%0 Conference Paper %1 Pierrot2011ShortTerm %A Pierrot, Amandine %A Goude, Yannig %B 16th Intelligent System Applications to Power Systems Conference, ISAP 2011 %D 2011 %J Proceedings of ISAP2011 %K demand statistics nwp electricitynetworks %P 410--415 %T Short-Term Electricity Load Forecasting With Generalized Additive Models %X Because of the French electricity market deregulation, Electricité de France has to experiment new load forecasting models, more adaptive than the operational ones. A statistical framework like Generalized Additive Models allows us to integrate both a regressive part with explanatory variables and an autoregressive part with lagged loads. The French electricity demand being strongly related to the current instant, we consider twenty-four daily time-series and fit one model for each hour. The selected variables are one-day-lagged loads, weather and calendar variables, and a global trend. Thanks to a cyclic spline fitted on the position of the current day during the year, we can model the summer break (a large decrease in the demand due to summer holiday). We compute the Root Mean Square Errors over one post-sample year to assess its accuracy for one-day ahead forecast. Our model, which is fitted over five years, can compete with the operational one. %@ 978-1-4577-0807-7

@inproceedings{Pierrot2011ShortTerm, abstract = {Because of the French electricity market deregulation, Electricit\'{e} de France has to experiment new load forecasting models, more adaptive than the operational ones. A statistical framework like Generalized Additive Models allows us to integrate both a regressive part with explanatory variables and an autoregressive part with lagged loads. The French electricity demand being strongly related to the current instant, we consider twenty-four daily time-series and fit one model for each hour. The selected variables are one-day-lagged loads, weather and calendar variables, and a global trend. Thanks to a cyclic spline fitted on the position of the current day during the year, we can model the summer break (a large decrease in the demand due to summer holiday). We compute the Root Mean Square Errors over one post-sample year to assess its accuracy for one-day ahead forecast. Our model, which is fitted over five years, can compete with the operational one.}, added-at = {2018-06-18T21:23:34.000+0200}, author = {Pierrot, Amandine and Goude, Yannig}, biburl = {https://www.bibsonomy.org/bibtex/2e3bbd8b572932af32f09ea6296cd143c/pbett}, booktitle = {16th Intelligent System Applications to Power Systems Conference, ISAP 2011}, citeulike-article-id = {14033057}, citeulike-attachment-1 = {Pierrot_Goude_2011_Demand_GAM.pdf; /pdf/user/pbett/article/14033057/1068497/Pierrot_Goude_2011_Demand_GAM.pdf; 4426a410548e88a6e5606f3fa5484a2d86255805}, comment = {(private-note)Can't find in the official proceedings. It is mentioned in the TOC http://www.proceedings.com/13174.html but doesn't seem to be in the actual proceedings place http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=6069629}, file = {Pierrot_Goude_2011_Demand_GAM.pdf}, interhash = {e2690dd67fb98f391c4823f75c367c95}, intrahash = {e3bbd8b572932af32f09ea6296cd143c}, isbn = {978-1-4577-0807-7}, journal = {Proceedings of ISAP2011}, keywords = {demand statistics nwp electricitynetworks}, location = {Hersonissos, Greece}, month = sep, organization = {IEEE}, pages = {410--415}, posted-at = {2016-05-11 10:21:21}, priority = {2}, timestamp = {2018-06-22T18:36:26.000+0200}, title = {Short-Term Electricity Load Forecasting With Generalized Additive Models}, year = 2011 }