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A NOVEL MULTI-OBJECTIVE GENETIC ALGORITHM FOR ECONOMIC POWER DISPATCH

机译:一种新的经济权力遗传算法

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A fuzzy multi-objective genetic algorithm (FMOGA) approach for the multi-objective economic power dispatch problem is presented in this paper. The economic power dispatch problem is a non-linear constrained multi-objective optimization problem. The proposed FMOGA approach handles the problem as a multi-objective problem with competing and non-commensurable fuel cost, emission and system active power loss objectives. The proposed FMOGA employs a fuzzy evaluation factor to the fitness function of MOGA, which can prevent the premature convergence of the genetic algorithm. As well FMOGA can deal with "gene drift" caused by large bound of objectives. Several optimization runs of the proposed FMOGA approach are carried out on the standard IEEE 30-bus test system. The results demonstrate the capabilities of the proposed approach to generate well-distributed Pareto-optimal non-dominated solutions of the multi-objective economic power dispatch.
机译:本文提出了一种模糊多目标遗传算法(FMoGA)多目标经济派遣问题的方法。经济权力调度问题是非线性约束的多目标优化问题。拟议的Fmoga方法将问题作为多目标问题,具有竞争和不可比较的燃料成本,排放和系统有源功率损耗目标。所提出的Fmoga采用模糊评价因子,对MOGA的健身功能,可以防止遗传算法的过早收敛。由于Fmoga可以处理由宗旨的大界引起的“基因漂移”。在标准IEEE 30-Bus测试系统上执行了所提出的FMoGA方法的几个优化运行。结果证明了提出的方法产生了多目标经济权力派遣的良好分布式静态的非主导解决方案的能力。

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