research-article

Online management framework for building HVAC systems considering peak shaving and thermal comfort: an experimental study

Authors:

Takao OnoyeAuthors Info & Claims

MSCPES '21: Proceedings of the 9th Workshop on Modeling and Simulation of Cyber-Physical Energy Systems

Article No.: 10, Pages 1 - 7

https://doi.org/10.1145/3470481.3472710

Published: 06 October 2021 Publication History

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Abstract

In this study, an online management framework for building HVAC (Heating, Ventilation, and Air-Conditioning) systems, which achieves peak shaving and thermal comfort improvement, has been designed and studied experimentally. We formulate a model predictive control (MPC) problem for the HVAC control, of which the objective is to minimize the electricity costs and demand peak and maximize thermal comfort. A thermal equivalent circuit model (TECM) was developed to describe the target room's thermal behavior. The TECM is experimentally validated under different ambient temperatures, heat/cooling loads, and occupations. The temperature responses obtained from TECM have a good agreement with observations, and the maximum deviation is below 8%. The online management framework of the HVAC system was developed based on TECM, which includes a monitoring system based on HVAC built-in sensor and embedded technology and a real-time HVAC system control module based on the MPC problem. The performance of the proposed framework with different operating conditions was investigated in the actual room. The results show that the HVAC systems using this framework can achieve better room temperature control and a further improvement in energy efficiency.

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Fengl MLi WQin BZomaya A(2023)Online Demand Peak Shaving with Machine-Learned Advice in Cyber-Physical Energy Systems2023 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech)10.1109/DASC/PiCom/CBDCom/Cy59711.2023.10361461(1-8)Online publication date: 14-Nov-2023
https://doi.org/10.1109/DASC/PiCom/CBDCom/Cy59711.2023.10361461
Grassi BPiana ELezzi APilotelli M(2022)A Review of Recent Literature on Systems and Methods for the Control of Thermal Comfort in BuildingsApplied Sciences10.3390/app1211547312:11(5473)Online publication date: 28-May-2022
https://doi.org/10.3390/app12115473

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Published In

MSCPES '21: Proceedings of the 9th Workshop on Modeling and Simulation of Cyber-Physical Energy Systems

May 2021

83 pages

ISBN:9781450386081

DOI:10.1145/3470481

General Chairs:
Peter Palensky
TU Delft
,
Anurag Srivastava
Washington State University
,
Program Chair:
Edmund Widl
AIT Austrian Institute of Technology

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

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Published: 06 October 2021

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Fengl MLi WQin BZomaya A(2023)Online Demand Peak Shaving with Machine-Learned Advice in Cyber-Physical Energy Systems2023 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech)10.1109/DASC/PiCom/CBDCom/Cy59711.2023.10361461(1-8)Online publication date: 14-Nov-2023
https://doi.org/10.1109/DASC/PiCom/CBDCom/Cy59711.2023.10361461
Grassi BPiana ELezzi APilotelli M(2022)A Review of Recent Literature on Systems and Methods for the Control of Thermal Comfort in BuildingsApplied Sciences10.3390/app1211547312:11(5473)Online publication date: 28-May-2022
https://doi.org/10.3390/app12115473

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