dc.contributor.advisor | Mathisen, Geir | |
dc.contributor.advisor | Marafioti, Giancarlo | |
dc.contributor.author | Alves, Erick Fernando | |
dc.date.accessioned | 2018-08-17T09:54:18Z | |
dc.date.available | 2018-08-17T09:54:18Z | |
dc.date.issued | 2018-08-16 | |
dc.description.abstract | This work investigates and implements algorithms for reliable parameter identification for salient pole synchronous machines that can be used for condition monitoring, on line assessment of the power grid, and adaptive control. All these applications are steps necessary to enable a smarter power grid, in which seamless integrated digital technology provides state estimation, fault detection, and self-healing functionalities, with the ultimate goal of ensuring a reliable supply of electricity, and reducing vulnerability to natural disasters or attacks. | en_US |
dc.identifier.uri | https://hdl.handle.net/10037/13470 | |
dc.language.iso | eng | en_US |
dc.publisher | UiT Norges arktiske universitet | en_US |
dc.publisher | UiT The Arctic University of Norway | en_US |
dc.rights.accessRights | openAccess | en_US |
dc.rights.holder | Copyright 2018 The Author(s) | |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-sa/3.0 | en_US |
dc.rights | Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0) | en_US |
dc.subject.courseID | SHO6262 | |
dc.subject | VDP::Teknologi: 500::Elektrotekniske fag: 540 | en_US |
dc.subject | VDP::Technology: 500::Electrotechnical disciplines: 540 | en_US |
dc.subject | parameter identification | en_US |
dc.subject | synchronous machines | en_US |
dc.subject | smart grid | en_US |
dc.subject | condition monitoring | en_US |
dc.subject | stability assessment | en_US |
dc.subject | adaptive control | en_US |
dc.title | Reliable parameter identification for synchronous machines | en_US |
dc.type | Master thesis | en_US |
dc.type | Mastergradsoppgave | en_US |