Objective In the process of traditional offshore wind power operation and maintenance, the operation and maintenance task scheduling plan is often made according to the sea planning table. Due to the randomness and uncertainty of operation and maintenance tasks, temporary and urgent operation and maintenance tasks that may be added at sea need to be dealt with urgently. At this time, only the previous planning results can be adjusted manually, but the subjective adjustment inevitably lacks sufficient scientific rationality, thus affecting the overall efficiency of offshore operation and maintenance.

Method Therefore, in order to optimize the overall operation and maintenance efficiency, a dynamic scheduling planning method for the operation and maintenance tasks of offshore wind farms was constructed, and the multi-optimization objectives of ship operation and maintenance time, ship operation and maintenance mileage and team waiting time were put forward. Two optimization modes, off-grid and real-time were designed to realize the static planning and dynamic adjustment of operation and maintenance scheduling scheme. At the same time, combined with the gold rush optimization algorithm with fast convergence and good optimization effect, the rapid output of operation and maintenance scheduling planning scheme was realized.

Result Finally, a five-day operation and maintenance plan of an offshore wind farm is taken as an example for comparison and verification. Compared with the actual plan, the proposed method can reduce the operation andmaintenance time and mileage of each ship by 28.32 h and 62.82 km on average. It often takes more than one day to compare the manual operation and maintenance scheduling scheme, and the optimization process of the proposed method is rapid, which only takes 11 minutes.

Conclusion Through this method, the dynamic scheduling planning scheme of offshore wind farm operation and maintenance tasks can be quickly output, the operation and maintenance efficiency can be improved, and the operation and maintenance cost can be reduced.