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Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/129870
Title: 
Artificial immune networks Copt-aiNet and Opt-aiNet applied to the reconfiguration problem of radial electrical distribution systems
Author(s): 
Institution: 
Universidade Estadual Paulista (UNESP)
ISSN: 
0378-7796
Sponsorship: 
  • Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
  • Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
  • Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
Sponsorship Process Number: 
  • CAPES: BEX 3660/14-1
  • FAPESP: 2012/01100-6
Abstract: 
This paper presents two new approaches to solving the reconfiguration problem of electrical distribution systems (EDS) using the Copt-aiNet (Artificial Immune Network for Combinatorial Optimization) and Opt-aiNet (Artificial Immune Network for Optimization) algorithms. The Copt-aiNet and Opt-aiNet algorithms are efficient optimization techniques inspired by the immune network theory (aiNet). The reconfiguration problem is a complex combinatorial problem that aims at identifying the best radial topology for the EDS in order to minimize power losses. A specialized forward/backward radial power flow was used to evaluate each proposed solution proposal in order to determine its power losses and its feasibility regarding the operational constraints of the EDS. The algorithms were developed in the C++ programming language and test systems of 33, 70, 84, 119, and 136 nodes, along with a real system of 417 nodes, were used to validate the proposed method. The obtained results were compared with the best solutions found in the specialized literature in order to verify the efficiency of the proposed algorithms. (C) 2014 Elsevier B.V. All rights reserved.
Issue Date: 
1-Feb-2015
Citation: 
Electric Power Systems Research. Lausanne: Elsevier Science Sa, v. 119, p. 304-312, 2015.
Time Duration: 
304-312
Publisher: 
Elsevier B.V.
Keywords: 
  • Artificial immune networks
  • Copt-aiNet
  • Metaheuristics
  • Opt-aiNet
  • Reconfiguration of electrical distribution systems
  • Reduction of power losses
Source: 
http://www.sciencedirect.com/science/article/pii/S0378779614003666
URI: 
Access Rights: 
Acesso restrito
Type: 
outro
Source:
http://repositorio.unesp.br/handle/11449/129870
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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