Identification of Sub/Super-Synchronous Control Interaction Paths Using Dissipative Energy Flow

Kaustav Chatterjee; Sameer Nekkalapu; Sayak Mukherjee; Ramij Raja Hossain; Marcelo Elizondo

Home/Archive/arXiv

arXiv · 2508.11561

Identification of Sub/Super-Synchronous Control Interaction Paths Using Dissipative Energy Flow

Kaustav Chatterjee·Sameer Nekkalapu·Sayak Mukherjee·Ramij Raja Hossain·Marcelo Elizondo

View original source ↗Read source document ↗Export metadata ↓

Abstract

Sub- and super-synchronous control interactions (SSCIs) are oscillations arising from adverse interactions between inverter-based resource (IBR) controls and the power network. SSCIs often involve multiple frequencies and propagate through complex, interconnected paths, making it difficult for model-based approaches to identify both the sources and the paths of oscillatory energy flow. This paper extends the Dissipative Energy Flow (DEF) method, originally developed for low-frequency electromechanical oscillations, to identify SSCI sources and dynamic interaction paths across multiple frequencies using three-phase voltage and current measurements. The approach operates in the dq frame using dynamic phasors, enabling mode-specific DEF computation from bandpass-filtered signals. An electromagnetic transient (EMT) case study on a meshed network with synchronous generator and type-3 wind farm resources under series-compensated conditions demonstrates the method's capability to distinguish frequency-dependent source and sink roles, including cases where the same resource acts as a source at one frequency and a sink at another. The results show DEF can provide a physics-based and automation-friendly tool for SSCI diagnosis in IBR-rich grids.

Explore related subjects

eess.SY cs.SY

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

Kaustav Chatterjee, Sameer Nekkalapu, Sayak Mukherjee, Ramij Raja Hossain, Marcelo Elizondo. 2025-08-15. Identification of Sub/Super-Synchronous Control Interaction Paths Using Dissipative Energy Flow. https://arxiv.org/abs/2508.11561

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

arXiv2026

Observability and parameter estimation of a generic model for aggregated distributed energy resources

We propose a novel framework for estimating the parameters of an aggregated distributed energy resources (DER A) model. First, we introduce a rigorous method to determine whether all model parameters are estimable. When they are not, our approach identifies the subset of parameters that can be estimated. The proposed framework offers new insights into the number and specific parameters that can be reliably estimated based on commonly available measurements. It also highlights the limitations of calibrating such models. Second, we introduce a Kalman filtering method to calibrate the DER A model. Since we account for nonlinear effects such as saturation and deadbands, we develop a specific mechanism to handle smoothing functions within the Kalman filter. Specifically, we consider the extended and the unscented Kalman filter. We demonstrate the effectiveness of the proposed framework on a modified IEEE 34-node distribution feeder with inverter- based resources. Our findings align with the North American Electric Reliability Corporation's parameterization guideline and underscore the importance of model calibration in accurately capturing the collective dynamics of distributed energy resources installed on distribution systems.

eess.SY↗

arXiv2026

Salted Fisher Information for Hybrid Systems

Discrete events change how parameter-influence propagates in hybrid systems. Prevailing Fisher information for- mulations assume that sensitivities evolve smoothly according to continuous-time variational equations and therefore neglect the sensitivity updates induced by discrete events. This paper derives a Fisher information matrix formulation compatible with hybrid systems. To do so, we use the saltation matrix, which encodes the first-order transformation of sensitivities induced by discrete events. We call the resulting formulation the salted Fisher information matrix (SFIM). The proposed framework unifies continuous information accumulation during flows with discrete updates at event times. We also show that hybrid persistence of excitation is sufficient for the SFIM to be positive definite

eess.SY↗

arXiv2026

Min-Max Grassmannian Optimization for Online Subspace Tracking

We propose GeRoST (Geometrically Robust Subspace Tracking), an online subspace tracking algorithm that models uncertainty in a subspace using a Grassmannian ball. We derive an exact scalar dual for the worst-case subspace problem, establish conditions for a unique worst-case subspace and a Riemannian gradient, and characterize the minimum radius needed to cover a dimensional extension of the target subspace. Each update uses either a spectral direction computed in a reduced subspace or the gradient of the window reconstruction loss. Our numerical experiments show that GeRoST achieves lower mean post-fault prediction error than GREAT in system identification. In video separation, it achieves higher precision and a better precision--recall balance, as measured by the F$_1$ score, than both GREAT and GRASTA at the reported thresholds, with lower recall and longer runtime.

eess.SY↗