IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v253y2019ic12.html
   My bibliography  Save this article

Clustering representative days for power systems generation expansion planning: Capturing the effects of variable renewables and energy storage

Author

Listed:
  • Scott, Ian J.
  • Carvalho, Pedro M.S.
  • Botterud, Audun
  • Silva, Carlos A.

Abstract

Decision makers rely on models to make important regulatory, policy, and investment decisions. For power systems, these models must capture (i) the future challenges introduced by the integration of large quantities of variable renewable energy sources and (ii) the role that energy storage technologies should play. In this paper, we explore several different approaches to selecting representative days for generation expansion planning models, focusing on capturing these dynamics. Further, we propose a new methodology for adjusting the outputs of clustering algorithms that provides three advantages: the targeted level of net demand is captured, the underlying net demand shapes that define ramping challenges are accurately represented, and the relationship between annual energy and peak demand is captured. This weighting methodology reduces the magnitude of the error in the representative day based generation expansion planning models estimation of costs by 61% on average. The results also demonstrate the importance of carefully performing the clustering of representative days for both system costs and technology mix. In most cases improvements to the total cost of different representative day based expansion plans are realised where conventional generation capacity is substituted for energy storage. Based on the energy storage technology selected we conclude this capacity is being used to address ramping challenges as opposed to shifting renewable generation from off to on peak periods, reinforcing the importance of capturing detailed intraday dynamics in the representative day selection process.

Suggested Citation

  • Scott, Ian J. & Carvalho, Pedro M.S. & Botterud, Audun & Silva, Carlos A., 2019. "Clustering representative days for power systems generation expansion planning: Capturing the effects of variable renewables and energy storage," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    • Handle: RePEc:eee:appene:v:253:y:2019:i:c:12
    DOI: 10.1016/j.apenergy.2019.113603
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261919312772
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2019.113603?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. Nahmmacher, Paul & Schmid, Eva & Hirth, Lion & Knopf, Brigitte, 2016. "Carpe diem: A novel approach to select representative days for long-term power system modeling," Energy, Elsevier, vol. 112(C), pages 430-442.
    2. 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.
    3. 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.
    4. Pfenninger, Stefan, 2017. "Dealing with multiple decades of hourly wind and PV time series in energy models: A comparison of methods to reduce time resolution and the planning implications of inter-annual variability," Applied Energy, Elsevier, vol. 197(C), pages 1-13.
    5. 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.
    6. EHRENMANN, Andreas & SMEERS, Yves, 2011. "Generation capacity expansion in a risky environment: a stochastic equilibrium analysis," LIDAM Reprints CORE 2379, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    7. Deane, J.P. & Drayton, G. & Ó Gallachóir, B.P., 2014. "The impact of sub-hourly modelling in power systems with significant levels of renewable generation," Applied Energy, Elsevier, vol. 113(C), pages 152-158.
    8. Oree, Vishwamitra & Sayed Hassen, Sayed Z. & Fleming, Peter J., 2017. "Generation expansion planning optimisation with renewable energy integration: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 790-803.
    9. Pereira, Sérgio & Ferreira, Paula & Vaz, A.I.F., 2017. "Generation expansion planning with high share of renewables of variable output," Applied Energy, Elsevier, vol. 190(C), pages 1275-1288.
    10. Heuberger, Clara F. & Rubin, Edward S. & Staffell, Iain & Shah, Nilay & Mac Dowell, Niall, 2017. "Power capacity expansion planning considering endogenous technology cost learning," Applied Energy, Elsevier, vol. 204(C), pages 831-845.
    11. Koltsaklis, Nikolaos E. & Dagoumas, Athanasios S. & Georgiadis, Michael C. & Papaioannou, George & Dikaiakos, Christos, 2016. "A mid-term, market-based power systems planning model," Applied Energy, Elsevier, vol. 179(C), pages 17-35.
    12. Lund, Peter D. & Lindgren, Juuso & Mikkola, Jani & Salpakari, Jyri, 2015. "Review of energy system flexibility measures to enable high levels of variable renewable electricity," Renewable and Sustainable Energy Reviews, Elsevier, vol. 45(C), pages 785-807.
    13. Frew, Bethany A. & Becker, Sarah & Dvorak, Michael J. & Andresen, Gorm B. & Jacobson, Mark Z., 2016. "Flexibility mechanisms and pathways to a highly renewable US electricity future," Energy, Elsevier, vol. 101(C), pages 65-78.
    14. Frew, Bethany A. & Jacobson, Mark Z., 2016. "Temporal and spatial tradeoffs in power system modeling with assumptions about storage: An application of the POWER model," Energy, Elsevier, vol. 117(P1), pages 198-213.
    15. Mallapragada, Dharik S. & Papageorgiou, Dimitri J. & Venkatesh, Aranya & Lara, Cristiana L. & Grossmann, Ignacio E., 2018. "Impact of model resolution on scenario outcomes for electricity sector system expansion," Energy, Elsevier, vol. 163(C), pages 1231-1244.
    16. Andreas Ehrenmann & Yves Smeers, 2011. "Generation Capacity Expansion in a Risky Environment: A Stochastic Equilibrium Analysis," Operations Research, INFORMS, vol. 59(6), pages 1332-1346, December.
    17. Merrick, James H., 2016. "On representation of temporal variability in electricity capacity planning models," Energy Economics, Elsevier, vol. 59(C), pages 261-274.
    18. 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.
    19. Geoffrey J. Blanford, James H. Merrick, John E.T. Bistline, and David T. Young, 2018. "Simulating Annual Variation in Load, Wind, and Solar by Representative Hour Selection," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    20. Koltsaklis, Nikolaos E. & Dagoumas, Athanasios S., 2018. "State-of-the-art generation expansion planning: A review," Applied Energy, Elsevier, vol. 230(C), pages 563-589.
    21. 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.
    22. 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.
    23. 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.
    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. 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.
    2. 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.
    3. 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.
    4. Karl-Kiên Cao & Kai von Krbek & Manuel Wetzel & Felix Cebulla & Sebastian Schreck, 2019. "Classification and Evaluation of Concepts for Improving the Performance of Applied Energy System Optimization Models," Energies, MDPI, vol. 12(24), pages 1-51, December.
    5. Teichgraeber, Holger & Brandt, Adam R., 2022. "Time-series aggregation for the optimization of energy systems: Goals, challenges, approaches, and opportunities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 157(C).
    6. 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).
    7. 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).
    8. Dagoumas, Athanasios S. & Koltsaklis, Nikolaos E., 2019. "Review of models for integrating renewable energy in the generation expansion planning," Applied Energy, Elsevier, vol. 242(C), pages 1573-1587.
    9. Koltsaklis, Nikolaos E. & Dagoumas, Athanasios S., 2018. "State-of-the-art generation expansion planning: A review," Applied Energy, Elsevier, vol. 230(C), pages 563-589.
    10. 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).
    11. Kuepper, Lucas Elias & Teichgraeber, Holger & Baumgärtner, Nils & Bardow, André & Brandt, Adam R., 2022. "Wind data introduce error in time-series reduction for capacity expansion modelling," Energy, Elsevier, vol. 256(C).
    12. Yeganefar, Ali & Amin-Naseri, Mohammad Reza & Sheikh-El-Eslami, Mohammad Kazem, 2020. "Improvement of representative days selection in power system planning by incorporating the extreme days of the net load to take account of the variability and intermittency of renewable resources," Applied Energy, Elsevier, vol. 272(C).
    13. Vrionis, Constantinos & Tsalavoutis, Vasilios & Tolis, Athanasios, 2020. "A Generation Expansion Planning model for integrating high shares of renewable energy: A Meta-Model Assisted Evolutionary Algorithm approach," Applied Energy, Elsevier, vol. 259(C).
    14. Oree, Vishwamitra & Sayed Hassen, Sayed Z. & Fleming, Peter J., 2019. "A multi-objective framework for long-term generation expansion planning with variable renewables," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    15. 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).
    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. Henrik C. Bylling & Salvador Pineda & Trine K. Boomsma, 2020. "The impact of short-term variability and uncertainty on long-term power planning," Annals of Operations Research, Springer, vol. 284(1), pages 199-223, January.
    18. Göke, Leonard & Kendziorski, Mario, 2022. "Adequacy of time-series reduction for renewable energy systems," Energy, Elsevier, vol. 238(PA).
    19. Tong Koecklin, Manuel & Fitiwi, Desta & de Carolis, Joseph F. & Curtis, John, 2020. "Renewable electricity generation and transmission network developments in light of public opposition: Insights from Ireland," Papers WP653, Economic and Social Research Institute (ESRI).
    20. James H. Merrick & John E. T. Bistline & Geoffrey J. Blanford, 2021. "On representation of energy storage in electricity planning models," Papers 2105.03707, arXiv.org, revised May 2021.

    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:253:y:2019:i:c:12. 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.