An oblique angle and polarization insensitive metamaterial absorber (MA) are highly desired for the visible and infrared optical applications like, wave energy harvesting, optical filters, and detecting thermal leaks and electrical defects. In this paper, a multi-layered MA consisting of two layers of tungsten resonators on a silicon dioxide substrate, coated with additional SiO₂ materials is investigated. The unit cell size of the MA is 0.5λ × 0.5λ × 0.8λ, at the lowest wavelength. The proposed MA offers an average absorption of 92% from 400 nm to 2400 nm with stable oblique incident angles up to 45°. The structure also achieves polarization insensitivity at the entire visible and near-infrared spectrum. Moreover, the MA is found highly compatible for solar absorber applications with high y A_AM1.5. The structure is also compatible for filter application in optical communication system by modifying the plasmonic nano structure. The modified structure can block the wavelengths of the visible band (450 nm to 800 nm) and transmit optical communication bands (800 to 1675 nm). These versatile absorption and filtering performance make the proposed design highly potential for solar energy harvesting, photodetection, thermal imaging, photo-trapping, and optical communications applications.

By bringing smart and advanced solutions, the Internet of Things (IoT) has opened up new dimensions of innovative services and processing power for contemporary living standards. IoT has a wide range of devices and communication entities as a result of the widespread applications of these services, making network management a challenging task. Therefore, it is critical to redesign the IoT network’s management. The inherent programmability and centralized capabilities of software-defined networking (SDN) make network management simpler, enable network abstraction, make network evolution easier, and have the potential to handle the IoT network. However, security issues still present the IoT dilemma. Distributed Denial of Service (DDoS) attacks are among the most significant security threats in IoT systems. This paper studies in-depth DDoS attacks in IoT and in SDN. A review of different detection and mitigation techniques based on SDN, blockchain and machine learning models is conducted. A holistic, secure IoT system is proposed on the basis of SDN with multicontrollers. Blockchain is considered to guarantee security in distributed SDN-IoT networks and ANN to improve the detection and mitigation process.

The use of FACTS devices in power systems has become increasingly popular in recent years, as they offer a number of benefits, including improved voltage profile, reduced power losses, and increased system reliability and safety. However, determining the optimal type, location, and size of FACTS devices can be a challenging optimization problem, as it involves mixed integer, nonlinear, and nonconvex constraints. To address this issue, researchers have applied various optimization techniques to determine the optimal configuration of FACTS devices in power systems. The paper provides an in-depth and comprehensive review of the various optimization techniques that have been used in published works in this field. The review classifies the optimization techniques into four main groups: classical optimization techniques, metaheuristic methods, analytic methods, and mixed or hybrid methods. Classical optimization techniques are conventional optimization approaches that are widely used in optimization problems. Metaheuristic methods are stochastic search algorithms that can be effective for nonconvex constraints. Analytic methods involve sensitivity analysis and gradient-based optimization techniques. Mixed or hybrid methods combine different optimization techniques to improve the solution quality. The paper also provides a performance comparison of these different optimization techniques, which can be useful in selecting an appropriate method for a specific problem. Finally, the paper offers some advice for future research in this field, such as developing new optimization techniques that can handle the complexity of the optimization problem and incorporating uncertainties into the optimization model. Overall, the paper provides a valuable resource for researchers and practitioners in the field of power systems optimization, as it summarizes the various optimization techniques that have been used to solve the FACTS optimization problem and provides insights into their performance and applicability.

The visible and infrared wavelengths are the most frequently used electromagnetic (EM) waves in the frequency spectrum; able to penetrate the atmosphere and reach Earth’s surface. These wavelengths have attracted much attention in solar energy harvesting; thermography; and infrared imaging applications for the detection of electrical failures; faults; or thermal leakage hot spots and inspection of tapped live energized components. This paper presents a numerical analysis of a compact cubic cross-shaped four-layer metamaterial absorber (MA) structure by using a simple metal-dielectric-metal-dielectric configuration for wideband visible and infrared applications. The proposed MA achieved above 80% absorption in both visible and near-infrared regions of the spectrum from 350 to 1250 nm wavelength with an overall unit cell size of 0.57λ × 0.57λ × 0.59λ. The SiO₂ based anti-reflection coating of sandwiched tungsten facilitates to achieve the wide high absorption bandwidth. The perceptible novelty of the proposed metamaterial is to achieve an average absorptivity of 95.3% for both visible and infrared wavelengths with a maximum absorptivity of 98% from 400 nm to 900 nm. Furthermore, the proposed structure provides polarization insensitivity with a higher oblique incidence angle tolerance up to 45°.

Combined economic emission dispatch (CEED) problems are among the most crucial problems in electrical power systems. The purpose of the CEED is to plan the outputs of all production units available in the electrical power system in such a way that the cost of fuel and polluted emissions are minimized while respecting the equality and inequality constraints of the system and efficiently responding to the power load required. The rapid depletion of these sources causes limitation and increases the price of fuel. It is therefore very important that scientific research in the last few decades has been oriented toward the integration of renewable energy systems (RES) such as wind and PV as an alternative source. Furthermore, the CEED problem including RES is the most important problem with regard to electrical power field optimization. In this study, a classification of optimization techniques that are widely used, such as traditional methods, non-conventional methods, and hybrid methods, is summarized. Many optimization methods have been presented and each of them has its own advantages and disadvantages for solving this complex CEED problem, including renewable energy. A review of different optimization techniques for solving this CEED problem is explored in this present paper. This review will encourage researchers in the future to gain knowledge of the best approaches applicable to solve CEED problems for practical electrical systems.

This paper presents a hardware implementation upon a Field Programmable Gate Array (FPGA) of improved Vector Control Strategies (VCSs) based on a Fuzzy Logic System (FLS) of a grid-connected wind energy conversion system. Usually, the classical VCS is based on fixed-gain Proportional Integral Derivative (PID) controllers, which are known to exhibit limited performance against the nonlinear behavior of wind systems, such as rapid fluctuations of the wind speed and uncertainties of the system parameters. In order to overcome this limitation, an improved VCS based on Fuzzy Gain Scheduling PID controllers (VCS-FGS-PID) is suggested in this work to guarantee good tracking, high accuracy and good robustness under system parameter variations. Indeed, the PID controller gains are tuned, in real-time, by the FLS. In addition, the proposed VCS-FGS-PID methods are implemented on the FPGA in order to reduce the delays and the period of the system of the control loop, thanks to its parallel processing. In fact, the performance of the suggested VCS-FGS-PID approaches are proved by digital simulation with the Xilinx system generator tool under Matlab/Simulink, in addition to an experimental hardware-in-the-loop implementation using the FPGA. The obtained results demonstrate that the proposed VCS-FGS-PID techniques offer better performance as regards good tracking and high accuracy and good robustness against stator resistance variability compared to VCS-PI.