Model-based predictive control of multi-zone commercial building with a lumped building modelling approach

Jaewan Joe; Piljae Im; Borui Cui; Jin Dong

doi:10.1016/j.energy.2022.125494

Model-based predictive control of multi-zone commercial building with a lumped building modelling approach

Jaewan Joe, Piljae Im, Borui Cui, Jin Dong

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11 Scopus citations

Abstract

This study investigates the applicability of a lumped building modeling approach to model-based predictive control (MPC) to alleviate the complex modeling process of the grey-box multi-zone building model. Based on experimental data, two building models were estimated in this study. The detailed model as a reference case and a lumped model were estimated with decentralized and conventional approaches, respectively. Then, simulations were performed with two boundary conditions, including the comfort bound and electricity cost structure. The performances of the MPC with the detailed and lumped models were analyzed compared to the feedback control. More savings was achieved with a larger comfort bound and more aggressive electricity cost structure. The savings potential of the proposed lumped model approach was not as high as that of the detailed model. However, the proposed method yields good control performance, whose savings was approximately 8.6% over that of feedback control. These results suggest that the proposed method can be used to facilitate MPC implementation in multi-zone building applications.

Original language	English
Article number	125494
Journal	Energy
Volume	263
DOIs	https://doi.org/10.1016/j.energy.2022.125494
State	Published - Jan 15 2023

Funding

This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea Government ( MSIT ) (No. 2021R1F1A1064452 ). This material is based upon work supported by DOE's Office of Science and BTO . This research used resources of ORNL's Building Technologies Research and Integration (BTRIC), which is a DOE Office of Science User Facility. This work was funded by fieldwork proposal CEBT105 under DOE BTO activity nos. BT0302000 and BT0305000 . This manuscript has been authored by UT-Battelle LLC under contract DEAC05-00OR22725 with DOE . The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes.

Funders	Funder number
U.S. Department of Energy	BT0305000, BT0302000
Office of Science
Building Technologies Office
UT-Battelle	DEAC05-00OR22725
Ministry of Science, ICT and Future Planning	2021R1F1A1064452
National Research Foundation of Korea

Keywords

Decentralized modeling approach
Grey-box building model
Lumped building model
Model-based predictive control

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10.1016/j.energy.2022.125494

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title = "Model-based predictive control of multi-zone commercial building with a lumped building modelling approach",

abstract = "This study investigates the applicability of a lumped building modeling approach to model-based predictive control (MPC) to alleviate the complex modeling process of the grey-box multi-zone building model. Based on experimental data, two building models were estimated in this study. The detailed model as a reference case and a lumped model were estimated with decentralized and conventional approaches, respectively. Then, simulations were performed with two boundary conditions, including the comfort bound and electricity cost structure. The performances of the MPC with the detailed and lumped models were analyzed compared to the feedback control. More savings was achieved with a larger comfort bound and more aggressive electricity cost structure. The savings potential of the proposed lumped model approach was not as high as that of the detailed model. However, the proposed method yields good control performance, whose savings was approximately 8.6% over that of feedback control. These results suggest that the proposed method can be used to facilitate MPC implementation in multi-zone building applications.",

keywords = "Decentralized modeling approach, Grey-box building model, Lumped building model, Model-based predictive control",

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AU - Joe, Jaewan

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AU - Cui, Borui

AU - Dong, Jin

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Y1 - 2023/1/15

N2 - This study investigates the applicability of a lumped building modeling approach to model-based predictive control (MPC) to alleviate the complex modeling process of the grey-box multi-zone building model. Based on experimental data, two building models were estimated in this study. The detailed model as a reference case and a lumped model were estimated with decentralized and conventional approaches, respectively. Then, simulations were performed with two boundary conditions, including the comfort bound and electricity cost structure. The performances of the MPC with the detailed and lumped models were analyzed compared to the feedback control. More savings was achieved with a larger comfort bound and more aggressive electricity cost structure. The savings potential of the proposed lumped model approach was not as high as that of the detailed model. However, the proposed method yields good control performance, whose savings was approximately 8.6% over that of feedback control. These results suggest that the proposed method can be used to facilitate MPC implementation in multi-zone building applications.

AB - This study investigates the applicability of a lumped building modeling approach to model-based predictive control (MPC) to alleviate the complex modeling process of the grey-box multi-zone building model. Based on experimental data, two building models were estimated in this study. The detailed model as a reference case and a lumped model were estimated with decentralized and conventional approaches, respectively. Then, simulations were performed with two boundary conditions, including the comfort bound and electricity cost structure. The performances of the MPC with the detailed and lumped models were analyzed compared to the feedback control. More savings was achieved with a larger comfort bound and more aggressive electricity cost structure. The savings potential of the proposed lumped model approach was not as high as that of the detailed model. However, the proposed method yields good control performance, whose savings was approximately 8.6% over that of feedback control. These results suggest that the proposed method can be used to facilitate MPC implementation in multi-zone building applications.

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Model-based predictive control of multi-zone commercial building with a lumped building modelling approach

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Keywords

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