Decentralized Optimal Neuro-controllers for Generation and Transmission Devices in an Electric Power Network
In this paper, the dual heuristic programming (DHP) optimization algorithm is applied for the design of two LOCAL nonlinear optimal neuro-controllers on a practical multi-machine power system. One neuro-controller is designed to replace the conventional linear controllers, which are the automatic voltage regulator (AVR) and speed-governor (GOV), for a synchronous generator. The other is a new external neuro-controller for the series capacitive reactance compensator (SCRC), flexible ac transmission systems (FACTS) device. The PSCAD/EMTDC® simulation results show that interactions of two DHP neuro-controllers with different control objectives improve the system performance more effectively compared to when each one operates without the presence of the other one.
J. Park et al., "Decentralized Optimal Neuro-controllers for Generation and Transmission Devices in an Electric Power Network," Engineering Applications of Artificial Intelligence, Elsevier, Jan 2005.
The definitive version is available at https://doi.org/10.1016/j.engappai.2004.08.014
Electrical and Computer Engineering
Duke Power Company
Georgia Institute of Technology
National Science Foundation (U.S.)
University of Missouri--Rolla
Keywords and Phrases
Decentralized Control; Dual Heuristic Programming; Optimal Neuro-Controller; Power Network; Series Capacitive Reactance Compensator
International Standard Serial Number (ISSN)
Article - Journal
© 2005 Elsevier, All rights reserved.
01 Jan 2005