Online Dynamic Mode Decomposition Based System Identification of Multi-Zone Building HVAC Systems

Tumin Wu; Mohammed M. Olama; Seddik M. Djouadi

doi:10.1109/KPEC65465.2025.11045037

Online Dynamic Mode Decomposition Based System Identification of Multi-Zone Building HVAC Systems

Tumin Wu, Mohammed M. Olama, Seddik M. Djouadi

Computational Systems Engineering and Cy

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Many works have recently been conducted to reduce the electricity consumption of smart buildings and allow them to support various grid services. Most of these works require accurate system models for the various appliances in the building including heating, ventilation, and air conditioning (HVAC) units. In this paper, we investigate a recursive data-driven system identification strategy to construct the thermal model for a time-varying building with a multi-zone HVAC unit. The online dynamic mode decomposition (DMD)-based strategy is employed to identify the multi-zone thermal building dynamics, where a simple information update (rank-1) is selected to avoid computational complexity. The DMD-based identification strategy is validated using a real gymnasium building equipped with a 4-zone HVAC unit, and its performance is compared with that of the traditional nuclear-norm subspace identification (N2SID) strategy.

Original language	English
Title of host publication	2025 IEEE Kansas Power and Energy Conference, KPEC 2025
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9798331535032
DOIs	https://doi.org/10.1109/KPEC65465.2025.11045037
State	Published - 2025
Event	2025 IEEE Kansas Power and Energy Conference, KPEC 2025 - Manhattan, United States Duration: Apr 24 2025 → Apr 25 2025

Publication series

Name	2025 IEEE Kansas Power and Energy Conference, KPEC 2025

Conference

Conference	2025 IEEE Kansas Power and Energy Conference, KPEC 2025
Country/Territory	United States
City	Manhattan
Period	04/24/25 → 04/25/25

Funding

This manuscript has been authored by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (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. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (https://www.energy.gov/doepublic-access-plan).

Keywords

Building HVAC system
dynamic mode decomposition
multi-zone HVAC unit
nuclear norm subspace identification
system identification

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10.1109/KPEC65465.2025.11045037

Cite this

@inproceedings{7d47e33bea02431897d2b27262f1d44a,

title = "Online Dynamic Mode Decomposition Based System Identification of Multi-Zone Building HVAC Systems",

abstract = "Many works have recently been conducted to reduce the electricity consumption of smart buildings and allow them to support various grid services. Most of these works require accurate system models for the various appliances in the building including heating, ventilation, and air conditioning (HVAC) units. In this paper, we investigate a recursive data-driven system identification strategy to construct the thermal model for a time-varying building with a multi-zone HVAC unit. The online dynamic mode decomposition (DMD)-based strategy is employed to identify the multi-zone thermal building dynamics, where a simple information update (rank-1) is selected to avoid computational complexity. The DMD-based identification strategy is validated using a real gymnasium building equipped with a 4-zone HVAC unit, and its performance is compared with that of the traditional nuclear-norm subspace identification (N2SID) strategy.",

keywords = "Building HVAC system, dynamic mode decomposition, multi-zone HVAC unit, nuclear norm subspace identification, system identification",

author = "Tumin Wu and Olama, \{Mohammed M.\} and Djouadi, \{Seddik M.\}",

note = "Publisher Copyright: {\textcopyright} 2025 IEEE.; 2025 IEEE Kansas Power and Energy Conference, KPEC 2025 ; Conference date: 24-04-2025 Through 25-04-2025",

year = "2025",

doi = "10.1109/KPEC65465.2025.11045037",

language = "English",

series = "2025 IEEE Kansas Power and Energy Conference, KPEC 2025",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2025 IEEE Kansas Power and Energy Conference, KPEC 2025",

}

Wu, T, Olama, MM & Djouadi, SM 2025, Online Dynamic Mode Decomposition Based System Identification of Multi-Zone Building HVAC Systems. in 2025 IEEE Kansas Power and Energy Conference, KPEC 2025. 2025 IEEE Kansas Power and Energy Conference, KPEC 2025, Institute of Electrical and Electronics Engineers Inc., 2025 IEEE Kansas Power and Energy Conference, KPEC 2025, Manhattan, United States, 04/24/25. https://doi.org/10.1109/KPEC65465.2025.11045037

Online Dynamic Mode Decomposition Based System Identification of Multi-Zone Building HVAC Systems. / Wu, Tumin; Olama, Mohammed M.; Djouadi, Seddik M.
2025 IEEE Kansas Power and Energy Conference, KPEC 2025. Institute of Electrical and Electronics Engineers Inc., 2025. (2025 IEEE Kansas Power and Energy Conference, KPEC 2025).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Online Dynamic Mode Decomposition Based System Identification of Multi-Zone Building HVAC Systems

AU - Wu, Tumin

AU - Olama, Mohammed M.

AU - Djouadi, Seddik M.

PY - 2025

Y1 - 2025

N2 - Many works have recently been conducted to reduce the electricity consumption of smart buildings and allow them to support various grid services. Most of these works require accurate system models for the various appliances in the building including heating, ventilation, and air conditioning (HVAC) units. In this paper, we investigate a recursive data-driven system identification strategy to construct the thermal model for a time-varying building with a multi-zone HVAC unit. The online dynamic mode decomposition (DMD)-based strategy is employed to identify the multi-zone thermal building dynamics, where a simple information update (rank-1) is selected to avoid computational complexity. The DMD-based identification strategy is validated using a real gymnasium building equipped with a 4-zone HVAC unit, and its performance is compared with that of the traditional nuclear-norm subspace identification (N2SID) strategy.

AB - Many works have recently been conducted to reduce the electricity consumption of smart buildings and allow them to support various grid services. Most of these works require accurate system models for the various appliances in the building including heating, ventilation, and air conditioning (HVAC) units. In this paper, we investigate a recursive data-driven system identification strategy to construct the thermal model for a time-varying building with a multi-zone HVAC unit. The online dynamic mode decomposition (DMD)-based strategy is employed to identify the multi-zone thermal building dynamics, where a simple information update (rank-1) is selected to avoid computational complexity. The DMD-based identification strategy is validated using a real gymnasium building equipped with a 4-zone HVAC unit, and its performance is compared with that of the traditional nuclear-norm subspace identification (N2SID) strategy.

KW - Building HVAC system

KW - dynamic mode decomposition

KW - multi-zone HVAC unit

KW - nuclear norm subspace identification

KW - system identification

UR - https://www.scopus.com/pages/publications/105010556150

U2 - 10.1109/KPEC65465.2025.11045037

DO - 10.1109/KPEC65465.2025.11045037

M3 - Conference contribution

AN - SCOPUS:105010556150

T3 - 2025 IEEE Kansas Power and Energy Conference, KPEC 2025

BT - 2025 IEEE Kansas Power and Energy Conference, KPEC 2025

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2025 IEEE Kansas Power and Energy Conference, KPEC 2025

Y2 - 24 April 2025 through 25 April 2025

ER -

Online Dynamic Mode Decomposition Based System Identification of Multi-Zone Building HVAC Systems

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