In this article, a hybrid technique is proposed for improving the transient and small signal response in micro grid using virtual inertia. The proposed hybrid technique is the combined execution of both the emperor penguin optimizer (EPO) and butterfly optimization algorithm (BOA), and hence it is called EPOBOA technique. The major objective of the EPOBOA technique is to “optimize the control parameters to regulate the changes occurred in the grid parameter such as voltage and frequency based on the variations of inertia”. Here, the EPO is executed to modify the parameters of virtual synchronous generator units to achieve the objective function. The searching behaviour of the EPO is adapted by using the hunting behaviour of BOA. The proposed technique is executed in MATLAB/Simulink work site, and the experimental results are analyzed under three test cases: normal condition, irradiation change condition, and load change condition. The performance of the proposed technique is compared with different existing techniques and the calculated frequency deviation index of the proposed technique in all the cases is 0.0051, 0.0045, and 0.0047 and found to be very optimal compared with existing methods. Overall, the experimental outcomes show that the proposed EPOBOA method is more efficient and confirm its ability to solve the issues.

在本文中，提出了一种使用虚拟惯性改善微电网中瞬态和小信号响应的混合技术。提出的混合技术是帝企鹅优化器（EPO）和蝶形优化算法（BOA）的组合执行，因此被称为EPOBOA技术。EPOBOA技术的主要目标是“基于惯性的变化，优化控制参数以调节电网参数中发生的变化，例如电压和频率”。在此，执行EPO以修改虚拟同步发电机单元的参数以实现目标功能。通过使用BOA的搜寻行为来调整EPO的搜索行为。所提出的技术在MATLAB / Simulink工作站点中执行，并在正常情况，辐照变化情况和负荷变化情况三个测试案例下分析了实验结果。将所提出的技术的性能与不同的现有技术进行比较，并且在所有情况下所计算出的该技术的频率偏差指数分别为0.0051、0.0045和0.0047，并且与现有方法相比是非常理想的。总体而言，实验结果表明，提出的EPOBOA方法更有效，并证实了其解决问题的能力。0047，并且发现与现有方法相比非常理想。总体而言，实验结果表明，提出的EPOBOA方法更有效，并证实了其解决问题的能力。0047，并且发现与现有方法相比非常理想。总体而言，实验结果表明，提出的EPOBOA方法更有效，并证实了其解决问题的能力。