This paper presents a novel minimum seeking algorithm referred to as the Hunger Games Search (HGS) algorithm. The HGS is used to obtain optimal values in the model describing proton exchange membrane fuel cells (PEMFCs). The PEMFC model has many parameters that are linked in a nonlinear manner, as well as a set of constraints. The HGS was used with the aforementioned model to test its performance against nonlinear models. The main aim of the optimization problem was to obtain accurate values of PEMFC parameters. The proposed heuristic algorithm was used with two commercial PEMFCs: the Ballard Mark V and the BCS 500 W. The simulation results obtained using the HGS-based model were compared to the experimental results. The effectiveness of the proposed model was verified under various temperature and partial pressure conditions. The numerical output results of the HGS-based fuel cell model were compared with other optimization algorithm-based models with respect to their efficiency. Moreover, the parametric t-test and other statistical analysis methods were employed to check the robustness of the proposed algorithm under various independent runs. Using the proposed HGS-based PEMFC model, a model with very high precision could be obtained, affecting the operation and control of the fuel cells in the simulation analyses.

In this study, a novel bonobo optimizer (BO) technique is applied to find the optimal design for an off-grid hybrid renewable energy system (HRES) that contains a diesel generator, photovoltaics (PV), a wind turbine (WT), and batteries as a storage system. The proposed HRES aims to electrify a remote region in northern Saudi Arabia based on annualized system cost (ASC) minimization and power system reliability enhancement. To differentiate and evaluate the performance, the BO was compared to four recent metaheuristic algorithms, called big-bang–big-crunch (BBBC), crow search (CS), the genetic algorithm (GA), and the butterfly optimization algorithm (BOA), to find the optimal design for the proposed off-grid HRES in terms of optimal and worst solutions captured, mean, convergence rate, and standard deviation. The obtained results reveal the efficacy of BO compared to the other four metaheuristic algorithms where it achieved the optimal solution of the proposed off-grid HRES with the lowest ASC (USD 149,977.2), quick convergence time, and fewer oscillations, followed by BOA (USD 150,236.4). Both the BBBC and GA algorithms failed to capture the global solution and had high convergence time. In addition, they had high standard deviation, which revealed that their solutions were more dispersed with obvious oscillations. These simulation results proved the supremacy of BO in comparison to the other four metaheuristic algorithms.

Small-signal models of dc-dc converters are often designed using a state-space averaging approach. This design can help discuss and derive the control-oriented and other frequency-domain attributes, such as input or output impedance parameters. This paper aims to model the dc-dc converters for PV application by employing a capacitor on the input side. The modeling, design, and analysis of the dc-dc converters regarding the input capacitor is limited in the literature. Five dc-dc converters, including buck, boost, buck-boost, ĆUK, and SEPIC converters, are designed and implemented using the state-space average modeling approach in MATLAB/Simulink. The circuit topology of each converter and the state-space matrices are derived considering every constraint. A rigorous and compelling analysis of the dc-dc converters is carried out to compare system stability and, ultimately, the dynamic performance. The output of the resulting small-signal models has been demonstrated in the time-domain against topology simulations. All the converters are exposed to unpredictable weather conditions and the simulations are carried out in the PSIM software. The perturb and observe (P&O) maximum power point tracking (MPPT) algorithm is applied in all the converters to ensure maximum power point (MPP) achievement. The results showcase that the boost converter outperforms all other converters in terms of stability, settling time, and overshoot.

Photovoltaic (PV) module behavior is not linear in nature with respect to environmental conditions and hence exhibits nonlinear PV curves. There is only a single point in the nonlinear PV curve at which the power is maximum. Therefore, special methods have been proposed to track this maximum power point (MPP). This paper proposed an intelligent method for MPP tracking (MPPT) based on adaptive neuro-fuzzy inference system (ANFIS) controller. The proposed system consists of a PV module connected to a DC-DC isolated Ćuk converter and load. A MATLAB/SIMULINK-based MPPT model is built to test the behavior of the proposed method. The proposed method is tested under different weather scenarios. Simulation results exhibit the successful tracking of the proposed method under all ambient conditions. Comparison of the tracking behavior of the proposed method with the perturb and observe method is also presented in the simulation results. In addition, a 220 W prototype with the help of dSPACE 1104 data acquisition system is built and tested under practical weather conditions on a sunny day as well as on a cloudy day. Experimental results are presented to verify the effectiveness of the proposed method. These results exhibit satisfactory performance under different practical weather conditions.

A three-phase multilevel inverter topology for use in various applications is proposed. The present topology introduces a combination of a cascaded H-bridge multilevel inverter with a cascaded three-phase voltage source inverter (three-phase triple voltage source inverter (TVSI)). This combination will increase the number of voltage levels generated when using fewer components compared with the conventional multilevel inverter topologies for the same voltage levels generated. The other advantage gained from the proposed configuration is the assurance of a continuous power supply to the grid in case of failure in one part of the proposed configuration. In addition, the voltage stresses on switches are reduced by half compared if each part in the proposed topology is working independently. The comparison of the proposed topology with some conventional multilevel inverter topologies is presented. The proposed topology is built in the SIMULINK environment and is simulated under various loads in addition to being connected to the grid. Phase-shifted pulse width modulation technique is used to generate the required switching pulses to drive the switches of the proposed topology. The inverter is experimentally implemented in the lab, and the switching pulses are generated with the help of MicroLabBox produced by dSPACE (digital signal processing and control engineering) company. The simulation and experimental results and their comparisons are presented to verify the proposed topology’s effectiveness and reliability.

Renewable energy systems (RESs) have introduced themselves as vital solutions for energy supply in remote regions, wherein main utility supply systems are not available. The construction of microgrid (MG) systems is useful candidate for proper control and management with hybrid RESs. However, RESs-based MGs face reduced power system inertia due to the dependency of RESs on power electronic converter systems. Accordingly, preserving nominal operating frequency and reduced deviations in tie-line power are crucial elements for proper operation of interconnected MGs in remote areas. To overcome this problem, load frequency control (LFC) systems have proven featured solutions. Therefore, this paper proposes a new non-integer LFC method based on the fractional order (FO) control theory for LFC in interconnected MGs in remote areas. The proposed control is based on the three degree of freedom (3DoF) cascaded 1+proportional-integral-derivative-accelerated (PIDA) controller with FOPI controller, namely 3DoF 1+PIDA/FOPI LFC scheme. The proposed 3DoF 1+PIDA/FOPItakes the advantages of the accelerated term of PIDA control to improve power system transients, regarding maximum overshoot/undershoot and settling times. Additionally, it employs outer loop to reduce errors and faster inner loop to mitigate disturbances effects. The contribution of plug-in controlled electric vehicles (EVs) are considered to enhance the frequency regulation functions. An optimized design of the proposed 3DoF 1+PIDA/FOPI LFC scheme is proposed using the newly developed hybrid equilibrium optimizer (EO)-slime mould optimization (SMA) algorithm (namely EOSMA optimizer). The EOSMA combines the features of the EO and SMA powerful optimization algorithms. A two interconnected MGs in remote areas with RESs and EVs inclusions with high penetration levels is selected to verify the proposed 3DoF 1+PIDA/FOPI LFC scheme and the EOSMA optimizer. The results show high ability of the proposed controller and design scheme to minimize MGs’ frequency and tie-line power fluctuations and to preserve frequency stability and security.