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A Combination of Genetic Algorithm and Particle Swarm Optimization for Optimal Distributed Generation Location and Sizing in Distribution Systems with Fuzzy Optimal Theory
64
Citations
30
References
2012
Year
Electrical Engineering/Particle Swarm OptimizationEngineeringSmart GridEnergy ManagementFuzzy Optimal TheoryActive Distribution NetworkSmart Distribution NetworkPower System OptimizationGenetic AlgorithmSystems EngineeringDistribution SystemsDistributed Energy GenerationParticle Swarm OptimizationElectric Power DistributionEnergy Distribution
Distributed generation (DG) sources are becoming more prominent in distribution systems due to the incremental demands for electrical energy. Locations and capacities of DG sources have profoundly impacted on the system losses in a distribution network. In this paper, a novel combined genetic algorithm (GA)/particle swarm optimization (PSO) is presented for optimal location and sizing of DG on distribution systems. The objective is to minimize network power losses, to obtain better voltage regulation, and to improve the voltage stability within the framework of system operation and security constraints in radial distribution systems. This multi-objective optimization problem is transformed to single objective problem by employing fuzzy optimal theory. A detailed performance analysis is carried out on 33 and 69 bus systems to demonstrate the effectiveness of the proposed methodology.
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