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A review of applications of deep learning in power systems

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DOI: 10.23977/ssge.2022.040102 | Downloads: 26 | Views: 722

Author(s)

Peiye Li 1

Affiliation(s)

1 School of Electrical and Electronic Engineering, North China Electric Power University, Baoding, Hebei, 071000, China

Corresponding Author

Peiye Li

ABSTRACT

Deep learning is a major branch of machine learning. Combining its powerful data processing capabilities with power systems is an important path to promote the intelligence of power systems. This paper first introduces the application characteristics and scope of application of deep learning, and then introduces the technical characteristics of power systems such as massive data, interconnectivity, and efficient intelligence. The application status of deep learning and power system integration in various aspects such as power system and equipment fault diagnosis, power load and new energy power prediction, and power system operation control is reviewed. On this basis, the challenges and key technologies of the operation of the new power system are discussed, and the application of the deep learning model in the power system is prospected.

KEYWORDS

Power system, deep learning, fault diagnosis, power prediction, operation regulation

CITE THIS PAPER

Peiye Li, A review of applications of deep learning in power systems. Smart Systems and Green Energy (2022) Vol. 4: 7-10. DOI: http://dx.doi.org/10.23977/ssge.2022.040102.

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