Two-Stage Transformer–Customer Relationship Identification Strategy for Low-Voltage Distribution Grid Using Physics-Guided Graph Attention Network

Yang Lei, Fan Yang, Yanjun Feng (), Wei Hu and Yinzhang Cheng
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Yang Lei: Power Science Research Institute of State Grid Hubei Electric Power Co., Wuhan 430048, China
Fan Yang: Power Science Research Institute of State Grid Hubei Electric Power Co., Wuhan 430048, China
Yanjun Feng: Power Science Research Institute of State Grid Shanxi Electric Power Co., Taiyuan 030021, China
Wei Hu: Power Science Research Institute of State Grid Hubei Electric Power Co., Wuhan 430048, China
Yinzhang Cheng: Institute of Power Distribution, College of Electrical Engineering, Southeast University, Nanjing 210096, China

Energies, 2025, vol. 18, issue 16, 1-17

Abstract: Accurate transformer–customer relationships are crucial for the efficient operation and high-quality service of the low-voltage distribution grid (LVDG). This paper proposes a novel two-stage transformer–customer relationship identification strategy for LVDG using physics-guided graph attention network (PGAT). First, considering both transient and steady-state voltage fluctuations, a modified piecewise aggregate approximation (MPAA) algorithm is developed to preprocess raw measurement data through compression and denoising while preserving key voltage correlation features. Second, electrical similarity among customers is explored using the Modified Piecewise Aggregate Approximation K-means (MPAA-K-means) algorithm, enabling preliminary identification of transformer–customer relationships. Then, a training paradigm based on PGAT is introduced to characterize node features constrained by grid topology and electrical properties, achieving refined identification of transformer–customer relationships. Finally, testing results on real LVDG demonstrate the effectiveness and accuracy of the proposed two-stage identification strategy, providing new insights for transformer–customer relationship identification.

Keywords: low-voltage distribution grid; transformer–customer relationship; physics-guided graph attention network; modified piecewise aggregate approximation; K-means (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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