Title :
Online clustering modeling of large-scale photovoltaic power plants
Author :
Zhimin Ma;Jinghong Zheng;Shouzhen Zhu;Xinwei Shen; Ling Wei;Xiaoyu Wang; Kun Men
Author_Institution :
Dept. of Electrical Engineering, Tsinghua University, Beijing, China
fDate :
7/1/2015 12:00:00 AM
Abstract :
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.
Keywords :
"Inverters","Sensitivity","Power system dynamics","Photovoltaic systems","Indexes"
Conference_Titel :
Power & Energy Society General Meeting, 2015 IEEE
DOI :
10.1109/PESGM.2015.7285745