Powering AI: The Unique AI Load Features, Challenges and Opportunities -Slides

Abstract:As large language models (LLMs) continue to advance various industries, they are driving multi-hundred-billion-dollar investments in AI-centric data/computation centers in the coming years. Alongside well-known concerns regarding sustainability and energy use, there is a growing need to address a less frequently discussed issue: the dynamic and potentially disruptive power consumption patterns of AI infrastructure. These systems, characterized by rapid transients, ultra-low inertia, sharp power surges/dips, span a wide range of power demands—from hundreds of watts to megawatts and even reach gigawatts in near future. These unique characteristics pose complex challenges for power electronics systems tasked with managing energy conversion and control within data centers and across power grids. Power electronics, already critical for efficient energy management, are becoming even more essential in maintaining grid stability as AI infrastructure introduces these unprecedented load dynamics. The fast-changing power requirements of AI workloads have the potential to cause severe transients, which could impact the reliability and resilience of power grids. This webinar will examine the scale and nature of AI-related power consumption, present mathematical models to describe AI workload behavior, and explore the role of power electronics in mitigating the risks associated with LLM-induced transients. By focusing on the interaction between AI infrastructure and power electronics, this session aims to emphasize the importance of interdisciplinary collaboration to ensure the sustainable development of AI technologies while safeguarding the reliability of power grids. It is intended to foster discussion among researchers, engineers, and practitioners in power electronics, encouraging exploration of solutions to these emerging challenges.