A Fuzzy Logic Based Approach to Priority Determination for Smart Distribution Substations

Germany's goal of climate neutrality by 2045 leads among others to an increase of electrical load and generation capacities in low voltage grids as well as need for grid expansion. Smart secondary substations can provide real-time measurements for low voltage state estimation, supporting applications like grid-oriented control (§14a EnWG) and deferring of grid expansion. To achieve widespread deployment of smart distribution substations in the coming years with limited resources, prioritizing is essential. This paper presents a fuzzy logic based methodology for determining priority values for distribution substations, with only little input data. The rule-based Fuzzy system ensures transparency, traceability and is suitable for large-scale datasets. The approach is demonstrated using exemplary real-world grid data.

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Published
2025-06-29
DOI
https://doi.org/10.1109/powertech59965.2025.11180606
Primary Topic
Power Systems and Technologies
Type
article
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A Fuzzy Logic Based Approach to Priority Determination for Smart Distribution Substations

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article

A Fuzzy Logic Based Approach to Priority Determination for Smart Distribution Substations

F. Wirtz, David Echternacht, Stefan Dorendorf, M. Wilch, Marius Wienand, Eileen Trunczik
article en

Abstract

Germany's goal of climate neutrality by 2045 leads among others to an increase of electrical load and generation capacities in low voltage grids as well as need for grid expansion. Smart secondary substations can provide real-time measurements for low voltage state estimation, supporting applications like grid-oriented control (§14a EnWG) and deferring of grid expansion. To achieve widespread deployment of smart distribution substations in the coming years with limited resources, prioritizing is essential. This paper presents a fuzzy logic based methodology for determining priority values for distribution substations, with only little input data. The rule-based Fuzzy system ensures transparency, traceability and is suitable for large-scale datasets. The approach is demonstrated using exemplary real-world grid data.

Beiersdorf (Germany) (DE), GKN (Germany) (DE), Synovo (Germany) (DE), West German Heart and Vascular Center Essen (DE), Bavarian Center for Applied Energy Research (DE)
Openalex Percentile: Top 72%
Power Systems and Technologies
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