Combined Prediction of Short-term Wind Power Considering Correlation of Meteorological Features and Fluctuation Process

被引：0

作者：

Ye L. ^{[1
]}

Zhao J. ^{[1
]}

Lu P. ^{[1
]}

Pei M. ^{[1
]}

Chen M. ^{[2
]}

Wang B. ^{[3
]}

Che J. ^{[3
]}

机构：

[1] College of Information and Electrical Engineering, China Agricultural University, Beijing

[2] State Grid Corporation of China, Beijing

[3] China Electric Power Research Institute, Beijing

来源：

Dianli Xitong Zidonghua/Automation of Electric Power Systems | 2021年 / 45卷 / 04期

关键词：

Combined prediction; Correlation of fluctuation process; Meteorological characteristic factor; Short-term wind power prediction; Weather fluctuation process;

D O I：

10.7500/AEPS20191112002

中图分类号：

学科分类号：

摘要：

To cope with the problems of difficulties in extraction of the critical meteorological factors and the weak relevance between the weather and power fluctuation processes, a combined prediction method of short-term wind power considering correlation of meteorological features and fluctuation processes is proposed. At first, the meteorological characteristic factors of numerical weather prediction (NWP) are obtained by the rule of minimal redundancy maximal relevance (mRMR) to classify the weather fluctuation processes. Further, considering the relationship between weather and power fluctuation processes, a short-term combined prediction model is constrcuted, which takes meteorological characteristic factors as inputs and wind power as output. Finally, the prediction values of wind power associated with different weather processes are combined in time series to get the prediction results of short-term wind power, which takes fluctuation processes as the output. Case study shows that the combined prediction method with correlations of fluctuation processes which takes meteorological characteristic factors as inputs can significantly improve the prediction accuracy of the short-term wind power. © 2021 Automation of Electric Power Systems Press.

引用

页码：54 / 62

页数：8

共 25 条

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