Luis A. Garcia-Reyes

Nicolae Darii, Luis A. Garcia-Reyes, Ignasi Ventura Nadal et al.

This paper introduces a systematic gray-box identification framework for voltage-source converter models based solely on terminal time-series data. The proposed approach combines a physically informed white-box standard model with iterative time-domain calibration to estimate controller parameters that mimic the behavior of the black-box model in electromagnetic transient (EMT) simulations. Unlike conventional frequency-domain identification methods, the framework leverages time-domain data more effectively to better constrain the surrogate model across a broader operating range and capture reference-signal dynamics. To evaluate the accuracy of the identified model, the paper presents additional frequency-domain validation metrics based on Nyquist analysis and singular value decomposition, allowing for both quantitative assessment of model divergence and qualitative classification of mismatch types. The methodology is tested on cases with increasing structural uncertainty, from exact parametric recovery to an actual detailed EMT black-box model. Results demonstrate that the proposed framework can accurately recover parameters when the internal structure is known, adjust for moderate structural mismatch with extra degrees of freedom, and offer a reliability measure for small-signal stability analysis of converter models protected by intellectual property

Luis A. Garcia-Reyes, Josep Arévalo-Soler, Oriol Gomis-Bellmunt et al.

Modern power systems increasingly rely on power electronic converters, yet many of these devices are provided as black-box models, limiting the applicability of conventional small-signal analysis (SSA) tools. This work presents a unified multi-variable fitted state-space (SSA-FITSS) methodology that enables accurate small-signal modeling of black-box Voltage Source Converters (VSCs) using frequency-domain (FD) identification, adaptive pole-expansion, and reduced-order realization. The method includes an automated state-interpretation strategy that assigns fitted states to representative control-loop categories based on their dominant frequency ranges, providing an approximate but meaningful physical interpretation of the identified dynamics. This capability allows extensive modal analysis, including eigenvalue sensitivities and participation factors, in systems where internal converter details are unavailable. The methodology is validated on a grid-following (GFL) VSC and applied to the New England system, which contains multiple black-box converters operating in both GFL and grid-forming (GFM) modes. Results show that the SSA-FITSS models accurately reproduce converter and system dynamics, support full eigenvalue-based analysis, and reveal stability limits under varying synchronous generation and GFL penetration levels. The approach overcomes key limitations of existing identification-based techniques by enabling scalable, interpretable, and system-wide stability assessment.