On the fast convergence modeling and accurate calculation of PV output energy for operation and planning studies

Navabi, Reza; Abedi, Sajjad; Hosseinian, Seyed Hossein; Pal, Ranadip

doi:10.1016/j.enconman.2014.09.070

Cited by 48 publications

(16 citation statements)

References 18 publications

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“…This panel type has been used because the financial project mentioned in the acknowledgment was focused on it. It has been studied and compared with other types in Navabi et al 80…”

Section: Validationmentioning

confidence: 99%

Fault detection and diagnosis in photovoltaic panels by radiometric sensors embedded in unmanned aerial vehicles

Ramírez

Das

Márquez

2021

Progress in Photovoltaics

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Photovoltaic solar energy is increasing its capacity in the global electric market due to its lower operating costs and higher efficiency, together with the support of the governments. Photovoltaic solar panels require high initial investments, and it is necessary to use advanced and efficient methods that lead to the maintainability and reliability of these systems, extending their life cycle and productivity. New condition monitoring systems are being applied to reduce the cost of inspections and ensure efficient data collection. The main contribution of this paper is a new efficient and low-cost condition monitoring system based on radiometric sensors. The thermal patterns of the main photovoltaic faults (hot spot, fault cell, open circuit, bypass diode, and polarization) are studied in real photovoltaic panels. Different scenarios are considered, analyzing online the main patterns of the faults by Internet of Things.The accuracies of the results are statistically analyzed and compared with fault-free scenarios. The validation of the approach is done by thermographic analysis of the experiments and employing a different radiometric sensor. The detection of faults with statistical analysis is achieved in 100% of the cases, and the identification of the specific fault in 96% of the scenarios. An artificial neural network and classification learner algorithms are employed to validate the results, obtaining similar results for fault identification, 95% and 94%, respectively, and 100% for fault detection.

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“…This panel type has been used because the financial project mentioned in the acknowledgment was focused on it. It has been studied and compared with other types in Navabi et al 80…”

Section: Validationmentioning

confidence: 99%

Fault detection and diagnosis in photovoltaic panels by radiometric sensors embedded in unmanned aerial vehicles

Ramírez

Das

Márquez

2021

Progress in Photovoltaics

View full text Add to dashboard Cite

show abstract

“…On the other hand, some of the researchers have proposed other methods to overcome the drawbacks of the analytical method, such as Newton Raphson (NR) based methods Easwarakhanthan et al, 1986;Villalva et al, 2009, Levenberg-Marquardt (LM) algorithm Ma et al, 2014;Tossa et al, 2014, artificial neural network based methods (Karabacak and Cetin, 2014;Karatepe et al, 2006;Karamirad et al, 2013;Bonanno et al, 2012;Patra and Maskell, 2012;Patra, 2011), evolutionary algorithms (EA) Dizqah et al, 2014;Moldovan et al, 2009;Zagrouba et al, 2010;Ismail et al, 2013;Hamid et al, 2013;Khanna et al, 2015;Ye et al, 2009;Askarzadeh and Dos Santos Coelho, 2015;Siddiqui and Abido, 2013;Yuan et al, 2014;Barukčić et al, 2014;Ishaque et al, 2012 and some other numerical techniques (Navabi et al, 2015;Lineykin et al, 2014) for this purpose. As a matter of fact, there are some drawbacks of NR based method for estimating PV module's model parameters.…”

Section: Introductionmentioning

confidence: 99%

Extraction of photovoltaic module model’s parameters using an improved hybrid differential evolution/electromagnetism-like algorithm

et al. 2015

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“…However, a significant deviation occurs between the simulated and actual performances of a PV module [9]. Meanwhile, numerical methods, such as the Newton-Raphson method (NRM) [10], the Levenberg-Marquardt method [11,12], and other numerical techniques [13], are also used to extract the parameters of a PV module model. A combination of analytical and numerical (i.e., NRM) solutions was proposed by Hejri et al [14] to extract five parameters of a double-diode PV model using the manufacturer specifications of the PV module.…”

Section: Introductionmentioning

confidence: 99%

Parameters extraction of double diode photovoltaic module’s model based on hybrid evolutionary algorithm

Muhsen

Ghazali

Khatib³

et al. 2015

Energy Conversion and Management

140

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On the fast convergence modeling and accurate calculation of PV output energy for operation and planning studies

Cited by 48 publications

References 18 publications

Fault detection and diagnosis in photovoltaic panels by radiometric sensors embedded in unmanned aerial vehicles

Fault detection and diagnosis in photovoltaic panels by radiometric sensors embedded in unmanned aerial vehicles

Extraction of photovoltaic module model’s parameters using an improved hybrid differential evolution/electromagnetism-like algorithm

Parameters extraction of double diode photovoltaic module’s model based on hybrid evolutionary algorithm

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