Subjects -> ELECTRONICS (Total: 207 journals)
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 ECTI Transactions on Electrical Engineering, Electronics, and CommunicationsNumber of Followers: 1     Open Access journal ISSN (Online) 1685-9545 Published by ECTI Association  [1 journal]
• Synchrophasor-Based Online Transient Stability Assessment Using Regression
Models

• Authors: P. K. Chandrashekhar, S. G. Srivani
Pages: 143 - 151
Abstract: An online post-fault transient stability assessment method is proposed in this study using synchrophasor or PMU measurements. Initially, a post-fault multimachine system is converted into a suitable one machine infinite bus (OMIB) system using the single machine equivalent (SIME) method. Thus, the  $P_a$-$\delta$ trajectory obtained through the OMIB system enabled a normalized transient stability index to be calculated offline. By using synchrophasor measurements before and during the fault as inputs, the regression model can be trained offline to predict the normalized stability margins. Following a fault, the synchrophasor measurements are used as input to this trained model for online stability margin prediction. If the predicted margin is negative, then the post-fault power system is indicated to be unstable. Alternatively, positive values for the predicted margin identify the system as stable. The proposed assessment method is verified using the New England (NE) 39 bus test system. The results obtained are then compared with offline simulations.
PubDate: 2022-06-21
DOI: 10.37936/ecti-eec.2022202.246763
Issue No: Vol. 20, No. 2 (2022)

• Mathematical Modeling and Numerical Analysis of SPIM Drive Using Modified
SVPWM Technique

• Authors: Vishal Rathore, Krishna Bihari Yadav
Pages: 152 - 162
Abstract: This paper presents a modified space-vector pulse width modulation (SVPWM) technique for a five-level inverter that provides complete control over the multiple space-vector voltages of a six-phase inverter. This technique involves splitting six phases into two three-phase five-level inverters connected in parallel. A six-phase induction motor (SPIM) drive with a distributed neutral is considered as the load. This paper also presents a comparative analysis between the proposed and conventional SVPWM inverter-fed SPIM drives. To investigate the analytical developments and voltage limits, MATLAB/Simulink environment was used in this study. A prototype was developed in the laboratory for analyzing the harmonic components of the phase voltages and currents. The efficacy of the proposed technique was validated by means of comprehensive experiments, and the results discussed herein.
PubDate: 2022-06-21
DOI: 10.37936/ecti-eec.2022202.246877
Issue No: Vol. 20, No. 2 (2022)

• Radio-Heat Contrasts of UAVs and Their Weather Variability at 12 GHz, 20
GHz, 34 GHz, and 94 GHz Frequencies

• Authors: Nikolay Ruzhentsev, Simeon Zhyla, Vladimir Pavlikov, Valerii Volosyuk, Eduard Tserne, Anatoliy Popov, Oleksandr Shmatko, Ivan Ostroumov, Nataliia Kuzmenko, Kostiantyn Dergachov, Olga Sushchenko, Yuliya Averyanova, Maksym Zaliskyi, Oleksandr Solomentsev, Olena Havrylenko, Borys Kuznetsov, Tatyana Nikitina
Pages: 163 - 173
Abstract: This work describes the procedure for determining the expected values of UAV radio-heat contrasts ($\Delta&space;T$) and discusses its angular dependences, as well as the estimation of UAV detection distances at four points cm and mm ranges (12 GHz, 20 GHz, 34 GHz, and 94 GHz). This paper reveals the pronounced frequency dependence on brightness temperature ($T_{b}$) and $\Delta&space;T$ of a fiberglass unmanned aerial vehicle (UAV) made from composite fiberglass materials. The quantified experiments are conducted against a sky background under various weather conditions and wave ranges. The qualitative physical interpretation of these properties and their frequency dependence is proposed, reflecting the coefficient values and radio brightness of the background. The weak influence of weather on the observed UAVs in the X and Ku bands are demonstrated along with the multiple decreasing detection characteristics and advantages of the W band under bad weather conditions (the appearance of rain or thick cloud). This work presents data on the values of UAV contrasts, observed against the background of the sky and the regularities noted could be useful for predicting the effectiveness of the proposed radiometric detection and tracking system.
PubDate: 2022-06-21
DOI: 10.37936/ecti-eec.2022202.246878
Issue No: Vol. 20, No. 2 (2022)

• Experimental Investigations into the Behavior of Scaling Factors in a
Fuzzy Logic Speed Control Induction Motor with Model Reference Adaptive
Control

• Authors: Muhamad Zamani Bin Ismail, Md. Hairul Nizam Talib, Zulkifilie Ibrahim, Jurifa Binti Mat Lazi, Mohd Shahrul Azmi Mohamad Yusoff, Baharuddin Bin Ismail
Pages: 174 - 185
Abstract: This paper presents a self-tuning fuzzy logic speed controller (FLSC) with model reference adaptive control (MRAC) for an induction motor (IM) drive system. The MRAC is examined by output scaling the factor tuner for optimum motor speed performance. A detailed investigation is carried out on the scaling factor control of the input change error and main FLSC output increment. This proposed method utilizes seven simplified rules of the 5 × 5 matrix membership functions to minimize the computational burden and memory space limitations. All simulation work is conducted using Simulink and Fuzzy Tools in the MATLAB software and the experimental testing with the aid of a digital signal controller board, dSPACE DS1103. Based on the results, the output scaling factor makes a more significant impact on the performance effect compared to the input error scaling factor. The input change error and output SF also exhibit similar behavior, indicating that a large range of UoD tuners works well in terms of capability load rejection while a small range of UoD tuners performs well in terms of rise time. The analysis includes no-load and load tests to ascertain the overshoot percentage, rise time, and settling time for transient and steady-state conditions.
PubDate: 2022-06-21
DOI: 10.37936/ecti-eec.2022202.246896
Issue No: Vol. 20, No. 2 (2022)

• A Novel Interval-Based Protocol for Time Coordination in Wireless Sensor
and IoT Networks – An Analytical Analysis

• Authors: K. L. V. Sai Prakash Sakuru, N. Bheema Rao
Pages: 186 - 196
Abstract: This paper proposes a novel interval intersection-based protocol for time coordination in wireless sensor and IoT networks. The common notion of time amid the nodes in a distributed environment can be achieved through the message exchange process, which experiences random delay (send, access, propagation, and reception), thus making the time coordination process difficult. Several researchers have proposed algorithms to handle the error in estimation using various methods. This paper analytically analyzes the proposed novel unidirectional interval intersection method for mitigating the uncertainty in the interval width. The offset and slope estimation errors are then reduced under different conditions to verify the effectiveness of the proposed coordination algorithm. The model is simulated under three different delay models: uniform, normal, and truncated exponential. Their performance is then compared in terms of coordination efficiency.
PubDate: 2022-06-21
DOI: 10.37936/ecti-eec.2022202.246901
Issue No: Vol. 20, No. 2 (2022)

• Development of Open Switch Fault-Tolerant Capability in CCS-MLI Topology

• Authors: Dhananjay Kumar, Rajesh Kumar Nema, Sushma Gupta, Niraj Kumar Dewangan
Pages: 197 - 205
Abstract: Multilevel inverters (MLIs) are very popular in renewable energy applications and other DC to AC conversion systems due to their reliability, reduced voltage stress, low total harmonic distortion (THD), reduced filter size, low electromagnetic interference, etc. Consequently, the photovoltaic (PV) generation systems, mainly installed in remote areas, require highly reliable systems. The high failure rate of sources and power semiconductor devices results in very low reliability for inverters used in PV generation systems. The aim of this study is to develop a five-level MLI topology with fault-tolerant (FT) characteristics. Therefore, a highly resilient fault-tolerance topology, based on a cross-connected source-based MLIs (CCS-MLI) structure, is proposed in this paper. The developed CCS-MLI topology can tolerate open switch faults in any single switch failure. The proposed system and results developed in a MATLAB/Simulink environment are discussed under normal and faulty states. The simulation results are validated experimentally. Finally, the quantitative and qualitative superiority of the proposed CCS-MLI is demonstrated through the comparative analysis of other recent topologies.
PubDate: 2022-06-21
DOI: 10.37936/ecti-eec.2022202.246903
Issue No: Vol. 20, No. 2 (2022)

• Sensitivity Analysis of Switched Reluctance Motor for Potential
Application in Electric Vehicles Considering Weight Factor

• Authors: Karunakaran Vijayalakshmi, Kandadai Nagaratnam Srinivas
Pages: 206 - 215
Abstract: The switched reluctance motor (SRM), an environmentally friendly machine, is suitable for application in electric vehicles (EV) in recent days. This paper presents an SRM sensitivity analysis focussing on weight of the materials used for stator and rotor for use in electric vehicle application. Two SRM structures are considered, namely normal stator tooth and tapered stator tooth. Thirteen materials widely used in the SRM are considered for these two structures to perform the proposed sensitivity analysis. The major outputs of torque, speed, power, iron loss, efficiency, copper loss, and power factor are gathered through finite element analysis (FEA) simulation. Each of the 13 materials are examined for normal tooth and tapered tooth geometrical structures. The results are discussed, focusing on the fitness of the considered SRM structures for EV application. As weight-sensitive vehicles, the materials used in EVs are compared against the respective motor weights obtained through analysis to recommend the lightest motor for production.
PubDate: 2022-06-21
DOI: 10.37936/ecti-eec.2022202.246904
Issue No: Vol. 20, No. 2 (2022)

• Two-Axis Solar Tracker Applied With All-Electric Ship

• Authors: Nattapon Boonyapakdee
Pages: 216 - 224
Abstract: The all-electric ship (AES) offers new hope for the reduction of fuel consumption and carbon emissions. To fully exploit the photovoltaics (PVs) installed on the AES, the two-axis solar tracker is proposed to find the best tilt and surface azimuth angles of PV panels. The tilt angle is computed by particle swarm optimization (PSO) regarding the time and ship location. The surface azimuth angle is adjusted according to the hemisphere. The dynamic performance of the proposed solar tracker is evaluated using MATLAB/Simulink simulation. According to the simulation results, the proposed solar tracker can obtain maximum energy all day, while the voyage time, fuel consumption, and carbon emissions are significantly reduced. Moreover, the proposed solar tracker can effectively operate under communication delay caused by the global positioning system (GPS).
PubDate: 2022-06-21
DOI: 10.37936/ecti-eec.2022202.246905
Issue No: Vol. 20, No. 2 (2022)

• EEG-based Biometric Authentication Using Machine Learning: A Comprehensive
Survey

• Authors: Tarik Bin Shams, Md. Sakir Hossain, Md. Firoz Mahmud, Md. Shahariar Tehjib, Zahid Hossain, Md. Ileas Pramanik
Pages: 225 - 241
Abstract: An electroencephalogram (EEG) is a measurement that reflects the overall electrical activity in the brain. EEG signals are effective for biometric authentication and robust against malware attacks and any kind of fraud activities due to the uniqueness of the signals. Significant progress in research on EEG-based authentication has been achieved in the last few years, with machine learning being extensively used for classifying EEG signals. However, to the best of our knowledge, there has been no investigation into the overall progress made in such research. In this paper, the literature on the various factors involved in state-of-the-art biometric authentication systems is reviewed. We provide a thorough comparison of different machine learning biometric authentication techniques. The comparison criteria include the research objectives, machine learning algorithms, computational complexity, source of brainwaves, feature extraction methods, number of channels, and so on. Alongside the discussion of existing works, directions for future research are suggested to improve authentication accuracy. This paper provides an in-depth discussion of different advanced biometric authentication techniques, and a vivid picture of state-of-the-art machine learning-based biometric authentication techniques using EEG.
PubDate: 2022-06-21
DOI: 10.37936/ecti-eec.2022202.246906
Issue No: Vol. 20, No. 2 (2022)

• Performance of DSSS Signal Transmission with SCM over Low-Frequency MMF
Passbands

• Authors: Jaruwat Patmanee, Surachet Kanprachar
Pages: 242 - 255
Abstract: The transmission of a high data rate signal over low-frequency passbands of multimode fibers is studied in this paper. The subcarrier multiplexing (SCM) technique is applied to mitigate the frequency-selective nature of the passbands, at which many nulls can degrade the signal transmission. The subcarrier frequencies must be chosen appropriately, especially for some low-frequency passbands; otherwise, poorly received subcarrier signals will be obtained, affecting the entire transmission. Rather than transmitting many subcarrier signals over these passbands, the direct sequence spread spectrum (DSSS) technique can be adopted. In this work, a high data rate signal is transmitted over 1 km of multimode fiber using the 3-dB modal band and six other low-frequency passbands. The signal is separated into four sub-signals transmitted over four different channels: the 3-dB modal band, two low-frequency passbands, and one passband (containing four low-frequency passbands). In the last passband, the sub-signal is transmitted using the DSSS, while the other sub-signals are transmitted through amplitude shift keying (ASK) modulation. The performance of the system is determined using the bit error rate (BER). The findings reveal that by applying the DSSS to some low-frequency passbands, robustness is obtained in the subcarrier frequency for use in the DSSS passband. A BER lower than 10-9 with a total data rate of 600 Mbps is achieved. This data rate is three times higher than the data rate obtained by the 3-dB modal band. This performance is achieved without applying any error-correction code.
PubDate: 2022-06-21
DOI: 10.37936/ecti-eec.2022202.246907
Issue No: Vol. 20, No. 2 (2022)

• Multi-objective Dynamic Expansion Planning of Active Meshed Distribution
Network: Sizing, Siting, and Timing of Hub and Voltage Regulators

Pages: 256 - 268
Abstract: Distribution network expansion planning is a technique for managing the system effectively in the face of future challenges. This work investigates the design of a mesh distribution network to allocate substations, DGs, voltage regulators, feeder routing, switch placement, and the integration of multiple energy carrier systems. Dynamic modeling for multi-objective system expansion planning is proposed in this study to identify the optimal plan and operational strategy. The uncertainties related to DGs, electricity, heat load, and their prices are considered in the planning process. A 54-Bus distribution network is applied to evaluate the methodology and discuss the results.
PubDate: 2022-06-21
DOI: 10.37936/ecti-eec.2022202.246908
Issue No: Vol. 20, No. 2 (2022)

• A New Multivariate Linear Regression MPPT Algorithm for Solar PV System
with Boost Converter

• Authors: P. Venkata Mahesh, S. Meyyappan, Rama Koteswara Rao Alla
Pages: 269 - 281
Abstract: Operating solar photovoltaic (PV) panels at the maximum power point (MPP) is considered to enrich energy conversion efficiency. Each MPP tracking technique (MPPT) has its conversion efficiency and methodology for tracking the MPP. This paper introduces a new method for operating the PV panel at MPP by implementing the multivariate linear regression (MLR) machine learning algorithm. The MLR machine learning model in this study is trained and tested using the data collected from the PV panel specifications. This MLR algorithm can predict the maximum power available at the panel, and the voltage corresponds to this maximum power for specific values of irradiance and temperature. These predicted values help in the calculation of the duty ratio for the boost converter. The MATLAB/SIMULINK results illustrate that, as time progresses, the PV panel is forced to operate at the MPP predicted by the MLR algorithm, yielding a mean efficiency of more than 96% in the steady-state operation of the PV system, even under variable irradiances and temperatures.
PubDate: 2022-06-21
DOI: 10.37936/ecti-eec.2022202.246909
Issue No: Vol. 20, No. 2 (2022)

• Behavior of the Social Spider Technique on Network Reconfiguration

• Authors: Dipu Sarkar, Pushpanjalee Konwar
Pages: 282 - 295
Abstract: The goal of this paper is to offer a new strategy for solving the network reconfiguration problem with the aim of decreasing real power loss and enhancing the voltage profile in the distribution system. Social spider optimization (SSO), a new swarm algorithm, is employed to concurrently reconfigure and find the best network. The proposed method was tested on 30-bus mesh and 33-bus radial distribution systems at fixed load levels. To show the performance and efficacy of the suggested method, it was compared to optimization methodology, such as the genetic algorithm, harmony search algorithm, Kruskal's maximal spanning tree, discrete evolutionary programming, and cuckoo search algorithm. The findings reveal that SSO is a strategy worth investigating for tackling the network reconfiguration problem.
PubDate: 2022-06-21
DOI: 10.37936/ecti-eec.2022202.246910
Issue No: Vol. 20, No. 2 (2022)

• An Advanced Neuro-Fuzzy Tuned PID Controller for Pitch Control of
Horizontal Axis Wind Turbines

• Authors: Sachin Goyal, Vinay Kumar Deolia, Sanjay Agrawal
Pages: 296 - 305
Abstract: Modern power systems comprise a variety of generating systems, including conventional thermal power stations and advanced renewable generating sources, one contender being a wind energy conversion system (WECS). Blade pitch control is an important part of the highly non-linear WECS. Many control strategies have been proposed by researchers around the globe. Current research work focuses on developing a control structure for a non-linear pitch control system using an advanced neuro-fuzzy tuned PID (NF-PID) controller. This approach utilizes the simplicity of a PID controller and the power of a soft computing technique like neuro-fuzzy to handle non-linearity. The model in this study is developed on the MATLAB Simulink platform and the obtained simulation results satisfy the requirements of constant output power even if the wind speed input changes abruptly.
PubDate: 2022-06-21
DOI: 10.37936/ecti-eec.2022202.246911
Issue No: Vol. 20, No. 2 (2022)

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