基于中国电网结构及一线典型城市车辆出行特征的PHEV二氧化碳排放分析
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摘要
中国电网火电比例的空间差异与插电式混合动力汽车(PHEV)驱动能源的二元性增加了研究PHEV二氧化碳排放的复杂性.使用上海市50辆PHEV汽车13万km的数据,研究了基于PHEV实际运行数据的二氧化碳排放评估方法,分析了PHEV纯电驱动里程比例及其影响因素,获得了纯电续驶里程、充电频率、电网构成对PHEV二氧化碳排放强度的影响,展望了2020年PHEV技术水平的二氧化碳减排效果.结果表明,我国一线城市PHEV乘用车出行主要集中在50 km以内的范围,占日常出行频次的70%;在2016年全国平均电网结构下,续驶里程超过50 km的PHEV比传统燃油车少排放15%以上的二氧化碳;在高比例可再生能源电网结构的地区,PHEV碳排放可降至100. 0 g·km~(-1)以下,相比平均电网结构下碳排放水平降低幅度在28%以上;在2016年平均电网结构及技术水平下,纯电续驶里程增加(50～100 km)、充电频率增加(0. 5～2次·d~(-1))对碳排放的改善幅度不明显;与2016年相比,2020年PHEV燃油经济性和电耗水平的改善可降低32%的碳排放.
Spatial-domain changes in the proportion of thermal power in the power grids of China and the duality of PHEV-driven energy have increased the complexity of research on the CO_2 emissions of plug-in hybrid electric vehicles( PHEVs). 130 000 km of driving data from 50 PHEV vehicles operating in Shanghai is studied to derive methods to evaluate the carbon dioxide emission of PHEV vehicles. The electric drive distance ratio of the PHEV and its influencing factors are analyzed. The effects of the electric range,charging frequency,and power grid composition on the carbon emission intensity of PHEV are analyzed,and the effect of the level of progress for PHEV in 2020 on CO_2 emission reductions is forecast. The results of the study show that the daily vehicle kilometers travelled by PHEV passenger cars in China's first-tier cities are mainly concentrated within a range of 50 km,accounting for 70% of total trips. Under the national grid structure in 2016,PHEVs with a driving range of more than 50 km emit at least 15% less carbon dioxide than conventional vehicles. In areas with a high proportion of renewable energy grid structure,PHEV carbon dioxide emissions can be reduced to below 100. 0 g·km~(-1),which is more than 28% lower than that achieved using the national grid structure. Based on the national grid structure and technical level in 2016,increasing the all-electric range( 50-100 km) and the charging frequency( 0. 5 times·d~(-1) to 2 times·d~(-1)) has no obvious effect on reducing CO_2 emissions. The PHEV fuel economy and electricity consumption levels in 2020 could reduce carbon dioxide emissions by 32% compared to those in 2016.
Spatial-domain changes in the proportion of thermal power in the power grids of China and the duality of PHEV-driven energy have increased the complexity of research on the CO_2 emissions of plug-in hybrid electric vehicles( PHEVs). 130 000 km of driving data from 50 PHEV vehicles operating in Shanghai is studied to derive methods to evaluate the carbon dioxide emission of PHEV vehicles. The electric drive distance ratio of the PHEV and its influencing factors are analyzed. The effects of the electric range,charging frequency,and power grid composition on the carbon emission intensity of PHEV are analyzed,and the effect of the level of progress for PHEV in 2020 on CO_2 emission reductions is forecast. The results of the study show that the daily vehicle kilometers travelled by PHEV passenger cars in China's first-tier cities are mainly concentrated within a range of 50 km,accounting for 70% of total trips. Under the national grid structure in 2016,PHEVs with a driving range of more than 50 km emit at least 15% less carbon dioxide than conventional vehicles. In areas with a high proportion of renewable energy grid structure,PHEV carbon dioxide emissions can be reduced to below 100. 0 g·km~(-1),which is more than 28% lower than that achieved using the national grid structure. Based on the national grid structure and technical level in 2016,increasing the all-electric range( 50-100 km) and the charging frequency( 0. 5 times·d~(-1) to 2 times·d~(-1)) has no obvious effect on reducing CO_2 emissions. The PHEV fuel economy and electricity consumption levels in 2020 could reduce carbon dioxide emissions by 32% compared to those in 2016.
引文
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[30] Wu X,Aviquzzaman M,Lin Z H. Analysis of plug-in hybrid electric vehicles'utility factors using GPS-based longitudinal travel data[J]. Transportation Research Part C:Emerging Technologies,2015,57:1-12.
[31] Requia W J,Adams M D,Arain A,et al. Carbon dioxide emissions of plug-in hybrid electric vehicles:a life-cycle analysis in eight Canadian cities[J]. Renewable and Sustainable Energy Reviews,2017,78:1390-1396.
[32] Kelly J C,Mac Donald J S,Keoleian G A. Time-dependent plugin hybrid electric vehicle charging based on national driving patterns and demographics[J]. Applied Energy,2012,94:395-405.
[33] Mac Pherson N D,Keoleian G A,Kelly J C. Fuel economy and greenhouse gas emissions labeling for plug-in hybrid vehicles from a life cycle perspective[J]. Journal of Industrial Ecology,2012,16(5):761-773.
[34] Faria R,Marques P,Moura P,et al. Impact of the electricity mix and use profile in the life-cycle assessment of electric vehicles[J]. Renewable and Sustainable Energy Reviews,2013,24:271-287.
[35] Wang H W,Zhang X B,Ouyang M G. Energy consumption of electric vehicles based on real-world driving patterns:a case study of Beijing[J]. Applied Energy,2015,157:710-719.
[36] Zhang X B,Wang H W. Utility factors derived from Beijing passenger car travel survey[R]. Netherlands:The FISITA 2014World Automotive Congress,2014. 1-10.
[37] Davies J,Kurani K S. Moving from assumption to observation:implications for energy and emissions impacts of plug-in hybrid electric vehicles[J]. Energy Policy,2013,62:550-560.
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