Application and comparison of metaheuristic techniques to reactive power planning problem

Eghbal, Mehdi, Yorino, Naoto, Zoka, Yoshifumi and El-Araby, E. E. (2008) Application and comparison of metaheuristic techniques to reactive power planning problem. IEEJ Transactions on Electrical and Electronic Engineering, 3 6: 721-730. doi:10.1002/tee.20335


Author Eghbal, Mehdi
Yorino, Naoto
Zoka, Yoshifumi
El-Araby, E. E.
Title Application and comparison of metaheuristic techniques to reactive power planning problem
Journal name IEEJ Transactions on Electrical and Electronic Engineering   Check publisher's open access policy
ISSN 1931-4973
1931-4981
Publication date 2008-11
Sub-type Article (original research)
DOI 10.1002/tee.20335
Volume 3
Issue 6
Start page 721
End page 730
Total pages 10
Place of publication Hoboken, NJ, United States
Publisher John Wiley & Sons
Language eng
Abstract This paper presents the application and comparison of metaheuristic techniques to reactive power planning (RPP) problem which involves optimal allocation and combination of to-be-installed VAr sources to satisfy voltage constraints during normal and contingency states for multiple load levels. The main objective of the proposed RPP problem is to minimize the investment cost through balanced installation of SCs and SVCs while keeping a specified security level and minimizing the amount of load shedding. The problem is formulated as a large scale mixed integer nonlinear programming problem, which is a nonsmooth and nondifferentiable optimization problem using conventional optimization techniques and induces lots of local minima. Among the metaheuristic techniques, genetic algorithm (GA), particle swarm optimization (PSO) and evolutionary particle swarm optimization (EPSO) are applied to solve the RPP problem. To investigate the effectiveness of the metaheuristic techniques, the proposed approaches have been successfully tested on IEEE-14 buses, as well as IEEE-57 buses test system. The results obtained are compared and the effectiveness of each technique has been illustrated.
Keyword metaheuristic techniques
reactive power planning
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status Non-UQ

Document type: Journal Article
Sub-type: Article (original research)
Collection: School of Mechanical & Mining Engineering Publications
 
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