EA Techniques for Optimal Power Flow. Parameter Tuning by Mathematical Test Functions

被引：0
|
作者：
Solomonesc, Florin [1 ]
Barbulescu, Constantin [1 ]
Kilyeni, Stefan [1 ]
Pop, Oana [1 ]
Cornoiu, Marius [1 ]
Olariu, Adrian [1 ]
机构：
[1] Politehn Univ Timisoara, Timisoara, Romania
来源：
ACTA POLYTECHNICA HUNGARICA | 2014年 / 11卷 / 01期
关键词：
evolutionary algorithm; test function; crossover rate; mutation rate; random mutation; variable step mutation; EXPANSION; NETWORK; ALGORITHM; GA;
D O I：
暂无
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
The goal of this paper is to establish the best values for evolutionary algorithm main parameters. To do this, a real coded algorithm is tested on Rosenbrock, Schwefel and Rastrigin functions. Different genetic operators' implementation ways are described. Several numbers of variables have been analyzed. An original software tool has been developed in a Matlab environment. The most complex three mathematical test functions have been implemented within the software tool; these functions are considered as ideal for studying the behaviour of the algorithm. The settings established are crucial in the optimal power flow computing and the transmission network expansion planning, by means of EA techniques.
引用
收藏
页码：153 / 172
页数：20
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