Virtual surface temperature sensor for multi-zone commercial buildings

被引:4
|
作者
Yu, Yuebin [1 ]
Woradechjumroen, Denchai [1 ]
Yu, Daihong [2 ]
机构
[1] Univ Nebraska, 1110 S67th ST,PKI104F, Omaha, NE 68182 USA
[2] Lawrence Technol Univ, Southfield, MI 48033 USA
关键词
System identification; Commercial Buildings; RTUs; Virtual sensor; Supervisory control;
D O I
10.1016/j.egypro.2014.11.896
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Multi-zone structure is commonly used in small commercial office buildings, retail stores and supermarket. While there is no adjacent wall between the zones, the impact of a neighbor zone on the current zone can be approximated and analyzed through the application of virtual walls. It is critical to accurately estimate the virtual wall surface temperature in order to evaluate the model uncertainty and apply improved supervisory control on multiple rooftop air-conditioning units (RTUs). We propose an innovative virtual surface temperature sensor based on system identification to solve this challenge. The validation of the virtual temperature model is processed by the three validation criteria: goodness of fit (G), mean squared error (MSE) and coefficient of determination (R-2) through off control conditions with data obtained from a building simulation platform. Further, the sensitivity analysis using the on-control three conditions (under-sizing, properly sizing and oversizing condition) is conducted for analyzing and evaluating the performance of this system-identification based virtual sensor. (C) 2014 The Authors. Published by Elsevier Ltd.
引用
收藏
页码:21 / 24
页数:4
相关论文
共 50 条
  • [1] Distributed resource allocation for multi-zone commercial buildings
    Mei, Jun
    Xia, Xiaohua
    INNOVATIVE SOLUTIONS FOR ENERGY TRANSITIONS, 2019, 158 : 2872 - 2877
  • [2] Distributed Control of Multi-zone Commercial Buildings for Demand Response
    Tang, Suigu
    Xu, Yinliang
    2017 IEEE CONFERENCE ON ENERGY INTERNET AND ENERGY SYSTEM INTEGRATION (EI2), 2017,
  • [3] Smart decentralized MPC for temperature control in multi-zone buildings
    Gommers, Sjors
    Lazar, Mircea
    2021 29TH MEDITERRANEAN CONFERENCE ON CONTROL AND AUTOMATION (MED), 2021, : 415 - 420
  • [4] A data driven method for optimal sensor placement in multi-zone buildings
    Suryanarayana, Gowri
    Arroyo, Javier
    Helsen, Lieve
    Lago, Jesus
    ENERGY AND BUILDINGS, 2021, 243
  • [5] A deep reinforcement learning control method for multi-zone precooling in commercial buildings
    Fan, Yuankang
    Fu, Qiming
    Chen, Jianping
    Wang, Yunzhe
    Lu, You
    Liu, Ke
    APPLIED THERMAL ENGINEERING, 2025, 260
  • [6] Performance analysis and comparison of data-driven models for predicting indoor temperature in multi-zone commercial buildings
    Cui, Borui
    Im, Piljae
    Bhandari, Mahabir
    Lee, Sangkeun
    ENERGY AND BUILDINGS, 2023, 298
  • [7] Thermal Dynamic Models for Predicting the Indoor Temperature of Multi-Zone Buildings
    Koumbari, Nicos
    Tziovani, Lysandros
    Asprou, Markos
    Hadjidemetriou, Lenos
    Timotheou, Stelios
    2024 INTERNATIONAL CONFERENCE ON SMART ENERGY SYSTEMS AND TECHNOLOGIES, SEST 2024, 2024,
  • [8] Distributed Flexibility Characterization and Resource Allocation for Multi-zone Commercial Buildings in the Smart Grid
    Hao, He
    Lian, Jianming
    Kalsi, Karanjit
    Stoustrup, Jakob
    2015 54TH IEEE CONFERENCE ON DECISION AND CONTROL (CDC), 2015, : 3161 - 3168
  • [9] An inverse hygrothermal model for multi-zone buildings
    Cai, Jie
    Braun, James
    JOURNAL OF BUILDING PERFORMANCE SIMULATION, 2016, 9 (05) : 510 - 528
  • [10] COMOB: A MATLAB toolbox for sensor placement and contaminant event monitoring in multi-zone buildings
    Kyriacou, Alexis
    Michaelides, Michalis P.
    Eliades, Demetrios G.
    Panayiotou, Christos G.
    Polycarpou, Marios M.
    BUILDING AND ENVIRONMENT, 2019, 154 : 348 - 361