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dc.contributor.authorAmbarita, Evi Elisa
dc.contributor.authorKuncara, Ivan
dc.contributor.authorWidyotriatmo, Augie
dc.contributor.authorKarlsen, Anniken Susanne Thoresen
dc.contributor.authorScibilia, Francesco
dc.contributor.authorHasan, Agus Ismail
dc.date.accessioned2024-06-21T08:52:04Z
dc.date.available2024-06-21T08:52:04Z
dc.date.created2023-11-23T21:49:23Z
dc.date.issued2023
dc.identifier.citationIECON 2023- 49th Annual Conference of the IEEE Industrial Electronics Societyen_US
dc.identifier.isbn979-8-3503-3182-0
dc.identifier.urihttps://hdl.handle.net/11250/3135236
dc.description.abstractThe issue of cyber-attacks against wind farm sensor systems is the focus of this research. A novel method for detecting and estimating the magnitude of such attacks using a discrete-time adaptive observer is presented. The proposed observer is derived by augmenting the filtered measurement equation into the state space model of individual wind turbines. The key contribution of the paper is the development of an adaptive observer that can accurately estimate the attacks. The performance of the observer is evaluated through numerical simulations showing that it is effective in estimating the magnitude of the attacks. The proposed method using a discrete-time adaptive observer should be relevant for real-world settings to improve the security and reliability of wind farm operations.en_US
dc.language.isoengen_US
dc.publisherIEEEen_US
dc.relation.ispartofIECON 2023- 49th Annual Conference of the IEEE Industrial Electronics Society
dc.titleOn Cyber-Attacks Against Wind Farmsen_US
dc.title.alternativeOn Cyber-Attacks Against Wind Farmsen_US
dc.typeChapteren_US
dc.description.versionpublishedVersionen_US
dc.identifier.doi10.1109/IECON51785.2023.10312110
dc.identifier.cristin2201385
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.qualitycode1


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