Optimum Exergy Efficiency Research Articles

Performance comparison of multi-objective evolutionary algorithms for exergetic and exergoenvironomic optimization of a benchmark combined heat and power system

This paper compares the Non-dominated sorting genetic algorithm-II, Pareto envelope-based selection algorithm-II, and Strength Pareto evolutionary algorithm-II, while optimizing a benchmark combined heat and power system with two conflicting objectives. The most effective algorithm is determined based on the statistical parameters evaluated from 30 runs of execution, considering the hypervolume indicator and the average computational time as the performance criteria. A comparative assessment shows that the Pareto envelope-based selection algorithm-II is superior to the other two algorithms. Further, in this study, a multi-criteria decision analysis is performed on the Pareto set obtained from the Pareto envelope-based selection algorithm-II, using the technique for order preference by similarity to an ideal solution, combined with the Entropy method. To show the advantages of multi-objective optimization, the optimal solutions are also compared with the base case, and previously published results of the benchmark problem corresponding to single-objective optimization. From the Pareto envelope-based selection algorithm-II derived optimal solutions, 15.82% increase in the exergy efficiency and 12.22% reduction in the system cost rate are achieved over the base case results. The present optimal exergy efficiency is 11.89% higher and the system cost rate is 1.9% lower than the single-objective based optimal results.

Economic performance assessment of a novel combined power generation cycle

In this paper, to improve the performance of the thermodynamic system and reduce greenhouse gas emissions and fuel utilization, a novel power generation system based on syngas-fueled solid oxide fuel cell, gas turbine, organic flash cycle, and a thermoelectric generator was devised. The performance of the proposed system was analyzed through energy, exergy, exergoeconomic, economic, and environmental viewpoints. Finally, the multi-objective particle swarm optimization algorithm and TOPSIS and LINMAP decision-making methods were employed to obtain the optimum performance. According to the obtained results at the base operation condition, the main performance metrics were FX, FX, FX, FX, FX. For fuel cost of 3 $/GJ and electricity cost of FX, the payback time was around FXyears with a total profit of FX at the end of the economic lifetime. The parametric study revealed that the SOFC with anode and cathode gas recycling exhibits a higher exergy efficiency and lower Levelized total emissions. For the energy-cost optimization scenario, the optimum energy efficiency selected by LINMAP methods was FX, and the minimum total specific cost selected by TOPSIS method was FX. For the exergy-cost optimization scenario, the optimum exergy efficiency selected by TOPSIS was FX.

Thermodynamic analysis and comparison of a novel dual-ejector based organic flash combined power and refrigeration cycle driven by the low-grade heat source

This proposes a novel dual-ejector based organic flash combined power and refrigeration cycle, which replaces the two throttle valves with two ejectors for the basic flash cycle, to provide power and cooling simultaneously for users. Detailed mathematical models of the proposed system are built and validated. The preliminary analysis results show that the exergy efficiency reaches 45.59% under geothermal water at 150℃. Then a parametric analysis is conducted to investigate the effects of five key parameters on system performance. The results show that both an optimal flash pressure and an extraction pressure exist to maximize the exergy efficiency. Finally, the proposed cycle, the separated power and refrigeration cycle consisting of a basic organic flash cycle and an ejector refrigeration cycle, and the basic organic flash cycle are optimized and compared by examining seven different organic fluids such as R245fa, R141b, R123, R245ca, R601, R365mfc, and R600. The results show that the R245fa brings the highest exergy efficiency to both the proposed cycle and organic flash cycle among seven involved organic fluids. Compared with the basic organic flash cycle, the proposed cycle with R245fa has a 4.91% percentage point higher exergy efficiency, 10.44% higher net power output, and an extra 172.6 kW of refrigeration output. Meanwhile, the optimal exergy efficiency and net power output of the proposed cycle are 5.82–6.80% percentage point higher and 15.06–23.87% higher than those of the separated power and refrigeration cycle. An exergy analysis suggests that the throttling losses are indeed significantly reduced by replacing the throttle valves with the ejectors for the organic flash cycle.

3E analysis and optimization of an innovative cogeneration system based on biomass gasification and solar photovoltaic thermal plant

In this study, an innovative hybrid solar/biomass cogeneration plant is designed and optimized to generate power and heat. Solar energy is harnessed using photovoltaic/thermal (PV/T) components to produce hydrogen via the water electrolysis method. The produced fuel is then used as an additive in the combustion chamber (CC) of a gas turbine (GT) cycle. The primary fuel used in the CC is high-temperature syngas produced in the gasification process of wooden biomass. Additionally, a steam Rankine cycle (SRC) coupled with a thermoelectric generator (TEG) is utilized to achieve higher efficiency. The proposed system is investigated in detail using thermodynamic approaches of energy, exergy, and exergo-economic analyses. The energy and exergy efficiencies of the system are determined as 69.15% and 23.11%, respectively. The system produces 14.55 MW of electricity with a total cost rate of $633.04/h and a unit product cost of $4.66/GJ. Finally, two optimizations are performed with the exergy efficiency and total cost rate and also exergy efficiency and levelized cost of electricity (LCOE) as the objective functions. In the first optimization, the optimum exergy efficiency is 4.02% less than that of the base case. However, the total cost rate of the system is improved drastically from $633.04/h in the base case to $212.29/h in the optimal case. In the second one, better exergy efficiency and also LCOE is achievable in comparison with the base case.

An Exergetic Model for the Ambient Air Temperature Impacts on the Combined Power Plants and its Management Using the Genetic Algorithm

4E analysis is used on a Brayton–Rankine combined cycle power plant (CCPP) with a dual pressure heat recovery steam generation (HRSG) system. A multi-objective genetic-based evolutionary optimization has been used to estimate the most optimal exergy efficiency status, exergy cost reduction, carbon emission reduction, and NOx emission reduction. For the validation of the data, the simulation results are compared with the plant’s data. This study investigates the effect of every decisive parameter on the objective performance parameters of the CCPP. The primary estimated results are the emission rates, efficiencies, and the exergoeconomic cost of the system. At the optimum operational state, the exergy efficiency may increase by 10%, while the total emissions may decrease by 14.6%. The conventional technical measures’ effectiveness to improve the combined cycle power plant’s energy performance is applied to the simulated case study. Results have shown that the main source of the exergy destruction in this system is the HRSG and the combustion chamber, and also the overall performance of the plant shows great sensitivity to the ambient air temperature. This fact has shown that climate change and global warming are effective in thermal power plants’ performance. Therefore, the effect of the climate change on the ambient air temperature impact on the power plant and the 4E performance of the simulated combined cycle power plant is also studied. The results show that, due to the global warming effect, the exergy efficiency of the CCPP unit is decreased by over 0.2% in the last two decades, which can be generalized to all thermal electricity generation units throughout the world based on the mean global temperature rise in the last decades.

Optimization of a new renewable energy system for producing electricity, hydrogen and ammonia

In this paper, an exergoeconomic analysis and optimization of a combined solar and wind energy based system is proposed. The trigeneration system produces ammonia, hydrogen and electricity through integrated solar photovoltaic panels and wind turbines. Also, an ammonia fuel cell unit is utilized for generating power during insufficient available energy. The overall exergetic efficiency is found to be 29.7% and the corresponding energetic efficiency is 28.5% under design conditions. In addition, the total cost rate is obtained as 63,345 $/h. Moreover, multi-objective optimization is performed with various decision variables at different combinations of solar intensities and wind speeds, considering the maximization of exergy efficiency and minimization of total cost rates. The developed system provides better optimal operation points under high wind speeds. The optimal exergy efficiency is found to vary between 10.9% and 38.2% depending on the available solar and wind energy. The corresponding optimal total cost rates vary between 11,959 $/h and 59,755 $/h, respectively. Several parametric studies are also performed to determine the effects of changing system conditions on the thermodynamic and economic performance of the developed system.

Possibility of optimal efficiency prediction of an organic Rankine cycle based on molecular property method for high-temperature exhaust gases

Working fluid selection is critical for the system design of an organic Rankine cycle (ORC). Computer-aided molecular design (CAMD) provides a new approach to search novel working fluids. In this study, the possibility of using molecular properties to predict the optimal system performance of an ORC is investigated. First, for a heat source of high-temperature exhaust gases, the influences of the molecular properties including the critical temperature and the specific heat capacity on the exergy efficiency of an ORC using 10 alkanes as working fluid are estimated. Then, the possibility of using the parameters of PC-SAFT to assess the optimal efficiency of the ORC is explored. The relation of the optimal temperature difference between the heat source and the molecular properties is determined. The prediction precision of PC-SAFT method is compared with the other four different molecular property methods. The results indicate that the parameters of PC-SAFT can be used to predict the optimal exergy efficiency of ORC system and the corresponding optimal heat source temperature. The average deviations of the exergy efficiency predicted is only 1.44% for the PC-SAFT method. The search range of the optimal working fluid can be decreased and the computation load is reduced significantly.

Development and multiobjective optimization of an integrated flash-binary geothermal power plant with reverse osmosis desalination and absorption refrigeration for multi-generation

This study investigates the thermodynamic and economic aspects of a multigeneration plant for inherent production of freshwater, power, cooling and heating by utilizing geothermal energy. The developed plant utilizes geothermal energy at a target temperature of 200 °C through a single flash-binary power plant with reinjection. The results of the thermodynamic analysis show that the overall plant energy and exergy efficiency of the plant can be as high as 61 % and 37.8 %, respectively, while the plant cost varies between 160–330 $/h. Optimization results show that an optimal exergy efficiency of 58 % is achievable when the plant cost rate is 242 $/h. The results indicate that geothermal driven freshwater production is one of the most economically feasible renewable driven clean production options, while a flash/binary power plant results in higher efficiency and lower electricity costs.

Multi-objective optimization of a concentrated solar energy driven trigeneration plant with thermal energy storage: A case study for Turkey

A Plant for trigeneration of freshwater, power and cooling has been developed and optimized for higher efficiency and lower plant cost. Parabolic trough collectors with thermal energy storage are considered using thermal oil as the heat transfer fluid. Solar heat is utilized to produce power via a Toluene-based Rankine cycle for power generation and cooling via an Absorption chiller. A part of the generated power is used to run a Reverse Osmosis desalination plant. The solar data is taken from a southern city in Turkey. Exergy efficiency and plant cost rate of the system vary between 9–14% and 287–335 $/h, respectively. A multiobjective optimization study depicts that optimal exergy efficiency of %12.5 is obtainable at a plant cost rate of 328 $/h. Freshwater cost is strongly dependent on the cost of solar electricity and shows a significant fluctuation due to variable solar availability condition. The results of the studied system depict that sustainable and economical plant operation is possible in short/near terms when the investment costs of utilized technologies are competitive with those used in conventional plants.

Multi-objective optimization and decision analysis of a system based on biomass fueled SOFC using couple method of entropy/VIKOR

A power generation system including solid oxide fuel cell (SOFC), gasifier, and high-temperature sodium heat pipes was modeled using the Lagrange method of undetermined multipliers. The model validation was performed in comparison with the data available in the literature. The results showed that the presented model had a high validity. The parametric analysis showed that there was an optimum value for current density to achieve the highest net power but the exergy efficiency was reduced gradually with the current density. Response surface methodology (RSM) was utilized for multi-objective optimization purpose. The analysis of variance (ANOVA) was performed and different regression models with high validity were presented for power (R2 = 93.40%) and exergy efficiency (R2 = 96.22%). The one-objective optimization was performed using the interaction effect of parameters derived by ANOVA. The multi-objective optimization results indicated that the optimum power was achieved at relatively low exergy efficiencies and the optimum exergy efficiency was accompanied by low powers. A stepwise multi-objective optimization procedure was conducted and an optimum region was recognized. The performance of the system was assessed from energy, exergy, and environmental viewpoints for different biomasses including pine sawdust, groundnut shell, rice straw, rice husk, eucalyptus, sunflower shell, and sugarcane bagasse. Multi-criteria decision making (MCDM) analysis was implemented in order to select the biomass with the best performance. The cold gas efficiency, energy efficiency, exergy destruction rate, CO2 emission, and fuel flow rate were selected as different criteria. The MCDM results revealed that eucalyptus had the best performance.

Investigation of Exergy of Double-Pipe Heat Exchanger Using Synthesized Hybrid Nanofluid Developed by Modeling

Synthesized copper oxide nanoparticles were incorporated on the surfaces of carbon nanotubes using ultrasonication condition and incipient wetness impregnation technique (IWI). Morphological surfaces and structures of the prepared nanocomposite were investigated by the Scanning Electron Microscopy (SEM) and X-ray diffraction (XRD). Results showed a modification of thermophysical properties of prepared hybrid nanofluids compared to untreated carbon nanotube-water. Four parameters (Reynolds number, nanofluid volume fraction, twisted (pitch) ratio, and cavity diameter ratio) were investigated, and their impacts on the exergy efficiency enhancement of double-pipe heat exchanger were determined. Modifying response surface methodology-central composite design (RSM-CCD) to realize the optimal exergy efficiency of the system (98.4 %) showed the possibility to improve all control variables contemporarily and with significant accuracy. There was a strong correlation between the experimental and predicted values by Artificial Neural Network-Genetic Algorithm (ANN-GA) (R2 = 0.92). Minimum mean square error (MSE) was found using a three-layer ANN with 10 neurons in the hidden layer. The results show that the increased Reynolds number and nanofluid volume fraction lead to increases in the heat transfer and exergy efficiency of the system. However, while adding pitches and cavities of the spiral strip to heat exchanger increases heat transfer due to the increasing turbulence flow, at larger pitches and cavity numbers, heat transfer and exergy efficiency were reduced. This was confirmed using two computer-modeling approaches which allow optimization of the exergy of the system.

Exergy efficiency optimization model of motorized spindle system for high-speed dry hobbing

High-speed dry hobbing (HSDH) has been regarded as an environmentally benign gear machining technique. Current research on energy efficiency of machine tool focuses on the energy efficiency for workpiece material removal but rarely involves the energy consumption required to control thermal stability. Due to the fact that thermal effect dominates the machining accuracy and accuracy consistency, especially in the dry machining process, the energy consumption for thermal stability control should be taken as useful energy consumption. In view of this, by taking the motorized spindle system (MSS) as the study objective, which is a core subsystem of machine tool enabling HSDH and characterizes intensive and inefficient energy consumption, an exergy-based method is proposed to evaluate the comprehensive energy efficiency of MSS. Furthermore, an exergy efficiency optimization model is proposed to maximize total exergy efficiency and minimize average temperature of MSS. A solution method integrating Pareto Dominant-based Multi-objective Simulated Annealing (PDMOSA) and Technique for Order of Preference by Similarity to an Ideal Solution (TOPSIS) is proposed to search the best solution of the optimization model. A case study is introduced to validate the proposed model and a final optimal solution is obtained at the total exergy efficiency of 53.5% with balanced temperature of 35.4 °C. The cooling water in MSS is identified to be a dominant factor that affects total exergy destruction. The presented model can give a reference to select appropriate process parameters of MSS for green and precision machining.

Exergy and improvement potential of hybrid photovoltaic thermal/thermoelectric (PVT/TE) air collector

In this paper, a review of exergy and improvement potential (IP) of solar thermal systems is presented. The review includes exergy analysis of photovoltaic thermal (PVT) systems, solar drying systems and solar collectors. Solar collectors, which are the most essential components of solar thermal systems, receive solar energy and convert it into thermal energy. Since the solar/PVT collector system is an essential component when the design of sustainability is considered, exergy analysis, which provides a more representative performance rating. In addition, a theoretical and experimental performance of hybrid photovoltaic thermal/thermoelectric (PVT/TE) air collector is investigated. A steady-state thermal analysis of a hybrid PVT/TE air collector is developed to predict air outlet and photovoltaic (PV) temperatures. The predicted results are in close agreement with the experimental study. The percentage error of air outlet and PV temperatures between theoretical and experimental value is 1.1% and 2.6% respectively. On the other hand, the simulated model is then used to study the performances of a hybrid PVT/TE air collector using exergy analysis for the mass flow rate ranging between 0.001 kg/s to 0.15 kg/s and a solar radiation of 600 W/m2. The effect of mass flow rate on exergy efficiency and an advance prospective are observed. The optimum exergy efficiency of PVT/TE obtained is relatively 0.38. In addition, IP is proposed in this study.

Parametric analysis and optimization for exergoeconomic performance of a combined system based on solid oxide fuel cell-gas turbine and supercritical carbon dioxide Brayton cycle

Fuel cell-gas turbine hybrid system is a potential field of investigation. This study establishes a modeling and optimization framework for a novel hybrid system consisting of a solid oxide fuel cell, a gas turbine and a supercritical carbon dioxide Brayton cycle. Based on the proposed thermodynamical model, a parametric analysis is investigated to determine the impacts of several key parameters on the system exergoeconomic performance. Meanwhile, bi-objective optimization is conducted for maximizing the exergy efficiency and minimizing the levelized cost of electricity via the Epsilon-constraint approach. The Linear Programming Techniques for Multidimensional Analysis of Preference decision-making approach is further employed to select the Pareto optimum solution from Pareto frontiers. The results show that several extreme values for the exergy efficiency and the levelized cost of electricity exist in a series of sensitivity curves, respectively. The Pareto frontiers indicates that with the increase of the exergy efficiency, the levelized cost of electricity shows a moderately increasing trend at first and increases rapidly afterward. Overall, at the Pareto optimum solution, the combined system can achieve an optimal exergy efficiency and levelized cost of electricity by 68% and 0.0575 $ kWh−1, respectively.

Comparative study of two novel micro-CCHP systems based on organic Rankine cycle and Kalina cycle

With regard to the significant role of combined cooling, heating, and power (CCHP) systems in performance enhancement of power plants, two novel micro-CCHP systems are presented which are based on organic Rankine cycle (ORC) and Kalina cycle (KC) as topping cycles. Additionally, ejector refrigeration cycle (ERC) and vapor compression heat pump cycle (VCHPC) are utilized as the bottoming cycle of the power systems. To demonstrate feasibility of the recommended micro-CCHP systems, an exhaustive thermodynamic modeling and exergoeconomic analysis are employed as the most effective tools for performance evaluation of the systems. Also, to get better performance of the systems, single- and multi-criteria optimizations are carried out, using genetic algorithm. It is figured out that the KC-based micro-CCHP system has higher optimum thermal efficiency and total sum unit cost of the product (SUCP) than the ORC-based micro-CCHP system, while it had lower exergy efficiency. Regarding that, the optimum thermal efficiency for the ORC- and KC-based micro-CCHP systems are computed by 76.54% and 77.32%, respectively, whilst the optimum exergy efficiency for the ORC- and KC-based micro-CCHP systems are calculated by 48.37% and 31.2%, respectively. In addition, generator had the major exergy destruction rate among all components for both systems. Furthermore, the results of parametric study proved that higher thermal (energy) efficiency can be computed with increasing the heat source temperature, heater temperature, evaporation temperature, and terminal temperature difference of the recovery heat exchangers.

Multi-criteria optimization and comparative performance analysis of a power plant fed by municipal solid waste using a gasifier or digester

The Waste-to-Energy technology through gasification, pyrolysis, combustion, and digestion has recently turned into an unavoidable alternative for the municipalities in various parts of the World. Besides a considerable reduction in the waste volume, it can generate steam and electricity. In the present work, two techniques (gasification and digestion) are implemented in the Tehran’s 3 MW Waste-to-Energy power plant; where these technologies are investigated and compared from the viewpoint of thermodynamics, thermoeconomic, and environmental impacts. Also, multi-objective optimization based on genetic algorithm is applied to find the optimum exergy efficiency and total product unit cost of each model. The input municipal solid waste is converted to a high enthalpy syngas via gasification or biogas via digestion to provide the required heat for steam generation in a Rankine power cycle. The best ranges of the effective parameters in optimal point for both models are obtained from the scattered distribution method. Also, the exergy destruction and the exergetic efficiency of every component is calculated to assess the irreversibilities in the system. Results show that the gasifier and the combustion chamber have the highest exergy destruction in the models (a) and (b). Parametric study and environmental impact analysis indicate that model (b) is the more suitable option from energy, exergy, exergoeconomic, and environmental viewpoints. From the multi-objective optimization results, it is inferred that the exergy efficiency for the model (a) and (b) at the optimum point is 17.98% and 19.02%, respectively while the corresponding total product unit cost is 28.31 $/GJ and 27.68 $/GJ.

Energy and exergy analysis of reciprocating natural gas expansion engine based on valve configurations

Natural gas pressure should be reduced in city gate stations before consuming. Part of the physical exergy of this high pressure gas is wasted if throttling valves are employed for pressure reduction. Reciprocating natural gas expansion engine (RNGEE) could be utilized to recover most of the physical exergy. In this study, a single acting RNGEE is investigated thermodynamically in order to optimize the ports opening/closing times. For this purpose, cylinder and slide valves and two types of piston valves have been modeled and compared. Based on an exergy analysis, a genetic algorithm has been developed to optimize the valves timing. Moreover, effects of the pressure ratio on the exergetic efficiency and power generation of the RNGEE have been studied numerically. Methane was modeled as a real gas by employing AGA8 equation of state. Results showed that beside importance of exergy efficiency optimization, inlet process period has also critical impacts on engine performance. Moreover, power generation is almost the same while using cylinder or flange valves (∼1986 kW/kg) with exergy efficiencies of 83.6% and 82.7% respectively. In contrast, slide and piston valves are found to have lower power generation (1746 kW/kg and 1753 kW/kg respectively) with the exergy efficiency of ∼72%.

Multi-objective optimization and sensitivity analysis of an organic Rankine cycle coupled with a one-dimensional radial-inflow turbine efficiency prediction model

The organic Rankine cycle (ORC) has been demonstrated to be a viable approach to recover low-grade waste heat and has been widely investigated in recent years. In the current research focused on the multi-objective optimization problem of ORC systems, few scholars consider the variation in turbine efficiency with the cycle parameters. This paper focused on the comparison of multi-objective optimization with variable turbine efficiency and that with constant turbine efficiency. The results obtained for the two types of turbine efficiency were compared, and the differences were analyzed. Flue gas at 523.15 K was used as the heat source, and pentane, hexane, heptane, cyclohexane, benzene and toluene were selected as working fluid candidates. The one-dimensional radial-inflow turbine efficiency prediction model was applied to replace constant turbine efficiency. The multi-objective model in conjunction with the turbine efficiency model was constructed by defining the net power output and system total cost per unit net power output as the objective functions. The non-dominated sorting genetic algorithm-II (NSGA-II) was used to optimize the evaporation temperature and condensation temperature as the decision variables. With the aid of the ideal point, the optimal solution of each working fluid was selected from the Pareto frontier. The results showed that the turbine efficiency varies with changes in evaporation temperature and condensation temperature. In the multi-optimization with constant turbine efficiency, toluene and cyclohexane are the optimal working fluids, whereas with variable turbine efficiency, benzene is the optimal working fluid. In the sensitivity analysis, the optimal exergy efficiency shows opposite trends for the multi-objective optimization with constant and variable turbine efficiency.

Multi-objective optimization of a gas turbine-based CCHP combined with solar and compressed air energy storage system

The small-scale compressed air energy storage system (CAES) combined with renewable energy sources (RES) is becoming increasing popular in distributed energy system (DES), which allows RES uninterrupted and improves the supply capacity of power system. In order to balance the electricity load and improve the energy efficiency of CCHP system in combined cooling, heating and power (CCHP) system, the paper described a CCHP system combined with solar and compressed air energy storage (CCHP-S-CAES). Solar energy was coupled with the CAES in this paper to heat the high-pressure air from air storage cavern. The proposed system consists of a conventional CCHP, a CAES and a solar energy collector/storage system, which stores the surplus electric power of gas turbine during off-peak time and releases it during on-peak time. Sensitivity analysis on the CCHP-S-CAES system was conducted to investigate the effects of the key parameters on its performances. It is clear that the performances of the CCHP-S-CAES system are mainly determined by the pressure ratio of compressor, the inlet pressure and temperature of turbine and the effectiveness of heat exchangers. In addition, a multi-objective optimization based on the Non-dominated sorting Genetic Algorithm-II (NSGA-II) is performed for obtaining the optimum performance of the CCHP-S-CAES system from the view of investment cost and exergy efficiency. The results show that the optimal exergy efficiency of the proposed system is about 53.10% and 45.36% in maximum heating condition and maximum cooling condition respectively.

Optimization of the combined supercritical CO2 cycle and organic Rankine cycle using zeotropic mixtures for gas turbine waste heat recovery

In order to further improve the efficiency of the gas turbine, a novel combined supercritical CO2 regenerative cycle and organic Rankine cycle using zeotropic mixtures for waste heat recovery of gas turbine is proposed. The zeotropic mixtures used in the present study are cyclopentane/R365mfc. Exergoeconomic analysis is reported for the proposed system and parametric studies have been carried out to investigate the effect of system parameters on the exergy efficiency and the unit cost of electricity. The multi-objective optimization method based on genetic algorithm is chosen to obtain the optimum system parameters. The results show that the overall values of the exergoeconomic factor, the optimal exergy efficiency and the optimal unit cost of electricity of the proposed system are 31.88%, 62.23% and 3.95 cent/kW h, respectively. The obtained result reveals the superiority of the proposed combined regenerative S-CO2 cycle and ORC system compared to the combined basic S-CO2 cycle and ORC system, the combined recompression S-CO2 cycle and ORC system. Therefore, the proposed system is suitable for gas turbine waste heat recovery, and it has advantages of deep utilization of waste heat, high efficiency and low cost.