Uncovering Contributing Factors to Interruptions in the Power Grid: An Arctic Case

Odin Foldvik Eikeland, Filippo Maria Bianchi, Inga Setså Holmstrand, Sigurd Bakkejord, Sergio Santos and Matteo Chiesa
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Odin Foldvik Eikeland: Department of Physics and Technology, UiT the Arctic University of Norway, 9037 Tromso, Norway
Filippo Maria Bianchi: Department of Mathematics and Statistics, UiT the Arctic University of Norway, 9037 Tromso, Norway
Inga Setså Holmstrand: Distribution System Operator Arva, 9024 Tromso, Norway
Sigurd Bakkejord: Distribution System Operator Arva, 9024 Tromso, Norway
Sergio Santos: Department of Physics and Technology, UiT the Arctic University of Norway, 9037 Tromso, Norway
Matteo Chiesa: Department of Physics and Technology, UiT the Arctic University of Norway, 9037 Tromso, Norway

Energies, 2022, vol. 15, issue 1, 1-21

Abstract: Electric failures are a problem for customers and grid operators. Identifying causes and localizing the source of failures in the grid is critical. Here, we focus on a specific power grid in the Arctic region of Northern Norway. First, we collected data pertaining to the grid topology, the topography of the area, the historical meteorological data, and the historical energy consumption/production data. Then, we exploited statistical and machine-learning techniques to predict the occurrence of failures. The classification models achieve good performance, meaning that there is a significant relationship between the collected variables and fault occurrence. Thus, we interpreted the variables that mostly explain the classification results to be the main driving factors of power interruption. Wind speed of gust and local industry activity are found to be the main controlling parameters in explaining the power failure occurrences. The result could provide important information to the distribution system operator for implementing strategies to prevent and mitigate incoming failures.

Keywords: energy analytics; machine learning; anomaly detection; power interruptions; unbalanced classification (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: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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