Hybrid Mean-Variance Mapping Optimization for Non-Convex Economic Dispatch Problems

作     者：Khoa, Truong H. Vasant, Pandian M. Singh, Balbir Mahinder Singh Dieu, V. N. 

作者机构：Univ Teknol PETRONAS Dept Elect & Elect Engn Seri Iskandar Malaysia Ton Duc Thang Univ Fac Elect & Elect Engn Ho Chi Minh City Vietnam Univ Teknol PETRONAS Dept Fundamental & Appl Sci Seri Iskandar 32610 Perak Malaysia HCMC Univ Technol Dept Power Syst Ho Chi Minh City Vietnam 

出 版 物：《INTERNATIONAL JOURNAL OF SWARM INTELLIGENCE RESEARCH》 (国际群智能研究杂志)

年 卷 期：2017年第8卷第4期

页      面：34-59页

核心收录：

学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：GA scheme of Universiti Teknologi PETRONAS 

主　　题：Economic Dispatch Mean-Variance Mapping Optimization Multiple Fuels Prohibited Operating Zone ValvePoint Effects 

摘      要：The economic dispatch (ED) is one of the important optimization problems in power system generation for fuel cost saving. This paper proposes a hybrid variant of mean-variance mapping optimization (MVMO-SH) for solving such problem considering the non-convex objective functions. The new proposed method is a hybrid variant of the original mean-variance mapping optimization algorithm (MVMO) with the embedded local search and multi-parent crossover to enhance its global search ability and improve solution quality for optimization problems. The proposed MVMO-SH is tested on different non-convex ED problem including valve point effects, multiple fuels and prohibited operating zones characteristics. The result comparisons from the proposed method with other methods in the literature have indicated that the proposed method is more robust and provides better solution quality than the others. Therefore, the proposed MVMO-SH is a promising method for solving the complex ED problems in power systems.