Comparative study of PV power forecast using parametric and nonparametric PV models

Abstract

Forecast procedures for large ground mounted PV plants or smaller BIPV or BAPV systems may use a parametric or a nonparametric model of the PV system. In this paper, both approaches are used independently to calculate the energy delivered to the grid on an hourly basis in forecast procedures that use meteorological variables from a Numerical Weather Prediction model as inputs, and their performances against real generation data from six PV plants are analyzed. The parametric approach relies on mathematical models with several parameters that describe the PV systems and it was implemented in MATLAB whereas the nonparametric approach is based on Quantile Regression Forests with training and forecast stages and its code was built in R. The parametric approach presented more significant bias on its results, mostly due to the input data and the transposition model of irradiance from a horizontal surface to the plane of the PV array.