Stochastic simulation of partial discharge inception

TL;DR

This paper introduces a Monte Carlo simulation method to estimate the probability and timing of electric discharge inception in gases, accounting for complex geometries and feedback mechanisms.

Contribution

It presents a novel stochastic simulation approach that models partial discharge inception using unstructured grids and feedback effects, extending previous deterministic models.

Findings

The method accurately predicts discharge inception probabilities.

It effectively models complex electrode geometries.

Simulation results align with particle-based benchmarks.

Abstract

We present a Monte Carlo method for simulating the inception of electric discharges in gases. The input consists of an unstructured grid containing the electrostatic field. The output of the model is the estimated probability of discharge inception per initial electron position, as well as the estimated time lag between the appearance of the initial electron and discharge inception. To obtain these quantities electron avalanches are simulated for initial electron positions throughout the whole domain, also including regions below the critical electric field. Avalanches are assumed to propagate along field lines, and they can produce additional avalanches due to photon and ion feedback. If the number of avalanches keeps increasing over time we assume that an electric discharge will eventually form. A statistical distribution for the electron avalanche size is used, which is also valid for gases with strong electron attachment. We compare this distribution against the results of particle simulations. Furthermore, we demonstrate examples of inception simulations in 2D Cartesian, 2D axisymmetric and 3D electrode geometries.