Intelligent Power Quality Disturbance Detection in Smart Grid System

Abstract

Classification of accurate Power quality (PQ) disturbance is essential for power grid operation and control. Increasing the use of electronics loads makes power system signals contaminated with disturbance and distortion and, thus, increases the complexity of detecting and classifying PQ disturbance signals. This paper proposes a machine learning classifier for detecting and classifying PQ disturbances to address this issue. A large computer-based simulation for generating PQ disturbances in PSCAD/EMTDC environment has been carried out to show the effectiveness of the proposed classification framework. The results show better performance than several state-of-art methods in classifying single and multiple PQ disturbances signals from fewer input features. © 2021 IEEE.