發(fā)布時(shí)間：2018-01-02 12:21

  本文關(guān)鍵詞：輸氣管道調(diào)峰方案模擬與優(yōu)化研究　出處：《西南石油大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 調(diào)峰 負(fù)荷預(yù)測(cè) 方案評(píng)價(jià) SPS 儲(chǔ)氣庫

【摘要】：天然氣作為一種清潔能源,消費(fèi)需求量逐年增長。雖然我國天然氣供應(yīng)能力在不斷提升,但由于消費(fèi)需求增長快速,所以不可避免地會(huì)存在供氣與用氣不均衡問題。如何保證下游用戶平穩(wěn)用氣,是天然氣管道運(yùn)營工作中的重點(diǎn),本文的研究就是在這樣的背景下提出的。本文通過使用MATLAB編程,對(duì)單一的灰色預(yù)測(cè)模型和人工神經(jīng)網(wǎng)絡(luò)預(yù)測(cè)模型進(jìn)行預(yù)測(cè)分析,結(jié)合兩種方法的優(yōu)點(diǎn),提出了一種基于灰色模型和人工神經(jīng)網(wǎng)絡(luò)的天然氣負(fù)荷組合預(yù)測(cè)模型,其實(shí)質(zhì)是一種殘差修正型組合預(yù)測(cè)模型。經(jīng)檢驗(yàn),組合模型負(fù)荷預(yù)測(cè)量與實(shí)際值最貼近。同時(shí),收集了CD管道工藝系統(tǒng)基礎(chǔ)數(shù)據(jù),使用瞬態(tài)水力模擬軟件SPS構(gòu)建了 CD管道仿真模型,并對(duì)模型進(jìn)行了有效性檢驗(yàn)和壓力校核。在燃?xì)庳?fù)荷預(yù)測(cè)結(jié)果的基礎(chǔ)上,本文分析了位于CD管道儲(chǔ)氣庫下游I市的用氣規(guī)律,得到I市峰月峰日的缺口氣量,以此為基礎(chǔ)數(shù)據(jù)對(duì)輸氣管道調(diào)峰方案進(jìn)行了研究�？紤]儲(chǔ)氣庫是否投產(chǎn),由CD管道承擔(dān)I市城市燃?xì)庥脩舴逶路迦者B續(xù)72小時(shí)的調(diào)峰任務(wù),對(duì)全線壓縮機(jī)開啟方案和儲(chǔ)氣庫的采氣方案進(jìn)行比選。對(duì)于儲(chǔ)氣庫投運(yùn)的調(diào)峰方案,提出了 "高峰采氣" "平穩(wěn)采氣"兩種采氣原則,根據(jù)這兩種原則分別制定了三種輸量的儲(chǔ)氣庫的采氣方案,每種輸量又制定了兩種不同的開機(jī)方案,然后利用SPS軟件對(duì)每種工況進(jìn)行模擬并進(jìn)行了方案初步分析,得到了預(yù)選調(diào)峰方案。接著采用了灰色關(guān)聯(lián)分析法,理想解法和秩和比法三種方法對(duì)調(diào)峰方案分別評(píng)價(jià),采用組合評(píng)價(jià)法"平均值法"將多種單一評(píng)價(jià)方法得到的評(píng)價(jià)結(jié)論進(jìn)行組合。為了檢驗(yàn)將單一的評(píng)價(jià)模型進(jìn)行集合是否具有合理性,使用了 spearman等級(jí)關(guān)聯(lián)系數(shù)法在模型集成前后進(jìn)行了檢驗(yàn),基于組合模型評(píng)價(jià)出的排名前五的調(diào)峰方案反映了組合評(píng)價(jià)的可靠性。最后,在方案評(píng)價(jià)分析的基礎(chǔ)上,提出了調(diào)峰方案的優(yōu)化建議。
[Abstract]:Natural gas as a clean energy, consumer demand increased year by year. Although the supply of natural gas in China is on the rise, but due to the rapid growth in consumer demand, so inevitably there will be gas supply and gas imbalance. How to ensure the smooth downstream users of gas, natural gas is the key work in the pipeline operation. The research is proposed under this background. In this paper, through the use of MATLAB programming, analyze the single grey prediction model and artificial neural network prediction model, combining the advantages of the two methods, put forward a combination prediction model of gas load and grey model based on artificial neural network, its essence is a kind of the residual modified combination forecasting model. After test, the load forecasting model combined with the actual measurement value closest to. At the same time, to collect the basic data processing system using CD pipeline, hydraulic transient The simulation software SPS to construct the CD pipeline simulation model, and the model of the effectiveness of the inspection and checking the pressure. The predicted results based on gas load, this paper analyzes the gas storage pipe located downstream of CD I city gas law, gas gap get I City peak month peak day, as the research on the transmission gas pipeline peak basic data storage. Consider whether the production, by CD I of city gas pipeline to assume the user peak monthly peak day 72 consecutive hours of peak shaving tasks, gas recovery program on the full range of compressor open scheme and gas storage are compared. For peak gas storage operation, put forward the "peak of gas production" stable gas production "two gas production principle, according to the two principles were developed in three kinds of transportation amount of gas storage gas recovery program, each output has developed two different boot scheme, and then for each condition by using SPS software A preliminary analysis of the scheme and simulation, pre peak shaving scheme was obtained. Then by using the gray correlation analysis method, TOPSIS method and RSR method three peak were evaluated, using the combination evaluation method of "average method" will be a variety of single evaluation methods evaluation conclusion. In order to test the combination a single evaluation model set is reasonable, using the Spearman rank correlation coefficient method was tested in the model integration and combination evaluation model of the top five peaking scheme reflects the reliability based on combination evaluation. Finally, based on the analysis in project evaluation, put forward suggestions to optimize the peak.

【學(xué)位授予單位】：西南石油大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TE832

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本文編號(hào)：1369195