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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 |