基于改进灰狼算法的VSG参数自适应控制策略

Adaptive VSG Parameter Control Strategy Based on Improved Grey Wolf Optimization

由于传统的虚拟同步发电机(Virtual synchronous generator,VSG)转动惯量和阻尼系数固定不变,在电网受到扰动时,系统的功率和频率输出会发生振荡,使系统失去了一定的动态调节性能。为了解决该问题,提出一种基于改进灰狼算法VSG参数自适应控制策略。根据VSG系统受到扰动时角速度变化率对转动惯量和阻尼系数变化影响,建立了参数自适应控制函数。在系统稳定条件下,利用改进灰狼算法对虚拟同步发电机参数选择初始值,使系统的有功功率和频率输出具有更好的动态性能,提高系统的稳定性。最后通过仿真对比现有的其他控制策略,验证所提策略的有效性和优越性。

Due to the traditional virtual synchronous generator(VSG)has a fixed rotational inertia and damping coefficient,the power and frequency output of the system will oscillate when the grid is disturbed,causing the system to lose a certain dynamic regulation performance.To address this problem,an adaptive control strategy based on the improved grey wolf optimization is proposed.According to the influence of angular velocity change rate on the variation of moment of inertia and damping coefficient when the VSG system is disturbed,a parameter adaptive control function is established.Under the stable conditions of the system,the optimal values of the virtual synchronous generator parameters are selected by using the improved grey wolf optimization,so as to make the system have a better dynamic performance in the power and frequency outputs.Finally,the effectiveness and feasibility of the proposed strategy are verified by comparing it with other existing control strategies through simulation.