Multi-objective Evolutionary Algorithm with Discrete Differential Mutation Operator for Service Restoration in Large-Scale Distribution Systems

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• 作者：Danilo Sipoli Sanches (16)
  Telma Worle de Lima (17)
  Jo茫o Bosco A. London Junior (18)
  Alexandre Cl谩udio Botazzo Delbem (19)
  Ricardo S. Prado (20)
  Frederico G. Guimar茫es (21)
  
  16. Federal Technological University of Paran谩 ; Corn茅lio Proc贸pio ; Brazil
  17. Institute of Informatics ; Federal University of Goias ; UFG ; Goi芒nia ; Brazil
  18. S茫o Carlos Engineering School of University of S茫o Paulo ; S茫o Carlos ; SP ; Brazil
  19. Institute of Mathematics and Computer Science ; University of S茫o Paulo ; S茫o Carlos ; SP ; Brazil
  20. Federal Institute of Minas Gerais ; Ouro Preto ; Brazil
  21. Department of Electrical Engineering ; Universidade Federal de Minas Gerais ; UFMG ; Belo Horizonte ; Brazil
  
• 刊名：Lecture Notes in Computer Science
• 出版年：2015
• 出版时间：2015
• 年：2015
• 卷：9019
• 期：1
• 页码：498-513
• 全文大小：338 KB
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  5. Delbem, ACB, Carvalho, A, Policastro, CA, Pinto, AKO, Honda, K, Garcia, AC Node-depth encoding for evolutionary algorithms applied to network design. In: Deb, K, Tari, Z eds. (2004) Genetic and Evolutionary Computation 鈥?GECCO 2004. Springer, Heidelberg, pp. 678-687 CrossRef
  6. Sanches, DS, Junior, JBAL, Delbem, ACB (2014) Multi-objective evolutionary algorithm for single and multiple fault service restoration in large-scale distribution systems. Electric Power Systems Research 110: pp. 144-153 CrossRef
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  8. Gois, MM, Sanches, DS, Martins, J, Junior, JBAL, Delbem, ACB Multi-objective evolutionary algorithm with node-depth encoding and strength pareto for service restoration in large-scale distribution systems. In: Purshouse, RC, Fleming, PJ, Fonseca, CM, Greco, S, Shaw, J eds. (2013) Evolutionary Multi-Criterion Optimization. Springer, Heidelberg, pp. 771-786 CrossRef
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  16. Sanches, D., Lima, T., Santos, A., Delbem, A., London, J.: Node-depth encoding with recombination for multi-objective evolutionary algorithm to solve loss reduction problem in large-scale distribution systems. In: Power and Energy Society General Meeting, pp. 1鈥?. IEEE, July 2012
  17. Prado, RS, Silva, RCP, Guimar aes, FG, Neto, OM (2010) A new differential evolution based metaheuristic for discrete optimization. International Journal of Natural Computing Research 1: pp. 15-32 CrossRef
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• 作者单位：Evolutionary Multi-Criterion Optimization
• 丛书名：978-3-319-15891-4
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence and Robotics
  Computer Communication Networks
  Software Engineering
  Data Encryption
  Database Management
  Computation by Abstract Devices
  Algorithm Analysis and Problem Complexity
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1611-3349

文摘

The network reconfiguration for service restoration in distribution systems is a combinatorial complex optimization problem that usually involves multiple non-linear constraints and objectives functions. For large networks, no exact algorithm has found adequate restoration plans in real-time, on the other hand, Multi-objective Evolutionary Algorithms (MOEA) using the Node-depth enconding (MEAN) is able to efficiently generate adequate restorations plans for relatively large distribution systems. This paper proposes a new approach that results from the combination of MEAN with characteristics from the mutation operator of the Differential Evolution (DE) algorithm. Simulation results have shown that the proposed approach, called MEAN-DE, properly designed to restore a feeder fault in networks with significant different bus sizes: 3,860 and 15,440. In addition, a MOEA using subproblem Decomposition and NDE (MOEA/D-NDE) was investigated. MEAN-DE has shown the best average results in relation to MEAN and MOEA/D-NDE. The metrics \(R_2\) , \(R_3\) , Hypervolume and \(\epsilon \) -indicators were used to measure the quality of the obtained fronts.