Abstract

The failure of wind turbines is a multi-faceted problem and its monetary impact is often unpredictable. In this study, we present a novel application of survival analysis on wind turbine reliability, including accounting for previous failures and the history of scheduled maintenance. We investigated the operational, climatic and geographical factors that affect wind turbine failure and modeled the risk rate of wind turbine failure based on data from 109 turbines in Germany operating for a period of 19 years. Our analysis showed that adequately scheduled maintenance can increase the survival of wind turbine systems and electric subsystems up to 2.8 and 3.8 times, respectively, compared to the systems without scheduled maintenance. Geared-drive wind turbines and their electrical systems were observed to have 1.2- and 1.4- times higher survival, respectively, compared to direct-drive turbines and their electrical systems. It was also found that the survival of frequently-failing wind turbine components, such as switches, was worse in geared-drive than in direct-drive wind turbines. We show that survival analysis is a useful tool to guide the reduction of the operating and maintenance costs of wind turbines.

Highlights

  • Wind energy is being deployed increasingly and its global capacity has doubled over the last six years [1]

  • Our aim is to the investigate factors that impact on wind turbine survival and inform the actions that need to be taken to reduce the potential for failures

  • We identified the probability of failure of a wind turbine at a certain time using the Kaplan–Meier estimator [24] and estimated the cumulative hazard using a Nelson–Aalen estimator [25], while comparing the survival of separate groups of wind turbines by applying statistical tests such as a log-rank test [26], which will be explained

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Summary

Introduction

Wind energy is being deployed increasingly and its global capacity has doubled over the last six years [1]. The availability of wind turbines has reached 98% level in European wind farms [2], improvements of reliability are still needed. The problem is two-fold, one is the high operation and maintenance (O&M) cost, the other is the lost energy production. Wind turbines are monitored during scheduled maintenances and/or by condition monitoring systems to sustain uninterrupted energy production and to avoid high O&M costs. The scheduled maintenance included visual inspection, non-destructive testing methods such as ultrasound and acoustic emissions, and oil level testing and vibration analysis, while condition monitoring systems consist of pressure, heat and vibration sensors [3,4]. Wind farm operators need to develop either new techniques or new decision support tools for their O&M strategies in order to reach the goal of maximizing energy production while minimizing O&M costs

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