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The principal aim of the current research is the design and optimization of a multi-generation unit capable of generating electricity and potable water and hydrogen. The system comprises a gas turbine unit, a high-temperature solid-oxide fuel cell (SOFC), a combustion chamber, and a multi-effect desalination (MED) system. The pressurized steam and fuel enter the anode side of high-temperature SOFC and the air goes to the cathode side. Due to reactions inside the SOFC, a high amount of electricity produces, and excess H 2 enters the combustion chamber. Hot flue gases can run a gas turbine and a MED unit to generate more electrical power and desalinated water. The study illustrated the impact of current density on voltage losses and output power and output voltage of SOFC. A parametric examination is also conducted to demonstrate the influence of primary design variables on the system performance. Exergo-economic multi-criteria optimization is used to determine the optimized parameters to obtain the higher efficiency and lower cost of fuel and equipment. Calculations represented that the suggested arrangement is able to generate 53.46 kg/s desalinated water, and 54.8 MW electricity and 7.43 kg/h hydrogen energy. The system exergy efficiency under this condition is about 36.45% but the results of optimization showed that this value could rise up between 50.8% and 61.17% with the lowest system cost.

In the current work, a solar-based energy plant that includes an organic Rankine cycle, an NH 3 − LiNO 3 operated refrigeration system, reverse osmosis desalination, and hydrogen production device are integrated, modeled, and optimized. A parametric examination is designed with Matlab software to show the impact of varying primary system variables on outputs like system total energy, exergy efficiency, and total exergy output. All processes have been carried out for different working fluids, namely iso-butane, Propane, n-octane, and the results are compared. Parametric analysis reveals that at solar radiation of 800 W/m2, which is reasonable for the sun in most of the Middle East, selecting n-Octane as a working media results in an increase in the hydrogen production rate of about 150%. This also confirms the importance of selecting the right working fluid for the ORC unit. Moreover, the influence of substantial decision variables on the hydrogen production, net out pout power, exergy efficiency indicated that multi-criteria optimization is necessary. The multi-objective optimization strategy suggests the TIP = 1753 kPa, Toil = 99 °C , η i s t u r = 0.9, η i s p u m p = 0.87, and AHeliostat = 2800 m2, for the optimum state of the studied system. Additionally, the scatter distribution and sensitivity analysis for optimum point introduced by multi-criteria optimization utilized for better understanding the optimization process.

In the present work, the performance improvement of a waste heat recovery system is investigated by applying a fuel cell and thermoelectric generator. With the use of energy, exergy, exergo-economic, and environmental analyses (4E analysis), the performance of the improved system is evaluated. A mathematical simulation in the Engineering Equation Solver (EES) is developed for basic and modified systems. Comparative analysis is carried out to demonstrate the benefit of the suggested system. The logical and correct combination of appropriate subsystems can lead to the maximum exploitation of an energy source, which is the innovation of the present work. The comparison of suggested system (PR/FC-TEG) with the CHP system indicates that the net output power of the PR/FC-TEG system is 3881 kW compared with 958.4 kW for the CHP system. However adding fuel cell to the PR/FC-TEG system increase output power by about 2162 kW, and it imposes 4823 kW exergy destruction rate to the system. The exergy destruction rate of the PEM FC, regenerator, and vapor generator are about 88.96% of the total exergy destruction rate, which infers the importance of these components in the PR/FC-TEG system improvement. Parametric analysis on the PR/FC-TEG performance with changing four influencing parameters is performed. Results indicate that increasing the turbine 1 inlet temperature by about 1.1% increases the cost of generated electricity from 72.92 to 73.88 $/GJ and decreases the sustainability index from 1.68 to 1.65. The multi-objective optimization of the developed system can be a promising option for future study.

In the present work a comparative exergy analysis, multi-objective optimization, as well as extended environmental analysis of a geothermal-based power and refrigeration system, is carried out. Different arrangements with the ammonia-water refrigeration cycle, organic Rankine cycle (ORC), and thermoelectric generator (TEG) are investigated. The current work novelties are the presentation of a novel power-refrigeration system driven by a geothermal source and the employment of TEG units to recover geothermal energy, besides extended environmental assessment. The results of sensitivity analysis indicate that the highest net output work capacity is for the suggested system (configuration 3). Exergy analysis exhibits that in all cases, the absorber has the highest exergy destruction rate and one of the lowest exergy efficiency because it is the first component, which gains the heat from the geothermal source. The suggested system produces 495.2 kW net output power and the highest energy efficiency of 19.42%, which are 131.7 kW, and 3.84% higher than configuration 1(base system). Optimization results represent that in the optimum point, W net shows about 33.3% improvement compared with the un-optimized condition. It is found that configuration 3 which consists of cogeneration with two loops of ammonia-water power cycle with refrigeration system along with an additional thermoelectric generator for enhanced waste heat recovery has the highest environmental footprints because of multiple components installed that would occupy more space, electricity, materials, and other resources for its construction, operation, maintenance, and end-of-life.

Current work deals with exergy and exergoeconomic performance evaluation and bi-objective optimization of a newly introduced advanced energy system with geothermal source. The suggested system is composed of a low-grade organic Rankine cycle, an absorption chiller, and a low-temperature PEM electrolyzer. In three stages, the thermal energy of geo-fluid is transferred to the organic Rankine cycle, the refrigeration cycle, and the PEM electrolyzer. The generated electricity by ORC feeds to the electrolyzer to produce hydrogen as a suitable energy storage. Using a prepared code in MATLAB software, thermodynamic and economic behavior of the system is simulated properly. The exergy analysis outcomes show that the PEM electrolyzer, generator, and heat exchanger are responsible of 77% of total exergy destruction rate of studied system so that electrolyzer with 1218 kW has the highest irreversibility among all components. Calculations show that the overall energy and exergy efficiency of the system are 41 and 50%. In addition, parametric study on different variables such as geothermal source temperature, reference environment temperature, and turbine inlet pressure is considered. To find the optimum states of studied system, various bi-objective scenarios are presented. The results of optimization represent that based on introduced optimization states and employing designer criteria, the best optimum state of suggested system can be determined. A novel aspect of current works goes back to the bi-criteria optimization to determine the optimum states of the suggested system.

Selecting the best type of molten medium as energy storage needs a good insight into various properties, which change with temperature and the combination of different compositions. This research aims to understand the influences of the temperature and composition of different mass percent of metal nitrates on the viscosity and thermal conductivity of new molten salt for concentrating solar plants. The experimental outcomes indicate that the viscosity of molten salt strongly changes with the salt composition. In addition, the thermal conductivity and density of molten salt composed of 30 mass% LiNO3, 13 mass% NaNO3, and 57 mass% KNO3 with increasing temperature experience severe decrement. To determine useful correlations for the melting point and viscosity of proposed molten salt, an Artificial Neural Network based on the Group Method of Data Handling is employed. Two polynomials for melting point temperature and viscosity of molten salt are carried out. Results indicate that suggested models predict the experimental values for viscosity and melting point temperature with high accuracy. Calculations of $${R}^{2}$$ values for viscosity and melting pointe are 0.9289 and 0.9678 that show reasonable accuracy of models.

The present study deals with the development and thermodynamic assessments of a solar-assisted Kalina cycle with solar energy as the prime mover. Three configurations of the studied systems were su...

In the present work, a numerical study is conducted to improve the thermal performance of a circular pipe fitted with the elliptical-cut twisted tape (ECT) inserts in presence of a nanofluid as the working fluid. A comparison between the pipe with and without ECTs in different cases is implemented. This investigation is accomplished for a 3D periodically turbulent flow with constant heat flux on the walls. The effect of inserting the ECTs with different parameters, namely the ratio of short diameter to twisted tape width (WA = a/W = 0.7, 0.8, 0.9) as well as the ratio of long diameter to short diameter of the twisted tape (BA = b/a = 2, 2.5, 3) is examined. In the case of WA = 0.7 and BA = 2 for Reynolds number of 7000, the Nusselt number and thermal efficiency factor (TEF) are maximum with the values about 117.25 and 1.392, which show 6.18% and 6.6% improvement compared to the case with the square-cut twisted tape. Moreover, the Cupric Oxide nanoparticles-enhanced fluid with the nanoparticle concentration ranging from 1 to 4% is used to study the effects of the nanofluid on the heat transfer performance of the different configurations. Based on the results, the highest Nusselt number and TEF occur at the concentration of 4%, which are equal to 177.81 and 1.7637, respectively. Moreover, the TEF for the case with the elliptical-cut twisted tape and nanofluid is 21% higher than the same geometry with water as the working fluid, and 26% higher than the square-cut twisted tape in the presence of water.

In this study, thermodynamic simulation is developed to strengthening power generation efficiency utilizing liquefied natural gas (LNG) cold source by thermoelectric generators (TGs) for hydrogen production. Firstly, an organic Rankine cycle (ORC) is specified to use the cold energy of the LNG. Then, the cycle is simulated and the results are validated against the available research study data. Afterward, six locations are suggested to install the TGs and the effects of each of these locations on the cycle performance are evaluated. In addition, the economic evaluation of the selected system is done based on annual cash flow, levelized cost and payback time. The results indicate that the highest enhancement in thermal efficiency (TE) is related to Case “d” which the TG added between the seawater and LNG line. The results show that the TE will become 6.876% if the 80% output heat from the seawater enters the TG for the proposed system. From the results: by increasing the γ c o n d and γ e v a p , the values of thermal efficiency, hydrogen production rate and W n e t / W T E G decrease. The economic analysis represented that the payback time for added TG modules with 1 $/W price for TG is 1.29 years.

The primary goal of the current study is thermodynamic and environmental modeling and multi-objective optimization of a new hybrid energy system. The suggested ocean-based energy conversion system consists of an organic Rankine cycle (ORC), a solar flat plate collector, a proton exchange membrane (PEM) electrolyzer boosted with thermoelectric generator (TEG) module. Exergy and exergo-environmental as two powerful tools are employed to the precise assessment of the suggested system. To achieve the best performance of the integrated system, multi-criteria optimization with different objective functions is carried out. As the results of the parametric analysis indicate, defined objective goals have an appropriate conflict with changing decision variables, which is necessary in multi-criteria optimization. Four decision variables namely solar flat plate collector area ( A p ), solar radiation intensity (I), collector temperature ( T col ), and condenser temperature ( T cond ) are chosen as decision variables. In all optimization scenarios, the net output power is common, which is based on the selected optimum points value changing between 201.02 kW and 268.17 kW. Additionally, in various optimization scenarios, the area of solar flat plate collectors tends to get a higher value in the allowable domain. The provided information in multi-objective optimization can provide good insight to engineers and system designers to select the best system configuration.

Regarding the high expense of the exploiting energy from energy resources, each innovation or modification on the energy systems with the aim of enhancing the efficiency and affordability is so valuable. Along with this fact, in the present work, the effects of employing thermoelectric (TEG) unit in a recompression Brayton cycle ( $${\text{sCO}}_{2}$$ -reB/TEG) are examined. The results of thermodynamic modeling represents that adding the thermoelectric to the system in the s $${\text{CO}}_{2}$$ -reB can improve the net output power about 2.41 kW and increase the first and second law efficiency of s $${\text{CO}}_{2}$$ -reB/TEG system about 1.09% and 1.12% in comparison with s $${\text{CO}}_{2}$$ -reB system. Additionally the exergo-economic analysis for s $${\text{CO}}_{2}$$ -reB/TEG revealed that the reactor and turbine II should be considered more than other elements from exergo-economic point of view since the highest values of $$\dot{Z}_{\rm k} + \dot{C}_{\rm D,k}$$ belong to these components. After identifying the important parameters as well as evaluating system from thermodynamic and economic aspects, a multi-objective optimization is implemented on the $${\text{sCO}}_{2}$$ -reB-TEG system for determining the optimum conditions. Two optimization scenarios are defined using the results of parametric analysis. Multi-objective optimization with first scenario results in total cost rate of 1.6 $ h−1 and total exergy efficiency of 0.5 in minimum temperature, maximum temperature and compression ratio of 36.17 °C, 577.15 °C and 1.6. Furthermore, for optimization based on second scenario results in total exergy destruction cost and exergy destruction rate of 3.04 $ h−1 and 435.85 kW in 48.75 °C, 569.77 °C and 3.44 for minimum temperature, maximum temperature and compression ratio.

The current work is about analysis and multi-objective optimization (MOO) of weir-type solar still systems equipped with phase change material (PCM) regarding the exergetic and economic performance. To do so, the energetic and exergetic modeling of the suggested system is conducted then the substantial economic factors is applied to obtain the total cost rate of the considered SSDS. The total exergetic efficiency and total annual cost (TAC) is considered objective functions. Four parameters include mass of the PCM (mPCM), inlet brine water flow rate ( $$ {\dot{m}}_{\mathrm{f}} $$ ), gap distance (d), and insulation width (xins) is chosen as decision variables. Moreover, a genetic algorithm–based MOO was applied to find the optimum states of evaluated solar still unit. The outputs represented that increasing the brine feed water mass flow rate does not affect the TAC while decreasing distilled water production rate. The scattered distribution of optimum states infers that the optimum value of PCM mass is about 1 kg. In addition, applied MOO reveals that with optimization of the studied system, the exergy efficiency increases about 1.47% and the annual distilled water increases 4.35% compared with the non-optimized system. The suggested system is capable to produce fresh water in remote areas without any pollution as well as in a low cost rate.

The objective of current research is the optimization of a novel parabolic trough solar collector assisted power-refrigeration system. The innovative system utilizes CO2 as a working fluid, which is a natural medium and consisted of three sub-cycles: a Brayton cycle, a Rankine cycle, and a vapor compression refrigeration cycle. The main advantages of utilizing CO2 as working fluid are; available in large quantities, environmentally friendly properties such as negligible global warming potential and zero-ozone depletion, and excellent thermodynamic properties. The required heat energy demand of the system is supplied by solar energy using a PTSC. The thermodynamic performance of the system is examined in terms of energy and exergy analyses for a specified design configuration. An economic analysis of the suggested system is carried out for the optimization procedure. With the optimization results, the optimum design parameters are determined for better system operating conditions. The results of tri-objective optimization represent that the total exergy destruction rate decreased 436.7 kW regarding the basic system with the initial value of design parameters. However, the net power output of the system decreased from 353.21 kW to 280.1 kW, and the total annual cost of the system decreased from 8.215 $/h to 5.74 $/h.

The present work aim is performance improvement of an integrated geothermal system by proposing the integration of organic Rankine flash cycle (ORFC) with the Proton exchange membrane fuel cell (PEMFC) and waste heat recovery from condensers using thermoelectric generator (TEG) modules. To achieve this goal, a novel integrated system is proposed, thermodynamically modeled, investigated, and compared with the conventional system. To assess the performance of proposed system, thermodynamic and economic evaluations are performed. The results indicate that R123 as working fluid, has the best performance for the conventional and proposed systems. The findings demonstrate that with employing TEG modules an increase of 2.7% and 2.8%, for the first and second law efficiencies can be obtained respectively. Additionally, the results of parametric analysis indicate that however the geothermal fluid temperature increment decreases the first and second law efficiencies of the system, it leads to the net output power enhancement. Also, enhancement of the flash vessel pressure ratio increases the first and second law efficiency as well. Additionally, the simple payback method showed that a payback time between 1.25 years and 25 years according to the TEG modules cost can be achieved.

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 .

The current research examined and compared two new hydrogen production systems as well as optimization procedures to determine the best optimum conditions. Developed systems include two integrated systems in one of them a vanadium chloride cycle is used to produce hydrogen from biogas and the other a proton exchange membrane electrolyzer (PEME) is used. Both suggested systems are integrated with a solid oxide fuel cell (SOFC) and an anaerobic digester (AD). A parametric investigation is performed on the systems to determine the effects of changing parameters such as solid oxide fuel cell temperature, fuel cell working pressure, current density, and utilization factor the thermodynamic, economic, and environmental performance of the systems. Findings indicated that the current density of 0.54 was about 5.5 % higher than the system with electrolysis, while the cost rate of the system was 22% percent lower. With the change of SOFC temperature from 900 K to 1300 K, the results showed that in 1000 K, the emission reach 0.273 kg/kWh, which was the lowest value. Moreover, by enhancing the utilization factor from 0.65 to 0.9, the amount of pollution in the system with vanadium chloride cycle was reduced by 24%, which the reduction for the system with PEME was about 20%. Carried out analysis based on the thermodynamic, economic, and environmental index indicated a multi-objective optimization for studied systems. Both developed systems were optimized and the best performance conditions were determined based on the definition of the ideal point.

The present paper deals with numerical simulation and triple-objective optimization of a double-tube heat exchanger equipped with an elliptic cross section in the presence of TiO2 nanofluid. A CFD simulation is done to find the thermal, fluid flow, and entropy generation behavior of suggested heat exchanger configuration. The results indicate that the change of geometrical and operational parameters has different influences on the suggested heat exchanger performance. Findings show that increasing the Reynolds number from 10,000 to 50,000 with TiO2 concentration of 0.3% results in increasing overall heat transfer coefficient from 9445.8 to 14,622 W m−2 K−1 for the spiral diameter of 220 mm. The results of specific entropy generation infer that in the Reynolds number of 4000 with changing TiO2 particle concentration from 0 (pure water) to 0.3%, the specific entropy generation increases from 0.97 to 1.209 kJ kg−1 K−1. A triple-objective optimization with overall heat transfer, friction factor, and specific entropy generation as objective functions, and nanoparticle concentration, Reynolds number, and spiral diameter as decision variables, is done. Different states regarding three objectives introduces as optimum studied system.

Thermoelectric waste heat recovery systems (WHRSs) can be used appropriately to recover wasted heat from various industrial processes. In the current work, new thermodynamic modeling was developed to harvesting waste heat from an integrated system includes an externally fired gas turbine and a biomass gasifier by three thermoelectric WHRSs. The biomass system consisted a gas turbine cycle, an organic Rankine cycle (ORC) and a domestic water heater were first thermodynamically modeled, and then effects of adding thermoelectric WHRSs to different locations of the system were investigated. It is observed that first law efficiency of the system ( η 1 ) will become 17.11% (an increase of 0.35%) if the total output heat from the stack enters W H R S s . The efficiencies of the system can be increased from 16.76% to 17.93% by placing a WHRS on the condenser of ORC. Moreover, the operating parameters have a significant effect on the integrated system efficiency; the influence of increasing α G E on the efficiencies is in contrast to the effect of enhancing α c o n d . In addition, an economic assessment of integrating WHRSs with the biomass gasifier integrated system is conducted and the conditions are indicated under which the proposed system is profitable. Furthermore, the results of genetic algorithm based multi-objective optimization shows that with the use of γ DU = 2 and γ L , O R C = 30 defined thermal efficiencies are at their optimum state.

Purpose Present research focus on using solar energy as a renewable option for office buildings in different climatic conditions in Iran. To seeking a way to use clean solar energy and reduce current expense in buildings an investigation carried out. Nine office buildings in various climatic regions selected as case studies. Through a precise examination, buildings specifications, energy demand and climate information carried out. In the first step based on the buildings type and hot water demand, solar water heater systems designed for each case. In the second step, a cost-benefit analysis is done to detriment the economic aspects of implement aforementioned type of solar system. A cost-benefit analysis is done from saving energy and return time of investment point of view. Results indicate that solar water heater with low investment about US$500 and payback time between 2 and 5 years can be noticed as a desirable renewable option in case studies. Furthermore, analysis reveals that thermal load of building is more effective on fuel saving in building, while solar radiation intensity has more effective on the payback in solar water heater utilization. Design/methodology/approach In this study based on thermal load of nine building office and radiation of different part of Kermnashah province, the possibility of solar water system is investigated. Findings Analyses reveal that the thermal load of building is more effective on fuel saving, while solar radiation intensity has more effective on the payback in solar water heater utilization. The main originality goes back to consideration of different meteorological conditions in solar water heater selection.

The current research deals with the thermodynamic and economic assessments of an integrated thermoelectric generator system with the liquefied natural gas production process. The main aim of the present work is investigation the influence of the thermoelectric generators modules location, in a liquefied natural gas production cycle, on the thermodynamic and economic criteria. A Matlab code has been developed to assess the integrated system performance. Suggested integrated systems include adding the thermoelectric generators between the condensers and evaporators (Case I) and adding the thermoelectric generators between the condensers and ambient air (Case II). The results show that the position of the thermoelectric generators considerably influences the system performance. The results indicates that in Case I (with adding thermoelectric generators between condenser and evaporator) the system performance deteriorate drastically. The results for Case II exhibit that the coefficient of performance increases with an increase in x value. Moreover, economic analysis of employment of thermoelectric generators in liquefaction cycle indicates that with thermoelectric generator cost of 1 $/W the payback rate of investment is less than 2 years (1.29 years).

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 current research presents the thermodynamic modeling and assessment of the solar-based integrated energy systems (IES) for hydrogen production with and without thermoelectric generators (TEGs) waste heat recovery system (WHRS). The results show that the net output power of the conventional system is 66.9 kW and 14 k W more power can be generated by using the TEGs WHRS in the IES. The net output power of the proposed system reaches 78.7 kW, indicating an enhancement by 17.6%. Also, increasing output power leads to an increase in the efficiency of IES from 6.9% to 8.1%. It means that, with the use of WHRS the efficiency is increased by 1.2%. However, more increase in efficiency is observed in the proposed system, and the variations of efficiency relative to the mass flow rate of the collector are extremely slight in the conventional system. Moreover, modeling results demonstrate that the hydrogen production rate in the proposed system is approximately 16% more than that in the conventional system. Furthermore, if the figure of merit is increased from 0.001 1 / K to 0.009 1 / K , a significant enhancement from 0.4% to 1.9% (for TEGs WHRS efficiency) could be achieved.

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.

This manuscript presents the bicriteria optimization of a polygeneration system to be installed in a tertiary sector building, considering economic and environmental objective functions. Electricity, hot water, steam, and cooling demands were considered. The bicriteria problem considered the annual costs and the annual carbon footprint. Updated environmental information was obtained through the application of the Life Cycle Assessment methodology and implemented within a Mixed Integer Linear Programming (MILP) model, along with economic and legal data. Solar photovoltaic energy and biomass were available, as well as natural gas and diesel. The energy system could import and export electricity to the electric grid. Individual optimal solutions were obtained from economic (annual costs) and environmental (annual carbon footprint) viewpoints were different, and the .constraint method was utilized to tackle these conflicting objectives. It was verified that significant reductions in annual costs could be obtained if the annual carbon footprint was partially compromised. A configuration based on one gas engine, two biomass boilers and three mechanical chillers was recommended, with an annual carbon footprint of 2,895,909 kg CO2-eq/year (approximately 570,000 kg CO2-eq/year less each year in comparison with the economic optimal) at a total annual cost of R$ 1,429,435.

In this paper, a numerical study is conducted to examine the energy and exergy performance and multi-objective optimization of a novel exhaust air heat recovery system made up of a building integrated photovoltaic/thermal (BIPV/T) collector and a thermal wheel (TW) system. The innovative BIPV/T-TW system is capable of pre-heating/pre-cooling the ambient fresh air in winter/summer and also producing electricity. Comparisons are carried out on the basis of energy and exergy by considering three different exhaust air heat recovery systems including the BIPV/T-TW system, the conventional BIPV/T collector, and the convectional TW system. It is observed that the BIPV/T-TW system has the best energy performance among the considered systems in all months of the year, while its exergy performance is lower than the BIPV/T system. Then, the multi-objective optimization technique is utilized to obtain the optimal values of geometric and operating parameters in order to maximize the annual useful energy and exergy obtained from the BIPV/T-TW system. It is found that annual useful energy and exergy gained by the optimized system is 196.31 MWh and 30.15 MWh, which is 563.8% and 1394.1% higher than the un-optimized system, respectively.

This paper mainly focuses on the design and optimization of a novel integrated system to meet fresh water, electricity, and hot water demands. A novel combination of different system is used to generate multi products. The exergy and economic analyses are combined to carry out a parametric study to find the impact of main decision variables on a polygeneration system. The exergy analysis reveals that combustion chamber and gasifier have the highest exergy destruction rates with 84% of the system total exergy destruction rate. In addition, the system exergy efficiency shows that in the initial state, the exergy efficiency of polygeneration system is 27.9%. Results show that an increment in the gasification temperature from 950 K to 1150 K leads to fresh water flow rate increases from 1060 m3/day to 1160 m3/day. The parametric study of the system reveals that the defined objective functions are highly depends on the changes in the nine decision variables. Using a genetic algorithm optimization method, the optimum design values are obtained. The results of multi-objective optimization show that within reasonable changes for decision variables, the system exergy efficiency can change between 20% and to 42%, and the system total cost rate can vary from 100 $ / h to 600 $ / h .

This chapter deals with the multiobjective optimization of a geothermal power plant. In this regard, a geothermal-based organic Rankine cycle (ORC) working with n-pentane is proposed using the real data and properties of the geothermal well located in northwest Iran. The geothermal fluid is extracted at 145°C from the well with a mass flow rate of 391.9 kg/s and reinjected at a temperature of 86.6°C. For the evaluation of the system performance, the detailed energy and exergy analyses are conducted first. Following that, a parametrical analysis is carried out to examine the effect of system parameters on the cycle performance, such as turbine inlet temperature, pressure, working fluid condensing pressure, geothermal fluid temperature, reinjection temperature, etc. In addition, a multiobjective optimization technique is applied to determine the optimum operation parameters by maximizing the power generation and minimizing the exergy destruction rate.

In the current research, a comprehensive thermodynamic study of an innovative biomass-geothermal power plant combined with a desalination system is presented and analyzed. The suggested system is a geothermal based cascaded steam/organic Rankine cycle benefiting from municipal solid waste combustion in order to enhance its performance. Besides, the exhaust gasses of municipal solid waste combustion are utilized as the primary energy source for driving a multi-effect desalination subsystem which converts the seawater into low salinity water. A comprehensive approach including energy and exergy analyses along with thermoeconomic evaluation is applied to investigate the viability of the plant. First of all, validation of the presented model has been tested by means of comparing the results with published data, through which a good agreement has achieved. The energy and exergy efficiencies can be reached to 13.9% and 19.4% respectively while the total product cost rate of the system is estimated to be 285.3 $/h. Moreover, environmental analysis is conducted in terms of estimation of CO2 and NOx emissions to address the environmental benefits of utilizing municipal solid waste combustion instead of coal for improving the performance of the geothermal power plant. Results indicate that municipal solid waste utilization saves 8,092 tonnes of CO2 emission and 36 tonnes of NOx emission annually in relative to coal utilization. Finally, a three-objective optimization is performed regarding exergy efficiency, total product cost rate, and CO2 emission rate as objective functions through applying the Genetic Algorithm in order to figure out the optimum performance of the system and the Pareto frontier is extracted. The results of optimization indicate that in the optimum case, exergy efficiency of 20.72%, total product cost rate of 306.1 $/h and CO2 emission rate of 1967.7 tonnes/y are achievable. © 2020 Elsevier Ltd

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.

This research work aims to assess the performance of an innovative exhaust air energy recovery system consisting of a building integrated photovoltaic/thermal (BIPV/T) and a thermal wheel (TW). This BIPV/T-TW system has two main operating modes, namely winter and summer. The exhaust air is used for pre-heating and pre-cooling the ambient fresh air through a TW in the winter and summer modes of operation, respectively. Besides, the pre-heated fresh air (in the winter mode) and the heated exhaust air (in the summer mode) is used for reducing the temperature of PV panels and consequently improving their electrical efficiency. The electrical and thermal performance of the system is calculated and compared with those of the conventional BIPV/T and TW systems. Besides, a performance evaluation criterion (PEC) is defined in this study to investigate the overall performance of the studied systems. The results shows that the BIPV/T-TW system has higher PEC than the BIPV/T and TW systems. Furthermore, the effect of various important parameters on the yearly average PEC of the BIPV/T-TW system is analyzed. The economic assessment of BIPV/T-TW represents that the return time of investment according to simple payback (SP) and net present value (NPV) is a reasonable value.