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.
History
Year
2018
Thesis type
Doctoral thesis
Faculty/School
School of Computing and Information Technology
Language
English
Disclaimer
Unless otherwise indicated, the views expressed in this thesis are those of the author and do not necessarily represent the views of the University of Wollongong.