Optimal reactive power planning using evolutionary algorithms: A comparative study for evolutionary programming, evolutionary strategy, genetic algorithm, and linear programming

被引：173
|
作者：
Lee, KY [1 ]
Yang, FF [1 ]
机构：
[1] Penn State Univ, Dept Elect Engn, University Pk, PA 16802 USA
来源：
IEEE TRANSACTIONS ON POWER SYSTEMS | 1998年 / 13卷 / 01期
基金：
美国国家科学基金会;
关键词：
optimal reactive power planning; evolutionary algorithms; genetic algorithm;
D O I：
10.1109/59.651620
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
This paper presents a comparative study for three evolutionary algorithms (EAs) to the Optimal Reactive Power Planning (ORPP) problem: evolutionary programming, evolutionary strategy, and genetic algorithm. The ORPP problem is decomposed into P- and Q-optimization modules, and each module is optimized by the EAs in an iterative manner to obtain the global solution. The EA methods for the ORPP problem are evaluated against the IEEE 30-bus system as a common testbed, and the results are compared against each other and with those of linear programming.
引用
收藏
页码：101 / 108
页数：8
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