A Cluster Evolutionary Algorithm for Power System Economic Load Dispatch Optimization
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摘要: 电力经济负荷分配不仅能保证电力系统安全稳定地运行、延长机组使用寿命，还能节省能源，最大化电力企业的经济效益.此类问题可归为一种具有高维、不可微目标函数及多个非线性约束的数值优化问题.提出了一种新型的全局优化算法——簇类进化算法(cluster evolutionary algorithm, CEA)，并将其应用于求解ELD问题.CEA利用聚类过程在进化个体间构建一定结构的连接关系，并利用这种虚拟的簇类化组织来协调和控制系统的优化计算过程，提高群体的问题空间搜索效率以及抗早熟能力.在仿真实验中13个典型测试函数和3个IEEE系统被用于对CEA的性能进行检验.实验数据显示CEA对13个约束数值优化问题可用较小的计算代价获得较高质量的解，而对3个测试系统的计算结果则要好于目前已报道的最佳解.实验数据的统计分析显示CEA是一种高效的数值优化算法，可作为一种有效的ELD问题求解方法.Abstract: In electric power system, economic load dispatch (ELD) is an important topic, which can not only help to build up safety and stable operation plans and prolong the service life of generating units but also can save energy and maximize the economic benefits of power enterprise. The practical ELD problem has non-smooth cost function with nonlinear constraints which make it difficult to be effectively solved. In this study, a novel global optimization algorithm, cluster evolutionary algorithm (CEA), is proposed to solve ELD problem. In CEA, a virtual cluster organization has been constructed among individuals in order to dynamically adjust the searching process of simulated evolutionary system and improve the optimization efficiency of population. In simulations, the CEA has been applied to 13 testing functions and 3 IEEE testing systems for verifying its feasibility. The experiments have shown the CEA can get high quality solutions with lesser computation cost for 13 testing functions. Compared with the other existing techniques, the proposed algorithm has shown better performance for 3 IEEE systems. Considering the quality of the solution obtained, this method seems to be a promising alternative approach for solving the ELD problem in practical power system.
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