Solving Economic Dispatch Using Particle Swarm Optimization Combined with Gaussian Mutation

Aiming at enhancing the diversity of the traditional particle swarm optimization (PSO) algorithm, this paper proposes a method of combining the conventional PSO algorithm with Gaussian mutation (GM) operator to enhance the global search capability and investigate the performance of the proposed hybr...

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Bibliographic Details
Main Author: Sriyanyong, P.
Format: Conference Proceeding
Language:English
Subjects:
Convergence
Cost function
Economics
Generators
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Particle swarm optimization
Programming
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Summary:Aiming at enhancing the diversity of the traditional particle swarm optimization (PSO) algorithm, this paper proposes a method of combining the conventional PSO algorithm with Gaussian mutation (GM) operator to enhance the global search capability and investigate the performance of the proposed hybrid PSO-GM algorithm, while solving the economic dispatch (ED) problem considering non-smooth cost functions. In addition, the Diversity factor is also calculated to verify and compare the searching ability of the proposed PSO-GM with the traditional PSO algorithm. The experimental results show that the incorporation of Gaussian mutation increases the diversity of particles. Namely, it will lead to higher global search capability when compared the results with the traditional PSO algorithm and other algorithms under consideration.
DOI:10.1109/ECTICON.2008.4600572