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dc.contributor.authorRaveendran Nair, Unnikrishnan
dc.contributor.authorCosta Castelló, Ramon
dc.contributor.otherUniversitat Politècnica de Catalunya. Doctorat en Automàtica, Robòtica i Visió
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial
dc.date.accessioned2020-09-04T06:59:08Z
dc.date.available2020-09-04T06:59:08Z
dc.date.issued2020-05-21
dc.identifier.citationRaveendran, U.; Costa-Castelló, R. A model predictive control-based energy management scheme for hybrid storage system in islanded microgrids. "IEEE access", 21 Maig 2020, vol. 8, p. 97809-97822.
dc.identifier.issn2169-3536
dc.identifier.otherhttps://www.researchgate.net/publication/341559053_A_model_predictive_control_based_energy_management_scheme_for_hybrid_storage_system_in_islanded_microgrids
dc.identifier.urihttp://hdl.handle.net/2117/328377
dc.description.abstractModel predictive control (MPC) facilitates online optimal resource scheduling in electrical networks, thermal systems, water networks, process industry to name a few. In electrical systems, the capability of MPC can be used not only to minimise operating costs but also to improve renewable energy utilisation and energy storage system degradation. This work assesses the application of MPC for energy management in an islanded microgrid with PV generation and hybrid storage system composed of battery, supercapacitor and regenerative fuel cell. The objective is to improve the utilisation of renewable generation, the operational efficiency of the microgrid and the reduction in rate of degradation of storage systems. The improvements in energy scheduling, achieved with MPC, are highlighted through comparison with a heuristic based method, like Fuzzy inference. Simulated behaviour of an islanded microgrid with the MPC and fuzzy based energy management schemes will be studied for the same. Apart from this, the study also carries out an analysis of the computational demand resulting from the use of MPC in the energy management stage. It is concluded that, compared to heuristic methods, MPC ensures improved performance in an islanded microgrid.
dc.description.sponsorshipThis work was supported in part by the European Union’s Horizon 2020 Research and Innovation Program under the Marie Skłodowska Curie under Grant 675318 (INCITE), in part by the Spanish State Research Agency through the Maria de Maeztu Seal of Excellence to IRI under Grant MDM-2016-0656, and in part by the Spanish National Project DOVELAR (MCIU/AEI/FEDER, UE) under Grant RTI2018-096001-B-C32.
dc.format.extent14 p.
dc.language.isoeng
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.rightsAttribution 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Informàtica::Automàtica i control
dc.subjectÀrees temàtiques de la UPC::Energies::Tecnologia energètica::Emmagatzematge i transport de l'energia
dc.subject.lcshEnergy storage
dc.subject.lcshSmart power grids
dc.subject.otherEnergy management
dc.subject.otherModel predictive control
dc.subject.otherFuzzy systems
dc.subject.otherEnergy storage systems
dc.subject.otherDegradation reduction
dc.subject.otherIslanded microgrid
dc.titleA model predictive control-based energy management scheme for hybrid storage system in islanded microgrids
dc.typeArticle
dc.subject.lemacEnergia -- Emmagatzematge
dc.subject.lemacXarxes elèctriques intel·ligents
dc.contributor.groupUniversitat Politècnica de Catalunya. SAC - Sistemes Avançats de Control
dc.identifier.doi10.1109/ACCESS.2020.2996434
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttps://ieeexplore.ieee.org/document/9097839
dc.rights.accessOpen Access
local.identifier.drac29187721
dc.description.versionPostprint (published version)
dc.relation.projectidinfo:eu-repo/grantAgreement/MINECO/2PE/MDM-2016-0656
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/H2020/675318/EU/Innovative controls for renewable sources Integration into smart energy systems/INCITE
dc.relation.projectidinfo:eu-repo/grantAgreement/MICINN/2PE/RTI2018-096001-B-C32
local.citation.authorRaveendran, U.; Costa-Castelló, R.
local.citation.publicationNameIEEE access
local.citation.volume8
local.citation.startingPage97809
local.citation.endingPage97822


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Attribution 3.0 Spain
Except where otherwise noted, content on this work is licensed under a Creative Commons license : Attribution 3.0 Spain