The development of smart grid and electricity market requires more accurate and faster short-term load forecasting. Aiming at the problems of Radial Basis Function (RBF) network in electric system short term load forecasting, a novel algorithm integrated the advantages of RBF and Quantum Particle Swarm Optimization algorithm (QPSO) is proposed to improve the short-term load forecasting accuracy and speed. In this study, radial basis function network is trained by QPSO. After confirmed the nodes number of hidden layer, all network parameters are coded to individual particles to optimize learnin...
