Thermodynamic evaluation of a novel renewable energy system that simultaneously provides electricity, freshwater, and syngas using a multiobjective optimization approach

This research entails the simulation and thermodynamic evaluation of a combined solar‐powered system that is intended to achieve the energy necessary to construct factories in areas where other sources of energy are not available. The system comprises five major circuits: (1) a parabolic trough that collects solar energy and passes it to downstream circuits via an evaporator, (2) an organic Rankine cycle that generates electricity for devices and factories, (3) a proton exchange membrane electrolysis unit that produces hydrogen from pure water, (4) a methanation unit that produces gas by combining hydrogen and carbon dioxide, and (5) a reverse osmosis (RO) unit that purges seawater to produce freshwater. This investigation studies the efficiency of energy and exergy, the destruction rate of exergy, and the economic value of system components as a whole. The system is represented by the technical equation solver, and the results are obtained as a result. This research employs the genetic algorithm and Technique for Order of Preference by Similarity to Ideal Solution method to locate the most effective point. The achieved outcomes include a maximum total system efficiency of 54.935% and a minimum total cost of 2.578 $/GJ. Dated to the optimal point, the power generated is 305.5 kW, the required power of a single‐cell electrolyzer is 293.8 W, the mass flow rate of methane and hydrogen production is 448.92 kg/hr ${kg}/{hr}$ and 225.64 kg/h, respectively. The water volume generated by RO is 35.25 m3/h, and the total cost of the investment is 85.57 $/h.

Integrated energy systems are a suitable solution to meet the energy systems with higher efficiency.Also, proper integration of energy systems is a procedure to enhance the total energy efficiency and exergy of energy systems. 1 To assess the energy systems with high technology, the exergy concept gives an opportunity for experts. 2 Yüksel 3 assessed solar power plants integrated with the organic Rankine cycle (ORC) cycle from a thermodynamic point of view.The results show that solar radiation and increasing solar radiation have a close relationship with the efficiency of the proposed plant.The efficiency of the solar collector increases with the increase of the flow rate of the heat transfer fluid and the solar flux and decreases with the increase of the inlet temperature, which shows the capability of optimizing the solar collectors using the least squares support vector machine method. 4Parabolic trough solar thermal plants can be profitable under certain conditions. 5Desai and Bandyopadhyay 6 analyzed the implication of a solar-driven plant from the aspects of the economy and energy.Using solar radiation concentration to generate power was simulated in the proposed plant.After optimization, the initial results show that in the range from 4.5-7.5 to 3.5-7.5MPa (in specific pressure), the exergy and economic parameters improved.Nami and Akrami 7 scrutinized the integration of ORC and a proton exchange membrane (PEM) from developing and economic aspects in an energy system.To produce power and hydrogen simultaneously is the primary of their proposed system.They mentioned their system could generate power and hydrogen with an efficiency of 52.09% and calculated the cost of hydrogen, electricity, and steam to be around 30.97 $/kg, 4.81 cent/ kWh, and 20.56 $/ton, respectively.Ahmadi et al. 8 optimized a poly-generation system that included some cub systems, such as ocean thermal systems, solar collectors, and a PEM.Findings proved that after finding optimal conditions of operation, the exergy efficiency and total cost rate of the mentioned system reached 60% and 154 $/h, respectively.In another research, Khanmohammadi et al. 9 optimized a solar-based energy system using the optimization algorithm.The proposed system was examined in detail based on the concepts of exergy economic and exergy.According to the results, exergy efficiency and total cost rate obtained 3.2% and 22.3 $/h, respectively.To convert heat into useful work at low temperatures, cycles with organic operating fluids are so better than cycles with water. 10Adding an ORC unit downstream of the gas-steam combined cycle power plant increases the efficiency of the power plant by approximately 1.1%. 11The Use of the regenerative ORC to the gas turbine and the heat recovery steam generator cycle leads to a 2.5% increase and adding the absorption refrigeration cycle to the gas turbine and heat recovery steam generator/the regenerative ORC leads to a 0.75% increase in exergy efficiency of the whole cycle. 12With increasing solar radiation exergy efficiency increases.Using the combined cycle of the parabolic solar collector, a steam Rankine cycle and ORC in the downstream shows that R-134a has the highest exergy efficiency of 26% with the best exergy performance and then the integrated cycle R-152a with an exergy efficiency of 25%. 13 It is possible to produce syngas by electrolysis of water and carbon dioxide, but to obtain higher performance and efficiency, further improvements in production and electrocatalytic aspects are needed. 14Syngas can be generated at industrially significant rates through electrolysis. 15Creating conditions that lead to more electrical energy production will significantly improve the system's economic performance. 16Hydrogen is the cleanest energy carriers and the best alternative to fossil fuels. 3or many reasons, hydrogen can be considered a clean fuel alternative instead of conventional fuels.Briefly, hydrogen is a gas without carbon, an environmentally and renewable energy source that can be considered as a source for future alternatives to meet the world's energy needs. 17Additionally, researchers found different ways to produce hydrogens, such as electrolysis, catalytic methods, thermolysis processes, and steam-based methane reforming.Hydrogen synthesis as a base of the renewable energy process has gotten attention from scholars.On the other hand, the environmental impacts of the integrated energy system are lower than conventional energy systems and have high efficiency. 18Theory of the storage of thermal energy assessed from a thermodynamic point of view in an integrated energy system that included a solar collector and a PEM system.As a result, the proposed system to generate hydrogen and electrical power simultaneously had an important capacity that the efficiencies of products were obtained about 23.1% and 45%, respectively. 19Additionally, researchers in the literature 8,9,20,21 for the base of renewable energy systems try to find the optimal conditions by optimization algorithms.
According to the comprehensive research conducted by the author, there has been no study on the supply of main energies such as electricity, natural gas, and freshwater for a factory in areas where access to these energies is impossible.Therefore, the evaluation of exergy and economic exergy with a multiobjective optimization (MOO) method is studied in the case of parabolic trough solar collectors (PTSCs) integrated with PEM electrolyzer (PEME), methanation unit, reverse osmosis (RO), and excess electricity.In this research, the ORC is responsible for generating electricity by absorbing the sun's heat by the PTSC system.Meanwhile, the PEME system is responsible for producing hydrogen and transferring it to the methanation unit to produce natural gas (CH 4 ), and the RO system is also used for saltwater purification.On the basis of this, exergy analysis, economic exergy, and optimization with the MOO method and optimal solutions, that is, the Pareto frontier is illustrated.
The important achievements and goals of this research can be written as follows: • Proposing a new integrated system based on solar energy to provide the energy required to build factories in areas where energy is not available.• Production of electricity, methane, and freshwater based on the PTSCs integrated with ORC, PEME, methanation unit, and RO simultaneously.• Compared to other thermal thermodynamic cycles, such as heat collection systems, it has higher efficiency and outputs, like, freshwater and natural gas.
• Evaluation of energy, exergy, and exergy economics of the proposed system and optimization by the MOO method.

| DESCRIPTION OF CYCLE AND ASSUMPTIONS
Figure 1 shows the schematics proposed system.The plant includes five units: (1) PTSC for absorbing the solar energy, (2) an ORC and toluene as its operating fluid, (3) a PEME to generate hydrogen, (4) a methanation unit, which is used for methane production, and (5) an RO unit for freshwater production.By using a circulating pump in the PTSC cycle, the operating current fluid Thermonil-VP1 is pumped into the solar collectors (Point 1).A solar-energyconcentrated field heats the fluid, which is then passed into the evaporator (Points 2 and 3).In the evaporator, the heat of the PTSC working fluid is transferred to the working fluid of ORC.Superheated toluene is expanded in the turbine to produce electricity (Points 4-6).Lowpressure toluene steam changes to liquid after releasing heat to the brine water in the condenser (Points 6 and 7).Saturated toluene liquid leaves the condenser (Point 7).The brine water passes through of condenser and enters the RO unit to produce freshwater (Points 15-17).The required pressure for water treatment is made by a highpressure pump.
Electricity generated from ORC uses electrical loads of pumps and PEMEs to generate hydrogen by splitting up the water into hydrogen and oxygen (Points 8-10).The hydrogen generated in the electrolyzer is used in the methanation unit to produce methane (CH 4 ) with the reaction of carbon dioxide supplied by the factory (Points 11-13).The remaining part of the electricity is used for factory equipment.
As mentioned, the three required energies, which include excess electricity produced by the generator, natural gas produced by the methanation method, and freshwater produced by RO, have been included in this system to set up a factory.This method provides the ability to set up a factory in parts of the earth that do not have the possibility of transferring energy from the respective power plants.
The following assumptions are considered for mathematical modeling: • The pressure drop in the pipes is ignored.
• Pumps and the turbine have been taken into account as adiabatic components.• Kinetic and potential energy changes are assumed to be negligible.• The steady-state condition is prevailing for the proposed system.

| MATHEMATICAL MODELING
The analysis of the proposed system is assessed by the engineering software (engineering equation solver [EES]) to obtain energy, exergy, and exergy economic performances.

| Energy and exergy evaluation
All elements in the system are considered as a control volume for the purpose of simulation and mathematical modeling.In this part, the energy and exergy analysis of the proposed system have been detailed.The energy and exergy equilibrium for each element should be mentioned as 22     ṁ, h, Q ̇, and W ̇represented mass flow rate, specific enthalpy, heat transfer rate, and mechanical power, respectively.Also, the inlet, outlet, and destruction exergy rates are indicated by E ̇in , E ̇out , and E ̇D, respectively.

| PTSC system
To evaluate a single solar collector in terms of absorption of solar radiation, should proceed as 13 A mass flow rate of the receiver is demonstrated by mṖ TC , and specific heat and temperature are demon- strated by C p and T, respectively.Input and output of a receiver are indicated by r i and r o , respectively.The useful rate of energy can be determined as 13 An aperture is defined by A ap and an area by A ro .A PTSC includes F R , S, and U L , which explain the removed heat factor, the amount of heat gathered by the receiver and the overall heat loss modulus.In Equation (4), S, A ap , and F R are determined as 13 S G η = , b r (5) Direct solar radiation, collector width, outer diameter of the cover, collector length, and receiver efficiency are illustrated by G b , η r , W , D co , and L, respectively.Also, in Equation ( 7), F 1 is the collector productivity factor and it is the same for the receiver 13 : NADERIHAGH and AHMADI | 1007 where ρ c , γ, τ, α, and κ γ illustrate the reflection of the mirror, intercept factor, cover transmittance, receiver absorbance, and incidence angle modifier.Temperature difference between the ambient and the working fluid (U o ) and its U L is given by 13 A convection heat loss modulus between the surroundings and the cover and a radiation heat loss coefficient between the receiver and the cover is equal to D, h c ca , , h r ca , , h r cr , , and h c r in , , .The coefficients are determined as follows 13,[23][24][25] : ( ) Nusselt number is illustrated by Nusselt number, c denotes cover, and av denotes average.ε is emittance, σ is Stefan-Boltzmann constant and K refers to the thermal conductivity.T c can be considered as 13

T h T h h T
The heat inside the system, which is obtained from the solar radiation to the collector, is calculated as 13

(18c)
To obtain the rate of mass flow of the hydrogen getting out from the electrolyzer should be used the following equation 28 : where J is the current density, F is the Electricity, which is needed to generate hydrogen in the PEME is Here, V is the PEME voltage and A pem is the active surface area of the PEM cell.The output voltage of the electrolyzer for each cell is calculated as 26 where V 0 , η act a , , η act c , , η ohm , and η conc denote reversible potential, activation over the potential of the anode, activation over the potential of the cathode, Ohmic over potential of the electrolyte, and concentration over potential, respectively.Anode and cathode are denoted by the subscripts a and c, respectively.Reversible potential can be calculated as 22 V T = 1.229 − 8.5 × 10 ( − 298).
O P E M −4 (24)   According to Ohmic's law, η ohm is calculated as follows 22 : ohm pem (25)  In addition, the total Ohmic resistance can be written as 22


Besides, the local ionic conductivity of the membrane can be described as 22 PEM (27)   In this equation, x shows the depth of the membrane from the cathode to the membrane, and λ x ( ) is the content of water at a distance of x. λ x ( ) can be measured as 22 l is the thickness of the membrane, λ a and λ c show the contents of water at the anode and cathode membrane interface, respectively.The activation over potential is a measure of electrode activity.This represents the overpotential needed for the electrochemical reaction.The electrode activation over potential can be expressed by the Butler-Volmer equation as 28  where J i 0, is the exchange current density and the subscripts a and c indicate the anode and cathode, respectively.α is the symmetrical factor, and z is the number of electrons involved in each reaction.For water electrolysis, α and z are 0.5 and 2, respectively.The activation over potential of an electrode can be expressed explicitly as 28


The density of exchange current is a significant parameter in the calculation of the activation over potential.This indicates the readiness of the electrode to continue the electrochemical reaction.High exchange current density means high electrode reactivity.The density of exchange current for PEM electrolysis can be obtained as 28 where J i ref is the preexponential factor and E act i , is the activation energy for the anode and cathode, respectively.
The concentration over potential occurs during the reaction at the surface of electrodes because of the fluctuation in the concentration of H 2 inlet.The concentration over potential can be obtained as 26 where J 1 is the maximum current density of the cell and α pem is the electron transfer factor.

| Methanation unit system
The process of methanation to generate methane from hydrogen and carbon oxides (CO 2 ) can be written as 29 The mass conservation is the base of calculation to determine the mass flow rate of methane (CH 4 ) and steam (H O 2 ) generation and also the required carbon dioxide.This reaction occurs with the generation of hydrogen in the electrolyzer. 1he flow rate of CH 4 , H O 2 , and CO 2 outlet of the methanation unit can be calculated as

| RO system
RO is a physical process that can purify water for more applications, such as food processing, pharmaceuticals, power generation, seawater desalting, and municipal drinking water.Applying pressure by the driving force is the main factor of the RO process.The required energy for osmotic separation completely depends on the salinity of the solution.So, more energy is needed for saltier water. 30he mathematical model for the proposed RO system is described as presented in Nafey and Sharaf. 30he mass flow rate of the feed water m fw based on the recovery ratio RR and distillate mass flow rate m d can be written as fw d (37)   The salt concentration of the distillate product can be calculated as where X fw is the feed flow rate salt concentration, and SR is the salt rejection percentage and the rejected brine can be written as The estimation of the rejected salt concentration The estimation of the average salt concentration The equation of temperature correction factor (TCF) is The equation of membrane water permeability is The FF is the membrane fouling factor and to calculate osmotic pressure for the feed side, brine side, and distillate product side should be used below equations: The feed side average osmotic pressure is The net osmotic pressure across the membrane is The net pressure difference across the membrane is where A e denotes the element area (m 2 ), N e denotes the number of membrane elements, and N pv denotes the number of pressure vessels.The estimation of input power of the RO driving pump in kW can be written as

| Exergy evaluation
Exergy evaluation is a strong tool to obtain the precise value and kind of irreversibility in each state of energy systems.Exergy can play a significant role in using available energy sources. 31xergy in any process can be specified as the maximum useful work that occurs during a process. 26The exergy equilibrium equation can be applied by considering a control volume for each component as below 31,32 : where  Ex in i ,  Ex ȯut e , and Ex ̇D are the rate of exergy inlet, outlet, and destruction, respectively.
The exergy definition for each state can be calculated through the following equation 28 : where Ex ph and Ex ch are physical and chemical exergies, respectively.The chemical exergy of each substance can be found in Kotas. 33The physical exergy can be obtained by the following equation 28,34 : The general properties of thermodynamics are H , S, and T which denote enthalpy, entropy, and temperature, respectively, and subscript 0 shows the reference environment condition.
To find the components with a considerable portion in exergy destruction, a powerful thermodynamic-based assessment should be considered.Additionally, to gain a better insight into the exeroeconomic assessment, the exergy related to fuel and product of the system and its efficiency, the following relationship is expressed for each component: Table 1 reported the exergy destruction and exergy efficiency for all components.

| Exergy economic evaluation
Exergy economic evaluation is one the vital part of thermodynamics, that can analyze the cost of the process and the whole system by using exergy combined with economic assessment. 26In this part, the cost product for each component and for the total system is specified and obtained by exergy economic assessment.The cost equilibrium of the kth element as a specific control and cost equilibrium can be written as 22   Here, c is the unit cost of exergy in terms of $/GJ.To evaluate the system performance from the standpoint of the exergy economic, some variables like the cost rates of fuel (C ̇F) and product (C ̇P) are significant and can be applied as the following formats 31 : where c F k , is the fuel's unit price, c P k , is product's unit price, and C ̇D k , is the cost of exergy destruction.To find the total investment cost of components should be used the following equation 26,35 : where Z ̇K CI is the capital investment cost and Z ̇k OM is the operation and maintenance cost.Also, the yearly capital investment price for each component (kth component) is written by 31,36 Also, CRF can be obtained as follows: The equations mentioned above, OT , ϕ, i, and n show the number of annual operating hours (7680 h), the factor of maintenance (1.08), the rate of interest (10%), and the assumed life cycle for the proposed system (20 years), respectively. 31he purchase fee or the initial price of each component is reported in Table 2. Also, Zk for the current year is determined by the Chemical Engineering Plan Cost Index for the year 2022. 40

Price at current year original price
Price index of the current year Price index of the base year = × . ( About the equations of cost equilibrium, some critical components are reported in Table 3.

| Effectiveness parameters
The first and second laws of thermodynamics are used as evaluation tools to evaluate the energy and exergy performance of an integrated system and its total cost.Total exergy efficiency and total cost can be written as the following equations: (65) where W ̇tot elec , and E ̇Solar are the total electrical power supplies to the factory and entrance exergy to the system and function of the outer surface temperature of the sun (T = 5770K s ), respectively, and can be written as the following equations 41,42 : (67) . (68)

| The MOO method
Balancing simultaneously conflicting objectives is one of the common issues in designing a thermal system.A simple flowchart for a better understanding of the model procedure and optimization of the proposed system is presented in Figure 2.
With a MOO, a group of optimal solution points (Pareto frontier) is obtained more than a single objective optimization.One of the MOO's main purposes is to identify optimal points for balancing exergy efficiency and product cost.Determining the optimal point is difficult since the effective parameters of the design are many, but finding the optimal point can reduce the operating cost in the long run and give a suitable performance.MOO is a procedure based on a genetic algorithm, which is a practical and efficient method to find the optimal design point and determine the advantages of the plant parameters.Thus, in this paper, a MOO method based on an evolutionary algorithm is implemented using EES code and imported to MATLAB to discover the proper design point.In the genetic algorithm, random search repetition is used to determine the optimal solution points.With this method, these optimal points are collected in a Pareto frontier.The problem for multicriteria optimization can be defined as follows: [39] Component Z $ ( ) Pump-02  ⋮ In this procedure, each performance rating x ij in X is divided by its norm.The normalized ratings y i I j J ( = 1,2, …, ; = 1,2, …, ) ij should be obtained as follows: This conversion process is used to make it easier to compare the across attributes with the dimensionless unit.However, performing straightforwardly has challenges because the length scales are unequal.
The normalized performance ratings y ij should be obtained as matrix Y: (72) Other steps in detail, for example, integrate weight with rating, find positive and negative ideal solutions, obtain the separation values, and calculate the overall preference score have been described by Chakraborty. 44ere, total exergy efficiency (Equation 65) and total cost product (Equation 66) are significant parameters that are considered as conflict objectives.In such a way, total exergy efficiency and total cost product should be obtained as maximum and minimum points, respectively.

| Model validation
The selection of references for the validation process is from articles that are very similar in this field to the proposed system.In this way, the final results of the proposed system are checked for validation with a similar system of other articles to estimate the error rate.Each cycle is calculated with the same specifications and similar formulas so that the numbers obtained from the results can be compared in the form of graphs or output parameters.
For the proposed integrated system there are no other studies.So, it is an exclusive system, and it is impossible to compare the overall validation with independent results for similar systems.Therefore, for results' validation for each component is taken into account separately.
For the PTSC, the validation is done with the research by Habibollahzade et al., 22 where the error of outlet temperature of the collector with the same working fluid is −0.31%.Table 4 shows the numerical comparison of the model and reference using the mentioned equations.
For the ORC, the validation is done with the research by Razmi et al., 45 where the simple ORC is taken into account with Difluoromethane (R407C) as the operating fluid.Table 5 shows the comparison between the net power of ORC calculated by the present model and by Razmi et al. 45 Figure 3 shows the PEME validation, which compares the present model results with the research by Ioroi et al. 46 For the RO, the validation is done with the research by Nafey et al. 47 The comparative parameters are represented in Table 6.

| Model parametric inputs
The input parameter values for each component are reported in Tables 7 and 8. Therminol-VP-1 and toluene as working fluids are selected for PTSC and ORC, respectively.The ambient conditions such as pressure (101.3 kPa), temperature (298.15K), and wind velocity 3m/s are considered.Also, the temperature at the outlet of the solar collector is assumed 390°C (663 K).This is the maximum operating temperature of the selected oil that is used in the solar collector.

| RESULTS AND DISCUSSION
The proposed system integrated with five cycles as a multigeneration system to generate three main energies (electrical, methane, and freshwater) to run a factory.Validation and parametric study are assessed to find the important parameters of the proposed system.The thermodynamic properties of each component taken into account in this study are determined by the EES software.
EES is an engineering software that solves systems of simultaneous nonlinear equations.It enables many beneficial specialized functions and equations for the solution of thermodynamics and heat transfer problems.Minimizing or maximizing a chosen variable by varying a number of other variables is one of the optimization tools in EES.In this study, all the formulas in this software have been implemented.Then, the obtained outputs are used to find the optimal point by genetic algorithm.Subsequently, optimization of the integrated system and definition of optimal solutions of important parameters were conducted by the MOO method.

| Exergy evaluation
Figure 4 represents the proposed system components from standpoint of the exergy efficiency.As can be seen in the figure, the highest percentage of exergy efficiency is related to PTSC's pump, methanation unit, turbine, and evaporator with exergy efficiency of 100%, 89.8%, 88.29%, and 81.96%, respectively.Meanwhile, the lowest exergy efficiency related to the condenser is around 27.94%, mainly reasons belong to the inlet water and ambient temperature.By increasing the temperature difference between the inlet water and the ambient, the exergy efficiency of the condenser is increased.Following the condenser, RO has the second lowest exergy efficiency.The seawater salinity as inlet water to RO system is the most effective parameter in increasing the exergy efficiency.Additionally, PTSC and PEME have exergy efficiency of 43.25% and 51.17%, respectively.
The exergy destruction of each component of the proposed system is represented in Figure 5.In the order of this figure, the most exergy destruction is related to PTSC with more than 50%.This part of the proposed system is responsible for collecting solar energy and passing it to downstream circuits via an evaporator.Due to irreversibility, the greatest loss of energy received from the sun to convert it into work occurs in PTSC.From the standpoint of exergy destruction, the second most important unit is methanation which causes 16% of total exergy destruction.Also, as shown in the figure, 8% and 7% of the total exergy destruction belong to the condenser and evaporator, respectively.
The effect of beam radiation on total exergy efficiency and total product cost in Figure 6 are discussed.As seen The ORC and PTSC specifications used in the model. 13
T A B L E 8 The PEM and RO specifications used in the model. 28,31,48M 20,000

NADERIHAGH and AHMADI
| 1017 in the figure, by varying the beam radiation of the sun from 0.6 to 1.2 kW/m 2 , the total exergy efficiency of the system decreases from 64.44% to 47.83%.To better understand how changes in beam radiation led to increased or decreased exergy efficiency, one could refer to Equation (65).This phenomenon is related to the methanation unit.The reason is the high chemical exergy of methane with the amount of 51,836 as output and the low chemical exergy of carbon dioxide with the amount of 451.5 kJ/kg as input to the cycle and they do not change during the beam radiation.The total product cost of the system increases by increasing the beam radiation from 3.619 to 4.08 $/GJ.The reason is, that beam radiation has a direct effect on the power of components which leads to an increase or decrease in the total investment cost.The effect of the beam radiation on the net power of ORC, RO, PEM, and total electrical is shown in Figure 7.The results show that, by increasing the beam radiation within a certain range, the net power of ORC, RO, and total electrical that is supplied to the factory are increased, simultaneously.On the other hand, in the range of beam radiation that is shown in the figure, the net power of ORC increased from 560.4 to 1175 kW and total electrical generation for the factory consumptions increased from 98.52 to 528.6 kW, and the net RO power increased from 168.1 to 352.5 kW.As can be seen, the net power of PEM is a straight line (293.6 kW) and it is the same for the hydrogen mass flow rate (225.64 kg/h), as well.According to equations in Section 3.1.2,the calculations are taken into account for one cell and the total power of PEM and the hydrogen mass flow rate depend on the number of cells.In this research 1000 cells for the PEME and 30% of the ORC power generation for RO are considered.Additionally, the mass flow rate of distillate water is increased from 28.46 m hr / 3 to 49.57 m 3 /h accordingly.
Figure 8 shows the effect of PTSC's outlet temperature on total exergy efficiency and total product cost.The results illustrate when the outlet temperature is increased the total exergy efficiency is increased, versus the total product cost is decreased.The range of changes in both cases is insignificant.For exergy efficiency from temperature 536.2 to 663.2 K is between 52.41% and 53.33% (the range of change is 0.92%), and for product cost is 3.74 GJ $/ and 3.69 $/GJ (the range of change is 0.05 $/GJ).The maximum working temperature of Therminol VP-1 is 673.2K.
The effect of the ORC pump pressure ratio on total exergy efficiency and total product cost is shown in Figure 9.This figure illustrates that, by increasing r p2 from 25 to 50, the total exergy decreases and the total cost increases.Variation of total exergy and total cost in the mentioned range r p2 is between 54.97% and 52.72%, 3.81 GJ $/ and 3.90 $/GJ, respectively.Turbine inlet pressure can affect the system's performance as illustrated in Figure 10.Like the superheat temperature, the turbine's power increases by increasing the inlet pressure.Another significant parameter is the PEME temperature, which has an effect on exergy and product cost.As illustrated in Figure 11, by increasing the electrolyzer temperature from 323.2 to 373.2 K, the exergy efficiency of the system increases linearly while the total product cost decreases linearly.The range of increases for exergy efficiency for a cell is 0.04% and the range of decreases for product cost for a cell is 0.015 $/GJ.On the other hand, increasing temperature as shown in Figure 12 is the reason for decreasing the required electrical energy by the electrolyzer.In fact, the electrodes of the electrolyzer are more active at the high temperature.Additionally, with the increase in temperature, the exchange current density increases, and therefore the activation over potential decreases.In other words, the potential of the electrolyzer decreases with the increase in temperature, which causes a decrease in the electric energy input to the electrolyzer and an increase in the system's efficiency.For better understanding, the electrical energy required at 323.2 K is 299.7 W, and at 373.2 K is 290 W. As can be seen in Figure 12, hydrogen and methane productions are constant at the different temperatures of the PEME.The mass flow rates of hydrogen and methane for a cell are 0.2256 kg hr / and 0.4489 kg/h, respectively.The last effective parameter is illustrated in Figure 13 which is related to the number of pressure vessels in the RO system.By increasing the pressure vessel number from 15 to 60, the total exergy efficiency is decreased from 61.52% to 51.79%.Versus, the total product cost is increased from 3.07 GJ $/ to 4.02 $/GJ.The mass flow rate of distillate water is the parameter that increases with increasing the pressure vessels.In the range mentioned, the lowest mass flow rate is 27.35 m 3 /h and the highest mass flow rate is 43.36 m 3 /h.
A comprehensive parametric study proves that integrating the five cycles in a platform for producing three main energies to set up a factory in a far area without the mentioned energies is possible.The amount of energy production depends on the mentioned parameters.Additionally, enhancing the total exergy efficiency and decreasing the total product cost of the proposed system should be considered.

| Exergy and exergy economic evaluation
Some of the significant thermodynamic properties obtained from the system simulation are reported in Table 9. Temperature, pressure, mass flow rate, exergy rate, exergy cost, and cost rate are the parameters shown in Table 9 at different points of the situation with the assumptions of Tables 7 and 8.In Table 10 the exergy economic parameters for any component of the proposed system are reported.These parameters are the exergy destruction cost, the cost rate of product and fuel, exergy efficiency, and exergy economic factor.Additionally, it must be considered that the average electricity cost in Iran is supposed to be 1.38 $/GJ. 49he exergy economic factor ( f k ) measures system efficiency in terms of cost and evaluates the relative significance of exergy destruction and capital investment costs and has a vital role in the exergy economic evaluation.
The highest value of the exergy economic factor belongs to Pump-01, PTSC, Pump-03, PEME, and methanation, respectively, that are shown the costefficiency of reducing the capital investment cost for each component.For the PEME, the exergy economic factor illustrates that 84.35% of the relative cost difference is related to the operating and maintenance cost and the remaining 15.65% is caused by the exergy destruction.Enhancing exergy efficiency and reducing the cost of destruction and the operating and maintenance costs are suggested for these components.Irreversibility and the high cost of exergy destruction are the results of the high value of Z C ̇+ k D and the low value of exergy economic.For other components with less than 50% exergy economic factor, the operating and maintenance costs in the low range and the exergy destruction in the high condition are expected.

| Multiobjective optimization
Regarding optimizing the system by the MOO method, four major effective parameters are selected and reported in Table 11.
Total exergy efficiency and product cost are two objective functions of the proposed system are considered.The genetic algorithm of the MOO method is used to implement.The solution has been converged, after 70 epoch iterations.Optimal solution points are found in the Pareto frontier as shown in Figure 14.TOPSIS method is used to find the optimal point among the 70 points obtained in the Pareto frontier with the ranking definition.Point B is the most distant from the ideal point with an exergy of 55.872% and a total product cost of 3.338 $/GJ.Point A has the shortest distance from the ideal point with an exergy of 54.935% and a total product cost of 2.578 $/ GJ.Point C is introduced in the TOPSIS method as the closest point to the ideal point, which here is the same as point A.
According to the explanations provided, among the points obtained from the Pareto frontier, the optimal point for this research is point C with a total exergy of 54.935% and a total product cost of 2.578 $/GJ.

| CONCLUSION
In this study, the proposed system includes five subsystems, such as PTSC, ORC, RO, PEME, and methanation to produce electricity, freshwater, and natural gas.The system is evaluated from multiple aspects, such as energy, exergy, and exergy economy.The effective parameters are tested and evaluated as the main parameters to achieve the optimization results.The basis of MOO is the genetic algorithm, which is used to optimize the exergy and exergy economy of the proposed system.Points found in the Pareto limit are considered optimal solution points.The obtained results show that the proposed creation of a primary energy generation system is a very practical and promising approach to harvest energy resources in areas where there is no energy access opportunity.Also considering Table 12 as the MOO result, the exergy efficiency and total product cost of the optimal solution point with a well-balanced system are 54.935% and 2.578 $/GJ, respectively.
The results of this study can be summarized as follows: • Five subcircuits can be integrated into one circuit as the main plant for the production of basic energy such as electricity, freshwater, and methane with an exergy efficiency of 54.935% and a minimum total product cost of 2.578 $/GJ.• The smallest exergy damage belongs to the pump with 0%, and the largest exergy damage belongs to the PTSC with 54% • Jet radiation has a direct effect on the increase/ decrease of electricity, freshwater, and methane production.• Achieve high performance of PEME by increasing temperature.• Turbine inlet pressure plays an important role in increasing power generation and subsequent production of more freshwater and methane.
F I G U R E 14 The optimal solution points of the proposed system (Pareto frontier).
T A B L E 12 Exergy efficiency, total product cost, the mass flow rate of methane, and distillate water of proposed system on points A, B, and C according to values of the effective parameters.

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I G U R E 4 Calculated components exergy efficiency of the proposed system.PEME, proton exchange membrane electrolyzer; PTSC, parabolic trough solar collector; RO, reverse osmosis.F I G U R E 5 Exergy destruction of each component of the proposed system.PEME, proton exchange membrane electrolyzer; PTSC, parabolic trough solar collector; RO, reverse osmosis.

F I G U R E 6
Effect of beam radiation on total exergy efficiency and total product cost.F I G U R E 7 Effect of beam radiation on net power of components and the mass flow rate of distillate water.ORC, organic Rankine cycle; PEM, proton exchange membrane; RO, reverse osmosis.F I G U R E 8 Effect of the outlet temperature of parabolic trough solar collector on total exergy efficiency and total product cost.F I G U R E 9 Effect of organic Rankine cycle pump pressure ratio on total exergy efficiency and total product cost.F I G U R E 10 Effect of organic Rankine cycle pump pressure ratio on turbine power and entrance of the enthalpy.

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I G U R E 11 Effect of the PEM electrolyzer temperature total exergy and total product cost.PEM, proton exchange membrane.FI G U R E 12 Effect of the PEM electrolyzer temperature on cell power and mass flow rate of hydrogen and methane.PEM, proton exchange membrane.
Cost equilibrium of components of the proposed plant.
47mparison between the collector outlet temperatures calculated in this model and research of Habibollahzade et al.22Comparison between the net power of organic Rankine cycle in this model and Razmi et al.45Comparison results of the present model obtained with those of reports by Nafey et al.47 46A B L E 4 F I G U R E 3Comparison results of the present model with Ioroi et al.46for proton exchange membrane electrolyzer.TA B L E 6 Effect of the number of RO pressure vessel on total exergy efficiency and total product cost.RO, reverse osmosis.Properties of thermodynamic and exergy economic of each stats point.The parameters of exergy economics for each component of the proposed system.

Table 12
lists the design parameters with the objective functions at points A, B, and C as shown in the Pareto frontier.