Search

Summary: Bridgeless ac‐dc converters are the optimal choice for many applications, as they offer many advantages such as low distorted supply current, high power factor, and improved efficiency. This paper presents a new topology for a single‐phase bridgeless ac‐dc converter. The proposed hybrid topology is based on integrating the inverting and non‐inverting buck‐boost dc‐dc converters that are connected to the ac supply through an LC filter. To insure sinusoidal supply current, the proposed hybrid bridgeless ac‐dc converter is operated in discontinuous current mode. The proposed converter has many merits, such as a reduced number of components, enhanced efficiency, and soft start‐up capability. The operation modes and design of the proposed converter are presented. In addition, a design method is proposed for the input LC filter to minimize the voltage stress across switches. Moreover, a small signal model for the proposed converter is developed. The proposed converter topology is simulated to evaluate the dynamic behavior and verify the accuracy of the presented small signal model. Furthermore, an 850 W prototype is developed to validate the features of the proposed converter experimentally. Tight voltage regulation, sinusoidal supply current, and near‐to‐unity power factor operation are observed from the results, regardless of supply or load disturbances. [ABSTRACT FROM AUTHOR]

The wide use of communication layers in DC microgrids to transmit voltage and current measurements of each distributed generator unit (DGU) increases the possibility of exposure to cyber-attacks. Cyber-attackers can manipulate the measured data to distort the control system of microgrids, which may lead to a shutdown. This paper proposes distributed mitigation layers for the false data injection attacks (FDIA) on voltages and currents of DGUs in meshed DC microgrids. The proposed control strategy is based on integrating two layers for cyber-attack detection and mitigation to immune the primary and the secondary control loops of each DGU. The first layer is assigned to mitigate FDIAs on the voltage measurements needed for the voltage regulation task of the primary control loop. The second layer is devoted to the mitigation of FDIAs on the DGU current measurements, which are crucial for the secondary control level to guarantee the proper current sharing of each DGU. Artificial neural networks (ANNs) are employed to support these layers by estimating the authenticated measurements. Different simulation and experimental case studies are provided to demonstrate the proposed mitigation layers' effectiveness in detecting and mitigating cyber-attacks on voltage and current measurements. The simulation and experimental results are provided to evaluate the dynamic performance of the suggested control approach and to ensure the accurate operation of DC microgrids despite the existence of cyber-attacks on the measurements employed in the control strategy. Moreover, the control strategy succeeds to keep the maximum voltage error and the maximum error in current sharing within tolerance. [ABSTRACT FROM AUTHOR]

Dusty weather is a most important disturbance for photovoltaic (PV) systems, that may result in PV panels exposure to partial shading conditions where the PV panel characteristics show several maximum power points. Moreover, dusty weather conditions may lead to rapid changes in solar radiations. Thus, conventional power system tracking algorithms are not being capable to track the global maximum power point (GMPP). This paper provides an advanced maximum power point tracker for partial shading and dusty weather conditions. In the presented technique, scanning and power lock conditions are added to the conventional perturbations and observation technique in photovoltaic system under partial shading or dusty weather conditions. This tracking method scans the PV characteristic in steps and stores all the maximum power points in order to get the GMPP. The proposed tracker is capable to identify the uniform weather conditions to save it from having unnecessary scanning. In addition, this tracker permits dynamic tracking of the GMPP under dusty weather conditions with less fluctuations and stable operation compared to the conventional methods. Accurate and fast conversion to the GMPP during various weather conditions is accomplished using the proposed technique. The proposed modified perturb and observe technique is validated using simulation and practical results. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]