Adapting distance relay using artificial neural networks

Abstract EN

A universal distance relay that has merits over conventional relays is designed.

This relay has the ability to adapt more than one working characteristic by using an artificial neural networks technique(ANN)of the type Modified Multi-Layer Perceptron (MMLP) which uses additional nodes at the input layer to realize an adaptation through the required modifications on the distance relay characteristics.

The inputs of the added nodes referred to the factors that affect the distance relay characteristic such as: fault resistance, power transfer, mutual inductance and locations of feeding sources in the system.

A Matlab computer programming was used to simulate different power systems of (400, 132) KV to obtain impedance characteristic data, needed to train and test the ANN.

A laboratory power system (220V) has been operated as a computer simulation model and practically under the same conditions.

The designed universal relay gives good performance when tested on a computer model of this system.

The small difference between the practical results and that of simulation, encourage the use of designed relay to protect transmission lines in reality.