Sesay, A. B.Rezai, Sina2018-07-252018-07-252018-07-23http://hdl.handle.net/1880/107505Transformation of traditional power infrastructures to modern inter-connected electrical grids has resulted in the emergence of microgrids as modernization of the existing aging transmission and distribution systems. Microgrids allow integration of distributed energy resources (DER) such as wind farms (WF) and may utilize Flexible AC Transmission Systems (FACTS) such as Unified Power Flow Controller (UPFC). FACTS increase power flow capacity of transmission lines while DERs supply additional electric energy. In these systems, current direction, as well as power injections, may change at any time; hence, the protection task is complicated during fault occurrences. The fault data is highly nonlinear and nonstationary, making a conventional distance relay dysfunctional. To fix this, many researchers have used signal processing and soft computing techniques. However, previous works are inadequate in terms of scope and type of fault data acquired from circuits, which usually have simple topologies and are applicable to specific systems. In contrast, this work proposes a single-ended intelligent relaying scheme for high voltage UPFC-Compensated transmission lines in complex interconnected power systems with mesh/loop configurations. This study uses a microgrid model created in Matlab/Simulink, which includes a constant power source, a WF, a steam turbine synchronous generator (STSG), and UPFC for line compensation. Interestingly, most unpredictable in this circuit is the fault signature as it simultaneously combines the UPFC three-phase symmetric response as well as the responses from other interconnected sources. The study uses discrete wavelet transform (DWT) for feature extraction and artificial neuron network (ANN) for feature classification of fault currents. The main objectives are automatic detection and identification of fault type with the best accuracy, reliability, and reduced computational complexity. Furthermore, to analyze the impact of UPFC on fault, the study considers also: (i) circuit without UPFC and (ii) circuit without UPFC & DER. Furthermore, using a two-block ANN consisting of two parallel subclassifiers based on whether the fault involves ground or not, further improved the overall performance suggesting a modular ANN is preferred. Finally, the method achieved an early detection time of less than half cycle of post-fault data that is quite useful for breakers’ fast three-phase tripping operations.engUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.Fault IdentificationFault detectionFault classification,Transmission Line ProtectionUPFCUPFC-CompensatedCompensated Transmission LineLine Compensation with UPFCUnified Power Flow ControllerUPFC ControllerLine CompensationTransmission Line RelaysTransmission Line RelayingTransmission Relaying SystemTransmission Line Relaying SystemTransmission Line Relaying SchemeProtective Relaying SchemeProtectionIntelligent Protective Relaying SchemeIntelligent Relaying SchemeIntelligent Protective RelaysIntelligent ProtectionIntelligent Protection SchemeSingle-ended Intelligent Protective RelayingSingle-ended Intelligent Protective RelaysSingle-ended Intelligent Protective Relaying SystemSingle-ended Protection SystemSingle-ended Protection SchemeOne-ended Protection SystemOne-ended Protection RelaysOne-ended Protective RelayingOne-ended Protective Relaying SystemOne-ended Protective Relaying SchemeSingle Terminal Protective RelayingSingle-terminal Protective RelayingSingle-terminal ProtectionSingle-terminal Current-based RelaySingle-terminal Current-based RelayingDiscrete Wavelet TransformANN ClassifierDWT and ANN ClassifierProtection based on Discrete Wavelet Transform and ANN ClassifierProtection based on DWT and ANNRelays using DWT and ANNRelaying Scheme using ANNRelaying Scheme using DWTDWT and ANNDWT-ANNDWT and ANN FaultANN FaultDWT FaultDWT & ANN FaultANN CalssificationANN Fault DetectionMicrogridMicrogrid ProtectionComplex MicrogridComplex Microgrid ProtectionUPFC in MicrogridMicrogrid using UPFCTransmission Line Protection in MicrogridFACTS in Transmission LineFACTS Compensated Transmission LineHigh-Voltage Transmission LineHigh-Voltage Transmission Line ProtectionWavlete energy-based protectionFast Detection of faultsEarly detection of faultModular Neural Network Fault ClassificationModular ANN Fault ClassificationFault Identification based on ANNFault Identification based on Neural NetworkFault classification based on ANNFault Identification based on DWTFault detection based on DWTSingle-ended Protective RelayingSingle-ended RelayingSingle-ended Protective RelaysSingle-ended RelaysPower System ProtectionPower System Protective RelayingPower SystemSimulink modelling of microgridSimulink model of microgridSimulink modelling of power systemSimulink model of power systemSimulink model of test power systemTest Microgrid ModelTest Power System ModelFault studyFault studiesFault AnalysisTransmission Line Fault AnalysisTransmission Line Short Circuit AnalysisTransmission Line Short-Circuit AnalysisShort Circuit AnalysisShort-Circuit AnalysisTransmission Line FaultTransmission Line Short CircuitLine FaultEducation--TechnologyEducation--Tests and MeasurementsApplied SciencesArtificial IntelligenceEngineeringEngineering--Electronics and Electricalmaster thesis10.11575/PRISM/32686