Economic Model Predictive Control for Building Energy Systems

Jingran MA; S. Joe QIN; Bo LI; Tim SALSBURY

doi:10.1109/ISGT.2011.5759140

Economic Model Predictive Control for Building Energy Systems

Jingran MA^*
, S. Joe QIN
, Bo LI
, Tim SALSBURY

^*Corresponding author for this work

Research output: Book Chapters | Papers in Conference Proceedings › Conference paper (refereed) › Referred Conference Paper › peer-review

77 Citations (Scopus)

Abstract

The objective of this study is to demonstrate the effectiveness of model predictive control (MPC) in reducing the energy and demand costs for buildings in an electricity grid with time-of-use pricing and demand charges. A virtual model for a single floor, multi-zone commercial building equipped with a variable air volume (VAV) cooling system is built by Energyplus. Real-time data exchange between Energyplus and Matlab controller is realized by introducing the building controls virtual test bed (BCVTB) as a middleware. System identification technique is implemented to obtain the zone temperature and power model, which are to be used in the MPC framework. MPC with an economic objective function is formulated as a linear programming problem and solved. Pre-cooling effect during off-peak period and autonomous cooling discharging from the building thermal mass during on-peak period can be observed in a continuous weekly simulation. Cost savings brought by MPC are given by comparing with the baseline and other pre-programmed control strategies. © 2011 IEEE.

Original language	English
Title of host publication	IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT 2011
Publisher	Institute of Electrical and Electronics Engineers
ISBN (Electronic)	9781612842202
ISBN (Print)	9781612842189
DOIs	https://doi.org/10.1109/ISGT.2011.5759140
Publication status	Published - Jan 2011
Externally published	Yes
Event	2nd Conference on Innovative Smart Grid Technologies, ISGT 2011 - Anaheim, United States Duration: 17 Jan 2011 → 19 Jan 2011

Publication series

Name	Innovative Smart Grid Technologies (ISGT)
Publisher	Institute of Electrical and Electronics Engineers
ISSN (Print)	2165-4816
ISSN (Electronic)	2165-4824

Conference

Conference	2nd Conference on Innovative Smart Grid Technologies, ISGT 2011
Country/Territory	United States
City	Anaheim
Period	17/01/11 → 19/01/11

UN SDGs

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

SDG 7 Affordable and Clean Energy

Keywords

Building Energy System
EnergyPlus
Model Predictive Control
Peak Demand Reduction
Simulation
System Identification

Access to Document

10.1109/ISGT.2011.5759140

Cite this

@inproceedings{d2e41fa1ba0d4f5d8d5f2518217a9d08,

title = "Economic Model Predictive Control for Building Energy Systems",

abstract = "The objective of this study is to demonstrate the effectiveness of model predictive control (MPC) in reducing the energy and demand costs for buildings in an electricity grid with time-of-use pricing and demand charges. A virtual model for a single floor, multi-zone commercial building equipped with a variable air volume (VAV) cooling system is built by Energyplus. Real-time data exchange between Energyplus and Matlab controller is realized by introducing the building controls virtual test bed (BCVTB) as a middleware. System identification technique is implemented to obtain the zone temperature and power model, which are to be used in the MPC framework. MPC with an economic objective function is formulated as a linear programming problem and solved. Pre-cooling effect during off-peak period and autonomous cooling discharging from the building thermal mass during on-peak period can be observed in a continuous weekly simulation. Cost savings brought by MPC are given by comparing with the baseline and other pre-programmed control strategies. {\textcopyright} 2011 IEEE.",

keywords = "Building Energy System, EnergyPlus, Model Predictive Control, Peak Demand Reduction, Simulation, System Identification",

author = "Jingran MA and QIN, \{S. Joe\} and Bo LI and Tim SALSBURY",

year = "2011",

month = jan,

doi = "10.1109/ISGT.2011.5759140",

language = "English",

isbn = "9781612842189",

series = "Innovative Smart Grid Technologies (ISGT)",

publisher = "Institute of Electrical and Electronics Engineers",

booktitle = "IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT 2011",

address = "United States",

note = "2nd Conference on Innovative Smart Grid Technologies, ISGT 2011 ; Conference date: 17-01-2011 Through 19-01-2011",

}

MA, J, QIN, SJ, LI, B & SALSBURY, T 2011, Economic Model Predictive Control for Building Energy Systems. in IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT 2011., 5759140, Innovative Smart Grid Technologies (ISGT), Institute of Electrical and Electronics Engineers, 2nd Conference on Innovative Smart Grid Technologies, ISGT 2011, Anaheim, California, United States, 17/01/11. https://doi.org/10.1109/ISGT.2011.5759140

Economic Model Predictive Control for Building Energy Systems. / MA, Jingran; QIN, S. Joe; LI, Bo et al.
IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT 2011. Institute of Electrical and Electronics Engineers, 2011. 5759140 (Innovative Smart Grid Technologies (ISGT)).

Research output: Book Chapters | Papers in Conference Proceedings › Conference paper (refereed) › Referred Conference Paper › peer-review

TY - GEN

T1 - Economic Model Predictive Control for Building Energy Systems

AU - MA, Jingran

AU - QIN, S. Joe

AU - LI, Bo

AU - SALSBURY, Tim

PY - 2011/1

Y1 - 2011/1

N2 - The objective of this study is to demonstrate the effectiveness of model predictive control (MPC) in reducing the energy and demand costs for buildings in an electricity grid with time-of-use pricing and demand charges. A virtual model for a single floor, multi-zone commercial building equipped with a variable air volume (VAV) cooling system is built by Energyplus. Real-time data exchange between Energyplus and Matlab controller is realized by introducing the building controls virtual test bed (BCVTB) as a middleware. System identification technique is implemented to obtain the zone temperature and power model, which are to be used in the MPC framework. MPC with an economic objective function is formulated as a linear programming problem and solved. Pre-cooling effect during off-peak period and autonomous cooling discharging from the building thermal mass during on-peak period can be observed in a continuous weekly simulation. Cost savings brought by MPC are given by comparing with the baseline and other pre-programmed control strategies. © 2011 IEEE.

AB - The objective of this study is to demonstrate the effectiveness of model predictive control (MPC) in reducing the energy and demand costs for buildings in an electricity grid with time-of-use pricing and demand charges. A virtual model for a single floor, multi-zone commercial building equipped with a variable air volume (VAV) cooling system is built by Energyplus. Real-time data exchange between Energyplus and Matlab controller is realized by introducing the building controls virtual test bed (BCVTB) as a middleware. System identification technique is implemented to obtain the zone temperature and power model, which are to be used in the MPC framework. MPC with an economic objective function is formulated as a linear programming problem and solved. Pre-cooling effect during off-peak period and autonomous cooling discharging from the building thermal mass during on-peak period can be observed in a continuous weekly simulation. Cost savings brought by MPC are given by comparing with the baseline and other pre-programmed control strategies. © 2011 IEEE.

KW - Building Energy System

KW - EnergyPlus

KW - Model Predictive Control

KW - Peak Demand Reduction

KW - Simulation

KW - System Identification

UR - https://www.scopus.com/pages/publications/79957989642

U2 - 10.1109/ISGT.2011.5759140

DO - 10.1109/ISGT.2011.5759140

M3 - Conference paper (refereed)

SN - 9781612842189

T3 - Innovative Smart Grid Technologies (ISGT)

BT - IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT 2011

PB - Institute of Electrical and Electronics Engineers

T2 - 2nd Conference on Innovative Smart Grid Technologies, ISGT 2011

Y2 - 17 January 2011 through 19 January 2011

ER -

Economic Model Predictive Control for Building Energy Systems

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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