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An optimal home energy management system for modulating heat pumps and photovoltaic systems

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  • Langer, Lissy
  • Volling, Thomas

Abstract

Efficient residential sector coupling plays a key role in supporting the energy transition. In this study, we analyze the structural properties associated with the optimal control of a home energy management system and the effects of common technological configurations and objectives. We conduct this study by modeling a representative building with a modulating air-sourced heat pump, a photovoltaic(PV) system, a battery, and thermal storage systems for floor heating and hot-water supply. In addition, we allow grid feed-in by assuming fixed feed-in tariffs and consider user comfort. In our numerical analysis, we find that the battery, naturally, is the essential building block for improving self-sufficiency. However, in order to use the PV surplus efficiently grid feed-in is necessary. The commonly considered objective of maximizing self-consumption is not economically viable under the given tariff structure; however, close-to-optimal performance and significant reduction in solution times can be achieved by maximizing self-sufficiency. Based on optimal control and considering seasonal effects, the dominant order of PV distribution and the target states of charge of the storage systems can be derived. Using a rolling horizon approach, the solution time can be reduced to less than 1min (achieving a time resolution of 1h per year). By evaluating the value of information, we find that the common horizon of 24h for prediction and control results in unintended but avoidable end-of-horizon effects. Our input data and mixed-integer linear model developed using the Julia JuMP programming language are available in an open-source manner.

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  • Langer, Lissy & Volling, Thomas, 2020. "An optimal home energy management system for modulating heat pumps and photovoltaic systems," Applied Energy, Elsevier, vol. 278(C).
    • Handle: RePEc:eee:appene:v:278:y:2020:i:c:s0306261920311570
    DOI: 10.1016/j.apenergy.2020.115661
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    4. Lissy Langer, 2020. "An Optimal Peer-to-Peer Market Considering Modulating Heat Pumps and Photovoltaic Systems under the German Levy Regime," Energies, MDPI, vol. 13(20), pages 1-25, October.
    5. Rikkas, Rebecka & Lahdelma, Risto, 2021. "Energy supply and storage optimization for mixed-type buildings," Energy, Elsevier, vol. 231(C).
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    7. Zhang, Heng & Zhang, Shenxi & Hu, Xiao & Cheng, Haozhong & Gu, Qingfa & Du, Mengke, 2022. "Parametric optimization-based peer-to-peer energy trading among commercial buildings considering multiple energy conversion," Applied Energy, Elsevier, vol. 306(PB).
    8. Vering, Christian & Maier, Laura & Breuer, Katharina & Krützfeldt, Hannah & Streblow, Rita & Müller, Dirk, 2022. "Evaluating heat pump system design methods towards a sustainable heat supply in residential buildings," Applied Energy, Elsevier, vol. 308(C).
    9. Binghui Han & Younes Zahraoui & Marizan Mubin & Saad Mekhilef & Mehdi Seyedmahmoudian & Alex Stojcevski, 2023. "Optimal Strategy for Comfort-Based Home Energy Management System Considering Impact of Battery Degradation Cost Model," Mathematics, MDPI, vol. 11(6), pages 1-26, March.
    10. Langer, Lissy & Volling, Thomas, 2022. "A reinforcement learning approach to home energy management for modulating heat pumps and photovoltaic systems," Applied Energy, Elsevier, vol. 327(C).
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