Triple seasonal methods for short-term electricity demand forecasting

By James W. Taylor. European Journal of Operational Research, 2010

413 citations recorded by the source corpus.

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Short-Term Forecasting of Anomalous Load Using Rule-Based Triple Seasonal Methods (2013, methodology): “In [17], the following triple seasonal ARMA model has been proposed for modeling load on normal days”
An empirical comparison of alternate schemes for combining electricity spot price forecasts (2013, positive): “To our best knowledge, existing applications so far only include the work by Løland et al. (2012), Smith (1989), Taylor (2010) and Taylor and Majithia (2000) in the context of load and transmission congestion forecasting, and by Bordignon et al. (2013) and Raviv et al. (2013) in the context of spot…”
Application of residual modification approach in seasonal ARIMA for electricity demand forecasting: A case study of China (2012, methodology): “Taylor (2010) introduced the application of the triple seasonal methods in short-time electricity demand forecasting.”
Electricity price forecasting: A review of the state-of-the-art with a look into the future (2014, background): “Another relatively simple benchmark, which is very popular in load forecasting (see e.g. Taylor, 2010) but less popular in EPF, is exponential smoothing.”
Forecasting Time Series With Complex Seasonal Patterns Using Exponential Smoothing (2011, methodology): “To avoid the potentially large optimization problem, the initial states are usually approximated with various heuristics (Taylor 2003, 2010b; Gould et al. 2008), a practice that does not lead to optimized seed states.”