Print ISSN: 1681-6900

Online ISSN: 2412-0758

Author : A. Hassan, Fadhil


Artificial Neural Network Control of the Synchronous Generator AVR with Unbalanced Load Operating Conditions

Helen J. Jawad; Fadhil A. Hassan

Engineering and Technology Journal, 2010, Volume 28, Issue 17, Pages 5514-5523

This paper proposes the using of artificial neural networks (ANNs') to
control the synchronous generator automatic voltage regulator (AVR), with unbalance load operating conditions. The neural network for control a nonlinear system is described and used to demonstrate the effectiveness of the neural network for control the drives with nonlinearities. In this study, performances of a simulated neural network AVR evaluated for a wide range of unbalanced loads
operating conditions. The variance factors are calculated, as an indicator of optimum operation, and their values are compared for different feedback signals and various unbalanced operating conditions. The optimum control is introduced, which gives an average variance factor in ANN controller is about 1.105%, whereas the average variance factor in traditional PI controller is about 2.035%.