IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v283y2023ics0360544223024507.html
   My bibliography  Save this article

Linear or mixed integer programming in long-term energy systems modeling – A comparative analysis for a local expanding heating system

Author

Listed:
  • Vilén, Karl
  • Ahlgren, Erik O.

Abstract

Most computer models used in energy systems optimization modeling studies are formulated using linear equations. However, since linear formulations do not always well reflect real-world conditions, they may not always be adequate as policy and support tools. This is particularly the case for local system studies attempting to represent technologies at the individual scale, as in the case for local heating system modeling. Thus, the aim of this paper is to investigate differences in the resulting heating solutions and model solution times for a local expanding heating system. Three different investment cost structures for individual and district heating solutions for the heating of new housing are investigated using linear and mixed integer linear programming. The results show that the use of district heating is higher for the cost structures that use mixed integer linear programming than it is for the linear cost structures. This result is attributed mainly to the fact that individual air-to-water heat pumps benefit from the linear equation formulation due to its high coefficient of performance during summertime. This finding is important to consider when modeling local energy systems. The solution time is, however, significantly shorter for the linear formulations than for the mixed integer linear formulations.

Suggested Citation

  • Vilén, Karl & Ahlgren, Erik O., 2023. "Linear or mixed integer programming in long-term energy systems modeling – A comparative analysis for a local expanding heating system," Energy, Elsevier, vol. 283(C).
    • Handle: RePEc:eee:energy:v:283:y:2023:i:c:s0360544223024507
    DOI: 10.1016/j.energy.2023.129056
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544223024507
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2023.129056?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. Sadeghi, Hadi & Rashidinejad, Masoud & Abdollahi, Amir, 2017. "A comprehensive sequential review study through the generation expansion planning," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 1369-1394.
    2. Xiao, Biao & He, Lin & Zhang, Shihang & Kong, Tingting & Hu, Bin & Wang, R.Z., 2020. "Comparison and analysis on air-to-air and air-to-water heat pump heating systems," Renewable Energy, Elsevier, vol. 146(C), pages 1888-1896.
    3. Scott, Ian J. & Carvalho, Pedro M.S. & Botterud, Audun & Silva, Carlos A., 2021. "Long-term uncertainties in generation expansion planning: Implications for electricity market modelling and policy," Energy, Elsevier, vol. 227(C).
    4. O'Hegarty, R. & Kinnane, O. & Lennon, D. & Colclough, S., 2022. "Air-to-water heat pumps: Review and analysis of the performance gap between in-use and product rated performance," Renewable and Sustainable Energy Reviews, Elsevier, vol. 155(C).
    5. Cuisinier, Étienne & Lemaire, Pierre & Penz, Bernard & Ruby, Alain & Bourasseau, Cyril, 2022. "New rolling horizon optimization approaches to balance short-term and long-term decisions: An application to energy planning," Energy, Elsevier, vol. 245(C).
    6. Chang, Miguel & Thellufsen, Jakob Zink & Zakeri, Behnam & Pickering, Bryn & Pfenninger, Stefan & Lund, Henrik & Østergaard, Poul Alberg, 2021. "Trends in tools and approaches for modelling the energy transition," Applied Energy, Elsevier, vol. 290(C).
    7. Johansen, Katinka & Werner, Sven, 2022. "Something is sustainable in the state of Denmark: A review of the Danish district heating sector," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    8. Sandvall, Akram Fakhri & Ahlgren, Erik O. & Ekvall, Tomas, 2017. "Low-energy buildings heat supply–Modelling of energy systems and carbon emissions impacts," Energy Policy, Elsevier, vol. 111(C), pages 371-382.
    9. Siala, Kais & Mier, Mathias & Schmidt, Lukas & Torralba-Díaz, Laura & Sheykhha, Siamak & Savvidis, Georgios, 2022. "Which model features matter? An experimental approach to evaluate power market modeling choices," Energy, Elsevier, vol. 245(C).
    10. Werner, Sven, 2017. "District heating and cooling in Sweden," Energy, Elsevier, vol. 126(C), pages 419-429.
    11. Pospíšil, Jiří & Špiláček, Michal & Kudela, Libor, 2018. "Potential of predictive control for improvement of seasonal coefficient of performance of air source heat pump in Central European climate zone," Energy, Elsevier, vol. 154(C), pages 415-423.
    12. 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.
    13. Gonzalez-Salazar, Miguel & Klossek, Julia & Dubucq, Pascal & Punde, Thomas, 2023. "Portfolio optimization in district heating: Merit order or mixed integer linear programming?," Energy, Elsevier, vol. 265(C).
    14. 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.
    15. Beiron, Johanna & Göransson, Lisa & Normann, Fredrik & Johnsson, Filip, 2022. "A multiple system level modeling approach to coupled energy markets: Incentives for combined heat and power generation at the plant, city and regional energy system levels," Energy, Elsevier, vol. 254(PB).
    16. Romanchenko, Dmytro & Odenberger, Mikael & Göransson, Lisa & Johnsson, Filip, 2017. "Impact of electricity price fluctuations on the operation of district heating systems: A case study of district heating in Göteborg, Sweden," Applied Energy, Elsevier, vol. 204(C), pages 16-30.
    17. Andersen, Anders N. & Østergaard, Poul Alberg, 2019. "Analytic versus solver-based calculated daily operations of district energy plants," Energy, Elsevier, vol. 175(C), pages 333-344.
    18. Alabi, Tobi Michael & Aghimien, Emmanuel I. & Agbajor, Favour D. & Yang, Zaiyue & Lu, Lin & Adeoye, Adebusola R. & Gopaluni, Bhushan, 2022. "A review on the integrated optimization techniques and machine learning approaches for modeling, prediction, and decision making on integrated energy systems," Renewable Energy, Elsevier, vol. 194(C), pages 822-849.
    19. Connolly, D. & Lund, H. & Mathiesen, B.V. & Werner, S. & Möller, B. & Persson, U. & Boermans, T. & Trier, D. & Østergaard, P.A. & Nielsen, S., 2014. "Heat Roadmap Europe: Combining district heating with heat savings to decarbonise the EU energy system," Energy Policy, Elsevier, vol. 65(C), pages 475-489.
    20. Ommen, Torben & Markussen, Wiebke Brix & Elmegaard, Brian, 2014. "Comparison of linear, mixed integer and non-linear programming methods in energy system dispatch modelling," Energy, Elsevier, vol. 74(C), pages 109-118.
    21. Dmytro Romanchenko & Emil Nyholm & Mikael Odenberger & Filip Johnsson, 2019. "Flexibility Potential of Space Heating Demand Response in Buildings for District Heating Systems," Energies, MDPI, vol. 12(15), pages 1-23, July.
    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. Hasanien, Hany M. & Alsaleh, Ibrahim & Tostado-Véliz, Marcos & Zhang, Miao & Alateeq, Ayoob & Jurado, Francisco & Alassaf, Abdullah, 2024. "Hybrid particle swarm and sea horse optimization algorithm-based optimal reactive power dispatch of power systems comprising electric vehicles," Energy, Elsevier, vol. 286(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. Golmohamadi, Hessam & Larsen, Kim Guldstrand & Jensen, Peter Gjøl & Hasrat, Imran Riaz, 2022. "Integration of flexibility potentials of district heating systems into electricity markets: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
    2. Østergaard, Poul Alberg & Andersen, Anders N. & Sorknæs, Peter, 2022. "The business-economic energy system modelling tool energyPRO," Energy, Elsevier, vol. 257(C).
    3. Delmastro, Chiara & Gargiulo, Maurizio, 2020. "Capturing the long-term interdependencies between building thermal energy supply and demand in urban planning strategies," Applied Energy, Elsevier, vol. 268(C).
    4. Chang, Miguel & Lund, Henrik & Thellufsen, Jakob Zinck & Østergaard, Poul Alberg, 2023. "Perspectives on purpose-driven coupling of energy system models," Energy, Elsevier, vol. 265(C).
    5. Prina, Matteo Giacomo & Nastasi, Benedetto & Groppi, Daniele & Misconel, Steffi & Garcia, Davide Astiaso & Sparber, Wolfram, 2022. "Comparison methods of energy system frameworks, models and scenario results," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    6. Martin, Nick & Zinck Thellufsen, Jakob & Chang, Miguel & Talens-Peiró, Laura & Madrid-López, Cristina, 2024. "The many faces of heating transitions. Deeper understandings of future systems in Sweden and beyond," Energy, Elsevier, vol. 290(C).
    7. Dominković, D.F. & Weinand, J.M. & Scheller, F. & D'Andrea, M. & McKenna, R., 2022. "Reviewing two decades of energy system analysis with bibliometrics," Renewable and Sustainable Energy Reviews, Elsevier, vol. 153(C).
    8. 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).
    9. Wirtz, Marco, 2023. "nPro: A web-based planning tool for designing district energy systems and thermal networks," Energy, Elsevier, vol. 268(C).
    10. Haugen, Mari & Blaisdell-Pijuan, Paris L. & Botterud, Audun & Levin, Todd & Zhou, Zhi & Belsnes, Michael & Korpås, Magnus & Somani, Abhishek, 2024. "Power market models for the clean energy transition: State of the art and future research needs," Applied Energy, Elsevier, vol. 357(C).
    11. Fabian Scheller & Frauke Wiese & Jann Michael Weinand & Dominik Franjo Dominkovi'c & Russell McKenna, 2021. "An expert survey to assess the current status and future challenges of energy system analysis," Papers 2106.15518, arXiv.org.
    12. Han, Gwangwoo & Joo, Hong-Jin & Lim, Hee-Won & An, Young-Sub & Lee, Wang-Je & Lee, Kyoung-Ho, 2023. "Data-driven heat pump operation strategy using rainbow deep reinforcement learning for significant reduction of electricity cost," Energy, Elsevier, vol. 270(C).
    13. Østergaard, Poul Alberg & Andersen, Anders N., 2023. "Optimal heat storage in district energy plants with heat pumps and electrolysers," Energy, Elsevier, vol. 275(C).
    14. Md. Nasimul Islam Maruf, 2019. "Sector Coupling in the North Sea Region—A Review on the Energy System Modelling Perspective," Energies, MDPI, vol. 12(22), pages 1-35, November.
    15. Dominković, D.F. & Bačeković, I. & Sveinbjörnsson, D. & Pedersen, A.S. & Krajačić, G., 2017. "On the way towards smart energy supply in cities: The impact of interconnecting geographically distributed district heating grids on the energy system," Energy, Elsevier, vol. 137(C), pages 941-960.
    16. Guo, Yurun & Wang, Shugang & Wang, Jihong & Zhang, Tengfei & Ma, Zhenjun & Jiang, Shuang, 2024. "Key district heating technologies for building energy flexibility: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).
    17. David Drysdale & Brian Vad Mathiesen & Henrik Lund, 2019. "From Carbon Calculators to Energy System Analysis in Cities," Energies, MDPI, vol. 12(12), pages 1-21, June.
    18. Langevin, J. & Reyna, J.L. & Ebrahimigharehbaghi, S. & Sandberg, N. & Fennell, P. & Nägeli, C. & Laverge, J. & Delghust, M. & Mata, É. & Van Hove, M. & Webster, J. & Federico, F. & Jakob, M. & Camaras, 2020. "Developing a common approach for classifying building stock energy models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 133(C).
    19. Østergaard, Poul Alberg & Andersen, Anders N., 2021. "Variable taxes promoting district heating heat pump flexibility," Energy, Elsevier, vol. 221(C).
    20. Johansen, Katinka & Johra, Hicham, 2022. "A niche technique overlooked in the Danish district heating sector? Exploring socio-technical perspectives of short-term thermal energy storage for building energy flexibility," Energy, Elsevier, vol. 256(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:283:y:2023:i:c:s0360544223024507. 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.