The Potential Role of Machine Learning in Improving Protective Relaying of Substations

Protective relaying plays a crucial role in ensuring the reliable operation of substations and their equipment. As power systems become more complex, advanced techniques are needed to improve the effectiveness of protective relaying. This paper explores the potential role of machine learning in improving protective relaying mechanisms within substations. Various aspects of machine learning, including deep learning algorithms and data-driven approaches, are examined in the context of their application to protective relaying. The benefits and challenges associated with integrating machine learning techniques are discussed, highlighting their potential to enhance fault detection and prevent false tripping. Through this investigation, valuable insights are gained into the utilization of machine learning as a promising avenue for enhancing the reliability and efficiency of substation protection systems.