Multi-area State Estimation of Distribution Networks Based on Optimal Partition

The increasing scale of the distribution networks has brought huge challenges to the efficiency and reliability of state estimation. This paper proposed a multi-area state estimation of distribution networks based on optimal partition. By combining the Blondel Guillaume Lambiotte Lefebvre (BGLL) community discovery algorithm and the balanced optimization model, the distribution networks could be divided into high-inter-cohesive overlapping sub-areas with reasonable scales. Furthermore, the information interaction method was improved based on the equivalent load, so that |the state variables could be obtained by local estimation and system coordination. The simulation test was performed on IEEE 123, which verified the effectiveness of the proposed partition and multi-area state estimation method.