Regression Monte Carlo and Applications in Energy

This Thesis contains three separate parts. The first part is a monograph, where we
present the history and novel developments to the family of Regression Monte Carlo
algorithms applied to stochastic control problems. The second part explores different
applications and experiments where we show the behaviour, and some interesting
characteristics, of the methods presented in part I. The third, and last part of
the thesis deals with the current energy systems and features a study of optimal
design and management of a microgrid system inspired by the facility installed in
Huatacondo, Atacama desert, Chile.