本文選題：汽輪機組　切入點：敏度分析　出處：《華北電力大學(北京)》2016年碩士論文　論文類型：學位論文

【摘要】：復雜多變的邊界條件以及能效指標間的耦合問題給火電機組的節(jié)能優(yōu)化研究帶來了很大的挑戰(zhàn)。火電機組節(jié)能優(yōu)化的核心和難點在于火電機組能效指標基準狀態(tài)的確定。目前,火電機組關鍵能效指標的基準值確定往往僅僅采用機組設計值、變工況計算值或者熱力試驗值,每種基準值確定方法都有其局限性。隨著機組運行工況變化和設備性能狀態(tài)的改變,基準值己無法匹配機組的實際運行狀態(tài),使得運行指導受到很大限制,無法發(fā)現(xiàn)引起能效水平降低的真正原因�；谄啓C組海量歷史數(shù)據(jù)的數(shù)據(jù)挖掘方法能夠較好地匹配機組的實際狀態(tài),因此能夠很好地確定目標工況下機組實際可達的能效指標基準狀態(tài)。針對目前機組數(shù)據(jù)挖掘中面臨的多變復雜的邊界條件,多且耦合的能效指標以及指標差異的問題。本文通過基于模糊C均值聚類,灰色關聯(lián)約簡和主觀AHP層次分析法與客觀熵權(quán)法相結(jié)合的組合權(quán)重法的數(shù)據(jù)挖掘方式提取出目標工況下機組實際可達的能效指標基準狀態(tài)。但是基于數(shù)據(jù)挖掘得到的能效指標基準狀態(tài)受到運行邊界條件和實際設備狀態(tài)的影響,主要反映的是操作人員運行水平的高低,而沒有反映出目標工況下設備性能的基準狀態(tài)。因此,本文結(jié)合機組實際情況通過進一步構(gòu)建設備性能類指標的基準狀態(tài)模型,對挖掘得到的反映設備性能的能效指標進行修正,從而得到整個汽輪機組能效指標實際可達的基準狀態(tài),并且分析驗證了模型的準確性,從而為汽輪機組不同工況的能耗分析與節(jié)能診斷提供依據(jù)。最后,本文基于汽輪機組能效指標基準狀態(tài)的研究,對汽輪機系統(tǒng)能效優(yōu)化模塊展開了設計研究工作。對某600MW汽輪機組通過敏度分析找到影響該機組能耗的主要能效指標,基于能效指標的優(yōu)化知識庫,指導能效指標的優(yōu)化調(diào)整,最終達到提高機組能效水平的目的。
[Abstract]:The complex boundary conditions and the coupling problem between energy efficiency indexes bring great challenges to the energy conservation optimization of thermal power units. The core and difficulty of energy efficiency optimization of thermal power units lies in the determination of the benchmark state of energy efficiency index of thermal power units. The benchmark value of key energy efficiency index of thermal power unit is usually determined only by unit design value, variable working condition calculation value or thermal test value. With the change of unit operating condition and equipment performance state, the reference value can not match the actual operation state of the unit, so the operation guidance is greatly restricted. The real cause of the decrease in energy efficiency can not be found. The data mining method based on the massive historical data of steam turbine units can better match the actual status of the unit. Therefore, the benchmark state of the actual energy efficiency index of the unit can be determined very well under the target working condition. In view of the changeable and complex boundary conditions in the data mining of the unit at present, In this paper, based on fuzzy C-means clustering, the problem of multiple and coupled energy efficiency indexes and their differences is discussed. The data mining method of combined weight method, which combines grey relational reduction and subjective AHP analytic hierarchy process with objective entropy weight method, extracts the actual energy efficiency index datum state of the unit under the target working condition. However, based on the data mining, the results are obtained. The baseline state of the energy efficiency indicator to be reached is affected by the operating boundary conditions and the actual equipment state, It mainly reflects the operating level of the operator, but does not reflect the reference state of the equipment performance under the target operating condition. Therefore, this paper constructs the benchmark state model of the equipment performance class index by further constructing the reference state model according to the actual conditions of the unit. The energy efficiency index which reflects the performance of the equipment is modified, and the actual reference state of the energy efficiency index of the whole turbine unit is obtained, and the accuracy of the model is analyzed and verified. So as to provide the basis for energy consumption analysis and energy saving diagnosis of steam turbine unit under different working conditions. Finally, based on the research of energy efficiency index reference state of steam turbine unit, The energy efficiency optimization module of steam turbine system is designed and studied. The main energy efficiency indexes affecting the energy consumption of a 600MW steam turbine unit are found through sensitivity analysis, and the optimization knowledge base based on energy efficiency index is used to guide the optimization and adjustment of energy efficiency index. Finally, the purpose of improving the energy efficiency level of the unit is achieved.
【學位授予單位】：華北電力大學(北京)
【學位級別】：碩士
【學位授予年份】：2016
【分類號】：TM621;TK26

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