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Resource adequacy risks to the bulk power system in North America

Author

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  • Murphy, Sinnott
  • Apt, Jay
  • Moura, John
  • Sowell, Fallaw

Abstract

To keep the electric power system reliable, grid operators procure reserve generation capacity to protect against generator failures and significant deviation from the load forecast. Current methods for determining reserve requirements use historical generator availability data (recorded as failure events) to compute the fraction of the time each unit in the power system was unavailable unexpectedly. These values are then combined using analytical or simulation methods to yield a distribution of available capacity. From this distribution, the reserve capacity needed to maintain a particular reliability target may be determined. Such an approach implicitly assumes that generator failures occur independently of one another and that generator availability is not seasonal.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:appene:v:212:y:2018:i:c:p:1360-1376
    DOI: 10.1016/j.apenergy.2017.12.097
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    References listed on IDEAS

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    Cited by:

    1. Lavin, Luke & Murphy, Sinnott & Sergi, Brian & Apt, Jay, 2020. "Dynamic operating reserve procurement improves scarcity pricing in PJM," Energy Policy, Elsevier, vol. 147(C).
    2. Lai, Qiupin & Liu, Chengxi & Sun, Kai, 2021. "Vulnerability assessment for voltage stability based on solvability regions of decoupled power flow equations," Applied Energy, Elsevier, vol. 304(C).
    3. Gallego, Camilo A., 2025. "Marginal price impact under firm energy obligations in capacity remuneration mechanisms: The case of reliability options," Energy Economics, Elsevier, vol. 152(C).
    4. Sun, Yinong & Frew, Bethany & Dalvi, Sourabh & Dhulipala, Surya C., 2022. "Insights into methodologies and operational details of resource adequacy assessment: A case study with application to a broader flexibility framework," Applied Energy, Elsevier, vol. 328(C).
    5. 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.
    6. Murphy, Sinnott & Lavin, Luke & Apt, Jay, 2020. "Resource adequacy implications of temperature-dependent electric generator availability," Applied Energy, Elsevier, vol. 262(C).
    7. Chen, Tao & Pipattanasomporn, Manisa & Rahman, Imran & Jing, Zejia & Rahman, Saifur, 2020. "MATPLAN: A probability-based planning tool for cost-effective grid integration of renewable energy," Renewable Energy, Elsevier, vol. 156(C), pages 1089-1099.
    8. Tillmanns, M. & Schöttler, J. & Praktiknjo, A., 2026. "A review of probabilistic resource adequacy assessments in power systems: Methods, applications, and future challenges," Energy Policy, Elsevier, vol. 209(PA).

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