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The current research deals with thermodynamic and economic analyses and optimization of a geothermal system integrated with organic Rankine flash cycle (ORFC) and a polymer electrolyte membrane fuel cell (PEM-FC). A thermodynamic model for ORFC and PEM-FC is developed to investigate employing the PEM-FC in a combined geothermal ORFC. A comparative study is carried out to determine the effect of applying PEM-FC in a geothermal based ORFC. The validation of PEM-FC simulation with experimental data from the literature shows a good agreement. The results of numerical modeling indicate that using the rejected heat in the PEM-FC instead of the low-temperature geothermal source can increase the net output power from 254.9 kW to 1628.9 kW and the exergy efficiency from 23.77% to 36.19%, in the case of R123 as working fluid for the ORC system. Furthermore, using the PEM-FC imposes 9.07 US$/h cost rate to the system. Additionally the parametric study shows that the net output power and the total cost rate of the system are two major objective functions for the optimization. Thus, a multi-objective genetic algorithm is applied to determine the optimal values of design parameters with respect to some practical constraints. The results of the multi-criteria optimization represent that the optimum value of decision variables with considered objective functions are T 1 = 116 °C , r f l a s h = 0.55 , P F C = 230 kPa , and P 4 = 1208.4 kPa .

This research aims to understand the impacts of volume concentration of Fe3O4 nanoparticles and temperature on the viscosity & thermal conductivity of liquid paraffin based nanofluid. Several experiments are conducted in the Fe3O4 concentration range of 0.5–3% and temperature range of 20–90 °C. Oleic acid is utilized as a surfactant for the improved dispersibility and stability of nanofluids. It was found that the nanofluid behaves as a shear thinning fluid. Additionally, it was revealed that both the thermal conductivity and viscosity boost with increasing the nanoparticle concentration, whereas when the temperature increases the viscosity reduces and the thermal conductivity rises. Moreover, the Artificial Neural Network (ANN) was utilized to model the thermal conductivity and viscosity of the nanofluid using experimental data. The accuracy of the models was assessed based on four known statistical indices including root meant square (RMS), root mean square error (RMSE), mean absolute deviation (MAE), and coefficient of determination ( R 2 ). Results showed that the proposed model of thermal conductivity could estimate outputs with RMS, RMSE, MAE & R 2 values of 0.0678, 0.0179, 0.0041 and 0.96, respectively.

The objective of this experimental investigation is to assess the variations of thermal conductivity and viscosity of liquid paraffin-Al2O3 nanofluid containing oleic acid surfactant against temperature, nanoparticle mass concentration and surfactant concentration. The experiments are performed in the temperature range of 20–50 °C, nanoparticle mass concentration range of 1–5%, and surfactant/nanoparticle mass ratio of 1:3, 2:3 and 3:3. The results showed that the nanofluid behaves as a shear thinning fluid. Besides, it was found that boosting the nanoparticle concentration causes an increase in the thermal conductivity and viscosity, while augmenting the temperature results in a decrease in the viscosity and an increase in the thermal conductivity. Moreover, it was observed that the viscosity increases with surfactant concentration, while the thermal conductivity initially rises with surfactant concentration and then reduces. Furthermore, the Artificial Neural Network (ANN) was implemented to model the thermal conductivity and viscosity of the nanofluid using experimental data. The findings depicted that the thermal conductivity model predicts the outputs with RMS, RMSE, MAE and R2 values of 0.0381, 0.0018, 0.0015 and 0.982, respectively. Meanwhile, these values for the viscosity model were respectively 0.0662, 0.0179, 0.0044 and 0.96.

In the current research, an innovative biomass-based energy system is proposed for power and desalinated water production. The plant's primary components consist of a gasifier, a compressor, a heat exchanger, a gas turbine, a combustion chamber, and a Multi-effect desalination with thermal vapor compression (MED-TVC) unit. A comprehensive thermodynamic and thermoeconomic assessment is conducted on the proposed system. Besides, a parametric study is conducted to determine the effect of primary decision variables on the system performance. Multiple objective optimization using the multi-objective grey wolf optimizer (MOGWO) algorithm is applied to obtain the optimal solution with the highest exergy efficiency and the minimum amount of total cost rate. The artificial neural network (ANN) has an intermediary role in the optimization process to decrease computational time and enhance optimization speed. The relation between the objective function and decision variables is investigated, employing ANN to determine the energy system's optimum point. The generation rate for power and freshwater at the optimal point is equal to 5127 kW and 38.6 kg/s, respectively. Besides, the optimum value of the exergy efficiency and total cost rate are computed as 15.61% and 206.78 $/h, respectively. The results also revealed that the number of effects of the desalination unit does not affect the carbon dioxide emissions. Moreover, the scatter distribution of the key decision variable indicates that the air compressor pressure ratio is not a sensible variable, and their optimum points are distributed across the entire domain.

The present research deals with a novel hybrid system comprises of a salinity gradient solar pond (SGSP) integrated with a proton exchange membrane fuel cell (PEMFC) and a thermoelectric generator (TEG). The key novelty of this research is the use of PEMFC waste heat to increase the performance of the low-temperature heat source (solar pond). Also, a thermoelectric generator is employed in the proposed setup for complete waste energy recovery. In this paper, the proposed system's energy, exergy, and economic (3E) performance are investigated, as well as compared with two additional systems that were modelled by excluding TEG and PEMFC to showcase the benefits of the sub-systems in the final configuration. A parametric study is also conducted to investigate the effect of significant parameters on the overall system performance. The simulation results indicated that the integrated system's net output power is 2288.8 kW at a base case operating condition, with energy and exergy efficiency of 11.26% and 13.17%, respectively, and a system cost rate of 394 $/h. In comparison to other components in the integrated system, SGSP alone accounts for 75% of total exergy degradation and has the highest investment cost of 66.70 $/h. Further, to achieve the best system performance, a multi-criteria optimization is performed for the suggested system with net output power, energy efficiency, exergy efficiency, and system cost rate as objective functions. Besides, the multi-criteria decision analysis (MCDA) is also carried out on the obtained Pareto front using TOPSIS decision-maker to select the best operating condition that improves the output power, energy, and exergy efficiency by 52.6%, 49.6%, and 61.8%, respectively, at the expense of 5.2% increase in the system cost rate. The current investigation demonstrates how an appropriate optimized design of an integrated energy system using SGSP, PEMFC, and TEG can improve the overall performance with reasonable cost increment.

The development of heat and power generation systems has a major step towards sustainable development, reducing fossil energy consumption and reducing environmental pollution. Integrated energy systems are considered widely due to their high efficiency. In the present paper, an intercooled gas turbine system is developed to achieve a system with high thermal efficiency as well as better economic performance and cleaner production. The main goals of the suggested system is improvement of thermodynamic and exergo-economic performance beside multi-criteria optimization, which lead to improve the system sustainability. The intercooled gas turbine in the current work integrated with hot water system and thermoelectric generator unit to develop an advanced combined heat and power system. A comprehensive energy, exergy, and exergo-economic analyses are employed to price assessment of the new introduced system. A comparative analysis with conventional intercooled gas turbine system is presented. The results of thermodynamic modeling indicate that an improvement about 613.3 kW, 8.21 kW, and 12.3 kW can be obtained in the gas turbine, Kalina cycle, and regenerative organic Rankine cycle subsystems. The results of energy and exergy analysis show that the values of both energy and exergy efficiencies for all subsystems experience increment in the new introduced. Parametric analysis based on thermodynamic and exergo-economic criteria is done and a triple objective optimization conducted to determine the best system configurations. The Technique for Order of Preference by Similarity to Ideal Solution is employed to choose the final optimal state of the system. The result of optimum selection among non-dominant solutions suggested by Pareto points indicates that the energy efficiency, total exergy destruction rate and electricity cost rate are 53.91%, 2392.01 kW, and 52.29 $/h.

This experimental study is conducted to explore the rheological behavior of magnetite-water ferrofluid in the attendance of an external magnetic field (MF). Tetramethylammonium hydroxide is used as surfactant to increase the stability of prepared ferrofluids. The impacts of MF strength (0–480 G) and volume concentration of nanoparticles (0.3–1.5%) on the outcomes are examined. It was found that as the shear rate increases, the viscosity decreases sharply and then tends to a fixed number and therefore, the magnetite-water has non-Newtonian pseudoplastic behavior. It was also found that the application of the MF both increases the viscosity and enhances the non-Newtonian behavior of the ferrofluid. Moreover, it was found that the rise of nanoparticle concentration (φ) leads to the increase of ferrofluid viscosity. Then, the artificial neural network is applied to develop a prediction model for the rheological behavior of water- magnetite ferrofluid in both the absence and attendance of an external MF based on the obtained experimental data. The outcomes revealed that the developed models are capable of predicting the outputs in the absence and attendance of an external MF with R2 value of 0.9772 and 0.9692.

The present study deals with energy, exergy and environmental evaluation of an integrated ocean thermal energy conversion (OTEC) system include a flat plate solar collector, an organic Rankine cycle, an electrolyzer system boosted with a thermoelectric generator (TEG) unit. To precise assessment of suggested systems and determine the effects of adding thermoelectric generator to the system a comparative analysis is carried out. Two considered systems are solar ocean thermal energy conversion (S-OTEC) and solar ocean thermal energy conversion with thermoelectric (S-OTEC/TEG). A thermodynamic model is formed using Engineering Equation Solver (EES) to solve the set of linear equations governing on the component of the system. The result of exergy analyses shows that adding thermoelectric module to the S-OTEC results in exergy efficiency increment by 6.27%. Also adding thermoelectric unit to the system increase gross output power by 12.64 kW that the TEG pump input work in this case is 4.96 kW. Although the exergy destruction rate of the S-OTEC/TEG has a higher exergy destruction rate than S-OTEC, the exergy efficiency of S-OTEC/TEG is higher than S-OTEC. Environmental impact assessment criteria namely sustainability index (SI) and modified sustainability index (SI2), represent that applying TEG module to the system improves the SI2 while decreases the SI. Based on obtained results with methanol as working fluid, the SI change from 0.106 for S-OTEC to 0.183 for and S-OTEC/TEG system. In addition, the SI2 change from 1.949 to 2.220 when the TEG module added to the integrated system.

Renewable energies are sources of energy derived from inexhaustible natural resources. In other words, they are regenerated at the same speed at which they are consumed, and they are freely available. In the new millennium, we find multiple typologies of renewable energies, such as the sun and wind. The latter has undergone tremendous development and evolution owing both to economic and financial incentives and the increased concern with environmental protection. Initially, the integration of wind power into daily life was very difficult because the first power plants were very large, which caused great anxiety around the world – the so-called Not In My Back Yard (NIMBY) problem. For this reason the idea of a wind plant evolved into a softer idea which has brought both change in daily life and the respect for morphology, urbanism and city architecture. In Europe, wind energy has increased in use and quality more than in the USA. Germany and Denmark are the largest producers of wind energy, thanks to the quantity of the available rural spaces but also to effective policies, including permanent government subsidies. In Italy, in contrast, the wind energy boom occurred in the late 1990s. However, the country is reaching the standards of other European countries through widespread installations in Puglia, Sicily and Campania. But so far, we have made reference only to megawatt or multi-megawatt plants which are installed outside urban areas or in sufficiently hilly plains. A micro wind plant is different because it can be installed in an urban setting and inside buildings thanks to the advanced technology and reduced dimensions. A case study of micro wind power in the new scenario is the case proposed here of Sant’Arsenio in Campania. It is a small and uninhabited village which would allow the installation of equipment because of the open green spaces. The experimental work described here is aimed at promoting the return of citizens to the village.

Present paper deals with numerical modeling of heat transfer in a tube with two types of twisted tape inserted in a circular tube. Single twisted tape and double twisted (coaxial) tape as two enhancing elements are added to the circular tube. A numerical investigation conducted to explore the effects of these elements on the pressure drop (ΔP), convective heat transfer coefficient (h) and entropy generation (S). The results demonstrate that increasing the Reynolds number has a positive effect on the convective heat transfer coefficient in all cases due to enhance the flow swirling which improves the heat transfer on the tube wall. The results represent that the coaxial tape in the lower twisted ratio (TR) has a better performance than single tape while the opposite is true for a high twisted ratio. The results of pressure drop for two studied cases reveal that pressure drop in the coaxial tape is higher than single tape in all TRs and with increasing TRs the pressure drop experience a decrement. It can be concluded that the lower TR in two types of inserts leads to the lower total entropy generation. Also, the results of exergy destruction rate and second law efficiency demonstrate coaxial tape exhibit better performance than single tape. A genetic algorithm based multi-objective optimization for coaxial tape implemented. The results of optimization displays, the best performance can be achieved in the case TR, Reynolds number and heat flux are 3.46, 9008.93 and 97894.1 W/m 2 , respectively.

The application of the exergy and exergoeconomic analysis for energy conversion systems is growing steadily. This analysis is particularly useful for energy conversion systems such as the combined-cycle power plant (CCPP). This paper deals with exergy and exergoeconomic analysis of a combined-cycle power plant with supplementary firing. A process simulation program, IPSE Pro, is used to model the combined-cycle power plant. Exergy and exergoeconomic analysis is carried out by developing a Matlab code. Three configurations of the combined-cycle power plant are investigated and the effect of the configurations of a heat recovery steam generator (HRSG) and performance parameters such as fuel mass flow rate of duct burner and pressure ratio of compressor on combined-cycle performance have been studied. Exergy and exergy cost destruction rates are also calculated. Finally, the cost of generated power for the three configurations of combined-cycle power plant is calculated and the best location for the ...