Applying Bayesian Approach in Real-Time Monitoring of Converter-Driven Oscillation

Abstract

Increased use of wind and solar power is leading to significant changes in various properties of power systems. As these inverter-based resources are replacing synchronous generators, the existing dynamic characteristics of power systems change, and new stability phenomena are introduced in the system. Especially, converter-driven stability and oscillations caused by converters are an urgent and growing concern in power systems. Consequently, it is highly important to develop methods for detecting and monitoring converter-driven oscillations. This paper proposes a Bayesian approach for monitoring converter-driven oscillations. The approach utilizes ambient measurements and is able to identify the modal parameters (such as frequency and damping ratio) of the converter-driven oscillations continuously, in real-time. The performance of the proposed method is validated with measurements from two real-life events observed in the Finnish power system. The results show that the proposed approach is highly effective in rapidly detecting and monitoring converter-driven oscillations. It is recommended that transmission system operators implement a real-time monitoring method, such as the method proposed in this paper, for detecting and monitoring converter-driven oscillations.