Journal of Applied Research in Electrical Engineering
Volume:1 Issue: 2, Summer and Autumn 2022

The ever-increasing threat of air pollution as a serious health hazard throughout the world requires measuring prior to devising a structured solution. Air quality monitoring systems measure the amount of particulate matter such as particles and hazardous gases in the air. Information is required on the quality of air monitoring and dust detection system in order to make managerial decisions to improve environmental conditions and prevent and treat diseases caused by dust. The present study aims to develop a simple, highly sensitive, and economical monitoring system for the determination of air particulate. In this paper, we develop a real-time ad hoc wireless airborne particle monitoring system using the IEEE 802.15.4 low power sensor network technology called RTWSM, featuring a low-cost sensor node for mass production. Its dynamic features of high scalability and ad hoc architecture enable the design to provide significantly more useful information under all environments, including indoor or outdoor monitoring applications. The performance of the proposed monitoring sensor system is evaluated in environmental and industrial occupation debates to monitor the PM2.5 particle data. The results confirm that the proposed experimental setup works well for local air pollution monitoring and could be extended to automation industrial applications.

This paper uses the coordination between the reactive power of a solid oxide fuel cell (SOFC) and a battery to control the frequency within an islanded microgrid. By this coordination, the microgrid frequency regulation becomes faster and better during contingencies. Moreover, the energy storage capacity, which is usually required for the frequency control of islanded microgrids, has significantly been reduced. Furthermore, there will be no need to consider reserve capacity in renewable sources for frequency control. Therefore, renewable energy sources can be operated at their maximum power point. Also, this paper introduces a new frequency-reactive power control concept and a related coefficient that shows the degree of dependence of the microgrid frequency on the injected reactive power changes at each bus. This coefficient determines the priority of buses for the installation of reactive power control devices to control the frequency of the microgrid. Simulation studies have been performed in the MATLAB/Simulink environment. The results show the applicability and accuracy of the proposed coefficient and demonstrate the effectiveness of the coordinated control of reactive power between the SOFC and the battery for frequency control.

Direct Position Determination (DPD) is known as an optimal, single-step technique for localizing co-channel signal sources since it processes the data gathered from all the array receiver elements together. In contrast, the commonly used radio location techniques include two independent stages. First, they estimate some initial parameters like direction, time, time-difference, frequency of arrival, etc., or their combination, and second, they localize signal sources using the triangulation of loci generated by the first stage. This disjoint structure leads to the sub-optimality of conventional localization algorithms. In this paper, we compare the Location root-mean-square-Error Lower Bounds (LELB) for DPD and position finding by DOA (PF-DOA) to prove the superiority of DPD over PF-DOA, which are commonly used for tactical fields or outdoor applications. Moreover, we demonstrate the advantages of DPD for indoor localization applications compared to PF-DOA techniques in terms of localization accuracy. We also introduce the single-group-array (SGA) structure for DPD in indoor applications and reveal that it outperforms both the PF-DOA and DPD with a classical multi-group-array (MGA) structure.

Partial Discharge (PD) measurement is one of the main methods for condition monitoring of Gas Insulated Switchgears (GIS). Internal Ultra High Frequency (UHF) sensors can be applied for capturing PD propagated electromagnetic signals within the GIS. PD sensor placement inside the GIS is one of the main challenges for designing the online PD measuring system. For this aim, the impacts of different GIS components on the propagated PD electromagnetic wave should be studied. In this paper, different PD sensor position angles (with respect to PD sensor), are applied for investigating their sensitivity on the measuring PD electromagnetic wave. Two distinguishable parameters from the calculated PD electromagnetic waves, the first rated electric field and the signal’s power over the two frequency ranges (0.3-2 GHz and 0.3-3 GHz) are used for analyzing and quantifying the calculation results. The impacts of different enclosure diameters, different types of spacers, and various disconnector contact gap distances (under different voltage levels) on this wave propagation are studied. Additionally, the two standard GIS busbar profiles, named: L-shape and T-shape; are discussed in this paper. The results of this study show that the attenuation degree of the measured PD EM waves is strongly influenced by the busbar dimensions and its components configurations. The GIS busbar designer can employ these results to select the proper PD sensors and their installation locations.

This paper develops a new model for the optimal placement of switches (both manual and automatic ones) in distribution networks to simultaneously reduce energy loss and improve network security. Expected energy not supplied (EENS) is assumed as the security index, and a method is developed for more exact calculation of this index regarding drastic climatic changes along with global warming and the resultant effects on both power consumption patterns and power network occurrence. The objective function of the problem is minimizing investment and maintenance costs, the cost of energy loss, and EENS cost. The suggested model can locate optimal places for installing the switches and their seasonal closed and open states so that the total costs can be minimized. The model is implemented on two test networks and evaluated under different scenarios. According to the results, despite the higher costs of automatic switches, the application of automatic switches is more economical in low-security networks for improving network security.

This paper presents a novel method to discriminate between the magnetizing inrush and external and internal fault currents in power transformers. Fault type identification and faulted phase selection are also possible by the proposed algorithm. The proposed method has two main parts. First, by means of S-transform, which is the most accurate method in the field of signal processing, some useful features are extracted from the input signal. Then, the extracted features are converted to some numerical indices. In the second part, an effective decision maker is needed to classify the input signal. One of the best methods, which have been used for decision-making applications is fuzzy logic. So, the numerical indices are used as inputs for the fuzzy system. The output of the fuzzy system not only can reveal whether the input signal is the magnetizing inrush, external or internal fault, but it can also identify the fault type when there is an internal fault. Finally, the faulted phases can be identified with a supplemental algorithm. To generate the test signals, a three-phase transformer is modeled in PSCAD/EMTDC. Testing the proposed algorithm by different simulated data shows the robustness of the proposed method in the transformer differential protection.

Surface plasmon resonance (SPR) sensors have been widely considered for their sensitivity, accuracy, and appropriate response speed. This article simulates and analyzes the effects of phosphorene nanotubes (PNTs) layer with various diameters and rolling directions on the structure of SPR biosensor in the Lumerical software environment. The main structure is based on the structure of Kretschmann and the use of the BK7 prism, a gold (Au) layer, and the end layer of phosphorene nanotubes. The proposed SPR biosensor reflectance curves are obtained, analyzed, and compared for various modes of refractive index n = 1.33 and 1.339, resembling a neutral watery medium and a bacterial medium, respectively. The results show that the minimum reflection is achieved for 30 nm Au at an SPR resonance angle of θ = 71.59° while by adding phosphorene nanotubes, it is observed that at a diameter of 10.08 A and an armchair rolling direction, the configuration on the Au layer becomes favorable. The minimum reflectance of 0.199 is observed for the armchair phosphorene nanotubes (10.08A) layer over 30 nm Au. The combination also provides a sensitivity of 152°/RIU for Δn = 0.009 with a high detection accuracy of 0.079. The results demonstrate that the layer of phosphorene nanotubes has a positive effect on SPR biosensors, and it can be used as a controlling factor in SPR biosensors.

With the presence of distributed energy resources in the microgrid, the problem of load-frequency control (LFC) becomes one of the most important concerns. With changing the parameters of the microgrid components as well as the disturbances forced to the grid, designing a suitable LFC becomes more difficult. In this paper, the design of a Robust model predictive controller (RMPC) based on the linear matrix inequality as a secondary controller LFC system is discussed for controlling a microgrid on the shipboard. The main purpose of the proposed method is to improve the frequency stability of the microgrid in the presence of disturbances and the uncertainty of its parameters. The proposed controller simulation results, in several different scenarios, considering The uncertainty of the microgrid parameters as well as the input disturbances are compared. The main controllers are the fuzzy proportional-integral type1 and 2, and multi-objective multi-purpose functions optimized with the MOFPI (MBBHA), MOIT2FPI (MBHA) algorithm. The effectiveness of the proposed method in terms of The response speed and reduction of fluctuations and overcome uncertainties of the parameters, as well as robustness to disturbances, are discussed. Simulation is implemented in MATLAB software. The proposed method reduces the frequency oscillations caused by disturbances on the microgrid by 68% (68% improvement over other methods used in this field). Also, using this method, the damping speed of microgrid frequency fluctuations is increased by 53% (performance improvement).

Internet of Things (IoT)-based energy management systems (EMSs) are considered a new technology in which consumers can manage their electricity payments according to their preferences, such as reducing costs or increasing satisfaction. Each consumer has its own program for communicating with a central control unit. In addition, the central control unit that is responsible for energy pricing can access consumer information and network performance status through the IoT infrastructure. Therefore, technical analysis can be performed using big data to determine the optimal price in order to make a compromise between the buyer and the goals of the distribution system operators. This paper presents a model to accurately assess the impact of pricing on the behavior of IoT-based energy systems. Then, according to the load specifications of each item and the technical limitations of the distribution network, the best time to use pricing is determined. The results show that the higher the price variance, the more discomfort the consumer and the lower the daily payment. Therefore, in this paper, the main goal of energy management is to minimize the total weight of the costs paid and their discomfort level. The paper could facilitate further penetration of IoT-based EMSs into smart grids. The study was performed on an IEEE standard 33-bus network. Optimization was implemented using YALMIP and MOSEK toolboxes. Therefore, it can be concluded that IoT technology allows consumers to enjoy the benefits of the network and makes optimal consumption management possible.

The electrocardiogram is affected by various noises and one of the most important of which is 50 Hz power-line noise. On the other hand, it is necessary to use a battery in the portable device and so it requires the use of low power consumption circuits. Therefore, one of the challenges ahead when designing this type of device is the use of energy-saving filters with the ability to integrate devices and attenuate unwanted signals properly. This paper presents a low-power tunable sixth-order band-stop filter that does not need the off-chip capacitors. The filter structure is based on operational transconductance amplifiers (OTA) and integrated capacitors. Also, it is possible to change the central attenuation frequency of the proposed filter using bias voltage of the transconductance amplifiers. The proposed band-stop filter is designed and simulated in 180 nm CMOS technology at the transistor level. The simulation results show that the proposed filter can attenuate unwanted signals at 50 Hz by 102 dB while the maximum capacitance used in the filter is 54 pF. The power consumption of the proposed band-stop filter is 13.1 nW at a supply voltage of 1.8 V.

The mapping of DNA subsequences to a known reference genome, referred to as “short-read mapping”, is essential for next-generation sequencing. Hundreds of millions of short reads need to be aligned to a tremendously long reference sequence, making short-read mapping very time consuming. Day by day progress in Next-Generation Sequencing (NGS) is enabling the generation of DNA sequence data at ever faster rates and at low cost, which means a dramatic increase in the amounts of data being sequenced; nowadays, sequencing nearly 20 billion reads (short DNA fragments) costs about 1000 dollars per human genome and sequencers can generate 6 Terabases of data in less than two days. This article considered the seed extension kernel of the Burrows-Wheeler Alignment (BWA) genomic mapping algorithm for accelerating with FPGA devices. We have proposed an FPGA-based accelerated implementation for the seed extension kernel. The Smith-Waterman algorithm is used during the seed extension to find the optimum alignment between two sequences. The state-of-the-art architectures use 1D-systolic arrays to fill a similarity matrix, based on the best score out of all match combinations, mismatches and gaps are computed. The cells on the same anti-diagonal are calculated in parallel in these architectures. We propose a novel 2-dimensional architecture. Our new modified algorithm is based on two editing and calculating phases. In each step of calculation, some errors may occur in which all the cells on the same row and the same column are computed in parallel and, thereby, significantly speed up the process. Needless to say, these probable errors will be omitted before the next step of calculation begin. Our simulation results show that the proposed architecture can work with up to 312 MHz frequency in Synopsys Design-Compiler for 180-nm CMOS technology and be up to 570x and 1.4x faster than the software execution and the 1D-systolic arrays, respectively.

The output of a Digital Delta-Sigma Modulator (DDSM) is always a periodic signal and the input is constant. A hybrid DDSM is a premiere to its conventional counterpart for having a potential speed, by the choice of its smaller bus. This paper offers an implementation for multi-stage noise shaping (MASH) DDSMs that includes four modulators named hybrid DDSM-1, DDSM-2, DDSM-3, and DDSM-4. Also, it introduces a new solution, where the desired ratio in fractional frequency synthesizers is formed by combining four different modulos. The first stage modulator is a programmable modulus EFM1 and has a modulus M1 that is not a power of 2. The second, third, and fourth stage modulators are modified MASH 1-1, multi-modulus MASH 1-1-1, and the efficiently dithered MASH 1-1-1-1 modulator that has conventional modulus  M2, M3, and M4, respectively. The M1 modulus is optimally selected to synthesize the new structure of the desired frequencies. Design results confirm the suppositional predictions. In addition, the results of the circuit implementation proposed method offer a 17% reduction in hardware complexity.