IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v162y2016icp631-643.html
   My bibliography  Save this article

Impact of the level of temporal and operational detail in energy-system planning models

Author

Listed:
  • Poncelet, Kris
  • Delarue, Erik
  • Six, Daan
  • Duerinck, Jan
  • D’haeseleer, William

Abstract

To limit the computational cost, bottom-up long-term (LT) energy-system planning models typically have a stylized temporal representation and do not consider techno-economic operational constraints of power plants. Both these simplifications have been shown to have a significant impact on the results. However, increasing the level of temporal and techno-economic operational detail will result in an increased computational cost. In this regard, the first goal of this work is to quantify which of these simplifications has the highest impact on the results, and should therefore be prioritized for improving. To do so, the impact of both the low level of temporal and techno-economic operational detail are quantified for a varying penetration of intermittent renewable energy sources (IRES). For a high penetration of IRES, the gains obtained by improving the temporal representation are shown to outweigh the gains obtained by incorporating detailed techno-economic operational constraints. Therefore, improving the temporal representation is suggested to be prioritized. The second goal of this paper is to identify opportunities for model improvements. Different approaches to improve the temporal representation are proposed. While the focus in the literature lies primarily on the impact of the temporal resolution, this work more fundamentally considers and assesses different approaches of dealing with the temporal dimension. Using a different approach of defining the time slices to explicitly account for IRES variability is found to lead to a higher accuracy than can be obtained by simply increasing the temporal resolution, while requiring a lower number of time slices. Moreover, a temporal representation based on selecting a set of representative days can achieve an even higher accuracy, albeit requiring a higher number of time slices. An additional advantage of using representative days is that chronology is retained such that the impact of short-term dynamic fluctuations of IRES can be accounted for.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:appene:v:162:y:2016:i:c:p:631-643
    DOI: 10.1016/j.apenergy.2015.10.100
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261915013276
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2015.10.100?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. Gunnar Luderer & Volker Krey & Katherine Calvin & James Merrick & Silvana Mima & Robert Pietzcker & Jasper Vliet & Kenichi Wada, 2014. "The role of renewable energy in climate stabilization: results from the EMF27 scenarios," Climatic Change, Springer, vol. 123(3), pages 427-441, April.
    2. Gunnar Luderer & Volker Krey & Katherine Calvin & James Merrick & Silvana Mima & Robert Pietzcker & Jasper van Vliet & Kenichi Wada, 2014. "The role of renewable energy in climate stabilization: results from the EMF27 scenarios," Post-Print halshs-00961843, HAL.
    3. 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.
    4. 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.
    5. De Jonghe, Cedric & Delarue, Erik & Belmans, Ronnie & D'haeseleer, William, 2011. "Determining optimal electricity technology mix with high level of wind power penetration," Applied Energy, Elsevier, vol. 88(6), pages 2231-2238, June.
    6. Pina, André & Silva, Carlos A. & Ferrão, Paulo, 2013. "High-resolution modeling framework for planning electricity systems with high penetration of renewables," Applied Energy, Elsevier, vol. 112(C), pages 215-223.
    7. Martinsen, Dag & Linssen, Jochen & Markewitz, Peter & Vogele, Stefan, 2007. "CCS: A future CO2 mitigation option for Germany?--A bottom-up approach," Energy Policy, Elsevier, vol. 35(4), pages 2110-2120, April.
    8. Chiodi, Alessandro & Gargiulo, Maurizio & Rogan, Fionn & Deane, J.P. & Lavigne, Denis & Rout, Ullash K. & Ó Gallachóir, Brian P., 2013. "Modelling the impacts of challenging 2050 European climate mitigation targets on Ireland’s energy system," Energy Policy, Elsevier, vol. 53(C), pages 169-189.
    9. Rosen, Johannes & Tietze-Stöckinger, Ingela & Rentz, Otto, 2007. "Model-based analysis of effects from large-scale wind power production," Energy, Elsevier, vol. 32(4), pages 575-583.
    10. 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.
    11. 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.
    12. Ludig, Sylvie & Haller, Markus & Schmid, Eva & Bauer, Nico, 2011. "Fluctuating renewables in a long-term climate change mitigation strategy," Energy, Elsevier, vol. 36(11), pages 6674-6685.
    13. 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.
    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. Collins, Seán & Deane, John Paul & Poncelet, Kris & Panos, Evangelos & Pietzcker, Robert C. & Delarue, Erik & Ó Gallachóir, Brian Pádraig, 2017. "Integrating short term variations of the power system into integrated energy system models: A methodological review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 839-856.
    2. Thomas Heggarty & Jean-Yves Bourmaud & Robin Girard & Georges Kariniotakis, 2024. "Assessing the relative impacts of maximum investment rate and temporal detail in capacity expansion models applied to power systems," Post-Print hal-04383397, HAL.
    3. Mertens, Tim & Poncelet, Kris & Duerinck, Jan & Delarue, Erik, 2020. "Representing cross-border trade of electricity in long-term energy-system optimization models with a limited geographical scope," Applied Energy, Elsevier, vol. 261(C).
    4. Amorim, Filipa & Pina, André & Gerbelová, Hana & Pereira da Silva, Patrícia & Vasconcelos, Jorge & Martins, Victor, 2014. "Electricity decarbonisation pathways for 2050 in Portugal: A TIMES (The Integrated MARKAL-EFOM System) based approach in closed versus open systems modelling," Energy, Elsevier, vol. 69(C), pages 104-112.
    5. 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.
    6. Ringkjøb, Hans-Kristian & Haugan, Peter M. & Seljom, Pernille & Lind, Arne & Wagner, Fabian & Mesfun, Sennai, 2020. "Short-term solar and wind variability in long-term energy system models - A European case study," Energy, Elsevier, vol. 209(C).
    7. 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).
    8. Fehrenbach, Daniel & Merkel, Erik & McKenna, Russell & Karl, Ute & Fichtner, Wolf, 2014. "On the economic potential for electric load management in the German residential heating sector – An optimising energy system model approach," Energy, Elsevier, vol. 71(C), pages 263-276.
    9. Koltsaklis, Nikolaos E. & Georgiadis, Michael C., 2015. "A multi-period, multi-regional generation expansion planning model incorporating unit commitment constraints," Applied Energy, Elsevier, vol. 158(C), pages 310-331.
    10. Jain, A. & Yamujala, S. & Gaur, A. & Das, P. & Bhakar, R. & Mathur, J., 2023. "Power sector decarbonization planning considering renewable resource variability and system operational constraints," Applied Energy, Elsevier, vol. 331(C).
    11. Buchholz, Stefanie & Gamst, Mette & Pisinger, David, 2020. "Sensitivity analysis of time aggregation techniques applied to capacity expansion energy system models," Applied Energy, Elsevier, vol. 269(C).
    12. 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).
    13. 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).
    14. Niina Helistö & Juha Kiviluoma & Hannele Holttinen & Jose Daniel Lara & Bri‐Mathias Hodge, 2019. "Including operational aspects in the planning of power systems with large amounts of variable generation: A review of modeling approaches," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 8(5), September.
    15. McCallum, Peter & Jenkins, David P. & Peacock, Andrew D. & Patidar, Sandhya & Andoni, Merlinda & Flynn, David & Robu, Valentin, 2019. "A multi-sectoral approach to modelling community energy demand of the built environment," Energy Policy, Elsevier, vol. 132(C), pages 865-875.
    16. Poncelet, Kris & Delarue, Erik & D’haeseleer, William, 2020. "Unit commitment constraints in long-term planning models: Relevance, pitfalls and the role of assumptions on flexibility," Applied Energy, Elsevier, vol. 258(C).
    17. Seljom, Pernille & Rosenberg, Eva & Schäffer, Linn Emelie & Fodstad, Marte, 2020. "Bidirectional linkage between a long-term energy system and a short-term power market model," Energy, Elsevier, vol. 198(C).
    18. Haas, J. & Cebulla, F. & Cao, K. & Nowak, W. & Palma-Behnke, R. & Rahmann, C. & Mancarella, P., 2017. "Challenges and trends of energy storage expansion planning for flexibility provision in low-carbon power systems – a review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 603-619.
    19. Gerbelová, Hana & Amorim, Filipa & Pina, André & Melo, Mário & Ioakimidis, Christos & Ferrão, Paulo, 2014. "Potential of CO2 (carbon dioxide) taxes as a policy measure towards low-carbon Portuguese electricity sector by 2050," Energy, Elsevier, vol. 69(C), pages 113-119.
    20. Pina, André & Silva, Carlos A. & Ferrão, Paulo, 2013. "High-resolution modeling framework for planning electricity systems with high penetration of renewables," Applied Energy, Elsevier, vol. 112(C), pages 215-223.

    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:162:y:2016:i:c:p:631-643. 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.