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A multi-scale energy systems engineering approach towards integrated multi-product network optimization

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  • Demirhan, C. Doga
  • Tso, William W.
  • Powell, Joseph B.
  • Pistikopoulos, Efstratios N.

Abstract

21st century energy production, conversion, and delivery systems need to go through a transition to be less carbon-intensive while meeting an increasing energy demand. In a more and more interconnected world, energy systems of various sectors (e.g. power, fuels, chemicals, etc.) go through this transition via shifting the primary energy sources from carbon-intensive fossil-fuels to renewable and sustainable resources. With this study, we present a multi-scale strategy for optimal design and operation of multi-product process systems that can produce power, synthetic fuels, chemicals, and energy carriers from renewable and fossil resources. This multi-scale approach combines process synthesis, scheduling, and supply chain concepts in a mixed-integer linear programming model to address the trade-offs between integrating various fossil and renewable technologies. Our strategy is applied to integration of low-emission (i) synthetic liquid transportation fuels, (ii) hydrogen, (iii) ammonia, (iv) methanol, and (v) renewable power production from natural gas, solar, and wind energy at a location in Amarillo, Texas. Case study results show that with our approach various energy systems can be modeled either separately and integrated with the same common representation. Sectors integration to produce low-emission products in the same facility can result in 17% reduction in total production costs. While solar and wind energy are favorable to produce renewable power, current state-of-the-art methane conversion technologies are more favorable to produce hydrogen and hydrogen-based products.

Suggested Citation

  • Demirhan, C. Doga & Tso, William W. & Powell, Joseph B. & Pistikopoulos, Efstratios N., 2021. "A multi-scale energy systems engineering approach towards integrated multi-product network optimization," Applied Energy, Elsevier, vol. 281(C).
  • Handle: RePEc:eee:appene:v:281:y:2021:i:c:s0306261920314604
    DOI: 10.1016/j.apenergy.2020.116020
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    References listed on IDEAS

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    Cited by:

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    3. Wang, Jing & Kang, Lixia & Liu, Yongzhong, 2022. "A multi-objective approach to determine time series aggregation strategies for optimal design of multi-energy systems," Energy, Elsevier, vol. 258(C).
    4. Sgarbossa, Fabio & Arena, Simone & Tang, Ou & Peron, Mirco, 2022. "Reprint of: Renewable hydrogen supply chains: A planning matrix and an agenda for future research," International Journal of Production Economics, Elsevier, vol. 250(C).
    5. Ehsan Doniavi & Reza Babazadeh & Rezgar Hasanzadeh, 2023. "Optimization of Renewable Energy Supply Chain for Sustainable Hydrogen Energy Production from Plastic Waste," Sustainability, MDPI, vol. 15(24), pages 1-26, December.
    6. Kakodkar, R. & He, G. & Demirhan, C.D. & Arbabzadeh, M. & Baratsas, S.G. & Avraamidou, S. & Mallapragada, D. & Miller, I. & Allen, R.C. & Gençer, E. & Pistikopoulos, E.N., 2022. "A review of analytical and optimization methodologies for transitions in multi-scale energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 160(C).
    7. Jalving, Jordan & Ghouse, Jaffer & Cortes, Nicole & Gao, Xian & Knueven, Bernard & Agi, Damian & Martin, Shawn & Chen, Xinhe & Guittet, Darice & Tumbalam-Gooty, Radhakrishna & Bianchi, Ludovico & Beat, 2023. "Beyond price taker: Conceptual design and optimization of integrated energy systems using machine learning market surrogates," Applied Energy, Elsevier, vol. 351(C).
    8. Potrč, Sanja & Čuček, Lidija & Martin, Mariano & Kravanja, Zdravko, 2021. "Sustainable renewable energy supply networks optimization – The gradual transition to a renewable energy system within the European Union by 2050," Renewable and Sustainable Energy Reviews, Elsevier, vol. 146(C).

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