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International review of electrical engineering
Praise Worthy Prize
International review of electrical engineering

Praise Worthy Prize

双月刊

1827-6660

International review of electrical engineering/Journal International review of electrical engineering
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    Emulation Technique for Wind Turbines Using Servo Motor and Induction Motor

    Tammaruckwattana S.Taecharoenwiriyakun S.Tammarugwattana N.Suppaadirek N....
    162-177页
    查看更多>>摘要：© 2024 The Authors.This paper proposes the emulation technique for wind turbines using two types of motor, servo motor, and induction motor. The focus is on simulating the work process of wind turbines at multi-wind velocity to test the capacity and efficiency of generating three-phase electricity. The wind turbine emulator was created by using a program and mechanical parts. The goal of this emulator is to check the efficiency of wind turbine blades at different wind speeds and to test the accuracy of the simulation method by using a different motor. The first emulator uses a 400-Watt synchronous generator from a wind turbine connected to a 400-Watt servo motor controlled by a servo amplifier. The second emulator uses a 400-Watt synchronous generator from a similar wind turbine connected to a 400-watt induction motor installed with an encoder controlled by an inverter. Motor torque is calculated by using mathematic equations from the LabVIEW program, and the data of the wind turbine blade is simulated by using the ANSYS program.
      原文链接:
    • NETL
    • NSTL

    Performance Comparison of AVPSO and Firefly MPPT Algorithm in Solar Panel Optimization

    SuyantoAsy'ari M.K.Mohammad L.
    178-187页
    查看更多>>摘要：© 2024 Praise Worthy Prize S.r.l.-All rights reserved.The success of the optimization algorithm performance in the case of MPPT solar panels significantly led to a development of a lot of model variations and new algorithm modifications. The application of the right algorithm will greatly affect the output power of the solar panel, tracking speed, and stability of the final value. This study focuses on comparing the performance of AVPSO and Firefly optimization algorithms through PSIM and hardware simulations in a tropical environment with irradiated temperatures. The results of the hardware test show that both algorithms are able to get the same MPPT power results, while AVPSO can produce more power in the PSIM simulation test. In terms of tracking speed, AVPSO excels in hardware testing, while Firefly excels in PSIM simulation tests. The effect of MPPT tracking characteristics on the hardware shows that AVPSO has a temperature rise of two degrees Celsius lower than the firefly algorithm. The results show that the hardware tests and PSIM simulation from AVPSO as a new modified algorithm from PSO has advantages over the firefly predecessor algorithm in the MPPT case.
      原文链接:
    • NETL
    • NSTL

    Power Quality Analysis of a Photovoltaic Power Plant Connected to the Distribution Network: a Case Study of a 2 MWp Photovoltaic Power Plant

    Bouzbiba A.Taleb Y.Abbou A.
    188-196页
    查看更多>>摘要：© 2024 Praise Worthy Prize S.r.l.-All rights reserved.This article presents an in-depth analysis of the impact of connecting a photovoltaic (PV) power plant to the distribution networks (MV). The specificity of the study lies in the particular case of the connection of a 2 MWp photovoltaic power plant to the medium voltage network (22 kV). The power supply for this connection is provided by a three-phase inverter, a crucial element that can influence power quality by causing various disturbances such as harmonics, imbalances, and flickers. The context of the study explores power quality records, obtained via a quality analyzer installed in the connection between the inverter and the power grid, and thus providing an in-depth understanding of fluctuations and anomalies during the operation of the PV plant, particularly at the beginning and end of the day. This analysis includes a detailed assessment of power quality, highlighting both grid disturbances and those generated specifically by the PV plant installation. The results will contribute to a better understanding of the challenges involved in integrating PV power plants into distribution networks, paving the way for solutions and adjustments needed to ensure harmonious and efficient cohabitation between renewable energies and existing electricity infrastructures.
      原文链接:
    • NETL
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    Different Thermal Models for Calculating Transformer Hot-Spot Temperature and Comparing with Measurement Data

    Guri K.Najdenkoski K.
    197-207页
    查看更多>>摘要：© 2024 Praise Worthy Prize S.r.l.-All rights reserved.Ambient temperature, top oil temperature, and load are the three main parameters based on which the hot spot transformer temperature can be calculated. The operating temperature is of great importance for the transformer, not only in determining its power but also during the period of operation, because the increase of temperature causes deterioration of the characteristics of the insulation system, mainly in the windings and insulation oil. This paper focuses on hot spot temperature estimation based on calculation and measurement data. In this case, IEC and IEEE standards, Susa’s and Swift's model, and MATLAB/Simulink are used for the validity of the improved thermal model that analyzes the effect of wind velocity. The thermal performance was improved after incorporating wind velocity. As a reference, it was analyzed at 16:00 (h), when the load is a maximum of 1.18 p.u., at the same ambient temperature, a reduction of the temperature of the hot spot was observed by 10 °C lower or 9 % compared to the measured hot spot. The estimated hot spot temperature data are compared with measured data of a power transformer in operation. The proposed model has been validated using measurement data from a 31.5 MVA, 110/10.5 kV, Ynyn0d5 power transformer.
      原文链接:
    • NETL
    • NSTL

    HILBERT Transform as a Technique to Distinguish Between Broken Rotor Bar Fault and Load Torque Variation

    Makhdoum B.Benouzza N.
    208-216页
    查看更多>>摘要：© 2024 Praise Worthy Prize S.r.l.-All rights reserved.Motor Current Stator Analysis (MCSA) is widely used in the field of induction machine diagnostics due to its proven effectiveness in detecting various faults that can affect these machines. The broken rotor bar fault is one of the most common faults encountered in industry. This fault is characterized by its signature on the stator current spectrum, appearing as sidebands around the supply frequency at twice the slip frequency and its multiples. Indeed, despite the advantages of MCSA, it has limitations, as low-frequency torque oscillations that can induce frequency components similar to those of rotor faults when analyzing the motor current signal, which can cause false indications. This paper deals with a novel method for discrimination between broken bar fault and load torque variation of induction motors. This new method tracks the characteristic harmonic of the fault in the spectrum of the stator current envelope indicator signal. An in-depth analysis is conducted to emphasize the uniqueness of the proposal. This analysis aims to combine the Hilbert transform with the current indicator. The results obtained have showed that harmonics related to the rotor bar fault, such as 2sfs, appear around the DC component, while no signatures related to load torque variation exist on the spectrum of the stator current envelope indicator signal. The effectiveness of the proposed approach is validated through both simulation and experimental results.
      原文链接:
    • NETL
    • NSTL

    Machine Learning Approaches for Predicting Excitation Current in Synchronous Motors

    Marji G.S.
    217-225页
    查看更多>>摘要：© 2024 Praise Worthy Prize S.r.l.-All rights reserved.The excitation current has a significant impact on the operational efficiency of synchronous motors, which hold a pivotal position in several industrial applications. The main contribution of this study has been to conduct a comprehensive analysis of various machine learning models to make accurate predictions regarding the excitation current. Normalization and feature selection have been applied to the dataset before using various regression models, including Linear, Lasso, Ridge, and Elastic Net Regression, as well as Decision Tree and Random Forest Regression. The Random Forest Regression model demonstrates a test accuracy of 97.01%, indicating its superior performance compared to other models. The good performance of the linear models indicates a linear relationship between the predictors and the excitation current. Regression model has achieved 98% accuracy during training. The findings from this work have extensive implications, encompassing enhanced energy efficiency, extended motor lifespans, and reduced instances of operational interruptions. While the models show promise, it is crucial to recognize their limitations and the need for more research, particularly in the realms of nonlinear models and empirical verification in real-world scenarios.
      原文链接:
    • NETL
    • NSTL

    Improving Thin Film Thickness in TiN Coatings Using Particle Swarm Optimization Algorithm

    Abu-Khadrah A.
    226-234页
    查看更多>>摘要：© 2024 Praise Worthy Prize S.r.l.-All rights reserved.In hard coating materials, Titanium Nitride (TiN) is widely used as a surface coating material due to its excellent properties. In machining processes, it is crucial to optimize the coating process for better parameter selection. This optimization could enhance the performance of cutting tools. In this paper, TiN is coated on tungsten carbide tools using the Physical Vapor Deposition (PVD) method. Coating surface thickness is investigated as an output function that primarily depends on the Nitrogen gas pressure, Argon gas pressure, and turntable speed. The Particle Swarm Optimization algorithm (PSO) is utilized as an efficient metaheuristic technique for optimization purposes. PSO is integrated with Response Surface Methodology (RSM), which functions as a modeling method to generate the objective function for coating thickness. RSM also analyzes the effect of input parameters on the produced film thickness. Finally, Prediction Interval (PI) and Residual Error (e) are used to validate the RSM model. The results show that the actual value of film thickness falls within 95% accuracy and exhibits very low error. While PSO is found to be a powerful technique for optimizing coating thickness, it has reduced the ratio of the average experimental value by 75%.
      原文链接:
    • NETL
    • NSTL

    Design of Seawater Parameters Measuring Device and Data Storage System Using Node MCU ESP8266

    SuryadhiMarjonoCiptadi G.Rifandi S....
    235-243页
    查看更多>>摘要：© 2024 Praise Worthy Prize S.r.l.-All rights reserved.The literature on seawater quality monitoring is increasing, with various systems proposed. This article describes the design of a seawater parameters measuring device and data storage system using a Node MCU ESP8266. This device is designed to be very easy to operate, including for fishermen who catch fish at sea. Three sensors measure seawater parameters: temperature, pH, and salinity. The data obtained from these sensors is sent to the Node MCU ESP8266 and stored first as a solution to the absence of an internet connection at the time of data collection when fishermen catch fish at sea. When connected to the internet network, the data stored in the MicroSD card is sent to the server using the WiFi Module on the Node MCU ESP8266. The data on the server can be accessed via the web. Fishermen operate this device by charging the battery before leaving to catch fish. Arriving at the location to catch fish, fishermen put this device into the water. The device is tied with a rope to the net used by the fisherman or tied to the boat. To motivate fishermen to carry the device, it is also equipped with a fish caller to attract fish to approach the fishing gear.
      原文链接:
    • NETL
    • NSTL