Topology Identification Method for Primary Distribution Network with Limited Smart Meter Data

Abstract

The distribution networks are continuously undergoing structural changes caused by several factors, such as, the increase in connection of distributed energy resources to the network, which entail that the network operators make several adjustments to the structure of the network topology in order to improve its reliability. This paper presents a topology identification method for primary distribution network based on available limited data from transformers smart meters and feeder data for analysis. The method also aims to identify and correct any connectivity errors in the topology network. K-means clustering method is used as a correcting technique, to assign the uncertain or faulty connected distribution transformers to the most likely correct feeders. The proposed method is tested on a distribution network and the results show that the method is effective in correctly identifying the connection of distribution transformers on the feeders in the network. The technique can further be developed and be implemented by utility companies to update changes or correct errors in topology networks and enhance the operation of the networks.