Feeder load balancing using neural network

Authors:
Abhisek Ukil;Willy Siti;Jaco Jordaan
Affiliations:
Tshwane University of Technology, Pretoria, South Africa;Tshwane University of Technology, Pretoria, South Africa;Tshwane University of Technology, Pretoria, South Africa
Venue:
ISNN'06 Proceedings of the Third international conference on Advnaces in Neural Networks - Volume Part II
Year:
2006

Citing 1
Cited 4

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Distribution Feeder Load Balancing Using Support Vector Machines

IDEAL '08 Proceedings of the 9th International Conference on Intelligent Data Engineering and Automated Learning
Phase load balancing in the secondary distribution network using a fuzzy logic and a combinatorial optimization based on the Newton Raphson

IDEAL'09 Proceedings of the 10th international conference on Intelligent data engineering and automated learning

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Abstract

The distribution system problems, such as planning, loss minimization, and energy restoration, usually involve the phase balancing or network reconfiguration procedures. The determination of an optimal phase balance is, in general, a combinatorial optimization problem. This paper proposes optimal reconfiguration of the phase balancing using the neural network, to switch on and off the different switches, allowing the three phases supply by the transformer to the end-users to be balanced. This paper presents the application examples of the proposed method using the real and simulated test data.