Optimal Parameters Identification of PEMFC Using Flying Foxes Optimization Algorithm

Ahmed S. Menesy; Husam A. Ramadan; Salah Kamel; Ibrahim O. Habiballah; Hamdy M. Sultan

doi:10.1109/ETFG55873.2023.10407961

Optimal Parameters Identification of PEMFC Using Flying Foxes Optimization Algorithm

Ahmed S. Menesy^*, Husam A. Ramadan, Salah Kamel, Ibrahim O. Habiballah, Hamdy M. Sultan

^*Corresponding author for this work

Department of Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

Abstract

Recently, the contribution of fuel cell systems in electricity generation systems as an alternative to the conventional fossil fuel-powered plants has been increased due to their merits such as significant efficiency, reliability, cleanness, and fast response. In this study, a new optimization method for accurately determining the parameters of proton exchange membrane fuel cells (PEMFC) has been introduced. In which, the minimization of sum of squared error (SSE) between the estimated output voltage data and the actual measured can be realized through employing the Flying Foxes Optimization (FFO). To demonstrate the efficacy of the suggested algorithm, we tested it on multiple unique case studies. The outcomes were then benchmarked against several established optimization methods, such as are gray wolf optimizer (GWO), tree growth algorithm (TGA), harris hawks optimization (HHO), and farmland fertility optimizer (FFO). Furthermore, a statistical analysis has been investigated to validate proposed FFO algorithm's strength in addressing the optimization challenges associated with PEMFC parameter identification. The attainments showed the better superiority of the proposed FFO compared to other techniques in optimally identifying PEMFC parameters.

Original language	English
Title of host publication	2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781665471640
DOIs	https://doi.org/10.1109/ETFG55873.2023.10407961
State	Published - 2023
Event	2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023 - Wollongong, Australia Duration: 3 Dec 2023 → 6 Dec 2023

Publication series

Name	2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023

Conference

Conference	2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023
Country/Territory	Australia
City	Wollongong
Period	3/12/23 → 6/12/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

Keywords

Dynamic characteristics
FFO
Identification
PEMFC

ASJC Scopus subject areas

Artificial Intelligence
Energy Engineering and Power Technology
Renewable Energy, Sustainability and the Environment
Electrical and Electronic Engineering
Control and Optimization
Safety, Risk, Reliability and Quality

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/ETFG55873.2023.10407961

Cite this

Menesy, A. S., Ramadan, H. A., Kamel, S., Habiballah, I. O., & Sultan, H. M. (2023). Optimal Parameters Identification of PEMFC Using Flying Foxes Optimization Algorithm. In 2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023 (2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ETFG55873.2023.10407961

Menesy, Ahmed S. ; Ramadan, Husam A. ; Kamel, Salah et al. / Optimal Parameters Identification of PEMFC Using Flying Foxes Optimization Algorithm. 2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023. Institute of Electrical and Electronics Engineers Inc., 2023. (2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023).

@inproceedings{ef1b1b2d1d7749e8844fe2b93b196240,

title = "Optimal Parameters Identification of PEMFC Using Flying Foxes Optimization Algorithm",

abstract = "Recently, the contribution of fuel cell systems in electricity generation systems as an alternative to the conventional fossil fuel-powered plants has been increased due to their merits such as significant efficiency, reliability, cleanness, and fast response. In this study, a new optimization method for accurately determining the parameters of proton exchange membrane fuel cells (PEMFC) has been introduced. In which, the minimization of sum of squared error (SSE) between the estimated output voltage data and the actual measured can be realized through employing the Flying Foxes Optimization (FFO). To demonstrate the efficacy of the suggested algorithm, we tested it on multiple unique case studies. The outcomes were then benchmarked against several established optimization methods, such as are gray wolf optimizer (GWO), tree growth algorithm (TGA), harris hawks optimization (HHO), and farmland fertility optimizer (FFO). Furthermore, a statistical analysis has been investigated to validate proposed FFO algorithm's strength in addressing the optimization challenges associated with PEMFC parameter identification. The attainments showed the better superiority of the proposed FFO compared to other techniques in optimally identifying PEMFC parameters.",

keywords = "Dynamic characteristics, FFO, Identification, PEMFC",

author = "Menesy, \{Ahmed S.\} and Ramadan, \{Husam A.\} and Salah Kamel and Habiballah, \{Ibrahim O.\} and Sultan, \{Hamdy M.\}",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023 ; Conference date: 03-12-2023 Through 06-12-2023",

year = "2023",

doi = "10.1109/ETFG55873.2023.10407961",

language = "English",

series = "2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023",

address = "United States",

}

Menesy, AS, Ramadan, HA, Kamel, S, Habiballah, IO & Sultan, HM 2023, Optimal Parameters Identification of PEMFC Using Flying Foxes Optimization Algorithm. in 2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023. 2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023, Institute of Electrical and Electronics Engineers Inc., 2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023, Wollongong, Australia, 3/12/23. https://doi.org/10.1109/ETFG55873.2023.10407961

Optimal Parameters Identification of PEMFC Using Flying Foxes Optimization Algorithm. / Menesy, Ahmed S.; Ramadan, Husam A.; Kamel, Salah et al.
2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023. Institute of Electrical and Electronics Engineers Inc., 2023. (2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Optimal Parameters Identification of PEMFC Using Flying Foxes Optimization Algorithm

AU - Menesy, Ahmed S.

AU - Ramadan, Husam A.

AU - Kamel, Salah

AU - Habiballah, Ibrahim O.

AU - Sultan, Hamdy M.

PY - 2023

Y1 - 2023

N2 - Recently, the contribution of fuel cell systems in electricity generation systems as an alternative to the conventional fossil fuel-powered plants has been increased due to their merits such as significant efficiency, reliability, cleanness, and fast response. In this study, a new optimization method for accurately determining the parameters of proton exchange membrane fuel cells (PEMFC) has been introduced. In which, the minimization of sum of squared error (SSE) between the estimated output voltage data and the actual measured can be realized through employing the Flying Foxes Optimization (FFO). To demonstrate the efficacy of the suggested algorithm, we tested it on multiple unique case studies. The outcomes were then benchmarked against several established optimization methods, such as are gray wolf optimizer (GWO), tree growth algorithm (TGA), harris hawks optimization (HHO), and farmland fertility optimizer (FFO). Furthermore, a statistical analysis has been investigated to validate proposed FFO algorithm's strength in addressing the optimization challenges associated with PEMFC parameter identification. The attainments showed the better superiority of the proposed FFO compared to other techniques in optimally identifying PEMFC parameters.

AB - Recently, the contribution of fuel cell systems in electricity generation systems as an alternative to the conventional fossil fuel-powered plants has been increased due to their merits such as significant efficiency, reliability, cleanness, and fast response. In this study, a new optimization method for accurately determining the parameters of proton exchange membrane fuel cells (PEMFC) has been introduced. In which, the minimization of sum of squared error (SSE) between the estimated output voltage data and the actual measured can be realized through employing the Flying Foxes Optimization (FFO). To demonstrate the efficacy of the suggested algorithm, we tested it on multiple unique case studies. The outcomes were then benchmarked against several established optimization methods, such as are gray wolf optimizer (GWO), tree growth algorithm (TGA), harris hawks optimization (HHO), and farmland fertility optimizer (FFO). Furthermore, a statistical analysis has been investigated to validate proposed FFO algorithm's strength in addressing the optimization challenges associated with PEMFC parameter identification. The attainments showed the better superiority of the proposed FFO compared to other techniques in optimally identifying PEMFC parameters.

KW - Dynamic characteristics

KW - FFO

KW - Identification

KW - PEMFC

UR - https://www.scopus.com/pages/publications/85185777705

U2 - 10.1109/ETFG55873.2023.10407961

DO - 10.1109/ETFG55873.2023.10407961

M3 - Conference contribution

AN - SCOPUS:85185777705

T3 - 2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023

BT - 2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023

Y2 - 3 December 2023 through 6 December 2023

ER -

Menesy AS, Ramadan HA, Kamel S, Habiballah IO, Sultan HM. Optimal Parameters Identification of PEMFC Using Flying Foxes Optimization Algorithm. In 2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023. Institute of Electrical and Electronics Engineers Inc. 2023. (2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023). doi: 10.1109/ETFG55873.2023.10407961

Optimal Parameters Identification of PEMFC Using Flying Foxes Optimization Algorithm

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

UN SDGs

Access to Document

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Cite this