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大型公共建筑能耗动态模型的研究与应用
引用本文:马媛,于军琪,杨柳,杨创业,王磊.大型公共建筑能耗动态模型的研究与应用[J].计算机工程与应用,2011,47(16):214-217.
作者姓名:马媛  于军琪  杨柳  杨创业  王磊
作者单位:1. 西安建筑科技大学,信息与控制工程学院,西安,710055
2. 西安建筑科技大学,建筑学院,西安,710055
基金项目:国家自然科学基金,陕西省自然科学基础研究基金,陕西省教育厅专项科研计划项目,西安市城乡建设委员会基金
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。

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
修稿时间: 

Study on dynamic energy consumption model and application of large-scale public building
MA Yuan,YU Junqi,YANG Liu,YANG Chuangye,WANG Lei.Study on dynamic energy consumption model and application of large-scale public building[J].Computer Engineering and Applications,2011,47(16):214-217.
Authors:MA Yuan  YU Junqi  YANG Liu  YANG Chuangye  WANG Lei
Affiliation:1.School of Information and Control Engineering,Xi’an University of Architecture and Technology,Xi’an 710055,China 2.School of the Architecture,Xi’an University of Architecture and Technology,Xi’an 710055,China
Abstract: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.
Keywords:energy consumption  dynamic model  Recursive Least Squares(RLS)  multiple linear regressions  autoregressive
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