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

Juan M. Morales (), Antonio J. Conejo (), Henrik Madsen (), Pierre Pinson () and Marco Zugno ()
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Juan M. Morales: Technical University of Denmark
Antonio J. Conejo: University of Castilla – La Mancha
Henrik Madsen: Technical University of Denmark
Pierre Pinson: Technical University of Denmark
Marco Zugno: Technical University of Denmark

Chapter 3 in Integrating Renewables in Electricity Markets, 2014, pp 57-100 from Springer

Abstract: Abstract 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.

Keywords: Wind Farm; Stochastic Programming; Robust Optimization; Electricity Market; Reserve Capacity (search for similar items in EconPapers)
Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:spr:isochp:978-1-4614-9411-9_3

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DOI: 10.1007/978-1-4614-9411-9_3

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