Meta heuristic search algorithms for short-term hydrothermal scheduling

被引：0

作者：

Sinha, Nidul ^{[1
]}

Lai, Loi-Lei ^{[2
]}

机构：

[1] NIT, Dept Elect Engn, Silchar, India

[2] City Univ London, Energy Syst Grp, London, England

来源：

PROCEEDINGS OF 2006 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7 | 2006年

关键词：

fast evolutionary programming; particle swarm optimization; hydro-thermal scheduling;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper presents the performances of meta heuristic search algorithms in solving short-term hydro thermal scheduling problems. Meta heuristic search algorithms like GA, CEP, FEP, IFEP and PSO have been developed for hydrothermal scheduling problems. The performances of the algorithms are demonstrated on a test case. It has been observed that all the algorithms are capable of finding very nearly global solutions within a reasonable time but PSO algorithm was found to be the most efficient amongst them in terms of convergence rate, solution time and success rate.

引用

页码：4050 / +

页数：3

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