Very-short term solar power generation forecasting based on trend-additive and seasonal-multiplicative smoothing methodology

Ural Federal University named after the first President of Russia B.N. Yeltsin, Ekaterinburg, 620002 Mira str. 19, Russia

^* Corresponding author: lkhalyasmaa@mail.ru

Abstract

In conditions of development of generating facilities on renewable energy sources, the technology runs up to uncertainty in the operational and short-term planning of the power system operating modes. To date, reliable tools for forecasting the generation of solar power stations are required. This paper considers the methodology of operational forecasting of solar power stations output based on the mathematical apparatus of cubic exponential smoothing with trend and seasonal components. The presented methodology was tested based on the measuring data of a real solar power station. The average forecast error was not more than 10% for days with variable clouds and not more than 3% for clear days, which indicates the effectiveness of the proposed approach.