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An Improved Differential Evolution and Its Industrial Application

机译:改进的差分进化及其工业应用

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In this paper, an improved Differential Evolution (DE) that incorporates double wavelet-based operations is proposed to solve the Economic Load Dispatch (ELD) problem. The double wavelet mutations are applied in order to enhance DE in exploring the solution space more effectively for better solution quality and stability. The first stage of wavelet operation is embedded in the DE mutation operation, in which the scaling factor is governed by a wavelet function. In the second stage, a wavelet-based mutation operation is embedded in the DE crossover operation. The trial population vectors are modified by the wavelet function. A suite of benchmark test functions is employed to evaluate the performance of the proposed DE in different problems. The result shows empirically that the proposed method out-performs signifycantly the conventional methods in terms of convergence speed, solution quality and solution stability. Then the proposed method is applied to the Economic Load Dispatch with Valve-Point Loading (ELD-VPL) problem, which is a process to share the power demand among the online generators in a power system for minimum fuel cost. Two different conditions of the ELD problem have been tested in this paper. It is observed that the proposed method gives satisfactory optimal costs when compared with the other techniques in the literature.
机译:在本文中,提出了一种改进的差分进化算法(DE),该算法结合了基于双小波的运算,以解决经济负荷分配(ELD)问题。应用双小波突变是为了增强DE,以便更有效地探索溶液空间,从而获得更好的溶液质量和稳定性。小波运算的第一阶段嵌入到DE突变运算中,其中比例因子由小波函数控制。在第二阶段,在DE交叉操作中嵌入基于小波的变异操作。通过小波函数修改试验人口向量。使用一套基准测试功能来评估所提出的DE在不同问题中的性能。实验结果表明,该方法在收敛速度,解质量和解稳定性方面均优于常规方法。然后将所提出的方法应用于带阀点负荷的经济负荷分配(ELD-VPL)问题,该过程是在电力系统中的在线发电机之间共享电力需求以最小化燃料成本的过程。本文对ELD问题的两种不同条件进行了测试。可以看出,与文献中的其他技术相比,该方法可提供令人满意的最佳成本。

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