Panel Surface Research Articles

Machine learning and FPGA implementation for predicting luminance decay and temperature distribution in micro-LED displays

AbstractA machine learning-based method predicts the luminance decay of micro light emitting diode (micro-LED) displays, utilizing temperature distribution and degradation experiments alongside implementation on field-programmable gate array (FPGA). Micro-LEDs, used in outdoor and indoor billboards, experience degradation due to harsh environmental conditions. To model temperature distribution in indoor advertising displays using minimal data, a temperature model is constructed based on sensor from the panel and thermal images captured by a camera, in relation to the display pattern. The input data is processed using an FPGA, which transmits the sensed temperatures and display patterns to the micro-LED panel. Multilayer Perceptron (MLP), a type of neural network, predicts the temperature distribution over the panel surface, achieving an error of less than 1.1 °C. Separate degradation models forecast luminance decay, factoring in enclosure temperature, input current, and usage time, with distinct models for red, green, and blue LEDs. Exponential curve-fitting and interpolation, following TM-21 standards, ensure long-term accuracy. The luminance decay predictions have an average error below 1.05% (approximately 9 nits). The FPGA implementation minimizes resource consumption while maintaining prediction accuracy, making it suitable for real-time applications. The degradation model accurately predicts performance over tens or even hundreds of thousands of hours, aligning with the exponential decay trends defined by TM-21.

Comprehensive evaluation of solar floating photovoltaic prospective in Saudi Arabia: Comparative experimental investigation and thermal performance analysis

Recently, floating photovoltaic systems have been regarded as a promising technology for producing clean energy by utilizing the surface of water bodies, such as lakes, rivers and oceans. This study introduces a comparative experimental study and energy performance evaluation of a 1.0 kW offshore floating photovoltaic (FPV) system and a nearby traditional ground-based PV system (GPV) installed in the eastern province of Saudi Arabia. The FPV system was deployed in the Arabian Gulf, 25 m off the coast, at an average depth of 1 to 1.5 m depending on tide, wave, and current intensity. The FPV system employs a strong novel eco-friendly platform structure made of recycled buoyant materials such as engineered plastic drums and wood. This system is anchored with tension cables and concrete blocks that can withstand the changing sea water conditions. The GPV system, on the other hand, was installed 150 m inland from the shore. Real-time monthly data monitoring and assessment indicated that FPV systems outperformed GPV systems in terms of lower PV panel surface temperatures, higher power output, and panel efficiency. Based on daily average back surface temperatures, FPV system temperature was decreased by 7.5 % to 21.34 % when compared to GPV. Moreover, the FPV system efficiency was also increased by 12.2 % when compared to the GPV system. This study aims to assist in promoting the applicability of solar floating photovoltaic systems to synergistically fulfill the requirements of sustainable electricity production for the arid costal community in Saudi Arabia and similar areas.

Recycled PET foam core sandwich panels with reinforced hybrid composite facesheets: A sustainable approach for enhanced impact resistance

This research explores the Low-Velocity Impact behavior of thermoplastic composite sandwich panels with 100% recycled Polyethylene Terephthalate (PET) foam sourced from post-consumer plastic water bottles. Being recognized as a reliable technique, hybridization using stainless-steel mesh layers was employed to reinforce the panels’ composite facesheets of sandwich panels accessible for modular housing, cold storage rooms and cargo trucks. Adequate impregnation of the reinforcement metallic mesh layer alongside proper skin-to-core adhesion was accomplished by optimizing a two-phase compression molding method. The effect of hybridization on impact response of sandwich panels with two different PET foam core thicknesses, and stacking sequence were evaluated. It was revealed that reinforcing the impacted surface of the composite sandwich panels significantly increased the perforation threshold. Moreover, analyzing the post-impact section view of the samples indicated that hybridization modified the damage propagation response of the PET foam core sandwich composites, through which the energy absorption capacity was improved.

Evaluation of self-cleaning mechanisms for improving performance of roof-mounted solar PV panels: A comparative study.

Solar panel installation is generally exposed to dust. Therefore, soiling on the surface of the solar panels significantly reduces the effectiveness of solar panels. Accumulation of dust also shortens their lifespan and reduces efficiency by about 15% to 20%. A significant reduction in the efficiency of solar photovoltaic panels has been observed due to inadequate insulation and dust deposition or shading. To harness maximum solar energy from solar panels up to their rated capacity, they need to be cleaned periodically. Therefore, the current study focuses on the comparative performance analysis of two distinct types of self-cleaning mechanisms, namely self-cleaning wiper (SCW) and nano-coating method. These methods are economical and sustainable for the standard atmospheric conditions of Pakistan. Solar panels (reference, nano-coated, and self-cleaning wiper mechanism) were placed on the roof of the Mechanical Engineering Department MUST Mirpur AJK for five weeks. Solar irradiance, dust density & performance parameters of these three panels were recorded on weekly basis. It was observed that an increase in the rate of dust deposition negatively affects the conversion efficiency of solar panels. When dust density was increased from 7.5 to 18.15 (g/m2), the percentile drops in rated power (50W) for reference, nano-coated, and self-cleaning wiper mechanisms are 37%, 33% and 23%, respectively. Moreover, the payback period of nano-coated and SCW is 1.07 years and 2.79 years, respectively.

Improving solar panel performance using MPPT optimization algorithms

One of the primary challenges faced by solar energy systems is the issue of inconsistent lighting and uneven distribution of sunlight across the surface of solar panels. These conditions can result in a substantial reduction in the power output of the panels and, in some cases, the complete failure of certain solar cells. This paper examines the effects of shading on solar panel performance, focusing on how partial shading impacts energy production and efficiency through both experimental analysis and simulation. The findings emphasize the critical influence of shading patterns and configurations on the overall efficiency of photovoltaic systems. The study highlights the necessity of implementing shading mitigation strategies and optimization algorithms to enhance energy production and ensure the reliability of solar systems operating in environments with varying light conditions. This study showed that the use of optimization algorithms in photovoltaic systems exposed to shading increases their efficiency in terms of energy saving as well as performance stability. The simulation results shows that the GWO algorithm gives a higher performance than the other algorithms in the same partial shading conditions.

Innovative cooling for PV panels: Energy and exergy assessments of water-induced V-shaped channels

Panel temperature is one of the important parameters that influences the output from a solar photovoltaic (PV) panel. Higher panel surface temperature leads to deterioration of the electrical output of the panel. Many researchers have tried to improve the panel's cooling performance using various active and passive techniques. The present experimental investigation aims to estimate the panel performance of a PV panel fitted with V-shaped aluminium cooling channels at its back surface as a passive technique. Water is made to flow in these channels to cool the panel. The volume flow rate in the cooling channels varies between 0.3LPM and 0.6LPM in steps of 0.1LPM. All the chosen flow rates used in the study tend to improve the panel's output in terms of electrical efficiency through a drop in the panel temperature. For the volume flow rate corresponding to 0.3 LPM, a temperature drop of about 12.7 °C is seen, contributing to a decrement of about 21.6 % compared to the plain PV panel without cooling arrangements. The modified panel also yields about a 2.26 % improvement in electrical efficiency for the volume flow rate of 0.5 LPM, despite being a cloudy day. Therefore, the PV module equipped with V-shaped water-cooled channels is recommended for the enhanced performance of PV installations.

Optimal Scheduling of PV Panel Cleaning and Policy Implications Considering Uncertain Dusty Weather Conditions in the Middle East

Airborne dust easily accumulates on the top of solar panel surfaces and reduces the output power in arid regions. A commonly used mitigation solution for dust deposition issues is cleaning PV panels periodically. However, cleaning frequency affects the economic viability of solar PV systems, resulting in a trade-off between cleaning costs and energy loss costs. To address this issue, this study relates several metrics and develops a generic framework based on simulation and optimization to determine the optimal cleaning interval. Based on the computational tests, the optimal cleaning interval in Abu Dhabi is determined to be 34 days, which is longer than the currently recommended cleaning interval of 28 days. This study also identifies that energy recovery is responsive to decreases in unit cleaning costs in the presence of high electricity tariffs, whereas total cost savings show sensitivity when electricity tariffs are low. Finally, this study discusses energy policy implications by presenting an innovative concept involving the introduction of a cleaning subsidy which could reshape energy system cost dynamics, making PV systems economically competitive beyond the conventional levelized cost of electricity.

Deep Learning-Based Dust Detection on Solar Panels: A Low-Cost Sustainable Solution for Increased Solar Power Generation

The world is shifting towards renewable energy sources due to the harmful effects of fossils fuel-based power generation in the form of global warming and climate change. When it comes to renewable energy sources, solar-based power generation remains on top of the list as a clean and carbon cutting alternative to the fossil fuels. Naturally, the sites chosen for installing solar parks to generate electricity are the ones that get maximum solar radiance throughout the year. Consequently, such sites offer challenges for the solar panels such as increased temperature, humidity and high dust levels that negatively affect their power generation capability. In this work, we are more concerned with the detection of dust from the images of the solar panels so that the cleaning process can be done in time to avoid power loses due to dust accumulation on the surface of solar panels. To this end, we utilize state-of-art deep learning-based image classification models and evaluate them on a publicly available dataset to identify the one that gives maximum classification accuracy for dusty solar panel detection. We utilize pre-trained models of 20 deep learning models to encode the images that are then used to train and validate four variants of a support vector machine. Among the 20 models, we get the maximum classification of 86.79% when the images are encoded with the pre-trained model of DenseNet169 and then use these encodings with a linear SVM for image classification.

Performance investigation on PVT collector with cerium oxide nano fluids

The constant temperature rise on the solar panel surface causes a deterioration of electrical power generation. This article is provided with the performance of photovoltaic thermal (PVT) collector through cerium oxide with water as a base fluid. A small percentage of incoming radiation is transformed into electricity and rest of them is wasted as hot energy, the panel surface temperature will confine the performance of PV module. The research's objectives were to develop and construct a photovoltaic/thermal collector and evaluate its thermal and electrical energy as an output. The experimental investigation of PVT collector with two different concentration of cerium oxide 0.5 and 1.0 LPM (litres per minute). As per the investigations on the PVT collector results were obtained as electrical performance of collector was attained about 18.56 %, 19.12 % for the flow rate of 0.5 and 1.0 LPM. Similarly, thermal performance was achieved 48.38 %, 54.03 % for the flow rate of 0.5 and 1.0 LPM. Thermal conductivity of cerium oxide nano fluid was much better than the air and water. It was observed that employing a nano fluid to the receiver might increase the efficiency around 5–10 %, compared to utilising water as a base fluid, water can only generate 3–7 %. As a cooling medium, air has a relatively low production capacity between 2 and 3 %.

Optimization of graded and partial metamaterial treatments for enhanced broadband sound insulation in partition panels

Resonant metamaterials can achieve unprecedented vibroacoustic attenuation in lightweight partition panels through small resonators attached on a subwavelength scale. Conventional metamaterial treatments are effective only in a narrow band and typically cover the entire panel surface, posing important challenges for industrialization due to manufacturing and cost constraints. To address these issues, in this study we propose graded and partial metamaterial treatments, which are selectively distributed where they are the most effective, avoiding unnecessary coverage, and include a spatially varying resonance frequency for broadband effectiveness. The related design challenges are tackled by developing a numerical methodology that simultaneously optimizes the distribution and the grading of the treatment. The optimization objective is to maximize the broadband diffuse sound transmission loss (STL) of the metamaterial panel, while constraining the maximum fraction of treated area. Leveraging effective medium modelling, the approach efficiently incorporates local changes in the effective mass density of the metamaterial panel to represent partial treatments. Different design cases are considered for different target bands and panel dimensions. Results demonstrate that graded partial metamaterial treatments can achieve broadband improvements with a limited treated area, effectively suppressing the STL dips due to the modes of the host panel and to coincidence effects.

Experimental investigation of a nano coating efficiency for dust mitigation on photovoltaic panels in harsh climatic conditions

Dust accumulation on photovoltaic (PV) panels in arid regions diminishes solar energy absorption and panel efficiency. In this study, the effectiveness of a self-cleaning nano-coating thin film is evaluated in reducing dust accumulation and improving PV Panel efficiency. Surface morphology and elemental analysis of the nano-coating and dust are conducted. Continuous measurements of solar irradiances and ambient temperature have been recorded. SEM analysis of dust revealed irregularly shaped micron-sized particles with potential adhesive properties, causing shading effects on the PV panel surface. Conversely, the coating particles exhibited a uniform, spherical shape, suggesting effective prevention of dust adhesion. Solar irradiance ranged from 120 W/m² to a peak of 720 W/m² at noon. Application of the self-cleaning nano-coating thin film consistently increased short circuit current (Isc), with the coated panel averaging 2.8 A, which is 64.7% higher than the uncoated panel’s 1.7 A. The power output of the coated panel ranged from 7 W to 38 W, with an average of approximately 24.75 W, whereas the uncoated panel exhibited a power output between 3 W and 23 W, averaging around 14 W. These findings highlight the substantial potential of nano-coating for effective dust mitigation, particularly in dusty environments, thus enhancing PV system reliability.

Investigation of the cooling effect of wind on rooftop PV power plants

This study investigates the cooling of PV panels installed on the roof of a 5.9 MW power plant in Bursa, Turkey, under varying wind conditions. Meteorological measurements were conducted during the summer period to analyse the cooling effects. When wind speed differences were below 0.5 m/s, the cooling effect on the PV panels ranged between 2-3°C. However, when the wind speed differences approached 1 m/s, the cooling effect increased up to 7°C. At lower wind speeds, winds blowing from behind the panels provided better cooling, whereas side winds offered improved performance as wind speed increased. Due to the roof slope and the minimal gap between the panels and the roof, winds from behind were less effective, as they could not penetrate the back of the PV panels. Side winds, on the other hand, faced no difficulty in flowing over the panel surfaces but lost their cooling effect as they passed along the long rows of panels. These findings suggest that during the design phase of PV power plants, high wind speed locations should be prioritized, and optimal configurations should be implemented to ensure uniform wind access to all PV arrays.

Innovative passive cooling of photovoltaic panel using loop heat pipe technology with passive daytime radiative cooling

This paper proposes an innovative cooling technique that utilizes a loop heat pipe (LHP) and passive daytime radiative cooling. The proposed system uses LHP to move the heat load from the photovoltaic (PV) panel surface facing the Sun to a radiator surface where heat is radiated to the sky and dissipated to the surroundings by convection. The LHP allows heat removal from PV panel surface to the radiator surface with negligible temperature difference. Based on selected PV parameters and conditions, the proposed LHP-radiator cooling system achieves a peak temperature reduction of over 10 °C, leading to a 4.6 % enhancement in PV electrical efficiency compared to the reference efficiency. The selected systems’ results show an annual energy saving of 3.4 % (around 8.7 kWh/m2) for the year of 2022.

FDADNet: Detection of Surface Defects in Wood-Based Panels Based on Frequency Domain Transformation and Adaptive Dynamic Downsampling

The detection of surface defects on wood-based panels plays a crucial role in product quality control. However, due to the complex background and low contrast of defects in wood-based panel images, features extracted by traditional deep learning methods based on spatial domain processing often contain noise and blurred boundaries, which severely affects detection performance. To address these issues, we have proposed a wood-based panel surface defect detection method based on frequency domain transformation and adaptive dynamic downsampling (FDADNet). Specifically, we designed a Multi-axis Frequency Domain Weighted Information Representation Module (MFDW), which effectively decoupled the indistinguishable low-contrast defects from the background in the transform domain. Gaussian filtering was then employed to eliminate noise and blur between the defects and the background. Additionally, to tackle the issue of scale differences in defects that led to difficulties in accurate capture, we designed an Adaptive Dynamic Convolution (ADConv) module for downsampling. This method flexibly compressed and enhanced features, effectively improving the differentiation of the features of objects of varying scales in the transform space, and ultimately achieved effective defect detection. To compensate for the lack of data, we constructed a dataset of wood-based panel surface defects, WBP-DET. The experimental results showed that the proposed FDADNet effectively improved the detection performance of wood-based panel surface defects in complex scenarios, achieving a solid balance between efficiency and accuracy.

Enhancing PV Panel Performance with Different Types of Phase Change Material (PCM): An Experimental Study

This study examined two solar panels with a high producing capacity of 250 W for performance enhancement utilizing several types of paraffin wax (RT57, RT61, and RT68) connected to the panel's rear surface. Two solar panels (one reference and one combined with PCM; PV-PCM) are used for outdoor tests. The current implementation is made with three types of PCM with a fixed thickness (3 cm) and with different inclination angles of 10°, 20°, 30°, and 40°. According to the results, the PV panels' tops had the maximum temperature spread, while their bottoms showed the lowest variation in temperature. At an inclination angle of 10◦, the temperature on the upper side of the plate is 18.8% higher than the lower side, 14.3%, and 12.2% for PCM1, PCM2, and PCM3, respectively. There is also an improved electrical power output of 16.8% for the PV-PCM panel with 3 cm PCM thickness over the reference panel (PV) with a tilt angle of 40◦. Relatedly, raising the inclination angle from 10◦ to 40◦ improves the Energy efficiency of PV-PCM with a thickness of 3 cm PCM by 10.4%. Finally, using 3 cm thick PCM improves the Energy efficiency of the PV-PCM panel by 17.4% compared to PV with an inclination angle of 30◦.

IoT based Solar Panel Cleaning Rover

The primary objective of this proposed study is to design a system for effectively maintaining the cleanliness of solar panels, thereby enhancing their performance and longevity through an Internet of Things-based solar panel cleaning rover equipped with a sensors, and manual automation capabilities. A suite of sensors, including dust sensors, enables the rover to gather relevant data about the cleanliness status and ambient conditions surrounding the solar panels. Manual automation features empower users to intervene and control the rover's movements and cleaning actions as needed, providing flexibility and customization in operation. Furthermore, the rover is designed to connect directly with water tanks, facilitating an autonomous water supply for the cleaning process. A sponge brush mechanism is integrated into the rover's design to effectively remove dust from the solar panel surfaces. The proposed work has developed a prototype of the IoT-based solar panel cleaning rover, which has been tested to demonstrate its effectiveness in improving solar panel efficiency and reducing maintenance efforts.

Thermal performance and energy efficacy of membrane-assisted radiant cooling outdoors

Membrane-assisted radiant cooling systems offer a promising solution for directly cooling human bodies in outdoor settings. In this study a prototype system is experimentally assessed, which comprised of two wall-mounted panels and one ceiling-mounted panel with the cooling provided by a water chiller system. Three different radiant panel surface temperatures (Tsur =14.3°C, 17.8°C, 21.9°C) were tested to observe possible condensation and to measure the heat flux, and a thermal comfort survey was conducted in combination to analyze the system energy efficacy. The results indicate that selecting appropriate panel surface temperatures under different ambient universal thermal climate index (UTCI) conditions can not only effectively avoid energy surplus but also improve thermal comfort for people. When the ambient UTCI is 38.1°C, the panel surface temperature needs to be lowered to 14.3°C to achieve neutral thermal sensation while 333.7 W of cooling energy is required; but when the ambient UTCI is 29.9°C, a panel surface temperature of 21.9°C would suffice with a much lower energy demand. It is also concluded that the surface condensation may occur but can be controlled. This experimental study provides solid data for the further development of radiant cooling technology for open-space applications.

Initializing Compression Stress to Stabilize the Phase Homogeneity in Bifacial Semitransparent Perovskite Solar Cells

AbstractSemitransparent perovskite solar cells (ST‐PSCs) hold great promise for various commercial applications, including building integrated photovoltaics and tandem solar cells. The all‐inorganic perovskite, known for its outstanding optical transparency and thermal stability, emerges as a top contender for ST‐PSCs. However, challenges persist due to phase segregation, which hampers charge carrier transport and operational stability. In this study, an approach is proposed to address these challenges by employing strain engineering to reconstruct the perovskite texture, eliminating inhomogeneities within the perovskite film. The crucial role of compressive strain in stabilizing lattice rigidity and suppressing light‐induced ion migration is demonstrated. Furthermore, a transparent light‐harvesting architecture is devised utilizing a sandwiched layer of gold embedded between MoO3. This design enhances power generation by efficiently harnessing incident light from both the front and rear panel surfaces. Therefore, bifacial ST‐PSCs achieve an equivalent efficiency (ηeq) of 13.97% with an average visible light transmittance of 41.58%, yielding an outstanding light utilization efficiency of up to 5.8%. This research not only advances the understanding of perovskite material phase‐segregation behavior but also introduces an effective strategy for enhancing optical gain without compromising the semitransparent characteristics.

ANALISIS PERBANDINGAN KINERJA SISTEM PENDINGIN PV DENGAN CAIRAN AQUADES, AIR SUMUR, DAN TANPA PENDINGIN DENGAN MONITORING IOT

Solar Power Plants are an environmentally friendly energy source that utilizes sunlight energy which is converted into electricity. However, solar panels must maintain their performance. One of the impacts is that solar panels cannot work optimally if the temperature of the solar panels exceeds the safe temperature. This research examines the factors that cause the performance of solar panels to not work optimally, when the surface temperature of the solar panels is too hot and exceeds the safe temperature limit, then tools are needed to help the solar panels so that the working temperature is not too high. The technology used to control the temperature of solar panels is by utilizing IoT by maximizing the DS18B20 sensor and voltage sensor, to read the surface temperature of the panel, which will then wet the surface of the solar panel with distilled water and well water automatically if the surface temperature of the panel exceeds the safe temperature on the solar panel. And later you can monitor the temperature of the panel with a smartphone and also observe whether distilled water and well water can reduce the temperature on the surface of the panel. When collecting data, it can be compared to when without using cooling, the temperature on the panel is above 33 degrees. Meanwhile, when using a cooler the temperature obtained decreases. The well water cooler produces a temperature of 32 degrees, while the distilled water cooler produces a temperature of 30.5 degrees. It can be concluded that distilled water can reduce the temperature of the panel, so it can make the panel work optimally. So, in order to maximize the performance of the panels to utilize solar power, in this research, distilled water is very good for lowering the temperature on the surface of the panels.

Thermally Active Medium-Density Fiberboard (MDF) with the Addition of Phase Change Materials for Furniture and Interior Design.

No matter where we reside, the issue of greenhouse gas emissions impacts us all. Their influence has a disastrous effect on the earth's climate, producing global warming and many other irreversible environmental impacts, even though it is occasionally invisible to the independent eye. Phase change materials (PCMs) can store and release heat when it is abundant during the day (e.g., from solar radiation), for use at night, or on chilly days when buildings need to be heated. As a consequence, buildings use less energy to heat and cool, which lowers greenhouse gas emissions. Consequently, research on thermally active medium-density fiberboard (MDF) with PCMs is presented in this work. MDF is useful for interior design and furniture manufacturing. The boards were created using pine (Pinus sylvestris L.) and spruce (Picea abies L.) fibers, urea-formaldehyde resin, and PCM powder, with a phase transition temperature of 22 °C, a density of 785 kg m-3, a latent heat capacity of 160 kJ kg-1, a volumetric heat capacity of 126 MJ m-3, a specific heat capacity of 2.2 kJ kgK-1, a thermal conductivity of 0.18 W mK-1, and a maximum operating temperature of 200 °C. Before resination, the wood fibers were divided into two outer layers (16%) and an interior layer (68% by weight). Throughout the resination process, the PCM particles were solely integrated into the inner layer fibers. The mats were created by hand. A hydraulic press (AKE, Mariannelund, Sweden) was used to press the boards, and its operating parameters were 180 °C, 20 s/mm of nominal thickness, and 2.5 MPa for the maximum unit pressing pressure. Five variants of MDF with a PCM additive were developed: 0%, 5%, 10%, 30%, and 50%. According to the study, scores at the MOR, MOE, IB, and screw withdrawal resistance (SWR) tests decreased when PCM content was added, for example, MOE from 3176 to 1057 N mm-2, MOR from 41.2 to 11.5 N mm-2, and IB from 0.78 to 0.27 N mm-2. However, the results of the thickness swelling and water absorption tests indicate that the PCM particles do not exhibit a substantial capacity to absorb water, retaining the dimensional stability of the MDF boards. The thickness swelling positively decreased with the PCM content increase from 15.1 to 7.38% after 24 h of soaking. The panel's thermal characteristics improved with the increasing PCM concentration, according to the data. The density profiles of all the variations under consideration had a somewhat U-shaped appearance; however, the version with a 50% PCM content had a flatter form and no obvious layer compaction on the panel surface. Therefore, certain mechanical and physical characteristics of the manufactured panels can be enhanced by a well-chosen PCM addition.