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Open AccessArticle

Stability of Multiple Seasonal Holt-Winters Models Applied to Hourly Electricity Demand in Spain

Department of Applied Statistics, Operational Research and Quality, Universitat Politècnica de València, 46022 Valencia, Spain
Division of Computer Science, Universidad Pablo de Olavide, ES-41013 Seville, Spain
Author to whom correspondence should be addressed.
Appl. Sci. 2020, 10(7), 2630;
Received: 21 February 2020 / Revised: 1 April 2020 / Accepted: 6 April 2020 / Published: 10 April 2020
Electricity management and production depend heavily on demand forecasts made. Any mismatch between the energy demanded with respect to that produced supposes enormous losses for the consumer. Transmission System Operators use time series-based tools to forecast accurately the future demand and set the production program. One of the most effective and highly used methods are Holt-Winters. Recently, the incorporation of the multiple seasonal Holt-Winters methods has improved the accuracy of the predictions. These forecasts, depend greatly on the parameters with which the model is constructed. The forecasters need to deal with these parameters values when operating the model. In this article, the parameters space of the multiple seasonal Holt-Winters models applied to electricity demand in Spain is analysed and discussed. The parameters stability analysis leads to forecasters better understanding the behaviour of the predictions and managing their exploitation efficiently. The analysis addresses different time windows, depending on the period of the year as well as different training set sizes. The results show the influence of the calendar effect on these parameters and if it is necessary or not to update them in order to obtain a good accuracy over time. View Full-Text
Keywords: time series; forecasting; exponential smoothing; electricity demand time series; forecasting; exponential smoothing; electricity demand
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Trull, Ó.; García-Díaz, J.C.; Troncoso, A. Stability of Multiple Seasonal Holt-Winters Models Applied to Hourly Electricity Demand in Spain. Appl. Sci. 2020, 10, 2630.

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