本文選題：可計算一般均衡(CGE)模型 + 電動汽車　； 參考：《華北電力大學》2017年碩士論文

【摘要】：隨著全球變暖,惡劣的環(huán)境等問題的日益加劇,節(jié)能減排逐漸演變?yōu)槿祟惍斍懊媾R的重大環(huán)境問題之一。作為當今世上最大的發(fā)展中國家,最大的排放國,中國面臨著越來越大的減排壓力。為了經(jīng)濟軟著陸、降低碳排放,中國不得不加快低碳經(jīng)濟的腳步,推廣電動車將是一個降低能耗和二氧化碳排放的重要手段。根據(jù)國務院印發(fā)的《節(jié)能與新能源汽車產(chǎn)業(yè)發(fā)展規(guī)劃(2012—2020年)》,到2020年,純電動汽車和插電式混合動力汽車生產(chǎn)能力達200萬輛、累計產(chǎn)銷量超過500萬輛。國際形勢、國內(nèi)政策都體現(xiàn)了本文比較現(xiàn)實的研究意義。本文構(gòu)建了一個遞歸的中國能源環(huán)境動態(tài)的可計算一般均衡(CGE)模型,用以分析推廣電動汽車以及相關(guān)的政策和技術(shù),如電廠的碳捕集與封存(CCS)技術(shù)政策的經(jīng)濟-能源-環(huán)境影響。本文創(chuàng)新地以調(diào)整外生變量等方法在CGE模型中模擬中國電動汽車的相關(guān)數(shù)量,并根據(jù)不同的政策背景與實施的可能性,建立了5個推廣電動汽車的模擬情景。以期為中國政策的制定提供理論支持。結(jié)果顯示:在基準水平下的推廣政策配合CCS技術(shù)可以有效降低碳排放和緩解經(jīng)濟損失。雖然推廣電動汽車會對經(jīng)濟造成一定的損失,但是碳排放峰值將在2030年前出現(xiàn),將迎合2014年的《中美氣候變化聯(lián)合聲明》中國碳減排目標。高水平的推廣政策比基準水平的推廣政策在降低二氧化碳排放方面表現(xiàn)更加出色,但是造成的經(jīng)濟損失也是難以彌補的。CCS技術(shù)在電動車推廣和全國碳交易市場啟動的大背景下,在保護能源生產(chǎn)部門這一方面扮演了重要的角色:降低了GDP的損失,降低了碳排放,但是對降低我國石油依賴性并沒有顯著的影響。作為一個降低碳交易成本的配套選項,在電動車政策推廣的過程中CCS對碳價有著強烈的影響,精煉石油行業(yè)的保護與轉(zhuǎn)型是值得考慮的一大問題。綜上,本文認為,在全國碳交易市場啟動的前提下,以基準水平配合熱電廠的CCS技術(shù)是一個既保護經(jīng)濟,又能有效節(jié)能減排的的政策組合。
[Abstract]:With the global warming and the worsening of environmental problems, energy saving and emission reduction has gradually become one of the major environmental problems facing mankind. As the world's largest developing country and the largest emitter, China is under increasing pressure to reduce emissions. In order to achieve a soft landing and reduce carbon emissions, China will have to accelerate the pace of a low-carbon economy, and the promotion of electric vehicles will be an important means of reducing energy consumption and carbon dioxide emissions. According to the Energy Saving and New Energy Automobile Industry Development Plan (2012-2020) issued by the State Council, by 2020, the production capacity of pure electric vehicles and plug-in hybrid electric vehicles will reach 2 million and the cumulative production and sales volume will exceed 5 million. The international situation and domestic policies reflect the practical significance of this paper. In this paper, a recursive computable general equilibrium (CGE) model of energy environment dynamics in China is constructed to analyze the promotion of electric vehicles and related policies and technologies. For example, power plant carbon capture and sequestration (CCS) technology policy economic-energy-environmental impact. This paper innovatively simulates the number of electric vehicles in China by adjusting exogenous variables in the CGE model. According to the different policy background and the possibility of implementation, five simulation scenarios of promoting electric vehicles are established. In order to provide theoretical support for the formulation of Chinese policy. The results show that the policies combined with CCS technology can effectively reduce carbon emissions and mitigate economic losses. Although the introduction of electric vehicles will cost the economy, the peak carbon emissions will occur by 2030, catering to the 2014 Sino-U.S. Joint statement on Climate change, China's carbon reduction target. The high level of promotion policy is better than the benchmark level in reducing carbon dioxide emissions, but the economic loss caused by it is also difficult to make up. CCS technology has been launched in the context of electric vehicle promotion and the national carbon trading market. It plays an important role in protecting the energy production sector: it reduces the loss of GDP and carbon emissions, but it has no significant effect on reducing China's oil dependence. As an option to reduce the cost of carbon trading CCS has a strong influence on carbon price in the process of electric vehicle policy promotion. The protection and transformation of refining oil industry is a big problem to be considered. On the premise of starting the national carbon trading market, the CCS technology based on the standard level and thermal power plant is a policy combination that can protect economy and save energy effectively.
【學位授予單位】：華北電力大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：X24;F426.2

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