基于MVO算法针对风电SSCI抑制的参数智能优化

Intelligent Optimization of Parameters for Wind Power SSCI Suppression Based on MVO Algorithm

次同步控制相互作用(SSCI)是一种新型的次同步振荡现象,由双馈风机(DFIG)变流器与固定串补之间的相互作用导致。该文将双馈风机(DFIG)的SSCI抑制问题转化为变流器控制参数整定问题。首先基于多元宇宙优化算法(MVO),结合时域仿真模型,对DFIG变流器的控制参数进行智能优化;然后与现有的配置附加阻尼控制器(SDC)和增设可控串联补偿装置(TCSC)两种抑制方法对比,仿真结果表明,MVO算法优化后的变流器参数能更好地抑制DFIG的SSCI;最后与GWO、PSO-GSA算法对比,结果表明MVO算法优化后的控制参数能够更有效地降低系统振荡幅值。

Sub-synchronous control interaction(SSCI)caused by the interaction between the DFIG converter and series compensated transmission lines is a new type of sub-synchronous oscillation phenomenon.In this paper,the SSCI abatement problem of DFIG is transformed into the converter PI parameter tuning.Firstly,based on the multi-verse optimizer(MVO),combined with the time-domain simulation model,the DFIG inverter parameters are intelligently optimized.Secondly,it is configured with the existing supplementary damping control(SDC)and thyristor controlled series compensation(TCSC)device two suppression methods are compared,the simulation results show that the converter parameters optimized based on the MVO algorithm can better suppress the SSCI of DFIG.Finally,compared with the GWO and PSO-GSA algorithms,the results show that the control parameters optimized by the MVO algorithm can reduce the system oscillation amplitude more effectively.