IDEAS home Printed from https://ideas.repec.org/a/eee/rensus/v129y2020ics1364032120302082.html
   My bibliography  Save this article

Classification and challenges of bottom-up energy system models - A review

Author

Listed:
  • Prina, Matteo Giacomo
  • Manzolini, Giampaolo
  • Moser, David
  • Nastasi, Benedetto
  • Sparber, Wolfram

Abstract

This paper reviews the classification schemes used for bottom-up energy system modelling and proposes a novel one as re-elaboration of the previous schemes. Moreover, this paper identifies that the main challenges of this research field rotate around the concept of resolution. A matrix of challenges in which four main fields are identified: resolution in time, in space, in techno-economic detail and in sector-coupling. These main fields are divided into different levels of resolution: low, medium and high. The use of a low resolution introduces errors in the modelling as demonstrated by different studies. Several existing bottom-up energy system models are reviewed in order to classify them according to the proposed approach and map them through the proposed matrix. 13 different models are analyzed in the category of bottom-up short-term and 9 as bottom-up long-term energy system models. The following mapping shows how several models reach a high level of resolution in one or more than one area. However, the ultimate challenge is the simultaneous achievement of high resolution in all these fields. The literature review has shown how this final aim is not reached by any model at the current stage and it highlights the gap and weaknesses of this branch of research and the direction versus which is important to work to improve this type of modelling.

Suggested Citation

  • Prina, Matteo Giacomo & Manzolini, Giampaolo & Moser, David & Nastasi, Benedetto & Sparber, Wolfram, 2020. "Classification and challenges of bottom-up energy system models - A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 129(C).
    • Handle: RePEc:eee:rensus:v:129:y:2020:i:c:s1364032120302082
    DOI: 10.1016/j.rser.2020.109917
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1364032120302082
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.rser.2020.109917?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. Astudillo, Miguel F. & Vaillancourt, Kathleen & Pineau, Pierre-Olivier & Amor, Ben, 2017. "Can the household sector reduce global warming mitigation costs? sensitivity to key parameters in a TIMES techno-economic energy model," Applied Energy, Elsevier, vol. 205(C), pages 486-498.
    2. Connolly, D. & Lund, H. & Mathiesen, B.V., 2016. "Smart Energy Europe: The technical and economic impact of one potential 100% renewable energy scenario for the European Union," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 1634-1653.
    3. Hauser, Philipp & Heinrichs, Heidi U. & Gillessen, Bastian & Müller, Theresa, 2018. "Implications of diversification strategies in the European natural gas market for the German energy system," Energy, Elsevier, vol. 151(C), pages 442-454.
    4. Messner, S. & Golodnikov, A. & Gritsevskii, A., 1996. "A stochastic version of the dynamic linear programming model MESSAGE III," Energy, Elsevier, vol. 21(9), pages 775-784.
    5. Després, Jacques & Hadjsaid, Nouredine & Criqui, Patrick & Noirot, Isabelle, 2015. "Modelling the impacts of variable renewable sources on the power sector: Reconsidering the typology of energy modelling tools," Energy, Elsevier, vol. 80(C), pages 486-495.
    6. 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.
    7. Good, Nicholas, 2019. "Using behavioural economic theory in modelling of demand response," Applied Energy, Elsevier, vol. 239(C), pages 107-116.
    8. Mahbub, Md Shahriar & Cozzini, Marco & Østergaard, Poul Alberg & Alberti, Fabrizio, 2016. "Combining multi-objective evolutionary algorithms and descriptive analytical modelling in energy scenario design," Applied Energy, Elsevier, vol. 164(C), pages 140-151.
    9. Henrik Lund & Finn Arler & Poul Alberg Østergaard & Frede Hvelplund & David Connolly & Brian Vad Mathiesen & Peter Karnøe, 2017. "Simulation versus Optimisation: Theoretical Positions in Energy System Modelling," Energies, MDPI, vol. 10(7), pages 1-17, June.
    10. Frederiks, Elisha R. & Stenner, Karen & Hobman, Elizabeth V., 2015. "Household energy use: Applying behavioural economics to understand consumer decision-making and behaviour," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 1385-1394.
    11. 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.
    12. van Beeck, N.M.J.P., 1999. "Classification of Energy Models," Other publications TiSEM 6f2cbb5e-2d53-4be6-a4f9-9, Tilburg University, School of Economics and Management.
    13. Deane, J.P. & Chiodi, Alessandro & Gargiulo, Maurizio & Ó Gallachóir, Brian P., 2012. "Soft-linking of a power systems model to an energy systems model," Energy, Elsevier, vol. 42(1), pages 303-312.
    14. Henning, Hans-Martin & Palzer, Andreas, 2014. "A comprehensive model for the German electricity and heat sector in a future energy system with a dominant contribution from renewable energy technologies—Part I: Methodology," Renewable and Sustainable Energy Reviews, Elsevier, vol. 30(C), pages 1003-1018.
    15. Jebaraj, S. & Iniyan, S., 2006. "A review of energy models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 10(4), pages 281-311, August.
    16. Wierzbowski, Michal & Lyzwa, Wojciech & Musial, Izabela, 2016. "MILP model for long-term energy mix planning with consideration of power system reserves," Applied Energy, Elsevier, vol. 169(C), pages 93-111.
    17. Steven A. Gabriel & Andy S. Kydes & Peter Whitman, 2001. "The National Energy Modeling System: A Large-Scale Energy-Economic Equilibrium Model," Operations Research, INFORMS, vol. 49(1), pages 14-25, February.
    18. Haris Doukas & Alexandros Nikas & Mikel González-Eguino & Iñaki Arto & Annela Anger-Kraavi, 2018. "From Integrated to Integrative: Delivering on the Paris Agreement," Sustainability, MDPI, vol. 10(7), pages 1-10, July.
    19. Ringkjøb, Hans-Kristian & Haugan, Peter M. & Solbrekke, Ida Marie, 2018. "A review of modelling tools for energy and electricity systems with large shares of variable renewables," Renewable and Sustainable Energy Reviews, Elsevier, vol. 96(C), pages 440-459.
    20. Prina, Matteo Giacomo & Fanali, Lorenzo & Manzolini, Giampaolo & Moser, David & Sparber, Wolfram, 2018. "Incorporating combined cycle gas turbine flexibility constraints and additional costs into the EPLANopt model: The Italian case study," Energy, Elsevier, vol. 160(C), pages 33-43.
    21. Lorna A. Greening & Chris Bataille, 2009. "Bottom-up Models of Energy: Across the Spectrum," Chapters, in: Joanne Evans & Lester C. Hunt (ed.), International Handbook on the Economics of Energy, chapter 11, Edward Elgar Publishing.
    22. Warren B. Powell & Abraham George & Hugo Simão & Warren Scott & Alan Lamont & Jeffrey Stewart, 2012. "SMART: A Stochastic Multiscale Model for the Analysis of Energy Resources, Technology, and Policy," INFORMS Journal on Computing, INFORMS, vol. 24(4), pages 665-682, November.
    23. Vaillancourt, Kathleen & Alcocer, Yuri & Bahn, Olivier & Fertel, Camille & Frenette, Erik & Garbouj, Hichem & Kanudia, Amit & Labriet, Maryse & Loulou, Richard & Marcy, Mathilde & Neji, Yosra & Waaub,, 2014. "A Canadian 2050 energy outlook: Analysis with the multi-regional model TIMES-Canada," Applied Energy, Elsevier, vol. 132(C), pages 56-65.
    24. Prina, Matteo Giacomo & Lionetti, Matteo & Manzolini, Giampaolo & Sparber, Wolfram & Moser, David, 2019. "Transition pathways optimization methodology through EnergyPLAN software for long-term energy planning," Applied Energy, Elsevier, vol. 235(C), pages 356-368.
    25. 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.
    26. Batas Bjelić, Ilija & Rajaković, Nikola, 2015. "Simulation-based optimization of sustainable national energy systems," Energy, Elsevier, vol. 91(C), pages 1087-1098.
    27. Brown, T. & Schlachtberger, D. & Kies, A. & Schramm, S. & Greiner, M., 2018. "Synergies of sector coupling and transmission reinforcement in a cost-optimised, highly renewable European energy system," Energy, Elsevier, vol. 160(C), pages 720-739.
    28. Mathiesen, B.V. & Lund, H. & Connolly, D. & Wenzel, H. & Østergaard, P.A. & Möller, B. & Nielsen, S. & Ridjan, I. & Karnøe, P. & Sperling, K. & Hvelplund, F.K., 2015. "Smart Energy Systems for coherent 100% renewable energy and transport solutions," Applied Energy, Elsevier, vol. 145(C), pages 139-154.
    29. Palzer, Andreas & Henning, Hans-Martin, 2014. "A comprehensive model for the German electricity and heat sector in a future energy system with a dominant contribution from renewable energy technologies – Part II: Results," Renewable and Sustainable Energy Reviews, Elsevier, vol. 30(C), pages 1019-1034.
    30. Sadiqa, Ayesha & Gulagi, Ashish & Breyer, Christian, 2018. "Energy transition roadmap towards 100% renewable energy and role of storage technologies for Pakistan by 2050," Energy, Elsevier, vol. 147(C), pages 518-533.
    31. Gils, Hans Christian & Scholz, Yvonne & Pregger, Thomas & Luca de Tena, Diego & Heide, Dominik, 2017. "Integrated modelling of variable renewable energy-based power supply in Europe," Energy, Elsevier, vol. 123(C), pages 173-188.
    32. Kanudia, Amit & Loulou, Richard, 1998. "Robust responses to climate change via stochastic MARKAL: The case of Quebec," European Journal of Operational Research, Elsevier, vol. 106(1), pages 15-30, April.
    33. Jean Charles Hourcade & Mark Jaccard & Chris Bataille & Frédéric Ghersi, 2006. "Hybrid Modeling: New Answers to Old Challenges," Post-Print halshs-00471234, HAL.
    34. Konstantin Löffler & Karlo Hainsch & Thorsten Burandt & Pao-Yu Oei & Claudia Kemfert & Christian Von Hirschhausen, 2017. "Designing a Model for the Global Energy System—GENeSYS-MOD: An Application of the Open-Source Energy Modeling System (OSeMOSYS)," Energies, MDPI, vol. 10(10), pages 1-28, September.
    35. Doukas, Haris & Nikas, Alexandros, 2020. "Decision support models in climate policy," European Journal of Operational Research, Elsevier, vol. 280(1), pages 1-24.
    36. Welsch, Manuel & Deane, Paul & Howells, Mark & Ó Gallachóir, Brian & Rogan, Fionn & Bazilian, Morgan & Rogner, Hans-Holger, 2014. "Incorporating flexibility requirements into long-term energy system models – A case study on high levels of renewable electricity penetration in Ireland," Applied Energy, Elsevier, vol. 135(C), pages 600-615.
    37. Pina, André & Silva, Carlos & Ferrão, Paulo, 2011. "Modeling hourly electricity dynamics for policy making in long-term scenarios," Energy Policy, Elsevier, vol. 39(9), pages 4692-4702, September.
    38. Andrea Herbst & Felipe Andrés Toro & Felix Reitze & Eberhard Jochem, 2012. "Introduction to Energy Systems Modelling," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 148(II), pages 111-135, June.
    39. Howells, Mark & Rogner, Holger & Strachan, Neil & Heaps, Charles & Huntington, Hillard & Kypreos, Socrates & Hughes, Alison & Silveira, Semida & DeCarolis, Joe & Bazillian, Morgan & Roehrl, Alexander, 2011. "OSeMOSYS: The Open Source Energy Modeling System: An introduction to its ethos, structure and development," Energy Policy, Elsevier, vol. 39(10), pages 5850-5870, October.
    40. The Food Industry Center, University of Minnesota, 2019. "The Food Industry Center 2019 Annual Report," Annual Reports 290378, University of Minnesota, The Food Industry Center.
    41. Kimon Keramidas & Alban Kitous & Jacques Despres & Andreas Schmitz & Ana Diaz Vazquez & Silvana Mima & Peter Russ & Tobias Wiesenthal, 2017. "POLES-JRC model documentation," JRC Research Reports JRC107387, Joint Research Centre.
    42. van Beeck, N.M.J.P., 1999. "Classification of Energy Models," Research Memorandum 777, Tilburg University, School of Economics and Management.
    43. Chu, Wen-Xiao & Wang, Chi-Chuan, 2019. "A review on airflow management in data centers," Applied Energy, Elsevier, vol. 240(C), pages 84-119.
    44. Silver, Edward A. & Victor, R. & Vidal, V. & de Werra, Dominique, 1980. "A tutorial on heuristic methods," European Journal of Operational Research, Elsevier, vol. 5(3), pages 153-162, September.
    45. Sachs, Julia & Meng, Yiming & Giarola, Sara & Hawkes, Adam, 2019. "An agent-based model for energy investment decisions in the residential sector," Energy, Elsevier, vol. 172(C), pages 752-768.
    46. 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.
    47. Spandagos, Constantine & Ng, Tze Ling, 2018. "Fuzzy model of residential energy decision-making considering behavioral economic concepts," Applied Energy, Elsevier, vol. 213(C), pages 611-625.
    48. Atabay, Dennis, 2017. "An open-source model for optimal design and operation of industrial energy systems," Energy, Elsevier, vol. 121(C), pages 803-821.
    49. Hunter, Kevin & Sreepathi, Sarat & DeCarolis, Joseph F., 2013. "Modeling for insight using Tools for Energy Model Optimization and Analysis (Temoa)," Energy Economics, Elsevier, vol. 40(C), pages 339-349.
    50. Jean-Charles Hourcade, Mark Jaccard, Chris Bataille, and Frederic Ghersi, 2006. "Hybrid Modeling: New Answers to Old Challenges Introduction to the Special Issue of The Energy Journal," The Energy Journal, International Association for Energy Economics, vol. 0(Special I), pages 1-12.
    51. Prina, Matteo Giacomo & Cozzini, Marco & Garegnani, Giulia & Manzolini, Giampaolo & Moser, David & Filippi Oberegger, Ulrich & Pernetti, Roberta & Vaccaro, Roberto & Sparber, Wolfram, 2018. "Multi-objective optimization algorithm coupled to EnergyPLAN software: The EPLANopt model," Energy, Elsevier, vol. 149(C), pages 213-221.
    52. Terry Barker & Eva Alexandri & Jean-Francois Mercure & Yuki Ogawa & Hector Pollitt, 2016. "GDP and employment effects of policies to close the 2020 emissions gap," Climate Policy, Taylor & Francis Journals, vol. 16(4), pages 393-414, May.
    53. Pfenninger, Stefan & DeCarolis, Joseph & Hirth, Lion & Quoilin, Sylvain & Staffell, Iain, 2017. "The importance of open data and software: Is energy research lagging behind?," Energy Policy, Elsevier, vol. 101(C), pages 211-215.
    54. Poncelet, Kris & Delarue, Erik & Six, Daan & Duerinck, Jan & D’haeseleer, William, 2016. "Impact of the level of temporal and operational detail in energy-system planning models," Applied Energy, Elsevier, vol. 162(C), pages 631-643.
    55. Haydt, Gustavo & Leal, Vítor & Pina, André & Silva, Carlos A., 2011. "The relevance of the energy resource dynamics in the mid/long-term energy planning models," Renewable Energy, Elsevier, vol. 36(11), pages 3068-3074.
    56. Keppo, Ilkka & Strubegger, Manfred, 2010. "Short term decisions for long term problems – The effect of foresight on model based energy systems analysis," Energy, Elsevier, vol. 35(5), pages 2033-2042.
    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. 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).
    2. 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).
    3. Finke, Jonas & Bertsch, Valentin, 2023. "Implementing a highly adaptable method for the multi-objective optimisation of energy systems," Applied Energy, Elsevier, vol. 332(C).
    4. Finke, Jonas & Bertsch, Valentin, 2022. "Implementing a highly adaptable method for the multi-objective optimisation of energy systems," MPRA Paper 115504, University Library of Munich, Germany.
    5. 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).
    6. Vaccaro, Roberto & Rocco, Matteo V., 2021. "Quantifying the impact of low carbon transition scenarios at regional level through soft-linked energy and economy models: The case of South-Tyrol Province in Italy," Energy, Elsevier, vol. 220(C).
    7. Lopion, Peter & Markewitz, Peter & Robinius, Martin & Stolten, Detlef, 2018. "A review of current challenges and trends in energy systems modeling," Renewable and Sustainable Energy Reviews, Elsevier, vol. 96(C), pages 156-166.
    8. Prina, Matteo Giacomo & Groppi, Daniele & Nastasi, Benedetto & Garcia, Davide Astiaso, 2021. "Bottom-up energy system models applied to sustainable islands," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).
    9. Prina, Matteo Giacomo & Casalicchio, Valeria & Kaldemeyer, Cord & Manzolini, Giampaolo & Moser, David & Wanitschke, Alexander & Sparber, Wolfram, 2020. "Multi-objective investment optimization for energy system models in high temporal and spatial resolution," Applied Energy, Elsevier, vol. 264(C).
    10. Prina, Matteo Giacomo & Lionetti, Matteo & Manzolini, Giampaolo & Sparber, Wolfram & Moser, David, 2019. "Transition pathways optimization methodology through EnergyPLAN software for long-term energy planning," Applied Energy, Elsevier, vol. 235(C), pages 356-368.
    11. 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).
    12. 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).
    13. Ringkjøb, Hans-Kristian & Haugan, Peter M. & Solbrekke, Ida Marie, 2018. "A review of modelling tools for energy and electricity systems with large shares of variable renewables," Renewable and Sustainable Energy Reviews, Elsevier, vol. 96(C), pages 440-459.
    14. Borasio, M. & Moret, S., 2022. "Deep decarbonisation of regional energy systems: A novel modelling approach and its application to the Italian energy transition," Renewable and Sustainable Energy Reviews, Elsevier, vol. 153(C).
    15. 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.
    16. 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).
    17. Savvidis, Georgios & Siala, Kais & Weissbart, Christoph & Schmidt, Lukas & Borggrefe, Frieder & Kumar, Subhash & Pittel, Karen & Madlener, Reinhard & Hufendiek, Kai, 2019. "The gap between energy policy challenges and model capabilities," Energy Policy, Elsevier, vol. 125(C), pages 503-520.
    18. Matteo Giacomo Prina & Giampaolo Manzolini & David Moser & Roberto Vaccaro & Wolfram Sparber, 2020. "Multi-Objective Optimization Model EPLANopt for Energy Transition Analysis and Comparison with Climate-Change Scenarios," Energies, MDPI, vol. 13(12), pages 1-22, June.
    19. Yoro, Kelvin O. & Daramola, Michael O. & Sekoai, Patrick T. & Wilson, Uwemedimo N. & Eterigho-Ikelegbe, Orevaoghene, 2021. "Update on current approaches, challenges, and prospects of modeling and simulation in renewable and sustainable energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
    20. Viesi, Diego & Crema, Luigi & Mahbub, Md Shahriar & Verones, Sara & Brunelli, Roberto & Baggio, Paolo & Fauri, Maurizio & Prada, Alessandro & Bello, Andrea & Nodari, Benedetta & Silvestri, Silvia & To, 2020. "Integrated and dynamic energy modelling of a regional system: A cost-optimized approach in the deep decarbonisation of the Province of Trento (Italy)," Energy, Elsevier, vol. 209(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:rensus:v:129:y:2020:i:c:s1364032120302082. 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.