Chaotic simulated annealing neural network with decaying chaotic noise and its application in economic load dispatch of power systems

Mao Ya-Lin Mao Ya-Lin,Zhou Ming Zhou Ming,Zhang Guo-Zhong Zhang Guo-Zhong,Zhu Bin Zhu Bin

doi:10.1109/iri.2004.1431516

Chaotic simulated annealing neural network with decaying chaotic noise and its application in economic load dispatch of power systems

Mao Ya-Lin Mao Ya-Lin, Zhou Ming Zhou Ming + Show 2 more

https://doi.org/10.1109/iri.2004.1431516

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Publication Date: Nov 8, 2004

Citations: 3

Affiliation: Wuhan University

#Load Dispatch Of Power Systems #Chaotic Neural Network + Show 8 more

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Abstract

Based on chaotic neural network (CNN), chaotic simulated annealing model with decaying chaotic noise (CSA-DCN) is presented. This model combines some advantages of Hopfield neural network (HNN) and simulated annealing (SA) algorithm, and decaying chaotic noise produced by iterated functions of logistic map is inducted into this model, which means it can be used to solve many multidimensioned, discrete, nonconvex, nonlinear constrained optimization problems, such as economic load dispatch (ELD) of power systems. Involved the transmission loss and valve point effect (VPE), the CSA-DCN model is applied to solve the ELD problem, the simulation results of three examples show that the CSA-DCN model for the ELD problem is versatile, robust and efficient.

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