
==== Front
Heliyon
Heliyon
Heliyon
2405-8440
Elsevier

S2405-8440(24)12483-8
10.1016/j.heliyon.2024.e36452
e36452
Research Article
Investigation of a novel solar-assisted multigeneration system comprising water desalination systems, an absorption refrigeration system, a single-effect absorption heat transformer and two organic Rankine cycles
Salehi S. s.salehi@maragheh.ac.ir
⁎
Javanfam F.
Department of Mechanical Engineering, University of Maragheh, Maragheh, Iran
⁎ Corresponding author. s.salehi@maragheh.ac.ir
24 8 2024
15 9 2024
24 8 2024
10 17 e3645213 3 2024
15 7 2024
15 8 2024
© 2024 The Authors
2024
https://creativecommons.org/licenses/by-nc/4.0/ This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
A novel solar-assisted multigeneration system is proposed and examined from a thermodynamic perspective, designed to simultaneously produce electricity, distilled water, and refrigeration. The system utilizes solar energy through an absorption refrigeration generator and the heat recovery mechanism of an organic Rankine cycle (ORC). The absorption refrigeration system generates both refrigeration and the necessary heat for a single-effect absorption heat transformer, which in turn produces distilled water and power via an evaporative desalination system and an ORC, respectively. Additionally, two distinct humidification-dehumidification (HDH) desalination systems are integrated to enhance freshwater production.

The study evaluates the impact of various operational conditions on key performance parameters, including the coefficient of performance (COP), exergy coefficient of performance (ECOP), simple payback period (SPP), refrigeration capacity, total generated power, and distilled water production. Pareto frontiers are graphically constructed to identify optimal points and their corresponding parameter values. The results show that, with a total solar heat input of 250 kW, the system can generate 21.46 kW of electricity, 71.02 kW of refrigeration, and 100.65 g per second of distilled water. The optimal performance parameters are determined to be a COP of 2.13, an ECOP of 0.19, an SPP of 3.34 years, a power output of 16.77 kW, distilled water production of 99.84 g per second, and a refrigeration capacity of 74.44 kW.

Keywords

Absorption refrigeration
Single-effect absorption heat transformer
Humidification-dehumidification desalination system
Organic Rankine cycle
==== Body
pmc Nomenclature

A	heat transfer surface (m2)	
Abs	absorber	
AHT	absorption heat transformer	
AR	absorption refrigeration	
c	cost	
Con	condenser	
COP	coefficient of performance	
DeHum	dehumidifier	
ECOP	exergy coefficient of performance	
EES	engineering equation solver	
Eva	evaporator	
Gen	generator	
HDH	humidification de-humidification	
Hum	humidifier	
HX	heat exchanger	
h	specific enthalpy (kJ/kg)	
m	mass flow rate (kg/s)	
ORC	organic Rankine cycle	
P	pressure (kPa)	
PEC	purchased-equipment cost	
Q	heat transfer rate (kW)	
R	refrigeration	
REva	refrigeration evaporator	
SPP	simple payback period	
T	Temperature (oC)	
W	power (kW)	
X	concentration	
		
Greek letters	
ε	effectiveness	
η	thermal efficiency	
τ	number of system operating hours (hr)	
φ	relative humidity (%)	
ψ	exergy (kW)	
		
Subscripts	
Abs	absorber	
col	solar collector	
Con	condenser	
dw	distilled water	
elec	electricity	
Eva	evaporator	
Gen	Generator	
HX	heat exchanger	
in	inlet	
m	mean	
out	outlet	
P	pump	
u	useful	
0	environment	

1 Introduction

The burning of fossil fuels has driven global warming and dramatic climate shifts, posing a major threat to our planet. Water scarcity is just one of the many consequences nations are grappling with [1]. In response, there's a growing focus on developing clean energy sources and water purification technologies. The industrial sector, a major consumer of energy (around 37 %) [2], is a prime target for these advancements. Fossil fuels, the mainstay of industrial energy, are a significant source of carbon dioxide and pollutants, causing environmental damage [3]. Replacing these fuels with clean energy sources, along with implementing efficient integrated thermal systems, is seen as a promising solution [4].

Absorption refrigeration shines in two key areas: harnessing solar thermal energy [5] and capturing waste heat [6]. These eco-friendly systems stand out for their low electricity needs. Unlike traditional refrigerators with compressors, they operate quietly, offer easy control, and can be more cost-effective overall [7].

Researchers are constantly seeking ways to improve absorption systems. One study by Zhenghao et al. explored the impact of titanium oxide nanoparticles on an ammonia-water-lithium bromide system [8]. Their findings showed that these nanoparticles increased pressure in key parts of the system, leading to an impressive 18.96 % improvement in efficiency (COP). Another study by Zhu et al. introduced a solar-powered lithium bromide-water absorption system with a phase change element in Taiwan [9]. They compared collector efficiency and COP, finding that the phase change process boosted collector efficiency by 4.2 %. However, it's important to note that this system's COP was 7.9 % lower than the standard system.

As the global water crisis intensifies [10], a promising desalination method called humidification-dehumidification (HDH) is gaining traction. Inspired by nature's water cycle, HDH offers an eco-friendly way to extract fresh water from seawater using low-grade energy and minimal maintenance [[11], [12], [13]]. Researchers are actively improving HDH efficiency.

Elattar et al. analyzed a solar-powered HDH system, providing valuable data on water production, cooling capacity, and efficiency [14]. Tangellapalli combined HDH with a heat pump to generate clean water and air conditioning, achieving specific energy ratios [15]. Khass et al. conducted a comprehensive study on different HDH configurations for water and air heating, examining both thermal and economic performance [16].

Absorption heat transformers (AHTs) can be used for upgrading low-temperature heat sources in systems like Organic Rankine cycles, Kalina cycles, and absorption refrigeration [7,17,18]. They essentially boost the heat to a more useable level. One study by Xu et al. explored how a double-effect AHT could efficiently capture waste heat and separate it into different energy grades [19]. Their research focused on finding the optimal operating conditions for this process.

AHTs are also used for desalination. Ghiasirad et al. proposed a geothermal-powered system that uses an AHT to generate fresh water, electricity, and air conditioning, all while considering both efficiency and cost [17]. Similarly, Salehi et al. integrated an AHT into a geothermal power plant for desalination, optimizing key parameters for efficient power and water production [20].

The growing demand for sustainable energy solutions has intensified research into thermal systems capable of providing multiple outputs simultaneously. Among these, cogeneration and multigeneration systems have garnered significant attention due to their ability to enhance energy efficiency and resource utilization. Almohammadi et al. [21] numerically investigated a novel solar tri-generation system that integrates an Organic Rankine Cycle (ORC), a humidification-dehumidification water desalination system (HDH), and a desiccant cooling system (DCS) aimed at optimizing power generation, water desalination, and air conditioning. They showed that the maximum energy utilization factor obtained is 0.3018 using R123 and the improvement percentage of using R123 instead of n-Octane is 20 %. Efficiently harnessing solar energy for liquid hydrogen production is vital for a sustainable energy future. Bouzgarrou et al. [22] explored this with a cutting-edge solar-powered system that combines parabolic trough solar collectors (PTSCs), a sequential ORC, a liquefied natural gas (LNG) regasification unit, and a hydrogen production and liquefaction module. Their system achieves a net power output of 1.13 MW, produces hydrogen at 34.92 kg/h, and reduces CO₂ emissions by 255.96 kg/h, with a levelized cost of hydrogen (LCOH) at $3.59/kg. Furthermore, it provides a cooling capacity of 192 kW and projects an annual hydrogen output of 536.84 tons in San Francisco. Poly-generation systems offer a sustainable alternative for energy production in buildings by providing electricity, heating, cooling, and fresh water simultaneously. Alqaed et al. [23] investigated three solar-driven poly-generation configurations (BS, IS-I, and IS-II), integrating an ORC, a humidification-dehumidification desalination system, and a desiccant cooling system (DCS). Their analysis highlighted the IS-I system as the most efficient, delivering up to 102.0 kW of power, 29.94 kW of cooling, and 225.6 kW of heating. Additionally, the IS-II system excelled in water production, yielding 214.7 kg/h. González et al. [24] focused on optimizing VCR-ORC systems using objective functions based on the Helmholtz energy function and its derivatives. Their study evaluates several working fluids, identifying Pentane and R1233zd as top performers for these systems. They find that factors such as condenser temperature are crucial for system optimization, and they provide a comparative analysis that helps in selecting optimal working fluids and operating conditions. Karabuga et al. [25] examined a system powered by solar energy that simultaneously generates electricity, hydrogen, and cold energy. Their setup employs an ORC for electricity, a Proton Exchange Membrane electrolyzer (PEMe) for hydrogen production, and an ejector refrigeration system for cold energy. Utilizing an exergy-based approach, their study reveals that the overall system achieves an exergy efficiency of 2.082 % and calculates the cost of hydrogen production at $1.086 per kilogram.

As previously mentioned, many regions around the world, both in cities and rural areas, face a critical challenge: a lack of both fresh water and electricity. Climate change is making this problem even worse. For example, cities in the Middle East like Ahvaz, Iran, experience scorching summer temperatures that can exceed 50 °C. Classified as a subtropical hot desert [26], Ahvaz is one of the hottest cities on Earth. These hot regions also suffer from frequent power outages, which can cripple conventional refrigerators and create significant hardships. On the other hand, there's a gap in research on developing multigeneration systems specifically designed for the Middle East that address essential needs (power, water, refrigeration) using clean energy sources and remaining cost-effective. To address this critical issue, this study proposes a novel multigeneration system that simultaneously produces distilled water, power, and refrigeration. This innovative system incorporates an absorption refrigeration unit, an improved single-effect absorption heat transformer, two organic Rankine cycles, and water desalination technologies.

To assess the system's practicality, real-world weather data from Ahvaz, Iran was utilized [27]. In addition, comprehensive computer simulations were conducted using Engineering Equation Solver (EES) software to examine various performance parameters, including efficiency (COP, ECOP), payback period (SPP), cooling capacity (Q˙ R), power output (W), and water production rate (ṁdw). The findings are displayed as Pareto frontiers, highlighting the system's optimal operating conditions and performance values.

2 System description

The diagram in Fig. 1 illustrates the proposed system, designed to generate power, refrigeration, and fresh water through a solar-assisted multigeneration approach. This system consists of two organic Rankine cycles (ORCs), an absorption refrigeration system, an integrated single-effect absorption heat transformer (AHT), and two distinct types of humidification-dehumidification (HDH) systems.Fig. 1 Schematic cycle for the proposed system.

Fig. 1

Additionally, another desalination system is simultaneously connected to an AHT and an organic Rankine cycle. Solar collectors capture solar heat, which is first used to operate the absorption refrigeration system and subsequently to drive ORC2, generating the primary portion of the required power (W˙2).

The proposed multigeneration system includes two humidification-dehumidification (HDH) systems: open and closed, integrated with the absorption refrigeration system. The fluid stream exiting the condenser at state point 11 heats the seawater entering heat exchanger 1 (HX1) at state point 33. Simultaneously, ambient air at state point 36 undergoes humidification in the open HDH humidifier (Hum1) due to contact with the heated fluid stream. The humidified air then moves to the low-temperature dehumidifier (DeHum1), where it loses moisture, resulting in fresh water production.

The liquid stream exiting HX1 is throttled in two stages: first to the pressure level of DeHum1 and then to the pressure level of the refrigeration evaporator (REva) after being separated from stream 13. The flow pressure upon exiting REva is elevated using a vapor compressor before rejoining the stream exiting DeHum1. This combined fluid stream is directed to the absorber, where it absorbs the strong solution from the generator and releases heat. The heat released from the absorber is utilized in the flow exiting the dehumidifier of the closed HDH system (DeHum2), facilitating humidification and increasing fresh water production. Furthermore, the low-temperature flow leaving DeHum2 serves as a cooling flow in the condenser of ORC2.

Meanwhile, the heat dissipated by the condenser is used as a heat source for the absorption heat transformer (AHT), which is enhanced by an internal heat exchanger (HX2). This low-grade heat from the condenser fuels both the AHT evaporator and generator. Subsequently, this heat is upgraded within the AHT absorber. Given the AHT absorber's temperature, which exceeds 100 °C, the dissipated heat can be effectively used for desalination. The stream exiting the separation vessel and HX3 contributes to powering the other ORC, generating the second portion of power. The working fluid used in these ORCs is n-hexane (C6H14) [28].

3 Modeling and analysis

For investigations, Ahvaz reference-environment data [27] are utilized (i.e., T = 41 °C, P = 1 atm, and φ = 56 %). Furthermore, some simplifying assumptions are made as follows.● All heat exchangers are assumed to have an effectiveness of 80 % [4,7].

● Negligible pressure losses are assumed in pipelines and system components, except for expansion valves [7].

● It is assumed that the streams at the exits of all condensers and evaporators are in the saturated state [7].

● The weak and strong solutions exiting the absorbers and generators are assumed to be in the saturated state [29].

● The LiBr solutions in the absorbers and generators are assumed to be in equilibrium at their respective temperatures and pressures [29].

● Inlet seawater is assumed to have a pressure of 1 atm and a salinity of 35 g/kg [17].

3.1 Mathematical modeling

The proposed multigeneration system undergoes a thermodynamic analysis under steady-state conditions. Mass and energy conservation within a control volume experiencing a steady-state steady flow process, while neglecting changes in kinetic and potential energy, are expressed as follows.● Conservation of mass

(1) ∑m˙i=∑m˙e

(2) ∑m˙iXi=∑m˙eXe

● Conservation of Energy

(3) ∑Q˙+∑m˙inhin=∑W˙+∑m˙outhout

The governing equations for each system component are presented in Table 1.Table 1 Governing equations for each system component.

Table 1Equipment	Mass and energy balance equations	
Pump1	W˙P1=m˙20(h21−h20)	
ηis,P1=(h21s−h20)/(h21−h20)	
m˙21=m˙20	
x21=x20	
Pump2	W˙P2=m˙48(h49−h48)	
ηis,P2=(h49s−h48)/(h49−h48)	
m˙49=m˙48	
x49=x48	
Pump3	W˙P3=m˙41(h42−h41)	
ηis,P3=(h42s−h41)/(h42−h41)	
m˙41=m˙42	
x41=x42	
Pump4	W˙P4=m˙58(h58−h61)	
ηis,P4=(h58s−h61)/(h58−h61)	
m˙58=m˙61	
Pump5	W˙P5=m˙8(h8−h7)	
ηis,P5=(h8s−h7)/(h8−h7)	
m˙8=m˙7	
Turbine1	W˙Turbine1=m˙59(h59−h60)	
ηis,Turbine1=(h59−h60)/(h59−h60s)	
m˙60=m˙59	
Turbine2	W˙Turbine2=m˙4(h4−h5)	
ηis,Turbine2=(h4−h5)/(h4−h5s)	
m˙4=m˙5	
HRS1	m˙56h56+m˙58h58=m˙57h57+m˙59h59	
m˙58=m˙59	
m˙56=m˙57	
HRS2	m˙2h2+m˙9h9=m˙3h3+m˙4h4	
m˙2=m˙3	
m˙4=m˙9	
CondensorORC1	Q˙ConORC1=m˙61(h60−h61)	
m˙60=m˙61	
CondensorORC2	Q˙ConORC2=m˙6(h6−h7)	
m˙6=m˙7	
Recuperator	m˙5h5+m˙8h8=m˙6h6+m˙9h9	
m˙5=m˙6	
m˙8=m˙9	
Economizer	m˙23(h23−h24)=m˙21(h22−h21)	
m˙23=m˙24	
m˙21=m˙22	
x23=x24	
x21=x22	
EconomizerAHT	m˙45(h45−h46)=m˙50(h50−h49)	
m˙50=m˙49	
m˙45=m˙46	
x50=x49	
x45=x46	
AbsorberAHT	m˙44h44+m˙50h50−m˙45h45=m˙52(h53−h52)	
m˙44+m˙50=m˙45	
x45m˙45=x50m˙50	
Absorber	m˙19h19+m˙25h25−m˙20h20=m˙27(h27−h28)	
m˙25x25=m˙20x20	
m˙25+m˙19=m˙20	
Generator	m˙23h23+m˙10h10−m˙22h22=m˙1(h1−h2)	
m˙23x23=m˙22x22	
m˙10+m˙23=m˙22	
GeneratorAHT	Q˙GenAHT=m˙39h39+m˙48h48−m˙47h47	
Condensor	Q˙Con=m˙11(h10−h11)	
Q˙Con=Q˙GenAHT+Q˙EvaAHT	
CondensorAHT	Q˙ConAHT=m˙40(h40−h41)	
m˙40=m˙41	
Hum1	m˙36h36+m˙34h34=m˙35h35+m˙37h37	
m˙36+m˙34=m˙35+m˙37	
εHum1=max(h34−h35h34−hideal,35,h37−h36h37−hideal,36)	
Hum2	m˙29h29+m˙28h28=m˙31h31+m˙30h30	
m˙29+m˙28=m˙31+m˙30	
εHum2=max(h28−h30h28−hideal,30,h31−h29h31−hideal,29)	
DeHum1	m˙37h37+m˙13h13=m˙38h38+m˙17h17+m˙18h18	
εDeHum1=max(h13−h17h13−hideal,17,h37−h38h37−hideal,38)	
m˙13=m˙17	
m˙18+m˙17=m˙37	
DeHum2	m˙26h26+m˙31h31=m˙32h32+m˙29h29+m˙27h27	
m˙31=m˙32+m˙29	
εDeHum2=max(h27−h26h27−hideal,26,h31−h29h31−hideal,29)	
Refrigerant Evaporator	Q˙REva=m˙15(h15−h14)	
m˙14=m˙15	
EvaporatorAHT	Q˙EvaAHT=m˙44h44−m˙43h43	
Heat Exchanger1
(HX1)	m˙33(h34−h33)=m˙11(h11−h12)	
m˙33=m˙34	
m˙11=m˙12	
Heatexchanger2
(HX2)	m˙42(h43−h42)=m˙39(h39−h40)	
m˙39=m˙40	
m˙42=m˙43	
x39=x40	
x42=x43	
Heatexchanger3
(HX3)	m˙51(h52−h51)=m˙54(h54−h56)
m˙51=m˙52
m˙54=m˙56	
Heatexchanger4
(HX4)	Q˙AbsAHT=m˙52(h53−h52)	
m˙52=m˙53	
SP	m˙54=x53m˙53	
m˙55=(1−x53)m˙53	

The thermal efficiency of the solar collector (ηcol) is determined using the following equation, specifically considering the Flat Plate Collector with a selective absorber [30]:(4) ηcol=0.77−3.75Tm−T0GT−(Tm−T0)2GT

Eq. (4) incorporates the collector's fluid mean temperature (Tm=12(Tin,col+Tout,col)), the ambient temperature (T0), and the incident solar irradiation (GT) on the collector aperture.

The solar energy on the collector aperture (Qsolar) is determined as the product of the collector's collecting area (Acol) and the total incident solar irradiation:(5) Qsolar=Acol.GT

The useful heat production in the solar collector (Qu) can be expressed as follows:(6) Qu=ηcol.Qsolar

The exergy factor of solar irradiation (ψsolar) is computed using the Petela model, which considers the sun as a radiation reservoir:(7) ψsolar=(Q˙Gen+Q˙HRS2)[1−43(T0+273.155770)+13(T0+273.155770)4]

3.1.1 System performance indicators

The primary performance indices for the cogeneration system encompass the distilled water mass flow rate, refrigeration capacity, and power. These indices are defined considering that the system produces power, water, and refrigeration. To assess the system's thermodynamic performance, we utilize and express the COP and ECOP as follows:(8) COPAR=Q˙REva+Q˙Dehum1Q˙Gen+W˙Pump1

(9) COPAHT=Q˙AbsAHTQ˙EvaAHT+Q˙EvaAHT+W˙Pump1+W˙Pump2

(10) COPtotal=Q˙REva+m˙18hfg@T18+m˙32hfg@T32+m˙55hfg@T55+W˙1+W˙2Q˙Gen+Q˙HRS2+W˙vaporcompressor+∑W˙pumps

(11) {ECOP=W˙1+W˙2+Q˙REva(|1−T0+273.15T18+273.15|)+ψdwψsolar+W˙vaporcompressor+∑W˙pumpsψdw=∑i=18,32,55mi(hi−h0−T0(si−s0))

The financial analysis of the proposed system is conducted using the simple payback period (SPP). The SPP is calculated as the ratio of the total purchased equipment cost (PECtotal) to the system income derived from the production of primary products, including distilled water, refrigeration, and electricity. The mathematical expression for SPP is as follows:(12) SSP=PECtotalcelecW˙total+crefrigQ˙REva(|1−T0+273.15T18+273.15|)+cdwm˙dw.1τ

Where τ is assumed to be the annual operating hours, set at 8000 h. The unit costs of electricity, refrigeration, and distilled water, along with the system's operating conditions, are presented in Table 2. The purchased equipment cost (PEC) is calculated as the sum of costs for all components using the cost equations provided in Table 3. To account for inflation and bring all cost data to the reference year (2023), Eq. (13) is used.(13) Costatreferenceyear=OriginalcostCostindexforthereferenceyearCostindextfortheyearwhentheoriginalcostwasgained

Table 2 The simulation typical operating conditions and constrains.

Table 2Parameter	Value	
Ambient pressure, P0	101.3 kPa	
Ambient temperature for Ahvaz, T0	41 °C [27]	
Ambient relative humidity for Ahvaz, φ0	56 % [27]	
AR generator temperature, TGen	130 °C [7]	
AR condenser temperature, TCon	85 °C [7]	
AR absorber temperature, TAbs	50 °C [7]	
AR generator heat transfer rate, Q˙Gen	150 kW	
AHT generator temperature, TGen,AHT	80 °C [20]	
AHT condenser temperature, TCon,AHT	30 °C [20]	
AHT absorber temperature, TAbs,AHT	103 °C [20]	
AHT evaporator temperature, TEva,AHT	80 °C [20]	
HRS2 heat transfer rate, Q˙HRS2	75 kW	
HRS1 temperature, T59	T56-5 °C	
Flow temperature leaving collector, T1	135 °C	
Total incident solar irradiation, GT	1000 W/m2	
Turbine isentropic efficiency	80 %	
Pumps and compressor isentropic efficiencies	80 % [31]	
Seawater temperature, Tsw	25 °C [31]	
Seawater salinity, S	35 g/kg [31]	
HDH Pressure	101.3 kPa [31]	
Effectiveness of humidifier, εh	0.85 [[32], [33], [34]]	
Effectiveness of dehumidifier, εd	0.85 [[32], [33], [34]]	
UAEvap	85 kW/K [35]	
UAAbs	50 kW/K [36]	
UAGen	25 kW/K [35]	
UACond	65 kW/K [35]	
UAHX,Eco	2 kW/K [29]	
Electricity Cost, celec	60 $/GJ	
Distilled water cost, cdw	53 $/m3 [37]	
Refrigeration cost, crefrig	180 $/GJ [7]	

Table 3 Correlations used to determine component purchase equipment costs.

Table 3Components	Cost Equations ($)	CEPCI [38,39]	Ref.	
P1,2,3,4,5	PEC2000=2100(W˙10)0.26(1−ηη)0.5	576.1	[36]	
Absorber + SP	PEC2000=16500(A10)0.6	394.1	[17,40]	
AbsorberAHT	PEC2000=16500(A10)0.6	394.1	[40]	
Generator	PEC2000=17500(A10)0.6	394.1	[40]	
GeneratorAHT	PEC2000=17500(A10)0.6	394.1	[40]	
Condenser	PEC2000=8000(A10)0.6	394.1	[40]	
CondenserAHT	PEC2000=8000(A10)0.6	394.1	[40]	
Refrigerant Evaporator	PEC2000=16000(A10)0.6	394.1	[40]	
EvaporatorAHT	PEC2000=16000(A10)0.6	394.1	[40]	
TV	PEC2000=300	394.1	[40]	
Economizers	PEC2000=12000(A10)0.6	394.1	[40]	
HRS1,2	PEC1996=PEC0(1.63+1.66FP)
log10PEC0=4.3247−0.303log10A+0.1634(log10A)2
log10FP=0.03881−0.1127log10P+0.0818(log10P)2
(A is the heat transfer area in m2, and P is the pressure in barrages)	381.7	[37]	
Turbines	PEC1996=3.5PEC0
log10PEC0=2.2476−1.4965log10W˙−0.1618(log10W˙)2	381.7	[37]C	
CondenserORC1,2	PEC1996=PEC0(1.63+1.66FP)
log10PEC0=4.3247−0.303log10A+0.1634(log10A)2
log10FP=0.03881−0.1127log10P+0.0818(log10P)2
(A is the heat transfer area in m2, and P is the pressure in barrages)	381.7	[37]	
Humidifier1,2	PEC2012=133(m˙freshwater0.0015)0.6	584.6	[41]	
Dehumidifier1,2	PEC2012=70(m˙freshwater0.0015)0.6	584.6	[41]	
HX1,2,3,4 & Recuperator	PEC2000=PEC0(1.63+1.66.FP)
logPEC0=4.3247−0.303log10A+0.1634(log10A)2
logFP=0.03881−0.11272logPhe,i+0.08183(logPhe,i)2	397	[42]	

The cost index for the reference year is obtained from literature [38,39].

4 Results and discussion

In the present study, the theoretical simulation of the proposed multigeneration system was conducted using EES software. The simulation's operating conditions and constraints have been compiled and are presented in Table 2.

4.1 Validations

In the current study, data validation was performed in three sections.

4.1.1 Absorption refrigeration system

To validate the data for the absorption refrigeration system, results from Wu et al. [43] were employed. COP values were compared as depicted in Fig. 2, which incorporated data from both this study and the literature. As shown in Fig. 2, a high degree of agreement was observed between the values, with the maximum relative difference of about 5 %.Fig. 2 Data validation for the absorption refrigeration system.

Fig. 2

4.1.2 Absorption heat transformer

The data derived from the numerical simulation of the absorption heat transformer were subjected to validation by comparing them with the data reported by Zhao et al. [44]. The results of this comparison are illustrated in Fig. 3, where it is evident that the maximum relative difference is approximately −4%.Fig. 3 Data validation for the absorption heat transformer system.

Fig. 3

4.1.3 Humidification-dehumidification system

The validation of the numerical simulation for the HDH system involved comparing the obtained numerical data with the experimental data provided by Chiranjeevi and Srinivas [45]. The validation results revealed that, under identical experimental operating conditions (i.e., a mass flow rate of 125 Lit/h and a hot water temperature of 50 °C), a temperature rise of 10.8 °C was exhibited by the simulated system. This result fell within the range reported in the existing literature [45].

4.2 Data parametric analysis

A summary of properties for various state points at a temperature of 41 °C, a pressure of 1 atm, and a relative humidity of 56 % is presented in Table 4. According to the results gained, the closed HDH system, which is supplied by the AR absorber, outperforms the others by producing approximately 57 % of the fresh water (m˙32) due its higher mass flow rate. In contrast, the evaporative desalination system lags behind all systems (m˙54), contributing only 15 % of the total water production, while the remaining 28 % is attributed to the open HDH system (m˙18). Moreover, approximately 69 % of the total power is generated by ORC2 regarding its higher inlet energy, while the remaining power output is contributed by ORC1.Table 4 Calculated parameters for each state point.

Table 4States	m˙ (kg/s)	T (oC)	P (kPa)	quality	XLiBr	h˙ (kW/kg)	s˙ (kW/kg.K)	Salinity g/kg	φ (%)	ω (kgw/kga)	
1	2.329	150	475.7	0	–	632.3	1.842	0	–	–	
2	2.329	135	475.7	sc	–	567.9	1.687	0	–	–	
3	2.329	127.5	475.7	sc	–	535.7	1.607	0	–	–	
4	0.165	130.2	488.8	1	–	541.7	1.439	–	–	–	
5	0.165	80.7	25	sh	–	460.8	1.497	–	–	–	
6	0.165	37.8	25	sh	–	382.8	1.263	–	–	–	
7	0.165	30	25	0	–	7.079	0.024	–	–	–	
8	0.165	30.2	488.8	sc	–	8.027	0.025	–	–	–	
9	0.165	63.5	488.8	sc	–	86.07	0.268	–	–	–	
10	0.053	130	57.81	sh	–	2740	7.777	0	–	–	
11	0.053	85	57.81	0	–	355.9	1.134	0	–	–	
12	0.053	66.1	57.81	sc	–	276.7	0.907	0	–	–	
13	0.053	20	2.34	0.079	–	276.7	0.954	0	–	–	
14	0.032	15	1.71	0.087	–	276.7	0.966	0	–	–	
15	0.032	15	1.71	1	–	2528	8.779	0	–	–	
16	0.032	40.9	2.34	sh	–	2577	8.795	0	–	–	
17	0.021	20	2.34	1	–	2537	8.665	0	–	–	
18	0.015	21	101.3	0	–	88.11	0.310	0	–	–	
19	0.053	32.6	2.34	sh	–	2561	8.744	0	–	–	
20	1.137	50	2.34	–	0.542	112.3	0.316	–	–	–	
21	1.137	50.1	57.81	–	0.542	113.1	0.315	–	–	–	
22	1.137	122.7	57.81	–	0.542	267.7	0.747	–	–	–	
23	1.085	130	57.81	–	0.568	286.2	0.752	–	–	–	
24	1.085	51	57.81	–	0.568	123.2	0.304	–	–	–	
25	1.085	55.2	2.34	–	0.568	123.2	0.330	–	–	–	
26	3.451	25	101.3	–	–	99.7	0.350	35	–	–	
27	3.451	37.8	101.3	–	–	151.1	0.519	35	–	–	
28	3.451	48	101.3	–	–	191.8	0.647	35	–	–	
29	1.419	30.5	101.3	–	–	102.4	5.963	–	100	0.0280	
30	3.395	35.3	101.3	–	–	140.7	0.485	35.6	–	–	
31	1.474	46.8	101.3	–	–	223.4	6.352	–	95	0.0681	
32	0.055	30.5	101.3	0	–	127.8	0.443	0	–	–	
33	0.018	25	101.3	–	–	99.77	0.350	35	–	–	
34	0.018	84	101.3	–	–	336.6	1.075	35	–	–	
35	0.014	47.9	101.3	0	–	188.8	0.634	45.2	–	–	
36	0.904	41	101.3	–	–	113.4	5.999	–	56	0.0280	
37	0.908	33	101.3	–	–	116.6	6.009	–	100	0.0325	
38	0.893	21	101.3	–	–	60.9	5.824	–	100	0.0156	
39	0.026	80	4.25	sh	–	2560	8.74	0	–	–	
40	0.026	30.1	4.25	sh	–	2556	8.452	0	–	–	
41	0.026	30	4.25	0	–	125.7	0.437	0	–	–	
42	0.026	30	47.37	sc	–	125.7	0.437	0	–	–	
43	0.026	52.5	47.37	sc	–	220	0.737	0	–	–	
44	0.026	80	47.37	1	–	2643	7.611	0	–	–	
45	0.095	103	47.37	–	0.459	229	0.748	–	–	–	
46	0.095	91.1	4.25	–	0.459	200.7	0.672	–	–	–	
47	0.095	50.3	4.25	0.039	0.478	200.7	0.688	–	–	–	
48	0.069	80	4.25	–	0.629	210.2	0.435	–	–	–	
49	0.069	80.1	47.37	–	0.629	210.5	0.436	–	–	–	
50	0.069	100.8	47.37	–	0.629	248.9	0.541	–	–	–	
51	0.042	25	101.3	–	–	4.214	0.015	35	–	–	
52	0.042	90.1	101.3	–	–	15.93	0.050	35	–	–	
53	0.042	101.8	101.3	0.65	–	1872.4	5.166	100	–	–	
54	0.027	101.8	101.3	1	–	2678.1	7.331	0	–	–	
55	0.015	101.8	101.3	0	–	375.3	1.141	100	–	–	
56	0.027	100	101.3	0.81	–	2251.3	6.216	0	–	–	
57	0.027	37.2	101.3	sc	–	155.9	0.535	0	–	–	
58	0.328	32.2	3594	sc	–	96.7	0.351	–	–	–	
59	0.328	95	3594	1	–	272.3	0.853	–	–	–	
60	0.328	30	770.6	0.91	–	251.8	0.870	–	–	–	
61	0.328	30	770.6	0	–	93.58	0.348	–	–	–	
sc: subcooled.

sh: superheat.

4.2.1 Thermodynamic analysis

As shown in Fig. 1, solar heat is supplied simultaneously to both the absorption refrigeration generator and HRS2. This interaction significantly impacts energy and exergy performance parameters, particularly the COP and ECOP, as illustrated in Fig. 4. An increase in the QHRS2QGen ratio is closely associated with an improvement in the COP.Fig. 4 The trend of coefficient of performance (COP) and exergy coefficient of performance (ECOP) in relation to QHRS2QGen (HRS: Heat Recovery System).

Fig. 4

This improvement occurs because a higher QHRS2 increases the output power from turbine 2, enhancing the overall COP. Notably, the ECOP curve peaks at approximately QHRS2QGen = 0.75.

On the other hand, the temperature of the absorption refrigeration generator is crucial in determining the overall system performance. Fig. 5 shows the variation in both COP and ECOP concerning generator temperature. As evident in Fig. 5, increasing the generator temperature results in a gradual and consistent decline in COP due to the reduction in generator heat, while simultaneously causing a smooth increase in ECOP.Fig. 5 The trends of COP and ECOP in relation to the refrigeration generator temperature (TGen).

Fig. 5

Furthermore, the ratio of QHRS2QGen and the generator temperature can impact the solar collector efficiency, as defined in Eq. (4), by altering the mean temperature of the solar collector. Fig. 6 illustrates the variation in collector thermal efficiency at various generator temperatures and QHRS2QGen ratios. As shown in Fig. 6, an increase in generator temperature across four different QHRS2QGen ratios consistently leads to a decrease in collector efficiency. Based on Fig. 6, as the QHRS2QGen ratio increases by tenfold, the collector efficiency decreases by approximately 68.7 % at TGen = 150 °C. This behavior can be attributed to the significant increase in the inlet and outlet temperatures of the collector as the generator temperature rises, leading to a decrease in collector efficiency.Fig. 6 The relationship between solar collector efficiency and the refrigeration generator temperature (TGen) under varying ratios of QHRS2QGen (HRS: Heat Recovery System).

Fig. 6

The impact of both condenser and generator temperatures on the overall COP is examined and illustrated Fig. 7. As depicted in Fig. 7, when the generator temperature falls below 152 °C, elevating the condenser temperature leads to an improvement in the overall COP. Conversely, when temperatures exceed 152 °C, the relationship is reversed. The COP variations with the absorption generator temperature decrease at low condenser temperatures. This means that the COP reduction at high condenser temperatures is more significant than the COP reduction at low condenser temperatures. This behavior is due to changes in the mass flow rate of the absorption refrigeration system and consequently changes in the heat rejected from the absorption condenser. Considering that at generator temperatures higher than 152 °C, the condenser heat at lower temperatures is greater, the amount of heat provided to the absorption heat transformer also will be higher. This results in increased power and water production. Therefore, the COP will increase relative to high condenser temperatures.Fig. 7 The relationship between overall COP and the refrigeration generator temperature (TGen) at three different refrigeration condenser temperatures (TCon).

Fig. 7

On the other hand, the AHT absorber temperature is influenced by the AHT coefficient of performance (COPAHT), which has the potential to change the overall COP. Consequently, an examination of the variation in COPAHT with changes in the AHT absorber temperature is conducted and depicted in Fig. 8. As indicated by Fig. 8, when the AHT absorber temperature is increased, it can be noted that COPAHT remains constant up to approximately 130 °C. However, beyond this temperature threshold, a gradual decline is initiated, eventually leading to a sharp decrease of about 56 %. This behavior is due to the increased AHT absorber temperature causing a corresponding reduction in AHT absorber heat.Fig. 8 Variation of COPAHT with the absorber temperature (TAbsAHT) of the absorption heat transformer (AHT: Absorption Heat Transformer).

Fig. 8

The variation in AHT absorber temperature gives rise to alterations in both the fresh water flow rate produced by the absorption heat transformer and the power generated by ORC1 (W˙1). Consequently, the fluctuation of these two parameters versus AHT absorber temperature is depicted in Fig. 9. Based on Fig. 9, it's evident that as the absorber temperature increase, the flow rate and output power of the AHT cycle exhibit stability until reaching around 130 °C. Past this point, both parameters experience a gradual decline, culminating in a sharp drop of about 53–56 %, attributed to the diminished rejected heat from the AHT absorber.Fig. 9 Variation in fresh water mass flow rate (ṁ) and ORC1 power generation (W˙1) with AHT absorber temperature variations (TAbsAHT).

Fig. 9

The fluctuation in total fresh water mass flow rate and total generated power due to changes in the absorption refrigeration (AR) condenser temperature is illustrated in Fig. 10. According to Fig. 10, elevating the AR condenser temperature to around 72 °C results in an increase of approximately 7–10 % in both the total fresh water flow rate and the total generated power, attributed to the increased heat supplied to the AHT system Subsequently, both parameters experience a slight further increase, reaching a maximum value, before gradually diminishing.Fig. 10 Variation in total fresh water mass flow rate (ṁ) and total power generation (W˙) with refrigeration condenser temperature variations (TCon).

Fig. 10

4.2.2 General economic analysis

The behavior of the SPP in relation to both the AR generator temperature and the QHRS2QGen ratio is depicted in Fig. 11, Fig. 12, respectively. In Fig. 11, it is observed that as the AR generator temperature increases up to 130 °C, the SPP experiences a sharp decrease to approximately 3.6 years, after which it starts to gradually increase with a gentler slope.Fig. 11 Trend of simple payback period (SPP) variation with respect to absorption refrigeration generator temperature (TGen).

Fig. 11

Fig. 12 Trend of the simple payback period (SPP) variation with respect to the QHRS2QGen ratio.

Fig. 12

As for Fig. 12, the overall trend in SPP with the QHRS2QGen ratio is upward, indicating an increase in the payback period. Nevertheless, it's noteworthy that within the QHRS2QGen ratio range of 1–2.6, there is a slight, almost negligible, decrease in the SPP trend.

4.2.3 Pareto frontier solutions

In multi-objective optimization, the Pareto frontier is a crucial concept that aids in decision-making. It graphically represents the trade-offs between conflicting objectives when seeking the optimal solution. This frontier shows a set of design points where improving one objective comes at the cost of another. By exploring the Pareto frontier, decision-makers can make informed choices that align with their preferences and priorities, leading to well-balanced and efficient solutions. This concept is particularly valuable in complex engineering, economic, and decision-making scenarios where multiple competing objectives must be considered.

In multi-objective optimization solutions, determining the optimal design point on the Pareto frontier requires considering the decision maker's preferences. The "ideal point" is conceptualized as a state where all objective functions achieve their optimal values simultaneously. This ideal point serves as a critical reference for selecting the optimal design point. Given the impracticality of locating the ideal point on the Pareto frontier, it is common practice to designate the nearest point on the Pareto frontier to the ideal point as the ultimate optimal design point [46].

In the present study, the three-dimensional Pareto frontier solution is explored within the context of two distinct groups of performance parameters. The first group encompasses the COP, ECOP, and SPP. The second group includes distilled water mass flow rate (m˙dw), refrigeration heat transfer rate (Q˙R), and generated power (W˙), which are treated as three objective functions. The optimization objectives involve the maximization of COP and ECOP, as well as the minimization of SPP in the first group of performance parameters and maximization of m˙dw, Q˙R and W˙ in the second one. The decision variables involved in the construction of the Pareto frontiers pertain to the temperatures of key components within the absorption refrigeration system, specifically the evaporator (T15), the condenser (T11), and dehumidifier (T17).

Fig. 13 provides a comprehensive depiction of viable design points, exceeding a total of 145,000, for the proposed multigeneration system concerning the first set of objective functions (COP, ECOP, and SPP). Each of these points showcases values related to the first group of three objective functions, which are denoted in blue. To enhance clarity, Fig. 13 also includes two-dimensional scatter plot representations of these solutions, indicated in yellow.Fig. 13 Comprehensive representation of over 147000 feasible design points in blue, accompanied by the corresponding two-dimensional projection depicted in yellow.

Fig. 13

The Pareto frontier solution corresponding to the surface displayed in Fig. 13 is illustrated in Fig. 14, represented in blue. Two-dimensional projections of the 3D Pareto front are presented in yellow. As per the data provided in Fig. 14, the optimal point is characterized by values of COP, ECOP, and SPP at 2.13, 0.185, and 3.34 years, respectively. The corresponding decision values including T17, T15 and T11 are 25 °C, 9.13 °C and 76.65 °C, respectively.Fig. 14 Illustration of the Pareto frontier solution with COP, ECOP and SPP as objective functions, represented in blue. Corresponding two-dimensional projections are highlighted in yellow.

Fig. 14

Fig. 15 illustrates the Pareto frontier solution as a three-dimensional curved surface, defined by the coordinates of generated power (W˙), distilled water mass flow rate (m˙dw), and refrigeration heat transfer rate (Q˙R) for the proposed multigeneration system, depicted in blue. Additionally, Fig. 15 provides two-dimensional visualizations of the Pareto frontier solution, depicted in yellow. According to the figure, the optimal point features generated power, distilled water mass flow rate, and refrigeration heat transfer rate values of 16.77 kW, 99.84 g/s, and 74.44 kW, respectively. The corresponding decision values are T11 = 85.28 °C, T15 = 18 °C, and T17 = 25 °C.Fig. 15 Illustration of the Pareto frontier solution with fresh water flow rate (m˙dw), total generated power (W˙) and refrigeration heat transfer rate (Q˙R) as objective functions, represented in blue. Corresponding two-dimensional projections are depicted in yellow.

Fig. 15

The summaries of the data acquired from Fig. 14, Fig. 15 are presented in Table 5.Table 5 The results derived from the 3D Pareto frontier figures.

Table 5Objective variables	COP	ECOP	SPP (year)	W˙ (kW)	Q˙R (kW)	m˙dw (g/s)	T11 (oC)	T15 (oC)	T17 (oC)	
COP, ECOP and SPP	2.13	0.185	3.34	13.68	73.35	100.6	76.65	9.13	25	
W˙, Q˙R and m˙dw	2.17	0.175	3.54	16.77	74.4	99.84	85.28	18	25	

In spite of the utilization of 3D Pareto fronts within the current study, two-dimensional Pareto front solutions are also provided.

Fig. 16 shows the Pareto front considering COP and SPP as objective variables. According to Fig. 16, the optimal point is characterized by COP and SPP values of 2.136 and 3.37 year, respectively. The corresponding decision variables are T11 = 77.64 °C, T15 = 10.86 °C and T17 = 25 °C.Fig. 16 2D Pareto frontier solution with coefficient of performance (COP) and simple payback period (SPP) as objective functions.

Fig. 16

On the other hand, considering ECOP and SPP as the objective parameters, Fig. 17 illustrates the corresponding Pareto front. According to the data presented in Fig. 17, the optimal point is characterized by ECOP and SPP values of 0.1912 and 3.24 years, respectively. The corresponding values of the decision variables are as follows: T11 = 80.35 °C, T15 = 1 °C, and T17 = 25 °C.Fig. 17 2D Pareto frontier solution with exergy coefficient of performance (ECOP) and simple payback period (SPP)as objective functions.

Fig. 17

The summaries of the data obtained from Fig. 16, Fig. 17 are presented in Table 6.Table 6 The results derived from the 2D Pareto frontier figures.

Table 6Objective variables	COP	ECOP	SPP (year)	W˙ (kW)	Q˙R (kW)	m˙dw (g/s)	T11 (oC)	T15 (oC)	T17 (oC)	
COP and SPP	2.136	0.1812	3.37	14.32	73.52	100.5	76.65	9.13	25	
ECOP and SPP	2.102	0.1912	3.24	10.3	73.13	101.9	80.35	1	25	

Table 7 presents a comparison between the results of this study and data from other research. Key parameters such as COP, ECOP, SPP, W˙, Q˙R and m˙dw are used for evaluation. Despite the different operational conditions, as outlined in Table 7, the proposed system demonstrates relatively higher COP, SPP, Q˙R and m˙dw compared to the systems assessed in the literature.Table 7 Comparison of the proposed system with those documented in the literature.

Table 7Present Work and Reference	System Type	System Outputs	COP	ECOP	SPP (year)	W˙ (kW)	Q˙R (kW)	m˙dw (g/s)	
present work	multigeneration	power, cooling and fresh water	2.15	0.18	3.5	17.2	74	100.6	
Qasem et al. [47]	cogeneration	cooling and fresh water	1.3	–	–	–	–	278	
Almehmadi et al. [48]	multigeneration	power, cooling, heating, and freshwater	–	–	–	102.3	21	39.3	
Almehmadi et al. [49]	multigeneration	power, cooling, heating, and freshwater	–	–	–	102	29.9	59.6	
Esfandi et al. [50]	multigeneration	power, cooling and syngas	–	0.15	15.6	–	–	–	
Abdelhay et al. [51]	multigeneration	power, cooling and fresh water	0.78	0.24	–	46.8	88.3	72.7	

5 Conclusion

In this work entitled “Investigation of a Novel Solar-Assisted Multigeneration System Comprising Water Desalination Systems, an Absorption Refrigeration System, a Single-Effect Absorption Heat Transformer and Two Organic Rankine Cycles”, a novel solar-assisted multigeneration system capable of concurrently producing electricity, distilled water, and refrigeration is introduced. Solar energy is harnessed through an absorption refrigeration generator and the heat recovery mechanism of an organic Rankine cycle (ORC), coupled with two distinct humidification-dehumidification (HDH) desalination systems, addressing critical energy and water challenges. The general conclusion can be discussed from the following three aspects.

5.1 Thermodynamic aspects

Evaluation of critical thermodynamic parameters including coefficient of performance (COP), exergy coefficient of performance (ECOP), and refrigeration capacity provides valuable insights into the system's performance. Followings are the most important thermodynamic results.● An increase in the QHRS2QGen ratio is linked to an enhancement in the COP. This phenomenon can be elucidated through this fact that an augmentation in QHRS2 leads to an increase in the output power of Turbine 2, consequently yielding an overall elevation in the COP. Conversely, it is worth noting that the ECOP curve reaches its zenith at approximately QHRS2 = 0.75. On the other hand, elevating the generator temperature leads to a gradual and consistent decline in COP, while simultaneously promoting a smooth increase in ECOP.

● The closed HDH system, which is fed by the absorption refrigeration absorber, excels among the various systems, generating approximately 57 % of the fresh water output. In contrast, the evaporative desalination system underperforms in comparison to all other systems, contributing only 15 % to the total water production. The remaining 28 % is accounted for by the open HDH system.

● ORC2 generates around 69 % of the total power, with the remainder of the power output originating from ORC1.

5.2 Economic aspects

The economic feasibility of the system is evaluated through parameters like simple payback period (SPP) and total generated power. Considerations of cost-effectiveness and economic viability underline the importance of the proposed solution in addressing both thermal challenges and economic constraints. The following are the most significant economic outcomes.● As the absorption refrigeration generator temperature increases up to 130 °C, the SPP undergoes a significant decline, reaching a minimum of approximately 3.6 years. Subsequently, there is a gradual increase in the SPP. Moreover, there is a general positive correlation between the SPP and the QHRS2QGen ratio. However, it's important to highlight that within the QHRS2QGen ratio range of 1–2.6, there is a minor, almost inconsequential, dip in the SPP trend.

● Considering COP, ECOP and SPP as objective variables, the optimal point is characterized by values of COP, ECOP, and SPP at 2.13, 0.185, and 3.34 years, respectively. On the other hand, when evaluating distilled water mass flow rate (m˙dw), generated power (W˙), and refrigeration heat transfer rate (Q˙R) as objective parameters, the values at the optimal point are 16.77 kW for W˙, 99.84 g/s for m˙dw, and 74.44 kW for Q˙R.

5.3 Industrial aspects

The proposed system presents several significant industrial applications and benefits.I. Energy Efficiency and Cost Savings:● By generating 21.46 kW of electricity using solar energy and an ORC, industries can reduce their reliance on conventional fossil fuel-based power sources, lowering operational costs and minimizing carbon emissions.

● Producing 71.02 kW of refrigeration through the absorption refrigeration system offers a sustainable solution for industries requiring cooling processes, such as food and beverage, pharmaceuticals, and chemical manufacturing, significantly cutting down energy costs associated with conventional refrigeration methods.

II. Water Desalination:● The system's capability to produce up to 100.65 g per second of distilled water is particularly beneficial for industries in arid regions or those facing water scarcity, ensuring a reliable supply of high-quality distilled water for various industrial processes.

● Producing distilled water using solar energy reduces the environmental footprint compared to traditional desalination methods, which are energy-intensive and often reliant on non-renewable energy sources.

III. Optimal Integration and Scalability:● The modular nature of the system allows for scalable integration into existing industrial setups, facilitating incremental investments and minimizing initial capital expenditure.

● Its versatility in producing electricity, refrigeration, and distilled water makes it suitable for a wide range of industrial applications, from small-scale operations to large manufacturing plants.

IV. Sustainability and Regulatory Compliance:● Utilizing solar energy aligns with global trends towards renewable energy adoption and supports industries in meeting regulatory requirements and sustainability goals, enhancing corporate social responsibility profiles and attracting environmentally-conscious investors.

● By reducing reliance on fossil fuels and improving energy efficiency, the system contributes to significant reductions in greenhouse gas emissions, helping industries comply with environmental regulations and achieve sustainability certifications.

In summary, the proposed solar-assisted multigeneration system offers a robust and versatile solution for industrial applications, enhancing energy efficiency and sustainability while providing significant economic and environmental benefits. Its integration into various industries can drive advancements in renewable energy utilization, reduce operational costs, and support broader societal goals of environmental stewardship and sustainable development.

Data availability statement

The data associated with this study has not been deposited into a publicly available repository. However, the data will be made available upon request.

CRediT authorship contribution statement

S. Salehi: Writing – original draft, Visualization, Validation, Software, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. F. Javanfam: Writing – original draft, Methodology, Investigation.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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