Abstract

This paper presents the evaluation and optimization of an organic Rankine cycle (ORC) approached from four different perspectives: (1) selecting the ORC Cycle; (2) selecting the working fluid in accordance with the thermodynamic properties and environmental impacts; (3) analyzing energy and exergoeconomic; and finally, (4) advanced exergy and advanced exergoeconomic. The working fluid is selected based on the thermal source temperature and the environmental impacts including the reduction of ozone depletion (ODP) and global warming potential (GWP). Then, the selected working fluids in different cycles are investigated in terms of the thermodynamic properties based on energy and exergy concepts. The parameters of the selected cycles (from the perspective of energy and exergy), including the temperature and pressure of the input working fluid of the turbine, the pinch and approach temperature, and so on, are optimized by a genetic algorithm. Two objective functions of price and exergy efficiency are selected as the objective functions for optimal cycles. The results of this study reveal that single-pressure and dual-pressure cycles with recuperator and the R123 working fluid have the highest power and the lowest cost. It is indicated that the net power generation of dual pressure cycle with recuperator, single pressure with recuperator, and dual pressure cycle with two working fluids are 2.2 kW, (R123: 2.31 kW, R600: 1.72 kW) and 2.26 kW, respectively. Also, the cost of generated electricity for dual pressure cycle with recuperator, single pressure cycle with recuperator, and dual pressure cycle with two working fluids are 14.59, (R123: 13.03, R600: 21.95) and 16.78 (Cent/kWh), respectively. In addition, the results show that the cycles of dual pressure with recuperator and single pressure with recuperator with R123 as a working fluid have the highest exergy efficiency. The advanced exergy analysis indicated that the HRSG and turbine components are important to be improved based on exergetic performance.

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