室温空间特性差异性分析及抽样推断方法研究  

Study on difference analysis and sampling inference methods of room temperature spatial characteristics

作　　者：张旭 张浩浩 顾吉浩[3] ZHANG Xu;ZHANG Haohao;GU Jihao(National Energy Group Ningxia Electric Power Company Limited,Yinchuan 750001,China;Gongda Keya(Tianjin)Energy Technology Company Limited,Tianjin 300401,China;Hebei University of Technology,Tianjin 300401,China)

机构地区：[1]国家能源集团宁夏电力有限公司,银川750001 [2]工大科雅(天津)能源科技有限公司,天津300401 [3]河北工业大学,天津300401

出　　处：《综合智慧能源》2022年第9期51-58,共8页Integrated Intelligent Energy

基　　金：河北工业大学科技创新战略资助项目(20180902);国家能源集团宁夏电力有限公司项目(NXDL-2021-12)。

摘　　要：为进一步推进“双碳”目标的实现,供热领域的技术转型势在必行。近年来,物联网室温采集装置在供热行业得到了大规模普及应用。由于热用户室温采集数据受到设备安装比例、安装位置、系统误差、随机误差等因素影响,室温数据需要经过分析和处理后才能用于评价供热质量。基于数据清洗和抽样统计,提出了对典型室温空间特性差异性分析和评价方法,为海量热用户室温数据在供热质量评估和供热生产优化调控过程的应用,提供理论指导依据。To pursue the "dual carbon" target,technical transformations in heating industry is overwhelming. In recent years,networked room temperature acquisition devices have been widely used in this industry. Since the collected data of thermal energy users are affected by equipment installation ratio,installation location,systematic error,random error,etc.,the room temperature data needs to be analysed and processed before being used to evaluate the heating quality.Based on data cleaning and sampling statistics,difference analysis and sampling inference methods for classical room temperature spatial characteristics are proposed,which provides theoretical guidance for the application of room temperature data from massive heat users in heating quality assessment and heat supply optimization control.

关 键 词：物联网 室温数据 数据清洗 大数据分析 抽样方法 碳中和 智慧供热 

分 类 号：TK01[动力工程及工程热物理]