Majlesi Journal of Electrical Engineering
Volume:15 Issue: 4, Dec 2021

This work is designed to study the energy management of a Proton Exchange Membrane Fuel Cell (PEMFC), which is based on the activity and management of water and its effect on the electrolyte membrane (FC) as a function of the influx of hydrogen and oxygen, by taking into account the influence of humidification on the implementation of this electrical system to avoid drying and flooding that can cause deterioration of the FC. Th e cell voltage and system efficiency are also influenced by current density and operating temperature, and simulation results on MATLAB / Simulink are discussed.

In this article , the issue of sensor fault detection and identification with sensory information is considered. This is due to the dependence of successful Fult Detection (FD) method on correct sensory measurements that suffer from various soft sensory faults such as bias, drift, scaling factor, and hard faults that can be detected independently. They are not detectable but can be combined with other sensors. To solve this issue , firstly , a state space m odel for pump subsystem was constructed using the electrical simulation method. Then, the sensory soft faults are modeled and amplified to electro - pump state space model. Both system states and amplified sensory soft faults are then estimated using an Ext ended Kalman filter (EKF) in which nonlinear model of the induction motor is linearized around the estimated states. Information of current, angular velocity (encoder) and pressure sensors are melted for this goal . The efficiency of the method is firstly evaluated through simulation and then experimental results are provided from our laboratory setup . Measured volume cu rrents, flow , and pressure are compared with simulated signals, and results show that the proposed model is able to successfully describe the laboratory system with good precision . These results show that the model can describe the electro - pump dynamic with good precision.

Oscillation behavior is usually experienced in all power grids as an inherent characterization related to their very existence. Inter - area oscillations are considered to be the most likely to jeopardize the synchronous integrity in power grids. They cause declining the quality conditions of the transmitted power which could have adverse impacts on big consumers’ load fed directly from the transmission grid. Therefore, the prime target of this investigation is to alleviate the power oscillations resulting f rom the different grid disturbances. This aim is accomplished by utilizing a fuzzy based resistor braking strategy taking three energization signals into consideration. Additionally, various time latencies are considered to examine and evaluate the proposi tioned strategy under these conditions. Also, declined inertia situations resulting from the escalated incursion levels of grid - connected photovoltaic plants are considered to examine the propositioned strategy from a futuristic operational perspective. Fo r examining the effectivity of the propositioned strategy, non - linear time - domain simulation studies are conducted on Kundur benchmark via MATLAB/Simulink platform. Five comparative simulation studies of the benchmark after being subjected to variety of pe rturbations demonstrate the effectivity of propositioned strategy.

Grey Wolf optimizer is a well - known metaheuristic technique but it faces the problem of premature convergence, trapping in local optima and poor balance between exploration and exploitation. Hence , various modifications have been proposed over past few years. One such modification is modelling the prey position as dynamic in nature as shown in GWOLF. However , still it has been observed that to get better solutio n , GWOLF needs to be modified too , hen ce an improved version of GWO (IGWO) is proposed. IGWO has the advantage of both GWO and GWOLF. In this paper, IGWO is used to solve Dynamic Economic Dispatch (DED) problem. IGWO is having a better balance between exploitation and exploration for the compl ex problem such as Dynamic Economic Dispatch (DED) taking into account of valve - point effect, transmission losses and ramp - rate limits with and without Electric Vehicles (EVs). T he efficiency of the algorithm is demonstrated on solving different DED proble ms for 5 generator and 15 generator test systems with and without losses along with different charging profile distribution of electric vehicles. The results showcased by IGWO is compared with the other algorithm. The results obtained by IGWO algorithm ad opted in solving dynamic economic dispatch problem is giving competitive results as compared to the results given by other algorithm present in literature.

Advanced Metering Infrastructure (AMI) is an essential segment of the smart grids that is responsible for gathering, measuring and analyzing the electricity demand . Energy losses in the electricity distribution and transmission network and electricity theft detection are major challenges of electricity suppliers around the world. The analysis of consumption data related to the customers is one of the essential resources to identify electricity thieves. In this paper, the Crow Search Algorithm (CSA) is improved and the factors weight ( 푤 ) a nd awareness probability ( 퐴푃 ) are obtained dynamically and used to adjust the parameters 퐶 and 훾 related to the Support Vector Machine (SVM). The results illustrate that the ICSA - SVM framework has acceptable performance and detects fraudulent customers with high accuracy.

Although Named Data Network (NDN) has made a bright future in the Internet for high volume of requests by many users, how to send a request package (I - Pkt ) consciously from the consumer to the p roducer and returning the data package (D - Pkt) inversely is still one of its most important challenges. According to the recent limited researches, using service quality parameters beside an optimization algorithm li ke ant colony to find the optimal path has been an appropriate response to solve this problem. Insufficient attention to service quality parameters to find an optimal path is a problem to be focused on. In line with this, this study has addressed forwardin g using the Intelligent Water Drops (IWD) optimization algorithm. In this algorithm, the best possible path based on many parameters related to path quality like cost, delay and number of steps taken by the package (I - Pkt) will be selected. In other words, the water drop movement tries to find the optimal path through the amount of soil collection in the path or the velocity rate. The results of simulating in ndnSIM simulator show that comparing the ant colony, it has been improved in cost parameter on aver age by 23%, in hit ratio parameter by 24% and in hop count parameter by 13%. The general result is increasing service level quality in NDNs.

The use of wireless sensor networks is becoming more and more important due to the COVID - 19 pandemic and the living conditions of human beings today. The three main goals in designing this type of network are to reduce energy consumption, choose the shortest route and choose a reliable route for data transmission. In this paper, these th ree goals are considered in routing. Due to the fact that this type of network is exposed to many attacks, identifying malicious nodes and removing them creates security in this type of network. This paper presents an energy - aware and trusted - based routing method using learning automata and an evaluation function. Learning automata identifies trusted nodes (to send data) and malicious nodes using the corresponding evaluation function. The evaluation function considers the residual energy, the node's trust a nd the number of hops to the sink parameters. Thus, the data reaches its destination in a safe and reliable way. The evaluation results of the proposed method show an improvement in the performance of this method compared to other relevant methods.

In this paper, the design and optimization of a cascaded common source f our - stage millimeter wave amplifier in a 130 nm CMOS technology has been presented. First, Pi - shaped wideband impedance matching network s (IMNs) were used in the Input/Output Impedance Matching Networks (IOIMNs) and inter - stages . Next , single stubs were converted to symmetrical double stubs in the IOIMNs , an d an ultra - wideband inductor replaced each stub . Ultra - wideband inductors were also used in series in the inter - stage IMNs to achieve a higher gain in the wider frequency bandwidth. Then, t he impedance matrices of IOIMNs and inter - stage were calculated using Planar Circuit Analysis (PCA), which is based on the planar waveguide model and Segmentation/Desegmentation Methods ( SDSM s ) . Finally, by optimizing the length and characteristic impedance of each segment of microstrip line in the IMNs through using an intelligent optimization algorithm in MATLAB , the excellent IMNs were designed , which resulted in an amplifier with 푆 11 min = − 25 . 3 푑퐵 , 푆 22 min = − 20 . 6 푑퐵 , and 푆 21 max = 30 . 5 푑퐵 in the frequency range of 57 - 64 GHz. With this design method , in addition to incorporating the effect of discontinuities, the fringing fields at the edges of the microstrip as well as the conductor and dielectric losses , the effect of dispersion would be minimized by choosing a substrate whose thickness is much sma ller than the wavelength and its relative permittivity is low.

In this paper, for the first time, Threshold - voltage - adjust - implant is engineer ed to optimize body current in 45 nm Silicon - on - Insulator (SOI) MOSFET. The peak value and peak position concentration of the Gaussian implant under the gate oxide in the silicon body a re varied in order to optim ize the body current in SOI technology. The variations affect the devices ’ threshold voltage s. In order to make a fair comparison, the gate work function i s changed to obtain the same threshold voltage within the entire simulated devices and operating regi me. The body current i s monitored while the it i s swept from 0 V to 1.5 V. The maximum of the body current i s observed at V DS =1.5 V. The concentration of Threshold - voltage - adjust - implant peak value i s changed from 1.7E17 cm - 3 to 7E18 cm - 3 . The peak positio n of the implant i s varied from 0 nm right under the gate oxide to 20 nm below the gate oxide and silicon surface. It i s observed that the body current is minimized at the peak value concentration of 7E17 cm - 3 and peak position of 0 nm. This occurs by prop er choice of the gate work function and gate material. The minimization of body current leads to the less requirement for the number of body contacts and smaller gate parasitic capacitance which, in turn, concludes higher operating frequency and larger f T