Solar Cell Parameter Extraction Method from Illumination and Dark I-V Characteristics

Montalvo-Galicia, F.; Sanz-Pascual, M.T.; Rosales-Quintero, P.; Moreno, Mario

doi:10.3390/nano12121955

Cited by 6 publications

(1 citation statement)

References 42 publications

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“…Occasionally, the visual distinction between the two different diode regions is not very clear. In those cases, the diodes' region is treated as one and discussed [25].…”

Section: Introductionmentioning

confidence: 99%

Alternative preconditioning by utilization of a thin film module's dark diode fingerprint

Friedel,

Winter

2024

EPJ Photovolt.

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Although the continuously advancing silicon wafer-based modules dominate the commercial PV landscape, thin film technologies have not lost any of their attraction, especially in areas where their advantages count, like light weight, flexibility, and easy manufacturing. This has been the case for chalcogenides in the past and it will be for coming perovskite-based materials, whether as stand-alone, in multi- or heterojunction devices. Unfortunately, many thin film technologies suffer from metastability, i.e., their physical properties change temporarily with storage, transport or operating conditions, on time scales from hours to months. For this reason, preconditioning is crucial, before reliably evaluating such a module's performance. Presently, the respective preconditioning standards are exclusively focused on illumination-induced stabilization of the module's power at the maximum power point (PMPP). However, using PMPP as the only marker might not be the wisest choice. First, the PMPP is basically a black box, i.e., a module may show the same temporary power value at times, while being in very different condition if one looked closely on its device physics then. This may lead to false assumptions about the module's quality. Second, aiming for the highest stable PMPP of a module might not always be the desired goal, e.g., in warranty cases where the actual field performance of a module is in question and not how it would behave in perfect state after standard preconditioning. To overcome these limitations of present preconditioning standards, an alternative additional approach is required. In this report, we give a brief view on the inevitable shortcomings of present methods for thin film modules and demonstrate how the dark current characteristic of a thin film module can be used like a fingerprint instead, representing its device physics that define its actual state. Whereas in PV research, dark IV curves are commonly analyzed in detail for hints on charge transport mechanisms, interface properties or semiconductor degradation in the device, such effort would be inconvenient and unnecessary for fast-track commercial module testing. Here, we suggest focusing merely on the effective device properties, which are reflected quantitatively in the diode-parameters. The goal is to feed a recorded module dark current curve into an automated mathematical procedure, which fits the data to the double-diode model, enabling the extraction of the diode parameter-set. With this as a marker, instead of using solely PMPP during preconditioning treatments, it is much more likely that the desired previous physical state of a module is really reinstated. Additionally, the described dark current approach is conveniently independent of a light source's properties and insensitive to module soiling. The results presented here, give a first impression on the potential that such a method could have, showcasing effects of dark storage degradation and their recovery by illumination or bias-induced preconditioning on the dark current characteristics of individual CdTe and CIGS commercial PV-modules of different generations and manufacturers.

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“…Occasionally, the visual distinction between the two different diode regions is not very clear. In those cases, the diodes' region is treated as one and discussed [25].…”

Section: Introductionmentioning

confidence: 99%

Alternative preconditioning by utilization of a thin film module's dark diode fingerprint

Friedel,

Winter

2024

EPJ Photovolt.

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Metastability in Dark Current Diode Characteristics of Chalcogenide Photovoltaic Modules

Friedel

2024

Physica Rapid Research Ltrs

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While present trends in commercial PV are set on a‐Si/c‐Si heterojunctions and promising perovskites, the chalcogenides still attract interest as an excellent candidate for coming multi‐ and heterojunction devices with perovskites. Continuously enhanced over the years, typical metastabilities in thin film devices still remain, causing issues under outdoor operation. Unfortunately, qualitative assessment in commercial PV is solely focused on data at the maximum power point of its operation, whether in simple on‐site PV plant monitoring or following latest standards for certified laboratory testing, thus metastabilities merely register as undefined power fluctuations. We show in this study that dark current characteristics are a simple and yet field‐fit method, to identify metastable changes and take suitable counter measures. With this study, using commercial CdTe and CIGS showcase modules of various manufacturers and production generations, we demonstrate how dark current characteristics allow to pin‐point physical changes of the individual module, between its pristine state, outdoor operation, dark degradation and stabilization, like a fingerprint. Using the two‐diode model, we show that alterations to respective regimes of the characteristic can be assigned to typical defects, defining the module’s current state, and be used to it as a guide to evaluate its recuperation via preconditioning treatments.This article is protected by copyright. All rights reserved.

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Parameter identification of photovoltaic converter models

Obukhov,

Plotnikov,

Klimova

2023

jour

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The work aims to develop a simple and effective method for identifying the parameters of photovoltaic converter (PV-cell) models for their wide practical application. An exponential model having one diode and ﬁve parameters is adopted as the basic model of the photovoltaic converter to facilitate its easy integration into MatLab/Simulink simulation software. To identify the parameters of models of photovoltaic converters, an original method based on ﬁnding the minimum of the root-mean-square error between model and experimental volt-ampere characteristics was used. The effectiveness of the method was conﬁrmed by determining the parameters of different models of photovoltaic modules based on various technologies: thin-ﬁlm Shell ST40, monocrystalline Shell SP70, and polycrystalline Kyocera KC200GT. A developed technique for constructing mathematical models of photovoltaic converters in order to reproduce their electrical characteristics is presented. The solution is easily implemented in Excel spreadsheet software with the “Search for Solution” add-on installed. The proposed universal method for identifying the parameters of photoconverter models can be used to build models of a wide range of photovoltaic modules and solar cells. The model current-voltage characteristics of the considered photovoltaic modules are shown to be in good agreement with experimental characteristics across a wide range of temperature and insolation conditions corresponding to their actual operation. Higher accuracy is achieved when using the proposed identiﬁcation method to determine the electrical parameters of mathematical models of photovoltaic converters than when using other well-known analytical and numerical methods. The result is a simple and effective method for constructing mathematical models of photovoltaic converters, which does not require the use of programming or the development of specialized numerical algorithms, allowing it to be used to solve many technical problems related to the design and operation of photovoltaic systems.

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Solar Cell Parameter Extraction Method from Illumination and Dark I-V Characteristics

Cited by 6 publications

References 42 publications

Alternative preconditioning by utilization of a thin film module's dark diode fingerprint

Alternative preconditioning by utilization of a thin film module's dark diode fingerprint

Metastability in Dark Current Diode Characteristics of Chalcogenide Photovoltaic Modules

Parameter identification of photovoltaic converter models

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