Quantile Regression Post-Processing of Weather Forecast for Short-Term Solar Power Probabilistic Forecasting

Luca Massidda,Marino Marrocu

doi:10.3390/en11071763

Abstract

The inclusion of photo-voltaic generation in the distribution grid poses technical difficulties related to the variability of the solar source and determines the need for Probabilistic Forecasting procedures (PF). This work describes a new approach for PF based on quantile regression using the Gradient-Boosted Regression Trees (GBRT) method fed by numerical weather forecasts of the European Centre for Medium Range Weather Forecast (ECMWF) Integrated Forecasting System (IFS) and Ensemble Prediction System (EPS). The proposed methodology is compared with the forecasts obtained with Quantile Regression using only IFS forecasts (QR), with the uncalibrated EPS forecasts and with the EPS forecasts calibrated with a Variance Deficit (VD) procedure. The proposed methodology produces forecasts with a temporal resolution equal to or better than the meteorological forecast (1 h for the IFS and 3 h for EPS) and, in the case examined, is able to provide higher performances than those obtained with the other methods over a forecast horizon of up to 72 h.

Highlights

The inclusion of renewable generation in distribution grids poses technological challenges that need to be addressed to achieve technically and economically sustainable integration
The forecast procedure was tested on a medium-sized PV plant located on the German island of Borkum, oriented south, with a tilt angle of 38 deg and an approximate peak power of 1.3 MW
We have proposed a new methodology for the short-term probabilistic forecasting of solar power, based on the technique of quantile regression and on the post-processing of an ensemble of forecasts

Summary

Introduction

The inclusion of renewable generation in distribution grids poses technological challenges that need to be addressed to achieve technically and economically sustainable integration. One of the difficulties is linked to the variability of the solar source, which does not guarantee a flexible production, but depends on the weather conditions and may be subject to strong variations in the short term in relation to cloud cover. This is one of the reasons why the current regulations governing the electricity market in various regions favor the definition of a production profile one day in advance [1,2,3]. The project aims to propose an effective innovation in the use and distribution of electric power through the development of several energy storage technologies and an energy management system, enabling the implementation of a smart grid on the German island of Borkum in the North Sea

Methods

Discussion

Conclusion