Application of distributed model predictive approaches to temperature and CO2 concentration control in buildings

S.S.W. Walker; W. Lombardi; S. Lesecq; S. Roshany-Yamchi

doi:10.1016/j.ifacol.2017.08.107

Application of distributed model predictive approaches to temperature and CO₂ concentration control in buildings

S.S.W. Walker
, W. Lombardi
, S. Lesecq
, S. Roshany-Yamchi

Building Services

Research output: Contribution to journal › Conference article › peer-review

22 Citations (Scopus)

1 Downloads (Pure)

Abstract

In the context of energy consumption reduction, this paper focuses on the application of Model Predictive Control to occupants’ thermal comfort together with indoor air quality control while improving the whole building energy efficiency First, an open-space office split in three zones, located in Cork Institute of Technology, is modeled. A centralized MPC is designed to control the temperature and CO2 concentration in the three zones. Then, a distributed version of the MPC, with three separate local controllers, is considered. Finally, simulation results show that the distributed MPC solution achieves control performance quite close to the centralized version with less computing effort.

Original language	English
Pages (from-to)	2589-2594
Number of pages	6
Journal	IFAC-PapersOnLine
Volume	50
Issue number	1
DOIs	https://doi.org/10.1016/j.ifacol.2017.08.107
Publication status	Published - 1 Jul 2017
Event	20th World Congress of the International Federation of Automatic Control (IFAC 2017 World Congress) - Toulouse, France Duration: 9 Jul 2017 → 14 Jul 2017 Conference number: 20 https://www.ifac2017.org/

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

centralized
CO concentration
distributed
Energy management
Model Predictive Control
RC model
temperature

Access to Document

10.1016/j.ifacol.2017.08.107

Cite this

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title = "Application of distributed model predictive approaches to temperature and CO2 concentration control in buildings",

abstract = "In the context of energy consumption reduction, this paper focuses on the application of Model Predictive Control to occupants{\textquoteright} thermal comfort together with indoor air quality control while improving the whole building energy efficiency First, an open-space office split in three zones, located in Cork Institute of Technology, is modeled. A centralized MPC is designed to control the temperature and CO2 concentration in the three zones. Then, a distributed version of the MPC, with three separate local controllers, is considered. Finally, simulation results show that the distributed MPC solution achieves control performance quite close to the centralized version with less computing effort.",

keywords = "centralized, CO concentration, distributed, Energy management, Model Predictive Control, RC model, temperature",

author = "S.S.W. Walker and W. Lombardi and S. Lesecq and S. Roshany-Yamchi",

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AU - Walker, S.S.W.

AU - Lombardi, W.

AU - Lesecq, S.

AU - Roshany-Yamchi, S.

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AB - In the context of energy consumption reduction, this paper focuses on the application of Model Predictive Control to occupants’ thermal comfort together with indoor air quality control while improving the whole building energy efficiency First, an open-space office split in three zones, located in Cork Institute of Technology, is modeled. A centralized MPC is designed to control the temperature and CO2 concentration in the three zones. Then, a distributed version of the MPC, with three separate local controllers, is considered. Finally, simulation results show that the distributed MPC solution achieves control performance quite close to the centralized version with less computing effort.

KW - centralized

KW - CO concentration

KW - distributed

KW - Energy management

KW - Model Predictive Control

KW - RC model

KW - temperature

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