Optimization of maintenance scheduling for offshore wind turbines considering the wake effect of arbitrary wind direction

An optimization model for offshore wind farm maintenance scheduling is presented, considering minimum maintenance costs and maximum power generation. For power generation, the wind speed at each tower site plays an important role that is impacted not only by the dynamically changing wake overlap area and the consequence of variation of wind direction but also by the relative position of the wake affected by the maintenance status. This paper combines the wake model with the maintenance status to accurately express the input wind speed of the wind turbine (WT) in each period. Because the optimization model includes complex dynamical coupling relationships and a number of nonlinear constraints, mixed integer second-order cone programming (MISOCP) are employed to address these issues. The MISOCP model is relaxed as a mixed integer linear programming (MILP) model to improve computational efficiency and the ε-constraint method is utilized to handle the multi-objective function. The proposed model and method are tested in a short-term maintenance case of an offshore wind farm. The numerical results demonstrate that the proposed approach can achieve sound economic benefits and provide comprehensive decision support.