Study of series resonance overvoltage at LV side of transmission transformer during EHV cable energization

A series resonance between the leakage transformer inductance and HV cable capacitance can be excited by a voltage disturbance at the EHV side of the transformer. In this paper, the series resonance phenomenon is initially studied using lumped parameters to analytically obtain the resonance frequencies and estimate how each parameter affects the first series resonance as well as the harmonic content of the cable energization. For the load impedance two different configurations, consuming the same active and reactive power, are tested: parallel RL load and series RL load. It is concluded that the type of load model greatly affects the harmonic impedance of the system leading to different resonance behavior. The effect of the secondary circuit consisting of the transformer, the HV cable and the load is also investigated and is shown that it significantly affects the frequency of the harmonic content produced during EHV cable energization. In addition, the accuracy of the analytical formulas is assessed by modeling the basic circuit in PSCAD/EMTDC using the frequency-dependent phase model for cable and OHL modeling. Study of series resonance overvoltage at LV side of transmission transformer during EHV cable energization (PDF Download Available). Available from: https://www.researchgate.net/publication/318348369_Study_of_series_resonance_overvoltage_at_LV_side_of_transmission_transformer_during_EHV_cable_energization [accessed Feb 01 2018]

Application of open-air capacitive sensors for voltage monitoring near terminations in HV and EHV insulated connections

Contactless capacitive sensors are applied to monitor (over)voltages near the overhead line terminations of a substation or at cable to line transitions. The sensor response is the signal time derivative when loaded with a resistive impedance and the waveform is restored by integration. As part of this differentiating/integrating (D/I) measuring concept, the use of open-air sensors results in excellent EMC characteristics but the inherent cross-coupling to other phases has to be dealt with. Three applications are presented: 1) For a 150 kV cable termination the partial discharge activity needs to be related to momentary phase voltages; 2) Measured slow front overvoltage at a 380 kV cable termination from line energization are compared with predictions from numerical simulation; 3) The perspectives of employing the D/I method for (very) fast front overvoltages near a 380 kV circuit breaker are examined

Fractal geometry for distribution grid topologies

\u3cp\u3eThis paper presents an application of fractal geometry in the design, development and expansion of distribution networks. In order to prove that electrical grids are fractal in form, the fractal dimension of distribution networks is measured using the box-counting algorithm. Then a two dimensional stochastic dielectric breakdown model (DBM) is utilized in order to generate virtual distribution networks. The fractal dimension of the simulated growth patterns varied depending on η which is the exponent of the breakdown probability distribution. By controlling the value of η, growth patterns similar to the actual distribution networks could be produced. Finally, some electrical characteristics (maximum voltage drop, total power losses) of the fractal generated networks are measured and compared with the real distribution networks.\u3c/p\u3

Fractal geometry for distribution grid topologies

This paper presents an application of fractal geometry in the design, development and expansion of distribution networks. In order to prove that electrical grids are fractal in form, the fractal dimension of distribution networks is measured using the box-counting algorithm. Then a two dimensional stochastic dielectric breakdown model (DBM) is utilized in order to generate virtual distribution networks. The fractal dimension of the simulated growth patterns varied depending on η which is the exponent of the breakdown probability distribution. By controlling the value of η, growth patterns similar to the actual distribution networks could be produced. Finally, some electrical characteristics (maximum voltage drop, total power losses) of the fractal generated networks are measured and compared with the real distribution networks