Measurement-Aware Frequency Support in DFIG-Based Low-Inertia Systems Under Variable Load Profiles

Converter-interfaced wind generation reduces the effective inertial response of modern power systems and makes frequency dynamics more sensitive to load variability, measurement processing, and support-control tuning. This paper proposes a data-driven and measurement-aware framework to evaluate frequency support in a low-inertia system with doubly fed induction generator-based wind generation. Measured load and wind-speed data are converted into a reproducible scenario library and evaluated with an aggregated frequency model including droop support, synthetic inertia, reserve limitation, filtering, delay, and rate of change of frequency estimation. Results show that unsupported operation produces the largest frequency degradation, with a median nadir-point deviation of 2.208 Hz, while conventional droop reduces it to 0.714 Hz. Droop plus inertia and the proposed robust setting reduce this value to 0.493 Hz and 0.502 Hz, respectively, indicating comparable performance under the selected measurement- ware assessment, with a median rate of change of frequency close to 0.040 Hz/s. The load-model analysis shows that frequency-dependent load behavior changes the final frequency deviation, reducing it from 0.329 Hz to 0.318 Hz in the tested cases.