电气化道路技术环境评价

Q2 Engineering
Sirin Thanasrivanitchai, Suparatchai Vorarat, Aumnad Phdungsilp
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引用次数: 0

摘要

脱碳意识和燃料价格促使更大的替代能源部署。使用电气化道路系统(ERS)的电池电动卡车是一种很有前途的解决方案。本文的目的是评估燃料消耗和环境效益的6公里道路,泰国莱姆查邦港,以尝试下导电充电。以1280辆载货汽车为例,设计了工作日电池容量渗透率,年电力需求为1.608 TWh,灵活需求为1.65 TWh。输入符合泰国电力标准,每0.0016平方公里50kVA变电站,电压系统为22kV/400-230V。渗透需要525千瓦时的容量。结果表明,年燃油消耗量为592.43太瓦时,二氧化碳排放量为51.63 MtCO2。采用时间序列、固定效应和Tobit回归评价ERS后的疗效。时间序列分析表明,到2060年,林察班的二氧化碳排放量将接近于零,年均GDP为4%。固定效应表示具有近期泰国潜力的结果,而Tobit回归表示可能变化的影响。两种回归都表明,尽管ERS没有变化,但收入、石油资源、海洋开放程度和政治稳定性的变化对CO2排放有显著影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Techno-Environmental Assessment of Electrified Road
Decarbonization awareness and fuel price induced greater alternative energy deployment. Battery electric trucks using Electrified Road System (ERS) is a promising solution. The aim of this paper is to evaluate fuel consumption and environmental benefits in 6 km road in Laem Chabang Port, Thailand to try out the underneath conductive charging. Battery capacity penetrations were designed regarding 1,280 trucks on weekdays, the electricity annual demand reached 1.608 TWh and the flexible demand was at 1.65 TWh. The input observed Thailand’s electricity standard with 50kVA power substation per 0.0016 km2 and 22kV/400-230V voltage system. The penetration required 525 kWh capacity. The findings indicated that fuel consumption was at 592.43 TWh and CO2 emission were at 51.63 MtCO2 yearly. Consequence after ERS was evaluated with Time Series, Fixed Effect, and Tobit Regression. Time Series analysis showed that CO2 emission would be close to zero in 2060 with annual 4% Laem Chabang’s GDP. Fixed Effect signified the findings with recent Thailand potential, whilst Tobit Regression represented influence from possible change. Both regressions showed that variation in revenue, oil resource, openness to the sea, and political stability significantly affected CO2 emission although there was no change in the ERS.
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来源期刊
International Journal of Energy for a Clean Environment
International Journal of Energy for a Clean Environment Engineering-Automotive Engineering
CiteScore
3.30
自引率
0.00%
发文量
78
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