IDEAS home Printed from https://ideas.repec.org/a/eee/enepol/v147y2020ics0301421520305747.html
   My bibliography  Save this article

Dynamic operating reserve procurement improves scarcity pricing in PJM

Author

Listed:
  • Lavin, Luke
  • Murphy, Sinnott
  • Sergi, Brian
  • Apt, Jay

Abstract

Competitive electricity markets can procure reserve generation through a market in which the demand for reserves is administratively established. A downward sloping or stepped administrative demand curve is commonly termed an operating reserve demand curve (ORDC). We propose a dynamic formulation of an ORDC with generator forced outage probabilities conditional on ambient temperature to implement scarcity pricing in a wholesale electricity market. This formulation improves on common existing methods used by wholesale market operators to articulate ORDCs by explicitly accounting for a large source of observed variability in generator forced outages, whereby for a fixed load, more reserves are required during times of extreme heat and cold to maintain a constant risk of reserve shortage. Such a dynamic ORDC increases social welfare by $17.1 million compared to current practice in the PJM Interconnection during a high load week in a welfare-maximizing electricity market with co-optimized procurement of energy and reserves. A dynamic ORDC increases reserve prices under scarcity conditions, but has minimal effects on total market payments. The results are directly relevant to the modeled two-settlement electricity market in PJM, which is currently undergoing enhancements to its ORDC.

Suggested Citation

  • Lavin, Luke & Murphy, Sinnott & Sergi, Brian & Apt, Jay, 2020. "Dynamic operating reserve procurement improves scarcity pricing in PJM," Energy Policy, Elsevier, vol. 147(C).
    • Handle: RePEc:eee:enepol:v:147:y:2020:i:c:s0301421520305747
    DOI: 10.1016/j.enpol.2020.111857
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301421520305747
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.enpol.2020.111857?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. Murphy, Sinnott & Apt, Jay & Moura, John & Sowell, Fallaw, 2018. "Resource adequacy risks to the bulk power system in North America," Applied Energy, Elsevier, vol. 212(C), pages 1360-1376.
    2. Anthony Papavasiliou & Shmuel S. Oren, 2013. "Multiarea Stochastic Unit Commitment for High Wind Penetration in a Transmission Constrained Network," Operations Research, INFORMS, vol. 61(3), pages 578-592, June.
    3. Murphy, Sinnott & Sowell, Fallaw & Apt, Jay, 2019. "A time-dependent model of generator failures and recoveries captures correlated events and quantifies temperature dependence," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    4. Craig, Michael & Guerra, Omar J. & Brancucci, Carlo & Pambour, Kwabena Addo & Hodge, Bri-Mathias, 2020. "Valuing intra-day coordination of electric power and natural gas system operations," Energy Policy, Elsevier, vol. 141(C).
    5. Szinai, Julia K. & Sheppard, Colin J.R. & Abhyankar, Nikit & Gopal, Anand R., 2020. "Reduced grid operating costs and renewable energy curtailment with electric vehicle charge management," Energy Policy, Elsevier, vol. 136(C).
    6. Murphy, Sinnott & Lavin, Luke & Apt, Jay, 2020. "Resource adequacy implications of temperature-dependent electric generator availability," Applied Energy, Elsevier, vol. 262(C).
    7. William W. Hogan, 2013. "Electricity Scarcity Pricing Through Operating Reserves," Economics of Energy & Environmental Policy, International Association for Energy Economics, vol. 0(Number 2).
    8. PAPAVASILIOU, Anthony & OREN, Schmuel S., 2013. "Multiarea stochastic unit commitment for high wind penetration in a transmission constrained network," LIDAM Reprints CORE 2500, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    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. Haider Ali & Faheem Aslam & Paulo Ferreira, 2021. "Modeling Dynamic Multifractal Efficiency of US Electricity Market," Energies, MDPI, vol. 14(19), pages 1-16, September.
    2. Luigi Viola & Saeed Nordin & Daniel Dotta & Mohammad Reza Hesamzadeh & Ross Baldick & Damian Flynn, 2023. "Ancillary Services in Power System Transition Toward a 100% Non-Fossil Future: Market Design Challenges in the United States and Europe," Papers 2311.02090, arXiv.org.
    3. Dranka, Géremi Gilson & Ferreira, Paula & Vaz, A. Ismael F., 2021. "A review of co-optimization approaches for operational and planning problems in the energy sector," Applied Energy, Elsevier, vol. 304(C).
    4. Zhang, Yuanyuan & Zhao, Huiru & Li, Bingkang, 2022. "Research on the design and influence of unit generation capacity adequacy guarantee mechanism in the power market," Energy, Elsevier, vol. 248(C).

    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. Muñoz, Francisco D. & Suazo-Martínez, Carlos & Pereira, Eduardo & Moreno, Rodrigo, 2021. "Electricity market design for low-carbon and flexible systems: Room for improvement in Chile," Energy Policy, Elsevier, vol. 148(PB).
    2. Anthony Papavasiliou & Yves Smeers, 2017. "Remuneration of Flexibility using Operating Reserve Demand Curves: A Case Study of Belgium," The Energy Journal, International Association for Energy Economics, vol. 0(Number 6).
    3. Faezeh Akhavizadegan & Lizhi Wang & James McCalley, 2020. "Scenario Selection for Iterative Stochastic Transmission Expansion Planning," Energies, MDPI, vol. 13(5), pages 1-18, March.
    4. Brown, David P. & Muehlenbachs, Lucija, 2023. "The Value of Electricity Reliability: Evidence from Battery Adoption," Working Papers 2023-5, University of Alberta, Department of Economics.
    5. Victor M. Zavala & Kibaek Kim & Mihai Anitescu & John Birge, 2017. "A Stochastic Electricity Market Clearing Formulation with Consistent Pricing Properties," Operations Research, INFORMS, vol. 65(3), pages 557-576, June.
    6. Skolfield, J. Kyle & Escobedo, Adolfo R., 2022. "Operations research in optimal power flow: A guide to recent and emerging methodologies and applications," European Journal of Operational Research, Elsevier, vol. 300(2), pages 387-404.
    7. Noori, Ehsan & Khazaei, Ehsan & Tavaro, Mehdi & Bardideh, Farhad, 2019. "Economically Operation of Power Utilities Base on MILP Approach," MPRA Paper 95910, University Library of Munich, Germany.
    8. Howard, B. & Waite, M. & Modi, V., 2017. "Current and near-term GHG emissions factors from electricity production for New York State and New York City," Applied Energy, Elsevier, vol. 187(C), pages 255-271.
    9. Abdul Rauf & Mahmoud Kassas & Muhammad Khalid, 2022. "Data-Driven Optimal Battery Storage Sizing for Grid-Connected Hybrid Distributed Generations Considering Solar and Wind Uncertainty," Sustainability, MDPI, vol. 14(17), pages 1-27, September.
    10. Hain, Martin & Kargus, Tobias & Schermeyer, Hans & Uhrig-Homburg, Marliese & Fichtner, Wolf, 2022. "An electricity price modeling framework for renewable-dominant markets," Working Paper Series in Production and Energy 66, Karlsruhe Institute of Technology (KIT), Institute for Industrial Production (IIP).
    11. Munoz, Francisco D. & Pumarino, Bruno J. & Salas, Ignacio A., 2017. "Aiming low and achieving it: A long-term analysis of a renewable policy in Chile," Energy Economics, Elsevier, vol. 65(C), pages 304-314.
    12. Le Cadre, Hélène & Mezghani, Ilyès & Papavasiliou, Anthony, 2019. "A game-theoretic analysis of transmission-distribution system operator coordination," European Journal of Operational Research, Elsevier, vol. 274(1), pages 317-339.
    13. De Vos, K. & Stevens, N. & Devolder, O. & Papavasiliou, A. & Hebb, B. & Matthys-Donnadieu, J., 2019. "Dynamic dimensioning approach for operating reserves: Proof of concept in Belgium," Energy Policy, Elsevier, vol. 124(C), pages 272-285.
    14. Trine K. Boomsma, 2019. "Comments on: A comparative study of time aggregation techniques in relation to power capacity-expansion modeling," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(3), pages 406-409, October.
    15. Majid Al-Gwaiz & Xiuli Chao & Owen Q. Wu, 2017. "Understanding How Generation Flexibility and Renewable Energy Affect Power Market Competition," Manufacturing & Service Operations Management, INFORMS, vol. 19(1), pages 114-131, February.
    16. Varawala, Lamia & Dán, György & Hesamzadeh, Mohammad Reza & Baldick, Ross, 2023. "A generalised approach for efficient computation of look ahead security constrained optimal power flow," European Journal of Operational Research, Elsevier, vol. 310(2), pages 477-494.
    17. Johnson, Samuel C. & Papageorgiou, Dimitri J. & Mallapragada, Dharik S. & Deetjen, Thomas A. & Rhodes, Joshua D. & Webber, Michael E., 2019. "Evaluating rotational inertia as a component of grid reliability with high penetrations of variable renewable energy," Energy, Elsevier, vol. 180(C), pages 258-271.
    18. Sun, Mingyang & Cremer, Jochen & Strbac, Goran, 2018. "A novel data-driven scenario generation framework for transmission expansion planning with high renewable energy penetration," Applied Energy, Elsevier, vol. 228(C), pages 546-555.
    19. Aghaei, Jamshid & Nikoobakht, Ahmad & Siano, Pierluigi & Nayeripour, Majid & Heidari, Alireza & Mardaneh, Mohammad, 2016. "Exploring the reliability effects on the short term AC security-constrained unit commitment: A stochastic evaluation," Energy, Elsevier, vol. 114(C), pages 1016-1032.
    20. ARAVENA, Ignacio & PAPAVASILIOU, Anthony, 2016. "An Asynchronous Distributed Algorithm for solving Stochastic Unit Commitment," LIDAM Discussion Papers CORE 2016038, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    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:enepol:v:147:y:2020:i:c:s0301421520305747. 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/locate/enpol .

    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.