The assessment of changes in technology or load behaviors on distribution networks requires a rigorous understanding of the features of the network itself. In a typical distribution network, there will be hundreds of high voltage (HV) feeders and ten thousands of low voltage (LV) feeders. This work uses cluster analysis to identify statistically representative or prototypical HV feeders in the West Australian context. The representative HV feeder data will be used as an input to the development of Monte Carlo models to assess the impact of technology changes driven by Smart Grid deployments or load changes due to solar panel, air conditioning or electric vehicleuptake.