IEICE TRANSACTIONS on Fundamentals
Thermal-Comfort Aware Online Co-Scheduling Framework for HVAC, Battery Systems, and Appliances in Smart Buildings
Summary :
Energy management in buildings is vital for reducing electricity costs and maximizing the comfort of occupants. Excess solar generation can be used by combining a battery storage system and a heating, ventilation, and air-conditioning (HVAC) system so that occupants feel comfortable. Despite several studies on the scheduling of appliances, batteries, and HVAC, comprehensive and time scalable approaches are required that integrate such predictive information as renewable generation and thermal comfort. In this paper, we propose an thermal-comfort aware online co-scheduling framework that incorporates optimal energy scheduling and a prediction model of PV generation and thermal comfort with the model predictive control (MPC) approach. We introduce a photovoltaic (PV) energy nowcasting and thermal-comfort-estimation model that provides useful information for optimization. The energy management problem is formulated as three coordinated optimization problems that cover fast and slow time-scales by considering predicted information. This approach reduces the time complexity without a significant negative impact on the result's global nature and its quality. Experimental results show that our proposed framework achieves optimal energy management that takes into account the trade-off between electricity expenses and thermal comfort. Our sensitivity analysis indicates that introducing a battery significantly improves the trade-off relationship.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E106-A No.5 pp.698-706
- Publication Date
- 2023/05/01
- Publicized
- 2022/10/24
- Online ISSN
- 1745-1337
- DOI
- 10.1587/transfun.2022MAI0001
- Type of Manuscript
- Special Section INVITED PAPER (Special Section on Mathematical Systems Science and its Applications)
- Category
Authors
Daichi WATARI
Osaka University
Ittetsu TANIGUCHI
Osaka University
Francky CATTHOOR
Katholieke Universiteit Leuven,IMEC
Charalampos MARANTOS
National Technical University of Athens
Kostas SIOZIOS
Aristotle University of Thessaloniki
Elham SHIRAZI
Katholieke Universiteit Leuven,IMEC
Dimitrios SOUDRIS
National Technical University of Athens
Takao ONOYE
Osaka University
Keyword
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Daichi WATARI, Ittetsu TANIGUCHI, Francky CATTHOOR, Charalampos MARANTOS, Kostas SIOZIOS, Elham SHIRAZI, Dimitrios SOUDRIS, Takao ONOYE, "Thermal-Comfort Aware Online Co-Scheduling Framework for HVAC, Battery Systems, and Appliances in Smart Buildings" in IEICE TRANSACTIONS on Fundamentals,
vol. E106-A, no. 5, pp. 698-706, May 2023, doi: 10.1587/transfun.2022MAI0001.
Abstract: Energy management in buildings is vital for reducing electricity costs and maximizing the comfort of occupants. Excess solar generation can be used by combining a battery storage system and a heating, ventilation, and air-conditioning (HVAC) system so that occupants feel comfortable. Despite several studies on the scheduling of appliances, batteries, and HVAC, comprehensive and time scalable approaches are required that integrate such predictive information as renewable generation and thermal comfort. In this paper, we propose an thermal-comfort aware online co-scheduling framework that incorporates optimal energy scheduling and a prediction model of PV generation and thermal comfort with the model predictive control (MPC) approach. We introduce a photovoltaic (PV) energy nowcasting and thermal-comfort-estimation model that provides useful information for optimization. The energy management problem is formulated as three coordinated optimization problems that cover fast and slow time-scales by considering predicted information. This approach reduces the time complexity without a significant negative impact on the result's global nature and its quality. Experimental results show that our proposed framework achieves optimal energy management that takes into account the trade-off between electricity expenses and thermal comfort. Our sensitivity analysis indicates that introducing a battery significantly improves the trade-off relationship.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.2022MAI0001/_p
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@ARTICLE{e106-a_5_698,
author={Daichi WATARI, Ittetsu TANIGUCHI, Francky CATTHOOR, Charalampos MARANTOS, Kostas SIOZIOS, Elham SHIRAZI, Dimitrios SOUDRIS, Takao ONOYE, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Thermal-Comfort Aware Online Co-Scheduling Framework for HVAC, Battery Systems, and Appliances in Smart Buildings},
year={2023},
volume={E106-A},
number={5},
pages={698-706},
abstract={Energy management in buildings is vital for reducing electricity costs and maximizing the comfort of occupants. Excess solar generation can be used by combining a battery storage system and a heating, ventilation, and air-conditioning (HVAC) system so that occupants feel comfortable. Despite several studies on the scheduling of appliances, batteries, and HVAC, comprehensive and time scalable approaches are required that integrate such predictive information as renewable generation and thermal comfort. In this paper, we propose an thermal-comfort aware online co-scheduling framework that incorporates optimal energy scheduling and a prediction model of PV generation and thermal comfort with the model predictive control (MPC) approach. We introduce a photovoltaic (PV) energy nowcasting and thermal-comfort-estimation model that provides useful information for optimization. The energy management problem is formulated as three coordinated optimization problems that cover fast and slow time-scales by considering predicted information. This approach reduces the time complexity without a significant negative impact on the result's global nature and its quality. Experimental results show that our proposed framework achieves optimal energy management that takes into account the trade-off between electricity expenses and thermal comfort. Our sensitivity analysis indicates that introducing a battery significantly improves the trade-off relationship.},
keywords={},
doi={10.1587/transfun.2022MAI0001},
ISSN={1745-1337},
month={May},}
Copy
TY - JOUR
TI - Thermal-Comfort Aware Online Co-Scheduling Framework for HVAC, Battery Systems, and Appliances in Smart Buildings
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 698
EP - 706
AU - Daichi WATARI
AU - Ittetsu TANIGUCHI
AU - Francky CATTHOOR
AU - Charalampos MARANTOS
AU - Kostas SIOZIOS
AU - Elham SHIRAZI
AU - Dimitrios SOUDRIS
AU - Takao ONOYE
PY - 2023
DO - 10.1587/transfun.2022MAI0001
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E106-A
IS - 5
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - May 2023
AB - Energy management in buildings is vital for reducing electricity costs and maximizing the comfort of occupants. Excess solar generation can be used by combining a battery storage system and a heating, ventilation, and air-conditioning (HVAC) system so that occupants feel comfortable. Despite several studies on the scheduling of appliances, batteries, and HVAC, comprehensive and time scalable approaches are required that integrate such predictive information as renewable generation and thermal comfort. In this paper, we propose an thermal-comfort aware online co-scheduling framework that incorporates optimal energy scheduling and a prediction model of PV generation and thermal comfort with the model predictive control (MPC) approach. We introduce a photovoltaic (PV) energy nowcasting and thermal-comfort-estimation model that provides useful information for optimization. The energy management problem is formulated as three coordinated optimization problems that cover fast and slow time-scales by considering predicted information. This approach reduces the time complexity without a significant negative impact on the result's global nature and its quality. Experimental results show that our proposed framework achieves optimal energy management that takes into account the trade-off between electricity expenses and thermal comfort. Our sensitivity analysis indicates that introducing a battery significantly improves the trade-off relationship.
ER -
English
