Identification of aggregate building thermal dynamic model and unmeasured internal heat load from data

Zhong Guo; Austin R. Coffman; Jeffrey Munk; Piljae Im; Prabir Barooah

doi:10.1109/CDC40024.2019.9030198

Identification of aggregate building thermal dynamic model and unmeasured internal heat load from data

Zhong Guo, Austin R. Coffman, Jeffrey Munk, Piljae Im, Prabir Barooah

Integrated Building Deployment and Analy

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

4 Scopus citations

Abstract

This paper is on the problem of simultaneously identifying the parameters of an aggregate thermal dynamic model of a multi-zone building and unknown disturbances from input-output data. An aggregate model is a single-zone equivalent of a multi-zone building, and is useful for many purposes, including model based control of large heating, ventilation and air conditioning (HVAC) equipment that delivers thermal energy to the entire building. A key challenge in identification is the presence of unknown disturbance since it is not measurable but non-negligible.We first present a principled method to aggregate a multizone building model into a single zone model. We then provide a method to identify thermal parameters and the unknown disturbance for this aggregate (single-zone) model. Finally, we test our proposed identification algorithm to data generated from a virtual building. A key insight provided by the aggregation method allows us to recognize under what conditions the estimation of the disturbance signal will be necessarily poor and uncertain.

Original language	English
Title of host publication	2019 IEEE 58th Conference on Decision and Control, CDC 2019
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2958-2963
Number of pages	6
ISBN (Electronic)	9781728113982
DOIs	https://doi.org/10.1109/CDC40024.2019.9030198
State	Published - Dec 2019
Event	58th IEEE Conference on Decision and Control, CDC 2019 - Nice, France Duration: Dec 11 2019 → Dec 13 2019

Publication series

Name	Proceedings of the IEEE Conference on Decision and Control
Volume	2019-December
ISSN (Print)	0743-1546
ISSN (Electronic)	2576-2370

Conference

Conference	58th IEEE Conference on Decision and Control, CDC 2019
Country/Territory	France
City	Nice
Period	12/11/19 → 12/13/19

Funding

ZG, AC, and PB are with the Department of Mechanical and Aerospace Engineering at the University of Florida. PI and JM are with the Building Envelope & Urban Systems Research group at Oak Ridge National Laboratory, Oak Ridge, Tennessee. The research reported here has been partially supported by the NSF through awards 1463316 (CMMI) and 1646229 (CPS), and DOE GMLC grant titled “virtual batteries”. The authors would like to thank Naren Raman and Bo Chen for help with the Casadi software.

Access to Document

10.1109/CDC40024.2019.9030198

Cite this

Guo, Z., Coffman, A. R., Munk, J., Im, P., & Barooah, P. (2019). Identification of aggregate building thermal dynamic model and unmeasured internal heat load from data. In 2019 IEEE 58th Conference on Decision and Control, CDC 2019 (pp. 2958-2963). Article 9030198 (Proceedings of the IEEE Conference on Decision and Control; Vol. 2019-December). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CDC40024.2019.9030198

@inproceedings{0e304fe1057c47a491171e01a5bef86c,

title = "Identification of aggregate building thermal dynamic model and unmeasured internal heat load from data",

abstract = "This paper is on the problem of simultaneously identifying the parameters of an aggregate thermal dynamic model of a multi-zone building and unknown disturbances from input-output data. An aggregate model is a single-zone equivalent of a multi-zone building, and is useful for many purposes, including model based control of large heating, ventilation and air conditioning (HVAC) equipment that delivers thermal energy to the entire building. A key challenge in identification is the presence of unknown disturbance since it is not measurable but non-negligible.We first present a principled method to aggregate a multizone building model into a single zone model. We then provide a method to identify thermal parameters and the unknown disturbance for this aggregate (single-zone) model. Finally, we test our proposed identification algorithm to data generated from a virtual building. A key insight provided by the aggregation method allows us to recognize under what conditions the estimation of the disturbance signal will be necessarily poor and uncertain.",

author = "Zhong Guo and Coffman, {Austin R.} and Jeffrey Munk and Piljae Im and Prabir Barooah",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 58th IEEE Conference on Decision and Control, CDC 2019 ; Conference date: 11-12-2019 Through 13-12-2019",

year = "2019",

month = dec,

doi = "10.1109/CDC40024.2019.9030198",

language = "English",

series = "Proceedings of the IEEE Conference on Decision and Control",

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

pages = "2958--2963",

booktitle = "2019 IEEE 58th Conference on Decision and Control, CDC 2019",

}

Guo, Z, Coffman, AR, Munk, J, Im, P & Barooah, P 2019, Identification of aggregate building thermal dynamic model and unmeasured internal heat load from data. in 2019 IEEE 58th Conference on Decision and Control, CDC 2019., 9030198, Proceedings of the IEEE Conference on Decision and Control, vol. 2019-December, Institute of Electrical and Electronics Engineers Inc., pp. 2958-2963, 58th IEEE Conference on Decision and Control, CDC 2019, Nice, France, 12/11/19. https://doi.org/10.1109/CDC40024.2019.9030198

Identification of aggregate building thermal dynamic model and unmeasured internal heat load from data. / Guo, Zhong; Coffman, Austin R.; Munk, Jeffrey et al.
2019 IEEE 58th Conference on Decision and Control, CDC 2019. Institute of Electrical and Electronics Engineers Inc., 2019. p. 2958-2963 9030198 (Proceedings of the IEEE Conference on Decision and Control; Vol. 2019-December).

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

TY - GEN

T1 - Identification of aggregate building thermal dynamic model and unmeasured internal heat load from data

AU - Guo, Zhong

AU - Coffman, Austin R.

AU - Munk, Jeffrey

AU - Im, Piljae

AU - Barooah, Prabir

PY - 2019/12

Y1 - 2019/12

N2 - This paper is on the problem of simultaneously identifying the parameters of an aggregate thermal dynamic model of a multi-zone building and unknown disturbances from input-output data. An aggregate model is a single-zone equivalent of a multi-zone building, and is useful for many purposes, including model based control of large heating, ventilation and air conditioning (HVAC) equipment that delivers thermal energy to the entire building. A key challenge in identification is the presence of unknown disturbance since it is not measurable but non-negligible.We first present a principled method to aggregate a multizone building model into a single zone model. We then provide a method to identify thermal parameters and the unknown disturbance for this aggregate (single-zone) model. Finally, we test our proposed identification algorithm to data generated from a virtual building. A key insight provided by the aggregation method allows us to recognize under what conditions the estimation of the disturbance signal will be necessarily poor and uncertain.

AB - This paper is on the problem of simultaneously identifying the parameters of an aggregate thermal dynamic model of a multi-zone building and unknown disturbances from input-output data. An aggregate model is a single-zone equivalent of a multi-zone building, and is useful for many purposes, including model based control of large heating, ventilation and air conditioning (HVAC) equipment that delivers thermal energy to the entire building. A key challenge in identification is the presence of unknown disturbance since it is not measurable but non-negligible.We first present a principled method to aggregate a multizone building model into a single zone model. We then provide a method to identify thermal parameters and the unknown disturbance for this aggregate (single-zone) model. Finally, we test our proposed identification algorithm to data generated from a virtual building. A key insight provided by the aggregation method allows us to recognize under what conditions the estimation of the disturbance signal will be necessarily poor and uncertain.

UR - http://www.scopus.com/inward/record.url?scp=85082460298&partnerID=8YFLogxK

U2 - 10.1109/CDC40024.2019.9030198

DO - 10.1109/CDC40024.2019.9030198

M3 - Conference contribution

AN - SCOPUS:85082460298

T3 - Proceedings of the IEEE Conference on Decision and Control

SP - 2958

EP - 2963

BT - 2019 IEEE 58th Conference on Decision and Control, CDC 2019

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 58th IEEE Conference on Decision and Control, CDC 2019

Y2 - 11 December 2019 through 13 December 2019

ER -

Guo Z, Coffman AR, Munk J, Im P, Barooah P. Identification of aggregate building thermal dynamic model and unmeasured internal heat load from data. In 2019 IEEE 58th Conference on Decision and Control, CDC 2019. Institute of Electrical and Electronics Engineers Inc. 2019. p. 2958-2963. 9030198. (Proceedings of the IEEE Conference on Decision and Control). doi: 10.1109/CDC40024.2019.9030198

Identification of aggregate building thermal dynamic model and unmeasured internal heat load from data

Abstract

Publication series

Conference

Funding

Access to Document

Other files and links

Fingerprint

Cite this