TALK [MERL Seminar Series 2024] Di Shi presents talk titled AI-assisted Power Grid Dispatch and Control: Optimization, Safety, and Real-world Demonstrations
Date released: November 20, 2024
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TALK [MERL Seminar Series 2024] Di Shi presents talk titled AI-assisted Power Grid Dispatch and Control: Optimization, Safety, and Real-world Demonstrations (Learn more about the MERL Seminar Series.)
Date & Time:
Wednesday, November 20, 2024; 1:00 PM
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Abstract:
This presentation delves into the challenges and advancements in optimizing power system operations through Grid Mind, an innovative, data-driven framework designed to enhance the integration of renewable energy sources. Utilizing advanced learning algorithms, Grid Mind excels in strategic resource allocation and control, significantly improving efficiency and reliability in power systems with high renewable energy penetration. The transformative potential of this AI-assisted technology is highlighted through real-world applications, demonstrating its effectiveness in addressing the complexities of modern power systems. In addition, critical safety considerations and practical deployment challenges are explored, emphasizing the need for robust, secure, and adaptable solutions. This talk also discusses the capabilities of Grid Mind as a distributed, learning-based system optimized for edge devices, marking a significant advancement toward sustainable, safe, and efficient power system operations in an era dominated by renewable energy.
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Speaker:
Di Shi
New Mexico State University
Di Shi is an Associate Professor with the Klipsch School of Electrical and Computer Engineering at New Mexico State University. Before academia, he founded a tech startup focusing on energy systems AI, commercialized two technologies, and founded and led the AI & System Analytics group at GEIRINA. He has also held research positions at NEC Labs, EPRI, and Arizona State University. He leads two IEEE task forces/working groups on IoT and machine learning for power systems, holds 27 patents, and serves as associate editor for four IEEE and IET transactions. He led a team to the championship of 2019 L2RPN power system AI competition. He earned his Ph.D. and M.S. degrees from Arizona State University and a B.S. from Xi’an Jiaotong University. -
MERL Host:
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Research Areas: