返回
Generation Scheduling problem by Intelligent Genetic Algorithm
DOI:10.1016/j.compeleceng.2012.03.013.png)
摘要
En 中文
This paper presents a Genetic Algorithm (GA) solution to solve the Generation Scheduling (GS) problem with intelligent coding scheme. The intelligent coding scheme effectively handles minimum up/down time constraints of GS problem. GA with intelligent coding is called as Intelligent Genetic Algorithm (IGA). Penalty parameter-less constraint handling technique is used for satisfying power balance constraint. Performance of the IGA is tested on a 10-unit 24-h and 26-unit 24-h unit commitment test systems. The result obtained using IGA is compared with the results reported using Lagrangian Relaxation (LR), Enhanced Lagrangian Relaxation (ELR), LRGA, GA and Evolutionary Programming methods. Simulation results show the effects of intelligent coding scheme in obtaining feasible and minimum cost solution. (C) 2012 Elsevier Ltd. All rights reserved.
Keyword:
UNIT COMMITMENT PROBLEM
期刊
C
IF:
4.9
论文数:
6.7K
被引数:
1.3W
机构
引用论文
A hybrid neural network and simulated annealing approach to the unit commitment problem单元组合问题的混合神经网络和模拟退火方法

