Leveraging Large Language Models for Enhanced Design and Analysis in Power Engineering

This review article examines the applications of Large Language Models (LLMs) in power engineering with new design and analysis techniques. The study addresses issues such as controlling complicated grid data, automating design activities, and improving maintenance checks. Using LLMs' sophisticated natural language understanding and language generation capabilities, power engineers automate simulations, optimize configurations, and manage risk evaluation processes more efficiently. The article cites successful applications of LLMs with CAD and simulation tools, for which qualitative studies have shown enhanced efficiency and precision in analysis. Other issues like data reliability, model trust, and ethics are discussed and balanced with proposed recommendations such as modifying some models and human oversight. Recommendations stress the need for cross-disciplinary approaches that can adapt to these frameworks safely and effectively. LLMs creates strong, enduring, yet flexible, intelligent power systems, clearly stating systems poised to change engineering approaches in new energy paradigms.