Metaheuristics approaches to solve combinatorial optimization problems in distribution power systems. An application to Phase Balancing in low voltage three-phase networks

作     者：Schweickardt, Gustavo Gimenez Alvarez, Juan Manuel Casanova, Carlos 

作者机构：Univ Tecnol Nacl CONICET RA-3260 Concepcion Del Uruguay Argentina Univ Nacl San Juan CONICET Fac Ingn Desamparados San Juan Argentina 

出 版 物：《INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS》 (国际电力与能源系统杂志)

年 卷 期：2016年第76卷第Mar.期

页      面：1-10页

核心收录：

学科分类：0808[工学-电气工程] 08[工学] 

主　　题：Metaheuristic algorithm Swarm Intelligence Fuzzy sets Electric distribution Phase Balancing 

摘      要：Metaheuristics algorithms are widely recognized as one of most practical approaches for combinatorial optimization problems. One the most interesting areas of application are the power systems. In particular, Distribution Systems planning and operation. This paper presents some metaheuristics approaches to solve a typical combinatorial optimization problem: the Phase Balancing in Low Voltage Electric Distribution Systems. A model supported in Linear Integer-Mixed Programming is presented, to observe and discussing its limitations. From this, is introduced a new metaheuristic, called Fuzzy Evolutionary Particle Swarm Optimization, based in the Swarm Intelligence Principles and Evolution Strategies, which is extended to fuzzy domain to modeling a multi-objective optimization, by mean of a fuzzy fitness function. A simulation on a real system is presented, and advantages of this approach respect to the Classical Simulated Annealing and Particle Swarm metaheuristics, selected between the most representatives, are evidenced. (C) 2015 Elsevier Ltd. All rights reserved.