Reconfiguration of Radial Distribution Systems with Variable Demands Using the Clonal Selection Algorithm and the Specialized Genetic Algorithm of Chu-Beasley

作     者：Souza, Simone S. F. Romero, Ruben Pereira, Jorge Saraiva, Joao T. 

作者机构：Univ Estadual Paulista Dept Elect Engn UNESP BR-15385000 Ilha Solteira SP Brazil INESC TEC Ave Dr Roberto Frias 378 P-4200465 Oporto Portugal Univ Porto Ave Dr Roberto Frias 378 P-4200465 Oporto Portugal 

出 版 物：《JOURNAL OF CONTROL AUTOMATION AND ELECTRICAL SYSTEMS》 (J. Control Autom. Electr. Syst.)

年 卷 期：2016年第27卷第6期

页      面：689-701页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 08[工学] 0811[工学-控制科学与工程] 

基　　金：CAPES/Brazil CNPq/Brazil INESC TEC 

主　　题：Distribution systems reconfiguration Variable demands Clonal selection algorithm Specialized genetic algorithm of Chu-Beasley Artificial immune systems Metaheuristics 

摘      要：This paper presents two new approaches to solve the reconfiguration problem of electrical distribution systems (EDSs) with variable demands, using the CLONALG and the SGACB algorithms. The CLONALG is a combinatorial optimization technique inspired by biological immune systems, which aims at reproducing the main properties and functions of the system. The SGACB is an optimization algorithm inspired by natural selection and the evolution of species. The reconfiguration problem with variable demands is a complex combinatorial problem that aims at identifying the best radial topology for an EDS, while satisfying all technical constraints at every demand level and minimizing the cost of energy losses in a given operation period. Both algorithms were implemented in C++ and test systems with 33, 84, and 136 nodes, as well as a real system with 417 nodes, in order to validate the proposed methods. The obtained results were compared with results available in the literature in order to verify the efficiency of the proposed approaches.