Islanding Event Detection in Grid-Connected Distributed Generation Systems Using Unscented Kalman Filter

Table 6

Advantages of the unscented Kalman filter (UKF) and its distinction over DWT.

Features/attributes	Unscented Kalman filter (UKF)	Discrete wavelet transform (DWT)
Nonlinear system representation	Handles nonlinear systems without the need for linearization	Works mainly on signal decomposition; may not efficiently handle nonlinearity
Noise robustness	Highly proficient in noisy environments	More sensitive to noise, especially at high decomposition levels
Real-time processing	Ideal for real-time applications due to its recursive nature	Might not be as swift for real-time updates
State estimation	Provides state estimation, capturing underlying system dynamics	Decomposes the signal into frequency components without inherent state estimation
Harmonic analysis	Tailored to track specific harmonic components	Captures signal details across scales but does not target specific harmonics
Flexibility and adaptability	Adapts based on uncertainties, dynamic, and responsive	Depends on the choice of mother wavelet; lacks the dynamic adaptability of UKF
Systematic design procedures	Follows systematic procedure	A success might depend on the choice of mother wavelet and decomposition level