Short-term Load Forecasting Using Multiple Support Vector Machines Based on Fuzzy clustering

摘要：

According to the future of power load, a load forecasting method of multiple support vector machine based on fuzzy clustering is proposed. Data type, weather and temperature factors are considered in the model. Load data are classified using fuzzy clustering. Each class was modeled using support vector machines which best fitted the special class. The method was simulated utilizing the load data of Shan Dong electrical company from 2005 to 2007. The simulation result showed our method can improve the forecasting accuracy.

关键词： short-term load forecasting support vector machines fuzzy clustering

作者: Gaorong Liu xiao-hua

作者单位: Shool of Mathematics and Information, LuDong University,Yantai ShanDong Province,264025

会议类型: 国际会议

会议名称: 2009年中国控制与决策会议(2009 Chinese Control and Decision Conference)

会议地点: 广西桂林

会议语种:英文

页码: 3183-3186

在线出版日期: 2009-06-17（万方平台首次上网日期，不代表论文的发表时间）