A stochastic integer programming model for incorporating day-ahead trading of electricity into hydro-thermal unit commitment

We develop a two-stage stochastic integer programming model for the simultaneous optimization of power production and day-ahead power trading in a hydro-thermal system. The model rests on mixed-integer linear formulations for the unit commitment problem and for the price clearing mechanism at the power exchange. Foreign bids enter as random components into the model. We solve the stochastic integer program by a decomposition method combining Lagrangian relaxation and nonanticipativity with branch-and-bound in the spirit of global optimization. Finally, we report some first computational experiences.