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Economic Model Predictive Control for Hot Water Based Heating Systems in Smart Buildings
Institute of Physics, University of Oldenburg, Oldenburg, Germany
Centre for Electric Power and Energy, Department of Electrical Engineering, Technical University of Denmark, Roskilde, Denmark
Section of Building Energy, Department of Civil Engineering, Technical University of Denmark, Lyngby, Denmark
NEXT ENERGY, EWE Research Centre for Energy Technology at the University of Oldenburg, Oldenburg, Germany
- 1 Institute of Physics, University of Oldenburg, Oldenburg, Germany
- 2 Centre for Electric Power and Energy, Department of Electrical Engineering, Technical University of Denmark, Roskilde, Denmark
- 3 Section of Building Energy, Department of Civil Engineering, Technical University of Denmark, Lyngby, Denmark
- 4 NEXT ENERGY, EWE Research Centre for Energy Technology at the University of Oldenburg, Oldenburg, Germany
Energy and Power Engineering·Volume 09 (2017)·Pages 112–119·Published 6 April 2017·DOI10.4236/epe.2017.94B014
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Abstract
This paper presents a study to optimize the heating energy costs in a residential building with varying electricity price signals based on an Economic Model Predictive Controller (EMPC). The investigated heating system consists of an air source heat pump (ASHP) incorporated with a hot water tank as active Thermal Energy Storage (TES), where two optimization problems are integrated together to optimize both the ASHP electricity consumption and the building heating consumption utilizing a heat dynamic model of the building. The results show that the proposed EMPC can save the energy cost by load shifting compared with some reference cases.
KeywordsBuilding Energy Management SystemDemand ResponseEconomic Model Predictive ControlHeat PumpsSmart BuildingsThermal Energy Storage
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