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Degradation based optimization framework for long term applications of energy systems, case study: Solid oxide fuel cell stacks

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  • Roshandel, Ramin
  • Parhizkar, Tarannom

Abstract

Depletion of fossil fuels has increased the pressure on energy systems to operate in the most efficient and economical mode. This tendency promotes energy systems to operate at optimum operating conditions, which maximizes the system profit over lifetime. Recently, there have been many attempts to maximize lifetime profit. Most of them concentrate on the power generation aspect without incorporating further aspects such as system degradation and profitability through lifetime. However, the main intention of the system operators is to optimize the profitability of system at the moment of operation and not the total profitability through the system lifetime. In this study a novel approach is developed which considers degradation mechanisms in optimization procedure. A DBO (degradation based optimization) framework maximizes system profit through its lifetime. The proposed framework can be applied to energy systems and the optimum operating conditions and replacement intervals can be determined. Solid oxide fuel cell is considered as the case study to validate the developed framework. The results show the value and effectiveness of DBO framework to improve the lifetime profit during system operation. Using DBO, the system lifetime profit for proposed case study is increased up to 10.45%.

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  • Roshandel, Ramin & Parhizkar, Tarannom, 2016. "Degradation based optimization framework for long term applications of energy systems, case study: Solid oxide fuel cell stacks," Energy, Elsevier, vol. 107(C), pages 172-181.
    • Handle: RePEc:eee:energy:v:107:y:2016:i:c:p:172-181
    DOI: 10.1016/j.energy.2016.04.007
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    Cited by:

    1. Zaccaria, V. & Tucker, D. & Traverso, A., 2017. "Operating strategies to minimize degradation in fuel cell gas turbine hybrids," Applied Energy, Elsevier, vol. 192(C), pages 437-445.
    2. Yan, Dong & Liang, Lingjiang & Yang, Jiajun & Zhang, Tao & Pu, Jian & Chi, Bo & Li, Jian, 2017. "Performance degradation and analysis of 10-cell anode-supported SOFC stack with external manifold structure," Energy, Elsevier, vol. 125(C), pages 663-670.
    3. Ramadhani, F. & Hussain, M.A. & Mokhlis, H. & Hajimolana, S., 2017. "Optimization strategies for Solid Oxide Fuel Cell (SOFC) application: A literature survey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 460-484.
    4. Parhizkar, Tarannom & Mosleh, Ali & Roshandel, Ramin, 2017. "Aging based optimal scheduling framework for power plants using equivalent operating hour approach," Applied Energy, Elsevier, vol. 205(C), pages 1345-1363.
    5. Zhou, Daming & Gao, Fei & Breaz, Elena & Ravey, Alexandre & Miraoui, Abdellatif, 2017. "Degradation prediction of PEM fuel cell using a moving window based hybrid prognostic approach," Energy, Elsevier, vol. 138(C), pages 1175-1186.
    6. Du, Jiuyu & Ouyang, Minggao & Chen, Jingfu, 2017. "Prospects for Chinese electric vehicle technologies in 2016–2020: Ambition and rationality," Energy, Elsevier, vol. 120(C), pages 584-596.

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