DocumentCode :
791713
Title :
Coordination control of ULTC transformer and STATCOM based on an artificial neural network
Author :
Kim, Gwang Won ; Lee, Kwang Y.
Author_Institution :
Sch. of Electr. Eng., Univ. of Ulsan, South Korea
Volume :
20
Issue :
2
fYear :
2005
fDate :
5/1/2005 12:00:00 AM
Firstpage :
580
Lastpage :
586
Abstract :
This paper presents an artificial neural network (ANN)-based coordination control scheme for under load tap changing (ULTC) transformer and STATCOM. The objective of the coordination controller is to minimize both the amount of tap changes of the transformer and STATCOM output while maintaining an acceptable voltage magnitude at the substation bus. The coordination controller is designed to substitute for a classical ULTC mechanism by utilizing active and reactive powers, tap position, and STATCOM output. A competitive ANN is used as a classifier for tap positions and trained by a proposed iterative condensed nearest neighbor (ICNN) rule.
Keywords :
control system synthesis; neurocontrollers; on load tap changers; reactive power; static VAr compensators; substations; voltage control; STATCOM; ULTC transformer coordination control; active power; artificial neural network; iterative condensed nearest neighbor rule; reactive power; substation bus; under load tap changing; voltage regulation; Artificial neural networks; Automatic voltage control; Capacitors; Flexible AC transmission systems; Nearest neighbor searches; Neural networks; Power electronics; Reactive power control; Substations; Voltage control; Artificial neural network (ANN); STATCOM; ULTC transformer; condensed nearest neighbor rule; coordination control; voltage regulation;
fLanguage :
English
Journal_Title :
Power Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
0885-8950
Type :
jour
DOI :
10.1109/TPWRS.2005.846205
Filename :
1425548
Link To Document :
بازگشت