Efficient detection of faults and false data injection attacks in smart grid using a reconfigurable Kalman filter

Prakyath Dayananda (SJB Institute of Technology)
Mallikarjunaswamy Srikantaswamy (JSS Academy of Technical Education)
Sharmila Nagaraju (Sri Jayachamarajendra College of Engineering)
Rekha Velluri (CHRIST (Deemed to be University))
Doddananjedevaru Mahesh Kumar (JSS Academy of Technical Education)

International Journal of Power Electronics and Drive Systems (IJPEDS)
Vol 13, No 4: December 2022

The distribution denial of service (DDoS) attack, fault data injection attack (FDIA) and random attack is reduced. The monitoring and security of smart grid systems are improved using reconfigurable Kalman filter. Methods: A sinusoidal voltage signal with random Gaussian noise is applied to the Reconfigurable Euclidean detector (RED) evaluator. The MATLAB function randn() has been used to produce sequence distribution channel noise with mean value zero to analysed the amplitude variation with respect to evolution state variable. The detector noise rate is analysed with respect to threshold. The detection rate of various attacks such as DDOS, Random and false data injection attacks is also analysed. The proposed mathematical model is effectively reconstructed to frame the original sinusoidal signal from the evaluator state variable using reconfigurable Euclidean detectors.