Shaik, Abdul Gafoor

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.

In the present paper, a wavelet transform based alienation technique has been presented for the detection of islanding condition in a distribution system incorporate with distributed generations. A radial five bus system integrated with four doubly fed induction wind generators (DFIG) has been considered for the study. The voltage signals at various DG buses were decomposed with Daubechies wavelet transform to get approximation coefficients. The alienation coefficients of these approximate decompositions were termed as Islanding indexes. These indexes were compared with a predetermined threshold to detect Islanding condition. The same threshold value was utilized to discriminate a transient associated with sudden changes with load. The suggested algorithm was established by a few case studies involving changes in incidence angle and load. Thus, the proposed algorithm is found to be successful for Islanding detection.

This paper presents a fuzzy logic based synchronous reference frame algorithm for distribution static compensator to enhance the power quality of a weak AC grid. The proposed algorithm maintains constant DC-link voltage and extracts fundamental weighted values of load currents to es timate reference current. Thes e reference currents are utilized by DSTATCOM to mitigate the power quality. This control algorithm has been tested success fully in regulating the vol tage, mi tigating the harmonics, and load balancing for different types of loads at the point of common coupling.

Solar photo-voltaic (SPV) is a major contributor of renewable energy (RE) sources, which plays an important role in tackling climate change, reducing the cost of energy, improving the reliability of power supply, and providing access to energy. SPV is a major hope for “access to energy” for remote populations which are deprived of the conventional grid due to economical and feasibility issues. These issues are to be tackled in due course of time to enhance the reliability of the supply. The Extension of the grid to these areas weakens the strength of the grid. This results in a scenario of PV integration into a weak AC grid. However, solar integration into a weak AC grid provides power quality (PQ) challenges that limit the penetration levels. The other components which limit penetration levels include non-linear loads, dynamic loads, variable irradiations and partial shading etc. Various DFACTS devices in association with different conventional, adaptive and AI-based algorithms have been proposed in this article to mitigate PQ challenges associated with a weak grid to enhance penetration levels of Solar PV. This article provides a comprehensive review of various power quality challenges associated with SPV penetration and PQ mitigation techniques involving various DFACTS devices and control algorithms such as conventional control, adaptive control, and AI-based control algorithms. More than 130 research articles have been rigorously assessed, categorized, and listed in this article for quick reference for the advantage of engineers and academicians working in this area of research.

The synchronization of the Doubly-Fed Induction Generator (DFIG) into the weak AC grid is significantly affected due to the reactive power limitations associated with the built-in converter of the existing Wind Energy (WE) system. This is further restricted due to non-linear loads and Power Quality (PQ) deterioration. Therefore, there is a strong need for a system capable of managing reactive power without disturbing the existing infrastructure of WE sources. This paper proposes a novel reactive power-based solution for synchronizing the DFIG to the weak grid with high WE penetration by mitigating PQ disturbances and managing reactive power at the interconnection point using an additional Distribution-Static Compensator (DSTATCOM). A feed-forward second-order-based adaptive algorithm controls this reactive power compensator. The adaptive control extracts the active and reactive weights of load current to generate the reference signals by continuously tracking grid voltage, wind generation, and DC-link voltage. The proposed novel approach has been successfully implemented in MATLAB and validated with a laboratory-based experimental setup. The transient and steady-state analysis reveals the practical applicability of a proposed novel synchronization approach with a high WE penetration level.

This paper presents bearing fault detection and its diagnosis in a three phase induction motor using Stockwell transform of stator currents. The maximum magnitude and maximum phase angle plots are obtained from S-transform for various bearing conditions both on shaft-side and fan-side. The standard deviation of these plots are utilized to detect and analyze the bearing faults. The various bearing faults analyzed under case studies include defects in innerrace, outerrace, cage and balls. The experimental study shows that the S-transform based feature extraction can be effectively utilized for bearing fault detection and diagnosis in three phase induction motor.

Recognition and analysis of a fault diagnosis has a crucial role to ensure safe operation of power system. To overcome all existing drawbacks of fault location identification. Utilizing phasor measurement units, an algorithm is proposed to identify and locate faults in large transmission network. This is done to know the specific area of the location of fault by using following process as; initially voltage amplitude and current measure is calculated by using PMU data. After the calculation of voltage amplitude and current measure Discrete Wavelet Transform (DWT) start its extraction process. After the extraction of voltage and current measurements Faulted Bus Identification (FBI) index is calculated only for the PMU voltage measurements. Subsequently, set the maximum value of measured FBI index as threshold. At the same time, Data correlation analysis is performed on the taken raw PMU data. After this analysis, ring law used for calculation of Mean spectral radius (MSR).Accordingly, artificial neural network (ANN) is trained by using the calculated MSR. Finally, the trained ANN decides the exact fault location using the chosen threshold value. The method is tested and analyzed on the IEEE 13 bus systems for various fault conditions as well as implemented in the platform of MATLAB.

The global concern with power quality is increasing due to the penetration of renewable energy (RE) sources to cater the energy demands and meet de-carbonization targets. Power quality (PQ) disturbances are found to be more predominant with RE penetration due to the variable outputs and interfacing converters. There is a need to recognize and mitigate PQ disturbances to supply clean power to the consumer. This article presents a critical review of techniques used for detection and classification PQ disturbances in the utility grid with renewable energy penetration. The broad perspective of this review paper is to provide various concepts utilized for extraction of the features to detect and classify the PQ disturbances even in the noisy environment. More than 220 research publications have been critically reviewed, classified and listed for quick reference of the engineers, scientists and academicians working in the power quality area.

Renewable energy (RE) sources when integrated to utility network to form hybrid power system pose challenges in terms of stability and power quality. A method based on Stockwell's transform (S-transform) is presented in this paper for power quality (PQ) assessment and detection of islanding, outage and grid synchronization of renewable energy sources. Voltage signals are decomposed using multi-resolution analysis (MRA) of S-transform and features extracted are realized to assess the power quality disturbances associated with various events. Operational events are detected with the help of features extracted from the S-transform based decomposition of negative sequence component of voltage. A power quality index is proposed to rank the various operational events based on power quality. Proposed algorithm has been tested successfully on IEEE-13 bus test system with necessary modifications to integrate wind and solar PV generators to form the hybrid power system. Simulation results are validated in real time environment with the help of real time digital simulation (RTDS) system.

An adaptive neuro fuzzy based three phase four wire Shunt Active Power Filter is presented in this paper. The active power filter composed of asymmetric cascaded transformer multilevel converter and DC link capacitor. Under dynamic load conditions harmonic compensation and reactive power compensation can be achieved effectively. An ANFIS controller is designed to regulate voltage across DC link capacitor. The proposed method generates the compensation current reference which can handle reactive power requirement of non linear load and DC voltage regulation. Simulation results show fuzzy and ANFIS controller gives better harmonic compensation and DC link voltage regulation.