Forecasting Models for Hydropower Production Using ARIMA Method

Rising demand for energy consumption indicates that adequate energy supplies are essential for economic growth and social development. Nowadays, as fossil fuel is running out and discharging a huge amount of carbon emission, energy transformation to renewables is a must. However, developing and operating clean power plants are a momentous challenge as it is difficult to manage sustainable and long-lasting energy resources. A forecasting model is, therefore, a promising tool to predict the generation, consumption, and reservation of energy.In this paper, a long-term forecasting model for hydropower production using the autoregressive integrated moving average (ARIMA) time series method is proposed. The collected data was obtained from the Son La hydropower plant in Vietnam. The electricity generation in this plant demonstrates an upward trend in the future. Although the power capacity of the hydropower plant is significantly affected by environmental variability, having a forecasting model and a long-term plan will greatly benefit renewable energy production to keep up with economic growth. In addition, the simulation results can be used as a reference for further studies and strategic energy planning.