The electron swarm parameters, namely electron drift velocity, mean energy, effective ionization coefficient and limiting values of number-density-reduced electric fields, E/N, are calculated and assessed in SF₆+CF₄+Ar ternary mixtures for SF₆ concentrations that vary from 1% to 20% over a range of E/N from 50Td to 600Td by solving Boltzmann's equation. The limiting electric field values for the ternary mixtures are deduced from the graphs of the calculated effective ionization coefficients as a function of E/N. Furthermore, breakdown voltage measurements are conducted for the ternary mixtures. The limiting electric field values obtained from the measured breakdown voltages are compared with those of the Boltzmann analysis and found to be in good agreement. The insulation strength of the ternary mixtures with constant Ar concentrations indicated an increase with increasing contents of SF₆ while the share of CF₄ in the mixture reduced in the investigated E/N range up to 600 Td with SF₆ concentrations varying from 1% to 20%. Moreover, a significant synergy is observed due to the non-linear nature of the mixture, and the maximum synergy appears to be around 10% SF₆ in the mixtures of this study with fixed Ar concentration. Furthermore, theoretical calculations of breakdown voltages from Boltzmann analysis are found to be in good correlation with the experimental values.

This study offers two Support Vector Machine (SVM) models for fault detection and fault classification, respectively. Different short circuit events were generated using a 154 kV transmission line modeled in MATLAB/Simulink software. Discrete Wavelet Transform (DWT) is performed to the measured single terminal current signals before fault detection stage. Three level wavelet energies obtained for each of three-phase currents were used as input features for the detector. After fault detection, half cycle (10 ms) of three-phase current signals was recorded by 20 kHz sampling rate. The recorded currents signals were used as input parameters for the multi class SVM classifier. The results of the validation tests have demonstrated that a quite reliable, fault detection and classification system can be developed using SVM. Generated faults were used to training and testing of the SVM classifiers. SVM based classification and detection model was fully implemented in MATLAB software. These models were comprehensively tested under different conditions. The effects of the fault impedance, fault inception angle, mother wavelet, and fault location were investigated. Finally, simulation results verify that the offered study can be used for fault detection and classification on the transmission line.

Economic load dispatch (ELD) is one of most fundamental issue for energy generation and distribution in power systems. For this purpose, different optimization techniques are developed and applied to ELD problem. In this paper, vortex search algorithm (VSA) is proposed and used for solving ELD problem. VSA method was developed from nature by observing the state of stirring liquids. Transmission losses, valve point loading effect, ramp rate limits and prohibited operating zone constraints are considered to solve ELD problem with VSA method. The feasibility and effectivity of this method is demonstrated for different cases. Obtained results are compared with different developed algorithms and these results clearly point out that proposed VSA method gives successfully outputs.

Ultra-dilute SF₆ + N₂ mixtures are subjected to crossed fields with the applied magnetic field normal to the electric field in order to investigate critical magnetic field values for suppression of electron avalanche growth resulting in increased dielectric strength. Electron avalanche growth inhibition together with the related electron mean energy variation and electron energy distribution functions are reported in the binary mixtures subjected to the combined fields. Even if a very small amount of greenhouse gas (SF₆) is used, high dielectric strength can be achieved in the binary mixtures with 0.25%, 0.50%, 0.75%, 3%, and 7% SF₆ contents subjected to the evaluated combined fields. The magnitude of the crossed magnetic field, which results in avalanche growth inhibition, decreases as the electronegativity of the mixture is increased.

SF ₆ is a dielectric gas with high dielectric strength which is used in high voltage applications related to power equipment technology. However, its global warming potential (GWP) index and staying time in the atmosphere are very high. In this study, SF6 and its alternatives (tetrafluoromethane (CF4), methane (CH4) and carbon dioxide (CO ₂ )) are investigated with regard to insulation and molecular properties by calculating the distribution of electrostatic potentials using Gaussian 09 and Gauss View 5.0 molecular software programs. The molecular orbital values (homo and lumo), energy gap, hardness, electronegativity, total energy and molecular volume of each gas are obtained by this analysis. It has been found that there is a relationship between the electronegativity and the dielectric strength.