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Xiangtian Zheng 0002

dblp:178/0256-2 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2023
0000-0003-2884-3213ORCID · verified

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Energy systems and smart grids · 100%

Topics — the 1 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Energy systems and smart grids
power system planning and operation
0.712023
Massively Digitized Power Grid: Opportunities and Challenges of Use-Inspired AI · Proc. IEEE 2023

Methods — techniques the papers use, named apart from their topics

data analytics · 0.7artificial intelligence · 0.7
YearPublicationVenuePosition
2023 Massively Digitized Power Grid: Opportunities and Challenges of Use-Inspired AI
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 is 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.
Le Xie 0001, Xiangtian Zheng 0002, Yannan Sun, Tony Bruton
Proc. IEEE2