标题：Research on modeling spatiotemporal correlation of wind power forecast error on multiple wind farms based on Copula theory
作者：Qijun, Teng ;Chengfu, Wang ;Jun, Liang ;Zhengtang, Liang
作者机构：[Qijun, Teng ;Chengfu, Wang ;Jun, Liang ] School of Electrical Engineering, Shandong University, Ji Nan, China;[Zhengtang, Liang ] State Grid Shandong 更多
会议名称：2nd International Conference on Power and Renewable Energy, ICPRE 2017
会议日期：September 20, 2017 - September 23, 2017
来源：2017 2nd International Conference on Power and Renewable Energy, ICPRE 2017
摘要：The forecast errors of multiple geographically close wind farms have spatiotemporal dependence and this correlation has significant impact to the operation of power system. Therewith, this paper proposes a method to model spatiotemporal correlation of wind power forecast error for multiple wind farms based on Copula theory. Firstly, by comparing fitting accuracy of different fitting methods, KDE-based method with highest fitting accuracy is chose to fit marginal distribution of forecast error. Then, this paper proposes a high dimensional modeling method for short-term wind power forecast error using Copula function and obtains joint cumulative distribution function (JCDF) of forecast errors for multiple wind farms. Finally, the actual forecast error data of four wind farms is used to verily the model. Comparing with the actual dependence structure, the method based on Copula function can effectively model the spatiotemporal correlation and detect independence of wind power forecast errors. Thus the effectiveness of proposed method is proved by simulated results.
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