基于改进模糊C均值聚类算法的区域集中式光伏发电系统动态分群建模  

Dynamic Clustering Modeling of Regional Centralized Photovoltaic Power Plant Based on Improved Fuzzy C-Means Clustering Algorithm

作　　者：盛万兴[1] 季宇[1] 吴鸣[1] 刘海涛[1] 寇凌峰[1] 

机构地区：[1]中国电力科学研究院,北京市海淀区100192

出　　处：《电网技术》2017年第10期3284-3291,共8页Power System Technology

基　　金：国家重点研发计划项目(分布式可再生能源发电集群并网消纳关键技术及示范应用)(2016YFB0900400);国家电网公司科技项目"多分布式电源并网运行特性与仿真技术"资助~~

摘　　要：以光伏逆变器为核心,提出了一种区域集中式光伏发电系统动态分群建模方法。该方法以光伏逆变器控制参数向量及其对输出轨迹的灵敏度系数为聚类指标,采用改进的模糊C均值(fuzzy c-means algorithm,FCM)聚类算法得到系统在不同工况下光伏发电单元的聚类结果,实现光伏发电单元的动态分群,将同群的光伏发电单元合并成一个等值发电单元,得到区域集中式光伏发电系统的多机等值模型。通过仿真验证及误差分析,结果表明,提出的动态分群建模方法是合理的,建立的多机等值模型兼顾了模型精度和等值化简的需求,具有较高的应用价值。With PV inverter as the core part, a dynamic clustering modeling method of regional centralized photovoltaic（PV） power station is proposed in this paper. This method, taking control parameter vectors of PV inverter and its sensitivity coefficient corresponding to output trajectory as clustering index, adopts improved fuzzy C-means（FCM） algorithm to get clustering results of PV power generation units at different operating conditions. The same cluster of PV power generation units are merged into an equivalent PV power generation unit to establish an equivalent multi-device model of regional centralized PV power plant. Through simulation verification and error analysis, the result shows that the proposed dynamic clustering modeling method is reasonable, and the established equivalent model balances requirements in model accuracy and its equivalent simplification, with high application value.

关 键 词：区域集中式光伏发电系统 逆变器 动态分群 灵敏度分析 FCM算法 

分 类 号：TM721[电气工程—电力系统及自动化]