Power System Short-term Load Forecasting Based on Cooperative Co-evolutionary Immune Network Model

摘要：

The main objective of short-term load forecasting (STLF) is to provide load predictions for generation scheduling, economic load dispatch and security assessment at any time. A new forecasting approach is designed in this paper and the novel method based on the cooperative co-evolutionary and the immune algorithm is proposed. The cooperative coevolutionary immune network is used to evolve the structure and parameters of neural network. The proposed cooperative co-evolutionary immune network model has been implemented based on the actual data and compared with the traditional Radial-Basis Function (RBF) network method. The test results reveal that the cooperative co-evolutionary immune network method possesses far superior forecast precision than the Radial-Basis Function neural network method.

关键词： Electricity power system short-term load forecasting method neural network cooperative co-evolutionary immune algorithm

作者: Xin MA Hong-xiao WU

作者单位: School of Management and Economic North China University of Water Conservancy and Electric Power Zhe School of Electronic Information and Electrical Engineering Shanghai Jiaotong University Minhang, Sh

会议类型: 国际会议

会议名称: 2010 2nd International Conference on Education Technology and Computer(第二届IEEE教育技术与计算机国际会议 ICETC 2010)

会议地点: 上海

会议语种:英文

页码: 582-585

在线出版日期: 2010-06-22（万方平台首次上网日期，不代表论文的发表时间）