Optimizing Grid Reliability with AI-Enhanced Maintenance Strategies

Abstract

Electricity systems are very important to modern life because they provide power to homes, companies, and factories. Making sure that these grids work properly is very important, because problems with them can have big effects on the economy and society. Regular checks and repair plans are a big part of traditional maintenance methods, but they can be expensive and not work very well. In the past few years, there has been a rising interest in using artificial intelligence (AI) to improve grid dependability and repair methods. This essay gives an in-depth look at how AI can be used to improve upkeep methods in order to make the grid more reliable. The suggested method uses advanced machine learning algorithms and real-time data analysis to guess when equipment will break down and arrange repair tasks in order of importance. AI models can find patterns and trends in old maintenance records and data on how well equipment is working, which can help them figure out when and where problems are most likely to happen. Predictive maintenance methods are an important part of maintenance tactics that use AI. AI programs can find early signs of wear and tear or failure on equipment by constantly checking its health with sensors and Internet of Things (IoT) devices. This lets repair be done on time. This preventative method can cut down on the chance of failures and downtime by a large amount. AI can also be used to make repair plans and the use of resources more efficient. AI programs can figure out the best way to maintain the grid while keeping costs low by looking at things like how important the technology is, how much it costs, and how it can be used.