1. Reliability assessment of wind turbine generators by fuzzy universal generating function
- Author
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Tangfan Xiahou, Tudi Huang, Hong-Zhong Huang, Hua-Ming Qian, Yan-Feng Li, and Yu Liu
- Subjects
021103 operations research ,Universal generating function ,Computer science ,0211 other engineering and technologies ,0202 electrical engineering, electronic engineering, information engineering ,020201 artificial intelligence & image processing ,02 engineering and technology ,Safety, Risk, Reliability and Quality ,Turbine ,Fuzzy logic ,Industrial and Manufacturing Engineering ,Reliability (statistics) ,Reliability engineering - Abstract
Wind power has been widely used in the past decade because of its safety and cleanness. Double fed induction generator (DFIG), as one of the most popular wind turbine generators, suffers from degradation. Therefore, reliability assessment for this type of generator is of great significance. The DFIG can be characterized as a multi-state system (MSS) whose components have more than two states. However, due to the limited data and/or vague judgments from experts, it is difficult to obtain the accurate values of the states and thus it inevitably contains epistemic uncertainty. In this paper, the fuzzy universal generating function (FUGF) method is utilized to conduct the reliability assessment of the DFIG by describing the states using fuzzy numbers. First, the fuzzy states of the DFIG system’s components are defined and the entire system state is calculated based the system structure function. Second, all components’ states are determined as triangular fuzzy numbers (TFN) according to experts’ experiences. Finally, the reliability assessment of the DFIG based on the FUGF is conducted.
- Published
- 2021