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System estimation of the SOFCs using fractional-order social network search algorithm

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  • Liu, Lijun
  • Qian, Jin
  • Hua, Li
  • Zhang, Bin

Abstract

In the preset study, a new identifier system has been proposed for optimal model estimation of Solid Oxide Fuel Cell (SOFC) stacks. To afford an appropriate identification system, the voltage-current profile of the system has been considered. The main idea is to minimize the Mean Squared Error (MSE) value between the actual output voltage of the stack and the output value achieved by the proposed model. Here, the MSE minimization has been established based on a new improved metaheuristic technique, called Fractional-order Social Network Search algorithm. The main advantage of the proposed technique is that it provides better trade-off between the global optimum and local optimum values. After system designing, it has been implemented to a studied case and its results are put in comparison with several latest techniques with considering two scenarios. One scenario with constant pressure and variable temperature and one other scenario with constant pressure and variable temperature. Final results indicate that the presented identification system provides satisfying results against the other compared methods in optimum system identification of the SOFCs.

Suggested Citation

  • Liu, Lijun & Qian, Jin & Hua, Li & Zhang, Bin, 2022. "System estimation of the SOFCs using fractional-order social network search algorithm," Energy, Elsevier, vol. 255(C).
    • Handle: RePEc:eee:energy:v:255:y:2022:i:c:s0360544222014190
    DOI: 10.1016/j.energy.2022.124516
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    1. Nassef, Ahmed M. & Fathy, Ahmed & Sayed, Enas Taha & Abdelkareem, Mohammad Ali & Rezk, Hegazy & Tanveer, Waqas Hassan & Olabi, A.G., 2019. "Maximizing SOFC performance through optimal parameters identification by modern optimization algorithms," Renewable Energy, Elsevier, vol. 138(C), pages 458-464.
    2. Moslem Dehghani & Mohammad Ghiasi & Taher Niknam & Abdollah Kavousi-Fard & Mokhtar Shasadeghi & Noradin Ghadimi & Farhad Taghizadeh-Hesary, 2020. "Blockchain-Based Securing of Data Exchange in a Power Transmission System Considering Congestion Management and Social Welfare," Sustainability, MDPI, vol. 13(1), pages 1-21, December.
    3. Cai, Wei & Mohammaditab, Rasoul & Fathi, Gholamreza & Wakil, Karzan & Ebadi, Abdol Ghaffar & Ghadimi, Noradin, 2019. "Optimal bidding and offering strategies of compressed air energy storage: A hybrid robust-stochastic approach," Renewable Energy, Elsevier, vol. 143(C), pages 1-8.
    4. Liu, Yang & Wang, Wei & Ghadimi, Noradin, 2017. "Electricity load forecasting by an improved forecast engine for building level consumers," Energy, Elsevier, vol. 139(C), pages 18-30.
    5. Saeideh Mahdinia & Mehrdad Rezaie & Marischa Elveny & Noradin Ghadimi & Navid Razmjooy, 2021. "Optimization of PEMFC Model Parameters Using Meta-Heuristics," Sustainability, MDPI, vol. 13(22), pages 1-17, November.
    6. Wang, Nan & Wang, Dongxuan & Xing, Yazhou & Shao, Limin & Afzal, Sadegh, 2020. "Application of co-evolution RNA genetic algorithm for obtaining optimal parameters of SOFC model," Renewable Energy, Elsevier, vol. 150(C), pages 221-233.
    7. Paria Akbary & Mohammad Ghiasi & Mohammad Reza Rezaie Pourkheranjani & Hamidreza Alipour & Noradin Ghadimi, 2019. "Extracting Appropriate Nodal Marginal Prices for All Types of Committed Reserve," Computational Economics, Springer;Society for Computational Economics, vol. 53(1), pages 1-26, January.
    8. El-Hay, E.A. & El-Hameed, M.A. & El-Fergany, A.A., 2019. "Optimized Parameters of SOFC for steady state and transient simulations using interior search algorithm," Energy, Elsevier, vol. 166(C), pages 451-461.
    9. Yang, Zaoli & Ghadamyari, Mojtaba & Khorramdel, Hossein & Seyed Alizadeh, Seyed Mehdi & Pirouzi, Sasan & Milani, Muhammed & Banihashemi, Farzad & Ghadimi, Noradin, 2021. "Robust multi-objective optimal design of islanded hybrid system with renewable and diesel sources/stationary and mobile energy storage systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 148(C).
    10. Wang, Jian & Xu, Yi-Peng & She, Chen & Xu, Ping & Bagal, Hamid Asadi, 2022. "Optimal parameter identification of SOFC model using modified gray wolf optimization algorithm," Energy, Elsevier, vol. 240(C).
    11. Fathy, Ahmed & Rezk, Hegazy, 2022. "Political optimizer based approach for estimating SOFC optimal parameters for static and dynamic models," Energy, Elsevier, vol. 238(PC).
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