Performance Of Photovoltaic Panels Research Articles

Effects of climatic conditions of Al Seeb in Oman on the performance of solar photovoltaic panels

Human activities and climatic elements, including temperature, humidity, and wind speed, have an impact on natural dust deposition. Therefore, this study aims to investigate the effects of wind speed, relative humidity, and ambient temperature on the performance of soiled photovoltaic panels in Al Seeb, Oman. The study was conducted by exposing the solar PV panels to outdoor sunlight for a duration of two months. Parameters such as solar radiation, voltage, current, solar panel temperature, wind speed, relative humidity, and ambient temperature were collected in a short time interval. It was observed that the dust densities of 20.7 g/m2, 27 g/m2, and 41.3 g/m2 resulted in electrical power reductions of 18 %, 33 %, and 40 % for the panels uncleaned for one week, two weeks, and three weeks, respectively. The effect of daily dust resulted in an energy reduction of 14 %. Moreover, dust deposition decreases when the wind speed increases, resulting in a higher power output and vice versa. The higher the humidity, the stronger the dust's adhesion to the surface, resulting in more deposition and reduced power output. The maximum power output of 82.3 W was achieved at the wind speed of 10 m/s, 34.9 % relative humidity, and ambient temperature of 38.5 °C.

Innovative cooling technique to improve the performance of photovoltaic panels

The working performance of solar photovoltaic panels is affected by several factors. Accumulated dust and elevated temperatures from higher solar irradiance are the main factors. Therefore, a novel dual-cooling approach was employed, and its effect on the solar photovoltaic panels’ performance was investigated. The working front and backside temperatures, output power, and efficiency of the cooled solar photovoltaic panel were evaluated and compared. The results revealed that the current cooling process reduced the front and backside temperatures of the module by 22–45% and 34–47%, respectively, as compared with the dusty solar photovoltaic module. In the cooled photovoltaic module, the output current was higher by 26–48% and 4–5% compared with dusty and controlled modules, respectively, while the output voltage was found to be higher by 8–10% compared with the controlled and dusty modules. This led to a rise in output power for the cooled photovoltaic module by 22–51% and 8–13% compared to dusty and controlled modules throughout the day. In addition, the presence of dust on the photovoltaic module significantly reduces the overall efficiency to 11% compared to 17% when applying the cooling process. The levelized cost of electricity from the current cooled system was lower by 38.5% and 8% than in the dusty and uncooled systems, respectively. This means the proposed cooling system is efficient from an economic point of view. The results showed the distinct importance of the current dual-cooling process to avoid photovoltaic module degradation by accumulated dust and elevated temperatures.

Exploring the Impact of Diverse Cooling Duct Configurations on Photovoltaic Panel Performance

Photovoltaic (PV) panels are an emerging technology that captures solar energy and produces electricity. One key concern with PV panels is the detrimental effect of high temperatures on their performance and efficiency, which is leading to a shorter service life. Cooling the panels can help to maintain appropriate working temperatures, reduce the adverse effects of heat, and increase overall energy production. This research aims to investigate experimentally and numerically the effectiveness of a cooling channel with different configurations in lowering PV panels' temperature. The findings of the experiments show that cooling methods improved panel efficiency by 0.35% and reduced the intake temperature by 7%. In numerical analysis, different 3D cooling channel geometries were investigated, and the tapered duct was found to be the best in reducing Tav at 1.73%.

Wind-Induced Cooling Effects on Photovoltaic Panel Performance

This investigation evaluated the performance of a photovoltaic (PV) panel system under varied cooling speeds of a calibrated wind generator. The objectives encompassed the calibration of wind speed, integration of the wind generator with the PV panel system, monitoring the performance of the PV panel with wind-induced cooling, and analyzing overall performance under different wind generator settings. Parameters assessed included open circuit voltage, short circuit current, PV panel surface temperature, and power output. The tests were carried out both with and without wind cooling and under artificial and natural lighting conditions. Under artificial lighting conditions, the solar PV panel demonstrated suboptimal short circuit current compared to natural lighting conditions, leading to an overall decrease in power output. Moreover, the findings revealed a significant relationship between simulated wind speed and the overall performance of the PV panel, with notable variations in surface temperature, voltage level, current level, and power output. The statistical analysis supported these findings, with all dependent variables exhibiting statistically significant differences. The practical implications of these observations are pertinent to the design of more efficient and sustainable PV and PV-wind cooling systems. By comprehending the influence of wind on PV panel performance, system designers and operators can make informed decisions to maximize energy production and enhance the overall efficiency of the PV system.

Performance analysis of photovoltaic panel using machine learning method

Demand for energy is increasing as the world’s population grows, fossil fuels deplete on a daily basis, and climate conditions change. Renewable energy is more important than ever. Solar energy is the most accessible and cost-effective renewable energy source available today. Photovoltaic (PV) cells are the most promising way to convert solar energy into electricity. Wind speed, ambient temperature, incident radiation rate, and dust deposition are some of the internal and external variables that affect photovoltaic panel performance. Unwanted heat from the sun’s rays raises panel temperatures, reduces the amount of energy that solar cells can produce, and lowers conversion efficiency. Solar panels must be adequately cooled. The current research is focused on improving photovoltaic panel performance. The experimental system includes a fully automated photovoltaic panel, a microcontroller (NodeMCU8266), a DC pump, voltage and temperature sensors. The experiment was carried out with and without cooling of the PV panel. The findings suggest that keeping PV panel temperatures close to ambient temperatures improves performance. The Wi-Fi module collects real-time data on PV panel temperature, irradiation, ambient temperature, water temperature, and PV panel power output. The collected data was analyzed using machine learning. The PV panel’s performance was analyzed using the linear regression method.

Improving the Performance of Photovoltaic Solar Panels Using Argon-Filled Double-Glazing Cover as a Radiative Cooling

Improving the Performance of Photovoltaic Solar Panels Using Argon-Filled Double-Glazing Cover as a Radiative Cooling

Current Challenges in Operation, Performance, and Maintenance of Photovoltaic Panels

The installed solar capacity in the European Union has expanded rapidly in recent years. The production of these plants is stochastic and highly dependent on the weather. However, many factors should be considered together to estimate the expected output according to the weather forecast so that these new PV plants can operate at maximum capacity. Plants must be operated in coordination with maintenance operations and considering actual energy market prices. Various methods have recently been developed in the literature, ranging from the most impactful artificial-intelligence-based generation estimation methods to various diagnostic and maintenance methods. Moreover, the optimal operational and maintenance strategy usually depends on market regulation, and there are many concerns related to the distribution system operator. This review article aims to summarize and illustrate the challenges of operating and maintaining solar power plants and the economic and technical importance of these problems.

Prediction of the optimum photovoltaic output based on cell temperature and solar irradiance

Energy-harvesting photovoltaic (PV) systems are common, but due to the challenges in managing the output, they raise serious difficulties. Climate variables have an impact on the uneven output performance of PV panels. The sunlight and the surrounding environment are unlimited making it challenging to estimate a PV panel system's output of electricity. Not only that, The PV panel will only provide power in parallel with its rated capacity under the Standard Test Condition (STC). STC requires 1000 Watts of sun energy per meter square of solar irradiance and cell temperature of 25 degrees Celsius. Therefore, the changing weather, which will impact the output power, requires prediction. Since the PV panel output will not generate according to its rating, PV power generation predictions requiring calculations of elements such as weather, sun hours, and temperature play a significant role. Hence, this research is related to the prediction of the optimum photovoltaic output based on cell temperature and local solar irradiation. The novelty of this research is all of the surrounding parameters used to predict the PV output are focused on the local area in Batu Pahat, Johor where the UTHM campus is located.

Effects of cooling and interval cleaning on the performance of soiled photovoltaic panels in Muscat, Oman

Due to the present alarming environmental problem, the world has turned to photovoltaic (PV) solar energy as a sustainable, renewable, and environmentally friendly alternative. Solar energy technology has rapidly improved in recent decades, and the global installation of photovoltaic systems has been increasing at a rate of 24% annually. However, soiling on panels and high panel temperature affect the performance of photovoltaic systems, and this leads to significant production loss, especially in the Middle East, where the dust intensity and ambient air temperature are at their highest levels. This paper presents the influence of cooling and interval cleaning on the performance of the photovoltaic system installed in Muscat, Oman. The study involved cleaning the first panel at a comparable inclination angle. The second panel had its inclination angle changed. The third panel was designed to inject water for cooling purposes. In this case, the panel was subjected to water injection for 30 s once per week, followed by daily water injection for 120 s in the second week. All the results were compared with the fourth panel, which was neither cleaned nor touched. Measurements, including open circuit voltage, short circuit current, solar panel temperature, solar radiation, and power, were made in 1-min intervals using a data logger. The results of the experiment showed that cleaning the panel manually every three days resulted in the highest output power and efficiency, reaching 85.6 W with 23.6% efficiency. The cooling of the panel resulted in an increase in power, especially for the longer injection duration. Conclusively, water injection resulted in an energy output growth of 23.9%.

Optimal design and orientation of cooling technology for photovoltaic Plants: A comparative simulation study

Continued development in the field of solar photovoltaics requires improvements in cooling technology. Therefore, the present comprehensive simulation study aims to reach the optimal design and orientation of cooling technologies that achieve the highest performance of photovoltaic (PV) panels. To achieve the optimal design and orientation of the cooling channel inlet of air-cooled photovoltaic thermal collectors, seven different designs of cooling techniques distinct for cooling the PV panels from the bottom side were studied, including conventional side cooling (S1), cooling from the bottom through one slot (S2), cooling from the bottom through two slots (S3), cooling from the bottom through three slots (S4), cooling from the side and through one hole (S5), cooling from the side and through two holes (S6), and cooling from the side and through three holes (S7). Outcomes presented that the second scenario S2 is the optimal one, where the air outlet temperature is 315.9 K and the thermal efficiency is 14.6 %. In the second part of the study, the influences of air flowing (with Re varying between 1000 and 5500) on the performance of PV panels for two distinct scenarios (S1 and S2) were studied. According to simulation studies, using situations S1 and S2, the outlet temperatures are 318.26 K and 319.14 K, respectively, with Re = 1072 and Gr = 8.74E5. Also, S2 has a considerable thermal efficiency advantage over S1. The highest thermal efficiency for S1 and S2 is 51 % and 59 %, respectively, for Gr = 8.74E5 and Re = 5432 with an improvement of 15.68 %.

ENERGY & EXERGY ANALYSIS OF A PV PANEL WITH PASSIVE COOLING MECHANISM

A photovoltaic (PV) array is grately responsive to changes in temperature; contrarily, reduction in temperature is the major factor that subsidize to an raise in the electrical efficiency and output power of a PV system. To optimize the production of energy by PV panels and reduce their temperature, a photovoltaic (PV) cooling system is basically used. Nonetheless, more insolation is generally associated with higher temperatures, which is ambiguous for photovoltaic (PV) panels because they rely on that irradiance to create power. These extreme temperature rises have a devastating effect on how skillfully photovoltaic (PV) panels transforms energy. A solar photovoltaic (PV) system can opearte more accurately with an adequate cooling system on its surface. In this paper, a passive cooling model for the PV panel has been devloped which cools down the PV panel by employing dry grass and water at the back surface. A correlation has been made with a non-cooled panel. Two PV panels are simultaneously tested. Electrical output properties of both the PV panels have been recorded and energy and exergy analysis for the system has been presented to have a more detailed understanding of the cooling effect on PV panel performance. The cooled panel has an increase in efficiency by 47%. Along with the electrical efficiency, the thermal efficiency has also been presented in this paper for performance evaluation in the form of overall efficiency.

Effect of Anti-Reflective and Dust Spreading on Performance of Solar PV Panels

This study intends to better solar photovoltaic (PV) panel performance by employing anti-reflective coating and explore how dust affects solar panel effectiveness. Three equivalent solar PV panels were compared, having one of them being uncoated, the next one having a TiO2 nanomaterial coating, and the very last one having a SiO2 nanomaterial coating. PV panel surfaces are coated with superhydrophilicity TiO2 as well as superhydrophobic SiO2 nanomaterials using a cloth made of microfibers. With the aid of a photovoltaic (PV) analyser, the power output of each and every PV panel has been monitored during the month of November 2021. After one month of being exposed to the environment, the percentage improvement in efficiency for TiO2-coated panels was 7.66% and for SiO2 coated panels was 19.73% as compared to uncoated PV panels. Results demonstrate that SiO2 covered PV panels outperform the other two scenarios in terms of efficiency and power output. The frequency of photovoltaic panel washing is reduced by the application of coating. Different amounts of dust are evenly scattered on the surface of the PV panel in order to observe the effect of the dust. Additionally, as the amount of dust increases, the effectiveness of PV panels declines considerably. When 20g of dust is dispersed across the surface of a PV panel, its efficiency falls by 34.6 percent.

Thermal Effects on Photovoltaic Panel Efficiency and Enhanced Cooling Strategies for Optimal Performance

The influence of temperature on the performance of photovoltaic (PV) panels is a critical consideration in harnessing the potential of solar energy technology. This compilation of research papers explores the multifaceted impact of operating temperature on PV systems and the utilization of cooling technologies to enhance their efficiency. The studies consistently emphasize the detrimental effects of elevated temperatures on PV cells and modules and investigate various aspects, including temperature-dependent parameters, real-world environmental conditions, geographical distribution, and mitigation strategies. Accurate modeling and location-specific considerations are underscored as vital for optimizing PV system efficiency. As the world embraces renewable energy and sustainability, the insights presented in these papers offer valuable contributions to advancing solar power technology for a more sustainable future. Furthermore, this collection emphasizes the significance of addressing temperature-related efficiency losses in PV panels and the potential for cooling solutions to improve performance. Various cooling methods, such as air cooling, water cooling, evaporative cooling, and phase change materials, are explored to mitigate the impact of high operating temperatures on PV systems. Integrated systems that combine cleaning and cooling mechanisms to address both soiling and heating issues are proposed. Environmental and economic considerations are pivotal in assessing the feasibility of implementing cooling solutions in different settings. These studies collectively stress the need for effective cooling technologies, especially in regions with extreme temperatures and intense solar radiation, to unlock the full potential of PV systems. Researchers, engineers, and policymakers working in the field of renewable energy will find these findings valuable for advancing the efficient utilization of solar power

Improving the performance of photovoltaic panels using a direct water cooling system

Improving the performance of photovoltaic panels using a direct water cooling system

Artificial Neural Network and Genetic Algorithm-based prediction of photovoltaic panel performance with porous foam gradient and nano-enhanced phase change material

Photovoltaic panels (PV) become less efficient as the temperature rises. The use of porous foam gradient, phase change materials (PCMs), and nanoparticle-PCM (nePCM) can effectively lower the temperature of PV panels. This study employed numerical analysis using the finite volume method to investigate the effects of different types of PCMs (n-octadecane, decanoic acid natural, lauric acid, paraffin wax, and RT-42), mono and hybrid nanoparticles/PCM, and the position of PCM in the design system. The results indicate that the highest electrical efficiency of 9 % is achieved when the PCM is placed under the PV panel and the thickness of the PCM layer is 0.6 times the height of the microchannel. Furthermore, the use of a porous medium with a variable porosity coefficient that increases along the y-direction can significantly improve thermal and electrical efficiency (approximately 5–42 % and 5–48 % respectively). Additionally, incorporating PCM and hybrid nanoparticles-PCM enhances PV performance compared to the absence of nanoparticles. For TiO2, Ag, Al2O3, GO, and MWCNT nanoparticles, the thermal efficiency, electrical efficiency, and exergetic efficiency increase by approximately 24.18 %, 26.15 %, 26.28 %, 26.30 %, and 26.33 % respectively. Similarly, for hybrid nanoparticles such as GO-Al2O3, GO-Al2O3-MWCNT, MWCNT-GO, and MWCNT-Al2O3, these values increase by approximately 26.32 %, 26.3419 %, 26.3432 %, and 26.335 % respectively for thermal efficiency, and 5.16 %, 5.1702 %, 5.1704 %, and 5.1689 % respectively for electrical efficiency. Moreover, n-octadecane exhibits the highest melting fraction, while paraffin wax has the lowest melting fraction. Lastly, the genetic algorithm-neural network method was employed to estimate the PV electrical efficiency.

Experimental analysis of dust composition impact on Photovoltaic panel Performance: A case study

Solar Photovoltaic systems are greatly influenced by meteorological conditions of the surrounding area, dust is the most influencing one. Dust deposition on the surface of photovoltaic (PV) panel hinder the penetration of solar radiation to PV cells and eventually reduce the power production of PV system. To overcome dust-based power losses, frequent cleaning is required depending on geographical location, PV integration scheme and size of the PV power plant. In this manuscript, consequences of dust deposition on photovoltaic systems such as drop in radiation and output power operating are studied, and the optimal time interval for cleaning is determined. Airborne dust particles were collected for a month for morphological and meteorological characterization. The average mass concentrations of the sample are 187.63 μgm-3, showcasing an irregular distribution of dust particles having unlike shapes and sizes. In this study, the influence of dust deposition is quantified using temperature and insolation for clean and dirty PV panels. The overall performance of the PV system is studied based on a comparison of quantified and recorded data. Lastly, different cleaning methodologies are studied to procure the best ones. Power losses were brought down to 7% when PV panels were cleaned fortnightly, which is the most feasible interval in terms of balance between cleaning cost and energy wasted due to soiling.

Experimental and numerical study of enhancing the electrical performance of photovoltaic panel using phase change material in transient conditions

ABSTRACTThis study investigates employing a phase change material (PCM) to enhance the electrical power production and efficiency of photovoltaic (PV) panels. The PCM was placed at the backside of the collector, and the actual PV cell temperature values were recorded and evaluated by comparison in both cases with and without PCM. During the daytime and according to experimental findings, the existence of PCM decreased the cell temperature by an additional 9.5°C compared to a standard PV panel. The maximum generated power values using the hybrid PV/PCM system were 38.76 W on August 5th and 47 W on October 23rd, respectively. Conversely, the conventional PV generated only 35.2 W and 37 W on the same days. The results also revealed that the best electrical efficiencies were reached using the PV/PCM system at values of 12.1% and 15%, compared to 9.2% and 11.9% for conventional PV on the same days. A 1.38% greater energy production efficiency was reached using the hybrid PV/PCM system. Finally, using a numerical approach, the differential equations governing the energy exchange between the different layers were solved for both systems, and an excellent agreement for both the numerical results and the experimental data was confirmed.

An integrated cooling mechanism for photovoltaic systems

Photovoltaic (PV) panels, despite their potential as a renewable energy source, suffer from performance degradation due to temperature rise. This research proposes an integrated passive cooling system that combines finned convective and radiative cooling with graphite-infused phase change material (PCM) in a cascade configuration. The cascade arrangement creates temperature stratification, delaying and restricting temperature increases. Graphite-infused PCM enhances thermal conductivity, facilitating efficient heat dissipation. Additionally, a finned heat sink augments convective heat transfer between PCM and the ambient environment, increasing the heat transfer area. A thin silica layer with pyramid lattices is incorporated to improve radiative heat transfer, particularly beneficial in hot climates with a significant temperature difference between the PV cell and the sky. A mathematical model is developed and validated against experimental data to assess the system’s performance. The model simulates PV cell temperature variations for six different scenarios to identify the most effective cooling mechanism. The study demonstrates a remarkable 27 °C reduction in peak PV cell temperature, translating to a substantial up to 100% increase in overall PV cell efficiency. This research contributes to the evolving landscape of PV cooling technologies and provides valuable insights for optimizing PV panel performance.

Experimental study on impact of high voltage power transmission lines on silicon photovoltaics using artificial neural network

The recent trend of renewable energy has positioned solar cells as an excellent choice for energy production in today’s world. However, the performance of silicon photovoltaic (PV) panels can be influenced by various environmental factors such as humidity, light, rusting, temperature fluctuations and rain, etc. This study aims to investigate the potential impact of high voltage power transmission lines (HVTL) on the performance of solar cells at different distances from two high voltage levels (220 and 500 KV). In fact, HVTLs generate electromagnetic (EM) waves which may affect the power production and photocurrent density of solar cells. To analyze this impact, a real-time experimental setup of PV panel is developed (using both monocrystalline and polycrystalline solar cells), located in the vicinity of 220 and 500 KV HVTLs. In order to conduct this study systematically, the impact of HVTL on solar panel is being measured by varying the distance between the HVTL and the solar panels. However, it is important to understand that the obtained experimental values alone are insufficient for comprehensive verification under various conditions. To address this limitation, an Artificial Neural Network (ANN) is employed to generate HVTL impact curves for PV panels (particularly of voltage and current values) which are impractical to obtain experimentally. The inclusion of ANN approach enhances the understanding of the HVTL impact on solar cell performance across a wide range of conditions. Overall, this work presents the impact study of HVTL on two different types of solar cells at different distances from HVTL for two HV levels (i.e., 220 and 500 KV) and the comparison study of HVTL impact on both monocrystalline and polycrystalline solar cells.

Investigating the Impact of Partial Shading on Photovoltaic Panels and Enhancing their Efficiency using the Python

This research project focuses on investigating the impact of partial shading on photovoltaic (PV) panels and proposes methods to enhance their efficiency using Python programming. Partial shading can significantly reduce the performance of PV panels by creating imbalances in current and voltage outputs. By leveraging Python's computational capabilities, this study aims to develop simulation models and algorithms that accurately capture the behavior of shaded PV panels. The objectives of this research include building a comprehensive understanding of partial shading effects, developing a Python-based simulation framework, analyzing the impact of different shading patterns on PV panel efficiency, investigating novel techniques to enhance efficiency using Python, and evaluating proposed approaches through simulations and experimental validation. Through this investigation, we aim to contribute to the development of improved strategies for the design and operation of PV systems. By mitigating the negative effects of shading and enhancing PV panel efficiency, we can further promote the adoption of sustainable solar energy solutions. The outcomes of this research have the potential to advance the field of solar energy and facilitate a greener and cleaner future. Also, this paper aims to investigate the impact of partial shading on photovoltaic (PV) panels and explores methods to enhance their efficiency using Python. Partial shading can significantly reduce the overall output of PV systems, leading to suboptimal performance. By analyzing shading patterns and implementing intelligent algorithms, we can optimize PV panel configuration and improve their efficiency. In this study, the Python programming language will be utilized to develop simulation models, perform data analysis, and propose solutions for increasing the efficiency of shaded PV panels.