s. m. shahrtash

Aging and loss of hydrophobicity are among the most significant challenges in using polymer insulators in highly polluted areas. This leads to an increase in leakage current (LC) and the occurrence of dry band discharge (DBD) phenomena on the surface of the insulator, which may ultimately result in flashover and fault. This paper investigates the effect of aging on the intensity of DBD in polymer insulators. To this end, five sample insulators of varying ages were collected from a medium voltage distribution network, and after applying artificial pollution, their LCs were recorded in a fog chamber under nominal voltage conditions. Additionally, magnitude and duration of discharge were extracted from the LC signals and proposed as two indices for evaluating the aging of the insulators. Furthermore, a novel method for finite element modelling of polluted polymer insulators is presented. In the proposed method, the phenomenon of DBD in the pollution layer and the effect of insulator aging on the intensity of this phenomenon have been implemented. For this purpose, the electrical conductivity of the pollution layer is considered to be dynamic and a function of the electric field at the surface of the insulator. The parameters of the conductivity-field curve were calculated through low-voltage test and utilized in the simulations. The results of the finite element modelling are in accordance with test results and demonstrate an increase in the intensity of DBD with insulator aging.

The most important issue in power system designing and operating is minimizing losses and costs. Unlike existing methods which use a large amount of data across the entire network to determine optimal dispatch of shunt capacitors, this paper describes a method for optimal switching of capacitors in subtransmision substations only by using local data including voltage magnitude on 20kV and 63kV busbars, outgoing/incoming reactive powers on 63kV lines, and reactive load of 20kV side of subtransmision transformer. The simulations are carried out for Alborz Province MV network in IRAN using DIgSILENT 2018. Simulation results show an acceptable accuracy to minimize power loss in 63kV network.

This paper has proposed an on-line method of partial discharges (PDs) detection. Fundamental difficulty in PD measurement is that PD signal is so minute that can be easily contaminated by huge amount of noise and this makes PD detection rather obscure. Thus, noise reduction algorithms have been extensively deployed to mitigate the noise. Among which, Digital Signal Processing (DSP) techniques are becoming more and more applicable. Compared by linear predictor and Least Mean Square (LMS), a wavelet-based noise reduction algorithm has been utilised. Some significant considerations in wavelet denoising such as selection of level of decomposition and reconstruction, mother wavelets, methods of signal extension,thresholding criterion have been discussed deeply. In order to prove the effectiveness of our algorithm, real data extracted from an 11 kV cable has been used.