  The modelling of modern power markets requires the representation of the
following main features: (i) a stochastic dynamic decision process, with
uncertainties related to renewable production and fuel costs, among others; and
(ii) a game-theoretic framework that represents the strategic behavior of
multiple agents, for example in daily price bids. These features can be in
theory represented as a stochastic dynamic programming recursion, where we have
a Nash equilibrium for multiple agents. However, the resulting problem is very
challenging to solve. This work presents an iterative process to solve the
above problem for realistic power systems. The proposed algorithm is consist of
a fixed point algorithm, in which, each step is solved via stochastic dual
dynamic programming method. The application of the proposed algorithm are
illustrated in case studies with the Panama systems.
