Short-Term Load Forecasting Based On Improved Artificial Neural Networks

Short-Term Load Forecasting(STLF) is one of the most important contents of running and dispatching power system .It is a very important aspect of power system to ensure operating safely economically and achieve scientific management in the power system .And it is one part of energy management system as well as a necessary content of the electricity marketplace operation management.This paper firstly gives a summary for present method of load forecasting; Secondly, it has made a deep research into ANN modeling problem, and summarized a set of modeling method and principle; After studying plenty of documents and analyzing various important factors of electric power load the BP network with three-layer structure has been constructed, apply improved BP neural network, create short-term load forecasting models. And the network was trained with historical electric power load data, resulted successful short-term electric power load forecast. And the precision has risen to a higher level compared with the result forecasted by traditional methods, which proves the validity of artificial nerve network in the power load forecast field of short period.