A novel power swing detection algorithm using adaptive neuro fuzzy technique

Progress on power swing blocking schemes and the impact of renewable energy on power swing characteristics: A review

“…The authors concluded that the method was able to detect the feature as in [63]. In addition, this method [61] is not be affected by factors such as system parameters, fault inception time, fault position, and pre fault load flow condition.…”

“…ANFIS is an enhanced version of FLS with extraordinary features such as, generalization capability, noise immunity, robustness, and fault tolerance [61][62][63].…”

“…On the other hand, Esmaeilian et.al in [61] presented another algorithm using ANFIS. Here, the authors used three inputs which are the rate of change of currents (positive and negative sequence), normalized active power, and normalized reactive power.…”

Fault‐swing discrimination using Hilbert–Huang transform integrated discrete teager energy operator

“…Meanwhile, a fault during swing condition is more important to identify and respond in order to maintain the healthiness of the system. To perform this task, several techniques have been reported in the literature [3–15].…”

“…In the literature, the multiresolution analysis‐based techniques such as discrete wavelet transform (DWT) [9] and wavelet singular entropy [10] are also used for fault detection and out‐of‐step protection. In this context, training‐based approaches such as adaptive fuzzy neural inference system (ANFIS) [11], data mining‐based technique [12], differential power‐based approach [13], Taylor series‐based technique [14], and phase space‐based technique [15] are also used and reported. Recently, in [16], the authors have used Teager Kaiser energy operators (TKEO) of zero sequence voltage and negative sequence current to discriminate fault situation from swing situation.…”