CHARACTERISTICS OF CORONA DISCHARGE UNDER AC AND DC IN AIR INSULATION

• Main Author: Kodrat, Muhammad
• Format: Theses
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/80264
• Institution: Institut Teknologi Bandung

Partial Discharge is a tool used to evaluate the condition of the insulation of electrical equipment. The partial discharge (PD) phenomenon that occurs locally due to long-term impact on equipment will result in damage to electrical equipment. This thesis observes high voltage AC and DC partial discharge on air insulation where the sensors used are RC, HFCT and UHF CPMA antennas. What is done is observing and analyzing partial discharge inception voltage (PDIV), partial discharge extinction voltage (PDEV), partial discharge waveform, PRPD pattern, TRPD, and pulse sequence pattern (PSA) to determine the insulation characteristics. The measurement and analysis results used in this research are very useful for knowing the discharge mechanism that occurs at AC and DC voltages. In addition, observations based on time events provide sufficient information for statistical analysis of PD incidence. The method proposed by this research helps in mapping the corona discharge occurring based on the time domain characteristics of the PD waveform and magnitude. Another advantage of this mapping is that data differentiation and clustering can be done based on the rise time, fall time, and pulse width of the PD waveform. Furthermore, the PSA method is a method that can be used to determine the characteristics of PD pulses at DC pressure based on the pattern of PD events before and after, which this method is useful for knowing the characteristics of PD at DC. In addition to the above contributions in this thesis, an antenna is proposed and designed that is equipped with a very wide bandwidth so that the electromagnetic field sensor is suitable for PD detection applications under AC and DC electrical pressure. PD DC measurements are carried out using conventional and non- conventional sensors. Finally, the different types of PD DC were classified statistically.