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考虑精细化碳排放因子的平板玻璃企业低碳需求响应方法OA

Low carbon demand response approach for the flat glass industry considering refined carbon emission factors

中文摘要英文摘要

为解决用电侧碳排放因子选取过于粗糙的问题,进一步促进高碳排放企业用电行为的低碳化,提出一种考虑精细化碳排放因子的平板玻璃企业低碳需求响应方法.首先,以平板玻璃这一典型企业为例,通过分析平板玻璃生产的碳排放情况,建立平板玻璃企业的碳排放核算模型;然后,考虑潮流网损分摊,基于比例潮流追踪的方法,结合平板玻璃企业用电特性,对用户侧碳排放因子进行细化;最后,通过将碳排放因子与碳税结合,提出了基于碳排放因子的低碳需求响应模型,激励企业进行降碳用电行为.通过算例分析,证明了所提方法可以实现碳排放因子在时空分布层面的细化,并引导企业调整自身用电行为,挖掘其碳减排潜力.

In order to solve the problem that the selection of carbon emission factors on the power side is too rough,and further promote the low-carbon electricity consumption behavior of high-carbon emission enterprises,a low-carbon demand response method for flat glass manu-facturers considering fine carbon emission factors is proposed.Firstly,taking flat glass as a typical manufacturer,the carbon emission ac-counting model of flat glass enterprises is established by analyzing the carbon emission of flat glass production.Then,considering the power flow loss allocation,based on the method of proportional power flow tracking,combined with the power consumption characteristics of flat glass enterprises,the carbon emission factors on the user side are refined.Finally,by combining carbon emission factor and carbon tax,a low-carbon demand response model based on carbon emission factor is proposed to encourage enterprises to reduce carbon electricity con-sumption.Through the example analysis,it is proved that the proposed method can realize the refinement of carbon emission factors in the spatial and temporal distribution level,and guide enterprises to adjust their own electricity consumption behavior and tap their carbon emis-sion reduction potential.

李明冰;王平欣;夏晓东;杨剑;王清;朱红霞

山东大学 电气工程学院,济南 250061国网山东省电力公司 营销服务中心(计量中心),济南 250001国网山东省电力公司 营销服务中心(计量中心),济南 250001国网山东省电力公司 营销服务中心(计量中心),济南 250001国网山东省电力公司 营销服务中心(计量中心),济南 250001国网山东省电力公司 营销服务中心(计量中心),济南 250001

化学化工

平板玻璃企业碳排放碳排放因子电力潮流追踪需求响应

flat glass manufacturerscarbon footprintcarbon emission factorspower flow tracingdemand response

《电力需求侧管理》 2026 (2)

70-76,7

山东省自然科学基金资助项目(ZR2022QE145)国网山东电力公司科技项目(520633220020)

10.3969/j.issn.1009-1831.2026.02.011

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