Introduction. In recent years, the use of renewable energy has become essential to preserve the climate from pollution and global warming. To utilize renewable energy more effectively, the microgrid system has emerged, which is a combination of renewable energies such as wind and solar power. However, due to sudden and random climate fluctuations, energy deviation and instability problems have arisen. To address this, storage systems and diesel engines have been incorporated. Nevertheless, this approach has led to another issue: frequency deviation in the microgrid system. Therefore, most recent studies have focused on finding ways to reduce frequency deviation. The goal of this work is to study and compare various improvement methods in terms of frequency deviation. Methodology. We first simulated the microgrid system using the PID controller based on the following algorithms: krill herd algorithm (KHA) and cuckoo search algorithm (CSA). In the second phase, we replaced the PID controller with the multi-stage PID controller and optimized its parameters using the KHA and the CSA. In the final phase, we tested the response of the microgrid system to these methods under a range of influencing factors. Results. The results initially showed the superiority of the KHA over the other algorithms in improving the parameters of the PID controller. In the second phase, the results showed a significant advantage of the multi-stage PID controller in terms of speed and stabilization time, as well as in reducing the frequency deviation compared to the PID controller. Practical value. Based on the tests conducted on the microgrid system, we can conclude that the multi-stage PID controller based on the KHA can be relied upon to solve these types of problems within the microgrid system. References 36, tables 4, figures 10.