Performance of SMES unit on Artificial Neural Network based Multi-area AGC scheme

Abstract

This work investigates the performance of Superconducting Magnetic Energy Storage (SMES) unit on Artificial Neural Network (ANN) based multi-area AGC scheme. SMES units have been used to the power systems to inject or absorb active power. A three layer feed forward neural network (NN) is proposed for controller design and trained with Back propagation algorithm (BPA). The poolco based transaction can be implemented by optimizing the bids (price & capacity) submitted by the generating companies (Gencos) and distribution companies (Discos). The functioning of the proposed ANN based controller has been demonstrated on a two-area System.