NDLI: Application of metaheuristic methods to reactive power planning: a comparative study for GA, PSO and EPSO

Content Provider	IEEE Xplore Digital Library
Author	Eghbal, M. El-Araby, E.E. Yorino, N. Zoka, Y.
Copyright Year	2007
Description	Author affiliation: Hiroshima Univ., Hiroshima (Eghbal, M.)
Abstract	This paper proposes the application of metaheuristic methods to Reactive Power Planning (RPP). RPP involves optimal allocation of reactive sources to satisfy voltage constraints during normal and contingency states. The main objective of the proposed RPP is to make a trade-off between economy and security by determining the optimal combination of fast and slow controls (load shedding, new slow and fast VAR devices). The overall problem is formulated as a large scale mixed integer nonlinear programming problem. The proposed RPP problem is a combinatorial optimization problem, which cannot be solved easily by conventional optimization methods. Metaheuristic methods are reported to be efficient to solve combinatorial optimization problems. Among the well-known metaheuristic methods, this paper discovers the efficiency of Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Evolutionary PSO (EPSO) in solving the proposed RPP problem. The proposed approaches have been successfully tested on IEEE 14 bus system and a comparative study is illustrated.
Starting Page	3755
Ending Page	3760
File Size	376591
Page Count	6
File Format	PDF
ISBN	9781424409907
DOI	10.1109/ICSMC.2007.4414140
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-10-07
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Reactive power Power system planning Optimization methods Genetic algorithms Particle swarm optimization Power system modeling Power system simulation Simulated annealing System testing Voltage
Content Type	Text
Resource Type	Article

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