本文選題：脫硝　切入點(diǎn)：選擇性催化還原　出處：《浙江大學(xué)》2015年碩士論文　論文類型：學(xué)位論文

【摘要】：隨著國(guó)內(nèi)環(huán)保形勢(shì)的日益嚴(yán)峻,我國(guó)政府越來越重視火電廠污染物的排放問題。氮氧化物是火力電廠排放的一項(xiàng)主要污染物,所以環(huán)保部門對(duì)氮氧化物的排放制定了非常嚴(yán)格的標(biāo)準(zhǔn)。作為一種脫硝效率高、氨逃逸率低的煙氣脫硝方法,選擇性催化還原(SCR)技術(shù)成為了許多電廠的選擇。目前大多數(shù)電廠均在SCR控制系統(tǒng)中采用PID控制器,但由于SCR被控對(duì)象有非線性、大延遲的特點(diǎn),所以在現(xiàn)場(chǎng)運(yùn)行中,采用PID控制方式效果比較差。為了解決這些問題,改善控制品質(zhì),本文采用模型預(yù)測(cè)控制的方法對(duì)SCR控制系統(tǒng)進(jìn)行優(yōu)化,首先利用經(jīng)過預(yù)處理的現(xiàn)場(chǎng)數(shù)據(jù)通過模型辨識(shí)獲得過程模型,并對(duì)現(xiàn)有控制系統(tǒng)的控制特點(diǎn)和控制效果進(jìn)行整合分析,進(jìn)而運(yùn)用MATLAB進(jìn)行預(yù)測(cè)控制器設(shè)計(jì)并與現(xiàn)有控制方式進(jìn)行仿真比較,最后就氨逃逸軟測(cè)量和多變量模型預(yù)測(cè)控制在SCR控制系統(tǒng)中的應(yīng)用進(jìn)行仿真分析。仿真結(jié)果表明,模型預(yù)測(cè)控制可以很好的改善SCR控制系統(tǒng)的動(dòng)態(tài)特性及抗干擾能力,提高SCR出口氮氧化物濃度控制品質(zhì),降低噴氨量。本文中的氨逃逸軟測(cè)量的實(shí)現(xiàn)和SCR多變量模型預(yù)測(cè)控制的應(yīng)用不但可以提高SCR控制系統(tǒng)的控制品質(zhì),也為實(shí)際的SCR控制優(yōu)化提供了更加豐富的控制思路。
[Abstract]:With the increasingly serious situation of domestic environmental protection, the government of our country pays more and more attention to the emission of pollutants from thermal power plants. Nitrogen oxide is one of the main pollutants emitted from thermal power plants. So the environmental protection department has set very strict standards for NOx emissions. As a method of flue gas denitrification with high denitrification efficiency and low ammonia escape rate, Selective catalytic reduction (SCR) technology has become the choice of many power plants. At present, most power plants use PID controllers in SCR control systems, but because of the nonlinear and large delay characteristics of SCR controlled objects, they are in operation on the spot. In order to solve these problems and improve the control quality, the model predictive control method is used to optimize the SCR control system. Firstly, the process model is obtained by model identification using preprocessed field data, and the control characteristics and control effects of the existing control system are integrated and analyzed. Then the predictive controller is designed by using MATLAB and compared with the existing control methods. Finally, the application of ammonia escape soft sensing and multivariable model predictive control in SCR control system is simulated and analyzed. The simulation results show that, The model predictive control can improve the dynamic characteristics and anti-interference ability of SCR control system, and improve the quality of nitrogen oxide concentration control at the outlet of SCR. In this paper, the realization of soft sensing of ammonia escape and the application of SCR multivariable model predictive control can not only improve the control quality of SCR control system, but also provide more abundant control ideas for practical SCR control optimization.
【學(xué)位授予單位】：浙江大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：X773

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 蔡小峰;李曉蕓;;SNCR-SCR煙氣脫硝技術(shù)及其應(yīng)用[J];電力環(huán)境保護(hù);2008年03期

2 王杭州;;SCR對(duì)脫硝效率及SO_2轉(zhuǎn)化影響分析[J];電力科學(xué)與工程;2008年05期

3 朱衛(wèi)東;;火電廠煙氣脫硫脫硝監(jiān)測(cè)分析及氨逃逸量檢測(cè)[J];分析儀器;2010年01期

4 馬孝純;段躍非;朱亞波;;鍋爐脫硝SCR法的控制策略研究[J];電站系統(tǒng)工程;2013年01期

5 黃敏;吳曉烽;王楚玉;;淺析低氮燃燒技術(shù)在燃煤鍋爐中的應(yīng)用[J];能源與環(huán)境;2014年02期

6 肖曉存,王雪納;大氣中氮化物的污染與防治[J];煤炭技術(shù);2005年08期

7 周洪煜;趙乾;張振華;汪正海;;煙氣脫硝噴氨量SA-RBF神經(jīng)網(wǎng)絡(luò)最優(yōu)控制[J];控制工程;2012年06期

8 鄭東升;;兩種燃煤電廠逃逸氨的在線測(cè)量方法[J];科技廣場(chǎng);2013年08期

9 路璐;鐘智坤;吳華成;康璽;;脫硝氨逃逸采樣和測(cè)試方法的探討與優(yōu)化[J];華北電力技術(shù);2014年09期

10 劉劍;;氨逃逸在線檢測(cè)技術(shù)在火電廠SCR脫硝的應(yīng)用[J];科技與企業(yè);2014年12期

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