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Agrivoltaic (AV) systems offer a promising solution to global challenges, such as land scarcity, food insecurity, and increasing energy demand, by enabling the simultaneous production of photovoltaic (PV) electricity and agricultural outputs on the same land. This review synthesizes more than two decades of interdisciplinary research on solar–agriculture integration, including agrivoltaic systems, biomass-based approaches, and greenhouse-integrated photovoltaic technologies, with particular emphasis on their relevance to arid and semi-arid environments, such as those found in the Middle East. The impacts of different PV configurations (such as semi-transparent, bifacial, vertical, and sun-tracking modules) on crop productivity, microclimatic conditions, and land-use efficiency are critically examined. The findings indicate that AV systems, particularly in water-scarce, high-irradiance regions, can enhance climate resilience, reduce competition for land, and improve both energy and water-use efficiency. Recent advances in crop selection strategies, adaptive PV system designs, and smart irrigation technologies further strengthen the feasibility of these systems for Middle Eastern agricultural systems. Nevertheless, key challenges remain, including the need for region-specific design optimization, improved understanding of crop light requirements, and robust assessments of economic viability under diverse policy and market conditions. Overall, life cycle assessments and techno-economic analyses confirm the environmental and economic benefits of AV systems, especially for sustainable irrigation, agricultural productivity, and rural development in the Middle East context. This review provides strategic insights to support the sustainable deployment and scaling of agrivoltaic systems across Middle Eastern agricultural landscapes, informed by global experience. A dedicated regional assessment summarizes existing agrivoltaic pilots and feasibility studies across the Middle East and North Africa, highlighting technology choices, crop compatibility, and policy drivers. 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

This study presents an AI-driven computational framework for optimizing the orientation and spatial deployment of photovoltaic (PV) systems installed on uneven terrain, with the objective of enhancing energy efficiency and supporting sustainable energy development. The proposed methodology integrates PVsyst-based numerical simulations with statistical modeling and bio-inspired heuristic optimization algorithms, forming a hybrid machine learning–assisted decision-making approach. A heuristic–parametric optimization strategy was employed to evaluate multiple tilt and azimuth configurations, aiming to maximize specific energy yield and overall system performance, expressed through the performance ratio (PR). The model was validated using site-specific climatic data from Veracruz, Mexico, and identified an optimal azimuth orientation of approximately 267.3°, corresponding to an estimated PR of 0.8318. The results highlight the critical influence of azimuth orientation on photovoltaic efficiency and demonstrate strong consistency between simulation outputs, statistical analysis, and intelligent optimization results. From an industrial perspective, the proposed framework reduces planning uncertainty and energy losses associated with suboptimal configurations, enabling more reliable and cost-effective photovoltaic system design, particularly for installations on uneven terrain. Moreover, the methodology significantly reduces planning time and potential installation costs by eliminating the need for preliminary physical testing, offering a scalable and reproducible AI-assisted tool that can contribute to lower levelized energy costs, enhanced system reliability, and more efficient deployment of photovoltaic technologies in the renewable energy industry. Future work will extend the model toward a multivariable machine learning framework incorporating tilt angle, climatic variability, and photovoltaic technology type, further strengthening its applicability in real-world environments and its contribution to Sustainable Development Goal 7: affordable and clean energy. Full article

The global transition towards decentralized, decarbonized energy systems worldwide must include robust methods for controlling hybrid AC/DC microgrids to integrate diverse renewables and storage technologies effectively. This paper presents a Finite Control Set–Model Predictive Control (FCS-MPC) architecture for coordinated control of a hybrid microgrid comprising photovoltaic and wind generation, along with an energy storage system and MATLAB/Simulink component-level modeling. The islanded and grid-connected modes of operation are seamlessly simulated at the component level, ensuring maximum power point tracking and stability. The method has been experimentally validated through dynamic simulations across a range of operating conditions, demonstrating good performance: PV and wind MPPT efficiency > 99%, DC-link voltage control with <2% overshoot, AC voltage THD < 3%, and efficient grid synchronization. It is superior to conventional PID and sliding mode control in terms of dynamic response, voltage deviation (reduced compared to before), and power quality. The proposed FCS-MPC is an all-in-one solution to enhance the stability, reliability, and efficiency of modern hybrid microgrids. Full article

Enteroviruses (EVs) are small, non-enveloped RNA viruses that can cause diverse clinical outcomes, particularly severe in patients with primary immunodeficiency (PID) due to their impaired ability to clear infections. This study aimed to characterize EV excretion among 138 Tunisian PID patients over a five-year period, to identify circulating EV serotypes and assess their genetic diversity. A total of 558 stool samples were collected and analyzed by virus isolation and intratypic differentiation using RT-qPCR. Molecular typing was performed through Sanger sequencing of the VP1 region and whole genome sequencing using Next-Generation Sequencing (NGS) technologies. Phylogenetic analysis was conducted using the Maximum Likelihood (ML) method. EVs were detected in 55 stool samples from 23 patients. The excretion kinetics of EVs ranged between 30 and 946 days. Thirteen serotypes were identified, including one Poliovirus (PV) and twelve Non-Polio Enteroviruses (NPEVs), predominantly belonging to species B. Two previously unreported serotypes in Tunisia were detected: Coxsackievirus A5 (CVA5) and Echovirus type 19 (E19). In addition, five patients presented enhanced susceptibility to the excretion of successive EV serotypes, and one patient exhibited a co-infection. A possible recombination event was identified in one patient involving Coxsackievirus B5 (CVB5), Coxsackievirus A9 (CVA9) and Coxsackievirus B1 (CVB1) sequences. Phylogenetic analysis showed close genetic relationships with European, American and Asian strains. These findings underscore the dynamic nature of EV circulation and the importance of ongoing molecular surveillance to detect emerging serotypes and guide public health strategies. Full article

Optimizing photovoltaic (PV) installations requires precise understanding of the annual energy yield, which depends heavily on geographical location, panel technology, tilt, and azimuth. This study establishes the framework for a “European Photovoltaic Atlas”. In this pilot phase, the dynamic tool is applied to representative European climatic zones to compare diverse latitudes and technologies. Consequently, we aim to create a robust database and interactive visualization tool that allows users to analyze technology-specific yields based on variable orientation parameters. The study employs a large-scale simulation campaign using EnergyPlus coupled with a PVWatts model. Two photovoltaic technologies (PERC and TOPCon monocrystalline) have been simulated in seven European reference cities: Naples, Madrid, Berlin, Paris, London, Stockholm, and Warsaw. For each city and technology, simulations have been performed for a complete grid of orientations. The tilt was varied from 0° to 90° in 5° increments, and the azimuth was varied from 0° to 360° in 5° increments. All panels have been simulated at a height of 15 m to represent typical rooftop installations. The main result is a comprehensive database that links location, technology, tilt, azimuth, and normalized annual energy yield. This database feeds an interactive application developed in Python. This tool generates 2D heatmaps showing the surface orientation factor of any selected city–technology pair, 3D surface plots comparing performance across multiple technologies or locations simultaneously, and 2D charts estimating hourly annual productivity by varying technology efficiency values. The “Photovoltaic Atlas” serves as a practical decision support tool for architects and engineers by enabling the rapid optimization of photovoltaic systems and clearly illustrating performance in the European context. Full article

Large-aperture optical elements are increasingly in demand for applications in astronomy, high-power lasers, and aerospace technology, but their manufacturing and testing processes pose significant challenges. In this paper, we propose an ultra-large-aperture digital laser plane interferometric testing technique that combines the two-plate shearing absolute mutual testing method with micro-stress support technology. This method enables high-precision testing of Φ800 mm planar elements and offers advantages such as fast testing speed, high resolution, and precise alignment. Simulation results and comparisons with measurements from a ZYGO interferometer validate the effectiveness of the proposed method. Experimental testing of an Φ800 mm planar element yielded a PV value of 0.0923$\lambda$ and an RMS value of 0.0114$\lambda$ at a wavelength of 632.8 nm. The quantitative results are incorporated into the abstract and conclusions, highlighting the method’s minimal error and high accuracy. This technique provides a novel approach for high-precision testing of large-aperture optical elements. Full article

High-penetration integration of distributed photovoltaics (PV) into distribution networks introduces significant challenges regarding voltage limit violations and fluctuations. To address these issues, this manuscript proposes a hierarchical coordinated voltage control strategy for medium- and low-voltage distribution networks utilizing a cloud-edge collaboration architecture. The research methodology involves constructing a multi-objective optimization model at the cloud layer to minimize network losses and voltage deviations, solved via an improved Honey Badger Algorithm (HBA). Simultaneously, at the edge layer, a multi-mode coordinated control strategy incorporating Virtual Synchronous Generator (VSG) technology is developed to provide fast reactive power support and inertial response. Through simulation analysis on an IEEE 33-node test system, the findings demonstrate that the proposed strategy significantly mitigates voltage fluctuations and enhances the hosting capacity of distributed energy resources. The study concludes that the cloud-edge framework effectively decouples control time-scales, ensuring both global economic operation and local transient stability. These results are significant for advancing the resilient operation of active distribution networks with high renewable penetration. Full article

Filamentous fungi are widely used in biotechnological processes because they secrete significant amounts of protein, use inexpensive nutrient media, and are predictably scalable in technological processes. Penicillium verruculosum B1-537 (now renamed Talaromyces verruculosus) produces large amounts of secreted protein (up to 70 g/L) and is used for large-scale enzyme production. Although P. verruculosum has an excellent protein expression system under the control of a strong cbh1 promoter, some heterologous enzymes such as Aspergillus awamori glucoamylase (aaGlaA) are still produced in insufficient quantities (15–20% of the total secreted protein), and this limits the application of enzyme preparations derived from P. verruculosum strains in the alcohol industry for the enzymatic treatment of grain starch together with α-amylase. One of the well-known approaches to addressing this is signal peptide replacement to increase protein expression. Therefore, the aim of this study was to investigate the effectiveness of signal peptide replacement. Various signal peptides (SPs), which were previously used for other well-expressed heterologous proteins, such as xylanases, β-glucosidases, and others, were analyzed to determine their effect on aaGlaA secretion. Five plasmids containing signal peptide sequences fused to the glaA gene were constructed and used to transform P. verruculosum. The resulting strains were cultured and screened for protein content and glucoamylase activity. Copy number analysis was performed on the most productive strains. The best one was an SP of homologous glucoamylase in P. verruculosum (pvGlaA). The use of this particular SP increased the secretion of heterologous aaGlaA by 2.5 times when cultivating recombinant strains on cellulose-containing fermentation media for P. verruculosum. Thus, SP replacement is a useful way to increase expression levels in the P. verruculosum expression system. Application of this method in P. verruculosum could address some productivity issues and enable the large-scale production of other industrial and food enzymes. Full article

Driven by the global energy transition, the rapid expansion of photovoltaic (PV) capacity—particularly in China’s “sand-Gobi-desert” mega-bases—demands highly efficient collection technologies. DC collection, offering low losses, compactness, and high reliability, is emerging as a critical solution for large-scale integration. This paper provides a comprehensive review of PV DC step-up collection systems. First, it analyzes typical network architectures, compares AC versus DC schemes, and examines design constraints imposed by DC bus voltage levels. Second, control strategies are summarized across device, equipment, and system levels. Third, based on engineering practices in ultra-large-scale bases, key challenges regarding fault detection, efficiency optimization, economic viability, and grid code compatibility are identified alongside representative solutions. Finally, future trends in high-voltage hardware maturation, protection bottlenecks, real-time artificial intelligence, and specialized standardization are proposed. This study serves as a vital reference for the topology design and engineering standardization of PV DC collection systems. Full article

Residential buildings in Mediterranean regions remain major contributors to energy consumption and greenhouse gas emissions. Existing studies often assess renewable energy technologies or innovative building solutions in isolation, with limited attention to their combined performance across different residential typologies. This study evaluates the integrated impact of solar renewable energy systems and smart building technologies on the energy performance of residential buildings in Cyprus. A typology-based methodology is applied to three representative residential building types—detached, semi-detached, and apartment buildings—using dynamic energy simulation and scenario analysis. Results show that solar photovoltaic systems achieve higher standalone reductions than solar thermal systems, while smart building technologies significantly enhance operational efficiency and photovoltaic self-consumption. Integrated solar–smart scenarios achieve up to 58% reductions in primary energy demand and 55% reductions in CO₂ emissions, and 25–30 percentage-point increases in PV self-consumption, enabling detached and semi-detached houses to approach national nearly zero-energy building (nZEB) performance thresholds. The study provides climate-specific, quantitative evidence supporting integrated solar–smart strategies for Mediterranean residential buildings and offers actionable insights for policy-making, design, and sustainable residential development. Full article

Agrivoltaics is a rapidly expanding technology thanks to its energy, agronomic, and microclimatic benefits, which have been demonstrated in a variety of climatic contexts around the world. This study presents the first systematic review exclusively focused on experimental agrivoltaics field studies, based on the analysis of 82 peer-reviewed articles. The aim is to provide a cross-study comparable synthesis of how shading from different photovoltaic (PV) technologies affects microclimate, crop yield, and crop quality. The reviewed systems include four main categories of PV modules: conventional, bifacial, semi-transparent/transparent, including spectrally selectivity modules and concentrating photovoltaic systems (CPV). To handle heterogeneity and improve comparability, results were normalised against open-field controls as relative percentage variations. The analysis reveals a high variability in results, strongly influenced by crop type, climate, level of shading, and reduction in PAR (Photosynthetically Active Radiation). Studies conducted with the same shade intensity but under different climatic conditions show contrasting results, suggesting that there is no universally optimal agrivoltaics configuration. Nevertheless, the review allows us to identify recurring patterns of compatibility between crops and photovoltaic technologies, providing useful guidance for choosing the most suitable technology based on climate, crop physiology, and production objectives. Full article

The growing demand for high-efficiency photovoltaic (PV) technologies has intensified interest in advanced cell architectures, including hybrid passivated back contact (HPBC) solar cells. Conventional solder-based interconnection processes require high thermal budgets, which can induce thermomechanical stress and lead to performance degradation in thin back-contact cell structures. In this study, electrically conductive adhesive (ECA) interconnection is investigated as a low-thermal-budget, solder-free alternative for HPBC solar cells. The curing behavior of an acrylic-based, silver-filled ECA is systematically examined by controlling the upper lamp temperature and the welding time during the interconnection process. Electrical performance is evaluated through current–voltage characterization, fill factor, and series resistance analysis, while interfacial microstructural evolution is examined using scanning electron microscopy. The results identify a well-defined processing window in which adequate curing enables stable electrical contact formation. In contrast, both insufficient curing and excessive curing result in degraded electrical performance. To assess practical applicability, HPBC modules with an industry-relevant size of ~1000 × 1160 mm² are fabricated and evaluated using electroluminescence imaging and I–V measurements. By identifying a robust curing window and demonstrating its successful transfer from string-level interconnections to full-size HPBC modules, this study establishes a practical, low-thermal-budget, solder-free interconnection strategy for advanced back-contact PV architectures. Full article

This study systematically reviews and re-evaluates the international competitiveness and economic sustainability of China’s solar photovoltaic (PV) industry. Based on the PRISMA protocol, it integrates both qualitative and quantitative evidence from 70 core English-language publications published between 2000 and 2025. An analytical framework is developed that combines keyword co-occurrence analysis, thematic clustering, and mechanism pathway mapping. The study identifies three key thematic domains: policy governance mechanisms, economic feasibility and cost structures, and the coupling between technological innovation and environmental performance. The findings reveal a transition in China’s PV development pathway—from early policy-driven expansion to the co-evolution of institutional adaptation and market mechanisms—highlighting the dynamic tension among multi-level variables. Four institutional dimensions and associated variable chains are proposed, uncovering long-term contradictions such as the reliance on subsidies versus structural efficiency and the strategic mismatch between national industrial strategies and global decarbonization goals. The study suggests that future research should prioritize system modeling, feedback mechanism identification, and the theoretical expansion of multi-level governance frameworks. In doing so, this review provides a reusable variable classification framework for analyzing green industrial transformation and offers policy insights for emerging economies engaged in global climate governance. Full article