4E Analysis and Optimization of a Novel Hybrid Biomass-Solar System: Focusing on Peak Load Management and Environmental Emissions

Renewable energies are available as clean sources to replace fossil fuels. Providing continuous power without compromising the environment through hybridizing solar and biomass source is one of the promising solutions. This paper seeks to address thermodynamic, economic, and environmental analysis of a multi-generation system with the aim of supplying heating, cooling, electricity, fresh-water, and hydrogen. To do this, the considered system is divided into on-peak, mid-peak, and off-peak periods and modeled based on the consumption pattern at different hours of the day and night. Due to the availability of renewable energy during peak consumption periods, biomass, solar, and hybrid biomass-solar energies are used as energy sources. This leads to a reduction in biomass consumption and carbon dioxide emissions through storing approximately 10 tons of biomass during the day. A sensitivity analysis of the factors affecting the system ’ s function indicated that a growth in solar radiation from 600 to 1000 W/m 2 , results in a 35% improvement in exergy efficiency, a 2.7% raise in the total cost rate, and a 32.4% drop in CO 2 emissions of the system. Moreover, by changing the biomass flow rate from 0.5 to 1.5 kg/s, the exergy efficiency and total cost rate improved by 9.28%, 1.3%, respectively, and the CO 2 emissions rate increased from 0.41 to 1.14 tons/MWh. In addition, focusing on addressing economic and environmental concerns, the optimization of the proposed hybrid system is performed in two categories of objective functions. In the second category optimization, exergy efficiency, fresh water production, total cost rate and CO 2 emissions are determined as 31.75%, 74.75 kg/s, 324.60 $/h and 3.55 tons/MWh, respectively.


Introduction
More energy demand and environmental problems have led to more use of renewable sources.amongst them, solar energy is the cleanest and most plentiful source of energy.Solar source depends on both power of the sun and the number of hours it can be received.Another critical renewable resource is biomass, which has played an important role in human life since the beginning of human existence.The most common biomass sources are agricultural products, marine plants, and forest materials.The Global Energy Assessment reports that the amount of energy supplied by biomass is about 9.5% (Devi et al., 2003).
Each renewable energy source has unique characteristics that make it usable in certain conditions.Solar energy, despite its abundance, is intermittently unavailable at night or on cloudy days due to its dependence on environmental conditions.On the other hand, biomass energy is continuously available regardless of weather conditions, but its combustion releases carbon dioxide into the atmosphere.Consequently, combining energy sources in energy systems has become increasingly important to improve the efficiency of thermodynamic cycles (Bet Sarkis and Zare, 2018a).
The synergy between biomass and solar energy presents a viable combination that can be effectively implemented in multi-purpose systems, offering a consistent and dependable energy source.In recent years, extensive research has been conducted on the integration of biomass and solar energy in multi-generation systems, further establishing its feasibility and potential.Anvari et al. (2018) used biomass combustion energy with a solar turbine and steam Rankine cycle (SRC) to generate power in their hybrid system.The use of hybrid biomass-solar compared to the use of biomass energy source alone causes a 30% increase in electricity production and a 22% decrease in CO 2 emissions.To achieve continuous energy, Suresh et al. (2019) combined biomass and solar energy and designed a hybrid biomass-solar power plant with a steam Rankine cycle that utilizes both electrical and thermal storage.Pantaleo et al. (2020) investigated the thermodynamic analysis and techno-economic evaluation of a combined system of a biomass fueled external gas turbine and an organic Rankine cycle (ORC).In this analysis, thermal energy storage (TES) is used to compensate for solar collector fluctuations.Nami et al. (2021) proposed the use of a solar-assisted biomass-based tri-generation system to provide power, heating and cooling.This system provides an efficient and sustainable solution to meet domestic energy needs.Cao et al. (2021a) proposed using solar renewable energy to produce hydrogen.The hydrogen produced by the thermal photovoltaic panels is added to the combustion chamber and then reacts with the gases resulting from biomass fuel and air combustion.
Also, Jie Ling et al. (2022) conducted a study focused on enhancing the role of solar heat, particularly in the upper cycle of a hybrid system.Their work aimed to minimize the limitations and optimize the efficiency of the system by effectively combining and leveraging the benefits of both biomass and solar energy.To provide the energy required for the hydrogen production process along with the electrical energy production, Burulday et al. (2022) designed a solar power plant integrated with a biomass-based hydrogen production system.They reported an exergy efficiency of 55.8% for the hydrogen production process and 39.6% for the power generation systems.Kumar et al. (2022) conducted a case study on addressing the energy needs of energy-deficient rural communities.The study focused on utilizing locally available energy sources such as solar, biomass, and diesel.Notably, the results demonstrated that integrating solar energy into the optimal system model yielded impressive returns.Altayib and Dincer (2022) presented a hybrid system with constant useful outputs by controlling biomass combustion based on solar radiation changes.The results of this design showed that during periods of maximum solar radiation, biomass consumption can be reduced up to three times compared to night.In order to reduce CO 2 emissions and biomass consumption in renewable energy systems, Cao et al. (2022a) combined hydrogen produced by solar energy with biomass gasification-SOFC system.Exergy efficiency, CO 2 emission in this configuration was reported as 24.85%, 0.257 kg/kWh, respectively.On the other hand, Oner and Dincer (2022) proposed a new integrated system based on solar energy and biomass for the production of electricity, heating, fresh water and ethanol.By reporting energy efficiency of 53.4% and exergy efficiency of 41%, the authors showed that such hybrid systems are thermodynamically and environmentally more valuable and compatible.The study of the environmental performance of such hybrid power

A hel
Overall area of heliostat field (m   2023) introduced a multi-generation system that utilizes solar and waste resources.After conducting an in-depth analysis and optimization, they discovered that municipal solid waste, with a cost-effective lifespan of 4.28 years, is the most economically viable fuel for the system under investigation.Furthermore, the findings indicated that the system achieves energy and exergy efficiencies of 29.25% and 23.59%, respectively, when operating optimally.A multi-generation system supported by waste solar energy for ammonia production, electricity and heating supply was investigated by Acikalin and Dincer (2023).In this study, a CO 2 absorption system was deployed to reduce environmental pollution.Bozgeyik et al. (2023) studied a solar, geothermal and biomass based system for electricity, hydrogen, heating, cooling and fresh water production.Their investigated system with the production of 6.16 kg/s of fresh water had an overall system energy and exergy efficiency of 65.55% and 27.09%.
Based on literature review, thermodynamic and economic analyzes of multi-generation systems with hybrid biomass-solar energy sources is a method for sustainable electricity management.In addition, such combined systems reduce environmental pollution (Bozgeyik et al., 2023).In recent research, a groundbreaking multi-generational system has been developed to effectively mitigate environmental pollution by efficiently managing energy resources based on the specific electricity requirements of a given region.To assess the system's efficiency, a thorough analysis has been conducted, dividing day and night into three distinct periods: on-peak, mid-peak, and off-peak.This approach not only enables significant reduction in the consumption of biomass resources, but also effectively minimizes the release of harmful environmental pollutants.Furthermore, the on-peak period of the analyzed system involved a multi-objective optimization process divided into two categories of objectives.The first category focused on optimizing exergy efficiency, hydrogen production, and fresh water generation while considering the total cost rate of system.The second category, considering the importance of environmental pollutants, sought to simultaneously minimize the total cost rate and CO 2 emissions, while maximizing exergy efficiency and fresh water production.Finally, the main contributions of this study are summarized as follows: • Developing an innovative multi-generation system with hybrid biomass-solar energy that can produce electricity, fresh water, hydrogen, heat and cold air.• Using solar energy as a heat source of open and closed Brayton cycle in order to increase energy and produce more power.• Employing the waste heat from subsystems to produce power, heating, cooling, hydrogen and fresh water.• Comprehensive analysis of the proposed system based on load management using biomass-solar hybrid energy, biomass and solar energy alone.• Enhancing the efficiency and performance of the system through the hybridization of biomass and solar energy.• Optimization of the studied system in the on-peak period in three categories by limiting the total cost rate, CO 2 emission, and both the total cost rate and CO 2 emissions simultaneously.
This paper is organized as follows: after the literature review in the first part, the second section describes the system generally.Then, the next section provides system modeling in more detail in seven subsections.The simulation results are discussed in Section 4. In addition, the system's optimal settings are determined in Section 5. Finally, the last section summarizes the main findings of the paper.

System description
The present study utilizes biomass, solar, and hybrid biomass-solar energy sources to supply electricity, fresh water, hydrogen, cooling, and heating to meet the demand in the Zahedan region during off-peak, mid-peak, and on-peak times throughout 24 h of the day.A general schematic of the proposed system with hybrid biomass-solar sources is shown in Fig. 1.This multi-generation system includes an open and closed Brayton cycle, solar cycle, SRC, ORC, multi-effect desalination (MED) section, absorption refrigeration cycle, and proton exchange membrane (PEM) electrolyzer.The electricity demand profile at different hours of the day with the type of energy source used is given in Fig. 2.
During the peak period, electricity demand of the area reaches its maximum value; thus, the combined cycle uses a hybrid biomass-solar energy source.As shown in Fig. 1, fuel gasification products (point 3) with compressed air from the compressor (point 5) are added into the combustion chamber.After combustion, the resulting gases enter the gas turbine with a 2% pressure drop and at a temperature of 1370 K (point 6).In this high-pressure gas turbine, exhaust gases are compressed to a pressure of 3.24 bar (point 7) and generate power.These gases are heated by a heat exchanger related to the solar cycle and then are reentered at high temperatures to generate power in a low-pressure gas turbine (point 8).Further, these gases through the heat exchangers provide the energy needed for the MED section (points 9-16), the SRC (points 16-17), and the absorption refrigeration cycle (points 17-38).The solar cycle also meets the necessary energy for the closed Brayton cycle connected to the ORC (points 12-13).Helium, isobutane, and an ammonia-water mixture are available fluids for closed Brayton cycle, ORC, and absorption refrigeration, respectively.PEM electrolyzer produces hydrogen by consuming electricity and fresh water which is produced from the desalination process (points 24-25).The investigated multi-generation system is supported by biomass energy at off-peak and mid-peak during the night and solar energy at mid-peak during the day.
Below are the assumptions that have been considered during the modeling of the proposed multi-generation system.
• System performance is evaluated in steady state conditions (Xu et al., 2023).• Heat loss and pressure drop have been ignored along the pipes (Zhang et al., 2022).
• Kinetic and potential effects are neglected in the governing conservation equations (Lashgari et al., 2022).• The oxygen and nitrogen molar coefficients in air are 21.0%and 79.0%, respectively (Dai et al., 2023).

Modeling
The energy sources of the investigated multi-generation system are based on biomass fuel combustion in the Brayton cycle and supported by a solar heliostat field.Fresh water and hydrogen production is also done by multi-effect desalination and PEM electrolysis.The amount of energy received from biomass and renewable solar sources and the rate of hydrogen and fresh water produced need modeling.Each of these subsystems is separately formulated in the following subsections.Table 1 demonstrates technical characteristics of the proposed system which includes the input parameters of solar and biomass subsystems, MED and PEM electrolyzer.

Gasification and combustion model of biomass
In the combustion section, biomass is first converted into gas by the gasification process and is used as a continuous energy source.The type of biomass used in this model is wood with an empirical formula of CH 1.44 O 0.66 .In addition, Table 2 shows the gases produced from wood gasification (Zainal et al., 2001).
An expression for the general gasification reaction of biomass can be written as follows (Bet Sarkis and Zare, 2018b;Zainal et al., 2001): In the gasification equation for biomass fuel, w and n are considered for the amount of moisture and oxygen required, respectively.The moisture content (w) for biomass fuel is obtained according to Eq. ( 2).Moreover, MC is the amount of moisture per mole of wood (Bet Sarkis and Zare, 2018b).

MC = mass of water mass of wet biomass
× 100 The combustion reaction can be expressed chemically as follows (Cao et al., 2021a): The coefficients in relation to gaseous fuel are assumed based on Zainal et al. (2001), and then all the coefficients in the reaction equation are calculated with the balance for H, C, O, and N.

Heliostats field and receiver
The purpose of adding solar energy is to increase power without increasing the amount of biomass fuel, which reduces CO 2 emissions.The solar energy received by the heliostat field is transferred to the air passing through it, so that the hot gas exits at point 11 and enters the HRSG1, raising the temperature of the combustion products.
The total radiative energy of the sun absorbed by the heliostat is calculated from Eq. ( 5) (Zare and Hasanzadeh, 2016).
In Eq. ( 5), N hel is the number of the heliostat in the heliostat field, A hel is the overall area, and DNI is the direct normal irradiance received from the heliostat field.
Part of the heat energy absorbed by the heliostat field is lost through conduction and convection to the environment.Therefore, the amount of energy absorbed by the central receiver can be obtained as follows (Zare and Hasanzadeh, 2016): where η field is the solar tower heliostat field efficiency and is defined as (Besarati and Yogi Goswami, 2014): where η cos , η s&b , η int , η att , and η ref represent the cosine effect efficiency, the shading-blocking efficiency, the interception efficiency, the atmospheric attenuation efficiency, and the reflectivity of the heliostats, respectively.

Multi-effect desalination
The MED-TVC unit desalinates seawater in several stages to produce fresh water.As can be seen in the schematic drawn in Fig. 1, seawater with increasing temperature leads to the condensation of steam exiting (V5) from the last stage (MED condenser).The remaining steam from the condenser (V ev ) enters the ejector with the hot steam (S) exiting from the HRSG (point 20).This hot steam (S+V ev ) inside the tube acts as a heat source for the first effect of desalination.A portion of the heated seawater is sprayed as seawater effect (R) on the tubes inside which the hot steam is flowing (V i ).By transferring heat from the pipe walls, the steam inside the pipes condenses and leads to the evaporation of a part of the salt water sprayed outside the pipes.The steam formed on the outside of the tubes loses its salt and is transferred to the next stage (V i ).After that, the mentioned steam heats up the next part of the fluids and it condenses and turns into fresh water.Again, salt water is sprayed on the outer surface of the pipes and evaporates there, and the same process is repeated.Finally, all the fresh water produced is stored in a tank.
The total seawater flow is divided equally in each stage depending on the number of desalination effects.The compressed vapor temperature (T s+vev ) entering the first effect is obtained from Eq. ( 8).Therefore, with the balance of mass and energy, the amount of steam and salt water produced and the salinity of salt water for the steps are calculated according to the following equations (Chitgar and Emadi, 2021;Moghimi et al., 2018).
where S, V ev , N, T i , X fs , λ i , and T fs are motive steam flow rate, entrained vapor flow rate, the number of effects, the temperature of effect (i), feed seawater salinity, latent evaporation heat at T i , and feed seawater temperature, respectively.

Model of PEM electrolyzer
After separation, water enters electrolyzer where it is converted to oxygen, and hydrogen using electricity.The reaction of the PEME anode electrode is as follows (Razmi et al., 2022): The reaction of the cathode electrode can also be written as follows (Razmi et al., 2022): Therefore, the general reaction for hydrogen production is as follows (Safari and Dincer, 2018): Table 2 Chemical properties of biomass feedstock in the gasifier and the composition percentage of the produced synthesis gas (Zainal et al., 2001).
Here, ΔH is the total energy required for PEME, which is defined based on ΔG Gibbs energy and TΔS thermal energy as follows (Safari and Dincer, 2018): The molar rate of hydrogen produced by PEME can be defined using current density (J) and Faraday constant (F) as below (Ni et al., 2008): As mentioned earlier, PEME generates hydrogen by consuming electricity.The power required to produce hydrogen in PEME is (Ni et al., 2008): where V is the symbol of cell potential and is defined as follows (Mehrenjani et al., 2022a): where V 0 , V act and V ohmic represent reversible potential, over-activation potential, and ohmic potential, respectively.The equations for calculating them are given in Eq. ( 19) to Eq. ( 21).In addition, anode and cathode electrodes were indicated by subscripts a and c (Hai et al., 2023).
Here, R is the gas constant, J 0,i represents the exchange current density of PEME obtained by Eq. ( 22), and R PEM is overall ohmic resistance of PEME calculated by Eq. ( 23) (Hai et al., 2023).
Here, E act is the activation energy and σ m [λ(x)] represents the local ionic conductivity of PEME membrane and its relation can be presented a: (Ni et al., 2008): where λ(x) is the content of water at x distance, which is defined as follows (Alirahmi et al., 2021): High pressure gas turbine

Overall system efficiency
Exergy is the useful work potential in a system at a specified state.Exergy analysis is important for more efficient use of energy.The general equilibrium rate form of exergy is defined as the Eq. ( 26).The expressions Ėx Q , Ėx w and Ė x d represent the exergy of heat transferred, the exergy of work done and the rate of exergy destruction (Vinet and Zhedanov, 2011;Xu et al., 2023).
The exergy of each state consists of four physical, chemical, kinetic and potential components, which are defined in Eq. ( 29) to Eq. ( 32), respectively.Kinetic and potential exergy are neglected due to the insignificance of velocity and height changes (Balali et al., 2023;Khanmohammadi et al., 2023).
According to the Eq. ( 27), the parameters Ẇ and dVc.v dt express the time rate of energy transfer by work other than the work flow and the time rate of change of the volume of the control volume itself.The power produced in each section is defined as follows: Chemical exergy is very important in the irreversible chemical reaction where the chemical composition is out of equilibrium.Chemical exergy for the reaction performed in biomass combustion is calculated according to Eq. ( 37) (Algieri and Morrone, 2022).
Here, β parameter is defined by the weight fraction of hydrogen (Z H ), carbon (Z C ), and oxygen (Z O ) and obtained according to the following equation (Algieri and Morrone, 2022): Exergy efficiency of the system is obtained by dividing the exergy of useful products to total exergy input using Eq. ( 39): Table 3 summarizes the energy and exergy balances for each component.

Economic analysis
During the operation of the system, the cost must be considered.Therefore, the system is economically modeled considering the cost of components in different cycles.The cost of each component is calculated according to the maintenance factor (ϕ) and annual time per hour (N) as follows (Nasrabadi and Korpeh, 2023): where Z k represents the cost of purchasing element k, which is mentioned in Table 4 for each component.CRF indicating the capital recovery coefficient, which is obtained by Eq. ( 41) (Seshadri, 1996).
Here, i represent the interest rate (12%) and n is the service life of the system components (20 years).Based on cost indices, the equipment prices are updated from the initial year to the current year as follows (Mignard, 2014):

index of the present year cost index of the base year
Cost rates of each subsection during the on-peak period with hybrid biomass-solar sources are indicated in Fig. 3.The highest cost rate is related to the solar source with about 36% of the total cost of the system.

Environmental analysis
Findings from the analysis reveal alarming trends of environmental degradation resulting from anthropogenic activities, including industrial pollution, deforestation, habitat destruction, and greenhouse gas emissions.These activities have led to a decline in air and water quality, loss of biodiversity, soil erosion, and alteration of natural habitats (Cuan et al., 2023).
In this regard, in the current study, the effect of biomass-solar hybrid system on CO 2 emissions is studied by managing energy resources and the necessary power of the region.Therefore, the amount of CO 2 emissions for the system is reported by the following equation (Chen et al., 2023): Here, ṁCO2 and Ẇsystem represent the amount of CO 2 and the power produced by the system, respectively.

Validation
Validation of modeling results in subsystems has been performed.The accuracy of the PEM electrolyzer model was tested considering the cell potential changes by Ioroi et al. (2002).In addition, the fresh water produced in the Multi-effect desalination section was validated by Al-Mutaz and Wazeer (2014).The performed validations demonstrate good agreement as presented in Fig. 4 and Table 5.Furthermore, Table 6 compares the exergy efficiency of the system provided by three existing studies with the present study.In the article by Moghimi et al. (2018), biomass is used as the only source of energy, and in the article by Okonkwo et al. (2018), solar energy acts as the sole source of the system.Also, in the article of Anvari et al. (2018), the hybrid biomass-solar energy system has been investigated.As can be seen, the results of the present study are better than the existing studies in all three scenarios.

Parametric analysis for the hybrid biomass-solar system
The proposed system is designed to use biomass and solar energy sources.Therefore, the amount of solar radiation is the most sensitive factor that affects the performance of the system.The amount of CO 2 emission, total cost rate, exergy efficiency, power, hydrogen, and fresh water produced are the most important outputs of the proposed system.Fig. 5 shows how the system outputs are sensitive to the variability of solar radiation.As can be seen, it is understandable that a rise in solar radiation increases the heat input from the solar part, which leads to more power, hydrogen, and fresh water production and better exergy efficiency.With the increase of solar radiation from 600 to 1000 W/m 2 , the values of exergy efficiency and total cost rate grow from 24.18% to 32.66% and from 348.71 $/h to 358.25 $/h, respectively.It also causes a 58.4% increase in CO 2 emissions and a 2.7% increase in the total cost of the system.
The number of heliostats is the other factor that plays a basic role in the amount of energy received from the sun.The effect of this factor on the performance of the proposed system can be seen in Fig. 6.As seen, an increase in the number of heliostats from 350 to 650, increases electricity generation, exergy efficiency, and total cost rate by 58.9%, 44%, and 29.15%, respectively.In addition, the production of hydrogen and fresh water rises from 3.34 to 5.31 kg/h and from 71.18 to 71.76 kg/s, respectively.Also, the amount of CO 2 emission grows from 0.72 to 0.45 tons/MWh.
In the biomass sector, the biomass input flow rate is the most influential factor in the amount of heat released from combustion.By adding to the biomass flow rate in the gasifier, the combustion gases increase.This growth in flow rate produces more power and increases exergy efficiency of the system.The effect of biomass flow rate on system outputs is shown in Fig. 7.As can be seen, by changing the biomass flow rate from 0.5 to 1.5 kg/s, exergy efficiency and net output power grow from 29.12% to 31.82% and from 8.40 to 9.13 MW, respectively.Also, the increase in biomass flow leads to an increase in CO 2 emissions from 0.41 to 1.14 tons/MWh and the total cost rate from 354.41 $/h to 359.04 $/h.
Another parameter that affects the system outputs is the compressor pressure ratio.The operation of the investigated multi-generation system with increasing compressor pressure ratio from 5 to 14 is illustrated in Fig. 8.As it can be seen, by increasing the compressor pressure ratio, the output net power increases (from about 6.72-8.28MW).Exergy efficiency first increases and then decreases.Initially, with the increase in the pressure ratio, the temperature of the compressor outlet air increases, and as a result, the fuel consumption decreases due to reaching the temperature of the gas turbine.But at a pressure ratio greater than 9, the fuel consumption increases and as a result the exergy destruction of the combustion chamber, which has a significant effect on the total exergy destruction, increases and the exergy efficiency decreases.Also, with this action, the amount of CO 2 emissions decreases by 17.5% and the total cost rate increases by 4.3%.
A further parameter that affects system efficiency is the inlet temperature of the high-pressure gas turbine (GTIT).As depicted in Fig. 9, increasing GTIT improves all useful outputs of the system.An increase in GTIT makes the combined cycle operate at high temperature and increasing the generation of power, fresh water and hydrogen, and then exergy efficiency.The increase of GTIT from 1000 K to 1500 K increases The ambient temperature also affects the performance of the investigated hybrid system.The changes of the main outputs of the combined cycle with the increase of the ambient temperature are indicated in Fig. 10.As the ambient temperature increases from 278 to 318 K, the air   density increases, and the net output power of the system decreases from 8.83214 MW to 8.27704 MW.The production of hydrogen and the total cost of the system are also reduced from 4.4 to 4.12 kg/h and from 355.55 to 355.21 $/h, respectively.Finally, the exergy efficiency decreases from 32.86 to 27.34 and the CO 2 emission of the system increases from 0.55 to 0.58 tons/MWh.

Hourly analysis of the system
The present study is evaluated in Zahedan city with the consumption pattern described in Fig. 2 for 24 h a day.On 18 August 2019, the DNI and temperature data for this city were extracted and depicted in Fig. 11.In the current research, according to the pattern of electricity consumption, 24 h of a day are divided into on-peak, mid-peak, and off-peak periods, and biomass, solar and hybrid biomass-solar energies are used as energy sources.The off-peak load time is between 00:00 and 06:00.Due to the unavailability of solar energy, the electricity required during this period is met only by biomass combustion.According to Fig. 2, midpeak load time is considered between 06:00-11:00 and 16:00-00:00.Between 06:00 and 11:00, solar energy is used and between 16:00 and 00:00, biomass energy is used as an energy source.For on-peak load time between 11:00 and 16:00, the combined cycle is supported by hybrid biomass-solar energy.The use of renewable energy sources based on their availability during different periods leads to biomass storage and less CO 2 emissions.So that during mid-peak, the consumption of 6.6 tons of biomass is avoided with the support of solar energy.In addition, duo to the use of hybrid biomass-solar energy during on-peak, the amount of 3.3768 tons of biomass is stored during that period.In Fig. 12, the Fig. 9. Effect of GTIT on the investigated hybrid biomass-solar system.10.Effect of ambient temperature on the investigated hybrid biomass-solar system.comparison of CO 2 emissions during day and night hours for the system with biomass-solar and biomass sources is reported.The results of modeling for different periods of electricity consumption are reported in Table 7.

Optimization
The investigated system is a multi-purpose system because of addressing various objectives.Combined cycle optimization is done with the aim of maximizing fresh water, hydrogen production, and exergy efficiency while minimizing total cost rate and CO 2 emissions.For this purpose, the multi-objective optimization of the system is performed in two categories of objective functions.In the first category, exergy efficiency, hydrogen and fresh water production are optimized with the constraint of total system cost rate.In the second category, it is optimized by reducing the total cost rate and the amount of CO 2 emissions in front of the increase in exergy efficiency and fresh water production.
Number of heliostats (N hel ), solar cycle mass flow rate ( ṁCRS ), biomass mass flow rate ( ṁbiomass ), high-pressure gas turbine inlet temperature (GTIT), and compressor pressure ratio (rp comp ) were selected as the most significant variables, and the range of changes of these variables were presented in Table 8.The genetic algorithm (GA) method that follows the principles of biological evolution has been chosen as the optimization method of the proposed system.The GA strategy to find the optimal solution is iterative and random search.Table 9 presents various optimization considerations that play an important role in influencing the optimization process.These fractions are practically determined as optimal values for various optimization problems and allow faster and more accurate convergence of the process.In each search, the obtained objective functions are compared with their previous values, and the best value of that function is selected as the optimal point, and finally, due to the existence of independent and incomparable points, a set of Fig. 12.Effect of hybrid biomass-solar system on CO 2 emissions during the day.

Table 7
The results of the hourly review of the proposed system in Zahedan city on 18 August 2019, depending on the peak time and energy source.optimal points called the Pareto frontier is obtained instead of an optimal point.To find the optimal point in the Pareto front curve, based on the distance method, LINMAP (Linear Programming Technique for Multidimensional Analysis of Preferences) is utilized.In the LINMAP method, the objective functions are first transformed dimensionless using Eq. ( 44).The distance of the points in the Pareto front from the hypothetical ideal point (both objective functions are in their optimal state) is calculated by Eq. ( 46).Since all the points on the Pareto front curve are incomparable to each other, the closest point on the curve to the ideal point is chosen as the preferred optimal point (Mehrenjani et al., 2022b).
To check the performance and find the optimal solution points from different perspectives, multi-objective optimization was implemented.The hybrid system underwent optimization in two key categories, with primary emphasis on addressing both economic and environmental considerations specifically during peak periods.The first category targeted the minimization of the total cost rate, prioritizing cost efficiency as a primary goal.Meanwhile, the second category aimed to optimize both the CO 2 emissions and the total cost rate simultaneously, enabling a dual focus on environmental impact and economic performance.By incorporating these two distinct optimization objectives, the hybrid system sought to strike a balance between financial viability and sustainable practices during peak periods.The flowchart for multi-objective  optimization of the investigated system is drawn in Fig. 13.In the first category, optimization is done according to decision variables and objective functions, and its Pareto front diagram is shown in Fig. 14.The ideal point is the point where the total system cost rate is at a minimum and the useful thermodynamic outputs are at their maximum value, which is practically impossible.Therefore, based on the distance method (LINMAP), the closest point of the Pareto front to the ideal point is selected as the most appropriate point.The optimal point selected in the first category has total cost rate, exergy efficiency, hydrogen and fresh water production rate of 327.79 $/h, 35.26%, 5.37 kg/h and 75.51 kg/s, respectively.
For the second category with the objective functions of CO 2 emission, total cost rate, exergy efficiency and fresh water production, the Pareto front diagram is depicted in Fig. 15.This category was done due to the optimal performance of the system with economic and environmental restrictions.At the selected optimal point, the values of CO 2 emission, total cost rate, exergy efficiency and fresh water production are 3.55 tons/MWh, 324.60 $/h, 31.75% and 74.75 kg/s, respectively.
The values of decision variables and selected objective functions in three optimization categories for the selected points are reported in Table 10.
Scatter plots provide a visual representation of the relationship between decision variables and objective functions, allowing for quick data insight and analysis.In this regard, Fig. 16 shows the distribution of decision variables.The number of heliostats, gas turbine inlet temperature, and biomass flow rate are critical decision variables that have a potential impact on optimal system performance.According to the diagram, the distribution of these variables is spread over the entire range, which shows their relationship and influence on the objective functions.While the solar cycle mass flow rate and compressor pressure ratio variables are near the upper and lower limits, respectively.Therefore, for optimal system performance, it is appropriate to keep these parameters within the specified range.

Conclusion
In this study, a multi-generational system was designed with hybrid biomass-solar energy sources capable of cooling, heating, power, hydrogen and freshwater production.The optimal operation of the developed system was investigated for different periods of the day namely off-peak, mid-peak and on-peak based on the electricity consumption pattern in the region.The system is supported at different peaks according to the availability of each energy source at that time.During on-peak, the multi-generation system with hybrid biomass-solar energy support includes open and closed Brayton cycle, solar cycle, steam and organic Rankine cycle, multi-effect desalination section, absorption refrigeration cycle and PEM electrolyzer subsystems.In addition, the optimization of the studied system in the on-peak period was done in two categories by limiting the total cost rate and CO 2 emission and the total cost rate simultaneously with the genetic algorithm.Then, using the LINMAP method, the final optimal points were found for the selected objective functions in two categories.Finally, the most important findings of the paper are reviewed as follows: • The on-peak configuration, which uses hybrid biomass-solar energy, produces more power than the mid-peak and off-peak configurations and leads to an increase in the total cost rate.• Exergy efficiency of the system during off-peak between 16:00 and 23:00 with biomass source is higher than other configurations.• Due to the varying intensity of solar radiation throughout the day and its impact on power supply, the effect of solar radiation on the outputs of the hybrid system was evaluated.By changing this parameter between 600 and 1000 W/m 2 , the net output power generation increased by 47.4%.This led to a 35% improvement in exergy efficiency and a 2.7% growth in the total cost rate.While the amount of CO 2 emission drops by 32.4%.• Using more heliostat mirrors increases the heat received from solar energy.By increasing the number of heliostats from 350 to 650, exergy efficiency increased from 24.34% to 35.17%.But the total cost rate increased sharply from 314.92 $/h to 406.74 $/h.In addition, these changes lead to a decrease in the CO 2 emission of the system from 0.72 to 0.45 tons/MWh.• Biomass energy source is one of the most critical influencing parameters for providing the required outputs of the proposed system.
In the hybrid biomass-solar configuration, the effect of biomass fuel on the system function was analyzed.The increase in biomass fuel led to the production of more gases from combustion and ultimately had an upward effect on exergy efficiency, power, total cost rate, and CO 2 emission.By changing the biomass flow rate from 0.5 to 1.5 kg/ s, the values of exergy efficiency, power, and the total cost rate were improved by 9.28%, 8.68% and 1.3% respectively.Also, the amount of carbon dioxide emission increased from 0.41 to 1.14 tons/MWh and fresh water production from 71.03 to 73.46 kg/s.• The hybrid system was optimized with a focus on addressing both economic and environmental concerns.At the optimum point, exergy efficiency, fresh water production, total cost rate and CO 2 emission were determined to be 31.75%,74.75 kg/s, 324.60 $/h and 3.55 tons/MWh, respectively.
based solely on solar energy byOyekale et al. (2022) also points to their positive environmental and thermodynamic effects.Recognizing the advantages of renewable energy, Yuan et al. (2024) put forth a heating system that integrates both solar energy and biomass resources.The objective of this system is to decrease energy consumption and minimize CO 2 emissions specifically during the warm season.Mousavi Rabeti et al. (

Fig. 1 .
Fig. 1.General schematic of the new multi-generation hybrid biomass-solar system.

Fig. 2 .
Fig. 2. The amount of power required in a typical day (18 August 2019) in Zahedan-Iran.

Fig. 3 .
Fig. 3. Cost rates of each subsection in the on-peak period.

Fig. 6 .
Fig. 6.Effect of Number of on the investigated hybrid biomass-solar system.

Fig. 8 .
Fig.8.Effect of compressor pressure ratio on the investigated hybrid biomass-solar system.

Fig. 11 .
Fig. 11.The amount of DNI temperature during the day of 18 August 2019.

Fig. 13 .
Fig. 13.Flowchart for multi-objective optimization of the investigated system.

Fig. 14 .
Fig. 14.Four-dimensional Pareto frontier diagram considering exergy efficiency, total cost rate, hydrogen and freshwater production as objective functions.

Fig. 15 .
Fig. 15.Four-dimensional Pareto frontier diagram considering exergy efficiency, freshwater production, total cost rate, and CO 2 emission as objective functions.

Table 1
Design parameters of the multi-generation system.

Table 3
Energy and exergy destruction related relations.

Table 4
Cost functions for each component.

Table 5
Al-Mutaz and Wazeer (2014)y results for the current work with the results presented byAl-Mutaz and Wazeer (2014).

Table 6
Comparison of exergy efficiency of the investigated system with solar, biomass, and hybrid biomass-solar sources with existing studies.
Fig. 5. Effect of DNI the investigated hybrid biomass-solar system.M.Korpeh et al.net output power by 82.9% and leads to a 62.48% improvement in exergy efficiency.The amount of CO 2 emission decreases from 0.83 to 0.45 tons/MWh and the total cost rate increases from 351.61 to 358.68 $/h.

Table 8
Variation range of decision variables.

Table 9
Some assumptions and considerations of the GA.

Table 10
Values of decision variables and objective functions of the system in two categories.