Reactive Load Control of Parallel Transformer Operations Using Neural Networks

Abstract

Artificial Neural Network (ANN) is used in various fields including control and analysis of power systems. ANN in its learning process establishes the relationship between input variables by means of its weights updating, and provides a good response to another nonidentical but similar input. This paper proposes the use of neural network to control the on-load tap changer of parallel operation of two transformers supplying power to a local area. For simplicity, only two transformers are considered although operation of multiple transformers can be dealt with in a similar manner. A synthetic data set relating to tap changer operation sequence was used for training a backpropagation network to decide automatically on transformer’s on-load tap changer whether to raise, lower or hold the same desired position. Preliminary results show that a trained neural network can be successfully used for on load tap changing operation of transformers.