Print Email Facebook Twitter Volatility in Electrical Load Forecasting for Long-term Horizon Title Volatility in Electrical Load Forecasting for Long-term Horizon: An ARIMA-GARCH Approach Author Khuntia, S.R. (TU Delft Intelligent Electrical Power Grids) Rueda, José L. (TU Delft Intelligent Electrical Power Grids) van der Meijden, M.A.M.M. (TU Delft Intelligent Electrical Power Grids; TenneT TSO B.V.) Date 2016 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. Subject ARIMAARCHGARCHlong-term load forecastvolatility To reference this document use: http://resolver.tudelft.nl/uuid:21dd52e4-5862-459e-8a08-4ef25489da76 DOI https://doi.org/10.1109/PMAPS.2016.7764184 Publisher IEEE, Piscataway, NJ ISBN 978-1-5090-1970-0 Source 2016 International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2016 Event PMAPS 2016, 2016-10-16 → 2016-10-20, Beijing, China Part of collection Institutional Repository Document type conference paper Rights © 2016 S.R. Khuntia, José L. Rueda, M.A.M.M. van der Meijden Files PDF 11311693.pdf 686.37 KB Close viewer /islandora/object/uuid:21dd52e4-5862-459e-8a08-4ef25489da76/datastream/OBJ/view