Investigation of Operating Parameters and Degradation of Photovoltaic Panels in a Photovoltaic Power Plant

Kudelas, Dušan; Taušová, Marcela; Tauš, Peter; Gabániová, Ľubomíra; Koščo, Ján

doi:10.3390/en12193631

Cited by 18 publications

(12 citation statements)

References 14 publications

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“…(STC: temperature of 25 • C, irradiance of 1000 W/m 2 and air mass 1.5 (AM1.5) spectrum). The E out depends not only on the environmental and installation conditions of the PV system but also on failures and losses due to shading [23], dust and degradation [22,24,25] as shown by the coefficients F S and L F which consider the efficiency reduction when these phenomena occur. These phenomena affect the functioning of the module in differing invasive ways: failures can be catastrophic, locking the single-cell or module operation, or by deterioration, reducing the operation of the single cell or the entire module progressing in the file of the systems.…”

Section: Pv Systems Efficiencymentioning

confidence: 99%

Convolutional Neural Network for Dust and Hotspot Classification in PV Modules

et al. 2020

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This paper proposes an innovative approach to classify the losses related to photovoltaic (PV) systems, through the use of thermographic non-destructive tests (TNDTs) supported by artificial intelligence techniques. Low electricity production in PV systems can be caused by an efficiency decrease in PV modules due to abnormal operating conditions such as failures or malfunctions. The most common performance decreases are due to the presence of dirt on the surface of the module, the impact of which depends on many parameters and conditions, and can be identified through the use of the TNDTs. The proposed approach allows one to automatically classify the thermographic images from the convolutional neural network (CNN) of the system, achieving an accuracy of 98% in tests that last a couple of minutes. This approach, compared to approaches in literature, offers numerous advantages, including speed of execution, speed of diagnosis, reduced costs, reduction in electricity production losses.

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Section: Pv Systems Efficiencymentioning

confidence: 99%

Convolutional Neural Network for Dust and Hotspot Classification in PV Modules

et al. 2020

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“…Based on the deviation between the calculated temperature distribution and the output power of the PV module, the assumption of incorrect measurements of solar radiation was confirmed. The output power of PV modules is also significantly affected by degradation, which reduces the output power of the PV module by 1% annually [46]. Degradation of PV modules involves many types of effects such as cell cracking, yellowing, browning and more [47,48].…”

Section: Meteorological and Experimental Datamentioning

confidence: 99%

Experimental Validation of a Thermo-Electric Model of the Photovoltaic Module under Outdoor Conditions

et al. 2021

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An operating temperature of the photovoltaic (PV) module greatly affects performance and its lifetime. Therefore, it is essential to evaluate operating temperature of the photovoltaic module in different weather conditions and how it affects its performance. The primary objective of this paper is to present a dynamic thermo-electric model for determining the temperature and output power of the photovoltaic module. The presented model is validated with field measurement at the Institute of Energy Technology, Faculty of Energy Technology, University of Maribor, Slovenia. The presented model was compared with other models in different weather conditions, such as clear, cloudy and overcast. The evaluation was performed for the operating temperature and output power of the photovoltaic module using Root-Mean-Square-Error (RMSE) and Mean-Absolute-Error (MAE). The average RMSE and MAE values are 1.75 °C and 1.14 °C for the thermal part and 20.34 W and 10.97 W for the electrical part.

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“…In order to achieve carbon-free energy, it is primarily necessary, traditional, and nonrenewable sources such as coal, natural gas, and oil that need to be replaced by alternative energy sources such as photovoltaic, wind, and nuclear energy [7,8].…”

Section: Introductionmentioning

confidence: 99%

The Usage of UCG Technology as Alternative to Reach Low-Carbon Energy

et al. 2021

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Countries of the European Union have stated transition to carbon-neutral economy until the year of 2050. Countries with a higher share of coal-fired power generation currently have no solution to end their combustion and use clean, emission-free energy immediately. The solution to this problem in the energy industry appears to be the increased use of natural gas, which significantly reduces CO2 emissions. In this article, we investigated the possibility of using coal in situ, using UCG (underground coal gasification) technology. We focused on verified geological, hydrogeological, and tectonic information about the selected brown coal deposit in Slovakia. This information has been assessed in research projects in recent years at the Technical University. From the abovementioned information, possible adverse factors were evaluated. These factors affect the rock environment around the underground generator by UCG activity. As part of the process management, measures were proposed to eliminate the occurrence of pollution and adverse effects on the environment. In the final phase of the UCG technology, we proposed to carry out, in the boreholes and in the generator cavity, water flushing and subsequent grouting. The proposed are suitable materials for solidification and stabilization. Results of this article´s solutions are crucial in the case of usage of this so-called clean technology, not only in Slovakia but also worldwide.

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Investigation of Operating Parameters and Degradation of Photovoltaic Panels in a Photovoltaic Power Plant

Cited by 18 publications

References 14 publications

Convolutional Neural Network for Dust and Hotspot Classification in PV Modules

Convolutional Neural Network for Dust and Hotspot Classification in PV Modules

Experimental Validation of a Thermo-Electric Model of the Photovoltaic Module under Outdoor Conditions

The Usage of UCG Technology as Alternative to Reach Low-Carbon Energy

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