摘要
通过分析大型公共建筑能耗数据所具有的海量性、随机性、序列性等特征,建立了基于多元线性回归与一阶自回归算法的大型公共建筑能耗动态模型。研究了模型参数估计问题,结合F与χ2两种方法,理论验证了模型显著性与有效性;根据西安市某大型公共建筑能耗数据,实验验证了该模型的逼真性、可行性与强健性。因此,该模型能对既有与新建大型公共建筑能耗进行实时动态预测,解决了节能定量化研究、定额用能的"瓶颈"问题,为大型公共建筑能耗审计及等节能制度的实现提供科学指导。
By analyzing the energy consumption data of large-scale public building with the magnanimity,randomness,sequence and other features,an energy consumption dynamic model based on multiple linear regressions and first-order selfregression is established.It analyses the model parameter estimation,and it proves the significance and effectiveness in theory of this model by using F and χ2 tests.According to the energy consumption data of one large-scale public building in Xi'an city,the verisimilitude,feasibility and the healthiness of this model are validated by experiments.Therefore,this model can do a real-time dynamic prediction for the existing and new large-scale public buildings,it resolves the problem of the quantification of energy-saving and"energy-consumption within the quota",which offers scientific guidance to the realization of the audit,supervision and such energy-saving systems.
出处
《计算机工程与应用》
CSCD
北大核心
2011年第16期214-217,共4页
Computer Engineering and Applications
基金
国家自然科学基金No.50978210
陕西省自然科学基础研究基金(No.SJ08F30)
陕西省教育厅专项科研计划项目(No.08JK321)
西安市城乡建设委员会基金(市建发2009149号文件)~~
关键词
能耗
动态模型
递推最小二乘法(RLS)
多元线性回归
自回归
energy consumption
dynamic model
Recursive Least Squares(RLS)
multiple linear regressions
autoregressive