基于ISSA的STATCOM模型参数解耦辨识研究

为获取准确的静止同步补偿器模型参数以满足电力系统日益精细化的仿真要求,文中提出一种基于改进樽海鞘群算法的静止同步补偿器模型参数解耦辨识方法.首先基于现有静止同步补偿器机电暂态模型,建立满足暂态仿真计算要求的静止同步补偿器数学模型;然后对樽海鞘群算法进行改进,并将其应用于静止同步补偿器模型参数辨识;最后,针对模型结构耦合导致多参数辨识结果精度不高问题,提出基于STATCOM模型dq轴参数解耦辨识策略,分两步对模型参数进行辨识.仿真算例证明该算法能快速准确的辨识模型参数.

Research on Parameter Decoupling Identification of STATCOM Model Based on ISSA

In order to obtain accurate static synchronous compensator model parameters to meet the increasingly refined simulation requirements of power systems,a parameter decoupling identification method based on improved Salp Swarm Algorithm(ISSA)for static synchronous compensator is proposed.Firstly,based on the electromechanical transient model of the existing static synchronous compensator,the mathematical model of the static synchronous compensator that meets the requirements of transient simulation calculation is established.Then the algorithm of Salp Swarm Algorithm is improved and applied to the parameter identification of the static synchronous compensator model.Finally,the coupling of model structure leads to the low accuracy of multi-parameter identification results.A decoupling identification strategy based on STATCOM model dq axis parameters is proposed.The model parameters are identified in two steps.The simulation example shows that the algorithm can quickly and accurately identify the model parameters.