## 7 Conclusions  
In this paper, the issue of load frequency regulation in a contemporary shipboard microgrid (SMG) arising from the literature was investigated. The simulation model employed in this study comprised a variety of power-generating components, including a photovoltaic system, a diesel generator, a wave energy conversion system, a battery, and a flywheel storage system. The methodology followed for solving this load frequency control problem was divided into two phases: a controller optimization procedure and an analysis of the proposed controller's robustness. The SMG system was initially considered with a constant variation in the renewable sources and a constant step load variation, leveraging average values of real data to establish the values for the solar and wave sources. For the purposes of ensuring reliable results, three different controller architectures (PIDF, FOPID, and 2 DOF-PIDF) were evaluated, and their gains were obtained using various bio-inspired algorithms (ALO, GOA, GWO, HHO, JSO, and WOA). The simulation results indicated that the 2 DOF-PIDF-JSO controller exhibited superior performance in terms of power system stability compared to other controllers designed using heuristic algorithms (improved by 93.49%, 91.71%, 56.3%, 92.43%, and 91.22% for the ALO-, GOA-, GWO-, HHO-, and WOA  
Figure 14: Frequency response of the JSO-tuned 2 DOF-PIDF controller, under \(T_{fess}\), \(T_{kess}\), \(\tau_{d}\) parameters’ variation. Figure 13: Frequency response of the JSO-tuned 2 DOF-PIDF controller, under \(R\), \(D\), \(H\) parameters’ variation. tuned 2 DOF-PIDF controllers, respectively). Furthermore, the 2 DOF-PIDF-JSO controller yielded the lowest objective function, followed by the FOPID-JSO (deterioration of 85.93%) and PIDF-JSO (deterioration of 87.64%). The assessment and analysis of the results demonstrated that the proposed approach provides improved stability in terms of settling time and reduces frequency deviation, resulting in a reduction in peak overshoot and undershoot. To ensure the superiority and robustness of the 2 DOF-PIDF-JSO controller (second phase), three distinct simulation cases were considered. In the first case, according to real data, the renewable sources and load disturbances were categorized into three zones: high, medium, and low. This case was studied to show the 2 DOF-PID-JSO controller's dependability in potential disturbance scenarios, even in the worst-case scenario where the load is at its maximum and the renewable sources are unable to contribute. The second case incorporated real data obtained from a real data center, providing a more realistic simulation study. The final case involved a sensitivity analysis, which was conducted to evaluate the stability and robustness of the proposed JSO-tuned controller. The results of these simulations demonstrated the superior performance of the 2 DOF-PIDF-JSO controller in maintaining frequency control in the SMG system, highlighting its effectiveness in maintaining stability in the face of disturbances. The results presented indicated that the JSO algorithm outperformed all other algorithms across all examined cases. This can be attributed to the JSO algorithm's ability to rapidly identify promising areas without any disruption. By using a time control mechanism and a chaotic map to enhance the diversity of the initial population and alternate movements, the JSO algorithm achieved better outcomes due to a well-balanced approach between exploring and exploiting. As a result, the JSO algorithm has great potential as a metaheuristic algorithm for resolving a variety of optimization problems. Finally, some suggestions for future actions aiming to enhance the performance of load frequency control in SMGs may include:  
* The possibility of integrating other green energy sources, such as the combination of wind, PV, and wave energy, into these systems.