Litcius/Paper detail

Protection Scheme using Wavelet-Alienation-Neural Technique for UPFC Compensated Transmission Line

Bhuvnesh Rathore, Om Prakash Mahela, Baseem Khan, Sanjeevikumar Padmanaban

2021IEEE Access44 citationsDOIOpen Access PDF

Abstract

Fault analysis (detection, classification and location) of transmission network is of great importance in power system. A Wavelet-Alienation-Neural (WAN) technique has been developed for the fault analysis of Unified Power Flow Controller (UPFC) compensated transmission network. The detection and classification of various outages are accomplished by alienation of wavelet based approximate coefficients computed from current signals. The precise location of faults is carried out by an Artificial Neural Network fed from estimated approximate coefficients computed from voltage and current signals of the same quarter cycle. The robustness of the algorithm is proved with the case studies of varying fault locations, sampling frequency, system parameters, effects of noise, fault incipient angle, different control strategies and fault path impedances.

Topics & Concepts

Unified power flow controllerRobustness (evolution)WaveletElectric power transmissionControl theory (sociology)Artificial neural networkComputer scienceFault (geology)Transmission lineElectric power systemController (irrigation)Fault detection and isolationNoise (video)Wavelet transformAlgorithmPower (physics)EngineeringArtificial intelligenceTelecommunicationsPower flowElectrical engineeringGeologyImage (mathematics)ActuatorAgronomyChemistryControl (management)GeneSeismologyBiologyPhysicsBiochemistryQuantum mechanicsPower Systems Fault DetectionPower System Optimization and StabilityIslanding Detection in Power Systems