Abstract

In this study, a cooling/power cogeneration cycle consisting of vapor-compression refrigeration and organic Rankine cycles is proposed and investigated. Utilizing geothermal water as a low-temperature heat source, various operating fluids, including R134a, R22, and R143a, are considered for the system to study their effects on cycle performance. The proposed cycle is modeled and evaluated from thermodynamic and thermoeconomic viewpoints by the Engineering Equation Solver (EES) software. Thermodynamic properties as well as exergy cost rates for each stream are found separately. Using R143a as the working fluid, thermal and exergy efficiencies of 27.2% and 57.9%, respectively, are obtained for the cycle. Additionally, the total product unit cost is found to be 60.7 $/GJ. A parametric study is carried out to determine the effects of several parameters, such as turbine inlet pressure, condenser temperature and pressure, boiler inlet air temperature, and pinch-point temperature difference, on the cycle performance. The latter is characterized by such parameters as thermal and exergy efficiencies, refrigeration capacity, produced net power rate, exergy destruction rate, and the production unit cost rates. The results indicate that the system using R134a exhibits the lowest thermal and exergy efficiencies among other working fluids, while the systems using R22 and R143a exhibit the highest energy and exergy efficiencies, respectively. The boiler and turbine contribute the most to the total exergy destruction rate.

Highlights

  • Increasing population growth and, growing fossil fuel consumption along with its limited availability, combined with the effects of greenhouse gas emissions from these fuels, threaten the wellbeing of humans and the environment

  • The organic Rankine cycle (ORC) and its various configurations have been broadly used in geothermal power plants

  • The ORC can be combined with the vapor-compression refrigeration cycle (VCC) to produce cooling [7]

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Summary

Introduction

Increasing population growth and, growing fossil fuel consumption along with its limited availability, combined with the effects of greenhouse gas emissions from these fuels, threaten the wellbeing of humans and the environment. Lucia et al [4] carried out a review on different ground source typologies of heat pumps and introduced an approach for their modelling, from the viewpoints of thermodynamics They suggested two possible ways for second law optimization of these systems for their future developments; one was based on a dynamic approach and the other one was based on using a control algorithm, operating on a set of variable configuration parameters on the basis of a time-running calculation for minimum entropy. Based on machine learning techniques, Palagi and Sciubba [9] proposed a methodology for optimizing the thermodynamic cycle as well as the radial in-flow turbine employed in a small-scale ORC In this method the physical model of the thermodynamic cycle is converted into a set of continuous and differentiable functions. Tajni et al [14] examined a new hybrid cycle comprising an ORC and a VCC, in which a low-temperature heat source was used, like solar or geothermal heat. Higher produced power and lower total production costs were observed for the cases using m-xylene, p-xylene, and ethylbenzene as working fluids

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