A review on deterministic and stochastic models for electrical treeing initiation and propagation in solid insulation systems from the perspective of prediction assessment techniques
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2018-09-17 https://doi.org/10.14419/ijet.v7i4.18150 -
Cellular Automata (CA), Discharge Avalanche Model (DAM), Diffusion Limited Aggregation (DLA), Partial Discharge (PD), Self-Consistent Model (SCM). -
Abstract
Electrical treeing is a challenging prospect related to degradation mechanism in dielectrics that eventually leads to its breakdown. Treeing propagation depends on dielectric and electrode configuration thus leading to types such as branch, filamentary, bush etc. Though researchers have attempted a gamut of studies related to treeing, it is evident that appropriate choice of prognostic model is essential for prediction of ageing of insulation that emulate features such as dendrite length, channel width, space charge etc. Although studies related to treeing modeling have taken up depictions such as Diffusion Limited Aggregation, Field Limiting Space Charge etc. to obtain estimates of electric potential based on boundary value equations (Laplace and Poisson) utilizing tools such as Fractal Analysis, Cellular Automata etc., challenges such as space charge, inhomogeneity factor etc. continue to confront researchers. This research gives a detailed insight into a wide spectrum of studies related to treeing and ageing prediction assessment of insulation based on physical, electrical, numerical and analytical models developed thus far. This study also summarizes succinctly, the merits and limitations in each method and avenues for improvement. Finally, this research gives clues into important future opportunities related to methodologies for development pertaining to treeing prediction and ageing assessment.
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How to Cite
H, B., & S, V. (2018). A review on deterministic and stochastic models for electrical treeing initiation and propagation in solid insulation systems from the perspective of prediction assessment techniques. International Journal of Engineering & Technology, 7(4), 2271-2290. https://doi.org/10.14419/ijet.v7i4.18150Received date: 2018-08-24
Accepted date: 2018-08-24
Published date: 2018-09-17