It is increasingly difficult to identify complex cyberattacks in a wide range of industries, such as the Internet of Vehicles (IoV). The IoV is a network of vehicles that consists of sensors, actuators, network layers, and communication systems between vehicles. Communication plays an important role as an essential part of the IoV. Vehicles in a network share and deliver information based on several protocols. Due to wireless communication between vehicles, the whole network can be sensitive towards cyber-attacks.In these attacks, sensitive information can be shared with a malicious network or a bogus user, resulting in malicious attacks on the IoV. For the last few years, detecting attacks in the IoV has been a challenging task. It is becoming increasingly difficult for traditional Intrusion Detection Systems (IDS) to detect these newer, more sophisticated attacks, which employ unusual patterns. Attackers disguise themselves as typical users to evade detection. These problems can be solved using deep learning. Many machine-learning and deep-learning (DL) models have been implemented to detect malicious attacks; however, feature selection remains a core issue. Through the use of training empirical data, DL independently defines intrusion features. We built a DL-based intrusion model that focuses on Denial of Service (DoS) assaults in particular. We used K-Means clustering for feature scoring and ranking. After extracting the best features for anomaly detection, we applied a novel model, i.e., an Explainable Neural Network (xNN), to classify attacks in the CICIDS2019 dataset and UNSW-NB15 dataset separately. The model performed well regarding the precision, recall, F1 score, and accuracy. Comparatively, it can be seen that our proposed model xNN performed well after the feature-scoring technique. In dataset 1 (UNSW-NB15), xNN performed well, with the highest accuracy of 99.7%, while CNN scored 87%, LSTM scored 90%, and the Deep Neural Network (DNN) scored 92%. xNN achieved the highest accuracy of 99.3% while classifying attacks in the second dataset (CICIDS2019); the Convolutional Neural Network (CNN) achieved 87%, Long Short-Term Memory (LSTM) achieved 89%, and the DNN achieved 82%. The suggested solution outperformed the existing systems in terms of the detection and classification accuracy.

Active damping (AD) is a popular approach to suppress the resonance in LCL filtered grid-connected inverter (GCI) owing to lossless damping and efficient system design. In capacitor voltage (CV) damping methods, a differential compensator is essentially needed in feedback path where the damping effectiveness depends on emulated derivative characteristics of the compensator. Such capacitor voltage feedback compensation (CVFC) methods face design limitation at the critical resonance frequency and may require additional delay reduction to ensure stability. In this paper, an alternative parallel feedforward compensation (PFC) method is proposed to synthesize an almost strictly positive real (ASPR) plant and achieved damping with modified stability characteristics. A second-order bandpass section (BPS) employed as a compensator in damping loop based on the proposed control scheme. The main features of the proposed method are effective damping without critical resonance frequency damping limit, extended stable damping region, improved control performance and good robustness under filter parameters and grid inductance variation conditions. The simulation and experimental results are presented to verify the effectiveness of the proposed method.

Improvements in control of renewable energy-based microgrids are a growing area of interest. A hierarchical control structure is popularly implemented to regulate key parameters such as power sharing between generation sources, system frequency and node voltages. A distributed control infrastructure is realized by means of a communication network that spans the micro-distribution grid. Measured and estimated values, as well as corrective signals are transmitted across this network to effect required system regulation. However, intermittent latencies and failures of component communication links may result in power imbalances between generation sources, deviations in node voltages and system frequency. This paper proposes a hierarchical control structure to regulate the operation of an islanded AC microgrid experiencing communication link failures. The proposed strategy aims to virtually sub-divide the microgrid into controllable “islands”. Thereafter, active power sharing, frequency and voltage restoration is achieved by competing converter systems through multi-agent consensus. The effectiveness of the proposed methodology has been verified through stability analyses using system wide mathematical small signal models and case study simulations in MATLAB, Simpower systems.

This paper focuses on the study of a soft‐switched unidirectional boost‐type rectifier employing a snubber circuit, used as a front‐end converter stage in high‐power applications. The proposed rectifier operates with soft switching which results in high efficiency and low cost. The switching losses and electromagnetic interference (EMI) result in poor efficiency, therefore, soft switching techniques need to be developed to improve the efficiency. To achieve the desired result, the snubber circuit which consists of a lossless snubber switch cell and a resonant inductor, is introduced in the above‐mentioned converter. The topology of the proposed converter is derived from the conventional T‐type three‐level boost rectifier. The circuit operation, theoretical analysis, and simulation of the converter in MATLAB/Simulink environment are carried out. Finally, a 10 kW laboratory set‐up of the proposed soft‐switched unidirectional rectifier is built. The experimental results obtained validate the theoretical analysis of the circuit.

The impending environmental issues and growing concerns for global energy crises are driving the need for new opportunities and technologies that can meet significantly the higher demand of cleaner and sustainable energy systems. This necessitates the development of transportation and power generation systems. The deployment of electric vehicles (EVs) is considered as an emergent solution to meet the current and future energy crises and environmental issues. The electrification of transportation system is a promising approach to green the transportation systems and to reduce the issues of climate change. This paper inspects the present status, latest deployment and challenging issues in implementation of EVs infrastructural and charging systems in conjunction with several international standards and charging codes. In this study, the on-board and off-board categories of charging systems with unidirectional and bidirectional power flow are shown. Unidirectional charging offers hardware limitation and reduce interconnection issues. Bidirectional charging offers the fundamental feature of vehicle to grid technology. Cost issues and requirements for on-board energy storage systems are reduced with the accessibility of charging infrastructures Furthermore, an extensive analysis of international standards which are implemented for deployment of EVs are explained. Our study also compared and evaluated infrastructural and charging systems based on equipment, location and time of charging, cost, amount of power, impacts on the gird and other aspects.

In this paper, an active damping for LCL-type single phase grid connected inverter is proposed. The suggested methodology is based on Parallel Feedforward Compensation (PFC) technique that allows to add a compensator parallel with filter system. A capacitor voltage is feedback through a Bandpass section (BPS) to form a damping loop. Theoretical background of PFC, design of a bandpass section as a compensator and stability of proposed method has been analyzed. The main advantage of proposed method is simplicity and straightforward design procedure. The control performance is compared with active damping technique by a capacitor voltage feedback through lead-lag network. The Proportional Resonant (PR) controller is used for grid current regulation. Finally, the effectiveness of proposed method is examined in MATLAB environment and verified by simulation results.