Waterborne transparent anti‐smudge coating with cooling performance via molecular engineering

Detail analysis of microcontroller (μC)‐based smart dual‐axis automatic solar tracking system utilizable for different purpose is presented in this paper. Working of the proposed smart tracking system is based on the automatic rotation of photovoltaic (PV) panel depending on the intensity of sun light. It will help in maintaining the alignment of PV panels with the Sunlight to obtain maximum solar power at any instance. Intensity of sunlight on a particular alignment of solar PV panel varies throughout the day. As the intensity of light on PV panel decreases the proposed smart tracking system has the intelligence to automatically redirect the panel alignment to get maximum intensity of light. Four Light Dependent Resistor (LDR) sensors are placed on the surface of the PV panel to detect the intensity of light. Two servomotors are employed in the back side of PV panel system to align the panel with maximum luminous intensity. Design and construction of the proposed tracking system is presented to measure the efficiency over the fixed PV panel. Experimental results indicate that the power output of the PV system, using the proposed tracking system is increased up to 19.73% compare to the traditional fixed PV panel. The efficiency of the proposed design is considerably higher and comparable to the existing design which has the average efficiency around 12–15%.

Solar photovoltaic (PV) panels are projected to become the largest contributor of clean electricity generation worldwide. Maintenance and cleaning strategies are crucial for optimizing solar PV operations, ensuring a satisfactory economic return of investment. Nanocoating may have potential for optimizing PV operations; however, there is insufficient scientific evidence that supports this idea. Therefore, this study aims to investigate the effectiveness of nanocoating on the performance of solar photovoltaic (PV) panels installed in Al Seeb, Oman. A further study was also carried out to observe the influence of coating layers on the performance of PV panels. One SiO2 nanocoated solar panel, another regularly cleaned PV panel, and a reference uncleaned panel were used to carry out the study. The site of the study was treeless and sandy, with a hot and dry climate. A data logger was connected to the solar PV panel and glass panel to record the resulting voltage, current, temperature, and solar radiation. It was observed that nanocoated PV panels outperformed both regular PV panels and uncleaned PV panels. Nanocoated PV panels demonstrated an average efficiency of 21.6%, showing a 31.7% improvement over uncleaned panels and a 9.6% improvement over regularly cleaned panels. Although nanocoating displayed high efficiency, regular cleaning also contributes positively. Furthermore, even though nanocoated PV panels outperformed the other two panels, it is important to note that the performance difference between the regular cleaned PV panels and the nanocoated PV panels was small. This indicates that regular cleaning strategies and nanocoating can further contribute to maintaining a more efficient solar PV system. Coating in many layers was also observed to influence the performance of PV panels insignificantly, mainly the fourth layer coating appeared to have formed sufficient mass to retain heat.

A review on role of solar photovoltaic (PV) modules in enhancing sustainable water production capacity of solar distillation units

In areas of Indonesia that are crossed by the equator, the availability of sunlight is very potential and all day. Therefore in the case of application as a source of electrical energy to drive a water pump with a set of solar cell panels it is very possible. The level or intensity of sunlight illumination from sunrise to sunset is very different. The intensity of sunlight is certainly very influential on the ability of solar cell panels to convert them into electrical energy.Surely it will have an impact on the performance of the solar water pump system. Thus in this study will test the performance and analyze the performance of water pumps driven using electricity from solar cell panels. To achieve this goal measurements of the power generated by solar panels starting from 12:00 WIB to 16:00 WIB for three days (three repetitions) were carried out in the open field programmed in the Mechanical Engineering Study of Pamulang University. Data collection is done by measuring the intensity of sunlight, battery input power, and water discharge.The solar panel used is 100wp capacity, the highest solar panel power produced is 25.3W at 12:00 WIB with an intensity value of 114700 lux, while the lowest power value is 13.83 W at 16:00 WIB with an intensity value of 47301 lux. Charging a battery with a capacity of 12V / 35A from a minimum voltage to full using a 100 wp solar panel takes an average of 4 hours 28 minutes. The use of a battery with a capacity of 12V / 35A from full to minimal voltage conditions to drive an AC water pump takes an average of 1 hour 48 minutes and produces an average water volume of 1855.33 liters. Or the resulting average water discharge is 17.08 liters / minute.

Background: Solar Photo Voltaic (PV) module based electric power supply systems are being designed for remote unmanned oil and gas facilities where grid utility power is not available within vicinity. PV modules are used in applications such as measurement of process data, telemetry, gas detection, cathodic protection and lighting with voltage levels of 12V, 24V and 48V. Majority of PV modules are made of compounds of semi-conducting materials from Group IV (Silicon and Germanium) and alternatively Group-III/V and Group- II/VI. These materials are in mono crystalline, multi crystalline and in amorphous structure. Hot spot heating is a phenomenon, occurring in PV module, caused by faulty conditions such as partial shading / material imperfection / fabrication flaws / damages etc. When the faulty PV module/ cell operating current exceeds the short circuit current (Isc), it shall not produce energy, rather starts to consume power from the other PV cells connected in series. Due to the above phenomena localized heating is expected to occur wherein the temperature could rise in the range of 150 – 200 Deg.C. Built-in bypass diodes are provided in PV modules to prevent localized hotspot; however there are characteristics mismatches between the diode and module which does not prevent hotspot for all faulty cases. Hot spot test criteria defined in IEC 61215 & IEC 61646 / IEC 61730 / ANSI UL 1703 has inconsistencies hence not harmonized. Objectives: Application of solar PV module for hydrocarbon facilities may introduce fire hazards due to hotspot phenomena, where minimum ignition energy source of 20 micro Joules (Acetylene) or temperature above 100 Deg.C (Carbon Di-Sulphide) can become the source of ignition. This shall be scientifically studied and specific guidelines and/or standards shall be established based specific materials selection and engineering design. Methods: Hot Spot phenomena of PV module shall be tested with multiple variables and scenarios such as Module Materials and its structure, Current/ Voltage Level, Irradiation level, Type of shading, Location of Fault in the module. Results & Conclusions: Solar PV module application in hydrocarbon industry may call for specific material and design requirements to effectively prevent hotspot occurrence in an explosive atmosphere.

In remote areas the sun is a cheap source of electricity because instead of hydraulic generators it uses solar cells to produce electricity. But the output of solar cells depends on the intensity of sunlight and the angle of incidence. It means to get maximum efficiency; the solar panels must remain in front of the sun during the whole day. But due to the rotation of the earth, those panels can’t maintain their position always in front of the sun. This problem results in a decrease of their efficiency. So, to get a constant output, an automated system is to be required which should be capable to constantly rotate the solar panel. Automatic sun tracking system with photovoltaic plate to improve the efficiency of solar power generation was helpful to solve the problem, mentioned above. It is completely automatic and keeps the panel in front of the sun until that is visible. The unique feature of this system is that instead of taking the earth as its reference, it takes the sun as a guiding source. Its active sensors constantly monitor the sunlight and rotate the panel towards the direction where the intensity of sunlight is at maximum with the help of DC motor

As an alternative source of energy people all over the world have started using renewable energy. Renewable energy are unlimited sources of energy and they are completely free of cost. The most popular renewable energy sources are solar energy, wind energy, tidal energy, geothermal energy, hydro energy, biomass energy. Among the renewable energy sources, solar energy is the cleanest source of energy. Solar photovoltaic panel absorbs solar energy and produces electricity. The output of a solar photovoltaic panel depends on some factors such as sunlight intensity, solar panel surface temperature, solar cell materials, and shade and so on. To make sure that solar panel absorbs maximum irradiance from sun a tracking system is required which help the panel move towards the sun in day time according to sun light. In addition to control the surface temperature of solar photovoltaic panel, a microcontroller based automatic cooling system is designed. When the surface temperature of the panel is above the optimum temperature then the output of the solar panel is decreasing, to control the surface temperature an automatic cooling system will start and decrease the surface temperature of the solar panel consequence the performance is increasing. The main purpose of this work is to design and implement a microcontroller based automatic single axis solar tracking system with an automatic water-cooling system. These systems increase the output of the solar panel as well as rise the efficiency of the solar photovoltaic panel.

The installation of solar photovoltaic (PV) panels is growing globally as the international community is on track to transition from fossil fuel energy to clean and sustainable resources of energy such as solar energy, wind energy, hydropower, and bioenergy. Among various renewable energy technologies, the capacity of power generation using solar PV has grown dramatically in recent years around the world. With more and more fields and building roofs covered with PV panels, setting up solar panels with flexibility at various idle surfaces becomes important for cost reduction. Regarding making use of idled areas and surfaces for solar panels, it is also important to have a tool to predict the energy harvest and the cost in order to attract more and more customers. In an attempt to maximize the irradiance fallen on a PV panel of various orientations, the present study provides a general model to predict the energy harvest and also the optimal tilt angles and orientation of the panels when needed. The analysis can accurately calculate the instantaneous sunray vector and solar panel normal vector using Solar Position Algorithm to account for the “cosine” effect of the angle of incidence. And more importantly, weather conditions or clouds coverage conditions are also combined in the calculation for precise energy prediction. The solar energy received per unit area of a PV panel in every 5 minutes is summated or integrated for daylong period from sunrise to sunset considering 21 years of averaged cloud-cover meteorological data. The model presented here is employed to two examples of geographical sites at north and south hemispheres and can be applied to any location around the world. The results for the City of Tucson Arizona USA show that the amount of yearly solar energy captured by a solar tracking panel is 3619.32 kWh/m2, whereas the annual solar energy received by an optimally tilted solar panel of a slop same as the local latitude could reach to 2206 kWh/m2 (60.9% of that from a fully tracking system). The findings also indicate that by optimally adjusting the tilt angle two times a year, four times, and monthly, the yearly solar energy accumulation can be 65.534%, 65.525%, and 66.515% of that of a system with tracking, respectively. In the absence of rooftop or ground installation options, the study reveals that vertically installing PV solar panels on walls due south would attain about 32% of the annual solar collection compared to a fully tracked system.

The aim of this project explores the design and implementation of perturb and observe (P&O) Maximum Power Point Tracking (MPPT) method to optimize energy harvesting from solar photovoltaic (PV) systems. Our main aim was to design a system which can extract maximum power point (MPP) and maximum power point tracker (MPPT). By dynamically adjusting the operating point of the PV system, the P&O algorithm ensures maximum power output despite changes in environmental conditions such as sunlight intensity and temperature. The project involves developing and implementing the MPPT P&O algorithm, by the help of DC/DC Boost Converter using a MATLAB/SIMULINK. The results demonstrate the effectiveness of the P&O method in improving the efficiency and reliability of solar PV systems. Solar panels can lower utility bills and produce clean, environmentally friendly energy. The efficiency of photovoltaic solar panels is related to the quality of their photovoltaic (PV) cells. The conversion efficiency of a PV cell is the percentage of solar energy shining on a solar panel that is converted into usable electricity. The efficiency of solar panels has improved dramatically in recent years, from an average of around 15% conversion of sunlight to usable energy to around 20%. High-efficiency solar panels can reach nearly 23%. The power rating of a standard-sized panel has likewise increased from 250W to 370W. Keywords Solar Photovoltaic (PV) System, Maximum Power Point Tracking (MPPT), Perturb and Observe (P&O) Algorithm, DC/DC Converter (Boost Converter).

The conversion of solar energy into electricity by photovoltaic solar modules causes the temperature of the photovoltaic solar cells to rise, reducing their electrical efficiency. The heat dissipation of photovoltaic solar modules allows them to be cooled and the recovered heat can be used for residential and industrial applications. Many different cooling methods have been proposed to reduce the temperature of photovoltaic solar modules and improve electrical efficiency. These photovoltaic solar module cooling methods are classified into active, passive and hybrid cooling. Although most solar module air cooling techniques have been investigated, air cooling methods that optimise heat transfer through structural configuration have not been collectively studied. This paper reviews recent work on air-cooling methods for solar photovoltaic modules, focusing on natural and forced air circulation, efficient solar radiation collection and conversion, and improved heat transfer coefficient by air convection in a duct. These air-cooling methods are examined, analysed and compared, and the prospects for these different techniques are proposed. The results showed that forced-air cooling coupled with fins/baffles using phase-change materials and bifacial and thermoelectric photovoltaic modules are the most promising, despite their complex structures and very high investment costs. Thanks to their efficient heat transfer, their storage of excess heat and their significant reduction in the temperature of solar PV modules, these cooling techniques, which are recommended for promotion, can ensure rational use of energy.

Accumulation of dust from the outdoor environment on the panels of solar photovoltaic (PV) system is natural. There were studies that showed that the accumulated dust can reduce the performance of solar panels, but the results were not clearly quantified. The objective of this research was to study the effects of dust accumulation on the performance of solar PV panels. Experiments were conducted using dust particles on solar panels with a constant-power light source, to determine the resulting electrical power generated and efficiency. It was found from the study that the accumulated dust on the surface of photovoltaic solar panel can reduce the system-s efficiency by up to 50%.

The current geometric increase in the global deployment of solar photovoltaic (PV) modules, both at utility-scale and residential roof-top systems, is majorly attributed to its affordability, scalability, long-term warranty and, most importantly, the continuous reduction in the levelized cost of electricity (LCOE) of solar PV in numerous countries. In addition, PV deployment is expected to continue this growth trend as energy portfolio globally shifts towards cleaner energy technologies. However, irrespective of the PV module type/material and component technology, the modules are exposed to a wide range of environmental conditions during outdoor deployment. Oftentimes, these environmental conditions are extreme for the modules and subject them to harsh chemical, photo-chemical and thermo-mechanical stress. Asides from manufacturing defects, these conditions contribute immensely to PV module’s aging rate, defects and degradation. Therefore, in recent times, there has been various investigations into PV reliability and degradation mechanisms. These studies do not only provide insight on how PV module’s performance degrades over time, but more importantly, they serve as meaningful input information for future developments in PV technologies, as well as performance prediction for better financial modelling. In view of this, prompt and efficient detection and classification of degradation modes and mechanisms due to manufacturing imperfections and field conditions are of great importance towards minimizing potential failure and associated risks. In the literature, several methods, ranging from visual inspection, electrical parameter measurements (EPM), imaging methods, and most recently data-driven techniques have been proposed and utilized to measure or characterize PV module degradation signatures and mechanisms/pathways. In this paper, we present a critical review of recent studies whereby solar PV systems performance reliability and degradation were analyzed. The aim is to make cogent contributions to the state-of-the-art, identify various critical issues and propose thoughtful ideas for future studies particularly in the area of data-driven analytics. In contrast with statistical and visual inspection approaches that tend to be time consuming and require huge human expertise, data-driven analytic methods including machine learning (ML) and deep learning (DL) models have impressive computational capacities to process voluminous data, with vast features, with reduced computation time. Thus, they can be deployed for assessing module performance in laboratories, manufacturing, and field deployments. With the huge size of PV modules’ installations especially in utility scale systems, coupled with the voluminous datasets generated in terms of EPM and imaging data features, ML and DL can learn irregular patterns and make conclusions in the prediction, diagnosis and classification of PV degradation signatures, with reduced computation time. Analysis and comparison of different models proposed for solar PV degradation are critically reviewed, in terms of the methodologies, characterization techniques, datasets, feature extraction mechanisms, accelerated testing procedures and classification procedures. Finally, we briefly highlight research gaps and summarize some recommendations for the future studies.

Comprehensive numerical modeling and investigations have been carried out to analyze the effect of wind loads on various solar array mounting frame structures using ANSYS 18 Workbench (Mechanical). Extensive damages of solar arrays and mounting frames have been reported the world over due to high winds. In this study, six array mounting frame types have been considered, subjected to the basic wind of 55 m/s specified for coastal regions of India. India has six basic wind speed zones ranging from 33 m/s to 55 m/s. Many utility-scale solar farms installed in this region are susceptible to high winds. Solar arrays considered of dimension 6 m × 4 m consisting of 12 photo-voltaic (PV) panels each of size 1 m × 2 m, with panel tilt angle varying from 10° to 50°. Wind load subjected to the PV panels in the solar array considered as normal pressure force over the top and bottom surfaces to simulate forward and backward wind direction. Three different materials with their respective mechanical properties, i.e., structural steel channel for mounting truss members, aluminum casing to encapsulate PV panels, and plexiglass sheet for PV panels, were considered and simulated. Wind pressure forces have been determined, using respective net wind pressure coefficients, induced by respective wind speed and tilt angle. Maximum deformation and maximum stresses were determined by modeling and simulation in ANSYS Workbench and compared the results with various array mounting system arrangements for each case of panel tilt angle subjected to both forward and backward wind incidence.

Solar energy is the abundant renewable energy on earth which doesn't pollute the environment while producing the energy using Solar Photo Voltaic (PV) panel. Efficiency of the PV panel depends on the amount of light falls on it, due to the azimuth angle of solar panel, deposition of dust on PV panel reduces the efficiency of the energy generated. To increase the efficiency of the PV panel, periodically it has to be cleaned. This paper proposes a solar panel cleaning robot which periodically cleans PV panel autonomously, the surface of the panel is cleaned by blowing air, spraying the liquid and wiping out the dust with wiper and drying the wet content on the panel using cylindrical brush. The proposed robot is controlled remotely by Internet of Things (IoT) which reduces the human effort in the solar plant and can be remotely monitored. Also the robot is a self-powered generates the power required by Solar PV panel mounted on the robot. The proposed system increases the efficiency of the power generation by periodically cleaning using Robot.

Solar energy is a renewable energy source that is abundantly available in Indonesia. One way to utilize solar energy is to convert it into electrical energy using photovoltaic modules or solar panels, which are called solar power plants (PLTS). The construction of PLTS can accelerate the electrification ratio and reduce fossil materials. In this study, the author will design a 100 Wp solar power plant (PLTS) using a 1000watt inverter, while the research uses the Research and Development method, with stages covering system analysis, design, implementation and testing. The manufacture of PLTS is done by identifying components such as solar panels, DC wattmeter, SCC (Solar Charge Controller), battery, 1 Phase MCB, and AC Wattmeter. It can be concluded that to obtain electrical energy, weather conditions greatly affect the working system of solar panels. The maximum voltage from a 100wp solar panel that was designed and tested for 3 days in the worst month conditions was produced on the second and third days with a voltage value of 17.08 Volts at 12:00 noon and a minimum voltage was generated on the second day of testing, namely with a voltage value of 12.00 Volts at 12.00 Volts. 07:00 am. Furthermore, the 100 wp solar panel can only produce a maximum power of 256.01watt which was obtained on the second day of testing with an average voltage and current obtained of 14.19volt and 1.58 Ampere. The condition of the battery takes 5.47 hours or 328 minutes to fully charge energy to 100%. To maximize power gain and get the intensity of sunlight throughout the morning to evening, the use of the Single Axis solar tracker system is very effective.