Application of Genetic Algorithms and Hopfield Neural Networks to Combined Economic and Emission Dispatch (CEED)

被引：0
|
作者：
Benyahia, Mohamed [1 ]
Benasla, Lahouaria [1 ]
Rahl, Mostefa [1 ]
机构：
[1] Univ Sci & Technol Mohamed Boudiaf Oran, Dept Elect Engn, Fac Elect Engn, Elect Network Modelizat & Optimizat, Oran, Algeria
来源：
PRZEGLAD ELEKTROTECHNICZNY | 2009年 / 85卷 / 10期
关键词：
Hopfield Neural Network; Genetic Algorithm; optimization problem; transmission line loss;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
This paper presents the Genetic Algorithms (GA) and Hopfield Neural Network (HNN) to solve the Combined Economic and Emission Dispatch (CEED) problem. The equality constraints of power balance and the inequality generator capacity constraints are considered. The CEED problem is a bi-objective non linear optimization problem since it is obtained by considering both the economy and emission objectives. This bi-objectives problem is converted into a single objective function using a price penalty factor approach. In this paper AG and HNN are tested on six generators system and the results are compared. The solutions are quite encouraging and useful in the CEED.
引用
收藏
页码：111 / 115
页数：5
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