Solar

Urban soiling, consisting of dust, industrial byproducts, and other pollutants, presents a significant risk to the effectiveness and safety of solar energy systems. To achieve the goal of net zero, having renewable energy systems such as solar panels in urban environments can help. This review will examine the composition and variety of urban soiling and evaluate its impact on PV installation. The study will analyze the efficiency loss attributable to soiling, focusing on its impact on small-scale installations such as rooftops, building integrated photovoltaics (BIPVs), and large-scale urban solar installations. Furthermore, this study will also investigate various developing technologies and strategies to reduce the effects of urban soiling. This encompasses the examination of automated cleaning systems and robotic maintenance, with a specific focus on their potential effectiveness. This review aims to underline the importance of addressing urban soiling within the framework of sustainable urban development and the expansion of solar energy, with further research into the development of soiling mitigation technologies. Finally, soil management and further research gaps will be discussed. Full article

In the decarbonization process, the solar energy sector will play a crucial role, representing one of the key technologies for reducing greenhouse gas emissions. In Italy, photovoltaics stands out as the fastest-growing energy sector, thanks to the combination of favorable climatic conditions, supportive policies, and a growing interest in renewable energy sources. In this context, renewable energy communities (RECs) emerge as potential strategic tools for promoting the development of photovoltaics nationally and at the European level. Therefore, this study aims to examine the policy and regulatory frameworks governing RECs in Europe and Italy, highlighting their impact on the establishment, operation, and evolution of these communities. Through a critical analysis of legislative documents at both the European and national levels, this research identifies the key factors shaping the growth and functionality of RECs, such as governance structures, economic incentives, and social inclusivity. This study underscores the dual influence of comprehensive regulation and a certain degree of flexibility in fostering RECs’ adaptability to diverse contexts. Additionally, it identifies existing challenges, including regional implementation disparities, legal ambiguities, and potential conflicts with other renewable energy policies. The findings contribute to the ongoing discourse on decentralized energy systems, providing insights for policymakers to refine frameworks and maximize RECs’ contributions to sustainable energy transitions. Full article

This paper presents findings from the LEOPARD project, part of the LEAP-RE program, a joint European Union (EU) and African Union initiative to advance renewable energy solutions. The study employs a simulation-based approach to optimize solar-integrated microgrid configurations for rural electrification. The project deployed a solar-integrated pilot microgrid at the Songhai agroecological center in Benin to address key challenges, including load profile estimation, energy balancing, and diesel dependency reduction. A hybrid methodology integrating predictive modeling, real-time solar and weather data analysis, and performance simulations was employed, leading to a 65% reduction in diesel reliance and an LCOE of EUR 0.47/kWh. Quality control measures, including compliance with IEC 61215 and IEC 62485-2 standards, ensured system reliability under extreme conditions. Over 150 days, the system consistently supplied energy, preventing 10.16 tons of ${CO}_2$ emissions. Beyond the Benin pilot, the project conducted feasibility assessments in Senegal to evaluate microgrid replicability across different socio-economic and environmental conditions. These analyses highlight the scalability potential and the economic viability of expanding solar microgrids in rural areas. Additionally, this research explores innovative business models and real-time diagnostics to enhance microgrid sustainability. By providing a replicable framework, it promotes long-term energy access and regional adaptability. With a focus on community involvement and capacity building, this study supports efforts to reduce energy poverty, strengthen European–African collaboration, and advance the global clean energy agenda. Full article

The global energy landscape is experiencing growing challenges, with energy crises in regions such as South Africa underscoring the drive to accelerate the shift toward renewable energy solutions. This paper presents an approach for improving solar energy planning, specifically focusing on leveraging the capabilities of the ATlite software in conjunction with custom data. Using mathematical models, ATlite (which was initially developed by the Renewable Energy Group at the Frankfurt Institute for Advances Studies) is a Python software package that converts historical weather data into power generation potentials and time series for renewable energy technologies such as solar photovoltaic (PV) panels and wind turbines. The software efficiently combines atmospheric and terrain data from large regions using user-defined weights based on land use or energy yield. In this study, European Centre for Medium-Range Weather Forecasts reanalysis data (ERA5) data was modified using Kriging to enhance the resolution of each data field. This refined data was applied in ATlite, instead of utilizing the standard built-in data download and processing tools, to generate solar capacity factor maps and solar generation time series. This was utilized to identify specific PV technologies as well as optimal sites for solar power. Thereafter, a simulated power generation time series was compared with measured solar generation data, resulting in a root mean square error (RMSE) of 19.6 kW for a 250 kWp installation. This approach’s flexibility and versatility in the inclusion of custom data, led to the conclusion that it could be a suitable option for renewable energy planning and decision making in South Africa and globally, providing value to solar installers and planners. Full article

The rapid acceptance of solar photovoltaic (PV) energy across various countries has created a pressing need for more coordinated approaches to the sustainable monitoring and maintenance of these widely distributed installations. To address this challenge, several digitization architectures have been proposed, with one of the most recently applied being the digital twin (DT) system architecture. DTs have proven effective in predictive maintenance, rapid prototyping, efficient manufacturing, and reliable system monitoring. However, while the DT concept is well established in fields like wind energy conversion and monitoring, its scope of implementation in PV remains quite limited. Additionally, the recent increased adoption of autonomous platforms, particularly robotics, has expanded the scope of PV management and revealed gaps in real-time monitoring needs. DT platforms can be redesigned to ease such applications and enable integration into the broader energy network. This work provides a system-level overview of current trends, challenges, and future opportunities for DTs within renewable energy systems, focusing on PV systems. It also highlights how advances in artificial intelligence (AI), the internet-of-Things (IoT), and autonomous systems can be leveraged to create a digitally connected energy infrastructure that supports sustainable energy supply and maintenance. Full article

The reliable operation of photovoltaic (PV) systems is essential for sustainable energy production, yet their efficiency is often compromised by defects such as bird droppings, cracks, and dust accumulation. Automated defect detection is critical for addressing these challenges in large-scale solar farms, where manual inspections are impractical. This study evaluates three YOLO object detection models—YOLOv5, YOLOv8, and YOLOv11—on a comprehensive dataset to identify solar panel defects. YOLOv5 achieved the fastest inference time (7.1 ms per image) and high precision (94.1%) for cracked panels. YOLOv8 excelled in recall for rare defects, such as bird drops (79.2%), while YOLOv11 delivered the highest mAP@0.5 (93.4%), demonstrating a balanced performance across the defect categories. Despite the strong performance for common defects like dusty panels (mAP@0.5 > 98%), bird drop detection posed challenges due to dataset imbalances. These results highlight the trade-offs between accuracy and computational efficiency, providing actionable insights for deploying automated defect detection systems to enhance PV system reliability and scalability. Full article

A theoretical and experimental evaluation was conducted on a prototype radiative flux homogenizer (HOFRAC) specifically designed for the Solar Furnace at Instituto de Energías Renovables (HoSIER) of Universidad Nacional Autónoma de México. The development of HOFRAC included three versions (HOFRAC-PRO, HOFRAC-PRI, and HOFRAC-PRIK); each iteration incorporated improvements based on theoretical modeling and experimental results. Evaluations were performed using ray-tracing simulations and experimental tests capturing radiative flux distribution images. The last two versions were used to characterize a densely packed photovoltaic array operated in the solar furnace. Some results of this study show that misaligned mirrors in the furnace were identified as the main problem in achieving a high flux uniformity degree for photovoltaic concentration applications. Full article

The rapid proliferation of photovoltaic (PV) solar cells as a clean energy source has raised significant concerns regarding their end-of-life (EoL) management, particularly in terms of sustainability and waste reduction. This review comprehensively examines challenges, opportunities, and future directions in the recycling of PV solar cells, focusing on mechanical, thermal, and chemical recycling techniques. It also evaluates the scalability and practicality of these methods to different PV technologies, including crystalline silicon and thin-film modules. It explores the economic and environmental impacts of these processes, highlighting the necessity of developing robust recycling infrastructure and innovative technologies to address the anticipated surge in PV waste. Additionally, this review discusses the critical role of government policies and industry collaboration in overcoming the barriers to effective recycling. Furthermore, the importance of integrating design-for-recyclability principles into PV module development is emphasized, as it can significantly enhance material recovery and process efficiency. By advancing these strategies, the solar industry can achieve greater sustainability, reduce resource depletion, and mitigate environmental risks, thereby ensuring the long-term viability of solar energy as a key component of global renewable energy initiatives. Full article

This study explores the potential for co-locating floating photovoltaics (FPVs) with existing hydropower plants (HPPs) in Ecuador. Ecuador’s heavy reliance on hydropower for electricity generation, combined with recent blackouts caused by prolonged dry seasons, underscores the importance of diversifying energy sources. The integration of FPVs with HPPs offers a promising opportunity to enhance energy security by reducing dependency on a single energy source and improving economic, electrical, and environmental outcomes. In this paper, we assess all HPPs in Ecuador and quantify the potential performance of FPV systems when installed at their sites. Our results show that FPV systems can not only contribute additional electricity to the grid but also improve HPP performance by reducing water evaporation from reservoirs and maintaining generation capacity during dry seasons, when solar irradiation is typically higher. To model the energy production, yield, and performance of the FPV systems, we applied RINA’s methodology to estimate representative weather conditions for each site and simulate FPV performance, accounting for system design loss factors. Additionally, we calculated the water savings resulting from FPV installation. Our findings reveal that, out of approximately 70 HPPs in Ecuador, 11 present favorable conditions for large-scale FPV deployment. Among these, Cumbayá HPP (40 MW) exhibited the most suitable conditions, supporting a maximum FPV capacity of 17 MWp. Marcel Laniado de Wind HPP (213 MW) and Mazar HPP (170 MW) were also identified as optimal candidates, each with potential FPV capacities equal to their installed HPP capacities. While this study primarily aims to provide scientific evidence on the potential of FPV-HPP co-location, the results and methodology can also guide Ecuadorian government authorities and investors in adopting FPV technology to strengthen the country’s energy infrastructure. Full article

In this work, we propose a simulation tool designed for the analysis and optimization of bifacial photovoltaic (PV) modules, which are currently under the spotlight in the renewable energy scenario. The tool is conceived to support researchers and engineers by providing fast and accurate predictions of the PV module yield under various operating and environmental conditions. For a chosen geographical site, the impact of module orientation, tilt, albedo, sky conditions, ambient temperature, and so on can be effortlessly determined. In case of nonuniformity across the cells dictated by localized architectural shading, dirt, bird drops, and defects, a circuit-based cell-level approach can be activated to compute the module production. An extensive simulation campaign is performed by assuming that the panels are installed in Naples without loss of generality. Results are shown to give detailed insights into the performance of bifacial modules, thus providing unambiguous guidelines for their correct installation. Further analyses are conducted to demonstrate the tool capability to quantify the detrimental influence of a poorly-irradiated cell on the backside, as well as of cracked cells. Full article

The conventional unidirectional power flow model of centralized energy grids is being revolutionized by integrating renewable energy sources, particularly photovoltaic (PV) systems, to meet the escalating demand for electricity while ensuring sustainability. However, this integration challenges the efficiency and performance of power systems and impacts various parameters, including power quality, voltage profile, power factor, power loss, and load flow. This paper investigates the effects and performance of a grid-tied PV system integrated into the conventional power system, focusing on the Palestine Polytechnic University (PPU) 230 kWp PV plant as a real-world case study. Simulations conducted using ETAP software revealed that integrating the PV system resulted in a slight increase in the voltage level at the main bus of the PPU feeder, with an increase of 0.03% at the medium-voltage level. Additionally, the voltage level at the Point of Common Coupling (PCC) increased by 0.51% with a PV penetration level of only 14.7%, which remains within the acceptable range according to IEEE 1547 standards. These findings underscore the minimal impact of the PV system on the voltage profile and highlight the system’s ability to maintain power quality and efficiency even with the addition of renewable energy sources. The daily load profiles were studied with and without the PV system, providing a comprehensive analysis of its effects on the grid. Full article

The degradation of solar photovoltaic (PV) modules over time, which are aggravated by defects, significantly affects the performance of utility-scale PV parks. This study presents a quantitative assessment of the power loss from module defects and evaluates the cost-effectiveness of replacing defective modules at various stages of degradation. A module test site was established in Norway with six different defects, and continuous thermographic monitoring, combined with light IV measurements and electroluminescence (EL) imaging, provides partial support for further calculations on the long-term effects of the defects. The cumulative module energy loss is calculated over a 25-year park lifespan under both Norwegian and Chilean environmental conditions, with the latter representing higher solar irradiation levels. The energy gain from replacing the defective modules at various stages of degradation is compared to the costs of replacement, both for infant-life failures and mid-life failures. It is likely not beneficial to replace minor infant-life defects of 1% power loss in low-irradiation regions like Norway. For Chilean conditions, it can be cost-effective, but primarily if the module is replaced around mid park life, which gives a larger yield when replaced with a new module. For more severe defects of 10% loss, the replacement gain is above the replacement cost for high-irradiation locations, and replacing the 33% power loss defect is cost-effective for both locations, even when discovered late in the park lifetime. It is primarily beneficial to replace mid-life defects in high-irradiation locations. Full article

This work analyses load profiles for East African microgrids, and then investigates the integration of electric two-wheelers and portable storage into a solar PV with battery microgrid in Uganda, East Africa. By introducing e-mobility and portable storage, demand side management strategic load growth can thus be achieved and electricity access can be expanded. Battery degradation is also considered. The results showed a 98.5% reduction in PV energy curtailment and a 57% reduction in the levelized cost of energy (LCOE) from 0.808 USD/kWh to 0.350 USD/kWh when the electric two-wheeler and portable storage loads were introduced. Such reductions are important enablers of financial viability and sustainability of microgrids. It is possible to avoid emissions of up to 73.27 tons of CO₂/year with the proposed e-bikes, and an average of 160 customers could be served annually as off-microgrid consumers without requiring an investment in additional distribution infrastructure. Annual revenue could be increased by 135% by incorporating the additional loads. Sensitivity analyses were conducted by varying component costs, the battery lifetime, the interest rate, and the priority weighting of the additional loads. The battery costs were found to be a major contributor to lifecycle costs (LCC) and also have a big impact on the LCOE. The interest rate significantly affects the LCC as well. Full article

The move toward sophisticated sensor networks in ecological applications requires a substantial amount of energy. Energy storage solutions based simply on batteries are often not sufficient to cover the energy needs, so a standalone power supply using solar energy harvesting is generally required. However, designing an appropriate solar power supply without oversizing and avoiding output power disruption all year long is not a trivial task. This paper provides a set of guidelines as well as useful information and advice for environmental researchers and other non-experts to select the right components when designing their own autonomous solar power supply for a range between 10 mW and 10 W. The design steps are compiled into a comprehensive document, free of irrelevant information yet still presenting a general overview of the solar power supply design process, in order to make this task more accessible and understandable for non-experts. The methodology for simple initial dimensioning was carried out and applied to a real-life use case by using the estimated or measured daily consumption combined with free meteorological data of the deployment site provided by various websites. Next, an hourly simulation completed the first sizing. A year of experimental results validated the methodology. Full article

This paper focuses on the analytical modeling of albedo reflection in bifacial photovoltaic modules, with particular emphasis on the backside. First, we critically examine the approaches proposed in the literature, presenting them with a tutorial style and a uniform nomenclature. These approaches are demonstrated to yield physically meaningless results, as they erroneously assume that the ground area shaded by the module acts as a source of reflected irradiance independent of the portion of sky dome visible to such an area. Then we introduce a correction based on the view factor between the shaded area and the sky. The result is a comprehensive and accurate analytical model that also describes the case of suspended panels and can be easily implemented into PV plant simulators. Full article

This study presents an advanced defect detection approach for solar cells using the YOLOv10 deep learning model. Leveraging a comprehensive dataset of 10,500 solar cell images annotated with 12 distinct defect types, our model integrates Compact Inverted Blocks (CIBs) and Partial Self-Attention (PSA) modules to enhance feature extraction and classification accuracy. Training on the Viking cluster with state-of-the-art GPUs, our model achieved remarkable results, including a mean Average Precision (mAP@0.5) of 98.5%. Detailed analysis of the model’s performance revealed exceptional precision and recall rates for most defect classes, notably achieving 100% accuracy in detecting black core, corner, fragment, scratch, and short circuit defects. Even for challenging defect types such as a thick line and star crack, the model maintained high performance, with accuracies of 94% and 96%, respectively. The Recall–Confidence and Precision–Recall curves further demonstrate the model’s robustness and reliability across varying confidence thresholds. This research not only advances the state of automated defect detection in photovoltaic manufacturing but also underscores the potential of YOLOv10 for real-time applications. Our findings suggest significant implications for improving the quality control process in solar cell production. Although the model demonstrates high accuracy across most defect types, certain subtle defects, such as thick lines and star cracks, remain challenging, indicating potential areas for further optimization in future work. Full article

A novel spectral-corrected Performance Ratio calculation method that aligns the short-term Performance Ratio calculation to the annual calculated Performance Ratio is presented in this work. The spectral-corrected Performance Ratio allows short-term measurements to reasonably estimate the annual Performance Ratio, which decreases the need for long-term measures and data storage and assists with routine maintenance checkups. The piece-wise empirical model incorporates two spectral variables, a geographical location-based variable, the air mass, a PV-technology-based variable, and a newly defined spectral correction factor that results in a universal application. The spectral corrections show significant improvements, resulting in errors across different air mass and clearness index ranges, as well as temporal resolutions. The results indicate that a spectral correction methodology is possible and a viable solution to estimate the annual Performance Ratio. The results further indicate that by correcting the spectrum, short-term measurements can be used to predict the annual Performance Ratio with superior performance compared to the well-known normal and weather-corrected PR calculation methods. This approach is the first documented effort to address the spectrum’s influence on the utility-scale Performance Ratio calculation from hourly measurements. The empirical formula suggested for the Performance Ratio calculation can be of extreme value for the real-time monitoring of PV systems and enhancing PV power forecasting accuracy when the spectrum is considered instead of its usual omission. The model can be universally applicable, as it incorporates location and technology, marking a groundbreaking start to comprehending and incorporating the spectral influence in utility-scale PV systems. The novel calculation has widespread application in the PV industry, performance modelling, monitoring, and forecasting. Full article

This paper reports on the correlation between broken contact fingers and the shape of the current–voltage (I–V) curve of a photovoltaic (PV) module. It was found that the broken contact fingers of a solar cell in the PV module cause a noticeable change in the I–V curve of the PV module when the solar cell was partially shaded. The broken contact fingers were inspected by microscopic imaging and electroluminescence (EL) imaging, and a further investigation was carried out using a single solar cell. The results show that the fill factor of the cell decreased from 0.75 of full contact to 0.47 after 16 contact fingers were broken, confirming the correlation between the I–V curve shape and broken contact fingers. This result reveals that the shape of the I–V curve of a PV module under individual-cell partial shading may be used as an indicator of broken contact fingers, which offers an alternative approach to EL imaging for detecting broken contact fingers in PV modules in daylight. Full article

The optimization of photovoltaic (PV) systems is vital for enhancing efficiency and economic viability, especially under Partial Shading Conditions (PSCs). This study focuses on the development and comparison of traditional and advanced algorithms, including Perturb and Observe (P&O), Incremental Conductance (IC), Fuzzy Logic Control (FLC), Grey Wolf Optimization (GWO), Particle Swarm Optimization (PSO), and Artificial Neural Networks (ANN), for efficient Maximum Power Point Tracking (MPPT). Simulations conducted in the MATLAB/Simulink software package evaluated these algorithms’ performances under various shading scenarios. The results indicate that, while traditional methods like P&O and IC are effective under uniform conditions, advanced techniques, particularly ANN-based MPPT, exhibit superior efficiency and faster convergence under PSCs. This study concludes that integrating Artificial Intelligence (AI) and Machine Learning (ML) into MPPT algorithms significantly enhances the reliability and efficiency of PV systems, paving the way for a broader adoption of solar energy technologies in diverse environmental conditions. These findings contribute to advancing renewable energy technology and supporting green energy transition. Full article