Development and implementation of a multi-agent system for intelligent optimized power plant control.

Simple item page
dc.contributor.advisorLee, Kwang Y.
dc.contributor.authorHead, Jason D.
dc.contributor.departmentEngineering.en_US
dc.contributor.schoolsBaylor University. Dept. of Electrical and Computer Engineering.en_US
dc.date.accessioned2012-08-08T15:53:36Z
dc.date.available2012-08-08T15:53:36Z
dc.date.copyright2012-05
dc.date.issued2012-08-08
dc.description.abstractAs the demand for electric power grows and regulations on power plant operation become stricter, the size, and therefore complexity, of new power plant units is increasing while the intricacies of the multiple simultaneous processes that take place to generate electricity require tighter control. In order to provide a solution to some of the associated operational challenges arising from this situation, control techniques have been developed to allow optimized power plant control while considering non-fixed operating goals. Each of these techniques is computationally intensive, requiring a distributed, parallel control framework to implement each technique simultaneously in distributed subsystem environments. For these reasons, previous research has studied multi-agent systems as a means to implement such a control system. Therefore, the goal of this thesis is to fully develop a multi-agent system to coordinate and implement these techniques to control a third order fossil fuel power plant model.en_US
dc.description.degreeM.S.E.C.E.en_US
dc.identifier.urihttp://hdl.handle.net/2104/8433
dc.language.isoen_USen_US
dc.publisheren
dc.rightsBaylor University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. Contact librarywebmaster@baylor.edu for inquiries about permission.en_US
dc.rights.accessrightsWorldwide access.en_US
dc.rights.accessrightsAccess changed 1/13/14.
dc.subjectPower plant control.en_US
dc.subjectMulti-agent systems.en_US
dc.subjectMulti-objective optimization.en_US
dc.subjectNeural networks.en_US
dc.subjectModel predictive control.en_US
dc.titleDevelopment and implementation of a multi-agent system for intelligent optimized power plant control.en_US
dc.typeThesisen_US

Files

Original bundle

Now showing 1 - 2 of 2
Thumbnail Image
Name:
Jason_Head_masters.pdf
Size:
1.32 MB
Format:
Adobe Portable Document Format
Description:
Thesis
Download
No Thumbnail Available
Name:
Jason_Head_copyrightandavailabilityform.pdf
Size:
63.59 KB
Format:
Adobe Portable Document Format
Description:
Permission Form
Download

License bundle

Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.87 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

Electronic Theses and Dissertations
Theses/Dissertations - Electrical and Computer Engineering