Prediction method of output power long-term fluctuation characteristic for multiple wind farms after aggregation based on improved KDE method and GA-SVM

被引：0

作者：

Xiao B. ^{[1
]}

Xing S. ^{[2
]}

Wang M. ^{[3
]}

Yang S. ^{[3
]}

Gou X. ^{[3
]}

机构：

[1] School of Electrical Engineering, Northeast Electric Power University, Jilin

[2] Yanbian Power Supply Company of State Grid Jilin Electric Power Supply Co.,Ltd., Yanji

[3] State Grid Qinghai Electric Power Company, Xining

来源：

Dianli Zidonghua Shebei/Electric Power Automation Equipment | 2022年 / 42卷 / 02期

关键词：

Kernel density estimation; Multiple wind farms; Support vector machine; Wind power fluctuation characteristic;

D O I：

10.16081/j.epae.202111015

中图分类号：

学科分类号：

摘要：

Aiming at the problem that there exists new-added wind power installed capacity during the planning period but its corresponding measured wind power output data is lacked, which causes the long-term fluctuation characteristic of output power of multiple wind farms after aggregation in the planning target year is difficult to be accurately grasped and described, a prediction method for long-term fluctuation charac-teristic of output power of multiple wind farms after aggregation is proposed based on improved KDE(Kernel Density Estimation) method and GA-SVM(Support Vector Machine optimized by Genetic Algorithm). The long-term fluctuation characteristic of output power of wind power is described, and the relationship between installed capacity and wind power is analyzed during the aggregation process of multiple wind farms. The improved KDE method is used to generate the probability density curves of output power during the aggregation process of multiple wind farms with different installed capacities. GA-SVM is adopted to establish the probability density varying model of output power after aggregation of multiple wind farms. According to the corresponding relationship between probability distribution and duration power curve, the predicted probability density curve of output power for multiple wind farms after aggregation in the planning target year is inversed so that the duration power curve which can describe the long-term fluctuation characteristic of output power in the planning target year is obtained. Engineering project verifies the practicability and effectiveness of the proposed method. © 2022, Electric Power Automation Equipment Press. All right reserved.

引用

页码：77 / 84

页数：7

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