基于遗传算法和粒子群算法的阀点效应动态经济调度

Mikail Purlu, B. Turkay
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引用次数: 1

摘要

提出了一种基于遗传算法和粒子群算法的动态经济调度问题。DED的主要目的是使发电总成本最小化,以照顾每小时的各种负载需求。DED问题的解决还必须同时提供个体不平等和平等约束。该算法已在两个测试系统中得到应用,并考虑了传输损耗。首先选取3单元试验系统,其次选取考虑阀点效应的10单元试验系统。在测试系统上的仿真结果表明,与文献中使用的其他方法相比,这两种算法获得了最优和可靠的结果。
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Dynamic Economic Dispatch with Valve Point Effect by Using GA and PSO Algorithm
This paper presents Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) technique to solve dynamic economic dispatch (DED) problem. The main purpose of DED is to minimize total cost of generation power to take care of the various load demand in each hour. DED problem solution also must provide individual inequality and equality constraints at the same time. The algorithms have been applied to two test system, taking into account transmission losses. The first of the selected systems is 3 unit test system and the second is 10 unit system considering the valve point effect. Simulation results applied on the test systems show that the two algorithms obtained optimal and reliable results compared to the other methods used in the literature.
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