Research on the Impact of Redundancy Configuration and Opportunistic Maintenance on the Reliability of Ultra-High Voltage Flexible Direct Current Transmission Systems
DOI:
https://doi.org/10.4108/ew.13559Keywords:
Reliability evaluation, state duration sampling, Ultra-High Voltage Flexible Direct Current transmission systems, opportunistic maintenance, Standby strategy, Digital twin foundationAbstract
INTRODUCTION: Ultra-High Voltage Flexible Direct Current (UHVDC-F) transmission systems have become the preferred choice for long-distance power transmission due to their superior control flexibility and power quality, with their reliability directly determining regional grid stability.
OBJECTIVES: To ensure stable operation, it is essential to evaluate system reliability, quantify the enhancement effects of redundant components, and identify critical system vulnerabilities.
METHODS: This paper proposes an evaluation framework considering diverse redundancy schemes. For component-level redundancy, a state transition model incorporating spare resource constraints is developed. For sub-module level redundancy, an opportunistic maintenance strategy is introduced. The framework utilizes sequential Monte Carlo simulation to accurately capture the stochastic evolution and dynamic transitions of the system.
RESULTS: Results indicate that converter transformer redundancy most significantly boosts overall reliability. Furthermore, opportunistic maintenance for converter valves effectively mitigates degraded operation risks and extends the Mean Time Between Failures.
CONCLUSION: This research establishes a high-fidelity digital twin foundation for complex UHVDC-F operational states. Beyond enhancing assessment accuracy, these quantitative matrices can be seamlessly integrated into AI-driven asset management and cost optimization engines, transforming risk evaluation into active O&M economic scheduling to fortify large-scale grid resilience.
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Copyright (c) 2026 Kaixin Wu, Shilong Gao, Jinhua Dai; Yong Yang; Wanxin Feng, Shaogang Du, Yu Yu
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