Intelligent stability prediction and control strategy of wind power converter considering nonlinear characteristics

Abstract:
With the increasing penetration of wind power into power system, the influence of wind power on stability of power system is becoming more and more evident, in which case parameter variation is potential challenge for stability. Although LCL-filters are utilized due to their high energy density, power density and relatively smaller volume, they still have possible high-frequency resonance problem, which will impact on the stability of power system and needs to be avoided.
Although modelling, analysis and control methods have been intensively proposed to deal with the stability issues, these methods are basically linearized and time-invariant parameters, which fails to address the parameters variation. To be more specific, the resonance frequency of system might be in unstable region, when the inductance parameters of LCL-filters change because of its nonlinear or aging characteristics. Therefore, in order to deal with the problem in high-frequency stability, this project aims to develop stabilization control strategy with self-learning capability.

Funding: Self-funded