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How can renewable hydrogen compete with diesel in public transport? Robust design optimization of a hydrogen refueling station under techno-economic and environmental uncertainty

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  • Coppitters, Diederik
  • Verleysen, Kevin
  • De Paepe, Ward
  • Contino, Francesco

Abstract

Heavy-duty transport represents nearly 6% of the greenhouse gas emissions in Europe. Renewable hydrogen is a potential option to decarbonize heavy-duty transport, such as buses. Renewable hydrogen for buses promises excellent environmental performance, at the expense of a higher fuel cost, as opposed to a diesel-powered bus fleet. Despite the inherent uncertainty, feasibility studies in this framework generally assume deterministic techno-economic and environmental parameters, which can lead to a suboptimal performance that is sensitive to the random environment. To provide robust design alternatives, we applied robust design optimization on a wind- and solar-powered hydrogen refueling system and a hydrogen- and diesel-powered bus fleet, to optimize the Levelized Cost Of Driving (LCOD) and Carbon Intensity (CI), subject to technical, economic and environmental uncertainties. A fully diesel-powered bus fleet achieves the optimized LCOD mean of 1.24€/km, but it results in the worst LCOD standard deviation (0.11€/km), CI mean (1.33kg˙CO˙2,eq /km) and CI standard deviation (0.075kg˙CO˙2,eq /km) among the optimized designs. To reduce the LCOD standard deviation, CI mean and CI standard deviation, part of the diesel-powered bus fleet is converted into hydrogen-powered buses and the renewable-powered hydrogen refueling station is scaled accordingly. Converting 54% of the diesel-powered bus fleet into hydrogen-powered buses results in a decrease in LCOD standard deviation by 36%, a decrease in CI mean by 46% and a decrease in CI standard deviation by 51%, at the expense of an increase in LCOD mean by only 11%. Future work will focus on the integration of full-electric buses.

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  • Coppitters, Diederik & Verleysen, Kevin & De Paepe, Ward & Contino, Francesco, 2022. "How can renewable hydrogen compete with diesel in public transport? Robust design optimization of a hydrogen refueling station under techno-economic and environmental uncertainty," Applied Energy, Elsevier, vol. 312(C).
  • Handle: RePEc:eee:appene:v:312:y:2022:i:c:s0306261922001581
    DOI: 10.1016/j.apenergy.2022.118694
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    as
    1. Ryuji Kawamoto & Hideo Mochizuki & Yoshihisa Moriguchi & Takahiro Nakano & Masayuki Motohashi & Yuji Sakai & Atsushi Inaba, 2019. "Estimation of CO 2 Emissions of Internal Combustion Engine Vehicle and Battery Electric Vehicle Using LCA," Sustainability, MDPI, vol. 11(9), pages 1-15, May.
    2. Verleysen, Kevin & Parente, Alessandro & Contino, Francesco, 2021. "How sensitive is a dynamic ammonia synthesis process? Global sensitivity analysis of a dynamic Haber-Bosch process (for flexible seasonal energy storage)," Energy, Elsevier, vol. 232(C).
    3. Collins, Seán & Deane, John Paul & Poncelet, Kris & Panos, Evangelos & Pietzcker, Robert C. & Delarue, Erik & Ó Gallachóir, Brian Pádraig, 2017. "Integrating short term variations of the power system into integrated energy system models: A methodological review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 839-856.
    4. Boccard, Nicolas, 2009. "Capacity factor of wind power realized values vs. estimates," Energy Policy, Elsevier, vol. 37(7), pages 2679-2688, July.
    5. Fattahi, A. & Sijm, J. & Faaij, A., 2020. "A systemic approach to analyze integrated energy system modeling tools: A review of national models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 133(C).
    6. Li Zhang & Min Zheng & Dajun Du & Yihuan Li & Minrui Fei & Yuanjun Guo & Kang Li, 2020. "State-of-Charge Estimation of Lithium-Ion Battery Pack Based on Improved RBF Neural Networks," Complexity, Hindawi, vol. 2020, pages 1-10, December.
    7. Reichenberg, Lina & Hedenus, Fredrik & Odenberger, Mikael & Johnsson, Filip, 2018. "The marginal system LCOE of variable renewables – Evaluating high penetration levels of wind and solar in Europe," Energy, Elsevier, vol. 152(C), pages 914-924.
    8. Zakeri, Behnam & Syri, Sanna, 2015. "Electrical energy storage systems: A comparative life cycle cost analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 42(C), pages 569-596.
    9. Edwin R. Grijalva & José María López Martínez, 2019. "Analysis of the Reduction of CO 2 Emissions in Urban Environments by Replacing Conventional City Buses by Electric Bus Fleets: Spain Case Study," Energies, MDPI, vol. 12(3), pages 1-31, February.
    10. Zakaria, A. & Ismail, Firas B. & Lipu, M.S. Hossain & Hannan, M.A., 2020. "Uncertainty models for stochastic optimization in renewable energy applications," Renewable Energy, Elsevier, vol. 145(C), pages 1543-1571.
    11. Burkhardt, Jörg & Patyk, Andreas & Tanguy, Philippe & Retzke, Carsten, 2016. "Hydrogen mobility from wind energy – A life cycle assessment focusing on the fuel supply," Applied Energy, Elsevier, vol. 181(C), pages 54-64.
    12. George B. Dantzig, 1955. "Linear Programming under Uncertainty," Management Science, INFORMS, vol. 1(3-4), pages 197-206, 04-07.
    13. Deng, Zhongwei & Hu, Xiaosong & Lin, Xianke & Che, Yunhong & Xu, Le & Guo, Wenchao, 2020. "Data-driven state of charge estimation for lithium-ion battery packs based on Gaussian process regression," Energy, Elsevier, vol. 205(C).
    14. Coppitters, Diederik & De Paepe, Ward & Contino, Francesco, 2019. "Surrogate-assisted robust design optimization and global sensitivity analysis of a directly coupled photovoltaic-electrolyzer system under techno-economic uncertainty," Applied Energy, Elsevier, vol. 248(C), pages 310-320.
    15. Mavromatidis, Georgios & Orehounig, Kristina & Carmeliet, Jan, 2018. "A review of uncertainty characterisation approaches for the optimal design of distributed energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 88(C), pages 258-277.
    16. Coppitters, Diederik & De Paepe, Ward & Contino, Francesco, 2021. "Robust design optimization of a photovoltaic-battery-heat pump system with thermal storage under aleatory and epistemic uncertainty," Energy, Elsevier, vol. 229(C).
    17. Vicent Penadés-Plà & Tatiana García-Segura & Víctor Yepes, 2020. "Robust Design Optimization for Low-Cost Concrete Box-Girder Bridge," Mathematics, MDPI, vol. 8(3), pages 1-14, March.
    18. Osorio-Aravena, Juan Carlos & Aghahosseini, Arman & Bogdanov, Dmitrii & Caldera, Upeksha & Ghorbani, Narges & Mensah, Theophilus Nii Odai & Khalili, Siavash & Muñoz-Cerón, Emilio & Breyer, Christian, 2021. "The impact of renewable energy and sector coupling on the pathway towards a sustainable energy system in Chile," Renewable and Sustainable Energy Reviews, Elsevier, vol. 151(C).
    19. Zhang, Yang & Campana, Pietro Elia & Lundblad, Anders & Yan, Jinyue, 2017. "Comparative study of hydrogen storage and battery storage in grid connected photovoltaic system: Storage sizing and rule-based operation," Applied Energy, Elsevier, vol. 201(C), pages 397-411.
    20. Niaz, Saba & Manzoor, Taniya & Pandith, Altaf Hussain, 2015. "Hydrogen storage: Materials, methods and perspectives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 50(C), pages 457-469.
    21. Buttler, Alexander & Spliethoff, Hartmut, 2018. "Current status of water electrolysis for energy storage, grid balancing and sector coupling via power-to-gas and power-to-liquids: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 2440-2454.
    22. Zhang, Xiaojin & Bauer, Christian & Mutel, Christopher L. & Volkart, Kathrin, 2017. "Life Cycle Assessment of Power-to-Gas: Approaches, system variations and their environmental implications," Applied Energy, Elsevier, vol. 190(C), pages 326-338.
    23. Coppitters, Diederik & De Paepe, Ward & Contino, Francesco, 2020. "Robust design optimization and stochastic performance analysis of a grid-connected photovoltaic system with battery storage and hydrogen storage," Energy, Elsevier, vol. 213(C).
    24. Younesi, Abdollah & Shayeghi, Hossein & Safari, Amin & Siano, Pierluigi, 2020. "Assessing the resilience of multi microgrid based widespread power systems against natural disasters using Monte Carlo Simulation," Energy, Elsevier, vol. 207(C).
    25. Staffell, Iain & Pfenninger, Stefan, 2016. "Using bias-corrected reanalysis to simulate current and future wind power output," Energy, Elsevier, vol. 114(C), pages 1224-1239.
    26. Correa, G. & Muñoz, P. & Falaguerra, T. & Rodriguez, C.R., 2017. "Performance comparison of conventional, hybrid, hydrogen and electric urban buses using well to wheel analysis," Energy, Elsevier, vol. 141(C), pages 537-549.
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    Cited by:

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    2. Zheng, Yi & Wang, Jiawei & You, Shi & Li, Ximei & Bindner, Henrik W. & Münster, Marie, 2023. "Data-driven scheme for optimal day-ahead operation of a wind/hydrogen system under multiple uncertainties," Applied Energy, Elsevier, vol. 329(C).
    3. Nithin Isaac & Akshay K. Saha, 2024. "Forecasting Hydrogen Vehicle Refuelling for Sustainable Transportation: A Light Gradient-Boosting Machine Model," Sustainability, MDPI, vol. 16(10), pages 1-24, May.
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    5. Abadie, Luis Mª & Chamorro, José M., 2023. "Investment in wind-based hydrogen production under economic and physical uncertainties," Applied Energy, Elsevier, vol. 337(C).
    6. Costa, Alexis & Coppitters, Diederik & Dubois, Lionel & Contino, Francesco & Thomas, Diane & De Weireld, Guy, 2024. "Energy, exergy, economic and environmental (4E) analysis of a cryogenic carbon purification unit with membrane for oxyfuel cement plant flue gas," Applied Energy, Elsevier, vol. 357(C).
    7. Zuzanna Kłos-Adamkiewicz & Elżbieta Szaruga & Agnieszka Gozdek & Magdalena Kogut-Jaworska, 2023. "Links between the Energy Intensity of Public Urban Transport, Regional Economic Growth and Urbanisation: The Case of Poland," Energies, MDPI, vol. 16(9), pages 1-25, April.
    8. Zahir Barahmand & Marianne S. Eikeland, 2022. "Techno-Economic and Life Cycle Cost Analysis through the Lens of Uncertainty: A Scoping Review," Sustainability, MDPI, vol. 14(19), pages 1-22, September.

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