Fleet-level opportunistic maintenance for large-scale wind farms integrating real-time prognostic updating

Operation and maintenance (O&M) of wind farms has become progressively more important for renewable energy. The key challenge is that each modern large-scale wind farm normally consists of many wind turbines in parallel, while each complex turbine also contains diverse series of components. Traditional maintenance policies cannot handle such a complex system, let alone that each individual component undergoes different degradations. To reduce the scheduling complexity and maintenance cost, a fleet maintenance cost saving (FMCS) policy is developed to optimize condition-based opportunistic maintenance. Real-time condition data for each component is utilized to update its failure prognostic for avoiding the individual variation in the degradation process. On this basis, the whole wind farm is constructed as a fleet structure with series-parallel components. Power production loss within the same turbine and repeated personnel dispatch among other parallel turbines are analyzed to reduce the total maintenance cost efficiently. Through the case study, the framework with real-time prognostic updating and FMCS scheduling policy in component/fleet levels has been proven its economic advantages for future large-scale wind farms.