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 ProceedingsConference paper (refereed)Referred Conference Paperpeer-review

76 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 languageEnglish
Title of host publicationIEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT 2011
PublisherInstitute of Electrical and Electronics Engineers
ISBN (Electronic)9781612842202
ISBN (Print)9781612842189
DOIs
Publication statusPublished - Jan 2011
Externally publishedYes
Event2nd Conference on Innovative Smart Grid Technologies, ISGT 2011 - Anaheim, United States
Duration: 17 Jan 201119 Jan 2011

Publication series

NameInnovative Smart Grid Technologies (ISGT)
PublisherInstitute of Electrical and Electronics Engineers
ISSN (Print)2165-4816
ISSN (Electronic)2165-4824

Conference

Conference2nd Conference on Innovative Smart Grid Technologies, ISGT 2011
Country/TerritoryUnited States
CityAnaheim
Period17/01/1119/01/11

Keywords

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

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