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Comparison between Harmony Search Algorithm, Genetic Algorithm and Particle Swarm Optimization in Economic Power Dispatch

机译:经济分配中和谐搜索算法,遗传算法和粒子群算法的比较

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摘要

This paper presents a solution of economic power dispatch problem using Harmony Search (HS) algorithm. The method easily takes care of equality and inequality constraints of the power dispatch problem to find the optimal solution. To show its efficiency, the algorithm is applied to IEEE 118-bus power system having 54 generating units. The problem is also solved by Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) techniques. Results have shown that Harmony Search method gives minimum cost of production of real power and minimum power loss in the system as compared to Genetic Algorithm and Particle Swarm Optimization. This shows the robustness and effectiveness of this method. Moreover, cost of real power generation in dollar per hour per megawatt output of each generator is calculated to identify the least to most expensive generator in the system.
机译:本文提出了一种使用和谐搜索(HS)算法的经济权力分配问题解决方案。该方法可以轻松解决电力分配问题的等式和不等式约束,从而找到最佳解决方案。为了显示其效率,该算法被应用于具有54个发电单元的IEEE 118总线电力系统。遗传算法(GA)和粒子群优化(PSO)技术也解决了该问题。结果表明,与遗传算法和粒子群优化算法相比,和声搜索方法在系统中产生的有功功率成本最小,而功率损耗最小。这表明了该方法的鲁棒性和有效性。此外,计算每台发电机每兆瓦输出每小时的实际发电成本(以美元/小时为单位),以确定系统中最便宜的发电机到最昂贵的发电机。

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