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Title: Regression Monte Carlo and applications in energy
Author: Balata, Alessandro
ISNI:       0000 0004 8500 8983
Awarding Body: University of Leeds
Current Institution: University of Leeds
Date of Award: 2019
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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.
Supervisor: Palczewski, Jan Sponsor: NERC
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available