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An Improved Particle Swarm Optimization Algorithm for Unit Commitment
36
Citations
8
References
2008
Year
Unknown Venue
Unit CommitmentEngineeringMulti-particle Swarm OptimizationHybrid AlgorithmEnergy ManagementFirefly AlgorithmIntelligent OptimizationGenetic AlgorithmSystems EngineeringHybrid Optimization TechniqueCombinatorial OptimizationOperations Research
This paper presents a new approach via multi-particle swarm optimization (MPSO) to solve the unit commitment (UC) problem. A new strategy which can generate feasible particles and make the search space narrow within the feasible solutions is presented. Some particle swarms are generated by the new strategy, and location optimum solutions are searched in each particle swarm, then a new particle swarm is made up of location optimum solutions, and the global optimum solution is searching in this new particle swarm. The application of the new generating strategy in PSO can efficiently improve the global searching capability and escape from local minima. The simulation results show that the method is more efficient than genetic algorithm, and could obtain the global optimumsolution more probably.
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