Thermodynamic, economic and thermo-economic optimization of a new proposed organic Rankine cycle for energy production from geothermal resources

The main goal of this study is to propose and investigate a new organic Rankine cycle based on three considered configurations: basic organic Rankine cycle, regenerative organic Rankine cycle and two-stage evaporator organic Rankine cycle in order to increase electricity generation from geothermal sources. To analyze the considered cycles' performance, thermodynamic (energy and exergy based on the first and second laws of thermodynamics) and economic (specific investment cost) models are investigated. Also, a comparison of cycles modeling results is carried out in optimum conditions according to different optimization which consist thermodynamic, economic and thermo-economic objective functions for maximizing exergy efficiency, minimizing specific investment cost and applying a multi-objective function in order to maximize exergy efficiency and minimize specific investment cost, respectively. Optimized operating parameters of cycles include evaporators and regenerative temperatures, pinch point temperature difference of evaporators and degree of superheat. Furthermore, Peng Robinson equation of state is used to obtain thermodynamic properties of isobutane and R123 which are selected as dry and isentropic working fluids, respectively. The results of optimization indicate that, thermal and exergy efficiencies increase and exergy destruction decrease especially in evaporators for both working fluids in new proposed organic Rankine cycle compared to the basic organic Rankine cycle. Moreover, the amount of specific investment cost in new organic Rankine cycle is obtained less than basic organic Rankine cycle during thermodynamic and economic optimization for R123. Finally, a profitability evaluation of new proposed and basic systems is performed based on total production cost and return on investment for three countries: Iran, France and America. Its results show that Iran has the maximum amount of return on investment. (C) 2016 Elsevier Ltd. All rights reserved.