Transient stability enhancement of power grid by neural network controlled BFCL considering cyber-attacks
In this paper, a neural network predictive controlled bridge type fault current limiter (FCL) is proposed to enhance the transient stability of power systems. Cyber security issues on the performance of neural network controller is also investigated. It is noteworthy that simulations have been conducted by the Matlab/Simulink software. Both symmetrical and unsymmetrical types of permanent and temporary faults have been considered at different locations of a multi-machine power system. Based on the simulation results, it can be concluded that the bridge type FCL based on neural network predictive controller can enhance the transient stability of the system well. Moreover, the cyber-attack has profound effect on the controller performance and the system becomes fully unstable even with the presence of the neural network predictive controlled bridge type FCL.
Conference Proceedings - IEEE SOUTHEASTCON
Sadi, M., Zheng, H., & Ali, M. (2017). Transient stability enhancement of power grid by neural network controlled BFCL considering cyber-attacks. Conference Proceedings - IEEE SOUTHEASTCON https://doi.org/10.1109/SECON.2017.7925395