Volatility in Electrical Load Forecasting for Long-term Horizon
An ARIMA-GARCH Approach
Swasti Khuntia (TU Delft - Electrical Engineering, Mathematics and Computer Science)
J.L. Rueda (TU Delft - Electrical Engineering, Mathematics and Computer Science)
Mart van der Meijden (TenneT TSO B.V., TU Delft - Electrical Engineering, Mathematics and Computer Science)
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Abstract
Electrical load forecasting in long-term horizon of power systems plays an important role for system planning and development. Load forecast in long-term horizon is represented as time-series. Thus, it is important to check the effect of volatility in the forecasted load time-series. In short, volatility in long-term horizon affects four main actions: risk management, long-term actions, reliability, and bets on future volatility. To check the effect of volatility in load series, this paper presents a univariate time series-based load forecasting technique for long-term horizon based on data corresponding to a U.S. independent system operator. The study employs ARIMA technique to forecast electrical load, and also the analyzes the ARCH and GARCH effects on the residual time-series.