Forecasting of solar power generation in Vietnam deploying a simple GRU model

Solar energy is a renewable energy source that is widely used in the world. It is characterized by its instability and susceptibility to weather changes. Forecasting the power output of solar energy sources is crucial to help grid operators manage the power system according to supply and demand. Nowadays, Artificial Neural Network (ANN) models simplify and improve the accuracy of power forecasting by utilizing historical data. In short-term solar power forecasting, the Gate Recurrent Unit (GRU) model is simple, reliable, and highly accurate. This paper uses a simple GRU model for forecasting solar power output based on a two-year historical dataset collected from a solar power plant in the central region of Vietnam.