CSO Technique for Solving the Economic Dispatch Problem Considering the Environmental Constraints

被引：13

作者：

Mohapatra, Prabhujit ^{[1
]}

Das, Kedar Nath ^{[1
]}

Roy, Santanu ^{[1
]}

Kumar, Ram ^{[2
]}

Kumar, Ajai ^{[3
]}

机构：

[1] NIT Silchar, Dept Math, Silchar, Assam, India

[2] Katihar Engn Coll, Dept EEE, Katihar, India

[3] Gautam Buddha Univ, Sch ICT, Gautam Budh Nagar, Uttar Pradesh, India

来源：

ASIAN JOURNAL OF WATER ENVIRONMENT AND POLLUTION | 2019年 / 16卷 / 02期

关键词：

Load dispatch problem; competitive swarm optimization; computational intelligence; PARTICLE SWARM OPTIMIZATION; DIFFERENTIAL EVOLUTION; GENETIC ALGORITHM;

D O I：

10.3233/AJW190018

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

In this paper, the competitive swarm optimization (CSO) algorithm is applied for handling the economical load dispatch problem. The CSO algorithm is fundamentally encouraged by the particle swarm optimization (PSO) algoritlun, but it does not memorize the personal best and global best to update the swarms. Rather in CSO algorithm, a pairwise competitive scenario was presented, where the loser particle is updated from the winner particle and the winner particles are directly accepted to the next population. The algorithm has been performed to find the generations of different units in a plant to reduce the entire fuel price and to maintain the total demand as well as the losses. The experimental study and investigations have revealed better performance for the CSO algorithm than the PSO and numerous state-of-art meta-heuristic algorithms in solving the economical power dispatch problem.

引用

页码：43 / 50

页数：8

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