scholarly journals Pareto Optimal Reconfiguration of Power Distribution Systems Using a Genetic Algorithm Based on NSGA-II

Energies ◽  
2013 ◽  
Vol 6 (3) ◽  
pp. 1439-1455 ◽  
Author(s):  
Bogdan Tomoiagă ◽  
Mircea Chindriş ◽  
Andreas Sumper ◽  
Antoni Sudria-Andreu ◽  
Roberto Villafafila-Robles
Keyword(s):  
Genetic Algorithm ◽  
Power Distribution ◽  
Distribution Systems ◽  
Pareto Optimal ◽  
Power Distribution Systems ◽  
Nsga Ii ◽  
Optimal Reconfiguration

scholarly journals An Encoding Technique for Multiobjective Evolutionary Algorithms Applied to Power Distribution System Reconfiguration

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
J. L. Guardado ◽  
F. Rivas-Davalos ◽  
J. Torres ◽  
S. Maximov ◽  
E. Melgoza
Keyword(s):  
Evolutionary Algorithms ◽  
Power Distribution ◽  
Distribution System ◽  
Distribution Systems ◽  
Pareto Optimal ◽  
Pareto Optimal Solutions ◽  
Optimal Solutions ◽  
Power Distribution Systems ◽  
Encoding Scheme ◽  
Power Distribution System

Network reconfiguration is an alternative to reduce power losses and optimize the operation of power distribution systems. In this paper, an encoding scheme for evolutionary algorithms is proposed in order to search efficiently for the Pareto-optimal solutions during the reconfiguration of power distribution systems considering multiobjective optimization. The encoding scheme is based on the edge window decoder (EWD) technique, which was embedded in the Strength Pareto Evolutionary Algorithm 2 (SPEA2) and the Nondominated Sorting Genetic Algorithm II (NSGA-II). The effectiveness of the encoding scheme was proved by solving a test problem for which the true Pareto-optimal solutions are known in advance. In order to prove the practicability of the encoding scheme, a real distribution system was used to find the near Pareto-optimal solutions for different objective functions to optimize.

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