IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i22p6016-d446813.html
   My bibliography  Save this article

Experimental Long-Term Investigation of Model Predictive Heat Pump Control in Residential Buildings with Photovoltaic Power Generation

Author

Listed:
  • Sebastian Kuboth

    (Chair of Engineering Thermodynamics and Transport Processes (LTTT), Center of Energy Technology (ZET), University of Bayreuth, 95440 Bayreuth, Germany)

  • Theresa Weith

    (Chair of Engineering Thermodynamics and Transport Processes (LTTT), Center of Energy Technology (ZET), University of Bayreuth, 95440 Bayreuth, Germany)

  • Florian Heberle

    (Chair of Engineering Thermodynamics and Transport Processes (LTTT), Center of Energy Technology (ZET), University of Bayreuth, 95440 Bayreuth, Germany)

  • Matthias Welzl

    (Chair of Engineering Thermodynamics and Transport Processes (LTTT), Center of Energy Technology (ZET), University of Bayreuth, 95440 Bayreuth, Germany)

  • Dieter Brüggemann

    (Chair of Engineering Thermodynamics and Transport Processes (LTTT), Center of Energy Technology (ZET), University of Bayreuth, 95440 Bayreuth, Germany)

Abstract

This article presents a 125-day experiment to investigate model predictive heat pump control. The experiment was performed in two parallel operated systems with identical components during the heating season. One of the systems was operated by a standard controller and thus represented a reference to evaluate the model predictive control. Both test rigs were heated by an air-source heat pump which is influenced by real weather conditions. A single-family house model depending on weather measurement data ensured a realistic heat consumption in the test rigs. The adapted model predictive control algorithm aimed to minimize the operational costs of the heat pump. The evaluation of the measurement results showed that the electrical energy demand of the heat pump can be reduced and the coefficient of performance can be increased by applying the model predictive controller. Furthermore, the self-consumption of photovoltaic electricity, which is calculated by means of a photovoltaic model and global radiation measurement data, was more than doubled. Consequently, the energy costs of heat pump operation were reduced by 9.0% in comparison to the reference and assuming German energy prices. The results were further compared to the scientific literature and short-term measurements were performed with the same experimental setup. The dependence of the measurement results on the weather conditions and the weather forecasting quality are shown. It was found that the duration of experiments should be as long as possible for a comprehensive evaluation of the model predictive control potential.

Suggested Citation

  • Sebastian Kuboth & Theresa Weith & Florian Heberle & Matthias Welzl & Dieter Brüggemann, 2020. "Experimental Long-Term Investigation of Model Predictive Heat Pump Control in Residential Buildings with Photovoltaic Power Generation," Energies, MDPI, vol. 13(22), pages 1-17, November.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:22:p:6016-:d:446813
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/22/6016/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/13/22/6016/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Široký, Jan & Oldewurtel, Frauke & Cigler, Jiří & Prívara, Samuel, 2011. "Experimental analysis of model predictive control for an energy efficient building heating system," Applied Energy, Elsevier, vol. 88(9), pages 3079-3087.
    2. 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.
    3. Fischer, David & Madani, Hatef, 2017. "On heat pumps in smart grids: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 342-357.
    4. Ronny Gelleschus & Michael Böttiger & Thilo Bocklisch, 2019. "Optimization-Based Control Concept with Feed-in and Demand Peak Shaving for a PV Battery Heat Pump Heat Storage System," Energies, MDPI, vol. 12(11), pages 1-16, June.
    5. Franco, Alessandro & Fantozzi, Fabio, 2016. "Experimental analysis of a self consumption strategy for residential building: The integration of PV system and geothermal heat pump," Renewable Energy, Elsevier, vol. 86(C), pages 1075-1085.
    6. Salpakari, Jyri & Lund, Peter, 2016. "Optimal and rule-based control strategies for energy flexibility in buildings with PV," Applied Energy, Elsevier, vol. 161(C), pages 425-436.
    7. Fischer, David & Bernhardt, Josef & Madani, Hatef & Wittwer, Christof, 2017. "Comparison of control approaches for variable speed air source heat pumps considering time variable electricity prices and PV," Applied Energy, Elsevier, vol. 204(C), pages 93-105.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Krzysztof Księżopolski & Mirosław Drygas & Kamila Pronińska & Iwona Nurzyńska, 2020. "The Economic Effects of New Patterns of Energy Efficiency and Heat Sources in Rural Single-Family Houses in Poland," Energies, MDPI, vol. 13(23), pages 1-19, December.
    2. Parantapa Sawant & Oscar Villegas Mier & Michael Schmidt & Jens Pfafferott, 2021. "Demonstration of Optimal Scheduling for a Building Heat Pump System Using Economic-MPC," Energies, MDPI, vol. 14(23), pages 1-15, November.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Clauß, John & Stinner, Sebastian & Sartori, Igor & Georges, Laurent, 2019. "Predictive rule-based control to activate the energy flexibility of Norwegian residential buildings: Case of an air-source heat pump and direct electric heating," Applied Energy, Elsevier, vol. 237(C), pages 500-518.
    2. Efkarpidis, Nikolaos A. & Vomva, Styliani A. & Christoforidis, Georgios C. & Papagiannis, Grigoris K., 2022. "Optimal day-to-day scheduling of multiple energy assets in residential buildings equipped with variable-speed heat pumps," Applied Energy, Elsevier, vol. 312(C).
    3. 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.
    4. Maria Pinamonti & Alessandro Prada & Paolo Baggio, 2020. "Rule-Based Control Strategy to Increase Photovoltaic Self-Consumption of a Modulating Heat Pump Using Water Storages and Building Mass Activation," Energies, MDPI, vol. 13(23), pages 1-21, November.
    5. Langer, Lissy & Volling, Thomas, 2020. "An optimal home energy management system for modulating heat pumps and photovoltaic systems," Applied Energy, Elsevier, vol. 278(C).
    6. Clara Ceccolini & Roozbeh Sangi, 2022. "Benchmarking Approaches for Assessing the Performance of Building Control Strategies: A Review," Energies, MDPI, vol. 15(4), pages 1-30, February.
    7. Pospíšil, Jiří & Špiláček, Michal & Kudela, Libor, 2018. "Potential of predictive control for improvement of seasonal coefficient of performance of air source heat pump in Central European climate zone," Energy, Elsevier, vol. 154(C), pages 415-423.
    8. Fischer, David & Madani, Hatef, 2017. "On heat pumps in smart grids: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 342-357.
    9. Guo, Yurun & Wang, Shugang & Wang, Jihong & Zhang, Tengfei & Ma, Zhenjun & Jiang, Shuang, 2024. "Key district heating technologies for building energy flexibility: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).
    10. Nolting, Lars & Praktiknjo, Aaron, 2019. "Techno-economic analysis of flexible heat pump controls," Applied Energy, Elsevier, vol. 238(C), pages 1417-1433.
    11. Fraga, Carolina & Hollmuller, Pierre & Schneider, Stefan & Lachal, Bernard, 2018. "Heat pump systems for multifamily buildings: Potential and constraints of several heat sources for diverse building demands," Applied Energy, Elsevier, vol. 225(C), pages 1033-1053.
    12. Roselli, C. & Diglio, G. & Sasso, M. & Tariello, F., 2019. "A novel energy index to assess the impact of a solar PV-based ground source heat pump on the power grid," Renewable Energy, Elsevier, vol. 143(C), pages 488-500.
    13. Felten, Björn & Weber, Christoph, 2018. "The value(s) of flexible heat pumps – Assessment of technical and economic conditions," Applied Energy, Elsevier, vol. 228(C), pages 1292-1319.
    14. Wilke, Christoph & Bensmann, Astrid & Martin, Stefan & Utz, Annika & Hanke-Rauschenbach, Richard, 2018. "Optimal design of a district energy system including supply for fuel cell electric vehicles," Applied Energy, Elsevier, vol. 226(C), pages 129-144.
    15. Finck, Christian & Li, Rongling & Kramer, Rick & Zeiler, Wim, 2018. "Quantifying demand flexibility of power-to-heat and thermal energy storage in the control of building heating systems," Applied Energy, Elsevier, vol. 209(C), pages 409-425.
    16. Joshua M. Pearce & Nelson Sommerfeldt, 2021. "Economics of Grid-Tied Solar Photovoltaic Systems Coupled to Heat Pumps: The Case of Northern Climates of the U.S. and Canada," Energies, MDPI, vol. 14(4), pages 1-17, February.
    17. Knudsen, Michael Dahl & Georges, Laurent & Skeie, Kristian Stenerud & Petersen, Steffen, 2021. "Experimental test of a black-box economic model predictive control for residential space heating," Applied Energy, Elsevier, vol. 298(C).
    18. Psimopoulos, Emmanouil & Bee, Elena & Widén, Joakim & Bales, Chris, 2019. "Techno-economic analysis of control algorithms for an exhaust air heat pump system for detached houses coupled to a photovoltaic system," Applied Energy, Elsevier, vol. 249(C), pages 355-367.
    19. Golmohamadi, Hessam & Larsen, Kim Guldstrand & Jensen, Peter Gjøl & Hasrat, Imran Riaz, 2022. "Integration of flexibility potentials of district heating systems into electricity markets: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
    20. Marszal-Pomianowska, Anna & Widén, Joakim & Le Dréau, Jérôme & Heiselberg, Per & Bak-Jensen, Birgitte & de Cerio Mendaza, Iker Diaz, 2020. "Operation of power distribution networks with new and flexible loads: A case of existing residential low voltage network," Energy, Elsevier, vol. 202(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:13:y:2020:i:22:p:6016-:d:446813. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.