Optimal Scheduling of Preventive Maintenance for Offshore Wind Farms

Abstract

The maintenance cost of wind farms is one of the major factors influencing the profitability of wind projects. During preventive maintenance, the shutdown of wind turbines results in downtime wind energy losses. Appropriate determination of when to perform maintenance and which turbine(s) to maintain can reduce the overall downtime losses significantly. This paper uses a wind farm power generation model to evaluate downtime energy losses during preventive maintenance for a given group of wind turbines in the entire array. Wakes effects are taken into account to accurately estimate energy production over a specified time period. In addition to wind condition, the influence of wake effects is a critical factor in determining the selection of turbine(s) under maintenance. To minimize the overall downtime loss of an offshore wind farm due to preventive maintenance, an optimal scheduling problem is formulated that selects the maintenance time of each turbine. Weather conditions are imposed as constraints to ensure the safety of maintenance personnel, transportation, and tooling infrastructure. A genetic algorithm is used to solve the optimal scheduling problem. The maintenance scheduling is optimized for a utility-scale offshore wind farm with 25 turbines. The optimized schedule not only reduces the overall downtime loss by selecting the maintenance dates when wind speed is low, but also considers the wake effects among turbines. Under given wind direction, the turbines under maintenance are usually the ones that can generate strong wake effects on others during certain wind conditions, or the ones that generate relatively less power being under excessive wake effects.