Potential Energy Flexibility for a Hot-Water Based Heating System in Smart Buildings Via Economic Model Predictive Control

Awadelrahman M. A. Ahmed, Yi Zong, Lucian Mihet-Popa, Jorge Bruna, Carsten Agert, Xianyong Xiao

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

This paper studies the potential of shifting the heating energy consumption in a residential building to low price periods based on varying electricity price signals suing Economic Model Predictive Control strategy. The investigated heating system consists of a heat pump incorporated with a hot water tank as active thermal energy storage, where two optimization problems are integrated together to optimize both the heat pump electricity consumption and the building heating consumption. A sensitivity analysis for the system flexibility is examined. The results revealed that the proposed controller can successfully achieve significant shifting potentials compared to a baseline case.
Original languageEnglish
Title of host publicationProceedings of 2017 International Symposium on Computer Science and Intelligent Controls
Number of pages5
PublisherIEEE
Publication date2017
Pages1-5
ISBN (Print)978-1-5386-2941-3
DOIs
Publication statusPublished - 2017
Event2017 International Symposium on Computer Science and Intelligent Controls - Budapest University of Technology and Economics, Budapest, Hungary
Duration: 20 Oct 201722 Oct 2017

Conference

Conference2017 International Symposium on Computer Science and Intelligent Controls
LocationBudapest University of Technology and Economics
CountryHungary
CityBudapest
Period20/10/201722/10/2017

Keywords

  • Building Energy Management System
  • Demand Response
  • Economic Model Predictive Control
  • Energy Flexibility
  • Heat Pumps
  • Smart Buildings
  • Thermal Energy Storage

Cite this

Ahmed, A. M. A., Zong, Y., Mihet-Popa, L., Bruna, J., Agert, C., & Xiao, X. (2017). Potential Energy Flexibility for a Hot-Water Based Heating System in Smart Buildings Via Economic Model Predictive Control. In Proceedings of 2017 International Symposium on Computer Science and Intelligent Controls (pp. 1-5). IEEE. https://doi.org/10.1109/ISCSIC.2017.14