Impact of Plant Controls of Large-Scale Inverter-based Generation on Inter-Area Oscillations in the Continental Europe Power System

It is the third version of the SPD dynamic model, intended for use in dynamic analyses requiring representation of the entire synchronous area to adequately capture inter-area oscillations.

To avoid unnecessary model complexity, facilitate tuning, and improve the understanding of the impact of model parameters and their control strategies, default dynamics are intentionally applied to both synchronous and non-synchronous sources. With IBRs accounting for approximately 49% of total generation, and reaching up to 80% in selected areas, the influence of these resources on low-frequency inter-area oscillations was examined. The main contribution of the paper and its novelty come from systematic analysis of the impact of IBR sources and their control strategies on the damping and frequency of inter-area oscillations in the CESA region. This analysis is conducted on a full-scale bulk power system model of CESA, which significantly enhances the practical relevance of the results.

The model was developed incrementally, introducing dynamic representations of individual components in successive stages. Small-signal stability analysis was applied to validate the model against a reliable reference model and subsequently evaluate the impact of IBRs voltage and reactive power control on inter-area oscillation damping. It was found that, with a high share of IBRs in the areas participating in the lowest-frequency oscillations, the applied control mode and settings have a significant impact on modal properties. Fast voltage regulation, particularly when combined with high integral gain in plant controllers, can lead to reduced damping of inter-area modes. Improved damping performance can be obtained through alternative strategies such as power factor or reactive power control. Furthermore, replacing IBRs in areas not participating in the investigated modes with constant current loads does not visibly affect the modes’ parameters, while enabling faster computational performance. Finally, the work carried out provided knowledge and tools that will be useful for automatic development of stable dynamic models for CESA across a wide range of future scenarios with varying shares of renewable energy sources.