Optimal Power Flow Solution Using Evolutionary Computation Techniques

被引：0
|
作者：
Suharto, M. N. [1 ]
Hassan, M. Y. [1 ]
Majid, M. S. [1 ]
Abdullah, M. P. [1 ]
Hussin, F. [1 ]
机构：
[1] Univ Teknol Malaysia, Fac Elect Engn, Ctr Elect Energy Syst, Johor Baharu 81310, Malaysia
来源：
2011 IEEE REGION 10 CONFERENCE TENCON 2011 | 2011年
关键词：
Optimal Power Flow; Evolutionary Computation; Genetic Algorithm; Particle Swarm Optimization; Differential Evolution; DISPATCH; NEWTON;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
This paper presents evolutionary computation (EC) techniques and discusses their applicability to the optimal power flow (OPF) problem. The power flow problem is optimized to find the minimum fuel cost of all generating units while maintaining an acceptable system performance in terms of limits on the power outputs of generators, bus voltage and line flow. Different EC techniques such as genetic algorithm (GA), particle swarm optimization (PSO) and differential evolution (DE) are applied to solve the OPF problem for IEEE 30-bus system. The results are compared with the OPF solution obtained from MATPOWER that employs sequential quadratic programming to prove the effectiveness of the EC techniques. The computational results show that EC techniques work effectively and applicable to the OPF problem.
引用
收藏
页码：113 / 117
页数：5
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