Real-time Power System Topology Recognition through Convolutional Neural Networks

Abstract

This paper investigates the status of a transmission line (on/off) using a 140-bus Northeast Power Coordinating Council (NPCC) test system model [1]. The application of the software package ANDES [2] to obtain a database when solving this problem in the transient process of the power system is considered. The Deep Learning Neural Networks (DLNN) [3] were proposed to solve the problem, in particular, a convolutional neural network (CNN), the input variables of which are voltage and current phasors obtained from phasor measurement units (PMU). Calculations to determine the state of lines were performed using a program developed in the Julia language using the Flux package (a machine learning library that includes functions for creating CNN models). The results of the studies are presented.