Physical-data Fusion Modeling Method for Energy Consumption Analysis of Smart Building

作     者：Xiao Han Chaohai Zhang Yi Tang Yujian Ye Xiao Han;Chaohai Zhang;Yi Tang;Yujian Ye

作者机构：the Jiangsu Key Laboratory of New Energy Generation and Power ConversionNanjing University of Aeronautics and AstronauticsNanjing 211106China the School of Electrical EngineeringSoutheast UniversityNanjing 210096China the Department of Electrical and Electronic EngineeringImperial College LondonLondonU.K. 

出 版 物：《Journal of Modern Power Systems and Clean Energy》 (现代电力系统与清洁能源学报（英文）)

年 卷 期：2022年第10卷第2期

页      面：482-491页

核心收录：

学科分类：080802[工学-电力系统及其自动化] 0808[工学-电气工程] 08[工学] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：the National Natural Science Foundation of China(No.51877037) 

主　　题：Smart building physical-data fusion modeling method energy consumption precision model thermal-electrical conversion. 

摘      要：The energy consumption of buildings accounts for approximately 40%of total energy *** accurate energy consumption analysis of buildings can not only promise significant energy savings but also help estimate the demand response potential more accurately,and consequently brings benefits to the upstream power *** paper proposes a novel physical-data fusion modeling(PFM)method for modeling smart buildings that can accurately assess energy ***,a thermal process model of buildings and an electrical load model that focus on building heating,ventilation,and air conditioning(HVAC)systems are presented to analyze the thermal-electrical conversion process of energy consumption of ***,the PFM method is used to improve the accuracy of the energy consumption analysis model for buildings by modifying the parameters that are difficult to measure in the physical model(i.e.,it effectively modifies the electrical load model based on the proposed PFM method).Finally,case studies involving a real-world dataset recorded in a high-tech park in Changzhou,China,demonstrate that the proposed method exhibits superior performance with respect to the traditional physical modeling(TPM)method and data-driven modeling(DDM)method in terms of the achieved accuracy.