Abstract
New wind turbines are becoming more complex and reliability analysis of them rising in complexity. The systems are composed of many components. Fault tree is used as an useful tool to analyze these interrelations and provide a scheme of the wind turbine, to get a quick overview of the behavior of the system under certain conditions of the components. However, it is complicated and in some cases not possible, to identify the conditions that would generate a wind turbine failure. A quantitative and qualitative reliability analysis of the wind turbine is proposed in this study. Binary decision diagrams are employed as a suitable and operational method to facilitate this analysis and to get an analytical expression by the Boolean functions. The size of the binary decision diagram, i.e., the computational cost for solving the problem, has an important dependence on the order of the components or events considered. Different heuristic ranking methods are used to find an optimal order or one closed, and to validate the results: AND, level, top-down-left-right, deep-first search and breadth-first-search. Birnbaum and criticality importance measures are proposed to evaluate the relevance of each component. This analysis leads to classify the events according to their importance with respect to the probability of the top event. This analysis provides the basis for making medium and long-term maintenance strategies.
Highlights
Wind energy is one of the fasting-growing renewable energies because of the new wind turbines (WT), becoming higher and more complex, i.e., with more power electric generation [1]
This optimizes the time employed on maintenance, additional costs to maintenance and equipment researches are based on the detection and reduction of WTs false alarms by different advanced anareliability [25,26,27]
The top event analysis is done by quantitative evaluation, where the main methods can be classified as direct evaluation methods and methods based on the use of prime implicant (PI) sets
Summary
Wind energy is one of the fasting-growing renewable energies because of the new wind turbines (WT), becoming higher and more complex, i.e., with more power electric generation [1]. Njiri and Soeffker [6] showed that WTs are employing new designs, electronic, materials, elecconditions—together with the complexity of the WTs—drives maintenance operations to become trical, mechanical and control systems This is leading to increased production capacity and improved complicated [14]. This optimizes the time employed on maintenance, additional costs to maintenance and equipment researches are based on the detection and reduction of WTs false alarms by different advanced anareliability [25,26,27]. Many of these tasks involve the replacement of certain components due to the lytics [22,23].
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