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Solving the dynamic economic dispatch by a memory-based global differential evolution and a repair technique of constraint handling

机译:通过基于内存的全局差异演化和约束处理的修复技术解决动态经济调度

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In this paper, we propose a memory-based global differential evolution (MGDE) algorithm and a repair technique of constraint handling for the dynamic economic dispatch problems. On the one hand, MGDE modifies the mutation of DE/best/1, and uses a memory pool to provide more candidate solutions for this operation. Moreover, it adopts a randomly generated scale factor in the modified mutation to enhance its exploration capacity. In the crossover, a dynamical crossover rate is introduced to balance MGDE's global and local search capacities. On the other hand, a repair technique is designed for handling three kinds of constraints associated with generator capacity, power balance and generating unit ramp-rate. Moreover, a commonly used penalty function method is subsequently employed to handle the possible constraint violations associated with power balance and prohibited operation zones (POZs). To judge the performance of MGDE and the efficiency of the repair technique, we have solved six well-known DED problems taken from different sources. According to the experimental results, MGDE shows a superior performance in comparison with other improved DEs which also solve these problems. In the mean time, the repair technique of constraint handling has a high efficiency in eliminating or reducing the constraint violations. (C) 2018 Elsevier Ltd. All rights reserved.
机译:在本文中,我们提出了一种基于内存的全局差分进化(MGDE)算法和一种针对动态经济调度问题的约束处理修复技术。一方面,MGDE修改了DE / best / 1的突变,并使用内存池为该操作提供了更多候选解决方案。此外,它在修饰的突变中采用随机产生的比例因子来增强其探测能力。在分频中,引入动态分频率以平衡MGDE的全球和本地搜索能力。另一方面,设计一种维修技术来处理与发电机容量,功率平衡和发电机组斜率相关的三种约束。此外,随后采用常用的惩罚函数方法来处理与功率平衡和禁止的操作区(POZ)相关的可能的约束违规。为了判断MGDE的性能和修复技术的效率,我们解决了六个不同来源的著名DED问题。根据实验结果,与解决了这些问题的其他改进型DE相比,MGDE表现出优越的性能。同时,约束处理的修复技术在消除或减少约束违规方面具有很高的效率。 (C)2018 Elsevier Ltd.保留所有权利。

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