dc.contributor.advisor |
Xia, Xiaohua |
en |
dc.contributor.postgraduate |
Nwulu, Mnandi Ikechi |
en |
dc.date.accessioned |
2016-07-29T11:02:04Z |
|
dc.date.available |
2016-07-29T11:02:04Z |
|
dc.date.created |
2016-04-15 |
en |
dc.date.issued |
2015 |
en |
dc.description |
Thesis (PhD)--University of Pretoria, 2015. |
en |
dc.description.abstract |
The energy management of today s power system is of utmost importance because of the increasing
complexity of today s power system operations. One of the core energy management
functions is determining the optimal dispatch of conventional generators whilst minimizing
or maximizing some pre-determined objective function which can either be minimizing costs,
minimizing emissions or maximizing profit. These problems have been explicitly defined as
the Dynamic Economic Emissions Dispatch (DEED) which is concerned with determining
the optimal dispatch of generators whilst minimizing costs and minimizing emissions and the
Profit Based Dynamic Economic Emissions Dispatch (PBDEED) which determines the optimal
dispatch of generators whilst minimizing costs, emissions and maximizing profit.
In this thesis, both the DEED and PBDEED are integrated with Demand Response (DR)
programs. Integrating DR programs into the DEED and PBDEED problem instead of considering
both problems independently is meant to introduce optimality into both the supply
side and demand side of the power system. The DR programs used in this work are a Game Theory DR (GTDR) program which is an Incentive Based DR (IB-DR) program and a Time
of Use DR (TOU-DR)program which is a Price Based DR (PB-DR) program.
A Model Predictive Control (MPC) strategy is further deployed to solve the GTDR-DEED
and GTDR-PBDEED models and obtained results show that for GTDR-DEED, MPC yields
higher customer energy curtailment when compared to the open loop controller whilst obtained
results also show that MPC shows better robustness against uncertainties and disturbances.
Finally, the GTDR program is integrated with a microgrid which is powered by conventional
generators and Renewable Energy Sources (RES). The microgrid is in the grid connected
mode and power can be traded between the main grid and the microgrid. Again, the results
obtained from the optimal energy management of the microgrid collaborate results obtained
in the main grid and show that integrating demand response programs into the energy management
problem are mutually beneficial to utility and consumers alike and can bring about
desired demand reduction in the power system. |
en |
dc.description.availability |
Unrestricted |
en |
dc.description.degree |
PhD |
en |
dc.description.department |
Electrical, Electronic and Computer Engineering |
en |
dc.description.librarian |
tm2016 |
en |
dc.identifier.citation |
Nwulu, MI 2015, Optimal energy management of power systems and microgrids incorporating demand response programs, PhD Thesis, University of Pretoria, Pretoria, viewed yymmdd <http://hdl.handle.net/2263/56097> |
en |
dc.identifier.other |
A2016 |
en |
dc.identifier.uri |
http://hdl.handle.net/2263/56097 |
|
dc.language.iso |
en |
en |
dc.publisher |
University of Pretoria |
en_ZA |
dc.rights |
© 2016 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. |
|
dc.subject |
UCTD |
en |
dc.title |
Optimal energy management of power systems and microgrids incorporating demand response programs |
en |
dc.type |
Thesis |
en |