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dc.contributor.authorRodríguez-Gómez, Francisco
dc.contributor.authorDel-Campo-Avila, Jose 
dc.contributor.authorFerrer Cuesta, Marta
dc.contributor.authorMora-López, Llanos
dc.date.accessioned2022-06-27T10:44:07Z
dc.date.available2022-06-27T10:44:07Z
dc.date.issued2022-10-01
dc.identifier.citationFrancisco Rodríguez-Gómez, José del Campo-Ávila, Marta Ferrer-Cuesta, Llanos Mora-López, Data driven tools to assess the location of photovoltaic facilities in urban areas, Expert Systems with Applications, Volume 203, 2022, 117349, ISSN 0957-4174, https://doi.org/10.1016/j.eswa.2022.117349.es_ES
dc.identifier.urihttps://hdl.handle.net/10630/24498
dc.description.abstractUrban sustainability is a significant factor in combating climate change. Replacing polluting by renewable energies is fundamental to reduce the emission of greenhouse gases. Photovoltaic (PV) facilities harnessing solar energy, and particularly self-consumption PV facilities, can be widely used in cities throughout most countries. Therefore, locating spaces where photovoltaic installations can be integrated into urban areas is essential to reduce climate change and improve urban sustainability. An open-source software (URSUS-PV) to aid decision-making regarding possible optimal locations for photovoltaic panel installations in cities is presented in this paper. URSUS-PV is the result of a data mining process, and it can extract the characteristics of the roofs (orientation, inclination, latitude, longitude, area) in the urban areas of interest. By combining this information with meteorological data and characteristics of the photovoltaic systems, the system can predict both the next-day hourly photovoltaic energy production and the long-term photovoltaic daily average energy production.es_ES
dc.description.sponsorshipThis work has been supported by the project RTI2018-095097-B-I00 at the 2018 call for I+D+i Project of the Ministerio de Ciencia, Innovación y Universidades, Spain. Funding for open access charge: Universidad de Málaga/CBUA, Spain .es_ES
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectRecursos energéticos renovableses_ES
dc.subject.otherRenewable energyes_ES
dc.subject.otherPhotovoltaic systemses_ES
dc.subject.otherLiDAR images Semantic segmentationes_ES
dc.subject.otherRoof feature extractiones_ES
dc.subject.otherEnergy forecases_ES
dc.titleData driven tools to assess the location of photovoltaic facilities in urban areases_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.centroE.T.S.I. Informáticaes_ES
dc.identifier.doihttps://doi.org/10.1016/j.eswa.2022.117349
dc.rights.ccAtribución 4.0 Internacional*
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersiones_ES


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