Identifying Topology of Power Distribution Networks Based on Smart Meter Data

2016/09/09 by Jayadev P Satya, Nirav Bhatt, Satya, Jayadev P +6
Engineering · Physics and Astronomy · #Complex Network Analysis Techniques #FOS: Computer and information sciences #FOS: Electrical engineering #Machine Learning (cs.LG) #Optimal Power Flow Distribution #Power Quality and Harmonics #Smart Grid Energy Management #Smart Grid Security and Resilience #Systems and Control (eess.SY) #electronic engineering #information engineering

paper · pdf · doi:10.48550/arxiv.1609.02678

openalex publication_date 2016/09/09 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01

Abstract

In a power distribution network, the network topology information is essential for an efficient operation of the network. This information of network connectivity is not accurately available, at the low voltage level, due to uninformed changes that happen from time to time. In this paper, we propose a novel data--driven approach to identify the underlying network topology including the load phase connectivity from time series of energy measurements. The proposed method involves the application of Principal Component Analysis (PCA) and its graph-theoretic interpretation to infer the topology from smart meter energy measurements. The method is demonstrated through simulation on randomly generated networks and also on IEEE recognized Roy Billinton distribution test system.

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