Abstract
Among the different maintenance techniques applied to wind turbine (WT) components, online condition monitoring is probably the most promising technique. The maintenance models based on online condition monitoring have been examined in many studies. However, no study has considered preventive maintenance models with incorporated probabilities of correct and incorrect decisions made during continuous condition monitoring. This article presents a mathematical model of preventive maintenance, with imperfect continuous condition monitoring of the WT components. For the first time, the article introduces generalized expressions for calculating the interval probabilities of false positive, true positive, false negative, and true negative when continuously monitoring the condition of a WT component. Mathematical equations that allow for calculating the expected cost of maintenance per unit of time and the average lifetime maintenance cost are derived for an arbitrary distribution of time to degradation failure. A numerical example of WT blades maintenance illustrates that preventive maintenance with online condition monitoring reduces the average lifetime maintenance cost by 11.8 times, as compared to corrective maintenance, and by at least 4.2 and 2.6 times, compared with predetermined preventive maintenance for low and high crack initiation rates, respectively.
Highlights
There is a global transformation of energy production toward renewable energy sources, and wind power is a source that is developing at the highest rate
This article has proposed a new approach to optimizing preventive maintenance with online condition monitoring, which assumes that the built-in sensors are error-prone and based on the information they provide, incorrect decisions when determining the condition of the wind turbine (WT) component are possible
A mathematical model has been proposed to evaluate the probabilities of correct and incorrect decisions made on the results of continuous condition monitoring the deteriorating components of WT
Summary
There is a global transformation of energy production toward renewable energy sources, and wind power is a source that is developing at the highest rate. Wind power developed most rapidly in China and the United States, adding 21 GW and. 7.6 GW in 2018, reaching 217 GW and 96 GW, respectively [1] With such rapid growth of wind energy production, special attention is given to the lowered cost of 1 kWh of produced energy. According to IRENA [2], 1 kWh of energy produced by an offshore WT has decreased from 0.17 USD/kWh in 2010 to 0.14 USD/kWh in 2017. A significant reduction in the cost of produced wind energy can be achieved by reducing the cost of operation and maintenance (O&M).
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