Hazlee Azil Illias

Partial discharge behavior within a spherical cavity in a solid dielectric material as a function of frequency and amplitude of the applied voltage

Modeling of the partial discharge (PD) process allows a better understanding of the phenomena. In this paper, a simulation model for spherical cavities within a homogeneous dielectric material has been developed. The model is implemented using Finite Element Analysis (FEA) software in parallel with a mathematical package. This method provides many advantages over previous PD models because discharge events can be simulated dynamically and the electric field in the cavity can be calculated numerically. The model has been used to study the effect of different amplitudes and frequencies of the applied voltage and simulation results have been compared with experimental measurement results. It is found that certain model parameters are dependent on the applied stress and parameters that clearly affect PD activity can be readily identified, these parameters include; the electron detrapping time constant, the cavity surface conductivity, the initial electron generation rate and the extinction voltage. The influence of surface charge decay through conduction along the cavity wall on PD activity has also been studied.

Modeling of partial discharge activity in spherical cavities within a dielectric material

In this paper, a model for a spherical cavity within a homogeneous dielectric material was developed using finite element analysis (FEA) software. The model was used to study the influence of different cavity conditions on local electric field distribution and consequent PD activity. The study involved variation of cavity diameter and cavity location within the dielectric material. In addition, experimental measurements were undertaken using epoxy samples containing single spherical cavities of different diameters.

The influence of spherical cavity surface charge distribution on the sequence of partial discharge events

In this work, a model representing partial discharge (PD) behaviour of a spherical cavity within a homogeneous dielectric material has been developed to study the influence of cavity surface charge distribution on the electric field distribution in both the cavity and the material itself. The charge accumulation on the cavity surface after a PD event and charge movement along the cavity wall under the influence of electric field magnitude and direction has been found to affect the electric field distribution in the whole cavity and in the material. This in turn affects the likelihood of any subsequent PD activity in the cavity and the whole sequence of PD events. The model parameters influencing cavity surface charge distribution can be readily identified; they are the cavity surface conductivity, the inception field and the extinction field. Comparison of measurement and simulation results has been undertaken to validate the model.

Conductivity and electrical properties of corn starch–chitosan blend biopolymer electrolyte incorporated with ammonium iodide

This work focuses on the characteristics of polymer blend electrolytes based on corn starch and chitosan doped with ammonium iodide (NH4I). The electrolytes were prepared using the solution cast method. A polymer blend comprising 80wt% starch and 20wt% chitosan was found to be the most amorphous blend and suitable to serve as the polymer host. Fourier transform infrared spectroscopy analysis proved the interaction between starch, chitosan and NH4I. The highest room temperature conductivity of (3.04±0.32)◊10 4 Scm 1 was obtained when the polymer host was doped with 40wt% NH4I. This result was further proven by field emission scanning electron microscopy study. All electrolytes were found to obey the Arrhenius rule. Dielectric studies confirm that the electrolytes obeyed non-Debye behavior. The temperature dependence of the power law exponent s for the highest conducting sample follows the quantum mechanical tunneling model.

Conductivity and transport studies of plasticized chitosan-based proton conducting biopolymer electrolytes

This paper focuses on the conductivity and transport properties of chitosan-based solid biopolymer electrolytes containing ammonium thiocyanate (NH4SCN). The sample containing 40 wt% NH4SCN exhibited the highest conductivity value of (1.81 ± 0.50) × 10−4 S cm−1 at room temperature. Conductivity has increased to (1.51 ± 0.12) × 10−3 S cm−1 with the addition of 25 wt% glycerol. The temperature dependence of conductivity for both salted and plasticized systems obeyed the Arrhenius rule. The activation energy (Ea) was calculated for both systems and it is found that the sample with 40 wt% NH4SCN in the salted system obtained an Ea value of 0.148 eV and that for the sample containing 25 wt% glycerol in the plasticized system is 0.139 eV. From the Fourier transform infrared studies, carboxamide and amine bands shifted to lower wavenumbers, indicating that chitosan has interacted with NH4SCN salt. Changes in the C–O stretching vibration band intensity are observed at 1067 cm−1 with the addition of glycerol. The Rice and Roth model was used to explain the transport properties of the salted and plasticized systems.

Transformer Incipient Fault Prediction Using Combined Artificial Neural Network and Various Particle Swarm Optimisation Techniques

It is important to predict the incipient fault in transformer oil accurately so that the maintenance of transformer oil can be performed correctly, reducing the cost of maintenance and minimise the error. Dissolved gas analysis (DGA) has been widely used to predict the incipient fault in power transformers. However, sometimes the existing DGA methods yield inaccurate prediction of the incipient fault in transformer oil because each method is only suitable for certain conditions. Many previous works have reported on the use of intelligence methods to predict the transformer faults. However, it is believed that the accuracy of the previously proposed methods can still be improved. Since artificial neural network (ANN) and particle swarm optimisation (PSO) techniques have never been used in the previously reported work, this work proposes a combination of ANN and various PSO techniques to predict the transformer incipient fault. The advantages of PSO are simplicity and easy implementation. The effectiveness of various PSO techniques in combination with ANN is validated by comparison with the results from the actual fault diagnosis, an existing diagnosis method and ANN alone. Comparison of the results from the proposed methods with the previously reported work was also performed to show the improvement of the proposed methods. It was found that the proposed ANN-Evolutionary PSO method yields the highest percentage of correct identification for transformer fault type than the existing diagnosis method and previously reported works.

Partial discharge modelling in a spherical cavity within a dielectric insulation material as a function of frequency

The measurement of partial discharge (PD) is used in the performance assessment of an insulation system in high voltage components. Through modeling the discharge process a better understanding of the phenomena may be attained. This paper is an extension from previous works by the same authors which have considered the modeling of PD activity from a spherical cavity by using Finite Element Analysis (FEA) method. However, this paper describes the development of an improved model for a spherical cavity within a homogeneous dielectric material. The model developed has been used to study the influence of applied frequency on PD activity. The model has also been used to simulate the PD measurement results. Therefore, parameters in the model that are affecting PD frequency dependent behavior can be identified through comparison between experimental measurement and simulation results.

Determination of partial discharge time lag in void using physical model approach

Repetition of partial discharge (PD) activities within a dielectric insulation of high voltage equipment may lead to dielectric breakdown, eventually resulting in failure of the whole equipment. Thus, PD measurement is essential in high voltage insulation system. Modeling of PD activity may increase an understanding of PD phenomenon. One of the parameters which can be determined from PD modeling is the statistical time lag. In this work, a physical model of PD using finite element analysis (FEA) method has been developed to determine the relationship of statistical time lag with different applied stresses; these include different applied voltage, frequency and temperature. The statistical time lag as a function of different applied stresses was determined through comparison between measurement and simulation results. The proposed experimental-modeling approach may increase an understanding on the physical explanation about the statistical time lag.

The Effect of Plasticization on Conductivity and Other Properties of Starch/Chitosan Blend Biopolymer Electrolyte Incorporated with Ammonium Iodide

This work focuses on polymer electrolytes composed of a starch-chitosan blend host, ammonium iodide (NH4I) and glycerol. Fourier transform infrared (FTIR) analysis confirms the interaction of starch-chitosan-NH4I-glycerol. The highest room temperature conductivity is (1.28 ± 0.07) × 10−3 S cm−1, obtained by a sample containing 30 wt% glycerol. Dielectric studies showed that the electrolytes obeyed non-Debye behavior. The total ionic transference number for the 30 wt% glycerol sample was 0.991, and the conduction mechanism for this sample followed the quantum mechanical tunneling (QMT) model. Linear sweep voltammetry (LSV) showed that this sample was electrochemically stable up to 1.90 V. The highest conducting sample was used in the fabrication of an electrical double layer capacitor (EDLC) cell.

Partial discharges within two spherical voids in an epoxy resin

A void in a dielectric insulation material may exist due to imperfection in the insulation manufacturing or long term stressing. Voids have been identified as one of the common sources of partial discharge (PD) activity within an insulation system, such as in cable insulation and power transformers. Therefore, it is important to study PD phenomenon within void cavities in insulation. In this work, a model of PD activity within two spherical voids in a homogeneous dielectric material has been developed using finite element analysis software to study the parameters affecting PD behaviour. The parameters that have been taken into account are the void surface conductivity, electron generation rate and the inception and extinction fields. Measurements of PD activity within two spherical voids in an epoxy resin under ac sinusoidal applied voltage have also been performed. The simulation results have been compared with the measurement data to validate the model and to identify the parameters affecting PD behaviour. Comparison between measurements of PD activity within single and two voids in a dielectric material have also been made to observe the difference of the results under both conditions.