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Multi-objective design and operation of Solid Oxide Fuel Cell (SOFC) Triple Combined-cycle Power Generation systems: Integrating energy efficiency and operational safety

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  • Sharifzadeh, Mahdi
  • Meghdari, Mojtaba
  • Rashtchian, Davood

Abstract

Energy efficiency is one of the main pathways for energy security and environmental protection. In fact, the International Energy Agency asserts that without energy efficiency, 70% of targeted emission reductions are not achievable. Despite this clarity, enhancing the energy efficiency introduce significant challenge toward process operation. The reason is that the methods applied for energy-saving pose the process operation at the intersection of safety constraints. The present research aims at uncovering the trade-off between safe operation and energy efficiency; an optimization framework is developed that ensures process safety and simultaneously optimizes energy-efficiency, quantified in economic terms. The developed optimization framework is demonstrated for a solid oxide fuel cell (SOFC) power generation system. The significance of this industrial application is that SOFC power plants apply a highly degree of process integration resulting in very narrow operating windows. However, they are subject to significant uncertainties in power demand. The results demonstrate a strong trade-off between the competing objectives. It was observed that highly energy-efficient designs feature a very narrow operating window and limited flexibility. For instance, expanding the safe operating window by 100% will incur almost 47% more annualized costs. Establishing such a trade-off is essential for realizing energy-saving.

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  • Sharifzadeh, Mahdi & Meghdari, Mojtaba & Rashtchian, Davood, 2017. "Multi-objective design and operation of Solid Oxide Fuel Cell (SOFC) Triple Combined-cycle Power Generation systems: Integrating energy efficiency and operational safety," Applied Energy, Elsevier, vol. 185(P1), pages 345-361.
    • Handle: RePEc:eee:appene:v:185:y:2017:i:p1:p:345-361
    DOI: 10.1016/j.apenergy.2016.11.010
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    Cited by:

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    11. Meilin Lai & Daihui Zhang & Yu Li & Xiaolong Wu & Xi Li, 2024. "Application of Multiple Linear Regression and Artificial Neural Networks in Analyses and Predictions of the Thermoelectric Performance of Solid Oxide Fuel Cell Systems," Energies, MDPI, vol. 17(16), pages 1-30, August.
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    15. Rashid, Kashif & Dong, Sang Keun & Mehran, Muhammad Taqi & Lee, Dong Won, 2017. "Design and analysis of compact hotbox for solid oxide fuel cell based 1kW-class power generation system," Applied Energy, Elsevier, vol. 208(C), pages 620-636.
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    20. Gabrielli, Paolo & Fürer, Florian & Mavromatidis, Georgios & Mazzotti, Marco, 2019. "Robust and optimal design of multi-energy systems with seasonal storage through uncertainty analysis," Applied Energy, Elsevier, vol. 238(C), pages 1192-1210.

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