AI-Assisted Power Grid Dispatch and Control

This presentation explores challenges and advancements in optimizing power systems operations through Grid Mind, an innovative data-driven framework designed to enhance the integration of renewable energy sources. Employing advanced learning algorithms, this framework innovates in strategic resource allocation and control, thereby improving efficiency and reliability in power systems with a high penetration of renewables. The transformative potential of this AI-assisted technology is showcased through real-world applications, demonstrating its effectiveness in addressing the complexities of modern power systems. Moreover, the talk addresses critical safety considerations and practical deployment issues, underscoring the need for robust, secure, and adaptable solutions. The capabilities of Grid Mind as a distributed, learning-based system optimized for edge devices are discussed, showcasing a significant advancement towards sustainable, safe, and efficient power system operations in an era dominated by renewable energy.

Speaker: Di Shi, New Mexico State University

Room 292A