Abstract
Operation and maintenance (O&M) costs, and associated uncertainty, for wind turbines (WTs) is a significant burden for wind farm operators. Many wind turbine failures are unpredictable while causing loss of energy production, and may also cause loss of asset. This study utilized 753 O&M event data from 21 wind turbines operating in Germany, to improve the prediction of failure frequency and associated costs. We applied Bayesian updating to predict wind turbine failure frequency and time-to-repair (TTR), in conjunction to machine learning techniques for assessing costs associated with failures. We found that time-to-failure (TTF), time-to-repair and the cost of failures depend on operational and environmental conditions. High elevation (>100 m) of the wind turbine installation was found to increase both the probability of failures and probability of delayed repairs. Furthermore, it was determined that direct-drive turbines are more favorable at locations with high capacity factor (more than 40%) whereas geared-drive turbines show lower failure costs than direct-drive ones at temperate-coastal locations with medium capacity factors (between 20% and 40%). Based on these findings, we developed a decision support tool that can guide a site-specific selection of wind turbine types, while providing a thorough estimation of O&M budgets.
Highlights
Operation and maintenance (O&M) of wind turbines (WTs) can be a burden to wind farm operators.Many failures of wind turbines are unpredictable, and the uncertainty presents risks of loss of energy production, loss of asset and lacking O&M monetary budget
In an effort to better elucidate O&M risks and burdens, we recently investigated the impact of climatic region and turbine gear type by using Failure Modes Effects and Criticality Analysis (FMECA)
This study study presents presents applications applications of of two two reliability reliability prediction prediction approaches: approaches: The
Summary
Operation and maintenance (O&M) of wind turbines (WTs) can be a burden to wind farm operators. Many failures of wind turbines are unpredictable, and the uncertainty presents risks of loss of energy production, loss of asset and lacking O&M monetary budget. The corresponding total, during a 20 years-lifetime, O&M costs were around 2$M and 14.8$M for the onshore and the offshore wind turbine, respectively [1]. This was in addition to the cost for lost energy production during the failure and maintenance periods. Proactive maintenance is expected to decrease downtime and the cost of failure but the extent and frequency of needed maintenance is debatable [2,3]
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