Uruguay is a pioneer in the use of renewable sources of energy and can usually satisfy its total demand from renewable sources. Control and optimization of the system is complicated by half of the installed power  wind and solar sources  be ing noncontrollable with high uncertainty and variability. In this work we present a novel optimization technique for efficient use of the production facilities. The dy namical system is stochastic, and we deal with its nonMarkovian dynamics through a Lagrangian relaxation. Continuoustime optimal control and value function are found from the solution to a sequence of HamiltonJacobiBellman partial differential equations associated with the system. We introduce a monotone scheme to avoid spurious oscillations in the numerical solution and apply the technique to a number of examples taken from the Uruguayan grid. We use parallelization and change of variables to reduce the computational times. Finally, we study the usefulness of extra system storage capacity offered by batteries.
Date of Award  Jun 30 2019 

Original language  English (US) 

Awarding Institution   Computer, Electrical and Mathematical Science and Engineering


Supervisor  Raul Tempone (Supervisor) 

 optimal control
 renewable energy
 HamiltonJacobiBellman
 wind power optimiztion
 stochastic optimal control
 optimal energy dispatch