Open AccessDevelopment of Hybrid-Coded EPSO for Optimal Allocation of FACTS Devices in Uncertain Smart Grids
Author(s) -
Hiroyuki Mori,
Hajime Fujita
Publication year - 2011
Publication title -
procedia computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.334
H-Index - 76
ISSN - 1877-0509
DOI - 10.1016/j.procs.2011.08.081
Subject(s) - computer science , mathematical optimization , particle swarm optimization , smart grid , scheme (mathematics) , renewable energy , integer (computer science) , nonlinear system , optimal allocation , variable (mathematics) , algorithm , mathematics , ecology , mathematical analysis , physics , quantum mechanics , electrical engineering , biology , programming language , engineering
This paper presents hybrid-coded EPSO (Evolutionary Particle Swarm Optimization) for optimal allocation of FACTS (Flexible AC Transmission System) devices in uncertain smart grids. The optimal allocation of FACTS devices is one of the important tacks that increase nodal loadability to maximizing the supply of active power at specified nodes in smart grids. However, it is not easy to determine the optimal location and the optimal variable output of FACTS devices due to the nonlinear mixed integer problem. Under such circumstance, it requires a lot of computational time in considering the uncertainties due to renewable energy. In this paper, a hybrid-coded scheme of EPSO is proposed to reduce computational time and maintain solution accuracy. The proposed method has advantage to deal with real-coded and integer-coded variables at the same time. The proposed method is successfully applied to a sample system
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