1,721,126 research outputs found
Method for rating power cables buried in surface troughs
No full textAn alternative method is detailed by which the ambient temperature parameter as applied to the calculation of ratings of cables buried in surface trough installations can be determined. Improvement in the accuracy of cable rating calculations will allow greater utilisation of the cable asset and assist for example in the planning of system outages for maintenance work. The proposed model calculates the temperature at the cable burial depth based on measurements of solar radiation, windspeed and air temperature. The model is based on physical laws rather than empirical approaches that have been shown to be generally conservative in application. Results based on weather data monitored over a two-year period show that the ambient temperature of the soil at cable depth can be accurately determined and the model provides a significant improvement on existing methods
On-line condition monitoring of transition assets
No full textThere are a number of medium voltage (MV) power distribution cable networks worldwide that are constructed predominantly of mass impregnated paper cables - London being one of these. Paper insulated lead covered (PILC) cables were extensively laid in the 50s and 60s before the introduction of cheaper polymeric alternatives that were sufficiently reliable. The current operational state of these networks has shown a gradual increase in failure rates of the previously reliable paper cables that are drawing to the end of their expected design life. Utilities are faced with the prospect of the impending failure of large sections of their prized asset and are keen to develop tools to better understand the health of their hardware. The analysis of partial discharge (PD) signals produced by the cables has been identified as a economically viable option to provide continuous condition monitoring of PILC cable circuits. Clearly, a comprehensive understanding of how PD activity relates to the various failure mechanisms exhibited by cable circuits in the field is required. A recently published technique for PD source discrimination was coupled with an understanding of the experiment and applied to the experiment data to isolate the signals specific to each degradation mechanism [1]. This technique has been applied to both rotation machines and transformer systems with promising results. PD signal discrimination is seen as the first step towards an autonomous condition monitoring futur
Partial Discharge Source Discrimination using a Support Vector Machine
No full textPartial discharge (PD) measurements are an important tool for assessing the health of power equipment. Different sources of PD have different effects on the insulation performance of power apparatus. Therefore, discrimination between PD sources is of great interest to both system utilities and equipment manufacturers. This paper investigates the use of a wide bandwidth PD on-line measurement system consisting of a radio frequency current transducer (RFCT) sensor, a digital storage oscilloscope and a high performance personal computer to facilitate automatic PD source identification. Three artificial PD models were used to simulate typical PD sources which may exist within power system apparatus. Wavelet analysis was applied to pre-process measurement data obtained from the wide bandwidth PD sensor. This data was then processed using correlation analysis to cluster the discharges into different groups. A machine learning technique, namely the support vector machine (SVM) was then used to identify between the different PD sources. The SVM is trained to differentiate between the inherent features of each discharge source signal. Laboratory experiments where the trained SVM was tested using measurement data from the RFCT as opposed to conventional measurement data indicate that this approach has a robust performance and has great potential for use with field measurement dat
On-line partial discharge analysis of transmission and distribution assets
Full text linkIt is becoming increasingly clear that methodologies for PD classification based on standard laboratory experimental data are not readily applicable when assessing online PD data measured in the field. It is not just that field data is corrupted by noise and disturbance, but also the significant differences between typical laboratory experiments to generate PD data and the generation of PDs in high voltage plant due to degradation of the insulation system. In this paper, the use of nonlinear time-series analysis on field data is shown to yield useful information, methods involving dimension reduction techniques are shown to allow identification of different sources and finally a method for designing standard finite impulse response filters that approximate the nonlinear analytical approach and are easy to implement in condition monitoring systems are discussed
The use of Finite Element Analysis Modelling to Improve the Precision of High Voltage Cable Ratings
No full textPartial discharge within a spherical cavity in a dielectric material as a function of cavity size and material temperature
No full textFor high-voltage components, the measurement of partial discharge (PD) is a useful tool for performance assessment of electrical insulation. In this study, experimental measurements of PD activity for different spherical cavity sizes and material temperatures have been performed. A simulation model representing PD behaviour within spherical cavities in homogeneous dielectric materials has also been developed. The model has been used to study the influence of cavity size and material temperature on PD activity. Comparison of measurement and simulation results has been undertaken. The model uses a finite element analysis (FEA) method along with MATLAB code. It has been found that certain parameters in the model are both cavity size and temperature dependent. Thus, critical parameters influencing PD behaviour for different cavity sizes within the material and material temperatures can be identified; these are the charge decay time constant, cavity surface conductivity, electron generation rate (EGR), PD inception and extinction fields and the cavity temperature decay time constant
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