mlsanityData to 14 Oct 2026

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

arXiv 2205.05180 ↗First posted 10 May 2022eess.SY cs.AI cs.SYcited by 6

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Abstract (arXiv)

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.

Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Builds on 48 of its 239 references that are in the map. First posted on arXiv 10 May 2022.

Builds on

48 of 239 references.

References · 48

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36 more
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Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2022: 1; 2023: 0; 2024: 0; 2025: 3; 2026: 2.

6 papers.

  1. 2025A Scoping Review of Machine Learning Applications in Power System Protection and Disturbance Managementcited by 9
  2. 2025Global-Decision-Focused Neural ODEs for Proactive Grid Resilience Managementcited by 4
  3. 2025From Transformers to Large Language Models: A systematic review of AI applications in the energy sector towards Agentic Digital Twinscited by 2
  4. 2022Energy System Digitization in the Era of AI: A Three-Layered Approach towards Carbon Neutralitycited by 0
  5. 2026A Chain Is Only as Strong as Its Weakest Link: A Scoping Review of System Integration Audits in AIcited by 0
  6. 2026Structural Alignment for Reliable Industrial AI: Bridging Physical Reality, Data, Models, and Human Intentcited by 0