A review of China's energy consumption structure and outlook based on a long-range energy alternatives modeling tool

China＇s energy consumption experienced rapid growth over the past three decades, raising great concerns for the future adjustment of China＇s energy consumption structure. This paper first presents the historical evidence on China＇s energy consumption by the fuel types and sectors. Then, by establishing a bottom-up accounting framework and using long-range energy alternatives plan- ning energy modeling tool, the future of China＇s energy consumption structure under three scenarios is forecast. According to the estimates, China＇s total energy con- sumption will increase from 3014 million tonnes oil equivalent （Mtoe） in 2015 to 4470 Mtoe in 2040 under the current policies scenario, 4040 Mtoe in 2040 under the moderate policies scenario and 3320 Mtoe in 2040 under the strong policies scenario, respectively, lower than those of the IEA＇s estimations. In addition, the clean fuels （gas, nuclear and renewables） could be an effective alternative to the conventional fossil fuels （coal and oil） and offer much more potential. Furthermore, the industry sector has much strong reduction potentials than the other sectors. Finally, this paper suggests that the Chinese government should incorporate consideration of adjustment of the energy consumption structure into existing energy policies and measures in the future.

A process-level hierarchical structural decomposition analysis (SDA) of energy consumption in an integrated steel plant

A hierarchical structural decomposition analysis(SDA) model has been developed based on process-level input-output(I-O) tables to analyze the drivers of energy consumption changes in an integrated steel plant during 2011-2013. By combining the principle of hierarchical decomposition into D&L method, a hierarchical decomposition model for multilevel SDA is obtained. The developed hierarchical IO-SDA model would provide consistent results and need less computation effort compared with the traditional SDA model. The decomposition results of the steel plant suggest that the technology improvement and reduced steel final demand are two major reasons for declined total energy consumption. The technical improvements of blast furnaces, basic oxygen furnaces, the power plant and the by-products utilization level have contributed mostly in reducing energy consumption. A major retrofit of ancillary process units and solving fuel substitution problem in the sinter plant and blast furnace are important for further energy saving. Besides the empirical results, this work also discussed that why and how hierarchical SDA can be applied in a process-level decomposition analysis of aggregated indicators.

Optimization of energy consumption structure based on carbon emission reduction target:A case study in Shandong Province,China

It is urgent to significantly reduce greenhouse gas emissions to actively deal with global warming.This paper investigates Shandong Province,a typical province of energy consumption,as the research object,aiming to optimize total energy consumption and consumption structure in the future planning year.This paper constructs a methodological system to optimize energy consumption structure in Shandong Province,using a scenario combination of system dynamics(SD)prediction and analysis based on the coupling of key scenario elements affecting different energy consumption from different perspectives.Structural equation modeling and SD sensitivity analysis indicate an overlap between key factors restricting energy consumption.Pairing the key scenario factors can better reflect the internal mechanism of energy consumption development.Based on this,21 scenarios based on different combinations of the key elements are constructed.Through SD prediction and analysis,the most suitable scenario mode for optimizing energy consumption structure in Shandong Province is selected.This paper provides a suitable development range for the average gross domestic product growth rate,the proportion of secondary industry,energy consumption intensity of secondary industry,and the urbanization rate for Shandong Province.This paper can provide a reference for similar research and the government in formulating the optimization scheme of energy consumption structure.

Influencing factors and contribution analysis of CO_(2) emissions originating from final energy consumption in Sichuan Province,China

Within the context of CO_(2)emission peaking and carbon neutrality,the study of CO_(2)emissions at the provincial level is few.Sichuan Province in China has not only superior clean energy resources endowment but also great potential for the reduction of CO_(2)emissions.Therefore,using logarithmic mean Divisia index(LMDI)model to analysis the influence degree of different influencing factors on CO_(2)emissions from final energy consumption in Sichuan Province,so as to formulate corresponding emission reduction countermeasures from different paths according to the influencing factors.Based on the data of final energy consumption in Sichuan Province from 2010 to 2019,we calculated CO_(2)emission by the indirect emission calculation method.The influencing factors of CO_(2)emissions originating from final energy consumption in Sichuan Province were decomposed into population size,economic development,industrial structure,energy consumption intensity,and energy consumption structure by the Kaya-logarithmic mean Divisia index(LMDI)decomposition model.At the same time,grey correlation analysis was used to identify the correlation between CO_(2)emissions originating from final energy consumption and the influencing factors in Sichuan Province.The results showed that population size,economic development and energy consumption structure have positive contributions to CO_(2)emissions from final energy consumption in Sichuan Province,and economic development has a significant contribution to CO_(2)emissions from final energy consumption,with a contribution rate of 519.11%.The industrial structure and energy consumption intensity have negative contributions to CO_(2)emissions in Sichuan Province,and both of them have significant contributions,among which the contribution rate of energy consumption structure was 325.96%.From the perspective of industrial structure,secondary industry makes significant contributions and will maintain a restraining effect;from the perspective of energy consumption structure,industry sector has a significant contribution.The results of this paper are conducive to the implementation of carbon emission reduction policies in Sichuan Province.

Energy consumption hierarchical analysis based on interpretative structural model for ethylene production

Interpretative structural model(ISM) can transform a multivariate problem into several sub-variable problems to analyze a complex industrial structure in a more efficient way by building a multi-level hierarchical structure model. To build an ISM of a production system, the partial correlation coefficient method is proposed to obtain the adjacency matrix, which can be transformed to ISM. According to estimation of correlation coefficient, the result can give actual variable correlations and eliminate effects of intermediate variables. Furthermore, this paper proposes an effective approach using ISM to analyze the main factors and basic mechanisms that affect the energy consumption in an ethylene production system. The case study shows that the proposed energy consumption analysis method is valid and efficient in improvement of energy efficiency in ethylene production.

SUSTAINABLE DESIGN AND ENERGY CONSUMPTION ANALYSIS FOR STRUCTURAL COMPONENTS

The engineering community has been striving to design more sustainable buildings in an attempt to reduce both environmental impact and energy use during all phases of design,construction and operation.Design professionals currently have very limited guidance or tools to incorporate life-cycle and sustainability concepts into their designs.After reviewing the capabilities and limitations of four current life cycle analysis(LCA)computer programs,this research has selected the Athena Impact Estimator v4.0 to perform parametric studies of structural members made up of different construction materials.The energy consumption values are calculated and compared for columns,beams,concrete suspended slabs,precast double-tee sections and various other floor types.While Athena did offer some insights based on its LCA results,this research has concluded that existing LCA and sustainability analysis programs have too few options to meet the current needs of design professionals.A more accurate,sophisticated whole-building LCA tool needs to be developed to assess sustainable properties of design alternatives and to produce the most sustainable structural systems.

Analysis on Industry Structure Adjustment and Energy Consumption Based on Grey Theory——A Case Study of Qinghai Province

In view of the complexity and non-linearity of energy consumption system and the status quo of the development of energy in Qinghai Province,the relations between energy consumption and industrial structure is analyzed by using the quantitative analysis of grey relation degree by using the grey system theory.The relevancy degree among the primary industry,the secondary industry and the tertiary industry and living energy consumption are obtained,and then the trend of energy consumption in the following several years can be predicted.The results show that the secondary industry has the largest relevancy degree to the total energy consumption.In the end,according to the results of the research,several suggestions on how to saving energy are put forward.Firstly,the government should improve the high-tech industry and restrict the development of high-consumption and high-pollution industries.Secondly,the government should promote the low-carbon way of life;promote energy saving and control the energy consumption of the department of life.Thirdly,clean production should be actively promoted in the tertiary industry and the circular economy should be vigorously expanded.

Structural Decomposition Analysis to Investigate the Changes in Energy Consumption in Pakistan

The world energy demand is increasing due to rapid growth in the global economy,industrialization,and urbanization.Pakistan is also confronted with increasing energy demand on one hand and is confronted with the challenge of energy demand-supply gap on the other hand.Since energy is the major driver for growth,it becomes important to investigate the trends of energy consumption in a country and the factors that are most affecting the changes in the use of energy.This particular study aims to investigate the use of energy by all the economic sectors of Pakistan during 2000–2012.The major contribution is the first time application of structural decomposition analysi for energy usage along with using Input-Output data for the period of 2002–2012.The results show the fluctuation of the energy intensity of the sectors throughout the study period.Also,the overall effect of energy intensity is negative on energy consumption and it shows a negative contribution value of-80.90%for the study period.Furthermore,the focus on more energy-intensive products like cement,automobiles,iron,steel products and the increasing final demand of the economy contributes to the growth of energy consumption in Pakistan during 2000–2012.

Structural Decomposition Analysis of the Decline in China's CO_2 Emission Intensity 2005–2010

Here we utilize input-output tables for 2005 and 2010 to calculate the change in carbon dioxide emission intensity. Results show that total carbon dioxide emissions were 6.79 and 9.30 billion tons, and carbon dioxide emission intensity was 0.37 and 0.33 ton per thousand CNY in 2005 and 2010, respectively. Carbon dioxide emission intensity declined 11% over these five years. We used structural decomposition analysis modeling to measure the effect of four factors on this reduction in intensity. We found that the contribution values of energy structure, energy efficiency, economic growth mode and economic structure were -0.001, -0.102, 0.050, and 0.013 ton per thousand CNY, respectively. Changes in energy efficiency and energy structure are major factors promoting decreases in carbon dioxide emission intensity; the effect of the former is more distinct than the latter. Economic growth mode and economic structure are major factors that increase carbon dioxide emission intensity, whereby the effect of the former is more distinct than the latter.

农居建筑围护结构改造节能敏感性分析:以内蒙古河套地区为例

建筑节能问题是全社会普遍关注的焦点,农村建筑高能耗现状依然严峻。既有建筑节能多关注单一分类要素对能耗的量化影响,而不同组合要素对建筑热负荷影响的总体趋势、显著性和主次关系人们并不清楚。以内蒙河套地区农居为研究对象,通过正交实验、能耗模拟和多元回归方法,研究围护结构因素对建筑热性能的影响规律。结果显示:内蒙古河套地区建筑空间结构因素的主次顺序分别为阳光间进深>保温层厚度>透明围护结构>外墙结构>建筑朝向>窗墙比;当阳光间进深在1 m,保温70 mm,窗墙比为0.5时建筑热负荷最小;优化改造后,呼和浩特、包头、巴彦淖尔和鄂尔多斯的节能率分别为67.5%、69.2%、72.8%和76.5%,为分析空间围护结构因素量化规律和参数优选提供决策依据。

某超高层结构伸臂桁架在罕遇地震下的抗震性能分析

为了解伸臂桁架在罕遇地震下的耗能情况,以某8度区框架-核心筒-伸臂桁架超高层结构为研究对象,采用最小二乘加权调幅法选取7条地震波,基于Perform-3D弹塑性分析软件分析罕遇地震工况下各构件的塑性耗能。结果表明:连梁和伸臂桁架的塑性耗能总量相对均衡,平均占总耗能的73%。随着地震输入能量的增大,伸臂桁架的耗能比例呈上升趋势,从7.4%增加至30%,而连梁的耗能比例呈下降趋势,从75%减小至34%。伸臂桁架耗能的增加减小了连梁的损坏,验证了可将伸臂桁架视为超高层结构“结构保险丝”的观点。研究结果可为优化伸臂桁架性能,推动优化后的伸臂桁架在实际工程中的应用提供理论参考。

玉米深松机械的能耗分析及节能措施研究

深松机械通过翻松土壤底层,打破犁底层,为作物生长提供一个良好的土壤环境。但是深松机耕作深度较大,深松作业时会遇到较大的耕作阻力,从而导致能耗较高。基于玉米深松机械的结构和工作原理,综述了影响深松机械能耗的主要因素,总结了玉米深松机械节能的主要措施,如优化动力系统、采用高效动力系统、采用新型设计理念和使用智能控制系统等。研究结果可有效地降低玉米深松机械的能耗,提高其经济性和可持续性。

单耗分析理论的改进与初步应用

该文进一步发展单耗分析理论，将设备能耗划分为设备结构因素和系统拓扑因素附加单耗，探索揭示没备问附加单耗的耦合关系与依变特性，理论推导建立了2种类型附加单耗的定量模型。对燃气轮机系统进行改进单耗分析，结果表明，设备问存在复杂耦合作用关系；设备能耗的65％-75％源自设备自身结构的不完善，其余则由系统拓扑结构缺陷造成。理论从新角度诠释设备能耗的产生原因，为探索系统和单元双重节能优化打下基础。

中国产业能源消费氮氧化物排放影响因素分析

中国快速增长的能源消费导致大量的氮氧化物排放,研究能源消费的氮氧化物排放的影响因素对于减排政策制定具有重要意义。文章基于扩展的经济-能源-氮氧化物排放的投入产出模型,首次尝试将结构分解方法(structural decomposition analysis,SDA)运用于氮氧化物排放的影响因素分析。研究实例分析了1990-2010年中国生产部门能源消费的氮氧化物排放的变化趋势和影响因素,研究结果表明:1990-2010年中国生产部门能源消费氮氧化物共增排1 522万t,其中国内生产总值因素变动对增排贡献最大(贡献率为107.2%),氮氧化物排放系数因素变动对减排贡献最大(贡献率为-27.3%)。进一步分析表明,经济规模扩大是带动氮氧化物增排的主要原因,而技术水平提高是抑制氮氧化物增排最有效的措施,未来经济结构优化、能源强度降低和技术进步具有较大潜力,交通部门应受到特别关注。

我国产业结构的调整与能源消费的灰色关联分析

利用灰色理论中的灰色关联分析方法,对能源消费与产业结构进行了关联分析,得出第一产业、第二产业、第三产业及生活用能与能源消费的关联度,从而根据目前我国的产业结构调整政策及加入WTO后,国外投资对我国产业结构的影响,并对今后几年的能源消费做出了预测.

一次能源消费结构变化对我国单位GDP能耗影响效应研究

基于1980-2004年能源统计数据,首先利用通径分析法测算了一次能源消费结构、技术、管理因素与单位GDP能耗强度的关系,定量分析了各一次能源消费构成比例(煤,石油,天然气,水电等消耗比例)对单位GDP能耗的直接、间接和总影响程度;结果表明:技术水平及管理水平等不可测因素对我国单位GDP能耗起决定作用,石油消耗比例为单位GDP能耗变化的主要限制性因素,故在煤的消费比例下降幅度较小的情况下,要想达到节能降耗的目的,必须首先重视技术的进步及管理水平的提高,同时提高石油的使用比例,尤其要重视水电的发展。然后利用通径分析结果消除了多重共线性的影响,建立了单位GDP能耗同一次能源消费结构及其它相关因素间的多元回归模型,分析了能源消费结构的调整和优化对节能降耗的影响途径及影响效应。

双强度约束下行业低碳经济增长路径优化研究

本文建立了双强度约束下低碳经济增长多目标优化模型,分析了行业能耗强度和能源消费结构的调整对低碳经济增长路径的影响。结果表明,在经济增长、能源消耗与CO2排放协调发展情景中,若"十二五"期间各行业能耗强度和一次能源消费结构遵循"十一五"期间的变化趋势,则对农业、工业和建筑业的经济增长不利,对其他行业有利。在其基础上,若减少工业和建筑业能耗强度的降幅,增加其他行业能耗强度的降幅,可提高农业和建筑业的经济增长速度;优化能源消费结构能减缓工业和建筑业能耗强度的下降压力,且非化石能源比例可达11.4%。若在优化能源消费结构基础上,进一步减少工业和建筑业能耗强度的降幅,对各行业经济增长影响不大,但会增加全国能源消耗和CO2排放。各种情景中服务业增加值比重均可达47%,但进一步上升的潜力不大;全国及各行业能源消耗、CO2排放与经济增长之间均将处于弱脱钩状态。

能源节约视角下辽宁省产业结构实证分析

基于完全分解模型对辽宁省的能源消费和能源节约进行了分解计算,给出能源强度和产业结构对能源节约的影响效果和贡献率.虽然计算结果显示能源强度对能源节约起到主要作用,但由于产业结构与能源节约的密切关系,采用统计回归的方法讨论了产业结构调整对能源节约的推动作用,并发现工业、建筑业和交通业的产值比重与能源节约之间存在显著的关系.通过对回归结果的进一步研究找出上述各产业推动能源节约的临界产值比重,其中工业和交通业产值比重的变化趋势推动了省内能源节约的发展.

中国居民间接生活能源消费的结构分解分析

居民生活能源消费可分为直接和间接消费两部分，一般来说，后者远远大于前者。因此，在经济快速发展，能源消费迅猛增长的背景下，分析居民间接生活能源消费的变动趋势及原因，对于寻找节能途径与对策具有重要意义。本文以1987年～2002年为样本期，运用投入产出方法，构建结构分解分析模型，对中国居民间接生活能源消费的增长原因进行了实证分析。结果表明：促使间接生活能源消费增加的因素有居民消费总量增加、消费结构变化、城乡消费比例变化和中间生产技术变化，而起到抑制能源消费增加的因素唯有以直接能源消耗系数大幅下降为标志的节能技术进步。可见，由于我国正值工业化和城市化的中期阶段，居民消费变化和产业结构演进都成为能源消费上升的重要拉动因素，因此必须提倡适度合理的消费方式，促进生活节能；同时加快调整以重化工业为主导的产业结构，发挥结构节能效应。