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An efficient way to raise the proton exchange membrane fuel cell’s (PEMFC’s) power generation efficiency and power supply quality is to use maximum power point tracking (MPPT). Conventional MPPT approaches often have difficulty producing an effective control effect due to the PEMFC’s inherent nonlinear characteristics. Another challenge for systems...
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Perturb and observe (P&O) is a well-known maximum power point tracking (MPPT) algorithm that is used in solar photovoltaic (PV) systems to increase its efficiency. However, as the PV system uses solar irradiance and temperature for making electric power, the fast change of these two affects the performance of P&O and the efficiency of the PV system...
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Citations
... These control strategies have some disadvantages such as robustness, complexity, and difficulty for implementation. To overcome these disadvantages and ensure the MPPT efficiency of a PV system, several types of research as part of the artificial intelligence approach [33], [34] and robust nonlinear controller to achieve the conversion efficiency of the maximum energy of a PV system [35]. Robust nonlinear controllers based on Lyapunov stability have been proposed in the literature to improve PV performance under difficult operating conditions. ...
One of the main issues with grid-connected distributed energy systems, including photovoltaic (PV) systems, is the DC bus voltage's instability during load fluctuations and power line short circuits. This paper attempts to address this problem and proposes to use superconducting magnetic energy storage (SMES) to stabilize the voltage of the DC link and improve the power quality and transient stability of the power system. The investigated configurationcomponents are PV cells, boost converter, chopper, SMES, three level inverter (NPC), filter, grid, and load. MATLAB / Sim Power System is used to test the performance of a SMES in order to ensure the balance of the DC bus voltage of a PV system connected to the grid. Several scenarios were considered to show the performance and benefits of combining a SMES with the PV system. The outcomes of the examined scenarios (fault and load change) demonstrate the precision of the employed control systems, maintaining the DC voltage at acceptable levels(≈500 V), enhancesthe structure stability, and improving power quality(GPV THD = 4.34). Finally, it can be concluded that the proposed configuration will help in achieving high penetration scenarios of PV systems.
... The results are compared with (P&O with ANN) and (HC with ANN). A new hybrid MPPT method for PEMFC using artificial intelligence (AI) is proposed by Masoud and Sarvi (Safarishaal and Sarvi, 2023). Two AI-based MPPT methods for PEMFC considering rapid change in operating conditions are designed. ...
... The working point of the fuel stack in this hybrid controller is first moved close to the real MPP location using the beta constraint. Afterwards, the MPP's steady state error is optimized by using the fuzzy controller 56 ...
This research study presents the application of the FC-PCC (Fuzzy Logic Predictive Current Control) algorithm in the context of maximum power point tracking (MPPT) for a proton exchange membrane fuel cell system employing a three-level boost converter (TLBC). The proposed approach involves the integration of an intelligent fuzzy controller with a predictive current control strategy in order to improve the performance of MPP tracking. Initially, the utilization of fuzzy logic involves the utilization of data values obtained from the PEMFC. The maximum point (P-I) of the PEMFC polarization curve is determined, followed by the selection of the reference current. A predictive current control technique employs the reference current to ensure the voltage balance of the output capacitor in the three-level converter. The hardware-in-the-loop system utilizes a real-time and high-speed simulator, specifically the PLECS RT Box 1, to obtain the findings. The computational cost of the overall system is rather low, making it feasible to construct using PLECS RT Box 1. The new MPPT algorithm quickly finds the maximum power point (MPP) and balances the voltage of capacitors in a number of different proton exchange membrane fuel cells. The suggested MPPT technique has been verified to demonstrate rapid tracking of the maximum power point (MPP) location, as well as precise balancing of capacitor voltage and robustness to environmental variations. This approach was tested and found to outperform conventional MPPT methods like Perturb and Observe (P&O) and Incremental Conductance (IC) in terms of tracking duration, precision, and voltage balancing, achieving a 15% reduction in tracking duration, a 5% deviation from the MPP value for voltage, and superior stability under changing temperature and pressure.
... Control systems developed using MATLAB and Simulink enable the simulation of complex fuel cell behaviors and could help with the integration of various auxiliary components such as air and hydrogen supply lines, cooling circuits, and the PEMFC stack unit [162]. These systems could also incorporate advanced algorithms such as adaptive neural fuzzy inference systems and fuzzy logic controllers, which are effective in managing nonlinearities and ensuring optimal operation under varying conditions [163]. Additionally, distributed intelligence-and agent-based control architectures have been shown to enhance the efficiency and autonomy of PEM fuel cells by enabling real-time adjustments based on sensory and contextual information [164]. ...
This work studies the efficiency and long-term viability of powered hydrogen production. For this purpose, a detailed exploration of hydrogen production techniques has been undertaken, involving data collection, information authentication, data organization, and analysis. The efficiency trends, environmental impact, and hydrogen production costs in a landscape marked by limited data availability were investigated. The main contribution of this work is to reduce the existing data gap in the field of hydrogen production by compiling and summarizing dispersed data. The findings are expected to facilitate the decision-making process by considering regional variations, energy source availability, and the potential for technological advancements that may further enhance the economic viability of electrolysis. The results show that hydrogen production methods can be identified that do not cause significant harm to the environment. Photolysis stands out as the least serious offender, producing 0 kg of CO2 per kg of H2, while thermolysis emerges as the major contributor to emissions, with 20 kg of CO2 per kg of H2 produced.
... 4,5 With the advantages of zero pollution emission, high energy density, and conversion efficiency, the proton exchange membrane fuel cell (PEMFC) is widely used in mobile power, electric vehicles, and aerospace. [6][7][8] The PEMFC consists of a bipolar plate and membrane electrode assembly (MEA), which mainly includes a proton exchange membrane, catalytic layer (CL), and gas diffusion layer (GDL). During the operation of the PEMFC system, both the transport of reactants and the discharge of products require the role of flow channels. ...
Flow field design is critical to improving the overall performance of high-temperature proton exchange membrane fuel cells. Adding baffles in the flow channel has been proven to be effective in enhancing mass transfer. In this study, fuel cells with different baffle numbers, heights, and arrangements are numerically simulated to investigate the effects of reactant velocity, concentration distribution, and pressure drop on mass transfer and output performance. The results show that baffles are beneficial in improving cell performance, especially under high current density. With the increase in baffle number and height, the concentration of the reactant at the outlet decreases and the output power increases with the increase in pressure drop. The net power density growth rate is defined to characterize the cell performance. A lower pressure drop reduces the pumping power loss generated during reactant transfer, resulting in a staggered baffle structure with the highest net power density of 4329.65 W/m2. Compared with the traditional and parallel baffle channels, this value is improved by about 11.74% and 4.83%, respectively. Therefore, the optimized baffle channel can enhance the mass transfer, reduce the pumping power, and further improve the cell performance, providing an effective guide for the optimal design and development direction of the orientated flow channel.
... The algorithm initially starts from several countries; In fact, these countries are possible answers to the algorithm. [9][10][11][15][16]. Also, Particle Swarm Optimization (PSO) is a possible optimization. ...
In a railroad feeding system, detecting a location of pole to earth faults is important for safe operation of the system. The goal of this paper is to use a combination of the evolutionary algorithm and neural networks to increase the accuracy of single pole-to-earth fault detection and location on Tehran railroad power supply system. Accordingly, Imperialist Competitive Algorithm (ICA) and Particle Swarm Optimization (PSO) are used to train the neural network for enhancing learning process accuracy and the convergence. Owing to the nonlinearity of system, the fault detection is an ideal application for the proposed method where 600 Hz harmonic ripple method is used in this paper for fault detection. The substations were simulated by considering various situations in feeding the circuit, the transformer and the silicon rectifier has been developed by typical Tehran metro parameters. Required data for the network learning the process have been gathered from simulation results. 600Hz components value will change with the change of the location of single pole to earth fault. Therefore, 600Hz components are used as inputs of the neural network when fault location is the output of the network system. The simulation results show that the fault location can be accurately predicted in proposed methods.
Fuel cell-based power generation is the most utilized renewable energy source in the automotive industry because of its features clean energy, and less environmental pollution. The fuel cell output power is mainly depending on the operating temperature of the fuel cell. The fuel cell gives nonlinear voltage versus current characteristics. As a result, the extraction of maximum power from the fuel stack is very difficult. In order to extract the peak power from the fuel cell, a Maximum Power Point Tracking (MPPT) controller is used at various working temperature conditions of the fuel cell. The main contribution of this study is the introduction and comparative performance analysis of different hybrid MPPT controllers for selecting the optimum duty cycle for the fuel cell-fed boost converter system. The studied MPPT controllers are Adaptive Adjustable Step-based Perturb and Observe (AAS-P&O) controllers, Variable Step Value-Radial Basis Function Controller (VSV-RBFC), Adaptive Step Hill Climb (ASHC) based fuzzy technique, Variable P&O with Particle Swarm Optimization (VP&O-PSO), and Variable Step Grey Wolf Algorithm (VSGWA) based fuzzy logic controller. These hybrid MPPT controllers’ comparative performance analysis has been done in terms of tracking speed of MPP, oscillations across MPP, design complexity of controller, ability to handle fast changes of temperature values, and accuracy of MPP tracking. From the simulative performance results, it is identified that the VSGWA-based fuzzy controller gives superior performance when compared to the other controllers.
