Title page for ETD etd-09222011-095851

Document Type Master's Dissertation
Author Ekpenyong, Uduakobong Edet
Email uekpenyong@tuks.co.za
URN etd-09222011-095851
Document Title A model predictive control approach to generator maintenance scheduling
Degree MSc
Department Electrical, Electronic and Computer Engineering
Advisor Name Title
Prof X Xia Co-Supervisor
Prof J Zhang Supervisor
  • kontrole
  • partikel swerm optimalisering
  • optimalisering
  • onderhoud
  • modellering
  • kragopwekker
  • kragopwekker onderhoudskedule
  • control
  • swarm intelligence
  • model predictive control
  • genetic algorithm
  • swerm intelligensie
  • model voorspellende kontrole
  • genetiese algoritme
  • generator maintenance scheduling
  • generators
  • modelling
  • maintenance
  • optimization
  • particle swarm optimization
Date 2011-09-06
Availability unrestricted

The maintenance schedule of generators in power plants needs to match the electricity demand and needs to ensure the reliability of the power plant at a minimum cost of operation. In this study, a comparison is made between the modified generator maintenance scheduling model and the classic generator maintenance scheduling model using the reliability objective functions. Both models are applied to a 21-unit test system, and the results show that the modified generator maintenance scheduling model gives better and more reliable solutions than the regular generator maintenance scheduling model. The better results of the modified generator maintenance scheduling model are due the modified and additional constraints in the modified generator maintenance scheduling model. Due to the reliable results of the modified generator maintenance scheduling model, a robust model is formulated using the economic cost objective function. The model includes modified crew and maintenance window constraints, with some additional constraints such as the relationship constraints among the variables. To illustrate the robustness of the formulated GMS model, the maintenance of the Arnot power plant in South Africa is scheduled with open-loop and closed-loop controllers. Both controllers satisfy all the constraints but the closed-loop results are better than the open-loop results.

AFRIKAANS : Die onderhoudskedule vir kragopwekkers (OSK) in kragstasies moet kan voorsien in die vraag na elektrisiteit en moet die betroubaarheid van die kragstasie teen 地 minimum operasiekoste verseker. In hierdie studie word die betroubaarheidsdoelwitfunksie gebruik om 地 gewysigde onderhoudskeduleringsmodel vir kragopwekkers te vergelyk met die konvensionele onderhoudskeduleringsmodel. Beide modelle word toegepas op 'n 21-eenheid-toetsstelsel, en die resultate toon dat die gewysigde model 地 beter en meer betroubare oplossing bied as die konvensionele model. Die beter resultate van die gewysigde model is die gevolg van die gewysigde en bykomende beperkings in die gewysigde model. As gevolg van die betroubare resultate van die gewysigde onderhoudskeduleringsmodel word die koste-ekonomie-doelwitfunksie gebruik om 地 robuuste model te formuleer. Die model sluit gewysigde bemanning- en onderhoudvensterbeperkings in, met 地 paar bykomende beperkings soos die verhoudingsbeperkings tussen die veranderlikes. Om die robuustheid van die geformuleerde OSK-model te illustreer word die instandhouding van die Arnot kragstasie in Suid-Afrika geskeduleer met oop- en geslotelus-beheerders. Beide beheerders voldoen aan al die beperkinge, maar die geslotelusresultate is beter as die ooplusresultate.

ゥ 2011, 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.

Please cite as follows:

Ekpenyong, UE 2011, A model predictive control approach to generator maintenance scheduling, MSc dissertation, University of Pretoria, Pretoria, viewed yymmdd < http://upetd.up.ac.za/thesis/available/etd-09222011-095851 / >


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