Artificial Intelligent Techniques for Identifying the Cause of Disturbances in the Power Grid
DOI:
https://doi.org/10.47709/brilliance.v3i1.2165Keywords:
AI TECHNIQUES, POWER QUALITY, DISTURBANCE SOURCE LOCATION, POWER GRIDAbstract
The intricacy of the power system configuration, coupled with the contemporary trends in power generation and demand, renders the attainment of adequate supply quality a daunting task for distribution companies. Several regulations govern the power quality (PQ) of the electrical system. In addition, EN-50160 outlines the voltage characteristics supplied by public electricity networks, which directly impact distribution companies. Secondly, the EN-61000 standards series regulates the electromagnetic compatibility of network-connected devices, which affects the loads. Both power companies and device manufacturers are responsible for ensuring and being impacted by the quality of supply. Artificial Intelligence (AI) techniques refer to a variety of methods and algorithms that enable machines to perform tasks that typically require human-like intelligence, such as perception, reasoning, learning, and decision-making. AI techniques include machine learning, natural language processing, computer vision, robotics, expert systems, and other approaches that use algorithms to analyze and understand complex data, recognize patterns, and make predictions or decisions based on that data Notwithstanding the regulations, there are still unresolved aspects of the supply quality, one of the most significant being the location of the origin of disturbances. This article presents an investigation of the main techniques used to identify the cause of disturbances and locate their origin in the power grid.
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