Year

2018

Degree Name

Doctor of Philosophy

Department

School of Computing and Information Technology

Abstract

Smart Grid has been widely acknowledged as an efficient solution to the current energy system. Smart Grid market is a complex and dynamic market with different types of consumers and suppliers under an uncertain environment. An efficient management of Smart Grid market can benefit Smart Grid in multiple aspects, including reducing energy cost, improving energy efficiency and enhancing network reliability. This thesis focuses on improving demand management in Smart Grid market through developing innovative machine learning methods.

This thesis is unavailable until Saturday, July 06, 2019

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