Short-term Load Forecasting Based on Chaos Theory and RBF Neural Network

摘要：

Power system load is a nonlinear time series, for the complexity and nonlinear of power systems loads, this paper combines the idea of chaos theory, make full use of data in the reconstruction phase space power load based on the load of forecast, due to the approximation capability of neural networks with superior predictive ability, the use of RBF neural network-based method and Matlab simulation, the simulation shows that such a prediction algorithm to obtain good results.

关键词： load forecasting chaos RBF neural network

作者: Zhenzhen Yuan ShuangLiu LinyanXue Xiu e Yuan

作者单位: School of Business and Administration North China Electric Power University Baoding, China Department of Quality Technology Supervision Hebei University Baoding, China

会议类型: 国际会议

会议名称: 2011 Seventh International Conference on Natural Computation(第七届自然计算国际会议 ICNC 2011)

会议地点: 上海

会议语种:英文

页码: 541-543

在线出版日期: 2011-07-26（万方平台首次上网日期，不代表论文的发表时间）