Badr M. Alshammari

The impact of Partial Shading Conditions (PSCs) significantly influences the output of Photovoltaic Systems (PVSs). Under PSCs, the Power-Voltage (P-V) characteristic of the PVS unveils numerous power peaks, inclusive of local maxima and a global maximum. The latter represents the optimum power point. Traditional Maximum Power Point Tracking (MPPT) algorithms struggle to track the Global Maximum Power Point (GMPP). To address this, our study emphasizes the creation of a novel algorithm capable of identifying the GMPP. This approach combines the Cuckoo Search (CS) MPPT algorithm with an Integral Super-Twisting Sliding Mode Controller (STSMC) using their benefits to enhance the PVS performance under PSCs in terms of high efficiency, low power losses, and high-speed convergence towards the GMPP. The STSMC is a second-order Sliding Mode Control strategy that employs a continuous control action that attenuates the “chattering” phenomenon, caused when the first-order SMC technique is employed. Indeed, the proposed CS-STSMC-MPPT algorithm consists of two parts. The first one is based on the CS algorithm used for scanning the power-voltage curve to identify the GMPP, and subsequently generating the associated optimal voltage reference. The second part aims to track the voltage reference by manipulating the duty cycle of the boost converter. The proposed CS-STSMC-MPPT algorithm is featured by its strength against uncertainties and modeling errors. The obtained simulation results underline a high convergence speed and an excellent precision of the proposed method in identifying and tracking the GMPP with high efficiency under varying shading scenarios. For comparative purposes, this method is set against the hybrid CS-Proportional Integral Derivative, the conventional CS, the Particle Swarm Optimization, and the Perturb and Observe algorithms under different PSCs, including zero, weak, and severe shading. Simulation conducted in the Matlab/Simulink environment confirms the superior performance of the proposed CS-STSMC-MPPT algorithm in terms of precision, convergence speed, efficiency, and resilience.

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.

In the present study, the effects of reduced gravity and solar radiation on the magnetohydrodynamics (MHD) fluid flow and heat transfer past a solid and stationary sphere embedded in a porous medium are investigated. A model describing the considered configuration is put in dimensionless form using appropriate dimensionless variables and then transformed to primitive form for a smooth algorithm on a computing tool. A primitive form of the model is solved by employing the finite difference method. Solutions for variables of interest, such as velocity distribution and temperature field, along with their gradients, are depicted in graphs and tables. The main goal of the paper is to study the physical impact of reduced gravity on heat transfer and fluid flow around a sphere surface inserted in a porous medium in the presence of an applied magnetic field and solar radiation. The effects of the governing parameters, which are the reduced gravity parameter, magnetic field parameter, radiation parameter, porous medium parameter, and the Prandtl number, are discussed and physically interpreted. The displayed solutions indicate that velocity rises with the reduced gravity and solar radiation parameters but decreases with augmenting the Prandtl number, magnetic field parameter, and porous medium parameter. It is deduced from the presented results that the temperature becomes lower by increasing the values of the reduced gravity parameter and the Prandtl number, but, on the other hand, it becomes higher by increasing the values of the magnetic field, the porous medium, and the radiation parameters at all the considered positions of the surface of the sphere. A comparison between the present and already published results is performed to check the validity of the proposed numerical model.