OPTIMAL LOAD DISTRIBUTION IN POWER PLANT BASED ON GENETIC ALGORITHM

doi:10.19666/j.rlfd.2003.09.002

English

您当前的位置：

首页 >

文章列表页 >

OPTIMAL LOAD DISTRIBUTION IN POWER PLANT BASED ON GENETIC ALGORITHM

Thermal Power Generation Issue 9, Pages: 6-9(2003)

更新时间：2025-09-28

- OPTIMAL LOAD DISTRIBUTION IN POWER PLANT BASED ON GENETIC ALGORITHM
- 作者机构：
  
  1. 西安交通大学
  2. 红雁池第二发电有限责任公司,陕西,西安,710049
  3. ,新疆,乌鲁木齐
- 作者简介：
- 基金信息：
- DOI：10.19666/j.rlfd.2003.09.002
  CLC： TM621
- Published：2003
- 稿件说明：
移动端阅览
OPTIMAL LOAD DISTRIBUTION IN POWER PLANT BASED ON GENETIC ALGORITHM[J]. Thermal Power Generation, 2003, (9): 6-9.
DOI：

OPTIMAL LOAD DISTRIBUTION IN POWER PLANT BASED ON GENETIC ALGORITHM[J]. Thermal Power Generation, 2003, (9): 6-9. DOI： 10.19666/j.rlfd.2003.09.002.

摘要

简要介绍了遗传算法的基本原理

将其应用于发电厂解决了多台机组运行相互间负荷的最优分配问题。从仿真算例结果可见

采用的优化算法具有运算速度快、使用方便的特点

能够在线实现机组负荷的动态优化

改善机组的运行经济性

Abstract

The basic principle of genetic algorithm has briefly been described. Under application of the said algorithm in power plants

the problem of optimal load distribution among multiple units in operation has been solved. It can be found from results of simulated calculation as example

that the optimizing algorithm adopted features fast speed of computing operation and being easy to use. The online dynamic optimization of units’ load can be realized

improving economic aspects of units’ operation.

关键词

Keywords

references

Views

228

下载量

CSCD

Alert me when the article has been cited

提交

Publicity Resources

A thermal data rectification method based on genetic algorithm

Design optimization for distributed combined heat and power cogeneration systems:research progress

GA-SVM-based soft-sensor model for oxygen content in flue gas of utility boilers

Genetic algorithm based dynamic sliding mode water level control for steam generators in nuclear power stations

国产100MW机组综合节能改造

Related Author

ZHOU Weiqing

WANG Shun

LI Hui

DONG Xueyu

REN Hongbo

WU Qiong

LI Jianqiang

ZHAO Kai

Related Institution

Power Simulation and Control Center,Nanjing Institute of Technology

Huaneng Power International Inc.

College of Energy and Mechanical Engineering, Shanghai University of Electric Power

School of Energy Power and Mechanical Engineering, North China Electric Power University

Department of Automation, North China Electric Power University

AI问答

⁰