Show simple item record

dc.contributor.advisorSharma, Pawan
dc.contributor.advisorSharma, Charu
dc.contributor.authorAddisu, Wondwosen Eshetu
dc.date.accessioned2017-08-24T12:15:03Z
dc.date.available2017-08-24T12:15:03Z
dc.date.issued2017-06-12
dc.description.abstractAbstract Modern power systems need more intelligence and flexibility to maintain and control a generation load balance from subsequent serious disturbances due to the emerging of more renewable energy sources. This problem is becoming more significant today because of the increasing number of micro-grids (MGs). MGs usually use renewable energies in electrical production those fluctuate naturally. So, fluctuation and usual uncertainties in power systems cause the conventional controllers to be less efficient to provide a proper load frequency control (LFC) performance for a wide range of operating condition. Therefore, this thesis presents an intelligent control technique which is based on Adaptive Neuro-Fuzzy Inference System (ANFIS) architecture for an isolated wind-Solar PV-micro turbine-diesel based micro-grid (MG) system using Vehicle-to-Grid (V2G) integration. Accordingly, the V2G technology, the electric vehicle (EVs) may act as mobile energy storage units that could be a better solution for the inadequate LFC capacity and thereby to improve the frequency stability in an isolated MG. The performance of the proposed intelligent controller (ANFIs) is compared with conventional proportional-integral-derivative (PID) controller, Interval type-1 (IT1) Fuzzy controller and Interval type-2 (IT2) Fuzzy controller design methods. The results show that ANFIS based neuro-fuzzy LFC controller is having less settling time and improve dynamic responses for the considered MG systemen_US
dc.identifier.urihttps://hdl.handle.net/10037/11363
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 2017 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.subjectIntelligent control techniqueen_US
dc.subjectEVen_US
dc.subjectV2Gen_US
dc.subjectLFCen_US
dc.subjectInterval type-1 Fuzzy controlen_US
dc.subjectInterval type-2 Fuzzy controlen_US
dc.subjectProportional-Integral-Derivative controlen_US
dc.subjectAdaptive Neuro-Fuzzy Inference Systemen_US
dc.subjectMicro-Griden_US
dc.titleIntelligent load frequency control in an isolated wind-solar PV-micro turbine-diesel based micro-grid using V2G integrationen_US
dc.typeMaster thesisen_US
dc.typeMastergradsoppgaveen_US


File(s) in this item

Thumbnail
Thumbnail
Thumbnail

This item appears in the following collection(s)

Show simple item record

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)