Sustainable geothermal cooling of a residence in UAE using different refrigerants: a numerical analysis

Mona Albawab, Mamdouh El Haj Assad, Maryam Nooman AlMallahi, Sara Maen Asaad, Mahmoud Elgendi

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

This study investigates the feasibility of utilizing geothermal energy to mitigate the issue of substantial electricity requirements for cooling purposes in the United Arab Emirates (UAE), which is a crucial need for most of the year. The proposed solution involves harnessing geothermal energy as an alternative, eco-friendly, and readily available energy source. In this research, a ground source heat pump system is designed and tested through a parametric study and modeling simulation. Initially, the temperature distribution beneath the ground at various depths in the UAE is investigated, and the chosen location for the study was Al Ain City. Moreover, MATLAB software defines the system load by selecting a typical residential building and determining its cooling requirements. Based on this load, a comprehensive thermodynamic analysis is performed using the “GHX Design Toolbox”, and a mathematical model is developed to estimate the size of the ground source heat pump. The simulation considers the effect of the mass flow rate and exit temperature of the working fluid, the air’s dry-bulb temperature, the evaporator’s effectiveness on the coefficient of performance, cooling capacity, and the compressor’s performance. A 20-year operational scenario is simulated to evaluate the system’s performance over an extended period, and the results demonstrate reasonable readings throughout this extended time frame.

Original languageEnglish
JournalModeling Earth Systems and Environment
DOIs
Publication statusAccepted/In press - 2023

Keywords

  • COP
  • Geothermal energy
  • Heat pump
  • Modeling and simulation
  • Renewable energy

ASJC Scopus subject areas

  • Environmental Science(all)
  • Agricultural and Biological Sciences(all)
  • Computers in Earth Sciences
  • Statistics, Probability and Uncertainty

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