多参数协同自适应的改进虚拟同步控制策略

Improved Virtual Synchronization Control Strategy With Multi-parameter Adaptive Collaboration

由于常规虚拟同步发电机固定参数的控制策略并未充分发挥逆变器参数灵活可调的优势,对系统暂态过程影响较大,因此提出一种P/ω下垂系数、虚拟惯量和阻尼系数自适应协同调节策略。通过对双机并联虚拟同步发电机(virtual synchronous generator,VSG)并网系统进行数学建模,对VSG暂态过程进行分段分析,得到各阶段参数调节规律。结合系统惯量阻尼和P/ω下垂系数对并网小信号模型进行分析,确定P/ω下垂系数及阻尼系数的取值范围。将VSG角速度变化量及角速度瞬时变化率同惯量阻尼关联起来,实现惯量阻尼自适应协同调节,并且根据VSG角速度变化量实时进行P/ω下垂系数的自适应调节。最后,在MATLAB/Simulink仿真平台搭建双机并联VSG并网系统,分别在因负荷波动、出力波动和交流侧短路故障工况中,对比不同参数选择策略下,并网VSG系统暂态频率波动情况,验证所提参数自适应选择策略的有效性和优越性。

The conventional control strategy of the virtual synchronous generator with the fixed parameters has a great effect on the transient process of the system because it is not able to give a full play to the advantages of the flexible and adjustable inverter parameters.Therefore,an adaptive cooperative adjustment strategy of the P/ωdroop coefficient,the virtual inertia and the damping coefficient is proposed.Through the mathematical modeling for the dual-machine parallel virtual synchronous generator(VSG)grid-connected system,the VSG transient process is segmented and analyzed to obtain the regulation laws of the parameters in different stages.Combined with the system inertia damping and the P/ωdroop coefficient,the small signal model is analyzed to determine the ranges of the P/ωdroop coefficient and the damping coefficient.The variations of the VSG angular velocity and the instantaneous change rate of the angular velocity are associated with the inertia damping to realize the adaptive cooperative adjustment of the inertia damping,and the adaptive adjustment of the P/ωdroop coefficient is carried out in real time according to the variation of the VSG angular velocity.Finally,a dual-machine parallel VSG grid-connected system is built in the MATLAB/Simulink simulation platform.In the cases of the load fluctuation,the output fluctuation and the AC side short circuit fault,the transient frequency fluctuations of the grid-connected VSG system under different parameter selection strategies are compared to verify the effectiveness and superiority of the proposed parameter adaptive selection strategy.