The Reliability Evaluation Method of Generation System Based on the Importance Sampling Method and States Clustering

被引：13

作者：

Zhong, Sheng ^{[1
]}

Yang, Tianmeng ^{[2
]}

Wu, Yaowu ^{[2
]}

Lou, Suhua ^{[1
]}

Li, Taijun ^{[1
]}

机构：

[1] Cent Southern China Elect Power Design Inst, Wuhan 430074, Hubei, Peoples R China

[2] Huazhong Univ Sci & Technol, State Key Lab Adv Electromagnet Engn & Technol, Wuhan 430074, Hubei, Peoples R China

来源：

2017 2ND INTERNATIONAL CONFERENCE ON ADVANCES ON CLEAN ENERGY RESEARCH (ICACER 2017) | 2017年 / 118卷

关键词：

Monte Carlo simulation; importance sampling method; reliability evaluation method; states clustering;

D O I：

10.1016/j.egypro.2017.07.031

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

To improve the reliability evaluation efficiency of large scale power system, an efficient reliability evaluation method of generation system is proposed in this paper. It can improve the calculation efficiency both in the sampling method and states evaluation. Firstly, the importance sampling method is used to replace the conventional Monte Carlo sampling method, which can accelerate the convergence speed of iteration calculation. Secondly, the states clustering method is proposed to get several typical generating states to replace all sampling states, which can improve the calculation speed. Finally, the simulations based on the IEEE RTS-79 generating system and the actual power system are carried out, and the efficiency and accuracy of this evaluation method in this paper are verified. (C) 2017 The Authors. Published by Elsevier Ltd

引用

页码：128 / 135

页数：8

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