How Useful are Conventional <i>I–V</i>s for Performance Calibration of Single‐ and Two‐Junction Perovskite Solar Cells? A Statistical Analysis of Performance Data on ≈200 Cells from 30 Global Sources

Song, Tao; Friedman, Daniel; Kopidakis, Nikos

doi:10.1002/solr.202100867

Cited by 7 publications

(6 citation statements)

References 12 publications

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“…In contrast to, for example, III-V solar cells, current perovskite-on-silicon multijunction solar cells need to be measured under continuous illumination due to stability issues, for example, to perform maximum power point (MPP) tracking for precise efficiency determination [26][27][28]. Consequently, these measurements must be performed in a stable state of the light sources.…”

Section: Calibration Of the Solar Simulator Spectral Distributionmentioning

confidence: 99%

A precise method for the spectral adjustment of LED and multi‐light source solar simulators

Chojniak,

Schachtner,

Reichmuth

et al. 2024

Progress in Photovoltaics

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Solar simulators based on light‐emitting diodes (LEDs) usually consist of many spectrally different LEDs, which in sum produce a sun‐like spectrum. On the one hand, this results in the advantage of a high spectral tunability of these systems and on the other hand, however, also in the challenge of a high number of parameters which have to be set for the adjustment of a suitable simulator spectrum. Multijunction solar cells consisting of series‐connected subcells are very sensitive to spectral irradiance conditions, which are affecting the current and the fill factor of the device. A precise adjustment of the simulator spectrum based on the spectral responsivity of the subcells is therefore essential for accurate multijunction measurements. Therefore, the number of spectrally different light sources used should be at least as high as the number of subcells in the device under test. However, for the measurement of multijunction devices, the much higher number of spectrally different light sources in common LED solar simulators results in a plethora of different simulator spectra, potentially suitable for the measurement. Furthermore, the nonlinear intensity characteristics of the utilized LEDs as well as the distance‐dependent illumination uniformity of such solar simulators add complexity when aiming for a precise spectral adjustment. To tackle these challenges, a new spectral adjustment procedure which is based on a least square's solution algorithm and the definition of appropriate boundary conditions for the calculation of suitable simulator settings is introduced in this publication. Focusing on measurements carried out under constant illumination makes the presented method especially applicable for perovskite‐on‐silicon multijunction devices. Therefore, an adapted method for the determination of the solar simulator's spectral properties, considering thermal influences which are particularly relevant when carrying out continuous illumination measurements, is introduced in this work. The presented method is verified applying it on a Wavelabs SINUS 220 LED solar simulator by performing a measurement comparison on a multijunction solar cell with Fraunhofer ISE CalLab's well‐established multilight source solar simulator.

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Section: Calibration Of the Solar Simulator Spectral Distributionmentioning

confidence: 99%

A precise method for the spectral adjustment of LED and multi‐light source solar simulators

Chojniak,

Schachtner,

Reichmuth

et al. 2024

Progress in Photovoltaics

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“…This is believed to originate in different transient response times of different stacks, which causes hysteresis in J-V scans depending on the scan speed. [40,41] This is also why MPPT has become the standard method of determining PSC's stabilized efficiency. [42]…”

Section: Data Management and Track Selectionmentioning

confidence: 99%

High‐Throughput Aging System for Parallel Maximum Power Point Tracking of Perovskite Solar Cells

Köbler

Neubert²,

Jankovec

et al. 2022

Energy Tech

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“…Our previous work [ 39 ] has given a comprehensive discussion on this topic for all types of PVSK cells, and here we just present a brief summary with updated performance deviation histograms for PVSK‐based MJ cells only with a doubled sample size than in Ref. [39], as shown in Figure . First, we can observe that the deviations of all the performance parameters from the 2 J PVSK/Si cells are smaller than those from the 2 and 3 J all‐PVSK cells.…”

Section: Key Performance Measurement Aspectsmentioning

confidence: 99%

“…To investigate how much of the usefulness of a fast I–V scan, a more quantitative study of the performance differences on these MJ PVSK cells has been conducted with linear regression analysis in our previous publication. [ 39 ] In the next section, possible options for fast and accurate performance testing for MJ PVSK cells will be discussed based on these quantitative findings.…”

Section: Key Performance Measurement Aspectsmentioning

confidence: 99%

“…Since the Asymptotic I-V scan approach was established in 2017, over 130 two-terminal MJ PVSK cells (i.e., 61 2 J and 3 J all-PVSK cells, and 72 2-J PVSK/Si cells) from 21 global sources have been measured with this steady-state measurement protocol. Since this protocol records all the cell performance parameters (i.e., V OC , I SC , FF, P MAX , and η) for both fast and asymptotic I-V scans, it enables us to conduct a detailed comparative analysis of the performance differences between the two types of scans and evaluate the usefulness of fast I-V. Our previous work [39] has given a comprehensive discussion on this topic for all types of PVSK cells, and here we just present a brief summary with updated performance deviation histograms for PVSK-based MJ cells only with a doubled sample size than in Ref. [39], as shown in Figure 9.…”

Section: Conventional I-v Versus Steady-state Efficiency Measurementsmentioning

confidence: 99%

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How Should Researchers Measure Perovskite‐Based Monolithic Multijunction Solar Cells’ Performance? A Calibration Lab's Perspective

et al. 2022

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Perovskite multijunctions (PVSK MJs) have made remarkable progress with monolithic PVSK/PVSK tandems surpassing the efficiency of single‐junction (1 J) PVSK cells and PVSK/Si cells reported to exceed the 30% efficiency mark. These efficiencies are reported at standard test conditions (STC), established by the photovoltaic (PV) community to facilitate comparison between devices and technologies. Herein, it is discussed why an accurate STC performance measurement for a MJ is more complicated than for a 1 J cell and the special aspects to be considered when measuring the current–voltage characteristics and the performance of PVSK‐containing MJ cells are emphasized. It is discussed why a spectrally adjustable solar simulator is needed and the sequence of accurate performance measurement, namely measurement of the spectral response of each junction, adjustment of the spectrum, and appropriate protocols for measuring the power output of the device at STC, is presented. For all these, common errors and pitfalls that sometime lead to misleading interpretation of the results are presented, and the methods to evaluate the accuracy of the data when a spectrally adjustable solar simulator is not available are recommended. Finally, first step is taken toward recommending performance measurement approaches when high throughput is required as will eventually be in a production line.

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How Useful are Conventional I–Vs for Performance Calibration of Single‐ and Two‐Junction Perovskite Solar Cells? A Statistical Analysis of Performance Data on ≈200 Cells from 30 Global Sources

Cited by 7 publications

References 12 publications

A precise method for the spectral adjustment of LED and multi‐light source solar simulators

A precise method for the spectral adjustment of LED and multi‐light source solar simulators

High‐Throughput Aging System for Parallel Maximum Power Point Tracking of Perovskite Solar Cells

How Should Researchers Measure Perovskite‐Based Monolithic Multijunction Solar Cells’ Performance? A Calibration Lab's Perspective

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