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

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.