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Extreme day-ahead renewables scenario selection in power grid operations

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  • Terrén-Serrano, Guillermo
  • Ludkovski, Michael

Abstract

We propose and analyze the application of statistical functional depth metrics for the selection of extreme scenarios for realized electric load, as well as solar and wind generation in day-ahead grid planning. Our primary motivation is screening probabilistic scenarios to identify those most relevant for operational risk mitigation. To handle the high-dimensionality of the scenarios across asset classes and intra-day periods, we employ functional measures of depth to sub-select outlying scenarios that are most likely to be the riskiest for the grid operation. We investigate a range of functional depth measures, as well as a range of operational risks, including load shedding, operational costs, reserve shortfalls, and variable renewable energy curtailment. The effectiveness of the proposed screening approach is demonstrated through a case study on the realistic Texas-7k grid.

Suggested Citation

  • Terrén-Serrano, Guillermo & Ludkovski, Michael, 2025. "Extreme day-ahead renewables scenario selection in power grid operations," Applied Energy, Elsevier, vol. 391(C).
    • Handle: RePEc:eee:appene:v:391:y:2025:i:c:s0306261925004775
    DOI: 10.1016/j.apenergy.2025.125747
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