Augmenting the performance of photovoltaic panel by decreasing its temperature using various cooling techniques

Nabil, Tamer; Mansour, Tamer

doi:10.1016/j.rineng.2022.100564

Cited by 46 publications

(4 citation statements)

References 25 publications

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“…However, parking systems have multiple advantages, including capacity increases of dozens of percentage points compared to classical parking houses (there is no need to include handling areas; the client loads the vehicle in the system and can leave) as well as energy savings-photovoltaic panels and recuperation options allow houses equipped with such parking systems to operate in so-called island modes and, hence, not only supply energy to themselves but also send excess energy back to the network. This could be an even bigger factor using state-of-the-art photovoltaic technology (see, e.g., [34]).…”

Section: Discussionmentioning

confidence: 99%

Assessment of Automated Parking Garage Services as a Means to Sustainable Traffic Development in a Mid-Sized City

2023

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The research in this article deals with verifying the deficit of parking spaces from model examples in the city of Ostrava, Czech Republic. Specifically, it deals with the possibilities of solving these deficits using automated parking systems. The main data collection took place between 2010 and 2019; later, supplemental lockdown data (up until May 2022) were obtained. The main objective of this article was to use data to determine the profitability and functionality of automated parking systems in mid-sized cities such as Ostrava. The RING system was chosen as a suitable model for the automated parking system. The data (using a least-squares approximation) were used via statistical methods to make predictions for future years, including the construction of confidence limits for a given significance level. Based on data from 2011–2019, we found that the RING system would be profitable with a probability of 92.45% in the following years. We compared these predictions with the actual data and made a new prediction.

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Section: Discussionmentioning

confidence: 99%

Assessment of Automated Parking Garage Services as a Means to Sustainable Traffic Development in a Mid-Sized City

2023

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“…Moreover, it was shown that polycrystalline PV cell type is more affected than monocrystalline. Therefore, some other researchers focused on proposing and enhancing the cleaning methods to conquer the defect [36,37].…”

Section: Methodsmentioning

confidence: 99%

An Experimental Study on Simultaneous Use of Metal Fins and Mirror to Improve the Performance of Photovoltaic Panels

2022

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The world is inconceivable without an everlasting demand for energy. Nowadays, various kinds of renewable energies, such as solar energy, are developing rapidly, since they have the least negative environmental impacts. Irradiation intensity is one the most important parameters in photovoltaic (PV) technology, and so integration of mirrors with a PV module can improve its performance. Mounting mirrors increases the radiation intensity but, at the same time, raises the surface temperature, which in turn reduces the electrical efficiency. The novelty of this study is keeping the cell temperature low despite receiving more radiation by installing 10 aluminum fins on the back of the panel. All tests were experimentally performed in the hot climate of Dezful, Iran. As a result, the best tilt angle of the mirror was found at 30°, where the output power was enhanced by 3.3% and electrical efficiency was reduced by 0.5% compared with the conventional case. When aluminum fins were added as heat sinks, both output power and electrical efficiency were enhanced by 11.4% and 13.1%, respectively. Moreover, comprehensive discussions on both energy and exergy are provided. The entropy generation was also calculated and accordingly, the case of PV 30 + fin generates 1.6% less entropy than the base one.

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“…One challenge is the increase in surface temperature, especially in countries with high solar radiation. Nabil and Mansour [22] studied the performance of polycrystalline silicon (PV) photovoltaic modules using different cooling systems and compared the performance of PV modules with and without cooling. For each degree of temperature increase, the maximum output power of the PV modules tested decreases by up to 0.42%.…”

Section: Introduction and State Of The Artmentioning

confidence: 99%

Application of Machine Learning to Predict I-V Characteristics of PV Modules Based on Steady-State Solar Simulator

Porowski,

Kowalik,

Gorzelnik

et al. 2024

Preprint

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Photovoltaic modules should pass series of tests and examinations, verifying the electrical and thermal characteristics of the module, before being released to the market, examining the properties of the modules should undergo appropriate durability and efficiency tests under real outdoor conditions with exposure to climatic conditions and under laboratory conditions. The performance of photovoltaic cells depends on many factors, such as solar irradiance, module operating temperature, installation location, weather conditions and module shading. In this paper, three selected photovoltaic modules were examined using a large-scale steady-state solar simulator. The current-voltage (I-V) characteristics of the photovoltaic modules were experimentally tested and analyzed. The next step was to implement a three-layer artificial neural network model (MLP). The experimental data obtained in the previous step coupled with output data from MLP were then used in global sensitivity analysis (GSA). Experiments carried out on a large-scale stationary solar simulator showed differences between the values declared by the manufacturer and the values obtained from measurements of PV modules. The first module tested achieved the maximum power point greater than that specified by the manufacturer, while the other two showed power drops; it was 85-87% for the second module, and 95-98% for the third, respectively. The performed global sensitivity analysis (GSA) for the MLP model showed that the parameters: eff (22.9) and Voc/V (14.19) have the largest effect on the power-voltage relationship, while U (7.29) has the smallest effect. The usefulness of machine learning (ML) methods in the comparative analysis of PV modules has been proved.

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Augmenting the performance of photovoltaic panel by decreasing its temperature using various cooling techniques

Cited by 46 publications

References 25 publications

Assessment of Automated Parking Garage Services as a Means to Sustainable Traffic Development in a Mid-Sized City

Assessment of Automated Parking Garage Services as a Means to Sustainable Traffic Development in a Mid-Sized City

An Experimental Study on Simultaneous Use of Metal Fins and Mirror to Improve the Performance of Photovoltaic Panels

Application of Machine Learning to Predict I-V Characteristics of PV Modules Based on Steady-State Solar Simulator

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