Solar

In response to the growing need for accurate forecasting of electricity generation from PV installations, which is crucial both for enhancing self-consumption and for balancing the power grid, this study presents a comparative analysis of selected machine learning models. The research focuses on the XGBoost algorithm and LSTM neural networks, applied to predict PV energy production based on meteorological data and historical generation records from four medium-sized PV installations (30–50 kWp) located in Poland. Meteorological data were retrieved from open sources and combined with actual production measurements to build the training dataset. This paper discusses the challenges posed by these data at the given latitude, as well as issues related to processing data from newly launched installations. The performance of both approaches was evaluated in short- and medium-term forecasting, with particular attention to prediction accuracy, robustness to noisy data, and the ability to capture nonlinear relationships. Full article

Accurate prediction of the energy yield of bifacial photovoltaic (PV) modules requires a proper evaluation of albedo irradiance and the associated mismatch losses. In this work, an advanced tool for the assessment of the power production of bifacial modules is presented. The tool benefits from a refined numerical evaluation of ground-reflected irradiance performed through a view-factor-based cell-level approach within a realistic three-dimensional (3D) Sun-module-shadow geometry. This allows capturing both vertical and lateral nonuniformities in the irradiance distributions over the module surfaces, which are neglected in conventional module-level models. The irradiances incident on the cells are subsequently supplied to a circuit-based block, operating with a cell-level granularity as well, which computes the I–V characteristics and the maximum power point (MPP) at selected time instants. Simulations performed on a simplified tool variant assuming uniform albedo irradiance show that this approximation leads to a non-negligible overestimation of power output. An extensive comparison against state-of-the-art tools, including the previous version of our framework, allows us to conclude that the proposed method is especially advantageous for standalone modules or short-row configurations under medium-to-high albedo conditions. Moreover—like its previous version—the tool can handle a large variety of detrimental effects, namely, partial architectural shading, localized snow coverage, bird droppings, and faulty cells. Additionally, a non-zero elevation from the ground can be effectively described. It is also found that south-oriented 30°-tilted bifacial modules suffer from appreciable albedo-induced mismatch losses on the rear surface during summer under medium-albedo conditions, whereas vertically-mounted West- and East-oriented configurations are less affected by such losses. Experimental validation confirms the accuracy of the proposed framework. Full article

Façade-integrated solar cooling technologies enable the utilisation of façade surface potential and the provision of resilient cooling. This work compares three solar cooling scenarios, positioning a solar cooling element in the west and east façades. The 2ACE scenario is based on a compact adsorption cooling concept, while the 2PV scenario directly drives a compression chiller with photovoltaic elements, and 2PVB incorporates an additional battery. All Modelica system models are implemented in Modelon Impact and operated using dynamic optimisation for the hottest day of the year. Results indicate that the 2ACE scenario, utilising the adsorbent Silica Gel SG123, achieves near to double the self-sufficiency compared to Zeolite 13X. No clear optimal area balance between west and east elements is apparent. The 2PV scenario only surpasses the 2ACE scenario’s self-sufficiency with increased total element area, whereas 2PVB enables a drastic increase and complete self-sufficiency. This highlights the limitation of the adsorption cooling scenario due to its inability to compensate for ventilation’s electrical energy consumption. However, photovoltaic scenarios are heavily reliant on the assumed energy efficiency ratio. Additionally, slender buildings with a low AV ratio require less façade area to achieve the same self-sufficiency level as wider buildings. Full article

Achieving meaningful reductions in residential heating demand requires design strategies that can respond to climate-specific solar availability and envelope performance. Although passive solar principles are well established, their effectiveness remains highly context-dependent, and simplified prescriptive approaches may not capture interactions across different climates. This study presents an AI-guided evolutionary optimization framework for passive solar residential design, focusing exclusively on the reduction in annual space heating demand under standardized assumptions. A standardized single-story residential prototype is simulated across three climatic contexts: hot–dry (Riyadh), temperate (Barcelona), and cold (Toronto). Dynamic building performance simulations are conducted using EnergyPlus, coupled with DesignBuilder’s built-in Non-Dominated Sorting Genetic Algorithm II (NSGA-II) evolutionary optimization engine. Envelope-related variables, including the window-to-wall ratio, orientation, glazing configuration, and thermal mass, are optimized with a single objective: minimizing the annual heating load under idealized heating conditions. The results demonstrate substantial climate-dependent reductions in heating demand. In Toronto, the annual heating demand is reduced from approximately 16,900 kWh to 9600 kWh (≈43%). In Barcelona, a reduction from approximately 5650 kWh to 1990 kWh (≈65%) is achieved, while in Riyadh, heating demand is reduced from approximately 990 kWh to 39 kWh (>95%). The optimized solutions reveal distinct climate-specific design logic rather than universal passive rules. The results demonstrate that evolutionary optimization can support early-stage envelope design by revealing climate-specific heating strategies under clearly defined and comparable assumptions. Full article

This paper investigates the integration of on-site photovoltaic (PV) systems in the industrial sector under a zero feed-in configuration, where all generated electricity is consumed locally without export to the grid. The analysis follows the current Greek regulatory framework and uses real operating data from an insulation materials manufacturing plant. Twelve months of measured electricity demand were combined with Typical Meteorological Year (TMY) solar data to simulate PV systems of 500, 1000, 1500, and 2000 kWp. Annual PV production ranges from approximately 739 MWh (500 kWp) to 2970 MWh (2000 kWp), and it is all fully self-consumed by the factory due to its high and continuous load. However, given the plant’s large annual electricity use, the PV systems offset 1.0–2.8% of total consumption. The avoided grid purchases correspond to 40–160 MWh/year of net energy savings, delivering positive Net Present Value (NPV) when electricity tariffs exceed EUR 0.15/kWh. The results confirm that zero feed-in PV deployment is technically feasible and economically attractive for industrial facilities facing high electricity prices, while also enhancing sustainability by reducing dependency on the public grid. Full article

Recent advances in design, manufacturing and development techniques have been very relevant to making solar collectors feasible for production in a variety of applications. In the field of concentrated solar thermal technologies, several techniques have been developed to achieve high levels of radiation concentration. The generation of concave curvature geometry through the polishing of the reflective surface or through specialized machining is one of the most common methods. However, the way in which these bends are obtained can vary significantly, depending on the required quality of optical concentration for the application. This study presents a simple parametric technique to achieve a parabolic curvature for solar concentration applications. To do this, a controlled bending deformation was applied to a metal hollow profile beam supported by a pin and roller at each of the ends, and only two symmetric point loads were applied to generate a bending moment to induce a bending of a curved shape. It was found that, for a given load configuration, a parabolic geometry was generated along a partial center section of the beam. The analysis carried out showed that under the load configuration analyzed, up to 66% of the beam length adopted a fully parabolic geometry. The technique proposed in this work allows for the creation of parabolas with variable focal distances, offering versatility in the design of solar concentrating systems. It also allows corrective adjustments to be made during the assembly of the complete solar concentrator system. Full article

This study aimed to evaluate the thermal performance and operational behavior of an evacuated-tube solar collector field installed in a coastal hotel under real industrial conditions. The work analyzed temperature, irradiance, and mass-flow data to determine instantaneous efficiency and identify performance deterioration associated with fouling. A multivariable regression model was developed to predict collector efficiency as a function of operating parameters. The results showed an average efficiency of 40–55%, with a noticeable decrease attributed to soiling effects. The methodology and findings contribute to improving monitoring-based maintenance strategies and optimizing the energy performance of large-scale domestic hot-water systems. Full article

CPVG (Utility-scale photovoltaic generation) is expanding rapidly worldwide, yet its cumulative ecological effects remain insufficiently quantified. This review synthesizes current evidence to clarify how CPVG influences ecosystems through linked mechanisms of energy redistribution, biogeochemical cycling disturbance, and ecological responses. CPVG alters surface radiation balance, modifies microclimate, and disrupts carbon–nitrogen–water fluxes, thereby driving vegetation shifts, soil degradation, and biodiversity decline. These impacts accumulate across temporal scales—from short-term construction disturbances to long-term operational feedbacks—and propagate spatially from local to regional and watershed levels. Ecological outcomes differ substantially among deserts, grasslands, and agroecosystems due to contrasting resilience and limiting factors. Based on these mechanisms, we propose a multi-scale cumulative impact assessment framework integrating indicator development, multi-source monitoring, coupled modelling, and ecological risk tiering. A full-chain mitigation pathway is further outlined, emphasizing optimized siting, disturbance reduction, adaptive management, and targeted restoration. This study provides a systematic foundation for evaluating and regulating CPVG’s cumulative ecological impacts, supporting more sustainable solar deployment. Full article

Smart microgrids are localized energy systems that integrate distributed energy resources, such as photovoltaics (PVs) and battery storage, to optimize energy use, enhance reliability, and minimize environmental impacts. This paper investigates the operation of a smart microgrid installed at the Hellenic Mediterranean University (HMU) campus in Heraklion, Crete, Greece. The system, consisting of PVs and battery storage, operates under a zero feed-in scheme, which maximizes on-site self-consumption while preventing electricity exports to the main grid. With increasing PV penetration and growing grid congestion, this scheme is an increasingly relevant strategy for microgrid operations, including university campuses. A properly sized PV–battery microgrid operating under zero feed-in operation can remain financially viable over its lifetime, while additionally it can achieve significant environmental benefits. The study performed at the HMU Campus utilizes measured hourly data of load demand, solar irradiance, and ambient temperature, while PV and battery components were modeled based on real technical specifications. The study evaluates the system using financial and environmental performance metrics, specifically net present value (NPV) and annual greenhouse gas (GHG) emission reductions, complemented by sensitivity analyses for battery technology (lead–carbon and lithium-ion), load demand levels, varying electricity prices, and projected reductions in lithium-ion battery costs over the coming years. The findings indicate that the microgrid can substantially reduce grid electricity consumption, achieving annual GHG emission reductions exceeding 600 tons of CO₂. From a financial perspective, the optimal configuration consisting of a 760 kWp PV array paired with a 1250 kWh lead–carbon battery system provides a system autonomy of 46% and achieves an NPV of EUR 1.41 million over a 25-year horizon. Higher load demands and electricity prices increase the NPV of the optimal system, whereas lower load demands enhance the system’s autonomy. The anticipated reduction in lithium-ion battery costs over the next 5–10 years is expected to provide improved financial results compared to the base-case scenario. These results highlight the techno-economic viability of zero feed-in microgrids and provide valuable insights for the planning and deployment of similar systems in regions with increasing renewable penetration and grid constraints. Full article

Uncovering the interdependencies among barrier factors and pinpointing the most critical obstacles are essential to overcoming the resistance encountered by photovoltaic (PV) integration into electricity markets. This study first employs grounded theory to identify and categorize the key barriers impeding PV participation, thereby constructing a comprehensive barrier factor model. Subsequently, Interpretive Structural Modeling (ISM) is applied to systematically analyze the interrelations and hierarchical structure among these barriers. The results reveal that: (1) The complex system of PV participation comprises 15 distinct barriers, which can be grouped into 4 overarching categories: economic and cost-related challenges, policy and regulatory uncertainties, technological and infrastructure constraints, and environmental and resource limitations. (2) These barriers form a six-tier hierarchical structure, reflecting their layered influence. (3) Root-level barriers—such as inadequate government fiscal support and the absence of a comprehensive coordination mechanism—play a foundational role in hindering progress. In response, this study proposes policy recommendations, including establishing a unified and effective coordination framework to align renewable energy policies and formulating standardized guidelines for PV panel recycling. Full article

The increasing integration of solar energy into the power grid necessitates robust fault detection and diagnosis (FDD) guidelines to ensure energy continuity and optimize the performance of grid-connected photovoltaic (GCPV) systems. This research addresses a gap in the literature by systematically evaluating machine learning (ML) algorithms for the detection and classification of AC-side faults (inverter and grid faults) in GCPV systems. We utilized three commonly employed algorithms, namely K-Nearest Neighbors (KNN), Logistic Regression (LR), and Artificial Neural Networks (ANNs), to develop fault detection models. These models were trained using a monthly electrical dataset obtained from the AYCEM-GES-GCPV power plant in Giresun, Turkiye, and their performance was rigorously evaluated using classification accuracy, Area Under the Curve (AUC), and Receiver Operating Characteristic (ROC) analyses. The results demonstrate that the algorithms are highly effective in fault detection, with AUC values consistently exceeding the critical threshold. The obtained accuracies for KNN, LR, and ANN were 0.9826, 0.782, and 0.7096, respectively. These findings emphasize the high effectiveness of ML algorithms, with KNN exhibiting the best performance, for identifying AC-side faults in GCPV installations. While the study focused on AC-side fault detection, subsequent work developed a smart card module to identify complex DC side electrical faults and built a PV array for experimental testing. Full article

In Mediterranean cities, high solar radiation combined with limited shading and vegetation intensifies the urban heat island (UHI) phenomenon. As the road network often covers a large portion of the cities’ surfaces and is mostly constructed using asphalt pavements, it can significantly affect the urban microclimate, leading to low thermal comfort and increased energy consumption. Recycled and waste materials are increasingly used in the construction of pavements in accordance with the principle of sustainability for minimizing waste and energy to produce new materials based on a circular economy. The scope of this study is to evaluate the effect of recycled or waste materials used in road pavements on the urban microclimate. The surface and ambient temperature of urban pavements constructed with conventional asphalt and recycled/waste-based mixtures are assessed through simulation. Two study areas comprising large street junctions near metro stations in the city of Thessaloniki, in Greece, are examined under three scenarios: a conventional hot mix asphalt, an asphalt mixture containing steel slag, and a high-albedo mixture. The results of the research suggest that the use of steel slag could reduce the air temperature by 0.9 °C at 15:00, east European summer time (EEST), while the high-albedo scenario could reduce the ambient temperature by 1.6 °C at 16:00. The research results are useful for promoting the use of recycled materials, not only as a means of sustainably using resources but also for the improvement of thermal comfort in urban areas, the mitigation of the UHI effect, and the reduction of heat stress for human health. Full article

Bypass diode failure, particularly in the short-circuit mode, remains an under-addressed reliability issue in photovoltaic (PV) modules, causing severe power suppression and often leading to premature disposal of otherwise functional units. This study presents a non-destructive, field-applicable plug-in repair protocol for restoring modules affected by short-circuited bypass diodes. From twenty-two field-deployed modules, nine were analyzed in detail under healthy, single-fault, and dual-fault conditions. Controlled diode faults were introduced and subsequently repaired using commercially available plug-in bypass diodes. Electroluminescence (EL) imaging, current–voltage (I–V) testing, and extraction of series and shunt resistances were performed before and after repair. Results show that a single shorted diode deactivates one substring, reducing power by ~34–37%, while dual faults suppress over two-thirds of the active area, causing power losses above 67%. After repair, power deviation decreased to <3% for single faults and <7% for dual faults, with shunt resistance increasing by 52–262%, confirming removal of diode-induced leakage paths. Series resistance remained largely unchanged except in modules with irreversible cell-level damage accumulated during prolonged faulty operation. The findings demonstrate that short-circuited bypass diode faults are readily repairable and that component-level intervention can restore module performance, extend operational lifetime, and reduce unnecessary PV recycling. Full article

The deployment of solar and other renewable energy technologies (RETs) plays a central role in the global energy transition and the pursuit of sustainable development. Beyond reducing greenhouse gas emissions, these technologies generate far-reaching societal co-benefits that shape environmental quality, social equity, and economic growth. This study systematically reviews peer-reviewed literature published between 2009 and 2025 to identify, integrate, and assess empirical evidence on how RET deployment contributes to societal welfare. Following the SALSA framework and PRISMA guidelines, 147 studies were selected from Scopus and Web of Science. The evidence reveals a consistent welfare triad: environmental gains (emission and pollution reduction, climate mitigation), social gains (improved health, affordability, energy security, and inclusion), and economic gains (employment and income growth, local development). These benefits are, however, heterogeneous and depend on enabling conditions such as policy stability, financial development, grid integration, innovation capacity, and social acceptance. The review highlights that solar energy, in particular, acts as both an environmental and social catalyst in advancing sustainable welfare outcomes. The findings provide a comprehensive basis for policymakers and researchers seeking to design equitable and welfare-enhancing renewable energy transitions. Full article

While there is currently a significant opportunity for the construction of photovoltaic solar farms in the Southeastern United States, there is also a need for proper spatial planning that has not been adequately addressed by the existing literature. The objective of this study is to examine the adaptability of geographic information system-based multiple criteria decision analysis models developed for foreign contexts to the United States. This was accomplished through the application of a model developed originally for Thailand to the study area of Bibb County, Georgia, United States. Model results were analyzed to identify trends and provide concrete recommendations for future work. Using a six-rank classification scheme, 93% of Bibb County was found to have moderate suitability, while 5% and 2% had moderate-to-low and moderate-to-high suitability, respectively. Of the 11 model criteria, land usage and power line distance were found to have the largest impact on the area’s suitability. Statistical analysis identified positive trends indicating that these criteria explained 21% and 10% of the variance in the model’s output, respectively. Empirical verification proved the model structure to be viable for application in the Southeastern United States; however, additional examination of the model’s results found that there is room to improve the model for the local context. These improvements could potentially be realized through the reweighting of criteria and the re-establishment of evaluation benchmarks, allowing for the development of a truly robust model for the region. Full article

This study investigates the fire behaviour of building-integrated photovoltaic (PV) claddings, focusing on the progression from glass failure to ignition under different cavity conditions. Experimental tests were conducted on two common PV cladding types: bifacial dual-glass (GG) and monofacial glass–plastic (GP) modules. Results revealed that GP modules exhibited faster burning and higher peak heat release rates (HRR), reaching up to 600 kW, while GG modules burned more slowly with peak HRR between 50 and 100 kW. Cavity conditions, including depth, ventilation, and operational energization, were found to be vital in determining glass breakage, occurring between 400 and 550 °C, and cavity ignition and subsequent flame spread. The relationship between cavity fire dynamics and glass breakage suggests the importance of system design, particularly regarding cavity ventilation and flame barriers, for mitigating upward fire propagation. These results establish a basis for advancing numerical fire models through integration of critical parameters such as material properties, glass breakage, cavity ignition, and cavity configuration. This approach supports comprehensive real-scale analysis to guide the development of effective design recommendations, ultimately improving fire safety in PV-integrated construction. Full article

In response to the pressing climate change emergency, the rapid expansion of renewable energies, particularly photovoltaic (PV) power in Spain, is reconfiguring national energy landscapes, thereby necessitating detailed spatial analysis. This study aims to characterise the spatial distribution of PV energy in the country. Specifically, it employed the Administrative Register of Electricity Production Facilities (RAIPEE) database from 2000 to 2023 and a review of Environmental Impact Statements (EIA) from 2014 to 2023 to generate a facility density cartography. Additionally, the spatial statistic Moran’s I was used to detect aggregation patterns. The results demonstrated an aggregation tendency for low and medium power facilities (up to 10 MW), while the distribution of higher-capacity facilities appeared random. Examination of the facility density cartographies suggest significant variability among provinces and distribution trends centred around the country’s main urban regions. This approach to understanding the spatial dynamics of PV energy offers novel and crucial geospatial insights for renewable energy planning. Full article

As the penetration of distributed energy resources (DERs) continues to increase, there is conjecture concerning the power quality implications of the inverters used to interface these DERs with low-voltage (LV) electricity supply networks. As a power electronics converter, inverters are a known source of harmonic emissions. Using a combination of large-scale field measurements, laboratory evaluations of inverter performance, and power system modelling, this study applies an empirical data-driven approach to investigate the impact of small-scale solar PV inverters on LV harmonic distortion magnitudes. This multi-facetted approach, involving field data analysis, laboratory assessments of inverter performance, and power system simulation to evaluate the impact of small-scale DER on harmonic distortion in LV networks, is novel in comparison to other studies, which only utilise one or two of the analysis methods of simulation, laboratory evaluation, or analysis of field measurements but not all three. The analysis of field measurement data collected over the past decade does not indicate any significant changes in harmonic distortion magnitudes that can be attributed to the increasing penetration of DERs. Power system modelling, which incorporates data obtained from laboratory inverter performance evaluations, indicates that, even at very high levels of penetration, the harmonic current emissions from solar PV inverters are only sufficient to add modest levels of harmonic distortion to LV networks, a 0.25% increase in THD for 40% penetration and a 0.62% increase in THD for 100% penetration, providing an explanation for the findings of the field data analysis. Full article

Floating photovoltaic systems represent a promising solution for renewable energy generation, offering an alternative to agricultural land consumption. However, these installations have the potential to exert an effect on the aquatic ecosystem, emphasizing the necessity of effective monitoring strategies also related to system management issues. In this paper, the use of an unmanned surface vehicle, which can also operate as an autonomous surface vehicle, is proposed to overcome many difficulties of maintenance and monitoring in aquatic environments. A review of the extant literature reveals the scarcity of a cohesive monitoring framework for these plants, highlighting the urgent need for standardized guidelines for plant management and water quality monitoring. The implementation of automated plants directly addresses this gap by providing a tool for efficient and sustainable monitoring tasks, enabling, at the same time, aquatic ecosystem protection and energy production optimization. To address these challenges, a low-cost prototype of an autonomous surface vehicle is proposed. Preliminary test results on trajectory control and obstacle recognition are reported. Full article