Dynamic Prospective Average and Marginal GHG Emission Factors—Scenario-Based Method for the German Power System until 2050

Due to the continuous diurnal, seasonal, and annual changes in the German power supply, prospective dynamic emission factors are needed to determine greenhouse gas (GHG) emissions from hybrid and flexible electrification measures. For the calculation of average emission factors (AEF) and marginal em...

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Main Authors: Nils Seckinger, Peter Radgen
Format: Article
Language:English
Published: MDPI AG 2021-04-01
Series:Energies
Subjects:
Online Access:https://www.mdpi.com/1996-1073/14/9/2527
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spelling doaj-d269487f980c4f5da24ae890f86e51b42021-04-28T23:03:24ZengMDPI AGEnergies1996-10732021-04-01142527252710.3390/en14092527Dynamic Prospective Average and Marginal GHG Emission Factors—Scenario-Based Method for the German Power System until 2050Nils Seckinger0Peter Radgen1Institute of Energy Economics and Rational Energy Use (IER), University of Stuttgart, 70565 Stuttgart, GermanyInstitute of Energy Economics and Rational Energy Use (IER), University of Stuttgart, 70565 Stuttgart, GermanyDue to the continuous diurnal, seasonal, and annual changes in the German power supply, prospective dynamic emission factors are needed to determine greenhouse gas (GHG) emissions from hybrid and flexible electrification measures. For the calculation of average emission factors (AEF) and marginal emission factors (MEF), detailed electricity market data are required to represent electricity trading, energy storage, and the partial load behavior of the power plant park on a unit-by-unit, hourly basis. Using two normative scenarios up to 2050, different emission factors of electricity supply with regard to the degree of decarbonization of power production were developed in a linear optimization model through different GHG emission caps (Business-As-Usual, BAU: −74%; Climate-Action-Plan, CAP: −95%). The mean hourly German AEF drops to 182 g<sub>CO2eq</sub>/kWh<sub>el</sub> (2018: 468 g<sub>CO2eq</sub>/kWh<sub>el</sub>) in the BAU scenario by the year 2050 and even to 29 g<sub>CO2eq</sub>/kWh<sub>el</sub> in the CAP scenario with 3700 almost emission-free hours from power supply per year. The overall higher MEF decreases to 475 and 368 g<sub>CO2eq</sub>/kWh<sub>el</sub>, with a stricter emissions cap initially leading to a higher MEF through more gas-fired power plants providing base load. If the emission intensity of the imported electricity differs substantially and a storage factor is implemented, the AEF is significantly affected. Hence, it is not sufficient to use the share of RES in net electricity generation as an indicator of emission intensity. With these emission factors it is possible to calculate lifetime GHG emissions and determine operating times of sector coupling technologies to mitigate GHG emissions in a future flexible energy system. This is because it is decisive when lower-emission electricity can be used to replace fossil energy sources.https://www.mdpi.com/1996-1073/14/9/2527hourly emission factorsmarginal emission factoraverage emission factorlifetime emissionslife cycle assessmentelectrification
collection DOAJ
language English
format Article
sources DOAJ
author Nils Seckinger
Peter Radgen
spellingShingle Nils Seckinger
Peter Radgen
Dynamic Prospective Average and Marginal GHG Emission Factors—Scenario-Based Method for the German Power System until 2050
Energies
hourly emission factors
marginal emission factor
average emission factor
lifetime emissions
life cycle assessment
electrification
author_facet Nils Seckinger
Peter Radgen
author_sort Nils Seckinger
title Dynamic Prospective Average and Marginal GHG Emission Factors—Scenario-Based Method for the German Power System until 2050
title_short Dynamic Prospective Average and Marginal GHG Emission Factors—Scenario-Based Method for the German Power System until 2050
title_full Dynamic Prospective Average and Marginal GHG Emission Factors—Scenario-Based Method for the German Power System until 2050
title_fullStr Dynamic Prospective Average and Marginal GHG Emission Factors—Scenario-Based Method for the German Power System until 2050
title_full_unstemmed Dynamic Prospective Average and Marginal GHG Emission Factors—Scenario-Based Method for the German Power System until 2050
title_sort dynamic prospective average and marginal ghg emission factors—scenario-based method for the german power system until 2050
publisher MDPI AG
series Energies
issn 1996-1073
publishDate 2021-04-01
description Due to the continuous diurnal, seasonal, and annual changes in the German power supply, prospective dynamic emission factors are needed to determine greenhouse gas (GHG) emissions from hybrid and flexible electrification measures. For the calculation of average emission factors (AEF) and marginal emission factors (MEF), detailed electricity market data are required to represent electricity trading, energy storage, and the partial load behavior of the power plant park on a unit-by-unit, hourly basis. Using two normative scenarios up to 2050, different emission factors of electricity supply with regard to the degree of decarbonization of power production were developed in a linear optimization model through different GHG emission caps (Business-As-Usual, BAU: −74%; Climate-Action-Plan, CAP: −95%). The mean hourly German AEF drops to 182 g<sub>CO2eq</sub>/kWh<sub>el</sub> (2018: 468 g<sub>CO2eq</sub>/kWh<sub>el</sub>) in the BAU scenario by the year 2050 and even to 29 g<sub>CO2eq</sub>/kWh<sub>el</sub> in the CAP scenario with 3700 almost emission-free hours from power supply per year. The overall higher MEF decreases to 475 and 368 g<sub>CO2eq</sub>/kWh<sub>el</sub>, with a stricter emissions cap initially leading to a higher MEF through more gas-fired power plants providing base load. If the emission intensity of the imported electricity differs substantially and a storage factor is implemented, the AEF is significantly affected. Hence, it is not sufficient to use the share of RES in net electricity generation as an indicator of emission intensity. With these emission factors it is possible to calculate lifetime GHG emissions and determine operating times of sector coupling technologies to mitigate GHG emissions in a future flexible energy system. This is because it is decisive when lower-emission electricity can be used to replace fossil energy sources.
topic hourly emission factors
marginal emission factor
average emission factor
lifetime emissions
life cycle assessment
electrification
url https://www.mdpi.com/1996-1073/14/9/2527
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