INTERVAL FORECASTING FOR HEATING LOAD USING SUPPORT VECTOR REGRESSION AND ERROR CORRECTING MARKOV CHAINS

摘要：

As previously heating load forecasting methods are mostly deterministic, that is, point forecasting. In this paper, a new integrated interval forecasting approach based on support vector regression (SVR) and error correcting Markov chains is proposed to predict hourly heating load. Firstly, the architecture of the forecasting approach is presented. Then the forecasting system is applied to heating load collected from a certain heating supply station. Finally the forecast results are presented, and the simulation results illustrate that the forecasting approach can meet the demands of optimization control and operation for energy-saving.

关键词： Interval Forecasting Heating Load Support Vector Regression Markov Chains

作者: YONG-MING ZHANG WEI-GUI QI

作者单位: Department of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin, 150001, China

会议类型: 国际会议

会议名称: 2009 International Conference on Machine Learning and Cybernetics(2009机器学习与控制论国际会议)

会议地点: 保定

会议语种:英文

页码: 1106-1110

在线出版日期: 2009-07-12（万方平台首次上网日期，不代表论文的发表时间）