Search Results (2,111)

Decarbonizing the building sector requires integrating on-site renewable generation with systematic energy management. Among the most widely adopted alternatives are photovoltaic (PV) systems in buildings; however, they are often implemented as a standalone technological intervention (size–install–estimate savings), without being formally incorporated into an Energy Management System (EnMS) aimed at continuous improvement. In this context, this research addresses this gap through an integrated methodological framework aligned with ISO 50001, in which PV is explicitly included in energy performance management through energy review, the definition of an Energy Baseline (EnB), and the monitoring of Energy Performance Indicators (EnPIs) within the PDCA cycle. The approach articulates the analytical sizing of the PV system based on electricity demand and solar resources; its validation through simulation to ensure operational consistency and a technical, economic, and environmental assessment that translates PV generation into a verifiable reduction in energy imported from the grid and, consequently, into traceable improvements in EnPI under an audit-compatible scheme. The methodology is demonstrated in a multi-family building in Chorrillos, Lima (Peru), where a 14.5 kWp rooftop PV system (25 modules of 580 Wp) is designed to maximize self-consumption during daylight hours. The results show technical performance consistent with the demand profile, economic viability under the conditions of the case, and environmental benefits from replacing grid electricity, along with offsets associated mainly with the manufacture of PV components. The residual gap between the Post-PV EnPIs and the ISO 50001 target confirms that PV integration is a necessary but not sufficient first-cycle action within a comprehensive building decarbonization strategy, with demand-side management and envelope improvements identified as subsequent PDCA cycle priorities. In summary, the central contribution is not the PV sizing itself, but its operational and traceable integration within ISO 50001, making PV a quantifiable, verifiable, and scalable energy improvement action for residential buildings in emerging economies. Full article

This study evaluates the performance of a commercial silicon-based photovoltaic (PV) module under varying environmental conditions, including solar irradiance, module and ambient temperatures, humidity, and wind speed. Key performance indicators such as daily and lifetime energy output, CO₂ reduction, and potential income were analyzed. Machine learning techniques, including Linear Regression (LR), Artificial Neural Networks (ANN), Random Forest (RF), and XGBoost, were employed to predict photovoltaic (PV) efficiency under varying environmental conditions. The results indicate that solar irradiance is the primary driver of energy production, while elevated temperatures and high humidity reduce efficiency, and wind speed provides minor cooling benefits. Among the models, XGBoost achieved the highest predictive accuracy (Test R² = 0.9967), followed by RF and ANN, whereas LR underperformed due to a limited ability to capture nonlinear interactions. These findings highlight the critical influence of environmental and electrical factors on PV performance and demonstrate the effectiveness of advanced machine learning techniques, particularly XGBoost, in optimizing energy output and supporting sustainable energy planning. Full article

Ultra-large-scale offshore photovoltaic (PV) installations require efficient and reliable construction-phase inspection to ensure installation integrity and compliance with engineering specifications. As the deployment scale expands to thousands of platforms and millions of photovoltaic modules, conventional manual inspection becomes labor-intensive, time-consuming, and increasingly prone to omission errors. This study presents an autonomous inspection framework based on AI-driven computer vision for the detection and localization of missing photovoltaic modules in offshore PV systems. The proposed framework integrates high-resolution UAV-acquired RGB imagery, YOLOv8-based object detection, geographic coordinate transformation, spatial deduplication, and deterministic grid-based indexing to convert aerial observations into structured engineering inspection records. Each detected missing module is automatically assigned a unique platform identifier together with row–column coordinates, enabling engineering-level localization while eliminating redundant detections caused by overlapping UAV imagery. The proposed framework was validated using a dataset comprising 2800 annotated UAV images collected from a 1 GW offshore photovoltaic project. The experimental results revealed a recall of 96.15%, an F1-score of 98.04%, and a manual verification consistency of 96.83%. Geographic deduplication eliminated duplicate grid records, while the average processing time of 1.12 s per image demonstrates the computational feasibility of the framework for large-scale offshore deployment. The results confirm that integrating deep learning-based visual detection with geographic spatial mapping enables reliable, scalable, and engineering-oriented verification of missing photovoltaic modules during construction-phase inspection, thereby supporting standardized and data-driven acceptance workflows for large-scale renewable energy infrastructure. Full article

Prosumer communities, aggregations of residential and commercial entities equipped with distributed energy resources (DER), including photovoltaic systems, battery storage, and flexible loads, are emerging as critical organizational units in decarbonising smart grid architectures. Managing these communities effectively requires balancing economic efficiency with equity, autonomy, and environmental sustainability, objectives that conventional centralized control methods and existing multi-agent reinforcement learning (MARL) implementations fail to address simultaneously. This article proposes a value-aligned hierarchical multi-agent reinforcement learning (VA-HMARL) framework as a formally unified architecture that embeds equity (Jain’s Fairness Index J ≥ 0.90), individual autonomy, and carbon sustainability as hard constraints within the MARL reward structure. The framework integrates: a multi-objective Value Alignment Module (VAM) combining economic, fairness, sustainability, and comfort objectives; attention-based implicit coordination for scalable agent interaction; and differentially private federated policy aggregation (ε = 1.0, δ = 10⁻⁵) for GDPR-compliant collaborative learning. Simulation on a 20-prosumer community modelled on the IEEE 33-bus feeder over 10 Monte Carlo runs (300 episodes each) demonstrates: a 6.2% energy cost reduction versus the Rule-Based baseline (p = 0.0004); a Jain’s Fairness Index of 0.912 ± 0.031 at policy convergence (final 50 episodes), satisfying the J ≥ 0.90 community equity floor; and an 18.0% reduction in CO₂ emissions. The economic efficiency trade-off relative to performance-optimized MARL baselines is limited to 2.4%, within the 5% design target. These results establish VA-HMARL as a technically feasible and ethically grounded paradigm for autonomous decentralized energy governance. Full article

Grid-connected photovoltaic (PV) systems can serve not only as sources of active power but also as active power conditioners for improving power quality. This paper proposes an integrated control strategy for a single-phase grid-connected reduced-switch-count T-type inverter that simultaneously performs maximum power point tracking (MPPT) without a DC-DC conversion stage, compensates for nonlinear load harmonics, and minimises switching losses through a tailored multi-carrier pulse-width modulation (PWM) algorithm. A novel reference current derivation method based on a single-phase dq transformation framework unifies MPPT and active power filtering within a single control loop. The proposed system was validated through MATLAB/Simulink 2025b simulations for a 3500 W PV array supplying a nonlinear RL load with a full-bridge diode rectifier exhibiting a load current total harmonic distortion (THD) of approximately 46%. Simulation results demonstrate an MPPT efficiency of 99.8% at full irradiance (1000 W/m²), an overall system efficiency above 97%, and a grid current THD below 4% across the full irradiance operating range (0–1000 W/m²). Dynamic performance under step irradiance changes was also evaluated: the DC bus voltage deviation remains within 5 V for P&O step sizes between 0.00005 V and 0.0002 V, and the grid current THD recovers to below 5% within 2–6 grid cycles following each irradiance transition. Full article

Ion-exchange-strengthened 0.7 mm aluminosilicate glass offers a promising route to lightweight, mechanically robust front covers for building-integrated photovoltaic (BIPV) modules, but systematic characterization at sub-millimeter thicknesses remains limited. This study investigated 100 × 60 × 0.7 mm glass samples subjected to Na⁺/K⁺ ion exchange (6 h, 430 °C, KNO₃) and characterized mechanical and optical properties relevant to BIPV applications. Depth of layer (DOL) was cross-validated using three independent methods, mass gain diffusion modeling (31–37 μm), elasto-optic measurements (FSM-6000: 38–42 μm), and EDS Na/K depth profiling (35–40 μm), confirming consistent strengthened layer depth of 35–40 μm. Surface compressive stress measured 733 MPa (Series 2) and 773 MPa (Series 3), significantly exceeding conventional PV cover glass (490–515 MPa, 1 mm thickness). Vickers hardness increased by 17.7% (490 → 596 HV, p < 0.0001), demonstrating enhanced damage tolerance. Spectrophotometric analysis (200–2400 nm) showed transmittance >91% (380–2000 nm) and >92% (600–2000 nm) for both as-received and strengthened glass, confirming no optical degradation (p = 0.29–0.41). The 78–83% mass reduction relative to standard 3.2–4 mm glass, combined with superior CS/DOL and preserved optical performance, establishes ion-exchanged 0.7 mm aluminosilicate glass as a strong material-level candidate for next-generation lightweight BIPV modules. Future work requires module-scale mechanical validation (bending, impact testing per EN/IEC standards) and techno-economic assessment to verify system-level benefits. Full article

Series arc faults on the DC side of photovoltaic (PV) systems are a critical hazard that can trigger system fires. Conventional contact-based detection methods suffer from cumbersome installation and high retrofit cost, whereas existing non-contact approaches mostly rely on megahertz-level high-frequency sampling and therefore require expensive radio-frequency instrumentation or high-performance computing platforms. As a result, it remains difficult to simultaneously achieve strong interference immunity and real-time performance on low-cost embedded devices with limited resources. To address this engineering paradox between high-frequency sampling and constrained computational capability, this paper proposes a fully embedded, non-contact arc fault detection system based on a 12–80 kHz low-frequency sub-band selection strategy. By exploiting the physical characteristic of broadband energy elevation induced by arc faults, the proposed strategy avoids dependence on high-bandwidth hardware. Guided by this strategy, a Moebius-topology coaxial shielded loop antenna is employed as the near-field sensor, while an ultra-simplified passive analog front end is constructed directly by using the on-chip programmable gain amplifier and analog-to-digital converter of the microcontroller unit, enabling efficient signal acquisition and fast Fourier transform processing within the target sub-band. To cope with complex background noise in the low-frequency range, an environment-adaptive baseline mechanism based on exponential moving average and exponential absolute deviation is developed for dynamic decoupling. In addition, a lightweight INT8-quantized multilayer perceptron is introduced as a nonlinear auxiliary module, thereby forming a robust hybrid decision architecture with complementary rule-based and artificial intelligence components. Experimental results show that, under the tested household, laboratory, and PV-site conditions, the proposed system achieved an overall detection rate of 97%, while the remaining 3% mainly corresponded to failed ignition or non-sustained arc attempts rather than persistent false triggering during normal monitoring. Full article

Desalination by reverse osmosis (RO) of brackish water and seawater is a cost-competitive solution for supplying irrigation water in off-grid and water-stressed regions. This paper presents an experimental evaluation, thermodynamic analysis, and cost assessment of a solar photovoltaic brackish-water reverse osmosis (PV-BWRO) desalination system. Five feed salinity levels ranging from 993.6 to 3191.8 mg/L were tested. The results show that water production decreased with increasing feed salinity, from 3.29 m³/day at 24.6 mg/L to 1.48 m³/day at 152.9 mg/L. The calculated specific energy consumption values ranged from 1.80 to 3.61 kWh/m³ for solar irradiances of 1005.99 and 1018.47 W/m², respectively. An exergy analysis revealed that the solar panels and pump operated at efficiencies of 11.7% and 38.9%, while exergy destruction was mainly concentrated in the pretreatment stage (28.72%), membrane modules (42.5%), and reject stream (28.5%). Although the overall system efficiency remained low (maximum of 1.39%), the results highlight substantial potential for improvement through enhanced maintenance, optimized pretreatment, and exergy recovery strategies. The unit water production cost ranged from USD 0.49 at 993.6 mg/L to USD 1.87 at 3191.8 mg/L, assuming a target permeate total dissolved solids concentration of 500 mg/L. Full article

As global energy demands rise and concerns about environmental sustainability intensify, renewable energy sources like solar photovoltaic (PV) systems have gained significant attention. An integrated approach is proposed, leveraging spatial analysis using Helioscope, a 3D solar design tool, incorporated with Geographic Information System (GIS) data. This study conducted a spatial analysis of Cape Peninsula University of Technology (CPUT) Bellville campus’s potential for renewable energy, and the results are promising. The research indicated that the campus has enough rooftop space to optimally place solar panels with a capacity of 7.8 megawatts, which is more than the campus’s total energy needs of 6.3 megawatts. This study identified 13,249 modules that can be optimally placed to achieve this. Full article

The market for coloured photovoltaic modules offers a key opportunity for building-integrated photovoltaics (BIPV), as it enables more aesthetic and seamless integration into architecture. This study investigates how three common BIPV colours—anthracite, green, and terracotta—affect the performance of a BIPV ventilated façade. It presents a year-long field comparison, including thermal modelling and residual spectral loss estimation, of three screen-printed coloured BIPV strings installed on an east-facing ventilated façade, at the CIEMAT research centre in Madrid, Spain. Although anthracite modules exhibit the highest efficiency under standard test conditions (STC), green modules achieve the best performance ratio (PR) due to their lower spectral and thermal impacts. Results indicate that system design factors—such as façade orientation, module positioning and rear ventilation—significantly influence thermal and electrical performance. In particular, changes in solar spectral irradiance can have a strong impact on the performance of coloured modules, mainly due to their distinct spectral reflectance characteristics. This effect is especially relevant for reddish modules mounted on east- and west-facing façades, which, on clear days, receive sunlight with spectra shifted toward the near-infrared (NIR) region compared with midday conditions, which are closer to the standard AM1.5G solar spectrum. Prior optical characterisation, particularly spectral reflectance measurements, is therefore essential to accurately assess and predict the performance of coloured modules under real operating conditions. Full article

With the rapid development of the photovoltaic industry, the issue of high-value conversion and utilization of end-of-life photovoltaic modules emerges. This study proposes using them in silicon-air batteries and designs a one-step pretreatment process to obtain two types of anode materials: AB@Si and TC@Si. Additionally, to enhance the electrochemical performance of retired crystalline silicon from PV modules as anodes for silicon-air batteries and improve their mass conversion efficiency, this study introduces Triton X-100 into the KOH electrolyte to inhibit chemical corrosion of the anodes and investigates the mechanism of action of Triton X-100. The results indicate that the surfaces of AB@Si and TC@Si exhibit a pyramidal structure, demonstrating excellent passivation resistance when used in silicon-air batteries, with maximum mass conversion efficiencies of 3.5% and 1.83%, respectively. Under the influence of Triton X-100, the maximum mass conversion efficiencies reach 6.39% and 3.09%, respectively. Polarization curves and mass loss under non-current conditions indicate that Triton X-100 primarily affects the chemical corrosion process of the silicon anode, while its impact on electrochemical corrosion is negligible. Results from contact angle measurements and adsorption energy calculations indicate that Triton X-100 adsorbs onto the silicon surface via benzene ring groups or OH groups, reducing hydrophilicity and delaying the self-corrosion process of silicon, thereby improving the battery′s discharge lifespan and mass conversion efficiency. Full article

This paper presents a theoretical engineering feasibility analysis of the RK-X photocatalytic process for In Situ Resource Utilisation (ISRU) on Mars. Experimental validation under simulated Martian conditions is the essential next step before any mission deployment claim can be made. The RK-X process converts the two most abundant Martian resources, atmospheric carbon dioxide (CO₂) and subsurface water ice (H₂O), into formic acid (HCOOH) and oxygen (O₂) through a fulvic acid-based photocatalytic cycle validated at the industrial scale in Hungary. A reference module processing 10 tonnes of CO₂ per Earth year yields 10.459 tonnes of formic acid and 3.636 tonnes of oxygen, sufficient to sustain a six-person crew for approximately two Earth years with a 198% safety margin over nominal respiratory demand. The economic analysis indicates that importing equivalent oxygen from Earth costs $1.82–$3.64 million per year; equivalent energy storage (Li-ion) costs $30.5–$61 million for one-time use. Formic acid stores 15.25 MWh of energy in ambient-stable liquid form at a round-trip efficiency of 68.64% without cryogenic infrastructure. A photovoltaic array of 55.37 m² provides the primary energy source; a kilowatt-class nuclear fission reactor constitutes the strategic opportunity for continuous, dust-storm-immune operation with free thermal co-generation. Three critical research gaps have been identified requiring laboratory validation before Mars deployment: (i) catalyst performance at the Martian CO₂ partial pressure (p(CO₂) < 10 mbar, T = 15 °C); (ii) water ice and dry ice extraction at an operational scale; and (iii) integrated closed-loop system demonstration. Built on Earth-proven chemistry with identified, addressable development pathways, the RK-X process theoretically resolves the problems of oxygen supply, seasonal energy storage, water management, and cryogenic infrastructure within a single closed-loop chemical cycle. Full article

In Brazil, more than 80% of households rely on electricity for water heating, representing approximately 13% of residential electricity consumption and significantly contributing to peak grid demand. As a prominent alternative for supplying household thermal energy and reducing grid stress, this study experimentally evaluates, under tropical climate conditions, the performance of a modular water-based photovoltaic–thermal (PVT) system and compares it with a conventional photovoltaic (PV) system operating simultaneously under identical environmental conditions. The PVT system, based on commercial PV modules coupled to roll-bond heat exchangers, a storage tank, and a shower outlet, was tested under three hydraulic regimes: natural thermosiphon, closed-loop, and Forced circulation. A dedicated ESP32-based data acquisition system, integrated with a cloud platform, continuously monitors electrical, thermal, and meteorological variables. Results show that PVT modules exhibit a small electrical efficiency reduction due to increased cell temperatures, which is largely compensated by the simultaneous thermal generation, yielding overall efficiency gains of 74.04%, 76.53%, and 7.62% over the reference PV system for Normal, Forced, and Closed circulation, respectively. The comparative analysis identifies Forced-circulation scheduling and the matching between thermal generation and consumption as key factors for performance optimization. The findings provide practical guidelines for deploying PVT systems to replace electric showers in tropical regions, reducing residential electricity consumption and mitigating peak-demand stress on the grid. Full article

Solar tracking systems (STSs) are widely adopted in photovoltaic (PV) installations to increase energy yield by maintaining favorable module orientation relative to the sun’s trajectory. This paper presents a systematic review of STSs from an electrical engineering perspective, focusing on electrical performance, control strategies, and system integration aspects relevant to grid-connected PV applications. Fixed-tilt, single-axis, and dual-axis configurations are comparatively assessed in terms of output power, annual energy yield, influence on I–V and P–V characteristics, and auxiliary power consumption. The analysis emphasizes net energy gain rather than gross energy improvement. Control strategies are classified as open-loop, closed-loop, hybrid, and intelligent approaches. Their impact on tracking accuracy, actuator duty cycles, electrical stability, and coordination with maximum power point tracking (MPPT) algorithms is critically examined. A bibliographic and scientometric analysis is conducted to identify research trends, dominant themes, and existing gaps. The results indicate that single-axis tracking often provides the most favorable balance between energy gain and auxiliary consumption in utility-scale systems, while dual-axis configurations achieve higher absolute yield at increased complexity. The review highlights the need for standardized net-energy evaluation and grid-aware tracking strategies. Full article

The photovoltaic (PV) sector is at present one of the crucial components of renewable power engineering and one of the key pillars in the global power system transformation. This article compares the annual energy yields from real-life PV installations built in Częstochowa (Poland)—three stationary PV installations and one tracker PV installation. The PV installations are located within a 2 km radius, and except for very early morning and late evening hours, there is no shading, thus identical solar exposure conditions can be assumed for all analyzed PV installations. In the case of stationary PV installations, maximum energy production may be achieved if the PV modules are southward oriented and related to their tilt angles. In the case of installations on buildings, PV modules are rarely installed in their optimal orientation. Most often, the orientation of PV modules is directly related to the location of the building and the geometric structure of the roof. A tracking system, which involves mounting PV modules on platforms that track the sun’s path, increases energy yield per module power. Limitations for tracking PV systems include the requirement for adequate, shade-free space for their construction as well as high costs of the structure itself and its maintenance. During the period analyzed (2022–2025), no PV system outages resulting from exceeding the permissible voltage in the distribution network were recorded. The energy produced by individual PV systems was also compared with the values calculated in a simulation program used to estimate annual energy yields during the system design phase. Full article