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International Journal of Electrical and Computer Engineering

IJECE
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Published by Institute of Advanced Engineering and Science

ISSN : 20888708 EISSN : 27222578 DOI : -

Core Subject : Science, Engineering,

Computer Science & IT Electrical & Electronics Engineering

International Journal of Electrical and Computer Engineering (IJECE, ISSN: 2088-8708, a SCOPUS indexed Journal, SNIP: 1.001; SJR: 0.296; CiteScore: 0.99; SJR & CiteScore Q2 on both of the Electrical & Electronics Engineering, and Computer Science) is the official publication of the Institute of Advanced Engineering and Science (IAES). The journal is open to submission from scholars and experts in the wide areas of electrical, electronics, instrumentation, control, telecommunication and computer engineering from the global world.

Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)

Articles 6,393 Documents

299 300 301 302 303

Power fuzzy adaptive control for wind turbine Yacine Hocini; Ahmed Allali; Houari Merabet Boulouiha
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 5: October 2020
Publisher : Institute of Advanced Engineering and Science

In recent years, wind energy has become one of the most promising renewable energy sources. The doubly-fed induction generator (DFIG) is currently the most common type of generator used in wind farms. This paper describes an approach for the independent control of the active and reactive power of the variable-speed DFIG. This paper deals with the control of the active and reactive powers in a DFIG designed for a wind system. The simulation model including a 7 KW - DFIG driven by a wind turbine, a PWM inverter and the proposed control strategy are developed and implemented using Matlab Simulink.

A prior case study of natural language processing on different domain Shruthi J.; Suma Swamy
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 5: October 2020
Publisher : Institute of Advanced Engineering and Science

In the present state of digital world, computer machine do not understand the human’s ordinary language. This is the great barrier between humans and digital systems. Hence, researchers found an advanced technology that provides information to the users from the digital machine. However, natural language processing (i.e. NLP) is a branch of AI that has significant implication on the ways that computer machine and humans can interact. NLP has become an essential technology in bridging the communication gap between humans and digital data. Thus, this study provides the necessity of the NLP in the current computing world along with different approaches and their applications. It also, highlights the key challenges in the development of new NLP model.

Utilizing CaCO3, CaF2, SiO2, and TiO2 particles to enhance color homogeneity and luminous flux of WLEDs Nguyen Thi Phuong Loan; Nguyen Doan Quoc Anh
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 5: October 2020
Publisher : Institute of Advanced Engineering and Science

The chromatic homogeneity and luminous efficiency are two crucial elements for determining a high-quality phosphor-converted LEDs (pc-LEDs). Thus, this paper provides essential information in choosing the particles to enhance lighting properties of high performance pc-LEDs. Scattering enhancement particles (SEP) such as CaCO3, CaF2, SiO2, and TiO2, are combined with yellow phosphor Y3Al5O12:Ce3+ and applied to the lighting devices. Initially, optical simulations are carried out with the support of LightTools program. Next, the Mie-theory is applied to calculate and confirm the results. The calculation subjects are SEPs scattering properties within the band 455 -595 nm. The scattering results of TiO2 suggest it is the optimal choice for pc-LEDs color quality in comparison to the other SEPs; however, it causes the luminous flux to decrease significantly along with the increase in its concentration. Besides, with the addition of SiO2 grains, we can accomplish higher lumen output at all particle sizes. Meanwhile, the application of 30% CaCO3 can decrease the CCT deviation by 620 K making CaCO3 the potential particle to be selected for chromatic quality and light output enhancement of pc-LEDs.

Short-term wind speed forecasting system using deep learning for wind turbine applications Gokhan Erdemir; Aydin Tarik Zengin; Tahir Cetin Akinci
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 6: December 2020
Publisher : Institute of Advanced Engineering and Science

It is very important to accurately detect wind direction and speed for wind energy that is one of the essential sustainable energy sources. Studies on the wind speed forecasting are generally carried out for long-term predictions. One of the main reasons for the long-term forecasts is the correct planning of the area where the wind turbine will be built due to the high investment costs and long-term returns. Besides that, short-term forecasting is another important point for the efficient use of wind turbines. In addition to estimating only average values, making instant and dynamic short-term forecasts are necessary to control wind turbines. In this study, short-term forecasting of the changes in wind speed between 1-20 minutes using deep learning was performed. Wind speed data was obtained instantaneously from the feedback of the emulated wind turbine's generator. These dynamically changing data was used as an input of the deep learning algorithm. Each new data from the generator was used as both test and training input in the proposed approach. In this way, the model accuracy and enhancement were provided simultaneously. The proposed approach was turned into a modular independent integrated system to work in various wind turbine applications. It was observed that the system can predict wind speed dynamically with around 3% error in the applications in the test setup applications.

An efficient technique for out-of-band power reduction for the eliminated CP-STC-shaped system for 5G requirements Mohamed Yasin I. Afifi; Mohamed S. Elbakry; El-Sayed S. A. Soliman; A. A. Ammar
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 5: October 2020
Publisher : Institute of Advanced Engineering and Science

The most dominant needs for the recent wireless mobile applications are higher bandwidth (BW) efficiency, higher energy efficiency higher quality of services (QOS). The main technique in 4G systems is OFDM but it suffers from some limitations such as large peak to average power ratio (PAPR), higher Out-of-Band (OOB) power radiation, and wasting bandwidth efficiency due to cyclic prefix (CP) extension. In his paper, these OFDM limitations will be reduced with low computational complexity compared to filter bank multicarriers (FBMC). The proposed scheme is based on symbol time compression (STC) for OFDM system. The proposed STC-Shaped system is achieved via interleaver-spreader and symbol shaper in the transmitter side in addition to equalization and combining processes in the receiver side. Comparative study between the proposed system and the conventional OFDM in case of additive white Gaussian noise (AWGN) and COST 207 typical multipath fading channel will be presented. The numerical results show that the proposed STC-Shaped scheme reduces OOB significantly. The proposed scheme improves BER in multipath Rayleigh fading although it is without CP. Thus, the proposed system is more robust against inter symbol interference (ISI) compared to conventional OFDM system. Also, the numerical results show that the PAPR of the proposed system is decreased significantly and also, it is derived theoretically. Also, the proposed scheme overcomes CP extension, and hence increases the bandwidth (BW) efficiency. Finally, the computational complexity for the proposed scheme is derived and it has very low complexity compared to FBMC. The system performance measurments has been fulfilled using cumulative distribution function (CDF), power spectral density (PSD) and bit error rate (BER).

Harvesting in electric vehicles: combining multiple power tracking and fuel-cells Juan-Gerardo Parada-Salado; Luis-Fernando Gaona-Cárdenas; Martín-Antonio Rodríguez-Licea; Francisco-Javier Pérez-Pinal
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 5: October 2020
Publisher : Institute of Advanced Engineering and Science

Exploitation of green energy sources is essential to diminish the deterioration of our environment. The energy harvesting, represents an alternative to achieve greater range in electric and hybrid vehicles. An energy management strategy (EMS) must be optimized to obtain the best beneﬁts in such vehicles, which is not a trivial task. If harvesting or energy recovery devices are added, the EMS becomes a dual-purpose algorithm: minimizing fuel consumption and maximizing energy harvest through maximum power point tracking (MPPT) controllers. Known studies consider separate EMS, one for traction and another for regenerative braking, without considering harvest devices such as solar panels, regenerative suspension, thermal generators, among others. Furthermore, the electronic power converters used, are not designed to handle such unequal power levels. In this article, an electronic platform to include multiple energy harvesting devices in a fuel-cell hybrid electric vehicle, was presented together with a multiple MPPT-EMS. The EMS is easily implementable, and considers quasiconstant cell energy extraction and ﬁltering of current transients to the battery bank ensuring the longevity of the devices. A new mathematical model of the platform, a closed loop stability analysis, and numerical and Hardware-in-the-Loop (HIL) validations were presented. Some experimental validation results were also provided.

The effect of gamma value on support vector machine performance with different kernels Intisar Shadeed Al-Mejibli; Jwan K. Alwan; Dhafar Hamed Abd
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 5: October 2020
Publisher : Institute of Advanced Engineering and Science

Currently, the support vector machine (SVM) regarded as one of supervised machine learning algorithm that provides analysis of data for classification and regression. This technique is implemented in many fields such as bioinformatics, face recognition, text and hypertext categorization, generalized predictive control and many other different areas. The performance of SVM is affected by some parameters, which are used in the training phase, and the settings of parameters can have a profound impact on the resulting engine’s implementation. This paper investigated the SVM performance based on value of gamma parameter with used kernels. It studied the impact of gamma value on (SVM) efficiency classifier using different kernels on various datasets descriptions. SVM classifier has been implemented by using Python. The kernel functions that have been investigated are polynomials, radial based function (RBF) and sigmoid. UC irvine machine learning repository is the source of all the used datasets. Generally, the results show uneven effect on the classification accuracy of three kernels on used datasets. The changing of the gamma value taking on consideration the used dataset influences polynomial and sigmoid kernels. While the performance of RBF kernel function is more stable with different values of gamma as its accuracy is slightly changed.

Power quality improvement based on hybrid coordinated design of renewable energy sources for DC link channel DSTATCOM Ali Nasser Hussain; Ahmed Jadaan Ali; Firas Saaduldeen Ahmed
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 5: October 2020
Publisher : Institute of Advanced Engineering and Science

This paper presents a comprehensive analysis of power quality for static synchronous compensator on the distribution power system (DSTATCOM) when a different types of energy sources are used to supply the dc link channel of DSTATCOM. These types of power supplies have a different effect on the compensation of DSTATCOM due to operation nature of these sources. The dynamic response of the DSTATCOM has been investigated that produced by individual and hybrid energy sources to evaluate the influence of these sources in terms of time response, compensation process and reduce the harmonics of current for source. Three cases have been considered in this study. First the photovoltaic (PV) cells alone second the battery storage alone and third a hybrid coordinated design between (PV cells with battery storage) is used. A boost Dc-Dc circuit has been connected to a photovoltaic cell with Maximum Power Point Tracking (MPPT) while a Dc-Dc buck-boost circuit is used with a battery. High coordination between PV and battery circuits in the hybrid system is used in order to improve the performance. A synchronous reference frame (SRF) with unit vector has been used to control the STATCOM circuit. The simulation results show that the hybrid design has the superiority response compared to the individual sources.

Q-Learning vertical handover scheme in two-tier LTE-A networks Ammar Bathich; Mohd Asri Mansor; Saiful Izwan Suliman; Sinan Ghassan Abid Ali
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 6: December 2020
Publisher : Institute of Advanced Engineering and Science

Global mobile communication necessitates improved capacity and proper quality assurance for services. To achieve these requirements, small cells have been deployed intensively by long term evolution (LTE) networks operators beside conventional base station structure to provide customers with better service and capacity coverage. Accomplishment of seamless handover between Macrocell layer (first tier) and Femtocell layer (second tier) is one of the key challenges to attain the QoS requirements. Handover related information gathering becomes very hard in high dense femtocell networks, effective handover decision techniques are important to minimize unnecessary handovers occurred and avoid Ping-Pong effect. In this work, we proposed and implemented an efficient handover decision procedure based on users’ profiles using Q-learning technique in an LTE-A macrocell-femtocell networks. New multi-criterion handover decision parameters are proposed in typical/dense femtocells in microcells environment to estimate the target cell for handover. The proposed handover algorithms are validated using the LTE-Sim simulator under an urban environment. The simulation results showed noteworthy reduction in the average number of handovers.

A modified particle swarm optimization algorithm to enhance MPPT in the PV array Yoganandini A. P.; Anitha G. S.
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 5: October 2020
Publisher : Institute of Advanced Engineering and Science

Due to the growing demand for electrical power, the researchers are trying to fulfill this demand by considering different ways of renewable energy resource as existing energy resources failed to do so. The solar energy from the sun is freely available, and by using photovoltaic (PV) cell power can be generated. However, it depends on rays fall on the PV cell, climatic condition. Thus, to enhance the efficiency of the photovoltaic (PV) systems, maximum power point tracking (MPPT) of the solar arrays is needed.The output of solar arrays mainly depends on solar irradiance and temperature. The mismatch phenomenon takes place due to partial shade, and it causes to the power output, which brings the incorrect operation of traditional MPP tracker. In this shaded condition, PV array exhibits multiple extreme points. In general, under this scenario, the MPPT approaches fail to judge the MPP, and it leads to low efficiency. The conventional approaches of PSO based algorithms can able to track the MPP under shading condition. However, the optimization process leads to issues in tracking speed. Thus, there a need for an efficient MPPT system which can track MPPT effectively in shaded condition? Hence, the proposed manuscript presents a modified Particle Swarm Optimization (PSO) algorithm is introduced to enhance the tracking speed as well as performance. The outcomes of the proposed system are compared with the traditional PSO system and are found that the tracking speed of MPP, accuracy, and efficiency is improved.

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Home Page

OAI Link

Editorial Team

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Contact Name Tole Sutikno

Contact Email ijece@iaesjournal.com

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Journal Mail Official ijece@iaesjournal.com

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Location Kota yogyakarta, Daerah istimewa yogyakarta INDONESIA

Abstract

Abstract

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Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Contact Name
Tole Sutikno

Contact Email
ijece@iaesjournal.com

Phone
-

Journal Mail Official
ijece@iaesjournal.com

Editorial Address
-

Location
Kota yogyakarta,

Daerah istimewa yogyakarta

INDONESIA