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An Optimization Algorithm for Customer Topological Paths Identification in Electrical Distribution Networks

Maurizio Vassallo, Adrien Leerschool, Alireza Bahmanyar, Laurine Duchesne, Simon Gerard, Thomas Wehenkel, Damien Ernst

TL;DR

Results show that the method effectively addresses data inaccuracies and successfully identifies customer topological paths, providing a valuable tool for DSOs in developing accurate digital twins of their distribution networks.

Abstract

A customer topological path represents the sequence of network elements connecting an MV/LV transformer to a customer. Accurate knowledge of these paths is crucial for distribution system operators (DSOs) in digitalization, analysis, and network planning. This paper introduces an innovative approach to address the challenge of customer topological path identification (TPI) using only the limited and often inaccurate data available to DSOs. Specifically, our method relies only on geographic information system (GIS) data of network elements and the customer to MV/LV transformers connection information. We introduce an integer linear programming (ILP) optimization algorithm designed to identify customer topological paths that closely approximate the real electricity paths. The effectiveness of the proposed approach is demonstrated through its application to both an academic and a real-world electrical distribution network. Results show that the method effectively addresses data inaccuracies and successfully identifies customer topological paths, providing a valuable tool for DSOs in developing accurate digital twins of their distribution networks.

An Optimization Algorithm for Customer Topological Paths Identification in Electrical Distribution Networks

TL;DR

Results show that the method effectively addresses data inaccuracies and successfully identifies customer topological paths, providing a valuable tool for DSOs in developing accurate digital twins of their distribution networks.

Abstract

A customer topological path represents the sequence of network elements connecting an MV/LV transformer to a customer. Accurate knowledge of these paths is crucial for distribution system operators (DSOs) in digitalization, analysis, and network planning. This paper introduces an innovative approach to address the challenge of customer topological path identification (TPI) using only the limited and often inaccurate data available to DSOs. Specifically, our method relies only on geographic information system (GIS) data of network elements and the customer to MV/LV transformers connection information. We introduce an integer linear programming (ILP) optimization algorithm designed to identify customer topological paths that closely approximate the real electricity paths. The effectiveness of the proposed approach is demonstrated through its application to both an academic and a real-world electrical distribution network. Results show that the method effectively addresses data inaccuracies and successfully identifies customer topological paths, providing a valuable tool for DSOs in developing accurate digital twins of their distribution networks.
Paper Structure (41 sections, 21 equations, 5 figures, 1 table)

This paper contains 41 sections, 21 equations, 5 figures, 1 table.

Figures (5)

  • Figure 1: Visualization of the different sets of paths.
  • Figure 2: Representation of the different sets and their relationships.
  • Figure 3: Flowchart of the steps proposed by our methodology, $\mathfrak{M}()$, to identify the customer topological paths in electrical distribution networks.
  • Figure 4: Illustration of the process of identifying customer paths in the academic network considered.
  • Figure 5: Part of the real network considered.