Electric load forecasting methods: Tools for decision making

By Heiko Hahn, Silja Meyer-Nieberg, Stefan Wolfgang Pickl. European Journal of Operational Research, 2009

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Forecasting: theory and practice (2020, background): “Due to the importance of STLF, a vast number of researchers have proposed algorithms of different complexity and structure during the last years (Hahn et al., 2009).”
Wind Energy: Forecasting Challenges for Its Operational Management (2013, background): “Auto-Regressive (MSAR) models, also popular in econometrics since the work of Hamilton, J.D. (1989), assumes that the regime sequence relies on an unobservable process.”
A Strategy for Short-Term Load Forecasting by Support Vector Regression Machines (2013, background): “The overviews of the load forecasting methods can be found in [2], [3], and [10].”
Short term electricity demand forecasting using partially linear additive quantile regression with an application to the unit commitment problem (2018, methodology): “Short term forecasts are used to estimate the load demand up to a week ahead of a schedule [16].”