降低运维成本是保障海上风电经济效益的关键,运维方案优化对降低海上风电机组运维成本和提高发电量起着双重作用。根据风电机组零部件的可靠度模型,计算出每台风电机组最佳维修时机对应的时间窗,考虑提前维修和故障后维修的经济损失,建立包含时间窗约束的海上风电机组运维方案优化模型,然后设计基于参数优化的改进遗传算法计算出最优运维方案。最后采用某海上风电场内风电机组运维案例验证模型和算法,结果表明考虑时间窗约束的运维方案可大幅度提高海上风电的经济效益,改进遗传算法比传统遗传算法具有更强的寻优能力。
Abstract
It is the key to ensure the economic benefits of offshore wind power on reducing maintenance costs. Optimization maintenance scheme plays a dual role in reducing the maintenance costs of offshore wind turbines and increasing power generation. According to the reliability model of wind turbine components, the time window corresponding to the best maintenance opportunity for each wind turbine unit is calculated. Considering the economic losses due to premature maintenance and post-failure maintenance, an optimization model for offshore wind turbine maintenance considering time window constraints is established. Then, an improved genetic algorithm based on parameter optimization is designed to calculate the optimal maintenance scheme. Finally, a wind turbine maintenance case in an offshore wind farm is used to verify the model and algorithm. The results show that the maintenance scheme considering time window constraints can greatly improve the economic benefits of offshore wind power, and the improved genetic algorithm has stronger optimization ability than the traditional genetic algorithm.
关键词
海上风电 /
遗传算法 /
粒子群优化算法 /
运维方案优化 /
时间窗
Key words
offshore wind power /
genetic algorithms /
particle swarm optimization（PSO） /
optimization of maintenance scheme /
time window
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基金
国家重点研发计划（2018YFB1501302）
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