Small-signal stability models are required for plans that contribute to local, intra-regional and inter-regional frequency modes in the power system. This includes synchronous generators and their Power Oscillation Dampers (PODs), dynamic reactive support plant with PODs, and any other plant which can reasonably impact damping of small-signal oscillations as determined by Australian Energy Market Operator (AEMO) and the relevant Network Service Providers (NSPs).
Small-signal stability models may also be required for studying the effects of sub-synchronous oscillations, such as inverter control system interactions up to 25 Hz. This will include any plant which can potentially contribute to such oscillations as determined by AEMO and the relevant NSP.
For synchronous machines, a fully validated RMS transient stability model is typically adequate for this analysis, as long as the corresponding small-signal model can be derived from block diagrams or source code using standard mathematical linearization techniques. However, for asynchronous technology, small-signal models derived from RMS transient stability models may not be sufficient for analyzing such phenomena. AEMO recommends that small-signal models should represent all sub-synchronous frequencies.
This thesis is to formulate a frequency domain-based approach for modelling of wind energy system, focusing but not limited to type III (DFIG) wind turbine system. The models are then used for small-signal stability analysis and potentially control design as well as improvement.
YOUR TASKS
1. Conduct a methodologies state of the art review of system identification using impedance model and elect a suitable method to be used in the next steps
2. Derive and validate the Linear parameter-varying (LPV) model for windfarm DFIG model from the chosen method
3. Standardize the process of creating and validating the LPV model for power system model
YOUR PROFILE
4. Currently pursuing a Master's degree in Control/Electrical/Power systems, a mixed field of control and energy would be advantageous
5. Possess a strong understanding of energy power systems, especially for wind energy system
6. Familiar with MATLAB/Simulink/Simscape specialized power systems toolboxes
7. Have interest in Wind energy systems stability analysis and control design
8. Experienced in converter control system and/or wind farm control system would be a plus
9. Possessing programming knowledge in MATLAB and other languages such as Python, C/C++ would be advantageous
10. Fluent in English, with knowledge of German or other languages being an added advantage
11. Possess a self-organized personality and can handle complex technical problems with ease
12. Capable of working effectively in a multilingual and multicultural team