Publications Details

Photovoltaic System Modeling: Uncertainty and Sensitivity Analyses

Hansen, Clifford; Martin, Curtis E.

We report an uncertainty and sensitivity analysis for modeling AC energy from photovoltaic systems. Output from a PV system is predicted by a sequence of models. We quantify uncertainty in the output of each model using empirical distributions of each model’s residuals. We propagate uncertainty through the sequence of models by sampling these distributions to obtain an empirical distribution of a PV system’s output. We consider models that: (1) translate measured global horizontal, direct and global diffuse irradiance to plane-of-array irradiance; (2) estimate effective irradiance; (3) predict cell temperature; (4) estimate DC voltage, current and power; (5) reduce DC power for losses due to inefficient maximum power point tracking or mismatch among modules; and (6) convert DC to AC power. Our analysis considers a notional PV system comprising an array of FirstSolar FS-387 modules and a 250 kW AC inverter; we use measured irradiance and weather at Albuquerque, NM. We found the uncertainty in PV system output to be relatively small, on the order of 1% for daily energy. We found that uncertainty in the models for POA irradiance and effective irradiance to be the dominant contributors to uncertainty in predicted daily energy. Our analysis indicates that efforts to reduce the uncertainty in PV system output predictions may yield the greatest improvements by focusing on the POA and effective irradiance models.