Artificial Intelligence based Adaptive Harmonic Suppression Method for VSG in Offshore Wind Power Plants

Project Details



The interest in the utilization of offshore wind power is increasing significantly worldwide. For large-scale offshore wind power generation systems controlled by conventional control algorithms, large power generation fluctuations may lead to frequency or voltage problems of the system and even trigger the loss of synchronization. To address these problems, the virtual synchronous generator (VSG) control is widely used to provide frequency and voltage support for the grid. At present, the researches on VSG are mostly focused on the inertia, damping, and dynamic characteristics. But few relevant works are presented about the power quality issues of grid current in VSG-controlled system. For VSG-based offshore wind power generation system, harmonics are mainly caused by wind turbines, power converters, nonlinear loads, and interaction between offshore wind farms and the system. These harmonics can create complex interaction problems between offshore networks and control systems, and even lead to unpredictable equipment trip, especially in weak-grid situations. The reduction of the output impedance in most of the voltage-controlled harmonic suppression methods will result in an increase of the inrush fault current of VSG, which impairs the low voltage ride-through capability of the system.
In this sense, an adaptive harmonic suppression method for VSG in offshore wind plants based on artificial intelligence will be developed in this project to suppress both harmonic current and inrush fault current. The VSG control algorithm will be discussed in detail. The VSG-based hierarchical control strategy will be developed for offshore wind farms to enhance the stability of the system. The power quality and component harmonic contribution of the VSG-controlled offshore wind power plant will be analyzed, the harmonics and inrush fault current model of the system in both time and frequency domain will be developed. The harmonic and inrush fault current coordinated suppression approach of VSG will be developed. The optimal suppression strategy will be predicted based on machine learning algorithm to enhance the adaptivity. System performance will be validated in the islanded mode as well as grid-connected mode, the simulation will be carried out by MATLAB, and experimental verification will also be implemented.

Funding: Self-funded
Effective start/end date01/04/202131/03/2024


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