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Application of genetic algorithms to service restoration in distribution systems
Author(s) -
Fukuyama Yoshikazu,
Ueki Yoshiteru
Publication year - 1995
Publication title -
electrical engineering in japan
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.136
H-Index - 28
eISSN - 1520-6416
pISSN - 0424-7760
DOI - 10.1002/eej.4391150303
Subject(s) - genetic algorithm , mathematical optimization , computer science , optimization problem , combinatorial optimization , artificial neural network , service (business) , fuzzy logic , power (physics) , algorithm , mathematics , artificial intelligence , physics , economy , quantum mechanics , economics
Service restoration in distribution systems can be formulated as a combinatorial optimization problem to determine power sources for each load considering radial network constraints and power source limits. Until now, the problem has been considered using conventional methods, e.g., the branch‐and‐bounds method, expert system, neural networks, and fuzzy reasoning. Recently, Genetic Algorithms (GA) have been recognized as one of the efficient methods for solving large combinatorial optimization problems. The method can perform parallel search, and can more easily search optimal solutions. This paper presents an application of GA to service restoration in distribution systems. The feasibility of the proposed method is demonstrated on a typical distribution system model. The result shows that the method can solve the problem efficiently, and this tendency becomes dominant by increasing problem dimensions.