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Long-Term Electricity Load Forecasting Considering Volatility Using Multiplicative Error Model

Swasti R. Khuntia (), Jose L. Rueda () and Mart A.M.M. Van der Meijden ()
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Swasti R. Khuntia: Department of Electrical Sustainable Energy, Delft University of Technology, 2600 GA Delft, The Netherlands
Jose L. Rueda: Department of Electrical Sustainable Energy, Delft University of Technology, 2600 GA Delft, The Netherlands
Mart A.M.M. Van der Meijden: Department of Electrical Sustainable Energy, Delft University of Technology, 2600 GA Delft, The Netherlands

Energies, 2018, vol. 11, issue 12, 1-19

Abstract: Long-term electricity load forecasting plays a vital role for utilities and planners in terms of grid development and expansion planning. An overestimate of long-term electricity load will result in substantial wasted investment on the construction of excess power facilities, while an underestimate of the future load will result in insufficient generation and inadequate demand. As a first of its kind, this research proposes the use of a multiplicative error model (MEM) in forecasting electricity load for the long-term horizon. MEM originates from the structure of autoregressive conditional heteroscedasticity (ARCH) model where conditional variance is dynamically parameterized and it multiplicatively interacts with an innovation term of time-series. Historical load data, as accessed from a United States (U.S.) regional transmission operator, and recession data, accessed from the National Bureau of Economic Research, are used in this study. The superiority of considering volatility is proven by out-of-sample forecast results as well as directional accuracy during the great economic recession of 2008. Historical volatility is used to account for implied volatility. To incorporate future volatility, backtesting of MEM is performed. Two performance indicators used to assess the proposed model are: (i) loss functions in terms of mean absolute percentage error and mean squared error (for both in-sample model fit and out-of-sample forecasts) and (ii) directional accuracy.

Keywords: load forecast; long-term horizon; multiplicative error model; time-series forecasting; volatility (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
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