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Potential of predictive control for improvement of seasonal coefficient of performance of air source heat pump in Central European climate zone


  • Pospíšil, Jiří
  • Špiláček, Michal
  • Kudela, Libor


This paper compares different operation models of the air-to-water heat pump (HP). Detail focus of this study aims at a potential to increase seasonal coefficient of performance (SCOP) by utilising the predictive control. The considered predictive control uses an outdoor air temperature forecast for the upcoming 48 h. The predictive control operates the heat pump so that it runs, preferably, during the periods of the day with the highest air temperature. For a detailed assessment, a model of the heat supply system with a heat pump supplemented by a heat accumulator has been developed. The mathematical model involves detailed algorithm for time-dependent quantification of the heat demand for the considered model building. Dataset of real operation tests of the HP helps correctly evaluate the coefficient of performance (COP). An original algorithm of predictive control has been developed and tested for different operating parameters and different capacities of the heat accumulator. A long-term record of air temperatures from the last ten years is employed to evaluate the model. The mathematical model allows for a complex parametrical study to evaluate the relations of SCOP - accumulator capacity, SCOP - method of heat pump control.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:energy:v:154:y:2018:i:c:p:415-423
    DOI: 10.1016/

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    References listed on IDEAS

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    5. 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.
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    7. Wanjiru, Evan M. & Sichilalu, Sam M. & Xia, Xiaohua, 2017. "Model predictive control of heat pump water heater-instantaneous shower powered with integrated renewable-grid energy systems," Applied Energy, Elsevier, vol. 204(C), pages 1333-1346.
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    Cited by:

    1. Rakesh Sinha & Birgitte Bak-Jensen & Jayakrishnan Radhakrishna Pillai & Hamidreza Zareipour, 2019. "Flexibility from Electric Boiler and Thermal Storage for Multi Energy System Interaction," Energies, MDPI, Open Access Journal, vol. 13(1), pages 1-21, December.
    2. Jiří Pospíšil & Michal Špiláček & Pavel Charvát, 2019. "Seasonal COP of an Air-to-Water Heat Pump when Using Predictive Control Preferring Power Production from Renewable Sources in the Czech Republic," Energies, MDPI, Open Access Journal, vol. 12(17), pages 1-13, August.
    3. Rödder, Maximilian & Frank, Lena & Kirschner, Daniel & Neef, Matthias & Adam, Mario, 2018. "EnergiBUS4home – Sustainable energy resourcing in low-energy buildings," Energy, Elsevier, vol. 159(C), pages 638-647.
    4. Valeria Palomba & Efstratios Varvagiannis & Sotirios Karellas & Andrea Frazzica, 2019. "Hybrid Adsorption-Compression Systems for Air Conditioning in Efficient Buildings: Design through Validated Dynamic Models," Energies, MDPI, Open Access Journal, vol. 12(6), pages 1-28, March.
    5. Oravec, Juraj & Bakošová, Monika & Galčíková, Lenka & Slávik, Michal & Horváthová, Michaela & Mészáros, Alajos, 2019. "Soft-constrained robust model predictive control of a plate heat exchanger: Experimental analysis," Energy, Elsevier, vol. 180(C), pages 303-314.


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