Large‐scale deployment of distributed photovoltaic (PV) systems brings challenges such as voltage violation and increased active power loss. Due to its high efficiency and low cost, the centralized energy storage system (CESS) has become a key technology to optimize distribution network operation. This paper proposes a multiobjective optimization model for CESS configuration in typical scenarios of Chinese rural residential users and enterprises, which considers voltage deviation, active power loss, and comprehensive costs. The analytic hierarchy process (AHP) is used to assign differentiated weights to different scenarios, transforming the multiobjective problem into a single‐objective problem. The particle swarm optimization (PSO) algorithm is then used to solve the problem, finally achieving collaborative optimization of the access location and capacity configuration of CESS. The validity of the proposed optimization model is confirmed by case studies in typical scenarios. In the rural residential scenario, CESS controls the voltage deviation within ±5%, with costs reduced by more than 50% compared to distributed energy storage systems (DESSs). In the enterprise scenario, CESS eliminates the voltage overlimit and reduces the cost by 53.95%. The proposed optimal configuration method for CESS effectively improves the voltage stability and economic performance, providing a low‐cost energy storage solution for the large‐scale application of distributed PV.
The uncontrolled discharge of synthetic dyes into aquatic systems poses a serious environmental and public health concern due to their toxicity, persistence, and resistance to conventional treatment methods. Safranin-O (SO), a widely used cationic dye in textile, cosmetic, and medical industries, is particularly problematic because of its chemical stability and adverse biological effects. In this work, a polyaniline-modified carbon nanotubes/zinc oxide (CNTs/ZnO/PANI) ternary nanocomposite was successfully synthesized via an in-situ free-radical polymerization method and investigated as an efficient photocatalyst under the applied bias for the degradation of SO dye in aqueous solutions. Structural, morphological, and spectroscopic characterizations confirmed the effective integration of zinc oxide nanoparticles within the conductive carbon nanotubes and polyaniline matrix, resulting in improved surface area, reduced particle agglomeration, enhanced electrical conductivity, and extended light absorption. The photocatalytic performance of the synthesized nanocomposite was systematically evaluated under different operational parameters, including irradiation time, applied voltage, initial dye concentration, catalyst dosage, solution pH, and temperature. The results demonstrated that the combined application of light irradiation and external bias significantly enhanced dye degradation compared to photocatalysis, electrocatalysis, or catalytic treatment alone, highlighting a strong synergistic effect between photo-excitation and electric-field-assisted charge separation. Under identical experimental conditions, among the three nanocomposites, CNTs/ZnO/PANI exhibited the highest performance in dye degradation, that is, degraded 91% of 40 ppm SO dye. Kinetic analysis revealed that the degradation process best fit to pseudosecond-order kinetic model (R2~1), indicating a surface-controlled reaction mechanism dominated by chemisorption and reactive oxygen species generation. Thermodynamic investigations showed that the degradation reaction was endothermic and entropy-driven, with negative Gibbs free energy values at elevated temperatures confirming the spontaneous nature of the process. In addition, the nanocomposite exhibited good structural stability and retained substantial catalytic activity over multiple reuse cycles. Overall, this study demonstrates that the CNTs/ZnO/PANI nanocomposite is a highly efficient, stable, and recyclable photocatalyst under applied voltage, offering significant potential for sustainable wastewater treatment and environmental remediation applications.
Though solar power generation systems (SPGSs) are integral to the modern-day renewable energy infrastructure, they are strongly influenced by fluctuations in solar irradiance, temperature, and energy storage conditions. This study proposes a comparative optimization framework for better control performance of a battery integrated solar photovoltaic system with fractional-order PID (FOPID) controllers. The proposed system is developed in three major phases. First, the PV panels are modeled, considering the irradiance, temperature and time-varying environmental inputs. Second, the battery storage subsystem is integrated by modeling its electrical and thermal properties so that the energy flow between the PV panels, battery bank and load can be investigated under varying PV module operating conditions. Third, the two optimization algorithms, black hole optimization (BHO) and Harris Hawks Optimization (HHO) are optimized separately to adjust the five parameters of FOPID (Kp, Ki, Kd, λ, μ) using the nature-inspired algorithms. The above optimized controllers are implemented and tested in MATLAB/Simulink, with the same objective function and operating conditions to provide a fair comparison. The results indicate that the BHO-tuned controller results in inferior tracking performance and inferior convergence behavior for the investigated PV-battery system when compared with the controller tuned by using HHO. The proposed method enhances the voltage regulation, reduces the output fluctuation and improves the dynamic stability of the solar energy system in the changing environment. Finally, the study demonstrates that properly tuned fractional-order control combined with nature-inspired optimization can provide an effective solution for improving the performance and reliability of battery-integrated solar PV systems.
The article examines the energetic processes of the light-dependent phase of photosynthesis. It explores the nature of energy and charge transport in molecules containing isoprene and isoprenyl bonds. A mechanism is proposed for the operation of a quantum current generator—Mn4O5Ca(Н2О)4 proceeding through the formation of electron–hole pairs. The study explains the mechanisms of hydrogen peroxide formation in PS-II and its role as an intermediate energy carrier in the light phase of photosynthesis. The role and operating principles of P680 (PS-II) and P700 (PS-I) are described as natural photoelectrolyzers that function to remove excess electrons from chloroplasts. Furthermore, the operation of the proton molecular pump (Q-cycle) and the photosupercapacitor the В6f complex is explained. Within the electron transport chain, molecular electronic systems that monitor and control light-dependent redox reactions.
The analysis of parabolic trough solar collectors (PTSCs), aimed at achieving the highest thermal efficiency and reducing construction and maintenance costs, has garnered the attention of many researchers. In this study, the thermal and dynamic behavior of a PTSC has been analytically examined. The governing energy equations inside the receiver tube, including the equations of conductive, convective, and radiative energy exchange between the absorber tube, the glass walls, and the surrounding fluid flows, were formulated and balanced using the resistance method. A code in FORTRAN was written to solve the system of equations. This study investigated a new geometry involving two parallel fluid flows with counterflow and compared it with co-flow and conventional single-flow models. The effects of the fluid flow rate ratio on heat transfer from the absorber tube to the two fluid flows and thermal efficiency were thoroughly examined. The results indicated that the solar receiver with two counterflow streams showed lower thermal efficiency (about 30%) than the co-flow receiver under equal conditions (equal inlet temperatures and flow rates of both fluids). This drop in efficiency is attributed to the early and concentrated heat uptake by the outer fluid in counterflow, which reduces the effective temperature gradient for the inner fluid along the length of the absorber and increases radiative and convective losses due to higher average outer fluid temperatures. However, when the flow rate ratio of the external to the internal fluid was increased, the thermal efficiency increased by up to 50%.
PVM and PV/TM are currently common for greener energy generation, but the operating temperatures can greatly influence their performance. Hence, thermal management is crucial for improving performance and reliability. Our review details a detailed study on fin-based cooling techniques utilised for PVM and PV/TM. The method used for collecting the data was a systematic literature review, which aggregated classifications of relevant articles found in large scientific databases, concentrating on experimental and numerical papers published from 2005 to 2025. Among the studies included in the review, fin cooling, fin-integrated phase change material (PCM), fin-based thermoelectric module (TEM) hybrids and fin-enhanced PV/TM configurations were grouped. The results suggest that fin cooling is effective for reducing module temperature, whereas hybrid strategies, including fin-PCM systems, provide better thermal stability and increase energy efficiency across different operating conditions. Comparative analysis suggests that fin geometry, material properties, airflow conditions and climatic impact are key factors in system performance. Notwithstanding these improvements, many research gaps remain, including the lack of common performance metrics, limited studies on long-term durability, limited economic and life cycle assessments and the need for an optimised hybrid cooling configuration. Finally, advances in integrated fin-PCM, advanced materials and analytical data optimisation could lead the way towards realising such PVM and PV/TM cooling devices.
The persistent presence of pharmaceutical pollutants like amoxicillin (AMX) and cephalexin (CPX), and industrial dyes such as phenol red (PR) in wastewater poses serious ecological and public health risks, including antibiotic resistance. It necessitates efficient and low‐cost remediation technologies. Photocatalysts employing innovative and engineered nanomaterials such as bismuth oxide (Bi 2 O 3 ) and zinc oxide (ZnO) nanostructures exhibit considerable potential for eliminating pollutants. This study focused on the photodegradation of AMX, CPX, and PR utilizing green‐synthesized folic acid–ZnO–Bi 2 O 3 nanoparticles (F‐Zn‐Bi NPs) under visible light irradiation. Characterization of the synthesized photocatalyst was conducted using various techniques of powder x‐ray diffraction (PXRD), field emission scanning electron microscopy, energy dispersive x‐ray analysis, Fourier‐transform infrared (FT‐IR) spectroscopy, Brunner–Emmett–Teller (BET) analysis, thermal gravimetric analysis, and photoluminescence (Pl) and UV‐visible (UV‐vis) measurements. The characteristic properties of F‐Zn‐Bi NPs obtained by PXRD confirmed the coexistence of monoclinic phases of α ‐Bi 2 O 3 and ZnO, with an average crystallite size of 36.4 nm. Electron microscopy and BET analysis revealed a porous morphology with a specific surface area of 159.6 m 2 g −1 , which is favorable for surface adsorption of the pollutants. FT‐IR spectra of F‐Zn‐Bi NPs corroborated successful folic acid integration. A reduced band gap of 2.32 eV was also obtained by Tauc plot constructed from UV‐vis absorption and Pl data. F‐Zn‐Bi NPs exhibited degradation efficiencies of 93.7%, 90.0%, and 95.0% for PR, AMX, and CPX, respectively, within 300 min through a first‐order reaction kinetics. The novel F‐Zn‐Bi NPs demonstrated considerable potential for the remediation of pharmaceutical/dye–contaminated wastewater.
Photovoltaic technology is one of the most pioneering renewable methods for electricity generation. This technology has gained substantial attention over the past decade due to the significant decline in the cost of PV power plant construction. Consequently, a lot of studies focusing on the investigation and optimization of PV systems have been conducted in recent years. This work intends to conduct a comprehensive review of these advancements through a structured and meaningful classification. It provides an overview of studies performed on three main subjects related to the field of PV modules, including thermal aspects, computer-assisted methods, and an increase in incoming irradiation. Most existing review studies in PV systems address these three areas separately and view PV performance as a single outcome. In contrast, this paper introduces a broader operational perspective by defining PV system performance through four complementary dimensions. This work demonstrates that improvement strategies do not affect all aspects of system behavior in the same way. By integrating physical and data-driven approaches, this review shows how they interact in practice, discusses key trade-offs and gaps in the literature, and identifies future paths toward more efficient and reliable PV systems.
The increasing penetration of doubly fed induction generator (DFIG)–based wind farms, combined with series-compensated transmission and weak grid conditions, has significantly heightened the risk of subsynchronous resonance (SSR). In modern power systems, SSR is manifested as subsynchronous control interaction (SSCI), due to adverse interactions between converter control loops and grid impedance characteristics. This paper presents a review of SSR in DFIG-based wind farms, synthesizing recent advances in mechanism identification, mitigation strategies, and detection techniques. Grid strength on SSCI susceptibility is critically examined. Mitigation approaches are comparatively analyzed across system-level, device-based, and control-based categories. Field case studies and experimental validations are reviewed to highlight real-world performance and limitations. In verified case studies, mitigation techniques such as resonant controllers, sliding mode control (SMC), and hybrid systems that combine static synchronous compensators (STATCOMs) with battery energy storage systems (BESSs) show effectiveness. Their broad implementation is hindered by enduring issues, including multimodal resonance in hybrid grids, the scalability of lab-tested solutions, cybersecurity vulnerabilities, and a lack of data for AI models. The review also integrates recent advances in robust control frameworks for inverter-fed systems, optimal energy storage sizing under wake effects, and coordinated multilayer mitigation architectures, addressing identified gaps in practical deployment. Finally, emerging trends and challenges related to adaptive control and coordinated mitigation are discussed. The review provides actionable insights for system planners and operators seeking robust SSR mitigation in renewable-rich power systems.
This study presents the experimental development and evaluation of a roof-based thermoelectric generator (TEG) system, highlighting its potential and the key factors influencing its performance. With over 770 million people in Africa lacking access to electricity, particularly in rural areas, the research addresses the urgent need for decentralized, low-cost, and sustainable energy solutions. The metallic roof served as the hot junction, whereas passive air or water cooling maintained the temperature gradient across TEC1-12706 Peltier modules. A factorial design of experiment tested eight configurations, varying coolant type, roof color, and roof exposure to atmosphere. Statistical analysis using Minitab confirmed the significance of all three factors and their two-way interactions. The optimal configuration, a black roof covered with transparent glass and cooled by water, achieved a maximum temperature difference of 43.16 degrees C and an output voltage of 4.226 V using four modules. Integrated with the designed DC-DC booster converter, this setup successfully powered a 12-V DC light bulb and charged mobile phones. In practice, the devices operated reliably, verifying that the system delivered sufficient and stable electrical output for real applications. Comparative analysis with previous studies showed that the roof-based TEG system outperformed similar setups in terms of output voltage, even compared with systems using stronger heat sources such as electric heaters, brick furnaces, and automobile exhausts. This reveals the great capacity of roof-based TEG systems to serve as a practical renewable energy solution for the future. The roof-based TEG system offers substantial environmental and socioeconomic benefits. It reduces reliance on biomass and fossil fuels, lowers greenhouse gas emissions, and provides a clean, renewable energy source that can be integrated into existing rooftops without major structural modifications. The system ' s simplicity, scalability, and minimal maintenance requirements make it particularly suitable for rural electrification. This research establishes a strong foundation for the practical implementation of roof-based thermoelectric generation and underscores its potential as a transformative solution for clean energy access in underserved communities.
Understanding how molecular structure governs interfacial charge transfer and recombination dynamics is central to improving the efficiency of dye-sensitized solar cells (DSSCs). In this work, two pi-extended unsymmetrical squaraine sensitizers-TSQ-OMe and TSQ-NO2-were rationally designed to elucidate the role of substituent-driven electronic and steric modulation on photoenergy conversion. Both dyes exhibit intense far-red intramolecular charge-transfer (ICT)-type absorption above 660 nm, suitable energy-level alignment for TiO2 electron injection, and efficient dye regeneration, as suggested by electrochemical measurements and supported by DFT/TD-DFT calculations. When applied in DSSCs, TSQ-OMe delivers a power conversion efficiency of 7.78% in the presence of chenodeoxycholic acid (CDCA), outperforming TSQ-NO2 (6.41%). Electrochemical impedance spectroscopy (EIS) reveals that the methoxy substituent suppresses interfacial recombination by increasing charge-transfer resistance and prolonging electron lifetime, leading to enhanced open-circuit voltage and photocurrent density. In contrast, the nitro group induces stronger molecular polarization that accelerates back-electron transfer. These results demonstrate that precise substituent engineering in pi-extended squaraines provides an effective strategy for regulating recombination kinetics and improving photoenergy conversion efficiency in far-red DSSCs.
High-temporal-resolution solar radiation data are essential for photovoltaic (PV) system design, grid integration and forecasting, yet such measurements remain scarce in Sub-Saharan Africa. This study presents and analyses a 5-min ground-based dataset from Lawra, Ghana, spanning November 2020 to May 2022, including global horizontal irradiance (GHI), ambient temperature, relative humidity (RH) and wind speed. The results reveal strong seasonal and diurnal cycles in solar radiation and meteorological conditions. Daily GHI ranged from 2 to 7 kWh/m2/day, with reductions of up to 30% during the Harmattan season. Variability analysis showed that most 5-min GHI fluctuations were within +/- 100 W/m2, but extremes exceeding +/- 500 W/m2 occurred, highlighting potential challenges for inverter and storage sizing. Spectral and autocorrelation analyses confirmed dominant daily periodicity and short-term persistence, while extreme-event case studies highlighted rapid irradiance collapses under dust and cloud cover. Simulated PV yields for a 1 kWp reference system ranged between 2.5 and 6.5 kWh/kWp/day, with performance ratios (PRs) of 0.7-0.85 and capacity factors (CFs) of 10%-25%. Comparisons between 5-min and hourly aggregations demonstrated that coarser data underestimated variability, potentially leading to under designed systems. The findings highlight the importance of accounting for Harmattan-induced attenuation and short-term fluctuations in PV planning.
Accurate weather forecasting is a key requirement for the reliable operation and optimization of renewable energy systems, particularly solar photovoltaic (PV) installations. This study presents a comparative evaluation of three widely used machine learning algorithms-artificial neural networks (ANN), support vector regression (SVR), and random forest (RF)-for forecasting three critical meteorological parameters: ambient temperature, wind speed at 10 m, and global horizontal irradiance (GHI). Two climatically distinct cities were selected as case studies: Antalya (Turkey), representing a Mediterranean climate, and Cheboksary (Russia), representing a temperate continental climate. Using high-resolution weather datasets spanning from 2018 to 2023, the models were trained and tested for forecast horizons ranging from 1 to 10 days. The model performance was assessed using three standard evaluation metrics: root mean square error (RMSE), mean absolute error (MAE), and the coefficient of determination (R2). The results demonstrate that RF provided the lowest prediction error for temperature and wind speed across both locations, whereas ANN yielded the most accurate forecasts for GHI. Moreover, paired forecasts involving temperature and GHI showed the highest R2 values using ANN (0.968 and 0.948), and RF showed optimal accuracy for temperature and wind speed pairs (0.975 and 0.967). The findings underscore the importance of algorithm-climate interaction and offer insights for model selection in hybrid renewable energy system modeling.
The practical efficiency of Cu2ZnSnS4 (CZTS) thin-film solar cells remains constrained by unfavorable band alignment, high defect densities, and inefficient charge extraction at interfaces. This study numerically investigates and optimizes CZTS-based solar cells by evaluating four Cu-based hole transport layers (HTLs)-Cu2O, CuO, CuI, and CuSCN-to minimize recombination losses and enhance photovoltaic performance. The proposed device architecture (ITO/SnS2/CZTS/HTL/Pt) was simulated using the SCAPS-1D platform under standard illumination conditions (AM 1.5G, 1000 W/m(2), 300 K). Key parameters including layer thickness, doping concentration, defect density, operating temperature, and resistive losses were systematically optimized. The results reveal that Cu2O exhibits the most favorable energy band alignment and carrier transport properties, yielding the highest simulated power conversion efficiency (PCE) of 34.35%, with an open-circuit voltage of 1.192 V, short-circuit current density of 32.12 mA cm(-2), and fill factor of 89.7%. Maintaining low defect density, moderate absorber thickness (similar to 1.5 mu m), and high shunt resistance proved essential for optimal device stability and performance. These findings highlight the critical role of interface engineering and HTL optimization in CZTS-based photovoltaics, offering valuable design guidelines for future experimental validation and practical device fabrication.
Organic photovoltaics (OPVs) offer a promising pathway toward low-cost, flexible, and solution-processable solar energy technologies; however, rational materials design remains challenging due to the complex and nonlinear relationships between molecular electronic structure and optoelectronic performance. In this study, machine learning models are developed to predict the spectral overlap of organic photovoltaic materials, a physically meaningful descriptor that quantifies the compatibility between molecular absorption and the solar spectrum. Using a large-scale OPV molecular dataset, multiple regression models linear regression (LR), support vector regression (SVR), random forest (RF), and gradient-boosted regression trees (GBRT) are systematically evaluated under a fivefold cross-validation framework. Among these, ensemble-based models demonstrate superior predictive accuracy and robustness. To move beyond purely predictive performance, explainable machine learning analysis based on SHapley Additive exPlanations (SHAP) is employed to uncover interpretable structure-property relationships. The SHAP results consistently identify frontier orbital energies and gap-related descriptors as dominant contributors to spectral overlap, while revealing clear directional dependencies and nonlinear effects. Overall, this work establishes an interpretable, data-driven framework that links molecular electronic descriptors to spectral overlap, offering a valuable tool for accelerated screening and rational design of high-performance organic photovoltaic materials.
Due to the lack of access to grid electricity, milk preservation is a significant challenge in pastoral and rural areas of most African countries, despite the large volume of milk produced. Integrating milk pasteurization and chilling with a hybrid solar-thermal and photovoltaic system can enhance milk preservation, enabling milk to reach the market and generate income for pastoral and rural communities in off-grid areas of Africa. In this study, a MATLAB program was developed based on a transient model of a solar heating system and refrigeration system that uses a DC compressor powered by a photovoltaic panel for dynamic adaptive simulation of milk preservation temperature. The model facilitates reliable sizing of the evacuated-tube solar collector area, the PV array, and the DC compressor capacity for pasteurization and chilling based on the given milk volume for a particular location. Moreover, the annual performance of the system with a 50-L milk capacity at Semera, Ethiopia, was investigated. The simulation results show that milk can be effectively pasteurized at temperatures of 63 degrees C and higher after water is heated for 30 min at 10 a.m. Consequently, in less than 3 h, the milk chilling system can lower the milk ' s temperature to 4 degrees C. During the critical month, the time required was around 3 h and 10 min. Furthermore, the results show that the refrigeration cycle ' s coefficient of performance (COP) at the start of operation at 1800 rpm is 1.65. For the 24-V compressor, the highest COP recorded was 2.16 at a maximum speed of 3600 rpm. Nevertheless, when using the same compressor model with 48 V, the COP begins to decrease as the rpm exceeds 3600 rpm and eventually reaches a maximum speed of 6500 rpm. Hence, it can be concluded that solar-powered milk pasteurization and chiller can be used to alleviate the problem of milk preservation and market inaccessibility facing pastoralists and small-scale dairy farms in off-grid areas of semi-arid tropical regions.
Solar tracking is essential for efficiency, yet current market solutions present a trade-off: Active systems are precise but expensive and computationally demanding, while low-cost passive systems (e.g., LDRs) often lack accuracy. To address this gap, this work presents the design and validation of a passive solar tracking sensor based on gnomon shadow analysis using computer vision. Unlike complex direct imaging systems, this approach utilizes lightweight geometric transformations and color segmentation to estimate solar azimuth and elevation in real time. Experimental validation against NOAA models yielded angular errors ranging from 0.155 to 59.13 mrad in azimuth and from 36.49 to 66.84 mrad in elevation. Robustness tests demonstrated that the system maintains consistency even with camera position variations, showing a maximum deviation of 9.4 mrad. Furthermore, a computational benchmark confirmed the algorithm's efficiency, achieving a processing time of 3.69 s on a legacy low-end device (Intel Atom), which is sufficient for solar dynamics. These results distinguish the proposed method as a feasible, cost-effective alternative that achieves functional accuracy without the need for high-performance computing resources or expensive optical encoders.
The persistent presence of pharmaceutical pollutants like amoxicillin (AMX) and cephalexin (CPX), and industrial dyes such as phenol red (PR) in wastewater poses serious ecological and public health risks, including antibiotic resistance. It necessitates efficient and low-cost remediation technologies. Photocatalysts employing innovative and engineered nanomaterials such as bismuth oxide (Bi2O3) and zinc oxide (ZnO) nanostructures exhibit considerable potential for eliminating pollutants. This study focused on the photodegradation of AMX, CPX, and PR utilizing green-synthesized folic acid-ZnO-Bi2O3 nanoparticles (F-Zn-Bi NPs) under visible light irradiation. Characterization of the synthesized photocatalyst was conducted using various techniques of powder x-ray diffraction (PXRD), field emission scanning electron microscopy, energy dispersive x-ray analysis, Fourier-transform infrared (FT-IR) spectroscopy, Brunner-Emmett-Teller (BET) analysis, thermal gravimetric analysis, and photoluminescence (Pl) and UV-visible (UV-vis) measurements. The characteristic properties of F-Zn-Bi NPs obtained by PXRD confirmed the coexistence of monoclinic phases of alpha-Bi2O3 and ZnO, with an average crystallite size of 36.4 nm. Electron microscopy and BET analysis revealed a porous morphology with a specific surface area of 159.6 m2 g-1, which is favorable for surface adsorption of the pollutants. FT-IR spectra of F-Zn-Bi NPs corroborated successful folic acid integration. A reduced band gap of 2.32 eV was also obtained by Tauc plot constructed from UV-vis absorption and Pl data. F-Zn-Bi NPs exhibited degradation efficiencies of 93.7%, 90.0%, and 95.0% for PR, AMX, and CPX, respectively, within 300 min through a first-order reaction kinetics. The novel F-Zn-Bi NPs demonstrated considerable potential for the remediation of pharmaceutical/dye-contaminated wastewater.
Renewable energy, including solar photovoltaic (PV) technology, is essential for worldwide decarbonization. This study compares high-efficiency, large collector area (HE/LCA) modules to low-efficiency, small collector area (LE/SCA) modules with a 100 MW power capacity. RETScreen Expert was used to do a techno-economic and environmental study on two systems: the Jinko-615 W (HE/LCA) and the Seraphim-270 W (LE/SCA). Over a 20-year lifetime, the Jinko system is expected to provide more than double the total energy of the Seraphim system, which is 3.94 TWh. The Jinko system generated $44.83 million in power export income each year, compared with Seraphim’s $19.68 million, and had a far greater Net Present Value (NPV) of $132.81 million compared with Seraphim’s $58.31 million. A higher internal rate of return and a lower levelized cost of electricity ($0.085/kWh) emphasized the Jinko configuration’s stronger financial stability. The Jinko system significantly reduced greenhouse gas (GHG) emissions by 220,932 tCO2e annually, surpassing Seraphim’s decrease of 96,995 tCO2e. Sensitivity and probabilistic studies confirmed its higher possibility of long-term profitability and better financial resilience. The Jinko design provides a higher internal rate of return and a lower levelized cost of energy ($0.085/kWh), while also doubling annual GHG emission reductions. The study indicates that high-efficiency modules, while more expensive initially, yield superior economic and environmental benefits for utility-scale PV systems.
In this research, we present an environmentally friendly and high-efficiency thin-film solar cell using Cu(In,Ga)Se-2 (CIGS) that was modeled using SCAPS-1D software. The goal is to produce a nontoxic and sustainable photovoltaic device with improved performance. The optimal structure of the device FTO/WS2/CIGS/Cu2O/Au consists of a CIGS absorber, WS2 buffer, FTO electron transport layer (ETL), and Cu2O hole transport layer (HTL). The device performance is systematically analyzed with a focus on design parameters including absorber thickness, buffer thickness, defect density, operating temperature, contact work function, and doping concentration. The optimized structure that consists of a 1.0-mu m CIGS absorber, 0.05-mu m WS2 buffer, 0.05-mu m FTO ETL, and 0.5-mu m Cu2O HTL resulted in a simulated efficiency of 32.88%, with an open-circuit voltage (Voc) of 0.9184 V, short-circuit current density (Jsc) of 42.98 mA/cm(2), and fill factor (FF) of 83.28%. The addition of WS2 enhances the charge carrier transport and decreases the interface recombination because of band alignment and high electron mobility. These findings indicate the potential of using WS2 as a CIGS-based heterostructure for new generations of environmentally friendly thin-film solar cells.
