heets are a key polymeric component of a PV module and understanding its degradation is necessary to be able to predict the lifetime of PV modules. We are developing a backsheet predictive tests and a model based on point- in-time data from analytical techniques and datastreams that are applicable to both outdoor and indoor PV module backsheet studies and are supplemented with meteorology data, climatic and brand/model, and other accessible information. The predictive tests and models will specify indoor and outdoor exposure and evaluation data acquisition criteria, variable selection, and temporal duration and variation so as to be able to predict backsheet performance in various climatic zones. This backsheet performance prediction is based on defined backsheet failures in the field, and is quantified by tracking backsheet degradation in the field so as to determine degradation rates. The backsheet lifetime performance predictive tests and models, will be developed using a Stressor / Mechanism / Response framework in which all data are categorized as stressor, mechanism and performance (response) variables and are represented as discrete points-in-time datasets. We will develop and validate these accelerated indoor exposures and evaluations and models and cross-correlate the outdoor and accelerated indoor exposures and evaluations. The evaluation techniques include nondestructive spectroscopy and microscopy techniques and destructive techniques and will provide data in predefined variables, which are used in the predictive modeling.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.