Distribution network operation situation deduction method based on digital twin model

Power grid operation situation deduction serves as a critical decision-making basis for ensuring the safe and stable operation of power systems. However, distribution network situation deduction faces challenges due to the large number of electrical nodes and excessively high update frequencies of measurement data. To address this issue, this paper proposes the construction of a digital twin model for distribution network node topology to analyze operational trends and conduct optimization method analysis. The model adopts low-voltage-level transformers as nodes and their interconnection relationships as edges to establish the distribution network topology. The topological structure evolves over time driven by switch status parameters. Based on this digital twin model, the reconstructed topology is transmitted to the distribution network via the shortest path algorithm, enabling the network to compute its update cost based on electrical distance. Subsequently, continuous and discrete strategies are decoupled for distributed solving of the distribution network situation deduction model. For continuous strategies, a population-reduced differential evolution algorithm is employed. Considering the limited topological information exchange between distribution and microgrids, a topology calculation model combining virtual power flow and electrical distance methods is utilized to validate the effectiveness of the digital twin model in distribution network topology reconfiguration optimization.