DocumentCode :
2254889
Title :
CBR-based Load Estimation for Distribution Networks
Author :
Wu, Jianzhong ; Yu, Yixin
Author_Institution :
Sch. of Electr. Eng., Tianjin Univ.
fYear :
2006
fDate :
16-19 May 2006
Firstpage :
952
Lastpage :
955
Abstract :
Load estimation is very important for management and control of complex distribution networks. A novel method based on case-based-reasoning (CBR) is proposed for distribution network nodal load estimation. Principle of the method is analyzed, a hybrid learning algorithm is presented, and its application is discussed. The CBR-based load estimation method can build nodes and connections for a fuzzy neural network dynamically by a rapid and incremental learning procedure and can withstand the effect of bad data effectively through network self-organizing. The method is a key component of an integrated load and state estimation framework. The proposed method is tested on a 33-node system whose nodal load data come from a practical system, and test results show that it can provide high quality nodal load estimates
Keywords :
case-based reasoning; distribution networks; fuzzy neural nets; learning (artificial intelligence); power engineering computing; power system state estimation; CBR-based load estimation; case-based-reasoning; distribution network nodal load estimation; fuzzy neural network; hybrid learning algorithm; incremental learning procedure; network self-organizing; state estimation framework; Algorithm design and analysis; Extraterrestrial measurements; Fuzzy control; Fuzzy neural networks; Load modeling; Neodymium; Real time systems; Robust control; State estimation; System testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrotechnical Conference, 2006. MELECON 2006. IEEE Mediterranean
Conference_Location :
Malaga
Print_ISBN :
1-4244-0087-2
Type :
conf
DOI :
10.1109/MELCON.2006.1653256
Filename :
1653256
Link To Document :
بازگشت