会议专题

Short Term Load Forecasting Based on the Particle Swarm Optimization with Simulated Annealing

This paper presented an artificial neural network (ANN) method based on the particle swarm optimization (PSO) and simulated annealing (SA) for load forecasting. It train the ANN network and facilitate the tuning of the optimal network weight and threshold by using the modified PSO with SA. The ANN network has a better ability to escape from the local optimum and is more effective than the conventional PSO-based ANN. Then forecast the daily load by using the network. Simulation example shows that the proposed approach has good accuracy.

short term load forecasting artificial neural network particle swarm optimization simulated annealing

LIU Chen LIU Fasheng

School of Information Science and Technology, Shandong University of Science and Technology, Qingdao School of Information Science and Electrical Engineering, Shandong University of Science and Technol

国际会议

The 3rd International Institute of Statistics & Management Engineering Symposium(2010 国际统计与管理工程研讨会 IISMES)

威海

英文

140-144

2010-07-24(万方平台首次上网日期,不代表论文的发表时间)