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Reduction of the Market Splitting Occurrences: A Dynamic Line Rating Approach for the 2030 Iberian Day-ahead Market Scenarios

Authors: Algarvio, Hugo; Couto, António; Estanqueiro, Ana; Carvalho, Rui; Santos, Gabriel; Faia, Ricardo; Faria, Pedro; +1 Authors

Reduction of the Market Splitting Occurrences: A Dynamic Line Rating Approach for the 2030 Iberian Day-ahead Market Scenarios

Abstract

This article focused on a methodology to detect the impact of using Dynamic Line Rating (DLR) in the Iberian market with high penetrations of variable renewable generations (in 2030). Aligned with previous studies, this research identified that DLR increases transmission capacity by an average of 30% over the Seasonal Line Rating (SLR) approach. However, for around 3% of the time, the DLR capacity is below limits set by the Transmission System Operator (TSO), potentially causing line saturation, degradation, or even damage in severe cases. The study’s findings reveal that integrating DLR into cross-border capacities reduces the frequency of market splitting events in the Day-Ahead Market (DAM) from 1,512 to 514, enhancing price consistency. This shift also lowers price disparities from €19/MWh (SLR approach) to €12/MWh (DLR approach) in these events, resulting in an overall reduction of more than 1% in wholesale electricity prices. Adopting DLR could be instrumental in reaching the 2030 renewable energy goals. In the long term, it may reduce the need for new transmission line development, while in the short term, DLR can help prevent grid congestion, reduce market splitting, and limit curtailment of renewable generation.

Country
Portugal
Keywords

Dynamic models, Europe, Electricity, Computational modeling

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
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