Particle swarm optimization-based neural network model for short-term load forecasting

作者：Lu Ning^*; Zhou Jian Zhong; He Yao Yao

来源：Power System Protection and Control, 2010, 38(12): 65-68.

• LabViEW
• Load forecasting
• Load forecasting model
• Neural network model
• Optimal model
• Radial basis function
• Radial basis function neural networks
• Radial basis functions
• Random optimization method
• RBF model
• Short term load forecasting
• Simulation result
• Weighting factors

In order to improve the precision of short-term load forecasting, this paper proposes a new load forecasting model based on Particle Swarm Optimization(PSO). PSO is a novel random optimization method which has extensive capability of global optimization. PSO is used to optimize the weighting factor of Radial Basis RBF)neural network and the optimal model is applied to forecast load. LabView and MATLAB are employed to implement the model for short-term load forecasting. The simulation results show that the load forecasting model optimized by PSO is more accurate than the traditional RBF model.

• 出版日期2010