journal article·2024-01-01Open access

Residual flux density estimation of the three-phase transformer using BP neural network

Yuzhan Ren, Chengcheng Liu, Youhua Wang

AIP Advances· Volume 14· Issue 1

Abstract

When the off-line transformer is re-energized, the phase-controlled switching strategy can avoid the generation of inrush current by controlling the phase. To determine the closing phase, the residual flux density (Br) in the transformer core needs to be accurately measured. This paper proposes a Br estimation method for three-phase transformers based on the finite element method and BP neural network. Firstly, the direction of Br in each phase core is determined based on the transient current characteristics. Then, the three-phase transformer is simulated and the BP neural network is trained to estimate the Br based on the simulation results. The experimental results on a three-phase transformer show that the proposed method can accurately determine the direction and amplitude of Br in each phase of the three-phase transformer.
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Research context

OpenAlex topics: Magnetic Properties and Applications · Non-Destructive Testing Techniques · Power Transformer Diagnostics and Insulation

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology 1 , Tianjin 300130, China

Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability of Hebei Province, Hebei University of Technology 2 , Tianjin 300130, China

Funding

National Natural Science Foundation of China · S&T Program of Hebei

References (11)

Show source-provided references
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