IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v220y2018icp893-920.html
   My bibliography  Save this article

A multi-objective MILP model for the design and operation of future integrated multi-vector energy networks capturing detailed spatio-temporal dependencies

Author

Listed:
  • Samsatli, Sheila
  • Samsatli, Nouri J.

Abstract

A multi-objective optimisation model, based on mixed integer linear programming, is presented that can simultaneously determine the design and operation of any integrated multi-vector energy networks. It can answer variants of the following questions:

Suggested Citation

  • Samsatli, Sheila & Samsatli, Nouri J., 2018. "A multi-objective MILP model for the design and operation of future integrated multi-vector energy networks capturing detailed spatio-temporal dependencies," Applied Energy, Elsevier, vol. 220(C), pages 893-920.
    • Handle: RePEc:eee:appene:v:220:y:2018:i:c:p:893-920
    DOI: 10.1016/j.apenergy.2017.09.055
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261917313375
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2017.09.055?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. Xue, Shuai & Lewandowski, Iris & Wang, Xiaoyu & Yi, Zili, 2016. "Assessment of the production potentials of Miscanthus on marginal land in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 932-943.
    2. Kannan, Ramachandran, 2011. "The development and application of a temporal MARKAL energy system model using flexible time slicing," Applied Energy, Elsevier, vol. 88(6), pages 2261-2272, June.
    3. Devlin, Joseph & Li, Kang & Higgins, Paraic & Foley, Aoife, 2017. "A multi vector energy analysis for interconnected power and gas systems," Applied Energy, Elsevier, vol. 192(C), pages 315-328.
    4. Calderón, Andrés J. & Agnolucci, Paolo & Papageorgiou, Lazaros G., 2017. "An optimisation framework for the strategic design of synthetic natural gas (BioSNG) supply chains," Applied Energy, Elsevier, vol. 187(C), pages 929-955.
    5. Good, Nicholas & Martínez Ceseña, Eduardo A. & Zhang, Lingxi & Mancarella, Pierluigi, 2016. "Techno-economic and business case assessment of low carbon technologies in distributed multi-energy systems," Applied Energy, Elsevier, vol. 167(C), pages 158-172.
    6. Staffell, Iain & Green, Richard, 2014. "How does wind farm performance decline with age?," Renewable Energy, Elsevier, vol. 66(C), pages 775-786.
    7. Liu, Xuezhi & Mancarella, Pierluigi, 2016. "Modelling, assessment and Sankey diagrams of integrated electricity-heat-gas networks in multi-vector district energy systems," Applied Energy, Elsevier, vol. 167(C), pages 336-352.
    8. Samsatli, Sheila & Samsatli, Nouri J. & Shah, Nilay, 2015. "BVCM: A comprehensive and flexible toolkit for whole system biomass value chain analysis and optimisation – Mathematical formulation," Applied Energy, Elsevier, vol. 147(C), pages 131-160.
    Full references (including those not matched with items on IDEAS)

    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. Danko Vidović & Elis Sutlović & Matislav Majstrović, 2021. "A Unique Electrical Model for the Steady-State Analysis of a Multi-Energy System," Energies, MDPI, vol. 14(18), pages 1-23, September.
    2. Scheller, Fabian & Bruckner, Thomas, 2019. "Energy system optimization at the municipal level: An analysis of modeling approaches and challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 105(C), pages 444-461.
    3. Hosseini, Seyed Hamid Reza & Allahham, Adib & Walker, Sara Louise & Taylor, Phil, 2020. "Optimal planning and operation of multi-vector energy networks: A systematic review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 133(C).
    4. 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).
    5. Good, Nicholas & Martínez Ceseña, Eduardo A. & Heltorp, Christopher & Mancarella, Pierluigi, 2019. "A transactive energy modelling and assessment framework for demand response business cases in smart distributed multi-energy systems," Energy, Elsevier, vol. 184(C), pages 165-179.
    6. 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).
    7. Shu, Kangan & Ai, Xiaomeng & Fang, Jiakun & Yao, Wei & Chen, Zhe & He, Haibo & Wen, Jinyu, 2019. "Real-time subsidy based robust scheduling of the integrated power and gas system," Applied Energy, Elsevier, vol. 236(C), pages 1158-1167.
    8. Hall, Lisa M.H. & Buckley, Alastair R., 2016. "A review of energy systems models in the UK: Prevalent usage and categorisation," Applied Energy, Elsevier, vol. 169(C), pages 607-628.
    9. Jäger, Tobias & McKenna, Russell & Fichtner, Wolf, 2015. "Onshore wind energy in Baden-Württemberg: a bottom-up economic assessment of the socio-technical potential," Working Paper Series in Production and Energy 7, Karlsruhe Institute of Technology (KIT), Institute for Industrial Production (IIP).
    10. Kolb, Sebastian & Plankenbühler, Thomas & Frank, Jonas & Dettelbacher, Johannes & Ludwig, Ralf & Karl, Jürgen & Dillig, Marius, 2021. "Scenarios for the integration of renewable gases into the German natural gas market – A simulation-based optimisation approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 139(C).
    11. Francisco Haces-Fernandez, 2020. "GoWInD: Wind Energy Spatiotemporal Assessment and Characterization of End-of-Life Activities," Energies, MDPI, vol. 13(22), pages 1-20, November.
    12. Abdollahzadeh, Hadi & Atashgar, Karim & Abbasi, Morteza, 2016. "Multi-objective opportunistic maintenance optimization of a wind farm considering limited number of maintenance groups," Renewable Energy, Elsevier, vol. 88(C), pages 247-261.
    13. Farrokhifar, Meisam & Nie, Yinghui & Pozo, David, 2020. "Energy systems planning: A survey on models for integrated power and natural gas networks coordination," Applied Energy, Elsevier, vol. 262(C).
    14. Niklas Andersen & Ola Eriksson & Karl Hillman & Marita Wallhagen, 2016. "Wind Turbines’ End-of-Life: Quantification and Characterisation of Future Waste Materials on a National Level," Energies, MDPI, vol. 9(12), pages 1-24, November.
    15. Abadie, Luis Mª & Chamorro, José M., 2023. "Investment in wind-based hydrogen production under economic and physical uncertainties," Applied Energy, Elsevier, vol. 337(C).
    16. Wang, Lixiao & Jing, Z.X. & Zheng, J.H. & Wu, Q.H. & Wei, Feng, 2018. "Decentralized optimization of coordinated electrical and thermal generations in hierarchical integrated energy systems considering competitive individuals," Energy, Elsevier, vol. 158(C), pages 607-622.
    17. Zhao, Ming & Memon, Muhammad Zaki & Ji, Guozhao & Yang, Xiaoxiao & Vuppaladadiyam, Arun K. & Song, Yinqiang & Raheem, Abdul & Li, Jinhui & Wang, Wei & Zhou, Hui, 2020. "Alkali metal bifunctional catalyst-sorbents enabled biomass pyrolysis for enhanced hydrogen production," Renewable Energy, Elsevier, vol. 148(C), pages 168-175.
    18. Hayashi, Daisuke & Huenteler, Joern & Lewis, Joanna I., 2018. "Gone with the wind: A learning curve analysis of China's wind power industry," Energy Policy, Elsevier, vol. 120(C), pages 38-51.
    19. Ramirez Camargo, Luis & Gruber, Katharina & Nitsch, Felix, 2019. "Assessing variables of regional reanalysis data sets relevant for modelling small-scale renewable energy systems," Renewable Energy, Elsevier, vol. 133(C), pages 1468-1478.
    20. Cannon, D.J. & Brayshaw, D.J. & Methven, J. & Coker, P.J. & Lenaghan, D., 2015. "Using reanalysis data to quantify extreme wind power generation statistics: A 33 year case study in Great Britain," Renewable Energy, Elsevier, vol. 75(C), pages 767-778.

    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:220:y:2018:i:c:p:893-920. 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.