Shaik, Abdul Gafoor

This paper presents the experimental investigation of power quality (PQ) disturbances associated with the grid integrated wind energy generator. PQ disturbances associated with the grid synchronization and outage of doubly fed induction generator (DFIG) based wind energy generation system have been investigated in the presence of various types of loads. The voltage signal has been captured at point of common coupling (PCC) using the data acquisition system consisting of power quality analyser, laptop, and WT viewer software. The voltage signal has been analysed using MATLAB software to find the PQ disturbances. It has been observed that the PQ disturbances such as voltage fluctuations, flicker, voltage sag, voltage swell and harmonics are associated with the grid synchronization and outage of DFIG based wind energy conversion system.

This paper presents a novel method for detecting bearing faults using multi-resolution analysis of stator current signals based on Stockwell Transform. The sampled stator current signals are analyzed with the help of Stockwell Transform to extract features namely maximum magnitude and maximum phase angle. The statistics of these features are further utilized to detect and classify the bearing faults in outer race, inner race, cage and balls. The experimental results show that the proposed approach is capable of detecting various bearing faults in induction motor.

This paper presents a Wavelet based transmission line protection algorithm which uses centroid difference for fault detection and support vector regression for the fault location. The sample of three phase currents signals of both the terminals of the line are synchronized and decomposed with Wavelet Transform to obtain the absolute values of approximate coefficients over moving window of a cycle. For the decomposition of current signal dbl mother wavelet is used. Two centroid at each cycle is computed using k-means clustering. The centroid difference is computed at both terminal added to obtain fault index. The fault index is compared with a threshold to detect the faulty phase and to classify the fault. The same approximate coefficients of post fault current transient obtain over half a cycle are used for the estimation of fault location with the help of support vector regression. A large number of case studies involving changes in fault impedance, fault incidence angle and fault location have been conducted to establish the performance of the proposed algorithm.

This paper deals with an algorithm, based on wavelet-Alienation coefficients for protection of wind farm connected distribution network. The proposed algorithm takes the differential current signal of grid node and wind farm coupling node. The Wavelet transform used to extract the approximation coefficients of all the three-phase current signals. Alienation coefficients of each differential phase current obtained over a half cycle is used to identify and categorize the various faults. A modified IEEE13 bus test feeder system used for simulation in MATLAB. Proposed technique tested for detection of all shunt faults at each bus of the distribution system.

Fast identification and classification of the faults in distribution network is a crucial task to ensure reliable power supply to the end user. This paper presents a protection scheme which makes use of Empirical Mode Decomposition of three phase current signals of a distribution network. The current signals measured at the substation bus over a moving window of one cycle are decomposed to obtain first level intrinsic mode function IMF1 and residue R1. A fault index which is nothing but the absolute mean of R1 is calculated for each phase and compared with a threshold to detect and categorize the type of fault. The proposed algorithm has been successfully tested on IEEE 13 bus system by varying the type of fault, fault incidence angle and fault location. The selectivity of the proposed scheme has been established by testing the algorithm with non faulty transients such as load switching and capacitor switching.

Wind Energy (WE) is intermittent and uncertain in nature, and its integration with weak AC grid in the presence of inductive loads largely deteriorates the power quality (PQ). In such scenario grid synchronization at higher WE, penetration level becomes a major challenge in the distribution network. This paper presents a method to mitigate PQ issues in weak AC grid with high WE penetration using distribution static compensator (DSTATCOM) controlled by an adaptive linear neural network-based least mean square (ADALINE-LMS) control algorithm. This control algorithm minimizes the current error by continuous tracking of active unit voltage templates and extracting the weight component of the load current to estimate reference current signals. These reference signals and actual weak AC grid current signals are fed to the hysteresis current controller to generate switching signals for DSTATCOM thereby facilitating smooth grid synchronization and enhance WE penetration level. The proposed control algorithm has been successfully implemented in case a weak AC grid with higher WE penetration level in MATLAB environment.

Integration of distributed generation (DG) sources poses new protection challenges in distribution system. The fault current characteristics change due to bidirectional flow of current and unpredictable nature of DG sources. In this work, Stockwell transform based protection scheme has been proposed to detect and classify faults in a distribution network integrated with a solar photo voltaic power plant (SPV). The post fault current transients measured over a moving window at the substation are decomposed using S- Transform to obtain the peak magnitude of second harmonic content which is defined as fault index. This fault index is compared with a threshold (TF) to detect and classify faults. The proposed algorithm has been successfully implemented on IEEE 13 bus system with numerous case studies involving variations of fault incidence angles and fault locations in MATLAB environment. The immunity of the proposed algorithm to switching transients, energization/de-energization of power components and noisy environment has also been established.

In this work, Hilbert-Huang Transform (HHT) is applied for fast detection and location of faults using quarter cycle post fault current information, measured at the secondary of the substation transformer. Empirical Mode Decomposition (EMD) is carried out over a moving window to obtain first level residue, on which Hilbert Transform (HT) is applied in order to obtain the instantaneous attributes. Standard deviations of instantaneous frequency (SDIF), amplitude (SDIA) and average value of residue (AVR) are obtained for computing fault location indices. A tree like logic flow is implemented by comparing these indices with thresholds to identify the zone of fault and subsequently the exact fault location. The proposed algorithm has been implemented for IEEE 13 bus distribution system using MATLAB. Various case studies involving changes in fault type, fault incidence angle, bus location, fault resistance have been carried out in order to establish the proposed algorithm. It has also been established that the protection algorithm is not affected by non faulty transients such as switching of compensating equipment.

Wind energy (WE) source becomes widely used renewable energy sources for generating green, clean, and sustainable electrical energy due to their low cost and high efficiency. Integration of WE sources into the weak AC grid with unbalanced load is a significant cause of power quality deterioration. Therefore, wind side inverter is not capable of fulfilling the reactive power requirement and penetration level of the active power of the wind is very less. Thus, distribution static compensator (DSTATCOM) is a smart solution to enhance the capability of WE sources to support the voltage of weak grids during the increase of WE penetration. In this work, the fourth-order least mean fourth (LMF) based adaptive control algorithm is proposed for smooth control of real and reactive power requirement by generating switching signals for DSTATCOM to enhance the WE penetration in weak AC grid in the presence of unbalanced load. The control algorithm has been successfully implemented in the MATLAB environment.

Distribution system protection against faults is a vital task for reliability of a power system. In the proposed work, three phase current signals obtained at substation of an IEEE 13 bus system are initially decomposed using empirical mode decomposition (EMD). The higher frequency components, Intrinsic mode functions (IMFs) of this decomposition are eliminated leaving behind a residue containing predominantly fundamental frequency. This residue being monotonic in nature, is utilized to generate visually distinct symmetrical dot patterns (SDP) for three phases. These SDPs are then correlated with those obtained under normal conditions to obtain a fault index based on alienation method. The faults are successfully detected and classified when the fault index is above a predetermined threshold. This algorithm has been successfully established for various types of faults with changing fault incidence angle, fault resistance at all the buses of the distribution system. The proposed algorithm is found to be fast in detecting and classifying faults within half cycle.