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Charaterization of Emerging Computing Architectures for Dynamic Simulation of Future Power Grids with Large-Scale Power Electronics

by Jongchan Choi, Suman Debnath, Phani Ratna Vanamali Marthi
Publication Type
Conference Paper
Book Title
2022 IEEE Energy Conversion Congress and Exposition (ECCE)
Publication Date
Page Numbers
1 to 8
Publisher Location
New Jersey, United States of America
Conference Name
2022 IEEE Energy Conversion Congress and Exposition (ECCE)
Conference Location
Detroit, Michigan, United States of America
Conference Sponsor
IEEE Power Electronics Society (PELS), IEEE Industrial Applications Society (IAS)
Conference Date
The increasing penetration of power electronics in power grids significantly raises the computing requirements in a real-time (and/or fast) simulation of the power grid. The real-time simulation is an enabler for evaluating controllers, protection systems, new equipment, and twinning. In this paper, emerging computing architectures such as tensor processing units (TPU), neural/neuromorphic processing units (NPU), and quantum processing units (QPU) are introduced and characterized for the real-time (and/or fast) simulation of power electronics-dominated power grids. The metrics and the process to characterize emerging computing architectures to perform real-time (and/or fast) simulations of future power grids with power electronics are discussed. Three of the emerging computing units are characterized based on these metrics and the process developed. This characterization will enable identification and comparison of emerging computing architectures that can perform real-time (and/or fast) simulation of future power grids.