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eTransport: Investment planning in energy supply systems with multiple energy carriers


  • Bakken, Bjorn H.
  • Skjelbred, Hans I.
  • Wolfgang, Ove


The need for local energy planning is not reduced after liberalization. Both integrated energy companies and local governments have to consider alternative solutions across traditional supply and demand sectors and make plans for the total integrated energy infrastructure. This situation has created a need for new improved methodologies and tools for system planning and operation that include multiple energy carriers and sufficient topological details. In this paper, a novel optimisation model ‘eTransport’ is presented that takes into account both the topology of multiple energy infrastructures and the technical and economic properties of different investment alternatives. The model minimises total energy system cost (investments, operation and emissions) of meeting predefined energy demands of electricity, gas, space heating and tap water heating within a geographical area over a given planning horizon, including alternative supply infrastructures for multiple energy carriers. The model employs a nested optimisation, calculating both the optimal diurnal operation of the energy system and the optimal expansion plan typically 20–30 years into the future. The model is tested on a number of real case studies, and a full graphical user interface has been implemented. A sample case study is included to demonstrate the use of the model.

Suggested Citation

  • Bakken, Bjorn H. & Skjelbred, Hans I. & Wolfgang, Ove, 2007. "eTransport: Investment planning in energy supply systems with multiple energy carriers," Energy, Elsevier, vol. 32(9), pages 1676-1689.
  • Handle: RePEc:eee:energy:v:32:y:2007:i:9:p:1676-1689
    DOI: 10.1016/

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    References listed on IDEAS

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    Cited by:

    1. Løken, Espen & Botterud, Audun & Holen, Arne T., 2009. "Use of the equivalent attribute technique in multi-criteria planning of local energy systems," European Journal of Operational Research, Elsevier, vol. 197(3), pages 1075-1083, September.
    2. Jan Abrell and Hannes Weigt, 2016. "Investments in a Combined Energy Network Model: Substitution between Natural Gas and Electricity?," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).
    3. 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.
    4. Hür Bütün & Ivan Kantor & François Maréchal, 2019. "An Optimisation Approach for Long-Term Industrial Investment Planning," Energies, MDPI, Open Access Journal, vol. 12(21), pages 1-33, October.
    5. Ba, Birome Holo & Prins, Christian & Prodhon, Caroline, 2016. "Models for optimization and performance evaluation of biomass supply chains: An Operations Research perspective," Renewable Energy, Elsevier, vol. 87(P2), pages 977-989.
    6. De Meyer, Annelies & Cattrysse, Dirk & Rasinmäki, Jussi & Van Orshoven, Jos, 2014. "Methods to optimise the design and management of biomass-for-bioenergy supply chains: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 31(C), pages 657-670.
    7. Pantaleo, Antonio & Candelise, Chiara & Bauen, Ausilio & Shah, Nilay, 2014. "ESCO business models for biomass heating and CHP: Profitability of ESCO operations in Italy and key factors assessment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 30(C), pages 237-253.
    8. Fu, Xueqian & Li, Gengyin & Wang, Huaizhi, 2018. "Use of a second-order reliability method to estimate the failure probability of an integrated energy system," Energy, Elsevier, vol. 161(C), pages 425-434.
    9. Mancarella, Pierluigi, 2014. "MES (multi-energy systems): An overview of concepts and evaluation models," Energy, Elsevier, vol. 65(C), pages 1-17.
    10. 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.
    11. van Dyken, Silke & Bakken, Bjorn H. & Skjelbred, Hans I., 2010. "Linear mixed-integer models for biomass supply chains with transport, storage and processing," Energy, Elsevier, vol. 35(3), pages 1338-1350.
    12. Münster, Marie & Morthorst, Poul Erik & Larsen, Helge V. & Bregnbæk, Lars & Werling, Jesper & Lindboe, Hans Henrik & Ravn, Hans, 2012. "The role of district heating in the future Danish energy system," Energy, Elsevier, vol. 48(1), pages 47-55.
    13. Marini, Abbas & Latify, Mohammad Amin & Ghazizadeh, Mohammad Sadegh & Salemnia, Ahmad, 2015. "Long-term chronological load modeling in power system studies with energy storage systems," Applied Energy, Elsevier, vol. 156(C), pages 436-448.
    14. Rubio Rodríguez, M.A. & Feitó Cespón, M. & De Ruyck, J. & Ocaña Guevara, V.S. & Verma, V.K., 2013. "Life cycle modeling of energy matrix scenarios, Belgian power and partial heat mixes as case study," Applied Energy, Elsevier, vol. 107(C), pages 329-337.
    15. Wright, Daniel G. & Dey, Prasanta K. & Brammer, John G., 2013. "A fuzzy levelised energy cost method for renewable energy technology assessment," Energy Policy, Elsevier, vol. 62(C), pages 315-323.
    16. Müller, C. & Hoffrichter, A. & Wyrwoll, L. & Schmitt, C. & Trageser, M. & Kulms, T. & Beulertz, D. & Metzger, M. & Duckheim, M. & Huber, M. & Küppers, M. & Most, D. & Paulus, S. & Heger, H.J. & Schnet, 2019. "Modeling framework for planning and operation of multi-modal energy systems in the case of Germany," Applied Energy, Elsevier, vol. 250(C), pages 1132-1146.
    17. Klokk, Ø. & Schreiner, P.F. & Pagès-Bernaus, A. & Tomasgard, A., 2010. "Optimizing a CO2 value chain for the Norwegian Continental Shelf," Energy Policy, Elsevier, vol. 38(11), pages 6604-6614, November.
    18. Zhou, Yizhou & Wei, Zhinong & Sun, Guoqiang & Cheung, Kwok W. & Zang, Haixiang & Chen, Sheng, 2018. "A robust optimization approach for integrated community energy system in energy and ancillary service markets," Energy, Elsevier, vol. 148(C), pages 1-15.


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