Preliminary Exploration of Carbon Emission Estimation Technology Based on Power Big Data

LIU Yuliang; LI Yaowang; DU Ershun; ZHANG Ning; KANG Chongqing; DU Siyuan

doi:10.7500/AEPS20240905004

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Preliminary Exploration of Carbon Emission Estimation Technology Based on Power Big Data

Power System Analysis and Optimization from Carbon Perspective | 更新时间：2026-02-28

- Preliminary Exploration of Carbon Emission Estimation Technology Based on Power Big Data
- Automation of Electric Power Systems Vol. 50, Issue 3, Pages: 17-25(2026)
- 作者机构：
  
  1.清华大学电机工程与应用电子技术系，北京市 100084
  2.清华四川能源互联网研究院，四川省成都市 610213
  3.国网北京市电力公司，北京市 100031
- 作者简介：
- 基金信息：
  
  State Grid Corporation of China(5700-202411271A-1-1-ZN)
- DOI：10.7500/AEPS20240905004
  CLC：
- Received：05 September 2024，
  
  Revised：2025-01-23，
  
  Online First：11 April 2025，
  
  Published：10 February 2026
- 稿件说明：
移动端阅览
刘昱良,李姚旺,杜尔顺等.基于电力大数据的碳排放测算技术初探[J].电力系统自动化,2026,50(3):17-25.

LIU Yuliang,LI Yaowang,DU Ershun,et al.Preliminary Exploration of Carbon Emission Estimation Technology Based on Power Big Data[J].Automation of Electric Power Systems,2026,50(3):17-25.
刘昱良,李姚旺,杜尔顺等.基于电力大数据的碳排放测算技术初探[J].电力系统自动化,2026,50(3):17-25. DOI： 10.7500/AEPS20240905004.

LIU Yuliang,LI Yaowang,DU Ershun,et al.Preliminary Exploration of Carbon Emission Estimation Technology Based on Power Big Data[J].Automation of Electric Power Systems,2026,50(3):17-25. DOI： 10.7500/AEPS20240905004.

摘要

能源活动是二氧化碳排放的最主要来源，即时、准确地掌握能源活动碳排放是支撑政府和企业把握碳排放总量和制定碳管控策略的基础。然而，核算法难以支撑高频度碳排放计算，实测法又需要安装额外设备，导致目前尚无低成本、高频度的碳排放测算手段。为此，文中利用电力消费与能源活动间的关联关系，提出一种基于电力大数据的能源活动碳排放测算（简称“以电测碳”）技术。首先，提出了“以电测碳”技术的方法架构，并从数据角度出发，详细调研分析了相关基础数据情况，探讨了现有数据的潜在应用范围。其次，构建了基于时间序列的区域-行业-企业通用“以电测碳”模型，并结合中国实际数据开展了测算效果分析。分析结果表明，所提方法能够有效提升碳排放测算的时效性。最后，对“以电测碳”技术未来的研究与应用方向进行了展望。

Abstract

Energy activities are the primary sources of carbon dioxide emissions. Accurate and near real-time monitoring of carbon emissions from energy activities is fundamental for governments and enterprises to grasp the total carbon emissions and formulate carbon management strategies. However

existing accounting methods are insufficient for high-frequency carbon emission calculations

whereas direct measurement methods necessitate additional equipment to be installed. Consequently

low-cost and high-frequency carbon emission estimation techniques remain unavailable. To address this issue

by using the correlation between electricity consumption and energy activities

this paper proposes an estimation technology for carbon emissions from energy activities based on power big data (abbreviated as “electricity-based carbon emission estimation”). Firstly

the methodological framework for “electricity-based carbon emission estimation” technology is proposed. From a data-centric perspective

a detailed investigation and analysis on related foundational data are conducted

and the potential application scope of existing data is explored. Secondly

a time-series based “electricity-based carbon emission estimation” model applicable at regional

industrial

and enterprise levels is constructed

followed by an evaluation of its effectiveness using actual data from China. The analysis results demonstrate that the proposed method can significantly improve the timeliness of carbon emission estimation. Finally

the future research and potential application directions for the “electricity-based carbon emission estimation” technology are prospected.

关键词

Keywords

references

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