Search Results (940)

Türkiye’s strategic geographical location offers an exceptional opportunity for solar energy harvesting, yet optimizing large-scale investments requires rigorous pre-assessment methodologies. This study presents a comprehensive multi-criteria techno-economic analysis and real-world validation of a 13.18 MWp solar power plant (SPP) located in Kirsehir, a region characterized by high solar irradiance (1750 kWh/m²). Utilizing PVsyst software, four distinct configurations—monofacial and bifacial modules at 21° and 25° tilt angles—were systematically simulated and evaluated across varying equity-to-loan ratios using key financial indicators (NPV, IRR, PI, and Payback Period). The simulation results identified the 21° bifacial configuration, enhanced by the innovative integration of high-albedo industrial calcite (CaCO₃) waste as ground cover, as the optimal engineering solution. Crucially, the accuracy of this optimization was evaluated against 12 months of field data. While the raw measured annual production was recorded as 22,793,323 kWh, the validation was strictly based on the production adjusted for grid outages (23,499,604 kWh). Comparing this adjusted value with the simulated annual generation (22,816,114 kWh) yielded a total annual discrepancy of only 3% and a volumetrically weighted average error of 5.07%. Furthermore, to isolate model fidelity from inter-annual meteorological variability, the validation was assessed using the Performance Ratio (PR). The adjusted volumetrically weighted PR (87.43%) demonstrated a remarkably close alignment with the simulated PR (87.48%), exhibiting a marginal deviation of merely 0.05%. These performance metrics indicate a general consistency between the simulation model and operational field records across the evaluated period. Environmentally, the maximized energy yield of the 21° bifacial system facilitates the avoidance of approximately 6507.58 tonnes of CO₂ emissions annually. This research not only establishes the viability of scalable, low-cost calcite ground covers but also provides a highly robust, de-risked decision-support framework for utility-scale PV investments in similar geographic latitudes. Full article

The selection of georeferenced meteorological databases is a critical technical and financial factor in photovoltaic (PV) system sizing. This study evaluates how database choice affects PV generation estimates and economic feasibility by combining bibliometric screening, technical validation, financial indicators, and multicriteria analysis. A bibliometric review of 5658 documents indexed in Scopus and Web of Science supports the selection of seven databases, compared across ten Brazilian locations. PV generation is estimated using both a simplified sizing approach and a higher-temporal-resolution model based on hourly irradiance, ambient temperature, and module thermal coefficients, enabling comparison with measured generation in a three-year case study in João Pessoa. Performance is assessed using MAE, MAPE, RMSE, $R^2$, NPV, payback and the Analytic Hierarchy Process. Under the adopted PV model and AHP weighting structure, NASA POWER shows the strongest overall multicriteria performance in the analyzed Brazilian sample, ranking first in seven locations. Database choice causes variations of up to 4.70 years in payback and BRL 105,709.36 in NPV, equivalent to USD 21,082.84 at the 22 May 2026 exchange rate. The simplified CRESESB-based method overestimates annual generation by 6.79–12.64%, whereas NASA POWER reaches a best annual deviation of $-1.66\%$ in 2024. Full article

The nature of solar radiation and the high penetration of photovoltaic (PV) systems in the smart electrical grid necessitate the development of models driven by historical operational data capable of precisely estimating the performance of PV systems. In this work, six proposed models are applied to predict the conversion efficiency of a 7.98 kWp rooftop on-grid PV system in Jordan. The dataset comprises 179 daily samples obtained during a single spring–summer period (17 March–24 September 2014). The efficiency modeled is the combined efficiency of the modules and inverter as a system. The proposed models are Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), Gradient Boosting (GB), Gaussian Process Regression (GPR), and Elastic Net (EN). The effectiveness of these proposed models is assessed by calculating four performance metrics, namely, the Mean Square Error, prediction accuracy, Coefficient of Determination (R²), and adjusted R², and benchmarking the results with those of six prediction models discussed in our previous work. The results from the unweighted Decision-Making Matrix show that RF showed the best overall performance among the proposed and benchmark models considered. By contrast, the SVM, DT, and GB models exhibited moderate predictive behavior. However, Elastic Net is the worst-performing model among the 12 proposed and benchmark models discussed in this work. Moreover, the RF model’s consistently low prediction error supports its practical utility for PV system performance estimation, despite a slightly higher training cost than simpler models. Full article

Peripheral vestibulopathy (PV) is a common disorder that causes dizziness and balance impairment, substantially affecting patients’ quality of life. When symptoms persist, they frequently lead to anxiety, depression, and an increased risk of social isolation. Although central vestibular compensation (CVC) often promotes functional recovery, current pharmacological options remain limited and are primarily aimed at symptom control. Consequently, they should be considered adjuncts rather than alternatives to rehabilitation-based strategies. Vestibular rehabilitation (VR) remains the cornerstone of treatment for promoting functional recovery in patients with PV. Based on the complementary mechanisms of adaptation, substitution, and habituation, VR enhances the central nervous system’s ability to compensate for vestibular deficits by optimizing the integration of visual, proprioceptive, and residual vestibular inputs. Robust evidence from both clinical and preclinical studies has demonstrated its efficacy in improving postural stability, dynamic balance, gaze stabilization, and overall functional performance. Experimental studies using animal models have further highlighted the critical role of active sensorimotor training in ecologically relevant environments for enhancing vestibular compensation. Pharmacological interventions may further facilitate these adaptive processes by modulating the neurobiological mechanisms underlying vestibular compensation, thereby improving responsiveness to rehabilitation. Likewise, emerging neuromodulation approaches, including galvanic vestibular stimulation, have shown promising potential to enhance neural plasticity and augment the effects of rehabilitation. Consequently, combining VR with targeted pharmacological therapies and/or vestibular stimulation techniques may provide synergistic benefits and maximize functional recovery. In conclusion, vestibular rehabilitation should remain the foundation of PV management and be integrated with pharmacological and neuromodulatory approaches within a multidisciplinary therapeutic framework. Further research is needed to optimize rehabilitation protocols, identify the biological determinants of successful vestibular compensation, and develop personalized therapeutic strategies aimed at maximizing functional recovery and improving patients’ quality of life. Full article

For large-scale photovoltaic plant inspection, UAV-based infrared–visible real-time detection can combine thermal abnormality information with appearance and structural cues. This is useful for improving inspection and maintenance efficiency. However, in real UAV inspection, differences in sensor resolution, field of view, and flight attitude can cause weak misalignment between the two modalities. Since complex image registration is difficult to perform before real-time inference, this misalignment can affect cross-modal feature fusion and defect localization. To address this problem, this paper proposes Frequency-Aware Fusion YOLO (FAF-YOLO) for dual-modal photovoltaic defect detection. We also build a real-scene infrared–visible dual-modal photovoltaic defect dataset, named DM-PV, which covers six defect categories related to thermal anomalies and external environmental interference. FAF-YOLO is based on a dual-branch YOLO detection framework. The C3k2-DPRG module is used to enhance defect boundaries, local details, and neighborhood context. The Frequency-aware Selective Fusion (FSF) module models low-frequency structural information and high-frequency detail responses separately, which reduces edge ghosting and background mis-fusion caused by weak misalignment. A Multi-Scale Differentiated Decoupled Head is then used to handle scale-specific prediction and improve small-defect localization and regional-anomaly discrimination. Experimental results show that FAF-YOLO achieves 92.5% Precision, 86.7% Recall, 91.7% ${\mathrm{mAP}}_{50}$, and 61.4% ${\mathrm{mAP}}_{50:95}$ on the DM-PV dataset. It outperforms several mainstream dual-modal detection methods and has lower parameters and computational complexity. Further tests for real-time inspection show that the proposed method keeps more stable performance under weak misalignment perturbations. It also reaches an inference speed of 33 FPS on the Jetson Orin Nano edge platform, which verifies its effectiveness and deployability for UAV-based real-time photovoltaic inspection. Full article

Solar photovoltaic (PV) expansion in fast-growing tropical regions requires engineering-based frameworks that compare deployment pathways in terms of electricity generation, spatial footprint, and economic performance. This study develops a techno-spatial and economic assessment of rooftop versus land-based PV deployment in a biodiversity-sensitive region of the Mexican Caribbean. The novelty lies in linking the technical, spatial, ecological, and financial dimensions of rooftop and land-based PV deployment within a single place-based framework. The framework uses a common annual electricity-output basis and integrates three modules: rooftop PV technical potential estimated from housing-census data and conservative performance assumptions; an equivalent-generation land-based PV counterfactual to estimate spatial footprint and conditional ecological exposure; and a household-scale discounted cash-flow assessment under Mexico’s subsidized residential tariff category 1C and high-consumption residential tariff (DAC, Doméstica de Alto Consumo). Under baseline assumptions, rooftop PV could provide approximately 227 megawatt-peak ($\mathrm{M}{\mathrm{W}}_{\mathrm{p}}$) of installed capacity and 330 gigawatt-hours per year ($\mathrm{G}\mathrm{W}\mathrm{h} {\mathrm{y}\mathrm{r}}^{-1}$) without additional land occupation. Producing the same output through land-based PV would require about 486 hectares ($\mathrm{h}\mathrm{a}$) and, under a forest-overlap scenario, could imply 89,600–95,300 tonnes of carbon dioxide (${\mathrm{t} \mathrm{C}\mathrm{O}}_2$) in potential conversion-related emissions. Rooftop PV showed positive economic performance under both tariffs, with stronger returns under DAC conditions. The study provides a bounded engineering-oriented comparison of PV deployment pathways rather than predictions of siting, land conversion, or adoption. Full article

Conventional soldered interconnects—necessarily requiring high-temperature processes to melt solder (tin)—are posing reliability challenges to crystalline silicon solar cell modules due to residual stress stemming from the mismatch of the coefficient of thermal expansion of the materials involved. On the other hand, electrically conductive adhesives (ECAs) have been shown to exhibit sufficiently promising improvements in mechanical and electrical properties to be used as silicon solar cell interconnects. However, the current ECA technology is dominated by ECAs with dispersed silver particles, which makes them costly and could cause embrittlement of the ECA at higher concentrations. This study investigates the potential application of a novel ECA, with composite metal particles, made of a nickel and Sn95Ag4Cu1 solder mixture and dispersed in a high-density polyethylene matrix for the solar cell interconnection. The test PV modules show comparable electrical and mechanical performance to that of soldered cell modules, despite the fact that the ECA application is still rather early in its learning curve. The present study suggests that the novel ECA could lead to a promising alternative to the conventional soldering process and the more costly silver-filled ECAs. Full article

This paper presents a simplified dimensionless model for predicting the electrical performance of photovoltaic (PV) modules under varying irradiance and temperature conditions. Unlike conventional equivalent-circuit models that require detailed parameter extraction, the proposed approach employs dimensional analysis to establish direct relationships between key PV operating points and normalized environmental variables, without assuming a predefined physical model. The model is validated using experimental datasets from Sandia National Laboratories, covering a wide range of irradiance (100–1100 W/m²) and module temperatures (15–75 °C). Model accuracy is evaluated using normalized root mean square error (nRMSE). The results demonstrate strong predictive capability, with average nRMSE values below 2.5% for maximum power point voltage and current, below 1% for maximum power, and low errors for open-circuit voltage and short-circuit current. To the best of the authors’ knowledge, this represents the first application of the Buckingham $\pi$ theorem to derive dimensionless scaling laws for predicting PV module electrical characteristics under varying irradiance and temperature conditions. The proposed model provides a computationally efficient and accurate alternative to conventional PV models. Moreover, the dimensionless framework offers strong potential for predicting the performance of complex multiphysics energy systems, where conventional equivalent-circuit-based approaches are often difficult to apply or fail to achieve satisfactory accuracy. Full article

Dust accumulation on photovoltaic (PV) module surfaces significantly reduces energy yield in arid environments, yet traditional water-based cleaning techniques are unsustainable. This study presents a complete evaluation of electrodynamic screen (EDS) technology as a waterless cleaning solution, with a focus on dust removal efficiency and the critical trade-offs between energy gains and losses. Using printed circuit board (PCB) technology, a three-phase EDS system was designed and constructed, and its performance was simulated on COMSOL Multiphysics. Under optimal conditions of 50 Hz and a 66% duty cycle, the system achieves 52% dust removal efficiency while consuming less than one watt-hour per square meter during operation. The novelty of this study lies not merely in the hardware, but in the analytical lens applied and the holistic loss–gain methodology that quantitatively assesses, over a seven-day cycle, the reduction in dust-induced optical loss, the intrinsic optical transmission loss introduced by the EDS layer itself, and the operational energy cost of running the system. Rather than focusing on removal efficiency in isolation, this study enables a site-specific evaluation of whether, and when, EDS technology delivers a net energy benefit. By integrating material properties, local soiling conditions, and all major loss mechanisms, this study provides a low-cost and analytical tool for researchers and solar farm operators to assess the real-world feasibility of EDS cleaning before deployment. While the proposed PCB technology is not itself suitable for field deployment, it serves as a low-cost development platform for optimizing electrode geometry and excitation parameters prior to investment in transparent materials. Full article

In high-density cities, limited roof and ground areas constrain conventional photovoltaic (PV) deployment. Vertical bifacial photovoltaic (bPV) modules offer an alternative by making good use of building and infrastructure surfaces while harvesting irradiance on both sides. This study develops an integrated module-level framework for evaluating tilted and vertical bPV modules. It couples two-sided anisotropic irradiance calculations with five-parameter electrical and steady-state thermal models. Unlike irradiance-only or configuration-specific assessments, the framework consistently compares bPV and monofacial PV (mPV) modules across tilt and azimuth configurations while jointly quantifying power output, module temperature, bifacial gain, and angular losses. Predicted power output agreed well with outdoor measurements across four representative mounting configurations, and annual predictions were comparable to PVsyst and SAM results. Applied to Hong Kong, the framework identified optimum tilt angles of approximately 20° for bPV and 18° for mPV modules. A vertical west-facing bPV module achieved 96.3% of the annual energy yield of optimally tilted mPV, with a bifacial gain of 67.2% and an angular-loss-related power loss of 4.8%. These results show that vertical bPV can approach optimally tilted mPV performance while utilizing otherwise unused building surfaces, supporting preliminary design decisions in land-constrained cities. Full article

To reveal the degradation mechanism and the formation mechanism of multiple power peaks in photovoltaic modules under irregular shading conditions, this study investigated the performance of full-cell photovoltaic modules through a combination of experimental and simulation approaches. First, the I–V and P–V characteristics of photovoltaic modules under partial and complete shading of photovoltaic cells at different locations were analyzed. The results show that, under local partial shading conditions, the photovoltaic module characteristics are mainly determined by the shaded area, whereas under complete cell shading conditions, the performance degradation primarily depends on the number of bypassed cell strings. A single-diode photovoltaic module simulation model was developed, and the coupling effects of representative partial shading ratios and the number of participating cell strings were analyzed on the MATLAB/Simulink platform. The results indicate that the characteristics of photovoltaic modules under partial shading conditions are jointly governed by the coupling effects of shading ratio and cell-string participation. As the shaded area increases, the degree of electrical mismatch among cells becomes more pronounced, causing the P–V characteristics to evolve from a single-peak profile to a multi-peak profile, accompanied by reduced peak differences and increasingly blurred characteristic boundaries. Through a comprehensive analysis of the simulation and experimental results, it is found that complex shading conditions enhance the multi-peak characteristics of power while causing the peak values to converge. These accompanying features increase the likelihood of multi-peak power points, thereby posing greater challenges to inverter operation and maximum power point tracking techniques in photovoltaic arrays. It is of great significance for optimizing the configuration of photovoltaic arrays and designing high-precision maximum power point tracking strategies. Full article

Rooftop bifacial photovoltaic (PV) performance depends on both the optical properties of the roof surface and the installation geometry. This simulation-based study assessed a planned rooftop PV installation on a school building in Brno, Czech Republic, using PV*SOL simulations and statistical post-processing in R. The principal dataset comprised 238 bifacial scenarios combining seven spatially distinct roof zones assigned nominal albedo values from 8% to 80%, 17 module tilts from 0° to 80°, and row spacings of 1.00 and 2.10 m. Because each nominal albedo was associated with a different physical roof zone, the results represent combined roof-zone, reflectance and geometry responses rather than the isolated causal effect of albedo. The highest annual specific yield was obtained in the roof-zone scenario assigned 70% nominal albedo. The maximum was 1296.60 kWh/kWp at 1.00 m spacing and 35° tilt and 1359.34 kWh/kWp at 2.10 m spacing and 50° tilt. Under the fixed 25° reference configuration, the bifacial system outperformed the matched monofacial reference in all seven scenarios, with bifacial gain ranging from 7.57% to 11.23%. An empirical response-surface model reproduced the complete simulation grid with adjusted $R^2=0.980$ and RMSE of 13.94 kWh/kWp. For the representative 6.0 kWp subarray, the maximum lifetime incremental avoided-emission difference relative to the matched 8% reference was 10.35 t CO₂. Within the predefined Monte Carlo ranges, the highest-ranked scenarios produced positive incremental net present value in all 5000 sampled combinations. The findings show that roof reflectance should be evaluated together with tilt, spacing and spatial roof context. They do not establish a universally optimal albedo or rooftop configuration. Full article

As China confronts an unprecedented surge in decommissioned photovoltaic (PV) modules, establishing a robust and comprehensive recycling mode has become an urgent task. However, the existing literature lacks a systematic investigation into multi-stakeholder responsibility models for end-of-life PV management. To bridge this critical gap, firstly, this study conceptualized three multi-stakeholder PV recycling modes and developed an 11-parameter cost–benefit analysis model to dynamically evaluate their economic disparities under varying scenarios. Secondly, the framework is applied to a regional case involving 55 prefecture-level cities in the Shandong, Jiangsu, Anhui, and Zhejiang provinces in China. The results showed that the collaborative recycling mode involving retailers and third parties achieved optimal economic performance, incurring a lower cost (64.30 million CNY) than the alternative modes (70.41 and 80.25 million CNY, respectively). Cost structural analysis revealed that the collection, storage, transportation, and processing stages were the critical bottlenecks for cost control across all three modes. Scenario simulations further indicated a non-linear dynamic: while expanding the recovery scale enhanced profitability, excessive network optimization (beyond 20%) or prolonged storage durations yielded diminishing returns. Comprehensively, the maximum net benefit was achieved by synergizing scale expansion with moderate network optimization and a strict 30-day storage limit. Ultimately, these findings demonstrate the economic feasibility of multi-entity responsibility modes, providing a universal methodological framework for other regions and countries to construct efficient, low-cost PV recycling systems. Full article

Under extreme high-temperature conditions, heat accumulation in rooftop photovoltaic (PV) arrays can substantially reduce PV conversion efficiency and output power. To improve the thermal and power-generation performance of rooftop PV systems, this study developed a computational fluid dynamics (CFD) model for a rooftop PV array and validated it using field measurements from Chongqing, China. The relative root mean square errors (rRMSEs) between simulated and measured backsheet temperatures at the three measurement points were 6.31%, 7.52%, and 8.45%, respectively, indicating acceptable model accuracy. The effects of mounting height, tilt angle, and front-to-rear row spacing on PV backsheet temperature, conversion efficiency, and output power were then investigated. A central composite design (CCD) within response surface methodology (RSM) was used to establish regression models linking the design variables to the objective functions. Finally, an NSGA-III-based multi-objective optimization framework combined with TOPSIS was used to identify the optimal configuration. For the rooftop PV array studied under extreme summer conditions in Chongqing, the TOPSIS-selected compromise solution corresponded to a mounting height of 0.90 m, a tilt angle of 15.63°, and a front-to-rear row spacing of 2.96 m. Compared with the original configuration, the optimized passive installation geometry reduced the peak PV backsheet temperature by 2.3 °C without active cooling, water consumption, or additional energy input. Under the same meteorological and irradiance conditions, this temperature reduction increased conversion efficiency by 0.5% and output power by 0.4%. Detailed inter-row short-wave shading and electrical mismatch were not explicitly modeled. Therefore, the row-spacing effect mainly reflects changes in ventilation and module temperature under the same irradiance input. The proposed framework provides a practical reference for installing and optimizing rooftop PV arrays in hot-climate regions. Full article

Perovskite solar cells (PSCs) have emerged as one of the most promising next-generation photovoltaic (PV) technologies due to their high power conversion efficiencies, low-temperature processing, and potential for low-cost manufacturing. Despite these advantages, several challenges remain that hinder their large-scale commercialization, particularly related to environmental sustainability, long-term stability, and end-of-life management (EoL). Life cycle assessment (LCA) has become an essential tool to evaluate the environmental impacts of emerging PV technologies and to identify critical hotspots across the supply chain. At the same time, concerns regarding material toxicity, particularly lead content, as well as the lack of established recycling pathways, highlight the importance of effective EoL management strategies. This review examines the current state of research on the life cycle environmental performance of perovskite solar modules (PSMs) and evaluates emerging approaches for sustainable EoL management. The study synthesizes the existing literature on manufacturing processes, environmental impact indicators, material recovery, recycling technologies, and circular economy strategies relevant to perovskite PVs. Particular attention is given to innovation-driven approaches that integrate sustainability considerations into technology development and commercialization pathways. By identifying key environmental hotspots, technological challenges, and research gaps, this review provides insights into how sustainable innovation and circular resource management can support the transition of PSMs from laboratory-scale research to economically viable and scalable commercial deployment. Full article