首页    期刊浏览 2024年10月05日 星期六
登录注册

文章基本信息

  • 标题:COMPARATIVE STUDY OF ECONOMIC load dispatch (ELD) USING MODIFIED HOPFIELD NEURAL NETWORK
  • 本地全文:下载
  • 作者: Er. Mukesh Garg Er. Manjeet Singh Er. Vineet Girdher
  • 期刊名称:International Journal of Computing and Business Research
  • 电子版ISSN:2229-6166
  • 出版年度:2012
  • 出版社:International Journal of Computing and Business Research
  • 摘要:The economic load dispatch (ELD) is one of the most important optimization problems from the view point of power system to derive optimal economy. Classically, it is to Identify the optimal combination of generation level of all generating units which minimizes the total fuel cost while satisfying the load. This classical ELD formulation has been solved by various methods like Lagrange method, Newton’s method etc.This paper presents the Hopfield Neural Network (HNN) to solve the Economic Environmental Dispatch (EED) problem. The equality constraints of power balance and the inequality generator capacity constraints are considered. The EED problem is a biobjective non linear optimization problem since it is obtained by considering both the economy and emission objectives. This biobjectives problem is converted into a single objective function using a price penalty factor approach. In this paper HNN are tested on six generators system and the results are compared. The solutions are quite encouraging and useful in the EED
  • 关键词:Hopfield Neural Network; optimization problem; transmission line loss; emission and economic;dispatch
国家哲学社会科学文献中心版权所有