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Bidding in day-ahead electricity markets : a dynamic programming approach

par De Boeck, Jérôme ;Fortz, Bernard ;Labbé, Martine ;Marcotte, Etienne
Organisme financeur Université libre de Bruxelles
Publication Publié, 2021-12-03

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Résumé :

Strategic bidding problems have gained a lot of attention with the introduction of deregulated electricity markets where producers and retailers trade electricity in a day-ahead market ran by a Market Operator (MO). All actors propose bids composed of a unit production price and a quantity of electricity to the MO. Based on these bids the MO selects the most interesting ones and defines the spot price of electricity at which all actors are paid. As the price of electricity is determined by the bids of all actors, a bidding Generation Company (GC) faces a high risk regarding its profit when placing bids as the bids of competitors are not known in advance. In this paper, we propose a novel dynamic programming approach for the Stochastic Bidding Problem (SBP) of a GC in day-ahead market considering uncertainty over the competitor bids. We prove this problem is NP-hard and study two variants of this problem. Firstly, a relaxation providing an upper bound which is solved in polynomial time (SBP-R). Secondly, a bidding problem considering fixed bidding quantities (SBP-Q) that has previously been solved through heuristic methods. We prove SBP-Q is NP-hard and solve it to optimality in pseudo-polynomial time. SBP-Q is solved on much larger instances than in previous studies and show in numerical results that its optimal value is under 1% of the optimal value of SBP by using the upper bound provided by SBP-R.