Uncertainty of the Electricity Emission Factor Incorporating the Uncertainty of the Fuel Emission Factors
Kun Mo Lee and
Min Hyeok Lee
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Kun Mo Lee: Department of Environmental and Safety Engineering, Ajou University, 206 Worldcup-ro, Yeongtong-gu, Suwon-si 16499, Korea
Min Hyeok Lee: Global Manufacturing Center, SHE Group, Samsung Electro-Mechanics, 150, Maeyeong-ro, Yeongtong-gu, Suwon-si 16674, Gyeonggi-do, Korea
Energies, 2021, vol. 14, issue 18, 1-14
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 CO 2 -eq/kWh, 0.437 kg CO 2 -eq/kwh, and 2.56%, respectively.
Keywords: GHG emission; electricity emission factor; fuel emission factor; uncertainty; bootstrap (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (1)
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