Iterative State Estimation With Weight Tuning and Pseudo-Measurement Generation

The proliferation of distributed generation (DG) in the power system at low and medium voltage levels is creating challenges to the operation and control of the network and its protection system. Recent studies focus on using smart methods to deal with these challenges. These methods require access to information that can be provided by distribution network state estimation. However, state estimation in the distribution network is hindered by limited network observability and increased uncertainty due to the presence of DGs. With the threat of false data injection attacks, the security of state estimation is also a concern. To this end, this article proposes an iterative state estimation that uses: 1) an extended state vector that includes DG outputs; 2) pseudo-measurement generation based on DG characteristics and static voltage control modes; and 3) a weight updating algorithm that incorporates bad data detection. Simulations on a 44-node test distribution network show that the proposed iterative method improves the estimation of the status and outputs of the DGs and subsequently increases the accuracy of the fault current calculation.