摘要
随着风力发电技术的快速发展,风电机组效率的提升对于降低发电成本至关重要。风电机组变桨距控制系统能够在复杂风况条件下降低机组载荷,平滑功率输出。针对控制策略可能导致风力发电机组无法有效跟踪风速变化,进而无法实现最大功率跟踪,同时可能引起功率输出的大幅波动,影响电网稳定性和电能质量等问题,提出利用粒子群算法优化PID变桨控制。建立了基于粒子群算法的PID参数自整定变桨控制策略,并引入柯西变异算子对控制策略进行优化,提高寻优能力,通过MATLAB/Simulink联合仿真。结果表明,基于PSO的优化策略能够显著提高风力发电机的功率捕获能力,平滑功率波动,有效延长机组在役时间。
With the increasing development of wind power generation technology,the wind turbine efficiency improvement is critical to reducing the cost of power generation.The variable pitch control system of wind turbine can reduce the load of the turbine and smooth the power output under complex wind conditions.Improper control strategy may cause the wind turbine unable to effectively follow the change of wind speed,thus unable to achieve the maximum power tracking,and may also cause large fluctuations in power output,affecting the stability of the grid and power quality.In view of the aforementioned problems,this paper proposes the optimization of PID variable pitch control by particle swarm optimization(PSO).The PID parameter self-tuning variable pitch control strategy based on particle swarm optimization is established,and Cauchy mutation operator is introduced to optimize the control strategy and improve the optimization ability.Finally,the co-simulation is carried out by MATLAB/Simulink.The results show that the optimization strategy based on PSO can significantly improve the power capture capability of wind turbines,smooth power fluctuations,and effectively extend the in-service time of wind turbines.
作者
王向伟
岳大为
商悦阳
姜皓龄
WANG Xiangwei;YUE Dawei;SHANG Yueyang;JIANG Haoling(Hebei Branch,Huaneng New Energy Co.,Ltd.,Shijiazhuang Hebei 050000,China;Province-Ministry Jointly Established State Key Laboratory of Reliability and Intelligence of Electrical Equipment(Hebei University of Technology),Tianjin 300130,China;School of Electrical Engineering,Hebei University of Technology,Tianjin 300130,China)
出处
《湖北电力》
2024年第5期44-50,共7页
Hubei Electric Power
基金
国家自然科学基金(面上项目)(项目编号:52077054)。
关键词
风力发电机
变桨距控制
粒子群算法
风力发电
PID
新能源
清洁能源
wind turbine
variable pitch control
particle swarm algorithm
wind turbine generators
PID
new energy
clean energy
