Abstract
In DC shipboard power systems (DC-SPS), the enhanced network complexity and high penetration of power electronic devices make the system level reliability a critical design aspect. This paper proposes a stochastic framework for the reliability assessment of DC-SPSs based on a three-stage Monte Carlo (MC) simulation, including component failure sampling, active fault propagation, and reliability index calculation. The proposed MC framework is verified for a simplified meshed DC grid through comparison with an analytical method. Later, the advantages of the MC method are demonstrated for a dynamic positioning vessel equipped with a ring-type DC power system architecture. The results quantify the impact of redundancy on the reliability of a DC-SPS, show the spread in the subsystem repair times, and reveal the system's availability during both the initialization and steady-state. Combined, the simulation results reveal the strengths and weaknesses of the designed grid, guiding the focus for future reliability enhancements.
Original language | English |
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Title of host publication | Proceedings of the 2024 IEEE Sixth International Conference on DC Microgrids (ICDCM) |
Publisher | IEEE |
Number of pages | 7 |
ISBN (Electronic) | 979-8-3503-6363-0 |
ISBN (Print) | 979-8-3503-6364-7 |
DOIs | |
Publication status | Published - 2024 |
Event | 6th IEEE International Conference on Direct Current Microgrids, ICDCM 2024 - Columbia, United States Duration: 5 Aug 2024 → 8 Aug 2024 |
Conference
Conference | 6th IEEE International Conference on Direct Current Microgrids, ICDCM 2024 |
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Country/Territory | United States |
City | Columbia |
Period | 5/08/24 → 8/08/24 |
Bibliographical note
Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-careOtherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.
Keywords
- DC grid
- Monte Carlo
- Reliability
- Shipboard power systems