發(fā)布時(shí)間：2018-02-26 22:21

  本文關(guān)鍵詞： 二氧化碳 BP神經(jīng)網(wǎng)絡(luò) 計(jì)算方法 燃煤電廠(chǎng)　出處：《北京交通大學(xué)》2014年碩士論文　論文類(lèi)型：學(xué)位論文

【摘要】：氣候變化已成為各國(guó)進(jìn)行政治、經(jīng)濟(jì)和文化博弈的重要議題。因溫室效應(yīng)引起的環(huán)境問(wèn)題逐漸引起了人們的關(guān)注。為全面控制二氧化碳等溫室氣體的排放,以緩解氣候變暖給人類(lèi)經(jīng)濟(jì)和社會(huì)帶來(lái)的不利影響,國(guó)際各國(guó)開(kāi)始紛紛采取行動(dòng)——約束排放和減少排放,共同為應(yīng)對(duì)氣候變化做出努力。 控制減排的首要環(huán)節(jié)是了解當(dāng)下二氧化碳排放情況。電力行業(yè)是二氧化碳主要排放行業(yè)之一,國(guó)際上雖然已經(jīng)有大量關(guān)于燃煤電廠(chǎng)二氧化碳排放量計(jì)算的方法研究,但大多是依據(jù)各自國(guó)家的煤炭統(tǒng)計(jì)數(shù)據(jù)、電力設(shè)備運(yùn)行狀況等設(shè)計(jì)的。我國(guó)煤炭分布不均,質(zhì)量參差不齊,其質(zhì)量對(duì)于發(fā)電設(shè)備影響極大。而且,電力相關(guān)統(tǒng)計(jì)資料并不完善,電力運(yùn)行工況與國(guó)外相比存在較大差異,若直接套用國(guó)際現(xiàn)有方法,必然會(huì)與真實(shí)值之間存在很大誤差。由于國(guó)外的方法學(xué)理念較為完善,因此借鑒國(guó)外方法建立符合中國(guó)國(guó)情的燃煤電廠(chǎng)二氧化碳排放計(jì)算方法是一種省時(shí)省力又較準(zhǔn)確的計(jì)算方法。 本文深入探討了我國(guó)煤炭質(zhì)量情況及其對(duì)發(fā)電性能的影響。首先,我國(guó)煤炭分布情況及煤炭質(zhì)量特征顯示我國(guó)煤炭資源分布不均,地區(qū)間煤炭質(zhì)量差異較大,且煤炭指標(biāo)如灰分、硫分、揮發(fā)分等指標(biāo)數(shù)據(jù)與國(guó)外指標(biāo)存在顯著差異。而且,煤炭資源分布與消費(fèi)分布極不協(xié)調(diào),江蘇、浙江、山東、廣東等需求量較高的地區(qū)煤炭資源卻較為貧瘠,致使電煤供應(yīng)成為制約電煤質(zhì)量的一大因素；這些地區(qū)實(shí)際用煤質(zhì)量波動(dòng)較大,多不符合設(shè)計(jì)煤質(zhì)要求。本文選擇10家典型電廠(chǎng)作為主要研究對(duì)象,分別從煤炭發(fā)熱量、灰分、硫分、水分等煤質(zhì)指標(biāo)入手,分析其對(duì)發(fā)電設(shè)備的影響,結(jié)果顯示《IPCC指南》中的缺省系數(shù)無(wú)法直接應(yīng)用于我國(guó)電廠(chǎng)二氧化碳排放計(jì)算中 為了更準(zhǔn)確的建立我國(guó)燃煤電廠(chǎng)二氧化碳排放量的計(jì)算方法,本文結(jié)合電廠(chǎng)設(shè)備運(yùn)行理論,通過(guò)工業(yè)分析數(shù)據(jù)(全水分Mar、收到基灰分Aar、收到基揮發(fā)分Var、固定碳FCar四個(gè)數(shù)據(jù))預(yù)測(cè)收到基含碳量Car,繼而通過(guò)鍋爐燃燒理論,得出燃煤發(fā)電過(guò)程和脫硫過(guò)程的計(jì)算公式。 在工業(yè)分析數(shù)據(jù)預(yù)測(cè)收到基含碳量Car時(shí),采用BP神經(jīng)網(wǎng)絡(luò)的非線(xiàn)性映射特征,利用Matlab建立可通過(guò)工業(yè)分析數(shù)據(jù)(全水分Mar、收到基灰分Aar、收到基揮發(fā)分Var、固定碳FCar)預(yù)測(cè)Car的神經(jīng)網(wǎng)絡(luò)模型。通過(guò)網(wǎng)絡(luò)學(xué)習(xí)與優(yōu)化,最終使得學(xué)習(xí)后的數(shù)據(jù)預(yù)測(cè)值的相對(duì)誤差絕對(duì)值為0.602%,新數(shù)據(jù)預(yù)測(cè)結(jié)果的相對(duì)誤差絕對(duì)值平均可降低至2.827%。 為了驗(yàn)證上述計(jì)算方法的準(zhǔn)確性,以江蘇某發(fā)電廠(chǎng)為例,利用BP神經(jīng)網(wǎng)絡(luò)模型預(yù)測(cè),收到基平均值Car的相對(duì)誤差可降至0.24%,通過(guò)計(jì)算,該燃煤電廠(chǎng)固定源二氧化碳排放量為4.923×106t/n。利用《2006IPCC指南》中提供的缺省因子計(jì)算所得二氧化碳排放量為5.244×106t/n,高于電廠(chǎng)實(shí)際二氧化碳排放量6.5個(gè)百分點(diǎn)。
[Abstract]:Climate change has become an important issue in the political, economic and cultural game between countries. The environmental problems caused by Greenhouse Effect have gradually attracted people's attention. In order to comprehensively control greenhouse gas emissions such as carbon dioxide, In order to mitigate the adverse effects of global warming on human economy and society, international countries have begun to take actions to curb emissions and reduce emissions, and make joint efforts to deal with climate change. The first step in controlling emission reduction is to understand the current situation of carbon dioxide emissions. The power industry is one of the major carbon dioxide emission industries. Although there has been a lot of international research on the calculation methods of carbon dioxide emissions from coal-fired power plants, However, most of them are designed on the basis of the coal statistics of their respective countries and the operation status of power equipment. The distribution of coal in China is uneven, the quality of coal is uneven, and the quality of coal has a great impact on the power generation equipment. Moreover, the statistical data related to electricity are not perfect. There is a great difference between the operating conditions of electric power and foreign countries. If the existing international methods are applied directly, there is bound to be a great error between the actual value and the actual value. Therefore, it is a time-saving and labor-saving and accurate calculation method to establish the calculation method of carbon dioxide emissions of coal-fired power plants in accordance with China's national conditions by using foreign methods for reference. In this paper, the coal quality in China and its influence on power generation performance are discussed. Firstly, the coal distribution and coal quality characteristics in China show that the distribution of coal resources in China is uneven, and the coal quality varies greatly among regions. And the coal index such as ash, sulfur, volatile matter and so on index data have the remarkable difference with the foreign index, moreover, the coal resources distribution and the consumption distribution are extremely inharmonious, Jiangsu, Zhejiang, Shandong, The coal resources in high demand areas such as Guangdong are relatively poor, resulting in the supply of thermal coal becoming a major factor restricting the quality of thermal coal, and the actual quality of coal used in these areas fluctuates greatly. In this paper, 10 typical power plants are selected as the main research objects, starting with coal calorific value, ash content, sulphur content, moisture content and so on, the influence of coal quality on power generation equipment is analyzed. The results show that the default coefficient in IPCC Guide can not be directly applied to the calculation of carbon dioxide emissions from power plants in China. In order to establish a more accurate calculation method of carbon dioxide emissions from coal-fired power plants in China, this paper combines the operation theory of power plant equipment, Based on the data of industrial analysis (all moisture, received base ash, base ash, base volatile, fixed carbon FCar), the basic carbon content Carr is predicted, and the calculation formula of coal-fired power generation process and desulfurization process is obtained through boiler combustion theory. When the base carbon content (Car) is predicted by the industrial analysis data, the nonlinear mapping feature of BP neural network is used. A neural network model for predicting Car by industrial analysis data (total moisture Marr, received base ash Aarus, received base volatile matter Vara, fixed carbon FCars) was established by using Matlab. Finally, the absolute value of the relative error of the predicted data after learning is 0.602, and the absolute value of the relative error of the new data can be reduced to 2.827 on average. In order to verify the accuracy of the above calculation methods, taking a power plant in Jiangsu province as an example, the relative error of the base average Car can be reduced to 0.24 by using BP neural network model. The fixed source carbon dioxide emission of the coal-fired power plant is 4.923 脳 10 ~ (6) t / n. using the default factors provided in the 2006 IPCC guidelines, the calculated carbon dioxide emissions are 5.244 脳 10 ~ (6) t / n, which is 6.5 percentage points higher than the actual carbon dioxide emissions of the power plant.
【學(xué)位授予單位】：北京交通大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類(lèi)號(hào)】：X773

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