Enhanced particle swarm optimizer for power system applications | IEEE Conference Publication | IEEE Xplore

Enhanced particle swarm optimizer for power system applications


Abstract:

Power system networks are complex systems that are highly nonlinear and non-stationary, and therefore, their performance is difficult to optimize using traditional optimi...Show More

Abstract:

Power system networks are complex systems that are highly nonlinear and non-stationary, and therefore, their performance is difficult to optimize using traditional optimization techniques. This paper presents an enhanced particle swarm optimizer for solving constrained optimization problems for power system applications, in particular, the optimal allocation of multiple STATCOM units. The study focuses on the capability of the algorithm to find feasible solutions in a highly restricted hyperspace. The performance of the enhanced particle swarm optimizer is compared with the classical particle swarm optimization (PSO) algorithm, genetic algorithm (GA) and bacterial foraging algorithm (BFA). Results show that the enhanced PSO is able to find feasible solutions faster and converge to feasible regions more often as compared with other algorithms. Additionally, the enhanced PSO is capable of finding the global optimum without getting trapped in local minima.
Date of Conference: 21-23 September 2008
Date Added to IEEE Xplore: 07 November 2008
ISBN Information:
Conference Location: St. Louis, MO, USA

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