Optimal economic power dispatch using genetic algorithms

M. Yoshimi, K. Swarup, Y. Izui
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引用次数: 22

Abstract

This paper presents the genetic algorithm approach to adaptive optimal economic dispatch of electrical power systems. Genetic algorithms, also termed as the machine learning approach to artificial intelligence, are powerful stochastic optimization techniques with potential features of random search, hill climbing, statistical sampling and competition. Genetic algorithmic approach to power system optimization, as reported here for a case of economic power dispatch, consists essentially of minimizing the objective function while gradually satisfying the constraint relations. The unique problem solving strategy of the genetic algorithm and their suitability for power system optimization is described. The advantages of the genetic algorithmic approach in terms of problem reduction, flexibility and solution methodology are also discussed. The suitability of the proposed approach is described for the case of a 15 generator power system.<>
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基于遗传算法的最优经济电力调度
提出了电力系统自适应最优经济调度的遗传算法方法。遗传算法,也被称为人工智能的机器学习方法,是一种强大的随机优化技术,具有随机搜索、爬坡、统计抽样和竞争的潜在特征。本文以电力经济调度为例,采用遗传算法进行电力系统优化,其本质是在逐步满足约束关系的同时使目标函数最小化。介绍了遗传算法独特的求解策略及其在电力系统优化中的适用性。讨论了遗传算法在问题简化、灵活性和求解方法等方面的优势。对于一个15台发电机的电力系统,描述了所提出的方法的适用性。
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