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44 results on '"Boubakeur, Ahmed"'

3. AC Flashover: An Analysis with Influence of the Pollution, Potential and Electric Field Distribution on High Voltage Insulator

Author

Benguesmia, Hani, M’Ziou, Nassima, Boubakeur, Ahmed, Haddar, Mohamed, Series editor, Bartelmus, Walter, Series editor, Chaari, Fakher, Series editor, Zimroz, Radoslaw, Series editor, Abbes, Mohamed Slim, editor, Choley, Jean-Yves, editor, Boukharouba, Taoufik, editor, Elnady, Tamer, editor, Kanaev, Andrei, editor, and Ben Amar, Mounir, editor

Published
2015
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15. Modelling the Effect of Thermal Aging on Transformer Oil Electrical Characteristics Using a Regression Approach.

Author

Abdi, Sifeddine, Haddad, Abderrahmane Manu, Harid, Noureddine, and Boubakeur, Ahmed

Subjects
INSULATING oils, BREAKDOWN voltage, REGRESSION analysis
Abstract

The effect of thermal aging on the electrical properties of the insulating oil used for transformers has been explored in this experimental work. In particular the dielectric dissipation factor, the resistivity and the breakdown voltage have been measured and correlated. The numerical results predicted by mathematical model and those measured in the laboratory have been compared by using a regression analysis. Experiments on thermal aging were performed on insulating oil (Borak 22, Nynas, Austria) during a period of time of 5000-h at three different temperatures. First, the transformer oil's dielectric dissipation factor, the resistivity and the breakdown voltage are measured after every 500 h of aging. Then, polynomial and exponential regression expressions are proposed for modelling the oil's electrical parameters variations with thermal ageing at different aging temperatures and periods. The results show that after thermal aging, the resistivity and the breakdown voltage decrease with thermal aging, however, the dielectric dissipation factor which increases. This trend is similar for all different aging temperatures. The numerical results show close agreement with the measured results for all the samples and all studied properties. The regression model presents strong correlation with high coefficients (>94%). [ABSTRACT FROM AUTHOR]

Published
2023
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16. Accurate Insulating Oil Breakdown Voltage Model Associated with Different Barrier Effects

Author

Ghoneim, Sherif S.M., Dessouky, Sobhy S., Boubakeur, Ahmed, Elfaraskoury, Adel A., Sharaf, Ahmed B. Abou, Mahmoud, Karar, Lehtonen, Matti, Darwish, Mohamed M. F., Taif University, Port Said University, National Polytechnic School, Algeria, Egyptian Electricity Holding Company, Mataria Technical College, Department of Electrical Engineering and Automation, Power Systems and High Voltage Engineering, Aalto-yliopisto, and Aalto University

Subjects
lcsh:Chemistry, lcsh:QD1-999, Transformers, barrier effect, Box–Behnken design, lcsh:TP1-1185, transformers, Box-Behnken design, Breakdown voltage, lcsh:Chemical technology, Barrier effect, breakdown voltage
Abstract

In modern power systems, power transformers are considered vital components that can ensure the grid’s continuous operation. In this regard, studying the breakdown in the transformer becomes necessary, especially its insulating system. Hence, in this study, Box–Behnken design (BBD) was used to introduce a prediction model of the breakdown voltage (VBD) for the transformer insulating oil in the presence of different barrier effects for point/plane gap arrangement with alternating current (AC) voltage. Interestingly, the BBD reduces the required number of experiments and their costs to examine the barrier parameter effect on the existing insulating oil VBD. The investigated variables were the barrier location in the gap space (a/d)%, the relative permittivity of the barrier materials (εr), the hole radius in the barrier (hr), the barrier thickness (th), and the barrier inclined angle (θ). Then, only 46 experiment runs are required to build the BBD model for the five barrier variables. The BBD prediction model was verified based on the statistical study and some other experiment runs. Results explained the influence of the inclined angle of the barrier and its thickness on the VBD. The obtained results indicated that the designed BBD model provides less than a 5% residual percentage between the measured and predicted VBD. The findings illustrated the high accuracy and robustness of the proposed insulating oil breakdown voltage predictive model linked with diverse barrier effects.

Published
2021
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17. Improved Optimization of the Charge Simulation Method for the Calculation of the Electric Field Around Overhead Transmission Lines Using Statistical Methods.

Author

Allal, Abdalali, Boubakeur, Ahmed, and Mujezinović, Adnan

Subjects
ELECTRIC lines, ELECTRIC fields, MONTE Carlo method, PROBABILITY density function, MAXIMUM likelihood statistics
Abstract

In order to decide the appropriate arrangements of fictitious charges in the charge simulation method, the use of the Monte Carlo method is proposed for the estimation of the probability density function of two variables, the radius ratio, and the angle ratio. The scale and shape parameters of the Weibull's distribution are determined by the maximum likelihood estimator. The obtained results are used to calculate the electric field at arbitrary points in the neighborhood of high voltage transmission lines. The comparisons between the results computed by this method, the results calculated by the genetic algorithm, and those measured, confirm the effectiveness and accuracy of the proposed method. [ABSTRACT FROM AUTHOR]

Published
2022
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34. Use of Neural Network Algorithms in Prediction of XLPE HV Insulation Properties under Thermal Aging

Author

Boubakeur Ahmed and Boukezzi Larbi

Subjects
symbols.namesake, Artificial neural network, Computer science, Gaussian, symbols, Random optimization, Radial basis function, High voltage, Thermal aging, Artificial neural network algorithm, Algorithm, Term (time)
Abstract

Some Artificial neural network algorithms have been used to predict properties of high voltage electrical insulation under thermal aging in term to reduce the aging experiment time. In this work we present a short comparison of the obtained results in the case of Cross-linked Polyethylene (XLPE). The theoretical and the experimental results are concordant. As a neural network application, we propose a new method based on Radial Basis Function Gaussian network (RBFG) trained by two algorithms: Random Optimization Method (ROM) and Back-propagation (BP).

Published
2013

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