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An Importance Analysis–Based Weight Evaluation Framework for Identifying Key Components of Multi-Configuration Off-Grid Wind Power Generation Systems under Stochastic Data Inputs

Author

Listed:
  • Lingling Bin

    (State Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University, Tianjin 300072, China)

  • Haiyang Pan

    (School of Renewable Energy, North China Electric Power University, Beijing 102206, China)

  • Li He

    (State Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University, Tianjin 300072, China)

  • Jijian Lian

    (State Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University, Tianjin 300072, China)

Abstract

Wind power systems have great potential due to its inexhaustible nature and benign environmental impacts. Especially in remote areas, where wind is plentiful, but it is difficult to get grid-connected power, an off-grid wind power system is an effective alternative for power supply. Reliable and safe operation of the generating system are essential for electricity production and supply. Importance analysis to identify key components of the system is a critical part of reliability assessment. This paper proposes an importance analysis–based weight evaluation framework for identifying key components of multi-configuration off-grid wind power generation systems under stochastic inputs. In the framework, the joint importance analysis based on Birnbaum importance and Criticality importance are introduced to analyze the system reliability and failure rate. Wind speed with stochastic characteristics, load demand with multiple scenarios, and energy transfer with different paths are also merged into the evaluation framework. The results reveal that the rectifier, battery, discharge load, and valve controller dominate the reliability of the off-grid wind power generation system. High priority should be placed on these components during the design phase and maintenance stage. The proposed approach is a positive step forward in promoting component importance analysis and providing more theoretical supports in system design, reliability analysis, and monitoring scheme formulation.

Suggested Citation

  • Lingling Bin & Haiyang Pan & Li He & Jijian Lian, 2019. "An Importance Analysis–Based Weight Evaluation Framework for Identifying Key Components of Multi-Configuration Off-Grid Wind Power Generation Systems under Stochastic Data Inputs," Energies, MDPI, vol. 12(22), pages 1-22, November.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:22:p:4372-:d:287857
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    Cited by:

    1. Artur Łukaszewski & Łukasz Nogal & Sylwester Robak, 2020. "Weight Calculation Alternative Methods in Prime’s Algorithm Dedicated for Power System Restoration Strategies," Energies, MDPI, vol. 13(22), pages 1-20, November.
    2. Hongyan Dui & Xiaoqian Zheng & Jianjun Guo & Hui Xiao, 2022. "Importance measure-based resilience analysis of a wind power generation system," Journal of Risk and Reliability, , vol. 236(3), pages 395-405, June.

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