Improving Power System Reliability Calculation Efficiency With EPSO Variants

被引：51

作者：

Miranda, Vladimiro ^{[1
,2
]}

Carvalho, Leonel de Magalhaes ^{[1
,2
]}

da Rosa, Mauro Augusto ^{[1
,2
]}

Leite da Silva, Armando M. ^{[3
]}

Singh, Chanan ^{[4
]}

机构：

[1] INESC Porto, Oporto, Portugal

[2] Univ Porto, FEUP, Fac Engn, P-4100 Oporto, Portugal

[3] Univ Fed Itajuba, Inst Elect Engn, Itajuba, Brazil

[4] Texas A&M Univ, Dept Elect & Comp Engn, College Stn, TX 77843 USA

来源：

IEEE TRANSACTIONS ON POWER SYSTEMS | 2009年 / 24卷 / 04期

关键词：

Evolutionary algorithms; Monte Carlo sampling; particle swarm; population-based methods; reliability analysis; MONTE-CARLO-SIMULATION; GENERATION;

D O I：

10.1109/TPWRS.2009.2030397

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This paper presents an application of evolutionary particle swarm optimization (EPSO)-based methods to evaluate power system reliability. Population-based (PB) methods appear as competitors to the traditional Monte Carlo simulation (MCS), because they are computationally efficient in estimating a variety of reliability indices. The work reported in this paper demonstrates that EPSO variants can focus the search in the region of the state space where contributions to the formation of a reliability index may be found, instead of conducting a blind sampling of the space. The results obtained with EPSO are compared to MCS and with other PB methods.

引用

页码：1772 / 1779

页数：8

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