A comparison of univariate methods for forecasting electricity demand up to a day ahead
By James W. Taylor, L. D. Menezes, Patrick E. McSharry. 2006
545 citations recorded by the source corpus.
Subfields: Electrical and Electronic Engineering, Management Science and Operations Research
View Paper: https://www.semanticscholar.org/paper/574b3aae951f3b9438c27756b893bb06d081880e
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Electrical and Electronic Engineering
- Rob J Hyndman
- James W. Taylor
- Ralph D. Snyder
- Alysha M. De Livera
- Kafait Ullah
- M. Imran
- Mohammed A. Alghassab
- Aneeque A. Mir
In Management Science and Operations Research
- James W. Taylor
- Rob J Hyndman
- Alysha M. De Livera
- Ralph D. Snyder
- Eran Raviv
- Kafait Ullah
- M. Imran
- Zafar Ali Khan
Citations in the corpus
- Electric load forecasting methods: Tools for decision making (2009, methodology): “tial smoothing for double seasonality, artificial neural network, and a regression method with principal component analysis (PCA) (Taylor et al., 2006).”
- Forecasting Day-Ahead Electricity Prices: Utilizing Hourly Prices (2013, methodology): “The MAPE evaluates the forecast error relative to the actual price level, and is traditionally used to measure accuracy in electricity load forecasting (Taylor et al., 2006).”
- A Review of Electricity Demand Forecasting in Low and Middle Income Countries: The Demand Determinants and Horizons (2020, background): “For short term load forecasting, for example, multiplicative seasonal ARIMA models have been widely popular for years among forecasters [69].”
- Forecasting Time Series With Complex Seasonal Patterns Using Exponential Smoothing (2011, methodology): “In an analysis of electricity demand data, Taylor (2003b) illustrated that the inclusion of both seasonal components in the model is beneficial relative to including just one of the seasonal components.”
- Forecasting intraday time series with multiple seasonal cycles using parsimonious seasonal exponential smoothing (2009, background): “Keywords: Forecasting; Time Series; Exponential smoothing; Electricity load; Call centre arrivals”
- Modeling and forecasting short-term electricity load: A comparison of methods with an application to Brazilian data (2008, background): “Many other recent papers in the literature have adopted the same strategy and do not include temperatures; see, for example, Carpinteiro, Reis, and Silva (2004), Taylor et al. (2006) and Soares and Souza (2006).”