Feeder load balancing using neural network

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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. © Springer-Verlag Berlin Heidelberg 2006.

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Ukil, A., Siti, W., & Jordaan, J. (2006). Feeder load balancing using neural network. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3972 LNCS, pp. 1311–1316). Springer Verlag. https://doi.org/10.1007/11760023_190

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