Optimal maintenance planning and resource allocation for wind farms based on non-dominated sorting genetic algorithm-II

The complex structure and harsh working environment of wind turbines cause frequent failures and unavailability of these turbines in wind farms. To promote the long-term stable development of wind power and enhance its market competitiveness, the reduction of operation and maintenance costs is particularly important, which are estimated to account for approximately 1/3 of the total life cycle cost. With the continuous increase in the size and number of wind turbines, wind farm maintenance tasks and resources are increasing and becoming unpredictable. The realization of the dynamic scheduling of maintenance tasks and resources under various constraints has become vital. In this study, an optimal multi-objective model of maintenance planning and resource allocation for wind farms is established. The maintenance tasks are obtained according to the preset maintenance strategy and current operating status of the wind turbine components. The dynamic requirements of maintenance planning and resource allocation for different wind farms in adjacent areas are periodically generated, and the Non dominated sorting genetic algorithm-II (NSGA-II) is adopted to conduct a combinatorial optimization process. The validity of the proposed model are verified by a corresponding case study, along with a comparative analysis with other optimization algorithms and a sensitivity study of different parameters. (c) 2020 Elsevier Ltd. All rights reserved.

Automated summary

The frequent failures and high maintenance costs of wind turbines in wind farms have a significant impact on the stable development of wind power. This study establishes an optimal model for maintenance planning and resource allocation in wind farms under various constraints, aiming to address the dynamic maintenance needs efficiently.