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

As 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.

Name thesis:degree_name

M.S.E.C.E.

Level thesis:degree_level

Masters

Grantor

Baylor University.

Year dc:date.issued

2012

Author dc:creator

• Head, Jason D.

Advisor dc:contributor.advisor

• Lee, Kwang Y.

• Power plant control.
• Multi-agent systems.
• Multi-objective optimization.
• Neural networks.
• Model predictive control.

Statement dc:rights

• Baylor University works 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 libraryquestions@baylor.edu for inquiries about permission.

Language dc:language.iso

en

Handle dc:identifier.uri

https://hdl.handle.net/2104/8433

OAI identifier oai:identifier

oai:baylor-ir.tdl.org:2104/8433