Generic Multi-Frequency Modelling and Model Validation Methods for Converter-Based Renewable Energy Generators

Vast amounts of Renewable Energy Generators (REG), i.e., Wind Turbines (WT) and Photo-Voltaic (PV) panels, are connected to power systems using power converters. Dynamic and steady-state performances of the converter-based REGs differ from the conventional synchronous machines. REGs are required to provide certain levels of stability and reliability.

Consequently, exclusive grid connection codes, international standards, and analytical models have been developed. However, multi-frequency (or harmonic) interactions, which are increasing challenges, have not been completely solved and analyzed yet. The state-of-the-art multi-frequency models are linearized and averaged representatives of non-linear converter systems, and detailed information is required for trustworthy analyses.

Besides, nowadays, converter-based grid emulators have been diploid for grid code compliance testing. The international test standards have been issued to assess harmonic emissions, but the test results are not sufficient for harmonic stability assessment and model validation. This PhD project proposes generic multi-frequency modeling and model validation methods for converter-based REGs.

The proposed methods are based on Fourier analysis of REG responses to small-signal perturbations. This way, any significant non-linearity can be identified and addressed. The proposed generic models are categorized into two main groups of converter-connected REGs (i.e., Type 4 WTs and PV systems) and Type 3 WTs.

The proposed models and validation methodology are verified experimentally by perturbation tests on a 2MVA Type 3 WT and a 2MVA PV converter using a 7MVA grid emulator. Furthermore, the experimental analysis of emissions from Type 3 WTs is demonstrated by site tests on a 2.2MVA Type 3 WT using a 15MVA grid emulator and field measurements from a 0.85MVA Type 3 WT.

Besides, supplementary simulations are conducted to investigate effective parameters on the test results.