Optimal reactive power dispatch problem using a two-archive multi-objective grey wolf optimizer

被引:82
|
作者
Nuaekaew, Kasem [1 ]
Artrit, Pramin [1 ]
Pholdee, Nantiwat [2 ]
Bureerat, Sujin [2 ]
机构
[1] Khon Kaen Univ, Dept Elect Engn, Robot Engn Res Lab, Fac Engn, Khon Kaen 40002, Thailand
[2] Khon Kaen Univ, Dept Mech Engn, Sustainable Infrastruct Res & Dev Ctr, Fac Engn, Khon Kaen 40002, Thailand
关键词
Two-archive multi-objective grey wolf optimizer; Multi-objective optimal reactive power dispatch; Pareto dominance; Voltage deviation; PARTICLE SWARM OPTIMIZATION; IMPERIALIST COMPETITIVE ALGORITHM; DIFFERENTIAL EVOLUTION ALGORITHM; GENETIC ALGORITHM; VOLTAGE STABILITY; EMISSION; SEARCH; COST; FLOW;
D O I
10.1016/j.eswa.2017.06.009
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, a novel two-archive Multi-Objective Grey Wolf Optimizer (2ArchMGWO) is proposed for solving Multi-Objective Optimal Reactive Power Dispatch (MORPD) problems. The optimizer has been improved from its original Multi-Objective Grey Wolf Optimizer (MGWO) by modifying the reproduction operator and adding the 2-archive concept to the algorithm. It is then implemented on solving MORPD with objective functions being active power loss minimization and voltage profile improvement (voltage deviation minimization). The generator bus voltages, tap setting transformers and shunt reactive power sources or flexible alternating current transmission systems are set as design variables. The proposed algorithm along with other existing multiobjective optimizers are applied to solve three test problems with the standard IEEE 30-bus, IEEE 57-bus, and the IEEE 118-bus power systems. The optimum results obtained from the various optimizers performance are compared based on the hypervolume indicator and they reveal that 2ArchMGWO is clearly superior to the others. (C) 2017 Elsevier Ltd. All rights reserved.
引用
收藏
页码:79 / 89
页数:11
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