Parameter identification of solar cells and fuel cell using improved social spider algorithm

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Hadi Kashefi ◽  
Ahmad Sadegheih ◽  
Ali Mostafaeipour ◽  
Mohammad Mohammadpour Omran
Keyword(s):  
Fuel Cell ◽  
Proton Exchange Membrane ◽  
Search Space ◽  
Proton Exchange ◽  
Model Parameters ◽  
Social Spider ◽  
Content Type ◽  
Pv Systems ◽  
Modified Method ◽  
Social Spider Algorithm

Purpose To design, control and evaluate photovoltaic (PV) systems, an accurate model is required. Accuracy of PV models depends on model parameters. This study aims to use a new algorithm called improved social spider algorithm (ISSA) to detect model parameters. Design/methodology/approach To improve performance of social spider algorithm (SSA), an elimination period is added. In addition, at the beginning of each period, a certain number of the worst solutions are replaced by new solutions in the search space. This allows the particles to find new paths to get the best solution. Findings In this paper, ISSA is used to estimate parameters of single-diode and double-diode models. In addition, effect of irradiation and temperature on I–V curves of PV modules is studied. For this purpose, two different modules called multi-crystalline (KC200GT) module and polycrystalline (SW255) are used. It should be noted that to challenge the performance of the proposed algorithm, it has been used to identify the parameters of a type of widely used module of fuel cell called proton exchange membrane fuel cell. Finally, comparing and analyzing of ISSA results with other similar methods shows the superiority of the presented method. Originality/value Changes in the spider’s movement process in the SSA toward the desired response have improved the algorithm’s performance. Higher accuracy and convergence rate, skipping local minimums, global search ability and search in a limited space can be mentioned as some advantages of this modified method compared to classic SSA.

Grid – connected operation and performance of hybrid DG having PV and PEMFC

Circuit World ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Nayana Shetty ◽  
Chakrasali R.L.
Keyword(s):  
Fuel Cell ◽  
Distributed Generation ◽  
Proton Exchange Membrane ◽  
Photovoltaic Cell ◽  
Proton Exchange ◽  
Solar Irradiation ◽  
Pv System ◽  
Content Type ◽  
Contemporary World ◽  
And Performance

Purpose “the purpose of this study/paper” or “this study/paper aims to” in the Purpose section of the Abstract. The integration of distributed generation (DG) to the utility grid is yet another approach to provide reliable and secured power. Design/methodology/approach The significant concern in this contemporary world are the day-to-day increasing power demand, lack of energy and increasing environmental pollution, which are threatening the existence of living things. Findings The research focus here is to adequacy and security in the grid-integrated hybrid distributed generation (DG) having photovoltaic (PV) and proton exchange membrane fuel cell. Originality/value PV system is a clean source of generation and suitable for many applications. Photovoltaic cell captures the energy from solar irradiation. To track the maximum power from PV, perturb and observe method is used. As it is intermittent in nature, integrating PV with fuel cell makes the hybrid source more reliable. Power electronic interfacing devices are used to integrate this hybrid DG source to microgrid. The simulation of this grid-connected hybrid DG is performed using Matlab/Simulink environment.

Dynamic Modeling and Simulation of an Optimized Proton Exchange Membrane Fuel Cell System

2007 ◽  
Author(s):  
M. T. Outeiro ◽  
R. Chibante ◽  
A. S. Carvalho ◽  
A. T. de Almeida
Keyword(s):  
Fuel Cells ◽  
Fuel Cell ◽  
Proton Exchange Membrane ◽  
Cell Model ◽  
Pem Fuel Cell ◽  
Energy System ◽  
Cell System ◽  
Proton Exchange ◽  
Model Parameters ◽  
Sustainable Energy System

Hydrogen and fuel cells are widely regarded as the key to energy solutions for the 21st century. These technologies will contribute significantly to a reduction in environmental impact, enhanced energy security and development of new energy industries. Fuel cells operating with hydrogen have the potential to contribute to the transition for a future sustainable energy system with low-CO2 emissions. In this paper a dynamic PEM fuel cell model, implemented in Matlab/Simulink, is presented. In order to estimate the PEM fuel cell model parameters, an optimization based approach is used. The optimization is carried out using the Simulated Annealing (SA) algorithm. This optimization process evolves converging to a minimum of the objective function. The flexibility and robustness of SA as a global search method are extremely important advantages of this method. A good agreement between experimental and simulated results is observed. This optimized PEM fuel cell model can significantly help designers of fuel cell systems by providing a tool to perform accurate design and consequently to improve system efficiency.

scholarly journals Fuel Cell Fractional-Order Model via Electrochemical Impedance Spectroscopy

2021 ◽  
Vol 5 (1) ◽  
pp. 21
Author(s):  
Riccardo Caponetto ◽  
Fabio Matera ◽  
Emanuele Murgano ◽  
Emanuela Privitera ◽  
Maria Gabriella Xibilia
Keyword(s):  
Electrochemical Impedance Spectroscopy ◽  
Fuel Cell ◽  
Impedance Spectroscopy ◽  
Fractional Order ◽  
Proton Exchange Membrane ◽  
Electrochemical Impedance ◽  
Equivalent Circuit Model ◽  
Proton Exchange ◽  
Model Parameters ◽  
Data Driven Approach

The knowledge of the electrochemical processes inside a Fuel Cell (FC) is useful for improving FC diagnostics, and Electrochemical Impedance Spectroscopy (EIS) is one of the most used techniques for electrochemical characterization. This paper aims to propose the identification of a Fractional-Order Transfer Function (FOTF) able to represent the FC behavior in a set of working points. The model was identified by using a data-driven approach. Experimental data were obtained testing a Proton Exchange Membrane Fuel Cell (PEMFC) to measure the cell impedance. A genetic algorithm was firstly used to determine the sets of fractional-order impedance model parameters that best fit the input data in each analyzed working point. Then, a method was proposed to select a single set of parameters, which can represent the system behavior in all the considered working conditions. The comparison with an equivalent circuit model taken from the literature is reported, showing the advantages of the proposed approach.

scholarly journals Online Modeling of a Fuel Cell System for an Energy Management Strategy Design

Energies ◽  
2020 ◽  
Vol 13 (14) ◽  
pp. 3713 ◽  
Author(s):  
Mohsen Kandidayeni ◽  
Alvaro Macias ◽  
Loïc Boulon ◽  
João Pedro F. Trovão
Keyword(s):  
Fuel Cell ◽  
Energy Management ◽  
Management Strategy ◽  
Proton Exchange Membrane ◽  
Cell System ◽  
Proton Exchange ◽  
Fuel Cell Vehicle ◽  
Model Parameters ◽  
Energy Management Strategy ◽  
Initial Values

An energy management strategy (EMS) efficiently splits the power among different sources in a hybrid fuel cell vehicle (HFCV). Most of the existing EMSs are based on static maps while a proton exchange membrane fuel cell (PEMFC) has time-varying characteristics, which can cause mismanagement in the operation of a HFCV. This paper proposes a framework for the online parameters identification of a PMEFC model while the vehicle is under operation. This identification process can be conveniently integrated into an EMS loop, regardless of the EMS type. To do so, Kalman filter (KF) is utilized to extract the parameters of a PEMFC model online. Unlike the other similar papers, special attention is given to the initialization of KF in this work. In this regard, an optimization algorithm, shuffled frog-leaping algorithm (SFLA), is employed for the initialization of the KF. The SFLA is first used offline to find the right initial values for the PEMFC model parameters using the available polarization curve. Subsequently, it tunes the covariance matrices of the KF by utilizing the initial values obtained from the first step. Finally, the tuned KF is employed online to update the parameters. The ultimate results show good accuracy and convergence improvement in the PEMFC characteristics estimation.

scholarly journals Optimizing PEMFC model parameters using ant lion optimizer and dragonfly algorithm: A comparative study

2019 ◽  
Vol 9 (6) ◽  
pp. 5295
Author(s):  
Zainuddin Mat Isa ◽  
Norkharziana Mohd Nayan ◽  
Mohd Hafiz Arshad ◽  
Nor Ashbahani Mohamad Kajaan
Keyword(s):  
Fuel Cell ◽  
Proton Exchange Membrane ◽  
Proton Exchange ◽  
The Other ◽  
Model Parameters ◽  
Dragonfly Algorithm ◽  
Ant Lion Optimizer ◽  
Great Performance ◽  
Ant Lion ◽  
Exchange Membrane

This paper introduced two optimization algorithms which are Ant Lion Optimizer (ALO) and Dragonfly Algorithm (DA) for extracting the Proton Exchange Membrane Fuel Cell (PEMFC) polarization curve parameters. The results produced by both algorithms are being compared to observe their performance. As a results, the ALO shows great performance compared to DA. Furthermore, these results also being compared with the results of the other reported metaheuristics algorithms. The ALO and DA presented competitive results.

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