## 7 Recently Proposed Intelligent Techniques for Power Systems
### Wavelet Transformation  
Fourier transform (FT) was employed to analyze faults in transmission lines, although it has drawbacks such as fixed resolution and frequency localization. Wavelet transform has lately become a potent technique for removing crucial information from voltage and current signals for transmission line relaying. It can get over the restrictions of FT. Wavelets are mathematical operations used to create a model for a nonstationary signal with several tiny wavelike components. Wavelet transform and its use in the power system are discussed in [121]. Wavelets are time- and frequency-localized by dilation (through translation). Wavelet transform offers a quick and efficient method for examining nonstationary voltage and current waveforms. It is also ideally suited for irregular wideband signals and may contain both sinusoidal and impulsive transients. It may be used to quickly and precisely find defects in parallel transmission lines. [PERSON] et al. [136] compare the discrete wavelet transform (DWT) and discrete Fourier transform (DFT) for locating and categorizing transmission line problems. The authors utilized Matlab simulation to compare DFT with DWT, and the findings reveal that the DWT approach performs better for fault classification and for determining the location of faults when more than one phase is involved in the fault, while in the instance of a line-to-ground fault, the DFT technique performs better at predicting the location of faults. In order to locate faults in transmission lines, ref. [137] presented an approach based on wavelet transform. For this aim, wavelet transform analyzes fault-generated traveling waves to expose their journey periods between the fault and the relay sites. Wavelet transform was introduced by [138], and an online application for power system relaying was suggested. It can use a tiny data window to isolate the impulse and high-frequency components and extract the fundamental frequency component. Ref. [139] suggested a method based on wavelet transform for transmission line distance protection. In order to identify flaws, the observed current signals were first decomposed using a db1 wavelet, and the norm of the detail coefficients (D1) for each current was determined. When a norm value exceeds a predetermined threshold, there is a disturbance in that phase. Wavelet transform-based digital transmission system protection and wavelet MRA-based fault diagnostics have been proposed by [140; 141]. Wavelet transforms and first-level high-frequency information of currents and voltages were employed to extract features from the fault transients. Single faulty phase current information from both ends was utilized to locate faults, and local terminal information was used for categorization. To protect transmission lines using series compensation, wavelet transform was proposed by [127]. To identify fault zones, the scientists employed db4 (Daubechies) mother wavelets, and to classify faults, they used Harr. The simulation results demonstrate that the suggested approach has a very high accuracy in fault detection, zone identification, and faulty phase identification. Faults of various sorts, conditions, and locations have been tested. [PERSON] et al. [142] suggested a wavelet-based method for locating, classifying, and detecting faults in transmission lines. The scientists sampled a line's three-phase voltage and current data using a global positioning system with synchronizing clocks at both ends. The three-phase voltages and currents of the local terminal are decomposed with the help of the Biot4.4 mother wavelet for location ANN, which is utilized for defect detection, classification, and estimate. To detect high impedance problems in an EHV transmission line, [PERSON]. [143] presented a discrete wavelet-transformed approach.