Sustainable Energy Production Research Articles

Combining solar panels with plants for sustainable energy and food production: state of the art

The need for alternative energy sources becomes extensive because of the escalating cost of fossil fuels. The goal of this paper is to examine the effectiveness of combining photovoltaics and agriculture for better yield. Photovoltaic (PV) solar plants will compete with farms for available land. In this study, the methodologies are discussed how it is possible to maximize land utilization by placing solar arrays and food crops on the same plot of land. The term is proposed "agrivoltaic system" to describe this setup. Conventional solutions (discrimination of agricultural and energy extracting) were compared to two agrivoltaic schemes with varying density of PV arrays using land equivalent ratios. We utilized a crop model to simulate the amount of sunlight reaching the crop from an array of solar panels and to speculate on the yield reduction that would result from the partial shading. These early findings suggest that agrivoltaic systems may be highly effective; the two densities of PV panels were anticipated to boost worldwide land production by 73%. One possible explanation for the success of these hybrid systems is the presence of facilitation mechanisms analogous to those seen in agroforestry. At the end it is suggested that in places where arable land is rare, new solar plants may find it beneficial to produce both power and food.

Efficient Low-Temperature Nutrient Removal from Agricultural Digestate Using Microalgae

Humanity is facing an energy crisis triggered by the depletion of fossil fuels, rapid industrialization, and the growthof the global population. These trendsput an emphasis on searching for alternative energy sources. Additionally, the rising concentration of carbon dioxide in the atmosphere is driving climate change, which poses serious threats. In this scenario, microalgae emerge as a promising solution for both sustainable energy production and CO2 sequestration. Digestate, a nutrient-rich by-product of anaerobic digestion, is considered a cost-effective nutrient source for microalgae cultivation. Utilizing digestate not only enhances the sustainability and economic feasibility of microalgal biofuels but also offers a method for wastewater treatment. Nevertheless, the application of digestate is limited by its high optical density and substantialamount of total solids.In this study, several pretreatment methods were tested to increase the feasibility of digestate application for microalgae cultivation. Our findings show that various centrifugation methods and vacuum filtration decrease the content of total solids but are not effective in reducing optical density. Although the use of microalgae in treating various wastewaters has shown promising outcomes, the effectiveness of nutrient removal at low temperatures remainslargely unexplored.To fill this gap, green microalga Chlorella sorokiniana was cultivated in pretreated diluted liquid digestate in dynamic springtime weather conditions in a covered open race-way pond integrated into a biogas plant.During the cultivation, high solar irradiance and low temperatures were recorded resulting in suboptimal conditions for C. sorokinianagrowth. Although low productivity of C. sorokiniana was detected, the nutrient removal efficiency was high. C. sorokiniana could efficiently remove 83% of nitrogen and 85% of phosphorus showing very promising results of the use of microalgae for wastewater treatment in high latitude regions.

Enhancing sustainable energy production through biomass gasification gas technology: a review

This proposed research investigates the sustainable and innovative use of biomass gasification for generating electricity. Biomass gasification is a versatile and eco-friendly technology that converts organic materials, such as agricultural residues, forestry waste, and even municipal solid waste, into a valuable source of clean energy. This research delves into the various aspects of this technology, including its processes, efficiency, environmental impact, and potential applications in power generation. Biomass gasification gas, often referred to as syngas, presents a promising avenue for addressing the rising energy demand while lowering greenhouse gas emissions and preventing climate change. This research seeks to offer a thorough insight into the principles and practices behind biomass gasification, highlighting its role in the transition towards a sustainable and renewable energy future. The research will investigate the technical and economic feasibility of utilizing biomass gasification gas for electricity generation, examining the benefits, challenges, and opportunities associated with this alternative energy source. By addressing critical issues such as feedstock availability, gasifier technology, gas cleaning processes, and power plant integration, this study seeks to offer valuable insights into the potential of biomass gasification gas as a clean and renewable energy solution.

AUTOMATIC OPERATION OF ON-GRID SOLAR SYSTEM WITH PROTECTION SCHEME

The on-grid solar energy system is becoming a pivotal component of modern electrical grids due to its potential for sustainable energy production and reduced environmental impact. The integration of automatic operation and protection schemes is essential to ensure optimal performance, reliability, and safety of these systems. This research paper delves into the development and implementation of an automatic operation strategy for an on-grid solar system, incorporating a robust protection scheme to mitigate common operational risks. We explore various components and design considerations, detailing the control strategies employed to achieve seamless system function and high performance. A thorough analysis of the data collected from the implemented system highlights the efficacy and reliability of the proposed method. Additionally, the research compares the findings with existing studies to position the results within the broader academic dialogue. Our findings show significant improvements in both the operational efficiency and protection capabilities of the solar system, thus providing valuable insights for future advancements in renewable energy integration. The developed methodologies could lead to enhanced system durability and energy yield, thereby promoting the broader adoption of renewable energy solutions. As we mentioned in Title, we are going to make the Operation of Solar System Automatic with Protection Scheme. This is very beneficial as point of view to on-Grid Solar Systems which is a Need of Today’s World.

Harnessing the energy potential of rosehip wastes towards sustainable energy supply

Using renewable energy technologies comes to the forefront for sustainable energy, economy, and environmental management. In regions with high agricultural production, it is becoming increasingly important to contribute to sustainable energy production by using agricultural wastes as biomass. For this purpose, the evaluation of the energy potential and catalytic pyrolysis of rosehip seed (RS) and rosehip pomace (RP), which are considered the main wastes of rosehip, were investigated to obtain improved bio-oil. While C10+ hydrocarbons of alkane and alkene origin were mostly found in the composition of bio-oil, the highest ratio belongs to 50CL50RP650. Especially when only RS and RP were present, both the temperature of 650°C and the presence of catalyst were more effective in obtaining aliphatics. In the use of the blend, one of these parameters was sufficient and the volatile matter increased and fixed carbon decreased, especially as the RP ratio (70%) in the blend increased. The heating value (18.5–19 MJ/kg) and volatile matter (63–66%) of the wastes were high, while ash (0%) and moisture (2%-3%) contents were low, which is important in terms of energy potential. In the combustion profiles, the Tmax was generally higher for the blends.

Hydroxyl-Bonded Co Single Atom Site on Boroncarbonitride Surface Realizes Non-sacrificial H2O2 Synthesis in the Near-Infrared Region.

Photocatalytic synthesis of hydrogen peroxide (H2O2) from O2 and H2O under near-infrared light is a sustainable renewable energy production strategy, but challenging reaction. The bottleneck of this reaction lies in the regulation of O2 reduction path by photocatalyst. Herein, we construct the center of the one-step two-electron reduction (OSR) pathway of O2 for H2O2 evolution via the formation of the hydroxyl-bonded Co single-atom sites on boroncarbonitride surface (BCN-OH2/Co1). Our experimental and theoretical prediction results confirm that the hydroxyl group on the surface and the electronic band structure of BCN-OH2/Co1 are the key factor in regulating the O2 reduction pathway. In addition, the hydroxyl-bonded Co single-atom sites can further enrich O2 molecules with more electrons, which can avoid the one-electron reduction of O2 to •O2 -, thus promoting the direct two-electron activation hydrogenation of O2. Consequently, BCN-OH2/Co1 exhibited a high H2O2 evolution apparent quantum efficiency of 0.8% at 850nm, better than most of the previously reported photocatalysts. This study reveals an important reaction pathway for the generation of H2O2, emphasizing that precise control of the active site structure of the photocatalyst is essential for achieving efficient conversion of solar-to-chemical. This article is protected by copyright. All rights reserved.

Monitoring through AI Based Remote Access Vehicle in Hydro Power Plant

The development of hydroelectric power is essential to the production of sustainable energy. Continuous monitoring and maintenance are necessary to guarantee the safe and effective functioning of hydroelectric plants. A revolutionary method for improving the security, effectiveness, and monitoring capacities of hydroelectric power plants is presented in the project "Monitoring through AI-Based Remote Access Vehicle in Hydro Power Plant."This creative project uses cutting-edge technologies, such as Bluetooth connectivity, artificial intelligence (AI), Raspberry Pi, and sensor systems, to develop a remotely controlled car that is specifically designed to meet the demands of hydroelectric power plant conditions. Real-time object detection and obstacle avoidance are made possible by this configuration, guaranteeing safe passage across the complex industrial infrastructure.Incorporating a temperature sensor also makes it easier to identify fire situations early on, while a water-detecting sensor protects against water leaks. By utilizing AI algorithms for object recognition, vehicles can detect and react to impediments in a proactive manner, hence decreasing the likelihood of accidents. As sentinels, the temperature and water leakage sensors keep an eye on things constantly and send out alarms right once if anything seems out of the ordinary. Reduced reliance on in-person inspections due to remote monitoring capabilities results in lower costs and more dependability. To sum up, this initiative tackles important issues pertaining to hydro power plant maintenance, efficiency, and safety

Wind energy resource assessment and wind turbine selection analysis for sustainable energy production

The objective of this study is to perform an analysis to determine the most suitable type of wind turbine that can be installed at a specific location for electricity generation, using annual measurements of wind characteristics and meteorological parameters. Wind potential analysis has shown that the analyzed location is suitable for the development of a wind farm. The analysis was carried out for six different types of wind turbines, with a power ranging from 1.5 to 3.0 MW and a hub height set at 80 m. Wind power potential was assessed using the Weibull analysis. The values of the scale coefficient c were determined, and a large monthly variation was observed, with values ranging from 1.92 to 8.36 m/s and an annual value of 4.95 m/s. Monthly values for the shape coefficient k varied between 0.86 and 1.53, with an annual value of 1.07. Additionally, the capacity factor of the turbines was determined, ranging from 17.75 to 22.22%. The Vestas turbine, with a nominal power of 2 MW and a capacity factor of 22.22%, proved to be the most efficient wind turbine for the specific conditions of the location. The quantity of greenhouse gas emissions that will be reduced if this type of turbine is implemented was also calculated, considering the average CO2 emission intensity factor (kg CO2/kWh) of the national electricity system.

Simulation and experimental study of grid-connected photovoltaic power plants in a hot desert climate with fixed and dual-axis tracking

ABSTRACT This paper presents a comprehensive investigation into the performance of grid-connected photovoltaic (PV) power plants situated in a hot desert climate. The study employs a combination of simulation models and experimental data to assess the impact of two tracking systems – fixed and dual-axis – on the overall efficiency and energy yield of the PV installations. Through detailed simulations, we analyze the dynamic behavior of the PV systems under varying solar irradiance and the atmospheric conditions typical of hot desert environments. The dual-axis tracking system is compared against the conventional fixed-mount system to evaluate its effectiveness in maximizing energy production and improving the overall efficiency of the PV power plants. Experimental data collected from an actual grid-connected PV facility in a hot desert region is incorporated to validate the simulation results and enhance the accuracy of the study. The observed performance metrics include energy output, system reliability, and the impact of environmental factors on long-term sustainability. In general, in all weather conditions, solar tracking provides better yields than a fixed solar module, generating about 32% and 12% more energy in sunny and overcast weather conditions, respectively. Under sunny weather, the two-axis sun tracking system and a fixed tilt angle produce 333.228 kWh and 247.56 kWh of energy, respectively. The energy yield generated on a partly cloudy day by a two-axis sun tracking system and a fixed tilt angle PV system is 281.496 kWh and 257.856 kWh, respectively. In addition, the highest electricity gain for two-axis solar trackers versus fixed PV plants was found to be 34.6%, and the lowest value was found to be 9.16%. The experimental analysis shows that the efficiency of the polycrystalline PV module is 12% and 14% on sunny days and cloudy days, respectively. The comparison between fixed and dual-axis tracking systems contributes to the optimization of PV installations, enabling more informed decisions for sustainable energy production in regions characterized by high temperatures and intense solar radiation. To support the expanding applications of grid-tied PV systems with a sun tracker in the same or comparable location and climate conditions (Saharan environment), these studies have the practical utility of advising and offering helpful feedback to engineers, system designers, contractors, and investors.

Vacancy modulation on NiTi-layered double hydroxides towards highly selective CO2 photoreduction

Photoreduction of carbon dioxide (CO2) is a promising way to achieve sustainable energy production and alleviate environmental problems. Herein, we report a NiTi-layered double hydroxides photocatalyst with bivalent and trivalent metal vacancies (denoted as NiVTiV-LDHs) via alkali-etching amphoteric metal cations (Zn and Al) from NiZnTiAl-LDHs precursor. The NiVTiV-LDHs attains a CH4 selectivity of 94% with a production rate of 2398 µmol g−1 h−1, which is preponderant to the state-of-the-art photocatalysts. Operando X-ray absorption fine structure (XAFS) and Fourier-transform infrared spectroscopy (FT-IR) characterizations combined with density functional theory (DFT) calculations corroborate that Ni2+δ−O(H)−Ti3+ζ sites modulated by adjacent vacancies exhibits a declined 3d-orbital occupancy, accelerating the charge transfer for boosting CH4 formation. Moreover, the unique adsorption configuration (Ni2+δ/Ti3+ζ−CO) not only stabilizes the key intermediate *CO for further protonation, but also induces a decreased energy barrier of the rate-determining step (hydrogenation of *OCH3), accounting for the robust photocatalytic CO2 reduction towards CH4.

Unveiling the Low-Lying Spin States of [Fe3S4] Clusters via the Extended Broken-Symmetry Method.

Photosynthetic water splitting, when synergized with hydrogen production catalyzed by hydrogenases, emerges as a promising avenue for clean and renewable energy. However, theoretical calculations have faced challenges in elucidating the low-lying spin states of iron-sulfur clusters, which are integral components of hydrogenases. To address this challenge, we employ the Extended Broken-Symmetry method for the computation of the cubane-[Fe3S4] cluster within the [FeNi] hydrogenase enzyme. This approach rectifies the error caused by spin contamination, allowing us to obtain the magnetic exchange coupling constant and the energy level of the low-lying state. We find that the Extended Broken-Symmetry method provides more accurate results for differences in bond length and the magnetic coupling constant. This accuracy assists in reconstructing the low-spin ground state force and determining the geometric structure of the ground state. By utilizing the Extended Broken-Symmetry method, we further highlight the significance of the geometric arrangement of metal centers in the cluster's properties and gain deeper insights into the magnetic properties of transition metal iron-sulfur clusters at the reaction centers of hydrogenases. This research illuminates the untapped potential of hydrogenases and their promising role in the future of photosynthesis and sustainable energy production.

O‐2p Hybridization Enhanced Transformation of Active γ‐NiOOH by Chromium Doping for Efficient Urea Oxidation Reaction

AbstractThe electrooxidation of urea holds great potential for converting urea from wastewater into hydrogen, contributing to environmental protection and sustainable energy production. This necessitates the development of highly efficient and stable catalysts for the urea oxidation reaction (UOR). In this study, a NiCoCr‐LDH/NF (nickel‐cobalt‐chromium layered double hydroxide/nickel foam) electrode is successfully synthesized via a simple hydrothermal method, demonstrating excellent electrocatalytic performance with a low work potential of 1.38 V at a high current density of 100 mA cm−2. In situ, Raman spectra analysis revealed that the incorporation of chromium (Cr) facilitated the generation of active γ‐NiOOH species and catalyst reconstruction. Density functional theory (DFT) simulations confirmed that the lower formation energy of γ‐NiOOH is due to the weakened interaction of O─H bonds because of a narrow energy range of hybridization between O‐2pz orbitals and H‐1s orbitals. The introduction of Cr also improved the adsorption energy of urea molecules and its intermediates, thereby enhancing the overall activity of UOR. With its excellent electrocatalytic performance, unique electronic states, and coordination structures, the NiCoCr‐LDH/NF electrode showcases great potential for practical applications in the field of energy catalysis.

Photocatalytic degradation of antibiotics and antimicrobial and anticancer activities of two-dimensional ZnO nanosheets

Active pharmaceutical ingredients have emerged as an environmentally undesirable element because of their widespread exploitation and consequent pollution, which has deleterious effects on living things. In the pursuit of sustainable environmental remediation, biomedical applications, and energy production, there has been a significant focus on two-dimensional materials (2D materials) owing to their unique electrical, optical, and structural properties. Herein, we have synthesized 2D zinc oxide nanosheets (ZnO NSs) using a facile and practicable hydrothermal method and characterized them thoroughly using spectroscopic and microscopic techniques. The 2D nanosheets are used as an efficient photocatalyst for antibiotic (herein, end-user ciprofloxacin (CIP) was used as a model antibiotic) degradation under sunlight. It is observed that ZnO NSs photodegrade ~ 90% of CIP within two hours of sunlight illumination. The molecular mechanism of CIP degradation is proposed based on ex-situ IR analysis. Moreover, the 2D ZNO NSs are used as an antimicrobial agent and exhibit antibacterial qualities against a range of bacterial species, including Escherichia coli, Staphylococcus aureus, and MIC of the bacteria are found to be 5 μg/l and 10 μg/l, respectively. Despite having the biocompatible nature of ZnO, as-synthesized nanosheets have also shown cytotoxicity against two types of cancer cells, i.e. A549 and A375. Thus, ZnO nanosheets showed a nontoxic nature, which can be exploited as promising alternatives in different biomedical applications.

Technological innovations and optimized work methods in subsea maintenance and production

Subsea maintenance and production represent critical aspects of offshore operations, vital for sustaining energy production and ensuring operational efficiency. However, these endeavors face numerous challenges, including the complexities of deepwater environments, harsh weather conditions, and the high costs associated with traditional maintenance methods. To address these challenges, this paper explores the integration of technological innovations and optimized work methods in subsea operations. Technological innovations play a pivotal role in revolutionizing subsea maintenance and production. Remote monitoring and control systems enable real-time data collection and decision-making, enhancing operational visibility and efficiency. Autonomous underwater vehicles (AUVs) offer the capability to conduct inspections and repairs in remote and hazardous environments, reducing human intervention and associated risks. Robotics and automation further streamline maintenance tasks, improving accuracy and reducing downtime. Advanced materials and coatings enhance equipment durability and corrosion resistance, prolonging asset lifecycles and reducing maintenance requirements. In parallel, optimized work methods offer strategic approaches to enhance subsea operations' effectiveness. Predictive maintenance strategies leverage data analytics and machine learning to anticipate equipment failures, enabling proactive interventions and minimizing downtime. Condition-based monitoring facilitates real-time assessment of asset health, enabling timely maintenance interventions and cost savings. Integrated asset management systems provide holistic insights into asset performance and facilitate informed decision-making. Lean operations and continuous improvement methodologies further optimize workflows, driving operational excellence and cost efficiency. Through case studies and industry examples, this paper highlights the successful implementation of technological innovations and optimized work methods in subsea maintenance and production. Furthermore, it explores future trends, regulatory considerations, and the importance of industry collaborations in shaping the future of subsea operations. Ultimately, the integration of these approaches offers a pathway towards enhanced operational efficiency, reduced costs, and sustainable subsea operations. Keywords: Technological Innovations, Optimized Work Methods, Subsea Maintenance and Production.

Technical analysis of exploiting untapped wind power for sustainable hydrogen energy production

Technical analysis of exploiting untapped wind power for sustainable hydrogen energy production

Unlocking the potential of depleted dry batteries: A dual-purpose approach for waste mitigation and sustainable energy production

Electronic-waste (e-waste) poses a serious environmental challenge due to the increasing consumption and disposal of electronic devices. In the present work a novel method is proposed to repurpose e-waste and bio-waste into a single-chamber and mediator-less microbial fuel cells using dead, non-rechargeable D-type dry batteries. The carbonaceous material inside the dry batteries was replaced with kitchen waste sludge, which served as the substrate. The outer zinc casing was also reused as the anode and the carbon rod as the cathode. Treating the kitchen waste sludge with dilute nitric acid improved the performance of the microbial fuel cells by enhancing the biodegradability and conductivity of the substrate. The untreated microbial fuel cells produced a maximum power density of 15.0 mW/kg at a maximum current density of 50.0 mA/kg, while the treated microbial fuel cells achieved 67.0 mW/kg at 178.0 mA/kg. The main mechanism behind the working of the device is the combined action of galvanic and microbial processes, which synergistically generate electricity from e-waste and bio-waste. Moreover, when four treated microbial fuel cells were connected in series, a high open circuit voltage of 3.3 V was achieved. These microbial fuel cells stand out as eco-conscious and lightweight alternatives to conventional dry batteries, presenting an environmentally sustainable solution for waste management and clean energy production.

Who brings emissions home? Comparing female and male breadwinner households by matching techniques

This paper tests the hypothesis that female and male breadwinner household present significant differences in the greenhouse gases (GHG) emissions patterns induced by consumption. We investigate this issue by studying a sample of consumption basket of Spanish households for 2008, 2014, and 2018, linking consumption levels with emissions by means of input-output analysis. Once a vector of GHG emissions have been calculated for each household sampled, we apply the Propensity Score Matching estimator to analyze the mean difference between households with female and male breadwinners, finding a significant negative effect of having female breadwinner households on the GHG emissions patterns derived by household energy consumption, mainly due to the larger use of private transport by male breadwinner households. These results contribute to the growing demand for studies linking environment and gender and to expose the role of women in sustainable energy production and consumption. Therefore, policies that encourage the inclusion of women in different economic activities are also likely to have climate related benefits.

Heavily vanadium-doped LiFePO4 olivine as electrode material for Li-ion aqueous rechargeable batteries

Since LiFePO4 batteries play a major role in the transition to safe, more affordable and sustainable energy production, numerous strategies have been applied to modify LFP cathode, with the aim of improving its electrochemistry. In this contribution, a highly vanadium-doped LiFe0.9V0.1PO4/C composite (LFP/C-10V) is synthesized using the glycine combustion method and characterized by x-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), Thermogravimetry Differential Thermal Analysis (TGDTA) and Cyclic Voltammetry (CV). It is shown that 10wt.% of vanadium can substitute Fe positions, thus decreasing unit cell volume, which is followed by generation of Li3V2PO4 traces, as detected by CV. High vanadium doping does not change the carbon content in the composite (≈13 wt%) but improves its electronic conductivity and electrochemical performance in both aqueous and organic electrolytes. The reversibility and current response are increasing following the trend: LFP/C, LFP/C -3mol%V, LFP/C - 5 mol % and LFP/C-10 mol %. The best specific capacity is obtained for the most highly doped olivine, which exhibits a reversible process at 1 mV s−1 in an aqueous electrolyte, thus showing a peak-to-peak distance of 56 mV. The high capacity of LFPC-10V is measured in both LiNO3 and NaNO3 electrolytes amounting to around 100 mAh g−1 at 20 mV s−1. Still, the material is only stable in LiNO3 electrolyte, making it more suitable for Li than Na-ion aqueous rechargeable batteries.

Waste-to-energy poly-generation scheme for hydrogen/freshwater/power/oxygen/heating capacity production; optimized by regression machine learning algorithms

Utilization of machine learning techniques in the analysis and enhancement of poly-generation energy systems improves their efficiency and sustainability. Also, waste-to-energy systems propose a hopeful answer for both waste management and sustainable energy and water production. The production of hydrogen and freshwater through these systems not only provides valuable resources but also contributes to environmental sustainability. This research utilizes artificial intelligence's machine learning algorithms to examine and enhance a waste-to-energy system within a poly-generation energy system that generates hydrogen, freshwater, power, oxygen, and hot air. The integrated system consists of a waste combustion chamber, a proton exchange membrane electrolyzer, a supercritical carbon dioxide Brayton cycle, and a desalination system. Based on the findings, the machine learning algorithms exhibiting R-squared values exceeding 99% are considered strong fits. Additionally, all algorithms with high predicted R-squared values have the capability to accurately forecast new data using the provided training data. The emissions of 669.7 g/kWh and an efficiency of 69.62% are achieved when the pressure ratio is 10.73 and the temperature is 863.6 °C under optimal conditions. The accuracy and validity of the machine learning techniques are further confirmed by the strong agreement with thermodynamic modeling.

Design and multi-criteria optimization and financial assessment of an innovative combined power plant and desalination process

Geothermal power generation programs are crucial due to their long-term sustainability and environmentally friendly characteristics, particularly for potential energy-based applications in the future. Innovative designs can yield improve efficien by mitigating irreversibility, resulting in enhanced power production. Hence, this study investigates an innovative cascade thermal design model that employs geothermal resources to enhance the efficiency and output of low-temperature power generation systems, specifically through the integration of organic flash and organic Rankine cycles. Additionally, this model introduces a novel cogeneration approach by incorporating a desalination unit based on humidification-dehumidification processes, aiming to concurrently produce electricity and fresh water. Employing a combination of thermodynamic analysis and financial assessment, the system's performance was simulated and optimized in MATLAB, using the Multi-Objective Particle Swarm Optimization (MOPSO) method. A sensitivity analysis preceded the optimization, leading to the development of three distinct optimization scenarios focused on balancing power and freshwater production, maximizing exergetic efficiency and net present value, and optimizing fixed capital investment for maximum financial viability. The results highlight the second scenario as particularly effective, achieving a power generation of 254.3 kW, an exergetic efficiency of 44.84 %, and a net present value of $405,099. Conversely, the third scenario offers the best balance between freshwater production capacity (0.504 kg/s), fixed capital investment ($820,822), and a payback period of 7.12 years. This research demonstrates the potential of integrating advanced thermal models with geothermal resources for sustainable and efficient energy and freshwater production, marking a significant step forward in the development of eco-friendly cogeneration systems.