A Dynamic Asymmetric Overcurrent-Limiting Strategy for Grid-Forming Modular Multilevel Converters Considering Multiple Physical Constraints
Year: 2025
Type: article
Abstract: Grid-forming (GFM) converters are promising for renewable energy integration, but their overcurrent limitation during grid faults remains a critical challenge. Existing overcurrent-limiting strategies were primarily developed for two-level converters and are often inadequate for Modular Multilevel Converters (MMCs). By overlooking the MMC’s unique topology and internal physical constraints, these conventional methods compromise both operational safety and grid support capabilities. Thus, this paper proposes a dynamic asymmetric overcurrent-limiting strategy for grid-forming MMCs that considers multiple physical constraints. The proposed strategy establishes a dynamic asymmetric overcurrent boundary based on three core physical constraints: capacitor voltage ripple, capacitor voltage peak, and the modulation signal. This boundary accurately defines the converter’s true safe operating area under arbitrary operating conditions. To address the complexity of the boundary’s analytical form for real-time application, an offline-trained neural network is introduced as a high-precision function approximator to efficiently and accurately reproduce this dynamic asymmetric boundary. The effectiveness of the proposed strategy is verified by hardware-in-the-loop experiments. Experimental results demonstrate that the proposed strategy reduces the capacitor voltage ripple by 30.7% and maintains the modulation signal safely within the linear range, significantly enhancing both system safety and fault ride-through performance.
Source: Symmetry
DOI: 10.3390/sym18010053
Institutions: State Grid Corporation of China (China), Zhejiang University
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,896
Funder: State Grid Corporation of China
OpenAlex ID: W7117455317