Modern Applied Science · 2010 · 19 citations · 19 references
ArchitectureElectrical EngineeringDesign OptimizationEnergy EconomicsOptimizationCongestion ControlCongestion ManagementElectricity MarketsEvolutionary ComputationEvolutionary OptimizationPopulation-based SearchCongestion OptimizationCongestion ReductionDifferential EvolutionElectricity Market AnalysisEvolutionary AlgorithmsParticle Swarm OptimizationPower System PlanningSolution Quality Assessment
In the emerging restructured power system, the congestion management (CM) has become extremely important in order to ensure the security and reliability of the system. This paper proposes an algorithm for congestion management in a pool based electricity market based on differential evolution (DE). The aim of the proposed work is to minimize deviations from preferred transaction schedules and hence the congestion cost. Numerical results on test system namely IEEE 30 Bus System is presented for illustration purpose and the results are compared with Particle swarm optimization (PSO) in terms of solution quality. The comprehensive experimental results prove that the DE is one among the challenging optimization methods which is indeed capable of obtaining higher quality solutions for the proposed problem.
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