Fault Identification of UPFC-Compensated Transmission Lines in Complex Microgrids Using an Intelligent Relaying Scheme Based on Discrete Wavelet Transform and ANN Classifier
Creators: name: Rezai, Sina
Publisher: name: Graduate Studies
Year: 2018
Subjects: subject: Fault Identification
subject: Fault detection
subject: Fault classification,
subject: Transmission Line Protection
subject: UPFC
subject: UPFC-Compensated
subject: Compensated Transmission Line
subject: Line Compensation with UPFC
subject: Unified Power Flow Controller
subject: UPFC Controller
subject: Line Compensation
subject: Transmission Line Relays
subject: Transmission Line Relaying
subject: Transmission Relaying System
subject: Transmission Line Relaying System
subject: Transmission Line Relaying Scheme
subject: Protective Relaying Scheme
subject: Protection
subject: Intelligent Protective Relaying Scheme
subject: Intelligent Relaying Scheme
subject: Intelligent Protective Relays
subject: Intelligent Protection
subject: Intelligent Protection Scheme
subject: Single-ended Intelligent Protective Relaying
subject: Single-ended Intelligent Protective Relays
subject: Single-ended Intelligent Protective Relaying System
subject: Single-ended Protection System
subject: Single-ended Protection Scheme
subject: One-ended Protection System
subject: One-ended Protection Relays
subject: One-ended Protective Relaying
subject: One-ended Protective Relaying System
subject: One-ended Protective Relaying Scheme
subject: Single Terminal Protective Relaying
subject: Single-terminal Protective Relaying
subject: Single-terminal Protection
subject: Single-terminal Current-based Relay
subject: Single-terminal Current-based Relaying
subject: Discrete Wavelet Transform
subject: ANN Classifier
subject: DWT and ANN Classifier
subject: Protection based on Discrete Wavelet Transform and ANN Classifier
subject: Protection based on DWT and ANN
subject: Relays using DWT and ANN
subject: Relaying Scheme using ANN
subject: Relaying Scheme using DWT
subject: DWT and ANN
subject: DWT-ANN
subject: DWT and ANN Fault
subject: ANN Fault
subject: DWT Fault
subject: DWT &amp; ANN Fault
subject: ANN Calssification
subject: ANN Fault Detection
subject: Microgrid
subject: Microgrid Protection
subject: Complex Microgrid
subject: Complex Microgrid Protection
subject: UPFC in Microgrid
subject: Microgrid using UPFC
subject: Transmission Line Protection in Microgrid
subject: FACTS in Transmission Line
subject: FACTS Compensated Transmission Line
subject: High-Voltage Transmission Line
subject: High-Voltage Transmission Line Protection
subject: Wavlete energy-based protection
subject: Fast Detection of faults
subject: Early detection of fault
subject: Modular Neural Network Fault Classification
subject: Modular ANN Fault Classification
subject: Fault Identification based on ANN
subject: Fault Identification based on Neural Network
subject: Fault classification based on ANN
subject: Fault Identification based on DWT
subject: Fault detection based on DWT
subject: Single-ended Protective Relaying
subject: Single-ended Relaying
subject: Single-ended Protective Relays
subject: Single-ended Relays
subject: Power System Protection
subject: Power System Protective Relaying
subject: Power System
subject: Simulink modelling of microgrid
subject: Simulink model of microgrid
subject: Simulink modelling of power system
subject: Simulink model of power system
subject: Simulink model of test power system
subject: Test Microgrid Model
subject: Test Power System Model
subject: Fault study
subject: Fault studies
subject: Fault Analysis
subject: Transmission Line Fault Analysis
subject: Transmission Line Short Circuit Analysis
subject: Transmission Line Short-Circuit Analysis
subject: Short Circuit Analysis
subject: Short-Circuit Analysis
subject: Transmission Line Fault
subject: Transmission Line Short Circuit
subject: Line Fault
subject: Education--Technology
subject: Education--Tests and Measurements
subject: Applied Sciences
subject: Artificial Intelligence
subject: Engineering
subject: Engineering--Electronics and Electrical

description: Transformation 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 &amp; 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.