be engaging end users aiming at dissemination of the best practice in the usage of wind power predictions....

  6. A survey on wind power ramp forecasting.

    Energy Technology Data Exchange (ETDEWEB)

    Ferreira, C.; Gama, J.; Matias, L.; Botterud, A.; Wang, J. (Decision and Information Sciences); (INESC Porto)

    2011-02-23

    The increasing use of wind power as a source of electricity poses new challenges with regard to both power production and load balance in the electricity grid. This new source of energy is volatile and highly variable. The only way to integrate such power into the grid is to develop reliable and accurate wind power forecasting systems. Electricity generated from wind power can be highly variable at several different timescales: sub-hourly, hourly, daily, and seasonally. Wind energy, like other electricity sources, must be scheduled. Although wind power forecasting methods are used, the ability to predict wind plant output remains relatively low for short-term operation. Because instantaneous electrical generation and consumption must remain in balance to maintain grid stability, wind power's variability can present substantial challenges when large amounts of wind power are incorporated into a grid system. A critical issue is ramp events, which are sudden and large changes (increases or decreases) in wind power. This report presents an overview of current ramp definitions and state-of-the-art approaches in ramp event forecasting.

  7. Short time ahead wind power production forecast

    International Nuclear Information System (INIS)

    Sapronova, Alla; Meissner, Catherine; Mana, Matteo

    2016-01-01

    An accurate prediction of wind power output is crucial for efficient coordination of cooperative energy production from different sources. Long-time ahead prediction (from 6 to 24 hours) of wind power for onshore parks can be achieved by using a coupled model that would bridge the mesoscale weather prediction data and computational fluid dynamics. When a forecast for shorter time horizon (less than one hour ahead) is anticipated, an accuracy of a predictive model that utilizes hourly weather data is decreasing. That is because the higher frequency fluctuations of the wind speed are lost when data is averaged over an hour. Since the wind speed can vary up to 50% in magnitude over a period of 5 minutes, the higher frequency variations of wind speed and direction have to be taken into account for an accurate short-term ahead energy production forecast. In this work a new model for wind power production forecast 5- to 30-minutes ahead is presented. The model is based on machine learning techniques and categorization approach and using the historical park production time series and hourly numerical weather forecast. (paper)

  8. Wind power forecasting: IEA Wind Task 36 & future research issues

    DEFF Research Database (Denmark)

    Giebel, Gregor; Cline, J.; Frank, Helmut Paul

    2016-01-01

    , MetOffice, met.no, DMI,...), operational forecaster and forecast users.The Task is divided in three work packages: Firstly, a collaboration on the improvement of the scientific basis for the wind predictions themselves. This includes numerical weather prediction model physics, but also widely......Bench. Thirdly, we will be engaging end users aiming at dissemination of the best practice in the usage of wind power predictions. As first results, an overview of current issues for research in short-term forecasting of wind power is presented....

  9. Sharing wind power forecasts in electricity markets: A numerical analysis

    DEFF Research Database (Denmark)

    Exizidis, Lazaros; Pinson, Pierre; Kazempour, Jalal

    2016-01-01

    In an electricity pool with significant share of wind power, all generators including conventional and wind power units are generally scheduled in a day-ahead market based on wind power forecasts. Then, a real-time market is cleared given the updated wind power forecast and fixed day-ahead decisi...

  10. Direct Interval Forecasting of Wind Power

    DEFF Research Database (Denmark)

    Wan, Can; Xu, Zhao; Pinson, Pierre

    2013-01-01

    This letter proposes a novel approach to directly formulate the prediction intervals of wind power generation based on extreme learning machine and particle swarm optimization, where prediction intervals are generated through direct optimization of both the coverage probability and sharpness, wit......, without the prior knowledge of forecasting errors. The proposed approach has been proved to be highly efficient and reliable through preliminary case studies using real-world wind farm data, indicating a high potential of practical application.......This letter proposes a novel approach to directly formulate the prediction intervals of wind power generation based on extreme learning machine and particle swarm optimization, where prediction intervals are generated through direct optimization of both the coverage probability and sharpness...

  11. Utility operating strategy and requirements for wind power forecast

    Science.gov (United States)

    Dub, W.; Pape, H.

    1983-06-01

    The commitment of a generation system including wind energy conversion systems will be based on wind speed and wind power forecasts. Forecasts for time spans of equal length with the startup/shutdown times of conventional units will be of great importance. The paper discusses forecast horizons up to 3 hours and 6 hours respectively. In addition, the problem of getting good wind speed forecasts is investigated by fitting time series models to wind speed data. Finally, the impact of hypothetical perfect forecasts on the commitment of intermediate load units is demonstrated by means of the wind power variations within spans up to 3 hours.

  12. 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

  13. 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

  14. Probabilistic Wind Power Forecasting with Hybrid Artificial Neural Networks

    DEFF Research Database (Denmark)

    Wan, Can; Song, Yonghua; Xu, Zhao

    2016-01-01

    The uncertainty of wind power generation imposes significant challenges to optimal operation and control of electricity networks with increasing wind power penetration. To effectively address the uncertainties in wind power forecasts, probabilistic forecasts that can quantify the associated...... via a bootstrap technique. Subsequently, the maximum likelihood estimation method is employed to construct a distinct neural network to estimate the noise variance of forecasting results. The proposed approach has been tested on multi-step forecasting of high-resolution (10-min) wind power using...... actual wind power data from Denmark. The numerical results demonstrate that the proposed hybrid artificial neural network approach is effective and efficient for probabilistic forecasting of wind power and has high potential in practical applications....

  15. On probabilistic forecasting of wind power time-series

    DEFF Research Database (Denmark)

    Pinson, Pierre

    Wind power generation is a nonlinear and bounded variable, partly owing to the power curve that converts wind to electric power, and partly owing to the very stochastic nature of wind itself. Predictive densities of wind power generation should account for that effect. Such densities are clearly...... power dynamics. In both cases, the model parameters are adaptively and recursively estimated, time-adaptativity being the result of exponential forgetting of past observations. The probabilistic forecasting methodology is applied at the Horns Rev wind farm in Denmark, for 10-minute ahead probabilistic...... forecasting of wind power generation. Probabilistic forecasts generated from the proposed methodology clearly have higher skill than those obtained from a classical Gaussian assumption about wind power predictive densities. Corresponding point forecasts also exhibit significantly lower error criteria....

  16. Wind Power Forecasting Error Distributions: An International Comparison; Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Hodge, B. M.; Lew, D.; Milligan, M.; Holttinen, H.; Sillanpaa, S.; Gomez-Lazaro, E.; Scharff, R.; Soder, L.; Larsen, X. G.; Giebel, G.; Flynn, D.; Dobschinski, J.

    2012-09-01

    Wind power forecasting is expected to be an important enabler for greater penetration of wind power into electricity systems. Because no wind forecasting system is perfect, a thorough understanding of the errors that do occur can be critical to system operation functions, such as the setting of operating reserve levels. This paper provides an international comparison of the distribution of wind power forecasting errors from operational systems, based on real forecast data. The paper concludes with an assessment of similarities and differences between the errors observed in different locations.

  17. Wind Power Forecasting Error Distributions: An International Comparison

    DEFF Research Database (Denmark)

    Hodge, Bri-Mathias; Lew, Debra; Milligan, Michael

    2012-01-01

    Wind power forecasting is essential for greater penetration of wind power into electricity systems. Because no wind forecasting system is perfect, a thorough understanding of the errors that may occur is a critical factor for system operation functions, such as the setting of operating reserve...... levels. This paper provides an international comparison of the distribution of wind power forecasting errors from operational systems, based on real forecast data. The paper concludes with an assessment of similarities and differences between the errors observed in different locations....

  18. Effective Short-term Forecasting of Wind Farms Power

    Directory of Open Access Journals (Sweden)

    Elżbieta Bogalecka

    2015-09-01

    Full Text Available Forecasting a specific wind farm’s (WF generation capacity within a 24 hour perspective requires both a reliable forecast of wind, as well as supporting tools. This tool is a dedicated model of wind farm power. This model should include not only general rules of wind to mechanical energy conversion, but also the farm’s specific features. There are many factors that influence a farm’s generation capacity, and any forecast of it, even with an accurate weather forecast, carries error. This paper presents analytical, statistical, and neuron models of wind farm power. The study is based on data from a real wind farm. Most attention is paid to the neuron models, due to a neuron network’s capability to restore farm-specific details. The research aims to answer the headline question: whether and to what extent a wind farm’s power can be forecast short-term?

  19. Probabilistic forecasting of wind power generation using extreme learning machine

    DEFF Research Database (Denmark)

    Wan, Can; Xu, Zhao; Pinson, Pierre

    2014-01-01

    Accurate and reliable forecast of wind power is essential to power system operation and control. However, due to the nonstationarity of wind power series, traditional point forecasting can hardly be accurate, leading to increased uncertainties and risks for system operation. This paper proposes...... an extreme learning machine (ELM)-based probabilistic forecasting method for wind power generation. To account for the uncertainties in the forecasting results, several bootstrapmethods have been compared for modeling the regression uncertainty, based on which the pairs bootstrap method is identified...... with the best performance. Consequently, a new method for prediction intervals formulation based on theELMand the pairs bootstrap is developed.Wind power forecasting has been conducted in different seasons using the proposed approach with the historical wind power time series as the inputs alone. The results...

  20. INFERENCE AND SENSITIVITY IN STOCHASTIC WIND POWER FORECAST MODELS.

    KAUST Repository

    Elkantassi, Soumaya

    2017-10-03

    Reliable forecasting of wind power generation is crucial to optimal control of costs in generation of electricity with respect to the electricity demand. Here, we propose and analyze stochastic wind power forecast models described by parametrized stochastic differential equations, which introduce appropriate fluctuations in numerical forecast outputs. We use an approximate maximum likelihood method to infer the model parameters taking into account the time correlated sets of data. Furthermore, we study the validity and sensitivity of the parameters for each model. We applied our models to Uruguayan wind power production as determined by historical data and corresponding numerical forecasts for the period of March 1 to May 31, 2016.

  1. Short-Term Wind Speed Forecasting for Power System Operations

    KAUST Repository

    Zhu, Xinxin

    2012-04-01

    The emphasis on renewable energy and concerns about the environment have led to large-scale wind energy penetration worldwide. However, there are also significant challenges associated with the use of wind energy due to the intermittent and unstable nature of wind. High-quality short-term wind speed forecasting is critical to reliable and secure power system operations. This article begins with an overview of the current status of worldwide wind power developments and future trends. It then reviews some statistical short-term wind speed forecasting models, including traditional time series approaches and more advanced space-time statistical models. It also discusses the evaluation of forecast accuracy, in particular, the need for realistic loss functions. New challenges in wind speed forecasting regarding ramp events and offshore wind farms are also presented. © 2012 The Authors. International Statistical Review © 2012 International Statistical Institute.

  2. 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...

  3. The economic value of accurate wind power forecasting to utilities

    Energy Technology Data Exchange (ETDEWEB)

    Watson, S.J. [Rutherford Appleton Lab., Oxfordshire (United Kingdom); Giebel, G.; Joensen, A. [Risoe National Lab., Dept. of Wind Energy and Atmospheric Physics, Roskilde (Denmark)

    1999-03-01

    With increasing penetrations of wind power, the need for accurate forecasting is becoming ever more important. Wind power is by its very nature intermittent. For utility schedulers this presents its own problems particularly when the penetration of wind power capacity in a grid reaches a significant level (>20%). However, using accurate forecasts of wind power at wind farm sites, schedulers are able to plan the operation of conventional power capacity to accommodate the fluctuating demands of consumers and wind farm output. The results of a study to assess the value of forecasting at several potential wind farm sites in the UK and in the US state of Iowa using the Reading University/Rutherford Appleton Laboratory National Grid Model (NGM) are presented. The results are assessed for different types of wind power forecasting, namely: persistence, optimised numerical weather prediction or perfect forecasting. In particular, it will shown how the NGM has been used to assess the value of numerical weather prediction forecasts from the Danish Meteorological Institute model, HIRLAM, and the US Nested Grid Model, which have been `site tailored` by the use of the linearized flow model WA{sup s}P and by various Model output Statistics (MOS) and autoregressive techniques. (au)

  4. Wind power forecasting accuracy and uncertainty in Finland

    Energy Technology Data Exchange (ETDEWEB)

    Holttinen, H.; Miettinen, J.; Sillanpaeae, S.

    2013-04-15

    Wind power cannot be dispatched so the production levels need to be forecasted for electricity market trading. Lower prediction errors mean lower regulation balancing costs, since relatively less energy needs to go through balance settlement. From the power system operator point of view, wind power forecast errors will impact the system net imbalances when the share of wind power increases, and more accurate forecasts mean less regulating capacity will be activated from the real time Regulating Power Market. In this publication short term forecasting of wind power is studied mainly from a wind power producer point of view. The forecast errors and imbalance costs from the day-ahead Nordic electricity markets are calculated based on real data from distributed wind power plants. Improvements to forecasting accuracy are presented using several wind forecast providers, and measures for uncertainty of the forecast are presented. Aggregation of sites lowers relative share of prediction errors considerably, up to 60%. The balancing costs were also reduced up to 60%, from 3 euro/MWh for one site to 1-1.4 euro/MWh to aggregate 24 sites. Pooling wind power production for balance settlement will be very beneficial, and larger producers who can have sites from larger geographical area will benefit in lower imbalance costs. The aggregation benefits were already significant for smaller areas, resulting in 30-40% decrease in forecast errors and 13-36% decrease in unit balancing costs, depending on the year. The resulting costs are strongly dependent on Regulating Market prices that determine the prices for the imbalances. Similar level of forecast errors resulted in 40% higher imbalance costs for 2012 compared with 2011. Combining wind forecasts from different Numerical Weather Prediction providers was studied with different combination methods for 6 sites. Averaging different providers' forecasts will lower the forecast errors by 6% for day-ahead purposes. When combining

  5. Use of wind power forecasting in operational decisions.

    Energy Technology Data Exchange (ETDEWEB)

    Botterud, A.; Zhi, Z.; Wang, J.; Bessa, R.J.; Keko, H.; Mendes, J.; Sumaili, J.; Miranda, V. (Decision and Information Sciences); (INESC Porto)

    2011-11-29

    The rapid expansion of wind power gives rise to a number of challenges for power system operators and electricity market participants. The key operational challenge is to efficiently handle the uncertainty and variability of wind power when balancing supply and demand in ths system. In this report, we analyze how wind power forecasting can serve as an efficient tool toward this end. We discuss the current status of wind power forecasting in U.S. electricity markets and develop several methodologies and modeling tools for the use of wind power forecasting in operational decisions, from the perspectives of the system operator as well as the wind power producer. In particular, we focus on the use of probabilistic forecasts in operational decisions. Driven by increasing prices for fossil fuels and concerns about greenhouse gas (GHG) emissions, wind power, as a renewable and clean source of energy, is rapidly being introduced into the existing electricity supply portfolio in many parts of the world. The U.S. Department of Energy (DOE) has analyzed a scenario in which wind power meets 20% of the U.S. electricity demand by 2030, which means that the U.S. wind power capacity would have to reach more than 300 gigawatts (GW). The European Union is pursuing a target of 20/20/20, which aims to reduce greenhouse gas (GHG) emissions by 20%, increase the amount of renewable energy to 20% of the energy supply, and improve energy efficiency by 20% by 2020 as compared to 1990. Meanwhile, China is the leading country in terms of installed wind capacity, and had 45 GW of installed wind power capacity out of about 200 GW on a global level at the end of 2010. The rapid increase in the penetration of wind power into power systems introduces more variability and uncertainty in the electricity generation portfolio, and these factors are the key challenges when it comes to integrating wind power into the electric power grid. Wind power forecasting (WPF) is an important tool to help

  6. Short-term wind power combined forecasting based on error forecast correction

    International Nuclear Information System (INIS)

    Liang, Zhengtang; Liang, Jun; Wang, Chengfu; Dong, Xiaoming; Miao, Xiaofeng

    2016-01-01

    Highlights: • The correlation relationships of short-term wind power forecast errors are studied. • The correlation analysis method of the multi-step forecast errors is proposed. • A strategy selecting the input variables for the error forecast models is proposed. • Several novel combined models based on error forecast correction are proposed. • The combined models have improved the short-term wind power forecasting accuracy. - Abstract: With the increasing contribution of wind power to electric power grids, accurate forecasting of short-term wind power has become particularly valuable for wind farm operators, utility operators and customers. The aim of this study is to investigate the interdependence structure of errors in short-term wind power forecasting that is crucial for building error forecast models with regression learning algorithms to correct predictions and improve final forecasting accuracy. In this paper, several novel short-term wind power combined forecasting models based on error forecast correction are proposed in the one-step ahead, continuous and discontinuous multi-step ahead forecasting modes. First, the correlation relationships of forecast errors of the autoregressive model, the persistence method and the support vector machine model in various forecasting modes have been investigated to determine whether the error forecast models can be established by regression learning algorithms. Second, according to the results of the correlation analysis, the range of input variables is defined and an efficient strategy for selecting the input variables for the error forecast models is proposed. Finally, several combined forecasting models are proposed, in which the error forecast models are based on support vector machine/extreme learning machine, and correct the short-term wind power forecast values. The data collected from a wind farm in Hebei Province, China, are selected as a case study to demonstrate the effectiveness of the proposed

  7. A General Probabilistic Forecasting Framework for Offshore Wind Power Fluctuations

    DEFF Research Database (Denmark)

    Trombe, Pierre-Julien; Pinson, Pierre; Madsen, Henrik

    2012-01-01

    Accurate wind power forecasts highly contribute to the integration of wind power into power systems. The focus of the present study is on large-scale offshore wind farms and the complexity of generating accurate probabilistic forecasts of wind power fluctuations at time-scales of a few minutes...... fluctuations are characterized by highly volatile dynamics which are difficult to capture and predict. Due to the lack of adequate on-site meteorological observations to relate these dynamics to meteorological phenomena, we propose a general model formulation based on a statistical approach and historical wind...... power measurements only. We introduce an advanced Markov Chain Monte Carlo (MCMC) estimation method to account for the different features observed in an empirical time series of wind power: autocorrelation, heteroscedasticity and regime-switching. The model we propose is an extension of Markov...

  8. Sharing wind power forecasts in electricity markets: A numerical analysis

    International Nuclear Information System (INIS)

    Exizidis, Lazaros; Kazempour, S. Jalal; Pinson, Pierre; Greve, Zacharie de; Vallée, François

    2016-01-01

    Highlights: • Information sharing among different agents can be beneficial for electricity markets. • System cost decreases by sharing wind power forecasts between different agents. • Market power of wind producer may increase by sharing forecasts with market operator. • Extensive out-of-sample analysis is employed to draw reliable conclusions. - Abstract: In an electricity pool with significant share of wind power, all generators including conventional and wind power units are generally scheduled in a day-ahead market based on wind power forecasts. Then, a real-time market is cleared given the updated wind power forecast and fixed day-ahead decisions to adjust power imbalances. This sequential market-clearing process may cope with serious operational challenges such as severe power shortage in real-time due to erroneous wind power forecasts in day-ahead market. To overcome such situations, several solutions can be considered such as adding flexible resources to the system. In this paper, we address another potential solution based on information sharing in which market players share their own wind power forecasts with others in day-ahead market. This solution may improve the functioning of sequential market-clearing process through making more informed day-ahead schedules, which reduces the need for balancing resources in real-time operation. This paper numerically evaluates the potential value of sharing forecasts for the whole system in terms of system cost reduction. Besides, its impact on each market player’s profit is analyzed. The framework of this study is based on a stochastic two-stage market setup and complementarity modeling, which allows us to gain further insights into information sharing impacts.

  9. Forecast of wind energy production and ensuring required balancing power

    International Nuclear Information System (INIS)

    Merkulov, M.

    2010-01-01

    The wind energy is gaining larger part of the energy mix around the world as well as in Bulgaria. Having in mind the irregularity of the wind, we are in front of a challenge for management of the power grid in new unknown conditions. The world's experience has proven that there could be no effective management of the grid without forecasting tools, even with small scale of wind power penetration. Application of such tools promotes simple management of large wind energy production and reduction of the quantities of required balancing powers. The share of the expenses and efforts for forecasting of the wind energy is incomparably small in comparison with expenses for keeping additional powers in readiness. The recent computers potential allow simple and rapid processing of large quantities of data from different sources, which provides required conditions for modeling the world's climate and producing sophisticated forecast. (author)

  10. Forecasting wind power production from a wind farm using the RAMS model

    DEFF Research Database (Denmark)

    Tiriolo, L.; Torcasio, R. C.; Montesanti, S.

    2015-01-01

    The importance of wind power forecast is commonly recognized because it represents a useful tool for grid integration and facilitates the energy trading. This work considers an example of power forecast for a wind farm in the Apennines in Central Italy. The orography around the site is complex...... and the horizontal resolution of the wind forecast has an important role. To explore this point we compared the performance of two 48 h wind power forecasts using the winds predicted by the Regional Atmospheric Modeling System (RAMS) for the year 2011. The two forecasts differ only for the horizontal resolution...... of the ECMWF Integrated Forecasting System (IFS), whose horizontal resolution over Central Italy is about 25 km at the time considered in this paper. Because wind observations were not available for the site, the power curve for the whole wind farm was derived from the ECMWF wind operational analyses available...

  11. Quantile Forecasting of Wind Power Using Variability Indices

    Directory of Open Access Journals (Sweden)

    Patrick McSharry

    2013-02-01

    Full Text Available Wind power forecasting techniques have received substantial attention recently due to the increasing penetration of wind energy in national power systems. While the initial focus has been on point forecasts, the need to quantify forecast uncertainty and communicate the risk of extreme ramp events has led to an interest in producing probabilistic forecasts. Using four years of wind power data from three wind farms in Denmark, we develop quantile regression models to generate short-term probabilistic forecasts from 15 min up to six hours ahead. More specifically, we investigate the potential of using various variability indices as explanatory variables in order to include the influence of changing weather regimes. These indices are extracted from the same wind power series and optimized specifically for each quantile. The forecasting performance of this approach is compared with that of appropriate benchmark models. Our results demonstrate that variability indices can increase the overall skill of the forecasts and that the level of improvement depends on the specific quantile.

  12. Short-Term Wind Power Interval Forecasting Based on an EEMD-RT-RVM Model

    OpenAIRE

    Haixiang Zang; Lei Fan; Mian Guo; Zhinong Wei; Guoqiang Sun; Li Zhang

    2016-01-01

    Accurate short-term wind power forecasting is important for improving the security and economic success of power grids. Existing wind power forecasting methods are mostly types of deterministic point forecasting. Deterministic point forecasting is vulnerable to forecasting errors and cannot effectively deal with the random nature of wind power. In order to solve the above problems, we propose a short-term wind power interval forecasting model based on ensemble empirical mode decomposition (EE...

  13. Development and testing of improved statistical wind power forecasting methods.

    Energy Technology Data Exchange (ETDEWEB)

    Mendes, J.; Bessa, R.J.; Keko, H.; Sumaili, J.; Miranda, V.; Ferreira, C.; Gama, J.; Botterud, A.; Zhou, Z.; Wang, J. (Decision and Information Sciences); (INESC Porto)

    2011-12-06

    Wind power forecasting (WPF) provides important inputs to power system operators and electricity market participants. It is therefore not surprising that WPF has attracted increasing interest within the electric power industry. In this report, we document our research on improving statistical WPF algorithms for point, uncertainty, and ramp forecasting. Below, we provide a brief introduction to the research presented in the following chapters. For a detailed overview of the state-of-the-art in wind power forecasting, we refer to [1]. Our related work on the application of WPF in operational decisions is documented in [2]. Point forecasts of wind power are highly dependent on the training criteria used in the statistical algorithms that are used to convert weather forecasts and observational data to a power forecast. In Chapter 2, we explore the application of information theoretic learning (ITL) as opposed to the classical minimum square error (MSE) criterion for point forecasting. In contrast to the MSE criterion, ITL criteria do not assume a Gaussian distribution of the forecasting errors. We investigate to what extent ITL criteria yield better results. In addition, we analyze time-adaptive training algorithms and how they enable WPF algorithms to cope with non-stationary data and, thus, to adapt to new situations without requiring additional offline training of the model. We test the new point forecasting algorithms on two wind farms located in the U.S. Midwest. Although there have been advancements in deterministic WPF, a single-valued forecast cannot provide information on the dispersion of observations around the predicted value. We argue that it is essential to generate, together with (or as an alternative to) point forecasts, a representation of the wind power uncertainty. Wind power uncertainty representation can take the form of probabilistic forecasts (e.g., probability density function, quantiles), risk indices (e.g., prediction risk index) or scenarios

  14. Estimation of the uncertainty in wind power forecasting

    International Nuclear Information System (INIS)

    Pinson, P.

    2006-03-01

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

  15. TradeWind Deliverable 2.2: Forecast error of aggregated wind power

    DEFF Research Database (Denmark)

    Giebel, Gregor; Sørensen, Poul Ejnar; Holttinen, Hannele

    2007-01-01

    This report is written in fulfilment of Task 2.3 in the TradeWind project (EU sponsored, under the Intelligent Energy Europe initiative): Wind Power Integration and Exchange in the Trans-European Power Market. The Task description is as follows: Task 2.3: Forecast error of aggregated wind power...... Estimates of forecast error of aggregated production for time horizons of intraday and dayahead markets in future will be produced. This will be done by reference to published studies of forecasting for wind generation, and from internal knowledge of WP2 participants. Modelling of wind power fluctuations...

  16. Forecasting for Wind Power Plants in Quebec, Canada

    Science.gov (United States)

    Dyck, Sarah

    2010-05-01

    The SPEO project (Système de Prévisions ÉOlienne) is a collaborative research effort between Environment Canada (EC) and Hydro-Québec (HQ) and has been in operation since May of 2007. It provides a 48 hour high resolution (2.5 km) wind forecast, four times daily, in order to assist in the successful management of wind power from plants in the Gaspé Region of Québec, Canada. Early in 2010, the number of forecasts increased to four times a day. The Canadian Global Environmental Multiscale-Limited Area Model (GEM-LAM), at the heart of this system, is driven by the operational regional forecasts at 15 km resolution from the Canadian Meteorological Centre. This system has been evaluated using observations from EC meteorological stations and special masts installed at wind power plants and the results will be discussed. Specifically, an effort was made to examine the predictability of rare events critical in the operations of wind power plants such as strong winds and high atmospheric turbulence, which can force wind turbines to shut down. Future research for the improvement of this forecasting system will also be presented.

  17. Introducing distributed learning approaches in wind power forecasting

    DEFF Research Database (Denmark)

    Pinson, Pierre

    2016-01-01

    Renewable energy forecasting is now of core interest to both academics, who continuously propose new forecast methodologies, and forecast users for optimal operations and participation in electricity markets. In view of the increasing amount of data being collected at power generation sites, thanks...... to substantial deployment of generating capacities and increased temporal resolution, it may now be possible to build large models accounting for all space-time dependencies. This will eventually allow to significantly improve the quality of short-term renewable power forecasts. However, in practice, it is often...... to large datasets in Australia (22 wind farms) and France (85 wind farms) are used to illustrate the interest and performance of our proposal....

  18. Accurate Short-Term Power Forecasting of Wind Turbines: The Case of Jeju Island’s Wind Farm

    OpenAIRE

    BeomJun Park; Jin Hur

    2017-01-01

    Short-term wind power forecasting is a technique which tells system operators how much wind power can be expected at a specific time. Due to the increasing penetration of wind generating resources into the power grids, short-term wind power forecasting is becoming an important issue for grid integration analysis. The high reliability of wind power forecasting can contribute to the successful integration of wind generating resources into the power grids. To guarantee the reliability of forecas...

  19. Evaluation of Nonparametric Probabilistic Forecasts of Wind Power

    DEFF Research Database (Denmark)

    Pinson, Pierre; Møller, Jan Kloppenborg; Nielsen, Henrik Aalborg, orlov 31.07.2008

    Predictions of wind power production for horizons up to 48-72 hour ahead comprise a highly valuable input to the methods for the daily management or trading of wind generation. Today, users of wind power predictions are not only provided with point predictions, which are estimates of the most...... likely outcome for each look-ahead time, but also with uncertainty estimates given by probabilistic forecasts. In order to avoid assumptions on the shape of predictive distributions, these probabilistic predictions are produced from nonparametric methods, and then take the form of a single or a set...

  20. 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

  1. Powering Up With Space-Time Wind Forecasting

    KAUST Repository

    Hering, Amanda S.

    2010-03-01

    The technology to harvest electricity from wind energy is now advanced enough to make entire cities powered by it a reality. High-quality, short-term forecasts of wind speed are vital to making this a more reliable energy source. Gneiting et al. (2006) have introduced a model for the average wind speed two hours ahead based on both spatial and temporal information. The forecasts produced by this model are accurate, and subject to accuracy, the predictive distribution is sharp, that is, highly concentrated around its center. However, this model is split into nonunique regimes based on the wind direction at an offsite location. This paper both generalizes and improves upon this model by treating wind direction as a circular variable and including it in the model. It is robust in many experiments, such as predicting wind at other locations. We compare this with the more common approach of modeling wind speeds and directions in the Cartesian space and use a skew-t distribution for the errors. The quality of the predictions from all of these models can be more realistically assessed with a loss measure that depends upon the power curve relating wind speed to power output. This proposed loss measure yields more insight into the true value of each models predictions. © 2010 American Statistical Association.

  2. A General Probabilistic Forecasting Framework for Offshore Wind Power Fluctuations

    Directory of Open Access Journals (Sweden)

    Henrik Madsen

    2012-03-01

    Full Text Available Accurate wind power forecasts highly contribute to the integration of wind power into power systems. The focus of the present study is on large-scale offshore wind farms and the complexity of generating accurate probabilistic forecasts of wind power fluctuations at time-scales of a few minutes. Such complexity is addressed from three perspectives: (i the modeling of a nonlinear and non-stationary stochastic process; (ii the practical implementation of the model we proposed; (iii the gap between working on synthetic data and real world observations. At time-scales of a few minutes, offshore fluctuations are characterized by highly volatile dynamics which are difficult to capture and predict. Due to the lack of adequate on-site meteorological observations to relate these dynamics to meteorological phenomena, we propose a general model formulation based on a statistical approach and historical wind power measurements only. We introduce an advanced Markov Chain Monte Carlo (MCMC estimation method to account for the different features observed in an empirical time series of wind power: autocorrelation, heteroscedasticity and regime-switching. The model we propose is an extension of Markov-Switching Autoregressive (MSAR models with Generalized AutoRegressive Conditional Heteroscedastic (GARCH errors in each regime to cope with the heteroscedasticity. Then, we analyze the predictive power of our model on a one-step ahead exercise of time series sampled over 10 min intervals. Its performances are compared to state-of-the-art models and highlight the interest of including a GARCH specification for density forecasts.

  3. Using ensemble NWP wind power forecasts to improve national power system management

    Science.gov (United States)

    Cannon, D.; Brayshaw, D.; Methven, J.; Coker, P.; Lenaghan, D.

    2014-12-01

    National power systems are becoming increasingly sensitive to atmospheric variability as generation from wind (and other renewables) increases. As such, the days-ahead predictability of wind power has significant implications for power system management. At this time horizon, power system operators plan transmission line outages for maintenance. In addition, forecast users begin to form backup strategies to account for the uncertainty in wind power predictions. Under-estimating this uncertainty could result in a failure to meet system security standards, or in the worst instance, a shortfall in total electricity supply. On the other hand, overly conservative assumptions about the forecast uncertainty incur costs associated with the unnecessary holding of reserve power. Using the power system of Great Britain (GB) as an example, we construct time series of GB-total wind power output using wind speeds from either reanalyses or global weather forecasts. To validate the accuracy of these data sets, wind power reconstructions using reanalyses and forecast analyses over a recent period are compared to measured GB-total power output. The results are found to be highly correlated on time scales greater than around 6 hours. Results are presented using ensemble wind power forecasts from several national and international forecast centres (obtained through TIGGE). Firstly, the skill with which global ensemble forecasts can represent the uncertainty in the GB-total power output at up to 10 days ahead is quantified. Following this, novel ensemble forecast metrics are developed to improve estimates of forecast uncertainty within the context of power system operations, thus enabling the development of more cost effective strategies. Finally, the predictability of extreme events such as prolonged low wind periods or rapid changes in wind power output are examined in detail. These events, if poorly forecast, induce high stress scenarios that could threaten the security of the power

  4. 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......-varying regression model. In a second step, time-series models, i.e., ARMA and Holt–Winters, are applied to account for residual autocorrelation and seasonal dynamics. Empirical results are presented for out-of-sample forecasts of day-ahead prices in the Western Danish price area of Nord Pool's Elspot, during a two...

  5. Wind Power Forecasting Error Frequency Analyses for Operational Power System Studies: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Florita, A.; Hodge, B. M.; Milligan, M.

    2012-08-01

    The examination of wind power forecasting errors is crucial for optimal unit commitment and economic dispatch of power systems with significant wind power penetrations. This scheduling process includes both renewable and nonrenewable generators, and the incorporation of wind power forecasts will become increasingly important as wind fleets constitute a larger portion of generation portfolios. This research considers the Western Wind and Solar Integration Study database of wind power forecasts and numerical actualizations. This database comprises more than 30,000 locations spread over the western United States, with a total wind power capacity of 960 GW. Error analyses for individual sites and for specific balancing areas are performed using the database, quantifying the fit to theoretical distributions through goodness-of-fit metrics. Insights into wind-power forecasting error distributions are established for various levels of temporal and spatial resolution, contrasts made among the frequency distribution alternatives, and recommendations put forth for harnessing the results. Empirical data are used to produce more realistic site-level forecasts than previously employed, such that higher resolution operational studies are possible. This research feeds into a larger work of renewable integration through the links wind power forecasting has with various operational issues, such as stochastic unit commitment and flexible reserve level determination.

  6. Leveraging stochastic differential equations for probabilistic forecasting of wind power using a dynamic power curve

    DEFF Research Database (Denmark)

    Iversen, Jan Emil Banning; Morales González, Juan Miguel; Møller, Jan Kloppenborg

    2017-01-01

    Short-term (hours to days) probabilistic forecasts of wind power generation provide useful information about the associated uncertainty of these forecasts. Standard probabilistic forecasts are usually issued on a per-horizon-basis, meaning that they lack information about the development of the u...

  7. Wind power forecasting : state-of-the-art 2009.

    Energy Technology Data Exchange (ETDEWEB)

    Monteiro, C.; Bessa, R.; Miranda, V.; Botterud, A.; Wang, J.; Conzelmann, G.; Decision and Information Sciences; INESC Porto

    2009-11-20

    Many countries and regions are introducing policies aimed at reducing the environmental footprint from the energy sector and increasing the use of renewable energy. In the United States, a number of initiatives have been taken at the state level, from renewable portfolio standards (RPSs) and renewable energy certificates (RECs), to regional greenhouse gas emission control schemes. Within the U.S. Federal government, new energy and environmental policies and goals are also being crafted, and these are likely to increase the use of renewable energy substantially. The European Union is pursuing implementation of its ambitious 20/20/20 targets, which aim (by 2020) to reduce greenhouse gas emissions by 20% (as compared to 1990), increase the amount of renewable energy to 20% of the energy supply, and reduce the overall energy consumption by 20% through energy efficiency. With the current focus on energy and the environment, efficient integration of renewable energy into the electric power system is becoming increasingly important. In a recent report, the U.S. Department of Energy (DOE) describes a model-based scenario, in which wind energy provides 20% of the U.S. electricity demand in 2030. The report discusses a set of technical and economic challenges that have to be overcome for this scenario to unfold. In Europe, several countries already have a high penetration of wind power (i.e., in the range of 7 to 20% of electricity consumption in countries such as Germany, Spain, Portugal, and Denmark). The rapid growth in installed wind power capacity is expected to continue in the United States as well as in Europe. A large-scale introduction of wind power causes a number of challenges for electricity market and power system operators who will have to deal with the variability and uncertainty in wind power generation when making their scheduling and dispatch decisions. Wind power forecasting (WPF) is frequently identified as an important tool to address the variability and

  8. Trading wind generation from short-term probabilistic forecasts of wind power

    DEFF Research Database (Denmark)

    Pinson, Pierre; Chevallier, Christophe; Kariniotakis, Georges

    2007-01-01

    Due to the fluctuating nature of the wind resource, a wind power producer participating in a liberalized electricity market is subject to penalties related to regulation costs. Accurate forecasts of wind generation are therefore paramount for reducing such penalties and thus maximizing revenue...... participation. Such strategies permit to further increase revenues and thus enhance competitiveness of wind generation compared to other forms of dispatchable generation. This paper formulates a general methodology for deriving optimal bidding strategies based on probabilistic forecasts of wind generation....... Despite the fact that increasing accuracy in spot forecasts may reduce penalties, this paper shows that, if such forecasts are accompanied with information on their uncertainty, i.e., in the form of predictive distributions, then this can be the basis for defining advanced strategies for market...

  9. Scaling forecast models for wind turbulence and wind turbine power intermittency

    Science.gov (United States)

    Duran Medina, Olmo; Schmitt, Francois G.; Calif, Rudy

    2017-04-01

    The intermittency of the wind turbine power remains an important issue for the massive development of this renewable energy. The energy peaks injected in the electric grid produce difficulties in the energy distribution management. Hence, a correct forecast of the wind power in the short and middle term is needed due to the high unpredictability of the intermittency phenomenon. We consider a statistical approach through the analysis and characterization of stochastic fluctuations. The theoretical framework is the multifractal modelisation of wind velocity fluctuations. Here, we consider three wind turbine data where two possess a direct drive technology. Those turbines are producing energy in real exploitation conditions and allow to test our forecast models of power production at a different time horizons. Two forecast models were developed based on two physical principles observed in the wind and the power time series: the scaling properties on the one hand and the intermittency in the wind power increments on the other. The first tool is related to the intermittency through a multifractal lognormal fit of the power fluctuations. The second tool is based on an analogy of the power scaling properties with a fractional brownian motion. Indeed, an inner long-term memory is found in both time series. Both models show encouraging results since a correct tendency of the signal is respected over different time scales. Those tools are first steps to a search of efficient forecasting approaches for grid adaptation facing the wind energy fluctuations.

  10. Short-term spatio-temporal wind power forecast in robust look-ahead power system dispatch

    KAUST Repository

    Xie, Le

    2014-01-01

    We propose a novel statistical wind power forecast framework, which leverages the spatio-temporal correlation in wind speed and direction data among geographically dispersed wind farms. Critical assessment of the performance of spatio-temporal wind power forecast is performed using realistic wind farm data from West Texas. It is shown that spatio-temporal wind forecast models are numerically efficient approaches to improving forecast quality. By reducing uncertainties in near-term wind power forecasts, the overall cost benefits on system dispatch can be quantified. We integrate the improved forecast with an advanced robust look-ahead dispatch framework. This integrated forecast and economic dispatch framework is tested in a modified IEEE RTS 24-bus system. Numerical simulation suggests that the overall generation cost can be reduced by up to 6% using a robust look-ahead dispatch coupled with spatio-temporal wind forecast as compared with persistent wind forecast models. © 2013 IEEE.

  11. Simulation of Wind-Battery Microgrid Based on Short-Term Wind Power Forecasting

    Directory of Open Access Journals (Sweden)

    Konstantinos N. Genikomsakis

    2017-11-01

    Full Text Available The inherently intermittent and highly variable nature of wind necessitates the use of wind power forecasting tools in order to facilitate the integration of wind turbines in microgrids, among others. In this direction, the present paper describes the development of a short-term wind power forecasting model based on artificial neural network (ANN clustering, which uses statistical feature parameters in the input vector, as well as an enhanced version of this approach that adjusts the ANN output with the probability of lower misclassification (PLM method. Moreover, it employs the Monte Carlo simulation to represent the stochastic variation of wind power production and assess the impact of energy management decisions in a residential wind-battery microgrid using the proposed wind power forecasting models. The results indicate that there are significant benefits for the microgrid when compared to the naïve approach that is used for benchmarking purposes, while the PLM adjustment method provides further improvements in terms of forecasting accuracy.

  12. Short-Term Wind Power Forecasting Using the Enhanced Particle Swarm Optimization Based Hybrid Method

    OpenAIRE

    Wen-Yeau Chang

    2013-01-01

    High penetration of wind power in the electricity system provides many challenges to power system operators, mainly due to the unpredictability and variability of wind power generation. Although wind energy may not be dispatched, an accurate forecasting method of wind speed and power generation can help power system operators reduce the risk of an unreliable electricity supply. This paper proposes an enhanced particle swarm optimization (EPSO) based hybrid forecasting method for short-term wi...

  13. Different Models for Forecasting Wind Power Generation: Case Study

    Directory of Open Access Journals (Sweden)

    David Barbosa de Alencar

    2017-11-01

    Full Text Available Generation of electric energy through wind turbines is one of the practically inexhaustible alternatives of generation. It is considered a source of clean energy, but still needs a lot of research for the development of science and technologies that ensures uniformity in generation, providing a greater participation of this source in the energy matrix, since the wind presents abrupt variations in speed, density and other important variables. In wind-based electrical systems, it is essential to predict at least one day in advance the future values of wind behavior, in order to evaluate the availability of energy for the next period, which is relevant information in the dispatch of the generating units and in the control of the electrical system. This paper develops ultra-short, short, medium and long-term prediction models of wind speed, based on computational intelligence techniques, using artificial neural network models, Autoregressive Integrated Moving Average (ARIMA and hybrid models including forecasting using wavelets. For the application of the methodology, the meteorological variables of the database of the national organization system of environmental data (SONDA, Petrolina station, from 1 January 2004 to 31 March 2017, were used. A comparison among results by different used approaches is also done and it is also predicted the possibility of power and energy generation using a certain kind of wind generator.

  14. Do regional weather models contribute to better wind power forecasts? A few Norwegian case studies

    DEFF Research Database (Denmark)

    Bremnes, John Bjørnar; Giebel, Gregor

    2017-01-01

    In most operational wind power forecasting systems statistical methods are applied to map wind forecasts from numerical weather prediction (NWP) models into wind power forecasts. NWP models are complex mathematical models of the atmosphere that divide the earth’s surface into a grid. The spatial...... resolution of this grid determines how accurate meteorological processes can be modeled and thereby also limits forecast quality. In this study, two global and four regional operational NWP models with spatial horizontal resolutions ranging from 1 to 32 km were applied to make wind power forecasts up to 66...

  15. Time-consistent calibration of short-term regional wind power ensemble forecasts

    Directory of Open Access Journals (Sweden)

    Stephan Späth

    2015-04-01

    Full Text Available With increasing wind power capacity, accurate uncertainty forecasts get more and more important for grid integration. The uncertainty of forecasts can be quantified by ensemble forecasts. We use ensemble forecasts from the COSMO-DE EPS to generate short-term ensemble forecasts of regionally aggregated wind power. The wind power forecasts are generated by an optimised regional power curve model that is based on minimum score estimation and leads to wind power forecasts with small deterministic errors. Remaining bias and dispersion errors in the wind power forecasts are removed by statistical post-processing (also called calibration with ensemble model output statistics and the temporal rank correlation of the raw ensemble is maintained by ensemble copula coupling. The verification of raw and calibrated ensembles shows both strong improvements by calibration and the benefit of ensuring time consistency with ensemble copula coupling. The improvements are indicated by the multivariate energy score as well as in a proposed univariate verification approach that is based on integrated wind power forecast and measurement trajectories. Slight deficits in time consistency of the forecasts remain because the theoretical assumptions of ensemble copula coupling are not always fulfilled as the COSMO-DE EPS is based on distinguishable ensemble members. The more training days are used for calibration against measurements of regionally aggregated wind power, the lower is the improvement by calibration which contradicts former results for different variables like wind speed.

  16. Evaluation of Wind Power Forecasts from the Vermont Weather Analytics Center and Identification of Improvements

    Energy Technology Data Exchange (ETDEWEB)

    Optis, Michael [National Renewable Energy Lab. (NREL), Golden, CO (United States); Scott, George N. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Draxl, Caroline [National Renewable Energy Lab. (NREL), Golden, CO (United States)

    2018-02-02

    The goal of this analysis was to assess the wind power forecast accuracy of the Vermont Weather Analytics Center (VTWAC) forecast system and to identify potential improvements to the forecasts. Based on the analysis at Georgia Mountain, the following recommendations for improving forecast performance were made: 1. Resolve the significant negative forecast bias in February-March 2017 (50% underprediction on average) 2. Improve the ability of the forecast model to capture the strong diurnal cycle of wind power 3. Add ability for forecast model to assess internal wake loss, particularly at sites where strong diurnal shifts in wind direction are present. Data availability and quality limited the robustness of this forecast assessment. A more thorough analysis would be possible given a longer period of record for the data (at least one full year), detailed supervisory control and data acquisition data for each wind plant, and more detailed information on the forecast system input data and methodologies.

  17. Investigating the Correlation Between Wind and Solar Power Forecast Errors in the Western Interconnection: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, J.; Hodge, B. M.; Florita, A.

    2013-05-01

    Wind and solar power generations differ from conventional energy generation because of the variable and uncertain nature of their power output. This variability and uncertainty can have significant impacts on grid operations. Thus, short-term forecasting of wind and solar generation is uniquely helpful for power system operations to balance supply and demand in an electricity system. This paper investigates the correlation between wind and solar power forecasting errors.

  18. Short-Term Forecasting of Loads and Wind Power for Latvian Power System: Accuracy and Capacity of the Developed Tools

    Directory of Open Access Journals (Sweden)

    Radziukynas V.

    2016-04-01

    Full Text Available The paper analyses the performance results of the recently developed short-term forecasting suit for the Latvian power system. The system load and wind power are forecasted using ANN and ARIMA models, respectively, and the forecasting accuracy is evaluated in terms of errors, mean absolute errors and mean absolute percentage errors. The investigation of influence of additional input variables on load forecasting errors is performed. The interplay of hourly loads and wind power forecasting errors is also evaluated for the Latvian power system with historical loads (the year 2011 and planned wind power capacities (the year 2023.

  19. Short-Term Wind Power Forecasting Using the Enhanced Particle Swarm Optimization Based Hybrid Method

    Directory of Open Access Journals (Sweden)

    Wen-Yeau Chang

    2013-09-01

    Full Text Available High penetration of wind power in the electricity system provides many challenges to power system operators, mainly due to the unpredictability and variability of wind power generation. Although wind energy may not be dispatched, an accurate forecasting method of wind speed and power generation can help power system operators reduce the risk of an unreliable electricity supply. This paper proposes an enhanced particle swarm optimization (EPSO based hybrid forecasting method for short-term wind power forecasting. The hybrid forecasting method combines the persistence method, the back propagation neural network, and the radial basis function (RBF neural network. The EPSO algorithm is employed to optimize the weight coefficients in the hybrid forecasting method. To demonstrate the effectiveness of the proposed method, the method is tested on the practical information of wind power generation of a wind energy conversion system (WECS installed on the Taichung coast of Taiwan. Comparisons of forecasting performance are made with the individual forecasting methods. Good agreements between the realistic values and forecasting values are obtained; the test results show the proposed forecasting method is accurate and reliable.

  20. Modeling and forecasting of wind power generation - Regime-switching approaches

    DEFF Research Database (Denmark)

    Trombe, Pierre-Julien

    of more renewable energy into power systems since these systems are subjected to maintain a strict balance between electricity consumption and production, at any time. For this purpose, wind power forecasts offer an essential support to power system operators. In particular, there is a growing demand...... of high and low variability. They also yield substantial gains in probabilistic forecast accuracy for lead times of a few minutes. However, these models only integrate historical and local measurements of wind power and thus have a limited ability for notifying regime changes for larger lead times....... For that purpose, there is a long tradition in using meteorological forecasts of wind speed and direction that are converted into wind power forecasts. Nevertheless, meteorological forecasts are not informative on the intra-hour wind variability and thus cannot be used in the present context focusing on temporal...

  1. High-quality Wind Power Scenario Forecasts for Decision-making Under Uncertainty in Power Systems

    DEFF Research Database (Denmark)

    Delikaraoglou, Stefanos; Pinson, Pierre

    2014-01-01

    The large scale integration of wind generation in existing power systems requires novel operational strategies and market clearing mechanisms to account for the variable nature of this energy source. An efficient method to cope with this uncertainty is stochastic optimization which however requires......-valued and probabilistic predictions as well as scenarios representing the spatio-temporal dependence structure of forecast errors. The applicability of the proposed framework is demonstrated with a small-scale stochastic unit commitment model....... high-quality forecasts in the form of scenarios. The main goal of this work is to release a public dataset of wind power forecasts to be used as a reference for future research. To that extent, we provide a complete framework to describe wind power uncertainty in terms of single...

  2. Wind power forecasting for a real onshore wind farm on complex terrain using WRF high resolution simulations.

    Science.gov (United States)

    Ángel Prósper Fernández, Miguel; Casal, Carlos Otero; Canoura Fernández, Felipe; Miguez-Macho, Gonzalo

    2017-04-01

    Regional meteorological models are becoming a generalized tool for forecasting wind resource, due to their capacity to simulate local flow dynamics impacting wind farm production. This study focuses on the production forecast and validation of a real onshore wind farm using high horizontal and vertical resolution WRF (Weather Research and Forecasting) model simulations. The wind farm is located in Galicia, in the northwest of Spain, in a complex terrain region with high wind resource. Utilizing the Fitch scheme, specific for wind farms, a period of one year is simulated with a daily operational forecasting set-up. Power and wind predictions are obtained and compared with real data provided by the management company. Results show that WRF is able to yield good wind power operational predictions for this kind of wind farms, due to a good representation of the planetary boundary layer behaviour of the region and the good performance of the Fitch scheme under these conditions.

  3. Probabilistic Forecast of Wind Power Generation by Stochastic Differential Equation Models

    KAUST Repository

    Elkantassi, Soumaya

    2017-04-01

    Reliable forecasting of wind power generation is crucial to optimal control of costs in generation of electricity with respect to the electricity demand. Here, we propose and analyze stochastic wind power forecast models described by parametrized stochastic differential equations, which introduce appropriate fluctuations in numerical forecast outputs. We use an approximate maximum likelihood method to infer the model parameters taking into account the time correlated sets of data. Furthermore, we study the validity and sensitivity of the parameters for each model. We applied our models to Uruguayan wind power production as determined by historical data and corresponding numerical forecasts for the period of March 1 to May 31, 2016.

  4. “Section to Point” Correction Method for Wind Power Forecasting Based on Cloud Theory

    Directory of Open Access Journals (Sweden)

    Dunnan Liu

    2015-01-01

    Full Text Available As an intermittent energy, wind power has the characteristics of randomness and uncontrollability. It is of great significance to improve the accuracy of wind power forecasting. Currently, most models for wind power forecasting are based on wind speed forecasting. However, it is stuck in a dilemma called “garbage in, garbage out,” which means it is difficult to improve the forecasting accuracy without improving the accuracy of input data such as the wind speed. In this paper, a new model based on cloud theory is proposed. It establishes a more accurate relational model between the wind power and wind speed, which has lots of catastrophe points. Then, combined with the trend during adjacent time and the laws of historical data, the forecasting value will be corrected by the theory of “section to point” correction. It significantly improves the stability of forecasting accuracy and reduces significant forecasting errors at some particular points. At last, by analyzing the data of generation power and historical wind speed in Inner Mongolia, China, it is proved that the proposed method can effectively improve the accuracy of wind speed forecasting.

  5. Hour-Ahead Wind Speed and Power Forecasting Using Empirical Mode Decomposition

    Directory of Open Access Journals (Sweden)

    Ying-Yi Hong

    2013-11-01

    Full Text Available Operation of wind power generation in a large farm is quite challenging in a smart grid owing to uncertain weather conditions. Consequently, operators must accurately forecast wind speed/power in the dispatch center to carry out unit commitment, real power scheduling and economic dispatch. This work presents a novel method based on the integration of empirical mode decomposition (EMD with artificial neural networks (ANN to forecast the short-term (1 h ahead wind speed/power. First, significant parameters for training the ANN are identified using the correlation coefficients. These significant parameters serve as inputs of the ANN. Owing to the volatile and intermittent wind speed/power, the historical time series of wind speed/power is decomposed into several intrinsic mode functions (IMFs and a residual function through EMD. Each IMF becomes less volatile and therefore increases the accuracy of the neural network. The final forecasting results are achieved by aggregating all individual forecasting results from all IMFs and their corresponding residual functions. Real data related to the wind speed and wind power measured at a wind-turbine generator in Taiwan are used for simulation. The wind speed forecasting and wind power forecasting for the four seasons are studied. Comparative studies between the proposed method and traditional methods (i.e., artificial neural network without EMD, autoregressive integrated moving average (ARIMA, and persistence method are also introduced.

  6. Adaptive robust polynomial regression for power curve modeling with application to wind power forecasting

    DEFF Research Database (Denmark)

    Xu, Man; Pinson, Pierre; Lu, Zongxiang

    2016-01-01

    Wind farm power curve modeling, which characterizes the relationship between meteorological variables and power production, is a crucial procedure for wind power forecasting. In many cases, power curve modeling is more impacted by the limited quality of input data rather than the stochastic nature...... of the energy conversion process. Such nature may be due the varying wind conditions, aging and state of the turbines, etc. And, an equivalent steady-state power curve, estimated under normal operating conditions with the intention to filter abnormal data, is not sufficient to solve the problem because...... of the lack of time adaptivity. In this paper, a refined local polynomial regression algorithm is proposed to yield an adaptive robust model of the time-varying scattered power curve for forecasting applications. The time adaptivity of the algorithm is considered with a new data-driven bandwidth selection...

  7. Enhanced short-term wind power forecasting and value to grid operations. The wind forecasting improvement project

    Energy Technology Data Exchange (ETDEWEB)

    Orwig, Kirsten D. [National Renewable Energy Laboratory (NREL), Golden, CO (United States). Transmission Grid Integration; Benjamin, Stan; Wilczak, James; Marquis, Melinda [National Oceanic and Atmospheric Administration, Boulder, CO (United States). Earth System Research Lab.; Stern, Andrew [National Oceanic and Atmospheric Administration, Silver Spring, MD (United States); Clark, Charlton; Cline, Joel [U.S. Department of Energy, Washington, DC (United States). Wind and Water Power Program; Finley, Catherine [WindLogics, Grand Rapids, MN (United States); Freedman, Jeffrey [AWS Truepower, Albany, NY (United States)

    2012-07-01

    The current state-of-the-art wind power forecasting in the 0- to 6-h timeframe has levels of uncertainty that are adding increased costs and risks to the U.S. electrical grid. It is widely recognized within the electrical grid community that improvements to these forecasts could greatly reduce the costs and risks associated with integrating higher penetrations of wind energy. The U.S. Department of Energy has sponsored a research campaign in partnership with the National Oceanic and Atmospheric Administration (NOAA) and private industry to foster improvements in wind power forecasting. The research campaign involves a three-pronged approach: (1) a one-year field measurement campaign within two regions; (2) enhancement of NOAA's experimental 3-km High-Resolution Rapid Refresh (HRRR) model by assimilating the data from the field campaign; and (3) evaluation of the economic and reliability benefits of improved forecasts to grid operators. This paper and presentation provide an overview of the regions selected, instrumentation deployed, data quality and control, assimilation of data into HRRR, and preliminary results of HRRR performance analysis. (orig.)

  8. Probabilistic Wind Power Ramp Forecasting Based on a Scenario Generation Method: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Qin [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Florita, Anthony R [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Krishnan, Venkat K [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Hodge, Brian S [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Cui, Mingjian [Univ. of Texas-Dallas, Richardson, TX (United States); Feng, Cong [Univ. of Texas-Dallas, Richardson, TX (United States); Wang, Zhenke [Univ. of Texas-Dallas, Richardson, TX (United States); Zhang, Jie [Univ. of Texas-Dallas, Richardson, TX (United States)

    2017-08-31

    Wind power ramps (WPRs) are particularly important in the management and dispatch of wind power, and they are currently drawing the attention of balancing authorities. With the aim to reduce the impact of WPRs for power system operations, this paper develops a probabilistic ramp forecasting method based on a large number of simulated scenarios. An ensemble machine learning technique is first adopted to forecast the basic wind power forecasting scenario and calculate the historical forecasting errors. A continuous Gaussian mixture model (GMM) is used to fit the probability distribution function (PDF) of forecasting errors. The cumulative distribution function (CDF) is analytically deduced. The inverse transform method based on Monte Carlo sampling and the CDF is used to generate a massive number of forecasting error scenarios. An optimized swinging door algorithm is adopted to extract all the WPRs from the complete set of wind power forecasting scenarios. The probabilistic forecasting results of ramp duration and start time are generated based on all scenarios. Numerical simulations on publicly available wind power data show that within a predefined tolerance level, the developed probabilistic wind power ramp forecasting method is able to predict WPRs with a high level of sharpness and accuracy.

  9. Probabilistic Wind Power Ramp Forecasting Based on a Scenario Generation Method

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Qin [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Florita, Anthony R [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Krishnan, Venkat K [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Hodge, Brian S [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Cui, Mingjian [University of Texas at Dallas; Feng, Cong [University of Texas at Dallas; Wang, Zhenke [University of Texas at Dallas; Zhang, Jie [University of Texas at Dallas

    2018-02-01

    Wind power ramps (WPRs) are particularly important in the management and dispatch of wind power and currently drawing the attention of balancing authorities. With the aim to reduce the impact of WPRs for power system operations, this paper develops a probabilistic ramp forecasting method based on a large number of simulated scenarios. An ensemble machine learning technique is first adopted to forecast the basic wind power forecasting scenario and calculate the historical forecasting errors. A continuous Gaussian mixture model (GMM) is used to fit the probability distribution function (PDF) of forecasting errors. The cumulative distribution function (CDF) is analytically deduced. The inverse transform method based on Monte Carlo sampling and the CDF is used to generate a massive number of forecasting error scenarios. An optimized swinging door algorithm is adopted to extract all the WPRs from the complete set of wind power forecasting scenarios. The probabilistic forecasting results of ramp duration and start-time are generated based on all scenarios. Numerical simulations on publicly available wind power data show that within a predefined tolerance level, the developed probabilistic wind power ramp forecasting method is able to predict WPRs with a high level of sharpness and accuracy.

  10. Detecting, categorizing and forecasting large romps in wind farm power output using meteorological observations and WPPT

    DEFF Research Database (Denmark)

    Cutler, N.; Kay, M.; Jacka, K.

    2007-01-01

    The Wind Power Prediction Tool (WPPT) has been installed in Australia for the first time, to forecast the power output from the 65MW Roaring 40s Renewable Energy P/L Woolnorth Bluff Point wind form. This article analyses the general performance of WPPT as well as its performance during large romps...... are not as complicated as Woolnorth Bluff Point. Large ramps are considered critical events for a wind power forecast for energy trading as well as managing power system security. A methodology is developed to detect large ramp events in the wind farm power data. Forty-one large ramp events are detected over I year...... (swings) in power output. In addition to this, detected large ramps are studied in detail and categorized. WPPT combines wind speed and direction forecasts from the Australian Bureau of Meteorology regional numerical weather prediction model, MesoLAPS, with real-time wind power observations to make hourly...

  11. Space-time wind speed forecasting for improved power system dispatch

    KAUST Repository

    Zhu, Xinxin

    2014-02-27

    To support large-scale integration of wind power into electric energy systems, state-of-the-art wind speed forecasting methods should be able to provide accurate and adequate information to enable efficient, reliable, and cost-effective scheduling of wind power. Here, we incorporate space-time wind forecasts into electric power system scheduling. First, we propose a modified regime-switching, space-time wind speed forecasting model that allows the forecast regimes to vary with the dominant wind direction and with the seasons, hence avoiding a subjective choice of regimes. Then, results from the wind forecasts are incorporated into a power system economic dispatch model, the cost of which is used as a loss measure of the quality of the forecast models. This, in turn, leads to cost-effective scheduling of system-wide wind generation. Potential economic benefits arise from the system-wide generation of cost savings and from the ancillary service cost savings. We illustrate the economic benefits using a test system in the northwest region of the United States. Compared with persistence and autoregressive models, our model suggests that cost savings from integration of wind power could be on the scale of tens of millions of dollars annually in regions with high wind penetration, such as Texas and the Pacific northwest. © 2014 Sociedad de Estadística e Investigación Operativa.

  12. Detecting, categorizing and forecasting large romps in wind farm power output using meteorological observations and WPPT

    DEFF Research Database (Denmark)

    Cutler, N.; Kay, M.; Jacka, K.

    2007-01-01

    The Wind Power Prediction Tool (WPPT) has been installed in Australia for the first time, to forecast the power output from the 65MW Roaring 40s Renewable Energy P/L Woolnorth Bluff Point wind form. This article analyses the general performance of WPPT as well as its performance during large romps...... (swings) in power output. In addition to this, detected large ramps are studied in detail and categorized. WPPT combines wind speed and direction forecasts from the Australian Bureau of Meteorology regional numerical weather prediction model, MesoLAPS, with real-time wind power observations to make hourly...... forecasts of the wind farm power output. The general performances of MesoLAPS and WPPTore evaluated over I year using the root mean square error (RMSE). The errors are significantly lower than for basic benchmark forecasts but higher than for many other WPPT installations, where the site conditions...

  13. Combined time-varying forecast based on the proper scoring approach for wind power generation

    DEFF Research Database (Denmark)

    Chen, Xingying; Jiang, Yu; Yu, Kun

    2017-01-01

    Compared with traditional point forecasts, combined forecast have been proposed as an effective method to provide more accurate forecasts than individual model. However, the literature and research focus on wind-power combined forecasts are relatively limited. Here, based on forecasting error...... distribution, a proper scoring approach is applied to combine plausible models to form an overall time-varying model for the next day forecasts, rather than weights-based combination. To validate the effectiveness of the proposed method, real data of 3 years were used for testing. Simulation results...... demonstrate that the proposed method improves the accuracy of overall forecasts, even compared with a numerical weather prediction....

  14. New tool for integration of wind power forecasting into power system operation

    DEFF Research Database (Denmark)

    Gubina, Andrej F.; Keane, Andrew; Meibom, Peter

    2009-01-01

    The paper describes the methodology that has been developed for transmission system operators (TSOs) of Republic of Ireland, Eirgrid, and Northern Ireland, SONI the TSO in Northern Ireland, to study the effects of advanced wind power forecasting on optimal short-term power system scheduling...... for evaluation of the impacts that different types of wind energy forecasts (stochastic vs. deterministic vs. perfect) have on the schedules, and how the new incoming information via in-day scheduling impacts the quality of the schedules. Within the methodology, metrics to assess the quality of the schedules....... The resulting schedules take into account the electricity market conditions and feature optimal reserve scheduling. The short-term wind power prediction is provided by the Anemos tool, and the scheduling function, including the reserve optimisation, by the Wilmar tool. The proposed methodology allows...

  15. Spatio-temporal modelling for short term wind power forecasts. Why, when and how.

    Science.gov (United States)

    Lenzi, Amanda; Steinsland, Ingelin; Pinson, Pierre

    2017-04-01

    This study is based on a case study of 349 wind farms in Western Denmark with available energy production every 15 minutes for 6 years. Our aim is to do short term forecasting up to 5 hours ahead based on previous observations. We want sharp and calibrated probabilistic forecasts for both individual wind farms and for aggregated energy production, for example the energy production in the whole region. To obtain this we propose two Bayesian spatio-temporal models, and obtain full probabilistic forecasts of wind power. The models are based on the stochastic partial differential equation (SPDE) approach to spatial-temporal modelling which enables fast inference using integrated nested Laplace approximations (INLA) as well as dimension reduction. We provide detailed analysis on the forecast performances on the individual and aggregated level based on appropriate metrics tailored for probability forecasts for both the spatial temporal models as well as for temporal models for individual wind farms. The case study as well as simulation studies demonstrate that forecasts that are individually reliable do not need to produce an aggregated forecasts that are reliable. Indeed, the case study shows that even when all individual forecasts are calibrated can the aggregated forecasts be so uncalibrated that less that 20% of the observations fall within the 95% forecast interval. T he results and methodology are both relevant for wind power forecasts in other regions as well as for spatial-temporal modeling and decisions in general.

  16. Research on Short-Term Wind Power Prediction Based on Combined Forecasting Models

    Directory of Open Access Journals (Sweden)

    Zhang Chi

    2016-01-01

    Full Text Available Short-Term wind power forecasting is crucial for power grid since the generated energy of wind farm fluctuates frequently. In this paper, a physical forecasting model based on NWP and a statistical forecasting model with optimized initial value in the method of BP neural network are presented. In order to make full use of the advantages of the models presented and overcome the limitation of the disadvantage, the equal weight model and the minimum variance model are established for wind power prediction. Simulation results show that the combination forecasting model is more precise than single forecasting model and the minimum variance combination model can dynamically adjust weight of each single method, restraining the forecasting error further.

  17. Comparison of the economic impact of different wind power forecast systems for producers

    Science.gov (United States)

    Alessandrini, S.; Davò, F.; Sperati, S.; Benini, M.; Delle Monache, L.

    2014-05-01

    Deterministic forecasts of wind production for the next 72 h at a single wind farm or at the regional level are among the main end-users requirement. However, for an optimal management of wind power production and distribution it is important to provide, together with a deterministic prediction, a probabilistic one. A deterministic forecast consists of a single value for each time in the future for the variable to be predicted, while probabilistic forecasting informs on probabilities for potential future events. This means providing information about uncertainty (i.e. a forecast of the PDF of power) in addition to the commonly provided single-valued power prediction. A significant probabilistic application is related to the trading of energy in day-ahead electricity markets. It has been shown that, when trading future wind energy production, using probabilistic wind power predictions can lead to higher benefits than those obtained by using deterministic forecasts alone. In fact, by using probabilistic forecasting it is possible to solve economic model equations trying to optimize the revenue for the producer depending, for example, on the specific penalties for forecast errors valid in that market. In this work we have applied a probabilistic wind power forecast systems based on the "analog ensemble" method for bidding wind energy during the day-ahead market in the case of a wind farm located in Italy. The actual hourly income for the plant is computed considering the actual selling energy prices and penalties proportional to the unbalancing, defined as the difference between the day-ahead offered energy and the actual production. The economic benefit of using a probabilistic approach for the day-ahead energy bidding are evaluated, resulting in an increase of 23% of the annual income for a wind farm owner in the case of knowing "a priori" the future energy prices. The uncertainty on price forecasting partly reduces the economic benefit gained by using a

  18. On maximizing profit of wind-battery supported power station based on wind power and energy price forecasting

    DEFF Research Database (Denmark)

    Khalid, Muhammad; Aguilera, Ricardo P.; Savkin, Andrey V.

    2017-01-01

    This paper proposes a framework to develop an optimal power dispatch strategy for grid-connected wind power plants containing a Battery Energy Storage System (BESS). Considering the intermittent nature of wind power and rapidly varying electricity market price, short-term forecasting...... Dynamic Programming tool which can incorporate the predictions of both wind power and market price simultaneously as inputs in a receding horizon approach. The proposed strategy is validated using real electricity market price and wind power data in different scenarios of BESS power and capacity...... of these variables is used for efficient energy management. The predicted variability trends in market price assist in earning additional income which subsequently increase the operational profit. Then on the basis of income improvement, optimal capacity of the BESS can be determined. The proposed framework utilizes...

  19. On maximizing profit of wind-battery supported power station based on wind power and energy price forecasting

    DEFF Research Database (Denmark)

    Khalid, Muhammad; Aguilera, Ricardo P.; Savkin, Andrey V.

    2017-01-01

    of these variables is used for efficient energy management. The predicted variability trends in market price assist in earning additional income which subsequently increase the operational profit. Then on the basis of income improvement, optimal capacity of the BESS can be determined. The proposed framework utilizes......This paper proposes a framework to develop an optimal power dispatch strategy for grid-connected wind power plants containing a Battery Energy Storage System (BESS). Considering the intermittent nature of wind power and rapidly varying electricity market price, short-term forecasting...... Dynamic Programming tool which can incorporate the predictions of both wind power and market price simultaneously as inputs in a receding horizon approach. The proposed strategy is validated using real electricity market price and wind power data in different scenarios of BESS power and capacity...

  20. Demand forecast of turbines in the offshore wind power industry

    DEFF Research Database (Denmark)

    Martinez-Neri, Ivan

    2014-01-01

    How important is it for a manufacturing company to be able to predict the demand of their products? How much will it lose in inventory costs due to a bad forecasting technique? And what if the product in question is composed of more than 100,000 parts and costs millions of euros a piece? This art......? This article summarises the reasoning followed by a European manufacturer to determine the demand curve of finished offshore wind turbines and how to forecast it for the purpose of production planning.......How important is it for a manufacturing company to be able to predict the demand of their products? How much will it lose in inventory costs due to a bad forecasting technique? And what if the product in question is composed of more than 100,000 parts and costs millions of euros a piece...

  1. Probabilistic wind power forecasting based on logarithmic transformation and boundary kernel

    International Nuclear Information System (INIS)

    Zhang, Yao; Wang, Jianxue; Luo, Xu

    2015-01-01

    Highlights: • Quantitative information on the uncertainty of wind power generation. • Kernel density estimator provides non-Gaussian predictive distributions. • Logarithmic transformation reduces the skewness of wind power density. • Boundary kernel method eliminates the density leakage near the boundary. - Abstracts: Probabilistic wind power forecasting not only produces the expectation of wind power output, but also gives quantitative information on the associated uncertainty, which is essential for making better decisions about power system and market operations with the increasing penetration of wind power generation. This paper presents a novel kernel density estimator for probabilistic wind power forecasting, addressing two characteristics of wind power which have adverse impacts on the forecast accuracy, namely, the heavily skewed and double-bounded nature of wind power density. Logarithmic transformation is used to reduce the skewness of wind power density, which improves the effectiveness of the kernel density estimator in a transformed scale. Transformations partially relieve the boundary effect problem of the kernel density estimator caused by the double-bounded nature of wind power density. However, the case study shows that there are still some serious problems of density leakage after the transformation. In order to solve this problem in the transformed scale, a boundary kernel method is employed to eliminate the density leak at the bounds of wind power distribution. The improvement of the proposed method over the standard kernel density estimator is demonstrated by short-term probabilistic forecasting results based on the data from an actual wind farm. Then, a detailed comparison is carried out of the proposed method and some existing probabilistic forecasting methods

  2. Short-term wind power forecasting: probabilistic and space-time aspects

    DEFF Research Database (Denmark)

    Tastu, Julija

    a statistical model which would improve the quality of state-of-the-art prediction methods by accounting for the fact that forecasts errors made by such locally-optimized forecasting methods propagate in space and in time under the influence of prevailing weather conditions. Subsequently, the extension from...... work deals with the proposal and evaluation of new mathematical models and forecasting methods for short-term wind power forecasting, accounting for space-time dynamics based on geographically distributed information. Different forms of power predictions are considered, starting from traditional point...... forecasts, then extending to marginal predictive densities and, finally, considering multivariate space-time trajectories. Point predictions is the most classical approach to wind power forecasting, only providing single-valued estimates of the expected future power generation. The objective is to introduce...

  3. Using Analog Ensemble to generate spatially downscaled probabilistic wind power forecasts

    Science.gov (United States)

    Delle Monache, L.; Shahriari, M.; Cervone, G.

    2017-12-01

    We use the Analog Ensemble (AnEn) method to generate probabilistic 80-m wind power forecasts. We use data from the NCEP GFS ( 28 km resolution) and NCEP NAM (12 km resolution). We use forecasts data from NAM and GFS, and analysis data from NAM which enables us to: 1) use a lower-resolution model to create higher-resolution forecasts, and 2) use a higher-resolution model to create higher-resolution forecasts. The former essentially increases computing speed and the latter increases forecast accuracy. An aggregated model of the former can be compared against the latter to measure the accuracy of the AnEn spatial downscaling. The AnEn works by taking a deterministic future forecast and comparing it with past forecasts. The model searches for the best matching estimates within the past forecasts and selects the predictand value corresponding to these past forecasts as the ensemble prediction for the future forecast. Our study is based on predicting wind speed and air density at more than 13,000 grid points in the continental US. We run the AnEn model twice: 1) estimating 80-m wind speed by using predictor variables such as temperature, pressure, geopotential height, U-component and V-component of wind, 2) estimating air density by using predictors such as temperature, pressure, and relative humidity. We use the air density values to correct the standard wind power curves for different values of air density. The standard deviation of the ensemble members (i.e. ensemble spread) will be used as the degree of difficulty to predict wind power at different locations. The value of the correlation coefficient between the ensemble spread and the forecast error determines the appropriateness of this measure. This measure is prominent for wind farm developers as building wind farms in regions with higher predictability will reduce the real-time risks of operating in the electricity markets.

  4. Comparison of two new short-term wind-power forecasting systems

    Energy Technology Data Exchange (ETDEWEB)

    Ramirez-Rosado, Ignacio J. [Department of Electrical Engineering, University of Zaragoza, Zaragoza (Spain); Fernandez-Jimenez, L. Alfredo [Department of Electrical Engineering, University of La Rioja, Logrono (Spain); Monteiro, Claudio; Sousa, Joao; Bessa, Ricardo [FEUP, Fac. Engenharia Univ. Porto (Portugal)]|[INESC - Instituto de Engenharia de Sistemas e Computadores do Porto, Porto (Portugal)

    2009-07-15

    This paper presents a comparison of two new advanced statistical short-term wind-power forecasting systems developed by two independent research teams. The input variables used in both systems were the same: forecasted meteorological variable values obtained from a numerical weather prediction model; and electric power-generation registers from the SCADA system of the wind farm. Both systems are described in detail and the forecasting results compared, revealing great similarities, although the proposed structures of the two systems are different. The forecast horizon for both systems is 72 h, allowing the use of the forecasted values in electric market operations, as diary and intra-diary power generation bid offers, and in wind-farm maintenance planning. (author)

  5. Knowledge Mining Based on Environmental Simulation Applied to Wind Farm Power Forecasting

    Directory of Open Access Journals (Sweden)

    Dongxiao Niu

    2013-01-01

    Full Text Available Considering the inherent variability and uncertainty of wind power generation, in this study, a self-organizing map (SOM combined with rough set theory clustering technique (RST is proposed to extract the relative knowledge and to choose the most similar history situation and efficient data for wind power forecasting with numerical weather prediction (NWP. Through integrating the SOM and RST methods to cluster the historical data into several classes, the approach could find the similar days and excavate the hidden rules. According to the data reprocessing, the selected samples will improve the forecast accuracy echo state network (ESN trained by the class of the forecasting day that is adopted to forecast the wind power output accordingly. The developed methods are applied to a case of power forecasting in a wind farm located in northwest of China with wind power data from April 1, 2008, to May 6, 2009. In order to verify its effectiveness, the performance of the proposed method is compared with the traditional backpropagation neural network (BP. The results demonstrated that knowledge mining led to a promising improvement in the performance for wind farm power forecasting.

  6. An application and verification of ensemble forecasting on wind power to assess operational risk indicators in power grids

    Energy Technology Data Exchange (ETDEWEB)

    Alessandrini, S.; Ciapessoni, E.; Cirio, D.; Pitto, A.; Sperati, S. [Ricerca sul Sistema Energetico RSE S.p.A., Milan (Italy). Power System Development Dept. and Environment and Sustainable Development Dept.; Pinson, P. [Technical University of Denmark, Lyngby (Denmark). DTU Informatics

    2012-07-01

    Wind energy is part of the so-called not schedulable renewable sources, i.e. it must be exploited when it is available, otherwise it is lost. In European regulation it has priority of dispatch over conventional generation, to maximize green energy production. However, being variable and uncertain, wind (and solar) generation raises several issues for the security of the power grids operation. In particular, Transmission System Operators (TSOs) need as accurate as possible forecasts. Nowadays a deterministic approach in wind power forecasting (WPF) could easily be considered insufficient to face the uncertainty associated to wind energy. In order to obtain information about the accuracy of a forecast and a reliable estimation of its uncertainty, probabilistic forecasting is becoming increasingly widespread. In this paper we investigate the performances of the COnsortium for Small-scale MOdelling Limited area Ensemble Prediction System (COSMO-LEPS). First the ensemble application is followed by assessment of its properties (i.e. consistency, reliability) using different verification indices and diagrams calculated on wind power. Then we provide examples of how EPS based wind power forecast can be used in power system security analyses. Quantifying the forecast uncertainty allows to determine more accurately the regulation reserve requirements, hence improving security of operation and reducing system costs. In particular, the paper also presents a probabilistic power flow (PPF) technique developed at RSE and aimed to evaluate the impact of wind power forecast accuracy on the probability of security violations in power systems. (orig.)

  7. Combination of Deterministic and Probabilistic Meteorological Models to enhance Wind Farm Power Forecasts

    International Nuclear Information System (INIS)

    Bremen, Lueder von

    2007-01-01

    Large-scale wind farms will play an important role in the future worldwide energy supply. However, with increasing wind power penetration all stakeholders on the electricity market will ask for more skilful wind power predictions regarding save grid integration and to increase the economic value of wind power. A Neural Network is used to calculate Model Output Statistics (MOS) for each individual forecast model (ECMWF and HIRLAM) and to model the aggregated power curve of the Middelgrunden offshore wind farm. We showed that the combination of two NWP models clearly outperforms the better single model. The normalized day-ahead RMSE forecast error for Middelgrunden can be reduced by 1% compared to single ECMWF. This is a relative improvement of 6%. For lead times >24h it is worthwhile to use a more sophisticated model combination approach than simple linear weighting. The investigated principle component regression is able to extract the uncorrelated information from two NWP forecasts. The spread of Ensemble Predictions is related to the skill of wind power forecasts. Simple contingency diagrams show that low spread corresponds is more often related to low forecast errors and high spread to large forecast errors

  8. Very-short-term wind power probabilistic forecasts by sparse vector autoregression

    DEFF Research Database (Denmark)

    Dowell, Jethro; Pinson, Pierre

    2016-01-01

    A spatio-temporal method for producing very-shortterm parametric probabilistic wind power forecasts at a large number of locations is presented. Smart grids containing tens, or hundreds, of wind generators require skilled very-short-term forecasts to operate effectively, and spatial information...... is highly desirable. In addition, probabilistic forecasts are widely regarded as necessary for optimal power system management as they quantify the uncertainty associated with point forecasts. Here we work within a parametric framework based on the logit-normal distribution and forecast its parameters....... The location parameter for multiple wind farms is modelled as a vector-valued spatiotemporal process, and the scale parameter is tracked by modified exponential smoothing. A state-of-the-art technique for fitting sparse vector autoregressive models is employed to model the location parameter and demonstrates...

  9. Refined Diebold-Mariano Test Methods for the Evaluation of Wind Power Forecasting Models

    Directory of Open Access Journals (Sweden)

    Hao Chen

    2014-07-01

    Full Text Available The scientific evaluation methodology for the forecast accuracy of wind power forecasting models is an important issue in the domain of wind power forecasting. However, traditional forecast evaluation criteria, such as Mean Squared Error (MSE and Mean Absolute Error (MAE, have limitations in application to some degree. In this paper, a modern evaluation criterion, the Diebold-Mariano (DM test, is introduced. The DM test can discriminate the significant differences of forecasting accuracy between different models based on the scheme of quantitative analysis. Furthermore, the augmented DM test with rolling windows approach is proposed to give a more strict forecasting evaluation. By extending the loss function to an asymmetric structure, the asymmetric DM test is proposed. Case study indicates that the evaluation criteria based on DM test can relieve the influence of random sample disturbance. Moreover, the proposed augmented DM test can provide more evidence when the cost of changing models is expensive, and the proposed asymmetric DM test can add in the asymmetric factor, and provide practical evaluation of wind power forecasting models. It is concluded that the two refined DM tests can provide reference to the comprehensive evaluation for wind power forecasting models.

  10. Numerical forecast test on local wind fields at Qinshan Nuclear Power Plant

    International Nuclear Information System (INIS)

    Chen Xiaoqiu

    2005-01-01

    Non-hydrostatic, full compressible atmospheric dynamics model is applied to perform numerical forecast test on local wind fields at Qinshan nuclear power plant, and prognostic data are compared with observed data for wind fields. The results show that the prognostic of wind speeds is better than that of wind directions as compared with observed results. As the whole, the results of prognostic wind field are consistent with meteorological observation data, 54% of wind speeds are within a factor of 1.5, about 61% of the deviation of wind direction within the 1.5 azimuth (≤33.75 degrees) in the first six hours. (authors)

  11. A Simple and Effective Approach for the Prediction of Turbine Power Production From Wind Speed Forecast

    Directory of Open Access Journals (Sweden)

    Marino Marrocu

    2017-11-01

    Full Text Available An accurate forecast of the power generated by a wind turbine is of paramount importance for its optimal exploitation. Several forecasting methods have been proposed either based on a physical modeling or using a statistical approach. All of them rely on the availability of high quality measures of local wind speed, corresponding generated power and on numerical weather forecasts. In this paper, a simple and effective wind power forecast technique, based on the probability distribution mapping of wind speed forecast and observed power data, is presented and it is applied to two turbines located on the island of Borkum (Germany in the North Sea. The wind speed forecast of the ECMWF model at 100 m from the ground is used as the prognostic meteorological parameter. Training procedures are based entirely on relatively short time series of power measurements. Results show that our approach has skills that are similar or better than those obtained using more standard methods when measured with mean absolute error.

  12. Ensemble Nonlinear Autoregressive Exogenous Artificial Neural Networks for Short-Term Wind Speed and Power Forecasting.

    Science.gov (United States)

    Men, Zhongxian; Yee, Eugene; Lien, Fue-Sang; Yang, Zhiling; Liu, Yongqian

    2014-01-01

    Short-term wind speed and wind power forecasts (for a 72 h period) are obtained using a nonlinear autoregressive exogenous artificial neural network (ANN) methodology which incorporates either numerical weather prediction or high-resolution computational fluid dynamics wind field information as an exogenous input. An ensemble approach is used to combine the predictions from many candidate ANNs in order to provide improved forecasts for wind speed and power, along with the associated uncertainties in these forecasts. More specifically, the ensemble ANN is used to quantify the uncertainties arising from the network weight initialization and from the unknown structure of the ANN. All members forming the ensemble of neural networks were trained using an efficient particle swarm optimization algorithm. The results of the proposed methodology are validated using wind speed and wind power data obtained from an operational wind farm located in Northern China. The assessment demonstrates that this methodology for wind speed and power forecasting generally provides an improvement in predictive skills when compared to the practice of using an "optimal" weight vector from a single ANN while providing additional information in the form of prediction uncertainty bounds.

  13. Ensemble Nonlinear Autoregressive Exogenous Artificial Neural Networks for Short-Term Wind Speed and Power Forecasting

    Science.gov (United States)

    Lien, Fue-Sang; Yang, Zhiling; Liu, Yongqian

    2014-01-01

    Short-term wind speed and wind power forecasts (for a 72 h period) are obtained using a nonlinear autoregressive exogenous artificial neural network (ANN) methodology which incorporates either numerical weather prediction or high-resolution computational fluid dynamics wind field information as an exogenous input. An ensemble approach is used to combine the predictions from many candidate ANNs in order to provide improved forecasts for wind speed and power, along with the associated uncertainties in these forecasts. More specifically, the ensemble ANN is used to quantify the uncertainties arising from the network weight initialization and from the unknown structure of the ANN. All members forming the ensemble of neural networks were trained using an efficient particle swarm optimization algorithm. The results of the proposed methodology are validated using wind speed and wind power data obtained from an operational wind farm located in Northern China. The assessment demonstrates that this methodology for wind speed and power forecasting generally provides an improvement in predictive skills when compared to the practice of using an “optimal” weight vector from a single ANN while providing additional information in the form of prediction uncertainty bounds. PMID:27382627

  14. Influence of local wind speed and direction on wind power dynamics – Application to offshore very short-term forecasting

    DEFF Research Database (Denmark)

    Gallego, Cristobal; Pinson, Pierre; Madsen, Henrik

    2011-01-01

    on one-step ahead forecasting and a time series resolution of 10 min. It has been found that the local wind direction contributes to model some features of the prevailing winds, such as the impact of the wind direction on the wind variability, whereas the non-linearities related to the power......Wind power time series usually show complex dynamics mainly due to non-linearities related to the wind physics and the power transformation process in wind farms. This article provides an approach to the incorporation of observed local variables (wind speed and direction) to model some...... of these effects by means of statistical models. To this end, a benchmarking between two different families of varyingcoefficient models (regime-switching and conditional parametric models) is carried out. The case of the offshore wind farm of Horns Rev in Denmark has been considered. The analysis is focused...

  15. Incorporating Wind Power Forecast Uncertainties Into Stochastic Unit Commitment Using Neural Network-Based Prediction Intervals.

    Science.gov (United States)

    Quan, Hao; Srinivasan, Dipti; Khosravi, Abbas

    2015-09-01

    Penetration of renewable energy resources, such as wind and solar power, into power systems significantly increases the uncertainties on system operation, stability, and reliability in smart grids. In this paper, the nonparametric neural network-based prediction intervals (PIs) are implemented for forecast uncertainty quantification. Instead of a single level PI, wind power forecast uncertainties are represented in a list of PIs. These PIs are then decomposed into quantiles of wind power. A new scenario generation method is proposed to handle wind power forecast uncertainties. For each hour, an empirical cumulative distribution function (ECDF) is fitted to these quantile points. The Monte Carlo simulation method is used to generate scenarios from the ECDF. Then the wind power scenarios are incorporated into a stochastic security-constrained unit commitment (SCUC) model. The heuristic genetic algorithm is utilized to solve the stochastic SCUC problem. Five deterministic and four stochastic case studies incorporated with interval forecasts of wind power are implemented. The results of these cases are presented and discussed together. Generation costs, and the scheduled and real-time economic dispatch reserves of different unit commitment strategies are compared. The experimental results show that the stochastic model is more robust than deterministic ones and, thus, decreases the risk in system operations of smart grids.

  16. Multi-Stage Optimization-Based Automatic Voltage Control Systems Considering Wind Power Forecasting Errors

    DEFF Research Database (Denmark)

    Qin, Nan; Bak, Claus Leth; Abildgaard, Hans

    2017-01-01

    cost and the generator reactive power output cost. The problem is formulated in a multi-stage optimal reactive power flow (MORPF) framework, solved by the nonlinear programming techniques via a rolling process. The voltage uncertainty caused by wind power forecasting errors is considered in the optimal...

  17. Short-Term Wind Electric Power Forecasting Using a Novel Multi-Stage Intelligent Algorithm

    Directory of Open Access Journals (Sweden)

    Haoran Zhao

    2018-03-01

    Full Text Available As the most efficient renewable energy source for generating electricity in a modern electricity network, wind power has the potential to realize sustainable energy supply. However, owing to its random and intermittent instincts, a high permeability of wind power into a power network demands accurate and effective wind energy prediction models. This study proposes a multi-stage intelligent algorithm for wind electric power prediction, which combines the Beveridge–Nelson (B-N decomposition approach, the Least Square Support Vector Machine (LSSVM, and a newly proposed intelligent optimization approach called the Grasshopper Optimization Algorithm (GOA. For data preprocessing, the B-N decomposition approach was employed to disintegrate the hourly wind electric power data into a deterministic trend, a cyclic term, and a random component. Then, the LSSVM optimized by the GOA (denoted GOA-LSSVM was applied to forecast the future 168 h of the deterministic trend, the cyclic term, and the stochastic component, respectively. Finally, the future hourly wind electric power values can be obtained by multiplying the forecasted values of these three trends. Through comparing the forecasting performance of this proposed method with the LSSVM, the LSSVM optimized by the Fruit-fly Optimization Algorithm (FOA-LSSVM, and the LSSVM optimized by Particle Swarm Optimization (PSO-LSSVM, it is verified that the established multi-stage approach is superior to other models and can increase the precision of wind electric power prediction effectively.

  18. Spatio‐temporal analysis and modeling of short‐term wind power forecast errors

    DEFF Research Database (Denmark)

    Tastu, Julija; Pinson, Pierre; Kotwa, Ewelina

    2011-01-01

    for the spatio‐temporal dependencies observed in the wind generation field. However, it is intuitively expected that, owing to the inertia of meteorological forecasting systems, a forecast error made at a given point in space and time will be related to forecast errors at other points in space in the following...... of small size like western Denmark, significant correlation between the various zones is observed for time delays up to 5 h. Wind direction is shown to play a crucial role, while the effect of wind speed is more complex. Nonlinear models permitting capture of the interdependence structure of wind power...... period. The existence of such underlying correlation patterns is demonstrated and analyzed in this paper, considering the case‐study of western Denmark. The effects of prevailing wind speed and direction on autocorrelation and cross‐correlation patterns are thoroughly described. For a flat terrain region...

  19. Probabilistic wind power forecasting with online model selection and warped gaussian process

    International Nuclear Information System (INIS)

    Kou, Peng; Liang, Deliang; Gao, Feng; Gao, Lin

    2014-01-01

    Highlights: • A new online ensemble model for the probabilistic wind power forecasting. • Quantifying the non-Gaussian uncertainties in wind power. • Online model selection that tracks the time-varying characteristic of wind generation. • Dynamically altering the input features. • Recursive update of base models. - Abstract: Based on the online model selection and the warped Gaussian process (WGP), this paper presents an ensemble model for the probabilistic wind power forecasting. This model provides the non-Gaussian predictive distributions, which quantify the non-Gaussian uncertainties associated with wind power. In order to follow the time-varying characteristics of wind generation, multiple time dependent base forecasting models and an online model selection strategy are established, thus adaptively selecting the most probable base model for each prediction. WGP is employed as the base model, which handles the non-Gaussian uncertainties in wind power series. Furthermore, a regime switch strategy is designed to modify the input feature set dynamically, thereby enhancing the adaptiveness of the model. In an online learning framework, the base models should also be time adaptive. To achieve this, a recursive algorithm is introduced, thus permitting the online updating of WGP base models. The proposed model has been tested on the actual data collected from both single and aggregated wind farms

  20. A hybrid wind power forecasting model based on data mining and wavelets analysis

    International Nuclear Information System (INIS)

    Azimi, R.; Ghofrani, M.; Ghayekhloo, M.

    2016-01-01

    Highlights: • An improved version of K-means algorithm is proposed for clustering wind data. • A persistence based method is applied to select the best cluster for NN training. • A combination of DWT and HANTS methods is used to provide a deep learning for NN. • A hybrid of T.S.B K-means, DWT and HANTS and NN is developed for wind forecasting. - Abstract: Accurate forecasting of wind power plays a key role in energy balancing and wind power integration into the grid. This paper proposes a novel time-series based K-means clustering method, named T.S.B K-means, and a cluster selection algorithm to better extract features of wind time-series data. A hybrid of T.S.B K-means, discrete wavelet transform (DWT) and harmonic analysis time series (HANTS) methods, and a multilayer perceptron neural network (MLPNN) is developed for wind power forecasting. The proposed T.S.B K-means classifies data into separate groups and leads to more appropriate learning for neural networks by identifying anomalies and irregular patterns. This improves the accuracy of the forecast results. A cluster selection method is developed to determine the cluster that provides the best training for the MLPNN. This significantly accelerates the forecast process as the most appropriate portion of the data rather than the whole data is used for the NN training. The wind power data is decomposed by the Daubechies D4 wavelet transform, filtered by the HANTS, and pre-processed to provide the most appropriate inputs for the MLPNN. Time-series analysis is used to pre-process the historical wind-power generation data and structure it into input-output series. Wind power datasets with diverse characteristics, from different wind farms located in the United States, are used to evaluate the accuracy of the hybrid forecasting method through various performance measures and different experiments. A comparative analysis with well-established forecasting models shows the superior performance of the proposed

  1. An Advanced Bayesian Method for Short-Term Probabilistic Forecasting of the Generation of Wind Power

    Directory of Open Access Journals (Sweden)

    Antonio Bracale

    2015-09-01

    Full Text Available Currently, among renewable distributed generation systems, wind generators are receiving a great deal of interest due to the great economic, technological, and environmental incentives they involve. However, the uncertainties due to the intermittent nature of wind energy make it difficult to operate electrical power systems optimally and make decisions that satisfy the needs of all the stakeholders of the electricity energy market. Thus, there is increasing interest determining how to forecast wind power production accurately. Most the methods that have been published in the relevant literature provided deterministic forecasts even though great interest has been focused recently on probabilistic forecast methods. In this paper, an advanced probabilistic method is proposed for short-term forecasting of wind power production. A mixture of two Weibull distributions was used as a probability function to model the uncertainties associated with wind speed. Then, a Bayesian inference approach with a particularly-effective, autoregressive, integrated, moving-average model was used to determine the parameters of the mixture Weibull distribution. Numerical applications also are presented to provide evidence of the forecasting performance of the Bayesian-based approach.

  2. Benefits of spatiotemporal modeling for short-term wind power forecasting at both individual and aggregated levels

    DEFF Research Database (Denmark)

    Lenzi, Amanda; Steinsland, Ingelin; Pinson, Pierre

    2018-01-01

    the advantage of being able to produce spatially out-of-sample forecasts. We use a Bayesian hierarchical framework to obtain fast and accurate forecasts of wind power generation not only at wind farms where recent data are available but also at a larger portfolio including wind farms without recent observations...

  3. Stochastic Dynamic AC Optimal Power Flow Based on a Multivariate Short-Term Wind Power Scenario Forecasting Model

    Directory of Open Access Journals (Sweden)

    Wenlei Bai

    2017-12-01

    Full Text Available The deterministic methods generally used to solve DC optimal power flow (OPF do not fully capture the uncertainty information in wind power, and thus their solutions could be suboptimal. However, the stochastic dynamic AC OPF problem can be used to find an optimal solution by fully capturing the uncertainty information of wind power. That uncertainty information of future wind power can be well represented by the short-term future wind power scenarios that are forecasted using the generalized dynamic factor model (GDFM—a novel multivariate statistical wind power forecasting model. Furthermore, the GDFM can accurately represent the spatial and temporal correlations among wind farms through the multivariate stochastic process. Fully capturing the uncertainty information in the spatially and temporally correlated GDFM scenarios can lead to a better AC OPF solution under a high penetration level of wind power. Since the GDFM is a factor analysis based model, the computational time can also be reduced. In order to further reduce the computational time, a modified artificial bee colony (ABC algorithm is used to solve the AC OPF problem based on the GDFM forecasting scenarios. Using the modified ABC algorithm based on the GDFM forecasting scenarios has resulted in better AC OPF’ solutions on an IEEE 118-bus system at every hour for 24 h.

  4. Short-term load and wind power forecasting using neural network-based prediction intervals.

    Science.gov (United States)

    Quan, Hao; Srinivasan, Dipti; Khosravi, Abbas

    2014-02-01

    Electrical power systems are evolving from today's centralized bulk systems to more decentralized systems. Penetrations of renewable energies, such as wind and solar power, significantly increase the level of uncertainty in power systems. Accurate load forecasting becomes more complex, yet more important for management of power systems. Traditional methods for generating point forecasts of load demands cannot properly handle uncertainties in system operations. To quantify potential uncertainties associated with forecasts, this paper implements a neural network (NN)-based method for the construction of prediction intervals (PIs). A newly introduced method, called lower upper bound estimation (LUBE), is applied and extended to develop PIs using NN models. A new problem formulation is proposed, which translates the primary multiobjective problem into a constrained single-objective problem. Compared with the cost function, this new formulation is closer to the primary problem and has fewer parameters. Particle swarm optimization (PSO) integrated with the mutation operator is used to solve the problem. Electrical demands from Singapore and New South Wales (Australia), as well as wind power generation from Capital Wind Farm, are used to validate the PSO-based LUBE method. Comparative results show that the proposed method can construct higher quality PIs for load and wind power generation forecasts in a short time.

  5. Wind power forecasting system EOlienne SPEO : development, preliminary results and integration at Hydro-Quebec

    Energy Technology Data Exchange (ETDEWEB)

    Forcione, A.; Roberge, G. [Hydro-Quebec, Varennes, PQ (Canada). IREQ; Yu, W.; Glazer, A.; Benoit, R.; Plante, A.; Tran, L.D.; Chardon, L. [Environment Canada, Ottawa, ON (Canada)

    2007-07-01

    Wind generation forecasting at Hydro-Quebec was discussed with particular reference to the collaborative efforts between the utility's Research Institute and Environment Canada in developing the Systeme de Prevision EOlienne (SPEO). The European ANEMOS platform was installed at Hydro-Quebec Distribution in 2006. Operational forecasts using the Global Environmental Multi-scale model (GEM) from the Canadian Meteorological Centre served as input for SPEO. This presentation evaluated the performance of the forecasting model, and presented best approaches for long term use and continuous improvement. SPEO was developed to forecast wind and other atmospheric variables, and not generated power. The development of the software began in September 2006 with the development and integration of necessary components, followed by the calibration of the system, 15 months of operational forecasts, experimentation and final analysis in 2008. The GEM-global model provides 10 days and 240 hours of hourly forecasts with 35 km resolution, while the GEM-regional model provides 2 days and 48 hours of hourly forecasts with 15 km resolution. It was shown that the development of a good forecasting system depends entirely on the availability of a maximum number of observation sources, which for SPEO includes 13 Environment Canada stations and wind farm masts. The final value of a wind forecasting system also depends on compatibility with the electric system management tools and processes. Research is ongoing to improve SPEO through validation tools, integration of newly available observations, recalibration and experimentation. Future tasks will be to extend the 48 hour horizon, to optimize the number crunching efficiency and to characterize wind farms more precisely. figs.

  6. Accurate Medium-Term Wind Power Forecasting in a Censored Classification Framework

    DEFF Research Database (Denmark)

    Dahl, Christian M.; Croonenbroeck, Carsten

    2014-01-01

    We provide a wind power forecasting methodology that exploits many of the actual data's statistical features, in particular both-sided censoring. While other tools ignore many of the important “stylized facts” or provide forecasts for short-term horizons only, our approach focuses on medium......-term forecasts, which are especially necessary for practitioners in the forward electricity markets of many power trading places; for example, NASDAQ OMX Commodities (formerly Nord Pool OMX Commodities) in northern Europe. We show that our model produces turbine-specific forecasts that are significantly more...... accurate in comparison to established benchmark models and present an application that illustrates the financial impact of more accurate forecasts obtained using our methodology....

  7. Power Flow Simulations of a More Renewable California Grid Utilizing Wind and Solar Insolation Forecasting

    Science.gov (United States)

    Hart, E. K.; Jacobson, M. Z.; Dvorak, M. J.

    2008-12-01

    Time series power flow analyses of the California electricity grid are performed with extensive addition of intermittent renewable power. The study focuses on the effects of replacing non-renewable and imported (out-of-state) electricity with wind and solar power on the reliability of the transmission grid. Simulations are performed for specific days chosen throughout the year to capture seasonal fluctuations in load, wind, and insolation. Wind farm expansions and new wind farms are proposed based on regional wind resources and time-dependent wind power output is calculated using a meteorological model and the power curves of specific wind turbines. Solar power is incorporated both as centralized and distributed generation. Concentrating solar thermal plants are modeled using local insolation data and the efficiencies of pre-existing plants. Distributed generation from rooftop PV systems is included using regional insolation data, efficiencies of common PV systems, and census data. The additional power output of these technologies offsets power from large natural gas plants and is balanced for the purposes of load matching largely with hydroelectric power and by curtailment when necessary. A quantitative analysis of the effects of this significant shift in the electricity portfolio of the state of California on power availability and transmission line congestion, using a transmission load-flow model, is presented. A sensitivity analysis is also performed to determine the effects of forecasting errors in wind and insolation on load-matching and transmission line congestion.

  8. Predictor-weighting strategies for probabilistic wind power forecasting with an analog ensemble

    Directory of Open Access Journals (Sweden)

    Constantin Junk

    2015-04-01

    Full Text Available Unlike deterministic forecasts, probabilistic predictions provide estimates of uncertainty, which is an additional value for decision-making. Previous studies have proposed the analog ensemble (AnEn, which is a technique to generate uncertainty information from a purely deterministic forecast. The objective of this study is to improve the AnEn performance for wind power forecasts by developing static and dynamic weighting strategies, which optimize the predictor combination with a brute-force continuous ranked probability score (CRPS minimization and a principal component analysis (PCA of the predictors. Predictors are taken from the high-resolution deterministic forecasts of the European Centre for Medium-Range Weather Forecasts (ECMWF, including forecasts of wind at several heights, geopotential height, pressure, and temperature, among others. The weighting strategies are compared at five wind farms in Europe and the U.S. situated in regions with different terrain complexity, both on and offshore, and significantly improve the deterministic and probabilistic AnEn forecast performance compared to the AnEn with 10‑m wind speed and direction as predictors and compared to PCA-based approaches. The AnEn methodology also provides reliable estimation of the forecast uncertainty. The optimized predictor combinations are strongly dependent on terrain complexity, local wind regimes, and atmospheric stratification. Since the proposed predictor-weighting strategies can accomplish both the selection of relevant predictors as well as finding their optimal weights, the AnEn performance is improved by up to 20 % at on and offshore sites.

  9. Using Quantile Regression to Extend an Existing Wind Power Forecasting System with Probabilistic Forecasts

    DEFF Research Database (Denmark)

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

    2006-01-01

    speed (due to the non-linearity of the power curve) and the forecast horizon. With respect to the predictability of the actual meteorological situation a number of explanatory variables are considered, some inspired by the literature. The article contains an overview of related work within the field...

  10. Application of numerical weather prediction in wind power forecasting: Assessment of the diurnal cycle

    Directory of Open Access Journals (Sweden)

    Tobias Heppelmann

    2017-06-01

    Full Text Available For a secure integration of weather dependent renewable energies in Germany's mixed power supply, precise forecasts of expected wind power are indispensable. These in turn are heavily dependent on numerical weather prediction (NWP. With this relevant area of application, NWP models need to be evaluated concerning new variables such as wind speed at hub heights of wind power plants. This article presents verification results of the deterministic NWP forecasts of the global ICON model, its ICON-EU nest, the COSMO-EU, and the COSMO-DE as well as of the ensemble prediction system COSMO-DE-EPS of the German National Weather Service (DWD, against wind mast observations. The focus is on the diurnal cycle in the Planetary Boundary Layer as wind power forecasts for Germany exhibit pronounced systematic amplitude and phase errors in the morning and evening hours. NWP forecasts with lead times up to 48 hours are examined. All considered NWP models reveal shortcomings concerning the representation of the diurnal cycle. Especially in summertime at onshore locations, when Low-Level Jets form, nocturnal wind speeds at hub height are underestimated. In the COSMO model, stable conditions are not sufficiently reflected in the first part of the night and the vertical mixing after sunrise establishes too late. The verification results of the COSMO-DE-EPS confirm the deficiencies of the deterministic forecasts. The deficiencies are present in all ensemble members and thus indicate potential for improvement not only in the model physics parameterization but also concerning the physical ensemble perturbations.

  11. Price Forecasting of Electricity Markets in the Presence of a High Penetration of Wind Power Generators

    Directory of Open Access Journals (Sweden)

    Saber Talari

    2017-11-01

    Full Text Available Price forecasting plays a vital role in the day-ahead markets. Once sellers and buyers access an accurate price forecasting, managing the economic risk can be conducted appropriately through offering or bidding suitable prices. In networks with high wind power penetration, the electricity price is influenced by wind energy; therefore, price forecasting can be more complicated. This paper proposes a novel hybrid approach for price forecasting of day-ahead markets, with high penetration of wind generators based on Wavelet transform, bivariate Auto-Regressive Integrated Moving Average (ARIMA method and Radial Basis Function Neural Network (RBFN. To this end, a weighted time series for wind dominated power systems is calculated and added to a bivariate ARIMA model along with the price time series. Moreover, RBFN is applied as a tool to correct the estimation error, and particle swarm optimization (PSO is used to optimize the structure and adapt the RBFN to the particular training set. This method is evaluated on the Spanish electricity market, which shows the efficiency of this approach. This method has less error compared with other methods especially when it considers the effects of large-scale wind generators.

  12. Wind Power Forecasting Based on Echo State Networks and Long Short-Term Memory

    DEFF Research Database (Denmark)

    López, Erick; Allende, Héctor; Gil, Esteban

    2018-01-01

    Wind power generation has presented an important development around the world. However, its integration into electrical systems presents numerous challenges due to the variable nature of the wind. Therefore, to maintain an economical and reliable electricity supply, it is necessary to accurately...... predict wind generation. The Wind Power Prediction Tool (WPPT) has been proposed to solve this task using the power curve associated with a wind farm. Recurrent Neural Networks (RNNs) model complex non-linear relationships without requiring explicit mathematical expressions that relate the variables...... involved. In particular, two types of RNN, Long Short-Term Memory (LSTM) and Echo State Network (ESN), have shown good results in time series forecasting. In this work, we present an LSTM+ESN architecture that combines the characteristics of both networks. An architecture similar to an ESN is proposed...

  13. Evaluation of different operational strategies for lithium ion battery systems connected to a wind turbine for primary frequency regulation and wind power forecast accuracy improvement

    DEFF Research Database (Denmark)

    Swierczynski, Maciej Jozef; Stroe, Daniel Ioan; Stan, Ana-Irina

    2012-01-01

    High penetration levels of variable wind energy sources can cause problems with their grid integration. Energy storage systems connected to wind turbine/wind power plants can improve predictability of the wind power production and provide ancillary services to the grid. This paper investigates...... economics of different operational strategies for Li-ion systems connected to wind turbines for wind power forecast accuracy improvement and primary frequency regulation....

  14. Adaptive modelling and forecasting of offshore wind power fluctuations with Markov-switching autoregressive models

    DEFF Research Database (Denmark)

    Pinson, Pierre; Madsen, Henrik

    optimized is based on penalized maximum-likelihood, with exponential forgetting of past observations. MSAR models are then employed for 1-step-ahead point forecasting of 10-minute resolution time-series of wind power at two large offshore wind farms. They are favourably compared against persistence and Auto......Wind power production data at temporal resolutions of a few minutes exhibits successive periods with fluctuations of various dynamic nature and magnitude, which cannot be explained (so far) by the evolution of some explanatory variable. Our proposal is to capture this regime-switching behaviour......Regressive (AR) models. It is finally shown that the main interest of MSAR models lies in their ability to generate interval/density forecasts of significantly higher skill....

  15. Adaptive modelling and forecasting of offshore wind power fluctuations with Markov-switching autoregressive models

    DEFF Research Database (Denmark)

    Pinson, Pierre; Madsen, Henrik

    2012-01-01

    optimized is based on penalized maximum likelihood, with exponential forgetting of past observations. MSAR models are then employed for one-step-ahead point forecasting of 10 min resolution time series of wind power at two large offshore wind farms. They are favourably compared against persistence......Wind power production data at temporal resolutions of a few minutes exhibit successive periods with fluctuations of various dynamic nature and magnitude, which cannot be explained (so far) by the evolution of some explanatory variable. Our proposal is to capture this regime-switching behaviour...... and autoregressive models. It is finally shown that the main interest of MSAR models lies in their ability to generate interval/density forecasts of significantly higher skill....

  16. Can Weather Radars Help Monitoring and Forecasting Wind Power Fluctuations at Large Offshore Wind Farms?

    DEFF Research Database (Denmark)

    Trombe, Pierre-Julien; Pinson, Pierre; Madsen, Henrik

    2011-01-01

    The substantial impact of wind power fluctuations at large offshore wind farms calls for the development of dedicated monitoring and prediction approaches. Based on recent findings, a Local Area Weather Radar (LAWR) was installed at Horns Rev with the aim of improving predictability, controlability...... and potentially maintenance planning. Additional images are available from a Doppler radar covering the same area. The parallel analysis of rain events detection and of regime sequences in wind (and power) fluctuations demonstrates the interest of employing weather radars for a better operation and management...... of offshore wind farms....

  17. Statistical learning for wind power: A modeling and stability study towards forecasting

    Science.gov (United States)

    Fischer, Aurélie; Montuelle, Lucie; Mougeot, Mathilde; Picard, Dominique

    2017-12-01

    We focus on wind power modeling using machine learning techniques. We show on real data provided by the wind energy company Ma{\\"i}a Eolis, that parametric models, even following closely the physical equation relating wind production to wind speed are outperformed by intelligent learning algorithms. In particular, the CART-Bagging algorithm gives very stable and promising results. Besides, as a step towards forecast, we quantify the impact of using deteriorated wind measures on the performances. We show also on this application that the default methodology to select a subset of predictors provided in the standard random forest package can be refined, especially when there exists among the predictors one variable which has a major impact.

  18. Enhanced Short-Term Wind Power Forecasting and Value to Grid Operations: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Orwig, K.; Clark, C.; Cline, J.; Benjamin, S.; Wilczak, J.; Marquis, M.; Finley, C.; Stern, A.; Freedman, J.

    2012-09-01

    The current state of the art of wind power forecasting in the 0- to 6-hour time frame has levels of uncertainty that are adding increased costs and risk on the U.S. electrical grid. It is widely recognized within the electrical grid community that improvements to these forecasts could greatly reduce the costs and risks associated with integrating higher penetrations of wind energy. The U.S. Department of Energy has sponsored a research campaign in partnership with the National Oceanic and Atmospheric Administration (NOAA) and private industry to foster improvements in wind power forecasting. The research campaign involves a three-pronged approach: 1) a 1-year field measurement campaign within two regions; 2) enhancement of NOAA's experimental 3-km High-Resolution Rapid Refresh (HRRR) model by assimilating the data from the field campaign; and 3) evaluation of the economic and reliability benefits of improved forecasts to grid operators. This paper and presentation provides an overview of the regions selected, instrumentation deployed, data quality and control, assimilation of data into HRRR, and preliminary results of HRRR performance analysis.

  19. IEA Wind Task 36 Forecasting

    Science.gov (United States)

    Giebel, Gregor; Cline, Joel; Frank, Helmut; Shaw, Will; Pinson, Pierre; Hodge, Bri-Mathias; Kariniotakis, Georges; Sempreviva, Anna Maria; Draxl, Caroline

    2017-04-01

    Wind power forecasts have been used operatively for over 20 years. Despite this fact, there are still several possibilities to improve the forecasts, both from the weather prediction side and from the usage of the forecasts. The new International Energy Agency (IEA) Task on Wind Power Forecasting tries to organise international collaboration, among national weather centres with an interest and/or large projects on wind forecast improvements (NOAA, DWD, UK MetOffice, …) and operational forecaster and forecast users. The Task is divided in three work packages: Firstly, a collaboration on the improvement of the scientific basis for the wind predictions themselves. This includes numerical weather prediction model physics, but also widely distributed information on accessible datasets for verification. Secondly, we will be aiming at an international pre-standard (an IEA Recommended Practice) on benchmarking and comparing wind power forecasts, including probabilistic forecasts aiming at industry and forecasters alike. This WP will also organise benchmarks, in cooperation with the IEA Task WakeBench. Thirdly, we will be engaging end users aiming at dissemination of the best practice in the usage of wind power predictions, especially probabilistic ones. The Operating Agent is Gregor Giebel of DTU, Co-Operating Agent is Joel Cline of the US Department of Energy. Collaboration in the task is solicited from everyone interested in the forecasting business. We will collaborate with IEA Task 31 Wakebench, which developed the Windbench benchmarking platform, which this task will use for forecasting benchmarks. The task runs for three years, 2016-2018. Main deliverables are an up-to-date list of current projects and main project results, including datasets which can be used by researchers around the world to improve their own models, an IEA Recommended Practice on performance evaluation of probabilistic forecasts, a position paper regarding the use of probabilistic forecasts

  20. Wind Energy Management System EMS Integration Project: Incorporating Wind Generation and Load Forecast Uncertainties into Power Grid Operations

    Energy Technology Data Exchange (ETDEWEB)

    Makarov, Yuri V.; Huang, Zhenyu; Etingov, Pavel V.; Ma, Jian; Guttromson, Ross T.; Subbarao, Krishnappa; Chakrabarti, Bhujanga B.

    2010-01-01

    The power system balancing process, which includes the scheduling, real time dispatch (load following) and regulation processes, is traditionally based on deterministic models. Since the conventional generation needs time to be committed and dispatched to a desired megawatt level, the scheduling and load following processes use load and wind and solar power production forecasts to achieve future balance between the conventional generation and energy storage on the one side, and system load, intermittent resources (such as wind and solar generation), and scheduled interchange on the other side. Although in real life the forecasting procedures imply some uncertainty around the load and wind/solar forecasts (caused by forecast errors), only their mean values are actually used in the generation dispatch and commitment procedures. Since the actual load and intermittent generation can deviate from their forecasts, it becomes increasingly unclear (especially, with the increasing penetration of renewable resources) whether the system would be actually able to meet the conventional generation requirements within the look-ahead horizon, what the additional balancing efforts would be needed as we get closer to the real time, and what additional costs would be incurred by those needs. To improve the system control performance characteristics, maintain system reliability, and minimize expenses related to the system balancing functions, it becomes necessary to incorporate the predicted uncertainty ranges into the scheduling, load following, and, in some extent, into the regulation processes. It is also important to address the uncertainty problem comprehensively by including all sources of uncertainty (load, intermittent generation, generators’ forced outages, etc.) into consideration. All aspects of uncertainty such as the imbalance size (which is the same as capacity needed to mitigate the imbalance) and generation ramping requirement must be taken into account. The latter

  1. Correlation-constrained and sparsity-controlled vector autoregressive model for spatio-temporal wind power forecasting

    DEFF Research Database (Denmark)

    Zhao, Yongning; Ye, Lin; Pinson, Pierre

    2018-01-01

    The ever-increasing number of wind farms has brought both challenges and opportunities in the development of wind power forecasting techniques to take advantage of interdependenciesbetweentensorhundredsofspatiallydistributedwind farms, e.g., over a region. In this paper, a Sparsity......-Controlled Vector Autoregressive (SC-VAR) model is introduced to obtain sparse model structures in a spatio-temporal wind power forecasting framework by reformulating the original VAR model into a constrained Mixed Integer Non-Linear Programming (MINLP) problem. It allows controlling the sparsity of the coefficient...... and forecasting, the original SC-VAR is modified and a Correlation-Constrained SC-VAR (CCSC-VAR) is proposed based on spatial correlation information about wind farms. Our approach is evaluated based on a case study of very-short-term forecasting for 25 wind farms in Denmark. Comparison is performed with a set...

  2. Implementation of a Model Output Statistics based on meteorological variable screening for short‐term wind power forecast

    DEFF Research Database (Denmark)

    Ranaboldo, Matteo; Giebel, Gregor; Codina, Bernat

    2013-01-01

    A combination of physical and statistical treatments to post‐process numerical weather predictions (NWP) outputs is needed for successful short‐term wind power forecasts. One of the most promising and effective approaches for statistical treatment is the Model Output Statistics (MOS) technique....... In this study, a MOS based on multiple linear regression is proposed: the model screens the most relevant NWP forecast variables and selects the best predictors to fit a regression equation that minimizes the forecast errors, utilizing wind farm power output measurements as input. The performance of the method...... is evaluated in two wind farms, located in different topographical areas and with different NWP grid spacing. Because of the high seasonal variability of NWP forecasts, it was considered appropriate to implement monthly stratified MOS. In both wind farms, the first predictors were always wind speeds (at...

  3. Spatial and Temporal Wind Power Forecasting by Case-Based Reasoning Using Big-Data

    Directory of Open Access Journals (Sweden)

    Fabrizio De Caro

    2017-02-01

    Full Text Available The massive penetration of wind generators in electrical power systems asks for effective wind power forecasting tools, which should be high reliable, in order to mitigate the effects of the uncertain generation profiles, and fast enough to enhance power system operation. To address these two conflicting objectives, this paper advocates the role of knowledge discovery from big-data, by proposing the integration of adaptive Case Based Reasoning models, and cardinality reduction techniques based on Partial Least Squares Regression, and Principal Component Analysis. The main idea is to learn from a large database of historical climatic observations, how to solve the windforecasting problem, avoiding complex and time-consuming computations. To assess the benefits derived by the application of the proposed methodology in complex application scenarios, the experimental results obtained in a real case study will be presented and discussed.

  4. Short-Term Forecasting of Inertial Response from a Wind Power Plant: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Muljadi, Eduard; Gevorgian, Vahan; Hoke, Andy

    2016-09-01

    The total inertia stored in all rotating masses (synchronous generators, induction motors, etc.) connected to a power system grid is an essential force that keeps the system stable after disturbances. Power systems have been experiencing reduced inertia during the past few decades [1]. This trend will continue as the level of renewable generation (e.g., wind and solar) increases. Wind power plants (WPPs) and other renewable power plants with power electronic interfaces are capable of delivering frequency response (both droop and/or inertial response) by a control action; thus, the reduction in available online inertia can be compensated by designing the plant control to include frequency response. The source of energy to be delivered as inertial response is determined by the type of generation (wind, photovoltaic, concentrating solar power, etc.) and the control strategy chosen. The importance of providing ancillary services to ensure frequency control within a power system is evidenced from many recent publications with different perspectives (manufacturer, system operator, regulator, etc.) [2]-[6]. This paper is intended to provide operators with a method for the real-time assessment of the available inertia of a WPP. This is critical to managing power system stability and the reserve margin. In many states, modern WPPs are required to provide ancillary services (e.g., frequency regulation via governor response and inertial response) to the grid. This paper describes the method of estimating the available inertia and the profile of the forecasted response from a WPP.

  5. Wind Energy Management System Integration Project Incorporating Wind Generation and Load Forecast Uncertainties into Power Grid Operations

    Energy Technology Data Exchange (ETDEWEB)

    Makarov, Yuri V.; Huang, Zhenyu; Etingov, Pavel V.; Ma, Jian; Guttromson, Ross T.; Subbarao, Krishnappa; Chakrabarti, Bhujanga B.

    2010-09-01

    The power system balancing process, which includes the scheduling, real time dispatch (load following) and regulation processes, is traditionally based on deterministic models. Since the conventional generation needs time to be committed and dispatched to a desired megawatt level, the scheduling and load following processes use load and wind power production forecasts to achieve future balance between the conventional generation and energy storage on the one side, and system load, intermittent resources (such as wind and solar generation) and scheduled interchange on the other side. Although in real life the forecasting procedures imply some uncertainty around the load and wind forecasts (caused by forecast errors), only their mean values are actually used in the generation dispatch and commitment procedures. Since the actual load and intermittent generation can deviate from their forecasts, it becomes increasingly unclear (especially, with the increasing penetration of renewable resources) whether the system would be actually able to meet the conventional generation requirements within the look-ahead horizon, what the additional balancing efforts would be needed as we get closer to the real time, and what additional costs would be incurred by those needs. In order to improve the system control performance characteristics, maintain system reliability, and minimize expenses related to the system balancing functions, it becomes necessary to incorporate the predicted uncertainty ranges into the scheduling, load following, and, in some extent, into the regulation processes. It is also important to address the uncertainty problem comprehensively, by including all sources of uncertainty (load, intermittent generation, generators’ forced outages, etc.) into consideration. All aspects of uncertainty such as the imbalance size (which is the same as capacity needed to mitigate the imbalance) and generation ramping requirement must be taken into account. The latter unique

  6. Increase of the Integration Degree of Wind Power Plants into the Energy System Using Wind Forecasting and Power Consumption Predictor Models by Transmission System Operator

    Directory of Open Access Journals (Sweden)

    Manusov V.Z.

    2017-12-01

    Full Text Available Wind power plants’ (WPPs high penetration into the power system leads to various inconveniences in the work of system operators. This fact is associated with the unpredictable nature of wind speed and generated power, respectively. Due to these factors, such source of electricity must be connected to the power system to avoid detrimental effects on the stability and quality of electricity. The power generated by the WPPs is not regulated by the system operator. Accurate forecasting of wind speed and power, as well as power load can solve this problem, thereby making a significant contribution to improving the power supply systems reliability. The article presents a mathematical model for the wind speed prediction, which is based on autoregression and fuzzy logic derivation of Takagi-Sugeno. The new model of wavelet transform has been developed, which makes it possible to include unnecessary noise from the model, as well as to reveal the cycling of the processes and their trend. It has been proved, that the proposed combination of methods can be used simultaneously to predict the power consumption and the wind power plant potential power at any time interval, depending on the planning horizon. The proposed models support a new scientific concept for the predictive control system of wind power stations and increase their degree integration into the electric power system.

  7. Probabilistic forecasting of wind power at the minute time-scale with Markov-switching autoregressive models

    DEFF Research Database (Denmark)

    Pinson, Pierre; Madsen, Henrik

    2008-01-01

    Better modelling and forecasting of very short-term power fluctuations at large offshore wind farms may significantly enhance control and management strategies of their power output. The paper introduces a new methodology for modelling and forecasting such very short-term fluctuations. The proposed...... consists in 1-step ahead forecasting exercise on time-series of wind generation with a time resolution of 10 minute. The quality of the introduced forecasting methodology and its interest for better understanding power fluctuations are finally discussed....... methodology is based on a Markov-switching autoregressive model with time-varying coefficients. An advantage of the method is that one can easily derive full predictive densities. The quality of this methodology is demonstrated from the test case of 2 large offshore wind farms in Denmark. The exercise...

  8. The effects of forecast errors on the merchandising of wind power; Auswirkungen von Prognosefehlern auf die Vermarktung von Windstrom

    Energy Technology Data Exchange (ETDEWEB)

    Roon, Serafin von

    2012-02-28

    A permanent balance between consumption and generation is essential for a stable supply of electricity. In order to ensure this balance, all relevant load data have to be announced for the following day. Consequently, a day-ahead forecast of the wind power generation is required, which also forms the basis for the sale of the wind power at the wholesale market. The main subject of the study is the short-term power supply, which compensates errors in wind power forecasting for balancing the wind power forecast errors at short notice. These forecast errors effects the revenues and the expenses by selling and buying power in the day-ahead, intraday and balance energy market. These price effects resulting from the forecast errors are derived from an empirical analysis. In a scenario for the year 2020 the potential of conventional power plants to supply power at short notice is evaluated from a technical and economic point of view by a time series analysis and a unit commitment simulation.

  9. Dynamic sizing of energy storage for hedging wind power forecast uncertainty

    DEFF Research Database (Denmark)

    Pinson, Pierre; Papefthymiou, George; Klöckl, Bernd

    2009-01-01

    . This approach leads to a dynamic assessment of the energy storage capacity for different delivery periods. In such a context, energy storage is used as a means of risk hedging against penalties from the regulation market. The application of the algorithm on real data (both measurements and forecasts......In market conditions where program responsible parties are penalized for deviations from proposed bids, energy storage can be used for compensating the energy imbalances induced by limited predictability of wind power. The energy storage capacity necessary for performing this task will differ......) of the yearly output of a wind farm shows that the application of a dynamic daily sizing of the necessary storage leads to a significant reduction of the storage capacity used, without affecting the producer's profit significantly. The method proposed here may provide the basis for the introduction of storage...

  10. 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.

  11. Wind Power accuracy and forecast. D3.1. Assumptions on accuracy of wind power to be considered at short and long term horizons

    Energy Technology Data Exchange (ETDEWEB)

    Morthorst, P.E.; Coulondre, J.M.; Schroeder, S.T.; Meibom, P.

    2010-07-15

    The main objective of the Optimate project (An Open Platform to Test Integration in new MArkeT designs of massive intermittent Energy sources dispersed in several regional power markets) is to develop a new tool for testing these new market designs with large introduction of variable renewable energy sources. In Optimate a novel network/system/market modelling approach is being developed, generating an open simulation platform able to exhibit the comparative benefits of several market design options. This report constitutes delivery 3.1 on the assumptions on accuracy of wind power to be considered at short and long term horizons. The report handles the issues of state-of-the-art prediction, how predictions for wind power enter into the Optimate model and a simple and a more advanced methodology of how to generate trajectories of prediction errors to be used in Optimate. The main conclusion is that undoubtedly, the advanced approach is to be preferred to the simple one seen from a theoretical viewpoint. However, the advanced approach was developed to the Wilmar-model with the purpose of describing the integration of large-scale wind power in Europe. As the main purpose of the Optimate model is not to test the integration of wind power, but to test new market designs assuming a strong growth in wind power production, a more simplified approach for describing wind power forecasts should be sufficient. Thus a further development of the simple approach is suggested, eventually including correlations between geographical areas. In this report the general methodologies for generating trajectories for wind power forecasts are outlined. However, the methods are not yet implemented. In the next phase of Optimate, the clusters will be defined and the needed data collected. Following this phase actual results will be generated to be used in Optimate. (LN)

  12. From probabilistic forecasts to statistical scenarios of short-term wind power production

    DEFF Research Database (Denmark)

    Pinson, Pierre; Papaefthymiou, George; Klockl, Bernd

    2009-01-01

    on the development of the forecast uncertainty through forecast series. However, this additional information may be paramount for a large class of time-dependent and multistage decision-making problems, e.g. optimal operation of combined wind-storage systems or multiple-market trading with different gate closures...

  13. Electrical Energy Forecasting and Optimal Allocation of ESS in a Hybrid Wind-Diesel Power System

    Directory of Open Access Journals (Sweden)

    Hai Lan

    2017-02-01

    Full Text Available Due to the increasingly serious energy crisis and environmental pollution problem, traditional fossil energy is gradually being replaced by renewable energy in recent years. However, the introduction of renewable energy into power systems will lead to large voltage fluctuations and high capital costs. To solve these problems, an energy storage system (ESS is employed into a power system to reduce total costs and greenhouse gas emissions. Hence, this paper proposes a two-stage method based on a back-propagation neural network (BPNN and hybrid multi-objective particle swarm optimization (HMOPSO to determine the optimal placements and sizes of ESSs in a transmission system. Owing to the uncertainties of renewable energy, a BPNN is utilized to forecast the outputs of the wind power and load demand based on historic data in the city of Madison, USA. Furthermore, power-voltage (P-V sensitivity analysis is conducted in this paper to improve the converge speed of the proposed algorithm, and continuous wind distribution is discretized by a three-point estimation method. The Institute of Electrical and Electronic Engineers (IEEE 30-bus system is adopted to perform case studies. The simulation results of each case clearly demonstrate the necessity for optimal storage allocation and the efficiency of the proposed method.

  14. Wind Power Forecasting Using Multi-Objective Evolutionary Algorithms for Wavelet Neural Network-Optimized Prediction Intervals

    Directory of Open Access Journals (Sweden)

    Yanxia Shen

    2018-01-01

    Full Text Available The intermittency of renewable energy will increase the uncertainty of the power system, so it is necessary to predict the short-term wind power, after which the electrical power system can operate reliably and safely. Unlike the traditional point forecasting, the purpose of this study is to quantify the potential uncertainties of wind power and to construct prediction intervals (PIs and prediction models using wavelet neural network (WNN. Lower upper bound estimation (LUBE of the PIs is achieved by minimizing a multi-objective function covering both interval width and coverage probabilities. Considering the influence of the points out of the PIs to shorten the width of PIs without compromising coverage probability, a new, improved, multi-objective artificial bee colony (MOABC algorithm combining multi-objective evolutionary knowledge, called EKMOABC, is proposed for the optimization of the forecasting model. In this paper, some comparative simulations are carried out and the results show that the proposed model and algorithm can achieve higher quality PIs for wind power forecasting. Taking into account the intermittency of renewable energy, such a type of wind power forecast can actually provide a more reliable reference for dispatching of the power system.

  15. 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...

  16. Forecastability as a Design Criterion in Wind Resource Assessment: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, J.; Hodge, B. M.

    2014-04-01

    This paper proposes a methodology to include the wind power forecasting ability, or 'forecastability,' of a site as a design criterion in wind resource assessment and wind power plant design stages. The Unrestricted Wind Farm Layout Optimization (UWFLO) methodology is adopted to maximize the capacity factor of a wind power plant. The 1-hour-ahead persistence wind power forecasting method is used to characterize the forecastability of a potential wind power plant, thereby partially quantifying the integration cost. A trade-off between the maximum capacity factor and the forecastability is investigated.

  17. A Wind Forecasting System for Energy Application

    Science.gov (United States)

    Courtney, Jennifer; Lynch, Peter; Sweeney, Conor

    2010-05-01

    Accurate forecasting of available energy is crucial for the efficient management and use of wind power in the national power grid. With energy output critically dependent upon wind strength there is a need to reduce the errors associated wind forecasting. The objective of this research is to get the best possible wind forecasts for the wind energy industry. To achieve this goal, three methods are being applied. First, a mesoscale numerical weather prediction (NWP) model called WRF (Weather Research and Forecasting) is being used to predict wind values over Ireland. Currently, a gird resolution of 10km is used and higher model resolutions are being evaluated to establish whether they are economically viable given the forecast skill improvement they produce. Second, the WRF model is being used in conjunction with ECMWF (European Centre for Medium-Range Weather Forecasts) ensemble forecasts to produce a probabilistic weather forecasting product. Due to the chaotic nature of the atmosphere, a single, deterministic weather forecast can only have limited skill. The ECMWF ensemble methods produce an ensemble of 51 global forecasts, twice a day, by perturbing initial conditions of a 'control' forecast which is the best estimate of the initial state of the atmosphere. This method provides an indication of the reliability of the forecast and a quantitative basis for probabilistic forecasting. The limitation of ensemble forecasting lies in the fact that the perturbed model runs behave differently under different weather patterns and each model run is equally likely to be closest to the observed weather situation. Models have biases, and involve assumptions about physical processes and forcing factors such as underlying topography. Third, Bayesian Model Averaging (BMA) is being applied to the output from the ensemble forecasts in order to statistically post-process the results and achieve a better wind forecasting system. BMA is a promising technique that will offer calibrated

  18. Day-Ahead Wind Power Forecasting Using a Two-Stage Hybrid Modeling Approach Based on SCADA and Meteorological Information, and Evaluating the Impact of Input-Data Dependency on Forecasting Accuracy

    Directory of Open Access Journals (Sweden)

    Dehua Zheng

    2017-12-01

    Full Text Available The power generated by wind generators is usually associated with uncertainties, due to the intermittency of wind speed and other weather variables. This creates a big challenge for transmission system operators (TSOs and distribution system operators (DSOs in terms of connecting, controlling and managing power networks with high-penetration wind energy. Hence, in these power networks, accurate wind power forecasts are essential for their reliable and efficient operation. They support TSOs and DSOs in enhancing the control and management of the power network. In this paper, a novel two-stage hybrid approach based on the combination of the Hilbert-Huang transform (HHT, genetic algorithm (GA and artificial neural network (ANN is proposed for day-ahead wind power forecasting. The approach is composed of two stages. The first stage utilizes numerical weather prediction (NWP meteorological information to predict wind speed at the exact site of the wind farm. The second stage maps actual wind speed vs. power characteristics recorded by SCADA. Then, the wind speed forecast in the first stage for the future day is fed to the second stage to predict the future day’s wind power. Comparative selection of input-data parameter sets for the forecasting model and impact analysis of input-data dependency on forecasting accuracy have also been studied. The proposed approach achieves significant forecasting accuracy improvement compared with three other artificial intelligence-based forecasting approaches and a benchmark model using the smart persistence method.

  19. Daily Average Wind Power Interval Forecasts Based on an Optimal Adaptive-Network-Based Fuzzy Inference System and Singular Spectrum Analysis

    Directory of Open Access Journals (Sweden)

    Zhongrong Zhang

    2016-01-01

    Full Text Available Wind energy has increasingly played a vital role in mitigating conventional resource shortages. Nevertheless, the stochastic nature of wind poses a great challenge when attempting to find an accurate forecasting model for wind power. Therefore, precise wind power forecasts are of primary importance to solve operational, planning and economic problems in the growing wind power scenario. Previous research has focused efforts on the deterministic forecast of wind power values, but less attention has been paid to providing information about wind energy. Based on an optimal Adaptive-Network-Based Fuzzy Inference System (ANFIS and Singular Spectrum Analysis (SSA, this paper develops a hybrid uncertainty forecasting model, IFASF (Interval Forecast-ANFIS-SSA-Firefly Alogorithm, to obtain the upper and lower bounds of daily average wind power, which is beneficial for the practical operation of both the grid company and independent power producers. To strengthen the practical ability of this developed model, this paper presents a comparison between IFASF and other benchmarks, which provides a general reference for this aspect for statistical or artificially intelligent interval forecast methods. The comparison results show that the developed model outperforms eight benchmarks and has a satisfactory forecasting effectiveness in three different wind farms with two time horizons.

  20. The influence of the new ECMWF Ensemble Prediction System resolution on wind power forecast accuracy and uncertainty estimation

    DEFF Research Database (Denmark)

    Alessandrini, S.; Pinson, Pierre; Sperati, S.

    2011-01-01

    The importance of wind power forecasting (WPF) is nowadays commonly recognized because it represents a useful tool to reduce problems of grid integration and to facilitate energy trading. If on one side the prediction accuracy is fundamental to these scopes, on the other it has become also clear...... Prediction System (EPS) can be used as indicator of a three-hourly, three days ahead, wind power forecast’s accuracy. In particular it has been noticed that to extract usable information from data the Ensemble members needed to be statistically calibrated, since the rank histograms for the three-day period...... that a reliable estimation of their uncertainty could be a useful information too. In fact the prediction accuracy is unfortunately not constant and can depend on the location of a particular wind farm, on the forecast time and on the atmospheric situation. Previous studies indicated that the ECMWF Ensemble...

  1. On-line quantile regression in the RKHS (Reproducing Kernel Hilbert Space) for operational probabilistic forecasting of wind power

    International Nuclear Information System (INIS)

    Gallego-Castillo, Cristobal; Bessa, Ricardo; Cavalcante, Laura; Lopez-Garcia, Oscar

    2016-01-01

    Wind power probabilistic forecast is being used as input in several decision-making problems, such as stochastic unit commitment, operating reserve setting and electricity market bidding. This work introduces a new on-line quantile regression model based on the Reproducing Kernel Hilbert Space (RKHS) framework. Its application to the field of wind power forecasting involves a discussion on the choice of the bias term of the quantile models, and the consideration of the operational framework in order to mimic real conditions. Benchmark against linear and splines quantile regression models was performed for a real case study during a 18 months period. Model parameter selection was based on k-fold crossvalidation. Results showed a noticeable improvement in terms of calibration, a key criterion for the wind power industry. Modest improvements in terms of Continuous Ranked Probability Score (CRPS) were also observed for prediction horizons between 6 and 20 h ahead. - Highlights: • New online quantile regression model based on the Reproducing Kernel Hilbert Space. • First application to operational probabilistic wind power forecasting. • Modest improvements of CRPS for prediction horizons between 6 and 20 h ahead. • Noticeable improvements in terms of Calibration due to online learning.

  2. Integration of wind generation forecasts. Volume 2

    International Nuclear Information System (INIS)

    Ahlstrom, M.; Zavadil, B.; Jones, L.

    2005-01-01

    WindLogics is a company that specializes in atmospheric modelling, visualization and fine-scale forecasting systems for the wind power industry. A background of the organization was presented. The complexities of wind modelling were discussed. Issues concerning location and terrain, shear, diurnal and interannual variability were reviewed. It was suggested that wind power producers should aim to be mainstream, and that variability should be considered as intrinsic to fuel supply. Various utility operating impacts were outlined. Details of an Xcel NSP wind integration study were presented, as well as a studies conducted in New York state and Colorado. It was concluded that regulations and load following impacts with wind energy integration are modest. Overall impacts are dominated by costs incurred to accommodate wind generation variability and uncertainty in the day-ahead time frame. Cost impacts can be reduced with adjustments to operating strategies, improvements in wind forecasting and access to real-time markets. Details of WindLogic's wind energy forecast system were presented, as well as examples of day ahead and hour ahead forecasts and wind speed and power forecasts. Screenshots of control room integration, EMS integration and simulations were presented. Details of a utility-scale wind energy forecasting system funded by Xcel Renewable Development Fund (RDF) were also presented. The goal of the system was to optimize the way that wind forecast information is integrated into the control room environment. Project components were outlined. It was concluded that accurate day-ahead forecasting can lead to significant asset optimization. It was recommended that wind plants share data, and aim to resolve issues concerning grid codes and instrumentation. refs., tabs., figs

  3. Wind Farm Power Forecasting for Less Than an Hour Using Multi Dimensional Models

    DEFF Research Database (Denmark)

    Knudsen, Torben; Bak, Thomas; Jensen, Tom Nørgaard

    2018-01-01

    The paper focus on prediction of wind farm power for horizons of 0-10 minutes and not more than one hour using statistical methods. These short term predictions are relevant for both transmission system operators, wind farm operators and traders. Previous research indicates that for short time...... horizons the persistence method performs as well as more complex methods. However, these results are based on accumulated power for an entire wind farm. The contribution in this paper is to develop multi-dimensional linear methods based on measurements of power or wind speed from individual wind turbine...... in a wind farm. These multi-dimensional methods are compared with the persistence method using real 1 minute average data from the Sheringham Shoal wind farm with 88 turbines. The results show that the use of measurements from individual turbines reduce the prediction errors 5-10% and also improves...

  4. Hour-ahead wind power and speed forecasting using simultaneous perturbation stochastic approximation (SPSA) algorithm and neural network with fuzzy inputs

    International Nuclear Information System (INIS)

    Hong, Ying-Yi; Chang, Huei-Lin; Chiu, Ching-Sheng

    2010-01-01

    Wind energy is currently one of the types of renewable energy with a large generation capacity. However, since the operation of wind power generation is challenging due to its intermittent characteristics, forecasting wind power generation efficiently is essential for economic operation. This paper proposes a new method of wind power and speed forecasting using a multi-layer feed-forward neural network (MFNN) to develop forecasting in time-scales that can vary from a few minutes to an hour. Inputs for the MFNN are modeled by fuzzy numbers because the measurement facilities provide maximum, average and minimum values. Then simultaneous perturbation stochastic approximation (SPSA) algorithm is employed to train the MFNN. Real wind power generation and wind speed data measured at a wind farm are used for simulation. Comparative studies between the proposed method and traditional methods are shown.

  5. A comparison between the ECMWF and COSMO Ensemble Prediction Systems applied to short-term wind power forecasting on real data

    DEFF Research Database (Denmark)

    Alessandrini, S.; Sperati, S.; Pinson, Pierre

    2013-01-01

    within COnsortium for Small-scale MOdelling) applied for power forecasts on a real case in Southern Italy is presented. The approach is based on retrieving meteorological ensemble variables (i.e. wind speed, wind direction), using them to create a power Probability Density Function (PDF) for each 0-72. h......Wind power forecasting (WPF) represents a crucial tool to reduce problems of grid integration and to facilitate energy trading. By now it is advantageous to associate a deterministic forecast with a probabilistic one, in order to give to the end-users information about prediction uncertainty...

  6. The use of different ensemble forecasting systems for wind power prediction on a real case in the South of Italy

    DEFF Research Database (Denmark)

    Alessandrini, Stefano; Sperati, Simone; Pinson, Pierre

    2012-01-01

    Short-term forecasting applied to wind energy is becoming increasingly important due to the constant growth of this renewable source, whose uncertainty requires a constant effort to meet the needs of the national electrical systems and their operators. Regarding to this, the probabilistic approach...... the data to wind energy: the spread calculated on wind power can then be used as an accuracy predictor due to its level of correlation with the deterministic WPF error. In this presentation we investigate the performances for both wind power and accuracy prediction of the new EPS used at the ECMWF, whose...... horizontal resolution was increased on January 2010 from 60 km to 32 km, on a complex terrain area already used in previous studies and located in Southern Italy. The work consists in the use of the ECMWF deterministic model in a WPF approach followed by a recursive feed-forward Neural Networks (NN...

  7. Enhanced Forecasting Approach for Electricity Market Prices and Wind Power Data Series in the Short-Term

    Directory of Open Access Journals (Sweden)

    Gerardo J. Osório

    2016-08-01

    Full Text Available The uncertainty and variability in electricity market price (EMP signals and players’ behavior, as well as in renewable power generation, especially wind power, pose considerable challenges. Hence, enhancement of forecasting approaches is required for all electricity market players to deal with the non-stationary and stochastic nature of such time series, making it possible to accurately support their decisions in a competitive environment with lower forecasting error and with an acceptable computational time. As previously published methodologies have shown, hybrid approaches are good candidates to overcome most of the previous concerns about time-series forecasting. In this sense, this paper proposes an enhanced hybrid approach composed of an innovative combination of wavelet transform (WT, differential evolutionary particle swarm optimization (DEEPSO, and an adaptive neuro-fuzzy inference system (ANFIS to forecast EMP signals in different electricity markets and wind power in Portugal, in the short-term, considering only historical data. Test results are provided by comparing with other reported studies, demonstrating the proficiency of the proposed hybrid approach in a real environment.

  8. Wind power forecasting-a review of the state of the art

    DEFF Research Database (Denmark)

    Giebel, Gregor; Kariniotakis, George

    2017-01-01

    This chapter gives an overview over past and present attempts to predict wind power for single turbines, wind, farms or for whole regions, for a few minutes up to a few days ahead. It is based on a survey and report (Giebel et al., 2011) initiated in the frame of the European project ANEMOS, whic...

  9. Eco-forecasting see different for or against the big wind power sites development

    International Nuclear Information System (INIS)

    Wallut, J.M.; Bal, J.L.

    2002-01-01

    The wind energy is the most economical and technological developed industry of the renewable energy, but it is not perhaps the best way to fight with the greenhouse gases. The pro and the con of the wind power are discussed in this paper. (A.L.B.)

  10. The “Weather Intelligence for Renewable Energies” Benchmarking Exercise on Short-Term Forecasting of Wind and Solar Power Generation

    DEFF Research Database (Denmark)

    Sperati, Simone; Alessandrini, Stefano; Pinson, Pierre

    2015-01-01

    A benchmarking exercise was organized within the framework of the European Action Weather Intelligence for Renewable Energies (“WIRE”) with the purpose of evaluating the performance of state of the art models for short-term renewable energy forecasting. The exercise consisted in forecasting...... the power output of two wind farms and two photovoltaic power plants, in order to compare the merits of forecasts based on different modeling approaches and input data. It was thus possible to obtain a better knowledge of the state of the art in both wind and solar power forecasting, with an overview...... and comparison of the principal and the novel approaches that are used today in the field, and to assess the evolution of forecast performance with respect to previous benchmarking exercises. The outcome of this exercise consisted then in proposing new challenges in the renewable power forecasting field...

  11. The “Weather Intelligence for Renewable Energies” Benchmarking Exercise on Short-Term Forecasting of Wind and Solar Power Generation

    Directory of Open Access Journals (Sweden)

    Simone Sperati

    2015-09-01

    Full Text Available A benchmarking exercise was organized within the framework of the European Action Weather Intelligence for Renewable Energies (“WIRE” with the purpose of evaluating the performance of state of the art models for short-term renewable energy forecasting. The exercise consisted in forecasting the power output of two wind farms and two photovoltaic power plants, in order to compare the merits of forecasts based on different modeling approaches and input data. It was thus possible to obtain a better knowledge of the state of the art in both wind and solar power forecasting, with an overview and comparison of the principal and the novel approaches that are used today in the field, and to assess the evolution of forecast performance with respect to previous benchmarking exercises. The outcome of this exercise consisted then in proposing new challenges in the renewable power forecasting field and identifying the main areas for improving accuracy in the future.

  12. MPC for Wind Power Gradients - Utilizing Forecasts, Rotor Inertia, and Central Energy Storage

    DEFF Research Database (Denmark)

    Hovgaard, Tobias Gybel; Larsen, Lars F. S.; Jørgensen, John Bagterp

    2013-01-01

    decentralized energy storage in the turbines’ inertia combined with a central storage unit or deferrable consumers can be utilized to achieve this goal at a minimum cost. We propose a variation on model predictive control to incorporate predictions of wind speed. Due to the aerodynamics of the turbines...... the model contains nonconvex terms. To handle this nonconvexity, we propose a sequential convex optimization method, which typically converges in fewer than 10 iterations. We demonstrate our method in simulations with various wind scenarios and prices for energy storage. These simulations show substantial......We consider the control of a wind power plant, possibly consisting of many individual wind turbines. The goal is to maximize the energy delivered to the power grid under very strict grid requirements to power quality. We define an extremely low power output gradient and demonstrate how...

  13. Integrated Wind Power Planning Tool

    DEFF Research Database (Denmark)

    Rosgaard, Martin H.; Hahmann, Andrea N.; Nielsen, Torben S.

    This poster presents the Public Service Obligation (PSO) funded project PSO 10464 "Integrated Wind Power Planning Tool". The project goal is to integrate a Numerical Weather Prediction (NWP) model with statistical tools in order to assess wind power fluctuations, with focus on short term...... forecasting for existing wind farms, as well as long term power system planning for future wind farms....

  14. A Multi Time Scale Wind Power Forecasting Model of a Chaotic Echo State Network Based on a Hybrid Algorithm of Particle Swarm Optimization and Tabu Search

    Directory of Open Access Journals (Sweden)

    Xiaomin Xu

    2015-11-01

    Full Text Available The uncertainty and regularity of wind power generation are caused by wind resources’ intermittent and randomness. Such volatility brings severe challenges to the wind power grid. The requirements for ultrashort-term and short-term wind power forecasting with high prediction accuracy of the model used, have great significance for reducing the phenomenon of abandoned wind power , optimizing the conventional power generation plan, adjusting the maintenance schedule and developing real-time monitoring systems. Therefore, accurate forecasting of wind power generation is important in electric load forecasting. The echo state network (ESN is a new recurrent neural network composed of input, hidden layer and output layers. It can approximate well the nonlinear system and achieves great results in nonlinear chaotic time series forecasting. Besides, the ESN is simpler and less computationally demanding than the traditional neural network training, which provides more accurate training results. Aiming at addressing the disadvantages of standard ESN, this paper has made some improvements. Combined with the complementary advantages of particle swarm optimization and tabu search, the generalization of ESN is improved. To verify the validity and applicability of this method, case studies of multitime scale forecasting of wind power output are carried out to reconstruct the chaotic time series of the actual wind power generation data in a certain region to predict wind power generation. Meanwhile, the influence of seasonal factors on wind power is taken into consideration. Compared with the classical ESN and the conventional Back Propagation (BP neural network, the results verify the superiority of the proposed method.

  15. Wind power

    International Nuclear Information System (INIS)

    Gipe, P.

    2007-01-01

    This book is a translation of the edition published in the USA under the title of ''wind power: renewable energy for home, farm and business''. In the wake of mass blackouts and energy crises, wind power remains a largely untapped resource of renewable energy. It is a booming worldwide industry whose technology, under the collective wing of aficionados like author Paul Gipe, is coming of age. Wind Power guides us through the emergent, sometimes daunting discourse on wind technology, giving frank explanations of how to use wind technology wisely and sound advice on how to avoid common mistakes. Since the mid-1970's, Paul Gipe has played a part in nearly every aspect of wind energy development from installing small turbines to promoting wind energy worldwide. As an American proponent of renewable energy, Gipe has earned the acclaim and respect of European energy specialists for years, but his arguments have often fallen on deaf ears at home. Today, the topic of wind power is cropping up everywhere from the beaches of Cape Cod to the Oregon-Washington border, and one wind turbine is capable of producing enough electricity per year to run 200 average American households. Now, Paul Gipe is back to shed light on this increasingly important energy source with a revised edition of Wind Power. Over the course of his career, Paul Gipe has been a proponent, participant, observer, and critic of the wind industry. His experience with wind has given rise to two previous books on the subject, Wind Energy Basics and Wind Power for Home and Business, which have sold over 50,000 copies. Wind Power for Home and Business has become a staple for both homeowners and professionals interested in the subject, and now, with energy prices soaring, interest in wind power is hitting an all-time high. With chapters on output and economics, Wind Power discloses how much you can expect from each method of wind technology, both in terms of energy and financial savings. The book updated models

  16. Improving weather forecasts for wind energy applications

    Science.gov (United States)

    Kay, Merlinde; MacGill, Iain

    2010-08-01

    Weather forecasts play an important role in the energy industry particularly because of the impact of temperature on electrical demand. Power system operation requires that this variable and somewhat unpredictable demand be precisely met at all times and locations from available generation. As wind generation makes up a growing component of electricity supply around the world, it has become increasingly important to be able to provide useful forecasting for this highly variable and uncertain energy resource. Of particular interest are forecasts of weather events that rapidly change wind energy production from one or more wind farms. In this paper we describe work underway to improve the wind forecasts currently available from standard Numerical Weather Prediction (NWP) through a bias correction methodology. Our study has used the Australian Bureau of Meteorology MesoLAPS 5 km limited domain model over the Victoria/Tasmania region, providing forecasts for the Woolnorth wind farm, situated in Tasmania, Australia. The accuracy of these forecasts has been investigated, concentrating on the key wind speed ranges 5 - 15 ms-1 and around 25 ms-1. A bias correction methodology was applied to the NWP hourly forecasts to help account for systematic issues such as the NWP grid point not being at the exact location of the wind farm. An additional correction was applied for timing issues by using meteorological data from the wind farm. Results to date show a reduction in spread of forecast error for hour ahead forecasts by as much as half using this double correction methodology - a combination of both bias correction and timing correction.

  17. Improving weather forecasts for wind energy applications

    International Nuclear Information System (INIS)

    Kay, Merlinde; MacGill, Iain

    2010-01-01

    Weather forecasts play an important role in the energy industry particularly because of the impact of temperature on electrical demand. Power system operation requires that this variable and somewhat unpredictable demand be precisely met at all times and locations from available generation. As wind generation makes up a growing component of electricity supply around the world, it has become increasingly important to be able to provide useful forecasting for this highly variable and uncertain energy resource. Of particular interest are forecasts of weather events that rapidly change wind energy production from one or more wind farms. In this paper we describe work underway to improve the wind forecasts currently available from standard Numerical Weather Prediction (NWP) through a bias correction methodology. Our study has used the Australian Bureau of Meteorology MesoLAPS 5 km limited domain model over the Victoria/Tasmania region, providing forecasts for the Woolnorth wind farm, situated in Tasmania, Australia. The accuracy of these forecasts has been investigated, concentrating on the key wind speed ranges 5 - 15 ms -1 and around 25 ms -1 . A bias correction methodology was applied to the NWP hourly forecasts to help account for systematic issues such as the NWP grid point not being at the exact location of the wind farm. An additional correction was applied for timing issues by using meteorological data from the wind farm. Results to date show a reduction in spread of forecast error for hour ahead forecasts by as much as half using this double correction methodology - a combination of both bias correction and timing correction.

  18. A Time-Varying Potential-Based Demand Response Method for Mitigating the Impacts of Wind Power Forecasting Errors

    Directory of Open Access Journals (Sweden)

    Jia Ning

    2017-11-01

    Full Text Available The uncertainty of wind power results in wind power forecasting errors (WPFE which lead to difficulties in formulating dispatching strategies to maintain the power balance. Demand response (DR is a promising tool to balance power by alleviating the impact of WPFE. This paper offers a control method of combining DR and automatic generation control (AGC units to smooth the system’s imbalance, considering the real-time DR potential (DRP and security constraints. A schematic diagram is proposed from the perspective of a dispatching center that manages smart appliances including air conditioner (AC, water heater (WH, electric vehicle (EV loads, and AGC units to maximize the wind accommodation. The presented model schedules the AC, WH, and EV loads without compromising the consumers’ comfort preferences. Meanwhile, the ramp constraint of generators and power flow transmission constraint are considered to guarantee the safety and stability of the power system. To demonstrate the performance of the proposed approach, simulations are performed in an IEEE 24-node system. The results indicate that considerable benefits can be realized by coordinating the DR and AGC units to mitigate the WPFE impacts.

  19. Limited Area Forecasting and Statistical Modelling for Wind Energy Scheduling

    DEFF Research Database (Denmark)

    Rosgaard, Martin Haubjerg

    forecast accuracy for operational wind power scheduling. Numerical weather prediction history and scales of atmospheric motion are summarised, followed by a literature review of limited area wind speed forecasting. Hereafter, the original contribution to research on the topic is outlined. The quality...... control of wind farm data used as forecast reference is described in detail, and a preliminary limited area forecasting study illustrates the aggravation of issues related to numerical orography representation and accurate reference coordinates at ne weather model resolutions. For the o shore and coastal...... sites studied limited area forecasting is found to deteriorate wind speed prediction accuracy, while inland results exhibit a steady forecast performance increase with weather model resolution. Temporal smoothing of wind speed forecasts is shown to improve wind power forecast performance by up to almost...

  20. Rejoinder on: Space-time wind speed forecasting for improved power system dispatch

    KAUST Repository

    Zhu, Xinxin

    2014-02-27

    We are thankful to the four reviewers for providing very valuable and insightful comments. We have divided our rejoinder into two main parts: (1) the rotating RSTD model; and (2) the integration of wind power into a power system. In each part, we present our views on the various comments of the discussants and provide further discussion. © 2014 Sociedad de Estadística e Investigación Operativa.

  1. ANEMOS: Development of a next generation wind power forecasting system for the large-scale integration of onshore and offshore wind farms.

    Science.gov (United States)

    Kariniotakis, G.; Anemos Team

    2003-04-01

    Objectives: Accurate forecasting of the wind energy production up to two days ahead is recognized as a major contribution for reliable large-scale wind power integration. Especially, in a liberalized electricity market, prediction tools enhance the position of wind energy compared to other forms of dispatchable generation. ANEMOS, is a new 3.5 years R&D project supported by the European Commission, that resembles research organizations and end-users with an important experience on the domain. The project aims to develop advanced forecasting models that will substantially outperform current methods. Emphasis is given to situations like complex terrain, extreme weather conditions, as well as to offshore prediction for which no specific tools currently exist. The prediction models will be implemented in a software platform and installed for online operation at onshore and offshore wind farms by the end-users participating in the project. Approach: The paper presents the methodology of the project. Initially, the prediction requirements are identified according to the profiles of the end-users. The project develops prediction models based on both a physical and an alternative statistical approach. Research on physical models gives emphasis to techniques for use in complex terrain and the development of prediction tools based on CFD techniques, advanced model output statistics or high-resolution meteorological information. Statistical models (i.e. based on artificial intelligence) are developed for downscaling, power curve representation, upscaling for prediction at regional or national level, etc. A benchmarking process is set-up to evaluate the performance of the developed models and to compare them with existing ones using a number of case studies. The synergy between statistical and physical approaches is examined to identify promising areas for further improvement of forecasting accuracy. Appropriate physical and statistical prediction models are also developed for

  2. Evaluation of the wind farm parameterization in the Weather Research and Forecasting model (version 3.8.1) with meteorological and turbine power data

    Science.gov (United States)

    Lee, Joseph C. Y.; Lundquist, Julie K.

    2017-11-01

    Forecasts of wind-power production are necessary to facilitate the integration of wind energy into power grids, and these forecasts should incorporate the impact of wind-turbine wakes. This paper focuses on a case study of four diurnal cycles with significant power production, and assesses the skill of the wind farm parameterization (WFP) distributed with the Weather Research and Forecasting (WRF) model version 3.8.1, as well as its sensitivity to model configuration. After validating the simulated ambient flow with observations, we quantify the value of the WFP as it accounts for wake impacts on power production of downwind turbines. We also illustrate with statistical significance that a vertical grid with approximately 12 m vertical resolution is necessary for reproducing the observed power production. Further, the WFP overestimates wake effects and hence underestimates downwind power production during high wind speed, highly stable, and low turbulence conditions. We also find the WFP performance is independent of the number of wind turbines per model grid cell and the upwind-downwind position of turbines. Rather, the ability of the WFP to predict power production is most dependent on the skill of the WRF model in simulating the ambient wind speed.

  3. Evaluation of the wind farm parameterization in the Weather Research and Forecasting model (version 3.8.1 with meteorological and turbine power data

    Directory of Open Access Journals (Sweden)

    J. C. Y. Lee

    2017-11-01

    Full Text Available Forecasts of wind-power production are necessary to facilitate the integration of wind energy into power grids, and these forecasts should incorporate the impact of wind-turbine wakes. This paper focuses on a case study of four diurnal cycles with significant power production, and assesses the skill of the wind farm parameterization (WFP distributed with the Weather Research and Forecasting (WRF model version 3.8.1, as well as its sensitivity to model configuration. After validating the simulated ambient flow with observations, we quantify the value of the WFP as it accounts for wake impacts on power production of downwind turbines. We also illustrate with statistical significance that a vertical grid with approximately 12 m vertical resolution is necessary for reproducing the observed power production. Further, the WFP overestimates wake effects and hence underestimates downwind power production during high wind speed, highly stable, and low turbulence conditions. We also find the WFP performance is independent of the number of wind turbines per model grid cell and the upwind–downwind position of turbines. Rather, the ability of the WFP to predict power production is most dependent on the skill of the WRF model in simulating the ambient wind speed.

  4. Decision Support Tools for Electricity Retailers, Wind Power and CHP Plants Using Probabilistic Forecasts

    DEFF Research Database (Denmark)

    Zugno, Marco; Morales González, Juan Miguel; Madsen, Henrik

    2015-01-01

    This paper reviews a number of applications of optimization under uncertainty in energy markets resulting from the research project ENSYMORA. A general mathematical formulation applicable to problems of optimization under uncertainty in energy markets is presented. This formulation can......: trading for a price-maker wind power producer, management of heat and power systems, operation for retailers in a dynamic-price market. A selection of results shows the viability and appropriateness of the presented stochastic optimization approaches for managing energy systems under uncertainty....

  5. The combined value of wind and solar power forecasting improvements and electricity storage

    Energy Technology Data Exchange (ETDEWEB)

    Hodge, Bri-Mathias; Brancucci Martinez-Anido, Carlo; Wang, Qin; Chartan, Erol; Florita, Anthony; Kiviluoma, Juha

    2018-03-01

    As the penetration rates of variable renewable energy increase, the value of power systems operation flexibility technology options, such as renewable energy forecasting improvements and electricity storage, is also assumed to increase. In this work, we examine the value of these two technologies, when used independently and concurrently, for two real case studies that represent the generation mixes for the California and Midcontinent Independent System Operators (CAISO and MISO). Since both technologies provide additional system flexibility they reduce operational costs and renewable curtailment for both generation mixes under study. Interestingly, the relative impacts are quite similar when both technologies are used together. Though both flexibility options can solve some of the same issues that arise with high penetration levels of renewables, they do not seem to significantly increase or decrease the economic potential of the other technology.

  6. Observability of wind power

    International Nuclear Information System (INIS)

    Gonot, J.P.; Fraisse, J.L.

    2009-01-01

    The total installed capacity of wind power grows from a few hundred MW at the beginning of 2005 to 3400 MW at the end of 2008. With such a trend, a total capacity of 7000 MW could be reached by 2010. The natural variability of wind power and the difficulty of its predictability require a change in the traditional way of managing supply/demand balance, day-ahead margins and the control of electrical flows. As a consequence, RTE operators should be informed quickly and reliably of the real time output power of wind farms and of its evolvement some hours or days ahead to ensure the reliability of the French electrical power system. French specificities are that wind farms are largely spread over the territory, that 95 % of wind farms have an output power below 10 MW and that they are connected to the distribution network. In this context, new tools were necessary to acquire as soon as possible data concerning wind power. In two years long, RTE set up an observatory of wind production 'IPES system' enable to get an access to the technical characteristics of the whole wind farms, to observe in real time 75 % of the wind generation and to implement a forecast model related to wind generation. (authors)

  7. Application and verification of ECMWF seasonal forecast for wind energy

    Science.gov (United States)

    Žagar, Mark; Marić, Tomislav; Qvist, Martin; Gulstad, Line

    2015-04-01

    A good understanding of long-term annual energy production (AEP) is crucial when assessing the business case of investing in green energy like wind power. The art of wind-resource assessment has emerged into a scientific discipline on its own, which has advanced at high pace over the last decade. This has resulted in continuous improvement of the AEP accuracy and, therefore, increase in business case certainty. Harvesting the full potential output of a wind farm or a portfolio of wind farms depends heavily on optimizing operation and management strategy. The necessary information for short-term planning (up to 14 days) is provided by standard weather and power forecasting services, and the long-term plans are based on climatology. However, the wind-power industry is lacking quality information on intermediate scales of the expected variability in seasonal and intra-annual variations and their geographical distribution. The seasonal power forecast presented here is designed to bridge this gap. The seasonal power production forecast is based on the ECMWF seasonal weather forecast and the Vestas' high-resolution, mesoscale weather library. The seasonal weather forecast is enriched through a layer of statistical post-processing added to relate large-scale wind speed anomalies to mesoscale climatology. The resulting predicted energy production anomalies, thus, include mesoscale effects not captured by the global forecasting systems. The turbine power output is non-linearly related to the wind speed, which has important implications for the wind power forecast. In theory, the wind power is proportional to the cube of wind speed. However, due to the nature of turbine design, this exponent is close to 3 only at low wind speeds, becomes smaller as the wind speed increases, and above 11-13 m/s the power output remains constant, called the rated power. The non-linear relationship between wind speed and the power output generally increases sensitivity of the forecasted power

  8. The Wind Forecast Improvement Project (WFIP). A Public-Private Partnership Addressing Wind Energy Forecast Needs

    Energy Technology Data Exchange (ETDEWEB)

    Wilczak, James M. [NOAA, Boulder, CO (United States); Finley, Cathy [WindLogics, Inc., St. Paul, MN (United States); Freedman, Jeff [AWS Truepower, Albany, NY (United States); Cline, Joel [USDOE Office of Energy Efficiency and Renewable Energy, Washington, DC (United States); Bianco, L. [Univ. of Colorado, Boulder, CO (United States); Olson, J. [Univ. of Colorado, Boulder, CO (United States); Djalaova, I. [Univ. of Colorado, Boulder, CO (United States); Sheridan, L. [WindLogics, Inc., St. Paul, MN (United States); Ahlstrom, M. [WindLogics, Inc., St. Paul, MN (United States); Manobianco, J. [Meso, Inc., Troy, NY (United States); Zack, J. [Meso, Inc., Troy, NY (United States); Carley, J. [National Oceanic and Atmospheric Administration (NOAA), College Park, MD (United States); Benjamin, S. [NOAA, Boulder, CO (United States); Coulter, R. L. [Argonne National Lab. (ANL), Lemont, IL (United States); Berg, Larry K. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Mirocha, Jeff D. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Clawson, K. [National Oceanic and Atmospheric Administration (NOAA), Idaho Falls, ID (United States); Natenberg, E. [Meso, Inc., Troy, NY (United States); Marquis, M. [NOAA, Boulder, CO (United States)

    2015-10-30

    The Wind Forecast Improvement Project (WFIP) is a public-private research program, the goals of which are to improve the accuracy of short-term (0-6 hr) wind power forecasts for the wind energy industry and then to quantify the economic savings that accrue from more efficient integration of wind energy into the electrical grid. WFIP was sponsored by the U.S. Department of Energy (DOE), with partners that include the National Oceanic and Atmospheric Administration (NOAA), private forecasting companies (WindLogics and AWS Truepower), DOE national laboratories, grid operators, and universities. WFIP employed two avenues for improving wind power forecasts: first, through the collection of special observations to be assimilated into forecast models to improve model initial conditions; and second, by upgrading NWP forecast models and ensembles. The new observations were collected during concurrent year-long field campaigns in two high wind energy resource areas of the U.S. (the upper Great Plains, and Texas), and included 12 wind profiling radars, 12 sodars, 184 instrumented tall towers and over 400 nacelle anemometers (provided by private industry), lidar, and several surface flux stations. Results demonstrate that a substantial improvement of up to 14% relative reduction in power root mean square error (RMSE) was achieved from the combination of improved NOAA numerical weather prediction (NWP) models and assimilation of the new observations. Data denial experiments run over select periods of time demonstrate that up to a 6% relative improvement came from the new observations. The use of ensemble forecasts produced even larger forecast improvements. Based on the success of WFIP, DOE is planning follow-on field programs.

  9. Drivers of imbalance cost of wind power

    DEFF Research Database (Denmark)

    Obersteiner, C.; Siewierski, T.; Andersen, Anders

    2010-01-01

    In Europe an increasing share of wind power is sold on the power market. Therefore more and more wind power generators become balancing responsible and face imbalance cost that reduce revenues from selling wind power. A comparison of literature illustrates that the imbalance cost of wind power...... varies in a wide range. To explain differences we indentify parameters influencing imbalance cost and compare them for case studies in Austria, Denmark and Poland. Besides the wind power forecast error also the correlation between imbalance and imbalance price influences imbalance cost significantly...... of imperfect forecast is better suited to reflect real cost incurred due to inaccurate wind power forecasts....

  10. Decision Support Tools for Electricity Retailers, Wind Power and CHP Plants Using Probabilistic Forecasts

    Directory of Open Access Journals (Sweden)

    Marco Zugno

    2015-06-01

    Full Text Available This paper reviews a number of applications of optimization under uncertainty in energy markets resulting from the research project ENSYMORA. A general mathematical formulation applicable to problems of optimization under uncertainty in energy markets is presented. This formulation can be effortlessly adapted to describe different approaches: the deterministic one (usable within a rolling horizon scheme, stochastic programming and robust optimization. The different features of this mathematical formulation are duly interpreted with a view to the energy applications reviewed in this paper: trading for a price-maker wind power producer, management of heat and power systems, operation for retailers in a dynamic-price market. A selection of results shows the viability and appropriateness of the presented stochastic optimization approaches for managing energy systems under uncertainty.

  11. Non-parametric probabilistic forecasts of wind power: required properties and evaluation

    DEFF Research Database (Denmark)

    Pinson, Pierre; Nielsen, Henrik Aalborg; Møller, Jan Kloppenborg

    2007-01-01

    of a single or a set of quantile forecasts. The required and desirable properties of such probabilistic forecasts are defined and a framework for their evaluation is proposed. This framework is applied for evaluating the quality of two statistical methods producing full predictive distributions from point...

  12. 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

  13. Wind power

    International Nuclear Information System (INIS)

    2006-06-01

    This road-map proposes by the Group Total aims to inform the public on the wind power. It presents the principles, the technology takes off, its applications and technology focus, the global market trends and the outlooks and Total commitments in the domain. (A.L.B.)

  14. Correlation-constrained and sparsity-controlled vector autoregressive model for spatio-temporal wind power forecasting

    DEFF Research Database (Denmark)

    Zhao, Yongning; Ye, Lin; Pinson, Pierre

    2018-01-01

    and forecasting, the original SC-VAR is modified and a Correlation-Constrained SC-VAR (CCSC-VAR) is proposed based on spatial correlation information about wind farms. Our approach is evaluated based on a case study of very-short-term forecasting for 25 wind farms in Denmark. Comparison is performed with a set...... of traditional local methods and spatio-temporal methods. The results obtained show the proposed CCSC-VAR has better overall performance than both the original SC-VAR and other benchmark methods, taking into account all evaluation indicators, including sparsitycontrol ability, sparsity, accuracy and efficiency...

  15. Probabilistic forecasts of wind power generation accounting for geographically dispersed information

    DEFF Research Database (Denmark)

    Tastu, Julija; Pinson, Pierre; Trombe, Pierre-Julien

    2014-01-01

    be optimized by accounting for spatio-temporal effects that are so far merely considered. The way these effects may be included in relevant models is described for the case of both parametric and nonparametric approaches to generating probabilistic forecasts. The resulting predictions are evaluated on the real...... of the first order moments of predictive densities. The best performing approach, based on adaptive quantile regression, using spatially corrected point forecasts as input, consistently outperforms the state-of-theartbenchmark based on local information only, by 1.5%-4.6%, depending upon the lead time....

  16. The use of different ensemble forecasting systems for wind power prediction on a real case in the South of Italy

    DEFF Research Database (Denmark)

    Alessandrini, Stefano; Sperati, Simone; Pinson, Pierre

    Short-term forecasting applied to wind energy is becoming increasingly important due to the constant growth of this renewable source, whose uncertainty requires a constant effort to meet the needs of the national electrical systems and their operators. Regarding to this, the probabilistic approac...

  17. Wind field forecast for accidental release of radiative materials

    International Nuclear Information System (INIS)

    Kang Ling; Chen Jiayi; Cai Xuhui

    2003-01-01

    A meso-scale wind field forecast model was designed for emergency environmental assessment in case of accidental release of radiative materials from a nuclear power station. Actual practice of the model showed that it runs fast, has wind field prediction function, and the result given is accurate. With meteorological data collected from weather stations, and pre-treated by a wind field diagnostic model, the initial wind fields at different times were inputted as initial values and assimilation fields for the forecasting model. The model, in turn, worked out to forecast meso-scale wind field of 24 hours in a horizontal domain of 205 km x 205 km. And then, the diagnostic model was employed again with the forecasting data to obtain more detail information of disturbed wind field by local terrain in a smaller domain of 20.5 km x 20.5 km, of which the nuclear power station is at the center. Using observation data in January, April, July and October of 1996 over the area of Hangzhou Bay, wind fields in these 4 months were simulated by different assimilation time and number of the weather stations for a sensitive test. Results indicated that the method used here has increased accuracy of the forecasted wind fields. And incorporating diagnostic method with the wind field forecast model has greatly increased efficiency of the wind field forecast for the smaller domain. This model and scheme have been used in Environmental Consequence Assessment System of Nuclear Accident in Qinshan Area

  18. Day-Ahead Wind Speed Forecasting Using Relevance Vector Machine

    Directory of Open Access Journals (Sweden)

    Guoqiang Sun

    2014-01-01

    Full Text Available With the development of wind power technology, the security of the power system, power quality, and stable operation will meet new challenges. So, in this paper, we propose a recently developed machine learning technique, relevance vector machine (RVM, for day-ahead wind speed forecasting. We combine Gaussian kernel function and polynomial kernel function to get mixed kernel for RVM. Then, RVM is compared with back propagation neural network (BP and support vector machine (SVM for wind speed forecasting in four seasons in precision and velocity; the forecast results demonstrate that the proposed method is reasonable and effective.

  19. Strategic wind power trading considering rival wind power production

    DEFF Research Database (Denmark)

    Exizidis, Lazaros; Kazempour, Jalal; Pinson, Pierre

    2016-01-01

    In an electricity market with high share of wind power, it is expected that wind power producers may exercise market power. However, wind producers have to cope with wind’s uncertain nature in order to optimally offer their generation, whereas in a market with more than one wind producers......, uncertainty of rival wind power generation should also be considered. Under this context, this paper addresses the impact of rival wind producers on the offering strategy and profits of a pricemaker wind producer. A stochastic day-ahead market setup is considered, which optimizes the day-ahead schedules...... considering a number of foreseen real-time scenarios. The results indicate that strategic wind producer is more likely to exercise market power having a mid-mean or low-mean forecast distribution, rather than having a high-mean one. Furthermore, it is observed that its offering strategy varies considerably...

  20. A Comparison of the Performance of Advanced Statistical Techniques for the Refinement of Day-ahead and Longer NWP-based Wind Power Forecasts

    Science.gov (United States)

    Zack, J. W.

    2015-12-01

    Predictions from Numerical Weather Prediction (NWP) models are the foundation for wind power forecasts for day-ahead and longer forecast horizons. The NWP models directly produce three-dimensional wind forecasts on their respective computational grids. These can be interpolated to the location and time of interest. However, these direct predictions typically contain significant systematic errors ("biases"). This is due to a variety of factors including the limited space-time resolution of the NWP models and shortcomings in the model's representation of physical processes. It has become common practice to attempt to improve the raw NWP forecasts by statistically adjusting them through a procedure that is widely known as Model Output Statistics (MOS). The challenge is to identify complex patterns of systematic errors and then use this knowledge to adjust the NWP predictions. The MOS-based improvements are the basis for much of the value added by commercial wind power forecast providers. There are an enormous number of statistical approaches that can be used to generate the MOS adjustments to the raw NWP forecasts. In order to obtain insight into the potential value of some of the newer and more sophisticated statistical techniques often referred to as "machine learning methods" a MOS-method comparison experiment has been performed for wind power generation facilities in 6 wind resource areas of California. The underlying NWP models that provided the raw forecasts were the two primary operational models of the US National Weather Service: the GFS and NAM models. The focus was on 1- and 2-day ahead forecasts of the hourly wind-based generation. The statistical methods evaluated included: (1) screening multiple linear regression, which served as a baseline method, (2) artificial neural networks, (3) a decision-tree approach called random forests, (4) gradient boosted regression based upon an decision-tree algorithm, (5) support vector regression and (6) analog ensemble

  1. Enhanced regional forecasting considering single wind farm distribution for upscaling

    International Nuclear Information System (INIS)

    Bremen, Lueder von; Saleck, Nadja; Heinemann, Detlev

    2007-01-01

    With increasing wind power penetration the need for more accurate wind power forecasts increases to raise the market value of wind power. State-of-the-art wind power forecasting tools are considered either statistical or physical. Fundamentally new techniques are rare, thus it is tried to establish a new approach. The spatial decomposition of wind power generation in Germany can be done with principle component analysis to extract the main pattern of variability. They have a physical meaning when linked with typical weather situation. The first four eigenvectors explain about 94 % of the observed variance. The time-evolving principle components are linked with the total wind power feed-in in Germany and are used for its estimation. A new wind power forecasting model has been implemented with this approach and shows very good results that are comparable with state-of-the-art commercial wind power forecast models. The day-ahead forecast error for a common intercomparison period Jan-Jul 2006 is 4.4 %. The suggested approach offers wide ranges for future developments (e.g. several NWP models), because it is computationally very cheap to run

  2. Wind Energy: Forecasting Challenges for its Operational Management

    DEFF Research Database (Denmark)

    Pinson, Pierre

    2013-01-01

    in a probabilistic framework. Even though,eventually, the forecaster may only communicate single-valued predictions.The existing approaches to wind power forecasting are subsequently described, with focus on single-valued predictions, predictive marginal densities and space-time trajectories. Upcoming challenges...... related to generating improved and new types of forecasts, as well as their verification and value to forecast users, are finally discussed. ½...

  3. Short-Term Wind Speed Hybrid Forecasting Model Based on Bias Correcting Study and Its Application

    OpenAIRE

    Mingfei Niu; Shaolong Sun; Jie Wu; Yuanlei Zhang

    2015-01-01

    The accuracy of wind speed forecasting is becoming increasingly important to improve and optimize renewable wind power generation. In particular, reliable short-term wind speed forecasting can enable model predictive control of wind turbines and real-time optimization of wind farm operation. However, due to the strong stochastic nature and dynamic uncertainty of wind speed, the forecasting of wind speed data using different patterns is difficult. This paper proposes a novel combination bias c...

  4. An improved market penetration model for wind energy technology forecasting

    Energy Technology Data Exchange (ETDEWEB)

    Lund, P.D. [Helsinki Univ. of Technology, Espoo (Finland). Advanced Energy Systems

    1995-12-31

    An improved market penetration model with application to wind energy forecasting is presented. In the model, a technology diffusion model and manufacturing learning curve are combined. Based on a 85% progress ratio that was found for European wind manufactures and on wind market statistics, an additional wind power capacity of ca 4 GW is needed in Europe to reach a 30 % price reduction. A full breakthrough to low-cost utility bulk power markets could be achieved at a 24 GW level. (author)

  5. An improved market penetration model for wind energy technology forecasting

    International Nuclear Information System (INIS)

    Lund, P.D.

    1995-01-01

    An improved market penetration model with application to wind energy forecasting is presented. In the model, a technology diffusion model and manufacturing learning curve are combined. Based on a 85% progress ratio that was found for European wind manufactures and on wind market statistics, an additional wind power capacity of ca 4 GW is needed in Europe to reach a 30 % price reduction. A full breakthrough to low-cost utility bulk power markets could be achieved at a 24 GW level. (author)

  6. Day-ahead wind speed forecasting using f-ARIMA models

    International Nuclear Information System (INIS)

    Kavasseri, Rajesh G.; Seetharaman, Krithika

    2009-01-01

    With the integration of wind energy into electricity grids, it is becoming increasingly important to obtain accurate wind speed/power forecasts. Accurate wind speed forecasts are necessary to schedule dispatchable generation and tariffs in the day-ahead electricity market. This paper examines the use of fractional-ARIMA or f-ARIMA models to model, and forecast wind speeds on the day-ahead (24 h) and two-day-ahead (48 h) horizons. The models are applied to wind speed records obtained from four potential wind generation sites in North Dakota. The forecasted wind speeds are used in conjunction with the power curve of an operational (NEG MICON, 750 kW) turbine to obtain corresponding forecasts of wind power production. The forecast errors in wind speed/power are analyzed and compared with the persistence model. Results indicate that significant improvements in forecasting accuracy are obtained with the proposed models compared to the persistence method. (author)

  7. 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...

  8. Multi-step wind speed forecasting based on a hybrid forecasting architecture and an improved bat algorithm

    International Nuclear Information System (INIS)

    Xiao, Liye; Qian, Feng; Shao, Wei

    2017-01-01

    Highlights: • Propose a hybrid architecture based on a modified bat algorithm for multi-step wind speed forecasting. • Improve the accuracy of multi-step wind speed forecasting. • Modify bat algorithm with CG to improve optimized performance. - Abstract: As one of the most promising sustainable energy sources, wind energy plays an important role in energy development because of its cleanliness without causing pollution. Generally, wind speed forecasting, which has an essential influence on wind power systems, is regarded as a challenging task. Analyses based on single-step wind speed forecasting have been widely used, but their results are insufficient in ensuring the reliability and controllability of wind power systems. In this paper, a new forecasting architecture based on decomposing algorithms and modified neural networks is successfully developed for multi-step wind speed forecasting. Four different hybrid models are contained in this architecture, and to further improve the forecasting performance, a modified bat algorithm (BA) with the conjugate gradient (CG) method is developed to optimize the initial weights between layers and thresholds of the hidden layer of neural networks. To investigate the forecasting abilities of the four models, the wind speed data collected from four different wind power stations in Penglai, China, were used as a case study. The numerical experiments showed that the hybrid model including the singular spectrum analysis and general regression neural network with CG-BA (SSA-CG-BA-GRNN) achieved the most accurate forecasting results in one-step to three-step wind speed forecasting.

  9. Trend chart: wind power. Third quarter 2016

    International Nuclear Information System (INIS)

    Reynaud, Didier

    2016-11-01

    This publication presents the wind energy situation of continental France and overseas territories during the third quarter 2016: total connected load, new connected facilities, regional distribution of wind power production, evolution of quarterly production, distribution of facilities versus power, evolution forecasts of the French wind power park, projects in progress, detailed regional results, methodology used

  10. Trend chart: wind power. Second quarter 2016

    International Nuclear Information System (INIS)

    Reynaud, Didier

    2016-08-01

    This publication presents the wind energy situation of continental France and overseas territories during the second quarter 2016: total connected load, new connected facilities, regional distribution of wind power production, evolution of quarterly production, distribution of facilities versus power, evolution forecasts of the French wind power park, projects in progress, detailed regional results, methodology used

  11. Trend chart: wind power. First quarter 2017

    International Nuclear Information System (INIS)

    2017-05-01

    This publication presents the wind energy situation of continental France and overseas territories during the first quarter 2017: total connected load, new connected facilities, regional distribution of wind power production, evolution of quarterly production, distribution of facilities versus power, evolution forecasts of the French wind power park, projects in progress, detailed regional results, methodology used

  12. Trend chart: wind power. First quarter 2016

    International Nuclear Information System (INIS)

    Reynaud, Didier

    2016-05-01

    This publication presents the wind energy situation of continental France and overseas territories during the first quarter 2016: total connected load, new connected facilities, regional distribution of wind power production, evolution of quarterly production, distribution of facilities versus power, evolution forecasts of the French wind power park, projects in progress, detailed regional results, methodology used

  13. Trend chart: wind power. Third quarter 2015

    International Nuclear Information System (INIS)

    Reynaud, Didier

    2015-11-01

    This publication presents the wind energy situation of continental France and overseas territories during the third quarter 2015: total connected load, new connected facilities, regional distribution of wind power production, evolution of quarterly production, distribution of facilities versus power, evolution forecasts of the French wind power park, projects in progress, detailed regional results, methodology used

  14. Trend chart: wind power. Forth quarter 2015

    International Nuclear Information System (INIS)

    Reynaud, Didier

    2016-02-01

    This publication presents the wind energy situation of continental France and overseas territories during the forth quarter 2015: total connected load, new connected facilities, regional distribution of wind power production, evolution of quarterly production, distribution of facilities versus power, evolution forecasts of the French wind power park, projects in progress, detailed regional results, methodology used

  15. Trend chart: wind power. Forth quarter 2016

    International Nuclear Information System (INIS)

    Coltier, Yves

    2017-02-01

    This publication presents the wind energy situation of continental France and overseas territories during the forth quarter 2016: total connected load, new connected facilities, regional distribution of wind power production, evolution of quarterly production, distribution of facilities versus power, evolution forecasts of the French wind power park, projects in progress, detailed regional results, methodology used

  16. Trend chart: wind power. Fourth quarter 2017

    International Nuclear Information System (INIS)

    Moreau, Sylvain

    2018-02-01

    This publication presents the wind energy situation of continental France and overseas territories during the fourth quarter 2017: total connected load, new connected facilities, regional distribution of wind power production, evolution of quarterly production, distribution of facilities versus power, evolution forecasts of the French wind power park, projects in progress, detailed regional results, revision of results

  17. Trend chart: wind power. Third quarter 2017

    International Nuclear Information System (INIS)

    2017-11-01

    This publication presents the wind energy situation of continental France and overseas territories during the third quarter 2017: total connected load, new connected facilities, regional distribution of wind power production, evolution of quarterly production, distribution of facilities versus power, evolution forecasts of the French wind power park, projects in progress, detailed regional results, revision of results

  18. Trend chart: wind power. Second quarter 2017

    International Nuclear Information System (INIS)

    2017-08-01

    This publication presents the wind energy situation of continental France and overseas territories during the second quarter 2017: total connected load, new connected facilities, regional distribution of wind power production, evolution of quarterly production, distribution of facilities versus power, evolution forecasts of the French wind power park, projects in progress, detailed regional results, revision of results

  19. Wind power variability and power system reserves in South Africa

    DEFF Research Database (Denmark)

    Sørensen, Poul Ejnar; Litong-Palima, Marisciel; Hahmann, Andrea N.

    2017-01-01

    Variable renewable generation, primarily from wind and solar, introduces new uncertainties in the operation of power systems. This paper describes and applies a method to quantify how wind power development will affect the use of short-term automatic reserves in the future South African power...... system. The study uses a scenario for wind power development in South Africa, based on information from the South African transmission system operator (Eskom) and the Department of Energy. The scenario foresees 5% wind power penetration by 2025. Time series for wind power production and forecasts...... are simulated, and the duration curves for wind power ramp rates and wind power forecast errors are applied to assess the use of reserves due to wind power variability. The main finding is that the 5% wind power penetration in 2025 will increase the use of short-term automatic reserves by approximately 2%....

  20. From short term power forecasting to nowcasting - Benefiting from meteorological forecasts and measurements

    Science.gov (United States)

    Mey, Britta; Braun, Axel; Good, Garrett; Vogt, Stephan; Wessel, Arne; Dobschinski, Jan

    2016-04-01

    Today, wind and solar power forecasts with time horizons from zero to about three hours are essential for the reliable grid and market integration of wind and solar energy. With respect to closure times of German intra-day markets, power forecasts with time horizons of about one to two hours and an update frequency of 15 minutes are required for final trading activities, reducing the uncertainty of the day-ahead forecast of the previous day. Regarding grid security aspects, grid operators utilize such forecasts to create continuous intra-day grid congestion forecasts. In addition to these preventive measures, wind and solar power become more and more important for the provision of ancillary services by wind and solar farm operators. This use case mainly requires power forecasts with time horizons of less than one hour. In general, forecasts with time horizons below three hours are investigated within the nowcasting research area. Nowcasting models are mainly based on current observations and extrapolation methods. With respect to wind and solar power forecasts with horizons of up to three hours, it has been shown in studies that real-time power measurements have the highest information content as compared to other potential model input parameters. We will present results from studies focusing on the benefit of meteorological data (forecasts and/or measurements) in the field of solar and wind power forecasts with time horizons of up to a few hours. Wind farm forecast errors are for example reduced by using numerical weather prediction (NWP) data in the wind power prediction model along with real-time wind farm power measurements. Furthermore, spatially distributed NWP data in combination with German total wind power measurements helped in the reduction of extreme forecast errors. By using global radiation forecasts as an input for wind power forecasts, forecast error during sunrise and sunset could be reduced. In the field of German total solar power, nowcasting

  1. Integrated Wind Power Planning Tool

    DEFF Research Database (Denmark)

    Rosgaard, M. H.; Hahmann, Andrea N.; Nielsen, T. S.

    This poster describes the status as of April 2012 of the Public Service Obligation (PSO) funded project PSO 10464 \\Integrated Wind Power Planning Tool". The project goal is to integrate a meso scale numerical weather prediction (NWP) model with a statistical tool in order to better predict short...... term power variation from off shore wind farms, as well as to conduct forecast error assessment studies in preparation for later implementation of such a feature in an existing simulation model. The addition of a forecast error estimation feature will further increase the value of this tool, as it...

  2. Impact of Public Aggregate Wind Forecasts on Electricity Market Outcomes

    DEFF Research Database (Denmark)

    Exizidis, Lazaros; Kazempour, Jalal; Pinson, Pierre

    2017-01-01

    Following a call to foster a transparent and more competitive market, member states of the European transmission system operator are required to publish, among other information, aggregate wind power forecasts. The publication of the latter information is expected to benefit market participants...... by offering better knowledge of the market operation, leading subsequently to a more competitive energy market. Driven by the above regulation, we consider an equilibrium study to address how public information of aggregate wind power forecasts can potentially affect market results, social welfare as well...... as the profits of participating power producers. We investigate, therefore, a joint day-ahead energy and reserve auction, where producers offer their conventional power strategically based on a complementarity approach and their wind power at generation cost based on a forecast. In parallel, an iterative game...

  3. Latin America wind market assessment. Forecast 2013-2022

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2013-10-15

    Wind Power Activities by Country: Developers/Owners, Wind Plant Sizes, Wind Turbines Deployed, Commissioning Dates, Market Share, and Capacity Forecasts Latin American markets are a subject of intense interest from the global wind industry. Wind plant construction across Latin America is modest compared to the more established markets like the United States, Europe, and China, but it is an emerging market that is taking off at a rapid pace. The region has become the hottest alternative growth market for the wind energy industry at a time when growth rates in other markets are flat due to a variety of policy and macroeconomic challenges. Globalization is driving sustainable economic growth in most Latin American countries, resulting in greater energy demand. Wind is increasingly viewed as a valuable and essential answer to increasing electricity generation across most markets in Latin America. Strong wind resources, coupled with today's sophisticated wind turbines, are providing cost-effective generation that is competitive with fossil fuel generation. Most Latin American countries also rely heavily on hydroelectricity, which balances well with variable wind generation. Navigant Research forecasts that if most wind plants under construction with planned commissioning go online as scheduled, annual wind power installations in Latin America will grow from nearly 2.2 GW in 2013 to 4.3 GW by 2022. This Navigant Research report provides a comprehensive view of the wind energy market dynamics at play in Latin America. It offers a country-by-country analysis, outlining the key energy policies and development opportunities and barriers and identifying which companies own operational wind plants and which wind turbine vendors supplied those projects. Market forecasts for wind power installations, capacity, and market share in Latin America, segmented by country and company, extend through 2022. The report also offers an especially close analysis of Brazil and Mexico

  4. Integrated Wind Power Planning Tool

    DEFF Research Database (Denmark)

    Rosgaard, M. H.; Giebel, Gregor; Nielsen, T. S.

    2012-01-01

    This poster presents the current state of the public service obligation (PSO) funded project PSO 10464, with the working title "Integrated Wind Power Planning Tool". The project commenced October 1, 2011, and the goal is to integrate a numerical weather prediction (NWP) model with purely statisti......This poster presents the current state of the public service obligation (PSO) funded project PSO 10464, with the working title "Integrated Wind Power Planning Tool". The project commenced October 1, 2011, and the goal is to integrate a numerical weather prediction (NWP) model with purely...... statistical tools in order to assess wind power fluctuations, with focus on long term power system planning for future wind farms as well as short term forecasting for existing wind farms. Currently, wind power fluctuation models are either purely statistical or integrated with NWP models of limited...... resolution. With regard to the latter, one such simulation tool has been developed at the Wind Energy Division, Risø DTU, intended for long term power system planning. As part of the PSO project the inferior NWP model used at present will be replaced by the state-of-the-art Weather Research & Forecasting...

  5. The impact of wind power on electricity prices

    Energy Technology Data Exchange (ETDEWEB)

    Brancucci Martinez-Anido, Carlo; Brinkman, Greg; Hodge, Bri-Mathias

    2016-08-01

    This paper investigates the impact of wind power on electricity prices using a production cost model of the Independent System Operator - New England power system. Different scenarios in terms of wind penetration, wind forecasts, and wind curtailment are modeled in order to analyze the impact of wind power on electricity prices for different wind penetration levels and for different levels of wind power visibility and controllability. The analysis concludes that electricity price volatility increases even as electricity prices decrease with increasing wind penetration levels. The impact of wind power on price volatility is larger in the shorter term (5-min compared to hour-to-hour). The results presented show that over-forecasting wind power increases electricity prices while under-forecasting wind power reduces them. The modeling results also show that controlling wind power by allowing curtailment increases electricity prices, and for higher wind penetrations it also reduces their volatility.

  6. The Forecasting Procedure for Long-Term Wind Speed in the Zhangye Area

    OpenAIRE

    Guo, Zhenhai; Dong, Yao; Wang, Jianzhou; Lu, Haiyan

    2010-01-01

    Energy crisis has made it urgent to find alternative energy sources for sustainable energy supply; wind energy is one of the attractive alternatives. Within a wind energy system, the wind speed is one key parameter; accurately forecasting of wind speed can minimize the scheduling errors and in turn increase the reliability of the electric power grid and reduce the power market ancillary service costs. This paper proposes a new hybrid model for long-term wind speed forecasting based on the fir...

  7. Climatology and trend of wind power resources in China and its surrounding regions: a revisit using Climate Forecast System Reanalysis data

    Science.gov (United States)

    Lejiang Yu; Shiyuan Zhong; Xindi Bian; Warren E. Heilman

    2015-01-01

    The mean climatology, seasonal and interannual variability and trend of wind speeds at the hub height (80 m) of modern wind turbines over China and its surrounding regions are revisited using 33-year (1979–2011) wind data from the Climate Forecast System Reanalysis (CFSR) that has many improvements including higher spatial resolution over previous global reanalysis...

  8. From wind ensembles to probabilistic information about future wind power production - results from an actual application

    DEFF Research Database (Denmark)

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

    2006-01-01

    horizon we aim at supplying quantiles of the wind power production conditional on the information available at the time at which the forecast is generated. This involves: (i) transformation of meteorological ensemble forecasts into wind power ensemble forecasts and (ii) calculation of quantiles based......Meteorological ensemble forecasts aim at quantifying the uncertainty of the future development of the weather by supplying several possible scenarios of this development. Here we address the use of such scenarios in probabilistic forecasting of wind power production. Specifically, for each forecast...... on the wind power ensemble forecasts. Given measurements of power production, representing a region or a single wind farm, we have developed methods applicable for these two steps. While (ii) should in principle be a simple task we found that the probabilistic information contained in the wind power ensembles...

  9. Wind Power Meteorology

    DEFF Research Database (Denmark)

    Lundtang Petersen, Erik; Mortensen, Niels Gylling; Landberg, Lars

    Wind power meteorology has evolved as an applied science, firmly founded on boundary-layer meteorology, but with strong links to climatology and geography. It concerns itself with three main areas: siting of wind turbines, regional wind resource assessment, and short-term prediction of the wind...... resource. The history, status and perspectives of wind power meteorology are presented, with emphasis on physical considerations and on its practical application. Following a global view of the wind resource, the elements of boundary layer meteorology which are most important for wind energy are reviewed......: wind profiles and shear, turbulence and gust, and extreme winds. The data used in wind power meteorology stem mainly from three sources: onsite wind measurements, the synoptic networks, and the re-analysis projects. Wind climate analysis, wind resource estimation and siting further require a detailed...

  10. Evaluation of Dynamical Downscaling Resolution Effect on Wind Energy Forecast Value for a Wind Farm in Central Sweden

    DEFF Research Database (Denmark)

    Rosgaard, Martin Haubjerg; Hahmann, Andrea N.; Nielsen, Torben Skov

    2014-01-01

    For any energy system relying on wind power, accurate forecasts of wind fluctuations are essential for efficient integration into the power grid. Increased forecast precision allows end-users to plan day-ahead operation with reduced risk of penalties which in turn supports the feasibility of wind...... energy. The present study aims to quantify value added to wind energy forecasts in the 12-48 hour leadtime by downscaling global numerical weather prediction (NWP) data from the National Centers for Environmental Prediction Global Forecast System (GFS) using the limited-area NWP model described...

  11. Climatological attribution of wind power ramp events in East Japan and their probabilistic forecast based on multi-model ensembles downscaled by analog ensemble using self-organizing maps

    Science.gov (United States)

    Ohba, Masamichi; Nohara, Daisuke; Kadokura, Shinji

    2016-04-01

    Severe storms or other extreme weather events can interrupt the spin of wind turbines in large scale that cause unexpected "wind ramp events". In this study, we present an application of self-organizing maps (SOMs) for climatological attribution of the wind ramp events and their probabilistic prediction. The SOM is an automatic data-mining clustering technique, which allows us to summarize a high-dimensional data space in terms of a set of reference vectors. The SOM is applied to analyze and connect the relationship between atmospheric patterns over Japan and wind power generation. SOM is employed on sea level pressure derived from the JRA55 reanalysis over the target area (Tohoku region in Japan), whereby a two-dimensional lattice of weather patterns (WPs) classified during the 1977-2013 period is obtained. To compare with the atmospheric data, the long-term wind power generation is reconstructed by using a high-resolution surface observation network AMeDAS (Automated Meteorological Data Acquisition System) in Japan. Our analysis extracts seven typical WPs, which are linked to frequent occurrences of wind ramp events. Probabilistic forecasts to wind power generation and ramps are conducted by using the obtained SOM. The probability are derived from the multiple SOM lattices based on the matching of output from TIGGE multi-model global forecast to the WPs on the lattices. Since this method effectively takes care of the empirical uncertainties from the historical data, wind power generation and ramp is probabilistically forecasted from the forecasts of global models. The predictability skill of the forecasts for the wind power generation and ramp events show the relatively good skill score under the downscaling technique. It is expected that the results of this study provides better guidance to the user community and contribute to future development of system operation model for the transmission grid operator.

  12. Wind Power Now!

    Science.gov (United States)

    Inglis, David Rittenhouse

    1975-01-01

    The government promotes and heavily subsidizes research in nuclear power plants. Federal development of wind power is slow in comparison even though much research with large wind-electric machines has already been conducted. Unless wind power programs are accelerated it will not become a major energy alternative to nuclear power. (MR)

  13. Interval forecasts of a novelty hybrid model for wind speeds

    Directory of Open Access Journals (Sweden)

    Shanshan Qin

    2015-11-01

    Full Text Available The utilization of wind energy, as a booming technology in the field of renewable energies, has been highly regarded around the world. Quantification of uncertainties associated with accurate wind speed forecasts is essential for regulating wind power generation and integration. However, it remains difficult work primarily due to the stochastic and nonlinear characteristics of wind speed series. Traditional models for wind speed forecasting mostly focus on generating certain predictive values, which cannot properly handle uncertainties. For quantifying potential uncertainties, a hybrid model constructed by the Cuckoo Search Optimization (CSO-based Back Propagation Neural Network (BPNN is proposed to establish wind speed interval forecasts (IFs by estimating the lower and upper bounds. The quality of IFs is assessed quantitatively using IFs coverage probability (IFCP and IFs normalized average width (IFNAW. Moreover, to assess the overall quality of IFs comprehensively, a tradeoff between informativeness (IFNAW and validity (IFCP of IFs is examined by coverage width-based criteria (CWC. As an applicative study, wind speeds from the Xinjiang Region in China are used to validate the proposed hybrid model. The results demonstrate that the proposed model can construct higher quality IFs for short-term wind speed forecasts.

  14. Evaluation of Dynamical Downscaling Resolution Effect on Wind Energy Forecast Value for a Wind Farm in Central Sweden

    DEFF Research Database (Denmark)

    Rosgaard, Martin Haubjerg; Hahmann, Andrea N.; Nielsen, Torben Skov

    For any energy system relying on wind power, accurate forecasts of wind fluctuations are essential for efficient utilisation in the power grid. Statistical wind power prediction tools [1] use numerical weather prediction (NWP) model data along with measurements and can correct magnitude errors op...... the two time series. Results on limited-area NWP model performance, with focus on the 12th to 48th forecast hour horizon relevant for Elspot auction bidding on the Nord Pool Spot market [2], are presented....

  15. Evaluation of Dynamical Downscaling Resolution Effect on Wind Energy Forecast Value for a Wind Farm in Central Sweden

    DEFF Research Database (Denmark)

    Rosgaard, Martin Haubjerg; Hahmann, Andrea N.; Nielsen, Torben Skov

    For any energy system relying on wind power, accurate forecasts of wind fluctuations are essential for efficient utilisation in the power grid. Statistical wind power prediction tools [1] use numerical weather prediction (NWP) model data along with measurements and can correct magnitude errors...... the two time series. Results on limited-area NWP model performance, with focus on the 12th to 48th forecast hour horizon relevant for Elspot auction bidding on the Nord Pool Spot market [2], are presented....

  16. Wind forecasting for grid code compliance

    Energy Technology Data Exchange (ETDEWEB)

    Vanitha, V.; Kishore, S.R.N. [Amrita Vishwa Vidyapeetham Univ.. Dept. of Electrical and Electronics Engineering, Coimbatore (India)

    2012-07-01

    This work explores Adaptive Neuro-Fuzzy Inference Systems (ANFIS) to forecast the average hourly wind speed. To determine the characteristics of ANFIS that best suited the target wind speed forecasting system, several ANFIS models were trained, tested and compared. Different types and number of inputs, training and checking sizes, type and number of membership functions and techniques to generate the initial (FIS) were analyzed. Comparisons with other forecasting methods were analyzed the models were given wind speed, direction and air pressure as inputs having the best forecasting accuracy. SCADA system is utilized to obtain the wind speed to the forecasting system in the host computer where ANFIS is present. The SCADA is located in the central room, the substation of the wind farm, or even at a remote off site point. The data obtained from the site is plotted at every instant and the predicted wind speed is displayed and also exported to the excel sheet which will be sent/e-mailed in the form of Graphs and excel sheets to the operator, State load dispatch centre (SLDC) and to the customer. (Author)

  17. Wind power soars

    Energy Technology Data Exchange (ETDEWEB)

    Flavin, C. [Worldwatch Inst., Washington, DC (United States)

    1996-12-31

    Opinions on the world market for wind power are presented in this paper. Some data for global wind power generating capacity are provided. European and other markets are discussed individually. Estimated potential for wind power is given for a number of countries. 3 figs.

  18. Method of forecasting power distribution

    International Nuclear Information System (INIS)

    Kaneto, Kunikazu.

    1981-01-01

    Purpose: To obtain forecasting results at high accuracy by reflecting the signals from neutron detectors disposed in the reactor core on the forecasting results. Method: An on-line computer transfers, to a simulator, those process data such as temperature and flow rate for coolants in each of the sections and various measuring signals such as control rod positions from the nuclear reactor. The simulator calculates the present power distribution before the control operation. The signals from the neutron detectors at each of the positions in the reactor core are estimated from the power distribution and errors are determined based on the estimated values and the measured values to determine the smooth error distribution in the axial direction. Then, input conditions at the time to be forecast are set by a data setter. The simulator calculates the forecast power distribution after the control operation based on the set conditions. The forecast power distribution is corrected using the error distribution. (Yoshino, Y.)

  19. Wind Speed Forecasting by Wavelet Neural Networks: A Comparative Study

    Directory of Open Access Journals (Sweden)

    Chuanan Yao

    2013-01-01

    Full Text Available Due to the environmental degradation and depletion of conventional energy, much attention has been devoted to wind energy in many countries. The intermittent nature of wind power has had a great impact on power grid security. Accurate forecasting of wind speed plays a vital role in power system stability. This paper presents a comparison of three wavelet neural networks for short-term forecasting of wind speed. The first two combined models are two types of basic combinations of wavelet transform and neural network, namely, compact wavelet neural network (CWNN and loose wavelet neural network (LWNN in this study, and the third model is a new hybrid method based on the CWNN and LWNN models. The efficiency of the combined models has been evaluated by using actual wind speed from two test stations in North China. The results show that the forecasting performances of the CWNN and LWNN models are unstable and are affected by the test stations selected; the third model is far more accurate than the other forecasting models in spite of the drawback of lower computational efficiency.

  20. Peak Wind Tool for General Forecasting

    Science.gov (United States)

    Barrett, Joe H., III

    2010-01-01

    The expected peak wind speed of the day is an important forecast element in the 45th Weather Squadron's (45 WS) daily 24-Hour and Weekly Planning Forecasts. The forecasts are used for ground and space launch operations at the Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS). The 45 WS also issues wind advisories for KSC/CCAFS when they expect wind gusts to meet or exceed 25 kt, 35 kt and 50 kt thresholds at any level from the surface to 300 ft. The 45 WS forecasters have indicated peak wind speeds are challenging to forecast, particularly in the cool season months of October - April. In Phase I of this task, the Applied Meteorology Unit (AMU) developed a tool to help the 45 WS forecast non-convective winds at KSC/CCAFS for the 24-hour period of 0800 to 0800 local time. The tool was delivered as a Microsoft Excel graphical user interface (GUI). The GUI displayed the forecast of peak wind speed, 5-minute average wind speed at the time of the peak wind, timing of the peak wind and probability the peak speed would meet or exceed 25 kt, 35 kt and 50 kt. For the current task (Phase II ), the 45 WS requested additional observations be used for the creation of the forecast equations by expanding the period of record (POR). Additional parameters were evaluated as predictors, including wind speeds between 500 ft and 3000 ft, static stability classification, Bulk Richardson Number, mixing depth, vertical wind shear, temperature inversion strength and depth and wind direction. Using a verification data set, the AMU compared the performance of the Phase I and II prediction methods. Just as in Phase I, the tool was delivered as a Microsoft Excel GUI. The 45 WS requested the tool also be available in the Meteorological Interactive Data Display System (MIDDS). The AMU first expanded the POR by two years by adding tower observations, surface observations and CCAFS (XMR) soundings for the cool season months of March 2007 to April 2009. The POR was expanded

  1. On the market impact of wind energy forecasts

    International Nuclear Information System (INIS)

    Jonsson, Tryggvi; Pinson, Pierre; Madsen, Henrik

    2010-01-01

    This paper presents an analysis of how day-ahead electricity spot prices are affected by day-ahead wind power forecasts. Demonstration of this relationship is given as a test case for the Western Danish price area of the Nord Pool's Elspot market. Impact on the average price behaviour is investigated as well as that on the distributional properties of the price. By using a non-parametric regression model to assess the effects of wind power forecasts on the average behaviour, the non-linearities and time variations in the relationship are captured well and the effects are shown to be quite substantial. Furthermore, by evaluating the distributional properties of the spot prices under different scenarios, the impact of the wind power forecasts on the price distribution is proved to be considerable. The conditional price distribution is moreover shown to be non-Gaussian. This implies that forecasting models for electricity spot prices for which parameters are estimated by a least squares techniques will not have Gaussian residuals. Hence the widespread assumption of Gaussian residuals from electricity spot price models is shown to be inadequate for these model types. The revealed effects are likely to be observable and qualitatively similar in other day-ahead electricity markets significantly penetrated by wind power. (author)

  2. Wind power takes over

    International Nuclear Information System (INIS)

    2002-01-01

    All over the industrialized world concentrated efforts are being made to make wind turbines cover some of the energy demand in the coming years. There is still a long way to go, however, towards a 'green revolution' as far as energy is concerned, for it is quite futile to use wind power for electric heating. The article deals with some of the advantages and disadvantages of developing wind power. In Norway, for instance, environmentalists fear that wind power plants along the coast may have serious consequences for the stocks of white-tailed eagle and golden eagle. An other factor that delays the large-scale application of wind power in Norway is the low price of electricity. Some experts, however, maintain that wind power may already compete with new hydroelectric power of intermediate cost. The investment costs are expected to go down with one third by 2020, when wind power may be the most competitive energy source to utilize

  3. Wind power integration connection and system operational aspects

    CERN Document Server

    Fox, Brendan

    2014-01-01

    Wind Power Integration provides a wide-ranging discussion on all major aspects of wind power integration into electricity supply systems. This second edition has been fully revised and updated to take account of the significant growth in wind power deployment in the past few years. New discussions have been added to describe developments in wind turbine generator technology and control, the network integration of wind power, innovative ways to integrate wind power when its generation potential exceeds 50% of demand, case studies on how forecasting errors have affected system operation, and an update on how the wind energy sector has fared in the marketplace. Topics covered include: the development of wind power technology and its world-wide deployment; wind power technology and the interaction of various wind turbine generator types with the utility network; and wind power forecasting and the challenges faced by wind energy in modern electricity markets.

  4. Potentials of wind power

    International Nuclear Information System (INIS)

    Bezrukikh, P.P.; Bezrukikh, P.P.

    2000-01-01

    The ecological advantages of the wind power facilities (WPF) are considered. The possibilities of small WPF, generating the capacity from 40 W up to 10 kW, are discussed. The basic technical data on the national and foreign small WPF are presented. The combined wind power systems are considered. Special attention is paid to the most perspective wind-diesel systems, which provide for all possible versions of the electro-power supply. Useful recommendations and information on the wind power engineering are given for those, who decided to build up a wind facility [ru

  5. Wind Power Prediction Considering Nonlinear Atmospheric Disturbances

    OpenAIRE

    Yagang Zhang; Jingyun Yang; Kangcheng Wang; Zengping Wang

    2015-01-01

    This paper considers the effect of nonlinear atmospheric disturbances on wind power prediction. A Lorenz system is introduced as an atmospheric disturbance model. Three new improved wind forecasting models combined with a Lorenz comprehensive disturbance are put forward in this study. Firstly, we define the form of the Lorenz disturbance variable and the wind speed perturbation formula. Then, different artificial neural network models are used to verify the new idea and obtain better wind spe...

  6. Wind power. [electricity generation

    Science.gov (United States)

    Savino, J. M.

    1975-01-01

    A historical background on windmill use, the nature of wind, wind conversion system technology and requirements, the economics of wind power and comparisons with alternative systems, data needs, technology development needs, and an implementation plan for wind energy are presented. Considerable progress took place during the 1950's. Most of the modern windmills feature a wind turbine electricity generator located directly at the top of their rotor towers.

  7. Wind electric power generation

    International Nuclear Information System (INIS)

    Koch, M.K.; Wind, L.; Canter, B.; Moeller, T.

    2001-01-01

    The monthly statistics of wind electric power generation in Denmark are compiled from information given by the owners of the private wind turbines. For each wind turbine the name of the site and of the type of turbine is given, and the power generation data are given for the month in question together with the total production in 1999 and 2000. Also the data of operation start are given. On the map of Denmark the sites of the wind turbines are marked. (CLS)

  8. Wind power today

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1998-04-01

    This publication highlights initiatives of the US DOE`s Wind Energy Program. 1997 yearly activities are also very briefly summarized. The first article describes a 6-megawatt wind power plant installed in Vermont. Another article summarizes technical advances in wind turbine technology, and describes next-generation utility and small wind turbines in the planning stages. A village power project in Alaska using three 50-kilowatt turbines is described. Very brief summaries of the Federal Wind Energy Program and the National Wind Technology Center are also included in the publication.

  9. Conditional prediction intervals of wind power generation

    DEFF Research Database (Denmark)

    Pinson, Pierre; Kariniotakis, Georges

    2010-01-01

    A generic method for the providing of prediction intervals of wind power generation is described. Prediction intervals complement the more common wind power point forecasts, by giving a range of potential outcomes for a given probability, their so-called nominal coverage rate. Ideally they inform...... of the situation-specific uncertainty of point forecasts. In order to avoid a restrictive assumption on the shape of forecast error distributions, focus is given to an empirical and nonparametric approach named adapted resampling. This approach employs a fuzzy inference model that permits to integrate expertise...

  10. Challenges on wind power development in China

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Qianjin; Shi, Jingli

    2010-09-15

    Wind power has experienced exponential growth in China in the past five years, which exceeds the most optimistic expectations. The increasing penetration and aggressive future plan are arousing big concerns about its impact on operation and security of existing power networks. This paper introduces present condition of wind power development in China and the challenges on both grid integration and regulations. Most of these challenges are economical rather than technical. Feed-in tariff policies and grid code are the key countermeasures. Accurate wind forecast and economical mass energy storage are needed to guarantee compliance of wind power to the grid.

  11. Wind Power Prediction Considering Nonlinear Atmospheric Disturbances

    Directory of Open Access Journals (Sweden)

    Yagang Zhang

    2015-01-01

    Full Text Available This paper considers the effect of nonlinear atmospheric disturbances on wind power prediction. A Lorenz system is introduced as an atmospheric disturbance model. Three new improved wind forecasting models combined with a Lorenz comprehensive disturbance are put forward in this study. Firstly, we define the form of the Lorenz disturbance variable and the wind speed perturbation formula. Then, different artificial neural network models are used to verify the new idea and obtain better wind speed predictions. Finally we separately use the original and improved wind speed series to predict the related wind power. This proves that the corrected wind speed provides higher precision wind power predictions. This research presents a totally new direction in the wind prediction field and has profound theoretical research value and practical guiding significance.

  12. Forecast of icing events at a wind farm in Sweden

    DEFF Research Database (Denmark)

    Davis, Neil; Hahmann, Andrea N.; Clausen, Niels-Erik

    2014-01-01

    This paper introduces a method for identifying icing events using a physical icing model, driven by atmospheric data from the Weather Research and Forecasting (WRF) model, and applies it to a wind park in Sweden. Observed wind park icing events were identified by deviation from an idealized power...... curve and observed temperature. The events were modeled using a physical icing model with equations for both accretion and ablation mechanisms (iceBlade). The accretion model is based on the Makkonen model but was modified to make it applicable to the blades of a wind turbine rather than a static...

  13. The Forecasting Procedure for Long-Term Wind Speed in the Zhangye Area

    Directory of Open Access Journals (Sweden)

    Zhenhai Guo

    2010-01-01

    Full Text Available Energy crisis has made it urgent to find alternative energy sources for sustainable energy supply; wind energy is one of the attractive alternatives. Within a wind energy system, the wind speed is one key parameter; accurately forecasting of wind speed can minimize the scheduling errors and in turn increase the reliability of the electric power grid and reduce the power market ancillary service costs. This paper proposes a new hybrid model for long-term wind speed forecasting based on the first definite season index method and the Autoregressive Moving Average (ARMA models or the Generalized Autoregressive Conditional Heteroskedasticity (GARCH forecasting models. The forecasting errors are analyzed and compared with the ones obtained from the ARMA, GARCH model, and Support Vector Machine (SVM; the simulation process and results show that the developed method is simple and quite efficient for daily average wind speed forecasting of Hexi Corridor in China.

  14. Wind power generation and dispatch in competitive power markets

    Science.gov (United States)

    Abreu, Lisias

    Wind energy is currently the fastest growing type of renewable energy. The main motivation is led by more strict emission constraints and higher fuel prices. In addition, recent developments in wind turbine technology and financial incentives have made wind energy technically and economically viable almost anywhere. In restructured power systems, reliable and economical operation of power systems are the two main objectives for the ISO. The ability to control the output of wind turbines is limited and the capacity of a wind farm changes according to wind speeds. Since this type of generation has no production costs, all production is taken by the system. Although, insufficient operational planning of power systems considering wind generation could result in higher system operation costs and off-peak transmission congestions. In addition, a GENCO can participate in short-term power markets in restructured power systems. The goal of a GENCO is to sell energy in such a way that would maximize its profitability. However, due to market price fluctuations and wind forecasting errors, it is essential for the wind GENCO to keep its financial risk at an acceptable level when constituting market bidding strategies. This dissertation discusses assumptions, functions, and methodologies that optimize short-term operations of power systems considering wind energy, and that optimize bidding strategies for wind producers in short-term markets. This dissertation also discusses uncertainties associated with electricity market environment and wind power forecasting that can expose market participants to a significant risk level when managing the tradeoff between profitability and risk.

  15. Wind Power Career Chat

    Energy Technology Data Exchange (ETDEWEB)

    2011-01-01

    This document will teach students about careers in the wind energy industry. Wind energy, both land-based and offshore, is expected to provide thousands of new jobs in the next several decades. Wind energy companies are growing rapidly to meet America's demand for clean, renewable, and domestic energy. These companies need skilled professionals. Wind power careers will require educated people from a variety of areas. Trained and qualified workers manufacture, construct, operate, and manage wind energy facilities. The nation will also need skilled researchers, scientists, and engineers to plan and develop the next generation of wind energy technologies.

  16. A new wind speed forecasting strategy based on the chaotic time series modelling technique and the Apriori algorithm

    International Nuclear Information System (INIS)

    Guo, Zhenhai; Chi, Dezhong; Wu, Jie; Zhang, Wenyu

    2014-01-01

    Highlights: • Impact of meteorological factors on wind speed forecasting is taken into account. • Forecasted wind speed results are corrected by the associated rules. • Forecasting accuracy is improved by the new wind speed forecasting strategy. • Robust of the proposed model is validated by data sampled from different sites. - Abstract: Wind energy has been the fastest growing renewable energy resource in recent years. Because of the intermittent nature of wind, wind power is a fluctuating source of electrical energy. Therefore, to minimize the impact of wind power on the electrical grid, accurate and reliable wind power forecasting is mandatory. In this paper, a new wind speed forecasting approach based on based on the chaotic time series modelling technique and the Apriori algorithm has been developed. The new approach consists of four procedures: (I) Clustering by using the k-means clustering approach; (II) Employing the Apriori algorithm to discover the association rules; (III) Forecasting the wind speed according to the chaotic time series forecasting model; and (IV) Correcting the forecasted wind speed data using the associated rules discovered previously. This procedure has been verified by 31-day-ahead daily average wind speed forecasting case studies, which employed the wind speed and other meteorological data collected from four meteorological stations located in the Hexi Corridor area of China. The results of these case studies reveal that the chaotic forecasting model can efficiently improve the accuracy of the wind speed forecasting, and the Apriori algorithm can effectively discover the association rules between the wind speed and other meteorological factors. In addition, the correction results demonstrate that the association rules discovered by the Apriori algorithm have powerful capacities in handling the forecasted wind speed values correction when the forecasted values do not match the classification discovered by the association rules

  17. The Wind Forecast Improvement Project (WFIP). A Public/Private Partnership for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits of Utility Operations -- the Northern Study Area

    Energy Technology Data Exchange (ETDEWEB)

    Finley, Cathy [WindLogics, St. Paul, MN (United States)

    2014-04-30

    This report contains the results from research aimed at improving short-range (0-6 hour) hub-height wind forecasts in the NOAA weather forecast models through additional data assimilation and model physics improvements for use in wind energy forecasting. Additional meteorological observing platforms including wind profilers, sodars, and surface stations were deployed for this study by NOAA and DOE, and additional meteorological data at or near wind turbine hub height were provided by South Dakota State University and WindLogics/NextEra Energy Resources over a large geographical area in the U.S. Northern Plains for assimilation into NOAA research weather forecast models. The resulting improvements in wind energy forecasts based on the research weather forecast models (with the additional data assimilation and model physics improvements) were examined in many different ways and compared with wind energy forecasts based on the current operational weather forecast models to quantify the forecast improvements important to power grid system operators and wind plant owners/operators participating in energy markets. Two operational weather forecast models (OP_RUC, OP_RAP) and two research weather forecast models (ESRL_RAP, HRRR) were used as the base wind forecasts for generating several different wind power forecasts for the NextEra Energy wind plants in the study area. Power forecasts were generated from the wind forecasts in a variety of ways, from very simple to quite sophisticated, as they might be used by a wide range of both general users and commercial wind energy forecast vendors. The error characteristics of each of these types of forecasts were examined and quantified using bulk error statistics for both the local wind plant and the system aggregate forecasts. The wind power forecast accuracy was also evaluated separately for high-impact wind energy ramp events. The overall bulk error statistics calculated over the first six hours of the forecasts at both the

  18. Early warnings of extreme winds using the ECMWF Extreme Forecast Index

    OpenAIRE

    Petroliagis, Thomas I.; Pinson, Pierre

    2014-01-01

    The European FP7 SafeWind Project aims at developing research towards a European vision of wind power forecasting, which requires advanced meteorological support concerning extreme wind events. This study is focused mainly on early warnings of extreme winds in the early medium-range. Three synoptic stations (airports) of North Germany (Bremen, Hamburg and Hannover) were considered for the construction of time series of daily maximum wind speeds. All daily wind extremes were found to be linked...

  19. Offshore Wind Power Data

    DEFF Research Database (Denmark)

    Cutululis, Nicolaos Antonio; Litong-Palima, Marisciel; Zeni, Lorenzo

    2012-01-01

    Wind power development scenarios are critical when trying to assess the impact of the demonstration at national and European level. The work described in this report had several objectives. The main objective was to prepare and deliver the proper input necessary for assessing the impact of Demo 4...... – Storm management at national and European level. For that, detailed scenarios for offshore wind power development by 2020 and 2030 were required. The aggregation level that is suitable for the analysis to be done is at wind farm level. Therefore, the scenarios for offshore wind power development offer...... details about the wind farms such as: capacity and coordinates. Since the focus is on the impact of storm fronts passage in Northen Europe, the offshore wind power scenarios were estimated only for the countries at North and Baltic Sea. The sources used are public sources, mentioned in the reference list...

  20. Wind power in France

    International Nuclear Information System (INIS)

    Tuille, F.; Courtel, J.

    2015-01-01

    After 3 years of steady decreasing, wind power has resumed growth in 2014 in France and the preliminary figures of 2015 confirm this trend. About 1100 MW were installed in 2014 which was almost twice as much as it was installed the year before. This renaissance is mostly due to the implementation of Brottes' law that eases the installations of wind farms by suppressing the wind power development areas (that were interfering with regional wind power schemes) and by suppressing the minimum number of 5 turbines for any new wind farms. Another important incentive measure was the announcement in January 2015 of a new financial support scheme in replacement of the policy of guaranteed purchase price for the electricity produced. In 2014 the total wind power produced in mainland France reached 17 TW which represented 3.1% of the production of electricity. (A.C.)

  1. Danish Wind Power

    DEFF Research Database (Denmark)

    Lund, Henrik; Hvelplund, Frede; Østergaard, Poul Alberg

    In a normal wind year, Danish wind turbines generate the equivalent of approx. 20 percent of the Danish electricity demand. This paper argues that only approx. 1 percent of the wind power production is exported. The rest is used to meet domestic Danish electricity demands. The cost of wind power......, a study made by the Danish think tank CEPOS claimed the opposite, i.e. that most of the Danish wind power has been exported in recent years. However, this claim is based on an incorrect interpretation of statistics and a lack of understanding of how the international electricity markets operate...... is paid solely by the electricity consumers and the net influence on consumer prices was as low as 1-3 percent on average in the period 2004-2008. In 2008, the net influence even decreased the average consumer price, although only slightly. In Denmark, 20 percent wind power is integrated by using both...

  2. Wind power prediction models

    Science.gov (United States)

    Levy, R.; Mcginness, H.

    1976-01-01

    Investigations were performed to predict the power available from the wind at the Goldstone, California, antenna site complex. The background for power prediction was derived from a statistical evaluation of available wind speed data records at this location and at nearby locations similarly situated within the Mojave desert. In addition to a model for power prediction over relatively long periods of time, an interim simulation model that produces sample wind speeds is described. The interim model furnishes uncorrelated sample speeds at hourly intervals that reproduce the statistical wind distribution at Goldstone. A stochastic simulation model to provide speed samples representative of both the statistical speed distributions and correlations is also discussed.

  3. Climate Wind Power Resources

    Directory of Open Access Journals (Sweden)

    Nana M. Berdzenishvili

    2013-01-01

    Full Text Available Georgia as a whole is characterized by rather rich solar energy resources, which allows to construct alternative power stations in the close proximity to traditional power plants. In this case the use of solar energy is meant. Georgia is divided into 5 zones based on the assessment of wind power resources. The selection of these zones is based on the index of average annual wind speed in the examined area, V> 3 m / s and V> 5 m / s wind speed by the summing duration in the course of the year and V = 0. . . 2 m / s of passive wind by total and continuous duration of these indices per hour.

  4. Enabling Wind Power Nationwide

    Energy Technology Data Exchange (ETDEWEB)

    Jose Zayas, Michael Derby, Patrick Gilman and Shreyas Ananthan,

    2015-05-01

    Leveraging this experience, the U.S. Department of Energy’s (DOE’s) Wind and Water Power Technologies Office has evaluated the potential for wind power to generate electricity in all 50 states. This report analyzes and quantifies the geographic expansion that could be enabled by accessing higher above ground heights for wind turbines and considers the means by which this new potential could be responsibly developed.

  5. Wind Power in Georgia

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2012-11-01

    Georgia has good wind power potential. Preliminary analyses show that the technical wind power potential in Georgia is good. Meteorological data shows that Georgia has four main areas in Georgia with annual average wind speeds of over 6 m/s and two main areas with 5-6 m/s at 80m. The most promising areas are the high mountain zone of the Great Caucasus, The Kura river valley, The South-Georgian highland and the Southern part of the Georgian Black Sea coast. Czech company Wind Energy Invest has recently signed a Memorandum of Understanding with Georgian authorities for development of the first wind farm in Georgia, a 50MW wind park in Paravani, Southern Georgia, to be completed in 2014. Annual generation is estimated to 170.00 GWh and the investment estimated to 101 million US$. Wind power is suited to balance hydropower in the Georgian electricity sector Electricity generation in Georgia is dominated by hydro power, constituting 88% of total generation in 2009. Limited storage capacity and significant spring and summer peaks in river flows result in an uneven annual generation profile and winter time shortages that are covered by three gas power plants. Wind power is a carbon-free energy source well suited to balance hydropower, as it is available (often strongest) in the winter and can be exported when there is a surplus. Another advantage with wind power is the lead time for the projects; the time from site selection to operation for a wind power park (approximately 2.5 years) is much shorter than for hydro power (often 6-8 years). There is no support system or scheme for renewable sources in Georgia, so wind power has to compete directly with other energy sources and is in most cases more expensive to build than hydro power. In a country and region with rapidly increasing energy demands, the factors described above nevertheless indicate that there is a commercial niche and a role to play for Georgian wind power. Skra: An example of a wind power development

  6. Scour Forecasting for Offshore Wind Parks

    DEFF Research Database (Denmark)

    Hartvig, Peres Akrawi

    , scour forecasts facilitate the comparison between a scour design based on either deployment of scour-protection or enhanced structural design. The broad goal is to develop a method that produces accurate scour forecasts for offshore wind parks. The present research investigates more specifically which...... two legacies that deal with these two research questions in dialectical ways. The first legacy is a framework for the scour geometry based on epistemological considerations, theoretical concepts and model scale experiments. Relevant parameters are reviewed, defined and discussed. The combined use...

  7. Improving Wind Ramp Forecasts by the HRRR System via Statistical Postprocessing

    Science.gov (United States)

    Worsnop, Rochelle; Scheuerer, Michael; Hamill, Thomas M.

    2017-04-01

    Wind power forecasting is gaining enormous international significance as more and more countries and regions enact policies to increase the use of renewable energy. Wind ramps pose a particular challenge in decision-making processes in the wind energy industry since a sudden decrease or increase in wind energy production must be balanced by conventional power generators and could be costly for wind farm operators. In this study, we assess the performance of the High-Resolution Rapid Refresh (HRRR) numerical weather prediction model in predicting wind ramps with up to 12 hours of lead time at two wind tower locations in the United States. Novel statistical postprocessing methodology is used to generate scenarios of short-term wind power production; this probabilistic enhancement of the deterministic HRRR forecasts significantly improves the skill in predicting wind ramp events, and could be implemented by wind farm operators to support decision-making.

  8. Wind power costs in Portugal

    Energy Technology Data Exchange (ETDEWEB)

    Saleiro, C. [Univ. of Minho, Dept. of Biological Engineering (Portugal); Araujo, M.; Ferreira, P. [Univ. of Minho, Dept. of Production and Systems (Portugal)

    2007-05-15

    In a way to reduce the external energy dependence, increasing also the investments in renewable energy sources and aiming for the concretization of the European renewable objectives, the Portuguese government defined a goal of 5100 MW of installed wind power, up to 2012. If the drawn objectives are accomplished, by 2010 the wind power share may reach values comparable to leading countries like Denmark, Germany or Spain. The Portuguese forecasts also indicate a reinforcement of the natural gas fired generation in particular through the use of the combined cycle technology, following the European tendency. This analysis sets out to evaluate the total generating cost of wind power and CCGT in Portugal. A life cycle cost analysis was conducted, including investment costs, O and M costs, fuel costs and external costs of emissions, for each type of technology. For the evaluation of the externalities ExternE values were used. The results show that presently the wind power production cost is higher than the CCGT one, at least from the strictly financial point of view. CCGT costs increase significantly when charges for externalities are included. However, they only reach levels higher than the equivalents for wind power for high externality costs estimations. This partially results from the low load factor of the wind farms in Portugal and also from the low emission levels of the gas fired technology used in the comparison. A sensitive analysis of the technical and economical parameters was also conducted. Particular attention was given to the natural gas prices due to the possible increase over time. The fuel escalation rate is the parameter that has larger effects on the final costs. It was verified that the total cost of wind plant is more influenced by the load factor than the total cost of CCGT. (au)

  9. WIND TURBINES FOR WIND POWER INSTALLATIONS

    Directory of Open Access Journals (Sweden)

    Barladean A.S.

    2008-04-01

    Full Text Available The problem of wind turbine choice for wind power stations is examined in this paper. It is shown by comparison of parameters and characteristics of wind turbines, that for existing modes and speeds of wind in territory of Republic of Moldova it is necessary to use multi-blade small speed rotation wind turbines of fan class.

  10. Offshore Wind Power

    DEFF Research Database (Denmark)

    Negra, Nicola Barberis

    The aim of the project is to investigate the influence of wind farms on the reliability of power systems. This task is particularly important for large offshore wind farms, because failure of a large wind farm might have significant influence on the balance of the power system, and because offshore...... Carlo simulation is used for these calculations: this method, in spite of an extended computation time, has shown flexibility in performing reliability studies, especially in case of wind generation, and a broad range of results which can be evaluated. The modelling is then extended to the entire power...... system considering conventional power plants, distributed generation based on wind energy and CHP technology as well as the load and transmission facilities. In particular, the different models are used to represent two well-known test systems, the RBTS and the IEEE-RTS, and to calculate...

  11. The difficult wind power

    International Nuclear Information System (INIS)

    Groenaas, Sigbjoern

    2005-01-01

    The article presents a brief survey of the conditions for wind power production in Norway and points out that several areas should be well suited. A comparison to Danish climate is made. The wind variations, turbulence problems and regional conditions are discussed

  12. Wind power barometer

    International Nuclear Information System (INIS)

    2006-01-01

    This annual evaluation is a synthesis of works published in 2006. Comparisons are presented between the wind power performances and European Commission White Paper and Biomass action plan objectives. Germany and Spain are no longer the only countries ensuring European Union market growth. The market sees also a rise in importance of wind power in United Kingdom, Portugal, Italy and France. (A.L.B.)

  13. Coupling the Weather Research and Forecasting (WRF) model and Large Eddy Simulations with Actuator Disk Model: predictions of wind farm power production

    Science.gov (United States)

    Garcia Cartagena, Edgardo Javier; Santoni, Christian; Ciri, Umberto; Iungo, Giacomo Valerio; Leonardi, Stefano

    2015-11-01

    A large-scale wind farm operating under realistic atmospheric conditions is studied by coupling a meso-scale and micro-scale models. For this purpose, the Weather Research and Forecasting model (WRF) is coupled with an in-house LES solver for wind farms. The code is based on a finite difference scheme, with a Runge-Kutta, fractional step and the Actuator Disk Model. The WRF model has been configured using seven one-way nested domains where the child domain has a mesh size one third of its parent domain. A horizontal resolution of 70 m is used in the innermost domain. A section from the smallest and finest nested domain, 7.5 diameters upwind of the wind farm is used as inlet boundary condition for the LES code. The wind farm consists in six-turbines aligned with the mean wind direction and streamwise spacing of 10 rotor diameters, (D), and 2.75D in the spanwise direction. Three simulations were performed by varying the velocity fluctuations at the inlet: random perturbations, precursor simulation, and recycling perturbation method. Results are compared with a simulation on the same wind farm with an ideal uniform wind speed to assess the importance of the time varying incoming wind velocity. Numerical simulations were performed at TACC (Grant CTS070066). This work was supported by NSF, (Grant IIA-1243482 WINDINSPIRE).

  14. Statistical Analysis of the Impact of Wind Power on Market Quantities and Power Flows

    DEFF Research Database (Denmark)

    Pinson, Pierre; Jónsson, Tryggvi; Zugno, Marco

    2012-01-01

    In view of the increasing penetration of wind power in a number of power systems and markets worldwide, we discuss some of the impacts that wind energy may have on market quantities and cross-border power flows. These impacts are uncovered through statistical analyses of actual market and flow da...... of load and wind power forecasts on Danish and German electricity markets....

  15. Dynamic model of frequency control in Danish power system with large scale integration of wind power

    DEFF Research Database (Denmark)

    Basit, Abdul; Hansen, Anca Daniela; Sørensen, Poul Ejnar

    2013-01-01

    This work evaluates the impact of large scale integration of wind power in future power systems when 50% of load demand can be met from wind power. The focus is on active power balance control, where the main source of power imbalance is an inaccurate wind speed forecast. In this study, a Danish...... power system model with large scale of wind power is developed and a case study for an inaccurate wind power forecast is investigated. The goal of this work is to develop an adequate power system model that depicts relevant dynamic features of the power plants and compensates for load generation...... imbalances, caused by inaccurate wind speed forecast, by an appropriate control of the active power production from power plants....

  16. Multistep Wind Speed Forecasting Based on Wavelet and Gaussian Processes

    Directory of Open Access Journals (Sweden)

    Niya Chen

    2013-01-01

    Full Text Available Accurate wind speed forecasts are necessary for the safety and economy of the renewable energy utilization. The wind speed forecasts can be obtained by statistical model based on historical data. In this paper, a novel W-GP model (wavelet decomposition based Gaussian process learning paradigm is proposed for short-term wind speed forecasting. The nonstationary and nonlinear original wind speed series is first decomposed into a set of better-behaved constitutive subseries by wavelet decomposition. Then these sub-series are forecasted respectively by GP method, and the forecast results are summed to formulate an ensemble forecast for original wind speed series. Therefore, the previous process which obtains wind speed forecast result is named W-GP model. Finally, the proposed model is applied to short-term forecasting of the mean hourly and daily wind speed for a wind farm located in southern China. The prediction results indicate that the proposed W-GP model, which achieves a mean 13.34% improvement in RMSE (Root Mean Square Error compared to persistence method for mean hourly data and a mean 7.71% improvement for mean daily wind speed data, shows the best forecasting accuracy among several forecasting models.

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

    International Nuclear Information System (INIS)

    Liu, Heping; Shi, Jing; Qu, Xiuli

    2013-01-01

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

  18. 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...... 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....... 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...

  19. Potential of Offshore Wind Energy and Extreme Wind Speed Forecasting on the West Coast of Taiwan

    Directory of Open Access Journals (Sweden)

    Pei-Chi Chang

    2015-02-01

    Full Text Available It is of great importance and urgency for Taiwan to develop offshore wind power. However, relevant data on offshore wind energy resources are limited. This study imported wind speeds measured by a tidal station and a buoy into the software WAsP to estimate the high-altitude wind speeds in the two areas. A light detection and ranging (Lidar system was set up near the tidal station and buoy. High-altitude wind speeds measured by the Lidar system were compared with the WAsP-estimated values, and it was discovered that the two data sets were consistent. Then, long-term wind speed data observed by buoys and tidal stations at various locations were imported into WAsP to forecast wind speeds at heights of 55–200 m on the west coast of Taiwan. The software WAsP Engineering was used to analyze the extreme wind speeds in the same areas. The results show that wind speeds at 100 m are approximately 9.32–11.24 m/s, which means that the coastal areas of west Taiwan are rich in wind energy resources. When a long-term 10-min average wind speed is used, the extreme wind speed on the west coast is estimated to be between 36.4 and 55.3 m/s.

  20. Adequacy of operating reserves for power systems in future european wind power scenarios

    DEFF Research Database (Denmark)

    Das, Kaushik; Litong-Palima, Marisciel; Maule, Petr

    2015-01-01

    operating reserves. To study the effects of these imbalances, anticipated wind scenarios for European power systems are modelled for 2020 and 2030. Wind power forecasts for different time scales and real-time available wind power are modelled. Based on these studies, this paper qualitatively analyzes......Wind power generation is expected to increase in Europe by large extent in future. This will increase variability and uncertainty in power systems. Imbalances caused due to uncertainty in wind power forecast can trigger frequency instability in the system. These imbalances are handled using...... the adequacy of primary and secondary reserves requirements for future European power systems. This paper also discusses the challenges due to the uncertainty in wind power forecasts and their possible solutions for wind installation scenarios for 2020 and 2030....

  1. Probabilistic Wind Speed Forecasting using Ensembles and Bayesian Model Averaging

    National Research Council Canada - National Science Library

    Sloughter, J. M; Gneiting, Tilmann; Raftery, Adrian E

    2008-01-01

    Probabilistic forecasts of wind speed are becoming critical as interest grows in wind as a clean and renewable source of energy, in addition to a wide range of other uses, from aviation to recreational boating...

  2. Optimal prediction intervals of wind power generation

    DEFF Research Database (Denmark)

    Wan, Can; Wu, Zhao; Pinson, Pierre

    2014-01-01

    direct optimization of both the coverage probability and sharpness to ensure the quality. The proposed method does not involve the statistical inference or distribution assumption of forecasting errors needed in most existing methods. Case studies using real wind farm data from Australia have been...... penetration beforehand. This paper proposes a novel hybrid intelligent algorithm approach to directly formulate optimal prediction intervals of wind power generation based on extreme learning machine and particle swarm optimization. Prediction intervals with Associated confidence levels are generated through...

  3. Electric power systems advanced forecasting techniques and optimal generation scheduling

    CERN Document Server

    Catalão, João P S

    2012-01-01

    Overview of Electric Power Generation SystemsCláudio MonteiroUncertainty and Risk in Generation SchedulingRabih A. JabrShort-Term Load ForecastingAlexandre P. Alves da Silva and Vitor H. FerreiraShort-Term Electricity Price ForecastingNima AmjadyShort-Term Wind Power ForecastingGregor Giebel and Michael DenhardPrice-Based Scheduling for GencosGovinda B. Shrestha and Songbo QiaoOptimal Self-Schedule of a Hydro Producer under UncertaintyF. Javier Díaz and Javie

  4. Four wind speed multi-step forecasting models using extreme learning machines and signal decomposing algorithms

    International Nuclear Information System (INIS)

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

    2015-01-01

    Highlights: • A hybrid architecture is proposed for the wind speed forecasting. • Four algorithms are used for the wind speed multi-scale decomposition. • The extreme learning machines are employed for the wind speed forecasting. • All the proposed hybrid models can generate the accurate results. - Abstract: Realization of accurate wind speed forecasting is important to guarantee the safety of wind power utilization. In this paper, a new hybrid forecasting architecture is proposed to realize the wind speed accurate forecasting. In this architecture, four different hybrid models are presented by combining four signal decomposing algorithms (e.g., Wavelet Decomposition/Wavelet Packet Decomposition/Empirical Mode Decomposition/Fast Ensemble Empirical Mode Decomposition) and Extreme Learning Machines. The originality of the study is to investigate the promoted percentages of the Extreme Learning Machines by those mainstream signal decomposing algorithms in the multiple step wind speed forecasting. The results of two forecasting experiments indicate that: (1) the method of Extreme Learning Machines is suitable for the wind speed forecasting; (2) by utilizing the decomposing algorithms, all the proposed hybrid algorithms have better performance than the single Extreme Learning Machines; (3) in the comparisons of the decomposing algorithms in the proposed hybrid architecture, the Fast Ensemble Empirical Mode Decomposition has the best performance in the three-step forecasting results while the Wavelet Packet Decomposition has the best performance in the one and two step forecasting results. At the same time, the Wavelet Packet Decomposition and the Fast Ensemble Empirical Mode Decomposition are better than the Wavelet Decomposition and the Empirical Mode Decomposition in all the step predictions, respectively; and (4) the proposed algorithms are effective in the wind speed accurate predictions

  5. Wind farm electrical power production model for load flow analysis

    International Nuclear Information System (INIS)

    Segura-Heras, Isidoro; Escriva-Escriva, Guillermo; Alcazar-Ortega, Manuel

    2011-01-01

    The importance of renewable energy increases in activities relating to new forms of managing and operating electrical power: especially wind power. Wind generation is increasing its share in the electricity generation portfolios of many countries. Wind power production in Spain has doubled over the past four years and has reached 20 GW. One of the greatest problems facing wind farms is that the electrical power generated depends on the variable characteristics of the wind. To become competitive in a liberalized market, the reliability of wind energy must be guaranteed. Good local wind forecasts are therefore essential for the accurate prediction of generation levels for each moment of the day. This paper proposes an electrical power production model for wind farms based on a new method that produces correlated wind speeds for various wind farms. This method enables a reliable evaluation of the impact of new wind farms on the high-voltage distribution grid. (author)

  6. Wind power barometer

    International Nuclear Information System (INIS)

    Anon.

    2010-01-01

    The global wind power market not only repelled the strictures of the financial crisis, but saw the installation of 37 GW in 2009, which is almost 10 GW up on 2008. China and the United States registered particularly steady growth and the European Union also picked up momentum to break its installation record. A total capacity of 158 GW of wind power are now installed across the world from which 74.8 GW in the European Union. Among the European countries Denmark has the highest wind capacity per inhabitant in 2009: 627.5 kW/1000 inhabitants. Spain seeks to limit its market's growth in order to better manage the development of wind energy across the country. German growth is back, Italy chalks up a new record for installation and the French market is becoming increasingly regulated. United-Kingdom is developing offshore wind farms: the offshore capacity could reasonably rise to 20000 MW by 2020. The last part of the article reports some economical news from the leading players: Vestas, GE-Energy, Gamesa, Enercon, Sinovel and Siemens. (A.C.)

  7. A New Hybrid Forecasting Strategy Applied to Mean Hourly Wind Speed Time Series

    Directory of Open Access Journals (Sweden)

    Stylianos Sp. Pappas

    2014-01-01

    Full Text Available An alternative electric power source, such as wind power, has to be both reliable and autonomous. An accurate wind speed forecasting method plays the key role in achieving the aforementioned properties and also is a valuable tool in overcoming a variety of economic and technical problems connected to wind power production. The method proposed is based on the reformulation of the problem in the standard state space form and on implementing a bank of Kalman filters (KF, each fitting an ARMA model of different order. The proposed method is to be applied to a greenhouse unit which incorporates an automatized use of renewable energy sources including wind speed power.

  8. Hydro-Quebec and Environment Canada wind energy forecasting project

    Energy Technology Data Exchange (ETDEWEB)

    Forcione, A.; Roberge, G. [Hydro-Quebec, Saguenay, PQ (Canada). IREQ; Petrucci, F.; Yu, W. [Environment Canada, Gatineau, PQ (Canada)

    2008-07-01

    This presentation outlined a joint wind energy forecasting project currently being conducted by Hydro-Quebec and Environment Canada. The aim of the project is to provide high quality next day hourly forecasts to permit optimal planning and scheduling of wind balancing needs. The quality of next day hourly forecasts depends on the availability of high quality numerical weather prediction modelling output. The model currently being developed by the researchers has been designed to provide 48-hour high resolution, hourly wind forecasts. The Systeme de Provision Eolienne (SPEO) uses mesoscale and microscale operational forecast components from Environment Canada as well as local meteorological observations to provide the wind forecast. Operational forecasts are generated using a global environmental multi-scale model (GEM). Digital elevation models are used to provide high resolution physical data. Case studies of wind forecasts made using the model were provided, as well as flow charts describing a chronology of processes used by the model. It was concluded that the model provides accurate next day wind forecasts. tabs., figs.

  9. An Experimental Investigation of FNN Model for Wind Speed Forecasting Using EEMD and CS

    Directory of Open Access Journals (Sweden)

    Jianzhou Wang

    2015-01-01

    Full Text Available With depletion of traditional energy and increasing environmental problems, wind energy, as an alternative renewable energy, has drawn more and more attention internationally. Meanwhile, wind is plentiful, clean, and environmentally friendly; moreover, its speed is a very important piece of information needed in the operations and planning of the wind power system. Therefore, choosing an effective forecasting model with good performance plays a quite significant role in wind power system. A hybrid CS-EEMD-FNN model is firstly proposed in this paper for multistep ahead prediction of wind speed, in which EEMD is employed as a data-cleaning method that aims to remove the high frequency noise embedded in the wind speed series. CS optimization algorithm is used to select the best parameters in the FNN model. In order to evaluate the effectiveness and performance of the proposed hybrid model, three other short-term wind speed forecasting models, namely, FNN model, EEMD-FNN model, and CS-FNN model, are carried out to forecast wind speed using data measured at a typical site in Shandong wind farm, China, over three seasons in 2011. Experimental results demonstrate that the developed hybrid CS-EEMD-FNN model outperforms other models with more accuracy, which is suitable to wind speed forecasting in this area.

  10. Gearless wind power generator

    Energy Technology Data Exchange (ETDEWEB)

    Soederlund, L.; Ridanpaeae, P.; Vihriaelae, H.; Peraelae, R. [Tampere Univ. of Technology (Finland). Lab. of Electricity and Magnetism

    1998-12-31

    During the wind power generator project a design algorithm for a gearless permanent magnet generator with an axially orientated magnetic flux was developed and a 10 kW model machine was constructed. Utilising the test results a variable wind speed system of 100 kW was designed that incorporates a permanent magnet generator, a frequency converter and a fuzzy controller. This system produces about 5-15% more energy than existing types and stresses to the blades are minimised. The type of generator designed in the project represents in general a gearless solution for slow-speed electrical drives. (orig.)

  11. Forecasting nuclear power supply with Bayesian autoregression

    International Nuclear Information System (INIS)

    Beck, R.; Solow, J.L.

    1994-01-01

    We explore the possibility of forecasting the quarterly US generation of electricity from nuclear power using a Bayesian autoregression model. In terms of forecasting accuracy, this approach compares favorably with both the Department of Energy's current forecasting methodology and their more recent efforts using ARIMA models, and it is extremely easy and inexpensive to implement. (author)

  12. Evaluating winds and vertical wind shear from Weather Research and Forecasting model forecasts using seven planetary boundary layer schemes

    DEFF Research Database (Denmark)

    Draxl, Caroline; Hahmann, Andrea N.; Pena Diaz, Alfredo

    2014-01-01

    with different PBL parameterizations at one coastal site over western Denmark. The evaluation focuses on determining which PBL parameterization performs best for wind energy forecasting, and presenting a validation methodology that takes into account wind speed at different heights. Winds speeds at heights...... regarding wind energy at these levels partly depends on the formulation and implementation of planetary boundary layer (PBL) parameterizations in these models. This study evaluates wind speeds and vertical wind shears simulated by theWeather Research and Forecasting model using seven sets of simulations...

  13. Short-term Probabilistic Forecasting of Wind Speed Using Stochastic Differential Equations

    DEFF Research Database (Denmark)

    Iversen, Jan Emil Banning; Morales González, Juan Miguel; Møller, Jan Kloppenborg

    2016-01-01

    It is widely accepted today that probabilistic forecasts of wind power production constitute valuable information for both wind power producers and power system operators to economically exploit this form of renewable energy, while mitigating the potential adverse effects related to its variable...... and uncertain nature. In this paper, we propose a modeling framework for wind speed that is based on stochastic differential equations. We show that stochastic differential equations allow us to naturally capture the time dependence structure of wind speed prediction errors (from 1 up to 24 hours ahead) and......, most importantly, to derive point and quantile forecasts, predictive distributions, and time-path trajectories (also referred to as scenarios or ensemble forecasts), all by one single stochastic differential equation model characterized by a few parameters....

  14. Wind power development. Status and perspectives

    International Nuclear Information System (INIS)

    Morthorst, P.E.

    1998-09-01

    This is the final report on the status and long-term perspectives for the development of wind power, contributing to the Macro Task E1 on production cost for fusion and alternative technologies, part of the programme for Socio-Economic Research on Fusion. The report concentrates on the development of the production costs for wind power, limited to turbines connected to the public grid. The report shows status and perspectives for production costs for wind turbines until the year 2020-30. In general two trends have dominated the grid-connected wind turbine development until now: The average size of the turbines sold at the market place has increased substantially, while at the same time the efficiency of turbine electricity production has increased steadily. Together these trends have increased the cost-effectiveness of wind power by almost 45% over a time span of 9-10 years. Looking at perspectives, a substantial cut in wind power cost per kWh can be expected within the next 20-30 years. A survey performed for a number of long-term forecasts for the wind power technology in general shows a decrease in production costs of 2-2.5% p.a., which implies that the cost of wind-generated electricity would be halved by the year 2030, probably making it fully competitive to conventional fossil fuel based electricity production. (au)

  15. Online Short-term Solar Power Forecasting

    DEFF Research Database (Denmark)

    Bacher, Peder; Madsen, Henrik; Nielsen, Henrik Aalborg

    This poster presents two approaches to online forecasting of power production from PV systems. The methods are suited for online forecasting in many applications and here they are used to predict hourly values of solar power for horizons up to 32 hours.......This poster presents two approaches to online forecasting of power production from PV systems. The methods are suited for online forecasting in many applications and here they are used to predict hourly values of solar power for horizons up to 32 hours....

  16. Online Short-term Solar Power Forecasting

    DEFF Research Database (Denmark)

    Bacher, Peder; Madsen, Henrik; Nielsen, Henrik Aalborg

    2011-01-01

    This poster presents two approaches to online forecasting of power production from PV systems. The methods are suited for online forecasting in many applications and here they are used to predict hourly values of solar power for horizons up to 32 hours.......This poster presents two approaches to online forecasting of power production from PV systems. The methods are suited for online forecasting in many applications and here they are used to predict hourly values of solar power for horizons up to 32 hours....

  17. The Application of TAPM for Site Specific Wind Energy Forecasting

    Directory of Open Access Journals (Sweden)

    Merlinde Kay

    2016-02-01

    Full Text Available The energy industry uses weather forecasts for determining future electricity demand variations due to the impact of weather, e.g., temperature and precipitation. However, as a greater component of electricity generation comes from intermittent renewable sources such as wind and solar, weather forecasting techniques need to now also focus on predicting renewable energy supply, which means adapting our prediction models to these site specific resources. This work assesses the performance of The Air Pollution Model (TAPM, and demonstrates that significant improvements can be made to only wind speed forecasts from a mesoscale Numerical Weather Prediction (NWP model. For this study, a wind farm site situated in North-west Tasmania, Australia was investigated. I present an analysis of the accuracy of hourly NWP and bias corrected wind speed forecasts over 12 months spanning 2005. This extensive time frame allows an in-depth analysis of various wind speed regimes of importance for wind-farm operation, as well as extreme weather risk scenarios. A further correction is made to the basic bias correction to improve the forecast accuracy further, that makes use of real-time wind-turbine data and a smoothing function to correct for timing-related issues. With full correction applied, a reduction in the error in the magnitude of the wind speed by as much as 50% for “hour ahead” forecasts specific to the wind-farm site has been obtained.

  18. Wind Powering America

    International Nuclear Information System (INIS)

    Flowers, L.; Dougherty, P. J.

    2001-01-01

    At the June 1999 Windpower Conference, the Secretary of Energy launched the Office of Energy Efficiency and Renewable Energy's Wind Powering America (WPA) initiative. The goals of the initiative are to meet 5% of the nation's energy needs with wind energy by 2020 (i.e., 80,000 megawatts installed), to double the number of states that have more than 20 megawatts (MW) of wind capacity to 16 by 2005 and triple it to 24 by 2010, and to increase wind's contribution to Federal electricity use to 5% by 2010. To achieve the Federal government's goal, DOE would take the leadership position and work with its Federal partners. Subsequently, the Secretary accelerated the DOE 5% commitment to 2005. Achieving the 80,000 MW goal would result in approximately$60 billion investment and$1.5 billion of economic development in our rural areas (where the wind resources are the greatest). The purpose of this paper is to provide an update on DOE's strategy for achieving its goals and the activities it has undertaken since the initiative was announced

  19. Wind Powering America

    Energy Technology Data Exchange (ETDEWEB)

    Flowers, L. (NREL); Dougherty, P. J. (DOE)

    2001-07-07

    At the June 1999 Windpower Conference, the Secretary of Energy launched the Office of Energy Efficiency and Renewable Energy's Wind Powering America (WPA) initiative. The goals of the initiative are to meet 5% of the nation's energy needs with wind energy by 2020 (i.e., 80,000 megawatts installed), to double the number of states that have more than 20 megawatts (MW) of wind capacity to 16 by 2005 and triple it to 24 by 2010, and to increase wind's contribution to Federal electricity use to 5% by 2010. To achieve the Federal government's goal, DOE would take the leadership position and work with its Federal partners. Subsequently, the Secretary accelerated the DOE 5% commitment to 2005. Achieving the 80,000 MW goal would result in approximately $60 billion investment and $1.5 billion of economic development in our rural areas (where the wind resources are the greatest). The purpose of this paper is to provide an update on DOE's strategy for achieving its goals and the activities it has undertaken since the initiative was announced.

  20. Pricing offshore wind power

    International Nuclear Information System (INIS)

    Levitt, Andrew C.; Kempton, Willett; Smith, Aaron P.; Musial, Walt; Firestone, Jeremy

    2011-01-01

    Offshore wind offers a very large clean power resource, but electricity from the first US offshore wind contracts is costlier than current regional wholesale electricity prices. To better understand the factors that drive these costs, we develop a pro-forma cash flow model to calculate two results: the levelized cost of energy, and the breakeven price required for financial viability. We then determine input values based on our analysis of capital markets and of 35 operating and planned projects in Europe, China, and the United States. The model is run for a range of inputs appropriate to US policies, electricity markets, and capital markets to assess how changes in policy incentives, project inputs, and financial structure affect the breakeven price of offshore wind power. The model and documentation are made publicly available. - Highlights: → We calculate the Breakeven Price (BP) required to deploy offshore wind plants. → We determine values for cost drivers and review incentives structures in the US. → We develop 3 scenarios using today's technology but varying in industry experience. → BP differs widely by Cost Scenario; relative policy effectiveness varies by stage. → The low-range BP is below regional market values in the Northeast United States.

  1. Wind power barometer

    International Nuclear Information System (INIS)

    Anon.

    2012-01-01

    Despite the economic crisis affecting most of the globe's major economies, wind energy continues to gain supporters around the world. Global wind power capacity increased by 40.5 GW between 2010 and 2011 compared to a 39 GW rise between 2009 and 2010, after deduction of decommissioned capacity. By the end of 2011 global installed wind turbine capacity should stand at around 238.5 GW, and much of the world's growth is being driven by capacity build-up in the emerging markets (China, India...). In 2011 Asia was the world's biggest market (52%) ahead of Europe (24.5%) and North-America (19.7%). Europe has still the largest wind power capacity in the world with 40.6% of total in 2011. 2011 was another tough year for Vestas company while Gamesa company has managed to maintain positive profit growth by gaining market shares abroad. Siemens keeps its lead in the offshore market. The Chinese market is now suffering form excess capacity and Chinese companies fell prey to domestic competition

  2. Wind power integration : From individual wind turbine to wind park as a power plant

    NARCIS (Netherlands)

    Zhou, Y.

    2009-01-01

    As power capacities of single wind turbine, single wind park and total wind power installation are continuously increasing, the wind power begins to challenge the safety operation of the power system. This thesis focuses on the grid integration aspects such as the dynamic behaviours of wind power

  3. Doppler Lidar in the Wind Forecast Improvement Projects

    Directory of Open Access Journals (Sweden)

    Pichugina Yelena

    2016-01-01

    Full Text Available This paper will provide an overview of some projects in support of Wind Energy development involving Doppler lidar measurement of wind flow profiles. The high temporal and vertical resolution of these profiles allows the uncertainty of Numerical Weather Prediction models to be evaluated in forecasting dynamic processes and wind flow phenomena in the layer of rotor-blade operation.

  4. Wind power in modern power systems

    DEFF Research Database (Denmark)

    Chen, Zhe

    2013-01-01

    In recent years, wind power is experiencing a rapid growth, and large-scale wind turbines/wind farms have been developed and connected to power systems. However, the traditional power system generation units are centralized located synchronous generators with different characteristics compared...... with wind turbines. This paper presents an overview of the issues about integrating large-scale wind power plants into modern power systems. Firstly, grid codes are introduced. Then, the main technical problems and challenges are presented. Finally, some possible technical solutions are discussed....

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

    International Nuclear Information System (INIS)

    Zhou Junyi; Shi Jing; Li Gong

    2011-01-01

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

  6. A Novel Empirical Mode Decomposition With Support Vector Regression for Wind Speed Forecasting.

    Science.gov (United States)

    Ren, Ye; Suganthan, Ponnuthurai Nagaratnam; Srikanth, Narasimalu

    2016-08-01

    Wind energy is a clean and an abundant renewable energy source. Accurate wind speed forecasting is essential for power dispatch planning, unit commitment decision, maintenance scheduling, and regulation. However, wind is intermittent and wind speed is difficult to predict. This brief proposes a novel wind speed forecasting method by integrating empirical mode decomposition (EMD) and support vector regression (SVR) methods. The EMD is used to decompose the wind speed time series into several intrinsic mode functions (IMFs) and a residue. Subsequently, a vector combining one historical data from each IMF and the residue is generated to train the SVR. The proposed EMD-SVR model is evaluated with a wind speed data set. The proposed EMD-SVR model outperforms several recently reported methods with respect to accuracy or computational complexity.

  7. Early warnings of extreme winds using the ECMWF Extreme Forecast Index

    DEFF Research Database (Denmark)

    Petroliagis, Thomas I.; Pinson, Pierre

    2014-01-01

    regimes. Overall, it becomes clear that the first indications of an extreme wind event might come from the ECMWF deterministic and/or probabilistic components capturing very intense weather systems (possible windstorms) in the medium term. For early warnings, all available EPS Extreme Forecast Index (EFI......The European FP7 SafeWind Project aims at developing research towards a European vision of wind power forecasting, which requires advanced meteorological support concerning extreme wind events. This study is focused mainly on early warnings of extreme winds in the early medium-range. Three synoptic...... stations (airports) of North Germany (Bremen, Hamburg and Hannover) were considered for the construction of time series of daily maximum wind speeds. All daily wind extremes were found to be linked to very intense surface cyclonic circulation systems being advected mainly by southwest and northwest flow...

  8. A hybrid wavelet transform based short-term wind speed forecasting approach.

    Science.gov (United States)

    Wang, Jujie

    2014-01-01

    It is important to improve the accuracy of wind speed forecasting for wind parks management and wind power utilization. In this paper, a novel hybrid approach known as WTT-TNN is proposed for wind speed forecasting. In the first step of the approach, a wavelet transform technique (WTT) is used to decompose wind speed into an approximate scale and several detailed scales. In the second step, a two-hidden-layer neural network (TNN) is used to predict both approximated scale and detailed scales, respectively. In order to find the optimal network architecture, the partial autocorrelation function is adopted to determine the number of neurons in the input layer, and an experimental simulation is made to determine the number of neurons within each hidden layer in the modeling process of TNN. Afterwards, the final prediction value can be obtained by the sum of these prediction results. In this study, a WTT is employed to extract these different patterns of the wind speed and make it easier for forecasting. To evaluate the performance of the proposed approach, it is applied to forecast Hexi Corridor of China's wind speed. Simulation results in four different cases show that the proposed method increases wind speed forecasting accuracy.

  9. Gearless wind power generator

    Energy Technology Data Exchange (ETDEWEB)

    Soederlund, L.; Ridanpaeae, P.; Vihriaelae, H.; Peraelae, R. [Tampere Univ. of Technology (Finland). Lab. of Electricity and Magnetism

    1998-10-01

    In the project a 100 kW axial flux permanent magnet wind power generator has been designed. The toroidal stator with air gap winding is placed between two rotating discs with permanent magnets. The magnet material is NdBFe due to its excellent magnetic properties compared to other materials. This type of topology enables a very large number of poles compared to conventional machine of the same size. A large number of poles is required to achieve a low rotational speed and consequently a direct driven system. The stator winding is formed by rectangular coils. The end winding is very short leading to small resistive losses. On the other hand, the absence of iron teeth causes eddy current losses in the conductors. These can be restricted to an acceptable level by keeping the wire diameter and flux density small. This means that the number of phases should be large. Several independent three phase systems may be used. The toothless stator also means that the iron losses are small and there exists no cogging torque

  10. Assembling Markets for Wind Power

    DEFF Research Database (Denmark)

    Pallesen, Trine

    This project studies the making of a market for wind power in France. Markets for wind power are often referred to as ‘political markets: On the one hand, wind power has the potential to reduce CO2-emissions and thus stall the effects of electricity generation on climate change; and on the other...... hand, as an economic good, wind power is said to suffer from (techno-economic) ‘disabilities’, such as high costs, fluctuating and unpredictable generation, etc. Therefore, because of its performance as a good, it is argued that the survival of wind power in the market is premised on different...... instruments, some of which I will refer to as ‘prosthetic devices’. This thesis inquires into two such prosthetic devices: The feed-in tariff and the wind power development zones (ZDE) as they are negotiated and practiced in France, and also the ways in which they affect the making of markets for wind power....

  11. Challenges, problems and possible solutions in wind generator systems from the aspect of forecast, planning and delivery of wind energy

    International Nuclear Information System (INIS)

    Giovski, Nikola

    2014-01-01

    The fundamental difficulties of integrating wind energy into the power system arise from its large temporal variability and limited predictability. That's why the integration of wind power presents major challenge for today's operating and planning practices of the power system operators. Accurate predictions of the possible wind power output, in time intervals relevant for creating schedules for production and exchange capacity, allows to system operators and dispatching personnel more efficient power system management. Despite the challenges and problems that arise due to integration of wind power into power systems, which need to be solved or reduced, wind power has its advantages that should be utilized. The effective integration of wind power plants into the transmission grid should allow them to represent the backbone of future energy systems. Modern wind generators represent production units that have the ability to participate in the management of energy systems e.g. in the regulation of frequency, voltage and other network operating requirements. This paper provides a brief overview of global experiences with the challenges, problems and possible solutions that appear in wind generator systems from the aspect of forecasting, planning and delivery of wind energy. (author)

  12. A high resolution WRF model for wind energy forecasting

    Science.gov (United States)

    Vincent, Claire Louise; Liu, Yubao

    2010-05-01

    The increasing penetration of wind energy into national electricity markets has increased the demand for accurate surface layer wind forecasts. There has recently been a focus on forecasting the wind at wind farm sites using both statistical models and numerical weather prediction (NWP) models. Recent advances in computing capacity and non-hydrostatic NWP models means that it is possible to nest mesoscale models down to Large Eddy Simulation (LES) scales over the spatial area of a typical wind farm. For example, the WRF model (Skamarock 2008) has been run at a resolution of 123 m over a wind farm site in complex terrain in Colorado (Liu et al. 2009). Although these modelling attempts indicate a great hope for applying such models for detailed wind forecasts over wind farms, one of the obvious challenges of running the model at this resolution is that while some boundary layer structures are expected to be modelled explicitly, boundary layer eddies into the inertial sub-range can only be partly captured. Therefore, the amount and nature of sub-grid-scale mixing that is required is uncertain. Analysis of Liu et al. (2009) modelling results in comparison to wind farm observations indicates that unrealistic wind speed fluctuations with a period of around 1 hour occasionally occurred during the two day modelling period. The problem was addressed by re-running the same modelling system with a) a modified diffusion constant and b) two-way nesting between the high resolution model and its parent domain. The model, which was run with horizontal grid spacing of 370 m, had dimensions of 505 grid points in the east-west direction and 490 points in the north-south direction. It received boundary conditions from a mesoscale model of resolution 1111 m. Both models had 37 levels in the vertical. The mesoscale model was run with a non-local-mixing planetary boundary layer scheme, while the 370 m model was run with no planetary boundary layer scheme. It was found that increasing the

  13. Wind power bidding in electricity markets with high wind penetration

    International Nuclear Information System (INIS)

    Vilim, Michael; Botterud, Audun

    2014-01-01

    Highlights: • We analyze the pricing systems and wind power trading in electricity markets. • We propose a model that captures the relation between market prices and wind power. • A probabilistic bidding model can increase profits for wind power producers. • Profit maximizing bidding strategies carry risks for power system operators. • We conclude that modifications of current market designs may be needed. - Abstract: Objective: The optimal day-ahead bidding strategy is studied for a wind power producer operating in an electricity market with high wind penetration. Methods: A generalized electricity market is studied with minimal assumptions about the structure of the production, bidding, or consumption of electricity. Two electricity imbalance pricing schemes are investigated, the one price and the two price scheme. A stochastic market model is created to capture the price effects of wind power production and consumption. A bidding algorithm called SCOPES (Supply Curve One Price Estimation Strategy) is developed for the one price system. A bidding algorithm called MIMICS (Multivariate Interdependence Minimizing Imbalance Cost Strategy) is developed for the two price system. Results: Both bidding strategies are shown to have advantages over the assumed “default” bidding strategy, the point forecast. Conclusion: The success of these strategies even in the case of high deviation penalties in a one price system and the implicit deviation penalties of the two price system has substantial implications for power producers and system operators in electricity markets with a high level of wind penetration. Practice implications: From an electricity market design perspective, the results indicate that further penalties or regulations may be needed to reduce system imbalance

  14. Real-time impact of power balancing on power system operation with large scale integration of wind power

    DEFF Research Database (Denmark)

    Basit, Abdul; Hansen, Anca Daniela; Sørensen, Poul Ejnar

    2017-01-01

    Highly wind power integrated power system requires continuous active power regulation to tackle the power imbalances resulting from the wind power forecast errors. The active power balance is maintained in real-time with the automatic generation control and also from the control room, where...... power system model. The power system model takes the hour-ahead regulating power plan from power balancing model and the generation and power exchange capacities for the year 2020 into account. The real-time impact of power balancing in a highly wind power integrated power system is assessed...

  15. Wind-Ramp-Forecast Sensitivity to Closure Parameters in a Boundary-Layer Parametrization Scheme

    Science.gov (United States)

    Jahn, David E.; Takle, Eugene S.; Gallus, William A.

    2017-09-01

    Wind ramps are relatively large changes in wind speed over a period of a few hours and present a challenge for electric utilities to balance power generation and load. Failures of boundary-layer parametrization schemes to represent physical processes limit the ability of numerical models to forecast wind ramps, especially in a stable boundary layer. Herein, the eight "closure parameters" of a widely used boundary-layer parameterization scheme are subject to sensitivity tests for a set of wind-ramp cases. A marked sensitivity of forecast wind speed to closure-parameter values is observed primarily for three parameters that influence in the closure equations the depth of turbulent mixing, dissipation, and the transfer of kinetic energy from the mean to the turbulent flow. Reducing the value of these parameters independently by 25% or by 50% reduces the overall average in forecast wind-speed errors by at least 24% for the first two parameters and increases average forecast error by at least 63% for the third parameter. Doubling any of these three parameters increases average forecast error by at least 67%. Such forecast sensitivity to closure parameter values provides motivation to explore alternative values in the context of a stable boundary layer.

  16. Pool Strategy of a Price-Maker Wind Power Producer

    DEFF Research Database (Denmark)

    Zugno, Marco; Morales González, Juan Miguel; Pinson, Pierre

    2013-01-01

    We consider the problem of a wind power producer trading energy in short-term electricity markets. The producer is a price-taker in the day-ahead market, but a price-maker in the balancing market, and aims at optimizing its expected revenues from these market floors. The problem is formulated...... or median forecast of wind power distribution. Finally, sensitivity analyses are carried out to assess the impact on the offering strategy of the producer's penetration in the market, of the correlation between wind power production and residual system deviation, and of the shape of the forecast...

  17. Wind power's coming of age

    International Nuclear Information System (INIS)

    Phillips, J.A.

    1992-01-01

    This article examines the role that wind power has in meeting future energy demand. The topics of the article include demonstration of current technology, an overview of research and market activity, institutional and regulatory barriers and other issues, financing of wind power projects, incentives and penalties, current market experience, national trends in application of wind power plants, advanced technologies, intermittency, power quality, and transmission and distribution

  18. Adaptive calibration of (u,v)‐wind ensemble forecasts

    DEFF Research Database (Denmark)

    Pinson, Pierre

    2012-01-01

    Ensemble forecasts of (u,v)‐wind are of crucial importance for a number of decision‐making problems related to e.g. air traffic control, ship routeing and energy management. The skill of these ensemble forecasts as generated by NWP‐based models can be maximised by correcting for their lack of suf...

  19. Marketing of wind power; Vermarktung von Windenergie

    Energy Technology Data Exchange (ETDEWEB)

    Roon, Serafin von [Forschungsstelle fuer Energiewirtschaft e.V., Muenchen (Germany)

    2011-07-01

    With the integration of the fluctuating production in the system of power supply, there is the question about the impact on the electricity market. The special features of the commercialization of wind energy are: (1) The production exclusively takes place supply-dependent; (2) With fex exceptions, the supplied current is compensated according to the Renewable Energy Law; (3) The actual sale is performed by the operators of transmission systems; (4) The marginal cost are close to zero; (5) The day-ahead marketing solely based on a faulty prognosis. The author of the contribution under consideration reports on the actors and the process of wind power marketing. The alternative of direct marketing and the associated barriers and opportunities are discussed. The impact of the marketing of wind power on pricing in the electricity market is shown by means of an empirical analysis. The compensation amounts are be quantified, and the resulting cost to the balance of the forecast error are estimated.

  20. Modeling of Wind Power Plant

    Energy Technology Data Exchange (ETDEWEB)

    Spacil, D.; Santarius, P. [VSB - Technical University of Ostrava, Department of Electrical Measurement, FEECS, 17. listopadu 15, 708 33 Ostrava- Poruba (Czech Republic); Dobrucky, B. [University of Zilina, Department of Mechatronics and Electronics, FEE, Univerzitna 1, 010 26 Zilina (Slovakia)

    2006-07-01

    The electrical power produced by the wind power plant has increased in the last years in the world and probably will increase further in the future. Therefore, wind power plants have a significant influence on the power production. In this article the connection of the wind turbine to a grid is described in order to determine the impact of the existing wind turbines as well as planned wind turbines on the grid and ensure the proper functioning of the wind turbine. The purpose of the presented work is to find an analytical generator model for the simulation of the wind power plant and determine the influence on the grid by programming with Matlab/Simulink.

  1. The wind power of Mexico

    International Nuclear Information System (INIS)

    Hernandez-Escobedo, Q.; Manzano-Agugliaro, F.; Zapata-Sierra, A.

    2010-01-01

    The high price of fossil fuels and the environmental damage they cause have encouraged the development of renewable energy resources, especially wind power. This work discusses the potential of wind power in Mexico, using data collected every 10 min between 2000 and 2008 at 133 automatic weather stations around the country. The wind speed, the number of hours of wind useful for generating electricity and the potential electrical power that could be generated were estimated for each year via the modelling of a wind turbine employing a logistic curve. A linear correlation of 90.3% was seen between the mean annual wind speed and the mean annual number of hours of useful wind. Maps were constructed of the country showing mean annual wind speeds, useful hours of wind, and the electrical power that could be generated. The results show that Mexico has great wind power potential with practically the entire country enjoying more than 1700 h of useful wind per year and the potential to generate over 2000 kW of electrical power per year per wind turbine installed (except for the Chiapas's State). Indeed, with the exception of six states, over 5000 kW per year could be generated by each turbine. (author)

  2. The wind power of Mexico

    Energy Technology Data Exchange (ETDEWEB)

    Hernandez-Escobedo, Q. [Gerencia de Energias No Convencionales, Instituto de Investigaciones Electricas, Reforma 113 Col. Palmira, C. P. 62490, Cuernavaca, Morelos (Mexico); Manzano-Agugliaro, F.; Zapata-Sierra, A. [Departamento de Ingenieria Rural, Universidad de Almeria, La Canada de San Urbano, 04120 Almeria (Spain)

    2010-12-15

    The high price of fossil fuels and the environmental damage they cause have encouraged the development of renewable energy resources, especially wind power. This work discusses the potential of wind power in Mexico, using data collected every 10 min between 2000 and 2008 at 133 automatic weather stations around the country. The wind speed, the number of hours of wind useful for generating electricity and the potential electrical power that could be generated were estimated for each year via the modelling of a wind turbine employing a logistic curve. A linear correlation of 90.3% was seen between the mean annual wind speed and the mean annual number of hours of useful wind. Maps were constructed of the country showing mean annual wind speeds, useful hours of wind, and the electrical power that could be generated. The results show that Mexico has great wind power potential with practically the entire country enjoying more than 1700 h of useful wind per year and the potential to generate over 2000 kW of electrical power per year per wind turbine installed (except for the Chiapas's State). Indeed, with the exception of six states, over 5000 kW per year could be generated by each turbine. (author)

  3. Results of verification and investigation of wind velocity field forecast. Verification of wind velocity field forecast model

    International Nuclear Information System (INIS)

    Ogawa, Takeshi; Kayano, Mitsunaga; Kikuchi, Hideo; Abe, Takeo; Saga, Kyoji

    1995-01-01

    In Environmental Radioactivity Research Institute, the verification and investigation of the wind velocity field forecast model 'EXPRESS-1' have been carried out since 1991. In fiscal year 1994, as the general analysis, the validity of weather observation data, the local features of wind field, and the validity of the positions of monitoring stations were investigated. The EXPRESS which adopted 500 m mesh so far was improved to 250 m mesh, and the heightening of forecast accuracy was examined, and the comparison with another wind velocity field forecast model 'SPEEDI' was carried out. As the results, there are the places where the correlation with other points of measurement is high and low, and it was found that for the forecast of wind velocity field, by excluding the data of the points with low correlation or installing simplified observation stations to take their data in, the forecast accuracy is improved. The outline of the investigation, the general analysis of weather observation data and the improvements of wind velocity field forecast model and forecast accuracy are reported. (K.I.)

  4. Trading wind energy on the basis of probabilistic forecasts both of wind generation and of market quantities

    DEFF Research Database (Denmark)

    Zugno, Marco; Jónsson, Tryggvi; Pinson, Pierre

    2013-01-01

    in liberalized electricity markets and to assess its performance. At first, the so-called optimal quantile strategy is revisited. It is proved that without market power, i.e. under the price-taker assumption, this strategy maximizes expected market revenues. Forecasts of wind power production, of day......-ahead and real-time market prices and of the system imbalance are inputs to this strategy. Subsequently, constraining of the bid that maximizes the expected revenues is proposed as a way to overcome the strategy's disregard of practical limitations and, at the same time, of risk. Two constraining techniques......Wind power is not easily predictable and non-dispatchable. Nevertheless, wind power producers are increasingly urged to participate in electricity market auctions in the same manner as conventional power producers. The aim of this paper is to propose an operational strategy for trading wind energy...

  5. Disadvantages of the wind power

    International Nuclear Information System (INIS)

    Andersen, Odd W.

    2005-01-01

    The article discussed various disadvantages of the wind power production and focuses on turbine types, generators, operational safety and development aspects. Some environmental problems are mentioned

  6. Wind Tunnel Measurements at LM Wind Power

    DEFF Research Database (Denmark)

    Bertagnolio, Franck

    2012-01-01

    This section presents the results obtained during the experimental campaign that was conducted in the wind tunnel at LM Wind Power in Lunderskov from August 16th to 26th, 2010. The goal of this study is to validate the so-called TNO trailing edge noise model through measurements of the boundary...... layer turbulence characteristics and the far-field noise generated by the acoustic scattering of the turbulent boundary layer vorticies as they convect past the trailing edge. This campaign was conducted with a NACA0015 airfoil section that was placed in the wind tunnel section. It is equipped with high...

  7. Wind Energy Forecasting: A Collaboration of the National Center for Atmospheric Research (NCAR) and Xcel Energy

    Energy Technology Data Exchange (ETDEWEB)

    Parks, K.; Wan, Y. H.; Wiener, G.; Liu, Y.

    2011-10-01

    The focus of this report is the wind forecasting system developed during this contract period with results of performance through the end of 2010. The report is intentionally high-level, with technical details disseminated at various conferences and academic papers. At the end of 2010, Xcel Energy managed the output of 3372 megawatts of installed wind energy. The wind plants span three operating companies1, serving customers in eight states2, and three market structures3. The great majority of the wind energy is contracted through power purchase agreements (PPAs). The remainder is utility owned, Qualifying Facilities (QF), distributed resources (i.e., 'behind the meter'), or merchant entities within Xcel Energy's Balancing Authority footprints. Regardless of the contractual or ownership arrangements, the output of the wind energy is balanced by Xcel Energy's generation resources that include fossil, nuclear, and hydro based facilities that are owned or contracted via PPAs. These facilities are committed and dispatched or bid into day-ahead and real-time markets by Xcel Energy's Commercial Operations department. Wind energy complicates the short and long-term planning goals of least-cost, reliable operations. Due to the uncertainty of wind energy production, inherent suboptimal commitment and dispatch associated with imperfect wind forecasts drives up costs. For example, a gas combined cycle unit may be turned on, or committed, in anticipation of low winds. The reality is winds stayed high, forcing this unit and others to run, or be dispatched, to sub-optimal loading positions. In addition, commitment decisions are frequently irreversible due to minimum up and down time constraints. That is, a dispatcher lives with inefficient decisions made in prior periods. In general, uncertainty contributes to conservative operations - committing more units and keeping them on longer than may have been necessary for purposes of maintaining reliability

  8. A methodology for Electric Power Load Forecasting

    Directory of Open Access Journals (Sweden)

    Eisa Almeshaiei

    2011-06-01

    Full Text Available Electricity demand forecasting is a central and integral process for planning periodical operations and facility expansion in the electricity sector. Demand pattern is almost very complex due to the deregulation of energy markets. Therefore, finding an appropriate forecasting model for a specific electricity network is not an easy task. Although many forecasting methods were developed, none can be generalized for all demand patterns. Therefore, this paper presents a pragmatic methodology that can be used as a guide to construct Electric Power Load Forecasting models. This methodology is mainly based on decomposition and segmentation of the load time series. Several statistical analyses are involved to study the load features and forecasting precision such as moving average and probability plots of load noise. Real daily load data from Kuwaiti electric network are used as a case study. Some results are reported to guide forecasting future needs of this network.

  9. A combined model based on CEEMDAN and modified flower pollination algorithm for wind speed forecasting

    International Nuclear Information System (INIS)

    Zhang, Wenyu; Qu, Zongxi; Zhang, Kequan; Mao, Wenqian; Ma, Yining; Fan, Xu

    2017-01-01

    Highlights: • A CEEMDAN-CLSFPA combined model is proposed for short-term wind speed forecasting. • The CEEMDAN technique is used to decompose the original wind speed series. • A modified optimization algorithm-CLSFPA is proposed to optimize the weights of the combined model. • The no negative constraint theory is applied to the combined model. • Robustness of the proposed model is validated by data sampled from four different wind farms. - Abstract: Wind energy, which is stochastic and intermittent by nature, has a significant influence on power system operation, power grid security and market economics. Precise and reliable wind speed prediction is vital for wind farm planning and operational planning for power grids. To improve wind speed forecasting accuracy, a large number of forecasting approaches have been proposed; however, these models typically do not account for the importance of data preprocessing and are limited by the use of individual models. In this paper, a novel combined model – combining complete ensemble empirical mode decomposition adaptive noise (CEEMDAN), flower pollination algorithm with chaotic local search (CLSFPA), five neural networks and no negative constraint theory (NNCT) – is proposed for short-term wind speed forecasting. First, a recent CEEMDAN is employed to divide the original wind speed data into a finite set of IMF components, and then a combined model, based on NNCT, is proposed for forecasting each decomposition signal. To improve the forecasting capacity of the combined model, a modified flower pollination algorithm (FPA) with chaotic local search (CLS) is proposed and employed to determine the optimal weight coefficients of the combined model, and the final prediction values were obtained by reconstructing the refined series. To evaluate the forecasting ability of the proposed combined model, 15-min wind speed data from four wind farms in the eastern coastal areas of China are used. The experimental results of

  10. Improving Wind-Ramp Forecasts in the Stable Boundary Layer

    Science.gov (United States)

    Jahn, David E.; Takle, Eugene S.; Gallus, William A.

    2017-06-01

    The viability of wind-energy generation is dependent on highly accurate numerical wind forecasts, which are impeded by inaccuracies in model representation of boundary-layer processes. This study revisits the basic theory of the Mellor, Yamada, Nakanishi, and Niino (MYNN) planetary boundary-layer parametrization scheme, focusing on the onset of wind-ramp events related to nocturnal low-level jets. Modifications to the MYNN scheme include: (1) calculation of new closure parameters that determine the relative effects of turbulent energy production, dissipation, and redistribution; (2) enhanced mixing in the stable boundary layer when the mean wind speed exceeds a specified threshold; (3) explicit accounting of turbulent potential energy in the energy budget. A mesoscale model is used to generate short-term (24 h) wind forecasts for a set of 15 cases from both the U.S.A. and Germany. Results show that the new set of closure parameters provides a marked forecast improvement only when used in conjunction with the new mixing length formulation and only for cases that are originally under- or over-forecast (10 of the 15 cases). For these cases, the mean absolute error (MAE) of wind forecasts at turbine-hub height is reduced on average by 17%. A reduction in MAE values on average by 26% is realized for these same cases when accounting for the turbulent potential energy together with the new mixing length. This last method results in an average reduction by at least 13% in MAE values across all 15 cases.

  11. Generation of statistical scenarios of short-term wind power production

    DEFF Research Database (Denmark)

    Pinson, Pierre; Papaefthymiou, George; Klockl, Bernd

    2007-01-01

    Short-term (up to 2-3 days ahead) probabilistic forecasts of wind power provide forecast users with a paramount information on the uncertainty of expected wind generation. Whatever the type of these probabilistic forecasts, they are produced on a per horizon basis, and hence do not inform...... on the development of the forecast uncertainty through forecast series. This issue is addressed here by describing a method that permits to generate statistical scenarios of wind generation that accounts for the interdependence structure of prediction errors, in plus of respecting predictive distributions of wind...

  12. What day-ahead reserves are needed in electric grids with high levels of wind power?

    International Nuclear Information System (INIS)

    Mauch, Brandon; Apt, Jay; Jaramillo, Paulina; Carvalho, Pedro M S

    2013-01-01

    Day-ahead load and wind power forecasts provide useful information for operational decision making, but they are imperfect and forecast errors must be offset with operational reserves and balancing of (real time) energy. Procurement of these reserves is of great operational and financial importance in integrating large-scale wind power. We present a probabilistic method to determine net load forecast uncertainty for day-ahead wind and load forecasts. Our analysis uses data from two different electric grids in the US with similar levels of installed wind capacity but with large differences in wind and load forecast accuracy, due to geographic characteristics. We demonstrate that the day-ahead capacity requirements can be computed based on forecasts of wind and load. For 95% day-ahead reliability, this required capacity ranges from 2100 to 5700 MW for ERCOT, and 1900 to 4500 MW for MISO (with 10 GW of installed wind capacity), depending on the wind and load forecast values. We also show that for each MW of additional wind power capacity for ERCOT, 0.16–0.30 MW of dispatchable capacity will be used to compensate for wind uncertainty based on day-ahead forecasts. For MISO (with its more accurate forecasts), the requirement is 0.07–0.13 MW of dispatchable capacity for each MW of additional wind capacity. (letter)

  13. Wind Resource Assessment and Forecast Planning with Neural Networks

    Directory of Open Access Journals (Sweden)

    Nicolus K. Rotich

    2014-06-01

    Full Text Available In this paper we built three types of artificial neural networks, namely: Feed forward networks, Elman networks and Cascade forward networks, for forecasting wind speeds and directions. A similar network topology was used for all the forecast horizons, regardless of the model type. All the models were then trained with real data of collected wind speeds and directions over a period of two years in the municipal of Puumala, Finland. Up to 70th percentile of the data was used for training, validation and testing, while 71–85th percentile was presented to the trained models for validation. The model outputs were then compared to the last 15% of the original data, by measuring the statistical errors between them. The feed forward networks returned the lowest errors for wind speeds. Cascade forward networks gave the lowest errors for wind directions; Elman networks returned the lowest errors when used for short term forecasting.

  14. Methodology and forecast products for the optimal offering of ancillary services from wind in a market environment

    DEFF Research Database (Denmark)

    Bacher, Peder; Madsen, Henrik; Pinson, Pierre

    of wind power for example in the planning of ancillary power services, where the level of available wind power with a high degree of certainty is important to know. The presented extreme value models are applied to negative forecast residuals from state-of-the-art wind power forecast software...... of extreme weather induced phenomena, for example extreme water levels in a river, wind levels or at sea for design of dykes (de Haan and de Ronde, 1998). In insurance and finance the extreme value modelling is widespread (Embrechts et al., 1997). Extreme value statistics for energy and power applications...... is also widely used, for example for planning in wind power operation (Horvat et al., 2013) and peak wind prediction (Cook, 1982) and (Friederichs and Thorarinsdottir, 2012). Several books provide comprehensive introductions to extreme value theory, for example Coles (2001) and Beirlant et al. (2006...

  15. Online short-term solar power forecasting

    DEFF Research Database (Denmark)

    Bacher, Peder; Madsen, Henrik; Nielsen, Henrik Aalborg

    2009-01-01

    This paper describes a new approach to online forecasting of power production from PV systems. The method is suited to online forecasting in many applications and in this paper it is used to predict hourly values of solar power for horizons of up to 36 hours. The data used is fifteen-minute obser......This paper describes a new approach to online forecasting of power production from PV systems. The method is suited to online forecasting in many applications and in this paper it is used to predict hourly values of solar power for horizons of up to 36 hours. The data used is fifteen......-minute observations of solar power from 21 PV systems located on rooftops in a small village in Denmark. The suggested method is a two-stage method where first a statistical normalization of the solar power is obtained using a clear sky model. The clear sky model is found using statistical smoothing techniques....... Then forecasts of the normalized solar power are calculated using adaptive linear time series models. Both autoregressive (AR) and AR with exogenous input (ARX) models are evaluated, where the latter takes numerical weather predictions (NWPs) as input. The results indicate that for forecasts up to two hours...

  16. Wind speed forecasting using FEEMD echo state networks with RELM in Hebei, China

    International Nuclear Information System (INIS)

    Sun, Wei; Liu, Mohan

    2016-01-01

    Highlights: • FEEMD–RELM is proposed for wind speed forecasting. • Short-term and mid-term wind speed are forecasted by the proposed model. • PACF is introduced to select the input of RELM. • Three cases in Hebei province are applied in this paper. - Abstract: Reducing the dependence on fossil-fuel-based resources is becoming significant due to the detrimental effects on environment and global energy-dependent. Thus, increased attention has been paid to wind power, a type of clean and renewable energy. However, owing to the stochastic nature of wind speed, it is essential to build a wind speed forecasting model with high-precision for wind power utilization. Therefore, this paper proposes a hybrid model which combines fast ensemble empirical model decomposition (FEEMD) with regularized extreme learning machine (RELM). The original wind speed series are first decomposed into a limited number of intrinsic mode functions (IMFs) and one residual series. Then RELM is built to forecast the sub-series. Partial auto correlation function (PACF) is applied to analyze the intrinsic relationships between the historical speeds so as to select the inputs of RELM. To verify the developed models, short-term wind speed data in July 2010 and monthly data from January 2000 to May 2010 in Hong songwa wind farm, Chengde city are used for model construction and testing. Two additional forecasting cases in Hebei province are also applied to prove the model’s validity. The simulation test results show that the built model is effective, efficient and practicable.

  17. Wind power plant system services

    DEFF Research Database (Denmark)

    Basit, Abdul; Altin, Müfit

    Traditionally, conventional power plants have the task to support the power system, by supplying power balancing services. These services are required by the power system operators in order to secure a safe and reliable operation of the power system. However, as in the future the wind power...... is going more and more to replace conventional power plants, the sources of conventional reserve available to the system will be reduced and fewer conventional plants will be available on-line to share the regulation burden. The reliable operation of highly wind power integrated power system might...... then beat risk unless the wind power plants (WPPs) are able to support and participate in power balancing services. The objective of this PhD project is to develop and analyse control strategies which can increase the WPPs capability to provide system services, such as active power balancing control...

  18. Power distribution forecasting device for reactors

    International Nuclear Information System (INIS)

    Tsukii, Makoto

    1981-01-01

    Purpose: To save expensive calculations on the forecasting of reactor power distribution. Constitution: Core status (CSD) such as entire coolant flow rate, pressures in the reactor, temperatures at the outlet and inlet and positions for control rods are inputted into a power distribution calculation device to calculate the power distribution based on physical models intermittently. Further, present power distribution is calculated based on in-core neutron flux measured values and CSD in a process control computer. Further, the ratio of the calculation results of the latter to those of the former is calculated, stored and inputted into a correction device to correct the forecast power distribution obtained by the power distribution calculation device. This enables to forecast the power distribution with excellent responsivity in the reactor site. (Furukawa, Y.)

  19. Mastering the power of wind

    International Nuclear Information System (INIS)

    Stiegel, J.

    1999-01-01

    In this paper the author deals with environmental aspects use of fossil fuels for the energy production. As a way for our planet to get back to a normal and ecologically balanced system the fossil fuels reduction and their replacement by renewable racecourses is recommended. Energetic potential of flowing sun, wind and tidal waves as power resources is discussed. The natural ecological resources are best utilised in the United States where the installed wind power output is 1600 MW. With 360 MW installed output in 1991 the Denmark took lead among European countries in utilising the wind power. The most dynamic power plant development among the European Union countries was recorded in Germany, where the installed power output of the wind power plants is 632 MW, i.e. i.e. 11.5 times higher compared to 55 MW in 1991. The economy of wind power in Germany and in Slovakia is compared. In Slovakia with annual 200 000 kWh power generation annually and the present kWh purchase price guarantee the rate of return of 10 million slovak crowns investment into a wind power plant project is in 100 years. Although the first wind power plants have already been built in the Zahorie, Kremnicke Bane, and Secovce regions, the wind exploitation status in Slovakia is still limping. According to professionals, the wind conditions in Slovakia are not ideal, but sufficient for a supplementary wind power plant system, that can be quite motivating especially for villages. Mount Chopok or mount Krizna are ideal sites to erect the three-blade tower with respect to wind speed. And also the anticipated Kremnicke vrchy site is worth considering. (author)

  20. Active Power Control from Wind Power (Presentation)

    Energy Technology Data Exchange (ETDEWEB)

    Ela, E.; Brooks, D.

    2011-04-01

    In order to keep the electricity grid stable and the lights on, the power system relies on certain responses from its generating fleet. This presentation evaluates the potential for wind turbines and wind power plants to provide these services and assist the grid during critical times.

  1. High resolution probabilistic forecasting for wind energy applications.

    Science.gov (United States)

    Courtney, J.; Sweeney, C.; Lynch, P.

    2012-04-01

    This project aims to produce the best possible wind speed forecasts for the wind energy industry by using an optimal combination of well-established forecasting and post-processing methods. We start with the ECMWF 51 member ensemble prediction system (EPS) and produce a more accurate forecast than the ensemble mean. The 51 members are clustered to 8 weighted representative members (RMs) using a clustering technique. The 8 RMs are chosen to minimize the within-cluster spread, while maximizing the inter-cluster spread. The forecasts are then downscaled using two limited area models, WRF and COSMO, at two resolutions, 14km and 3km. Numerical weather prediction is far from perfect and each of the ensemble member forecasts contains errors, both systematic and chaotic. Systematic errors can be minimized with statistical post-processing. We apply four adaptive post-processing methods to each forecast which require only a short training period. The weighted ensemble mean of the post-processed ensembles is used as the input to a Bayesian Model Averaging (BMA) system. Each ensemble forecast probability density function (PDF) is weighted based on how well it has performed over a training period. The weighted PDFs are then summed to form the BMA PDF which represents the probability of all possible wind speeds and has been proven to outperform the ensemble mean. We present a detailed description of the above process and detail some preliminary results.

  2. MCMC for Wind Power Simulation

    NARCIS (Netherlands)

    Papaefthymiou, G.; Klöckl, B.

    2008-01-01

    This paper contributes a Markov chain Monte Carlo (MCMC) method for the direct generation of synthetic time series of wind power output. It is shown that obtaining a stochastic model directly in the wind power domain leads to reduced number of states and to lower order of the Markov chain at equal

  3. Assembling Markets for Wind Power

    DEFF Research Database (Denmark)

    Pallesen, Trine

    instruments, some of which I will refer to as ‘prosthetic devices’. This thesis inquires into two such prosthetic devices: The feed-in tariff and the wind power development zones (ZDE) as they are negotiated and practiced in France, and also the ways in which they affect the making of markets for wind power....

  4. Analysis of Wind Speed Forecasting Error Effects on Automatic Generation Control Performance

    Directory of Open Access Journals (Sweden)

    H. Rajabi Mashhadi

    2014-09-01

    Full Text Available The main goal of this paper is to study statistical indices and evaluate AGC indices in power system which has large penetration of the WTGs. Increasing penetration of wind turbine generations, needs to study more about impacts of it on power system frequency control. Frequency control is changed with unbalancing real-time system generation and load . Also wind turbine generations have more fluctuations and make system more unbalance. Then AGC loop helps to adjust system frequency and the scheduled tie-line powers. The quality of AGC loop is measured by some indices. A good index is a proper measure shows the AGC performance just as the power system operates. One of well-known measures in literature which was introduced by NERC is Control Performance Standards(CPS. Previously it is claimed that a key factor in CPS index is related to standard deviation of generation error, installed power and frequency response. This paper focuses on impact of a several hours-ahead wind speed forecast error on this factor. Furthermore evaluation of conventional control performances in the power systems with large-scale wind turbine penetration is studied. Effects of wind speed standard deviation and also degree of wind farm penetration are analyzed and importance of mentioned factor are criticized. In addition, influence of mean wind speed forecast error on this factor is investigated. The study system is a two area system which there is significant wind farm in one of those. The results show that mean wind speed forecast error has considerable effect on AGC performance while the mentioned key factor is insensitive to this mean error.

  5. Incorporating geostrophic wind information for improved space–time short-term wind speed forecasting

    KAUST Repository

    Zhu, Xinxin

    2014-09-01

    Accurate short-term wind speed forecasting is needed for the rapid development and efficient operation of wind energy resources. This is, however, a very challenging problem. Although on the large scale, the wind speed is related to atmospheric pressure, temperature, and other meteorological variables, no improvement in forecasting accuracy was found by incorporating air pressure and temperature directly into an advanced space-time statistical forecasting model, the trigonometric direction diurnal (TDD) model. This paper proposes to incorporate the geostrophic wind as a new predictor in the TDD model. The geostrophic wind captures the physical relationship between wind and pressure through the observed approximate balance between the pressure gradient force and the Coriolis acceleration due to the Earth’s rotation. Based on our numerical experiments with data from West Texas, our new method produces more accurate forecasts than does the TDD model using air pressure and temperature for 1to 6-hour-ahead forecasts based on three different evaluation criteria. Furthermore, forecasting errors can be further reduced by using moving average hourly wind speeds to fit the diurnal pattern. For example, our new method obtains between 13.9% and 22.4% overall mean absolute error reduction relative to persistence in 2-hour-ahead forecasts, and between 5.3% and 8.2% reduction relative to the best previous space-time methods in this setting.

  6. Power from the Wind

    Science.gov (United States)

    Roman, Harry T.

    2004-01-01

    Wind energy is the fastest-growing renewable energy source in the world. Over the last 20 years, the wind industry has done a very good job of engineering machines, improving materials, and economies of production, and making this energy source a reality. Like all renewable energy forms, wind energy's successful application is site specific. Also,…

  7. Wind power outlook 2006

    Energy Technology Data Exchange (ETDEWEB)

    anon.

    2006-04-15

    This annual brochure provides the American Wind Energy Association's up-to-date assessment of the wind industry in the United States. This 2006 general assessment shows positive signs of growth, use and acceptance of wind energy as a vital component of the U.S. energy mix.

  8. The economic benefit of short-term forecasting for wind energy in the UK electricity market

    International Nuclear Information System (INIS)

    Barthelmie, R.J.; Murray, F.; Pryor, S.C.

    2008-01-01

    In the UK market, the total price of renewable electricity is made up of the Renewables Obligation Certificate and the price achieved for the electricity. Accurate forecasting improves the price if electricity is traded via the power exchange. In order to understand the size of wind farm for which short-term forecasting becomes economically viable, we develop a model for wind energy. Simulations were carried out for 2003 electricity prices for different forecast accuracies and strategies. The results indicate that it is possible to increase the price obtained by around pound 5/MWh which is about 14% of the electricity price in 2003 and about 6% of the total price. We show that the economic benefit of using short-term forecasting is also dependant on the accuracy and cost of purchasing the forecast. As the amount of wind energy requiring integration into the grid increases, short-term forecasting becomes more important to both wind farm owners and the transmission/distribution operators. (author)

  9. Time Series Analysis and Forecasting for Wind Speeds Using Support Vector Regression Coupled with Artificial Intelligent Algorithms

    Directory of Open Access Journals (Sweden)

    Ping Jiang

    2015-01-01

    Full Text Available Wind speed/power has received increasing attention around the earth due to its renewable nature as well as environmental friendliness. With the global installed wind power capacity rapidly increasing, wind industry is growing into a large-scale business. Reliable short-term wind speed forecasts play a practical and crucial role in wind energy conversion systems, such as the dynamic control of wind turbines and power system scheduling. In this paper, an intelligent hybrid model for short-term wind speed prediction is examined; the model is based on cross correlation (CC analysis and a support vector regression (SVR model that is coupled with brainstorm optimization (BSO and cuckoo search (CS algorithms, which are successfully utilized for parameter determination. The proposed hybrid models were used to forecast short-term wind speeds collected from four wind turbines located on a wind farm in China. The forecasting results demonstrate that the intelligent hybrid models outperform single models for short-term wind speed forecasting, which mainly results from the superiority of BSO and CS for parameter optimization.

  10. Application of Ensemble Sensitivity Analysis to Observation Targeting for Short-term Wind Speed Forecasting in the Washington-Oregon Region

    Energy Technology Data Exchange (ETDEWEB)

    Zack, John [AWS Truewind, LLC, Albany, NY (United States); Natenberg, Eddie [AWS Truewind, LLC, Albany, NY (United States); Young, Steve [AWS Truewind, LLC, Albany, NY (United States); Knowe, Glenn Van [AWS Truewind, LLC, Albany, NY (United States); Waight, Ken [AWS Truewind, LLC, Albany, NY (United States); Manobianco, John [AWS Truewind, LLC, Albany, NY (United States); Kamath, Chandrika [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2010-10-01

    To economically and reliably balance electrical load and generation, electrical grid operators, also called Balancing Authorities (BA), need highly accurate electrical power generation forecasts in time frames ranging from a few minutes to six hours ahead. As wind power generation increases, there is a requirement to improve the accuracy of 0- to 6-hour ahead wind power forecasts. Forecasts covering this short look-ahead period have depended heavily on short-term trends obtained from the actual power production and meteorological data of a wind generation facility. Additional data are often available from Numerical Weather Prediction (NWP) models and sometimes from off-site meteorological towers near wind generation facilities.

  11. Forecasting Wind and Solar Generation: Improving System Operations, Greening the Grid (Spanish Version)

    Energy Technology Data Exchange (ETDEWEB)

    Tian, Tian; Chernyakhovskiy, Ilya; Brancucci Martinez-Anido, Carlo

    2016-04-01

    This document is the Spanish version of 'Greening the Grid- Forecasting Wind and Solar Generation Improving System Operations'. It discusses improving system operations with forecasting with and solar generation. By integrating variable renewable energy (VRE) forecasts into system operations, power system operators can anticipate up- and down-ramps in VRE generation in order to cost-effectively balance load and generation in intra-day and day-ahead scheduling. This leads to reduced fuel costs, improved system reliability, and maximum use of renewable resources.

  12. Use of ground-based wind profiles in mesoscale forecasting

    Science.gov (United States)

    Schlatter, Thomas W.

    1985-01-01

    A brief review is presented of recent uses of ground-based wind profile data in mesoscale forecasting. Some of the applications are in real time, and some are after the fact. Not all of the work mentioned here has been published yet, but references are given wherever possible. As Gage and Balsley (1978) point out, sensitive Doppler radars have been used to examine tropospheric wind profiles since the 1970's. It was not until the early 1980's, however, that the potential contribution of these instruments to operational forecasting and numerical weather prediction became apparent. Profiler winds and radiosonde winds compare favorably, usually within a few m/s in speed and 10 degrees in direction (see Hogg et al., 1983), but the obvious advantage of the profiler is its frequent (hourly or more often) sampling of the same volume. The rawinsonde balloon is launched only twice a day and drifts with the wind. In this paper, I will: (1) mention two operational uses of data from a wind profiling system developed jointly by the Wave Propagation and Aeronomy Laboratories of NOAA; (2) describe a number of displays of these same data on a workstation for mesoscale forecasting developed by the Program for Regional Observing and Forecasting Services (PROFS); and (3) explain some interesting diagnostic calculations performed by meteorologists of the Wave Propagation Laboratory.

  13. Global Energy Forecasting Competition 2012

    DEFF Research Database (Denmark)

    Hong, Tao; Pinson, Pierre; Fan, Shu

    2014-01-01

    The Global Energy Forecasting Competition (GEFCom2012) attracted hundreds of participants worldwide, who contributed many novel ideas to the energy forecasting field. This paper introduces both tracks of GEFCom2012, hierarchical load forecasting and wind power forecasting, with details...

  14. Nowcasting wind power for grid operation at RWE Transportnetz from Strom GmbH (RWE TSO)

    International Nuclear Information System (INIS)

    Ernst, B.; Vanzetta, J.

    2008-01-01

    This paper presented new methods of balancing power supply and demand for electricity systems that have a large share of wind power. Wind power forecasting plays a key role in integrating a large share of wind power into an electricity system, as it links the weather dependent production with the scheduled production of conventional power plants and the forecast of the electricity demand. Wind power forecasts are essential for grid operation. Since most European electricity markets focus on the day ahead market, wind balancing is also done the day ahead. A current trend is that the intra day markets are increasing in popularity and becoming more liquid. Therefore, nowcasting will play a vital role in improving wind power related economics because shorter timeframes are much easier and better to predict. Nowcasting uses actual measurements of weather and also considers power data. Many wind power prediction tools for day ahead forecasts are available. Most models have 3 common steps, notably numerical weather prediction, wind-to-power model and regional up-scaling. A comparison between recent measurements with the output of numerical weather models showed that nowcasting provides a forecast that outperforms a pure numerical weather forecast. The first results were very promising. All 3 nowcasting solutions were found to have their own unique advantages and limitations. Ongoing research will continue to improve wind power prediction. 2 refs., 3 figs

  15. A Hybrid Model Based on Ensemble Empirical Mode Decomposition and Fruit Fly Optimization Algorithm for Wind Speed Forecasting

    Directory of Open Access Journals (Sweden)

    Zongxi Qu

    2016-01-01

    Full Text Available As a type of clean and renewable energy, the superiority of wind power has increasingly captured the world’s attention. Reliable and precise wind speed prediction is vital for wind power generation systems. Thus, a more effective and precise prediction model is essentially needed in the field of wind speed forecasting. Most previous forecasting models could adapt to various wind speed series data; however, these models ignored the importance of the data preprocessing and model parameter optimization. In view of its importance, a novel hybrid ensemble learning paradigm is proposed. In this model, the original wind speed data is firstly divided into a finite set of signal components by ensemble empirical mode decomposition, and then each signal is predicted by several artificial intelligence models with optimized parameters by using the fruit fly optimization algorithm and the final prediction values were obtained by reconstructing the refined series. To estimate the forecasting ability of the proposed model, 15 min wind speed data for wind farms in the coastal areas of China was performed to forecast as a case study. The empirical results show that the proposed hybrid model is superior to some existing traditional forecasting models regarding forecast performance.

  16. Very short-term spatio-temporal wind power prediction using a censored Gaussian field

    DEFF Research Database (Denmark)

    Baxevani, Anastassia; Lenzi, Amanda

    2018-01-01

    to predict the level of wind power and the associated variability are critical. Ideally, one would like to obtain reliable probability density forecasts for the wind power distributions. We aim at contributing to the literature of wind power prediction by developing and analysing a spatio...

  17. The impact of scatterometer wind data on global weather forecasting

    Science.gov (United States)

    Atlas, D.; Baker, W. E.; Kalnay, E.; Halem, M.; Woiceshyn, P. M.; Peteherych, S.

    1984-01-01

    The impact of SEASAT-A scatterometer (SASS) winds on coarse resolution atmospheric model forecasts was assessed. The scatterometer provides high resolution winds, but each wind can have up to four possible directions. One wind direction is correct; the remainder are ambiguous or "aliases'. In general, the effect of objectively dealiased-SASS data was found to be negligible in the Northern Hemisphere. In the Southern Hemisphere, the impact was larger and primarily beneficial when vertical temperature profile radiometer (VTPR) data was excluded. However, the inclusion of VTPR data eliminates the positive impact, indicating some redundancy between the two data sets.

  18. Attitudes towards wind power

    International Nuclear Information System (INIS)

    Young, B.

    1993-01-01

    Planning permission for the construction of a small 'farm' of wind turbines at Delabole (Deli windfarm) had been obtained and it was intended to use this source of renewable energy by generating electricity and selling it to the electrical power companies for distribution through the National Grid. It was important, therefore, to establish just what the attitudes of local residents were to the proposed development. A programme of research was discussed with the developer and it was agreed that an attitude survey would be conducted in the local area in the summer of 1990, before the turbines were erected, and before the tourist season was completely spent in order to obtain the views of visitors as well. A similar survey would then be done one year later, when the Deli windfarm was established and running. In addition, control samples would be taken at these two times in Exeter to give baseline information on attitudes toward this topic. This proposal was put to the developer and agreement was reached with him and the UK Department of Energy who were providing financial support for the research. The results of the research are reported. (author)

  19. 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)

  20. A data-driven multi-model methodology with deep feature selection for short-term wind forecasting

    International Nuclear Information System (INIS)

    Feng, Cong; Cui, Mingjian; Hodge, Bri-Mathias; Zhang, Jie

    2017-01-01

    Highlights: • An ensemble model is developed to produce both deterministic and probabilistic wind forecasts. • A deep feature selection framework is developed to optimally determine the inputs to the forecasting methodology. • The developed ensemble methodology has improved the forecasting accuracy by up to 30%. - Abstract: With the growing wind penetration into the power system worldwide, improving wind power forecasting accuracy is becoming increasingly important to ensure continued economic and reliable power system operations. In this paper, a data-driven multi-model wind forecasting methodology is developed with a two-layer ensemble machine learning technique. The first layer is composed of multiple machine learning models that generate individual forecasts. A deep feature selection framework is developed to determine the most suitable inputs to the first layer machine learning models. Then, a blending algorithm is applied in the second layer to create an ensemble of the forecasts produced by first layer models and generate both deterministic and probabilistic forecasts. This two-layer model seeks to utilize the statistically different characteristics of each machine learning algorithm. A number of machine learning algorithms are selected and compared in both layers. This developed multi-model wind forecasting methodology is compared to several benchmarks. The effectiveness of the proposed methodology is evaluated to provide 1-hour-ahead wind speed forecasting at seven locations of the Surface Radiation network. Numerical results show that comparing to the single-algorithm models, the developed multi-model framework with deep feature selection procedure has improved the forecasting accuracy by up to 30%.

  1. Forecasting Canadian nuclear power station construction costs

    International Nuclear Information System (INIS)

    Keng, C.W.K.

    1985-01-01

    Because of the huge volume of capital required to construct a modern electric power generating station, investment decisions have to be made with as complete an understanding of the consequences of the decision as possible. This understanding must be provided by the evaluation of future situations. A key consideration in an evaluation is the financial component. This paper attempts to use an econometric method to forecast the construction costs escalation of a standard Canadian nuclear generating station (NGS). A brief review of the history of Canadian nuclear electric power is provided. The major components of the construction costs of a Canadian NGS are studied and summarized. A database is built and indexes are prepared. Based on these indexes, an econometric forecasting model is constructed using an apparently new econometric methodology of forecasting modelling. Forecasts for a period of 40 years are generated and applications (such as alternative scenario forecasts and range forecasts) to uncertainty assessment and/or decision-making are demonstrated. The indexes, the model, and the forecasts and their applications, to the best of the author's knowledge, are the first for Canadian NGS constructions. (author)

  2. Wind Power Today and Tomorrow

    Energy Technology Data Exchange (ETDEWEB)

    2004-03-01

    Wind Power Today and Tomorrow is an annual publication that provides an overview of the wind research conducted under the U.S. Department of Energy's Wind and Hydropower Technologies Program. The purpose of Wind Power Today and Tomorrow is to show how DOE supports wind turbine research and deployment in hopes of furthering the advancement of wind technologies that produce clean, low-cost, reliable energy. Content objectives include: educate readers about the advantages and potential for widespread deployment of wind energy; explain the program's objectives and goals; describe the program's accomplishments in research and application; examine the barriers to widespread deployment; describe the benefits of continued research and development; facilitate technology transfer; and attract cooperative wind energy projects with industry. This 2003 edition of the program overview also includes discussions about wind industry growth in 2003, how DOE is taking advantage of low wind speed region s through advancing technology, and distributed applications for small wind turbines.

  3. Wind Speed Forecasting Using Hybrid Wavelet Transform—ARMA Techniques

    Directory of Open Access Journals (Sweden)

    Diksha Kaur

    2015-01-01

    Full Text Available The objective of this paper is to develop a novel wind speed forecasting technique, which produces more accurate prediction. The Wavelet Transform (WT along with the Auto Regressive Moving Average (ARMA is chosen to form a hybrid whose combination is expected to give minimum Mean Absolute Prediction Error (MAPE. A simulation study has been conducted by comparing the forecasting results using the Wavelet-ARMA with the ARMA and Artificial Neural Network (ANN-Ensemble Kalman Filter (EnKF hybrid technique to verify the effectiveness of the proposed hybrid method. Results of the proposed hybrid show significant improvements in the forecasting error.

  4. A Review of Power Electronics for Wind Power

    DEFF Research Database (Denmark)

    Chen, Zhe

    2011-01-01

    The paper reviews the power electronic applications for wind energy systems. Main wind turbine systems with different generators and power electronic converters are described. The electrical topologies of wind farms with power electronic conversion are discussed. Power electronic applications...

  5. Two-Tier Reactive Power and Voltage Control Strategy Based on ARMA Renewable Power Forecasting Models

    Directory of Open Access Journals (Sweden)

    Jinling Lu

    2017-10-01

    Full Text Available To address the static voltage stability issue and suppress the voltage fluctuation caused by the increasing integration of wind farms and solar photovoltaic (PV power plants, a two-tier reactive power and voltage control strategy based on ARMA power forecasting models for wind and solar plants is proposed in this paper. Firstly, ARMA models are established to forecast the output of wind farms and solar PV plants. Secondly, the discrete equipment is pre-regulated based on the single-step prediction information from ARMA forecasting models according to the optimization result. Thirdly, a multi-objective optimization model is presented and solved by particle swarm optimization (PSO according to the measured data and the proposed static voltage stability index. Finally, the IEEE14 bus system including a wind farm and solar PV plant is utilized to test the effectiveness of the proposed strategy. The results show that the proposed strategy can suppress voltage fluctuation and improve the static voltage stability under the condition of high penetration of renewables including wind and solar power.

  6. Wind power developments in New Zealand

    International Nuclear Information System (INIS)

    Botha, P.; White, G.

    1997-01-01

    New Zealand currently generates approximately 86% of its electricity requirement from renewable energy sources, predominantly large hydro. Forecasts show that due to the expected increase in demand, a new mid-sized power station will be required by 1997/98. Due to the commercialisation and restructuring of the electricity market, and despite the country's commitment to CO 2 reductions, proposed new large generation projects are gas fired stations. The country's first commercial wind farm was commissioned in June 1996, in a market where there are no subsidies or tax benefits for non traditional energy generation. For wind power projects to compete with other forms of electricity generation, they need to take full advantage of all the benefits of being embedded into the local network. This paper considers these issues in the existing electricity market. (author)

  7. Compensating active power imbalances in power system with large-scale wind power penetration

    DEFF Research Database (Denmark)

    Basit, Abdul; Hansen, Anca Daniela; Altin, Müfit

    2016-01-01

    Large-scale wind power penetration can affectthe supply continuity in the power system. This is a matterof high priority to investigate, as more regulating reservesand specified control strategies for generation control arerequired in the future power system with even more highwind power...... penetration. This paper evaluates the impact oflarge-scale wind power integration on future power systems.An active power balance control methodology is usedfor compensating the power imbalances between thedemand and the generation in real time, caused by windpower forecast errors. The methodology...... for the balancepower control of future power systems with large-scalewind power integration is described and exemplified consideringthe generation and power exchange capacities in2020 for Danish power system....

  8. Noise from wind power plants

    International Nuclear Information System (INIS)

    Ljunggren, S.

    2001-12-01

    First, the generation of noise at wind power plants and the character of the sound is described. The propagation of the sound and its dependence on the structure of the ground and on wind and temperature is treated next. Models for calculation of the noise emission are reviewed and examples of applications are given. Different means for reducing the disturbances are described

  9. Are local wind power resources well estimated?

    Science.gov (United States)

    Lundtang Petersen, Erik; Troen, Ib; Jørgensen, Hans E.; Mann, Jakob

    2013-03-01

    Planning and financing of wind power installations require very importantly accurate resource estimation in addition to a number of other considerations relating to environment and economy. Furthermore, individual wind energy installations cannot in general be seen in isolation. It is well known that the spacing of turbines in wind farms is critical for maximum power production. It is also well established that the collective effect of wind turbines in large wind farms or of several wind farms can limit the wind power extraction downwind. This has been documented by many years of production statistics. For the very large, regional sized wind farms, a number of numerical studies have pointed to additional adverse changes to the regional wind climate, most recently by the detailed studies of Adams and Keith [1]. They show that the geophysical limit to wind power production is likely to be lower than previously estimated. Although this problem is of far future concern, it has to be considered seriously. In their paper they estimate that a wind farm larger than 100 km2 is limited to about 1 W m-2. However, a 20 km2 off shore farm, Horns Rev 1, has in the last five years produced 3.98 W m-2 [5]. In that light it is highly unlikely that the effects pointed out by [1] will pose any immediate threat to wind energy in coming decades. Today a number of well-established mesoscale and microscale models exist for estimating wind resources and design parameters and in many cases they work well. This is especially true if good local data are available for calibrating the models or for their validation. The wind energy industry is still troubled by many projects showing considerable negative discrepancies between calculated and actually experienced production numbers and operating conditions. 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. The

  10. A quick guide to wind power forecating : state-of-the-art 2009.

    Energy Technology Data Exchange (ETDEWEB)

    Monteiro, C.; Keko, H.; Bessa, R.; Miranda, V.; Botterud, A.; Wang, J.; Conzelmann, G.; Decision and Information Sciences; INESC Porto

    2009-11-20

    This document contains a summary of the main findings from our full report entitled 'Wind Power Forecasting: State-of-the-Art 2009'. The aims of this document are to provide guidelines and a quick overview of the current state-of-the-art in wind power forecasting (WPF) and to point out lines of research in the future development of forecasting systems.

  11. Starting to Explore Wind Power

    Science.gov (United States)

    Hare, Jonathan

    2008-01-01

    Described is a simple, cheap and versatile homemade windmill and electrical generator suitable for a school class to use to explore many aspects and practicalities of using wind to generate electrical power. (Contains 8 figures.)

  12. Forecasting and decision-making in electricity markets with focus on wind energy

    DEFF Research Database (Denmark)

    Jónsson, Tryggvi

    by these different characteristics. The thesis presents analyses of how this impact is realised in markets significantly penetrated by wind power. Due to its representation by forecasts in the supply curve, such predictions are used to describe their non-linear influence on the market prices. Methods adequately...... accounting for this effect in models for day-ahead forecasting of the prices are also presented in the thesis. Prompted by the volatile behaviour of electricity markets, considerable focus has been on time-varying and robust parameter estimates. The models derived are all based on well know methods from...... the statistical literature. The stochastic production of wind turbines prompts the need for alternative methods for optimally bidding wind power to day-ahead markets. Such bidding strategies are formulated in this thesis, which utilise the information provided by the market models. Bids that maximise expected...

  13. Wind farm - A power source in future power systems

    DEFF Research Database (Denmark)

    Chen, Zhe; Blaabjerg, Frede

    2009-01-01

    The paper describes modern wind power systems, introduces the issues of large penetration of wind power into power systems, and discusses the possible methods of making wind turbines/farms act as a power source, like conventional power plants in power systems. Firstly, the paper describes modern...... wind turbines and wind farms, and then introduces the wind power development and wind farms. An optimization platform for designing electrical systems of offshore wind farms is briefed. The major issues related to the grid connection requirements and the operation of wind turbines/farms in power...... systems are illustrated....

  14. Panorama 2016 - Offshore wind power

    International Nuclear Information System (INIS)

    Vinot, Simon

    2015-11-01

    While onshore wind power is a rapidly growing global industry, the offshore wind power market remains in its consolidation and globalization phase. This most mature of renewable marine energies continues to develop and can no longer be considered a niche industry. This fact sheet evaluates the market over the last several years, looking at its potential and its current rank in terms of electricity production costs. (author)

  15. Panorama 2013 - Offshore wind power

    International Nuclear Information System (INIS)

    Vinot, Simon

    2012-10-01

    While onshore wind power is already a well-developed global industry, offshore wind power is still in the consolidation and globalization phase. The most mature of marine renewable energies is beginning to venture off the European coast and even to other continents, driven by public policies and the ever increasing number of players joining this promising market, which should evolve into deeper waters thanks to floating structures. (author)

  16. Detecting and characterising ramp events in wind power time series

    International Nuclear Information System (INIS)

    Gallego, Cristóbal; Cuerva, Álvaro; Costa, Alexandre

    2014-01-01

    In order to implement accurate models for wind power ramp forecasting, ramps need to be previously characterised. This issue has been typically addressed by performing binary ramp/non-ramp classifications based on ad-hoc assessed thresholds. However, recent works question this approach. This paper presents the ramp function, an innovative wavelet- based tool which detects and characterises ramp events in wind power time series. The underlying idea is to assess a continuous index related to the ramp intensity at each time step, which is obtained by considering large power output gradients evaluated under different time scales (up to typical ramp durations). The ramp function overcomes some of the drawbacks shown by the aforementioned binary classification and permits forecasters to easily reveal specific features of the ramp behaviour observed at a wind farm. As an example, the daily profile of the ramp-up and ramp-down intensities are obtained for the case of a wind farm located in Spain

  17. Offshore wind power in Finland

    Energy Technology Data Exchange (ETDEWEB)

    Holttinen, H. [VTT Energy, Espoo (Finland)

    1998-12-31

    The objectives of the project were to estimate the technical offshore wind power potential of the Gulf of Bothnia, with cost assessments, to study icing conditions and ice loads, and to design a foundation suitable for the environmental conditions. The technical offshore potential from Vaasa to Tornio is huge, more than 40 TWh/a, although the cost of offshore wind power is still higher than on land. Wind turbines have not previously been designed for the icing conditions found in Gulf of Bothnia and the recommendations for load cases and siting of megawatt-class turbines are an important result of the project. (orig.)

  18. Power control and management of the grid containing largescale wind power systems

    Science.gov (United States)

    Aula, Fadhil Toufick

    The ever increasing demand for electricity has driven many countries toward the installation of new generation facilities. However, concerns such as environmental pollution and global warming issues, clean energy sources, high costs associated with installation of new conventional power plants, and fossil fuels depletion have created many interests in finding alternatives to conventional fossil fuels for generating electricity. Wind energy is one of the most rapidly growing renewable power sources and wind power generations have been increasingly demanded as an alternative to the conventional fossil fuels. However, wind power fluctuates due to variation of wind speed. Therefore, large-scale integration of wind energy conversion systems is a threat to the stability and reliability of utility grids containing these systems. They disturb the balance between power generation and consumption, affect the quality of the electricity, and complicate load sharing and load distribution managing and planning. Overall, wind power systems do not help in providing any services such as operating and regulating reserves to the power grid. In order to resolve these issues, research has been conducted in utilizing weather forecasting data to improve the performance of the wind power system, reduce the influence of the fluctuations, and plan power management of the grid containing large-scale wind power systems which consist of doubly-fed induction generator based energy conversion system. The aims of this research, my dissertation, are to provide new methods for: smoothing the output power of the wind power systems and reducing the influence of their fluctuations, power managing and planning of a grid containing these systems and other conventional power plants, and providing a new structure of implementing of latest microprocessor technology for controlling and managing the operation of the wind power system. In this research, in order to reduce and smooth the fluctuations, two

  19. Research and Application Based on Adaptive Boosting Strategy and Modified CGFPA Algorithm: A Case Study for Wind Speed Forecasting

    Directory of Open Access Journals (Sweden)

    Jiani Heng

    2016-03-01

    Full Text Available Wind energy is increasingly considered one of the most promising sustainable energy sources for its characteristics of cleanliness without any pollution. Wind speed forecasting is a vital problem in wind power industry. However, individual forecasting models ignore the significance of data preprocessing and model parameter optimization, which may lead to poor forecasting performance. In this paper, a novel hybrid [k, Bt] -ABBP (back propagation based on adaptive strategy with parameters k and Bt model was developed based on an adaptive boosting (AB strategy that integrates several BP (back propagation neural networks for wind speed forecasting. The fast ensemble empirical mode decomposition technique is initially conducted in the preprocessing stage to reconstruct data, while a novel modified FPA (flower pollination algorithm incorporating a conjugate gradient (CG is proposed for searching for the optimal parameters of the [k, Bt] -ABBP mode. The case studies of five wind power stations in Penglai, China are used as illustrative examples for evaluating the effectiveness and efficiency of the developed hybrid forecast strategy. Numerical results show that the developed hybrid model is simple and can satisfactorily approximate the actual wind speed series. Therefore, the developed hybrid model can be an effective tool in mining and analysis for wind power plants.

  20. Operating the Irish power system with increased levels of wind power

    DEFF Research Database (Denmark)

    Tuohy, A.; Denny, E.; Meibom, Peter

    2008-01-01

    This paper summarises some of the main impacts of large amounts of wind power installed in the island of Ireland. Using results from various studies performed on this system, it is shown that wind power will impact on all time frames, from seconds to daily planning of the system operation. Results...... from studies examining operation of the system with up to approximately 40% of electricity provided by wind show that some of the most important aspects to be considered include the type of wind turbine technology, the provision of reserve to accommodate wind forecasting error and the method used...

  1. Inclusion of routine wind and turbulence forecasts in the Savannah River Plant's emergency response capabilities

    International Nuclear Information System (INIS)

    Pendergast, M.M.; Gilhousen, D.B.

    1980-01-01

    The Savannah River Plant's emergency response computer system was improved by the implementation of automatic forecasts of wind and turbulence for periods up to 30 hours. The forecasts include wind direction, wind speed, and horizontal and vertical turbulence intensity at 10, 91, and 243 m above ground for the SRP area, and were obtained by using the Model Output Statistics (MOS) technique. A technique was developed and tested to use the 30-hour MOS forecasts of wind and turbulence issued twice daily from the National Weather Service at Suitland, Maryland, into SRP's emergency response program. The technique for combining MOS forecasts, persistence, and adjusted-MOS forecast is used to generate good forecasts any time of day. Wind speed and turbulence forecasts have been shown to produce smaller root mean square errors (RMSE) than forecasts of persistence for time periods over about two hours. For wind direction, the adjusted-MOS forecasts produce smaller RMSE than persistence for times greater than four hours

  2. Regime-based supervisory control to reduce power fluctuations from offshore wind power plants

    DEFF Research Database (Denmark)

    Barahona Garzón, Braulio; Cutululis, Nicolaos Antonio; Trombe, Pierre-Julien

    2013-01-01

    Wind power fluctuations, especially offshore, can pose challenges in the secure and stable operation of the power system. In modern large offshore wind farms, there are supervisory controls designed to reduce the power fluctuations. Their operation is limited due to the fact that they imply loss...... of production, hence revenue for the wind farm operator. On the other hand, progresses in short term forecasting, together with the increasing use of probabilistic forecasting can help in achieving efficient power fluctuations reduction with minimum lost production. Here we present supervisory control concepts...... that consider different wind power regimes to derive control setpoints by using a Markov-Switching AutoRegressive model. We evaluate the performance versus measured data in terms of power ramp characteristics and energy efficiency....

  3. Innovation paths in wind power

    DEFF Research Database (Denmark)

    Lema, Rasmus; Nordensvärd, Johan; Urban, Frauke

    Denmark and Germany both make substantial investments in low carbon innovation, not least in the wind power sector. These investments in wind energy are driven by the twin objectives of reducing carbon emissions and building up international competitive advantage. Support for wind power dates back...... paths: government policies, demand conditions, geography, value chains, and the strategies undertaken by firms. It demonstrates that the innovation paths common to both countries have roots in a confluence of determining factors which are mainly due to social and political priorities, preferences...... Denmark and Germany have common national causes, while company-specific strategies also influence the innovation paths in significant ways. This raises important questions about the national specificity of innovation paths in wind power development. Finally, the paper briefly addresses the increasing...

  4. Forecasting Production Losses at a Swedish Wind Farm

    DEFF Research Database (Denmark)

    Production loss due to icing has been identified as a problem both when siting turbines in cold climates, and when making forecasts of energy production for wind park management and energy markets. The Makkonen icing model (Makkonen, 2000), driven by output from the WRF mesoscale model, has been...... shown to predict periods of icing at a wind farm in northern Sweden (Davis et al, 2012) with improved skill compared to persistence and threshold models. Based on these results, we have developed a statistical model to estimate the loss of production at the wind park due to these icing periods. We...... compared this statistical model with a simpler method that does not rely on a physical icing model. In that method meteorological icing is identified as periods when WRF forecasts clouds and the temperature is below freezing. During these periods it is assumed that there is no production from the turbines...

  5. Advanced mesoscale forecasts of icing events for Gaspe wind farms

    International Nuclear Information System (INIS)

    Gayraud, A.; Benoit, R.; Camion, A.

    2009-01-01

    Atmospheric icing includes every event which causes ice accumulations of various shapes on different structures. In terms of its effects on wind farms, atmospheric icing can decrease the aerodynamic performance, cause structure overloading, and add vibrations leading to failure and breaking. This presentation discussed advanced mesoscale forecasts of icing events for Gaspe wind farms. The context of the study was discussed with particular reference to atmospheric icing; effects on wind farms; and forecast objectives. The presentation also described the models and results of the study. These included MC2, a compressible community model, as well as a Milbrandt and Yau condensation scheme. It was shown that the study has provided good estimates of the duration of events as well as reliable precipitation categories. tabs., figs.

  6. Options to Improve the Quality of Wind Generation Output Forecasting with the Use of Available Information as Explanatory Variables

    Directory of Open Access Journals (Sweden)

    Rafał Magulski

    2015-06-01

    Full Text Available Development of wind generation, besides its positive aspects related to the use of renewable energy, is a challenge from the point of view of power systems’ operational security and economy. The uncertain and variable nature of wind generation sources entails the need for the for the TSO to provide adequate reserves of power, necessary to maintain the grid’s stable operation, and the actors involved in the trading of energy from these sources incur additional of balancing unplanned output deviations. The paper presents the results of analyses concerning the options to forecast a selected wind farm’s output exercised by means of different methods of prediction, using a different range of measurement and forecasting data available on the farm and its surroundings. The analyses focused on the evaluation of forecast errors, and selection of input data for forecasting models and assessment of their impact on prediction quality improvement.

  7. The use of Markov chains in forecasting wind speed: Matlab source code and applied case study

    Directory of Open Access Journals (Sweden)

    Ionuţ Alexandru Petre

    2017-01-01

    Full Text Available The ability to predict the wind speed has an important role for renewable energy industry which relies on wind speed forecasts in order to calculate the power a wind farm can produce in an area. There are several well-known methods to predict wind speed, but in this paper we focus on short-term wind forecasting using Markov chains. Often gaps can be found in the time series of the wind speed measurements and repeating the measurements is usually not a valid option. In this study it is shown that using Markov chains these gaps from the time series can be filled (they can be generated in an efficient way, but only when the missing data is for a short period of time. Also, the developed Matlab programms that are used in the case study, are included in the paper beeing presented and commented by the authors. In the case study data from a wind farm in Italy is used. The available data are as average wind speed at an interval of 10 minutes in the time period 11/23/2005 - 4/27/2006.

  8. Wind Power in Electrical Distribution Systems

    DEFF Research Database (Denmark)

    Chen, Zhe

    2013-01-01

    Recent years, wind power is experiencing a rapid growth, large number of wind turbines/wind farms have been installed and connected to power systems. In addition to the large centralised wind farms connected to transmission grids, many distributed wind turbines and wind farms are operated...... as distributed generators in distribution systems. This paper discusses the issues of wind turbines in distribution systems. Wind power conversion systems briefly introduced, the basic features and technical characteristics of distributed wind power system are described, and the main technical demands...

  9. China Wind Power Outlook 2010

    International Nuclear Information System (INIS)

    Junfeng, Li; Pengfei, Shi; Hu, Gao

    2010-10-01

    China's wind power can reach 230 GW of installed capacity by 2020, which is equal to 13 times the current capacity of the Three Gorges Dam; its annual electricity output of 464.9 TWh could replace 200 coal fire power plants. In 2009, China led the world in newly installed wind-energy devices, reaching a capacity of 13.8 GW (10,129 turbines) - a rate of one new turbine every hour. In terms of overall capacity, China ranks second, at 25.8 GW. The report projects that by 2020, China's total wind power capacity will reach at least 150GW, possibly up to 230GW, which, if realized, could cut 410 million tons of CO2 emission, or 150 million tons of coal consumption. Compared to multinationals, many Chinese companies are young and lack a strong basis for research and development. Despite a renewable energy policy requiring grid companies to purchase all electricity from wind farms, access to wind power for the grid is frequently lagging behind an unstable, out-dated grid infrastructure. There is also the problem of a lack of incentives and penalties for grid companies, and slow progress in more wind energy technologies.

  10. Wind power in political whirlwind

    International Nuclear Information System (INIS)

    Morch, Stein

    2002-01-01

    In Norway, according to this article, shifting fair wind and head wind for wind power have changed to unpredictable political whirlwinds. That is, there is great uncertainty with respect to further development of wind power in Norway as well as in nearby markets such as Sweden, Denmark and the Netherlands. The government, represented by Enova, has announced reduced investment grants, and so the realization of a ''green'' market, at home or across the frontiers, becomes very important. The political goal of producing 3 TWh of wind power per year by 2010 apparently is still valid, but it is difficult to see any robust and convincing clarity when it comes to policy instruments and economical frames that will make it possible to reach that goal. In its directive on renewable energy sources in the energy generation, the EU has quoted a total increase in capacity from 14 percent in 1997 to 22 percent in 2010. This has been shared among the member countries as indicative targets and there is great freedom in the selection of policy instruments. At the end of 2002, the wind power production in Norway is 0.3 TWh/year

  11. The Wind Forecast Improvement Project (WFIP): A Public/Private Partnership for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits of Utility Operations. The Southern Study Area, Final Report

    Energy Technology Data Exchange (ETDEWEB)

    Freedman, Jeffrey M. [AWS Truepower, LLC, Albany, NY (United States); Manobianco, John [MESO, Inc., Troy, NY (United States); Schroeder, John [Texas Tech Univ., Lubbock, TX (United States). National Wind Inst.; Ancell, Brian [Texas Tech Univ., Lubbock, TX (United States). Atmospheric Science Group; Brewster, Keith [Univ. of Oklahoma, Norman, OK (United States). Center for Analysis and Prediction of Storms; Basu, Sukanta [North Carolina State Univ., Raleigh, NC (United States). Dept. of Marine, Earth, and Atmospheric Sciences; Banunarayanan, Venkat [ICF International (United States); Hodge, Bri-Mathias [National Renewable Energy Lab. (NREL), Golden, CO (United States); Flores, Isabel [Electricity Reliability Council of Texas (United States)

    2014-04-30

    This Final Report presents a comprehensive description, findings, and conclusions for the Wind Forecast Improvement Project (WFIP) -- Southern Study Area (SSA) work led by AWS Truepower (AWST). This multi-year effort, sponsored by the Department of Energy (DOE) and National Oceanographic and Atmospheric Administration (NOAA), focused on improving short-term (15-minute - 6 hour) wind power production forecasts through the deployment of an enhanced observation network of surface and remote sensing instrumentation and the use of a state-of-the-art forecast modeling system. Key findings from the SSA modeling and forecast effort include: 1. The AWST WFIP modeling system produced an overall 10 - 20% improvement in wind power production forecasts over the existing Baseline system, especially during the first three forecast hours; 2. Improvements in ramp forecast skill, particularly for larger up and down ramps; 3. The AWST WFIP data denial experiments showed mixed results in the forecasts incorporating the experimental network instrumentation; however, ramp forecasts showed significant benefit from the additional observations, indicating that the enhanced observations were key to the model systems’ ability to capture phenomena responsible for producing large short-term excursions in power production; 4. The OU CAPS ARPS simulations showed that the additional WFIP instrument data had a small impact on their 3-km forecasts that lasted for the first 5-6 hours, and increasing the vertical model resolution in the boundary layer had a greater impact, also in the first 5 hours; and 5. The TTU simulations were inconclusive as to which assimilation scheme (3DVAR versus EnKF) provided better forecasts, and the additional observations resulted in some improvement to the forecasts in the first 1 - 3 hours.

  12. Observability of wind power; Observabilite de la production eolienne

    Energy Technology Data Exchange (ETDEWEB)

    Gonot, J.P. [Reseau de Transport d' Electricite, Dir. du Projet IPES, 92 - La Defense (France); Fraisse, J.L. [Electricite Reseau Distribution France (ERDF), Service Raccordement, 92 - Paris la defense (France)

    2009-10-15

    The total installed capacity of wind power grows from a few hundred MW at the beginning of 2005 to 3400 MW at the end of 2008. With such a trend, a total capacity of 7000 MW could be reached by 2010. The natural variability of wind power and the difficulty of its predictability require a change in the traditional way of managing supply/demand balance, day-ahead margins and the control of electrical flows. As a consequence, RTE operators should be informed quickly and reliably of the real time output power of wind farms and of its evolvement some hours or days ahead to ensure the reliability of the French electrical power system. French specificities are that wind farms are largely spread over the territory, that 95 % of wind farms have an output power below 10 MW and that they are connected to the distribution network. In this context, new tools were necessary to acquire as soon as possible data concerning wind power. In two years long, RTE set up an observatory of wind production 'IPES system' enable to get an access to the technical characteristics of the whole wind farms, to observe in real time 75 % of the wind generation and to implement a forecast model related to wind generation. (authors)

  13. Offshore wind speed and wind power characteristics for ten ...

    Indian Academy of Sciences (India)

    This paper utilizes wind speed data measured at 3 and 10 m above water surface level using buoys at 10 stations in Ionian and Aegean Seas to understand the behaviour of wind and thereafter energy yield at these stations using 5 MW rated power offshore wind turbine. With wind power densities of 971 and 693 W/m2 at ...

  14. Pollutant forecasting error based on persistence of wind direction

    International Nuclear Information System (INIS)

    Cooper, R.E.

    1978-01-01

    The purpose of this report is to provide a means of estimating the reliability of forecasts of downwind pollutant concentrations from atmospheric puff releases. These forecasts are based on assuming the persistence of wind direction as determined at the time of release. This initial forecast will be used to deploy survey teams, to predict population centers that may be affected, and to estimate the amount of time available for emergency response. Reliability of forecasting is evaluated by developing a cumulative probability distribution of error as a function of lapsed time following an assumed release. The cumulative error is determined by comparing the forecast pollutant concentration with the concentration measured by sampling along the real-time meteorological trajectory. It may be concluded that the assumption of meteorological persistence for emergency response is not very good for periods longer than 3 hours. Even within this period, the possibiity for large error exists due to wind direction shifts. These shifts could affect population areas totally different from those areas first indicated

  15. Wind power; Die Kraft der Winde

    Energy Technology Data Exchange (ETDEWEB)

    Mardo, Dietrich

    2009-10-30

    Wind power plants are probably only one pillar of the bridge that is taking us into an energy future still unimaginable to us. They are extremely cost-intensive and bulky and they spoil our landscapes. Their patronage by political leaders is understandable considering our excessive dependence on oil and gas. True energy autonomy is currently still a utopian dream for a country as poor in resources as Germany. On the other hand, to reach Utopia you have to build bridges there. Seen this way all currently available types of renewable energy represent bridge technologies whose realisation is imperative.

  16. Wind Power Today: (2002) Wind Energy Research Highlights

    Energy Technology Data Exchange (ETDEWEB)

    2003-05-01

    Wind Power Today is an annual publication that provides an overview of the wind research conducted under the U.S. Department of Energy's Wind and Hydropower Technologies Program. The purpose of Wind Power Today is to show how DOE supports wind turbine research and deployment in hopes of furthering the advancement of wind technologies that produce clean, low-cost, reliable energy. Content objectives include: educate readers about the advantages and potential for widespread deployment of wind energy; explain the program's objectives and goals; describe the program's accomplishments in research and application; examine the barriers to widespread deployment; describe the benefits of continued research and development; facilitate technology transfer; and attract cooperative wind energy projects with industry. This 2002 edition of Wind Power Today also includes discussions about wind industry growth in 2002, how DOE is taking advantage of low wind speed regions through advancing technology, and distributed applications for small wind turbines.

  17. Ensemble and probabilistic forecasting of (u,v)-wind for the energy application

    DEFF Research Database (Denmark)

    Pinson, Pierre

    2011-01-01

    and probabilistic forecasts are becoming increasingly popular among the actors of the power system and electricity markets. The energy application is particularly interesting since covering a variety of decision-making problems requiring different types of input forecasts. A few of them will be reviewed...... behaviour embedding variability and potentially limited predictability. This forces substantial changes to the energy management and trading activities, which are to increasingly rely on high-quality meteorological forecasts for various lead times ranging from a few minutes to a few months, while evolving...... of the ensembles and the wind stochastic process. The parameters of these models are adaptively and recursively estimated, hence allowing for seasonal variations in the calibration while accommodating changes in the operational setup of the ensemble forecasting system considered. These model parameters are also...

  18. Wind Power Utilization Guide.

    Science.gov (United States)

    1981-09-01

    Contact: Ken O’Brock North Benton, OH 44449 Telephone: 216-584-4681 Pacific Energy Systems North Wind 615 Romero Canyon Road Contact: Fred Carr Santa... Natal St ation. NMa~port 121.: CO(. rok Is NN. ode 4. 12 Mai e otrp’. Di’i Ireastire Is- San Francisco (CA: I i r Nlech Pt;rr 3𔄁\\\\(’ŗ Norlnolk N\\N. I

  19. 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.

  20. Solar and wind forecasting by NARX neural networks

    Directory of Open Access Journals (Sweden)

    Di Piazza Annalisa

    2016-01-01

    Full Text Available The nonlinear autoregressive network with exogenous input (NARX is used to perform hourly solar irradiation and wind speed forecasting, according to a multi-step ahead approach. Temperature has been considered as the exogenous variable. The NARX topology selection is supported by a combined use of two techniques: (1 a genetic algorithm (GA-based optimization technique and (2 a method that determines the optimal network architecture by pruning (optimal brain surgeon (OBS strategy. The considered variables are observed at hourly scale in a seven year dataset and the forecasting is done for several time horizons in the range from 8 to 24 h ahead.

  1. Equilibrium pricing in electricity markets with wind power

    Science.gov (United States)

    Rubin, Ofir David

    Estimates from the World Wind Energy Association assert that world total wind power installed capacity climbed from 18 Gigawatt (GW) to 152 GW from 2000 to 2009. Moreover, according to their predictions, by the end of 2010 global wind power capacity will reach 190 GW. Since electricity is a unique commodity, this remarkable expansion brings forward several key economic questions regarding the integration of significant amount of wind power capacity into deregulated electricity markets. The overall dissertation objective is to develop a comprehensive theoretical framework that enables the modeling of the performance and outcome of wind-integrated electricity markets. This is relevant because the state of knowledge of modeling electricity markets is insufficient for the purpose of wind power considerations. First, there is a need to decide about a consistent representation of deregulated electricity markets. Surprisingly, the related body of literature does not agree on the very economic basics of modeling electricity markets. That is important since we need to capture the fundamentals of electricity markets before we introduce wind power to our study. For example, the structure of the electric industry is a key. If market power is present, the integration of wind power has large consequences on welfare distribution. Since wind power uncertainty changes the dynamics of information it also impacts the ability to manipulate market prices. This is because the quantity supplied by wind energy is not a decision variable. Second, the intermittent spatial nature of wind over a geographical region is important because the market value of wind power capacity is derived from its statistical properties. Once integrated into the market, the distribution of wind will impact the price of electricity produced from conventional sources of energy. Third, although wind power forecasting has improved in recent years, at the time of trading short-term electricity forwards, forecasting

  2. Wind power costs expected to decrease due to technological progress

    International Nuclear Information System (INIS)

    Williams, Eric; Hittinger, Eric; Carvalho, Rexon; Williams, Ryan

    2017-01-01

    The potential for future cost reductions in wind power affects adoption and support policies. Prior analyses of cost reductions give inconsistent results. The learning rate, or fractional cost reduction per doubling of production, ranges from −3% to +33% depending on the study. This lack of consensus has, we believe, contributed to high variability in forecasts of future costs of wind power. We find that learning rate can be very sensitive to the starting and ending years of datasets and the geographical scope of the study. Based on a single factor experience curve that accounts for capacity factor gains, wind quality decline, and exogenous shifts in capital costs, we develop an improved model with reduced temporal variability. Using a global adoption model, the wind-learning rate is between 7.7% and 11%, with a preferred estimate of 9.8%. Using global scenarios for future wind deployment, this learning rate range implies that the cost of wind power will decline from 5.5 cents/kWh in 2015 to 4.1–4.5 cents/kWh in 2030, lower than a number of other forecasts. If attained, wind power may be the cheapest form of new electricity generation by 2030, suggesting that support and investment in wind should be maintained or expanded. - Highlights: • Expectations for cost reductions in wind power is important for policy. • Wind learning rates are sensitive to data time period and regional choice. • We develop improved wind cost model with much reduced variability. • New model gives global wind learning rates between 7.7%-11%.

  3. RTE: the integration of wind energy in the power system

    International Nuclear Information System (INIS)

    Glachant, Magali; Neau, Emmanuel

    2011-03-01

    The total installed capacity of wind power in France grew from a few hundred MW at the beginning of 2005 to 5500 MW at the end of 2010. This fast growth is set to continue, and the French Government's decision of 15 December 2009 on the country's long-term investment programs in power generation requires France to have at least 25 GW of installed wind capacity (including 6 GW offshore) by 2020. But the French specificities are that wind farms are largely spread over the territory, and 95 % of them have an output power below 12 MW which means they are mainly connected to the distribution network. As a consequence, this new intermittent and decentralized production is not 'naturally' observable by RTE, whereas it has nevertheless impacts on the operation of the transmission system for which RTE is responsible. The natural variability of wind power and the difficulty of its predictability require indeed a change in the traditional way of ensuring balancing between production and demand, of managing day-ahead margins and of controlling the electrical flows. Furthermore RTE operators have to be informed quickly and reliably of the real time output power of wind farms and of its evolvement some hours or days ahead to ensure the reliability of the French electrical power system. In this context, new tools were necessary to RTE to acquire as soon as possible data concerning wind power. In two years long, RTE set up an observatory of wind production called the 'IPES system'. 'IPES' enables to get information about technical characteristics of the whole wind farms in France and to observe the wind generation by two ways: in real time with tele-metered data and in the short term with a forecast model integrated into the system. In addition, RTE currently carries out studies about the behavior and the forecasting of wind production integrated into the grids, as internal activities (about forecast methods), and in different projects (such as European projects: Safewind for

  4. Wind turbine wakes; power deficit in clusters and wind farms

    DEFF Research Database (Denmark)

    Hansen, Kurt Schaldemose; Barthelmie, Rebecca

    2012-01-01

    The purpose of this presentation is to present recent power deficit analysis based on wind farm measurements. The power deficit is used to validate wind farm prediction models for different inflow conditions......The purpose of this presentation is to present recent power deficit analysis based on wind farm measurements. The power deficit is used to validate wind farm prediction models for different inflow conditions...

  5. System-wide emissions implications of increased wind power penetration.

    Science.gov (United States)

    Valentino, Lauren; Valenzuela, Viviana; Botterud, Audun; Zhou, Zhi; Conzelmann, Guenter

    2012-04-03

    This paper discusses the environmental effects of incorporating wind energy into the electric power system. We present a detailed emissions analysis based on comprehensive modeling of power system operations with unit commitment and economic dispatch for different wind penetration levels. First, by minimizing cost, the unit commitment model decides which thermal power plants will be utilized based on a wind power forecast, and then, the economic dispatch model dictates the level of production for each unit as a function of the realized wind power generation. Finally, knowing the power production from each power plant, the emissions are calculated. The emissions model incorporates the effects of both cycling and start-ups of thermal power plants in analyzing emissions from an electric power system with increasing levels of wind power. Our results for the power system in the state of Illinois show significant emissions effects from increased cycling and particularly start-ups of thermal power plants. However, we conclude that as the wind power penetration increases, pollutant emissions decrease overall due to the replacement of fossil fuels.

  6. Learning to forecast wind at remote sites for wind energy applications. Final report

    Energy Technology Data Exchange (ETDEWEB)

    Notis, C.; Trettel, D.W.; Aquino, J.T.; Piazza, T.R.; Taylor, L.E.; Trask, D.C.; Wegley, H.L.; Miller, A.H.

    1983-01-01

    Observed wind patterns are correlated with synoptic or mescoscale weather systems. Six sites selected for analysis include Montauk Point, New York; Boone, North Carolina; Ludington, Michigan; Clayton, New Mexico; Amarillo, Texas; and San Gorgonio Pass, California. Objectives of the analysis are: to identify synoptic and/or mesoscale weather patterns that are associated with recognizable wind events at the sites; to define a set of criteria that uniquely describes such weather patterns; to estimate the reliability (accuracy) of forecasting rules derived from the association of weather patterns and site winds; and to attempt to separate any mesoscale effects of local topography from the synoptic-scale effects. One-to-one mapping of wind regimes onto synoptic types was not found. It was concluded that four factors should be examined when stratifying wind regimes: synoptic situation, descriptive climatology, pressure gradient vector, and winds aloft. The wind forecasting approach developed was intended for forecasting hourly average winds out to the 24 hour or possibly 36 hour time horizon. (LEW)

  7. Forecasting and Diagnostic Analysis of Plume Transport around a Power Plant.

    Science.gov (United States)

    Souto, J. A.; Pérez-Muñuzuri, V.; Decastro, M.; Souto, M. J.; Casares, J. J.; Lucas, T.

    1998-10-01

    A nonreactive Lagrangian atmospheric diffusion model is used for the simulation of SO2 concentration around the As Pontes 1400-MW power plant located in northwestern Spain. This diffusion model has two kinds of input: 1) diagnostic wind fields from real measurements and 2) forecast wind fields from a 24-h mesoscale prediction.This model-based system is applied for a particular day around the As Pontes 1400-MW power plant, which is a coal-fired power plant. The shape of estimated and forecast plumes are compared, and the meteorological prediction results are analyzed.

  8. A fuzzy chance-constrained program for unit commitment problem considering demand response, electric vehicle and wind power

    DEFF Research Database (Denmark)

    Zhang, Ning; Hu, Zhaoguang; Han, Xue

    2015-01-01

    , they can serve as reserve for wind power. To deal with the unit commitment problem, authors use a fuzzy chance- constrained program that takes into account the wind power forecasting errors. The numerical study shows that the model can promote the utilization of wind power evidently, making the power...

  9. Dynamic influences of wind power on the power system

    Energy Technology Data Exchange (ETDEWEB)

    Rosas, Pedro

    2003-03-01

    The thesis first presents the basics influences of wind power on the power system stability and quality by pointing out the main power quality issues of wind power in a small-scale case and following, the expected large-scale problems are introduced. Secondly, a dynamic wind turbine model that supports power quality assessment of wind turbines is presented. Thirdly, an aggregate wind farm model that support power quality and stability analysis from large wind farms is presented. The aggregate wind farm model includes the smoothing of the relative power fluctuation from a wind farm compared to a single wind turbine. Finally, applications of the aggregate wind farm model to the power systems are presented. The power quality and stability characteristics influenced by large-scale wind power are illustrated with three cases. In this thesis, special emphasis has been given to appropriate models to represent the wind acting on wind farms. The wind speed model to a single wind turbine includes turbulence and tower shadow effects from the wind and the rotational sampling turbulence due to the rotation of the blades. In a park scale, the wind speed model to the wind farm includes the spatial coherence between different wind turbines. Here the wind speed model is applied to a constant rotational speed wind turbine/farm, but the model is suitable to variable speed wind turbine/farm as well. The cases presented here illustrate the influences of the wind power on the power system quality and stability. The flicker and frequency deviations are the main power quality parameters presented. The power system stability concentrates on the voltage stability and on the power system oscillations. From the cases studied, voltage and the frequency variations were smaller than expected from the large-scale wind power integration due to the low spatial correlation of the wind speed. The voltage quality analysed in a Brazilian power system and in the Nordel power system from connecting large

  10. Operation of Power Grids with High Penetration of Wind Power

    Science.gov (United States)

    Al-Awami, Ali Taleb

    The integration of wind power into the power grid poses many challenges due to its highly uncertain nature. This dissertation involves two main components related to the operation of power grids with high penetration of wind energy: wind-thermal stochastic dispatch and wind-thermal coordinated bidding in short-term electricity markets. In the first part, a stochastic dispatch (SD) algorithm is proposed that takes into account the stochastic nature of the wind power output. The uncertainty associated with wind power output given the forecast is characterized using conditional probability density functions (CPDF). Several functions are examined to characterize wind uncertainty including Beta, Weibull, Extreme Value, Generalized Extreme Value, and Mixed Gaussian distributions. The unique characteristics of the Mixed Gaussian distribution are then utilized to facilitate the speed of convergence of the SD algorithm. A case study is carried out to evaluate the effectiveness of the proposed algorithm. Then, the SD algorithm is extended to simultaneously optimize the system operating costs and emissions. A modified multi-objective particle swarm optimization algorithm is suggested to identify the Pareto-optimal solutions defined by the two conflicting objectives. A sensitivity analysis is carried out to study the effect of changing load level and imbalance cost factors on the Pareto front. In the second part of this dissertation, coordinated trading of wind and thermal energy is proposed to mitigate risks due to those uncertainties. The problem of wind-thermal coordinated trading is formulated as a mixed-integer stochastic linear program. The objective is to obtain the optimal tradeoff bidding strategy that maximizes the total expected profits while controlling trading risks. For risk control, a weighted term of the conditional value at risk (CVaR) is included in the objective function. The CVaR aims to maximize the expected profits of the least profitable scenarios, thus

  11. Exploiting sparsity of interconnections in spatio-temporal wind speed forecasting using Wavelet Transform

    International Nuclear Information System (INIS)

    Tascikaraoglu, Akin; Sanandaji, Borhan M.; Poolla, Kameshwar; Varaiya, Pravin

    2016-01-01

    Highlights: • We propose a spatio-temporal approach for wind speed forecasting. • The method is based on a combination of Wavelet decomposition and structured-sparse recovery. • Our analyses confirm that low-dimensional structures govern the interactions between stations. • Our method particularly shows improvements for profiles with high ramps. • We examine our approach on real data and illustrate its superiority over a set of benchmark models. - Abstract: Integration of renewable energy resources into the power grid is essential in achieving the envisioned sustainable energy future. Stochasticity and intermittency characteristics of renewable energies, however, present challenges for integrating these resources into the existing grid in a large scale. Reliable renewable energy integration is facilitated by accurate wind forecasts. In this paper, we propose a novel wind speed forecasting method which first utilizes Wavelet Transform (WT) for decomposition of the wind speed data into more stationary components and then uses a spatio-temporal model on each sub-series for incorporating both temporal and spatial information. The proposed spatio-temporal forecasting approach on each sub-series is based on the assumption that there usually exists an intrinsic low-dimensional structure between time series data in a collection of meteorological stations. Our approach is inspired by Compressive Sensing (CS) and structured-sparse recovery algorithms. Based on detailed case studies, we show that the proposed approach based on exploiting the sparsity of correlations between a large set of meteorological stations and decomposing time series for higher-accuracy forecasts considerably improve the short-term forecasts compared to the temporal and spatio-temporal benchmark methods.

  12. Validation of Model Forecasts of the Ambient Solar Wind

    Science.gov (United States)

    Macneice, P. J.; Hesse, M.; Kuznetsova, M. M.; Rastaetter, L.; Taktakishvili, A.

    2009-01-01

    Independent and automated validation is a vital step in the progression of models from the research community into operational forecasting use. In this paper we describe a program in development at the CCMC to provide just such a comprehensive validation for models of the ambient solar wind in the inner heliosphere. We have built upon previous efforts published in the community, sharpened their definitions, and completed a baseline study. We also provide first results from this program of the comparative performance of the MHD models available at the CCMC against that of the Wang-Sheeley-Arge (WSA) model. An important goal of this effort is to provide a consistent validation to all available models. Clearly exposing the relative strengths and weaknesses of the different models will enable forecasters to craft more reliable ensemble forecasting strategies. Models of the ambient solar wind are developing rapidly as a result of improvements in data supply, numerical techniques, and computing resources. It is anticipated that in the next five to ten years, the MHD based models will supplant semi-empirical potential based models such as the WSA model, as the best available forecast models. We anticipate that this validation effort will track this evolution and so assist policy makers in gauging the value of past and future investment in modeling support.

  13. Wind power in Arctic regions

    International Nuclear Information System (INIS)

    Lundsager, P.; Ahm, P.; Madsen, B.; Krogsgaard, P.

    1993-07-01

    Arctic or semi-arctic regions are often endowed with wind resources adequate for a viable production of electricity from the wind. Only limited efforts have so far been spent to introduce and to demonstrate the obvious synergy of combining wind power technology with the problems and needs of electricity generation in Arctic regions. Several factors have created a gap preventing the wind power technology carrying its full role in this context, including a certain lack of familiarity with the technology on the part of the end-users, the local utilities and communities, and a lack of commonly agreed techniques to adapt the same technology for Arctic applications on the part of the manufacturers. This report is part of a project that intends to contribute to bridging this gap. The preliminary results of a survey conducted by the project are included in this report, which is a working document for an international seminar held on June 3-4, 1993, at Risoe National Laboratory, Denmark. Following the seminar a final report will be published. It is intended that the final report will serve as a basis for a sustained, international effort to develop the wind power potential of the Arctic and semi-arctic regions. The project is carried out by a project group formed by Risoe, PA Energy and BTM Consult. The project is sponsored by the Danish Energy Agency of the Danish Ministry of Energy through grant no. ENS-51171/93-0008. (au)

  14. Wind power and bird kills

    International Nuclear Information System (INIS)

    Raynolds, M.

    1998-01-01

    The accidental killing of birds by wind generators, and design improvements in the towers that support the turbines that might cut down on the bird killings were discussed. The first problem for the industry began in the late 1980s when the California Energy Commission reported as many as 160 birds (the majority being raptors, including the protected golden eagle) killed in one year in the vicinity of wind power plants. The key factor identified was the design of the towers as birds of prey are attracted to lattice towers as a place to hunt from. Tubular towers do not provide a place for the birds to perch, therefore they reduce the potential for bird strikes. Bird strikes also have been reported in Spain and the siting of the towers have been considered as the principal cause of the bird strikes. In view of these incidents, the wind power industry is developing standards for studying the potential of bird strikes and is continuing to study bird behaviour leading to collisions, the impact of topography, cumulative impacts and new techniques to reduce bird strikes. Despite the reported incidents, the risk of bird strikes by wind turbines, compared to other threats to birds such as pollution, oil spills, and other threats from fossil and nuclear fuels, is considered to be negligible. With continuing efforts to minimize incidents by proper design and siting, wind power can continue to grow as an environmentally sound and efficient source of energy

  15. Short-Term Solar Collector Power Forecasting

    DEFF Research Database (Denmark)

    Bacher, Peder; Madsen, Henrik; Perers, Bengt

    2011-01-01

    This paper describes a new approach to online forecasting of power output from solar thermal collectors. The method is suited for online forecasting in many applications and in this paper it is applied to predict hourly values of power from a standard single glazed large area flat plate collector....... The method is applied for horizons of up to 42 hours. Solar heating systems naturally come with a hot water tank, which can be utilized for energy storage also for other energy sources. Thereby such systems can become an important part of energy systems with a large share of uncontrollable energy sources......-adaptive linear models. The approach is similar to the one by Bacher et al. (2009), but contains additional effects due to differences between solar thermal collectors and photovoltaics. Numerical weather predictions provided by Danish Meteorological Institute are used as input. The applied models adapt over time...

  16. Impact of advanced wind power ancillary services on power system

    DEFF Research Database (Denmark)

    Hansen, Anca Daniela; Altin, Müfit

    The objective of this report is to illustrate and analyse, by means of simulation test cases, the impact of wind power advanced ancillary services, like inertial response (IR), power oscillation damping (POD) and synchronising power (SP) on the power system. Generic models for wind turbine, wind...... power plant and power system are used in the investigation....

  17. Wind Power predictability a risk factor in the design, construction and operation of Wind Generation Turbines

    Science.gov (United States)

    Thiesen, J.; Gulstad, L.; Ristic, I.; Maric, T.

    2010-09-01

    Summit: The wind power predictability is often a forgotten decision and planning factor for most major wind parks, both onshore and offshore. The results of the predictability are presented after having examined a number of European offshore and offshore parks power predictability by using three(3) mesoscale model IRIE_GFS and IRIE_EC and WRF. Full description: It is well known that the potential wind production is changing with latitude and complexity in terrain, but how big are the changes in the predictability and the economic impacts on a project? The concept of meteorological predictability has hitherto to some degree been neglected as a risk factor in the design, construction and operation of wind power plants. Wind power plants are generally built in places where the wind resources are high, but these are often also sites where the predictability of the wind and other weather parameters is comparatively low. This presentation addresses the question of whether higher predictability can outweigh lower average wind speeds with regard to the overall economy of a wind power project. Low predictability also tends to reduce the value of the energy produced. If it is difficult to forecast the wind on a site, it will also be difficult to predict the power production. This, in turn, leads to increased balance costs and a less reduced carbon emission from the renewable source. By investigating the output from three(3) mesoscale models IRIE and WRF, using ECMWF and GFS as boundary data over a forecasting period of 3 months for 25 offshore and onshore wind parks in Europe, the predictability are mapped. Three operational mesoscale models with two different boundary data have been chosen in order to eliminate the uncertainty with one mesoscale model. All mesoscale models are running in a 10 km horizontal resolution. The model output are converted into "day a head" wind turbine generation forecasts by using a well proven advanced physical wind power model. The power models

  18. Modelling of hydro and wind power in the regulation market

    International Nuclear Information System (INIS)

    Kiviluoma, J.; Holttinen, H.; Meibom, P.

    2006-01-01

    The amount of required regulation capacity in the power system is affected by the wind power prediction errors. A model has been developed which can evaluate the monetary effects of prediction errors. The model can be used to evaluate (1) the regulation costs of wind power, (2) regulation market prices including effects related to the participation of power producers in the regulating power market, (3) value of accurate wind forecasts and (4) the effect of decreasing the length of the spot market clearance. This article discusses the problems related to developing a realistic model of the regulating power market including the interaction between the spot market and the regulating power market. There are several issues that make things complicated. (1) How to calculate the minimum amount of needed secondary (minute) reserves. Traditionally the Nordic TSOs have used an N-1 criteria in each country to determine the required amounts of positive secondary reserve, but as installed wind power capacity grows, it will become relevant to include the wind power prediction errors in the estimation of secondary reserves. (2) Consumption forecast errors and plant outages also contribute to activation of regulating power and should have stochastic input series besides wind power. (3) Risk premiums and transaction costs in the regulating power market are difficult to estimate as well as the effects of the possible use of market power. This is especially true in the Nordic system with the high share of hydro power, since the water value and hydrological limitations make things more complex than in a thermal system. (4) The available regulation capacity is not necessarily equal to the truly available capacity. All producers don't participate in the regulation market although in principle they could. (orig.)

  19. Wind for Schools: A Wind Powering America Project

    Science.gov (United States)

    US Department of Energy, 2007

    2007-01-01

    The U.S. Department of Energy's (DOE's) Wind Powering America program (based at the National Renewable Energy Laboratory) sponsors the Wind for Schools Project to raise awareness in rural America about the benefits of wind energy while simultaneously educating college seniors regarding wind energy applications. The three primary project goals of…

  20. Wind Turbine Power Curves Incorporating Turbulence Intensity

    DEFF Research Database (Denmark)

    Sørensen, Emil Hedevang Lohse

    2014-01-01

    The performance of a wind turbine in terms of power production (the power curve) is important to the wind energy industry. The current IEC-61400-12-1 standard for power curve evaluation recognizes only the mean wind speed at hub height and the air density as relevant to the power production...

  1. Improving wind power quality with energy storage

    OpenAIRE

    Rasmussen, Claus Nygaard

    2009-01-01

    The results of simulation of the influence of energy storage on wind power quality are presented. Simulations are done using a mathematical model of energy storage. Results show the relation between storage power and energy, and the obtained increase in minimum available power from the combination of wind and storage. The introduction of storage enables smoothening of wind power on a timescale proportional to the storage energy. Storage does not provide availability of wind power at all times...

  2. International wind energy development. World market update 2012. Forecast 2013-2017

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2013-03-15

    The BTM wind report, World Market Update 2012, published by Navigant Research, is the eighteenth edition of this annual wind energy market report. The report includes more than 80 tables, charts and graphs illustrating global wind market development, as well as a wind market forecast for 2013?2017 and highlighted trends for the wind market through 2022. The report delivers several views on the fast?growing wind market, including: 1) More than 285 GW of wind power now installed globally; 2) 45GW of new capacity added in 2012, including 1.1 GW from offshore wind; 3) The United States surpassed China as the largest market in terms of new installations in 2012; 4) Europe lost its position as the largest world region in terms of new installations; 5) Wind installations in the Americas grew by 12.3 percent compared with 2011; 6) Big shake?up in the top ten wind turbine supplier ranking; 7) Strong Chinese presence among top 15 wind owner?operators; 8) Wind market structures continue to evolve; 9) The penetration of wind power in the world's electricity supply has reached 2.62 percent; 10) Offshore wind more than doubled the capacity added in 2011, with more than 4 GW currently under construction. With the addition of 44,951 MW in new installations in 2012, world wind power capacity grew to around 285,700 MW, an increase in the total wind power installation base of 18.6 percent. Market growth year-over-year in 2012, though a modest 7.8 percent, was still higher than in 2011. Average annual growth for the past five years has been 17.8 percent, achieved during the aftermath of the 2008 financial crisis, with traditionally large markets for wind power in economic recession in America and Europe. The wind power industry continues to demonstrate its ability to rapidly evolve to meet new demands in markets that face a variety of challenges. The focus on product diversification grows with wind turbine vendors designing machines for maximum energy production in low wind speed

  3. Voluntary Green Power Market Forecast through 2015

    Energy Technology Data Exchange (ETDEWEB)

    Bird, L.; Holt, E.; Sumner, J.; Kreycik, C.

    2010-05-01

    Various factors influence the development of the voluntary 'green' power market--the market in which consumers purchase or produce power from non-polluting, renewable energy sources. These factors include climate policies, renewable portfolio standards (RPS), renewable energy prices, consumers' interest in purchasing green power, and utilities' interest in promoting existing programs and in offering new green options. This report presents estimates of voluntary market demand for green power through 2015 that were made using historical data and three scenarios: low-growth, high-growth, and negative-policy impacts. The resulting forecast projects the total voluntary demand for renewable energy in 2015 to range from 63 million MWh annually in the low case scenario to 157 million MWh annually in the high case scenario, representing an approximately 2.5-fold difference. The negative-policy impacts scenario reflects a market size of 24 million MWh. Several key uncertainties affect the results of this forecast, including uncertainties related to growth assumptions, the impacts that policy may have on the market, the price and competitiveness of renewable generation, and the level of interest that utilities have in offering and promoting green power products.

  4. Offshore Wind Power Planning in Korea

    DEFF Research Database (Denmark)

    Seo, Chul Soo; Cha, Seung-Tae; Park, Sang Ho

    2012-01-01

    Wind power generation is globally recognized as the most universal and reliable form of renewable energy. Korea is currently depending mostly on coal and petroleum to generate electrical power and is now trying to replace them with renewable energy such as offshore wind power generation. To make...... that connecting offshore wind power generation to a power system has on the power system. This paper looks over offshore wind power planning in Korea and describes the development of impact assessment technology of offshore wind farms....

  5. Nordic wind power conference 2007. Proceedings

    International Nuclear Information System (INIS)

    Cutululis, Nicolaos; Soerensen, Poul

    2007-11-01

    This fourth Nordic Wind Power Conference was focused on power system integration and electrical systems of wind turbines and wind farms. NWPC presents the newest research results related to technical electrical aspects of wind power, spanning from power system integration to electrical design and control of wind turbines. The first NWPC was held in Trondheim (2000), Norway, the second in Gothenburg (2004), Sweden, and the third in Espoo (2006), Finland. Invited speakers, oral presentation of papers and poster sessions ensured this to be a valuable event for professionals and high-level students wanting to strengthen their knowledge on wind power integration and electrical systems. (au)

  6. Nordic wind power conference 2007. Proceedings

    Energy Technology Data Exchange (ETDEWEB)

    Cutululis, N.; Soerensen, P. (eds.)

    2007-11-15

    This fourth Nordic Wind Power Conference was focused on power system integration and electrical systems of wind turbines and wind farms. NWPC presents the newest research results related to technical electrical aspects of wind power, spanning from power system integration to electrical design and control of wind turbines. The first NWPC was held in Trondheim (2000), Norway, the second in Gothenburg (2004), Sweden, and the third in Espoo (2006), Finland. Invited speakers, oral presentation of papers and poster sessions ensured this to be a valuable event for professionals and high-level students wanting to strengthen their knowledge on wind power integration and electrical systems. (au)

  7. Stochastic Optimal Wind Power Bidding Strategy in Short-Term Electricity Market

    DEFF Research Database (Denmark)

    Hu, Weihao; Chen, Zhe; Bak-Jensen, Birgitte

    2012-01-01

    minimization problem for trading wind power in the short-term electricity market is described, to help the wind power owners optimize their bidding strategy. Stochastic optimization and a Monte Carlo method are adopted to find the optimal bidding strategy for trading wind power in the short-term electricity...... market in order to deal with the uncertainty of the regulation price, the activated regulation of the power system and the forecasted wind power generation. The Danish short-term electricity market and a wind farm in western Denmark are chosen as study cases due to the high wind power penetration here....... Simulation results show that the stochastic optimal bidding strategy for trading wind power in the Danish short-term electricity market is an effective measure to maximize the revenue of the wind power owners....

  8. Research Developments on Power System Integration of Wind Power

    DEFF Research Database (Denmark)

    Chen, Zhe; Hansen, Jens Carsten; Qiuwei, Wu

    2011-01-01

    This paper presents an overview on the recent research activities and tendencies regarding grid integration of wind power in Denmark and some related European activities, including power electronics for enhancing wind power controllability, wind turbines and wind farms modeling,wind power...... variability and prediction, wind power plant ancillary services, grid connection and operation, Smart grids and demand side management under market functionality. The topics of the first group of PhD program starting 2011 under the wind energy Sino-Danish Centre for Education & Research (SDC) are also...

  9. Research Developments on Power System Integration of Wind Power

    DEFF Research Database (Denmark)

    Chen, Zhe; Hansen, Jens Carsten; Wu, Qiuwei

    2011-01-01

    This paper presents an overview on the recent research activities and tendencies regarding grid integration of wind power in Denmark and some related European activities, including power electronics for enhancing wind power controllability, wind turbines and wind farms modeling, wind power...... variability and prediction, wind power plant ancillary services, grid connection and operation, Smart grids and demand side management under market functionality. The topics of the first group of PhD program starting 2011 under the wind energy Sino-Danish Centre for Education & Research (SDC) are also...

  10. Utilizing Climate Forecasts for Improving Water and Power Systems Coordination

    Science.gov (United States)

    Arumugam, S.; Queiroz, A.; Patskoski, J.; Mahinthakumar, K.; DeCarolis, J.

    2016-12-01

    Climate forecasts, typically monthly-to-seasonal precipitation forecasts, are commonly used to develop streamflow forecasts for improving reservoir management. Irrespective of their high skill in forecasting, temperature forecasts in developing power demand forecasts are not often considered along with streamflow forecasts for improving water and power systems coordination. In this study, we consider a prototype system to analyze the utility of climate forecasts, both precipitation and temperature, for improving water and power systems coordination. The prototype system, a unit-commitment model that schedules power generation from various sources, is considered and its performance is compared with an energy system model having an equivalent reservoir representation. Different skill sets of streamflow forecasts and power demand forecasts are forced on both water and power systems representations for understanding the level of model complexity required for utilizing monthly-to-seasonal climate forecasts to improve coordination between these two systems. The analyses also identify various decision-making strategies - forward purchasing of fuel stocks, scheduled maintenance of various power systems and tradeoff on water appropriation between hydropower and other uses - in the context of various water and power systems configurations. Potential application of such analyses for integrating large power systems with multiple river basins is also discussed.

  11. Uses and applications of climate forecasts for power utilities

    Energy Technology Data Exchange (ETDEWEB)

    Changnon, S.A.; Changnon, J.M.; Changnon, D. [Changnon Climatologist, Mahomet, IL (United States)

    1995-05-01

    The uses and potential applications of climate forecasts for electric and gas utilities were assessed: (1) to discern needs for improving climate forecasts and guiding future research, and (2) to assist utilities in making wise use of forecasts. In-depth structured interviews were conducted with 56 decision makers in six utilities to assess existing and potential uses of climate forecasts. Only 3 of the 56 use forecasts. Eighty percent of those sampled envisioned applications of climate forecasts, given certain changes and additional information. Primary applications exist in power trading, load forecasting, fuel acquisition, and systems planning, with slight differences in interests between utilities. Utility staff understand probability-based forecasts but desire climatological information related to forecasted outcomes, including analogs similar to the forecasts, and explanations of the forecasts. Desired lead times vary from a week to three months, along with forecasts of up to four seasons ahead. The new NOAA forecasts initiated in 1995 provide the lead times and longer-term forecasts desired. Major hindrances to use of forecasts are hard-to-understand formats, lack of corporate acceptance, and lack of access to expertise. Recent changes in government regulations altered the utility industry, leading to a more competitive world wherein information about future weather conditions assumes much more value. Outreach efforts by government forecast agencies appear valuable to help achieve the appropriate and enhanced use of climate forecasts by the utility industry. An opportunity for service exists also for the private weather sector. 17 refs., 1 fig., 9 tabs.

  12. Forecasting wind-driven wildfires using an inverse modelling approach

    Directory of Open Access Journals (Sweden)

    O. Rios

    2014-06-01

    Full Text Available A technology able to rapidly forecast wildfire dynamics would lead to a paradigm shift in the response to emergencies, providing the Fire Service with essential information about the ongoing fire. This paper presents and explores a novel methodology to forecast wildfire dynamics in wind-driven conditions, using real-time data assimilation and inverse modelling. The forecasting algorithm combines Rothermel's rate of spread theory with a perimeter expansion model based on Huygens principle and solves the optimisation problem with a tangent linear approach and forward automatic differentiation. Its potential is investigated using synthetic data and evaluated in different wildfire scenarios. The results show the capacity of the method to quickly predict the location of the fire front with a positive lead time (ahead of the event in the order of 10 min for a spatial scale of 100 m. The greatest strengths of our method are lightness, speed and flexibility. We specifically tailor the forecast to be efficient and computationally cheap so it can be used in mobile systems for field deployment and operativeness. Thus, we put emphasis on producing a positive lead time and the means to maximise it.

  13. PSS Controller for Wind Power Generation Systems

    Science.gov (United States)

    Domínguez-García, J. L.; Gomis-Bellmunt, O.; Bianchi, F.; Sumper, A.

    2012-10-01

    Small signal stability analysis for power systems with wind farm interaction is presented. Power systems oscillation modes can be excited by disturbance or fault in the grid. Variable speed wind turbines can be regulated to reduce these oscillations, stabilising the power system. A power system stabiliser (PSS) control loop for wind power is designed in order to increase the damping of the oscillation modes. The proposed power system stabiliser controller is evaluated by small signal analysis.

  14. Wind power today: 1999 Wind Energy program highlights

    Energy Technology Data Exchange (ETDEWEB)

    Weis-Taylor, Pat

    2000-04-06

    Wind Power Today is an annual publication that provides an overview for the Department of Energy's Wind Energy Program. The purpose of Wind Power Today is to show how DOE's Wind Energy Program supports wind turbine research and deployment in hopes of furthering the advancement of wind technologies that produce clean, low-cost, reliable energy for the 21st century. Content objectives include: Educate readers about the advantages and potential for widespread deployment of wind energy; explain DOE wind energy program objectives and goals; describe program accomplishments in research and application; examine the barriers to widespread deployment; describe benefits of continued research and development; facilitate technology transfer; attract cooperative wind energy projects with industry.

  15. Power Electronics Converters for Wind Turbine Systems

    DEFF Research Database (Denmark)

    Blaabjerg, Frede; Liserre, Marco; Ma, Ke

    2012-01-01

    The steady growth of installed wind power together with the upscaling of the single wind turbine power capability has pushed the research and development of power converters toward full-scale power conversion, lowered cost pr kW, increased power density, and also the need for higher reliability......, in the latter case with attention to series connection and parallel connection either electrical or magnetic ones (multiphase/windings machines/transformers). It is concluded that as the power level increases in wind turbines, medium-voltage power converters will be a dominant power converter configuration...

  16. Economic Operation of Power Systems with Significant Wind Power Penetration

    DEFF Research Database (Denmark)

    Farashbashi-Astaneh, Seyed-Mostafa

    This dissertation addresses economic operation of power systems with high penetration of wind power. Several studies are presented to address the economic operation of power systems with high penetration of variable wind power. The main concern in such power systems is high variability...... and unpredictability. Unlike conventional power plants, the output power of a wind farm is not controllable. This brings additional complexity to operation and planning of wind dominant power systems. The key solution in face of wind power uncertainty is to enhance power system flexibility. The enhanced flexibility......, cooperative wind-storage operation is studied. Lithium-Ion battery units are chosen as storage units. A novel formulation is proposed to investigate optimal operation of a storage unit considering power system balancing conditions and wind power imbalances. An optimization framework is presented to increase...

  17. DEWEPS - Development and Evaluation of new Wind forecasting tools with an Ensemble Prediction System

    Energy Technology Data Exchange (ETDEWEB)

    Moehrlen, C.; Joergensen, Jess

    2012-02-15

    There is an ongoing trend of increased privatization in the handling of renewable energy. This trend is required to ensure an efficient energy system, where improvements that make economic sense are prioritised. The reason why centralized forecasting can be a challenge in that matter is that the TSOs tend to optimize on physical error rather than cost. Consequently, the market is likely to speculate against the TSO, which in turn increases the cost of balancing. A privatized pool of wind and/or solar power is more difficult to speculate against, because the optimization criteria is unpredictable due to subjective risk considerations that may be taken into account at any time. Although there is and additional level of costs for the trading of the private volume, it can be argued that competition will accelerate efficiency from an economic perspective. The amount of power put into the market will become less predictable, when the wind power spot market bid takes place on the basis of a risk consideration in addition to the forecast information itself. The scope of this project is to contribute to more efficient wind power integration targeted both to centralised and decentralised cost efficient IT solutions, which will complement each other in market based energy systems. The DEWEPS project resulted in an extension of the number of Ensemble forecasts, an incremental trade strategy for balancing unpredictable power production, and an IT platform for efficient handling of power generation units. Together, these three elements contribute to less need for reserves, more capacity in the market, and thus more competition. (LN)

  18. Quantifying Uncertainty of Wind Power Production Through an Analog Ensemble

    Science.gov (United States)

    Shahriari, M.; Cervone, G.

    2016-12-01

    The Analog Ensemble (AnEn) method is used to generate probabilistic weather forecasts that quantify the uncertainty in power estimates at hypothetical wind farm locations. The data are from the NREL Eastern Wind Dataset that includes more than 1,300 modeled wind farms. The AnEn model uses a two-dimensional grid to estimate the probability distribution of wind speed (the predictand) given the values of predictor variables such as temperature, pressure, geopotential height, U-component and V-component of wind. The meteorological data is taken from the NCEP GFS which is available on a 0.25 degree grid resolution. The methodology first divides the data into two classes: training period and verification period. The AnEn selects a point in the verification period and searches for the best matching estimates (analogs) in the training period. The predictand value at those analogs are the ensemble prediction for the point in the verification period. The model provides a grid of wind speed values and the uncertainty (probability index) associated with each estimate. Each wind farm is associated with a probability index which quantifies the degree of difficulty to estimate wind power. Further, the uncertainty in estimation is related to other factors such as topography, land cover and wind resources. This is achieved by using a GIS system to compute the correlation between the probability index and geographical characteristics. This study has significant applications for investors in renewable energy sector especially wind farm developers. Lower level of uncertainty facilitates the process of submitting bids into day ahead and real time electricity markets. Thus, building wind farms in regions with lower levels of uncertainty will reduce the real-time operational risks and create a hedge against volatile real-time prices. Further, the links between wind estimate uncertainty and factors such as topography and wind resources, provide wind farm developers with valuable

  19. 8th international workshop on large-scale integration of wind power into power systems as well as on transmission networks for offshore wind farms. Proceedings

    International Nuclear Information System (INIS)

    Betancourt, Uta; Ackermann, Thomas

    2009-01-01

    Within the 8th International Workshop on Large-Scale Integration of Wind Power into Power Systems as well as on Transmission Networks for Offshore Wind Farms at 14th to 15th October, 2009 in Bremen (Federal Republic of Germany), lectures and posters were presented to the following sessions: (1) Keynote session and panel; (2) Grid integration studies and experience: Europe; (3) Connection of offshore wind farms; (4) Wind forecast; (5) High voltage direct current (HVDC); (6) German grid code issues; (7) Offshore grid connection; (8) Grid integration studies and experience: North America; (9) SUPWIND - Decision support tools for large scale integration of wind; (10) Windgrid - Wind on the grid: An integrated approach; (11) IEA Task 25; (12) Grid code issues; (13) Market Issues; (14) Offshore Grid; (15) Modelling; (16) Wind power and storage; (17) Power system balancing; (18) Wind turbine performance; (19) Modelling and offshore transformer.

  20. Recursive wind speed forecasting based on Hammerstein Auto-Regressive model

    International Nuclear Information System (INIS)

    Ait Maatallah, Othman; Achuthan, Ajit; Janoyan, Kerop; Marzocca, Pier

    2015-01-01

    Highlights: • Developed a new recursive WSF model for 1–24 h horizon based on Hammerstein model. • Nonlinear HAR model successfully captured chaotic dynamics of wind speed time series. • Recursive WSF intrinsic error accumulation corrected by applying rotation. • Model verified for real wind speed data from two sites with different characteristics. • HAR model outperformed both ARIMA and ANN models in terms of accuracy of prediction. - Abstract: A new Wind Speed Forecasting (WSF) model, suitable for a short term 1–24 h forecast horizon, is developed by adapting Hammerstein model to an Autoregressive approach. The model is applied to real data collected for a period of three years (2004–2006) from two different sites. The performance of HAR model is evaluated by comparing its prediction with the classical Autoregressive Integrated Moving Average (ARIMA) model and a multi-layer perceptron Artificial Neural Network (ANN). Results show that the HAR model outperforms both the ARIMA model and ANN model in terms of root mean square error (RMSE), mean absolute error (MAE), and Mean Absolute Percentage Error (MAPE). When compared to the conventional models, the new HAR model can better capture various wind speed characteristics, including asymmetric (non-gaussian) wind speed distribution, non-stationary time series profile, and the chaotic dynamics. The new model is beneficial for various applications in the renewable energy area, particularly for power scheduling

  1. POSSPOW: Possible Power of Offshore Wind Power Plants

    DEFF Research Database (Denmark)

    Giebel, Gregor; Göçmen, Tuhfe; Sørensen, Poul Ejnar

    2013-01-01

    will be verified on some of the large offshore wind farms owned by Vattenfall, and possibly in a DONG Energy wind farm too. Dedicated experiments to the wind flow in large offshore wind farms are planned. Main body of abstract Modern wind turbines have a SCADA signal called possible power. In normal operation...

  2. Harnessing wind power with sustained policy support

    Energy Technology Data Exchange (ETDEWEB)

    Meera, L. [BITS-Pilani. Dept. of Economics, Hyderabad (India)

    2012-07-01

    The development of wind power in India began in the 1990s, and has significantly increased in the last few years. The ''Indian Wind Turbine Manufacturers Association (IWTMA)'' has played a leading role in promoting wind energy in India. Although a relative newcomer to the wind industry compared with Denmark or the US, a combination of domestic policy support for wind power and the rise of Suzlon (a leading global wind turbine manufacturer) have led India to become the country with the fifth largest installed wind power capacity in the world. Wind power accounts for 6% of India's total installed power capacity, and it generates 1.6% of the country's power. (Author)

  3. Wind Tunnel Measurements at LM Wind Power

    DEFF Research Database (Denmark)

    Bertagnolio, Franck

    2012-01-01

    The optimization of airfoil profiles specifically designed for wind turbine application was initiated in the late 80’s [67, 68, 30, 15]. The first attempts to reduce airfoil noise for wind turbines made use of airfoil trailing edge serration. Themodification of airfoil shapes targeted at noise...... reduction is more recent. An important effort was produced in this direction within the SIROCCO project. This latter work involved measurements on full size wind turbines and showed that trailing edge serration may proved a viable solution for mitigating wind turbine noise though it has not been implemented...... on commercial wind turbine yet. It should be mentioned here that the attenuation of turbulent inflow noise using wavy leading edge has recently been investigated [55], but this technique has still to be further validated for practical applications. In this paper, it is proposed to optimize an airfoil which...

  4. International wind energy development. World market update 1998. Forecast 1999-2003

    International Nuclear Information System (INIS)

    1999-03-01

    This is the fourth issue of the annual World Market Update from BTM Consult ApS, covering the year 1998. All figures in the status part refer to end of the year 1998, the past 3 years development is also assessed and the forecast looks 5 years ahead. The most significant figures and trends in 1998 were: The marketplace - The annual installation of new wind power capacity increased by 55% resulting in a cumulative installation by the end of 1998 of 10.153 MW. 1.766 MW was installed in Europe and the region is still the leading market regarding utilization of wind energy. The US market took a rapid pace and installed 577 MW during the year. The large Enron Wind Corp has taken the larger part of this market. On the supply side Danish NEG Micon A/S has consolidated the position as being the supplier of the most MW wind capacity in the world and the company has a world market share of 23,5 per cent. The company acquired the Danish Wind World af 1997 A/S which was among the larger companies in 1997. Also the Dutch manufacturer NedWind B.V. was acquired by NEG Micon A/S curing 1998. The group of 'other' manufactureres represents a minor percentage of deliveries than earlier and concentration in the industry seems to continue. The liberalized Energy Market and how to position the industry in this different economic environment will be a challenge for the wind industry way into the next century. In Europe, the European Commission's draft Directive with proposal for an outline of common rules for support of among other renewables wind energy has been set on another route which seems to delay the paper. In the US there are still hopes for a new period with PTC (Production Tax Credit). There are in some States hopes among the wind energy people that the 'Green Market Programs' will play a more dominant role in the future. In Asia the crises seems to halt the wind power development. Forecast and Technical trends - Based on the positive trends in the markets for wind power

  5. Wind power development and policies in China

    International Nuclear Information System (INIS)

    Liao, Cuiping; Farid, Nida R.; Jochem, Eberhard; Zhang, Yi

    2010-01-01

    The People's Republic of China foresees a target of 30 GW for installed wind power capacity by 2010 (2008: 12 GW). This paper reports on the technical and economic potentials of wind power, the recent development, existing obstacles, and related policies in China. The barriers to further commercialization of the wind power market are important and may deter the 100 GW capacity target of the Chinese government by 2020. The paper concludes that the diffusion of wind power in China is an important element for not only reducing global greenhouse gas emissions, but also for worldwide progress of wind power technology and needed economies of scale. (author)

  6. Sources of the wind power stations

    International Nuclear Information System (INIS)

    Chudivani, J.; Huettner, L.

    2012-01-01

    The paper deals with problems of the wind power stations. Describes the basic properties of wind energy. Shows and describes the different types of electrical machines used as a source of electricity in the wind power stations. Shows magnetic fields synchronous generator with salient poles and permanent magnets in the program FEMM. Describes methods for assessing of reversing the effects of the wind power stations on the distribution network. (Authors)

  7. Blowing in the Wind: A Review of Wind Power Technology

    Science.gov (United States)

    Harris, Frank

    2014-01-01

    The use of wind as a replenishable energy resource has come back into favour in recent decades. It is much promoted as a viable, clean energy option that will help towards reducing CO[subscript 2] emissions in the UK. This article examines the history of wind power and considers the development of wind turbines, together with their economic,…

  8. Confidence intervals for annual wind power production******

    Directory of Open Access Journals (Sweden)

    Bensoussan Alain

    2014-01-01

    Full Text Available Wind power is an intermittent resource due to wind speed intermittency. However wind speed can be described as a stochastic process with short memory. This allows us to derive a central limit theorem for the annual or pluri-annual wind power production and then get quantiles of the wind power production for one, ten or twenty years future periods. On the one hand, the interquantile spread offers a measurement of the intrinsic uncertainties of wind power production. On the other hand, different quantiles with different periods of time are used by financial institutions to quantify the financial risk of the wind turbine. Our method is then applied to real datasets corresponding to a French wind turbine. Since confidence intervals can be enhanced by taking into account seasonality, we present some tools for change point analysis on wind series.

  9. Endurance Wind Power : practical insights into small wind

    International Nuclear Information System (INIS)

    Hicks, D.

    2008-01-01

    This presentation discussed practical issues related to purchasing and installing small wind turbines in Canada. Wind power capacity can be estimated by looking at provincial wind maps as well as by seeking wind data at local airports. Wind resources are typically measured at heights of between 20 meters and 50 m. The height of a wind turbine tower can significantly increase the turbine's wind generating capacity. Turbine rotors should always be placed 30 feet higher than obstacles within 500 feet. Many provinces have now mandated utilities to accept renewable energy resources from grid-connected wind energy plants. Net billing systems are used to determine the billing relationship between power-producing consumers and the utilities who will buy the excess power and sell it to other consumers. Utilities are not yet mandated to purchase excess power, and it is likely that federal and provincial legislation will be needed to ensure that net billing systems continue to grow. Many Canadian municipalities have no ordinances related to wind turbine placements. Consumers interested in purchasing small wind turbines should ensure that the turbine has been certified by an accredited test facility and has an adequate safety system. The noise of the turbine as well as its power performance in relation to the purchaser's needs must also be considered. It was concluded that small wind turbines can provide a means for electricity consumers to reduce their carbon footprint and hedge against the inflationary costs of fossil-fuelled energy resources. tabs., figs

  10. Wind Power Today: 2000 Wind Energy Program Highlights

    Energy Technology Data Exchange (ETDEWEB)

    Weis-Taylor, W.

    2001-05-08

    Wind Power Today is an annual publication that provides an overview of the U.S. Department of Energy's Wind Energy Program. The purpose of Wind Power Today is to show how DOE's Wind Energy Program supports wind turbine research and deployment in hopes of furthering the advancement of wind technologies that produce clean, low-cost, reliable energy. Content objectives include: educate readers about the advantages and potential for widespread deployment of wind energy; explain the program's objectives and goals; describe the program's accomplishments in research and application; examine the barriers to widespread deployment; describe the benefits of continued research and development; facilitate technology transfer; and attract cooperative wind energy projects with industry.

  11. Footprints in the wind? Environmental impacts of wind power development

    Energy Technology Data Exchange (ETDEWEB)

    Magoha, P. [Jomo Kenyatta University of Agriculture and Technology, Nairobi (Cayman Islands). Dept. of Mechanical Engineering

    2002-10-01

    This paper reviews the environmental impacts of wind power development and examines noise generated by wind turbines, noise control methods, visual impacts and visibility, and the impact on wildlife and natural habitat. Details are given of other impacts such as electromagnetic interference and the disposal of materials used in the manufacture of parts of wind energy converters. Political issues and social costs of wind energy are considered.

  12. Dynamic Frequency Response of Wind Power Plants

    DEFF Research Database (Denmark)

    Altin, Müfit

    to maintain sustainable and reliable operation of the power system for these targets, transmission system operators (TSOs) have revised the grid code requirements. Also, the TSOs are planning the future development of the power system with various wind penetration scenarios to integrate more wind power...... according to their grid codes. In these scenarios particularly with high wind power penetration cases, conventional power plants (CPPs) such as old thermal power plants are planned to be replaced with wind power plants (WPPs). Consequently, the power system stability will be affected and the control...... capability of WPPs would be investigated. The objective of this project is to analyze and identify the power system requirements for the synchronizing power support and inertial response control of WPPs in high wind power penetration scenarios. The dynamic frequency response of WPPs is realized...

  13. Global wind power development: Economics and policies

    International Nuclear Information System (INIS)

    Timilsina, Govinda R.; Cornelis van Kooten, G.; Narbel, Patrick A.

    2013-01-01

    Existing literature indicates that theoretically, the earth's wind energy supply potential significantly exceeds global energy demand. Yet, only 2–3% of global electricity demand is currently derived from wind power despite 27% annual growth in wind generating capacity over the last 17 years. More than 95% of total current wind power capacity is installed in the developed countries plus China and India. Our analysis shows that the economic competitiveness of wind power varies at wider range across countries or locations. A climate change damage cost of US$20/tCO 2 imposed to fossil fuels would make onshore wind competitive to all fossil fuels for power generation; however, the same would not happen to offshore wind, with few exceptions, even if the damage cost is increased to US$100/tCO 2 . To overcome a large number of technical, financial, institutional, market and other barriers to wind power, many countries have employed various policy instruments, including capital subsidies, tax incentives, tradable energy certificates, feed-in tariffs, grid access guarantees and mandatory standards. Besides, climate change mitigation policies, such as the Clean Development Mechanism, have played a pivotal role in promoting wind power. Despite these policies, intermittency, the main technical constraint, could remain as the major challenge to the future growth of wind power. - Highlights: • Global wind energy potential is enormous, yet the wind energy contribution is very small. • Existing policies are boosting development of wind power. • Costs of wind energy are higher than cost of fossil-based energies. • Reasonable premiums for climate change mitigation substantially promote wind power. • Intermittency is the key challenge to future development of wind power

  14. FACTS Devices for Large Wind Power Plants

    DEFF Research Database (Denmark)

    Adamczyk, Andrzej Grzegorz; Teodorescu, Remus; Rodriguez, Pedro

    2010-01-01

    Growing number of wind turbines is changing electricity generation profile all over the world. However, high wind energy penetration affects power system safety and stability. For this reason transmission system operators (TSO) impose more stringent connection requirements on the wind power plant...

  15. International wind energy development. World market update 2002. Forecast 2003-2007

    International Nuclear Information System (INIS)

    2003-03-01

    This report highlights the development of the international wind power market during 2002 and the new forecast up to 2007. The data presented includes both supply side and demand side information. With 7,227 MW of new installations the total installed capacity of wind power grew to over 32,000 MW. This is the highest figure ever in a single year. The growth rate of 6% over 2001, however, was the lowest since 1996. In spite of this modest figure, the average growth rate over the past five years (from 1997) has been much higher, at 35.7%, and last year's record growth (2001 over 2000) was 52%. The key features of development during 2002 were: 7,227 MW new installed wind power; cumulative installed capacity by the end of 2002 had reached 32,037 MW, consisting of around 61,500 wind turbines dispersed over more than 40 countries; A major share of new installations took place in Europe, with 85.4% of the total. Germany accounted for 53% of the European total; America fell back form its peak level of 1,745 MW in 2001 to a modest 494 MW in 2002, with the majority installed in the USA; Development in Asia was lower than in 2001; Of the emerging markets in the Far East/Pacific, China and Australia were the only two markets to show growth over 2001; The Top Ten markets in the world are headed by Germany, Spain, Denmark and the USA. Newcomers to the Top Ten markets ranking were Australia and the Netherlands; In terms of cumulative installation, the German market passed the 10,000 MW milestone and is by far the largest market in the world. There were 12,000 MW installed in Germany by end of 2002. Spain became No. 2 with 5,042 MW; Penetration of wind power in the world's electricity supply had reached 0.4% by end of 2002. Ten of the world's roughly 25 suppliers of wind turbines are responsible for more than 90% of total supply in the global market. This trend is continuing, with the Top Ten manufacturers in 2002 delivering 95% of the total record installation. Vestas Wind

  16. Wind Power Today: Wind Energy Program Highlights 2001

    Energy Technology Data Exchange (ETDEWEB)

    2002-05-01

    Wind Power Today is an annual publication that provides an overview of the U.S. Department of Energy's Wind Energy Program accomplishments for the previous year. The purpose of Wind Power Today is to show how DOE's Wind Energy Program supports wind turbine research and deployment in hopes of furthering the advancement of wind technologies that produce clean, low-cost, reliable energy. Content objectives include: educate readers about the advantages and potential for widespread deployment of wind energy; explain the program's objectives and goals; describe the program's accomplishments in research and application; examine the barriers to widespread deployment; describe the benefits of continued research and development; facilitate technology transfer; and attract cooperative wind energy projects with industry. This 2001 edition of Wind Power Today also includes discussions about wind industry growth in 2001, how DOE is taking advantage of low wind speed regions through advancing technology, and distributed applications for small wind turbines.

  17. Power electronics converters for wind turbine systems

    DEFF Research Database (Denmark)

    Blaabjerg, Frede; Liserre, Marco; Ma, Ke

    2011-01-01

    The steady growth of installed wind power which reached 200 GW capacity in 2010, together with the up-scaling of the single wind turbine power capability - 7 MW’s has been announced by manufacturers - has pushed the research and development of power converters towards full scale power conversion,...

  18. Wind power potential and integration in Africa

    Directory of Open Access Journals (Sweden)

    Agbetuyi, A.F.

    2013-03-01

    Full Text Available Wind energy penetration into power networks is increasing very rapidly all over the world. The great concern about global warming and continued apprehensions about nuclear power around the world should drive most countries in Africa into strong demand for wind generation because of its advantages which include the absence of harmful emissions, very clean and almost infinite availability of wind that is converted into electricity. This paper shows the power available in the wind. It also gives an overview of the wind power potential and integration in some selected Africa countries like Egypt, Morocco, South Africa and Nigeria and the challenges of wind power integration in Africa’s continent are also discussed. The Northern part of Africa is known to be Africa’s Wind pioneers having installed and connected the Wind Energy Converters (WEC to the grid. About 97% of the continent’s total wind installations are located in Egypt, Morocco and Tunisia. Research work should commence on the identified sites with high wind speeds in those selected Africa countries, so that those potential sites can be connected to the grid. This is because the ability of a site to sufficiently accommodate wind generation not only depends on wind speeds but on its ability to interconnect to the existing grid. If these wind energy potentials are tapped and connected to the grid, the erratic and epileptic power supply facing most countries in Africa will be reduced; thereby reducing rural-urban migration and more jobs will be created.

  19. Wind power project; Proyecto eolico

    Energy Technology Data Exchange (ETDEWEB)

    Borja D, Marco A. [Instituto de Investigaciones Electricas, Cuernavaca, Morelos (Mexico)

    2003-07-01

    In the international scope, nowadays it is recognized that the wind power generation is an innovating activity of high technology that has been integrated to the electrical systems in order to diversify the power generation and to foment the sustainable development. In several industrialized countries no one discusses any longer if wind power generation is a viable alternative or not, because in the last ten years the facts have widely demonstrated their technical viability and environmental advantage with respect to the conventional generation schemes. [Spanish] En el ambito internacional, hoy en dia se reconoce que la generacion eoloelectrica es una actividad innovadora de alta tecnologia que se ha integrado a los sistemas electricos con el proposito de diversificar la generacion de electricidad y fomentar el desarrollo sustentable. En varios paises industrializados ya no se discute si la generacion eoloelectrica es una alternativa viable o no, pues en los ultimos diez anos los hechos han demostrado ampliamente su viabilidad tecnica y ventaja ambiental respecto a la generacion convencional.

  20. Wind up with continuous intra-day electricity markets? The integration of large-share wind power generation in Denmark

    International Nuclear Information System (INIS)

    Karanfil, Fatih; Li, Yuanjing

    2015-01-01

    This paper suggests an innovative idea to examine the functionality of an electricity intra-day market by testing causality among its fundamental components. As fluctuations of poorly predicted wind power generation are challenging the stability of the current electricity system, an intra-day market design can play an important role in managing wind forecast errors. Using Danish and Nordic data, it investigates the main drivers of the price difference between the intra-day and day-ahead markets, and causality between wind forecast errors and their counterparts. Our results show that the wind and conventional generation forecast errors significantly cause the intra-day price to differ from the day-ahead price, and that the relative intra-day price decreases with the unexpected amount of wind generation. Cross-border electricity exchanges are found to be important to handle wind forecast errors. Additionally, some zonal differences with respect to both causality and impulse responses are detected. This paper provides the first evidence on the persuasive functioning of the intra-day market in the case of Denmark, whereby intermittent production deviations are effectively reduced, and wind forecast errors are jointly handled through the responses from demand, conventional generation, and intra-day international electricity trade. (authors)

  1. Optimal Wind Power Uncertainty Intervals for Electricity Market Operation

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Ying; Zhou, Zhi; Botterud, Audun; Zhang, Kaifeng

    2018-01-01

    It is important to select an appropriate uncertainty level of the wind power forecast for power system scheduling and electricity market operation. Traditional methods hedge against a predefined level of wind power uncertainty, such as a specific confidence interval or uncertainty set, which leaves the questions of how to best select the appropriate uncertainty levels. To bridge this gap, this paper proposes a model to optimize the forecast uncertainty intervals of wind power for power system scheduling problems, with the aim of achieving the best trade-off between economics and reliability. Then we reformulate and linearize the models into a mixed integer linear programming (MILP) without strong assumptions on the shape of the probability distribution. In order to invest the impacts on cost, reliability, and prices in a electricity market, we apply the proposed model on a twosettlement electricity market based on a six-bus test system and on a power system representing the U.S. state of Illinois. The results show that the proposed method can not only help to balance the economics and reliability of the power system scheduling, but also help to stabilize the energy prices in electricity market operation.

  2. On practical challenges of decomposition-based hybrid forecasting algorithms for wind speed and solar irradiation

    International Nuclear Information System (INIS)

    Wang, Yamin; Wu, Lei

    2016-01-01

    This paper presents a comprehensive analysis on practical challenges of empirical mode decomposition (EMD) based algorithms on wind speed and solar irradiation forecasts that have been largely neglected in literature, and proposes an alternative approach to mitigate such challenges. Specifically, the challenges are: (1) Decomposed sub-series are very sensitive to the original time series data. That is, sub-series of the new time series, consisting of the original one plus a limit number of new data samples, may significantly differ from those used in training forecasting models. In turn, forecasting models established by original sub-series may not be suitable for newly decomposed sub-series and have to be trained more frequently; and (2) Key environmental factors usually play a critical role in non-decomposition based methods for forecasting wind speed and solar irradiation. However, it is difficult to incorporate such critical environmental factors into forecasting models of individual decomposed sub-series, because the correlation between the original data and environmental factors is lost after decomposition. Numerical case studies on wind speed and solar irradiation forecasting show that the performance of existing EMD-based forecasting methods could be worse than the non-decomposition based forecasting model, and are not effective in practical cases. Finally, the approximated forecasting model based on EMD is proposed to mitigate the challenges and achieve better forecasting results than existing EMD-based forecasting algorithms and the non-decomposition based forecasting models on practical wind speed and solar irradiation forecasting cases. - Highlights: • Two challenges of existing EMD-based forecasting methods are discussed. • Significant changes of sub-series in each step of the rolling forecast procedure. • Difficulties in incorporating environmental factors into sub-series forecasting models. • The approximated forecasting method is proposed to

  3. Integration of 18 GW Wind Energy into the Energy Market. Practical Experiences in Germany. Experiences with large-scale integration of wind power into power systems

    International Nuclear Information System (INIS)

    Krauss, C.; Graeber, B.; Lange, M.; Focken, U.

    2006-01-01

    This work describes the integration of 18 GW of wind power into the German energy market. The focus lies on reporting practical experiences concerning the use of wind energy in Germany within the framework of the renewable energy act (EEG) and the immediate exchange of wind power between the four German grid control areas. Due to the EEG the demand for monitoring the current energy production of wind farms and for short-term predictions of wind power has significantly increased and opened a broader market for these services. In particular for trading on the intraday market ultra short term predictions in the time frame of 1 to 10 hours require different approaches than usual dayahead predictions because the large numerical meteorological models are not sufficiently optimized for very short time horizons. It is shown that for this range a combination of a statistical and a deterministic model leads to significant improvements and stable results as it unites the characteristics of the current wind power production with the synoptic-scale meteorological situation. The possible concepts of balancing the remaining differences between predicted and actual wind power generation are discussed. As wind power prediction errors and load forecasting errors are uncorrelated, benefits can arise from a combined balancing. Finally practical experiences with wind power fluctuations and large forecast errors are presented.

  4. Power System Operation with Large Scale Wind Power Integration

    DEFF Research Database (Denmark)

    Suwannarat, A.; Bak-Jensen, B.; Chen, Z.

    2007-01-01

    The Danish power system starts to face problems of integrating thousands megawatts of wind power, which produce in a stochastic behavior due to natural wind fluctuations. With wind power capacities increasing, the Danish Transmission System Operator (TSO) is faced with new challenges related...... to the uncertain nature of wind power. In this paper, proposed models of generations and control system are presented which analyze the deviation of power exchange at the western Danish-German border, taking into account the fluctuating nature of wind power. The performance of the secondary control of the thermal...... power plants and the spinning reserves control from the Combined Heat and Power (CHP) units to achieve active power balance with the increased wind power penetration is presented....

  5. Improving wind power quality with energy storage

    DEFF Research Database (Denmark)

    Rasmussen, Claus Nygaard

    2009-01-01

    The results of simulation of the influence of energy storage on wind power quality are presented. Simulations are done using a mathematical model of energy storage. Results show the relation between storage power and energy, and the obtained increase in minimum available power from the combination...... of wind and storage. The introduction of storage enables smoothening of wind power on a timescale proportional to the storage energy. Storage does not provide availability of wind power at all times, but allows for a certain fraction of average power in a given timeframe to be available with high...... probability. The amount of storage capacity necessary for significant wind power quality improvement in a given period is found to be 20 to 40% of the energy produced in that period. The necessary power is found to be 80 to 100% of the average power of the period....

  6. Balancing modern Power System with large scale of wind power

    DEFF Research Database (Denmark)

    Basit, Abdul; Altin, Müfit; Hansen, Anca Daniela

    2014-01-01

    Power system operators must ensure robust, secure and reliable power system operation even with a large scale integration of wind power. Electricity generated from the intermittent wind in large propor-tion may impact on the control of power system balance and thus deviations in the power system...... frequency in small or islanded power systems or tie line power flows in interconnected power systems. Therefore, the large scale integration of wind power into the power system strongly concerns the secure and stable grid operation. To ensure the stable power system operation, the evolving power system has...... to be analysed with improved analytical tools and techniques. This paper proposes techniques for the active power balance control in future power systems with the large scale wind power integration, where power balancing model provides the hour-ahead dispatch plan with reduced planning horizon and the real time...

  7. 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

  8. A Peak Wind Probability Forecast Tool for Kennedy Space Center and Cape Canaveral Air Force Station

    Science.gov (United States)

    Crawford, Winifred; Roeder, William

    2008-01-01

    This conference abstract describes the development of a peak wind forecast tool to assist forecasters in determining the probability of violating launch commit criteria (LCC) at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) in east-central Florida. The peak winds are an important forecast element for both the Space Shuttle and Expendable Launch Vehicle (ELV) programs. The LCC define specific peak wind thresholds for each launch operation that cannot be exceeded in order to ensure the safety of the vehicle. The 45th Weather Squadron (45 WS) has found that peak winds are a challenging parameter to forecast, particularly in the cool season months of October through April. Based on the importance of forecasting peak winds, the 45 WS tasked the Applied Meteorology Unit (AMU) to develop a short-range peak-wind forecast tool to assist in forecasting LCC violatioas.The tool will include climatologies of the 5-minute mean end peak winds by month, hour, and direction, and probability distributions of the peak winds as a function of the 5-minute mean wind speeds.

  9. Modeling lifetime of high power IGBTs in wind power applications

    DEFF Research Database (Denmark)

    Busca, Cristian

    2011-01-01

    The wind power industry is continuously developing bringing to the market larger and larger wind turbines. Nowadays reliability is more of a concern than in the past especially for the offshore wind turbines since the access to offshore wind turbines in case of failures is both costly and difficult....... Lifetime modeling of future large wind turbines is needed in order to make reliability predictions about these new wind turbines early in the design phase. By doing reliability prediction in the design phase the manufacturer can ensure that the new wind turbines will live long enough. This paper represents...... an overview of the different aspects of lifetime modeling of high power IGBTs in wind power applications. In the beginning, wind turbine reliability survey results are briefly reviewed in order to gain an insight into wind turbine subassembly failure rates and associated downtimes. After that the most common...

  10. Forecasting Downdraft Wind Speeds Associated with Airmass Thunderstorms for Peterson Air Force Base, Colorado, Using the WSR-88D

    National Research Council Canada - National Science Library

    Steen, Travis

    1999-01-01

    .... During the same summer, Air Force Space Command units issued nearly 65% of their weather warnings for convective winds, making the forecasting of convective winds the most frequent challenge to forecasters...

  11. International wind energy development. World market update 2009. Forecast 2010-2014

    Energy Technology Data Exchange (ETDEWEB)

    2010-03-15

    This is the fifteenth edition of the annual World Market Update produced by BTM Consult ApS, and covers developments in the wind energy sector during 2009. As in previous editions, the report also assesses important changes over the last three years and forecasts progress for five years ahead. The special topic in this year's WMU is an evaluation of the aftermath of the COP-15 climate change negotiations in relation to future wind power development. The global market for wind power not only produced a record for new installations in 2009 of 38 GW installed capacity, it also created a new order in the balance of international wind power. The rapid increase in the rate of installations in both Asia and the US was already clear in 2008; that trend has continued at a faster pace in 2009. By far the largest number of new wind projects were seen in the US and China. Another new reality is that most of the world's manufacturing of wind turbines now takes place in China. As a result three Chinese companies are among the world's top ten turbine manufacturers. At the same time a rapid expansion of manufacturing capacity by European turbine makers has taken place in the US. Europe contributed 28.2% of the newly added capacity - 10,738 MW - taking the continent's total wind power generation capacity to 76,553 MW. The growth in Asia's markets has once again been staggering. With 14,991 MW of new installations, South and East Asia accounted for 39.4% of the global total in 2009. China was the major contributor, with 13,750 MW of new capacity, more than double that installed in 2008. In terms of cumulative installed wind power, the US is still the world leader, with 35,159 MW. China overtook Germany with a margin of less than 50 MW. China now has a total of 25,853 MW, followed by Germany's 25,813 MW. A new world order in wind power has become a reality. The forecast released in this WMU shows an average growth rate of 13.5% for the period 2010

  12. Wind power error estimation in resource assessments.

    Science.gov (United States)

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

    2015-01-01

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

  13. Network wind power over the Pacific Northwest

    Energy Technology Data Exchange (ETDEWEB)

    Hewson, E W; Baker, R W; Barber, D A; Peterson, B

    1978-09-01

    Since 1975 the Bonneville Power Administration (BPA) has been sponsoring wind power research at Oregon State University. A feasibility study that initially concentrated on the wind power potential in the Columbia River Gorge has expanded to the BPA service area which covers Washington, Oregon, Idaho, western Montana and northern Nevada. Previous BPA reports have documented the progress of this research.

  14. Power and energy balances. Forecast 2008

    International Nuclear Information System (INIS)

    2005-01-01

    Both the energy and power balance in 2008 is slightly better than the former Nordel estimate for 2007. This is due to additional investments in new generation capacity, new interconnections of total 1 000 MW to outside Nordel and reduced demand forecast in Sweden. The Nordic electricity system is able to meet the estimated consumption and the corresponding typical power demand pattern in average conditions. In long term the market is expected to maintain a reasonable balance between supply, imports and demand. Lower precipitation or colder temperature result in higher market prices that give incentives for increased imports, demand response and investments. This is expected to maintain the balance between supply and demand in the short and long term even in extreme situations. Allocation between imports and demand response in reality depends on the prevailing market prices and available generation resources outside Nordel. The interconnection capacities are expected to enable import volumes that can meet the increased peak demand. Some Nordic areas can be exposed to a risk for rationing or other measures because of extremely low precipitation. Nordic transmission capacities may prevent full utilization of Nordic thermal power in certain areas. The planned reinforcements in the 'five prioritised cross-sections' will improve the situation. The power balance and the internal bottlenecks in the continental Europe can have an effect on the import possibilities to the Nordic countries. The annual energy consumption in the Nordic market is estimated to grow by 20 TWh by year 2008 (1.2%la) from 395 TWh in 2004 (temperature corrected). In the three year period investments in power generation is expected to increase the available generation capacity and capability by 1500 MW and 10 TWhla in average conditions. Iceland is not included in the figures. The annual energy consumption in Iceland is estimated to grow by about 6.8 TWh by year 2008 (15 %la) due to two new aluminium

  15. Wind power in Norway; Vindkraft i Norge

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1998-12-01

    This report analyses business costs and socio-economic costs in the development of wind power in Norway and policy instruments to encourage such a development. It is founded on an analysis of the development of wind power in other countries, notably U.S.A, Denmark, Germany, the Netherlands and Britain. The report describes the institutional background in each country, the policy instruments that have been used and still are and the results achieved. The various cost components in Norwegian wind power development and the expected market price of wind power are also discussed. The discussion of instruments distinguishes between investment oriented and production oriented instruments. 8 refs., 9 figs., 3 tabs.

  16. An integrated system for wind energy forecast using meteorological models and statistical post-processing

    Science.gov (United States)

    Miranda, P.; Rodrigues, A.; Lopes, J.; Palma, J.; Tome, R.; Sousa, J.; Bessa, R.; Matos, J.

    2009-12-01

    With 3GW of installed wind turbines, corresponding to 23% of the total electric grid, and a 5-year plan that will grow that value above 5GW (near 40% of the grid), Portugal has been a recent success case for renewable energy development. Clearly such large share of wind energy in the national electric system implies a strong requirement for accurate wind forecasts, that can be used to forecast this highly variable energy source and allow for timely decision making in the energy markets, namely for on and off switching of alternative conventional sources. In the past 3 years, a system for 72h energy forecast in mainland Portugal was setup, using 6km resolution meteorological forecasts, forced by global GFS forecasts by NCEP. In the development phase, different boundary conditions (from NCEP and ECMWF) were tested, as well as different limited area models (namely MM5, Aladin, MesoNH and WRF) at resolutions from 12 to 2km, which were evaluated by comparison with wind observations at heights relevant for wind turbines (up to 80m) in different locations and for different synoptic conditions. The developed system, which works with a real time connection with wind farms, also includes a post-processing code that merges recent wind observations with the meteorological forecast, and converts the forecasted wind fields into forecasted energy, by incorporating empirical transfer functions of the wind farm. Wind conditions in Portugal are highly influenced by topography, as most wind farms are located in complex terrain, often in mountainous terrain, where stratification plays a significant role. Coastal effects are also highly relevant, especially during the Summer, where a strong diurnal cycle of the sea-breeze is superimposed on an equally strong boundary layer development, both with a significant impact on low level winds. These two ingredients tend to complicate wind forecasts, requiring fully developed meteorological models. In general, results from 2 full years of

  17. Security, protection, and control of power systems with large-scale wind power penetration

    Science.gov (United States)

    Acharya, Naresh

    As the number of wind generation facilities in the utility system is fast increasing, many issues associated with their integration into the power system are beginning to emerge. Of the various issues, this dissertation deals with the development of new concepts and computational methods to handle the transmission issues and voltage issues caused by large-scale integration of wind turbines. This dissertation also formulates a probabilistic framework for the steady-state security assessment of wind power incorporating the forecast uncertainty and correlation. Transmission issues are mainly related to the overloading of transmission lines, when all the wind power generated cannot be delivered in full due to prior outage conditions. To deal with this problem, a method to curtail the wind turbine outputs through Energy Management System facilities in the on-line operational environment is proposed. The proposed method, which is based on linear optimization, sends the calculated control signals via the Supervisory Control and Data Acquisition system to wind farm controllers. The necessary ramping of the wind farm outputs is implemented either by the appropriate blade pitch angle control at the turbine level or by switching a certain number of turbines. The curtailment strategy is tested with an equivalent system model of MidAmerican Energy Company. The results show that the line overload in high wind areas can be alleviated by controlling the outputs of the wind farms step-by-step over an allowable period of time. A low voltage event during a system fault can cause a large number of wind turbines to trip, depending on voltages at the wind turbine terminals during the fault and the under-voltage protection setting of wind turbines. As a result, an N-1 contingency may evolve into an N-(K+1) contingency, where K is the number of wind farms tripped due to low voltage conditions. Losing a large amount of wind power following a line contingency might lead to system

  18. Wind Turbine and Wind Power Plant Modelling Aspects for Power System Stability Studies

    DEFF Research Database (Denmark)

    Altin, Müfit; Hansen, Anca Daniela; Göksu, Ömer

    2014-01-01

    is not reasonable regarding the focus of the study. Therefore the power system operators should be aware of the modelling aspects of the wind power considering the related stability study and implement the required model in the appropriate power system toolbox. In this paper, the modelling aspects of wind turbines...... and wind power plants are reviewed for power system stability studies. Important remarks of the models are presented by means of simulations to emphasize the impact of these modelling details on the power system.......Large amount of wind power installations introduce modeling challenges for power system operators at both the planning and operational stages of power systems. Depending on the scope of the study, the modeling details of the wind turbine or the wind power plant are required to be different. A wind...

  19. Changing wind-power landscapes

    DEFF Research Database (Denmark)

    Möller, Bernd

    2006-01-01

    After more than 25 years of continuous development, Danish wind-energy landscapes are due for face changes. On-shore construction has ceased and necessary re-powering schemes have not been introduced as yet. Regional planning is discouraging, while conditions for erecting new turbines have become...... more stringent. One of the factors inhibiting development seems to be uncertainty in planning about the future impact on landscapes. Visual impact has rarely been an issue so far, but ever-increasing turbine size and less local involvement may change this. This paper presents a deterministic approach...... of determining the likely visual-impact on landscapes and population, taking into account that there is no clear threshold for perceived adverse visual-impact. A geographical information system (GIS) has been used to build a regional landscape model for Northern Jutland County, which is used to assess visibility...

  20. How wind power landscapes change

    DEFF Research Database (Denmark)

    Möller, Bernd

    2006-01-01

    viewsheds are computed for a variety of thresholds of visual impact, and since overlaid with population and land use data. The results indicate that the construction of new turbines replacing 40% of the old turbine stock and raising the installed capacity by 20% will not add to the comparative impact......Following 25 years of continuous development, Danish wind energy landscapes are going to face changes. Ceased on-shore construction, unresolved re-powering and stalled regional planning characterize the situation overshadowed by off-shore development. One of the factors inhibiting development...... appears to be planning uncertainty regarding the future impact on landscapes. Visual impact has seldom been an issue so far, but growing turbine size and less local involvement may change this. This paper presents a deterministic approach of quantifying percieved visual impact on landscapes and population...

  1. Evaluation of Dynamical Downscaling Resolution Effect on Wind Energy Forecast Value for a Wind Farm in Central Sweden

    DEFF Research Database (Denmark)

    Rosgaard, Martin Haubjerg; Hahmann, Andrea N.; Nielsen, Torben Skov

    2014-01-01

    energy. The present study aims to quantify value added to wind energy forecasts in the 12-48 hour leadtime by downscaling global numerical weather prediction (NWP) data from the National Centers for Environmental Prediction Global Forecast System (GFS) using the limited-area NWP model described...

  2. Wind Power: The Economic Impact of Intermittency

    OpenAIRE

    G. Cornelis van Kooten

    2009-01-01

    Wind is the fastest growing renewable energy source for generating electricity, but economic research lags behind. In this study, therefore, we examine the economics of integrating large-scale wind energy into an existing electrical grid. Using a simple grid management model to investigate the impact of various levels of wind penetration on grid management costs, we show that costs of reducing CO2 emissions by relying more on wind power depend on the generation mix of the existing electrical ...

  3. Realities and myths of wind power

    International Nuclear Information System (INIS)

    Juanico, Luis

    2001-01-01

    In the last ten years we have seen an impressive growth of electrical generation by wind power. However this increase cannot be explained by an advance of the technology or by the improvement of the economic factors. The explanation of the boom is based mostly on environmental aspects instead of strategic considerations on energy supply. In Argentina wind power is promoted as a kind of economically viable panacea based on four myths: the explosive growth of wind power, the decrease of costs as a function of the power increase, the wind power potential of Patagonia, the analogy with conventional technologies. The analysis of these myths shows that the global wind power production is very low and it is concentrated in few developed countries, it is supported by environmental interests and protected by important subsidies. In Argentina this support cannot be justified neither by environmental considerations nor by economic reasons

  4. Weather Research and Forecasting model simulation of an onshore wind farm: assessment against LiDAR and SCADA data

    Science.gov (United States)

    Santoni, Christian; Garcia-Cartagena, Edgardo J.; Zhan, Lu; Iungo, Giacomo Valerio; Leonardi, Stefano

    2017-11-01

    The integration of wind farm parameterizations into numerical weather prediction models is essential to study power production under realistic conditions. Nevertheless, recent models are unable to capture turbine wake interactions and, consequently, the mean kinetic energy entrainment, which are essential for the development of power optimization models. To address the study of wind turbine wake interaction, one-way nested mesoscale to large-eddy simulation (LES) were performed using the Weather Research and Forecasting model (WRF). The simulation contains five nested domains modeling the mesoscale wind on the entire North Texas Panhandle region to the microscale wind fluctuations and turbine wakes of a wind farm located at Panhandle, Texas. The wind speed, direction and boundary layer profile obtained from WRF were compared against measurements obtained with a sonic anemometer and light detection and ranging system located within the wind farm. Additionally, the power production were assessed against measurements obtained from the supervisory control and data acquisition system located in each turbine. Furthermore, to incorporate the turbines into very coarse LES, a modification to the implementation of the wind farm parameterization by Fitch et al. (2012) is proposed. This work was supported by the NSF, Grants No. 1243482 (WINDINSPIRE) and IIP 1362033 (WindSTAR), and TACC.

  5. Prophetic forecast on the nuclear power applications

    International Nuclear Information System (INIS)

    Lee, Chang-Kun

    1996-01-01

    It was asked to attempt the ''prophetic forecast''. The time required for the doubling of world population continued to shrink, and now it is mere 40 years. The life of a contemporary person is now sustained by some 30,000 different ''daily necessities'', and despite such proliferation of options, the avarice for much more has not diminished. Over the past 35 years, the Korean population has increased by 1.79 times, and the electric power generation by 168.53 fold. Similar mushrooming trends have occurred in water and food consumption, clothing, plastics, paper, iron and steel, aluminum and so forth. The annual minimum temperature in Seoul has sharply jumped up in the last 80 years, and in the last 2-3 years, sea level went up by 10 mm per annum. Nuclear energy will play a crucial role in helping save all forms of life on the earth and keep the biosphere clean and livable, by reducing the discharge of detrimental gases and contaminating effluents. The main cause of various problems is human population burst, but now there may be a reason for some optimism as far as containing unbounded population growth, by the dilution of sperm density in human semen. In order to avoid the crashing of a large planetoid on the earth in 2126, nuclear architects must develop powerful and accurate nuclear weapons to shoot it off course. The prophetic view is that by the active and judicious applications of nuclear power and technology, the continued survival of mankind will be able to be ensured. (K.I.)

  6. Power Quality Issues on Wind Power Installations in Denmark

    DEFF Research Database (Denmark)

    Sørensen, Poul Ejnar; Cutululis, Nicolaos Antonio; Lund, Torsten

    2007-01-01

    offshore wind farms connected at transmission level. In this perspective, the power quality issues are divided into local issues particularly related to the voltage quality in the distribution systems and global issues related to the power system control and stability. Power quality characteristics of wind......This paper introduces the power quality issues of wind power installations in a historic perspective, as the development from a few small wind turbines connected directly to the low voltage grid, to the present system with high penetration on the medium voltage distribution grids and two large...

  7. Wind power in Taiwan: Policy and development challenges

    International Nuclear Information System (INIS)

    Liou, Hwa Meei

    2011-01-01

    The main aim of this paper is in discussing the outcome of the government's policies aimed at promoting the wind power industry. By analyzing the policies on renewable energy and the direct and indirect support mechanisms, the author reviews the achievements, limitations and strategies faced during their various stages. This research discovered that the series of measures adopted between 2000 and 2005 including installation plans, financial incentives, feed-in tariffs, export credit subsidies and R and D, helped to initiate the early steps of private investment, and allow domestic wind capacity to see stable growth. After 2005 with more clear goals set for wind energy installed capacity policies, R and D and industrial cooperation mechanisms, there was even greater breakthrough in limited market, enabling Taiwan's fledgling wind power industry to take its first steps onto the international production chain. In particular, the passing of the Renewable Energy Development Act in 2009 incited rapid growth in the domestic market as well as driving further development in the domestic wind energy industry. Overall, in current stage there is a need to get a handle on the gap still existing between international technology and market and that in Taiwan, in order to strategically develop a competitive advantage globally. - Highlights: → Taiwan wind power industries are still in the early forming stages.→ There are direct and indirect policy incentives for promoting the wind power.→ In the short term, R and D will focus on forecasting technology and on key components.→ In the mid-term, small to mid-scale wind power generators are appreciated.→ Currently, developing offshore WP, the MW WP turbine equipment is the key strategies.

  8. Wind power in Taiwan: Policy and development challenges

    Energy Technology Data Exchange (ETDEWEB)

    Liou, Hwa Meei, E-mail: liouhm@mail.ntust.edu.tw [Graduate Institute of Technology Management, National Taiwan University of Science and Technology, 43, Sec. 4, Keelung Rd., Taipei 106, Taiwan (China)

    2011-06-15

    The main aim of this paper is in discussing the outcome of the government's policies aimed at promoting the wind power industry. By analyzing the policies on renewable energy and the direct and indirect support mechanisms, the author reviews the achievements, limitations and strategies faced during their various stages. This research discovered that the series of measures adopted between 2000 and 2005 including installation plans, financial incentives, feed-in tariffs, export credit subsidies and R and D, helped to initiate the early steps of private investment, and allow domestic wind capacity to see stable growth. After 2005 with more clear goals set for wind energy installed capacity policies, R and D and industrial cooperation mechanisms, there was even greater breakthrough in limited market, enabling Taiwan's fledgling wind power industry to take its first steps onto the international production chain. In particular, the passing of the Renewable Energy Development Act in 2009 incited rapid growth in the domestic market as well as driving further development in the domestic wind energy industry. Overall, in current stage there is a need to get a handle on the gap still existing between international technology and market and that in Taiwan, in order to strategically develop a competitive advantage globally. - Highlights: > Taiwan wind power industries are still in the early forming stages.> There are direct and indirect policy incentives for promoting the wind power.> In the short term, R and D will focus on forecasting technology and on key components.> In the mid-term, small to mid-scale wind power generators are appreciated.> Currently, developing offshore WP, the MW WP turbine equipment is the key strategies.

  9. An advanced strategy for wind speed forecasting using expert 2-D FIR filters

    Directory of Open Access Journals (Sweden)

    MOGHADDAM, A. A.

    2010-11-01

    Full Text Available Renewable energies such as wind and solar have become the most attractive means of electricity generation nowadays. Social and environmental benefits as well as economical issues result in further utilization of such these energy resources. In this regard, wind energy plays an important roll in operation of small-scale power systems like Micro Grid. On the other hand, wind stochastic nature in different time and place horizons, makes accurate forecasting of its behavior an inevitable task for market planners and energy management systems. In this paper an advanced strategy for wind speed estimation has been purposed and its superior performance is compared to that of conventional methods. The model is based on linear predictive filtering and image processing principles using 2-D FIR filters. To show the efficiency of purposed predictive model different FIR filters are designed and tested through similar data. Wind speed data have been collected during the period January 1, 2009 to December 31, 2009 from Casella automatic weather station at Plymouth. It is observed that 2-D FIR filters act more accurately in comparison with 1-D conventional representations; however, their prediction ability varies considerably through different filter sizing.

  10. Danish Wind Power Export and Cost

    DEFF Research Database (Denmark)

    Lund, Henrik; Hvelplund, Frede; Alberg Østergaard, Poul

    In a normal wind year, Danish wind turbines generate the equivalent of approx. 20 percent of the Danish electricity demand. This paper argues that only approx. 1 percent of the wind power production is exported. The rest is used to meet domestic Danish electricity demands. The cost of wind power......, a study made by the Danish think tank CEPOS claimed the opposite, i.e. that most of the Danish wind power has been exported in recent years. However, this claim is based on an incorrect interpretation of statistics and a lack of understanding of how the international electricity markets operate...... is paid solely by the electricity consumers and the net influence on consumer prices was as low as 1-3 percent on average in the period 2004-2008. In 2008, the net influence even decreased the average consumer price, although only slightly. In Denmark, 20 percent wind power is integrated by using both...

  11. Attitudes towards wind power development in Denmark

    DEFF Research Database (Denmark)

    Ladenburg, Jacob

    is preferred to land based development, which indicates that the wind power development should be taken off-shore. But, the results also point out that the land-based opportunities for wind power development are not exhausted. On a more detailed level, the results denote that the attitude towards both land...... based and off-shore wind power vary with age of the respondents and experience with wind turbines. Younger respondents are more positive towards wind power than older respondents, pointing towards an increase in acceptance in the future. The attitude was also found to covariate negatively......The present paper analyses the attitudes towards existing and future land-based turbines and off-shore wind farms. The analysis is carried out using a probit model to elicit systematic characteristics determining the attitude of the population. The analyses show that off-shore development...

  12. Wind Turbine Power Curve Design for Optimal Power Generation in Wind Farms Considering Wake Effect

    DEFF Research Database (Denmark)

    Tian, Jie; Zhou, Dao; Su, Chi

    2017-01-01

    In modern wind farms, maximum power point tracking (MPPT) is widely implemented. Using the MPPT method, each individual wind turbine is controlled by its pitch angle and tip speed ratio to generate the maximum active power. In a wind farm, the upstream wind turbine may cause power loss to its...... downstream wind turbines due to the wake effect. According to the wake model, downstream power loss is also determined by the pitch angle and tip speed ratio of the upstream wind turbine. By optimizing the pitch angle and tip speed ratio of each wind turbine, the total active power of the wind farm can...... be increased. In this paper, the optimal pitch angle and tip speed ratio are selected for each wind turbine by the exhausted search. Considering the estimation error of the wake model, a solution to implement the optimized pitch angle and tip speed ratio is proposed, which is to generate the optimal control...

  13. Development of Danish Wind Power Market

    DEFF Research Database (Denmark)

    Meyer, Niels I

    2007-01-01

    The modern phase of Danish wind power started after the oil crisis in 1973. During the eighties technological development resulted in increased cost efficiency. In the early nineties favourable feed-in tariffs were introduced together with easy access to the grid. As a result wind power was booming...

  14. Integration of large amounts of wind power. Markets for trading imbalances

    Energy Technology Data Exchange (ETDEWEB)

    Neimane, Viktoria; Axelsson, Urban [Vattenfall Research and Development AB, Stockholm (Sweden); Gustafsson, Johan; Gustafsson, Kristian [Vattenfall Nordic Generation Management, Stockholm (Sweden); Murray, Robin [Vattenfall Vindkraft AB, Stockholm (Sweden)

    2008-07-01

    The well-known concerns about wind power are related to its intermittent nature and difficulty to make exact forecasts. The expected increase in balancing and reserve requirements due to wind power has been investigated in several studies. This paper takes the next step in studying integration of large amounts of wind power in Sweden. Several wind power producers' and corresponding balance providers' perspective is taken and their imbalance costs modeled. Larger producers having wind power spread over larger geographical areas will have lower relative costs than producers having their units concentrated within limited geographical area. Possibilities of the wind power producers to reduce the imbalance costs by acting on after sales market are exposed and compared. (orig.)

  15. Imbalance costs in the Swedish system with large amounts of wind power

    Energy Technology Data Exchange (ETDEWEB)

    Carlsson, Fredrik; Neimane, Viktoria [Vattenfall Research and Development AB, Stockholm (Sweden)

    2009-07-01

    The well-known concerns about wind power are related to its intermittent nature and difficulty to make exact forecasts. The expected increase in balancing and reserve requirements due to wind power has been investigated in several studies. This paper takes the next step in studying integration of large amounts of wind power in Sweden. Several wind power producers' and corresponding balance providers' perspective is taken and their imbalance costs modeled. Larger producers having wind power spread over larger geographical areas will have lower relative costs than producers having their units concentrated within limited geographical area. Possibilities of the wind power producers to reduce the imbalance costs by acting on after sales market are exposed and compared. (orig.)

  16. Mitigation of Power System Oscillation Caused by Wind Power Fluctuation

    DEFF Research Database (Denmark)

    Su, Chi; Hu, Weihao; Chen, Zhe

    2013-01-01

    Wind power is increasingly integrated in modern power grids, which brings new challenges to the power system operation. Wind power is fluctuating because of the uncertain nature of wind, whereas wind shear and tower shadow effects also cause periodic fluctuations. These may lead to serious forced...... oscillation when the frequencies of the periodic fluctuations are close to the natural oscillation frequencies of the connected power system. By using modal analysis and time-domain simulations, this study studies the forced oscillation caused by the wind shear and tower shadow effects. Three forced...... oscillation mitigation controllers are proposed and compared. A model of direct-drive-full-convertor-based wind farm connected to the IEEE 10-machine 39-bus system is adopted as the test system. The calculations and simulations are conducted in DIgSILENT PowerFactory 14.0. Results are presented to show...

  17. Greenhouse gas emissions from operating reserves used to backup large-scale wind power.

    Science.gov (United States)

    Fripp, Matthias

    2011-11-01

    Wind farms provide electricity with no direct emissions. However, their output cannot be forecasted perfectly, even a short time ahead. Consequently, power systems with large amounts of wind power may need to keep extra fossil-fired generators turned on and ready to provide power if wind farm output drops unexpectedly. In this work, I introduce a new model for estimating the uncertainty in short-term wind power forecasts, and how this uncertainty varies as wind power is aggregated over larger regions. I then use this model to estimate the reserve requirements in order to compensate for wind forecast errors to a 99.999% level of reliability, and an upper limit on the amount of carbon dioxide that would be emitted if natural gas power plants are used for this purpose. I find that for regions larger than 500 km across, operating reserves will undo 6% or less of the greenhouse gas emission savings that would otherwise be expected from wind power.

  18. International wind energy development. World marked update 1999. Forecast 2000-2004

    International Nuclear Information System (INIS)

    2000-03-01

    This is the fifth issue of the annual World Market Update by BTM Consult ApS, covering the year 1999. All figures in the status refer to the end of year 1999. It is the last update from the 20th century, in which wind energy developed during the last two decades to become a very serious part of the world electricity supply. As in previous reports, the past 3 years' development in the wind energy sector is assessed, and the forecast looks 5 years ahead. Wind power is the world's fastest growing energy source, with an average annual growth rate of 40 % over the last five years. Wind energy is a clean and abundant energy source, and it is becomming a preferred source of energy not only due to the environmental benefits, but also because it has become increasingly cost competitive in the world energy markets. One of the most significant figures and trends from this fast growing market during 1999 was that the annual installation of new wind power capacity increased by 51 %, resulting in a cumulative installation by the end of 1999 of 13,932 MW. The growth rates in the wind industry can easily be compared to the growth rates in the IT sector, although the growth differ much from country to country. The high growth rates are still very much influenced by political and economical issues, but the continuously improved technology and thus also the redused cost of energy becomes more and more significant, and there are hardly any arguments left why wind energy should not play a very significant role in the electricity supply. Approximately 81 % of the new capacity of 3,922 were installed in Europe, emphasizing that this region is still the major market place. The US market picked up close to the PTC expiry date (Production Tax Credit) on June 30, 1999. In terms of single markets it was, however, the German market which once again took the lead with installed capacity of 1,568 MW. Germany thereby consolidated the position as the leading wind energy country in the world. Spain

  19. Calculation of Wind Power Limit adjusting the Continuation Power Flow

    International Nuclear Information System (INIS)

    Santos Fuentefria, Ariel; Castro Fernández, Miguel; Martínez García, Antonio

    2012-01-01

    The wind power insertion in the power system is an important issue and can create some instability problems in voltage and system frequency due to stochastic origin of wind. Know the Wind Power Limit is a very important matter. Existing in bibliography a few methods for calculation of wind power limit. The calculation is based in static constrains, dynamic constraints or both. In this paper is developed a method for the calculation of wind power limit using some adjust in the continuation power flow, and having into account the static constrains. The method is complemented with Minimal Power Production Criterion. The method is proved in the Isla de la Juventud Electric System. The software used in the simulations was the Power System Analysis Toolbox (PSAT). (author)

  20. A hybrid approach for short-term forecasting of wind speed.

    Science.gov (United States)

    Tatinati, Sivanagaraja; Veluvolu, Kalyana C

    2013-01-01

    We propose a hybrid method for forecasting the wind speed. The wind speed data is first decomposed into intrinsic mode functions (IMFs) with empirical mode decomposition. Based on the partial autocorrelation factor of the individual IMFs, adaptive methods are then employed for the prediction of IMFs. Least squares-support vector machines are employed for IMFs with weak correlation factor, and autoregressive model with Kalman filter is employed for IMFs with high correlation factor. Multistep prediction with the proposed hybrid method resulted in improved forecasting. Results with wind speed data show that the proposed method provides better forecasting compared to the existing methods.

  1. Reactive power control methods for improved reliability of wind power inverters under wind speed variations

    DEFF Research Database (Denmark)

    Ma, Ke; Liserre, Marco; Blaabjerg, Frede

    2012-01-01

    temperature fluctuation in the most stressed devices of 3L-NPC wind power inverter under severe wind speed variations can be significantly stabilized, and the reliability of the power converter can thereby be improved while the increased stress of the other devices in the same power converter......The thermal cycling of power switching devices may lead to failures that compromise the reliability of power converters. Wind Turbine Systems (WTS) are especially subject to severe thermal cycling which may be caused by the wind speed variations or power grid faults. This paper proposes a control...... method to relieve the thermal cycling of power switching devices under severe wind speed variations, by circulating reactive power among the parallel power converters in a WTS or among the WTS's in a wind park. The amount of reactive power is adjusted to limit the junction temperature fluctuation...

  2. Stability and control of wind farms in power systems

    DEFF Research Database (Denmark)

    Jauch, Clemens

    The Ph.D. project ‘Stability and Control of Wind Farms in Power Systems’ deals with some selected problems related to wind power in power systems. With increasing wind power penetration, wind turbines substitute the power production of conventional powerplants. Therefore, wind turbines also have ...

  3. The state-of-the-art in short-term prediction of wind power. A literature overview

    Energy Technology Data Exchange (ETDEWEB)

    Giebel, G.; Draxl, C. (Risoe DTU, Roskilde (Denmark)); Brownsword, R. (Rutherford Appleton Laboratory (RAL), Oxford (United Kingdom)); Kariniotakis, G. (ARMINES, Paris (France)); Denhard, M. (ECMWF, Reading (United Kingdom))

    2011-01-15

    This Deliverable of ANEMOS.plus (Advanced Tools for the Management of Electricity Grids with Large-Scale Wind Generation) and SafeWind projects presents the state of the art in wind power forecasting. More than 380 references of journal and conference papers have been reviewed. (LN)

  4. Wind Generators and Market Power

    DEFF Research Database (Denmark)

    Misir, Nihat

    Electricity production from wind generators holds significant importance in European Union’s 20% renewable energy target by 2020. In this paper, I show that ownership of wind generators affects market outcomes by using both a Cournot oligopoly model and a real options model. In the Cournot...... oligopoly model, ownership of the wind generators by owners of fossil-fueled (peakload) generators decreases total peakload production and increases the market price. These effects increase with total wind generation and aggregate wind generator ownership. In the real options model, start up and shut down...

  5. Validation of Sodar Measurements for Wind Power

    DEFF Research Database (Denmark)

    Hansen, Kurt Schaldemose

    2006-01-01

    A ground-based SODAR has been tested for 1½ years together with a traditional measurement set-up consisting of cups and vanes for measuring wind data for wind power assessment at a remote location. Many problems associated to the operation of a remote located SODAR have been solved during...... the project and a new remote power system has been designed. A direct comparison between SODAR and cup measurements revealed a limitation for the SODAR measurements during different weather conditions, especially since the SODAR was not able to measure wind speeds above 15 m/s due to an increasing back......-ground noise. Instead, using the SODAR as a profiler to establish representative wind speed profiles was successful. These wind speed profiles are combined with low height reference measurements to establish reliable hub height wind speed distributions. Representative wind speed profiles can be establish...

  6. Wind power production: from the characterisation of the wind resource to wind turbine technologies

    International Nuclear Information System (INIS)

    Beslin, Guy; Multon, Bernard

    2016-01-01

    Illustrated by graphs and tables, this article first describes the various factors and means related to the assessment of wind resource in the World, in Europe, and the factors which characterize a local wind resource. In this last respect, the authors indicate how local topography is taken into account to calculate wind speed, how time variations are taken into account (at the yearly, seasonal or daily level), the different methods used to model a local wind resource, how to assess the power recoverable by a wind turbine with horizontal axis (notion of Betz limit). In the second part, the authors present the different wind turbines, their benefits and drawbacks: vertical axis, horizontal axis (examples of a Danish-type wind turbine, of wind turbines designed for extreme conditions). Then, they address the technology of big wind turbines: evolution of technology and of commercial offer, aerodynamic characteristics of wind turbine and benefit of a varying speed (technological solutions, importance of the electric generator). They describe how to choose a wind turbine, how product lines are organised, how the power curve and energy capacity are determined. The issue of integration of wind energy into the power system is then addressed. The next part addressed the economy of wind energy production (annualized production cost, order of magnitude of wind electric power production cost). Future trends are discussed and offshore wind energy production is briefly addressed

  7. Power Quality Improvements in Wind Diesel Power Generation System

    Directory of Open Access Journals (Sweden)

    Omar Feddaoui

    2015-08-01

    Full Text Available Generation of electricity using diesel is costly for small remote isolated communities. At remote location electricity generation from renewable energy such as wind can help reduce the overall operating costs by reducing the fuel costs. However, the penetration of wind power into small diesel-based grids is limited because of its effect on power quality and reliability. This paper focuses on the combination of Wind Turbine and Diesel Generator systems for sustained power generation, to improve the power quality of wind generation system. The performances of the optimal control structure are assessed and discussed by means of a set of simulations.

  8. Power Electronics in Wind Turbine Systems

    DEFF Research Database (Denmark)

    Blaabjerg, Frede; Chen, Zhe; Teodorescu, Remus

    2006-01-01

    the conventional, fossil (and short term) based energy sources to renewable energy resources. The other is to use high efficient power electronics in power systems, power production and end-user application. This paper discuss the most emerging renewable energy source, wind energy, which by means of power...... electronics is changing from being a minor energy source to be acting as an important power source in the energy system. By that wind power is also getting an added value in the power system operation....

  9. Simulation of regional day-ahead PV power forecast scenarios

    DEFF Research Database (Denmark)

    Nuno, Edgar; Koivisto, Matti Juhani; Cutululis, Nicolaos Antonio

    2017-01-01

    at the expense of a high computational burden. Alternatively, some power system applications may require realistic forecasts rather than actual estimates; able to capture the uncertainty of weatherdriven generation. To this end, we propose a novel methodology to generate day-ahead forecast scenarios of regional...

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

    Science.gov (United States)

    Wesonga, Ronald

    2015-01-01

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