[2205.05180] Massively Digitized Power Grid: Opportunities and Challenges of Use-inspired AI
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Electrical Engineering and Systems Science > Systems and Control

arXiv:2205.05180 (eess)
[Submitted on 10 May 2022]

Title:Massively Digitized Power Grid: Opportunities and Challenges of Use-inspired AI

Authors:Le Xie, Xiangtian Zheng, Yannan Sun, Tong Huang, Tony Bruton
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Abstract:This article presents a use-inspired perspective of the opportunities and challenges in a massively digitized power grid. It argues that the intricate interplay of data availability, computing capability, and artificial intelligence (AI) algorithm development are the three key factors driving the adoption of digitized solutions in the power grid. The impact of these three factors on critical functions of power system operation and planning practices are reviewed and illustrated with industrial practice case studies. Open challenges and research opportunities for data, computing, and AI algorithms are articulated within the context of the power industry's tremendous decarbonization efforts.
Subjects: Systems and Control (eess.SY); Artificial Intelligence (cs.AI)
Cite as: arXiv:2205.05180 [eess.SY]
  (or arXiv:2205.05180v1 [eess.SY] for this version)
  https://doi.org/10.48550/arXiv.2205.05180

Submission history

From: Xiangtian Zheng [view email]
[v1] Tue, 10 May 2022 21:34:14 UTC (7,838 KB)
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