An Integer Programming-based Phase Identification in Distribution Network

Abstract

In this thesis, the identification of phases in power distribution systems was formulated using Integer Linear Programming (ILP). Unlike previous research focused on the load phase, the identification of phases in feeders requires consideration of the relationships with neighboring nodes, resulting in a total of 6 possible cases. These cases are represented using a permutation matrix. The objective function was set to minimize the sum of two functions. The one is Kirchhoff's Current Law (KCL) to each phase, and the used also similarity between load and current patterns. The constraints are set to ensure that the minimum required current for the load is provided at the node where the load is located. The proposed technique enables the identification of phases not only in feeders but also in loads, and its effectiveness is demonstrated through the performed in the IEEE 123 Test Feeder and modified IEEE 123 test feeder. Furthermore, even with a error, a high accuracy of 100% is achieved. The main contribution proposed a phase identification method that reflects the data measurement environment in Korea using current magnitude and the sum of three-phase active power. also, It can be used in practical environments due to its high accuracy including measurement errors.