A hybrid GA-PS-SQP method to solve power system valve-point economic dispatch problems

被引：191

作者：

Alsumait, J. S. ^{[1
]}

Sykulski, J. K. ^{[1
]}

Al-Othman, A. K. ^{[2
]}

机构：

[1] Univ Southampton, Elect & Comp Sci Sch, Elect Power Engn Grp, Highfield Southampton SO17 1BJ, England

[2] Publ Author Appl Educ & Training, Coll Tech Studies, Dept Elect Engn, Alrawda 73452, Kuwait

来源：

APPLIED ENERGY | 2010年 / 87卷 / 05期

关键词：

Economic dispatch; Valve-point effect; Direct Search method; Pattern Search method (PS); Genetic Algorithms (GA); Sequential Quadratic Programming (SQP); DIFFERENTIAL EVOLUTION; LOAD DISPATCH; GENETIC ALGORITHM; OPTIMIZATION; CONVERGENCE;

D O I：

10.1016/j.apenergy.2009.10.007

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

This study presents a new approach based on a hybrid algorithm consisting of Genetic Algorithm (GA), Pattern Search (PS) and Sequential Quadratic Programming (SQP) techniques to solve the well-known power system Economic dispatch problem (ED). GA is the main optimizer of the algorithm, whereas PS and SQP are used to fine tune the results of GA to increase confidence in the solution. For illustrative purposes, the algorithm has been applied to various test systems to assess its effectiveness. Furthermore, convergence characteristics and robustness of the proposed method have been explored through comparison with results reported in literature. The outcome is very encouraging and suggests that the hybrid GA-PS-SQP algorithm is very efficient in solving power system economic dispatch problem. (C) 2009 Elsevier Ltd. All rights reserved.

引用

页码：1773 / 1781

页数：9

共 34 条

[21]

Michalewicz Z., 1996, Genetic Algorithms + Data Structures = Evolution Programs, V3rd

[22] A new fuzzy adaptive hybrid particle swarm optimization algorithm for non-linear, non-smooth and non-convex economic dispatch problem [J].