IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v312y2022ics0306261922001581.html
   My bibliography  Save this article

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

Author

Listed:
  • 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.

Suggested Citation

  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261922001581
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2022.118694?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    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. 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.
    3. 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).
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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).
    10. 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).
    11. 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.
    12. 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.
    13. 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).
    14. Boccard, Nicolas, 2009. "Capacity factor of wind power realized values vs. estimates," Energy Policy, Elsevier, vol. 37(7), pages 2679-2688, July.
    15. 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.
    16. 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.
    17. 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.
    18. George B. Dantzig, 1955. "Linear Programming under Uncertainty," Management Science, INFORMS, vol. 1(3-4), pages 197-206, 04-07.
    19. 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).
    20. 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.
    21. 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).
    22. 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.
    23. 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).
    24. 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.
    25. 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.
    26. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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).
    2. Abadie, Luis Mª & Chamorro, José M., 2023. "Investment in wind-based hydrogen production under economic and physical uncertainties," Applied Energy, Elsevier, vol. 337(C).
    3. 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).
    4. 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.
    5. Gao, Chong & Lin, Junjie & Zeng, Jianfeng & Han, Fengwu, 2022. "Wind-photovoltaic co-generation prediction and energy scheduling of low-carbon complex regional integrated energy system with hydrogen industry chain based on copula-MILP," Applied Energy, Elsevier, vol. 328(C).
    6. 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.
    7. Àlex Alonso-Travesset & Diederik Coppitters & Helena Martín & Jordi de la Hoz, 2023. "Economic and Regulatory Uncertainty in Renewable Energy System Design: A Review," Energies, MDPI, vol. 16(2), pages 1-30, January.
    8. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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).
    2. 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).
    3. Àlex Alonso-Travesset & Diederik Coppitters & Helena Martín & Jordi de la Hoz, 2023. "Economic and Regulatory Uncertainty in Renewable Energy System Design: A Review," Energies, MDPI, vol. 16(2), pages 1-30, January.
    4. Petkov, Ivalin & Gabrielli, Paolo, 2020. "Power-to-hydrogen as seasonal energy storage: an uncertainty analysis for optimal design of low-carbon multi-energy systems," Applied Energy, Elsevier, vol. 274(C).
    5. Wang, Jing & Kang, Lixia & Huang, Xiankun & Liu, Yongzhong, 2021. "An analysis framework for quantitative evaluation of parametric uncertainty in a cooperated energy storage system with multiple energy carriers," Energy, Elsevier, vol. 226(C).
    6. 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.
    7. Østergaard, P.A. & Lund, H. & Thellufsen, J.Z. & Sorknæs, P. & Mathiesen, B.V., 2022. "Review and validation of EnergyPLAN," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    8. Go, Jaehyun & Byun, Jiwook & Orehounig, Kristina & Heo, Yeonsook, 2023. "Battery-H2 storage system for self-sufficiency in residential buildings under different electric heating system scenarios," Applied Energy, Elsevier, vol. 337(C).
    9. Bareiß, Kay & de la Rua, Cristina & Möckl, Maximilian & Hamacher, Thomas, 2019. "Life cycle assessment of hydrogen from proton exchange membrane water electrolysis in future energy systems," Applied Energy, Elsevier, vol. 237(C), pages 862-872.
    10. Qichen Wang & Zhengmeng Hou & Yilin Guo & Liangchao Huang & Yanli Fang & Wei Sun & Yuhan Ge, 2023. "Enhancing Energy Transition through Sector Coupling: A Review of Technologies and Models," Energies, MDPI, vol. 16(13), pages 1-31, July.
    11. Xavier Rixhon & Gauthier Limpens & Diederik Coppitters & Hervé Jeanmart & Francesco Contino, 2021. "The Role of Electrofuels under Uncertainties for the Belgian Energy Transition," Energies, MDPI, vol. 14(13), pages 1-23, July.
    12. Baldi, Francesco & Coraddu, Andrea & Kalikatzarakis, Miltiadis & Jeleňová, Diana & Collu, Maurizio & Race, Julia & Maréchal, François, 2022. "Optimisation-based system designs for deep offshore wind farms including power to gas technologies," Applied Energy, Elsevier, vol. 310(C).
    13. Guerra, K. & Haro, P. & Gutiérrez, R.E. & Gómez-Barea, A., 2022. "Facing the high share of variable renewable energy in the power system: Flexibility and stability requirements," Applied Energy, Elsevier, vol. 310(C).
    14. Wang, Jiajia & Yue, Xiyan & Wang, Peifen & Yu, Tao & Du, Xiao & Hao, Xiaogang & Abudula, Abuliti & Guan, Guoqing, 2022. "Electrochemical technologies for lithium recovery from liquid resources: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 154(C).
    15. Liu, Hailiang & Brown, Tom & Andresen, Gorm Bruun & Schlachtberger, David P. & Greiner, Martin, 2019. "The role of hydro power, storage and transmission in the decarbonization of the Chinese power system," Applied Energy, Elsevier, vol. 239(C), pages 1308-1321.
    16. Takyi-Aninakwa, Paul & Wang, Shunli & Zhang, Hongying & Yang, Xiaoyong & Fernandez, Carlos, 2022. "An optimized long short-term memory-weighted fading extended Kalman filtering model with wide temperature adaptation for the state of charge estimation of lithium-ion batteries," Applied Energy, Elsevier, vol. 326(C).
    17. Chen, Zheng & Zhao, Hongqian & Shu, Xing & Zhang, Yuanjian & Shen, Jiangwei & Liu, Yonggang, 2021. "Synthetic state of charge estimation for lithium-ion batteries based on long short-term memory network modeling and adaptive H-Infinity filter," Energy, Elsevier, vol. 228(C).
    18. Gorre, Jachin & Ortloff, Felix & van Leeuwen, Charlotte, 2019. "Production costs for synthetic methane in 2030 and 2050 of an optimized Power-to-Gas plant with intermediate hydrogen storage," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    19. Hu, Chunsheng & Ma, Liang & Guo, Shanshan & Guo, Gangsheng & Han, Zhiqiang, 2022. "Deep learning enabled state-of-charge estimation of LiFePO4 batteries: A systematic validation on state-of-the-art charging protocols," Energy, Elsevier, vol. 246(C).
    20. Yadav, Deepak & Banerjee, Rangan, 2020. "Net energy and carbon footprint analysis of solar hydrogen production from the high-temperature electrolysis process," Applied Energy, Elsevier, vol. 262(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:312:y:2022:i:c:s0306261922001581. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.