基于DFIG虚拟惯量的微电网双维自适应动态频率优化控制

为了解决微电网高风电渗透率带来的惯性不足问题,需要利用虚拟惯量控制等手段来释放新能源的调频能力。通过对双馈感应风电机组(doubly fed induction generator,DFIG)的虚拟惯量控制进行研究,使虚拟惯量在适应风速变化的同时,适应动态频率调整不同阶段的取值要求,从而实现双维自适应控制。此外,利用深度信念网络预测动态频率调整的指标,从而优化双维自适应虚拟惯量的控制参数。微电网中仿真验证的结果表明,双维自适应控制策略可有效防止频率突变,能够减小扰动后的动态频率偏差及频率恢复的时间,展现出了更优的调频效果。研究结果可为风电机组参与调频的相关控制研究提供参考。

Double Layer Adaptive Dynamic Frequency Optimization Control of Microgrid Based on DFIG Virtual Inertia

In order to solve the problem of insufficient inertia caused by the high wind power penetration rate of the microgrid,it is necessary to use the means of virtual inertia control to release the frequency modulation capability of new energy.By studying the virtual inertia control of the doubly fed induction generator(DFIG),the virtual inertia is not only adapted to the change of wind speed,but also adapted to the value requirements of different stages of dynamic frequency adjustment,thus achieving double-layer adaptive control.In addition,the deep belief network is used to predict the dynamic frequency adjustment index to optimize the parameters of double-ayer adaptive control.The simulation results based on microgrid show that the double-layer adaptive control strategy can effectively prevent frequency abrupt change,and reduce the dynamic frequency deviation and frequency recovery time after disturbance,which shows better frequency modulation effect.The paper can provide references for the related control research of wind turbines participating in frequency modulation.