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Energy, exergy, and exergoeconomic evaluations of various geothermal configurations are reported. The main operational and economic parameters of the cycles are evaluated and compared. Multi-objective optimization of the cycles is conducted using the artificial bee colony algorithm. A sensitivity assessment is carried out on the effect of production well temperature variation on system performance from energy and economic perspectives. The results show that the flash-binary cycle has the highest thermal and exergy efficiencies, at 15.6% and 64.3%, respectively. The highest generated power cost and pay-back period are attributable to the simple organic Rankine cycle (ORC). Raising the well-temperature can increase the exergy destruction rate in all configurations. However, the electricity cost and pay-back period decrease. Based on the results, in all cases, the exergoenvironmental impact improvement factor decreases, and the temperature rises. The exergy destruction ratio and efficiency of all components for each configuration are calculated and compared. It is found that, at the optimum state, the exergy efficiencies of the simple organic Rankine cycle, single flash, double flash, and flash-binary cycles respectively are 14.7%, 14.4%, 12.6%, and 14.1% higher than their relevant base cases, while the pay-back periods are 10.6%, 1.5% 1.4%, and 0.6% lower than the base cases.

This research presents the energy, exergy, economic, and environmental assessment, and multi-objective optimization of a flash-binary geothermal CCHP cycle. A sensitivity analysis of production well inlet temperature and cooling to power flow ratio on exergetic, economic, and environmental parameters was conducted. Furthermore, the effects of the inflation rate and plant working hours on economic parameters were investigated. Results showed that increasing the production well inlet temperature harms exergy efficiency and exergetic performance criteria and results in a gain in exergo-environmental impact index and heating capacity. In addition, the total plant cost increased by raising the production well temperature. Furthermore, increasing the cooling to power flow ratio caused a reduction in exergy efficiency, exergetic performance criteria, and produced net power and an enhancement in exergy destruction, cooling capacity, and total plant cost. The exergy efficiency and total cost rate in the base case were 58% and 0.1764, respectively. Optimization results showed that at the selected optimum point, exergy efficiency was 4.5% higher, and the total cost rate was 10.3% lower than the base case. Levelized cost of energy and the pay-back period at the optimum point was obtained as 6.22 c$/kWh, 3.43 years, which were 5.14% and 6.7% lower than the base case.

A comprehensive cost correlation analysis was conducted based on available cost correlations, and new equipment cost correlation models were proposed based on QUE$TOR modeling. Cost correlations for various types of equipment such as pumps, compressors, heat exchangers, air coolers, and pressure vessels were generated on the basis of extracted cost data. The models were derived on the basis of robust multivariable regression with the aim of minimizing the residuals by using the genetic algorithm. The proposed compressor models for both centrifugal and reciprocating types showed that the Turton cost estimation for carbon steel compressor and Matche’s and Mhhe’s data were compatible with the generated model. According to the results, the cost trend in the Turton correlation for carbon steel had a somewhat lower estimation than these correlations. Further, the cost trend of the Turton correlation for carbon steel pressure vessels was close to the presented model trend for both bullet and sphere types. The Turton cost trend for U-tube shell-and-tube heat exchangers with carbon steel shell and stainless steel tube was close to the proposed heat exchanger model. Furthermore, the Turton cost trend for the flat-plate heat exchanger using carbon steel was similar to the proposed model with a slight difference.