A comparison of genetic algorithms with conventional techniques on a spectrum of power economic dispatch problems

被引:11
|
作者
Li, F [1 ]
机构
[1] Univ Bath, Dept Elect & Elect Engn, Bath BA2 7AY, Avon, England
关键词
D O I
10.1016/S0957-4174(98)00018-9
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The mathematical formulation for a power economic dispatch problem can be variously defined according to utilities' central focus. Conventionally, it is common practice to approach different dispatch problems via different techniques. The time and design effort, thus induced in partly altering or entirely replacing the existing technique, is not desirable. This paper demonstrates the robustness of a search technique based on genetic algorithms (GAs) against a number of conventional techniques over a spectrum of power dispatch problems. The problems investigated are in increasing order of complexity. Initially, GAs cannot do better than conventional techniques when the simple problem formulation is encountered, e.g. in the case of static classic Economic Dispatch. However, when problems become progressively more complicated, GAs gradually overtake conventional techniques which are limited mainly by solution accuracy. The outcome of the study clearly shows the robustness and suitability of GAs on the power dispatch problems, and verifies the fact that the more complex the problem is, the more benefit one can obtain from a GA. (C) 1998 Elsevier Science Ltd. All rights reserved.
引用
收藏
页码:133 / 142
页数:10
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