This article introduces the ultrathin polarization-independent Metamaterial-based Absorber for the X-band (8-12 GHz) frequency range applications. The suggested shape of the unit cell contains four squares that are connected to each other. The presented unit cell design of a dual copper-coated FR-4 substrate is printed on the upper surface with a thickness of 1.6 mm. The simulated structure gives one absorption peak at the 9.572 GHz frequency range. The proposed square shape structure gives the perfect absorption of 99.88% at 9.572 GHz frequency. The imitated result illustrates the Metamaterial Absorber accede polarization-insensitive property. It has potential applications like active sensors (satellite), aeronautical navigation, radio-determination, radiolocation in civil, and radiolocation in the military. The formation of the design is polarization-independent for all incident angles. The depth of the proposed structure is very compact as compared to earlier designs.
Nowadays, Electric Vehicle (EV) technology is gaining pace with the modern requirement of limiting the fossil fuel consumption and greenhouse gas emission. However, such EVs require charging stations which are to be installed in the Distribution System (DS) and may be connected with different converter topologies as well as control techniques. Further, the current during the fault may be modulated due to the adopted control and protection circuits of the converters. When the fault occurs in the charging station, in case the fault is not cleared from the charging station, the backup should be provided by the detection of fault using the conventional protection technique: over current relay. Since the fault current is limited at the charging station, the backup relay may fail to detect the fault, which relies on change in current. Hence, development of a new technique is inevitable for fault detection if the DS is connected to the charging station. In this work, the wavelet transform-based scheme is proposed to enhance fault detection in the presence of battery charging station in DS. A charging station connected to 11 kV, 50 Hz AC substation is simulated in MATLAB/SIMULINK and results show the proposed method efficiently detects the fault in the DS.
The past few years researchers are rising dominance of deep learning and artificial intelligence in huge range of various applications like image and video compression. The paper provides a deep concept over for highly loss video compression model. In the existing neural networks of video encoding presence of quantity and level of redundancy provides unique problems. The ELBO utilized in variational autoencoders is strongly related to the rate distortion loss, which the autoencoder and prior are jointly trained to reduce. Although proposed method is straightforward, in this paper discover that it beats cutting-edge learning video compression networks interpolation. The work where systematically assess key design decisions, including the type of autoregressive prior and the usage of frame-based or spatio-temporal autoencoders. And also provide three modifications to the fundamental concept that highlight its advantages over more traditional compression techniques. In this paper proposed semantic compression, which trains the model to devote more bits to important objects. This work investigates the proposed multimodal compression, where it will presents how well our approach works when it comes to combining different modalities that have been collected by unconventional imaging sensors, such quad cameras. And finalize that approach makes unique video compression applications possible that were not possible with conventional codecs. Finally, at the end of the work in our multimodal compression studies significantly improves compression performance with the PSNR of 48. For future scope of work, a simple decoder can recreate videos with sufficient quality without compromising classification accuracy.
Electric vehicles (EVs) are becoming popular day by day because they lower the dependency on fossil fuels. A novel approach to building EV charging stations uses solar photovoltaic (SPV) integrated into the grid. Information on day-ahead grid electricity pricing is gathered using a forecasting system based on Nonlinear Autoregressive Neural Network (NARX). Later a price coefficient is added to further divide on-peak and off-peak grid electricity pricing. This paper proposes two different tariff-aware power management schemes for both on-peak and off-peak prices. It manages to provide a continuous power supply to the critical as well as EV loads. Both EV and the critical loads are able to receive a steady supply of electricity from the grid depending on tariff. The proposed scheme is validated using MATLAB Simulink 2020b.
This study mainly discusses the implications of solar radiation profiles and changes in load with respect to base load conditions on the PV placement, size, voltage violations, and curtailment cost of PV generation in the network. The PV installation is optimized using yearly solar radiation profiles, low, medium, and high, corresponding to three different locations. The network in the study is represented as a multiphase, with provision for the installation of both single- and three-phase PV systems. For the different load changes in either one of the phases or all three phases, the optimal placement and size of PV inverters are discussed. It is indicated that with load increase in all three phases, for low solar radiation profiles, the placement and size of PVs remain non-uniform, while for medium and high solar radiation, the distribution becomes comparatively uniform throughout the network. However, with a load increase in one of the phases, for low solar radiation, optimal placement compensates with three-phase PV installation, while for medium/high solar, the corresponding load increase phase contributes to greater PV installation. The voltage rise is observed at both load-connected and non-load-connected buses. Such buses in the network are those that form the common junction with the branches connected to another set of buses having optimally placed PVs. The voltage violations are experienced at the feeder end buses with single-phase PV installation, not only in the phase having a connected load but also in one of the other phases.
