Predication of Building Energy Consumption Based on PLSR
The building energy consumption (BEC) is influenced by many factors.For the existing building,the local weather condition is the most important influenced factor.The present prediction studies on BEC mainly apply two kinds of models.One is the model based on the mathematical statistics by mean of Multiple Linear Regression (MLR),which can not better deal with the problem of parameter relativities.Another is the engineering model based on the technology analysis,which is complicated and is difficult to master by general researchers.I order to solve these problems;this paper presents a prediction model of BEC by PLSR (Partial Least Square Regression).Through an calculation example of a building in Dalian,the BEC is predicted by use of this model taking weather condition as main factor.The result of 1.08% mean relative error shows that this model has better forecast precision compared with other studies,and could be considered as a new making decision tool for retrofitting and re-optimization design of air-conditioning systems in large-scale buildings.
Building energy consumption PLSR Weather conditions
Hailin Mu Ming Zhang Xudong Kang Yadong Ning Yongchen Song
Key Laboratory of Ocean Energy Utilization and Energy Conservation of Ministry of Education,Dalian University of Technology,Dalian,China
国际会议
The First International Conference on Building Energy and Environment(第一届建筑能源与环境国际会议)
大连
英文
1971-1978
2008-07-01（万方平台首次上网日期，不代表论文的发表时间）