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dc.creatorWang, Guang Chaoes_ES
dc.creatorKurtz, Benes_ES
dc.creatorBosch, Juan Luises_ES
dc.creatorParra Laita, Íñigo de laes_ES
dc.creatorKleissl, Janes_ES
dc.date.accessioned2021-03-18T09:23:53Z
dc.date.available2021-09-25T23:00:09Z
dc.date.issued2020
dc.identifier.issn1941-7012 (Electronic)
dc.identifier.urihttps://hdl.handle.net/2454/39419
dc.description.abstractLarge ramps and ramp rates in photovoltaic (PV) power output are of concern and sometimes even explicitly restricted by grid operators. Battery energy storage systems can smooth the power output and maintain ramp rates within permissible limits. To enable PV plant and energy storage system design and planning, a method to estimate the largest expected ramps for a given location is proposed. Because clouds are the dominant source of PV power output variability, an analytical relationship between the worst expected ramp rate, cloud motion vector, and the geometrical layout of the PV plant is developed. The ability of the proposed method to bracket actual ramp rates is assessed over 10 months under different meteorological conditions, demonstrating an average compliance rate of 98.9% for a 2 min evaluation time window. The largest observed ramp of 29.7% s(-1)is contained with the worst case estimate of 34.3% s(-1). This method provides a convenient yet economical approach to worst-case PV ramp rate modeling and is compatible with solar irradiance measured at coarse temporal resolution.en
dc.description.sponsorshipJuan Bosch was financed in part by Project No. PID2019-108953RB-C21, funded by the Ministerio de Ciencia e Innovación and co-financed by the European Regional Development Fund. In addition, Iñigo de la Parra was partially supported by the Spanish State Research Agency (AEI) and FEDER-UE under Grant Nos. DPI2016-80641-R and DPI2016-80642-R.en
dc.format.extent16 p.
dc.format.mimetypeapplication/pdfen
dc.language.isoengen
dc.publisherAmerican Institute of Physicsen
dc.relation.ispartofJournal of Renewable and Sustainable Energy, 2020, 12, 056302en
dc.rights© 2020 Author(s).en
dc.subjectSensorsen
dc.subjectSolar irradianceen
dc.subjectSolar power plantsen
dc.titleMaximum expected ramp rates using cloud speed sensor measurementsen
dc.typeinfo:eu-repo/semantics/articleen
dc.typeArtículo / Artikuluaes
dc.contributor.departmentUniversidad Pública de Navarra. Departamento de Ingeniería Eléctrica, Electrónica y de Comunicaciónes_ES
dc.contributor.departmentNafarroako Unibertsitate Publikoa. Ingeniaritza Elektriko, Elektroniko eta Telekomunikazio Sailaeu
dc.contributor.departmentUniversidad Pública de Navarra / Nafarroako Unibertsitate Publikoa. ISC - Institute of Smart Citieses_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessen
dc.rights.accessRightsAcceso abierto / Sarbide irekiaes
dc.embargo.terms2021-09-25
dc.identifier.doi10.1063/5.0021875
dc.relation.projectIDinfo:eu-repo/grantAgreement/ES/1PE/DPI2016-80641-Ren
dc.relation.projectIDinfo:eu-repo/grantAgreement/ES/1PE/DPI2016-80642-Ren
dc.relation.publisherversionhttps://doi.org/10.1063/5.0021875
dc.type.versioninfo:eu-repo/semantics/publishedVersionen
dc.type.versionVersión publicada / Argitaratu den bertsioaes


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