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

TL;DR

This paper presents an ILP-based optimization algorithm that accurately identifies customer topological paths in electrical distribution networks using limited GIS data, aiding DSOs in digitalization and network planning.

Contribution

The paper introduces a novel ILP optimization method for customer path identification that effectively handles data inaccuracies using only GIS and connection data.

Findings

Successfully applied to academic and real-world networks

Effectively addresses data inaccuracies in path identification

Provides a valuable tool for digital twin development

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.