Phase Identification of Smart Meters by Clustering Voltage Measurements

When a smart meter, be it single-phase or three-phase, is connected to a three-phase network, the phase(s) to which it is connected is (are) initially not known. This means that each of its measurements is not uniquely associated with a phase of the distribution network. This phase information is important because it can be used by Distribution System Operators to take actions in order to have a network that is more balanced. In this work, the correlation between the voltage measurements of the smart meters is used to identify the phases. To do so, the constrained k-means clustering method is first introduced as a reference, as it has been previously used for phase identification. A novel, automatic and effective method is then proposed to overcome the main drawback of the constrained k-means clustering, and improve the quality of the clustering. Indeed, it takes into account the underlying structure of the low-voltage distribution networks beneath the voltage measurements without a priori knowledge on the topology of the network. Both methods are analysed with real measurements from a distribution network in Belgium. The proposed algorithm shows superior performance in different settings, e.g. when the ratio of single-phase over three-phase meters in the network is high, when the period over which the voltages are averaged is longer than one minute, etc.