Ongoing Research Projects

Project Descriptions:
Condition monitoring on in-service generators and motors is important and necessary because deterioration and failure of stator windings is a major factor of equipment problems. Partial discharge (PD) measurement is commonly used to evaluate the condition and problem of stator winding. The effectiveness of prediction of individual winding problems based on high PD charge readings have been widely reported in the past. However, the interpretation of winding problems based on PD measurement readings is commonly based on experience personnel or expert judgment. This could result in variation of the interpretation depending on the person or hardship if the experts are not available. Therefore, in this project, methods that can automatically classify the type of defect within stator insulation of rotating machines with high accuracy are developed. This can minimise the time and cost of repair, maintenance and diagnosis.

Project descriptions:
Lightning overvoltage is one of the important factors causing flashover and damage to the insulators on transmission lines. Based on the Ground Flash Density map recorded by Lightning Detection System Lab at TNB Research, it was found that towers near to the main intake substation, Subang Jaya Town Centre (SJTC) are located within the area with flash density ranging from 35 to 40 flashes per km^2 per year. Therefore, a study on the application of surge arrester placement on the 500kV transmission line at SJTC is carried out in order to improve the lightning performance of the transmission line system.

Project Descriptions:
In compliance with next-generation high-voltage substations, ultra-high frequency (UHF) printable sensors are becoming more popular than ever for their online features in partial discharge (PD) diagnostics. However, PD signals mixing with different noises still exists as a major challenge for UHF sensors. Thus, it often difficult to detect PD when there is a high noise-floor due to telecommunication interferences. In this work, a printable sensor to inherently eliminate telecommunication interferences during PD detection in open substations is introduced.

Project Descriptions:
Medium voltage switchgear plays an important role in the power grid system, and ensuring its operation is the basis for a reliable power supply. However, monitoring partial discharge (PD) caused by different types of insulation defects in medium voltage switchgear is a huge challenge. Different PD signals have very similar characteristics and are difficult to distinguish, even for the most experienced experts. This study proposes a deep learning method for PD pattern recognition based on a convolutional neural network (CNN).