Optimization of Simultaneous Power Production and Trading by Stochastic Integer Programming
We develop a two-stage stochastic integer programming model for the simultaneous optimization of power production and day-ahead power trading. 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 of nonanticipativity with branch-and-bound in the spirit of global optimization. Finally, we report some first computational experiences.