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Paper Information

Journal:   AMIRKABIR   FALL 2007-WINTER 2008 , Volume 18 , Number 67-A (TOPICS IN: GROUPS OF ENGINEERING, ELECTRONIC, BIOMEDICAL, COMPUTER); Page(s) 25 To 33.
 
Paper: 

LOAD ESTIMATION OF DISTRIBUTION NETWORKS USING INVERSE PCA

 
 
Author(s):  YAGHOUTI A.A., PARSA MOGHADAM M.*, HAGHIFAM M.R., JOUHARI MAJD V.
 
* DEPARTMENT OF ENGINEERING, TARBIAT MODARES UNIVERSITY, TEHRAN, IRAN
 
Abstract: 

In this paper, an efficient method is proposed for load estimation of distribution networks with limited real-time data based on principal component analysis. The principal components of load variables are first detected off-line from historical data. Next, the interrelations between the load variables are developed using a new concept that we call Inverse PCA (IPCA) method; this leads to some proper models devised so that the distribution network becomes observable. Finally, through incorporation of a certain finite set of real time data measurements, the loads of all network nodes in real-time are estimated with a desired degree of accuracy via the IPCA method. A case study on a real network is considered in the paper to highlight better the merit of the proposed method. The experimental results easily show that the proposed method outperforms the previously cited techniques.

 
Keyword(s): DATA MINING, PRINCIPAL COMPONENT ANALYSIS, LOAD ESTIMATION, STATE ESTIMATION, DISTRIBUTION NETWORK
 
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