Environmental Diagnosis of Coastal Wetlands and Analysis of Anthropogenic Activities: Case of the West Coast of Algeria

The Mediterranean basin is rich in wetlands of great ecological, social and economic value. Yet these important  natural assets have been considerably degraded or destroyed, mainly during the 20th century. The wetlands of western Algeria are characterized by massive urbanization. This anarchic urbanization leads to over exploitation of the natural environment. The installation of numerous residential, industrial and tourist complex sites is a complication that suffocates many recreational sites and degrades the coastal environment. This situation has created a spatial disruption of the entire ecosystem, causing physical and biological disturbances. It is in this context that our diagnosis is inscribed to better understand the stakes of human activities and the urban dynamics of the Algerian west coast. The diagnosis made it possible to highlight an intense anthropogenic activities, and an important industrial activities generating numerous damages to the coastal environment

The correlation of transformer oil electrical properties with water content using a regression approach

An experimental investigation is conducted to measure and correlate the impact of the water content on the electrical characteristics of the mineral oil for transformers, particularly the breakdown voltage, the resistivity, and the dielectric dissipation factor. Regression method is carried out to compare the results obtained through laboratory experiments with those predicted using an analytical model. A treatment to reduce water content in oil involving filtration, degassing and dehydration using a SESCO mobile station was applied to the new, regenerated, and used oil samples in service. The breakdown voltage, the resistivity, and the dielectric dissipation factor of the samples were measured. Regression analysis using an exponential model was applied to examine the samples electrical properties. The results show that, after treatment, the breakdown voltage and resistivity increase as the water content decreases, unlike the dielectric dissipation factor which exhibits a decreasing trend. This trend is found to be similar for the three oil samples: new, regenerated, and used. The results of the regression analysis give close agreement with the experimental results for all the samples and all studied characteristics. The model shows strong correlation with high coefficients (>90%)

Accuracy improvement of power transformer faults diagnostic using KNN classifier with decision tree principle

Dissolved gas analysis (DGA) is the standard technique to diagnose the fault types of oil-immersed power transformers. Various traditional DGA methods have been employed to detect the transformer faults, but their accuracies were mostly poor. In this light, the current work aims to improve the diagnostic accuracy of power transformer faults using artificial intelligence. A KNN algorithm is combined with the decision tree principle as an improved DGA diagnostic tool. A total of 501 dataset samples are used to train and test the proposed model. Based on the number of correct detections, the neighbor’s number and distance type of the KNN algorithm are optimized in order to improve the classifier’s accuracy rate. For each fault, indeed, several input vectors are assessed to select the most appropriate one for the classifier’s corresponding layer, increasing the overall diagnostic accuracy. On the basis of the accuracy rate obtained by knots and type of defect, two models are proposed where their results are compared and discussed. It is found that the global accuracy rate exceeds 93% for the power transformer diagnosis, demonstrating the effectiveness of the proposed technique. An independent database is employed as a complimentary validation phase of the proposed research

Correlations between physico-chemical properties and dielectric behavior of thermally aged XLPE cables insulation

The carried out investigations aim at clarifying the correlations between physico-chemical properties and the variation of dielectric losses of Cross-Linked Polyethylene (XLPE) as Medium Voltage cable insulation during thermal aging. The used cables were manufactured by ELSEWEDY CABLES. They have been installed in Algeria where they must resist high temperatures that could exceed 50 degrees in the south of the country. For this aim, thermal aging measurements were performed on XLPE cables samples at 80, 100 and 140 °C for aging time of 5000 hours. The chemical properties were evaluated through Fourier Transform Infrared Spectrum (FTIR). In addition, the effect of aging on the crystallinity ratio, the lamellar thickness and the melting peak temperature was assessed using Differential Scanning Calorimetry (DSC). Frequency domain dielectric spectroscopy has been conducted on the aged XLPE cables in order to study the evolution of the dielectric losses. The obtained results showed that the principal aging mechanism is thermal oxidation which heads to deteriorate the morphology and increase both the polarization and losses, principally at low frequencies. It has been found that the color changes caused by the chains scission indicate the increase of interfaces between the cable insulating and semi-conductive layers, which could head to increase the dielectric losses due to the interfacial polarization

Influence of Artificial Thermal Aging on Transformer Oil Properties

This article presents research results on electrical and physic-chemical properties of insulating oil used for high-voltage applications under accelerated artificial thermal aging. Unlike in previously published work, this article gives an extensive set of test data of artificially aged transformer oil under various temperatures. In addition, the aging effect of test temperature on various properties of the oil was quantified. Continuous thermal aging tests were made on transformer oil (Borak 22, Sonelgaz, Nynas, Austria) using a 5000-hr test at four different temperatures of 80, 100, 120, and 140°C. First, the electrical properties of transformer oil, such as the dielectric dissipation factor and the breakdown voltage, are measured after every 500 hr of aging. Next, the physicochemical parameters, including the acidity degree, water content, color factor, kinematic viscosity, density, and flash point, are quantified in order to find the changes in the chemical composition of the insulating oil. The results show that thermal aging significantly affects the properties of transformer oil by the formation of acidic products and the formation of water in oil, which lead to the degradation of the oil's electrical and physicochemical properties

Power Transformer Fault Prediction using Naive Bayes and Decision tree based on Dissolved Gas Analysis

Power transformers are the basic elements of the power grid, which is directly related to the reliability of the electrical system. Many techniques were used to prevent power transformer failures, but the Dissolved Gas Analysis (DGA) remains the most effective one. Based on the DGA technique, this paper describes the use of two of the most effective machine learning algorithms: Naive Bayes and Decision Tree for the identification of power transformer’s faults. In our investigation, 9 different input vectors have been developed from widely known DGA techniques. 481 samples have been used and 6 types of faults have been considered. The evaluation result of the implementation of the proposed methods shows an effectiveness of 86.25% in power transformer’s fault recognition

Modelling the Effect of Thermal Aging on Transformer Oil Electrical Characteristics Using a Regression Approach

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%)

Effect of Isothermal Conditions on the Charge Trapping/Detrapping Parameters in e-Beam Irradiated Thermally Aged XLPE Insulation in SEM

The effect of isothermal conditions on the trapping/detrapping process of charges in e-beam irradiated thermally aged XLPE insulation in scanning electron microscopy (SEM) has been investigated. Different isothermal conditions ranging from room temperature to 120 °C are applied on both unaged and aged XLPE samples (2 mm thick) by a suitable arrangement associated with SEM. For each applied test temperature, leakage, and influence currents have been measured simultaneously during and after e-beam irradiation. Experimental results show a big difference between the fresh and aged material regarding trapping and detrapping behavior. It has been pointed out that in the unaged material deep traps govern the process, whereas the shallow traps take part in the aged one. Almost all obtained results reveal that the trapped charge decreases and then increases as the temperature increases for the unaged sample. A deflection temperature corresponding to a minimum is observed at 50 °C. However, for the aged material, the maximum trapped charge decreases continuously with increasing temperature, and the material seems to trap fewer charges under e-beam irradiation at high temperature. Furthermore, thermal aging leads to the occurrence of detrapping process at high temperatures even under e-beam irradiation, which explains the decrease with time evolution of trapped charge during this period. The recorded leakage current increases with increasing temperature for both cases with pronounced values for aged material. The effect of temperature and thermal aging on electrostatic influence factor (K) and total secondary electron emission yield (σ) were also studied