Trading Stochastic Production in Electricity Pools

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 7 in Integrating Renewables in Electricity Markets, 2014, pp 205-242 from Springer

Abstract: Abstract Renewable electricity producers must trade in day-ahead electricity markets in the same manner as conventional producers. However, their power production may be highly unpredictable and nondispatchable. This is the case, for example, of wind and solar power producers, which thus need to use the balancing market to mend eventual deviations with respect to their day-ahead schedule. This chapter presents close formulae to determine the optimal offering strategy of stochastic producers in the day-ahead market. The analytical solution to these formulae is available under certain assumptions on the probabilistic structure characterizing power production and market prices. Stochastic programming is then introduced as a powerful mathematical framework to rid the solution to the trading problem for stochastic producers of these simplifying assumptions.

Keywords: Stochastic Programming; Expected Profit; Mathematical Program With Equilibrium Constraint; Stochastic Producer; Adjustment Market (search for similar items in EconPapers)
Date: 2014
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DOI: 10.1007/978-1-4614-9411-9_7

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