DocumentCode :
160289
Title :
A modified artificial neural network based Distribution System reconfiguration for loss minimization
Author :
Kumar, K. Sathish ; Rajalakshmi, K. ; Karthikeyan, S. Prabhakar
Author_Institution :
VIT Univ., Vellore, India
fYear :
2014
fDate :
9-11 Jan. 2014
Firstpage :
1
Lastpage :
5
Abstract :
In this paper a new method for identifying best switching option in reconfiguration of Radial Distribution Systems (RDS) is presented. Feeder reconfiguration is defined as the technique to alter the structures in the distribution feeder by opening and closing the sectionalizing and tie switches. The reconfiguration includes selecting of set of sectional switches to be opened and tie switch to be closed such that the RDS has desired performance. Among several criteria considered in optimal system configuration, loss reduction criterion is very widely used. In this project a novel method is presented which utilizes feeder reconfiguration as a planning and real time control tool in order to restructure the primary feeders for the loss minimization. The mathematical formulation of the proposed method is given; the solution procedure is illustrated with an example. Here neural network approach for Optimal Reconfiguration of RDS is proposed.
Keywords :
neural nets; power distribution control; power distribution planning; power engineering computing; switching; artificial neural network; best switching option; distribution feeder; distribution system reconfiguration; loss minimization; planning tool; primary feeder; radial distribution systems; real time control tool; switch selection; Artificial neural networks; Equations; Load flow analysis; Loading; Switches; Training; Artificial Neural Network Approach (ANN); Feeder Reconfiguration; Loss Reduction; Radial Distribution Systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advances in Electrical Engineering (ICAEE), 2014 International Conference on
Conference_Location :
Vellore
Type :
conf
DOI :
10.1109/ICAEE.2014.6838513
Filename :
6838513
Link To Document :
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