A Building Model Framework for a Genetic Algorithm Multi-objective Model Predictive Control

Krzysztof Arendt, Ana Ionesi, Muhyiddine Jradi, Ashok Kumar Singh, Mikkel Baun Kjærgaard, Christian Veje, Bo Nørregaard Jørgensen

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

Abstract

Model Predictive Control (MPC) of building systems is a promising approach to optimize building energy performance. In contrast to traditional control strategies which are reactive in nature, MPC optimizes the utilization of resources based on the predicted effects. It has been shown that energy savings potential of this
technique can reach up to 40% compared to conventional control strategies depending on the particular building type. However, the effort needed to implement MPC in buildings is significant and often considered prohibitive. That is why until now fully-functional MPC has been implemented only in few buildings. The following difficulties hinder the widespread usage of MPC: (1) significant model development time, (2) limited portability of models, (3) model computational demand. In the present study a new model development framework for an MPC system based on a Genetic Algorithm (GA) optimization is proposed. The framework is intended to allow easy model adaptation for new buildings and fast simulations to meet the strict performance requirements of the GA optimization approach. This is achieved by the introduction of the generic zone model concept and the implementation of the Functional Mock-Up Interface, which is used to link the models with the MPC system. The framework was used to develop and run initial
thermal and CO2 models. Their performance and the implementation procedure are discussed in the present paper. The framework is going to be implemented in the MPC system planned to be deployed in chosen public and commercial buildings in
Denmark and United States.
Original languageEnglish
Title of host publicationCLIMA 2016 : Proceedings of the 12th REHVA World Congress
EditorsPer Kvols Heiselberg
Number of pages12
Volume8
Place of PublicationAalborg
PublisherAalborg University. Department of Civil Engineering
Publication date2016
Article number186
ISBN (Electronic)87-91606-33-0, 87-91606-36-5
Publication statusPublished - 2016
Event12th REHVA World Congress CLIMA 2016 - Aalborg, Denmark
Duration: 22. May 201625. May 2016
http://www.clima2016.org/

Conference

Conference12th REHVA World Congress CLIMA 2016
CountryDenmark
CityAalborg
Period22/05/201625/05/2016
Internet address

Keywords

  • building energy simulation
  • model development
  • model predictive control
  • functional mock-up interface
  • Multi-objective Optimization

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  • Cite this

    Arendt, K., Ionesi, A., Jradi, M., Singh, A. K., Kjærgaard, M. B., Veje, C., & Jørgensen, B. N. (2016). A Building Model Framework for a Genetic Algorithm Multi-objective Model Predictive Control. In P. K. Heiselberg (Ed.), CLIMA 2016: Proceedings of the 12th REHVA World Congress (Vol. 8). [186] Aalborg University. Department of Civil Engineering. http://vbn.aau.dk/files/233777863/paper_186.pdf