Search Results (301)

In this paper, a robust optimized controller is implemented in the photovoltaic generator system (PVGS). The PVGS is composed of individual photovoltaic (PV) cells, which convert solar energy to electrical energy. To optimize the efficiency of the PVGS under variable solar irradiance and temperatures, a maximum power point tracking (MPPT) controller is necessary. Additionally, the PVGS output voltage is typically low for many applications. To achieve the MPPT and to gain the output voltage, an increasing boost converter (IBC) is employed. Then, two issues should be considered in MPPT. At first, a smooth control signal for adjusting the duty cycle of the IBC is important. Another critical issue is the PVGS and IBC unknown sections, i.e., the total system uncertainty. Therefore, to address the system uncertainties and to regulate the smooth duty cycle of the converter, a robust dynamic sliding mode control (DSMC) is proposed. In DSMC, a low-pass integrator is placed before the system to suppress chattering and to produce a smooth actuator signal. However, this integrator increases the system states, and hence, a sliding mode observer (SMO) is proposed to estimate this additional state. The stability of the proposed control scheme is demonstrated using the Lyapunov theory. Finally, to demonstrate the effectiveness of the proposed method and provide a reliable comparison, conventional sliding mode control (CSMC) with the same proposed SMO is also implemented. Full article

Improving photovoltaic (PV) panel performance under extreme climatic conditions is critical for advancing sustainable energy systems. In hyper-arid regions, elevated operating temperatures significantly reduce panel efficiency. This study investigates and compares three cooling techniques—air cooling, water cooling, and porous media cooling—using thermal and electrical modeling based on CFD simulations in ANSYS. The numerical model replicates a PV system operating under peak solar irradiance (900 W/m²) and realistic ambient conditions in Adrar, Algeria. Simulation results show that air cooling leads to a modest temperature reduction of 6 °C and a marginal efficiency gain of 0.25%. Water cooling, employing a top-down laminar flow, reduces cell temperature by over 35 °C and improves net electrical output by 30.9%, despite pump energy consumption. Porous media cooling, leveraging passive evaporation through gravel, decreases panel temperature by around 30 °C and achieves a net output gain of 26.3%. Mesh sensitivity and validation against experimental data support the accuracy of the model. These findings highlight the significant potential of water and porous material cooling strategies to enhance PV performance in hyper-arid environments. The study also demonstrates that porous media can deliver high thermal effectiveness with minimal energy input, making it a suitable low-cost option for off-grid applications. Future work will integrate long-term climate data, real diffuser geometries, and experimental validation to further refine these models. Full article

Photovoltaic (PV) systems are key renewable energy sources due to their ease of implementation, scalability, and global solar availability. Enhancing their lifespan and performance is vital for wider adoption. Identifying degradation root causes is essential for improving PV design and maintenance, thus extending lifespan. This paper proposes a hybrid fault diagnosis method combining a bond graph-based PV cell model with empirical degradation models to simulate faults, and a deep learning approach for root-cause detection. The experimentally validated model simulates degradation effects on measurable variables (voltage, current, ambient, and cell temperatures). The resulting dataset trains an Optimized Feed-Forward Neural Network (OFFNN), achieving 75.43% accuracy in multi-class classification, which effectively identifies degradation processes. Full article

The flow velocity field of the oil-filled acrylic solar sphere is assessed using flow visualization, which includes image processing and Particle Image Velocimetry (PIV) measurements. The temperature, sphere size, and thickness all have an impact on the generated convection flow. The acrylic sphere, a contemporary concentrated photovoltaic technology, collects solar energy and concentrates it into a small focal region. This focus point is positioned precisely above a multi-junction apparatus that serves as an appliance for concentrator cells. Instead of producing the same amount of electricity as a typical photovoltaic panel (PV), this gadget can generate an enormous power rate directly. There are numerous industrial uses for acrylic spheres as well. This study paper aims to examine the flow properties inside a sphere and investigate the impact of the sphere’s temperature, size, and thickness on the fluid motion’s flow velocity. Furthermore, the goal of this research is to elucidate the correlation between these variables to enhance power-generating performance by achieving higher efficiency. The findings demonstrated that the flow structure value is greatly affected by the sphere size, thickness, and temperature. It is discovered that when the spherical thickness lowers, the velocity rises. As a result, the sphere performs better at lower liquid temperatures (35–40 °C), larger sizes (15–30 cm diameter), and reduced acrylic thickness (3–4 mm), leading to up to a 23% increase in power output and a 35–50% rise in internal flow velocity compared to thicker and smaller configurations. Therefore, reducing the sphere thickness by 1 mm results in approximately a 10% increase in average flow velocity at the top of the sphere, corresponding to an increase of about 0.0001 m/s. Notably, the sphere with a 3 mm thickness demonstrates superior power and efficiency compared to other thicknesses. As the sphere’s thickness decreases, the solar sphere’s output power and efficiency rise. The amount of sunlight absorbed by the acrylic photons increases with decreasing acrylic layer thickness; hence, the greater the output power, the higher the efficiency that follows. Full article

The aim of this study was the hydrothermal leaching of silver from waste monocrystalline silicon (m-Si) and polycrystalline silicon (p-Si) photovoltaic panel (PV) cells using organic acids, namely oxalic acid (OA) and citric acid (CA). Before leaching, two different pretreatment procedures were applied. First, the fluoropolymer backsheet was manually removed from the panel pieces and, then, the samples were subjected to high-temperature heating for the thermal degradation of the ethylene vinyl acetate (EVA) polymer. When removal by hand was not feasible, the second pretreatment procedure was followed by toluene immersion to remove the EVA and backsheet and separate the cells, glass, and films. After pretreatment, 4 M HCl leaching was applied to remove the aluminum layer from the cells. The remaining cells were subjected to hydrothermal leaching with organic acids to extract the silver. Several hydrothermal parameters were investigated, such as acid concentration (1-1.5-2 M), processing time (60-105-150 min), and temperature (150-180-210 °C), while the liquid-to-solid (L/S) ratio was fixed at 30 mL: 1 g, based on preliminary tests. Response surface methodology (RSM) was applied to optimize the hydrothermal leaching parameters. The optimized parameters were 210 °C, 95 min, 2 M CA or 210 °C, 60 min, 1 M OA. OA was more effective in Ag leaching than CA. The results were compared to HNO₃ leaching. The green leaching of silver from end-of-life PV panels with organic acids is an environmentally beneficial route. Full article

An experimental setup was developed, incorporating a monitored DualSun^® photovoltaic–thermal (PV/T) panel and a weather station to continuously record real-time climatic conditions. This setup enables an hour-by-hour comparison between the actual performance observed under real-world conditions and the predictions generated by the thermal model. The generated dataset was used to evaluate a thermal model derived from the literature, comparing its predictions with measured data. The model adopts a quasi-steady-state, one-dimensional approach based on heat balance equations applied to both the photovoltaic cells and the heat transfer fluid. Conducted during the summer of 2022, the experiment provides valuable insights into the accuracy of the literature-based thermal model under summer meteorological conditions. The results show a good correlation between the experimental data and the model’s predictions. The average deviation observed for the outlet fluid temperature is 0.1 °C during the day and 1.3 °C at night. Consequently, the findings underscore the model’s effectiveness for evaluating daytime performance, while also pointing out its limitations for nighttime predictions, especially when hybrid PV/T collectors are used for applications such as nighttime free cooling. Full article

The rise in temperature worldwide, especially in hot regions with extreme weather conditions, has made climate change one of the critical issues that degrades the solar photovoltaic (PV) system performance. In this paper, a new design of solar cells based on plasmonic thin-film Silver (Ag) technology is introduced. The new design is characterized by enhancing thermal effects, optical power absorption, and output power significantly, thus compensating for the deterioration in the solar cells efficiency when the ambient temperature rises to high levels. The temperature distribution on a PV solar module is determined using a three-dimensional computational fluid dynamics (CFD) model that includes the front glass, crystalline cells, and back sheet. Experimental and analytical results are presented to validate the CFD model. The parameters of temperature distribution, absorbed optical power, and output electrical power are considered to evaluate the device performance during daylight hours in summer. The effects of solar radiation falling on the solar cell, actual temperature of the environment, and wind speed are investigated. The results show that the proposed cells’ temperature is reduced by 1.2 °C thanks to the plasmonic Ag thin-film technology, which leads to enhance 0.48% real value as compared to that in the regular solar cells. Consequently, the absorbed optical power and output electrical power of the new solar cells are improved by 2.344 W and 0.38 W, respectively. Full article

Fuel cells, propulsion systems, and reaction control systems (RCSs) are just a few of the space applications that depend on pressure vessels (PVs) to safely hold high-pressure fluids while enduring extreme environmental conditions both during launch and in orbit. Under these challenging circumstances, PVs must be lightweight while retaining structural integrity in order to increase the efficiency and lower the launch costs. PVs have significant challenges in space conditions, such as extreme vibrations during launch, the complete vacuum of space, and sudden temperature changes based on their location within the satellite and orbit types. Determining the operational temperature limits and endurance of PVs in space applications requires assessing the combined effects of these factors. As the main propellant for satellites and rockets, hydrogen has great promise for use in future space missions. This study aimed to assess the structural integrity and determine the thermal operating limits of different types of hydrogen pressure vessels using finite element analysis (FEA) with Ansys 2019 R3 Workbench. The impact of extreme space conditions on the performances of various kinds of hydrogen pressure vessels was analyzed numerically in this work. This study determined the safe operating temperature ranges for Type 4, Type 3, and Type 1 PVs at an operating hydrogen storage pressure of 35 MPa in an absolute vacuum. Additionally, the dynamic performance was assessed through modal and random vibration analyses. Various aspects of Ansys Workbench were explored, including the influence of the mesh element size, composite modeling methods, and their combined impact on the result accuracy. In terms of the survival temperature limits, the Type 4 PVs, which consisted of a Nylon 6 liner and a carbon fiber-reinforced epoxy (CFRE) prepreg composite shell, offered the optimal balance between the weight (56.2 kg) and a relatively narrow operating temperature range of 10–100 °C. The Type 3 PVs, which featured an Aluminum 6061-T6 liner, provided a broader operational temperature range of 0–145 °C but at a higher weight of 63.7 kg. Meanwhile, the Type 1 PVs demonstrated a superior cryogenic performance, with an operating range of −55–54 °C, though they were nearly twice as heavy as the Type 4 PVs, with a weight of 106 kg. The absolute vacuum environment had a negligible effect on the mechanical performance of all the PVs. Additionally, all the analyzed PV types maintained structural integrity and safety under launch-induced vibration loads. This study provided critical insights for selecting the most suitable pressure vessel type for space applications by considering operational temperature constraints and weight limitations, thereby ensuring an optimal mechanical–thermal performance and structural efficiency. Full article

In response to the challenges posed by the high proportion of photovoltaic (PV) in electrolytic aluminum (EA) industrial isolated microgrids, such as the low carbon economy problem and the dynamic dispatchability of EA and its combined heat and power (CHP) unit, a multi-timescale optimal dispatching method considering the dynamic temperature characteristics of an aluminum electrolytic cell is proposed for an EA isolated microgrid. Firstly, based on an electrothermal coupling model, the electrolyte dynamic temperature expression of aluminum electrolytic is derived, and the optimal dispatching method of an EA load considering the dynamic temperature characteristics of EA is proposed. Secondly, based on the carbon emission models of CHP units and EA loads, and with the optimization objective of maximizing the operating revenue of industrial isolated microgrids, a day-ahead-intraday multi-timescale optimal dispatching model considering the participation of EA loads in the demand response (DR) for isolated microgrids was established. Finally, numerical results for an industrial isolated microgrid have verified the effectiveness of the proposed method in improving the PV consumption rate and realizing low-carbon and economic operation of industrial islanded microgrids. Full article

Organic phase change materials (PCMs) have been widely studied for thermal management applications, such as the passive cooling of silicon photovoltaic (PV) cells, whose efficiency is negatively affected by rising temperature. The aim of the present study is to investigate the shape stabilization of PCMs by using expanded graphite (EG) as a highly conductive supporting matrix, leading to the development of novel PCM/EG composites with melting temperatures in the range 30–50 °C. Different organic PCMs were selected and compared, i.e., two paraffins and a eutectic mixture of fatty acids (myristic and palmitic acid). The EG was vacuum-impregnated with organic PCMs, and, subsequently, powdery composites were cold-compacted to obtain dense heat-absorbing panels. The thermal conductivity was enhanced up to 6 W/m·K, guaranteeing composites with a melting enthalpy of 160 to 220 J/g. This study found that the EG vacuum impregnation method is suitable for PCM shape stabilization, and cold compaction allows for the formation of solid panels with improved thermal response. The obtained PCM/EG composites were utilized to produce panels of about 6 × 6 × 2 cm³, suitable for the thermal management of silicon PV. Full article

Accurate temperature prediction in bifacial photovoltaic (PV) modules is critical for optimizing solar energy systems. Conventional models face challenges to balance accuracy, interpretability, and computational efficiency. This study addresses these limitations by introducing a symbolic regression (SR) framework based on genetic algorithms to model nonlinear relationships between environmental variables and module temperature without predefined structures. High-resolution data, including solar radiation, ambient temperature, wind speed, and PV module temperature, were collected at 5 min intervals over a year from a 19.9 MW bifacial PV plant with trackers in San Marcos, Colombia. The SR model performance was compared with multiple linear regression, normal operating cell temperature (NOCT), and empirical regression models. The SR model outperformed others by achieving a root mean squared error (RMSE) of 4.05 °C, coefficient of determination (R²) of 0.91, Spearman’s rank correlation coefficient of 0.95, and mean absolute error (MAE) of 2.25 °C. Its hybrid structure combines linear ambient temperature dependencies with nonlinear trigonometric terms capturing solar radiation dynamics. The SR model effectively balances accuracy and interpretability, providing information for modeling bifacial PV systems. Full article

Green hydrogen is increasingly recognized as a sustainable energy vector, offering significant potential for the industrial sector, buildings, and sustainable transport. As countries work to establish infrastructure for hydrogen production, transport, and energy storage, they face several challenges, including high costs, infrastructure complexity, security concerns, maintenance requirements, and the need for public acceptance. To explore these challenges and their environmental impact, this study proposes a hybrid sustainable infrastructure that integrates photovoltaic solar energy for the production and storage of green hydrogen, with PEMFC fuel cells and a hybrid Power-to-Electricity (PtE) and Power-to-Gas (PtG) configurations. The proposed system architecture is governed by an innovative energy optimization and management (EMS) algorithm, allowing forecasting, control, and supervision of various PV–hydrogen–Grid transfer scenarios. Additionally, comprehensive daily and seasonal simulations were performed to evaluate power sharing, energy transfer, hydrogen production, and storage capabilities. Dynamic performance assessments were conducted under different conditions of solar radiation, temperature, and load, demonstrating the system’s adaptability. The results indicate an overall efficiency of 62%, with greenhouse gas emissions reduced to 1% and a daily production of hydrogen of around 250 kg equivalent to 8350 KWh/day. Full article

Mountain photovoltaic (PV) power stations cover vast areas and contain dense equipment. Once direct current arc faults occur in PV modules, they can pose a serious thermal threat to surrounding facilities and combustible materials, potentially resulting in a PV array fire accident. In this work, a series of PV module fire experiments were conducted to investigate the burning characteristics of PV modules exposed to the pool fire. The burning process, burning damage extent, and temperature distribution were measured and analyzed. The results showed that the surfaces of PV modules exhibited different burning characteristics due to the pool fire. Based on different characteristics, the front side was classified into four zones: intact zone, delamination zone, carbonization zone and burn-through zone. The back side was similarly divided into four zones: undamaged backsheet zone, burnt TPT zone, cell detachment zone and burn-through zone. Meanwhile, the burning process and surface temperature rise rate of intact PV modules were significantly lower than those of cracked modules at the same inclination angle. Cracked modules exhibited a heightened susceptibility to being rapidly burnt through by the pool fire. As the inclination angle increased from 0° to 60°, the burning damage extent and the expansion rate of high-temperature regions initially ascended and subsequently decreased, reaching their maximum at the inclination angle of 15°. These findings can offer valuable insights that can serve as a reference for the fire protection design and risk assessment of mountain PV power stations, ensuring their safe operation. Full article

Photovoltaic (PV) energy is gaining traction due to its direct conversion of sunlight to electricity without harming the environment. It is simple to install, adaptable in size, and has low operational costs. The power output of PV modules varies with solar radiation and cell temperature. To optimize system efficiency, it is crucial to track the PV array’s maximum power point. This paper presents a novel fixed-point FPGA design of a nonlinear maximum power point tracking (MPPT) controller based on synergetic control theory for driving autonomously standalone photovoltaic systems. The proposed solution addresses the chattering issue associated with the sliding mode controller by introducing a new strategy that generates a continuous control law rather than a switching term. Because it requires a lower sample rate when switching to the invariant manifold, its controlled switching frequency makes it better suited for digital applications. The suggested algorithm is first emulated to evaluate its performance, robustness, and efficacy under a standard benchmarked MPPT efficiency (${\eta }_{MPPT}$) calculation regime. FPGA has been used for its capability to handle high-speed control tasks more efficiently than traditional micro-controller-based systems. The high-speed response is critical for applications where rapid adaptation to changing conditions, such as fluctuating solar irradiance and temperature levels, is necessary. To validate the effectiveness of the implemented synergetic controller, the system responses under variant meteorological conditions have been analyzed. The results reveal that the synergetic control algorithm provides smooth and precise MPPT. Full article

The traditional uniform parallel microchannel structure in PV/T system results in the formation of high-temperature zones in a silicon cell. This paper proposes using the iterative optimization to change the uniform arrangement of microchannel width to a non-uniform arrangement, making the temperature distribution more uniform. A vertical Z-shape structure is selected as the optimization object for its relatively good performance. Its middle path resistance is high, resulting in a high-temperature zone in the middle-upper part of a silicon cell. Three characteristic parameters are compared to select the optimal monitored variable for the iterative calculations. Specific flow rate is found to be the best characteristic parameter, followed by flow rate, while flow velocity cannot be used for iteration. The optimization significantly improves the uniformity of temperature distribution in the silicon cell. The air layer further enhances the performance of the PV/T system, with a thickness of 7 mm being optimal. At the ambient temperature from −15 °C to 40 °C, the outlet water temperature ranges from 37.7 °C to 53.7 °C, and the overall efficiency ranges from 40.8% to 73.0%, showing good application potential. Full article