Artificial neural networks and clustering techniques applied in the reconfiguration of distribution systems
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Data
2006-07-01
Autores
Salazar, H.
Gallego, R.
Romero, R.
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Editor
Institute of Electrical and Electronics Engineers (IEEE)
Resumo
One objective of the feeder reconfiguration problem in distribution systems is to minimize the power losses for a specific load. For this problem, mathematical modeling is a nonlinear mixed integer problem that is generally hard to solve. This paper proposes an algorithm based on artificial neural network theory. In this context, clustering techniques to determine the best training set for a single neural network with generalization ability are also presented. The proposed methodology was employed for solving two electrical systems and presented good results. Moreover, the methodology can be employed for large-scale systems in real-time environment.
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Palavras-chave
artificial neural networks (ANNs), clustering techniques, feeder reconfiguration, optimization techniques
Como citar
IEEE Transactions on Power Delivery. Piscataway: IEEE-Inst Electrical Electronics Engineers Inc., v. 21, n. 3, p. 1735-1742, 2006.