Assessment of Wind Turbine Reliability Using Block Diagram Model

Document Type : Original Article

Authors

1 Assistant Professor, Faculty of New Sciences and Technologies, University of Tehran, Tehran, Iran

2 Master’s student, Department of Renewable Energy and Environment, Faculty of New Sciences and Technologies, University of Tehran, Iran

3 PhD student, Department of Renewable Energy and Environment, Faculty of New Sciences and Technologies, University of Tehran, Iran

Abstract

Reliability assessment of renewable energy systems is a key step in evaluating the feasibility of renewable energy projects. The assessment can provide valuable information on the availability and reliability, operation and maintenance strategies, and operating costs of systems. In this regard, the present study analyzes the reliability parameters of a wind turbine system using a statistical / simulation approach. To this end, the Reliability block diagram has been used for modeling the problem which has the capability of analyzing complex systems with a high number of components while providing simplicity and transparency in the concept presentation. For the modeling and simulation, RAM Commander software developed by ALD software company was utilized. The block diagram model was developed considering a series arrangement (8 subsystems and 94 components) and taking into account the probability distributions of failure time, repair time, and other reliability data for each block. results were then obtained by implementing the Monte Carlo algorithm. The results of this study contain the values of reliability, availability, and failure rate for a turbine during its lifetime. According to the results, the average availability of a turbine over a 20-year life span was more than 0.999. At 25 points, the turbine needed repairs, and the mean time between failures was calculated to be 7008 hours. The mean time between system critical (catastrophic) failures is 77928 hours. Also, the sensitivity analysis of the model to changing input variables is presented.

Keywords

References

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History

  • Receive Date: 28 August 2020
  • Revise Date: 06 October 2020
  • Accept Date: 17 May 2021

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