Measuring the impact of renewable generation in modern power systems using modal trajectories extracted via Fourier-sine filters and Lyapunov exponents

The energy transition taking place in electric energy systems has imposed challenges to operators and planners. Among these challenges, Dynamic Security Assessment (DSA) has become highly relevant due to the increasing variability in system response, influenced by the integration of inverter-based resources (IBRs), demand response, and variability of natural resources. In response to these needs, this research proposes a methodology for measuring the impact of high renewable energy integration in power systems, using Lyapunov Exponents (LEs) as a severity metric. The approach relies on modal trajectories extracted from synchrophasor data stemming from the power system simulated response, employing a set of FIR filters using primitive sine functions. This filtering technique decomposes frequency signals and estimates modal amplitudes to feed three stability indices combined into a global performance index to assess and rank system stability under large disturbances. The methodology is validated in a simulation environment using the New England 68-bus, 16-machine test system. Scenarios with levels of renewable penetration (5%, 10%, 15%, and 20%) are analyzed by modifying the system’s transient stability. Results show that modal patterns allow a robust evaluation of the event severity. The methodology qualitatively and quantitatively measures the impact on the system stability, supporting the efficient interpretation of large datasets and providing valuable insights for systems with increasing renewable energy sources.