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

Joe, Jaewan; Im, Piljae; Cui, Borui; Dong, Jin

doi:10.1016/j.energy.2022.125494

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

Journal Article · Mon Sep 26 00:00:00 EDT 2022 · Energy

DOI:https://doi.org/10.1016/j.energy.2022.125494· OSTI ID:1963139

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Inha University, Incheon (Korea, Republic of)
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Here 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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Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Organization:: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Energy Efficiency Office. Building Technologies Office; USDOE Office of Science (SC); National Research Foundation of Korea (NRF)

Grant/Contract Number:: AC05-00OR22725; 2021R1F1A1064452; BT0302000; BT0305000

OSTI ID:: 1963139

Alternate ID(s):: OSTI ID: 1891345

Journal Information:: Energy, Vol. 263, Issue 1; ISSN 0360-5442

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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