MPPT of PEM Fuel Cell Using PI-PD Controller Based on Golden Jackal Optimization Algorithm

Abstract

Subversive environmental impacts and limited amounts of conventional forms of energy necessitate the utilization of renewable energies (REs). Unfortunately, REs such as solar and wind energies are intermittent, so they should be stored in other forms to be used during their absence. One of the finest storage techniques for REs is based on hydrogen generation via an electrolyzer during abundance, then electricity generation by fuel cell (FC) during their absence. With reference to the advantages of the proton exchange membrane fuel cell (PEM-FC), this is preferred over other kinds of FCs. The output power of the PEM-FC is not constant, since it depends on hydrogen pressure, cell temperature, and electric load. Therefore, a maximum power point tracking (MPPT) system should be utilized with PEM-FC. The techniques previously utilized have some disadvantages, such as slowness of response and largeness of each oscillation, overshoot and undershoot, so this article addresses an innovative MPPT for PEM-FC using a consecutive controller made up of proportional-integral (PI) and proportional-derivative (PD) controllers whose gains are tuned via the golden jackal optimization algorithm (GJOA). Simulation results when applying the GJOA-PI-PD controller for MPPT of PEM-FC reveal its advantages over other approaches according to quickness of response, smallness of oscillations, and tininess of overshoot and undershoot. The overshoot resulting using the GJOA-PI-PD controller for MPPT of PEM-FC is smaller than that of perturb and observe, GJOA-PID, and GJOA-FOPID controllers by 98.26%, 86.30%, and 89.07%, respectively. Additionally, the fitness function resulting when using the GJOA-PI-PD controller for MPPT of PEM-FC is smaller than that of the aforementioned approaches by 93.95%, 87.17%, and 87.97%, respectively.

Optimization of PEMFC pressure control using fractional PI/D controller with non-integer order: design and experimental evaluation

“…Early studies were done by Podlubny [30] and Oustaloup et al [31][32][33][34][35]. In the research article [36][37][38][39][40] tuning recommendations are used to design the FPI controllers. The relative dead time ( ) t of the system, which is defined as in equation (19), is a crucial parameter in the FOPDT model that was identified in equation ( 22)…”

Enhancing Microgrid Inverter-Integrated Charging Station Performance through Optimization of Fractional-Order PI Controller Using the One-to-One Sine Cosine Algorithm

“…Mathematically, the output voltage of the fuel cell stack containing NFC cells can be calculated using the following expression [35,36]:…”

“…The symbol I FC represents the fuel cell current measured in Amperes (amp), while V cell denotes the output voltage of a single cell. The calculation for V cell is as follows [35,36]:…”

“…A represents the cell area in cm 2 . The concentration of dissolved oxygen (CO 2 ) at the catalytic interface is determined by Equation (8) [35,36]. The electrode resistance (R m ) is calculated using Equation ( 9), taking into account the length of the electrolyte (L).…”

Maximum Power Point Tracking of Photovoltaic Generation System Using Improved Quantum-Behavior Particle Swarm Optimization

“…Some researchers have treated MPPT as an optimization problem and controlled it using particle swarm optimization (PSO) [29] or other biomimetic algorithms [30][31][32]. Compared to other MPPT methods, biomimetic algorithms are suitable for long-term operation in MPPT systems.…”