本文選題：電力消費(fèi)需求 + 經(jīng)濟(jì)增長因素��； 參考：《浙江大學(xué)》2014年碩士論文

【摘要】：電力在當(dāng)今社會發(fā)揮著越來越重要的作用。實(shí)施能源戰(zhàn)略,促進(jìn)能源發(fā)展方式的轉(zhuǎn)變,都應(yīng)堅(jiān)持以電力為中心。“經(jīng)濟(jì)發(fā)展,電力先行”,電力消費(fèi)與市場的關(guān)聯(lián)愈加緊密。開展基于市場的電力消費(fèi)需求研究,具有重要而深遠(yuǎn)的現(xiàn)實(shí)意義。 電力消費(fèi)的市場影響因素眾多,本文從宏觀經(jīng)濟(jì)發(fā)展、產(chǎn)業(yè)結(jié)構(gòu)調(diào)整、終端能源消費(fèi)結(jié)構(gòu)和大用戶直購電四個維度,結(jié)合浙江省電力消費(fèi)實(shí)際對各影響因素進(jìn)行系統(tǒng)分析。分析其與各宏觀經(jīng)濟(jì)指標(biāo)的相關(guān)性,探討其受產(chǎn)業(yè)結(jié)構(gòu)調(diào)整的影響,給出能源結(jié)構(gòu)的演變特征,分析了引入大用戶直購電帶來的影響。以此為基礎(chǔ)建立電力消費(fèi)需求的預(yù)測模型。 本文依據(jù)電力消費(fèi)的市場影響因素,從經(jīng)濟(jì)增長、產(chǎn)業(yè)結(jié)構(gòu)、終端能源結(jié)構(gòu)三個方面(大用戶直購電尚未大規(guī)模開展,暫不考慮)建立預(yù)測模型。本文研究表征經(jīng)濟(jì)增長的投資、消費(fèi)、出口的經(jīng)濟(jì)指標(biāo)的時(shí)間序列與電力消費(fèi)時(shí)間序列的關(guān)系,運(yùn)用向量自回歸(VAR)模型探究電力需求與經(jīng)濟(jì)三大增長因素是否具有長期均衡關(guān)系,進(jìn)而建立電力需求的預(yù)測模型�；诋a(chǎn)業(yè)結(jié)構(gòu)發(fā)展預(yù)測電力需求需要分別預(yù)測出各產(chǎn)業(yè)的用電量情況。本文采用灰色理論對產(chǎn)值單耗進(jìn)行預(yù)測,引出最常用的灰色預(yù)測模型GM(1,1)模型,以及GM(1,1)模型的精確形式DGM(1,1)模型,和單序列一階非線性動態(tài)模型灰色Verhulst模型,根據(jù)數(shù)列特點(diǎn)采用具體預(yù)測模型。基于終端能源結(jié)構(gòu)的電力消費(fèi)需求采用具有無后效性特點(diǎn)的馬爾可夫預(yù)測,對終端能源結(jié)構(gòu)演化進(jìn)程進(jìn)行建模。以誤差平方和達(dá)到最小的準(zhǔn)則,建立最優(yōu)化模型求得轉(zhuǎn)移概率矩陣,再求解某一狀態(tài)下的概率,得到預(yù)測年份的終端能源概率進(jìn)而求得電力消費(fèi)量。對于以上幾種方法,本文采用殘差均方根法求得其各自的權(quán)重,進(jìn)行組合預(yù)測。 本文以浙江數(shù)據(jù)為例,采用建立的預(yù)測模型,以浙江省1995-2012年電力消費(fèi)數(shù)據(jù)為算例,編寫預(yù)測程序,對浙江2013-2020年電力需求進(jìn)行預(yù)測,并進(jìn)行組合預(yù)測。 國外電力市場的經(jīng)驗(yàn)表明,開展大用戶直購電能夠激發(fā)電力市場的潛力,是電力工業(yè)市場化改革的突破口。本文對大用戶直購電模式的核心問題進(jìn)行探討,就大用戶直購電的交易模式、輸電模式、市場準(zhǔn)入原則、條件及機(jī)制、輸配電價(jià)等予以設(shè)計(jì)。比較各種方案,給出現(xiàn)行建議方案及發(fā)展方向。 本文為基于市場的電力消費(fèi)需求相關(guān)研究提供借鑒與參考。
[Abstract]:Electric power is playing a more and more important role in today's society. To implement the energy strategy and promote the transformation of energy development mode, we should stick to the power as the center. "Economic development, electricity first", electricity consumption and the market more closely linked. The research of electricity consumption demand based on market has important and profound practical significance. There are many influential factors in the market of electric power consumption. This paper makes a systematic analysis of the influencing factors from the four dimensions of macro-economic development, industrial structure adjustment, end-energy consumption structure and direct electricity purchase by large users, combined with the actual situation of electricity consumption in Zhejiang Province. This paper analyzes the correlation between the energy structure and the macro-economic indexes, discusses the influence of industrial structure adjustment, gives the evolution characteristics of energy structure, and analyzes the influence brought by the introduction of direct electricity purchase by large customers. Based on this, a forecasting model of electricity consumption demand is established. According to the market influence factors of electric power consumption, this paper sets up a prediction model from three aspects: economic growth, industrial structure and terminal energy structure (the direct purchase of electricity by large users has not been carried out on a large scale for the time being). This paper studies the relationship between the time series of economic indicators representing economic growth and the time series of electricity consumption. The vector autoregressive (VAR) model is used to study whether there is a long-term equilibrium relationship between electricity demand and the three major economic growth factors, and then the forecasting model of power demand is established. It is necessary to forecast the electricity consumption of each industry based on the development of industrial structure. In this paper, the grey theory is used to predict the unit consumption of output value, and the most commonly used grey prediction model GM (1K1) model, as well as the exact form of the GM (1K1) model, and the grey Verhulst model of the first order nonlinear dynamic model of single sequence are derived. According to the characteristics of the series, the specific prediction model is adopted. Based on the terminal energy structure, the demand for electricity consumption is modeled by Markov prediction, which has the characteristics of no aftereffect, and the evolution process of the terminal energy structure is modeled. Based on the criterion of minimum error squared sum, the optimal model is established to obtain the transition probability matrix, and then the probability of a certain state is solved, and the terminal energy probability of the predicted year is obtained, and the power consumption is obtained. For the above methods, the residual mean square method is used to calculate their respective weights, and the combined prediction is carried out. Taking Zhejiang data as an example and taking Zhejiang power consumption data from 1995 to 2012 as an example, this paper makes a prediction program to forecast Zhejiang's electricity demand in 2013-2020 and carries out combined forecasting. The experience of foreign power market shows that direct purchase of electricity by large customers can stimulate the potential of electricity market, and it is a breakthrough in the market-oriented reform of electric power industry. In this paper, the core problems of direct electricity purchase by large users are discussed, and the transaction mode, transmission mode, market access principle, conditions and mechanism, transmission and distribution price are designed. Compare various schemes, give the current proposal and development direction. This paper provides reference and reference for the research of electricity consumption demand based on market.
【學(xué)位授予單位】：浙江大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：F426.61

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 康重慶,夏清,張伯明;電力系統(tǒng)負(fù)荷預(yù)測研究綜述與發(fā)展方向的探討[J];電力系統(tǒng)自動化;2004年17期

2 王卿然;張粒子;謝國輝;;跨地區(qū)電力交易輸電服務(wù)價(jià)格機(jī)制[J];電力系統(tǒng)自動化;2010年13期

3 朱鳳娟;王主丁;陸儉;張巧霞;向婷婷;;考慮小區(qū)發(fā)展不均衡的空間負(fù)荷預(yù)測分類分區(qū)法[J];電力系統(tǒng)自動化;2012年12期

4 陳澤淮;張堯;武志剛;;RBF神經(jīng)網(wǎng)絡(luò)在中長期負(fù)荷預(yù)測中的應(yīng)用[J];電力系統(tǒng)及其自動化學(xué)報(bào);2006年01期

5 張伏生,劉芳,趙文彬,孫自安,蔣光英;灰色Verhulst模型在中長期負(fù)荷預(yù)測中的應(yīng)用[J];電網(wǎng)技術(shù);2003年05期

6 胡江溢;陳西穎;;對大用戶直購電交易的探討[J];電網(wǎng)技術(shù);2007年24期

7 毛李帆;江岳春;龍瑞華;李妮;黃慧;黃珊;;基于偏最小二乘回歸分析的中長期電力負(fù)荷預(yù)測[J];電網(wǎng)技術(shù);2008年19期

8 周德強(qiáng);;改進(jìn)的灰色Verhulst模型在中長期負(fù)荷預(yù)測中的應(yīng)用[J];電網(wǎng)技術(shù);2009年18期

9 龍瑞華;毛弋;毛李帆;孫東杰;張芳明;張婷;陳宇哲;;基于誘導(dǎo)有序加權(quán)平均算子和馬爾可夫鏈的中長期電力負(fù)荷組合預(yù)測模型[J];電網(wǎng)技術(shù);2010年03期

10 牛東曉;成功;張博;王海峰;;基于MPCA-RBFNN的神經(jīng)網(wǎng)絡(luò)在中長期電力負(fù)荷預(yù)測中的應(yīng)用[J];華北電力大學(xué)學(xué)報(bào);2007年03期

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