Online Clustering Modeling of Large-Scale Photovoltaic Power Plants

被引：0

作者：

Ma, Zhimin ^{[1
]}

Zheng, Jinghong ^{[1
]}

Zhu, Shouzhen ^{[1
]}

Shen, Xinwei ^{[1
]}

Wei, Ling ^{[1
]}

Wang, Xiaoyu ^{[2
]}

Men, Kun ^{[3
]}

机构：

[1] Tsinghua Univ, Dept Elect Engn, Beijing 100084, Peoples R China

[2] Carleton Univ, Dept Elect, Ottawa, ON K1S 5B6, Canada

[3] China Southern Power Grid Corp, Elect Power Res Inst, Guangzhou, Guangdong, Peoples R China

来源：

2015 IEEE POWER & ENERGY SOCIETY GENERAL MEETING | 2015年

关键词：

Clustering index; online modeling; photovoltaic power plant; parameter sensitivity; photovoltaic generation;

D O I：

暂无

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

This paper presents an online clustering modeling method for large-scale photovoltaic (PV) power plants. The proposed method utilizes the defined feature distance of inverter control parameters as the clustering index to derive the equivalent PV plant model. Based on the offline parameter database and the online matching method, the feature distance weighted by online parameter sensitivity is obtained to cluster PV generation units by using the K-means clustering algorithm. The method to acquire equivalent parameters of each clustered PV model is also presented. Simulation results show that the proposed online modeling method is effective and can track the dynamic characteristics of PV power plants accurately.

引用

页数：5

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