Principal Cross-Border Flow Patterns in the European Electricity Markets

Schäfer, Mirko; Hofmann, Fabian; Abdel-Khalek, Hazem; Weidlich, Anke

doi:10.1109/eem.2019.8916334

Cited by 5 publications

(4 citation statements)

References 11 publications

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“…If residual grid mix data is available in real time, the current consumption-based carbon intensity estimation algorithms [1,4,8,21,23,24,[34][35][36] can be modified to incorporate PPAs and estimate 𝐶𝐼 𝑟𝑒𝑠 in real time. In that scenario, current online optimization algorithms will work without any modifications and report the true carbon reductions without any discrepancies, provided everyone follows 𝐶𝐼 𝑚𝑏 to evaluate their respective carbon footprint.…”

Section: Discussion and Future Workmentioning

confidence: 99%

The Green Mirage: Impact of Location- and Market-based Carbon Intensity Estimation on Carbon Optimization Efficacy

Maji,

Bashir,

Irwin

et al. 2024

The 15th ACM International Conference on Future and Sustainable Energy Systems

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In recent years, there has been an increased emphasis on reducing the carbon emissions from electricity consumption. Many organizations have set ambitious targets to reduce the carbon footprint of their operations as a part of their sustainability goals. The carbon footprint of any consumer of electricity is computed as the product of the total energy consumption and the carbon intensity of electricity. Third-party carbon information services provide information on carbon intensity across regions that consumers can leverage to modulate their energy consumption patterns to reduce their overall carbon footprint. In addition, to accelerate their decarbonization process, large electricity consumers increasingly acquire power purchase agreements (PPAs) from renewable power plants to obtain renewable energy credits that offset their "brown" energy consumption.There are primarily two methods for attributing carbon-free energy, or renewable energy credits, to electricity consumers: locationbased and market-based. These two methods yield significantly different carbon intensity values for various consumers. As there is a lack of consensus which method to use for carbon-free attribution, a concurrent application of both approaches is observed in practice. In this paper, we show that such concurrent applications can cause discrepancies in the carbon savings reported by carbon optimization techniques. Our analysis across three state-of-the-art carbon optimization techniques shows possible overestimation of up to 55.1% in the carbon reductions reported by the consumers and even increased emissions for consumers in some cases. We also find that carbon optimization techniques make different decisions under the market-based method and location-based method, and the market-based method can yield up to 28.2% less carbon savings than those claimed by the location-based method for consumers without PPAs. CCS CONCEPTS• General and reference → Estimation; Metrics; • Hardware → Impact on the environment.

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Section: Discussion and Future Workmentioning

confidence: 99%

The Green Mirage: Impact of Location- and Market-based Carbon Intensity Estimation on Carbon Optimization Efficacy

Maji,

Bashir,

Irwin

et al. 2024

The 15th ACM International Conference on Future and Sustainable Energy Systems

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“…It follows, that for net exporting countries the demand is only associated with internal generation, whereas the generation from net importing countries does not affect the composition of the demand in downstream countries. This type of coupling for instance has been used in [14], [19].…”

Section: Methodsmentioning

confidence: 99%

“…tion, load or cross-border flows published by ENTSO-E (for instance in [11]) or in other reports (for instance in [12]) might differ from aggregated hourly values due to ex-post consolidation taking into account other statistical resources [13], [14].…”

Section: Datamentioning

confidence: 99%

Tracing carbon dioxide emissions in the European electricity markets

Schäfer¹,

Tranberg²,

Jones³

et al. 2020

Preprint

Self Cite

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Consumption-based carbon emission measures aim to account for emissions associated with power transmission from distant regions, as opposed to measures which only consider local power generation. Outlining key differences between two different methodological variants of this approach, we report results on consumption-based emission intensities of power generation for European countries from 2016 to 2019. We find that in particular for well connected smaller countries, the consideration of imports has a significant impact on the attributed emissions. For these countries, implicit methodological choices in the inputoutput model are reflected in both hourly and average yearly emission measures.

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“…The co-variability of power production from renewable sources in different areas has usually been studied with a focus on the complementarity between wind and solar [17][18][19][20][21]. Similar assessments extended to power systems operations are, however, not common [22]. Regarding weather patterns, we link the operations of European power systems to a set of specific large-scale weather conditions, using the patterns identified in [23] and applied in successive works [24][25][26][27].…”

Section: Introductionmentioning

confidence: 99%

Climate variability on Fit for 55 European power systems

De Felice,

Koolen,

Kanellopoulos

et al. 2023

PLoS ONE

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The use of variable renewable energy sources to generate electricity introduces a dependency on meteorological factors into power systems. With the renewables share growing globally, often driven by political pressures, the reliability and efficiency of power systems are increasingly affected by this dependency. In this paper, we investigate the impact of the natural variability of meteorological parameters on the European power system in 2030. We specifically focus on (1) analysing the main European weather patterns affecting renewable energy production and (2) understanding the co-variability of this production among European countries. The identification of a set of patterns in the behaviour of key power system operation indicators allows us to analyse the relationship between large-scale weather regimes and daily power system operations in a 2030 European energy context. Regarding renewable generation, analysis of the co-variability shows that European power systems tend to form two clusters, in each of which all the regions tend to show a positive correlation among themselves and a negative correlation with the other cluster. Our analysis of the most important large-scale weather regimes shows that during cyclonic patterns, the carbon intensity of all the European power systems is lower than normal, while the opposite happens during blocking regimes.

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Principal Cross-Border Flow Patterns in the European Electricity Markets

Cited by 5 publications

References 11 publications

The Green Mirage: Impact of Location- and Market-based Carbon Intensity Estimation on Carbon Optimization Efficacy

The Green Mirage: Impact of Location- and Market-based Carbon Intensity Estimation on Carbon Optimization Efficacy

Tracing carbon dioxide emissions in the European electricity markets

Climate variability on Fit for 55 European power systems

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