Identification Method for Air-conditioning-Building Electrothermal Coupling System Based on Second-order Equivalent Thermal Parameter Analytical Solution

被引:0
|
作者
Pan D. [1 ]
Dong L. [1 ]
Fan S. [1 ]
Huang Y. [2 ]
Yang S. [2 ]
He G. [1 ]
机构
[1] Key Laboratory of Control of Power Transmission and Conversion, Ministry of Education, Shanghai Jiao Tong University, Shanghai
[2] Marketing Service Center of State Grid Jiangsu Electric Power Co., Ltd., Nanjing
来源
Dianli Xitong Zidonghua/Automation of Electric Power Systems | 2023年 / 47卷 / 11期
关键词
air-conditioning; analytical solution; average energy efficiency ratio; parameter identification; second-order equivalent thermal parameter model;
D O I
10.7500/AEPS20220624001
中图分类号
学科分类号
摘要
Modeling of air-conditioning-building electrothermal coupling system is the basis of tapping the potential of air-conditioning (AC) regulation. In order to solve the problems of limited fitting accuracy and insufficient consideration of electrothermal coupling characteristics in the current research of second-order equivalent thermal parameter (ETP) modeling, the analytical recursive form of second-order ETP model is first derived. It has the advantages of high fitting accuracy, bounded recursive values and flexible and adjustable step size, which can improve the accuracy, reliability and adaptability of the model to diversified data acquisition technologies. Then, the average energy efficiency ratio is used to describe the electrothermal conversion process of AC, and the parameter identification method for the air-conditioning-building electrothermal coupling analytical model considering the average energy efficiency ratio is proposed. The indoor air temperature fitting mechanism and heating capacity fitting mechanism are comprehensively used to optimize the parameters. Finally, an actual test environment is built to verify the performance of the proposed method. The results show that this method can significantly improve the accuracy of parameter identification on the existing basis, so as to provide a more accurate and reliable model basis for the energy system simulation, AC load control and other applications. © 2023 Automation of Electric Power Systems Press. All rights reserved.
引用
收藏
页码:77 / 87
页数:10
相关论文
共 29 条
  • [1] SHU Yinbiao, CHEN Guoping, HE Jingbo, Et al., Building a new electric power system based on new energy sources[J], Strategic Study of CAE, 23, 6, pp. 61-69, (2021)
  • [2] MENG Yan, XIAO Jucheng, HONG Juhua, Et al., Nodal customer directrix load considering demand response uncertainty:concept and model [J/OL], Automation of Electric Power Systems
  • [3] FAN Shuai, Yihan WEI, HE Guangyu, Et al., Discussion on demand response mechanism for new power systems [J], Automation of Electric Power Systems, 46, 7, pp. 1-12, (2022)
  • [4] HU Xiaoqing, Research on modeling and control strategy for air conditioning loads to participate in demand response in power system[D], (2017)
  • [5] FAN Shuai, HE Guangyu, ZHENG Xiangming, Et al., Research on online distributed optimization-based self-approaching optimization operation method of virtual power plant[J/OL], Proceedings of the CSEE
  • [6] SONDEREGGER R., Dynamic models of house heating based on equivalent thermal parameters[D], (1978)
  • [7] KERRISK J., Room weighting factors calculated from resistance-capacitance networks[R], (1980)
  • [8] HENCEY B., Online model estimation for predictive thermal control of buildings[J], IEEE Transactions on Control Systems Technology, 25, 4, pp. 1414-1422, (2017)
  • [9] WANG Junfeng, Research on dynamic room temperature prediction methods of building equivalent RC models based on system identification[D], (2019)
  • [10] JIANG Tingyu, Ping JU, WANG Chong, Aggregated power model of air-conditioning load considering stochastic adjustment behaviors of consumers[J], Automation of Electric Power Systems, 44, 3, pp. 105-113, (2020)