NDLI: Implementation of a multi-agent system for optimized multiobjective power plant control

Content Provider	IEEE Xplore Digital Library
Author	Head, J.D. Gomes, J.R. Williams, C.S. Lee, K.Y.
Copyright Year	2010
Description	Author affiliation: Department of Electrical and Computer Engineering, Baylor University, Waco, TX, U.S.A (Head, J.D.; Gomes, J.R.; Williams, C.S.; Lee, K.Y.)
Abstract	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 very complicated feat, which involves many individual computationally intensive tasks. For the presented method of design, these tasks include calculating feasible control valve operating ranges based on unit load demand, parameter optimization, training neural networks, monitoring and managing real-time input/output data, and task delegation, among others. It is because each of these tasks requires such computational overhead and these systems need to be coordinated among distributed environments that dividing them up into multiple agents is necessary. 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 multiobjective power plant controls in Matlab.
Starting Page	1
Ending Page	7
File Size	338292
Page Count	7
File Format	PDF
ISBN	9781424480463
e-ISBN	9781424480470
DOI	10.1109/NAPS.2010.5619588
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-09-26
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Power generation Message systems Mathematical model Feedforward neural networks Artificial neural networks Multiagent systems Monitoring reference governor Power plant control multi-agent systems multi-objective optimization
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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

Multi-Agent System implementation in JADE environment for power plant control

Analysis of the pareto front of a multi-objective optimization problem for a fossil fuel power plant

A Multiagent-System-Based Intelligent Reference Governor for Multiobjective Optimal Power Plant Operation

Cooperative output regulation of multi-agent systems

Solving Multi-agent Control Problems Using Particle Swarm Optimization

Windy-solar Power Generation system based on Multi-agent System

Studying on single neuron realization of feedforward two degree-of-freedom PID control

Levenberg Marquardt algorithm based economic load dispatch

Implementation of a multi-agent system for optimized multiobjective power plant control

Similar Documents

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

Multi-Agent System implementation in JADE environment for power plant control

Analysis of the pareto front of a multi-objective optimization problem for a fossil fuel power plant

A Multiagent-System-Based Intelligent Reference Governor for Multiobjective Optimal Power Plant Operation

Cooperative output regulation of multi-agent systems

Solving Multi-agent Control Problems Using Particle Swarm Optimization

Windy-solar Power Generation system based on Multi-agent System

Studying on single neuron realization of feedforward two degree-of-freedom PID control

Levenberg Marquardt algorithm based economic load dispatch

Implementation of a multi-agent system for optimized multiobjective power plant control