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Discussion on ‘Electrical load forecasting by exponential smoothing with covariates’by Rainer Göb, Kristina Lurz and Antonio Pievatolo

Discussion on ‘Electrical load forecasting by exponential smoothing with covariates’by Rainer... First, I would like to congratulate the authors on the idea and topic developed in this article. Accurately predicting electrical load is of vital importance for both power producers and electricity system operators (SOs). If the power producer makes an offer for the next day that he cannot generate, he receives a penalty from the SO and worse, the lack of electricity problem is typically solved by buying it from a foreign electricity market. In this article, the authors wisely used the hourly average temperature as a covariate. My experience with this kind of problem is that one of the weather variables that influence electricity demand in the Iberian Peninsula is the number of days the temperature falls below 0˚C . However, this temperature threshold, used in our work, is contradictory to that given by these authors. They take 15˚C as the threshold temperature and concretely state ‘15˚C is the threshold, below which the electricity consumption is deemed unaffected by the temperature’ (in Section 7 of the Manuscript). The choice made by the authors to establish this temperature as the threshold surprises me. In Spain, cold temperatures increase electricity consumption. A possible explanation for these contradictory thresholds is http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Applied Stochastic Models in Business and Industry Wiley

Discussion on ‘Electrical load forecasting by exponential smoothing with covariates’by Rainer Göb, Kristina Lurz and Antonio Pievatolo

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References (4)

Publisher
Wiley
Copyright
Copyright © 2013 John Wiley & Sons, Ltd.
ISSN
1524-1904
eISSN
1526-4025
DOI
10.1002/asmb.1999
Publisher site
See Article on Publisher Site

Abstract

First, I would like to congratulate the authors on the idea and topic developed in this article. Accurately predicting electrical load is of vital importance for both power producers and electricity system operators (SOs). If the power producer makes an offer for the next day that he cannot generate, he receives a penalty from the SO and worse, the lack of electricity problem is typically solved by buying it from a foreign electricity market. In this article, the authors wisely used the hourly average temperature as a covariate. My experience with this kind of problem is that one of the weather variables that influence electricity demand in the Iberian Peninsula is the number of days the temperature falls below 0˚C . However, this temperature threshold, used in our work, is contradictory to that given by these authors. They take 15˚C as the threshold temperature and concretely state ‘15˚C is the threshold, below which the electricity consumption is deemed unaffected by the temperature’ (in Section 7 of the Manuscript). The choice made by the authors to establish this temperature as the threshold surprises me. In Spain, cold temperatures increase electricity consumption. A possible explanation for these contradictory thresholds is

Journal

Applied Stochastic Models in Business and IndustryWiley

Published: Nov 1, 2013

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