今日自动化2024,Issue(5) :144-146.

基于改进贪心算法的主动配煤掺烧动态优化方法

Dynamic Optimization Method for Active Coal Blending and Co Firing Based on Improved Greedy Algorithm

罗胜 陈辉
今日自动化2024,Issue(5) :144-146.

基于改进贪心算法的主动配煤掺烧动态优化方法

Dynamic Optimization Method for Active Coal Blending and Co Firing Based on Improved Greedy Algorithm

罗胜 1陈辉1
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作者信息

  • 1. 浙江浙能兰溪发电有限责任公司,浙江金华 321100
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摘要

传统的配煤掺烧优化方法缺乏动态调整能力,导致锅炉在实际燃烧过程中的效果不佳,因此,提出一种基于改进贪心算法的主动配煤掺烧动态优化方法,该方法旨在预测燃烧效率与排放环保性.为实现锅炉热损失与烟尘排放量的最小化,构建一个多目标的主动配煤掺烧动态优化模型,通过运用改进后的贪心算法来求解这个模型,从而得到最佳的优化方案.试验结果表明,经过设计方法优化后,锅炉的烟尘排放量较优化前降低了69.82%,表明该方法能够有效找到最佳的配煤掺烧比,从而显著提高锅炉的燃烧效率和环保性能.

Abstract

The traditional optimization method of coal blending and CO combustion is lack of dynamic adjustment ability,which leads to the poor effect of boiler in the actual combustion process.Therefore,a dynamic optimization method of active coal blending and CO combustion based on improved greedy algorithm is proposed.This method aims to predict the combustion efficiency and emission environmental protection.These two key indicators are the important combustion characteristics in the process of boiler active coal blending.In order to minimize the heat loss and smoke emission of the boiler,a multi-objective dynamic optimization model of active coal blending and CO combustion is constructed.The model is solved by using the improved greedy algorithm,so as to obtain the best optimization scheme.The experimental results show that after the optimization of the design method,the soot emission of the boiler is reduced by 69.82%compared with that before the optimization,which shows that the method can effectively find the best coal blending ratio,so as to significantly improve the combustion efficiency and environmental protection performance of the boiler.

关键词

改进贪心算法/主动配煤掺烧/掺烧优化/动态优化方法

Key words

improving greedy algorithms/active coal blending and co firing/optimization of co firing/dynamic optimization methods

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出版年

2024
今日自动化

今日自动化

ISSN:
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