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Module Level Exposure and Evaluation Test (MLEET) for Real- world and Laboratory-based PV Modules: Common Data and Analytics for Quantitative Cross-correlation and Validation

Technical Report ·
DOI:https://doi.org/10.2172/1529093· OSTI ID:1529093
 [1];  [2];  [2]
  1. Case Western Reserve Univ., Cleveland, OH (United States); Case Western Reserve University
  2. Case Western Reserve Univ., Cleveland, OH (United States)
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Our objective is to develop a set of lifetime performance prediction models for PV modules. Models were developed based on common I-V, Pmp datastreams from modules under outdoor (real-world) exposure and indoor (laboratory-based) accelerated exposures and temporal analytics. These common datastreams that span both indoor and outdoor exposures were supplemented with additional information such as meteorology data, climate and PV module make/model and module specifications. The predictive models were developed using a stressor/mechanism/response framework in which all data are categorized as stressor, mechanism or performance variables and are represented as time-series datastreams. We develop and validate these accelerated indoor exposures and evaluation tests and models and cross-correlate the temporal signatures of PV module degradation mechanisms in the I-V, Pmp time-series between outdoor and accelerated indoor tests. The predictive test and model specify indoor and outdoor exposure and data acquisition criteria, variable selection, and temporal duration and variance.
Research Organization:
Case Western Reserve Univ., Cleveland, OH (United States)
Sponsoring Organization:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Solar Energy Technologies Office (EE-4S)
Contributing Organization:
Sandia National Laboratory, Terraform Power, UL, Fraunhofer-ISE
DOE Contract Number:
EE0007140
OSTI ID:
1529093
Report Number(s):
DOE-CWRU--0007140; 2163680374
Country of Publication:
United States
Language:
English

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Related Subjects

14 SOLAR ENERGY
data analytics
degradation
reliability