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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