Quadratic approximate dynamic programming for scheduling water resources: a case study

TL;DR

This paper introduces a quadratic approximate dynamic programming approach for scheduling water resources in power systems, demonstrating a 4% cost reduction in a case study of Uruguay's power system.

Contribution

The paper develops a novel quadratic approximation method for dynamic programming in water resource scheduling, combining quadratic value function fitting with semidefinite programming.

Findings

Achieved 4% cost reduction over myopic policy

Implemented quadratic programming for policy evaluation

Validated approach on a simplified Uruguayan power system

Abstract

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