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Abstract
An electric power market is formulated as a Stackelberg game where two firms, A and B, produce energy. Two distinct situations, according to the firm who plays the leader role, are analysed. In the first one, the firm A is the leader and the firm B is the follower, and in the second situation the players reverse their roles. In order to select the optimal strategy, the leader uses as knowledge his own perception of the market and anticipates the reactions of the other followers. The main goal of this paper is to understand the behaviour of the various agents that compose the electric power network, such as transmissions capacity, quantities of power generated and demanded, when the leadership changes.
The problem is formulated as a mathematical program with complementarity constraints (MPCC) and reformulated into a nonlinear program (NLP), allowing the use of robust NLP solvers. Computational results using Lancelot, Loqo and Snopt solvers are performed. The numerical experiments show that the firm profit is conditioned by the available information.