基于多联机运行监测大数据的住宅空调人行为模型参数提取及检验方法研究  

Study on Occupant Air-conditioning Behavior Modelling Parameter Extraction and Verification Method Based on VRF System Operating Monitoring Big Data

作　　者：吴奕 燕达[1] 周欣 钱明杨 晋远 孙红三[1] WU Yi;YAN Da;ZHOU Xin;QIAN Mingyang;JIN Yuan;SUN Hongsan(Building Environment Reseach Center,Tsinghua University,Beijing,China;School of Architecture,Southeast University,Nanjing,China)

机构地区：[1]清华大学建筑学院建筑节能研究中心,北京100084 [2]东南大学建筑学院,南京214135

出　　处：《建筑科学》2022年第12期192-203,共12页Building Science

基　　金：空调设备及系统运行节能国家重点实验室开放基金(ACSKL2020KT4);国家自然科学基金“建筑中典型行为模式及人群分布获取及检验方法研究”(51778321)。

摘　　要：近年来,随着城镇化进程不断发展与居民生活水平的逐步提升,我国住宅制冷能耗不断增加,实现住宅空调系统节能成为关键问题;而人员空调使用行为是影响住宅制冷能耗、造成能耗差异的重要原因之一。现有的空调人行为模型多基于入户调研数据,该数据采集方法采集的户数偏少且难以覆盖户内全空间;随着数据监控与云端传输技术的成熟,其逐渐取代传统的数据采集方法,使得空调运行数据能够易于实现跨时间、跨空间的大量数据采集。然而目前基于空调运行数据进行空调人行为模型研究较少,而本研究即针对空调运行大数据,提出了1套适用于该类数据库的空调人行为模型参数提取与检验方法,并以夏热冬冷地区的多联机监测大数据为案例,实现了1200个空调人行为模型参数提取,同时进行了检验。研究结果表明该方法能够从多联机运行监测大数据中有效提取住宅空调行为的关键信息,此方法适用于各类空调监测数据库,具有重要的工程价值。In recent years,with the continued urbanization and improvement in people’s living standards,energy consumption for residential cooling continues to rise,making energy saving a key issue for residential air conditioning systems.Occupant behavior features diversity in buildings,leading to significant discrepancies in building energy consumption.Existing occupant air-conditioning behavior models are usually based on in-house survey data,which faces problems of the limited number of households surveyed and failure to cover entire in-house space.With the advances data monitoring and cloud transmission technologies,replacing traditional data collection method,air-conditioning operating data at a large time and space scale has been made available to obtain real occupant indoor behavior.However,there lack studies on occupant air-conditioning behavior model based on air-conditioning operating data.In this study,a modeling parameter extraction and verification method of occupant air-conditioning behavior was proposed based on air-conditioning operating data.Taking the VRF monitoring big data in HSCW climate zone in China as the case study,1,200 occupant air-conditioning behavior model parameters were extracted and verified.The results show that this method can extract key information of occupant air-conditioning behaviors through VRF monitoring big data,thus being applicable for various air-conditioning monitoring database and of significant engineering value.

关 键 词：大数据 空调行为 随机模型 

分 类 号：TU831[建筑科学—供热、供燃气、通风及空调工程]