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dc.contributor.authorAlamin, Yaser Imad
dc.contributor.authorAnaty, Mensah K.
dc.contributor.authorÁlvarez Hervás, José Domingo 
dc.contributor.authorBouziane, Khalid
dc.contributor.authorPérez García, Manuel 
dc.contributor.authorYaagoubi, Reda
dc.contributor.authorCastilla, María del Mar
dc.contributor.authorBelkasmi, Merouan
dc.contributor.authorAggour, Mohammed
dc.date.accessioned2020-07-21T07:01:38Z
dc.date.available2020-07-21T07:01:38Z
dc.date.issued2020-07-06
dc.identifier.issn1996-1073
dc.identifier.urihttp://hdl.handle.net/10835/8351
dc.description.abstractConcentrator photovoltaic (CPV) is used to obtain cheaper and more stable renewable energy. Methods which predict the energy production of a power system under specific circumstances are highly important to reach the goal of using this system as a part of a bigger one or of making it integrated with the grid. In this paper, the development of a model to predict the energy of a High CPV (HCPV) system using an Artificial Neural Network (ANN) is described. This system is located at the University of Rabat. The performed experiments show a quick prediction with encouraging results for a very short-term prediction horizon, considering the small amount of data available. These conclusions are based on the processes of obtaining the ANN models and detailed discussion of the results, which have been validated using real dataes_ES
dc.language.isoenes_ES
dc.publisherMDPIes_ES
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectHCPVes_ES
dc.subjectpower predictiones_ES
dc.subjectRBFes_ES
dc.subjectANNes_ES
dc.titleVery Short-Term Power Forecasting of High Concentrator Photovoltaic Power Facility by Implementing Artificial Neural Networkes_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publisherversionhttps://www.mdpi.com/1996-1073/13/13/3493es_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES


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Attribution-NonCommercial-NoDerivatives 4.0 Internacional
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