A MILP Model for Phase Identification in LV Distribution Feeders Using Smart Meters Data

Abstract

Nowadays, with the increasing use of renewable energies in low voltage (LV) feeders, phase balancing research areas are of great importance. However, the lack of information about the hosting phase of customers and renewable sources is the missing link in such researches. To address this barrier, this paper proposes a mixed integer linear programming (MILP) method to identify the hosting phase of customers as well as renewable energies, such as photovoltaic (PV) panels. The model considers potential error in the input data. To overcome the complexity caused by data error, the input data in several time intervals are taken into account by the model. The model solves the phase identification problem through minimizing mean absolute error between estimated and measured parameters. The performance of the proposed method is tested on the IEEE 34-node test feeder and results are discussed thoroughly.