This study investigates the impact of electrical parameter variation of a high‐frequency transformer model on its sweep frequency response analysis (SFRA) signature to help in classification and interpretation. The simulations have been done using MATLAB and compared with the reference data. The results of SFRA measurements are repeatable up to and beyond 1MHz. The proposed diagnostic methodology using the Cross‐Correlation Coefficient Factor (CCF) is used to identify the transformer faults. CCF used to measure the degree of relationship between two variables that establish a relation between the predicted and actual data set. The results of this proposed methodology using the CCF compared with existing Chinese Standard factor (CSF) indicate that, the proposed method is valid to identify the transformer faults. Characteristics of the proposed scheme are fully analyzed by extensive MATLAB simulation studies that clearly reveal that this method can accurately identify the transformer faults compared with CSF. And also does not affected by different fault conditions such as transformer normal condition, Turn to Turn Fault for both HV, LV sides, Axial Fault and/or Radial Faults on both sides, Short Circuit Fault between H.V and L.V Sides, Short Circuit to Ground Fault for both HV, LV sides.

The general aim of this paper is to develop an accurate fault-location scheme that can solve the problems affecting the accuracy of the existing conventional fault locators achieving easier maintenance and restoration time reduction as well as economical aims. This consequently helps to fit the new deregulation policies and competitive marketing. This investigation successfully applies zero-sequence current (3I ₀) from the two terminals for earth high impedance fault (HIF) location, or negative-sequence currents from the two terminals of one faulted phase for line-to-line fault location. The HIF location is determined within only a maximum time of one cycle. The proposed scheme is insensitive to variations of different parameters, such as fault type, HIF behavior, wide-range transmission-line parameters variation, and fault inception angle. Staged fault testing results demonstrate that the proposed algorithm has feasible performance.

AFPMSM is lighter, has a higher power-to-weight ratio, is shorter in length, is less expensive, and has a higher efficiency than the radial flux motor. Then AFPMSM is more suitable for driving the EV than radial flux motor. The proposed technique in this paper is the sensorless-based SVPWM-DTC of AFPMSM to drive electric vehicles. Sensorless research becomes more important in this circumstance since the axial motor can be placed inside the vehicle tire due to its condensed size and shape similar to the tires. DTC provides less fluctuation for the driver during driving for safety and comfort. SVPWM is preferred for its high performance. When measuring speed using a sensorless estimator, sensor inaccuracy is minimized, and the AFPMS motor can be mounted inside the tire. The control system is tested using two EVs driving cycles, and the results promise high performance. NEDC and HWFET driving cycles are used to test the proposed control scheme in 100 times less than the actual driving cycles’ time to test the coherence of the sensorless estimator. The results demonstrate that the proposed technique is valid for real-time applications with high-performance, minimum torque fluctuations, and minimum transient and steady-state errors.

The optimal sizing of a hybrid energy system may be a difficult undertaking problem because of the huge number of structure settings and the irregular nature of solar radiation and wind power sources. This issue has a place with the classification of combinatorial enhancement, and its solution dependent on the classical technique may be a waste of time. In the present paper, the generation cost of isolated PV‐wind by bird system is minimized by increasing the capacity factor of the system by adjusting both of PV‐tilt angle and wind turbine hub height such that the average generated power is as near as possible to the generation peak. By considering the PV‐tilt angle and the turbine hub height, the diversity between the two generation patterns increases resulting in lower cost. The objective of the present paper is to find the optimal design of the PV‐wind hybrid system based on minimum cost criterion using a genetic algorithm. Also, it studies the effect of considering the PV‐tilt angle and wind turbine hub height as design parameters for different diversity levels of wind speed and sun irradiance patterns.

High impedance faults (HIFs) are difficult to detect by overcurrent protection relays. This paper presents an ATP/EMTP fault simulations studies based algorithm for high impedance fault detection in extra high voltage transmission line. The scheme recognizes the distortion of the voltage waveforms caused by the arcs usually associated with HIF. The discrete wavelet transform (DWT) based analysis, yields three phase voltage in the high frequency range which are fed to a classifier for pattern recognition. The classifier is based on an algorithm that uses recursive method to sum the absolute values of the high frequency signal generated over one cycle and shifting one sample. A HIF model of distribution is modified for EHV transmission lines. Characteristics of the proposed fault detection scheme are analyzed by extensive simulation studies that clearly reveal that the proposed method can accurately detect HIFs in the EHV transmission lines.