2024-03-29T12:34:20Zhttp://digital.csic.es/dspace-oai/requestoai:digital.csic.es:10261/1330232019-06-11T07:05:11Zcom_10261_106com_10261_4col_10261_485
Application of robust model predictive control to a renewable hydrogen-based microgrid
Velarde, P.
Maestre, Jose Maria
Ocampo-Martínez, Carlos
Bordons, C.
Ministerio de Economía y Competitividad (España)
Trabajo presentado a la 15th European Control Conference (ECC) celebrada en Aalborg (Dinamarca) del 29 de junio al 1 de julio de 2016.
In order to cope with uncertainties present in the renewable energy generation, as well as in the demand consumer, we propose in this paper the formulation and comparison of three robust model predictive control techniques, i.e., multi-scenario, tree-based, and chance-constrained model predictive control, which are applied to a nonlinear plant-replacement model that corresponds to a real laboratory-scale plant located in the facilities of the University of Seville. Results show the effectiveness of these three techniques considering the stochastic nature, proper of these systems.
Financial support from the Spanish Ministry of Economy and Competitiveness (COOPERA project, under grant DPI2013-46912-C2-1-R) and the project ECOCIS (Ref. DPI2013-482443-C2-1-R) is acknowledged.
Peer reviewed
2016-06-06T09:48:15Z
2016-06-06T09:48:15Z
2016
comunicación de congreso
http://purl.org/coar/resource_type/c_5794
ECC16 (2016)
http://hdl.handle.net/10261/133023
http://dx.doi.org/10.13039/501100003329
en
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info:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/DPI2013-46912-C2-1-R
info:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/DPI2013-48243-C2-1-R
Publisher's version
http://www.ecc16.eu/index.shtml
Sí
open