  We address the problem of scheduling water resources in a power system via
approximate dynamic programming.To this goal, we model a finite horizon
economic dispatch problemwith convex stage cost and affine dynamics, and
consider aquadratic approximation of the value functions. Evaluating
theachieved policy entails solving a quadratic program at each timestep, while
value function fitting can be cast as a semidefiniteprogram. We test our
proposed algorithm on a simplified versionof the Uruguayan power system,
achieving a four percent costreduction with respect to the myopic policy
