LAPSE:2023.19350
Published Article

LAPSE:2023.19350
Uncertainty of the Electricity Emission Factor Incorporating the Uncertainty of the Fuel Emission Factors
March 9, 2023
Abstract
Greenhouse gas (GHG) emission from electricity generation has been recognized as one of the most significant contributors to global warming. The GHG emission factor of electricity (hereafter, electricity emission factor) can be expressed as a function of three different (average, minimum, and maximum) fuel emission factors, monthly fuel consumption, and monthly net power generation. Choosing the average fuel emission factor over the minimum and maximum fuel emission factors is the cause of uncertainty in the electricity emission factor, and thus GHG emissions of the power generation. The uncertainties of GHG emissions are higher than those of the electricity emission factor, indicating that the uncertainty of GHG emission propagates in the GHG emission computation model. The bootstrapped data were generated by applying the bootstrap method to the original data set which consists of a 60-monthly average, and minimum and maximum electricity emission factors. The bootstrapped data were used for computing the mean, confidence interval (CI), and percentage uncertainty (U) of the electricity emission factor. The CI, mean, and U were [0.431, 0.443] kg CO2-eq/kWh, 0.437 kg CO2-eq/kwh, and 2.56%, respectively.
Greenhouse gas (GHG) emission from electricity generation has been recognized as one of the most significant contributors to global warming. The GHG emission factor of electricity (hereafter, electricity emission factor) can be expressed as a function of three different (average, minimum, and maximum) fuel emission factors, monthly fuel consumption, and monthly net power generation. Choosing the average fuel emission factor over the minimum and maximum fuel emission factors is the cause of uncertainty in the electricity emission factor, and thus GHG emissions of the power generation. The uncertainties of GHG emissions are higher than those of the electricity emission factor, indicating that the uncertainty of GHG emission propagates in the GHG emission computation model. The bootstrapped data were generated by applying the bootstrap method to the original data set which consists of a 60-monthly average, and minimum and maximum electricity emission factors. The bootstrapped data were used for computing the mean, confidence interval (CI), and percentage uncertainty (U) of the electricity emission factor. The CI, mean, and U were [0.431, 0.443] kg CO2-eq/kWh, 0.437 kg CO2-eq/kwh, and 2.56%, respectively.
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Keywords
bootstrap, electricity emission factor, fuel emission factor, GHG emission, uncertainty
Subject
Suggested Citation
LEE KM, LEE MH. Uncertainty of the Electricity Emission Factor Incorporating the Uncertainty of the Fuel Emission Factors. (2023). LAPSE:2023.19350
Author Affiliations
Journal Name
Energies
Volume
14
Issue
18
First Page
5697
Year
2021
Publication Date
2021-09-10
ISSN
1996-1073
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Original Submission
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PII: en14185697, Publication Type: Journal Article
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LAPSE:2023.19350
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https://doi.org/10.3390/en14185697
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Mar 9, 2023
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