CHEN Gongda;CHENG Guohui;CAI Rujin;ZOU Xiangbo;ZHU Wang;YE Ji;QIN Shiwei;TANG Shun;LU Weiye;

• 1:Guangdong Energy Group Science and Technology Research Institute Co.
• 2:Ltd.
• 3:Guangzhu Power Generation Co.
• 4:Ltd.of Zhuhai Special Economic Zone

Abstract：

In recent years, carbon measurement technology for flue gases has garnered increased attention. Nevertheless, due to the lack of comprehensive technical standards and systems in China, its formal implementation in the power generation industry remains limited, particularly concerning CO_2 monitoring data gaps. Effective methods for addressing CO_2 data gaps were investigated and three approaches were compared including retaining the last valid value before the gap, data conversion using oxygen based on default and median correction values, and utilizing the maximum carbon emission rate within the past 180 hours during long-term evaluations. The findings indicate that the maximum CO_2 volumetric fraction in actual fuel combustion varies under different load conditions, with distinct distribution patterns. For coal-fired units, the variability in the maximum CO_2 volumetric fraction is approximately 4%, with a median value of 18.67% that closely aligns with the default value. In contrast, for gas-fired units, the maximum CO_2 volumetric fraction exhibits two notable stages of variation, with a median value of 11.38%, differing by 0.12% from the default. Long-term evaluations show that the corrected method yields data most comparable to normal conditions, with monthly carbon emission deviations controlled within 1.5 tons, demonstrating high accuracy and applicability. However, while the 180-hour maximum value method can serve as an effective punitive management tool for carbon data, its widespread adoption may lead to overestimation of carbon emissions in international negotiations or transactions as flue gas monitoring becomes more prevalent in the coal-fired power sector.

Key Words： carbon measurement;CO_2 monitoring;thermal power;flue gas;data gaps imputation

Abstract:

Keywords:

Foundation: 国家重点研发计划资助项目(2021YFF0601001);; 广东省能源局广东省新型电力系统技术创新资助项目(1688950422168)

Authors: CHEN Gongda;CHENG Guohui;CAI Rujin;ZOU Xiangbo;ZHU Wang;YE Ji;QIN Shiwei;TANG Shun;LU Weiye;

DOI: 10.13226/j.issn.1006-6772.LC24041001

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