Search arXivSearch

arXiv · 2606.10589

Transient Stability of Offshore Energy Hubs

Abstract

Offshore energy hubs (OEHs) use grid-forming modular multilevel converters (MMCs) to enable large-scale offshore wind integration and multi-terminal HVDC operation. In HVDC-connected offshore wind farms and OEHs, the offshore grid-forming HVDC converters absorb active power from an offshore AC grid supplied by the wind farms and convert it to DC power for transmission to the onshore grid. Converter current limiting under different fault types in this setting is an understudied topic in the literature, which mostly focuses on power-injecting converters. This paper proposes a unified current-limiting strategy that combines a variable virtual impedance (VVI), based on a smooth threshold function, with a novel virtual-power (VP) mechanism derived from the power dissipated in the virtual resistance. The VVI ensures current limitation during fault-induced overcurrents while preserving voltage-source behavior, whereas the VP mechanism adds a compensating power term into the synchronization loop, enabling automatic power redistribution among converters. P-delta analysis further shows that a more resistive VVI can improve the transient stability of power-absorbing converters, while the proposed VP mechanism further enlarges the stability margin. EMT simulations validate that the combined VVI-VP strategy limits fault currents, maintains synchronism during severe faults, and achieves coordinated post-fault power sharing in fully converter-based OEHs.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Alban J. F. Duvivier, Dominic Groß, Daniel Müller, Nicolaos A. Cutululis. 2026-06-09. Transient Stability of Offshore Energy Hubs. https://arxiv.org/abs/2606.10589

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

KEEP EXPLORING

Related papers

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

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

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