Search Results (219)

The ground impedance (insulation resistance R_isol) of photovoltaic (PV) modules is usually measured only in the dry state, even though arrays frequently operate under dew-wet or rain-wet conditions, when leakage paths can change. We measured dry insulation resistance R_dry and IEC 61215 MQT 15 wet leakage resistance R_wet for N = 37 field-aged crystalline-silicon modules from utility-scale plants and related the results to the IEC 40 MΩ·m² criterion (R_wet × A ≥ 40). The measurements used 1000 V DC and a 2 min dwell; R_wet was obtained in a salted bath with a solution resistivity < 3500 Ω·cm. The median R_dry was 42.4 GΩ, whereas the median R_wet was 462.5 MΩ, resulting in a median R_dry/R_wet ratio of ~110×. Three modules (8.1%) failed the 40 MΩ·m² limit already in the dry state, whereas eight modules (21.6%) failed under IEC-wet conditions; five were dry-pass/wet-fail cases that would have passed dry screening. For a representative area A = 1.8 m², a practical conservative dry triage threshold of approximately 55.5 GΩ identifies modules needing IEC-wet verification rather than serving as a stand-alone limit. Overall, combining dry and IEC-wet measurements improves safety and supports sustainability through resource-efficient repowering/revamping and end-of-life decisions in large PV fleets, particularly in hot climates. Full article

Amidst the ongoing global energy crisis, environmental deterioration, and the exacerbation of climate change, the development of renewable energy, particularly solar energy, has become a central topic in the global energy transition. This study investigates a solar photovoltaic thermal (PVT) heat pump system that utilizes an expanded honeycomb-channel PVT module to enhance the comprehensive utilization efficiency of solar energy. A simulation platform for the solar PVT heat pump system was established using Aspen Plus software (V12), and the system’s performance impact mechanisms and engineering applications were researched. The results indicate that solar irradiance and the circulating water temperature within the PVT module are the primary factors affecting system performance: for every 100 W/m² increase in solar irradiance, the coefficient of performance for heating (COP_h) increases by 13.7%, the thermoelectric comprehensive performance coefficient (COP_co) increases by 14.9%, and the electrical efficiency of the PVT array decreases by 0.05%; for every 1 °C increase in circulating water temperature, the COP_h and COP_co increase by 11.8% and 12.3%, respectively, and the electrical efficiency of the PVT array decreases by 0.03%. In practical application, the system achieves an annual heating capacity of 24,000 GJ and electricity generation of 1.1 million kWh, with average annual COP_h and COP_co values of 5.30 and 7.60, respectively. The Life Cycle Cost (LCC) is 13.2% lower than that of the air-source heat pump system, the dynamic investment payback period is 4–6 years, and the annual carbon emissions are reduced by 94.6%, demonstrating significant economic and environmental benefits. This research provides an effective solution for the efficient and comprehensive utilization of solar energy, utilizing the low-global-warming-potential refrigerant R290, and is particularly suitable for combined heat and power applications in regions with high solar irradiance. Full article

Offshore floating photovoltaic (FPV) platforms are usually deployed in shallow waters with large tidal variations, where the modules of FPV are connected with each other via the connectors to form an array and mounted to the seabed via the mooring system. Therefore, the mooring system and module connectors have significant influence on the dynamic response characteristics of FPV. In targeting such shallow waters with large tidal ranges, this paper proposes four integrated mooring-connection schemes based on configuration and parameter customization guided by adaptability optimization, including two kinds of mooring systems, named as horizontal mooring system and catenary mooring system with clumps, and two kinds of connection schemes, named as cross-cable connection and hybrid connection, are proposed. The feasibility of the mooring systems to adhere to the tidal range and the influence of the connection schemes on the dynamic response of the FPV are numerically investigated in detail. Results indicate the two mooring systems have comparable positioning performance; horizontal mooring offers slightly better tidal adaptability but much higher mooring tension, compromising system safety. Hybrid connection yields smaller surge amplitudes than cross-cable connection but generates excessively large connection forces, also posing safety risks. Comprehensive comparison indicates that catenary mooring with clumps combined with cross-cable connection imposes lower requirements on platform structural safety factors, while horizontal mooring with cross-cable connection exhibits stronger adaptability to water level and environmental load direction changes in shallow waters. Full article

This study investigates the influence of array height, irradiance, and wind speed on temperature difference and thermal gradients in photovoltaic (PV) arrays operating in hot, arid conditions. A field experiment was conducted in Mesa, Arizona (latitude 33° N), using two fixed-tilt PV module arrays installed at different elevations—one at 1 m and the other at 2 m above ground level. Each array comprised seven monocrystalline PV modules arranged in a single row with an 18° tilt angle optimized for summer performance. Data were collected between June and September 2025, and the analysis was restricted to 10:00–13:00 h to avoid shading and ensure uniform irradiance exposure on both arrays. Measurements included module backsheet temperatures at the center and edge modules, ambient temperature, plane-of-array (POA) irradiance, and wind speed. By maintaining identical orientation, tilt, and exposure conditions across all PV configurations, the influence of array height was isolated by comparing module operating temperatures between the 1-m and 2-m installations (inter-array comparison). Under the same controlled conditions, the setup also enabled an examination of how the intra-array comparison affects temperature gradients along the PV modules themselves, thereby revealing edge-center thermal non-uniformities. Results indicate that the 2 m array consistently operated 1–3 °C cooler than the 1 m array, confirming the positive impact of elevation on convective cooling. This reduction corresponds to a 0.4–0.9% improvement in module efficiency or power based on standard temperature coefficients of crystalline silicon modules. The 1 m array exhibited a mean edge–center intra-array temperature gradient of −1.54 °C, while the 2 m array showed −2.47 °C, indicating stronger edge cooling in the elevated configuration. The 1 m array displayed a broader temperature range (−7 °C to +3 °C) compared to the 2 m array (−5 °C to +2 °C), reflecting greater variability and weaker convective uniformity near ground level. The intra-array temperature gradient became more negative as irradiance increased, signifying intensified edge cooling under higher solar loading. Conversely, wind speed inversely affected ΔT, mitigating thermal gradients at higher airflow velocities. These findings highlight the importance of array height (inter-array), string length (intra-array), irradiance, and wind conditions in optimizing PV system thermal and electrical performance. Full article

To explore the potential of solar energy in the pursuit of a more sustainable aviation sector, this research examines the feasibility of solar photovoltaic systems for battery recharge of electric or electric hybrid aircraft deployed at four airports in North Africa and North, Central, and South Europe, respectively: Cairo International, London Heathrow, Milan Malpensa, and Rome Fiumicino. Employing PVGIS software with Google Maps, a site-specific photovoltaic array can be designed, optimizing module tilt and orientation to maximize solar energy collection across various climatic conditions. The energy production of the photovoltaic systems at the selected airports is compared to the energy demand required for the annual recharge of the batteries (28 MWh each) used in a widely popular medium-range aircraft, the Airbus A320. Although the calculated amount of energy, allowing for daily capacities ranging from 6 to 10 batteries on average, is insufficient to support the extensive demand associated with the typical air traffic in such airports, the potential of solar energy to decarbonize aircraft seems an appropriate approach to be pursued. Locations with limited solar access necessitate hybrid solutions, especially in sunny regions. Full article

Agrivoltaic (APV) systems co-locate agricultural production and photovoltaic (PV) electricity generation on the same land to maximize land use efficiency. This study proposes an integrated assessment framework that jointly evaluates crop yield and electricity generation in APV systems. Unlike many previous APV studies that estimated crop responses from empirical PAR–photosynthesis relationships, this framework explicitly couples a process-based rice growth model (DSSAT-CERES-Rice) with irradiance and PV performance simulations (Honeybee-Radiance and PVlib) in a single workflow. The five-stage framework comprises (i) meteorological data acquisition and processing; (ii) 3D modeling in Rhinoceros; (iii) calculation of module front and rear irradiance and crop height irradiance using Honeybee; (iv) crop yield calculation with DSSAT; and (v) electricity generation calculation with PVlib. Using bifacial PV modules under rice cultivation in Gochang, Jeollabuk-do (Republic of Korea), simulations were performed with ground coverage ratio (GCR) and PV array azimuth as key design variables. As GCR increased from 20% to 50%, crop yield reduction (CYR) rose from 12% to 33%, while land equivalent ratio (LER) increased from 128% to 158%. To keep CYR within the domestic guideline of 20% while maximizing land use, designs with GCR ≤ 30% were found to be appropriate. At GCR 30%, CYR of 17–18% and LER of 139–140% were achieved, securing a balance between agricultural productivity and electricity generation. Although PV array azimuth had a limited impact on crop yield and electricity generation, southeast or southwest orientations showed more uniform irradiance distributions over the field than due south. A simple economic assessment was also conducted for the study site to compare total annual net income from rice and PV across GCR scenarios. The proposed framework can be applied to other crops and sites and supports design-stage decisions that jointly consider crop yield, electricity generation, and economic viability. Full article

Driven by the global energy transition and carbon-neutrality goals, virtual power plants (VPPs) are expected to aggregate distributed energy resources and participate in multiple electricity markets while achieving economic efficiency and low carbon emissions. However, the strong volatility of wind and photovoltaic generation, together with the coupling between electric and thermal loads, makes real-time VPP scheduling challenging. Existing deep reinforcement learning (DRL)-based methods still suffer from limited predictive awareness and insufficient handling of physical and carbon-related constraints. To address these issues, this paper proposes an improved model, termed SAC-LAx, based on the Soft Actor–Critic (SAC) deep reinforcement learning algorithm for intelligent VPP scheduling. The model integrates an Attention–xLSTM prediction module and a Linear Programming (LP) constraint module: the former performs multi-step forecasting of loads and renewable generation to construct an extended state representation, while the latter projects raw DRL actions onto a feasible set that satisfies device operating limits, energy balance, and carbon trading constraints. These two modules work together with the SAC algorithm to form a closed perception–prediction–decision–control loop. A campus integrated-energy virtual power plant is adopted as the case study. The system consists of a gas–steam combined-cycle power plant (CCPP), battery storage, a heat pump, a thermal storage unit, wind turbines, photovoltaic arrays, and a carbon trading mechanism. Comparative simulation results show that, at the forecasting level, the Attention–xLSTM (Ax) module reduces the day-ahead electric load Mean Absolute Percentage Error (${\mathrm{M}}_{\mathrm{A}\mathrm{P}\mathrm{E}}$) from 4.51% and 5.77% obtained by classical Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) models to 2.88%, significantly improving prediction accuracy. At the scheduling level, the SAC-LAx model achieves an average reward of approximately 1440 and converges within around 2500 training episodes, outperforming other DRL algorithms such as Deep Deterministic Policy Gradient (DDPG), Twin Delayed Deep Deterministic Policy Gradient (TD3), and Proximal Policy Optimization (PPO). Under the SAC-LAx framework, the daily net operating cost of the VPP is markedly reduced. With the carbon trading mechanism, the total carbon emission cost decreases by about 49% compared with the no-trading scenario, while electric–thermal power balance is maintained. These results indicate that integrating prediction enhancement and LP-based safety constraints with deep reinforcement learning provides a feasible pathway for low-carbon intelligent scheduling of VPPs. Full article

As a common large-scale civil engineering structure, cable-supported photovoltaic (PV) arrays are typically designed with a 25-year service life, with their primary structural system composed of beam-column frames, pre-tensioned cables and modules. Cable-supported photovoltaic arrays are susceptible to large-amplitude wind-induced vibrations (WIV), threatening structural safety and serviceability. This study investigates interference effects on an eight-row array that employs aeroelastic wind tunnel tests, focusing on how tilt angle and sag-to-span ratio influence vibration characteristics and interference mechanisms. Results show coupled vertical–torsional vibrations with amplitudes increasing with wind speed and that are more intense under wind suction than under wind pressure. Reducing tilt angle and sag-to-span ratio effectively suppresses vibrations and raises critical flutter speed. For interference effects, mean response demonstrates clear shielding with amplitudes decreasing leeward. In contrast, fluctuating response behavior depends on tilt angle: 5° tilt angle produces a shielding effect, while 25° tilt angle causes an amplification effect with periodic fluctuations. The 25° tilt angle shows greater sensitivity to wind speed, evidenced by decreasing interference coefficients from the second to eighth windward rows with increasing wind speed. Although reducing the sag-to-span ratio most effectively suppresses vibrations in the first windward row and consequently affects downstream interference coefficients, it does not alter the fundamental trends governed by tilt angle. Full article

The performance of large-scale photovoltaic (PV) power plants is strongly influenced by array layout parameters including module tilt angle, azimuth angle, and row spacing. These geometric variables jointly determine solar irradiance geometry, shading losses, and land-use efficiency, affecting annual energy yield and levelized cost of electricity. To achieve multi-objective comprehensive optimization of array layout parameters for a PV power generation system, a collaborative optimization strategy for PV array layout based on the lemur optimization (LO) algorithm is proposed in this paper. The method couples the Perez anisotropic irradiance model with a dynamic shading irradiance geometric model to simulate the effective insolation, incorporating land availability, shading thresholds, and maintenance access requirements. In addition, the LO algorithm is employed to solve resulting nonlinear and constrained problems, enabling an efficient global search across large parameter spaces. The case studies in Lianyungang, Dalian, and Fuzhou City show that the proposed scheme based on the LO algorithm improves annual energy yield compared with the existing optimization schemes, providing new theoretical methods and engineering application paths for the optimal layout of PV arrays. Full article

Floating photovoltaic (FPV) systems are promising for coastal aquaculture where reliable electricity is essential for pumping, oxygenation, sensing, and control. A sustainable FPV–storage hybrid tailored to monsoon-prone sites is developed, with emphasis on energy efficiency and structural resilience. The prototype combines dual-axis solar tracking with a spray-cooling and cleaning subsystem and an active wind-protection strategy that automatically flattens the array when wind speed exceeds 8.0 m/s. Temperature, wind speed, and irradiance sensors are coordinated by an Arduino-based supervisor to optimize tracking, thermal management, and tilt control. A 10 W floating module and a fixed-tilt reference were fabricated and tested outdoors in Penghu, Taiwan. The FPV achieved a 25.17% energy gain on a sunny day and a 40.29% gain under overcast and windy conditions, while module temperature remained below 45 °C through on-demand spraying, reducing thermal losses. In addition, a hybrid energy storage system (HESS), integrating a 12 V/10 Ah lithium-ion battery and a 12 V/24 Ah lead-acid battery, was validated using a priority charging strategy. During testing, the lithium-ion unit was first charged to stabilize the control circuits, after which excess solar energy was redirected to the lead-acid battery for long-term storage. This hierarchical design ensured both immediate power stability and extended endurance under cloudy or low-irradiance conditions. The results demonstrate a practical, low-cost, and modular pathway to couple FPV with hybrid storage for coastal energy resilience, improving yield and maintaining safe operation during adverse weather, and enabling scalable deployment across cage-aquaculture facilities. Full article

This paper presents a performance evaluation of a 140 kW solar array installed on the rooftop of the Mountain Line Transit Authority (MLTA) building in Morgantown, West Virginia (WV), USA, covering the period from 2013 to 2024. The grid-connected photovoltaic (PV) system consists of 572 polycrystalline PV modules, each rated at 245 watts. The study examines key performance parameters, including annual electricity production, average daily and annual capacity utilization hours (CUH), current array efficiency, and performance degradation. Monthly ambient temperature and global tilted irradiance (GTI) data were obtained from the NASA POWER website. During the assessment, observations were made regarding the tilt angles of the panels and corrosion of metal parts. From 2013 to 2024, the total electricity production was 1588 MWh, with an average annual output of 132 MWh. Over this 12-year period, the CO₂ emissions reduction attributed to the solar array is estimated at 1,413,497 kg, or approximately 117,791 kg/year, compared to emissions from coal-fired power plants in WV. The average daily CUH was found to be 2.93 h, while the current PV array efficiency in April 2024 was 10.70%, with a maximum efficiency of 14.30% observed at 2:00 PM. Additionally, an analysis of annual average performance degradation indicated a 2.28% decline from 2013 to 2016, followed by a much lower degradation of 0.17% from 2017 to 2023, as electricity production data were unavailable for most summer months of 2024. Full article

The main objective of this paper is to develop a maximum power point tracker (MPPT) for a photovoltaic module array (PVMA) under conditions of partial shading and sudden changes in solar irradiance. PVMAs exhibit nonlinear characteristics with respect to temperature and solar irradiance conditions. Therefore, when some modules in the array are shaded or when there is a sudden change in solar irradiance, the maximum power point (MPP) of the array will also change, and the power–voltage (P-V) characteristic curve may exhibit multiple peaks. Under such conditions, if the tracking algorithm employs a fixed step size, the time required to reach the MPP may be significantly prolonged, potentially causing the tracker to converge on a local maximum power point (LMPP). To address the issues mentioned above, this paper proposes a novel MPPT technique based on the nature-inspired idols algorithm (IA). The technique allows the promotion value (PM) to be adjusted through the anti-fans weight (afw) in the iteration formula, thereby achieving global maximum power point (GMPP) tracking for PVMAs. To verify the effectiveness of the proposed algorithm, a model of a 4-series–3-parallel PVMA was first established using MATLAB (2024b version) software under both non-shading and partial shading conditions. The voltage and current of the PVMAs were fed back, and the IA was then applied for GMPP tracking. The simulation results demonstrate that the IA proposed in this study outperforms existing MPPT techniques, such as particle swarm optimization (PSO), cat swarm optimization (CSO), and the bat algorithm (BA), in terms of tracking speed, dynamic response, and steady-state performance, especially when the array is subjected to varying shading ratios and sudden changes in solar irradiance. Full article

As photovoltaic (PV) deployment has expanded from rural sites to the built environment, rooftops are increasingly used for electricity generation. In these settings, the visible sky is often partially obstructed by adjacent walls, producing shading that reduces energy yield. This study quantifies the effect of wall shading on incident solar radiation and system losses, and contrasts it with inter-row (mutual) shading experienced by PV arrays in open fields. Systems installed near obscuring walls are subject to both phenomena. To our knowledge, the specific impact of wall shading on PV systems has not been examined comprehensively. We characterize how wall height governs shadow geometry, determine the resulting numbers of shaded and unshaded cells and modules, and assess how shaded modules influence the performance of the remaining modules in a series string. For the parameter set analyzed, annual energy losses are 7.7% due to wall shading and 4% due to inter-row shading, yielding a combined loss of 10.2%. The methods and results provide a practical basis for designers to estimate shading losses and expected energy production for PV systems sited near obscuring walls. Full article

Bifacial photovoltaic (PV) modules have the advantage of using light reflected off of the ground to contribute to power production. Predicting the energy gain is challenging and requires complex models to do so accurately. Often, module degradation over time is neglected in models for the sake of simplicity or is underestimated. Comparing outdoor and indoor current–voltage (I–V) performance for bifacial modules is more challenging than for monofacial modules, as there are additional variables to consider such as rear albedo non-uniformity, cell mismatch, and their effects on temperature. This challenge is compounded when heterogeneous degradation modes occur, such as polarization-type potential-induced degradation (PID-p). To examine the effects of PID-p on I–V predictions using an empirical data-driven approach, 16 bifacial PERC modules are installed outdoors on racks with different albedo conditions. A subset is exposed to high-voltage biases of −1500 V or +1500 V. Outdoor data are traced at irradiance ranges of 150–250 W/m², 500–600 W/m², and 900–1000 W/m². These curves are corrected using control module temperature, wire resistivity, and module resistance measured indoors. We examine several methods to transform indoor I–V curves to accurately, and more simply than existing methods, approximate outdoor performance for bifacial modules without and with varying levels of PID-p degradation. This way, bifacial performance modeling can be more accessible and informed by fielded, degraded modules. Distributions of percent errors between indoor and outdoor performance parameters and Mean Absolute Percent Errors (MAPEs) are used to assess method quality. Results including low-irradiance data (150–250 W/m²) are discussed but are filtered for quantifying method quality as these data introduce substantial errors. The method with the most optimal tradeoff between low MAPE and analysis simplicity involves measuring the front side of a module indoors at an irradiance equal to plane-of-array irradiance plus the product of module bifaciality and albedo irradiance. This method gives MAPE values of 1–6.5% for non-degraded and 1.6–5.9% for PID-p degraded module performance. Full article

Polarization information is essential for material identification, stress mapping, biological imaging, and robust vision under strong illumination, yet conventional approaches rely on external polarization optics and active biasing, which are bulky, alignment-sensitive, and power-hungry. A more desirable route is to encode polarization at the pixel level and read it out at zero bias, enabling compact, low-noise, and polarization imaging. Low-symmetry layered semiconductors provide persistent in-plane anisotropy as a materials basis for polarization selectivity. Here, we construct an eight-terminal radial ‘star-shaped’ Au/ReS₂ metal-semiconductor junction array pixel that operates in a genuine photovoltaic mode under zero external bias based on the photothermoelectric effect. Based on this, electrical summation of phase-matched multi-junction channels increases the signal amplitude approximately linearly without sacrificing the two-lobed modulation depth, achieving ‘gain by stacking’ without external amplification. The device exhibits millisecond-scale transient response and robust cycling stability and, as a minimal pixel unit, realizes polarization-resolved imaging and pattern recognition. Treating linear combinations of channels as operators in the polarization domain, these results provide a general pixel-level foundation for compact, zero-bias, and scalable polarization cameras and on-pixel computational sensing. Full article