ECE PhD Dissertation Defense: Bilgehan Donmez
December 2, 2020 @ 10:00 am - 11:00 am
PhD Dissertation Defense: Topology Error Detection in Power System State Estimation
Location: Teams Link
Abstract: Growth of renewable energy, changes in weather patterns, and increases in cyber- and physical-attacks are examples of recent challenges in power system operation. To keep up with these rapid transformations, it is imperative to improve the tools used in modern-day control centers.
As the centerpiece of system operations, improvements in state estimation (SE) accuracy would result in better situational awareness for system operators. The state estimate can often be compromised when there are errors in the assumed topology of the network. Therefore, topology error detection plays a key role in SE. In the first part of this dissertation, topology errors in the external systems, which are 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 of the system, the topology of the external system cannot be tracked in its usual way. This dissertation offers a computationally efficient external line outage detection algorithm that uses only the internal bus phase angles, any available phasor measurement units (PMUs), and the pre-contingency system topology of the system. 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 implementations use 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 or 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 operational and computational challenges, several strategies are employed to counter these issues. The proposed innovations include the formulations of two separate equality-constrained SE algorithms, the development of 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 adaptation to real-world systems.