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Application of Genetic Algorithm for Solving Optimum Power Flow Problems

机译:遗传算法在最优潮流计算中的应用

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An efficient and optimum economic operation and planning of electric power generation systems is very important. The basic requirement of power economic dispatch (ED) is to generate adequate electricity to meet load demand at the lowest possible cost under a number ofconstrains. Genetic Algorithms (GA) represents a class of general purpose stochastic search techniques which simulate natural inheritance by genetics. In this paper, the principles of genetics involving natural selection and evolutionary computing applied for producing an economic dispatch. By simulating "Survival of the fittest" among chromosomes, the optimal chromosome is searched by randomized information exchange. In every generation a new set of artificial chromosomes is created using bits and pieces of the fittest of old ones while randomized.
机译:高效有效的经济运行和规划发电系统非常重要。电力经济调度(ED)的基本要求是在多种约束下以尽可能低的成本产生足够的电力以满足负载需求。遗传算法(GA)代表了一类通用的随机搜索技术,可通过遗传学模拟自然遗传。本文将涉及自然选择和进化计算的遗传学原理应用于产生经济调度。通过模拟染色体之间的“适者生存”,可以通过随机信息交换来搜索最佳染色体。在每一代中,使用旧的优胜劣汰随机创建的一组新的人造染色体。

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