Using deep learning and meteorological parameters to forecast the photovoltaic generators intra-hour output power interval for smart grid control

Abstract:

In recent years, the photovoltaic generation installed capacity has been steadily growing thanks to its inexhaustible and non-polluting characteristics. However, solar generators are strongly dependent on intermittent weather parameters, increasing power systems' uncertainty level. Forecasting models have arisen as a feasible solution to decreasing photovoltaic generators' uncertainty level, as they can produce accurate pbkp_redictions. Traditionally, the vast majority of research studies have focused on the development of accurate pbkp_rediction point forecasters. However, in recent years some researchers have suggested the concept of pbkp_rediction interval forecasting, where not only an accurate pbkp_rediction point but also the confidence level of a given pbkp_rediction are computed to provide further information. This paper develops a new model for pbkp_redicting photovoltaic generators' output power confidence interval 10 min …

Año de publicación:

2022

Keywords:

Fuente:

google