Estimating Energy Market Schedules Using Historical Price Data: Preprint

Nicole Cortes, Xian Gao, Bernard Knueven, Alexander Dowling

Research output: Contribution to conferencePaper


The global climate crisis is expected to reshape the energy generation landscape in the coming decades. Increasing integration of non-dispatchable renewable energy resources into energy infrastructures and markets increases uncertainty and creates new opportunities for flexible energy systems. To conduct proper economic evaluation of flexible energy systems, such as integrated energy systems (IES), advancements in modelling of market interactions, such as bidding, is crucial. This work presents a shortcut algorithm which uses two mixed integer linear programs to compute dispatch schedules (e.g., hourly power production targets) that are constrained by the resource's bid information and characteristics (e.g., minimum up and down times) based on historical locational marginal price (LMP) data. This is orders of magnitude less data than required for a market clearing calculation with a full production cost model (PCM). We find the shortcut simulator recapitulates generator dispatch signals for the Prescient PCM with approximately 4% error for the RTS-GMLC test system.
Original languageAmerican English
Number of pages8
StatePublished - 2022
Event14th International Symposium on Process Systems Engineering (PSE 2021) - Kyoto, Japan
Duration: 19 Jun 202223 Jun 2022


Conference14th International Symposium on Process Systems Engineering (PSE 2021)
CityKyoto, Japan

Bibliographical note

See NREL/JA-2C00-84055 for paper as published in proceedings

NREL Publication Number

  • NREL/CP-2C00-81068


  • electricity generation
  • energy markets
  • integrated energy systems
  • multiscale simulation


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