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《Proceedings of the CSEE》 2013-34
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Probability Density Function of Day-ahead Wind Power Forecast Errors Based on Power Curves of Wind Farms

DING Huajie;SONG Yonghua;HU Zechun;WU Jincheng;FAN Xiaoxu;Department of Electrical Engineering,Tsinghua University;R&D Center of China Longyuan Power Group Corporation Limited;  
Distribution of wind power forecast error significantly affects the decision of dispatch and reserve etc. in power systems. Based on the ‘wind to power' day-ahead forecast procedure of wind farms, this paper put forward an approach to determine the probability density function of day-ahead wind power forecast error of wind farms. Firstly, this paper studied the power curve of wind power with least square fitting method and analyzed the influences of power curve-fitting error on day-ahead wind power forecast. Then the fitted power curve was used to study how the wind speed forecast error affects the wind power forecast error in different speed intervals analytically and by simulation. Finally, Monte-Carlo two-stage sampling was used to simulate the common effect of the fitting error of power curve and wind speed forecast error. The distributions of day-ahead forecast errors corresponding to different speed intervals were determined with Maximum Likelihood Estimation. Case study results based on historical data of an actual wind farm show that the proposed method can precisely depict the wind power forecast error under different wind speed, determine the proper wind speed range for each probability distribution, and provide references for optimal dispatch.
【Fund】: 国家高技术研究发展计划(863计划)资助项目(2012AA050218)~~
【CateGory Index】: TM614
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