Application of particle swarm optimization technique and its variants to generation expansion planning problem

This paper presents the application of particle swarm optimization (PSO) technique and its variants to least-cost generation expansion planning (GEP) problem. The GEP problem is a highly constrained, combinatorial optimization problem that can be solved by complete enumeration. PSO is one of the swa...

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Bibliographic Details
Published in:Electric power systems research 2004-08, Vol.70 (3), p.203-210
Main Authors: Kannan, S., Slochanal, S.Mary Raja, Subbaraj, P., Padhy, Narayana Prasad
Format: Article
Language:English
Subjects:
Combinatorial optimization
Composite PSO
Constriction factor approach
Differential evolution
Generation expansion planning
Particle swarm optimization
Penalty function approach
Stretched PSO
Swarm intelligence
Virtual mapping procedure
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Summary:This paper presents the application of particle swarm optimization (PSO) technique and its variants to least-cost generation expansion planning (GEP) problem. The GEP problem is a highly constrained, combinatorial optimization problem that can be solved by complete enumeration. PSO is one of the swarm intelligence (SI) techniques, which use the group intelligence behavior along with individual intelligence to solve the combinatorial optimization problem. A novel ‘virtual mapping procedure’ (VMP) is introduced to enhance the effectiveness of the PSO approaches. Penalty function approach (PFA) is used to reduce the number of infeasible solutions in the subsequent iterations. In addition to simple PSO, many variants such as constriction factor approach (CFA), Lbest model, hybrid PSO (HPSO), stretched PSO (SPSO) and composite PSO (C-PSO) are also applied to test systems. The differential evolution (DE) technique is used for parameter setting of C-PSO. The PSO and its variants are applied to a synthetic test system of five types of candidate units with 6- and 14-year planning horizon. The results obtained are compared with dynamic programming (DP) in terms of speed and efficiency.
ISSN:0378-7796
1873-2046
DOI:10.1016/j.epsr.2003.12.009