基于多目标遗传算法的电力锅炉燃烧效率优化
Optimization of Combustion Efficiency in Power Boilers Based on Multi Objective Genetic Algorithm
孙博1
作者信息
- 1. 福建大唐国际宁德发电有限责任公司,福建福安 355000
- 折叠
摘要
针对电力锅炉燃烧效率优化的传统定向局域约束方法稳定性不足问题,提出基于多目标遗传算法的优化方法.该方法明确优化目标,构建多阶约束机制,并通过多周期核验修正模型.测试显示,在不同负荷(20%～100%Pe)下,燃烧效率优化比均超6.5,有效提升了锅炉燃烧效率优化的稳定性和性能.
Abstract
A multi-objective genetic algorithm based optimization method is proposed to address the problem of insufficient stability in traditional directional local constraint methods for optimizing combustion efficiency of electric boilers.This method specifies the optimization objective,constructs a multi-level constraint mechanism,and corrects the model through multi period verification.Tests have shown that under different loads(20%～100%Pe),the combustion efficiency optimization ratio exceeds 6.5,effectively improving the stability and performance of boiler combustion efficiency optimization.
关键词
多目标测算/遗传算法/电力锅炉燃烧/锅炉燃烧/燃烧速度/效率优化Key words
multi-objective measurement/genetic algorithm/electric boiler combustion/boiler combustion/combustion rate/efficiency optimization引用本文复制引用
出版年
2024
NETL
NSTL
万方数据