清洁能源与非清洁能源之间的替代弹性:来自中国电力行业的证据

Caifei Luo, Keyu Zhang
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摘要

当前,我国正处于经济高质量发展阶段。不断增长的电力需求产生了大量的二氧化碳排放,这给中国电力行业的低碳发展带来了巨大压力。因此,中国高度重视各种清洁发电替代火力发电的潜力。有鉴于此,本研究利用 translog 生产函数研究了 1993 年至 2022 年非清洁能源发电(火力发电)和清洁能源发电(水力发电、核能发电和其他能源发电)的替代潜力,并提供了发电能源替代的情景分析。首先,本文采用 k 倍交叉验证法进行脊回归估计,避免了以往大多数文献中使用的脊迹图法造成的主观偏差。其次,与以往关于电力行业替代弹性的研究相比,本文在估计替代弹性时对清洁电力能源类型进行了细分,可以更好地分析火电与各种清洁电力之间的替代关系。最后,火电与各种清洁能源的替代弹性估计值大于 1,说明清洁能源发电可以有效替代非清洁能源发电。这为电力行业研究低碳发展提供了一个有效的替代弹性参数。情景分析表明,中国电力行业在保证电力供应的前提下,可以通过提高清洁发电比例来降低碳排放强度,这有助于中国政府调整政策的实施,促进电力行业碳排放提前达峰,并将碳排放控制在较低水平。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Elasticity of substitution between clean energy and non-clean energy: Evidence from the Chinese electricity industry

At present, China is in a stage of high-quality economic development. Rising demand for electricity has created a lot of CO2 emissions, which has put great pressure on the low-carbon development of China's power industry. Therefore, China attaches great importance to the potential of various clean power generation to replace thermal power generation. Given this, the study examines the potential for substitution of non-clean energy generation (thermal power generation) and clean energy generation (hydropower, nuclear power generation, and other energy generation) from 1993 to 2022 by using the translog production function and provides a scenario analysis of energy substitution for power generation. Firstly, the k-fold cross-validation method is used for ridge regression estimation in this paper, which avoids the subjective bias caused by the ridge trace diagram method used in most of the previous literatures. Secondly, compared with the previous research on the substitution elasticity of the power sector, this paper subdivides the types of clean power energy when estimating the substitution elasticity, which can better analyze the substitution relationship between thermal power and various clean power. Finally, the estimated substitution elasticity of thermal power and various clean energy sources is greater than 1, which indicates that clean energy generation can effectively replace non-clean energy generation. This provides an effective substitution elasticity parameter for the power sector to study low-carbon development. The scenario analysis show China's power sector can increase the proportion of clean power generation to reduce the carbon emission intensity while ensure power supply, which can help the Chinese government adjust the implementation of policies to promote the early peak of carbon emissions and keep carbon emission at a low level in the power sector.

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