By Topic

Multi-agent system based intelligent distributed control system for power plants

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Kwang Y. Lee ; Department of Electrical and Computer Engineering, Baylor University, Waco, TX 76798 ; Jason D. Head ; Jason R. Gomes ; Craig S. Williams

This paper presents an approach for intelligent distributed control of power plants using the concept of multi-agent systems (MAS). Solving the problem of optimally controlling a power plant based on multiple objectives, such as minimizing pollution, maximizing equipment life, etc., and coordinating each of the involved tasks that must be performed in distributed environments is a challenge, which involves many individual computationally intensive tasks. These tasks include calculating feasible control valve operating ranges based on unit load demand, multi-objective optimization, training neural networks, monitoring and managing real-time input/output data, and task delegation, among others. Since each of these tasks requires such computational overhead and these systems need to be coordinated among distributed environments, it is necessary to divide them up into multiple agents. The presented method of design of the multi-agent system is a continuation of research to develop a multi-agent system to implement a technique for computing optimal multi-objective power plant controls.

Published in:

2011 IEEE Power and Energy Society General Meeting

Date of Conference:

24-29 July 2011