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

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. Howev...

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Main Authors: Christian Baumann, Philipp Wohlgenannt, Wolfgang Streicher, Peter Kepplinger
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Energies
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Online Access:https://www.mdpi.com/1996-1073/18/1/100
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author Christian Baumann
Philipp Wohlgenannt
Wolfgang Streicher
Peter Kepplinger
author_facet Christian Baumann
Philipp Wohlgenannt
Wolfgang Streicher
Peter Kepplinger
author_sort Christian Baumann
collection DOAJ
description 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 <i>IDA ICE</i> 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.
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spelling doaj-art-e15af2f0a87d48c4a2e194129d9b1c022025-01-10T13:17:06ZengMDPI AGEnergies1996-10732024-12-0118110010.3390/en18010100Optimizing Heat Pump Control in an NZEB via Model Predictive Control and Building SimulationChristian Baumann0Philipp Wohlgenannt1Wolfgang Streicher2Peter Kepplinger3Illwerke vkw Endowed Professorship for Energy Efficiency, Energy Research Centre, Vorarlberg University of Applied Sciences, 6850 Dornbirn, AustriaIllwerke vkw Endowed Professorship for Energy Efficiency, Energy Research Centre, Vorarlberg University of Applied Sciences, 6850 Dornbirn, AustriaUnit of Energy Efficient Buildings, Department of Structural Engineering and Material Sciences, University of Innsbruck, Techniker Str. 13, 6020 Innsbruck, AustriaIllwerke vkw Endowed Professorship for Energy Efficiency, Energy Research Centre, Vorarlberg University of Applied Sciences, 6850 Dornbirn, AustriaEU 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 <i>IDA ICE</i> 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.https://www.mdpi.com/1996-1073/18/1/100heat pumpModel Predictive Control (MPC)Mixed-Integer Linear Programming (MILP)PV self-consumptiondemand responsenet-zero energy building (NZEB)
spellingShingle Christian Baumann
Philipp Wohlgenannt
Wolfgang Streicher
Peter Kepplinger
Optimizing Heat Pump Control in an NZEB via Model Predictive Control and Building Simulation
Energies
heat pump
Model Predictive Control (MPC)
Mixed-Integer Linear Programming (MILP)
PV self-consumption
demand response
net-zero energy building (NZEB)
title Optimizing Heat Pump Control in an NZEB via Model Predictive Control and Building Simulation
title_full Optimizing Heat Pump Control in an NZEB via Model Predictive Control and Building Simulation
title_fullStr Optimizing Heat Pump Control in an NZEB via Model Predictive Control and Building Simulation
title_full_unstemmed Optimizing Heat Pump Control in an NZEB via Model Predictive Control and Building Simulation
title_short Optimizing Heat Pump Control in an NZEB via Model Predictive Control and Building Simulation
title_sort optimizing heat pump control in an nzeb via model predictive control and building simulation
topic heat pump
Model Predictive Control (MPC)
Mixed-Integer Linear Programming (MILP)
PV self-consumption
demand response
net-zero energy building (NZEB)
url https://www.mdpi.com/1996-1073/18/1/100
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