Search Results (3,046)

This paper presents the design, modeling and experimental validation of an on-grid photovoltaic system with self-consumption, sized for the sustainable supply of a water pumping station. The system, composed of 68 photovoltaic panels, uses an architecture based on a Boost DC-DC converter controlled by the Perturb and Observe algorithm, raising the operating voltage to a high-voltage DC bus to maximize the conversion efficiency. The study integrates dynamic performance analysis through simulations in the Simulink environment, testing the stability of the DC bus under sudden irradiance shocks, with rigorous experimental validation based on field production data. The simulation results, which indicate a peak DC power of approximately 34 kW, are confirmed by real monitoring data that records a maximum of 35 kW, the error being justified by the high efficiency of the panels and system losses. Long-term validation, carried out over three years of operation (2023–2025), demonstrates the reliability of the technical solution, with the system generating a total of 124.68 MWh. The analysis of energy flows highlights a degree of self-consumption of 60.08%, while the absence of chemical storage is compensated for by injecting the surplus of 49.78 MWh into the national grid, which is used as an energy buffer. The paper demonstrates that using the grid to balance night-time or meteorological deficits, in combination with a stabilized DC bus, represents an optimal technical-economic solution for critical pumping infrastructures, eliminating the maintenance costs of the accumulators and ensuring continuous operation. Full article

In the face of accelerating climate change and urbanization, sustainable mobility infrastructure plays a critical role in reducing greenhouse gas emissions. This article assesses the Sunglider concept—an elevated, solar-powered transport system—through the New European Bauhaus (NEB) Compass, which emphasizes sustainability, inclusion, and esthetic value. Designed by architect Peter Kuczia and collaborators, Sunglider combines photovoltaic energy generation with modular, parametrically designed wooden pylons to form a lightweight, climate-positive mobility solution. The study evaluates the system’s technological feasibility, environmental performance, and urban integration potential, drawing on existing design documentation and simulation-based estimates. While Sunglider demonstrates strong alignment with NEB principles, including zero-emission operation and material circularity, its implementation is challenged by high initial investment, political and planning complexities, and integration into dense urban environments. Mitigation strategies—such as adaptive routing, visual screening, and universal station access—are proposed to address concerns around privacy, esthetics, and accessibility. The article positions Sunglider as a scalable and replicable model for mid-sized European cities, capable of advancing inclusive, carbon-neutral mobility while enhancing the urban experience. It concludes with policy and research recommendations, highlighting the importance of embedding infrastructure innovation within broader ecological and cultural transitions. 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

Photovoltaic installations are becoming an increasingly popular source of electricity around the world. The decision on where and how to install the modules and their location is made at the stage of building the installation and is crucial for obtaining the most beneficial effects of its operation. The choice of installation location and its geometry directly influence the following aspects, which determine maximum efficiency and thus economic benefits: solar irradiance, working cell temperature, shading, dust and soiling. Factors that have an unfavorable impact on the efficiency of a photovoltaic installation can be divided into those that should be taken into account at the design stage, such as the correct orientation and angle of inclination of the modules, and those that will play an important role during the use of the system: contamination of the front surface of the modules. This article discusses the impact of these factors and their importance for the proper operation of a photovoltaic installation. Full article

The large-scale integration of electric vehicles (EVs) presents both challenges and opportunities for power grid stability and renewable energy utilization. Vehicle-to-Grid (V2G) technology enables EVs to serve as mobile energy storage units, facilitating peak shaving and valley filling while promoting the local consumption of photovoltaic and wind power. However, uncertainties in renewable energy generation and EV arrivals complicate the scheduling of bidirectional charging in stations equipped with hybrid energy storage systems. To address this, this paper proposes a multi-stage rolling optimization framework combined with a fuzzy logic-based decision-making method. First, a bidirectional charging scheduling model is established with the objectives of maximizing station revenue and minimizing load fluctuation. Then, an EV charging potential assessment system is designed, evaluating both maximum discharge capacity and charging flexibility. A fuzzy controller is developed to allocate EVs to unidirectional or bidirectional chargers by considering real-time predictions of vehicle arrivals and renewable energy generation. Simulation experiments demonstrate that the proposed method consistently outperforms a greedy scheduling baseline. In large-scale scenarios, it achieves an increase in station revenue, elevates the regional renewable energy consumption rate, and provides an additional equivalent peak-shaving capacity. The proposed approach can effectively coordinate heterogeneous resources under uncertainty, providing a viable scheduling solution for EV-aggregated participation in grid services and enhanced renewable energy integration. Full article

This study investigates the state of the art related to the computational methods for solar cells. Numerical modeling is a basic pillar that is used to ensure the robust design of any device. In this paper, the results of a detailed science mapping-based analysis on the publications that focus on the “numerical modelling of solar cells” are presented. The query was conducted on the Web of Science for 2014–2024, and a subsequent filtering was performed. The results of this analysis provided the answers to the five research questions posed. The paper has been divided into two parts. In the first part, the literature search began with a broad examination, and 3259 studies were included in the analysis. To present the results in a visual form, graphs created using VOS viewer software have been used to identify the pattern of co-authorship, the geographical distribution of the authors, and the keywords most frequently used. In the second part, the analysis focused on three main aspects: (i) the influence of absorber layer thickness on optical absorption and device efficiency, (ii) the role of different ETL/HTL materials in charge transport, and (iii) the effect of illumination conditions on carrier dynamics and photovoltaic performance. By integrating the results across these dimensions, the study provides a comprehensive understanding of how these parameters collectively determine the efficiency and reliability of perovskite solar cells. Full article

This study aims to develop and apply a novel methodology to assess the scope, benefits and challenges of distributed photovoltaic generation (DG-PV). The research provides a replicable framework applicable to any country, as long as official energy consumption data are available and the nation is seeking to modify its energy matrix as part of a sustainable transition through the design of renewable-energy-based policies. To support the viability of the proposal, data from the Ecuadorian electrical system for the period between 2014 and 2024 were analyzed using technical, operational and socio-economic indicators defined in the methodology. These include renewable participation, energy diversification, DG-PV, technical efficiency, regulatory index, operational resilience and electrical coverage. The investigation concludes with the definition of a Distributed Photovoltaic Integration Index (DPII), which can be used to measure a country’s progress toward the proper implementation of renewable energy. The DPII supports informed decision-making by allowing utilities and policymakers to prioritize distributed photovoltaic integration and compare alternative energy transition scenarios. In the case of Ecuador, a DPII of 0.170 is obtained for 2024 compared to a value of 0 for 2014. This result is mainly due to an increase in renewable energy participation (P1), which rose from 0.49 to 0.76 during this period, largely supported by hydropower expansion. This value was obtained because over the last ten years, Ecuador has committed to implementing active policies that incorporate renewable energies, as well as other aspects such as technical efficiency and the expansion of electrical coverage. This approach offers a replicable quantitative tool for evaluating the integration of DG-PV, providing key information for energy planning and for the formulation of policies that promote the decarbonization, decentralization and digitalization of the national electrical system. Full article

The aim of this paper is to present the transformation of the network tariff system in Slovenia using a comprehensive assessment methodology for the techno-economic evaluation of electricity costs for households. The novelty of the proposed approach lies in the combined assessment of the previous and new network tariff systems, explicitly accounting for power-based network tariff components, time-block-dependent charges, and different support schemes for household photovoltaic systems, including net metering and credit note-based schemes. The results show that the transition from an energy-based to a more power-based network tariff system, introduced primarily to mitigate congestion in distribution networks, is not inherently disadvantageous for consumers and prosumers. When tariff structures are appropriately designed, the new framework can support efficient grid utilization and maintain favorable conditions for prosumers, particularly those integrating battery storage systems. Overall, the proposed methodology provides a transparent and robust framework for evaluating the economic impacts of network tariff reforms on residential consumers and prosumers, offering relevant insights for tariff design and the development of future low-carbon household energy systems. Full article

Accurate global irradiance (GI) forecasting is essential for improving photovoltaic (PV) energy management, stabilizing renewable power systems, and enabling intelligent control in solar-powered applications, including electric vehicles and smart grids. The highly stochastic and non-stationary nature of solar radiation, influenced by rapid atmospheric fluctuations and seasonal variability, makes short-term GI prediction a challenging task. To overcome these limitations, this work introduces a new hybrid forecasting architecture referred to as WTX–CBO, which integrates a Wavelet Transform (WT)-based decomposition module, an encoder–decoder Transformer model, and an XGBoost regressor, optimized using the Chaotic Billiards Optimizer (CBO) combined with the Adam optimization algorithm. In the proposed architecture, WT decomposes solar irradiance data into multi-scale components, capturing both high-frequency transients and long-term seasonal patterns. The Transformer module effectively models complex temporal and spatio-temporal dependencies, while XGBoost enhances nonlinear learning capability and mitigates overfitting. The CBO ensures efficient hyperparameter tuning and accelerated convergence, outperforming traditional meta-heuristics such as Particle Swarm Optimization (PSO) and Genetic Algorithms (GA). Comprehensive experiments conducted on real-world GI datasets from diverse climatic conditions demonstrate the outperformance of the proposed model. The WTX–CBO ensemble consistently outperformed benchmark models, including LSTM, SVR, standalone Transformer, and XGBoost, achieving improved accuracy, stability, and generalization capability. The proposed WTX–CBO framework is designed as a high-accuracy decision-support forecasting tool that provides short-term global irradiance predictions to enable intelligent energy management, predictive charging, and adaptive control strategies in solar-powered applications, including solar electric vehicles (SEVs), rather than performing end-to-end vehicle or photovoltaic power simulations. Overall, the proposed hybrid framework provides a robust and scalable solution for short-term global irradiance forecasting, supporting reliable PV integration, smart charging control, and sustainable energy management in next-generation solar systems. Full article

Soil corrosion is a critical durability and cost factor for metallic foundations in photovoltaic (PV) power plants, yet it is still addressed with fragmented criteria compared with atmospheric corrosion. This paper reviews the main soil corrosivity drivers relevant to PV installations—moisture and aeration dynamics, electrical resistivity, pH and buffer capacity, dissolved ions (notably chlorides and sulfates), microbiological activity, hydro-climatic variability and geological heterogeneity—highlighting their coupled and non-linear effects, such as differential aeration, macrocell formation and corrosion localization. Building on this mechanistic basis, an engineering-oriented methodological roadmap is proposed to translate soil characterization into durability decisions. The approach combines soil corrosivity classification according to DIN 50929-3 and DVGW GW 9, tiered estimation of hot-dip galvanized coating consumption using AASHTO screening, resistivity–pH correlations and ionic penalty factors, and verification against conservative NBS envelopes. When coating life is insufficient, a traceable steel thickness allowance based on DIN bare-steel corrosion rates is introduced to meet the target service life. The framework provides a practical and auditable basis for durability design and risk control of PV foundations in heterogeneous soils. The proposed framework shows that, for soils exceeding AASHTO mild criteria, zinc corrosion rates may increase by a factor of 1.3–1.7 when chloride and sulfate penalties are considered, potentially reducing coating service life by more than 40%. The methodology proposed enables designers to estimate the penalty factors for sulfates ($f_p\left({SO}_4^{2-}\right)$) and chlorides ($f_p\left({Cl}^{-}\right)$) in each specific project, calculating the appropriate values of $K_{{SO}_4^{2-}}$ and $K_{{Cl}^{-}}$ using electrochemical techniques—ER/LPR and EIS—to estimate the effect of the soluble salts content in the ${Zn}_{Corr Rate}$, not properly catch by the proxy indicator $V_{corr}\left(ER, pH\right)$ when sulfate and chloride content are over AAHSTO limits for mildly corrosive soils. Full article

Tunnel Oxide-Passivated Back Contact solar cells represent a next-generation photovoltaic technology with significant potential for achieving both high efficiency and low cost. This study addresses the challenge of low bifaciality inherent to the rear-side structure of TBC cells. Using the Quokka3 simulation and assuming high-quality surface passivation and fine-line printing accuracy, a systematic optimization was conducted. The optimization encompassed surface morphology, optical coatings, bulk material parameters (carrier lifetime and resistivity), and rear-side geometry (emitter fraction, metallization pattern and gap width). Through a multi-parameter co-optimization process aimed at enhancing conversion efficiency, a simulated conversion efficiency of 27.26% and a bifaciality ratio of 92.96% were achieved. The simulation analysis quantified the trade-off relationships between FF, bifaciality, and efficiency under different parameter combinations. This enables accurate prediction of final performance outcomes when prioritizing different metrics, thereby providing scientific decision-making support for addressing the core design challenges in the industrialization of TBC cells. Full article

Mosque buildings have symbolic significance, which makes them ideal candidates for implementing energy-efficient building design strategies. Mosques located in hot climates face several challenges in achieving thermal comfort while meeting energy efficiency requirements due to their distinct architectural features and intermittent occupancy patterns. Addressing these challenges requires integrating innovative energy-efficient retrofit strategies that cater to the characteristics of existing contemporary mosque buildings. Thus, this study provides a review of these approaches, considering both passive and active strategies. Passive strategies include thermal insulation, glazing upgrades, and shading improvements, while active ones include Heating, Ventilation, and Air Conditioning (HVAC) zoning and smart control, lighting upgrades, and the integration of photovoltaic panels. The findings highlight the potential of combining both passive and active retrofitting measures to achieve substantial energy performance improvements while addressing the thermal comfort needs of mosque buildings in hot climates. However, more research is needed on smart control systems and advanced building materials to further enhance energy performance in mosque buildings. By adopting these strategies, mosques can serve as models of energy-efficient design, promoting sustainability and resilience in their communities. Full article

The digital and ecological transition of the industrial sector requires methodological tools that integrate information modelling, performance simulation, and operational decision support. In this context, the present study introduces and tests a semi-automatic BIM-to-BEM framework to optimise human–machine interaction and support critical data interpretation through Graphical User Interfaces. The objective is to propose and validate a BIM-to-BEM workflow for an existing industrial facility to enable comparative evaluation of energy retrofit scenarios. The information model, developed through an interdisciplinary federated approach and calibrated using parametric procedures, was exported in the gbXML format to generate a dynamic, interoperable energy model. Six simulation scenarios were defined incrementally, including interventions on the building envelope, Heating, Ventilation and Air Conditioning (HVAC) systems, photovoltaic production, and relamping. Results are made accessible through dashboards developed with Business Intelligence tools, allowing direct comparison of different design configurations in terms of thermal loads and indoor environmental stability, highlighting the effectiveness of integrated solutions. For example, the combined interventions reduced heating demand by up to 32% without compromising thermal comfort, while in the relamping scenario alone, the building could achieve an estimated 300 MWh reduction in annual electricity consumption. The proposed workflow serves as a technical foundation for developing an operational and evolving Digital Twin, oriented toward the sustainable governance of building–system interactions. The method proves to be replicable and scalable, offering a practical reference model to support the energy transition of existing industrial environments. Full article

South Africa faces high energy costs, highlighting the urgent need for sustainable and cost-effective energy solutions. This study investigates the design of a cost-effective photovoltaic energy system that maximises savings and revenue for the school through energy trading. In this study, the school trades with 14 neighbouring households and 125 electric motorbikes. This research first applies Latin Hypercube Sampling to explore the solution space and determine which system parameters have a significant impact on supply reliability, investment costs, revenue and savings. Optimal solutions are generated using Non-Dominated Sorting Genetic Algorithm II for a range of system scenarios. Following this, the most promising scenario is selected and applied to 53 schools in the Western Cape. The results show that number of panels strongly correlates with both supply reliability and revenue, thus reducing the break-even years, while battery capacity affects investment costs and, to some extent, break-even years. Among the configurations tested, scenarios where schools traded with both households and electric motorbikes, particularly when both included their own battery systems, achieved the most favourable financial performance for the school, with break-even periods of less than five years under sufficient roof area and improved reliability for the external entities, with an average improvement of 60%. These findings demonstrate that peer-to-peer energy trading between schools and communities can enhance the financial feasibility and sustainability of decentralised solar systems, offering a scalable model for improving energy access and affordability in South Africa and possibly other developing countries. Full article