Extension of a low-tech Model Predictive Control (MPC) algorithm for grid-supportive heat pump operation

• Grid-friendly and cost-optimized operation of heat pumps in buildings with thermally activated components (TAB). • The MPC-algorithm enables the simultaneous optimization of comfort parameters and heat supply costs. • Processing of weather forecast data and day-ahead electricity prices. • Cost savings are possible without any significant loss of comfort. • Low-tech design allows easy implementation of the MPC in existing buildings. This paper presents the further development of a low-tech Model Predictive Control (MPC) for the grid-friendly operation of heat pumps. The developed algorithm is already available in the literature [1] and successfully implemented in multiple buildings. The overall goal is, to predictively optimize comfort parameters taking into account weather forecast data for 48 h. A simple mathematical building model and an optimization function are used to calculate the heating (or cooling) requirement and determine the optimum heating (cooling) output curve over time. Based on the initial results, the algorithm is extended to include an energy price forecast. This modification enables the simultaneous optimization of comfort and heat supply costs. This forecast-based cost & comfort function is designed for the use of heat pumps in buildings with thermally activated components (TAB). The extension enables the MPC to process day-ahead electricity prices or other price signals in addition to weather forecast data. This means that the operation of heat pumps can be shifted to periods that are beneficial to the grid. The algorithm is analysed and validated in a Matlab/Simulink building simulation for a heating period of one sample month. A case study with different price scenarios is the main part of this paper. Depending on the assumed price fluctuation, the simulation leads to cost savings between 6.65 % and 12.5 % for the observation period of one month. The simulation results thus show that heat generation can be shifted to times with lower electricity prices, which leads to a significant reduction in heating costs without any significant loss of comfort. In conclusion, the developed low-tech MPC enables grid-supportive operation of heat pumps.

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Publication Details

Journal
Energy and Buildings
Published
2024-08-31
DOI
https://doi.org/10.1016/j.enbuild.2024.114733
Citations
14
Primary Topic
Smart Grid Energy Management
Type
article
Field-Weighted Citation Impact
2.92
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article

Extension of a low-tech Model Predictive Control (MPC) algorithm for grid-supportive heat pump operation

Magdalena Wolf, Tobias Pröll, Vukasin Klepic
14 citations
Energy and Buildings
Smart Grid Energy Management
2.92
article

Extension of a low-tech Model Predictive Control (MPC) algorithm for grid-supportive heat pump operation

Magdalena Wolf, Tobias Pröll, Vukasin Klepic
article en
14 citations

Abstract

• Grid-friendly and cost-optimized operation of heat pumps in buildings with thermally activated components (TAB). • The MPC-algorithm enables the simultaneous optimization of comfort parameters and heat supply costs. • Processing of weather forecast data and day-ahead electricity prices. • Cost savings are possible without any significant loss of comfort. • Low-tech design allows easy implementation of the MPC in existing buildings. This paper presents the further development of a low-tech Model Predictive Control (MPC) for the grid-friendly operation of heat pumps. The developed algorithm is already available in the literature [1] and successfully implemented in multiple buildings. The overall goal is, to predictively optimize comfort parameters taking into account weather forecast data for 48 h. A simple mathematical building model and an optimization function are used to calculate the heating (or cooling) requirement and determine the optimum heating (cooling) output curve over time. Based on the initial results, the algorithm is extended to include an energy price forecast. This modification enables the simultaneous optimization of comfort and heat supply costs. This forecast-based cost & comfort function is designed for the use of heat pumps in buildings with thermally activated components (TAB). The extension enables the MPC to process day-ahead electricity prices or other price signals in addition to weather forecast data. This means that the operation of heat pumps can be shifted to periods that are beneficial to the grid. The algorithm is analysed and validated in a Matlab/Simulink building simulation for a heating period of one sample month. A case study with different price scenarios is the main part of this paper. Depending on the assumed price fluctuation, the simulation leads to cost savings between 6.65 % and 12.5 % for the observation period of one month. The simulation results thus show that heat generation can be shifted to times with lower electricity prices, which leads to a significant reduction in heating costs without any significant loss of comfort. In conclusion, the developed low-tech MPC enables grid-supportive operation of heat pumps.

Energy and BuildingsVol. 323
BOKU University (AT)
Affordable and clean energy
Openalex Percentile: Top 8%
Smart Grid Energy Management
2.92
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