Artificial Intelligence in Utilities: Predictive Maintenance and Beyond

Abstract

Artificial Intelligence (AI) and Machine Learning (ML) are transforming the utility industry, offering significant advancements in areas such as predictive maintenance, demand forecasting, and operational optimization. By leveraging AI-driven analytics, utilities can predict equipment failures, optimize maintenance schedules, forecast energy demand, and improve grid stability. Case studies from Duke Energy, Siemens, and Constellation Energy highlight the real-world benefits of AI in reducing costs, improving reliability, and enhancing customer satisfaction. However, challenges such as data quality, system integration, and regulatory compliance must be addressed for full-scale AI adoption. Future innovations, including self-healing grids and AI integration with renewable energy, underscore AI's potential to revolutionize utility operations and contribute to a more sustainable, reliable, and efficient energy landscape.