Opposition-based Modified Differential Evolution Algorithm for Power System Economic Load Dispatch

被引：0
|
作者：
Xia, Honggang [1 ,2 ]
Ding, Weixiang [3 ]
机构：
[1] Shenyang Univ, Informat Engn Coll, Shenyang 110004, Peoples R China
[2] Northeastern Univ, Informat & Sci Coll, Shenyang 110004, Peoples R China
[3] China Criminal Police Univ, Network Informat Ctr, Shenyang 110004, Peoples R China
来源：
MACHINE DESIGN AND MANUFACTURING ENGINEERING II, PTS 1 AND 2 | 2013年 / 365-366卷
关键词：
OMDE; opposed-learning; strategy; convergence; stability;
D O I：
10.4028/www.scientific.net/AMM.365-366.178
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
Opposition-based modified differential evolution algorithm (OMDE) is proposed for solving power System economic load dispatch in this paper. This algorithm integrates the opposition-based learning operation with the crossover operation to enhance the convergence of the algorithm and to prevent the algorithm from being trapped into the local optimum effectively. Besides, we employed a new strategy to dynamic adjust mutation rate (MR) and crossover rate (CR), which is aimed at further improving algorithm performance. Based on 6 units and 13 units power system experiment simulations, the OMDE has demonstrated stronger convergence and stability than original differential (DE) algorithm and other improved algorithms that reported in recent literature.
引用
收藏
页码：178 / +
页数：2
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