Categorizing Finnish distribution system operators by combined geographic data and K-means clustering

This study introduces a methodology for categorizing Finnish electricity distribution system operators (DSOs) using geographic spatial data. By employing geographic spatial data and k-means clustering, the study provides a rapid and unbiased method for categorization. The k-means clustering method grouped DSOs into seven categories, revealing more nuanced classifications beyond the traditional three classes. The results are coherent with earlier studies and suggest that geographic spatial data can effectively enable further studies and regulatory applications by bridging datasets from different publishers based on spatial data. Essential for further studies are internal variations within DSOs' operating environments for targeted network business regulation.

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Publication Details

Journal
IET conference proceedings.
Published
2025-10-14
DOI
https://doi.org/10.1049/icp.2025.1513
Primary Topic
Human Mobility and Location-Based Analysis
Type
article
Field-Weighted Citation Impact
0.00
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article

Categorizing Finnish distribution system operators by combined geographic data and K-means clustering

Joonas Kari, Joel Seppälä, Pertti Järventausta
IET conference proceedings.
Human Mobility and Location-Based Analysis
article

Categorizing Finnish distribution system operators by combined geographic data and K-means clustering

Joonas Kari, Joel Seppälä, Pertti Järventausta
article en

Abstract

This study introduces a methodology for categorizing Finnish electricity distribution system operators (DSOs) using geographic spatial data. By employing geographic spatial data and k-means clustering, the study provides a rapid and unbiased method for categorization. The k-means clustering method grouped DSOs into seven categories, revealing more nuanced classifications beyond the traditional three classes. The results are coherent with earlier studies and suggest that geographic spatial data can effectively enable further studies and regulatory applications by bridging datasets from different publishers based on spatial data. Essential for further studies are internal variations within DSOs' operating environments for targeted network business regulation.

IET conference proceedings.Vol. 2025(14)
Tampere University (FI), Radiation and Nuclear Safety Authority (FI)
Openalex Percentile: Top 71%
Human Mobility and Location-Based Analysis
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