Spatiotemporal Modeling of Real World Backsheets Field Survey Data: Hierarchical (Multilevel) Generalized Additive Models: Preprint

Raymond Wieser, Zelin (Zack) Li, Stephanie Moffitt, Ruben Zabalza, Evan Boucher, Silvana Ayala, Matthew Brown, Xiaohong Gu, Liang Ji, Colleen O'Brien, Adam Hauser, Greg O'Brien, Xuanji Yu, Roger French, Michael Kempe, Jared Tracy, Kausik Choudhury, William Gambogi, Laura Bruckman, Kenneth Boyce

Research output: Contribution to conferencePaper


Assessing photovoltaic module backsheet durability is critical to increasing module lifetime. Lab-based accelerating testing has recently failed to predict large scale failures of widely adopted polymeric materials. Field surveyed data is critical to assess the performance of component lifetime. Using a documented field survey protocol, 13 field surveys were conducted. Each measurement is encoded with its spatial location in respect to the other modules. By combining field survey data on degradation predictors with real time satellite weather data, data-driven predictive models of backsheet degradation were trained. LOESS models were constructed to investigate the spatial dependence of measurements. It was found that micro-climatic effects like treelines, ground surface changes, and elevation changes effected the magnitude and variance of the measurements. A GAM model was created to predict the value of degradation based on measured predictors. The model includes variables on the climate of the system and the location of each measurement in the PV mounting structure. The model performed well with an adj:R2 of 0:95 for yellowness index prediction. The model was cross-validated using k-folds.
Original languageAmerican English
Number of pages9
StatePublished - 2022
Event49th IEEE Photovoltaic Specialists Conference (PVSC 49) - Philadelphia, Pennsylvania
Duration: 5 Jun 202210 Jun 2022


Conference49th IEEE Photovoltaic Specialists Conference (PVSC 49)
CityPhiladelphia, Pennsylvania

Bibliographical note

See NREL/CP-5K00-85098 for paper as published in proceedings

NREL Publication Number

  • NREL/CP-5K00-81961


  • backsheet
  • degradation
  • field survey
  • modeling
  • spatio-temporal


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