dc.contributor.author | Pasarín, O. | |
dc.contributor.author | García Fernández, Pablo | |
dc.contributor.author | González, L. | |
dc.contributor.author | Villa, G. | |
dc.date.accessioned | 2024-07-11T07:34:08Z | |
dc.date.available | 2024-07-11T07:34:08Z | |
dc.date.issued | 2023 | |
dc.identifier.isbn | 979-835031644-5 | |
dc.identifier.uri | https://hdl.handle.net/10651/73682 | |
dc.description.sponsorship | This work was supported in part by the Spanish Ministry of Innovation and Science under Grant MCINN-22-TED2021-129796B-C21 and by the Principality of Asturias, FICYT, FEDER funds under Grant SV-PA-21-AYUD/2021/57546. | |
dc.format.extent | p. 1472-1479 | |
dc.language.iso | eng | |
dc.relation.ispartof | 2023 IEEE Energy Conversion Congress and Exposition, ECCE 2023 | |
dc.rights | ©, | |
dc.source | Scopus | |
dc.source.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85182917125&doi=10.1109%2fECCE53617.2023.10362169&partnerID=40&md5=bcf4f69579c5fc3684694d7dd2bb7f55 | |
dc.title | Multi-step machine learning forecasting of power consumption and pv generation for distributed energy management applications | |
dc.type | conference output | |
dc.identifier.doi | 10.1109/ECCE53617.2023.10362169 | |
dc.relation.publisherversion | http://dx.doi.org/10.1109/ECCE53617.2023.10362169 | |