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Analysis on the interaction between short-term operating reserves and adequacy

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  • Hermans, Mathias
  • Bruninx, Kenneth
  • Vitiello, Silvia
  • Spisto, Amanda
  • Delarue, Erik

Abstract

An electricity generation system adequacy assessment aims to generate statistically significant adequacy indicators given projected developments in, i.a., renewable and conventional generation, demand, demand response and energy storage availability. Deterministic unit commitment (DUC) models with exogenous reserve requirements, as often used in today's adequacy studies to represent day-to-day power system operations, do not account for the contribution of operating reserves to the adequacy of the system. Hence, the adequacy metrics obtained from such an analysis represent a worst-case estimate and should be interpreted with care. In this paper, we propose to use a DUC model with a set of state-of-the-art probabilistic reserve constraints (DUC-PR). The performance of the DUC-PR model in the context of adequacy assessments is studied in a numerical case study. The Expected Energy Not Served (EENS) volume obtained with the DUC model is shown to be a poor estimate of the true EENS volume. In contrast, the DUC-PR methodology yields an accurate estimate of the EENS volume without significantly increasing the computational burden. Policy makers should encourage adopting novel operational power system models, such as the DUC-PR model, to accurately estimate the contribution of operating reserves to system adequacy.

Suggested Citation

  • Hermans, Mathias & Bruninx, Kenneth & Vitiello, Silvia & Spisto, Amanda & Delarue, Erik, 2018. "Analysis on the interaction between short-term operating reserves and adequacy," Energy Policy, Elsevier, vol. 121(C), pages 112-123.
    • Handle: RePEc:eee:enepol:v:121:y:2018:i:c:p:112-123
    DOI: 10.1016/j.enpol.2018.06.012
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    References listed on IDEAS

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    1. Felder, Frank A., 2001. ""An Island of Technicality in a Sea of Discretion": A Critique of Existing Electric Power Systems Reliability Analysis and Policy," The Electricity Journal, Elsevier, vol. 14(3), pages 21-31, April.
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    3. Di Somma, M. & Graditi, G. & Heydarian-Forushani, E. & Shafie-khah, M. & Siano, P., 2018. "Stochastic optimal scheduling of distributed energy resources with renewables considering economic and environmental aspects," Renewable Energy, Elsevier, vol. 116(PA), pages 272-287.
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    Cited by:

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    2. Thanh Long Duong & Phuong Duy Nguyen & Van-Duc Phan & Dieu Ngoc Vo & Thang Trung Nguyen, 2019. "Optimal Load Dispatch in Competitive Electricity Market by Using Different Models of Hopfield Lagrange Network," Energies, MDPI, vol. 12(15), pages 1-24, July.
    3. Astier, Nicolas & Ovaere, Marten, 2022. "Reliability standards and generation adequacy assessments for interconnected electricity systems," Energy Policy, Elsevier, vol. 168(C).
    4. Le Chi Kien & Thanh Long Duong & Van-Duc Phan & Thang Trung Nguyen, 2020. "Maximizing Total Profit of Thermal Generation Units in Competitive Electric Market by Using a Proposed Particle Swarm Optimization," Sustainability, MDPI, vol. 12(3), pages 1-35, February.

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