A Novel Smart Grid State Estimation Method Based on Neural Networks - Abdel-Nasser, Mohamed; Mahmoud, Karar; Kashef, Heba (International Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI), 2022)
The rapid development in smart grids needs efficient state estimation methods. This paper presents a novel method for smart grid state estimation (e.g., voltages, active and reactive power loss) using artificial neural networks (ANNs). The proposed method which is called SE-NN (state estimation using neural network) can evaluate the state at any point of smart grid systems considering fluctuated loads. To demonstrate the effectiveness of the proposed method, it has been applied on IEEE 33-bus distribution system with different data resolutions. The accuracy of the proposed method is validated by comparing the results with an exact power flow method. The proposed SE-NN method is a very fast tool to estimate voltages and re/active power loss with a high accuracy compared to the traditional methods.
Keywords: renewable energies; neural network; smart grid; power loss; voltage profile; IJIMAI