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Modeling uncertainty in estimation of carbon dioxide abatement costs of energy-saving technologies for passenger cars in China

机译:在中国乘用车节能技术的二氧化碳减排成本估算中建立不确定性模型

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摘要

Estimation of carbon dioxide abatement cost is of the essence to promote energy-saving technologies (ESTs) in the passenger car sector, while the existence of various uncertainties of abatement cost may be major barriers for technology promotion. This study establishes the projected marginal abatement cost (MAC) curve of China's passenger car sector over the 2016-2030 period and conducts uncertainty modeling through Monte Carlo simulation. The impacts of uncertainties from oil price, electricity cost, energy-saving potential, incremental investment cost, and emission factor for electricity consumption on emission abatement costs of ESTs are analyzed separately and compared together. Results show that among the five uncertainties, oil price uncertainty has the largest impact on ESTs' emission abatement cost, but the impact does not differ significantly among different technology bundles. Uncertainties in electricity cost and in electricity emission factor affect significantly the MACs of new-energy paths. Compared with the above two uncertainties, uncertainties in energy-saving potential and in incremental investment cost have larger impacts on the MACs of traditional energy-saving paths. Among different vehicle types, the MACs of ESTs on small-displacement private cars are the least affected by various uncertainties.
机译:估算二氧化碳减排成本对于促进乘用车行业的节能技术至关重要,而减排成本的各种不确定性可能是技术推广的主要障碍。本研究建立了2016-2030年中国乘用车行业的预计边际减排成本(MAC)曲线,并通过蒙特卡洛模拟进行不确定性建模。分别分析并比较了油价,电力成本,节能潜力,增量投资成本和用电量排放因子等不确定性对无害环境技术减排成本的影响。结果表明,在这五种不确定性中,油价不确定性对无害环境技术的减排成本影响最大,但不同技术束之间的影响并没有显着差异。电力成本和电力排放因子的不确定性严重影响了新能源路径的MAC。与上述两个不确定性相比,节能潜力和增量投资成本中的不确定性对传统节能路径的MAC影响更大。在不同类型的车辆中,小排量私家车的无级变速器的MAC受到各种不确定性的影响最小。

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