针对现有风电场虚拟惯量协调控制在风电机组调频辅助功率协调分配方面的研究,提出一种基于风速预测的风电场虚拟惯量响应场级协同分配策略,具体是通过经验模式分解（EMD）和BP神经网络训练风速时序序列获得风速时序模型,预测短时段内的风速,根据实时转速和预测风速计算惯量分配权重因子,根据频率变化计算全场惯量响应值,通过惯量分配权重因子结合变流器容量限值给单机分配惯量响应值。该控制策略成功应用于云南某148.5 MW风电场站级调频测试,验证了算法的有效性。
Abstract
According to the current research of wind farm virtual inertia coordinated control for wind turbine power distribution of frequency regulation, this paper proposed a virtual inertial coordinated-control power distribution strategy based on wind speed prediction. Specifically, a time-series wind speed model resulting through BP neural network training with time-series wind speed and empirical mode decomposition （EMD） , thereby the short period wind speed can be predicted. The calculation of inertia distribution weighting factor is based on both real-time rotor speed and predicted wind speed, meanwhile,the whole field inertia response value is calculated by frequency variation.The inertia response value of each wind turbine is allocated through the inertia distribution weighting factor and the capacity of each converter. The control strategy in this paper has been successfully applied on a 148.5 MW wind farm in Yunnan. On the basis of frequency modulation test results, the effectiveness of the algorithm has been verified.
关键词
风电场 /
虚拟惯量控制 /
频率响应 /
协调控制 /
风速预测
Key words
wind farm /
virtual inertia control /
frequency response /
coordination control /
wind speed prediction
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基金
国家重点研发计划（2018YFB1503102）
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