Title :
RBF Neural Network Based on Genetic Algorithm Used in Line Loss Calculation for Distribution Network
Author :
Jiang, Huilan ; Yuan, Yunzhou ; Huang, Yi ; Li, Guixin
Author_Institution :
Tianjin Univ., Tianjin
Abstract :
In this paper, RBF neural network (RBFNN) based on genetic algorithm (GA) optimization is presented to deal with line losses calculation for power distribution networks. The centers and widths of hidden layer and the weights of the output layer are coded into one chromosome. It strengthens the cooperation between the hidden layer and the output layer, and avoids the risk of getting stuck into a local minimum. The simulation results indicate that the method presented has the advantages of a simple model, speedy learning and high precision.
Keywords :
distribution networks; genetic algorithms; power engineering computing; radial basis function networks; RBF neural network; chromosome; genetic algorithm; line loss calculation; power distribution networks; Artificial neural networks; Biological cells; Genetic algorithms; Load flow; Loss measurement; Neural networks; Neurons; Power system economics; Power system modeling; Power system simulation;
Conference_Titel :
Natural Computation, 2007. ICNC 2007. Third International Conference on
Conference_Location :
Haikou
Print_ISBN :
978-0-7695-2875-5
DOI :
10.1109/ICNC.2007.594
