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dc.contributor.authorSiniscalchi-Minna, Sara
dc.contributor.authorBianchi, Fernando Daniel
dc.contributor.authorOcampo-Martínez, Carlos
dc.contributor.authorDomínguez García, José Luis
dc.contributor.authorDe Schutter, Bart
dc.contributor.otherInstitut de Recerca en Energía de Catalunya
dc.date.accessioned2020-03-02T15:29:24Z
dc.date.available2021-01-07T01:34:44Z
dc.date.issued2020
dc.identifier.citationSiniscalchi-Minna, S. [et al.]. A non-centralized predictive control strategy for wind farm active power control: A wake-based partitioning approach. "Renewable Energy", 2020, vol. 150, p. 656-669.
dc.identifier.urihttp://hdl.handle.net/2117/178932
dc.description.abstractOwing to wake effects, the power production of each turbine in a wind farm is highly coupled to the operating conditions of the other turbines. Wind farm control strategies must take into account these couplings and produce individual power commands for each turbine. In this case, centralized control approaches might be prone to failures due to the high computational burden and communication dependency. To overcome this problem, this paper proposes a non-centralized scheme based on splitting the wind farm into almost uncoupled sets of turbines by solving a mixed-integer partitioning problem. In each set of turbines, a model predictive control strategy seeks to optimize the distribution of the power set-points among turbines such that the impact of the power losses due to the wake effect is reduced. Then, a supervisory controller coordinates the generation of each group to satisfy the power demanded by the grid operator. The effectiveness of the proposed control scheme in terms of reduction of computational costs and power regulation is confirmed by simulations for a wind farm of 42 turbines.
dc.language.isoeng
dc.publisherElsevier
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Enginyeria elèctrica
dc.subject.lcshElectrical engineering
dc.subject.otherWind farm control
dc.subject.otherNon-centralized control
dc.subject.otherPartitioning algorithms
dc.subject.otherModel predictive control
dc.subject.otherWake effect
dc.titleA non-centralized predictive control strategy for wind farm active power control: A wake-based partitioning approach
dc.typeArticle
dc.subject.lemacEnginyeria elèctrica
dc.identifier.doi10.1016/j.renene.2019.12.139
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/abs/pii/S0960148119320129
dc.rights.accessOpen Access
dc.description.versionPostprint (author's final draft)
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/H2020/675318/EU/Innovative controls for renewable sources Integration into smart energy systems/INCITE
local.citation.publicationNameRenewable Energy
local.citation.volume150
local.citation.startingPage656
local.citation.endingPage669


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