Topology error detection in power system state estimation

Abstract

State estimation (SE) is the centerpiece of power system operations in every modern control center around the world. Therefore, SE accuracy is crucial for reliable operation of power systems. The SE can often be compromised when there are errors in the assumed topology of the network. In this dissertation, a comprehensive analysis of topology errors is presented. Furthermore, new methods are developed to make topology error detection computationally feasible for large systems. In the first part of this dissertation, topology errors in the external systems, such as the neighboring control areas, are investigated. When a subset of measurements coming from an external area is lost, some parts of the system can become unobservable. Since SE cannot be carried out for the unobservable portion, the topology of the external system can no longer be tracked in its usual way. This dissertation offers a computationally efficient external line outage detection algorithm, which uses the internal bus phase angles, any available phasor measurement units (PMUs), and the pre-contingency system topology. Coupled with a post-verification step, this method is shown to be effective in detecting external line outages. The second part of the dissertation focuses on topology errors in the internal system. The conventional SE formulation uses the simplified bus-branch (BB) electrical network provided by the topology processor (TP). When the status of circuit breakers are not reported correctly to the TP, the electrical equivalent it creates will be inaccurate. Therefore, topology errors usually result in SE convergence problems and yield significantly biased estimates. To properly detect these types of errors, rather than using the typical BB representation, the network model is expanded to include circuit breakers and other switching devices in substations. SE is then reformulated to work with this detailed node-breaker (NB) model. Although the expansion of the model introduces computational challenges, several strategies are employed to counter these issues. The proposed innovations include two separate equality-constrained SE algorithms, two optimal meter placement algorithms, and utilization of parallel processing. As demonstrated through the simulations conducted, the methods developed in this dissertation are practical enough for application to real-world systems.