The increasing capacity of renewable generations, especially the wind generation has been playing a critical role in nowadays power systems. Unfortunately, an interaction between the wind turbine generator (WTGs) and fixed series compensation (FSC), namely the sub-synchronous interactions (SSI), has emerged in the power system in the last decade. Such phenomenon has taken different forms (i.e. sub-synchronous resonance) in the conventional power systems and has been mitigated by countermeasures such as power system stabilizers (PSS). However, due to the introduction of more complex power electronic-based controllers, the nowadays power systems have once again become unstable and new types of undamped oscillations have occurred. Some of these events are triggered by system events, others, occurred without any stimulus. This issue has caught great attentions around the world and many works in determining features, classifications, dynamics and mitigations of such phenomenon have been contributed. However, there is still a huge gap in the effective monitoring and mitigation of the complicated features encountered during SSI, and no commercial solution have been realized yet. To cope with these issues, this thesis attempts to provide some contributions to the areas where the monitoring and the mitigation of SSI still fall short. In brief, the existing methods have three limitations when monitoring the SSI in the power systems. The first is that the requirements of prior knowledge of signal parameters beforehand. The second is that the monitoring accuracy is affected by time-varying parameters, and the third is that the monitoring accuracy is affected by noises in the signals. In this thesis, an effective monitoring method, namely the Adaptive Linear Prediction-based Parameter Estimation (ALPPE) method have been proposed to overcome the aforementioned limitations. On the other hand, the existing mitigation methods have limitations such as the requirements of additional power equipment, complex implementation into real power systems and neglection of the time-varying oscillations frequency which have occurred in real-life SSI events. In this thesis, the Varying-Frequency Adaptive Filter (VFAF) has been proposed to overcome the above difficulties.
|Date of Award
|31 Dec 2020
- The University of Manchester
|Vladimir Terzija (Supervisor) & Victor Levi (Supervisor)