Building Energy Allocation Using Distributed Model Predictive Control

Hongyi Li; Jun Xu

doi:10.1109/CFASTA57821.2023.10243279

Building Energy Allocation Using Distributed Model Predictive Control

Hongyi Li^*
, Jun Xu

^*Corresponding author for this work

Harbin Institute of Technology Shenzhen
Ministry of Education of the People's Republic of China

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

Abstract

In this paper, a distributed energy allocation strategy for energy shortage scenarios is proposed. Users are allowed to set the priority order so that the proposed strategy is able to meet the urgent needs. A building model containing three zones is created in Energyplus and the strategy is deployed in Matlab.By introducing Mle+, a joint simulation of MATLAB and Energyplus is implemented. Centralized, decentralized and distributed model predictive control are applied to the energy shortage scenario respectively, and the results show that our approach can satisfy the urgent need for energy supply.

Original language	English
Title of host publication	Proceedings of the 2nd Conference on Fully Actuated System Theory and Applications, CFASTA 2023
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	166-171
Number of pages	6
ISBN (Electronic)	9798350332162
DOIs	https://doi.org/10.1109/CFASTA57821.2023.10243279
State	Published - 2023
Externally published	Yes
Event	2nd Conference on Fully Actuated System Theory and Applications, CFASTA 2023 - Qingdao, China Duration: 14 Jul 2023 → 16 Jul 2023

Publication series

Name	Proceedings of the 2nd Conference on Fully Actuated System Theory and Applications, CFASTA 2023

Conference

Conference	2nd Conference on Fully Actuated System Theory and Applications, CFASTA 2023
Country/Territory	China
City	Qingdao
Period	14/07/23 → 16/07/23

Keywords

Distributed strategy
building energy distribution
model predictive control

Access to Document

10.1109/CFASTA57821.2023.10243279

Cite this

Li, H., & Xu, J. (2023). Building Energy Allocation Using Distributed Model Predictive Control. In Proceedings of the 2nd Conference on Fully Actuated System Theory and Applications, CFASTA 2023 (pp. 166-171). (Proceedings of the 2nd Conference on Fully Actuated System Theory and Applications, CFASTA 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CFASTA57821.2023.10243279

@inproceedings{4932493516f24028b2651c44afd6bf8c,

title = "Building Energy Allocation Using Distributed Model Predictive Control",

abstract = "In this paper, a distributed energy allocation strategy for energy shortage scenarios is proposed. Users are allowed to set the priority order so that the proposed strategy is able to meet the urgent needs. A building model containing three zones is created in Energyplus and the strategy is deployed in Matlab.By introducing Mle+, a joint simulation of MATLAB and Energyplus is implemented. Centralized, decentralized and distributed model predictive control are applied to the energy shortage scenario respectively, and the results show that our approach can satisfy the urgent need for energy supply.",

keywords = "Distributed strategy, building energy distribution, model predictive control",

author = "Hongyi Li and Jun Xu",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2nd Conference on Fully Actuated System Theory and Applications, CFASTA 2023 ; Conference date: 14-07-2023 Through 16-07-2023",

year = "2023",

doi = "10.1109/CFASTA57821.2023.10243279",

language = "英语",

series = "Proceedings of the 2nd Conference on Fully Actuated System Theory and Applications, CFASTA 2023",

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

pages = "166--171",

booktitle = "Proceedings of the 2nd Conference on Fully Actuated System Theory and Applications, CFASTA 2023",

address = "美国",

}

Li, H & Xu, J 2023, Building Energy Allocation Using Distributed Model Predictive Control. in Proceedings of the 2nd Conference on Fully Actuated System Theory and Applications, CFASTA 2023. Proceedings of the 2nd Conference on Fully Actuated System Theory and Applications, CFASTA 2023, Institute of Electrical and Electronics Engineers Inc., pp. 166-171, 2nd Conference on Fully Actuated System Theory and Applications, CFASTA 2023, Qingdao, China, 14/07/23. https://doi.org/10.1109/CFASTA57821.2023.10243279

Building Energy Allocation Using Distributed Model Predictive Control. / Li, Hongyi; Xu, Jun.
Proceedings of the 2nd Conference on Fully Actuated System Theory and Applications, CFASTA 2023. Institute of Electrical and Electronics Engineers Inc., 2023. p. 166-171 (Proceedings of the 2nd Conference on Fully Actuated System Theory and Applications, CFASTA 2023).

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

TY - GEN

T1 - Building Energy Allocation Using Distributed Model Predictive Control

AU - Li, Hongyi

AU - Xu, Jun

PY - 2023

Y1 - 2023

N2 - In this paper, a distributed energy allocation strategy for energy shortage scenarios is proposed. Users are allowed to set the priority order so that the proposed strategy is able to meet the urgent needs. A building model containing three zones is created in Energyplus and the strategy is deployed in Matlab.By introducing Mle+, a joint simulation of MATLAB and Energyplus is implemented. Centralized, decentralized and distributed model predictive control are applied to the energy shortage scenario respectively, and the results show that our approach can satisfy the urgent need for energy supply.

AB - In this paper, a distributed energy allocation strategy for energy shortage scenarios is proposed. Users are allowed to set the priority order so that the proposed strategy is able to meet the urgent needs. A building model containing three zones is created in Energyplus and the strategy is deployed in Matlab.By introducing Mle+, a joint simulation of MATLAB and Energyplus is implemented. Centralized, decentralized and distributed model predictive control are applied to the energy shortage scenario respectively, and the results show that our approach can satisfy the urgent need for energy supply.

KW - Distributed strategy

KW - building energy distribution

KW - model predictive control

UR - https://www.scopus.com/pages/publications/85173608755

U2 - 10.1109/CFASTA57821.2023.10243279

DO - 10.1109/CFASTA57821.2023.10243279

M3 - 会议稿件

AN - SCOPUS:85173608755

T3 - Proceedings of the 2nd Conference on Fully Actuated System Theory and Applications, CFASTA 2023

SP - 166

EP - 171

BT - Proceedings of the 2nd Conference on Fully Actuated System Theory and Applications, CFASTA 2023

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2nd Conference on Fully Actuated System Theory and Applications, CFASTA 2023

Y2 - 14 July 2023 through 16 July 2023

ER -

Li H, Xu J. Building Energy Allocation Using Distributed Model Predictive Control. In Proceedings of the 2nd Conference on Fully Actuated System Theory and Applications, CFASTA 2023. Institute of Electrical and Electronics Engineers Inc. 2023. p. 166-171. (Proceedings of the 2nd Conference on Fully Actuated System Theory and Applications, CFASTA 2023). doi: 10.1109/CFASTA57821.2023.10243279

Building Energy Allocation Using Distributed Model Predictive Control

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