中国电机工程学报2016，Vol.36Issue(2)：399-406,596,9.DOI:10.13334/j.0258-8013.pcsee.2016.02.010
基于多变量相空间重构和卡尔曼滤波的冷热电联供系统负荷预测方法
Cooling, Heating and Electrical Load Forecasting Method for CCHP System Based on Multivariate Phase Space Reconstruction and Kalman Filter
摘要
Abstract
A novel cooling, heating and electrical load forecasting method based on multivariate phase space reconstruction and Kalman filter algorithm was proposed. Initially, the multivariate time series were constructed by choosing the cooling load, heating load, electrical load and weather factors time series based on the correlation coefficient between the variables. Furthermore, the phase space of multivariate time series was reconstructed based on the chaos theory and C-C method. Ultimately, an autoregression model for multivariate phase space was established by taking phase variables as state variables and the cooling, heating and electrical load were predicted by using Kalman filter algorithm. The cooling, heating and electrical load and weather historical datas of combined cooling, heating and power (CCHP) system in a hospital in northern China in August were validated by this method. Compared with the univariate method, this novel method has better load prediction preciseness because the coupled relationship among different variants of the cooling, heating and electrical load were taken into consideration. Case study validate the feasibility and effectiveness of this proposed load forecasting method.关键词
能源互联网/冷热电联供系统/负荷预测/多变量相空间重构/卡尔曼滤波Key words
energy internet/combined cooling heating and power (CCHP)/load forecasting/multivariate phase space reconstruction/Kalman filter分类
信息技术与安全科学引用本文复制引用
赵峰,孙波,张承慧..基于多变量相空间重构和卡尔曼滤波的冷热电联供系统负荷预测方法[J].中国电机工程学报,2016,36(2):399-406,596,9.基金项目
国家自然科学基金重大国际(地区)合作研究项目(61320106011) （地区）
国家 863 高技术基金项目(2014AA052802) （2014AA052802）
国家自然科学基金项目(61573224). Major International(Regional)Joint Research Project of the National Natural Science Foundation of China (NSFC)(61320106011) （61573224）
National High Technology Research and Development of China 863 Program (2014AA052802) （2014AA052802）
Project Supported by National Natural Science Foundation of China (61573224). （61573224）
