there are studies that have analyzed the performance of various components, such as batteries [8] and diesel generators [9] in electric ships. Additionally, environmental and economic considerations have been discussed in relation to hybrid systems that use photovoltaic (PV), diesel, and energy storage units [10; 11]. Some studies have also looked at ways to improve the efficiency of ship microgrids through energy management and maneuvering approaches [12]. Furthermore, much research has been performed on determining the optimal size of the ESS in hybrid MG systems to address the unpredictable and inconsistent nature of renewable resources [13; 14; 15]. However, there has been less focus on designing control strategies for shipboard microgrids. Some efforts that have been made in this regard are described in [16; 17; 18]. The purpose of [16] was to present a frequency-sharing approach for dealing with the PV panels' highly stochastic nature when integrated with naval MGs. Reference [17] presents a hybrid energy storage system that includes both batteries and ultracapacitors (UCs) to provide pulsating active power, resulting in a decrease in the capacity of batteries and DG and an increase in fuel consumption. The authors in [18] present a case study of a hybrid-electric ferry that utilizes a DC/AC hybrid distribution and ESS for the shipboard power system (SPS) to improve the efficiency. Prior research on control strategies for maritime microgrid systems have covered various topics. However, until recently, little attention has been given to the LFC problem in SMGs. In shipboard microgrids, LFC is a crucial issue since it regulates the balance between load demand and power generation [3]. LFC involves monitoring and controlling the frequency of the microgrid's power system in order to keep it within a safe operating range [19]. LFC's primary goal is to ensure that the frequency of the system remains stable and that any deviations are quickly corrected. In shipboard microgrids, LFC is particularly challenging due to the presence of intermittent RESs and the low inertia of the system. This means that the system is more susceptible to frequency fluctuations caused by changes in power generation or load demand. Several control strategies have already been proposed to address the LFC issue in conventional microgrid systems. Among others, these include proportional-integral-derivative (PID) [20], fractional-order PID (FOPID) [21], non-linear fractional-order PID (NLFOPID) [22], and a non-integer controller [23]. Furthermore, the optimal adjustment of the controller parameters is crucial for improving the dynamics of a system. To achieve this, various heuristic algorithmic tools such as teaching-learning-based optimization (TLBO) [24], the grasshopper optimization algorithm (GOA) [25], the genetic algorithm (GA) [26], salp swarm algorithm (SSA) optimization [27], particle swarm optimization (PSO) [28], and others are used to tune the controllers' parameters in microgrids. The majority of the earlier control techniques were developed for conventional generation units with high system inertia and do not take into account the intermittent nature of RESs for short-term frequency stabilization. However, maritime microgrids have low inertia and incorporate intermittent renewable energy sources. Although numerous LFC solutions have been suggested for traditional power systems and conventional MG, the amount of research conducted on dealing with LFC in marine/shipboard MGs is limited. Recent studies [29; 30; 31] proposed different algorithms for solving the issue of frequency control in different shipboard MG systems. Reference [29] introduces a coordinated control technique that utilizes an SSA-optimized hybrid fuzzy fractional-order PI-fractional-order PID (FFOPI-FOPID) to decrease frequency deviations caused by load changes. The GOA and butterfly optimization algorithm (BOA) are used to tune the controller gains of fuzzy-based PID with a filter and fractional-order controller in [30; 31], respectively.