Parameters Estimation of the Mathematical Model of Solid Oxide Fuel Cell Stacks based on a Fractional-order Water Strider Algorithm

被引:0
作者
Wu, Minrong [1 ]
Li, Shanshan [2 ]
Chen, Hongyan [3 ]
Duan, Wenqi [1 ]
Shafiee, Mohammadreza [4 ]
机构
[1] State Grid NingXia Elect Power Co Ltd, Yinchuan 750001, Ningxia, Peoples R China
[2] North China Elect Power Univ, Sch Control & Comp Engn, Beijing 102206, Peoples R China
[3] North China Elect Power Univ Hosp, Beijing 102206, Peoples R China
[4] Semnan Univ, Semnan, Iran
关键词
System identification; Fuel cell; Solid Oxide Fuel Cell; Fractional-order Water Strider Algorithm; PARTICLE SWARM OPTIMIZATION; NEURAL-NETWORK; DYNAMIC-MODEL; IDENTIFICATION; PREDICTION; VARIABLES;
D O I
10.1007/s42835-021-00862-x
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In recent decades, in the use of science and technology, extensive research has been conducted on an academic and industrial scale to introduce new sources of energy that are fully constructed to meet the needs of today's human beings. One of these new sources that use your special energy is a fuel cell. A fuel cell is a clean source that converts the chemical energy in a fuel directly into electrical energy by performing two separate electrochemical reactions separately. Providing a proper model for the Solid Oxide Fuel Cell (SOFC) as one of the useful fuel cells is critical for reducing the costs of the design. However, the complexity of this problem made it a challenging task owing to the complex and highly nonlinear nature. Particularly, for SOFCs, the model should be optimized under different temperature and pressure operating conditions. The present study proposes a newly developed version of the Water Strider Algorithm, called Fractional-order Water Strider Algorithm (FOWSA) for optimal identification of the SOFC parameters. Using the proposed FOWSA is introduced to improve the original WSA to provide better convergence and global optimization results. The efficiency of the suggested FOWSA has been firstly validated and then, the designed method is performed to a practical case study and the sensitivity analysis in terms of temperature and pressure. The final results indicate that the suggested method shows outstanding efficiency toward the compared methods.
引用
收藏
页码:73 / 84
页数:12
相关论文
共 55 条
[1]  
Abaza A., 2020, RECENT ADV ENG MATH, P135, DOI [10.1007/978-3-030-39847-7_10, DOI 10.1007/978-3-030-39847-7_10]
[2]   Extracting Appropriate Nodal Marginal Prices for All Types of Committed Reserve [J].
Akbary, Paria ;
Ghiasi, Mohammad ;
Pourkheranjani, Mohammad Reza Rezaie ;
Alipour, Hamidreza ;
Ghadimi, Noradin .
COMPUTATIONAL ECONOMICS, 2019, 53 (01) :1-26
[3]  
Azar A.T., 2018, VAIDYANATHAN FRACTIO
[4]   Model identification and strategy application for Solid Oxide Fuel Cell using Rotor Hopfield Neural Network based on a novel optimization method [J].
Ba, Shusong ;
Xia, Dong ;
Gibbons, Edward M. .
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY, 2020, 45 (51) :27694-27704
[5]   A Novel Approach to the Optimization of a Solid Oxide Fuel Cell Anode Using Evolutionary Algorithms [J].
Buchaniec, Szymon ;
Sciazko, Anna ;
Mozdzierz, Marcin ;
Brus, Grzegorz .
IEEE ACCESS, 2019, 7 :34361-34372
[6]   Optimal bidding and offering strategies of compressed air energy storage: A hybrid robust-stochastic approach [J].
Cai, Wei ;
Mohammaditab, Rasoul ;
Fathi, Gholamreza ;
Wakil, Karzan ;
Ebadi, Abdol Ghaffar ;
Ghadimi, Noradin .
RENEWABLE ENERGY, 2019, 143 :1-8
[7]   A complete polarization model of a solid oxide fuel cell and its sensitivity to the change of cell component thickness [J].
Chan, SH ;
Khor, KA ;
Xia, ZT .
JOURNAL OF POWER SOURCES, 2001, 93 (1-2) :130-140
[8]  
Couceiro M., 2016, Fractional Order Darwinian Particle Swarm Optimization, P11, DOI [DOI 10.1007/978-3-319-19635-02, DOI 10.1007/978-3-319-19635-0_1]
[9]   Blockchain-Based Securing of Data Exchange in a Power Transmission System Considering Congestion Management and Social Welfare [J].
Dehghani, Moslem ;
Ghiasi, Mohammad ;
Niknam, Taher ;
Kavousi-Fard, Abdollah ;
Shasadeghi, Mokhtar ;
Ghadimi, Noradin ;
Taghizadeh-Hesary, Farhad .
SUSTAINABILITY, 2021, 13 (01) :1-22
[10]   The price prediction for the energy market based on a new method [J].
Ebrahimian, Homayoun ;
Barmayoon, Saeed ;
Mohammadi, Mohsen ;
Ghadimi, Noradin .
ECONOMIC RESEARCH-EKONOMSKA ISTRAZIVANJA, 2018, 31 (01) :313-337