Multi-objective backtracking search algorithm for economic emission dispatch problem

被引:102
|
作者
Modiri-Delshad, Mostafa [1 ,3 ]
Abd Rahim, Nasrudin [1 ,2 ]
机构
[1] Wisma R&D Univ Malaya, UM Power Energy Dedicated Adv Ctr UMPEDAC, Level 4, Kuala Lumpur 59990, Malaysia
[2] King Abdulaziz Univ, Renewable Energy Res Grp, Jeddah 21589, Saudi Arabia
[3] Univ Malaya, Fac Engn, Dept Elect Engn, Kuala Lumpur 50603, Malaysia
关键词
Environmental concerns; Economic dispatch; Non-convex; Transmission loss; Backtracking search algorithm (BSA); ENVIRONMENTAL/ECONOMIC POWER DISPATCH; PARTICLE SWARM OPTIMIZATION; LOAD DISPATCH; EVOLUTIONARY ALGORITHMS; DIFFERENTIAL EVOLUTION; GENETIC ALGORITHM; SYSTEM;
D O I
10.1016/j.asoc.2015.11.020
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper presents the application of backtracking search algorithm (BSA) for solving an economic/emission dispatch (EED) problem as a multi-objective optimization problem. BSA is a newly developed evolutionary algorithm with one control parameter to solve numerical optimization problems. It utilizes crossover and mutation operators to advance optimization toward the optimal. The multi-objective BSA developed and presented in this paper uses an elitist external archive to store non dominated solutions known as pareto front. The problem of EED is also solved by weighted sum method, which combines both objectives of the problem into a single objective. Three test systems are the case studies verifying the effectiveness of BSA. The results are compared with those of other methods in literatures and confirm the high performance of BSA. (C) 2015 Elsevier B.V. All rights reserved.
引用
收藏
页码:479 / 494
页数:16
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