Reduced Anomaly Zone Determination for Topology Error Processing in Generalized State Estimation

The emergence of methods based on representing parts of the electrical network at the bus-section level has brought about new perspectives for topology error identification in real-time power system modeling. This work addresses the problem of determining the relevant portions of the network to be modeled in detail so as to ensure favorable topological conditions for topology error identification. Starting from the conventional bus-branch network model, the proposed approach performs error analysis and defines correlation indices from which an anomaly zone is identified. A graph theoretic algorithm is then used to expand the anomaly zone into a relevant subnetwork to be modeled at the bus section level. This subnetwork is greatly reduced in size, contains all suspect substations and exhibits the required properties for topology error identification conducted through generalized state estimation. The proposed methodology is evaluated through results obtained from test systems derived from the IEEE 14-bus and 30-bus networks.