Advanced Computational Techniques for Electricity Market Analysis considering Sustainable Energy Supply Issues
Speaker: Xun Zhou, ITEE
When: 2008-04-03 11:00:00
Venue: 78-420
Host: Dr X. Li and Dr ZY Dong
Abstract:Electricity industries worldwide are undergoing rapid and widespread
changes. These have been largely driven by the market-oriented
restructuring underway in many countries and the increasing global
environmental concerns about climate change. For the purpose of
avoiding serious consequences caused by climate change, Australian
government is proposing an emission trading scheme (ETS) and
planning to implement it from 2010. ETS is considered as the best
option of using market mechanism to achieve GHG emissions abatement
in the most cost-effective way. As power generations are the major
sources of Greenhouse Gas (GHG) emissions, once the ETS is
implemented, there will have far-reaching influences on the
Australian power industry both economically and technically. On the
one hand, ETS will increase extra costs for fossil fuel generators
and create uncertainties for power industry investment; on the other
hand, ETS will encourage the innovation and penetration of renewable
and low emission generation technologies. Distributed Generations
(DGs) is one of the typical applications since most of DGs are low
emissions and environmental friendly which can contribute to the
reduction of GHGs. However, applications of DGs in large scale have
faced complex control challenges in the operation of a low voltage
(LV) grid that need to be solved before the benefits of DGs can be
realised.
For this PhD research, we will first assess and quantify the
potential impact on, and change in, economic efficiency in the
electricity generation sector in Australian national electricity
market after the implementation of ETS, as opposed to without the
introduction of ETS.
Afterward, environmental benefits of Distributed Generations (DGs)
under ETS will be studied. Finally, we will study and provide tools
for the intelligently control of DG resources to facilitate their
widespread adoption, aiming at using multi-agent technologies to
design and develop an intelligent Microgrid framework to optimize
the operation of DGs through minimize costs and GHG emissions.
Biography:(biography unavailable)
Type: Ph.D confirmation
Contact:Dr X. Li and Dr ZY Dong, seminar host (zdong@itee.uq.edu.au)
or Guido Governatori (ITEE seminar co-ordinator)
(guido@itee.uq.edu.au)