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

Eghbal, Mehdi, El-Araby, E. E., Yorino, Naoto and Zoka, Yoshifumi (2007). Application of metaheuristic methods to reactive power planning: A comparative study for GA, PSO and EPSO. In: , Conference proceedings - IEEE International Conference on Systems, Man and Cybernetics. IEEE International Conference on Systems, Man and Cybernetics (SMC 2007), Montreal, Canada, (3360-3365). 7-10 October 2007.


Author Eghbal, Mehdi
El-Araby, E. E.
Yorino, Naoto
Zoka, Yoshifumi
Title of paper Application of metaheuristic methods to reactive power planning: A comparative study for GA, PSO and EPSO
Conference Paper Type Fully Published Paper
Conference name IEEE International Conference on Systems, Man and Cybernetics (SMC 2007)    (ERA 2010 Rank B)
DOI 10.1109/ICSMC.2007.4414140
Conference location Montreal, Canada
Conference dates 7-10 October 2007
Proceedings title Conference proceedings - IEEE International Conference on Systems, Man and Cybernetics   Check publisher's open access policy
Journal name 2007 Ieee International Conference On Systems, Man and Cybernetics, Vols 1-8   Check publisher's open access policy
Place published New York, United States
Publisher IEEE
Publication date 2007
ISBN 9781424409914; 1424409918
ISSN 1062-922X
Start page 3360
End page 3365
Total pages 5
Language eng
Abstract/Summary 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.
Q-Index Code E1
Q-Index Status Provisional Code
Institutional Status Non-UQ

Document type: Conference Paper
Sub-type: Fully Published Paper
Collection: School of Mechanical & Mining Engineering Publications
 
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Created: Thu, 16 Dec 2010, 09:00:12 EST