Wind turbine (WT) is now a major renewable energy resource used in the modern world. One of the most significant technologies that use the wind speed (WS) to generate electric power is the horizontal-axis wind turbine. In order to enhance the output power over the rated WS, the blade pitch angle (BPA) is controlled and adjusted in WT. This paper proposes and compares three different controllers of BPA for a 500-kw WT. A PID controller (PIDC), a fuzzy logic controller (FLC) based on Mamdani and Sugeno fuzzy inference systems (FIS), and a hybrid fuzzy-PID controller (HFPIDC) have been applied and compared. Furthermore, Genetic Algorithm (GA) and Particle swarm optimization (PSO) have been applied and compared in order to identify the optimal PID parameters (kp, ki, kd). The objective of GA and PSO is minimized the error signal in output power based on actual WS. The results for three different controllers show that the optimal hybrid FPIDC based on the Sugeno inference system with PSO produces the optimal results regard to reduce the error signal and stable output power under actual WS.
Most Internet of Vehicles (IoV) applications are delay-sensitive and require resources for data storage and tasks processing, which is very difficult to afford by vehicles. Such tasks are often offloaded to more powerful entities, like cloud and fog servers. Fog computing is decentralized infrastructure located between data source and cloud, supplies several benefits that make it a non-frivolous extension of the cloud. The high volume data which is generated by vehicles’ sensors and also the limited computation capabilities of vehicles have imposed several challenges on VANETs systems. Therefore, VANETs is integrated with fog computing to form a paradigm namely Vehicular Fog Computing (VFC) which provide low-latency services to mobile vehicles. Several studies have tackled the task offloading problem in the VFC field. However, recent studies have not carefully addressed the transmission path to the destination node and did not consider the energy consumption of vehicles. This paper aims to optimize the task offloading process in the VFC system in terms of latency and energy objectives under deadline constraint by adopting a Multi-Objective Evolutionary Algorithm (MOEA). Road Side Units (RSUs) x-Vehicles Mutli- Objective Computation offloading method (RxV-MOC) is proposed, where an elite of vehicles are utilized as fog nodes for tasks execution and all vehicles in the system are utilized for tasks transmission. The well-known Dijkstra's algorithm is adopted to find the minimum path between each two nodes. The simulation results show that the RxV-MOC has reduced significantly the energy consumption and latency for the VFC system in comparison with First-Fit algorithm, Best-Fit algorithm, and the MOC method.
In order to mitigate the effect of voltage sag on sensitive loads, a dynamic voltage restorer (DVR) should be used for this purpose. The DVR should be accompanied with a fast and accurate sag detection circuit or algorithm to determine the sag information as quickly as possible with an acceptable precision. This paper presents the numerical matrix method as a distinctive candidate for voltage sag detection. The design steps of this method are demonstrated in detail in this work. The simulation results exhibit the superiority of this technique over the other detection techniques in term of the speed and accuracy of detection, simplicity in implementation, and the memory size. The results also accentuate the recognition capability of the proposed method in distinguishing different types of voltage sag by testing three different voltage sag scenarios.
Nowadays, cloud computing has attracted the attention of large companies due to its high potential, flexibility, and profitability in providing multi-sources of hardware and software to serve the connected users. Given the scale of modern data centers and the dynamic nature of their resource provisioning, we need effective scheduling techniques to manage these resources while satisfying both the cloud providers and cloud users goals. Task scheduling in cloud computing is considered as NP-hard problem which cannot be easily solved by classical optimization methods. Thus, both heuristic and meta-heuristic techniques have been utilized to provide optimal or near-optimal solutions within an acceptable time frame for such problems. In this article, a summary of heuristic and meta-heuristic methods for solving the task scheduling optimization in cloud-fog systems is presented. The cost and time aware scheduling methods for both bag of tasks and workflow tasks are reviewed, discussed, and analyzed thoroughly to provide a clear vision for the readers in order to select the proper methods which fulfill their needs.
voltage sags represent the greatest threat to the sensitive loads of industrial consumers, the microprocessor based-loads, and any electrical sensitive components. In this paper, a special topology is proposed to mitigate deep and long duration sags by using a modified AC to AC boost converter with a new control method. A boost converter is redesigned with a single switch to produces an output voltage that is linearly proportional to the duty cycle of the switch. On the other hand, the proposed control system is based on introducing a mathematical model that relates the missing voltage to the duty cycle of the boost converter switch. The simulation results along with the system analysis are presented to confirm the effectiveness and feasibility of the proposed circuit.
This research presents a technique of an electro optic effect for enhancement the an accomplishment of an electro optics switch using Mat lab simulation program . this technique includes design a mathematical model for evaluate the effect of different parameters such as refractive index (n), distance of separation between waveguides (d), length of electrodes (L), relative refractive index (Δn), and switching voltage (V ), on the DC bias voltage of an electro optics switch. In this work the investigation of performance of an electro optics switch by analysis of an effect of distance between waveguides and the changing of refractive index on the bias voltage (V), and which optimizes when the wavelength is from 1300 into 1550 nm. Finally, an electro-optic active switch is designed and optimized, using the analytical model and which considers important device in the modern optical communication system.