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Article

Optimizing Heat Pump Control in an NZEB via Model Predictive Control and Building Simulation

by
Christian Baumann
1,2,*,
Philipp Wohlgenannt
1,2,3,
Wolfgang Streicher
4 and
Peter Kepplinger
1,2
1
Illwerke vkw Endowed Professorship for Energy Efficiency, Energy Research Centre, Vorarlberg University of Applied Sciences, 6850 Dornbirn, Austria
2
Josef Ressel Centre for Intelligent Thermal Energy Systems, Vorarlberg University of Applied Sciences, 6850 Dornbirn, Austria
3
Faculty of Engineering and Science, University of Agder, Jon Lilletuns vei 9, 4879 Grimstad, Norway
4
Unit of Energy Efficient Buildings, Department of Structural Engineering and Material Sciences, University of Innsbruck, Techniker Str. 13, 6020 Innsbruck, Austria
*
Author to whom correspondence should be addressed.
Energies 2025, 18(1), 100; https://doi.org/10.3390/en18010100
Submission received: 3 December 2024 / Revised: 23 December 2024 / Accepted: 28 December 2024 / Published: 30 December 2024
(This article belongs to the Special Issue Energy Efficiency and Energy Performance in Buildings)

Abstract

EU regulations get stricter from 2028 on by imposing net-zero energy building (NZEB) standards on new residential buildings including on-site renewable energy integration. Heat pumps (HP) using thermal building mass, and Model Predictive Control (MPC) provide a viable solution to this problem. However, the MPC potential in NZEBs considering the impact on indoor comfort have not yet been investigated comprehensively. Therefore, we present a co-simulative approach combining MPC optimization and IDA ICE building simulation. The demand response (DR) potential of a ground-source HP and the long-term indoor comfort in an NZEB located in Vorarlberg, Austria over a one year period are investigated. Optimization is performed using Mixed-Integer Linear Programming (MILP) based on a simplified RC model. The HP in the building simulation is controlled by power signals obtained from the optimization. The investigation shows reductions in electricity costs of up to 49% for the HP and up to 5% for the building, as well as increases in PV self-consumption and the self-sufficiency ratio by up to 4% pt., respectively, in two distinct optimization scenarios. Consequently, the grid consumption decreased by up to 5%. Moreover, compared to the reference PI controller, the MPC scenarios enhanced indoor comfort by reducing room temperature fluctuations and lowering the average percentage of people dissatisfied by 1% pt., resulting in more stable indoor conditions. Especially precooling strategies mitigated overheating risks in summer and ensured indoor comfort according to EN 16798-1 class II standards.
Keywords: heat pump; Model Predictive Control (MPC); Mixed-Integer Linear Programming (MILP); PV self-consumption; demand response; net-zero energy building (NZEB); building simulation heat pump; Model Predictive Control (MPC); Mixed-Integer Linear Programming (MILP); PV self-consumption; demand response; net-zero energy building (NZEB); building simulation

Share and Cite

MDPI and ACS Style

Baumann, C.; Wohlgenannt, P.; Streicher, W.; Kepplinger, P. Optimizing Heat Pump Control in an NZEB via Model Predictive Control and Building Simulation. Energies 2025, 18, 100. https://doi.org/10.3390/en18010100

AMA Style

Baumann C, Wohlgenannt P, Streicher W, Kepplinger P. Optimizing Heat Pump Control in an NZEB via Model Predictive Control and Building Simulation. Energies. 2025; 18(1):100. https://doi.org/10.3390/en18010100

Chicago/Turabian Style

Baumann, Christian, Philipp Wohlgenannt, Wolfgang Streicher, and Peter Kepplinger. 2025. "Optimizing Heat Pump Control in an NZEB via Model Predictive Control and Building Simulation" Energies 18, no. 1: 100. https://doi.org/10.3390/en18010100

APA Style

Baumann, C., Wohlgenannt, P., Streicher, W., & Kepplinger, P. (2025). Optimizing Heat Pump Control in an NZEB via Model Predictive Control and Building Simulation. Energies, 18(1), 100. https://doi.org/10.3390/en18010100

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