Paper
Spatial Characterization of Sub-Synchronous Oscillations Using Black-Box IBR Models
Authors
Muhammad Sharjeel Javaid, Gabriel Covarrubias Maureira, Ambuj Gupta, Debraj Bhattacharjee, Jianli Gao, Balarko Chaudhuri, Mark O'Malley
Abstract
Power systems with high penetration of inverter-based resources (IBRs) are prone to sub-synchronous oscillations (SSO). The opaqueness of vendor-specific IBR models limits the ability to predict the severity and the spread of SSO. This paper demonstrates that black-box IBR models estimated through frequency-domain identification techniques, along with dynamic network model can replicate the actual oscillatory behavior. The estimated IBR models are validated against actual IBR models in a closed-loop multi-IBR test system through modal analysis by comparing closed-loop eigenvalues, and participation factors. Furthermore, using output-observable right eigenvectors, spatial heatmaps are developed to visualize the spread and severity of dominant SSO modes. The case studies on the 11-bus and 39-bus test systems confirm that even with the estimated IBR models, the regions susceptible to SSO can be identified in IBR-dominated power systems.
Metadata
Related papers
Fractal universe and quantum gravity made simple
Fabio Briscese, Gianluca Calcagni • 2026-03-25
POLY-SIM: Polyglot Speaker Identification with Missing Modality Grand Challenge 2026 Evaluation Plan
Marta Moscati, Muhammad Saad Saeed, Marina Zanoni, Mubashir Noman, Rohan Kuma... • 2026-03-25
LensWalk: Agentic Video Understanding by Planning How You See in Videos
Keliang Li, Yansong Li, Hongze Shen, Mengdi Liu, Hong Chang, Shiguang Shan • 2026-03-25
Orientation Reconstruction of Proteins using Coulomb Explosions
Tomas André, Alfredo Bellisario, Nicusor Timneanu, Carl Caleman • 2026-03-25
The role of spatial context and multitask learning in the detection of organic and conventional farming systems based on Sentinel-2 time series
Jan Hemmerling, Marcel Schwieder, Philippe Rufin, Leon-Friedrich Thomas, Mire... • 2026-03-25
Raw Data (Debug)
{
"raw_xml": "<entry>\n <id>http://arxiv.org/abs/2603.15399v1</id>\n <title>Spatial Characterization of Sub-Synchronous Oscillations Using Black-Box IBR Models</title>\n <updated>2026-03-16T15:15:22Z</updated>\n <link href='https://arxiv.org/abs/2603.15399v1' rel='alternate' type='text/html'/>\n <link href='https://arxiv.org/pdf/2603.15399v1' rel='related' title='pdf' type='application/pdf'/>\n <summary>Power systems with high penetration of inverter-based resources (IBRs) are prone to sub-synchronous oscillations (SSO). The opaqueness of vendor-specific IBR models limits the ability to predict the severity and the spread of SSO. This paper demonstrates that black-box IBR models estimated through frequency-domain identification techniques, along with dynamic network model can replicate the actual oscillatory behavior. The estimated IBR models are validated against actual IBR models in a closed-loop multi-IBR test system through modal analysis by comparing closed-loop eigenvalues, and participation factors. Furthermore, using output-observable right eigenvectors, spatial heatmaps are developed to visualize the spread and severity of dominant SSO modes. The case studies on the 11-bus and 39-bus test systems confirm that even with the estimated IBR models, the regions susceptible to SSO can be identified in IBR-dominated power systems.</summary>\n <category scheme='http://arxiv.org/schemas/atom' term='eess.SY'/>\n <published>2026-03-16T15:15:22Z</published>\n <arxiv:comment>Accepted for IEEE PES General Meeting 2026, Montreal</arxiv:comment>\n <arxiv:primary_category term='eess.SY'/>\n <author>\n <name>Muhammad Sharjeel Javaid</name>\n </author>\n <author>\n <name>Gabriel Covarrubias Maureira</name>\n </author>\n <author>\n <name>Ambuj Gupta</name>\n </author>\n <author>\n <name>Debraj Bhattacharjee</name>\n </author>\n <author>\n <name>Jianli Gao</name>\n </author>\n <author>\n <name>Balarko Chaudhuri</name>\n </author>\n <author>\n <name>Mark O'Malley</name>\n </author>\n </entry>"
}