Estimation of power output and thermodynamic analysis of standard and finned photovoltaic panels
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Date
2021
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Journal Title
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Volume Title
Publisher
Bellwether Publishing, Ltd.
Access Rights
info:eu-repo/semantics/closedAccess
Abstract
This study deals with the estimation of power output and also thermodynamic analysis of two different photovoltaic panels. One of the panels is a standard photovoltaic module without fins (SPV), and the other one is a photovoltaic module with fins (FPV). First, a multi-layer feed-forward neural network structure is designed to estimate the daily power produced by photovoltaic modules. Furthermore, energy and exergy analyses were carried out to compare the performance of SPV and FPV panels. According to the thermodynamic analysis results using the experimental data obtained for two days (July 3, 2020 and August 4, 2020), it was calculated that the energy efficiency increased by a maximum of 8.77% and the exergy efficiency increased by a maximum of 25.9% in the FPV panel compared to the SPV panel. Moreover, considering the data obtained for each day during three months (July, August, and September), the total energy production increase in the FPV panel is approximately 6.7% compared to the SPV panel. © 2021 Taylor & Francis Group, LLC.
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Keywords
artificial neural network, energy analysis, exergy analysis, fin, passive cooling, Photovoltaic, prediction, Energy efficiency, Exergy, Feedforward neural networks, Fins (heat exchange), Photovoltaic cells, Thermoanalysis, Energy and exergy analysis, Exergy efficiencies, Multilayer feedforward neural networks, Photovoltaic modules, Photovoltaic panels, Power out put, Thermo dynamic analysis, Total energy, Multilayer neural networks
Journal or Series
Energy Sources, Part A: Recovery, Utilization and Environmental Effects
WoS Q Value
Q3
Scopus Q Value
Q2
