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Effect of ice thickness and snow cover depth on performance optimization of ground source heat pump based on the energy, exergy, economic and environmental analysis

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  • Nikitin, Andrey
  • Farahnak, Mehdi
  • Deymi-Dashtebayaz, Mahdi
  • Muraveinikov, Sergei
  • Nikitina, Veronika
  • Nazeri, Reza

Abstract

In recent years, due to the use of renewable energy such as geothermal and capability of reduction of energy consumption and greenhouse gas emissions by ground source heat pumps, these heat pump cycles have attracted considerable attention as a green energy system. The variations in temperature of soil play an important role in efficiency of ground source heat pump cycles which is determined by some effective parameters such as ambient temperature, soil type and depth. Besides, in cold regions where the ground is covered by snow and ice at least part of the year, the factors like the temperature and thickness of snow and ice layer are also effective on soil temperature. Therefore, this paper investigates the effects of variations of soil temperature on performance of ground source heat pump at different soil depths of 20 cm, 50 cm and 100 cm which are covered by 0 cm–50 cm of ice and 0 cm–40 cm of snow where the temperature of air ranges from −40 °C to 0 °C. The study is divided into two parts including the heat transfer analysis in soil covered with snow and ice using computational fluid dynamics and thermo-economic-environmental analysis of a proposed cascade ground source heat pump system. The proposed cascade heat pump cycle is operated using R41-R161 refrigerant pair as low global warming potential and zero ozone depletion potential working fluids. The continuity, Brinkman momentum and energy equations are firstly employed as governing equations for computational analysis to obtain the soil temperature profile. Then, the energy-exergy-economic-environmental analysis is performed to optimize the performance of the cascade ground source heat pump system based on the soil temperature profiles obtained from the previous step using Pareto-based multi-objective optimization method. Optimization results show that there is an optimal operating point for the proposed cascade ground source heat pump system where the maximum coefficient of performance of 3.2, maximum exergy efficiency of 64% and minimum total cost rate of 10300 $/year are obtained. Finally, the optimal soil depth and evaporator temperature are determined for different snow and ice thicknesses at different weather conditions.

Suggested Citation

  • Nikitin, Andrey & Farahnak, Mehdi & Deymi-Dashtebayaz, Mahdi & Muraveinikov, Sergei & Nikitina, Veronika & Nazeri, Reza, 2022. "Effect of ice thickness and snow cover depth on performance optimization of ground source heat pump based on the energy, exergy, economic and environmental analysis," Renewable Energy, Elsevier, vol. 185(C), pages 1301-1317.
    • Handle: RePEc:eee:renene:v:185:y:2022:i:c:p:1301-1317
    DOI: 10.1016/j.renene.2021.12.132
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    References listed on IDEAS

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    4. Ghorbani, Sobhan & Deymi-Dashtebayaz, Mahdi & Dadpour, Daryoush & Delpisheh, Mostafa, 2023. "Parametric study and optimization of a novel geothermal-driven combined cooling, heating, and power (CCHP) system," Energy, Elsevier, vol. 263(PF).
    5. Kheir Abadi, Majid & Davoodi, Vajihe & Deymi-Dashtebayaz, Mahdi & Ebrahimi-Moghadam, Amir, 2023. "Determining the best scenario for providing electrical, cooling, and hot water consuming of a building with utilizing a novel wind/solar-based hybrid system," Energy, Elsevier, vol. 273(C).
    6. Deymi-Dashtebayaz, Mahdi & Davoodi, Vajihe & Khutornaya, Julia & Sergienko, Olga, 2023. "Parametric analysis and multi-objective optimization of a heat pump dryer based on working conditions and using different refrigerants," Energy, Elsevier, vol. 284(C).
    7. Zhao, Zilong & Lv, Guoquan & Xu, Yanwen & Lin, Yu-Feng & Wang, Pingfeng & Wang, Xinlei, 2024. "Enhancing ground source heat pump system design optimization: A stochastic model incorporating transient geological factors and decision variables," Renewable Energy, Elsevier, vol. 225(C).

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