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A time-dependent model of generator failures and recoveries captures correlated events and quantifies temperature dependence

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

Abstract

Most current approaches to resource adequacy modeling assume that each generator in a power system fails and recovers independently of other generators with invariant transition probabilities. This assumption has been shown to be wrong. Here we present a new statistical model that allows generator failure models to incorporate correlated failures and recoveries. In the model, transition probabilities are a function of exogenous variables; as an example we use temperature and system load. Model parameters are estimated using 23 years of data for 1845 generators in the USA’s largest electricity market. We show that temperature dependencies are statistically significant in all generator types, but are most pronounced for diesel and natural gas generators at low temperatures and nuclear generators at high temperatures. Our approach yields significant improvements in predictive performance compared to current practice, suggesting that explicit models of generator transitions using jointly experienced stressors can help grid planners more precisely manage their systems.

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  • 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.
    • Handle: RePEc:eee:appene:v:253:y:2019:i:c:20
    DOI: 10.1016/j.apenergy.2019.113513
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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. Murphy, Sinnott & Lavin, Luke & Apt, Jay, 2020. "Resource adequacy implications of temperature-dependent electric generator availability," Applied Energy, Elsevier, vol. 262(C).
    3. Steinhäuser, J. Micha & Eisenack, Klaus, 2020. "How market design shapes the spatial distribution of power plant curtailment costs," Energy Policy, Elsevier, vol. 144(C).
    4. Zhang, Dongdong & Li, Chunjiao & Goh, Hui Hwang & Ahmad, Tanveer & Zhu, Hongyu & Liu, Hui & Wu, Thomas, 2022. "A comprehensive overview of modeling approaches and optimal control strategies for cyber-physical resilience in power systems," Renewable Energy, Elsevier, vol. 189(C), pages 1383-1406.
    5. Bromley-Dulfano, Isaac & Florez, Julian & Craig, Michael T., 2021. "Reliability benefits of wide-area renewable energy planning across the Western United States," Renewable Energy, Elsevier, vol. 179(C), pages 1487-1499.

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