| Autor: |
WANG Huifang, YE Ruikai, LUO Bin, ZHANG Bo, WU Xuefeng, LIU Jianmin |
| Jazyk: |
čínština |
| Rok vydání: |
2022 |
| Předmět: |
|
| Zdroj: |
Zhejiang dianli, Vol 41, Iss 10, Pp 3-10 (2022) |
| Druh dokumentu: |
article |
| ISSN: |
1007-1881 |
| DOI: |
10.19585/j.zjdl.202210001 |
| Popis: |
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. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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