The high-level penetration of intermittent renewable power generation may limit power system inertia, resulting in system frequency instability in increasing power converter-based energy sources. To resolve this problem, virtual inertia control using distributed gray wolf optimization (DGWO) method in a synchronous generator is simulated under a distinct output fluctuation condition. First, the DGWO algorithm was established to achieve a local and global balance solution, and standard test functions were employed to verify the model convergence. Second, the key parameters that determine the effect of the virtual inertia controller in the power grid were analyzed. A DGWO-based optimization strategy to stabilize inertia was also developed. Finally, simulation results using step and random loads under a high permeability level are provided to verify the effectiveness of the proposed model. In the step load disturbance, the system can recover from the disturbance point to the stable point after 3 s under the regulation of the proposed control strategy, which is reduced by 18 s compared with the traditional control method. In the random load test, it takes only 12 s, 63 s less than the traditional one. Accordingly, the power system frequency can be stabilized more quickly from a disturbance state to a stable stage.

间歇性可再生能源发电的高渗透率可能会限制电力系统的惯性，导致增加基于功率转换器的能源时系统频率不稳定。为了解决这个问题，在明显的输出波动条件下，对同步发电机中使用分布式灰狼优化（DGWO）方法的虚拟惯性控制进行了模拟。首先，建立DGWO算法实现局部和全局平衡解，并采用标准测试函数验证模型收敛性。其次，分析了决定虚拟惯性控制器在电网中效果的关键参数。还开发了一种基于 DGWO 的优化策略来稳定惯性。最后，提供了在高渗透率水平下使用阶跃和随机载荷的模拟结果，以验证所提出模型的有效性。在阶跃负载扰动下，系统在所提出的控制策略的调节下3 s后即可从扰动点恢复到稳定点，比传统控制方法减少了18 s。在随机负载测试中，只需要12秒，比传统的少63秒。因此，电力系统频率可以更快地从扰动状态稳定到稳定阶段。在随机负载测试中，只需要12秒，比传统的少63秒。因此，电力系统频率可以更快地从扰动状态稳定到稳定阶段。在随机负载测试中，只需要12秒，比传统的少63秒。因此，电力系统频率可以更快地从扰动状态稳定到稳定阶段。