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《Journal of Electric Power Science and Technology》 2008-01
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Short-term load forecast with QPSO-RBFNN and fuzzy logic for power systems

LI Pan-Rong1,HUA Wei-Dong2(1.Wuxi Radio and TV University,Wuxi 214021,China;2.Wuxi Power Supply Company,Wuxi 214061,China)  
Based on Short-term load forecast method with Radial Basis Function Neural Network(RBFNN)for power systems,a novel QPSO(quantum particle swarm optimization) algorithm is proposed for optimizing the weight of RBFNN,fuzzy theory is applied to corrected the forecast model,and a short-term load forecast method with QPSO-RBFNN and fuzzy logic is proposed in this paper.Some cases simulation results show that the method is with fast convergence,high precision,and application foreground.
【CateGory Index】: TM715
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