Title :
Application Of artificial immune system for detecting overloaded lines and voltage collapse prone buses in distribution network
Author :
J. V. Milanovic;Jingwei Lu
Author_Institution :
School of Electrical and Electronic Engineering, The University of Manchester, PO Box 88, Manchester, M60 1QD, UK
Abstract :
Biological immune systems are highly parallel, distributed, and adaptive systems, which use learning, memory, and associative retrieval to solve recognition and classification tasks. The Artificial Immune System (AIS) are capable of constructing and maintaining a dynamical and structural identity, capable of learning to identify previously unseen invaders and remembering what it has learnt. As a part of pioneering research in application of AIS to electrical power distribution systems, an AIS based software has been developed for identification of voltage collapse and line overload prone areas in distribution network. The applicability of AIS for this particular task is demonstrated on a 295-bus generic distribution system.
Keywords :
"Artificial immune systems","Voltage","Immune system","Maintenance","Power distribution","Fault diagnosis","Power system reliability","Adaptive systems","Application software","Data mining"
Conference_Titel :
PowerTech, 2009 IEEE Bucharest
Print_ISBN :
978-1-4244-2234-0
DOI :
10.1109/PTC.2009.5282036