An artificial neural network based power swing classification technique

Abstract

For reliable operation of power system protective relays, it is very important to distinguish between a fault, a stable power swing (power swing with decaying magnitude) and an unstable power swing (power swing with increasing magnitude). The traditional power swing detection schemes used in distance relay operation are not efficient enough in most cases. This paper proposes an artificial neural network (ANN) based scheme for power swing detection and classification. A simple 2 generator 4 feeder system was considered for simulations and the impedance loci for different fault conditions and swings were plotted. PSCAD-EMTDC power system simulation platform was used for this part. ANN based swing detection and classification systems using Learning Vector Quantization and Probabilistic Neural Network algorithm was designed in MATLAB environment with the simulation data. Experimental results establish that the proposed system can classify different faults and swings accurately. Thus, if incorporated within a smart energy management system,this system can be of great use for reliable and accurate operation of protective relays, even under power swing condition.