Economic Load Dispatch of Power Systems Based on Hysteretic Noisy Chaotic Neural Network

被引：0

作者：

Sun, Ming ^{[1
]}

Cui, Shaojie ^{[1
]}

Xu, Yaoqun ^{[2
]}

机构：

[1] Qiqihar Univ, Coll Comp & Control Engn, Qiqihar, Heilongjiang Pr, Peoples R China

[2] Harbin Univ Commerce, Inst Syst Engn, Harbin, Heilongjiang Pr, Peoples R China

来源：

PROCEEDINGS OF 2014 IEEE WORKSHOP ON ADVANCED RESEARCH AND TECHNOLOGY IN INDUSTRY APPLICATIONS (WARTIA) | 2014年

基金：

中国国家自然科学基金;

关键词：

economic load dispatch; power systems; hysteretic; noisy chaotic neural network; nonlinear optimization;

D O I：

暂无

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Hysteretic noisy chaotic neural network (HNCNN) has been proven to be a powerful tool in solving combinatorial optimization problems, which can increase the effective convergence toward optimal or near-optimal solutions by using both stochastic chaotic simulated annealing (SCSA) and hysteretic dynamics. Considering the excellent optimization performance of HNCNN, we apply HNCNN to better resolve economic load dispatch (ELD) of power system in this paper. In addition, the system loss and valve point effect are also involved in the simulation. Simulation results and analyses compared with other approaches are presented to illustrate efficiency of the HNCNN.

引用

页码：820 / 823

页数：4

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