本文關(guān)鍵詞：陜西省終端能源消費中電力消費發(fā)展預(yù)測研究　出處：《華北電力大學》2015年碩士論文　論文類型：學位論文

  更多相關(guān)文章： 終端消費 電力 影響因素 組合預(yù)測

【摘要】：終端能源消費是提升能源效率的重要一環(huán)。陜西省是我國能源資源富集區(qū)之一,但其電力消費水平還未達到全國平均水平。因此,有必要對陜西省終端能源消費中的電力消費情況進行深入分析研究,為能源結(jié)構(gòu)的優(yōu)化和可持續(xù)發(fā)展提供理論依據(jù)。本文首先對電力消費的影響因素進行了探討,將其分為生產(chǎn)用電和生活用電兩個方面進行分析。利用LMDI法將生產(chǎn)用電分解為經(jīng)濟效應(yīng)、結(jié)構(gòu)效應(yīng)和強度效應(yīng),結(jié)果表明,經(jīng)濟效應(yīng)是電力終端消費量增長的關(guān)鍵因素,強度效應(yīng)是抑制其增長的重要因素,結(jié)構(gòu)效應(yīng)的增長作用不明顯。利用灰色關(guān)聯(lián)度模型對生活用電的影響因素與生活用電量進行關(guān)聯(lián)度分析,得到與生活用電量的灰色關(guān)聯(lián)度由大到小的影響因素依次為：農(nóng)村居民家庭人均純收入、城鎮(zhèn)居民人均可支配收入、城鎮(zhèn)人口比例、平均每戶人數(shù)和人口。利用MIV-GRNN模型對所選取的所有因素進行敏感度分析,結(jié)果表明,對電力消費量和電力消費占比影響較大的因素有人口、平均每戶人數(shù)、第二產(chǎn)業(yè)GDP占比、第三產(chǎn)業(yè)GDP占比。根據(jù)數(shù)據(jù)歷史趨勢和影響因素對未來五年的電力消費量和電力消費占比進行預(yù)測。在傳統(tǒng)的變權(quán)重組合模型加入新的限制條件,并結(jié)合多項式回歸模型、GM(1,1)模型、多元線性回歸模型和GRNN模型,形成了改進變權(quán)重組合預(yù)測模型。經(jīng)擬合驗證,改進變權(quán)重組合模型減小了誤差,具有參考意義�；谠撃Ｐ偷念A(yù)測結(jié)果表明,雖然未來五年電力消費量和電力消費占比都呈現(xiàn)上升趨勢,但仍未達到滿意水平為提高電力在終端能源消費中的比重,對電力消費增長潛力從交通電氣化、工農(nóng)業(yè)生產(chǎn)和電器普及推廣三個角度進行分析,對已實行的電能替代措施和面臨的挑戰(zhàn)進行分析介紹,并為開拓陜西省電力消費市場提出相關(guān)建議。
[Abstract]:End energy consumption is an important part of improving energy efficiency. Shaanxi Province is one of the rich areas of energy resources in China, but its power consumption level has not reached the national average level. It is necessary to analyze and study the electric power consumption in the terminal energy consumption of Shaanxi Province. For the optimization of energy structure and sustainable development to provide a theoretical basis. Firstly, this paper discusses the influence factors of electricity consumption. It can be divided into two aspects: production power and daily electricity. The LMDI method is used to decompose the production power into economic effect, structural effect and intensity effect. The results show that the power consumption can be divided into three parts: economic effect, structural effect and intensity effect. Economic effect is the key factor of power terminal consumption growth, and intensity effect is an important factor to restrain its growth. The growth effect of structural effect is not obvious. The grey correlation model is used to analyze the influence factors of household electricity consumption and the living electricity consumption. The grey correlation degree between the power consumption and the rural households per capita net income, urban residents per capita disposable income, the proportion of urban population is the order of influencing factors from large to small. 3. The main factors are: rural households per capita net income, urban residents per capita disposable income, urban population ratio. The MIV-GRNN model is used to analyze the sensitivity of all the selected factors. The results show that the population has a great influence on the power consumption and the proportion of electricity consumption. Average household size, secondary industry GDP ratio. According to the historical trend and influencing factors of the tertiary industry, the paper predicts the power consumption and the power consumption ratio in the next five years. The new restriction condition is added to the traditional variable weight combination model. Combined with polynomial regression model, multivariate linear regression model and GRNN model, an improved variable weight combination prediction model was formed. The improved variable-weight combination model reduces the error and has reference significance. The prediction results based on the model show that although the power consumption and power consumption ratio will increase in the next five years. However, in order to improve the proportion of electricity in the end energy consumption, the potential of power consumption growth is analyzed from three aspects: traffic electrification, industrial and agricultural production and popularization of electrical appliances. This paper analyzes and introduces the electric power substitution measures and the challenges faced by them, and puts forward some suggestions for developing the electric power consumption market in Shaanxi Province.
【學位授予單位】：華北電力大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：F426.61

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