Work

Data-driven decision making for enhancing small-signal stability in hybrid AC/DC grids through converter control role assignment

Year: 2025

Type: article

Abstract: Hybrid AC/DC transmission grids incorporate High-Voltage Direct-Current links, enabled by the presence of Interconnecting Power Converters (IPCs). The control role assigned to each IPC significantly influences grid dynamics. Traditionally, these converters operate with static control roles, but recent studies have proposed scheduling their roles based on day-ahead forecasts to enhance stability performance. However, in systems with high renewable energy penetration, forecast deviations can render scheduled control assignments suboptimal or even lead to instability. To address this challenge, this work proposes an online scheduling recalculation algorithm that dynamically adapts IPC control roles during system operation. The approach leverages a data-driven multi-criteria decision-making framework, integrating surrogate models of conventional small-signal stability analysis tools to enable a fast computation of system stability and stability performance indicators. • Data-driven MCDM algorithm for IPC control, improving hybrid AC/DC grid stability. • Methodology to train ML surrogate models for fast stability assessment and performance estimation. • Scalablility enhancement via data mining, clustering, and set intersection.

Source: International Journal of Electrical Power & Energy Systems

DOI: 10.1016/j.ijepes.2025.110938

Authors: Francesca Rossi, Sergi Costa Dilmé, Josep Arévalo-Soler, Eduardo Prieto-Araujo, Oriol Gomis-Bellmunt

Institution: Universitat Politècnica de Catalunya

Language: English

Topic: Power System Optimization and Stability

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Affordable and clean energy, Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $3,920