Εμφάνιση απλής εγγραφής

dc.creatorPanapakidis I., Gousis G., Koltsaklis N., Dagoumas A.en
dc.date.accessioned2023-01-31T09:41:36Z
dc.date.available2023-01-31T09:41:36Z
dc.date.issued2021
dc.identifier10.1109/EEEIC/ICPSEurope51590.2021.9584682
dc.identifier.isbn9781665436120
dc.identifier.urihttp://hdl.handle.net/11615/77473
dc.description.abstractRenewable Energy Sources (RES) generation forecasting is an approach to handle the stochasticity of RES. This concept is very crucial to transform RES plants into dispatchable and integrated them for contemporary energy markets. The majority of the literature focuses on individual plants. The data are collected in a site and used as inputs in the forecasting model. The present paper is centered on aggregated energy system level. The total capacities of Photovoltaics (PV) and Wind Turbine (WT) power of a country are regarded. A scenarios-based approach is followed in order to investigate how the number and types of inputs influence the forecasting performance. While most studies of the literature focus on individual systems, the paper contributes on the RES forecasting literature through the consideration of the total PV and WT generation capacity on aggregated power system level. © 2021 IEEEen
dc.language.isoenen
dc.source21st IEEE International Conference on Environment and Electrical Engineering and 2021 5th IEEE Industrial and Commercial Power System Europe, EEEIC / I and CPS Europe 2021 - Proceedingsen
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85126439436&doi=10.1109%2fEEEIC%2fICPSEurope51590.2021.9584682&partnerID=40&md5=dc6c200de0d45e11b739ae12e7e1e9d4
dc.subjectDeep neural networksen
dc.subjectNatural resourcesen
dc.subjectRenewable energy resourcesen
dc.subjectSolar cellsen
dc.subjectTurbogeneratorsen
dc.subjectWind turbinesen
dc.subjectDeep learningen
dc.subjectNeural-networksen
dc.subjectPhotovoltaic generation forecastingen
dc.subjectPhotovoltaics generationsen
dc.subjectPoweren
dc.subjectPower systemen
dc.subjectRenewable energy sourceen
dc.subjectSystem levelsen
dc.subjectWind turbine generation forecastingen
dc.subjectWind-turbine generationen
dc.subjectForecastingen
dc.subjectInstitute of Electrical and Electronics Engineers Inc.en
dc.titleRenewable energy sources generation forecasting in aggregated energy system levelen
dc.typeconferenceItemen


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