Solar

Jordan faces significant, immediate challenges of enhancing energy security while mitigating greenhouse gas emissions. One of the most promising approaches to achieve sustainable development, energy security, and environmental conservation is to increase the integration of renewable energy into electricity generation. To this end, the Jordanian government aims to expand investments in the green energy sector, with solar and wind energy expected to play a crucial role in meeting energy demands and promoting environmental sustainability. This paper aims to examine the distinct dynamics, challenges, obstacles, and potential solutions related to establishing community solar and wind farms in suburban areas of Jordan. It seeks to highlight the opportunities and barriers influencing the adoption of sustainable energy in the country. Evaluation results from engaging 320 key stakeholders were obtained through a questionnaire, and after comprehensive analysis, it became evident that the benefits and positive aspects of solar and wind farms outweigh their drawbacks and obstacles. These insights can be useful in guiding policies and practices to make renewable energy community projects a reality within Jordan’s suburban areas. Additionally, the findings may serve as a valuable benchmark for other regions facing similar challenges in their pursuit of a sustainable energy future. Full article

This research develops and validates new decomposition models for hourly direct Normal Irradiance (DNI) estimations for Southern African data. Localised models were developed using data collected from the Southern African Universities Radiometric Network (SAURAN). Clustered areas within Southern Africa were identified, and the developed cluster decomposition models highlighted the potential advantages of grouping data based on shared geographical and climatic attributes. This clustering approach could enhance decomposition model performance, particularly when local data are limited or when data are available from multiple nearby stations. Further, a regional Southern African decomposition model, which encompasses a wide spectrum of climatic regions and geographic locations, exhibited notable improvements over the baseline models despite occasional overestimation or underestimation. The results demonstrated improved DNI estimation accuracy compared to the baseline models across all testing and validation datasets. These outcomes suggest that utilising a localised model can significantly enhance DNI estimations for Southern Africa and potentially for developing similar models in diverse geographic regions worldwide. The overall metrics affirm the substantial advancement achieved with the regional model as an accurate decomposition model representing Southern Africa. Two stations were used as a validation study, as an application example where no localised model was available, and the cluster and regional models both outperformed the comparative decomposition models. This study focused on validating the model for hourly DNI in Southern Africa within a range of $K_t$-intervals from 0.175 to 0.875, and the range could be expanded and validated for future studies. Implementing accurate decomposition models in developing countries can accelerate the adoption of renewable energy sources, diminishing reliance on coal and fossil fuels. Full article

Maryland is actively working towards doubling its Renewable Portfolio Standard (RPS) target, aiming to increase the share of renewable energy from 25% by 2020 to 50% by 2030. Furthermore, Maryland stands out as a state that strongly supports solar initiatives, offering incentives and specialized programs to assist residents in adopting solar energy solutions. The paper presents a multi-stage approach: Stage 1—Location Selection Process, Stage 2—Technical Feasibility Study, and Stage 3—Economical Feasibility Study. In Stage 1, the study focuses on three potential solar farm locations in Maryland: Westover, Princess Anne, and Eden. Stages 2 and 3 involve a feasibility assessment with detailed technical analysis using the NREL System Advisor Model (SAM) and PVWatts to determine monthly power to the grid and Energy Yield. Subsequently, economic feasibility is assessed using the NREL Clean Renewable Energy Estimation Simulation Tool (CREST), focusing on competitive levelized costs of energy (LCOE), payback time, and cumulative cash flows. Results indicate that all three locations exhibit promising solar irradiance levels, system outputs, and potential energy yields. Due to high solar irradiation, the Westover area has the highest energy yield at 1583.13 kWh/kW, while Princess Anne boasts the highest system output at 333.59 GWh. The economic evaluation suggests that all three locations become profitable within a two-year payback time, with competitive levelized costs of energy (LCOE). Westover emerges as the most cost-effective option at 5.99 cents/kWh, attributed to its higher solar irradiation values and energy yield compared to Princess Anne and Eden. Cumulative cash flows provide insights into long-term profitability, with Princess Anne, MD, having the highest Cumulative Cash Flow over 25 years at $183,383,304. By evaluating technical and economic aspects, this feasibility study offers quantitative insights to guide decision-making for the installation of Solar PV, considering both technological and economic feasibility. Full article

In this study, the sizing problem of hybrid diesel–photovoltaic–battery systems was determined using a particle swarm optimization approach. The goal was to optimize the number of solar panels and batteries that could be installed to reduce the overall cost of an isolated grid system, originally powered by diesel generators, located on Isabela Island in the Galapagos, Ecuador. In this study, real solar radiation and temperature profiles were used, as well as the load demand and electrical distribution system relative to this island. The results reveal that the total cost for the proposed approach is lower as it reaches the global optimal solution. It also highlights the advantage of a hybrid diesel–photovoltaic–battery (DG-PV-BAT) system compared to conventional systems operated exclusively by diesel generators (DGs) and systems made up of DGs and PV panels; compared to them, a reduction in diesel consumption and total cost (71% and 56%, respectively) is achieved. The DG-PV-BAT system also considerably improves environmental factors and the quality of the power line. This study demonstrates the advantages of hybridizing systems isolated from the network through the proposed approach. Full article

The tandem solar cell presents a potential solution to surpass the Shockley–Queisser limit observed in single-junction solar cells. However, creating a tandem device that is both cost-effective and highly efficient poses a significant challenge. In this study, we present proof of concept for a four-terminal (4T) tandem solar cell utilizing a wide bandgap (1.6–1.8 eV) perovskite top cell and a narrow bandgap (1.2 eV) antimony selenide (Sb₂Se₃) bottom cell. Using a one-dimensional (1D) solar cell capacitance simulator (SCAPS), our calculations indicate the feasibility of this architecture, projecting a simulated device performance of 23% for the perovskite/Sb₂Se₃ 4T tandem device. To validate this, we fabricated two wide bandgap semitransparent perovskite cells with bandgaps of 1.6 eV and 1.77 eV, respectively. These were then mechanically stacked with a narrow bandgap antimony selenide (1.2 eV) to create a tandem structure, resulting in experimental efficiencies exceeding 15%. The obtained results demonstrate promising device performance, showcasing the potential of combining perovskite top cells with the emerging, earth-abundant antimony selenide thin film solar technology to enhance overall device efficiency. Full article

We consider the restrictions on photovoltaic (PV) capacity that are caused by limitations on where panels can be sited and find quantitative evidence for the need for high efficiencies. We define 15% of the UK’s energy consumption as a “significant” contribution and, with London as an exemplar, we perform an idealised calculation that makes the most optimistic possible assumptions about the capabilities of future PV technologies and use published surveys on energy usage, dwelling type and insolation. We find that covering every UK domestic roof with the highest power conversion efficiency (PCE) solar panels currently commercially available could produce up to 9% of the UK’s energy. A 15% contribution would require PV technologies with >37% PCE, more than the theoretical Shockley–Queisser limit. Replacing the idealising assumptions with more realistic estimates increases this by 2–3 times. Alternatively, a solar farm using the currently available PCEs would require a politically challenging ~1200 km² of new land, roughly the area of Greater London, for this 15% contribution. We conclude that PCEs must be driven higher than even the Shockley–Queisser limit for PV to play a significant part in carbon mitigation. Full article

Integrating photovoltaic (PV) systems plays a pivotal role in the global shift toward renewable energy, offering significant environmental benefits. However, the PV installation should provide financial benefits for the utilities. Considering that the utility companies often incur costs for both energy and peak demand, PV installations should aim to reduce both energy and peak demand charges. Although PV systems can reduce energy needs during the day, their effectiveness in reducing peak demand, particularly in the early morning and late evening, is limited, as PV generation is zero or negligible at those times. To address this limitation, battery storage systems are utilized for storing energy during off-peak hours and releasing it during peak times. However, finding the optimal size of PV and the accompanying battery remains a challenge. While valuable optimization models have been developed to determine the optimal size of PV–battery systems, a certain gap remains where peak demand reduction has not been sufficiently addressed in the optimization process. Recognizing this gap, this study proposes a novel statistical model to optimize PV–battery system size for peak demand reduction. The model aims to flatten 95% of daily peak demands up to a certain demand threshold, ensuring consistent energy supply and financial benefit for utility companies. A straightforward and effective search methodology is employed to determine the optimal system sizes. Additionally, the model’s effectiveness is rigorously tested through a modified Monte Carlo simulation coupled with time series clustering to generate various scenarios to assess performance under different conditions. The results indicate that the optimal PV–battery system successfully flattens 95% of daily peak demand with a selected threshold of 2000 kW, yielding a financial benefit of USD 812,648 over 20 years. Full article

Nanocrystalline silicon oxide (nc-SiOx:H) is a multipurpose material with varied applications in solar cells as a transparent front contact, intermediate reflector, back reflector layer, and even tunnel layer for passivating contacts, owing to the easy tailoring of its optical properties. In this work, we systematically investigate the influence of the gas mixture (SiH₄, CO₂, PH₃, and H₂), RF power, and process pressure on the optical, structural, and passivation properties of thin n-type nc-SiOx:H films prepared in an industrial, high-throughput, plasma-enhanced chemical vapor deposition (PECVD) reactor. We provide a detailed description of the n-type nc-SiOx:H material development using various structural and optical characterization techniques (scanning electron microscopy (SEM), energy dispersive X-ray (EDX), Raman spectroscopy, and spectroscopic ellipsometry) with a focus on the relationship between the material properties and the passivation they provide to n-type c-Si wafers characterized by their effective carrier lifetime (τ_eff). Furthermore, we also outline the parameters to be kept in mind while developing different n-type nc-SiOx:H layers for different solar cell applications. We report a tunable optical gap (1.8–2.3 eV) for our n-type nc-SiOx:H films as well as excellent passivation properties with a τ_eff of up to 4.1 ms (implied open-circuit voltage (iV_oc)~715 mV) before annealing. Oxygen content plays an important role in determining the crystallinity and hence passivation quality of the deposited nanocrystalline silicon oxide films. Full article

This paper presents a comprehensive and systematic review of virtual reality (VR) as an innovative educational tool specifically for solar photovoltaic energy systems. VR technology, with its immersive and interactive capabilities, offers a unique platform for in-depth learning and practical training in the field of solar energy. The use of VR in this context not only enhances the understanding of solar photovoltaic (PV) systems but also provides a hands-on experience that is crucial for developing the necessary skills in this rapidly evolving field. Among the 6814 articles initially identified, this systematic review specifically examined 15 articles that focused on the application of VR in PV education. These selected articles demonstrate VR’s ability to accurately simulate real-world environments and scenarios related to solar energy, providing an in-depth exploration of its practical applications in this field. By offering a realistic and detailed exploration of PV systems, VR enables learners to gain a deeper understanding of harnessing, managing and using such a vast energy resource. The paper further discusses the implications of employing VR in educational settings, highlighting its potential to change the way solar energy professionals are trained, thereby contributing significantly to the acceleration of photovoltaic technology adoption and its integration into sustainable energy solutions. Full article

Solar energy forecasting is essential for the effective integration of solar power into electricity grids and the optimal management of renewable energy resources. Distinguishing itself from the existing literature, this review study provides a nuanced contribution by centering on advancements in forecasting techniques. While preceding reviews have examined factors such as meteorological input parameters, time horizons, the preprocessing methodology, optimization, and sample size, our study uniquely delves into a diverse spectrum of time horizons, spanning ultrashort intervals (1 min to 1 h) to more extended durations (up to 24 h). This temporal diversity equips decision makers in the renewable energy sector with tools for enhanced resource allocation and refined operational planning. Our investigation highlights the prominence of Artificial Intelligence (AI) techniques, specifically focusing on Neural Networks in solar energy forecasting, and we review supervised learning, regression, ensembles, and physics-based methods. This showcases a multifaceted approach to address the intricate challenges associated with solar energy predictions. The integration of Satellite Imagery, weather predictions, and historical data further augments precision in forecasting. In assessing forecasting models, our study describes various error metrics. While the existing literature discusses the importance of metrics, our emphasis lies on the significance of standardized datasets and benchmark methods to ensure accurate evaluations and facilitate meaningful comparisons with naive forecasts. This study stands as a significant advancement in the field, fostering the development of accurate models crucial for effective renewable energy planning and emphasizing the imperative for standardization, thus addressing key gaps in the existing research landscape. Full article

In recent years, research attention has increasingly focused on thin-film photovoltaics utilizing Sb₂Se₃ as an ideal absorber layer. This compound is favored due to its abundance, non-toxic nature, long-term stability, and the potential to employ various cost-effective and scalable vapor deposition (PVD) routes. On the other hand, improving passivation, surface treatment and p-type carrier concentration is essential for developing high-performance and commercially viable Sb₂Se₃ solar cells. In this study, Cu-doped Sb₂Se₃ solar devices were fabricated using two distinct PVD techniques, pulsed electron deposition (PED) and radio frequency magnetron sputtering (RFMS). Furthermore, 5%Cu:Sb₂Se₃ films grown via PED exhibited high open-circuit voltages (V_OC) of around 400 mV but very low short-circuit current densities (J_SC). Conversely, RFMS-grown Sb₂Se₃ films resulted in low V_OC values of around 300 mV and higher J_SC. To enhance the photocurrent, we employed strategies involving a thin NaF layer to introduce controlled local doping at the back interface and a bilayer p-doped region grown sequentially using PED and RFMS. The optimized Sb₂Se₃ bilayer solar cell achieved a maximum efficiency of 5.25%. Full article

With the global increase in the deployment of photovoltaic (PV) modules in recent years, the need to explore and understand their reported failure mechanisms has become crucial. Despite PV modules being considered reliable devices, failures and extreme degradations often occur. Some degradations and failures within the normal range may be minor and not cause significant harm. Others may initially be mild but can rapidly deteriorate, leading to catastrophic accidents, particularly in harsh environments. This paper conducts a state-of-the-art literature review to examine PV failures, their types, and their root causes based on the components of PV modules (from protective glass to junction box). It outlines the hazardous consequences arising from PV module failures and describes the potential damage they can bring to the PV system. The literature reveals that each component is susceptible to specific types of failure, with some components deteriorating on their own and others impacting additional PV components, leading to more severe failures. Finally, this review briefly summarises PV failure detection techniques, emphasising the significance of electrical characterisation techniques and underlining the importance of considering more electrical parameters. Most importantly, this review identifies the most prevalent degradation processes, laying the foundation for further investigation by the PV research community through modelling and experimental studies. This allows for early detection by comparing PV performance when failures or degradation occur to prevent serious progression. It is worth noting that most of the studies included in this review primarily focus on detailing failures and degradation observed in PV operations, which can be attributed to various factors, including the manufacturing process and other external influences. Hence, they provide explanations of these failure mechanisms and causes but do not extensively explore corrective actions or propose solutions based on either laboratory experiments or real-world experience. Although, within this field of study, there are corresponding studies that have designed experiments to suggest preventive measures and potential solutions, an in-depth review of those studies is beyond the scope of this paper. However, this paper, in turn, serves as a valuable resource for scholars by confining PV failures to critically evaluate available studies for preventative measures and corrective actions. Full article

Food waste is one of the biggest challenges we are facing nowadays. According to the Food and Agriculture Organization (FAO) of the United Nations, approximately one-third of all food produced in the world is lost at some stage between production and consumption, totaling 930 million tons of food per year. Meanwhile, 10.5% of humanity suffers from malnutrition, 26% are overweight and greenhouse gases derived from the food industry account for between 25 and 30% of total emissions (8 to 10% referring to food waste), exacerbating the current climate crisis. To address these concerns, there has been a growing inclination to seek alternatives to fossil fuels, including the adoption of solar energy across diverse sectors, including the food industry. Actions are needed in order to change these patterns. This review article aims to provide an overview of recent developments in the field of solar food dehydration and the types of dehydrators that have emerged. Extensive research and bibliographic analysis, including other review articles, have revealed a growing focus on investment in this area to develop solar dehydrators that are increasingly effective but as sustainable as possible. Full article

Renewable energy sources, distributed generation, multi-energy carriers, distributed storage, and low-temperature district heating systems, among others, are demanding a change in the way thermal networks are conceived, understood, and operated. Governments around the world are moving to increase the renewable share in energy distribution networks through legislation like the European Directive 2012/27 in Europe, and solar energy integration into district heating systems is arising as an interesting option to reduce operation costs and carbon footprint. This conveys an important investment that adds complexity to the management of thermal networks and often delays the return on investment due to the unpredictability of renewable energy sources, like solar radiation. To this end, this paper presents an optimisation methodology to aid in the operative control of an existing solar district heating system located in the northwest of France. The modelling of the system, which includes a large-scale solar field, a biomass boiler, a gas boiler, and thermal energy storage, was previously built in Dymola. The optimisation of this network was performed using MATLAB’s genetic algorithm (GA) and running the Dymola model as functional mock-up units, FMUs, using Simulink’s FMI Kit. The results show that the methodology presented here can reduce the current operation costs and improve the use of the daily storage of the DH system by a combination of mass flow control and the implementation of a flexibility function for the end-users. The cost-per-kWh was reduced by as much as 16% in a single day, and the share of heat supplied by the solar field on this day was increased by 5.22%. Full article

Detection of cracks in solar photovoltaic (PV) modules is crucial for optimal performance and long-term reliability. The development of convolutional neural networks (CNNs) has significantly improved crack detection, offering improved accuracy and efficiency over traditional methods. This paper presents a comprehensive review and comparative analysis of CNN-based approaches for crack detection in solar PV modules. The review discusses various CNN architectures, including custom-designed networks and pre-trained models, as well as data-augmentation techniques and ensemble learning methods. Additionally, challenges related to limited dataset sizes, generalizability across different solar panels, interpretability of CNN models, and real-time detection are discussed. The review also identifies opportunities for future research, such as the need for larger and more diverse datasets, model interpretability, and optimized computational speed. Overall, this paper serves as a valuable resource for researchers and practitioners interested in using CNNs for crack detection in solar PV modules. Full article

Qatar’s ambitious Vision 2030 includes a major shift towards clean energy, and residential solar PV installation can be an obvious option, given its abundant sunlight and high power for residential cooling. Despite significant solar panel farm investment, there has been limited progress in deploying solar panels on home roofs, and further research is needed to identify the potential for such an initiative and its impact on the country’s move towards clean energy. This field survey assesses the potential for residential rooftop solar panel installation across Qatar, considering space availability, currently utilized space, remaining space, shading, and roof type. It also provided indications of potential obstacles and shading that might affect panel sunlight exposure. The results showed that there is significant potential for installing solar panels on Qatari homes, which could contribute to a considerable portion of the energy consumed by households during peak usage periods, particularly in the summer months. Moreover, excess energy generated could be exported to other countries with high demand during periods of low demand in Qatar. The study’s findings complement previous research efforts and provide insights for policymakers and stakeholders to develop strategies that endorse the vision for 2030 and promote the transition towards clean energy in Qatar. Full article

Africa has abundant solar resources but only 2% of its current capacity is generated from renewable sources. Photovoltaics (PV) offer sustainable, decentralized electricity access to meet development needs. This review synthesizes the recent literature on PV in Africa, with a focus on Mozambique. The 10 most cited studies highlight the optimization of technical components, such as storage and bifacial modules, and challenges in integrating large-scale PV. Case studies demonstrated Mozambique’s potential for PV applications in water heating, irrigation, and rural electrification. These benefits include reduced emissions and energy access. However, barriers, such as high costs, lack of infrastructure, and training, exist. While solar cookers are insufficient, thermal systems have unrealized potential. Mozambique’s urban and rural electrification rates are 57% and 13%, respectively, despite its energy resources. Targeted policies, financing, and community engagement are essential for promoting adoption. While PV can sustainably expand electricity access, coordinated efforts must address costs, infrastructure, maintenance, and social factors for successful implementation. Mozambique has immense solar potential, but strategic planning and support are critical to unlocking these benefits. This review provides insights into optimizing PV systems and policy frameworks for a clean and inclusive energy production future in Africa, to synthesize the 10 most cited studies on photovoltaic solar energy in Africa, and to deeply reflect upon the current energy needs in Mozambique, the benefits of employing PV and solar thermal systems, and the challenges of implementing such systems within the Mozambican context. Full article

This study combines simulations and experiments to study the heat interactions between various types of roofs and the photovoltaic (PV) modules installed on them. Specifically, the performance of PV modules on a clay roof was compared with their performance on two types of metal roofs, a Box-profile metal roof and an Orientile metal roof, which differ in shape and geometry. Additionally, this study examined the cooling potential of three common metal roof pigments, iron (iii) oxide (Fe₂O₃), titanium dioxide (TiO₂) and basalt, on roof-installed PV modules. An unpigmented roof was also studied for comparison purposes. Model development and simulation were implemented in COMSOL Multiphysics, and the simulation results were validated and compared with field experiments. The maximum open-circuit voltages of the PV installations were found to be 21.096 V for the clay roof, 20.945 V for the Box-profile metal roof and 20.718 V for the Orientile metal roof. This study revealed that the unpigmented roof had higher solar cell temperatures compared to the pigmented models, with temperature gains ranging from 2.2 °C to 2.71 °C. Moreover, the unpigmented model displayed significantly higher surface radiosity than the pigmented models. The performance output of the modules also varied depending on the metal roof sheet shape and geometry, with the Box-profile metal roof yielding better results than the Orientile metal roof sheet. These results indicate that a specific roof pigmentation may have a small impact on a single PV module, but it can become significant in a large array of modules, especially if cooling through natural convection is hindered. Full article

A review of quality control for large irradiance datasets is applied as a case study for the Southern African Universities Radiometric Network (SAURAN) database. The quality control procedure is automated and applied to 24 stations from the database with a total of 848,189 hourly datapoints. From this, the individual station’s data quality is also analysed. The assessment validates the automated methodology without the need for a user-based review of the data. The SAURAN database can play a significant role in advancing solar and wind energy; however, the number of offline stations hinders this process. Data scarcity remains an obstacle to these goals, and therefore, recommendations are provided to address this. Recommendations regarding each site’s usability in time-series and discrete applications are made, which provides an overall indication of the SAURAN database’s irradiance measurement quality. Of the 24 measuring stations assessed, eight are recommended, 11 are recommended with cautious use, and five are recommended with extremely cautious use. These recommendations are based on multiple factors, such as whether a dataset has more than one full year of data or is missing minimal datapoints. Further, a study of the irradiance correlation between the stations was conducted. The results indicated groupings of different stations that showed highly correlated irradiance measurements and similar weather patterns. This is useful if a proposed renewable energy power plant, such as PV, falls within a cluster where the data from the SAURAN database can be used as a substitute if no data is available. SAURAN presents an opportunity for Southern Africa to increase its research outputs in solar and wind energy and lessen its dependency on fossil fuel-based energy production. Full article