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

Lingling Bin, Haiyang Pan, Li He and Jijian Lian
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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

Energies, 2019, vol. 12, issue 22, 1-22

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.

Keywords: importance analysis; off-grid wind power system; weight evaluation; Birnbaum importance (BI); Criticality importance (CI) (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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