Abstract:
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In the study of photovoltaic (PV) modules degradation, a statistical approach is necessary for lifetime prediction. Structural Equation Modeling (SEM) allows for exploratory modeling, resulting in a system of equations describing the univariate relationships between variables. However, SEM typically only fits a system of linear equations, while network SEM (netSEM) enables nonlinear relationships among variables. Applied to indoor accelerated and outdoor exposure tests of PV modules, netSEM also allows for cross-correlation of indoor and outdoor degradation models. The cross-correlation scale factor (CCSF), determined by ordinary least squares, re-normalizes the independent indoor exposure time variable to best cross-correlate with the outdoor (real-time) model. We evaluate the performance of different indoor/outdoor model combinations to determine the indoor accelerated test which most closely relates to real world performance. NetSEM/cross-correlation represents a new direction in reliability research.
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