Adaptive Zero-Crossing Regulation Algorithm for Multi-Winding Parallel-Wound Distribution TransFormers

Transformer losses significantly impact grid losses. The adaptive load distribution transformer can adjust voltage taps and automatically switch operating modes based on system conditions without disconnecting the load. This reduces no-load losses, cutting grid losses and improving energy efficiency. This paper proposes a multi-winding parallel-wound distribution transformer (MWPW-DT) model based on an adaptive zero-crossing adjustment algorithm. The model quickly adapts to load changes, keeping the transformer within an economical operating range. Simulation analysis in MATLAB/SIMULINK confirms the model's feasibility.

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Publication Details

Published
2024-10-25
DOI
https://doi.org/10.1109/appeec61255.2024.10922362
Primary Topic
Advanced Technology in Applications
Type
article
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Adaptive Zero-Crossing Regulation Algorithm for Multi-Winding Parallel-Wound Distribution TransFormers

Yang Wang, Jinwei Lin, Xu Sun, Wei Wang et al.
Advanced Technology in Applications
article

Adaptive Zero-Crossing Regulation Algorithm for Multi-Winding Parallel-Wound Distribution TransFormers

Yang Wang, Jinwei Lin, Xu Sun, Wei Wang, Bingyu Zhang, Chengyuan Luo, Yinbing Wu
article en

Abstract

Transformer losses significantly impact grid losses. The adaptive load distribution transformer can adjust voltage taps and automatically switch operating modes based on system conditions without disconnecting the load. This reduces no-load losses, cutting grid losses and improving energy efficiency. This paper proposes a multi-winding parallel-wound distribution transformer (MWPW-DT) model based on an adaptive zero-crossing adjustment algorithm. The model quickly adapts to load changes, keeping the transformer within an economical operating range. Simulation analysis in MATLAB/SIMULINK confirms the model's feasibility.

State Grid Corporation of China (China) (CN), Southeast University (CN)
Affordable and clean energy
Openalex Percentile: Top 55%
Advanced Technology in Applications
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