IDEAS home Printed from https://ideas.repec.org/a/spr/comgts/v12y2015i4p519-537.html
   My bibliography  Save this article

Boomer-Consumer: a model for load consumption and reserve offers in reserve constrained electricity markets

Author

Listed:
  • Nigel Cleland
  • Golbon Zakeri
  • Geoff Pritchard
  • Brent Young

Abstract

A model to determine the optimal consumption level and associated reserve offer for a large consumer in a co-optimised electricity market is presented. The method uses numerical simulation along with a full representation of the New Zealand electricity market dispatch model. Uncertainty is introduced through the use of stochastic demand sampling. We approach this process in three phases: phase one contains simulations to determine potential energy and reserve prices under uncertainty. Phase two uses a dynamic programming method, adapted from a generator model, to determine the optimal reserve offer. Phase three is the repetition of phase one with the optimal reserve offer intact. The model has been applied to a user in New Zealand and initial results have been presented. The model approached a theoretical maximum profitability when used as an input to a site curtailment response strategy. Copyright Springer-Verlag Berlin Heidelberg 2015

Suggested Citation

  • Nigel Cleland & Golbon Zakeri & Geoff Pritchard & Brent Young, 2015. "Boomer-Consumer: a model for load consumption and reserve offers in reserve constrained electricity markets," Computational Management Science, Springer, vol. 12(4), pages 519-537, October.
    • Handle: RePEc:spr:comgts:v:12:y:2015:i:4:p:519-537
    DOI: 10.1007/s10287-015-0241-2
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10287-015-0241-2
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10287-015-0241-2?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. Philip J. Neame & Andrew B. Philpott & Geoffrey Pritchard, 2003. "Offer Stack Optimization in Electricity Pool Markets," Operations Research, INFORMS, vol. 51(3), pages 397-408, June.
    2. Strbac, Goran, 2008. "Demand side management: Benefits and challenges," Energy Policy, Elsevier, vol. 36(12), pages 4419-4426, December.
    3. Hurlbut, David & Rogas, Keith & Oren, Shmuel, 2004. "Protecting the Market from "Hockey Stick" Pricing: How the Public Utility Commission of Texas is Dealing with Potential Price Gouging," The Electricity Journal, Elsevier, vol. 17(3), pages 26-33, April.
    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. Anna Schwele & Christos Ordoudis & Pierre Pinson & Jalal Kazempour, 2021. "Coordination of power and natural gas markets via financial instruments," Computational Management Science, Springer, vol. 18(4), pages 505-538, October.

    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. Cheng, Meng & Sami, Saif Sabah & Wu, Jianzhong, 2017. "Benefits of using virtual energy storage system for power system frequency response," Applied Energy, Elsevier, vol. 194(C), pages 376-385.
    2. McPherson, Madeleine & Stoll, Brady, 2020. "Demand response for variable renewable energy integration: A proposed approach and its impacts," Energy, Elsevier, vol. 197(C).
    3. Anna Kowalska-Pyzalska & Katarzyna Maciejowska & Katarzyna Sznajd-Weron & Rafal Weron, 2014. "Diffusion and adoption of dynamic electricity tariffs: An agent-based modeling approach," HSC Research Reports HSC/14/01, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
    4. Kowalska-Pyzalska, Anna & Maciejowska, Katarzyna & Suszczyński, Karol & Sznajd-Weron, Katarzyna & Weron, Rafał, 2014. "Turning green: Agent-based modeling of the adoption of dynamic electricity tariffs," Energy Policy, Elsevier, vol. 72(C), pages 164-174.
    5. Daví-Arderius, Daniel & Sanin, María-Eugenia & Trujillo-Baute, Elisa, 2017. "CO2 content of electricity losses," Energy Policy, Elsevier, vol. 104(C), pages 439-445.
    6. Claire M. Weiller & Michael G. Pollitt, 2013. "Platform markets and energy services," Working Papers EPRG 1334, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
    7. Costa-Campi, Maria Teresa & Daví-Arderius, Daniel & Trujillo-Baute, Elisa, 2018. "The economic impact of electricity losses," Energy Economics, Elsevier, vol. 75(C), pages 309-322.
    8. Liu, Yingqi, 2017. "Demand response and energy efficiency in the capacity resource procurement: Case studies of forward capacity markets in ISO New England, PJM and Great Britain," Energy Policy, Elsevier, vol. 100(C), pages 271-282.
    9. Schachter, Jonathan A. & Mancarella, Pierluigi & Moriarty, John & Shaw, Rita, 2016. "Flexible investment under uncertainty in smart distribution networks with demand side response: Assessment framework and practical implementation," Energy Policy, Elsevier, vol. 97(C), pages 439-449.
    10. Mazur, Christoph & Hoegerle, Yannick & Brucoli, Maria & van Dam, Koen & Guo, Miao & Markides, Christos N. & Shah, Nilay, 2019. "A holistic resilience framework development for rural power systems in emerging economies," Applied Energy, Elsevier, vol. 235(C), pages 219-232.
    11. Nouha Dkhili & David Salas & Julien Eynard & Stéphane Thil & Stéphane Grieu, 2021. "Innovative Application of Model-Based Predictive Control for Low-Voltage Power Distribution Grids with Significant Distributed Generation," Energies, MDPI, vol. 14(6), pages 1-28, March.
    12. Antonio Paola & David Angeli & Goran Strbac, 2018. "On Distributed Scheduling of Flexible Demand and Nash Equilibria in the Electricity Market," Dynamic Games and Applications, Springer, vol. 8(4), pages 761-798, December.
    13. Olga Bogdanova & Karīna Viskuba & Laila Zemīte, 2023. "A Review of Barriers and Enables in Demand Response Performance Chain," Energies, MDPI, vol. 16(18), pages 1-33, September.
    14. Wadim Strielkowski & Dalia Streimikiene & Alena Fomina & Elena Semenova, 2019. "Internet of Energy (IoE) and High-Renewables Electricity System Market Design," Energies, MDPI, vol. 12(24), pages 1-17, December.
    15. Zúñiga, K.V. & Castilla, I. & Aguilar, R.M., 2014. "Using fuzzy logic to model the behavior of residential electrical utility customers," Applied Energy, Elsevier, vol. 115(C), pages 384-393.
    16. Nolan, Sheila & Neu, Olivier & O’Malley, Mark, 2017. "Capacity value estimation of a load-shifting resource using a coupled building and power system model," Applied Energy, Elsevier, vol. 192(C), pages 71-82.
    17. Llaria, Alvaro & Curea, Octavian & Jiménez, Jaime & Camblong, Haritza, 2011. "Survey on microgrids: Unplanned islanding and related inverter control techniques," Renewable Energy, Elsevier, vol. 36(8), pages 2052-2061.
    18. Anjo, João & Neves, Diana & Silva, Carlos & Shivakumar, Abhishek & Howells, Mark, 2018. "Modeling the long-term impact of demand response in energy planning: The Portuguese electric system case study," Energy, Elsevier, vol. 165(PA), pages 456-468.
    19. Katz, Jonas, 2014. "Linking meters and markets: Roles and incentives to support a flexible demand side," Utilities Policy, Elsevier, vol. 31(C), pages 74-84.
    20. Asaad Mohammad & Ramon Zamora & Tek Tjing Lie, 2020. "Integration of Electric Vehicles in the Distribution Network: A Review of PV Based Electric Vehicle Modelling," Energies, MDPI, vol. 13(17), pages 1-20, September.

    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:spr:comgts:v:12:y:2015:i:4:p:519-537. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.