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

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  • Christian Baumann

    (Illwerke vkw Endowed Professorship for Energy Efficiency, Energy Research Centre, Vorarlberg University of Applied Sciences, 6850 Dornbirn, Austria
    Josef Ressel Centre for Intelligent Thermal Energy Systems, Vorarlberg University of Applied Sciences, 6850 Dornbirn, Austria)

  • Philipp Wohlgenannt

    (Illwerke vkw Endowed Professorship for Energy Efficiency, Energy Research Centre, Vorarlberg University of Applied Sciences, 6850 Dornbirn, Austria
    Josef Ressel Centre for Intelligent Thermal Energy Systems, Vorarlberg University of Applied Sciences, 6850 Dornbirn, Austria
    Faculty of Engineering and Science, University of Agder, Jon Lilletuns vei 9, 4879 Grimstad, Norway)

  • Wolfgang Streicher

    (Unit of Energy Efficient Buildings, Department of Structural Engineering and Material Sciences, University of Innsbruck, Techniker Str. 13, 6020 Innsbruck, Austria)

  • Peter Kepplinger

    (Illwerke vkw Endowed Professorship for Energy Efficiency, Energy Research Centre, Vorarlberg University of Applied Sciences, 6850 Dornbirn, Austria
    Josef Ressel Centre for Intelligent Thermal Energy Systems, Vorarlberg University of Applied Sciences, 6850 Dornbirn, Austria)

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.

Suggested Citation

  • Christian Baumann & Philipp Wohlgenannt & Wolfgang Streicher & Peter Kepplinger, 2024. "Optimizing Heat Pump Control in an NZEB via Model Predictive Control and Building Simulation," Energies, MDPI, vol. 18(1), pages 1-24, December.
    • Handle: RePEc:gam:jeners:v:18:y:2024:i:1:p:100-:d:1556906
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    References listed on IDEAS

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    1. Kuboth, Sebastian & Heberle, Florian & König-Haagen, Andreas & Brüggemann, Dieter, 2019. "Economic model predictive control of combined thermal and electric residential building energy systems," Applied Energy, Elsevier, vol. 240(C), pages 372-385.
    2. Weeratunge, Hansani & Narsilio, Guillermo & de Hoog, Julian & Dunstall, Simon & Halgamuge, Saman, 2018. "Model predictive control for a solar assisted ground source heat pump system," Energy, Elsevier, vol. 152(C), pages 974-984.
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