摘要
叶片是风电机组的核心部件之一,占风机总成本的20%,是影响风电机组运行寿命的重要因素。通过对叶片在几种不同载荷工况下叶根材料破坏时循环次数的计算,再结合线性累积损伤理论,得到了不同工况下的叶片损伤量。在同时考虑了风电机组叶片损伤、启停次数以及功率控制要求的条件下,建立了风电场的多目标调度模型;并采用二进制遗传算法(BGA)对该模型予以优化,获得了风电机组启停组合和目标功率值。在此基础上,再结合实际算例来验证该算法,通过合理的机组调度,实现了在保证输出功率控制要求的同时,来优化风电机组的启停、改善风电机组的运行寿命以及减少风电场电力系统的运行成本。
As one of the key components of wind turbine, blades not only account for 20% of the total cost of wind turbine, but also have larger much influence on units＇ service life. Through the ealculation of cycling times in the blade root damage process under different work loads, the total damage value of the blades under different loads are worked out based on linear cumulative damage theory. In consideration of the blade damage, start - stop times, and power control requirements of wind turbine units, a multi - target dispatching model of wind farm is established and optimized by binary genetic algorithm, through which the targets of optimal start - stop control and output power are obtained. After checking the results of the algorithm by calculation of actual situation, it shows that the dispatching solution could not only optimize the start - stop control, but also prolong the service life of the wind turbines, and reduce the operation cost of the wind power system.
出处
《人民长江》
北大核心
2016年第2期95-100,共6页
Yangtze River
关键词
叶片损伤量
风电功率
多目标优化
二进制遗传算法
风电场
blade damage value
power of wind turbine
multi - target optimization
binary genetic algorithm
wind farm
作者简介
柴丽君，女，硕士研究生，研究方向为能源技术经济与价值管理。E—mail：921060764@qq．com
