Solar, Volume 5, Issue 1 (March 2025) – 9 articles

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 [email protected] (93.4%), demonstrating a balanced performance across the defect categories. Despite the strong performance for common defects like dusty panels ([email protected] > 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