PowerGPT: A GPT-Like System for Smart Grid Data Analysis and Management

Abstract

Smart grid systems face significant challenges with power transformer maintenance due to the complex data generated and the critical role transformers play in grid reliability. Current solutions, such as reactive maintenance and scheduled inspections, often fall short of managing this complexity. Reactive maintenance is costly and introduces delays as faults are often only addressed after they've led to system issues. Scheduled inspections, while proactive, are time-intensive and do not capture real-time fault conditions. These drawbacks lead to increased operational costs, extended downtimes, and reduced grid reliability, emphasizing the need for a predictive and real-time fault management solution.

Researchers at Florida Atlantic University have developed PowerGPT, a pioneering system that leverages advanced deep learning and fault classification technologies specifically for smart grid applications. PowerGPT provides real-time, predictive diagnostics for power transformers, enabling proactive management of grid health and reducing costly downtime associated with reactive maintenance. Unlike traditional methods, PowerGPT integrates a high-accuracy classification model into a user-friendly, conversational interface that can analyze vast datasets quickly and effectively, identifying and categorizing faults with 97% accuracy. Currently, the innovation is at the proof-of-concept stage, with successful demonstrations of its diagnostic capabilities, and development is underway to expand its real-world application potential.

FAU seeks to advance this innovation into the marketplace through licensing or development partnerships.

Benefit

Market Application

Publications

A ChatGPT-like Solution for Power Transformer Condition Monitoring