IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v224y2021ics0360544221003510.html
   My bibliography  Save this article

The impact of urban district composition on storage technology reliance: trade-offs between thermal storage, batteries, and power-to-hydrogen

Author

Listed:
  • Petkov, Ivalin
  • Gabrielli, Paolo
  • Spokaite, Marija

Abstract

The composition of urban districts - residential, commercial, or ‘mixed’ topologies - can have drastically different energy load profiles and peak demands, leading to altered optimal District Multi-Energy System (D-MES) designs. Although demand-influenced differences in D-MES designs are generally understood, there is a research gap of how the interplay of various storage technologies differs between topologies. In this paper, we investigate the extent of D-MES reliance on storage technologies over various district topologies in central Europe. The core of this analysis relies on a multi-objective MILP optimization model utilized in an uncertainty analysis framework.

Suggested Citation

  • Petkov, Ivalin & Gabrielli, Paolo & Spokaite, Marija, 2021. "The impact of urban district composition on storage technology reliance: trade-offs between thermal storage, batteries, and power-to-hydrogen," Energy, Elsevier, vol. 224(C).
    • Handle: RePEc:eee:energy:v:224:y:2021:i:c:s0360544221003510
    DOI: 10.1016/j.energy.2021.120102
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544221003510
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2021.120102?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. Mancarella, Pierluigi, 2014. "MES (multi-energy systems): An overview of concepts and evaluation models," Energy, Elsevier, vol. 65(C), pages 1-17.
    2. Gabrielli, Paolo & Gazzani, Matteo & Martelli, Emanuele & Mazzotti, Marco, 2018. "Optimal design of multi-energy systems with seasonal storage," Applied Energy, Elsevier, vol. 219(C), pages 408-424.
    3. 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).
    4. Ferrari, Simone & Zagarella, Federica & Caputo, Paola & D'Amico, Antonino, 2019. "Results of a literature review on methods for estimating buildings energy demand at district level," Energy, Elsevier, vol. 175(C), pages 1130-1137.
    5. Gabrielli, Paolo & Fürer, Florian & Mavromatidis, Georgios & Mazzotti, Marco, 2019. "Robust and optimal design of multi-energy systems with seasonal storage through uncertainty analysis," Applied Energy, Elsevier, vol. 238(C), pages 1192-1210.
    6. Kotzur, Leander & Markewitz, Peter & Robinius, Martin & Stolten, Detlef, 2018. "Time series aggregation for energy system design: Modeling seasonal storage," Applied Energy, Elsevier, vol. 213(C), pages 123-135.
    7. Bracco, Stefano & Dentici, Gabriele & Siri, Silvia, 2016. "DESOD: a mathematical programming tool to optimally design a distributed energy system," Energy, Elsevier, vol. 100(C), pages 298-309.
    8. Orehounig, Kristina & Evins, Ralph & Dorer, Viktor, 2015. "Integration of decentralized energy systems in neighbourhoods using the energy hub approach," Applied Energy, Elsevier, vol. 154(C), pages 277-289.
    9. Flores, Robert J. & Brouwer, Jacob, 2018. "Optimal design of a distributed energy resource system that economically reduces carbon emissions," Applied Energy, Elsevier, vol. 232(C), pages 119-138.
    10. Ata, Mustafa & Erenoğlu, Ayşe Kübra & Şengör, İbrahim & Erdinç, Ozan & Taşcıkaraoğlu, Akın & Catalão, João P.S., 2019. "Optimal operation of a multi-energy system considering renewable energy sources stochasticity and impacts of electric vehicles," Energy, Elsevier, vol. 186(C).
    11. Mavromatidis, Georgios & Orehounig, Kristina & Carmeliet, Jan, 2018. "Comparison of alternative decision-making criteria in a two-stage stochastic program for the design of distributed energy systems under uncertainty," Energy, Elsevier, vol. 156(C), pages 709-724.
    12. Wouters, Carmen & Fraga, Eric S. & James, Adrian M., 2015. "An energy integrated, multi-microgrid, MILP (mixed-integer linear programming) approach for residential distributed energy system planning – A South Australian case-study," Energy, Elsevier, vol. 85(C), pages 30-44.
    13. Keirstead, James & Jennings, Mark & Sivakumar, Aruna, 2012. "A review of urban energy system models: Approaches, challenges and opportunities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(6), pages 3847-3866.
    14. Murray, Portia & Carmeliet, Jan & Orehounig, Kristina, 2020. "Multi-Objective Optimisation of Power-to-Mobility in Decentralised Multi-Energy Systems," Energy, Elsevier, vol. 205(C).
    15. Wu, Raphael & Mavromatidis, Georgios & Orehounig, Kristina & Carmeliet, Jan, 2017. "Multiobjective optimisation of energy systems and building envelope retrofit in a residential community," Applied Energy, Elsevier, vol. 190(C), pages 634-649.
    16. Mavromatidis, Georgios & Orehounig, Kristina & Carmeliet, Jan, 2018. "Design of distributed energy systems under uncertainty: A two-stage stochastic programming approach," Applied Energy, Elsevier, vol. 222(C), pages 932-950.
    17. Shams, Mohammad H. & Shahabi, Majid & Kia, Mohsen & Heidari, Alireza & Lotfi, Mohamed & Shafie-khah, Miadreza & Catalão, João P.S., 2019. "Optimal operation of electrical and thermal resources in microgrids with energy hubs considering uncertainties," Energy, Elsevier, vol. 187(C).
    18. Guelpa, Elisa & Marincioni, Ludovica & Deputato, Stefania & Capone, Martina & Amelio, Stefano & Pochettino, Enrico & Verda, Vittorio, 2019. "Demand side management in district heating networks: A real application," Energy, Elsevier, vol. 182(C), pages 433-442.
    19. Karmellos, M. & Georgiou, P.N. & Mavrotas, G., 2019. "A comparison of methods for the optimal design of Distributed Energy Systems under uncertainty," Energy, Elsevier, vol. 178(C), pages 318-333.
    20. Mehleri, Eugenia D. & Sarimveis, Haralambos & Markatos, Nikolaos C. & Papageorgiou, Lazaros G., 2012. "A mathematical programming approach for optimal design of distributed energy systems at the neighbourhood level," Energy, Elsevier, vol. 44(1), pages 96-104.
    21. Mavromatidis, Georgios & Orehounig, Kristina & Carmeliet, Jan, 2018. "Uncertainty and global sensitivity analysis for the optimal design of distributed energy systems," Applied Energy, Elsevier, vol. 214(C), pages 219-238.
    22. Murray, Portia & Orehounig, Kristina & Grosspietsch, David & Carmeliet, Jan, 2018. "A comparison of storage systems in neighbourhood decentralized energy system applications from 2015 to 2050," Applied Energy, Elsevier, vol. 231(C), pages 1285-1306.
    23. Majewski, Dinah Elena & Lampe, Matthias & Voll, Philip & Bardow, André, 2017. "TRusT: A Two-stage Robustness Trade-off approach for the design of decentralized energy supply systems," Energy, Elsevier, vol. 118(C), pages 590-599.
    24. Nastasi, Benedetto & Lo Basso, Gianluigi, 2016. "Hydrogen to link heat and electricity in the transition towards future Smart Energy Systems," Energy, Elsevier, vol. 110(C), pages 5-22.
    25. Comodi, Gabriele & Bartolini, Andrea & Carducci, Francesco & Nagaranjan, Balamurugan & Romagnoli, Alessandro, 2019. "Achieving low carbon local energy communities in hot climates by exploiting networks synergies in multi energy systems," Applied Energy, Elsevier, vol. 256(C).
    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. Perera, A.T.D. & Soga, Kenichi & Xu, Yujie & Nico, Peter S. & Hong, Tianzhen, 2023. "Enhancing flexibility for climate change using seasonal energy storage (aquifer thermal energy storage) in distributed energy systems," Applied Energy, Elsevier, vol. 340(C).
    2. Dong, Haoxin & Shan, Zijing & Zhou, Jianli & Xu, Chuanbo & Chen, Wenjun, 2023. "Refined modeling and co-optimization of electric-hydrogen-thermal-gas integrated energy system with hybrid energy storage," Applied Energy, Elsevier, vol. 351(C).
    3. Christina Papadimitriou & Marialaura Di Somma & Chrysanthos Charalambous & Martina Caliano & Valeria Palladino & Andrés Felipe Cortés Borray & Amaia González-Garrido & Nerea Ruiz & Giorgio Graditi, 2023. "A Comprehensive Review of the Design and Operation Optimization of Energy Hubs and Their Interaction with the Markets and External Networks," Energies, MDPI, vol. 16(10), pages 1-46, May.
    4. Le, Tay Son & Nguyen, Tuan Ngoc & Bui, Dac-Khuong & Ngo, Tuan Duc, 2023. "Optimal sizing of renewable energy storage: A techno-economic analysis of hydrogen, battery and hybrid systems considering degradation and seasonal storage," Applied Energy, Elsevier, vol. 336(C).
    5. Els van der Roest & Theo Fens & Martin Bloemendal & Stijn Beernink & Jan Peter van der Hoek & Ad J. M. van Wijk, 2021. "The Impact of System Integration on System Costs of a Neighborhood Energy and Water System," Energies, MDPI, vol. 14(9), pages 1-33, May.
    6. Kuang, Zhonghong & Chen, Qi & Yu, Yang, 2022. "Assessing the CO2-emission risk due to wind-energy uncertainty," Applied Energy, Elsevier, vol. 310(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. Mavromatidis, Georgios & Petkov, Ivalin, 2021. "MANGO: A novel optimization model for the long-term, multi-stage planning of decentralized multi-energy systems," Applied Energy, Elsevier, vol. 288(C).
    2. 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).
    3. Kachirayil, Febin & Weinand, Jann Michael & Scheller, Fabian & McKenna, Russell, 2022. "Reviewing local and integrated energy system models: insights into flexibility and robustness challenges," Applied Energy, Elsevier, vol. 324(C).
    4. Pickering, Bryn & Choudhary, Ruchi, 2021. "Quantifying resilience in energy systems with out-of-sample testing," Applied Energy, Elsevier, vol. 285(C).
    5. Niu, Jide & Li, Xiaoyuan & Tian, Zhe & Yang, Hongxing, 2023. "A framework for quantifying the value of information to mitigate risk in the optimal design of distributed energy systems under uncertainty," Applied Energy, Elsevier, vol. 350(C).
    6. Lerbinger, Alicia & Petkov, Ivalin & Mavromatidis, Georgios & Knoeri, Christof, 2023. "Optimal decarbonization strategies for existing districts considering energy systems and retrofits," Applied Energy, Elsevier, vol. 352(C).
    7. Christina Papadimitriou & Marialaura Di Somma & Chrysanthos Charalambous & Martina Caliano & Valeria Palladino & Andrés Felipe Cortés Borray & Amaia González-Garrido & Nerea Ruiz & Giorgio Graditi, 2023. "A Comprehensive Review of the Design and Operation Optimization of Energy Hubs and Their Interaction with the Markets and External Networks," Energies, MDPI, vol. 16(10), pages 1-46, May.
    8. Gabrielli, Paolo & Fürer, Florian & Mavromatidis, Georgios & Mazzotti, Marco, 2019. "Robust and optimal design of multi-energy systems with seasonal storage through uncertainty analysis," Applied Energy, Elsevier, vol. 238(C), pages 1192-1210.
    9. Petkov, Ivalin & Mavromatidis, Georgios & Knoeri, Christof & Allan, James & Hoffmann, Volker H., 2022. "MANGOret: An optimization framework for the long-term investment planning of building multi-energy system and envelope retrofits," Applied Energy, Elsevier, vol. 314(C).
    10. Mittelviefhaus, Moritz & Pareschi, Giacomo & Allan, James & Georges, Gil & Boulouchos, Konstantinos, 2021. "Optimal investment and scheduling of residential multi-energy systems including electric mobility: A cost-effective approach to climate change mitigation," Applied Energy, Elsevier, vol. 301(C).
    11. Maximilian Hoffmann & Leander Kotzur & Detlef Stolten & Martin Robinius, 2020. "A Review on Time Series Aggregation Methods for Energy System Models," Energies, MDPI, vol. 13(3), pages 1-61, February.
    12. Karmellos, M. & Georgiou, P.N. & Mavrotas, G., 2019. "A comparison of methods for the optimal design of Distributed Energy Systems under uncertainty," Energy, Elsevier, vol. 178(C), pages 318-333.
    13. Waibel, Christoph & Evins, Ralph & Carmeliet, Jan, 2019. "Co-simulation and optimization of building geometry and multi-energy systems: Interdependencies in energy supply, energy demand and solar potentials," Applied Energy, Elsevier, vol. 242(C), pages 1661-1682.
    14. Els van der Roest & Theo Fens & Martin Bloemendal & Stijn Beernink & Jan Peter van der Hoek & Ad J. M. van Wijk, 2021. "The Impact of System Integration on System Costs of a Neighborhood Energy and Water System," Energies, MDPI, vol. 14(9), pages 1-33, May.
    15. Hoffmann, Maximilian & Priesmann, Jan & Nolting, Lars & Praktiknjo, Aaron & Kotzur, Leander & Stolten, Detlef, 2021. "Typical periods or typical time steps? A multi-model analysis to determine the optimal temporal aggregation for energy system models," Applied Energy, Elsevier, vol. 304(C).
    16. 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.
    17. Heendeniya, Charitha Buddhika & Sumper, Andreas & Eicker, Ursula, 2020. "The multi-energy system co-planning of nearly zero-energy districts – Status-quo and future research potential," Applied Energy, Elsevier, vol. 267(C).
    18. Klemm, Christian & Vennemann, Peter, 2021. "Modeling and optimization of multi-energy systems in mixed-use districts: A review of existing methods and approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    19. Mavromatidis, Georgios & Orehounig, Kristina & Carmeliet, Jan, 2018. "Uncertainty and global sensitivity analysis for the optimal design of distributed energy systems," Applied Energy, Elsevier, vol. 214(C), pages 219-238.
    20. 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).

    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:energy:v:224:y:2021:i:c:s0360544221003510. 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.journals.elsevier.com/energy .

    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.