Optimized Parameters of SOFC for steady state and transient simulations using interior search algorithm

被引:68
作者
El-Hay, E. A. [1 ]
El-Hameed, M. A. [1 ]
El-Fergany, A. A. [1 ]
机构
[1] Zagazig Univ, Elect Power & Machines Dept, Fac Engn, Zagazig 44519, Egypt
关键词
SOFC system; Parameters' identifications; Steady-state and transient behaviors; Optimization methods; PI-controller; OXIDE FUEL-CELLS; IDENTIFICATION; MODEL; EXTRACTION; ENERGY;
D O I
10.1016/j.energy.2018.10.038
中图分类号
O414.1 [热力学];
学科分类号
摘要
A novel application of interior search optimizer (ISO) to define the necessary parameters to model solid oxide fuel cells (SOFCs) for further studies is presented. Sum of mean squared error (SMSE) is used to formulate the objective function to be optimized by the ISO subject to the validity of predefined constraints. The current study is carried out into two phases: i) under steady-state; various case studies under various operating conditions are demonstrated, and ii) at later stage, scenarios for transient performance of a SOFC system are investigated. In the same context, MATLAB/SIMULINK is used to implement the proposed ISO-based method. A standard proportional-integral (PO-controller is engaged to the dynamic model to improve its performance during transient disturbances. Transient responses of the stack current and voltage are analyzed due to load changes. Additionally, the hydrogen and oxygen flow rates along hydrogen utilization are investigated. For all test cases, detailed comparisons to other competing recent algorithms such as satin bowerbird algorithm, grasshopper optimizer and genetic algorithm are made to validate the numerical results. It can be emphasized that the comparisons along other demonstrations indicate the viability of the proposed ISO-based method in defining the unknown parameters of the SOFCs efficiently. (C) 2018 Elsevier Ltd. All rights reserved.
引用
收藏
页码:451 / 461
页数:11
相关论文
共 40 条
[1]   PEM fuel cell model and simulation in Matlab-Simulink based on physical parameters [J].
Abdin, Z. ;
Webb, C. J. ;
Gray, E. MacA. .
ENERGY, 2016, 116 :1131-1144
[2]   Effective parameters' identification for polymer electrolyte membrane fuel cell models using grey wolf optimizer [J].
Ali, M. ;
El-Hameed, M. A. ;
Farahat, M. A. .
RENEWABLE ENERGY, 2017, 111 :455-462
[3]  
[Anonymous], MATLAB 2017B
[4]  
Bentouati B, 2017, COGENT ENG, V4, DOI 10.1080/23311916.2017.1292598
[5]   Dynamic modeling of electrical characteristics of solid oxide fuel cells using fractional derivatives [J].
Cao, Hongliang ;
Deng, Zhonghua ;
Li, Xi ;
Yang, Jie ;
Qin, Yi .
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY, 2010, 35 (04) :1749-1758
[6]   PEM fuel cell modeling using differential evolution [J].
Chakraborty, Uday K. ;
Abbott, Travis E. ;
Das, Sajal K. .
ENERGY, 2012, 40 (01) :387-399
[7]   Static and dynamic modeling of solid oxide fuel cell using genetic programming [J].
Chakraborty, Uday Kumar .
ENERGY, 2009, 34 (06) :740-751
[8]   Modeling and performance evaluation of PEM fuel cell by controlling its input parameters [J].
Chavan, Sudarshan L. ;
Talange, Dhananjay B. .
ENERGY, 2017, 138 :437-445
[9]  
Chowdhury S., 2009, Microgrids and Active Distribution Networks
[10]   Zr and Y co-doped perovskite as a stable, high performance cathode for solid oxide fuel cells operating below 500 °C [J].
Duan, Chuancheng ;
Hook, David ;
Chen, Yachao ;
Tong, Jianhua ;
O'Hayre, Ryan .
ENERGY & ENVIRONMENTAL SCIENCE, 2017, 10 (01) :176-182