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This paper reports a comprehensive survey of well drilling time and cost. The models include both specific correlations on various well types and generalised correlations for rough estimation. The ...

An economic assessment of different geothermal power cycle configurations to generate cost models is conducted in this study. The thermodynamic and exergoeconomic modeling of the cycles is performed in MATLAB coupled to Refprop. The models were derived based on robust multivariable regression to minimize the residuals by using the genetic algorithm. The cross-validation approach is applied to determine a dataset to examine the model in the training phase for validation and reduce the overfitting problem. The generated cost models are the total cost rate, the plant’s total cost, and power generation cost. The cost models and the relevant coefficients are generated based on the most compatibilities and lower error. The results showed that one of the most influential factors on the ORC cycle is the working fluid type, which significantly affects the final economic results. Other parameters that considerably impact economic models results, of all configurations, are geothermal fluid pressure and temperature and inlet pressure of turbine. Rising the geothermal fluid mass flow rate has a remarkable impact on cost models as the capacity and size of equipment increases. The generated cost models in this study can estimate the mentioned cost parameters with an acceptable deviation and provide a fast way to predict the total cost of the power plants.

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.

Emissions of contaminants and CO2 are becoming a relevant issue for the development of geothermal energy projects. Organic Rankine (ORC) Cycles present in this light particular appeal in the light of the possibility of total reinjection of the geothermal fluid resource including Non-Condensable Gases (NCGs). The Castelnuovo (IT) case study conditions are considered a saturated vapour resource at 10 bar pressure. The performance of the ORC cycle for power generation from this geothermal resource is evaluated through mass and energy balances, stepping up to exergy, Life Cycle Analysis (LCA) and Exergo-Environmental analyses (EEvA). The applied methodology allows to identify the most critical components of the system and to evaluate the environmental indicators of the system.

In this study, a conceptual geothermal power plant with Non-Condensable Gases (NCGs) reinjection is analyzed from energy, exergy, exergo-economic, and environmental perspectives. The cycle is evaluated in considering both subcritical and supercritical working conditions. A sensitivity analysis comprising the variation of condensing temperature, turbine inlet pressure, and amount of NCGs within the geofluid is performed to assess the system performance from the thermodynamic, economic, and environmental points of view. The exergy efficiency results for the supercritical and the subcritical cycles are 52% and 50.5%, respectively. Results showed increasing the condensing temperature decreases exergy efficiency, net power, and exergetic performance parameters and increases total exergy destruction, exergo-destruction impact, and specific power cost in both working cases. According to the obtained results, an increase in the inlet pressure of the turbine in the supercritical case study reduces exergy efficiency and exergetic performance and increases the exergo-destruction impact factor. However, it increases the cycle exergy efficiency and exergetic performance criteria first and then decreases in a subcritical case. The LCOE for the supercritical cycle is 6.96 ( c € / k W h ) and for the subcritical is 5.52 ( c € / k W h ) . The highest exergy destruction rates are related to the main heat exchanger, condenser, and turbine, respectively.

In this paper, exergy, exergoeconomic, and exergoenvironmental analysis of a gas turbine cycle and its optimization has been carried out by MOPSO algorithm. Three objective functions, namely, total cost rate, exergy efficiency of cycle, and CO2 emission rate have been considered. The design variables considered are: compressor pressure ratio, combustion chamber inlet temperature, gas turbine inlet temperature, compressor, and gas turbine isentropic efficiency. The impact of change in gas turbine inlet temperature and compressor pressure ratio on CO2 emission rate as well as impact of changes in gas turbine inlet temperature on exergy efficiency of the cycle has been investigated in different compressor pressure ratios. The results showed that with increase in compressor pressure ratio and gas turbine inlet temperature, CO2 emission rate decreases, that is this reduction is carried out with a steeper slope at lower pressure compressor ratio and gas turbine inlet temperature. The results showed that exergy efficiency of the cycle increases with increase in gas turbine inlet temperature and compressor pressure ratio. The sensitivity analysis of fuel cost changes was performed on objective functions. The results showed that at higher exergy efficiencies total cost rate is greater, and sensitivity of fuel cost optimum solutions is greater than Pareto curve with lower total cost rate. Also, the results showed that sensitivity of changes in fuel cost rate per unit of energy on total cost rate is greater than the rate of CO2 emission.

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.

Thermodynamic, exergy, economic and environmental analysis of a solid oxide fuel cell and gas turbine hybrid cycle have been done in this paper. Also, multi-objective optimization of this cycle has been done by NSGA-II algorithm. In order to defining of the optimum design point, interactive fuzzy multi-objective method has been used. At optimum point, the cost function value, 0.0435 ( U S $ / s ) and exergy efficiency approximately 57.7 % have been obtained. As well, sensitivity analysis of fuel cost per energy unit into objective functions has been done. In addition, rising inlet temperature of gas turbine from 900 up to 1600 ( K ) , has caused an increase in output power up to 8.5 % and entropy generation about 30 % and a reduction in exergy efficiency from 61.9 % to 51.7 % . By evaluation of entropy generation rate, it has been concluded that most of enthalpy generation rate (32 % ) is related to combustion chamber. Increasing of fuel cell stack temperature causes an increase in exergy efficiency from 56.6 % up to 60.2 % and about 34.8% in output power of the cycle and a reduction in exergy efficiency from 62.8 % to 59.1 % and 8.4 % in fuel cell power. Also, payback time of this cycle is about 3.12 years.

In this paper the exergy, economic and environmental analysis of Aliabad Katoul power plant as well as its multiobjective optimization have been done by NSGA-II algorithm. Two objective functions have been considered. The first objective function is the total cost rate and the second objective function is environmental impact cost. Optimization of objective functions has been done in two modes namely cycle with and without air preheater. The results showed that the existence of air preheater reduces both objective functions. So that in optimum point, for cycle without air preheater, the amount of total cost rate has been about 30% and environmental cost rate was about 33% higher than cycle with air preheater. Also, sensitive analysis of objective functions to fuel unit cost was conducted. At the lower environmental cost rate that the total cost rate was higher, sensitivity of Pareto solutions to the fuel unit cost was more than some parts of figure with smaller total cost rate. Also, exergy losses of various components were obtained that conclusions illustrated that combustion chamber has the maximum rate of exergy destruction (about 73%). Impact of ambient temperature variation on exergy losses and efficiency for different components was studied. The conclusions illustrated that with growing in ambient temperature, exergy efficiency of all parts decreased and exergy losses increased. Also, by rising the ambient temperature, exergy efficiency decreased, so that an increase in temperature from 293 Kelvin to 323 Kelvin, total exergy efficiency decreased from about 51% to 49%.

In this paper, exergy and exergoeconomic analysis and optimisation of a gas turbine cycle (case study) were performed by using three algorithms: NSGA-II, MOPSO and MOEA-D. Two objective functions were considered: total cost rate and exergy efficiency. In Pareto solution, the middle point was considered as the optimal solution, which is the lowest total cost rate (1.922 US$/s) was obtained which was 30% less than MOPSO algorithm and 6.2% less than MOEA-D algorithm. Also, the exergy efficiency in the NSGA-II algorithm was obtained about 55.1% which was 12% greater than MOPSO algorithm and 10% greater than MOEA-D algorithm. Also a sensitivity analysis of the design variables on objective functions is performed. Results show the highest rate of exergy destruction in all three optimisation methods was related to the combustion chamber. After overall comparison of the performance of these algorithms, the results showed that the NSGA-II algorithm had the best performance than the two others.