Online stability assessment is an important problem that has not been solved completely yet. The purpose of this research is to tackle online transient stability assessment. Currently, most utility companies use step-by-step integration in order to set protective equipment so that they effectively work for critical contingencies. However, there are times an unforeseen contingency may occur which may cause the system to transit and the protective equipment to misoperate and does not isolate the disturbed part of the system. This research introduces a method that automatically determines a group of generators that participate in system separation and hence transient instability. The method consists of four phases: modeling and simulation, critical machines identification, online transient stability assessment, and critical clearing time calculation. In the modeling and simulation phase, the power system is built and the generators’ rotor angles and speeds are captured. In the critical machines identification phase, the average instantaneous rotor accelerating powers, coherency measures, the during-fault rotor angles and speeds characteristics, and the pre- and post-fault rotor angles are used to identify the Severely Disturbed Group (SDG) of machines. The results of this phase are used to calculate the kinetic energy of the SDG and potential energy of another (or possibly the same) group of generators. Utilization and success of the proposed method will be documented using results from the IEEE 39-Bus test system. Each step of each phase will be demonstrated as needed. The proposed method is compared to step-by-step integration and two direct methods. The suitability of the proposed method for operation will be shown in cases where the Y-Bus matrix and rotor angles and speeds are given. The proof of concept of the proposed method was used in simulating the test system and encouraging results of the simulation were published in [1] and [2]. The proof of concept is the foundation of the method proposed in this dissertation to determine transient stability of large-scale power systems.
| Identifer | oai:union.ndltd.org:uno.edu/oai:scholarworks.uno.edu:td-3114 |
| Date | 11 August 2015 |
| Creators | Al Marhoon, Hussain Hassan |
| Publisher | ScholarWorks@UNO |
| Source Sets | University of New Orleans |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | University of New Orleans Theses and Dissertations |
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