337-26

Automatic Tuning of Operator-Supplied Dynamic Models in PSS®E Based on Real-Plant Measurements

M. Lozano Deiros, D. Marquina Cordero, D. M. Rivas Ascaso

CIRCE – Technology Center, Parque Empresarial Dinamiza, Zaragoza (Spain).

2026-06-27

Transmission system operators require dynamic models calibrated to match real plant behavior, yet tuning is often manual, slow, and difficult to reproduce. This paper presents a fully automated calibration framework for renewable generation models based on Differential Evolution algorithms (DE), particularly Differential Evolution [1], implemented through the PSS®E Python API [2]. The calibration is formulated as a bounded nonlinear time-domain optimization problem in which candidate parameter sets are iteratively evaluated via dynamic simulations and compared against field measurements. The methodology is demonstrated on REE’s PPMREE5 module by tuning a set of 15 parameters selected for their impact on the frequency-response behavior. Using active-power frequency response tests under over- and under-frequency events, the proposed approach improves the agreement between simulated and measured responses and accurately reproduces both transient and steady-state behavior. The results show that the framework provides a systematic, reproducible and scalable alternative to manual tuning for renewable plant model validation.

Key words: Dynamic Model Calibration, Power System Dynamics, PSSE, Genetic Algorithms, Grid Code Compliance

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