In the second half of 2021 - the first half of 2023, the EU electricity markets were under unprecedented pressure caused by soaring gas prices and aggravated by other fundamental factors. This period corresponds to the energy crisis in the EU electric power sector. However, all EU electricity markets responded to the energy crisis differently. This paper proposes a methodology for revealing the energy crisis in the electricity market, which is based on the tools of descriptive statistics, explanatory data analysis and k-means clustering which allows to identification duration and phases of the energy crisis such as escalation, peak, and recovery phases. Using this methodology, the energy crisis was identified in the EU electricity markets (by separate bidding zones), and as a result, the starting and ending points of the energy crisis, as well as the changing by phases, were determined. Additionally, the use of hierarchical and agglomerative clustering methods made it possible to divide all EU electricity markets into 9 clusters by the evolution of the energy crisis and identify unaffected, resilient vulnerable markets to the energy crisis, and markets with their own dynamics.

Identification of the energy crisis in the EU electricity markets

Salashenko, Tetiana
;
Rubino, Alessandro;Khaustova, Viktoriia;Lippolis, Stella;Ilyash, Olha;Capozza, Claudia
2023-01-01

Abstract

In the second half of 2021 - the first half of 2023, the EU electricity markets were under unprecedented pressure caused by soaring gas prices and aggravated by other fundamental factors. This period corresponds to the energy crisis in the EU electric power sector. However, all EU electricity markets responded to the energy crisis differently. This paper proposes a methodology for revealing the energy crisis in the electricity market, which is based on the tools of descriptive statistics, explanatory data analysis and k-means clustering which allows to identification duration and phases of the energy crisis such as escalation, peak, and recovery phases. Using this methodology, the energy crisis was identified in the EU electricity markets (by separate bidding zones), and as a result, the starting and ending points of the energy crisis, as well as the changing by phases, were determined. Additionally, the use of hierarchical and agglomerative clustering methods made it possible to divide all EU electricity markets into 9 clusters by the evolution of the energy crisis and identify unaffected, resilient vulnerable markets to the energy crisis, and markets with their own dynamics.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11586/492580
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