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Prediction Model for the Internal Temperature of a Greenhouse with a Water-to-Water Heat Pump Using a Pellet Boiler as a Heat Source Using Building Energy Simulation

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  • Chung-Geon Lee

    (Agriculture and Life Sciences Research Institute, Kangwon National University, Hyoja 2 Dong 192-1, Chuncheon-si 24341, Korea)

  • La-Hoon Cho

    (Department of Interdisciplinary Program in Smart Agriculture, Kangwon National University, Hyoja 2 Dong 192-1, Chuncheon-si 24341, Korea)

  • Seok-Jun Kim

    (Department of Interdisciplinary Program in Smart Agriculture, Kangwon National University, Hyoja 2 Dong 192-1, Chuncheon-si 24341, Korea)

  • Sun-Yong Park

    (Department of Interdisciplinary Program in Smart Agriculture, Kangwon National University, Hyoja 2 Dong 192-1, Chuncheon-si 24341, Korea)

  • Dae-Hyun Kim

    (Department of Biosystems Engineering, Kangwon National University, Hyoja 2 Dong 192-1, Chuncheon-si 24341, Korea)

Abstract

Although smart farms are considered an alternative to traditional agriculture, they require large amounts of energy and high investment costs, hindering their efficient implementation. In the Republic of Korea, the energy supply is primarily for heating rather than cooling, necessitating the accurate prediction of the greenhouse internal temperature to determine the feasibility of agricultural management while using renewable energy. This study developed a model (TRNSYS) for predicting the internal temperature of a greenhouse using building energy simulation. A greenhouse heating experiment was conducted using a hybrid heating system simulated by TRNSYS to analyze the prediction model. The regression analysis of the experimental and simulation results revealed an R 2 and RMSE of 0.8834 and 3.61, respectively. A comparative analysis was conducted with the existing hot air heating system to evaluate the heating performance and economic feasibility of the hybrid system. Overall, the heating performance exhibited satisfactory results, whereas the economic analysis, based on life cycle cost, revealed a cost reduction effect of 9.45%. Hence, greenhouse heating using renewable energy can replace conventional fossil fuels with economic advantages. Moreover, the prediction of the internal temperature of the greenhouse will facilitate the design of a systematic smart farm business to prevent duplicate investment.

Suggested Citation

  • Chung-Geon Lee & La-Hoon Cho & Seok-Jun Kim & Sun-Yong Park & Dae-Hyun Kim, 2022. "Prediction Model for the Internal Temperature of a Greenhouse with a Water-to-Water Heat Pump Using a Pellet Boiler as a Heat Source Using Building Energy Simulation," Energies, MDPI, vol. 15(15), pages 1-17, August.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:15:p:5677-:d:880588
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    References listed on IDEAS

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    1. Chung-Geon Lee & La-Hoon Cho & Seok-Jun Kim & Sun-Yong Park & Dae-Hyun Kim, 2021. "Comparative Analysis of Combined Heating Systems Involving the Use of Renewable Energy for Greenhouse Heating," Energies, MDPI, vol. 14(20), pages 1-22, October.
    2. Sithole, H. & Cockerill, T.T. & Hughes, K.J. & Ingham, D.B. & Ma, L. & Porter, R.T.J. & Pourkashanian, M., 2016. "Developing an optimal electricity generation mix for the UK 2050 future," Energy, Elsevier, vol. 100(C), pages 363-373.
    3. Potrč, Sanja & Čuček, Lidija & Martin, Mariano & Kravanja, Zdravko, 2021. "Sustainable renewable energy supply networks optimization – The gradual transition to a renewable energy system within the European Union by 2050," Renewable and Sustainable Energy Reviews, Elsevier, vol. 146(C).
    Full references (including those not matched with items on IDEAS)

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