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dc.contributor.advisorHoff, Bjarte
dc.contributor.authorMokrushev, Ivan
dc.date.accessioned2019-08-21T07:21:58Z
dc.date.available2019-08-21T07:21:58Z
dc.date.issued2018-08-21
dc.description.abstractModel predictive control method becomes more popular in research over the last decade. Due to the growing popularity of the model predictive control concept, there are more and more questions about the effectiveness of this method in comparison with other methods. In this thesis cascaded model predictive control of grid connected voltage source converter with LCL filter has been evaluated. The relevant topics and literature regarding the existing control methods, applying requirements to a converter and different transistor technologies have been studied and reviewed. Three criteria of performance have been selected to compare the MPC method with conventional voltage oriented control method: total and individual harmonic distortion, power factor and power losses. The models have been simulated at rated initial values according to EU standards. The results of simulations have been compared. Existing transistor technologies which can be used in the control models have been investigated. Losses of the converter (without losses in the LCL filter) due to the use of each type of transistors have been calculated for each model.en_US
dc.identifier.urihttps://hdl.handle.net/10037/15983
dc.language.isoengen_US
dc.publisherUiT Norges arktiske universiteten_US
dc.publisherUiT The Arctic University of Norwayen_US
dc.rights.accessRightsopenAccessen_US
dc.rights.holderCopyright 2018 The Author(s)
dc.rights.urihttps://creativecommons.org/licenses/by-nc-sa/3.0en_US
dc.rightsAttribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0)en_US
dc.subject.courseIDSHO6262
dc.subjectVDP::Teknologi: 500::Elektrotekniske fag: 540en_US
dc.subjectVDP::Technology: 500::Electrotechnical disciplines: 540en_US
dc.subjectConverteren_US
dc.subjectVOCen_US
dc.subjectMPCen_US
dc.titleEvaluation of cascaded MPC performance in voltage source convertersen_US
dc.typeMaster thesisen_US
dc.typeMastergradsoppgaveen_US


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Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0)
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0)