Economic Power Dispatch with Environmental Constraints Using a Novel Hybrid Evolutionary Programming

被引:0
作者
Chen, Gonggui [1 ]
Li, Yinhong [1 ]
Duan, Xianzhong [1 ]
机构
[1] Huazhong Univ Sci & Technol, Coll Elect & Elect Engn, Wuhan 430074, Peoples R China
来源
ADVANCES IN NEURAL NETWORKS - ISNN 2009, PT 2, PROCEEDINGS | 2009年 / 5552卷
关键词
Environmental/economic dispatch; Modified average price penalty factor; Hybrid evolutionary programming; PARTICLE SWARM OPTIMIZATION; EMISSION DISPATCH; FLOW;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Environmental/economic dispatch (EED) is a bi-objective optimization problem with conflicting optimization objectives, the minimization of fuel cost and the minimization of emission. In this paper, a modified average price penalty factor (MAPPF) is introduced to convert the bi-objective EED problem into a single-objective optimization problem. A new hybrid evolutionary programming (HEP) methodology is proposed to solve the EED. In the methodology, a simple evolutionary programming (EP) is used as a basic level search, which can give a good direction to the optimal global region. Then, a local search procedure is adopted as a fine tuning to determine the optimal Solution. The methodology is applied to a 15-unit system and the numerical results indicate its effectiveness and practicality.
引用
收藏
页码:537 / 546
页数:10
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