【摘要】：在煤炭資源供應(yīng)日益緊張、煤炭?jī)r(jià)格上漲的嚴(yán)峻形勢(shì)下,加強(qiáng)挖掘燃煤火力發(fā)電機(jī)組的能耗特性,是實(shí)現(xiàn)機(jī)組節(jié)能運(yùn)行的重要基礎(chǔ),也是實(shí)現(xiàn)電力系統(tǒng)節(jié)能工作的一個(gè)重要方向,更是保障我國(guó)經(jīng)濟(jì)可持續(xù)發(fā)展的一個(gè)關(guān)鍵問(wèn)題。因此,做好火電機(jī)組節(jié)能工作的基礎(chǔ)性研究具有重要意義。針對(duì)此課題,論文主要工作如下：首先,利用因子分析法降維的功能挖掘出影響機(jī)組能耗的重要指標(biāo)。在火力發(fā)電機(jī)組的歷史運(yùn)行數(shù)據(jù)的基礎(chǔ)上,選取一組盡可能反映機(jī)組運(yùn)行狀態(tài)且與機(jī)組發(fā)電煤耗密切相關(guān)的參數(shù)。建立了機(jī)組能耗指標(biāo)的公因子分析模型,并對(duì)所提取的公因子數(shù)目進(jìn)行校驗(yàn),同時(shí)考慮因子分析法應(yīng)用中經(jīng)常被忽略的特殊因子,通過(guò)特殊因子方差估計(jì)值大小去間接地判斷所提取的機(jī)組能耗公因子分析模型是否出現(xiàn)Heywood現(xiàn)象,進(jìn)一步對(duì)所擬合出的能耗公因子模型的優(yōu)劣性進(jìn)行定量判斷。為了更有清晰地描述原始變量與少數(shù)公因子之間的關(guān)系,通過(guò)回歸法計(jì)算因子得分,實(shí)現(xiàn)用少數(shù)公因子描述原始數(shù)據(jù)信息結(jié)構(gòu)的目的,達(dá)到了降維的目的。其次,在火電機(jī)組目標(biāo)值挖掘過(guò)程中,利用數(shù)據(jù)挖掘技術(shù)中的加權(quán)模糊C均值聚類方法對(duì)機(jī)組能耗的重要運(yùn)行可控參數(shù)進(jìn)行目標(biāo)值的求解�？紤]到機(jī)組不同能耗指標(biāo)的樣本點(diǎn)對(duì)分類的影響不盡相同,因而在機(jī)組參數(shù)挖掘的過(guò)程中不同屬性的指標(biāo)對(duì)聚類的貢獻(xiàn)程度會(huì)有所差異,論文提出首先對(duì)機(jī)組的不同能耗指標(biāo)賦予不同的權(quán)重,再進(jìn)行目標(biāo)值的挖掘,所挖掘出來(lái)的目標(biāo)值更具合理性。最后,為了提高火電機(jī)組能耗評(píng)估的客觀性和科學(xué)性,論文提出利用層次分析法與熵權(quán)法相結(jié)合來(lái)確定機(jī)組能耗評(píng)估中各項(xiàng)指標(biāo)的權(quán)重值,克服了單一賦權(quán)法的缺點(diǎn),使權(quán)重的確定更為合理。在此基礎(chǔ)上,利用兩級(jí)模糊綜合評(píng)估方法對(duì)機(jī)組的能耗水平進(jìn)行評(píng)估,同時(shí)對(duì)比主觀賦權(quán)(層次分析法)得到權(quán)重的兩級(jí)模糊綜合評(píng)估結(jié)果。實(shí)例分析表明：該評(píng)估方法得出的評(píng)估結(jié)果更加完善和準(zhǔn)確,更符合火電機(jī)組能耗水平的實(shí)際情況。論文通過(guò)火電機(jī)組的實(shí)時(shí)工況進(jìn)行分析,對(duì)機(jī)組的能耗特征進(jìn)行提取,得到的分析結(jié)果與理論知識(shí)是相符合的,驗(yàn)證了所提模型和問(wèn)題分析思路的有效性和實(shí)用性,為實(shí)現(xiàn)火電機(jī)組的節(jié)能優(yōu)化運(yùn)行和調(diào)整奠定了一定的基礎(chǔ)。
[Abstract]:Under the severe situation that the supply of coal resources is increasingly tight and the coal price is rising, it is an important foundation for realizing the energy-saving operation of the units to strengthen the excavation of the energy consumption characteristics of coal-fired generating units. It is also an important direction to realize the energy saving of power system and a key problem to ensure the sustainable development of our country's economy. Therefore, it is of great significance to do a good job of energy-saving work of thermal power units. The main work of this paper is as follows: firstly, the important indexes which affect the unit energy consumption are excavated by the function of reducing dimension by factor analysis method. On the basis of the historical operation data of thermal power generating units, a group of parameters which reflect the operating state of the units and which are closely related to the coal consumption of generating units are selected. The common factor analysis model of unit energy consumption index is established, and the number of common factors extracted is verified, and the special factors which are often neglected in the application of factor analysis are considered. The Heywood phenomenon is indirectly judged by the estimated value of the variance of special factors, and the advantages and disadvantages of the fitted common factor model of energy consumption are further quantitatively judged. In order to more clearly describe the relationship between the original variables and a few common factors, the purpose of describing the information structure of the raw data by using a few common factors is realized by calculating the factor scores by the regression method, and the purpose of reducing the dimension is achieved. Secondly, in the process of target value mining of thermal power units, the weighted fuzzy C-means clustering method in data mining technology is used to solve the target values of important operating controllable parameters of unit energy consumption. Considering that the sample points of different unit energy consumption indexes have different effects on classification, the contribution of different attribute indexes to clustering will be different in the process of unit parameter mining. The paper puts forward that the different energy consumption indexes of the unit are given different weights at first, and then the target value is excavated, and the target value is more reasonable. Finally, in order to improve the objectivity and scientific nature of energy consumption assessment of thermal power units, the paper proposes to use AHP and entropy weight method to determine the weight value of each index in unit energy consumption evaluation, which overcomes the shortcoming of single weighting method. Make the determination of weight more reasonable. On this basis, the two-stage fuzzy comprehensive evaluation method is used to evaluate the energy consumption level of the unit, and the weighted two-stage fuzzy comprehensive evaluation results are obtained by comparing the subjective weight (AHP). The analysis of examples shows that the evaluation results obtained by this method are more perfect and accurate, and more in line with the actual situation of energy consumption level of thermal power units. Through the analysis of the real time working conditions of thermal power units, the energy consumption characteristics of the units are extracted, and the results are in accordance with the theoretical knowledge. The validity and practicability of the proposed model and problem analysis ideas are verified. It lays a foundation for energy-saving optimization and adjustment of thermal power units.
【學(xué)位授予單位】：長(zhǎng)沙理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TM621;TP311.13

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本文編號(hào)：2230488