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Reliability assessment method of wind power DC collection system based on MLFTA-SMC
Xueyan Bai1, Yanfang Fan2, Junjie Hou1
1School of Electrical Engineering, Xinjiang University, Urumqi, 830000, China.
Scientific Reports
|October 25, 2024
Summary
This study introduces a new method for assessing the reliability of wind power DC collection systems using multi-level fault tree analysis and state-space model checking (MLFTA-SMC). The proposed approach enhances the safety and stability of wind farm operations.
Area of Science:
- Electrical Engineering
- Renewable Energy Systems
- System Reliability
Background:
- Wind power DC collection systems are critical for wind farm operation.
- Assessing the reliability of these systems is essential for stable energy generation.
- Existing methods may not fully capture the complexities of these systems.
Purpose of the Study:
- To propose a novel reliability assessment method for wind power DC collection systems.
- To enhance the safety and stable operation of wind farms.
- To provide a superior approach for evaluating system reliability.
Main Methods:
- Analysis of wind power DC collection system topology and key equipment.
- Construction of multi-level fault tree models for event importance calculation.
- Application of the MLFTA-SMC method for reliability assessment.
Main Results:
- The proposed MLFTA-SMC method effectively assesses the reliability of different DC collection system topologies.
- Comprehensive importance of various events was calculated using fault tree models.
- Simulation on a 100 MW wind farm validated the method's effectiveness.
Conclusions:
- The MLFTA-SMC method demonstrates significant effectiveness and superiority for wind power DC collection system reliability assessment.
- The findings support improved operational safety and stability in wind farms.
- This method provides a robust framework for future reliability studies in renewable energy systems.
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