摘要
电动汽车碳排放影响因素较多,导致其精确预测难度较大。为此,本工作提出考虑时间相关性的电动汽车全生命周期碳排放量预测方法。从全生命周期理论出发,计量边际发电量、线损率、煤炭生产环节产生的碳排放量、电煤运输环节产生的碳排放量与发电环节的碳排放量,并将时间相关性应用到电动汽车行驶特征分析,计算直接碳排放量,以此完成考虑时间相关性的电动汽车全生命周期碳排放量预测。实验结果表明:在车辆上坡、下坡、拥堵与正常行驶情况下的碳排放量预测准确度较高,满足电动汽车碳排放量预测需求。
Because of several contributing factors,it is difficult to correctly anticipate electric vehicle carbon emissions.As a result,a strategy for predicting carbon emissions from electric cars during their whole life cycle is suggested,taking into account temporal correlation.On the whole life cycle theory,measuring marginal electricity,and coal production line loss,suggestions produce carbon emissions,and the carbon emissions formed by coal transportation link power link's carbon footprint,and applies time correlation to the analysis of characteristics of the electric car driving,calculate direct carbon emissions,to complete consideration of time correlation prediction in the whole life cycle of the electric car carbon emissions.The experimental findings reveal that the proposed measuring technique has high accuracy in carbon emission forecast under vehicle uphill,downhill,congestion,and regular driving scenarios,which satisfies the requirement for electric vehicle carbon emission prediction.
作者
武光华
李宏胜
李飞
陈博
张世科
WU Guanghua;LI Hongsheng;LI Fei;CHEN Bo;ZHANG Shike(Marketing Service Center,State Grid Hebei Electric Power Co.Ltd.,Shijiazhuang 050000,Hebei,China)
出处
《储能科学与技术》
CAS
CSCD
北大核心
2022年第7期2206-2212,共7页
Energy Storage Science and Technology
基金
国网河北省电力有限公司科技项目(kj2020-085)。
关键词
时间相关性
电动汽车
全生命周期
碳排放量
预测
边际发电量
time correlation
electric vehicles
full life cycle
carbon emissions
forecast
marginal power generation
