Sustainable Energy Production Research Articles

Hydrogen sulfide methane reforming: A kinetic modeling and techno-economic analysis study

Hydrogen sulfide (H2S) methane (CH4) reforming (H2SMR) is a promising process for sustainable energy production from conventional fuels, offering triple benefits for generating clean hydrogen (H2), consuming toxic H2S, and producing an economically valuable by-product carbon disulfide (CS2). In this work, we studied the optimal operating conditions and assessed the economic feasibility of the non-catalytic H2SMR process, employing a combination of kinetic modeling, process modeling, and techno-economic analysis. Plug flow reactor simulations were performed with our newly developed mechanism to shed light on the optimal operating conditions. It was concluded that a H2S/CH4 molar feed ratio of 2 results in the highest hydrogen production rate, and a feed ratio of 1–2 and a temperature of 1100–1300 °C are needed to maximize the CS2 production rate. However, feed ratios higher than 2 increase the conversion rate of CH4 and therefore benefit the purity of the H2 product. Comparing the cases for a feed ratio of 2 at 1300 °C and a feed ratio of 9 at 1200 °C, the cost is significantly higher for the feed ratio of 9, mainly attributed to the higher electricity cost for higher inlet flow rate and H2S recycling, as well as the cost for the additional steam required during the preheating process. The cost of hydrogen production by H2SMR process could be as low as $1.47/kgH2 for a feed ratio of 2 and solar PV as an energy source, which is more competitive than a cost of $1.97/kgH2 for the steam methane reforming process. Furthermore, since CS2 is a valuable by-product, the higher amount of CS2 formed at a feed ratio of 2 becomes the main source of revenue, which completely covers the cost of hydrogen production. This study demonstrates the huge potential of H2SMR process as a clean and economic-competitive way to produce hydrogen.

SrMoO4-based mixed-potential gas sensor for NH3 sensing in direct ammonia-fed fuel cells

Direct ammonia-fed fuel cells (DAFCs) are well known for sustainable energy production. However, the issue is a certain amount of unreacted NH3 fuel is obtained at the outlet. Thus, real-time monitoring and quantification are of utmost importance, nevertheless, this is troublesome due to the harsh thermodynamic conditions. This work aims to develop a mixed-potential sensing electrode for the detection of NH3 under reducing conditions (H2 atmosphere) at high temperatures. In this regard, a strontium molybdate (SrMoO4) sensing electrode (SE) is a potential solution due to its physical and chemical stability, along with its sensitivity to NH3 under reducing conditions. Therefore, an SrMoO4-based mixed-potential sensor is fabricated herein using yttria-stabilized zirconia (YSZ) as the electrolyte and platinum (Pt) as the reference electrode (RE) and is operated at 400–650 ℃. The maximum response exhibits about –21.57 mV toward 80 ppm NH3 at 500 ℃. Further, the sensitivity is –17.19 mV/decade towards 10–60 ppm and –45.33 mV/decade towards 60–320 ppm NH3 under 75% H2 balanced by N2 at 500 ℃. The as-fabricated sensor also has good selectivity towards NH3 and good cross-sensitivity towards other interfering gases and is stable in long-term repeated operation. The direct current (DC) polarization curves and electrochemical impedance spectroscopy (EIS) results demonstrate the sensing mechanism in accordance with the mixed-potential theory.

Evaluation of Distillery Fractions in Direct Methanol Fuel Cells and Screening of Reaction Products

Fuel cells represent an appealing avenue for harnessing eco-friendly energy. While their fuel supply traditionally stems from water electrolysis, an environmentally conscious approach also involves utilizing low-weight alcohols like methanol and ethanol. These alcohols, concentrated from sustainable sources within the enological by-product distillation process, offer a noteworthy contribution to the circular economy. This study delved into evaluating the efficacy of distillery fractions in powering methanol fuel cells. Beyond their energy-generation potential, the performed GC-MS analysis unveiled appreciable quantities of acetic acid resulting from the partial oxidation of ethanol. This revelation opens the door to intriguing possibilities, including the recovery and repurposing of novel compounds such as short-chain fatty acids (predominantly acetic acid), ketones, and aldehydes—establishing a link between sustainable energy production and the emergence of valuable by-product applications.

Sustainability of underground infrastructure – Part 1: Digitalisation-based carbon assessment and baseline for TBM tunnelling

Alongside the transition towards sustainable and renewable infrastructure and energy production, tunnelling projects that adopt tunnel boring machines (TBM) continue to increase in size and complexity. Life Cycle Assessment (LCA) methodologies have a significant impact on the Architecture, Engineering and Construction (AEC) industry, with a shift in focus to cost and carbon management across the infrastructure lifecycle through the use of digitalisation techniques and sustainability rating systems. This paper aims to develop a systematic framework to enhance the sustainability of underground infrastructure in the early design and construction stages, aiming for “build clever and efficiently”. This framework integrates digitalisation, carbon assessment standards, numerical modelling, and optimisation techniques to assess carbon emissions and establish benchmarks for construction products and processes. The approach uses parametric models to define tunnelling-related entities such as geological formations, TBM, and segments, designed with dimensional constraints that allow for adaptive modelling and interactions. Enabled by building information modelling (BIM) through parametric models enriched with domain properties, module-based carbon accounting is adopted to evaluate the footprint of material- and asset-level key emitters with functional units. Leveraging established databases, baselines for segmental lining designs and carbon reduction strategies are established. Through project-driven case studies, the correlations among geotechnical conditions, tunnel dimensions, and TBM operating parameters are developed to quantify TBM carbon emissions. A prototype programme demonstrates the framework's application on typical metro and road tunnels at different levels of details (LoD). This paper serves as a guideline for conducting embodied carbon assessments specifically tailored to TBM tunnelling, acknowledging the substantial contribution of the TBM construction process, which is controlled by geotechnical conditions.

Optimization of syngas production via methane bi-reforming using CeO2 promoted Cu/MnO2 catalyst

Currently, syngas plays an important role in renewable and sustainable energy production. The idea of manufacturing syngas via bi-reforming methane, which involves the combination of methane (CH4), carbon dioxide (CO2), and steam, appears very promising. As a result, the goal of this research is to improve syngas output by improving process parameters in methane bi-reforming using a 3%Ce-15%Cu/MnO2 catalyst. Optimization analysis was performed using response surface methodology (RSM). The ultrasonic impregnation (UI) method was employed to synthesize the catalysts used in this study. Following that, the catalyst was characterized using several techniques such as Brunauer-Emmett-Teller (BET), X-ray diffraction (XRD), temperature programmed reduction (TPR), temperature programmed desorption (TPD), and temperature programmed oxidation (TPO). The findings of the characterization show that the presence of CeO2 promoters has a dual effect on the size of CuO crystallites. Firstly, it reduces the size from 19.07 nm to 13.66 nm because to the dilutive effect generated by the inclusion of CeO2. Second, the presence of CeO2 promoter accelerates the transition from CuO to Cu0 metallic phase. Furthermore, the addition of CeO2 boosts the CH4 and CO2 conversion rates by 23.65% and 24.93%, respectively. As a result, the H2 yield increases significantly when compared to the unpromoted catalyst. The study investigates the influence of process parameters, specifically the reaction temperature (700–900℃), CO2 ratio (0.2–1), and gas hourly space velocity (GHSV) (16–36 L g cat−1 hr−1), on the conversion of CH4 and CO2, as well as the H2/CO ratio. The optimization study finds that the highest conversion rates for CH4 and CO2 are 78.32% and 72.45%, respectively, when the reaction temperature is 800 °C, the CO2 ratio is 0.6, and the gas hourly space velocity (GHSV) is 26 L g cat−1 hr−1. The optimum conditions result in the highest syngas ratio of 1.77. The results of the optimization are then assessed using the mean errors. The H2/CO ratio, as well as the average errors for CH4 and CO2 conversions, are discovered to be 0.15%, 0.95%, and 0%, respectively.

Territorial Impact Assessment for Coal Sites in Transition

This article describes a part of the POTENTIALS project promoted by the Research Fund for Coal and Steel (RFCS) of the EU, which, in general, has aimed to develop business models for the reuse of former industrial and mining sites in different European regions. The goal of this project focused on the creation of so-called eco-industrial parks to enable sustainable energy production and reduce waste and pollution on coal sites in transition. A key aspect was the development of a suitable territorial impact assessment (TIA), a new and complex policy tool for the assessment of the territorial impacts of EU policies and projects on territorial cohesion. Therefore, the special TEQUILA (Territorial Efficiency, Quality and Identity Layer Assessment) approach is used to describe the TIA for this case and emphasizes its application in assessing ex ante the impacts of the transition from a coal site to an eco-industrial park. It underlines the need for a differentiated understanding of the regional characteristics and potential impacts of transition policies or projects. Furthermore, the process and results of applying the TEQUILA methodology, a multicriteria analysis, in the context of regionalized impact models has shown how important it is to select well-defined, expert-based criteria, but at the same time, to establish a system that is flexible and adaptable to the needs of political decision makers and stakeholders considering the normative weights of the criteria. This has been illustrated by some examples.

Metal-Organic Frameworks-Derived Nanocarbon Materials and Nanometal Oxides for Photocatalytic Applications.

Harnessing low-density solar energy and converting it into high-density chemical energy through photocatalysis has emerged as a promising avenue for the production of chemicals and remediation of environmental pollution, which contributes to alleviating the overreliance on fossil fuels. In recent years, metal-organic frameworks (MOFs) have gained widespread application in the field of photocatalysis due to their photostability, tunable structures, and responsiveness in the visible light range. However, most MOFs exhibit relatively low response to light, limiting their practical applications. MOFs-derived nanomaterials not only retain the inherent advantages of pristine MOFs but also show enhanced light adsorption and responsiveness. This review categorizes and summarizes MOFs-derived nanomaterials, including nanocarbons and nanometal oxides, providing representative examples for the synthetic strategies of each category. Subsequently, the recent research progress on MOFs-derived materials in photocatalytic applications are systematically introduced, specifically in the areas of photocatalytic water splitting to H2, photocatalytic CO2 reduction, and photocatalytic water treatment. The corresponding mechanisms involved in each photocatalytic reaction are elaborated in detail. Finally, the review discusses the challenges and further directions faced by MOFs-derived nanomaterials in the field of photocatalysis, highlighting their potential role in advancing sustainable energy production and environmental remediation.

Potential mechanisms of propionate degradation and methanogenesis in anaerobic digestion coupled with microbial electrolysis cell system: Importance of biocathode

Microbial electrolysis cells (MEC) have the potential for enhancing the efficiency of anaerobic digestion (AD). In this study, microbiological and metabolic pathways in the biocathode of anaerobic digestion coupled with microbial electrolysis cells system (AD-MEC) were revealed to separate bioanode. The biocathode efficiently degraded 90 % propionate within 48 h, leading to a methane production rate of 3222 mL·m-2·d-1. The protein and heme-rich cathodic biofilm enhanced redox capacity and facilitated interspecies electron transfer. Key acid-degrading bacteria, including Dechloromonas agitata, Ignavibacteriales bacterium UTCHB2, and Syntrophobacter fumaroxidans, along with functional proteins such as cytochrome c and e-pili, established mutualistic relationships with Methanothrix soehngenii. This synergy facilitated a multi-pathway metabolic process that converted acetate and CO2 into methane. The study sheds light on the intricate microbial dynamics within the biocathode, suggesting promising prospects for the scalable integration of AD-MEC and its potential in sustainable energy production.

Potential of layer excreta as a substrate for sustainable production of green energy

Potential of layer excreta as a substrate for sustainable production of green energy

Solution for Integration of Renewable Energy Power Plants into Smart Grids with Active Power Control

This article addresses the integration of renewable energy power plants into smart grids and active power control. Renewable energy sources contribute to environmentally friendly and sustainable energy production, but the fluctuations inherent in these sources pose a challenge for energy grids. The article examines various technologies that can be used to overcome this challenge and make energy grids more reliable. Smart grids aim to improve energy grids by optimizing energy production, transmission, and distribution using data analytics, automation, and communication technologies. The integration of renewable energy power plants into these smart grids offers significant advantages, including the ability to predict energy production, integrate with energy storage systems, and manage energy demand. The article also emphasizes the importance of active power control. Active power control is used to manage energy production steadily, thereby maintaining grid stability. Balancing energy fluctuations from renewable energy sources and storing excess energy when needed enhances grid stability. In conclusion, this article discusses the crucial role of integrating renewable energy power plants into smart grids and implementing active power control in the energy sector. These integration and control methods are important steps in making energy grids more sustainable, efficient, and reliable.

High-performance heterometallic photocatalysts afforded by polyoxometalate synthons for efficient H2 production

MoS2-based materials have emerged as photoelectric semiconductors characterized by a narrow band gap, high capacity for absorbing visible light, and reduced H2 adsorption energy comparable to Pt. These attributes render them appealing for application in photocatalytic hydrogen production. Despite these advantages, the widespread adoption of MoS2-based materials remains hindered by challenges associated with limited exposure to active sites and suboptimal catalytic hydrogen production efficiency. To address these issues, we have designed and synthesized a new class of highly dispersed bimetallic/trimetallic sulfide materials. This was achieved by developing polyoxometalate synthons containing Ni-Mo elements, which were subsequently reacted with thiourea and CdS. The resulting Ni3S2-MoS2 and Ni3S2-MoS2-CdS materials achieve photocatalytic hydrogen production rates of 2770 and 2873 μmol g–1h−1, respectively. Notably, the rate of 2873 μmol g–1h−1 for Ni3S2-MoS2-CdS surpassed triple (3.23 times) the performance of CdS and nearly sextuple (5.77 times) that of single MoS2. These materials outperformed the majority of MoS2-based photocatalysts. Overall, this study introduces a straightforward methodology for synthesizing bimetallic/trimetallic sulfides with enhanced photocatalytic H2 evolution performance. Our findings underscore the potential of transition metal sulfide semiconductors in the realm of photocatalysis and pave the way for the development of more sustainable energy production systems.

Photo-thermal catalysis for sustainable energy production and environmental treatment

Photo-thermal-catalysts (PTC) exceptional features and ability to concurrently solve sustainable energy requirements and environmental problems have drawn scientific interest. The photo-thermal effect is the process by which photo-thermal conversion materials transform radiant energy from light into thermal energy. The photo-thermal therapy of energy and environmental treatment faces the urgent task of developing effective photo-thermal agents to address complicated problem demands. In this study, we take a look at the fundamental principles and underlying process of photo-thermal material catalysis. In addition, this review provides a concise summary of the most up-to-date findings concerning photo-thermal catalysis materials, which have been aggressively researched for a wide-spread sustainable energy and environment treatment uses. In order to motivate the creation of a high-efficiency photo-thermal catalytic pathway, the criteria and techniques for designing photo-thermal catalysts are presented. This will make it possible for a better absorption of the whole spectrum of solar energy as well as a greater conversion of solar energy to heat. Theoretical direction is offered for the continued development of this technology, and the promise of the practical use of photo-thermal catalysis for different solar-driven interfacial photo-thermal conversion technologies is anticipated. This paper offers a unique perspective on photo-thermal catalysis focussing on the synergistic effects and suggesting a potential route for future applications.

Selection of a Green Contractor for the Implementation of a Solar Power Plant Project

This study is focused on the problem of contractor selection for the implementation of a solar power plant project to produce electricity from sustainable sources for the needs of the company Voćar. The goal of this research is to select a construction contractor to install a solar power plant using sustainability criteria. With this power plant, the company Voćar can reduce its electricity costs and contribute to the production of sustainable energy. A total of three main sustainability criteria were used, in which six auxiliary criteria were symmetrically distributed. With these criteria, six suppliers were analyzed, and expert decision making was carried out with the application of the fuzzy–rough approach. To define the weights of the criteria, the SWARA method was utilized in this study. Based on the findings of this method, the most important criteria are the ecological criteria. Using the CRADIS method, the contractors were ranked, and the results show that contractor C6 has the best results and is the first choice for implementing this project. Choosing the best supplier increases the sustainability of project implementation and the realization of the expected effects.

A Review of Emerging Revenue Models for Low-carbon Hydrogen Technologies

Adoption of Low-Carbon Hydrogen (LCH) technologies is considered promising to curtail carbon emissions in the industrial sectors and substitute high carbon-intensive fuels. However, LCH technologies are still evolving and face several technical & commercial barriers. On the commercial side, they face economic viability and financial risks and, therefore, fail to attract investments. Recently, some countries have developed policy support to incentivize LCH technologies, but their reward mechanisms and design vary widely and lack a standardized approach. The paper aims to contribute to the current knowledge by discussing the theoretical underpinning of LCH revenue models. It reviews emerging revenue models for LCH technologies in Germany, the Netherlands, and the UK. The review covers CCfD (Carbon Contract for Difference) in Germany, SDE++ (Stimulation of Sustainable Energy Production and Climate Transition) in the Netherlands, and HPBM (Hydrogen production Business Model) in the United Kingdom (UK). The review highlighted CCfD acts as simple hedging instrument against CO2 market price fluctuations without any visibility on hydrogen prices in the market. In contrast, SDE++ and HPBM are found to more comprehensive incentive schemes for LCH development.

Performance enhancement of a three-phase grid-connected PV inverter system using fractional-order integral sliding mode controls

Grid-integrated photovoltaic (PV) systems hold significant promise for sustainable energy production. However, these systems often struggle with maintaining energy quality and stability in the face of fluctuating conditions. To address these challenges, this study proposes the use of fractional-order integral sliding mode control (FO-ISMC) for grid-connected PV systems. The system comprises solar panel arrays, a DC/DC boost converter with its controller, and a three-phase inverter integrated into the utility grid. The primary goals of this study are to maximize power extraction from the PV system and to regulate system currents, thereby improving effectiveness and power quality. The proposed method is further refined using the particle swarm optimization (PSO) algorithm to fine-tune parameter settings. By optimizing the command gains of the FOI-SMC, the PSO algorithm enhances system performance and stability. Leveraging fractional-order and integral terms provides the control signal with additional degrees of freedom, enhancing system performance in the presence of internal and external disturbances. Simulation results demonstrate the effectiveness of the proposed controller compared to the classical controller, where in the case of Irradiation taking the value of 500 W/m2, the proposed strategy reduced the values of constant voltage, active power, and reactive power by percentages estimated at 88.18%, 90%, and 70%, respectively, compared to the traditional strategy. Also, the overshoot value of active power was reduced in all completed cases compared to the traditional strategy by percentages estimated at 53.57%, 66.66%, and 65%, respectively. The proposed strategy reduced the response time of reactive power in all cases compared to the traditional strategy by percentages estimated at 58.59%, 28.80%, and 75%, respectively. These ratios show the high performance of the proposed control in improving the characteristics of the studied system compared to traditional control based on PI control.

Enhancing the Startup Rate of Microbial Methanogenic Systems through the Synergy of β-lactam Antibiotics and Electrolytic Cells.

The slow startup and suboptimal efficiency of microbial carbon sequestration and methane-production systems have not been fully resolved despite their contribution to sustainable energy production and the reduction of greenhouse gas emissions. These systems often grapple with persistent hurdles, including interference from miscellaneous bacteria and the slow enrichment of methanogens. To address these issues, this paper examines the synergistic effect of coupling β-lactam antibiotics with an electrolytic cell on the methanogenic process. The results indicated that β-lactam antibiotics exhibited inhibitory effects on Campylobacteria and Alphaproteobacteria (two types of miscellaneous bacteria), reducing their relative abundance by 53.03% and 87.78%, respectively. Nevertheless, it also resulted in a decrease in hydrogenogens and hindered the CO2 reduction pathway. When coupled with an electrolytic cell, sufficient electrons were supplied for CO2 reduction to compensate for the hydrogen deficiency, effectively mitigating the side effects of antibiotics. Consequently, a substantial improvement in methane production was observed, reaching 0.57 mL·L-1·d-1, exemplifying a remarkable 6.3-fold increase over the control group. This discovery reinforces the efficiency of methanogen enrichment and enhances methane-production levels.

Improved identification of fracture total factor characteristics and cross-scale flow channels by interpreting initial production data of horizontal wells

Fracture identification after hydraulic fracturing of tight gas reservoirs is crucial to fracturing evaluation, productivity analysis, and production plan. Owing to fracture branching, bending, extending, and reversing in reservoirs, a simplified straight fracture cannot fully describe fracture characteristics. The novelty of this study is that the coupling mechanism between the complex fracture network characteristics and well production performances is figured out, thus achieving the identification of fracture morphology in fractured reservoirs. In this study, a combined model including Laplace transform, boundary element method, Stehfest numerical inversion, and fractal theory presents transient well performances. The key contributions to productivities at different production stages are dynamically identified via a sensitivity analysis. The results clearly indicate that the fracture total length is the key factor determining productivities due to no fracture interference at initial production stage. Furthermore, the logarithm of productivity linearly depends on the logarithm of production time and the productivity contribution rate equals the ratio of fracture length to total length. Thus, an updated inversion method is proposed by interpreting initial production data based on a tree-shaped fracture network associated with fracture total factor and cross-scale characteristics. The inversion results well match with their targets, with an error of no more than 5 %, ensuring the accuracy and validity of the proposed method. This innovative approach with low requirements on field data is convenient to yield an accurate prediction of fracture morphology, thereby providing a feasible strategy for promoting sustainable production of clean energy in unconventional gas reservoirs.

Developing a hybridized thermodynamic and data-driven model for catalytic supercritical water gasification of biomass for hydrogen production

Supercritical water gasification (SCWG) of biomass offers a promising pathway for sustainable energy production. This study presents a novel approach that combines an artificial intelligence (AI) technique with the Gibbs minimization (GM) method to enhance the GM approach by involving the catalyst effect on the gasified yield. The proposed strategy incorporates a modified Gibbs energy calculation, incorporating a delta term that quantifies the influence of the catalyst’s properties on the Gibbs free energy. The delta term is determined using experimental data, including characteristics of biomass and the employed catalysts. An artificial neural network (ANN) model is developed to predict the delta value and is integrated with the GM method to improve the estimation of gasified product yields in the presence of a catalyst. The ANN model establishes correlations between the catalyst specifications such as pore volume, specific surface area, and pore diameter, and delta value. The trained model can predict the delta term, allowing the catalyst’s role to be considered within the GM technique. This integration addresses a limitation of the conventional thermodynamic model, which typically ignores the catalyst’s influence. The developed ANN model exhibits high accuracy, with an R2 value of 0.92 and a mean squared error (MSE) of 0.042. The hybridized GM approach substantially improves the hydrogen yield prediction compared to the basic model, enhancing (reducing) the MSE and mean absolute error by 98% and 93%, respectively. Furthermore, sensitivity analysis reveals that increasing temperature and reducing pressure contribute to improved hydrogen production. Additionally, lower biomass concentrations are shown to be beneficial for enhancing the hydrogen yield.

Analyzing the Impact of Pressure Ratio Variation on Gas Power Plant Performance at Takoradi Thermal Power Station

This study investigates the influence of pressure ratio variation on the performance of a gas turbine plant located at Aboadze, Ghana. The operational data including daily hourly measurements of pressure ratio, power output, ambient temperature, and gas fuel flow rate were collected during field visits conducted in February and March 2021. The thermal efficiency was computed using a validated equation, and data were analyzed using MAT LAB. The study reveals significant temporal fluctuations in the pressure ratio, power output, and thermal efficiency, highlighting the dynamic nature of the gas turbine plant's performance during daily operation. It was also observed that as the pressure ratio increases, the power output and thermal efficiency also increases and vice versa. The average highest and lowest pressure ratio recorded between February and March 2021 were 10.40 and 9.84 respectively, with corresponding average highest and lowest power output of 109 MW and 102 MW respectively. The result also showed an average daily variation in pressure ratio of 0.35 with corresponding power output difference of 5.25 MW. The finding showed that averagely, the lowest thermal efficiency and the highest thermal efficiency were 27.00 % and 28.00 % respectively.
 This study is of crucial importance for optimizing power generation efficiency and ensuring sustainable energy production. By studying a specific gas turbine plant located in Aboadze, Ghana, this research contributes valuable insights into the operational characteristics of such plants in the region.

Development of a modified gas turbine-based sustainable power generation and water treatment system; Economical/environmental considerations and data-driven optimization

Developing environmentally friendly solutions that optimize existing power plants while considering economic factors is crucial for ensuring sustainable energy production and mitigating environmental impact. This study promotes a gas turbine-based power plant design that prioritizes environmental concerns and underscores its versatility. The proposed setup is composed of various components, including a gas turbine, a Rankine cycle (RC), an organic Rankine cycle (ORC), a reverse osmosis (RO) desalination unit, a proton exchange membrane electrolyzer (PEME), and a hydrogen blending module. This system engenders the simultaneous generation of hydrogen, electrical power, and desalinated water. Additionally, the direct utilization of produced hydrogen in the proposed system offers improved technical performance and serves as an effective means to mitigate greenhouse gas emissions. A resilient programming code is formulated to systematically evaluate the system through the lenses of techno-economic and environmental considerations. Incorporating innovative modifications into the existing system resulted in an 8% cost reduction, a 1.2% decrease in carbon dioxide emissions, and a 5% enhancement in exergy efficiency. To attain optimal performance of the system, a data-driven and machine learning methodology is employed, wherein two distinct optimization scenarios are used to define the conditions that yield the utmost system performance. In the first scenario, the optimal values for cost, exergy efficiency, and normalized CO2 emissions have been computed as 39%, 5963 $/h, and 367.4 kg/MWh, respectively. In the subsequent scenario, the optimized system demonstrates the capability to generate a fresh water flow rate of 840.4 kg/s. Concurrently, the cost rate for the system equates to 7054.5 $/h.