Optimal design of autonomous desalination with storage energy system using SSO algorithm

Sustainable power sources, that is, the energy produced as of hydro control, biomass, wind, geothermal, sunlight, and sea resources deliberated as innovative choice intended to create clean energy and crisp water. The majority of the nations have challenged issues proceeding freshwater and power creation, which tends to the utilization of sustainable power source-controlled desalination frameworks. In this work expanding the clean water accessibility that satisfies the load need, Hybrid Renewable Energy Systems (HRES) on the basis of Reverse Osmosis Desalination (ROD) is structured and then displayed. HRES is getting to be well known for power applications because of advances in sustainable power sources. Here, an innovative calculation based on Social Spider Optimization (SSO) is aimed at explaining the required optimization tasks. The technique referenced is turned out to be powerful, utilizing sustainable power source framework. The proposed system is contrasted with a genuine contextual analysis in the eastern part of Iran, Canary Islands and outcomes demonstrate that it has been successfully utilized thinking about both power quality and cost. Also, the outcomes acquired by the suggested technique are very encouraging to outline the capability and strength of the introduced methodology.     

Optimal position and rating of DG in distribution networks by ABC–CS from load flow solutions illustrated by fuzzy-PSO

In this work, load flow problems of both radial distribution networks (RDNs) and mesh distribution networks (MDNs) have been solved using hybrid fuzzy-PSO algorithm. A new voltage stability index (VSI) is also indicated. Based on the suggested load flow, distributed generation (DG) is ready to conduct through the requirement; and with the support of inserting the optimal-sized DG unit in an exact way, the distribution system’s stability is also studied. The exact position of each DG unit has been computed using “loss sensitivity analysis,” whereas the optimal sizing of each DG unit has been done with the help of hybrid artificial bee colony and Cuckoo search algorithm. The suggested method is tested in the regular 33-node and 69-node RDNs as well as in 85-node and 119-node MDNs. The transcendence of the proposed operation has been centered with the aid of comparison to the other existing methods. The suggested VSI is also correlated with other two existing VSIs before and after placement of DG unit(s).

     

Controller Placement in Software Defined Internet of Things Using Optimization Algorithm

The current and future status of the internet is represented by the upcoming Internet of Things (IoT). The internet can connect the huge amount of data, which contains lot of processing operations and efforts to transfer the pieces of information. The emerging IoT technology in which the smart ecosystem is enabled by the physical object fixed with software electronics, sensors and network connectivity. Nowadays, there are two trending technologies that take the platform i.e., Software Defined Network (SDN) and IoT (SD-IoT). The main aim of the IoT network is to connect and organize different objects with the internet, which is managed with the control panel and data panel in the SD network. The main issue and the challenging factors in this network are the increase in the delay and latency problem between the controllers. It is more significant for wide area networks, because of the large packet propagation latency and the controller placement problem is more important in every network. In the proposed work, IoT is implementing with adaptive fuzzy controller placement using the enhanced sunflower optimization (ESFO) algorithm and Pareto Optimal Controller placement tool (POCO) for the placement problem of the controller. In order to prove the efficiency of the proposed system, it is compared with other existing methods like PASIN, hybrid SD and PSO in terms of load balance, reduced number of controllers and average latency and delay. With 2 controllers, the proposed method obtains 400 miles as average latency, which is 22.2% smaller than PSO, 76.9% lesser than hybrid SD and 91.89% lesser than PASIN.     

High dielectric response of cobalt aluminate mullite (CAM) nanocomposite over cobalt aluminate mullite polymer (CAMP) nanocomposite in PVDF matrix

In this communication we have compared the dielectric behavior of cobalt aluminate mullite (CAM) nanocomposite and cobalt aluminate mullite polymer (CAMP) nanocomposite with different molar concentration of Co ⁺² ions. The study of dielectric property of the CAM samples as well as that of the CAMP samples at room temperature shows that at all concentrations the dielectric constant is higher than pure mullite and there is a critical concentration of Co ⁺², where maximum enhancement of dielectric property occurs. This paper demonstrates that the loading of a conductive component into a highly insulating matrix is an effective way to fabricate composites with high permittivity as well as a charge storage material. We have designed a device using CAM as the electrode material and CAMP as the separator to compare it with a commercial Li-polymer ion mobile battery. We observed that the charge storage ability of the composite system is better than the commercial Li-polymer ion mobile battery. Our device persists for more than 24 h while the maximum voltage recorded by the device is 0.885 V, whereas the maximum voltage recorded by the conventional commercial Li-polymer ion mobile battery is 0.566 V.     

Method for Fault Diagnosis and Speed Control of PMSM

In the field of fault tolerance estimation, the increasing attention in electrical motors is the fault detection and diagnosis. The tasks performed by these machines are progressively complex and the enhancements are likewise looked for in the field of fault diagnosis. It has now turned out to be essential to diagnose faults at their very inception; as unscheduled machine downtime can upset deadlines and cause heavy financial burden. In this paper, fault diagnosis and speed control of permanent magnet synchronous motor (PMSM) is proposed. Elman Neural Network (ENN) is used to diagnose the fault of permanent magnet synchronous motor. Both the fault location and fault severity are considered. In this, eccentricity fault may occur in the motor. To control the speed of the permanent magnet synchronous motor, Dolphin Swarm Optimization (DSO) algorithm is used. The proposed work is simulated by using MATLAB in terms of amplitude, speed and torque. The comparison graph of speed vs. torque obtained by the proposed method gives better result compared to the other existing techniques. The proposed work is also compared with Particle Swarm Optimization (PSO) and Elephant Herding Optimization (EHO) algorithm. The proposed usage of Elman Neural Network to detect the fault and the usage of Dolphin Swarm Optimization algorithm to control the speed of the permanent magnet synchronous motor gives better outcome.     

Experimental and Theoretical Studies on the Viscosity–Structure Correlation for High Alumina-Silicate Melts

Blast furnaces are encountering high Alumina (Al₂O₃ > 25 pct) in the final slag due to the charging of low-grade ores. To study the viscosity behavior of such high alumina slags, synthetic slags are prepared in the laboratory scale by maintaining a chemical composition of Al₂O₃ (25 to 30 wt pct) CaO/SiO₂ ratio (0.8 to 1.6) and MgO (8 to 16 wt pct). A chemical thermodynamic software FactSage 7.0 is used to predict liquidus temperature and viscosity of the above slags. Experimental viscosity measurements are performed above the liquidus temperature in the range of 1748 K to 1848 K (1475 °C to 1575 °C). The viscosity values obtained from FactSage closely fit with the experimental values. The viscosity and the slag structure properties are intent by Fourier Transform Infrared (FTIR) and Raman spectroscopy. It is observed that increase in CaO/SiO₂ ratio and MgO content in the slag depolymerizes the silicate structure. This leads to decrease in viscosity and activation energy (167 to 149 kJ/mol) of the slag. Also, an addition of Al₂O₃ content increases the viscosity of slag by polymerization of alumino-silicate structure and activation energy from 154 to 161 kJ/mol. It is witnessed that the activation energy values obtained from experiment closely fit with the Shankar model based on Arrhenius equation.     

Electromagnetic band gap coupled tri-notched miniaturized ultra-wideband antenna loaded with slot and parasitic strip

An electromagnetic band gap (EBG) coupled miniaturized tri-notched printed ultra-wideband (UWB) monopole microstrip antenna having dimensions of 22 mm × 26 mm × 1.6 mm loaded with a slot in radiating patch and a parasitic strip in the ground plane has been presented. The proposed structure incorporates a square-shaped metallic radiating patch with a square EBG structure adjacent to the microstrip feed line, a U-shaped meandered slot over the radiating element, and a U-shaped parasitic resonator at the ground plane beneath the radiating element, to reject the C-band satellite downlink (3.7 to 4.2 GHz), WLAN frequency band (5.15 to 5.85 GHz), and X-band satellite downlink (7.25 to 7.75 GHz) frequency bands, respectively. The designed antenna operates in the frequency range from 3 to 11.1 GHz, with an impedance bandwidth of 8.1 GHz and a percentage bandwidth of 114%. Modification steps incorporating into the reference antenna to achieve the desired design objectives have been discussed, along with parametric studies. The proposed design has been simulated using Ansys HFSS, and measurement has been taken using standard measurement technique and compared with the simulated results.     

Effect of SiC nanoparticles on the wear behaviour of squeeze-cast AZ91–2.0Ca–0.3Sb alloy

The dry sliding wear behaviour of the AZ91–2.0Ca–0.3Sb alloy and the AZ91–2.0Ca–0.3Sb–xSiC_np nanocomposites have been investigated. The wear rate is lower for all the nanocomposites compared to the alloy. All the nanocomposites demonstrate the lower specific wear rates than the alloy. Among the nanocomposites, the one containing 2.0SiC_np exhibits the best tribological performance. The values of the coefficient of friction are lower for the nanocomposites than the alloy. The abrasion, adhesion, oxidation, and delamination are the dominant wear mechanisms. The 3D topography depicts that the addition of SiC_np to the AZ91–2Ca–0.3Sb alloy results in the reduced surface roughness during the wear tests, confirming the superior wear behaviour of the nanocomposites compared to the alloy.