An evaluation of methods for very short-term load forecasting using minute-by-minute British data

By James W. Taylor. 2008

257 citations recorded by the source corpus.

Subfields: Electrical and Electronic Engineering, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/d1c96b4eee21f1567d7aac2a6c9bf33e9a56fd98

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In Electrical and Electronic Engineering

In Management Science and Operations Research

Citations in the corpus

Using Smart Meter Data to Improve the Accuracy of Intraday Load Forecasting Considering Customer Behavior Similarities (2015, methodology): “For instance, Taylor [3] presented and compared several univariate methods including a comparison with an additional approach based on weather forecasts.”
Short-Term Load Forecasting With Exponentially Weighted Methods (2012, methodology): “Similar findings are reported in [8] for minute-by-minute data.”
Forecasting Time Series With Complex Seasonal Patterns Using Exponential Smoothing (2011, methodology): “The double seasonal Holt-Winters’ additive seasonal model 142 described by Taylor (2003) is given by BATS(1,1,0,0,m1,m2), and that with the residual 143 AR(1) adjustment in the model of Taylor (2003, 2008) is given by BATS(1,1,1,0,m1,m2). 144 The Holt-Winters’ additive triple seasonal model with AR(”
Beyond point forecasting: evaluation of alternative prediction intervals for tourist arrivals (2011, methodology): “3 For forecasting high frequency data (e.g., minute-by-minute), Taylor (2008) proposes a Holt-Winters’ exponential smoothing method with a double seasonal component, where prediction intervals could be constructed in the framework of the innovations state space models of Hyndman et al. (2008).”
Functional time series approach for forecasting very short-term electricity demand (2013, methodology): “[27], Taylor [40], and Trudnowski et al.”
A Review of Electricity Demand Forecasting in Low and Middle Income Countries: The Demand Determinants and Horizons (2020, methodology): “In [88], a double seasonal adaptation of the Holt–Winters’ exponential smoothing method, once again, is suggested as the method outperforming other techniques.”
Modeling and forecasting short-term electricity load: A comparison of methods with an application to Brazilian data (2008, unknown): “…issue; Dordonnat, Koopman, Ooms, Dessertaine, & Collet, 2008-this issue; Huang, 2003; Huang, Huang, & Wang, 2005; Nowicka-Zagrajek & Weron, 2002; Taylor, 2008-this issue; Taylor, de Menezes, & McSharry, 2006; and Weron, 2006), and in the machine intelligence framework (da Silva, Ferreira, &…”
Triple seasonal methods for short-term electricity demand forecasting (2010, methodology): “…in the exponential smoothing method of Gould et al. Research in this area would seem to be timely, given the increasing availability of intraday data in a variety of other applications, such as traffic management and call centre staff scheduling (see, for example, Lam et al., 2006; Taylor, 2008).”