Power flow matching-based topology identification of medium-voltage distribution networks via AMI measurements

Abstract

Topologies of medium-voltage distribution networks change frequently during normal operation to reduce line losses, handle outages, and accept more intermittent distribution generators. However, topologies generated by telecommunicating information are not credible enough for various reasons. This paper proposes a power flow matching-based topology identification methodology for radial medium-voltage distribution networks that are structurally loopy but operationally radial using only measurements from the advanced metering infrastructure. In the first stage, a mixed-integer quadratic programming model is formulated to obtain an initial radial network topology. Then in the second stage, using this initial topology as the reference tree, a spanning tree generation algorithm is adopted to locally search its neighboring spanning trees, on each of which power flow is executed using power injection measurements as loads. The spanning tree with the best matching performance between estimated and measured voltage magnitudes is selected as the final network topology. During the local search process, spanning trees are ranked according to their matching indices and those that show a bad matching performance are pruned to reduce computation costs. The effectiveness of the proposed methodology is tested using the 33-bus distribution network and an 80-bus realistic distribution network in China with promising results.