An Algorithm for Unit Commitment Based on Hopfield Neural Network

2008 ◽  
Author(s):  
Weixin Gao ◽  
Nan Tang ◽  
Xiangyang Mu
Keyword(s):  
Neural Network ◽  
Unit Commitment ◽  
Hopfield Neural Network

Application of Hopfield neural network in unit commitment problem

2009 ◽  
Vol 29 (4) ◽  
pp. 1028-1031
Author(s):  
Wei-xin GAO ◽  
Xiang-yang MU ◽  
Nan TANG ◽  
Hong-liang YAN
Keyword(s):  
Neural Network ◽  
Unit Commitment ◽  
Hopfield Neural Network ◽  
Unit Commitment Problem ◽  
Commitment Problem

scholarly journals AUGMENTED LAGRANGE HOPFIELD NEURAL NETWORK BASED METHOD FOR UNIT COMMITMENT

2012 ◽  
Vol 15 (2) ◽  
pp. 39-49
Author(s):  
Khai Phuc Nguyen ◽  
Dieu Ngoc Vo ◽  
Tu Phan Vu
Keyword(s):  
Neural Network ◽  
Heuristic Search ◽  
Unit Commitment ◽  
Optimal Solution ◽  
Hopfield Neural Network ◽  
Computer Time ◽  
Test Results ◽  
Unit Commitment Problem ◽  
Priority List ◽  
Commitment Problem

This paper proposed an enhanced merit order (EMO) and augmented Lagrange Hopfield neural network (ALHN) for solving unit commitment problem. This problem is solved on 2 stages. At first, with the heuristic search EMO method we plan the unit scheduling. And then, we use ALHN, a continuous Hopfield neural network combines with augmented Lagrange relaxation, to solve the economic dispatch problem. The proposed method is tested on systems with 10 units, 17 units and up to 100 units. The obtained results is compared to conventional priority list (PL-ALHN) and other methods in literature. Test results show that the proposed method is totally more efficient than PLALHN and others for finding optimal solution of unit commitment problem. And the computer time of proposed method is vastly faster than other methods.

Sign in / Sign up

Export Citation Format

Share Document