Real‐time estimation of solar irradiance and module temperature from maximum power point condition

Moshksar, Ehsan; Ghanbari, Teymoor

doi:10.1049/iet-smt.2017.0476

Cited by 16 publications

(14 citation statements)

References 34 publications

(80 reference statements)

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“…Our method estimates the solar irradiance with an nRMSE between 4.2% and 4.7%; from the state-of-the-art, it appears that some methods give a poorer value as 6%-8% for a short-circuit method [5], 6.4% and 6.8% for, respectively, a short-circuit and under-load methods [20] and even with an nRMSE equal to 15.1% for short-circuit method [29]; some other methods present an equivalent accuracy such as the method developed by Carrasco et al [31] with a 0.87% and 6.67% nRMSE for clear sky and cloudy sky days, respectively. Better results are obtained by Laudani et al [28] (nRMSE = 1.5-3.2%) and Moshksar and Ghanbari [33] with an average nRMSE of 1.08% (maximum 4.22%) for solar irradiance estimation.…”

Section: Mean Absolute Errors and Root Mean Square Errorsmentioning

confidence: 74%

“…Moshksar and Ghanbari [33] developed a reliable, yet somewhat complex method to estimate the solar irradiance and PV temperature in the maximum power point (MPP) conditions; the accuracy in terms of normalized absolute relative error, nMAE, is 1.08% (maximum 4.22%) and 0.53% (maximum 0.69%) for respectively the solar irradiance G and the PV cell module temperature T c .…”

mentioning

confidence: 99%

“…For the papers in which a method for computing both G and T c based on the current I mpp and the voltage V mpp in maximum power point conditions is used and that can be applied to systems that are under operation [33], it appears that the methods are often more elaborate and involve the determination of several parameters that have to be estimated, but when a computer is employed to collect measurements, no matter how complex the algorithm is, the calculations are easily and rapidly realized.…”

mentioning

confidence: 99%

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Experimental Application of Methods to Compute Solar Irradiance and Cell Temperature of Photovoltaic Modules

Abe

Dias

Notton

et al. 2020

Sensors

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Solar irradiance and cell temperature are the most significant aspects when assessing the production of a photovoltaic system. To avoid the need of specific sensors for quantifying such parameters, recent literature presents methods to estimate them through electrical measurements, using the photovoltaic module itself as a sensor. This work presents an application of such methods to data recorded using a research platform at University of Corsica, in France. The methods and the platform are briefly presented and the results are shown and discussed in terms of normalized mean absolute errors (nMAE) and root mean square errors (nRMSE) for various irradiance and cell temperature levels. The nMAE (and nRMSE) for solar irradiance are respectively between 3.5% and 3.9% (4.2% and 4.7%). Such errors on computed irradiance are in the same order of magnitude as those found in the literature, with a simple implementation. For cell temperatures estimation, the nMAE and nRMSE were found to be in the range 3.4%–8.2% and 4.3%–10.7%. These results show that using such methods could provide an estimation for the values of irradiance and cell temperature, even if the modules are not new and are not regularly cleaned, but of course not partially shaded.

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Section: Mean Absolute Errors and Root Mean Square Errorsmentioning

confidence: 74%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Experimental Application of Methods to Compute Solar Irradiance and Cell Temperature of Photovoltaic Modules

Abe

Dias

Notton

et al. 2020

Sensors

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“…Single phasing detection in induction motors has been done for computing symmetrical components, skewness and kurtosis values in the Park plane [30]. A non-linear model-based real-time estimation of solar irradiance and module temperature measurement have been carried out at MPPT condition [31]. Assessing the previous literature, it has been concluded that although the work has been proceeded in different domains, for fault estimation in hybrid microgrids, the solar-wind hybrid microgrid unsymmetrical fault analysis is not done using MRA of DWT and ST-based statistical analysis.…”

Section: Introductionmentioning

confidence: 99%

Fault analysis in solar–wind microgrid using multi‐resolution analysis and Stockwell transform‐based statistical analysis

Ray

Chattopadhyay

2020

IET Science, Measurement & Technology

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“…To have an enhanced understanding of the relationship between meteorological specifics and PV power generation, the equivalent circuit model of the PV system can be considered. The electrical parameters of the circuit are vaguely written as nonlinear and difficult purposes like temperature and radiation of solar [8,9].…”

mentioning

confidence: 99%

Temperature and Irradiance Based Analysis the Specific Variation of Pv Module

et al. 2021

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The effect of irradiance and increase of temperature on the back surface of the PV module would decrease the standardized efficiency of PV. To overcome this problem observed results of solar module (ORSM) and Newton Raphson’s (iterative) methods have been proposed in this research. This article compares ORSM and iterative methods of changing the specifications of a single diode model (SDM) extracted from a PV module beneath standard test conditions (STC) to calculate irradiance and various operating conditions. To make this comparison, the exact value of each diode parameter on the STC is essential. These are achieved by accepted algebraic values and iterative techniques. Newton Raphson’s technique has been proven to be the mainly precise method to find these specifications in STC. Therefore, these specifications are used to different techniques that change the parameters of an SDM with radiation and temperature. The MATLAB model is designed to assess the conducting of individual techniques by PVM. The results are compared with the measured data, and the accuracy of photovoltaic module efficiency has been achieved through different technologies at different temperature and insolation levels.

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Real‐time estimation of solar irradiance and module temperature from maximum power point condition

Cited by 16 publications

References 34 publications

Experimental Application of Methods to Compute Solar Irradiance and Cell Temperature of Photovoltaic Modules

Experimental Application of Methods to Compute Solar Irradiance and Cell Temperature of Photovoltaic Modules

Fault analysis in solar–wind microgrid using multi‐resolution analysis and Stockwell transform‐based statistical analysis

Temperature and Irradiance Based Analysis the Specific Variation of Pv Module

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