Abstract
Failure mode and effects analysis (FMEA) has been extensively used by wind turbine assembly manufacturers for analyzing, evaluating and prioritizing potential/known failure modes. However, several limitations are associated with its practical implementation in wind farms. First, the Risk-Priority-Number (RPN) of a wind turbine system is not informative enough for wind farm managers from the perspective of criticality; second, there are variety of wind turbines with different structures and hence, it is not correct to compare the RPN values of different wind turbines with each other for prioritization purposes; and lastly, some important economical aspects such as power production losses, and the costs of logistics and transportation are not taken into account in the RPN value. In order to overcome these drawbacks, we develop a mathematical tool for risk and failure mode analysis of wind turbine systems (both onshore and offshore) by integrating the aspects of traditional FMEA and some economic considerations. Then, a quantitative comparative study is carried out using the traditional and the proposed FMEA methodologies on two same type of onshore and offshore wind turbine systems. The results show that the both systems face many of the same risks, however there are some main differences worth considering.
Highlights
Wind energy has become an attractive source of renewable energy, and its installed capacity worldwide has grown significantly in recent years
We developed a new tool for risk and failure mode analysis of wind turbine systems by integrating the aspects of traditional Failure mode and effects analysis (FMEA) and some economic considerations
The traditional FMEA methodology is based on the risk-priority-number (RPN) index which is calculated by multiplying the occurrence (O), severity (S), and detection (D) of a failure
Summary
Wind energy has become an attractive source of renewable energy, and its installed capacity worldwide has grown significantly in recent years. The traditional FMEA methodology has been extensively used by wind turbine assembly manufacturers for analyzing, evaluating and prioritizing the potential/known failure modes [11]. In order to overcome these drawbacks, we extend our works in [15,19], and develop a mathematical tool for risk and failure mode analysis of wind turbine systems (both the onshore and offshore) based on three main factors: failure probability, incurred failure costs, and the fault detection possibility. Our results show that the proposed methodology can have a high potential to improve the safety as well as mitigate the operational risks associated with an unexpected failure within the wind farms (i.e., costly repair or replacement, lack of spare parts, transportation means and manpower, and loss of power production).
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