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Can Active Learning Benefit the Smart Grid? A Perspective on Overcoming the Data Scarcity

Authors :
Kun Qian
Tao Chen
Xiang Zha
Wei Guo
Source :
2019 IEEE 2nd International Conference on Electronics and Communication Engineering (ICECE).
Publication Year :
2019
Publisher :
IEEE, 2019.

Abstract

In the past decade, a plethora of efforts were given to the field of facilitating a better smart grid system by leveraging the power of artificial intelligence. Undoubtedly, machine learning is currently playing an increasingly important role in almost every aspect of power systems. However, in real practice, there is a much larger amount of unlabelled data than the one labelled by human experts. In this work, we make a perspective study on overcoming the data scarcity in smart grid. The active learning strategy will be proposed to provide a feasible solution for addressing the data scarcity challenge. In addition, we will give a discussion on current state-of-the-art and the limitations in previous work. We hope this work can be a good guide for researchers to further the relevant study in the near future.

Details

Database :
OpenAIRE
Journal :
2019 IEEE 2nd International Conference on Electronics and Communication Engineering (ICECE)
Accession number :
edsair.doi...........ee527b7f889dfd12c7a85b2d5b74d203
Full Text :
https://doi.org/10.1109/icece48499.2019.9058539