【摘要】：汽輪機(jī)抽汽回?zé)嵯到y(tǒng)節(jié)能優(yōu)化的核心和難點在于抽汽回?zé)嵯到y(tǒng)能效指標(biāo)基準(zhǔn)狀態(tài)的確定。復(fù)雜多變的邊界條件以及能效指標(biāo)間的耦合問題給汽輪機(jī)抽汽回?zé)嵯到y(tǒng)的節(jié)能優(yōu)化研究帶來了很大的挑戰(zhàn)。目前,汽輪機(jī)抽汽回?zé)嵯到y(tǒng)關(guān)鍵能效指標(biāo)的基準(zhǔn)值確定往往僅僅采用設(shè)計值、變工況計算值或者熱力試驗值,每種基準(zhǔn)值確定方法都有其局限性。隨著機(jī)組運行工況變化和設(shè)備性能狀態(tài)的改變,基準(zhǔn)值已無法匹配抽汽回?zé)嵯到y(tǒng)的實際運行狀態(tài),使得運行指導(dǎo)受到很大限制,無法發(fā)現(xiàn)引起能效水平降低的真正原因�；谄啓C(jī)抽汽回?zé)嵯到y(tǒng)海量歷史數(shù)據(jù)的數(shù)據(jù)挖掘方法能夠較好地匹配機(jī)組的實際運行狀態(tài),因此能夠很好地確定目標(biāo)工況下抽汽回?zé)嵯到y(tǒng)實際可達(dá)的能效指標(biāo)基準(zhǔn)狀態(tài)。針對目前抽汽回?zé)嵯到y(tǒng)數(shù)據(jù)挖掘中面臨的多變復(fù)雜的邊界條件,多且耦合的能效指標(biāo)以及指標(biāo)差異的問題。本文通過基于k-means聚類的數(shù)據(jù)挖掘方式提取出目標(biāo)工況下抽汽回?zé)嵯到y(tǒng)實際可達(dá)的能效指標(biāo)基準(zhǔn)狀態(tài)。但是基于數(shù)據(jù)挖掘得到的能效指標(biāo)基準(zhǔn)狀態(tài)受到運行邊界條件和實際設(shè)備狀態(tài)的影響,主要反映的是操作人員運行水平的高低,而沒有反映出目標(biāo)工況下設(shè)備性能的基準(zhǔn)狀態(tài)。因此,本文結(jié)合抽汽回?zé)嵯到y(tǒng)實際情況通過進(jìn)一步構(gòu)建設(shè)備性能類指標(biāo)的基準(zhǔn)狀態(tài)模型,對挖掘得到的反映設(shè)備性能的能效指標(biāo)進(jìn)行修正,從而得到整個汽輪機(jī)抽汽回?zé)嵯到y(tǒng)能效指標(biāo)實際可達(dá)的基準(zhǔn)狀態(tài),完成了關(guān)鍵能效指標(biāo)的耗差因子分析,同時采用基于機(jī)理與Ebislon仿真建模的方法完成了端差及給水溫度的基準(zhǔn)值及耗差因子的驗證,從而為汽輪機(jī)抽汽回?zé)嵯到y(tǒng)不同工況的能耗分析與能效診斷提供依據(jù)。最后,本文基于抽汽回?zé)嵯到y(tǒng)能效指標(biāo)基準(zhǔn)狀態(tài)的研究,對抽汽回?zé)嵯到y(tǒng)能效分析、評價與診斷系統(tǒng)展開了設(shè)計研究工作。對某1000MW汽輪機(jī)回?zé)嵯到y(tǒng)組通過耗差因子分析找到影響該抽汽回?zé)嵯到y(tǒng)能耗的主要能效指標(biāo),基于能效指標(biāo)的優(yōu)化知識庫,指導(dǎo)能效指標(biāo)的優(yōu)化調(diào)整,最終達(dá)到提高抽汽回?zé)嵯到y(tǒng)能效水平的目的。
[Abstract]:The core and difficulty of energy saving optimization of steam turbine extraction recuperation system lies in the determination of the benchmark state of energy efficiency index of extraction steam recovery system. The complex boundary conditions and the coupling problem between energy efficiency indexes have brought great challenges to the optimization of energy conservation of steam turbine extraction heat recovery system. At present, the reference value of the key energy efficiency index of steam turbine extraction recuperation system is usually determined only by the design value, the calculation value under off-condition or the thermal test value, and each method has its limitations. With the change of unit operating condition and equipment performance state, the reference value can not match the actual operation state of the extraction steam recovery system, so the operation guidance is greatly restricted, and the real cause of the reduction of energy efficiency level can not be found. The data mining method based on the massive historical data of steam turbine extraction recuperation system can well match the actual operating state of the unit, so it can determine the actual energy efficiency index reference state of the extraction regenerative system under the target working condition. In order to solve the problem of variable and complex boundary conditions, multiple coupled energy efficiency indexes and different indexes in data mining of extraction steam recuperation system. In this paper, the data mining method based on k-means clustering is used to extract the actual energy efficiency standard state of the extraction regenerative system under the target working condition. But the datum state of energy efficiency index based on data mining is affected by the operation boundary condition and the actual equipment state, which mainly reflects the operating level of the operator, but does not reflect the standard state of the equipment performance under the target working condition. Therefore, according to the actual situation of the extraction heat recovery system, this paper modifies the energy efficiency index which can reflect the equipment performance by further constructing the benchmark state model of the equipment performance index. Thus, the reference state of the energy efficiency index of the whole steam turbine recovery system is obtained, and the consumption difference factor analysis of the key energy efficiency index is completed. At the same time, based on mechanism and Ebislon simulation modeling method, the standard value and consumption factor of end difference and feed water temperature are verified, which provides the basis for energy consumption analysis and energy efficiency diagnosis of steam turbine recovery system under different working conditions. Finally, based on the research of the energy efficiency benchmark state of the extraction steam recovery system, the energy efficiency analysis, evaluation and diagnosis system of the extraction steam recovery system are designed and studied. The main energy efficiency indexes affecting the energy consumption of the recovery system of a 1000MW steam turbine are found through the analysis of the consumption difference factor. The optimization knowledge base based on the energy efficiency index is used to guide the optimization and adjustment of the energy efficiency index. Finally, the purpose of improving the energy efficiency of the extraction steam recuperator system is achieved.
【學(xué)位授予單位】：華北電力大學(xué)(北京)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TM621.3

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 王寧玲;楊勇平;楊志平;;多變邊界條件下火電機(jī)組能耗基準(zhǔn)狀態(tài)診斷[J];中國電機(jī)工程學(xué)報;2013年26期

2 楊勇平;楊志平;徐鋼;王寧玲;;中國火力發(fā)電能耗狀況及展望[J];中國電機(jī)工程學(xué)報;2013年23期

3 陸松;;熱力學(xué)分析在鍋爐系統(tǒng)中的應(yīng)用[J];中小企業(yè)管理與科技(上旬刊);2013年02期

4 楊志平;楊勇平;王寧玲;;1000MW汽輪機(jī)缸效率能耗敏度分析[J];中國電機(jī)工程學(xué)報;2012年26期

5 李慧君;高麗莎;;火力發(fā)電廠加熱器端差應(yīng)達(dá)值的確定[J];汽輪機(jī)技術(shù);2012年02期

6 于淑梅;劉佳琪;常澍平;郭江龍;;回?zé)峒訜崞髯児r端差基準(zhǔn)值研究[J];發(fā)電設(shè)備;2010年03期

7 李娜;黃孝彬;田志強(qiáng);隋麗穎;;生產(chǎn)過程數(shù)據(jù)穩(wěn)定性判斷的一種方法[J];華電技術(shù);2010年01期

8 牛成林;劉吉臻;馬永光;李建強(qiáng);;基于增量數(shù)據(jù)挖掘的氧量最優(yōu)值確定[J];中國電機(jī)工程學(xué)報;2009年35期

9 周小力;楊慧慈;唐佳明;;模糊綜合評價法在煙氣脫硫技術(shù)選型中的應(yīng)用[J];計算機(jī)與應(yīng)用化學(xué);2008年03期

10 余愚;孫海山;蔣永華;;液壓系統(tǒng)齒輪泵故障樹分析[J];機(jī)床與液壓;2007年09期

相關(guān)會議論文 前1條

1 馮春暉;陳彥橋;劉金琨;;數(shù)據(jù)挖掘技術(shù)在火電機(jī)組運行參數(shù)優(yōu)化中的應(yīng)用[A];中國自動化學(xué)會控制理論專業(yè)委員會B卷[C];2011年

相關(guān)博士學(xué)位論文 前5條

1 冉鵬;基于動態(tài)數(shù)據(jù)挖掘的電站熱力系統(tǒng)運行優(yōu)化方法研究[D];華北電力大學(xué);2012年

2 王寧玲;基于數(shù)據(jù)挖掘的大型燃煤發(fā)電機(jī)組節(jié)能診斷優(yōu)化理論與方法研究[D];華北電力大學(xué)（北京）;2011年

3 牛成林;增量數(shù)據(jù)挖掘及其在電站運行優(yōu)化中的理論研究及應(yīng)用[D];華北電力大學(xué)（北京）;2010年

4 王惠杰;基于混合模型的機(jī)組狀態(tài)重構(gòu)及運行優(yōu)化研究[D];華北電力大學(xué)（河北）;2009年

5 李建強(qiáng);基于數(shù)據(jù)挖掘的電站運行優(yōu)化理論研究與應(yīng)用[D];華北電力大學(xué)（河北）;2006年

相關(guān)碩士學(xué)位論文 前5條

1 王曉璐;火電機(jī)組能效評價體系探究[D];華北電力大學(xué);2012年

2 嚴(yán)亙暉;火電廠熱工過程的預(yù)測控制方法研究[D];浙江大學(xué);2011年

3 李宗山;機(jī)組經(jīng)濟(jì)運行模式數(shù)據(jù)挖掘系統(tǒng)的研究與開發(fā)[D];華北電力大學(xué)（北京）;2011年

4 鄭西西;基于關(guān)聯(lián)規(guī)則的火電廠優(yōu)化目標(biāo)值確定的研究[D];華北電力大學(xué);2011年

5 呂冰;企業(yè)能源審計與可再生能源利用[D];天津大學(xué);2008年

，

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