Improved differential evolution algorithms for handling economic dispatch optimization with generator constraints
Improved differential evolution algorithms for handling economic dispatch optimization with generator constraints
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DOI：
10.1016/j.enconman.2006.11.007
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发表时间：
2007-05
影响因子：
10.4
通讯作者：
L. Coelho;V. Mariani
中科院分区：
文献类型：
--
作者：
L. Coelho;V. Mariani
基于进化算法的全局优化可以作为许多工程优化问题的重要组成部分。进化算法在求解电力系统非线性、不可微和多模态优化问题方面取得了可喜的成果。差分进化算法是求解连续空间函数优化问题的一种简单有效的进化算法。据报道，在测试基准和真实的世界问题时，它的表现优于搜索引擎。本文提出了改进的DE算法，用于解决经济负荷分配问题，考虑到非线性发电机的功能，如斜坡率限制和禁止操作区的电力系统运行。DE算法及其变体验证了两个测试系统组成的6和15热单位。各种DE方法优于其他国家的最先进的算法在文献中报道的解决负荷分配问题的发电机约束。
Global optimization based on evolutionary algorithms can be used as the important component for many engineering optimization problems. Evolutionary algorithms have yielded promising results for solving nonlinear, non-differentiable and multi-modal optimization problems in the power systems area. Differential evolution (DE) is a simple and efficient evolutionary algorithm for function optimization over continuous spaces. It has reportedly outperformed search heuristics when tested over both benchmark and real world problems. This paper proposes improved DE algorithms for solving economic load dispatch problems that take into account nonlinear generator features such as ramp rate limits and prohibited operating zones in the power system operation. The DE algorithms and its variants are validated for two test systems consisting of 6 and 15 thermal units. Various DE approaches outperforms other state of the art algorithms reported in the literature in solving load dispatch problems with generator constraints.