학술논문

Assessment of Transient Disturbance using Discrete Fourier Transform and Feed Forward Neural Network based Hybrid Classifier
Document Type
Conference
Source
2023 IEEE 3rd International Conference on Sustainable Energy and Future Electric Transportation (SEFET) Sustainable Energy and Future Electric Transportation (SEFET), 2023 IEEE 3rd International Conference on. :1-6 Aug, 2023
Subject
Aerospace
Computing and Processing
Power, Energy and Industry Applications
Robotics and Control Systems
Transportation
Discrete Fourier transforms
Transportation
Voltage
Artificial neural networks
Feature extraction
Mathematical models
Power systems
Transient voltage disturbance
Discrete Fourier Transform
Feed forward neural network
Classification
Accuracy
Language
Abstract
Transient voltage disturbance is one of the prime disturbances occurring in power system, which is of two types' oscillatory transient and impulsive transient. This paper proposes a effective and accurate classifier to segregate normal voltage and transient voltage disturbances. To begin with, the different voltage waveforms for both normal and transient signals have been modelled using corresponding mathematical equations taking suitable sampling frequency in consideration. Secondly, suitable characteristics from these signals are being extracted. Thirdly, these extracted features have been fed into artificial neural network and checked for the output. At last, by checking the out-turn of the neural network, the input signal is getting classified into either normal voltage signal or transient disturbance signal.