Transformer-Customer Connectivity Relationship Identification for Low-Voltage Distribution System With High Penetration of Household PV Systems

Transformer-customer connectivity relationship is the index for electricity customers' connections to the up-level transformer in the low-voltage distribution systems. Such relationship serves as the foundation for low-voltage distribution system topology identification, hosting capacity analysis, and operation optimization. The existing identification methods have difficulty adapting to changes in power loss and voltage distribution characteristics caused by high PV penetrations. To overcome these challenges, this paper proposes a weighted convolution model to identify the transformer-customer connectivity relationship for low-voltage distribution systems with high penetration of household PV systems. This model encompasses two key components: a PV fluctuation-adaptive-weighted convolution power optimization model and an improved convolution voltage correlation optimization model. These components collectively capture the unique mapping relationship between customers and transformers, while mitigating the impact of PV fluctuations on power fitting and overcoming the transformer three-phase voltage asymmetry exacerbated by PV. Finally, the effectiveness of the proposed approach is validated through actual cases.