Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/62756
Title: Investigation of hybrid particle swarm optimization methods for solving transient-stability constrained optimal power flow problems
Authors: Chan, KY
Pong, GTY
Chan, KW 
Keywords: Particle swarm optimization
Genetic algorithms
Transient stability
Optimal power flow
Constrained optimization
Issue Date: 2008
Publisher: International Association of Engineers
Source: Engineering letters, 2008, v. 16, no. 1, p. 61-67 How to cite?
Journal: Engineering letters 
Abstract: In this paper, hybrid particle swarm optimization (PSO) is proposed for solving the challenging multi-contingency transient stability constrained optimal power flow (MC-TSCOPF) problem. The objective of this nonlinear optimization problem is to minimize the total fuel cost of the system and at the same time fulfil the transient stability requirements. The optimal power flow (OPF) with transient stability constraints considered is re-formulated as an extended OPF with additional rotor angle inequality constraints, which is suitable for hybrid PSO to solve. Comparison between various existing hybrid PSO techniques is carried out by solving the New England 39-bus system. Experimental results indicate that the hybrid PSO integrated with the mutation operation of genetic algorithms is better than the other existing hybrid PSO methods in both solution quality and stability. As a result, reasonable solutions can be reached with faster convergence speeds and smaller computational efforts.
URI: http://hdl.handle.net/10397/62756
ISSN: 1816-093X (print)
1816-0948 (online)
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