Zhejiang dianli (Oct 2022)

Practice and reflection on data-driven modeling in electric power domain

  • WANG Huifang,
  • YE Ruikai,
  • LUO Bin,
  • ZHANG Bo,
  • WU Xuefeng,
  • LIU Jianmin

DOI
https://doi.org/10.19585/j.zjdl.202210001
Journal volume & issue
Vol. 41, no. 10
pp. 3 – 10

Abstract

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Data-driven modeling, with its integrated use of such research paradigms as theory, experiment, and data, as well as its rapid application, will be more widely used for solving new problems in power system technology. To this end, the practice of data-driven modeling in the electric power domain is summarized and reflections concerning this matter are presented. First, data-driven modeling and its application in the electric power domain are presented. Then, the data-driven modeling practice for the poor performance of theoretical modeling is analyzed, and the common procedures in the modeling process are summarized. The practice of data-driven modeling based on power text data and power image data is introduced, and relevant experience and reflections are summarized. Finally, some comprehensions and reflections on the definition, conditions and procedures, advantages, and risks of data-driven modeling in the electric power domain are presented, and some issues on which importance ought to be attached in data-driven modeling in the electric power domain are discussed and summarized.

Keywords