Clearing the Day-Ahead Market with a High Penetration of Stochastic Production

  • Juan M. MoralesEmail author
  • Antonio J. Conejo
  • Henrik Madsen
  • Pierre Pinson
  • Marco Zugno
Part of the International Series in Operations Research & Management Science book series (ISOR, volume 205)


This chapter motivates, develops, and explains a market-clearing algorithm for the day-ahead market, intended for electric energy markets with a significant number of stochastic producers. To adequately mimic the real-world decision-making process, a two-stage stochastic programming model with recourse is presented. Market outcomes include both production and consumption quantities, and energy-only clearing prices. These prices embody desirable properties such as revenue adequacy in expectation and cost recovery, also in expectation. Complementarily, and as alternative to the two-stage stochastic programming approach, this chapter also introduces a dispatch method for energy and reserve that copes with uncertain generation using adaptive robust optimization. A number of clarifying examples illustrate the theoretical interest and practical relevance of the proposed market-clearing algorithms.


Wind Farm Stochastic Programming Robust Optimization Electricity Market Reserve Capacity 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Juan M. Morales
    • 1
    Email author
  • Antonio J. Conejo
    • 2
  • Henrik Madsen
    • 1
  • Pierre Pinson
    • 3
  • Marco Zugno
    • 1
  1. 1.DTU ComputeTechnical University of DenmarkLyngbyDenmark
  2. 2.University of Castilla – La ManchaCiudad RealSpain
  3. 3.DTU ElektroTechnical University of DenmarkLyngbyDenmark

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