摘要
为了实现风电场精细化控制,以当前风速、预测风速和机组输出功率为分析量,将模糊C均值聚类算法引入到风电场机组群分类问题中,并建立以风电场有功功率传输线路损耗最小和以风电机组总功率偏差损伤最小为优化目标的风电场有功功率双目标优化调度模型。采用改进的非劣排序遗传算法对所建立模型进行优化求解并与传统的风电场机组有功功率分配方法进行对比。算例分析结果表明,本文所提出的风电厂机组有功功率分配方法及分配策略使风电机组的有功功率出力方式相比传统方法可减少有功功率传输线损,并降低风电机组的偏差损伤,使得风电机组能更好地追踪调度中心出力需求,从而为风电场有功功率分配和精细化控制提供指导意义。
In order to realize the refined control of wind farms,taking the current wind speed,predicted wind speed and unit output power as the analysis quantities,the fuzzy C-means clustering algorithm was introduced into the wind farm unit group classification problem,and the dual objective optimal dispatching model of wind farm active power was established,which took the minimum loss of wind farm active power transmission line and the minimum damage of wind turbine total power deviation as the optimization objectives,and provided guidance for wind farm active power distribution and fine control.The nondominated sorting genetic algorithm-Ⅱ(NSGA-Ⅱ) algorithm was used to optimize the established model,and compared with the traditional active power allocation method of wind farm units.The example analysis results show that the proposed active power allocation method and strategy for wind power plants can reduce the active power transmission line loss of wind turbines and the deviation damage of wind turbines compared with traditional methods,so that wind turbines can be more efficient.It can better track the output demand of the dispatch center,so as to provide guidance for the active power distribution and refined control of wind farms.
作者
颜云松
陈汹
唐冠军
许士光
Yan Yunsong;Chen Xiong;Tang Guanjun;Xu Shiguang(NARI Technology Co.,Ltd.,Nanjing Jiangsu 211106,China)
出处
《电气自动化》
2023年第5期72-74,共3页
Electrical Automation
基金
国家电网公司科技项目(5100-202140478A-0-5-ZN)。
关键词
风电机组群
模糊C均值聚类算法
有功线损
功率偏差损伤
功率分配
wind turbine group
fuzzy C-means clustering algorithm
active power line loss
power deviation damage
power allocation