ISSN 1000-1239 CN 11-1777/TP

• 人工智能 •

一种基于簇类进化的电力经济负荷分配优化算法

1. (西安邮电大学计算机学院 西安 710121) (chenhao@xupt.edu.cn)
• 出版日期: 2016-07-01
• 基金资助:
国家自然科学基金项目(61203311,61105064)；陕西省教育厅科研计划项目(2013JK1183,2014JK1667)

A Cluster Evolutionary Algorithm for Power System Economic Load Dispatch Optimization

Chen Hao, Pan Xiaoying, Zhang Jie

1. (School of Computer Science and Technology, Xi’an University of Posts & Telecommunications, Xi’an 710121)
• Online: 2016-07-01

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.