基于節(jié)能降耗的遼寧能源發(fā)展戰(zhàn)略研究
發(fā)布時間：2018-12-27 13:18
【摘要】：能源是經濟和社會發(fā)展的重要物質基礎,生產和生活的方方面面都離不開能源。遼寧是能源消費大省,節(jié)能降耗任務十分艱巨。當前國外學者針對能源消費、能源強度等多個角度與經濟發(fā)展之間關系的研究頗為豐富,國內學者針對各省能源消費以及經濟發(fā)展水平之間存在的關系也進行了大量研究,但目前定量分析遼寧能源消費情況的不多,對未來進行預測的文獻更少。 論文首先對國內外大量相關文獻進行綜述,為本文的撰寫提供理論依據。其次對相關概念進行界定,并對遼寧能源消費的現狀進行分析,指出當前遼寧能源消費領域存在的諸多問題,因此實施能源發(fā)展戰(zhàn)略十分必要。再次綜合考慮人口、經濟發(fā)展、能源結構、產業(yè)結構和汽車擁有量等諸多因素,兼顧考慮數據的可獲得性,進行回歸分析,得出遼寧能源消費影響因素的定量分析結果�；貧w過程采取偏最小二乘方法,該方法在自變量存在嚴重多重共線性和樣本個數小于變量個數的條件下仍然適用,因此可更好的保證計算結果的準確性和可靠性。利用時間序列ARIMA和灰色預測組合預測模型對“十二五”期間遼寧能源消費總量進行預測,發(fā)現未來幾年遼寧省能源消費仍以較高的速度增長,并保持在很高的消費水平。ARIMA模型是預測精度較高的短期預測模型,灰色模型通過尋找等待預測系統(tǒng)的變化規(guī)律,對系統(tǒng)內部數據的未來變化進行預測,對隨時間變化遞增或遞減的序列預測效果較好。最后采用SWOT分析,對遼寧能源環(huán)境進行分析,制定出盡可能發(fā)揮優(yōu)勢、把握機遇、縮小劣勢和規(guī)避威脅的戰(zhàn)略。SWOT分析方法綜合考慮內外部環(huán)境,考慮問題比較全面,能夠客觀而準確的分析問題。
[Abstract]:Energy is an important material basis for economic and social development. Liaoning is a big energy consumption province, energy conservation and consumption reduction task is very arduous. At present, foreign scholars have done a lot of research on the relationship between energy consumption, energy intensity and economic development. Domestic scholars have also done a lot of research on the relationship between energy consumption and the level of economic development in various provinces. However, there is not much quantitative analysis of Liaoning energy consumption, and there are fewer literatures to predict the future. Firstly, the paper summarizes a large number of related literature at home and abroad to provide theoretical basis for the writing of this paper. Secondly, it defines the related concepts, analyzes the current situation of Liaoning energy consumption, and points out many problems in Liaoning energy consumption field, so it is necessary to implement the energy development strategy. Considering the factors such as population, economic development, energy structure, industrial structure and car ownership, and taking into account the availability of data, the quantitative analysis results of the factors affecting energy consumption in Liaoning are obtained. The partial least square method is adopted in the regression process. This method is still applicable under the condition that the independent variables have serious multiple collinearity and the number of samples is smaller than the number of variables, so the accuracy and reliability of the calculation results can be better guaranteed. The total energy consumption in Liaoning Province during the 12th Five-Year Plan period is predicted by using time series ARIMA and grey forecast combined forecasting model, and it is found that the energy consumption in Liaoning Province will still increase at a relatively high speed in the next few years. ARIMA model is a short-term prediction model with high prediction accuracy. Grey model predicts the future change of system data by looking for the change law of waiting prediction system. It is better to predict the series with increasing or decreasing with time. Finally, the SWOT analysis is used to analyze the energy environment in Liaoning Province, and a strategy is worked out to give full play to the advantages, seize the opportunities, reduce the disadvantages and avoid the threat. The SWOT analysis method considers the internal and external environment comprehensively, and considers the problems more comprehensively. Able to analyze problems objectively and accurately.
【學位授予單位】：大連交通大學
【學位級別】：碩士
【學位授予年份】：2013
【分類號】：F426.2
本文編號：2393129
[Abstract]:Energy is an important material basis for economic and social development. Liaoning is a big energy consumption province, energy conservation and consumption reduction task is very arduous. At present, foreign scholars have done a lot of research on the relationship between energy consumption, energy intensity and economic development. Domestic scholars have also done a lot of research on the relationship between energy consumption and the level of economic development in various provinces. However, there is not much quantitative analysis of Liaoning energy consumption, and there are fewer literatures to predict the future. Firstly, the paper summarizes a large number of related literature at home and abroad to provide theoretical basis for the writing of this paper. Secondly, it defines the related concepts, analyzes the current situation of Liaoning energy consumption, and points out many problems in Liaoning energy consumption field, so it is necessary to implement the energy development strategy. Considering the factors such as population, economic development, energy structure, industrial structure and car ownership, and taking into account the availability of data, the quantitative analysis results of the factors affecting energy consumption in Liaoning are obtained. The partial least square method is adopted in the regression process. This method is still applicable under the condition that the independent variables have serious multiple collinearity and the number of samples is smaller than the number of variables, so the accuracy and reliability of the calculation results can be better guaranteed. The total energy consumption in Liaoning Province during the 12th Five-Year Plan period is predicted by using time series ARIMA and grey forecast combined forecasting model, and it is found that the energy consumption in Liaoning Province will still increase at a relatively high speed in the next few years. ARIMA model is a short-term prediction model with high prediction accuracy. Grey model predicts the future change of system data by looking for the change law of waiting prediction system. It is better to predict the series with increasing or decreasing with time. Finally, the SWOT analysis is used to analyze the energy environment in Liaoning Province, and a strategy is worked out to give full play to the advantages, seize the opportunities, reduce the disadvantages and avoid the threat. The SWOT analysis method considers the internal and external environment comprehensively, and considers the problems more comprehensively. Able to analyze problems objectively and accurately.
【學位授予單位】：大連交通大學
【學位級別】：碩士
【學位授予年份】：2013
【分類號】：F426.2
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