Search arXiv⌕ Search
Home/Archive/arXiv

arXiv · 2608.07174

Stability Enhancement in Weak Grids with High Renewable Penetration: Synchronous Condenser vs. Converter-based Technologies

Rasool Heydari·Prabhat Ranjan Bana·Jean Philippe Hasler·Anders Bostrom·Mikael Halonen
View original source ↗Read source document ↗Export metadata ↓

Abstract

Integrating renewable energy sources into weak grids presents significant challenges for maintaining grid stability. Several essential services are required to ensure a stable and secure grid, including voltage support, fault current injection, system strength support, frequency control, and inertia support. Synchronous condensers, with their inherent inertia and fault current capabilities, have been traditional solutions for grid stability. Recent advancements in power electronics and control structures have led to the development of various technologies aimed at enhancing power grid stability. Static synchronous compensators (STATCOM) and Enhanced STATCOM, which can provide active and reactive power support, show considerable promise. These technologies offer grid-forming (GFM) capabilities that can significantly improve the stability of weak grids with high renewable penetration. Advancements in STATCOM and E-STATCOM technologies offer enhanced control tunability, controllable damping, and immediate response to grid perturbations. This paper investigates the comparative performance of synchronous condensers versus STATCOM and Enhanced STATCOM with grid-forming capability in providing services and enhancing the stability of weak grids with high renewable penetration.

Explore related subjects

eess.SYcs.SY

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Rasool Heydari, Prabhat Ranjan Bana, Jean Philippe Hasler, Anders Bostrom, Mikael Halonen. 2026-08-07. Stability Enhancement in Weak Grids with High Renewable Penetration: Synchronous Condenser vs. Converter-based Technologies. https://arxiv.org/abs/2608.07174

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↗