IDEAS home Printed from https://ideas.repec.org/a/eee/rensus/v66y2016icp27-37.html
   My bibliography  Save this article

Developing a thermally compensated electrolyser model coupled with pressurised hydrogen storage for modelling the energy efficiency of hydrogen energy storage systems and identifying their operation performance issues

Author

Listed:
  • Ali, Dallia
  • Gazey, Ross
  • Aklil, Daniel

Abstract

This paper proposes a thermally compensated electrolyser model coupled with a Pressurised Hydrogen Storage model for modelling Renewable Hydrogen Energy Storage Systems needed to support the uptake of renewable energy sources (RES) integration into the grid. The model accurately simulates the output of real world electrolyser and hydrogen storage installations and can be used as a tool for assessing their integrity with intermittent RES.

Suggested Citation

  • Ali, Dallia & Gazey, Ross & Aklil, Daniel, 2016. "Developing a thermally compensated electrolyser model coupled with pressurised hydrogen storage for modelling the energy efficiency of hydrogen energy storage systems and identifying their operation p," Renewable and Sustainable Energy Reviews, Elsevier, vol. 66(C), pages 27-37.
    • Handle: RePEc:eee:rensus:v:66:y:2016:i:c:p:27-37
    DOI: 10.1016/j.rser.2016.07.067
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1364032116304117
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.rser.2016.07.067?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. Connolly, D. & Lund, H. & Mathiesen, B.V. & Leahy, M., 2010. "A review of computer tools for analysing the integration of renewable energy into various energy systems," Applied Energy, Elsevier, vol. 87(4), pages 1059-1082, April.
    2. Manfren, Massimiliano & Caputo, Paola & Costa, Gaia, 2011. "Paradigm shift in urban energy systems through distributed generation: Methods and models," Applied Energy, Elsevier, vol. 88(4), pages 1032-1048, April.
    3. Moura, Pedro S. & de Almeida, Aníbal T., 2010. "The role of demand-side management in the grid integration of wind power," Applied Energy, Elsevier, vol. 87(8), pages 2581-2588, August.
    4. Erdinc, O. & Uzunoglu, M., 2012. "Optimum design of hybrid renewable energy systems: Overview of different approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(3), pages 1412-1425.
    5. Coll-Mayor, Debora & Paget, Mia & Lightner, Eric, 2007. "Future intelligent power grids: Analysis of the vision in the European Union and the United States," Energy Policy, Elsevier, vol. 35(4), pages 2453-2465, April.
    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. Huang, Chunjun & Zong, Yi & You, Shi & Træholt, Chresten & Zheng, Yi & Wang, Jiawei & Zheng, Zixuan & Xiao, Xianyong, 2023. "Economic and resilient operation of hydrogen-based microgrids: An improved MPC-based optimal scheduling scheme considering security constraints of hydrogen facilities," Applied Energy, Elsevier, vol. 335(C).
    2. Lee, Boreum & Lim, Dongjun & Lee, Hyunjun & Byun, Manhee & Lim, Hankwon, 2021. "Techno-economic analysis of H2 energy storage system based on renewable energy certificate," Renewable Energy, Elsevier, vol. 167(C), pages 91-98.
    3. Raj, Pankaj & Subudhi, Sudhakar, 2018. "A review of studies using nanofluids in flat-plate and direct absorption solar collectors," Renewable and Sustainable Energy Reviews, Elsevier, vol. 84(C), pages 54-74.
    4. Zheng, Yi & You, Shi & Bindner, Henrik W. & Münster, Marie, 2022. "Optimal day-ahead dispatch of an alkaline electrolyser system concerning thermal–electric properties and state-transitional dynamics," Applied Energy, Elsevier, vol. 307(C).

    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. Gamarra, Carlos & Guerrero, Josep M., 2015. "Computational optimization techniques applied to microgrids planning: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 413-424.
    2. Rae, Callum & Kerr, Sandy & Maroto-Valer, M. Mercedes, 2020. "Upscaling smart local energy systems: A review of technical barriers," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
    3. Ma, Weiwu & Xue, Xinpei & Liu, Gang, 2018. "Techno-economic evaluation for hybrid renewable energy system: Application and merits," Energy, Elsevier, vol. 159(C), pages 385-409.
    4. Villa-Arrieta, Manuel & Sumper, Andreas, 2018. "A model for an economic evaluation of energy systems using TRNSYS," Applied Energy, Elsevier, vol. 215(C), pages 765-777.
    5. Aste, Niccolò & Del Pero, Claudio & Leonforte, Fabrizio & Manfren, Massimiliano, 2013. "A simplified model for the estimation of energy production of PV systems," Energy, Elsevier, vol. 59(C), pages 503-512.
    6. Theresa Liegl & Simon Schramm & Philipp Kuhn & Thomas Hamacher, 2023. "Considering Socio-Technical Parameters in Energy System Models—The Current Status and Next Steps," Energies, MDPI, vol. 16(20), pages 1-19, October.
    7. Mehrabankhomartash, Mahmoud & Rayati, Mohammad & Sheikhi, Aras & Ranjbar, Ali Mohammad, 2017. "Practical battery size optimization of a PV system by considering individual customer damage function," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 36-50.
    8. Huang, Zishuo & Yu, Hang & Chu, Xiangyang & Peng, Zhenwei, 2017. "A goal programming based model system for community energy plan," Energy, Elsevier, vol. 134(C), pages 893-901.
    9. Sinha, Sunanda & Chandel, S.S., 2014. "Review of software tools for hybrid renewable energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 32(C), pages 192-205.
    10. Aste, Niccolò & Adhikari, R.S. & Manfren, Massimiliano, 2013. "Cost optimal analysis of heat pump technology adoption in residential reference buildings," Renewable Energy, Elsevier, vol. 60(C), pages 615-624.
    11. Cédric Clastres, 2011. "Smart grids : Another step towards competition, energy security and climate change objectives," Post-Print halshs-00617702, HAL.
    12. Alaia Sola & Cristina Corchero & Jaume Salom & Manel Sanmarti, 2018. "Simulation Tools to Build Urban-Scale Energy Models: A Review," Energies, MDPI, vol. 11(12), pages 1-24, November.
    13. Caballero, F. & Sauma, E. & Yanine, F., 2013. "Business optimal design of a grid-connected hybrid PV (photovoltaic)-wind energy system without energy storage for an Easter Island's block," Energy, Elsevier, vol. 61(C), pages 248-261.
    14. Yazdanie, M. & Orehounig, K., 2021. "Advancing urban energy system planning and modeling approaches: Gaps and solutions in perspective," Renewable and Sustainable Energy Reviews, Elsevier, vol. 137(C).
    15. Welsch, M. & Hermann, S. & Howells, M. & Rogner, H.H. & Young, C. & Ramma, I. & Bazilian, M. & Fischer, G. & Alfstad, T. & Gielen, D. & Le Blanc, D. & Röhrl, A. & Steduto, P. & Müller, A., 2014. "Adding value with CLEWS – Modelling the energy system and its interdependencies for Mauritius," Applied Energy, Elsevier, vol. 113(C), pages 1434-1445.
    16. Jha, Sunil Kr. & Bilalovic, Jasmin & Jha, Anju & Patel, Nilesh & Zhang, Han, 2017. "Renewable energy: Present research and future scope of Artificial Intelligence," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 297-317.
    17. Xie, Y.L. & Huang, G.H. & Li, W. & Ji, L., 2014. "Carbon and air pollutants constrained energy planning for clean power generation with a robust optimization model—A case study of Jining City, China," Applied Energy, Elsevier, vol. 136(C), pages 150-167.
    18. Fuchs, Marcus & Teichmann, Jens & Lauster, Moritz & Remmen, Peter & Streblow, Rita & Müller, Dirk, 2016. "Workflow automation for combined modeling of buildings and district energy systems," Energy, Elsevier, vol. 117(P2), pages 478-484.
    19. Karni Siraganyan & Amarasinghage Tharindu Dasun Perera & Jean-Louis Scartezzini & Dasaraden Mauree, 2019. "Eco-Sim: A Parametric Tool to Evaluate the Environmental and Economic Feasibility of Decentralized Energy Systems," Energies, MDPI, vol. 12(5), pages 1-22, February.
    20. Contreras, Javier & Rodríguez, Yeny E., 2014. "GARCH-based put option valuation to maximize benefit of wind investors," Applied Energy, Elsevier, vol. 136(C), pages 259-268.

    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:rensus:v:66:y:2016:i:c:p:27-37. 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/600126/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.