000032750 001__ 32750
000032750 005__ 20210121114448.0
000032750 0247_ $$2doi$$a10.3390/en80910464
000032750 0248_ $$2sideral$$a92884
000032750 037__ $$aART-2015-92884
000032750 041__ $$aeng
000032750 100__ $$aMonteiro, C.
000032750 245__ $$aExplanatory information analysis for day-ahead price forecasting in the Iberian electricity market
000032750 260__ $$c2015
000032750 5060_ $$aAccess copy available to the general public$$fUnrestricted
000032750 5203_ $$aThis paper presents the analysis of the importance of a set of explanatory (input) variables for the day-ahead price forecast in the Iberian Electricity Market (MIBEL). The available input variables include extensive hourly time series records of weather forecasts, previous prices, and regional aggregation of power generations and power demands. The paper presents the comparisons of the forecasting results achieved with a model which includes all these available input variables (EMPF model) with respect to those obtained by other forecasting models containing a reduced set of input variables. These comparisons identify the most important variables for forecasting purposes. In addition, a novel Reference Explanatory Model for Price Estimations (REMPE) that achieves hourly price estimations by using actual power generations and power demands of such day is described in the paper, which offers the lowest limit for the forecasting error of the EMPF model. All the models have been implemented using the same technique (artificial neural networks) and have been satisfactorily applied to the real-world case study of the Iberian Electricity Market (MIBEL). The relative importance of each explanatory variable is identified for the day-ahead price forecasts in the MIBEL. The comparisons also allow outlining guidelines of the value of the different types of input information.
000032750 536__ $$9info:eu-repo/grantAgreement/ES/MINECO/ENE2013-48517-C2-1-R$$9info:eu-repo/grantAgreement/ES/MINECO/ENE2013-48517-C2-2-R
000032750 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/
000032750 590__ $$a2.077$$b2015
000032750 591__ $$aENERGY & FUELS$$b43 / 88 = 0.489$$c2015$$dQ2$$eT2
000032750 592__ $$a0.785$$b2015
000032750 593__ $$aEnergy (miscellaneous)$$c2015$$dQ1
000032750 593__ $$aEnergy Engineering and Power Technology$$c2015$$dQ1
000032750 593__ $$aElectrical and Electronic Engineering$$c2015$$dQ1
000032750 593__ $$aRenewable Energy, Sustainability and the Environment$$c2015$$dQ2
000032750 593__ $$aControl and Optimization$$c2015$$dQ2
000032750 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000032750 700__ $$aFernandez-Jimenez, L.
000032750 700__ $$0(orcid)0000-0002-5502-4232$$aRamirez-Rosado, I.$$uUniversidad de Zaragoza
000032750 7102_ $$15009$$2535$$aUniversidad de Zaragoza$$bDpto. Ingeniería Eléctrica$$cÁrea Ingeniería Eléctrica
000032750 773__ $$g8, 9 (2015), 10464-10486$$pENERGIES$$tEnergies$$x1996-1073
000032750 8564_ $$s505646$$uhttps://zaguan.unizar.es/record/32750/files/texto_completo.pdf$$yVersión publicada
000032750 8564_ $$s91203$$uhttps://zaguan.unizar.es/record/32750/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000032750 909CO $$ooai:zaguan.unizar.es:32750$$particulos$$pdriver
000032750 951__ $$a2021-01-21-10:44:21
000032750 980__ $$aARTICLE