Weather Forecasting Error in Solar Energy Forecasting

TL;DR

This paper investigates the impact of weather forecast errors on solar energy prediction accuracy, analyzing the uncertainty in weather variables and their influence on PV energy forecasting models.

Contribution

It provides a detailed analysis of weather forecast uncertainties and identifies key weather variables affecting solar energy prediction accuracy.

Findings

Weather forecast errors vary significantly over six days.

Certain weather variables have a greater impact on energy forecasting accuracy.

Improving forecast accuracy of influential variables enhances PV energy predictions.

Abstract

As renewable distributed energy resources (DERs) penetrate the power grid at an accelerating speed, it is essential for operators to have accurate solar photovoltaic (PV) energy forecasting for efficient operations and planning. Generally, observed weather data are applied in the solar PV generation forecasting model while in practice the energy forecasting is based on forecasted weather data. In this paper, a study on the uncertainty in weather forecasting for the most commonly used weather variables is presented. The forecasted weather data for six days ahead is compared with the observed data and the results of analysis are quantified by statistical metrics. In addition, the most influential weather predictors in energy forecasting model are selected. The performance of historical and observed weather data errors is assessed using a solar PV generation forecasting model. Finally, a sensitivity test is performed to identify the influential weather variables whose accurate values can significantly improve the results of energy forecasting.