Ping-Chang Tsai
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Ping-Chang Tsai has a total of 5 co-authors. Here are the top co-authors by number of shared publications:
- Cheng-Chien Kuo
Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei 10607, Taiwan
2 shared publications - Chang-Kuo Chen
National Atomic Research Institute, Taoyuan City 32546, Taiwan
1 shared publication - Jia-Zhang Jhan
Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei 10607, Taiwan
1 shared publication - Samuel Sin-Shuan Tang
Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei 10607, Taiwan
1 shared publication - Yu-Min Hsueh
Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei 10607, Taiwan
1 shared publication
Latest Publications
- Open Access
- 31 January 2024
- Published by MDPI AG in Applied Sciences
- Vol. 14 (3) , 1195
Research on a Partial Discharge Expert System for the Diagnosis of Damaged Transformation Equipment
Partial discharge (PD) characteristics are very important for the diagnosis of damaged transformation equipment. If the power transmission and transformation equipment fails, it will cause large economic losses, and thus prevention is better than treatment. One of the effective methods for high-voltage insulation degradation detection is to observe the phenomenon of partial discharge of equipment, which is the earliest characteristic. Prevention can be carried out in advance, and trend observation is better than periodic inspection. Long-term observation can effectively reduce the probability of misjudgment. This project intends to develop a high-speed data-acquisition device to acquire the original discharge waveform data of partial discharge for noise suppression. In order to improve the diagnostic efficiency and accuracy of the diagnostic system, it is necessary to suppress the noise of the measurement data, so as to carry out the fault identification of the discharge type. Through this method, the actual operating data of the system can be recorded as the original discharge waveform, in order to understand the original discharge waveform conditions of the power transmission and transformation equipment in multiple partial discharge measurements, and then after noise suppression, it can be regarded as a type of partial discharge identification.
- 31 January 2024
- Published by MDPI AG in Applied Sciences
- Vol. 14 (3) , 1195
Open AccessResearch on a Partial Discharge Expert System for the Diagnosis of Damaged Transformation Equipment
Partial discharge (PD) characteristics are very important for the diagnosis of damaged transformation equipment. If the power transmission and transformation equipment fails, it will cause large economic losses, and thus prevention is better than treatment. One of the effective methods for high-voltage insulation degradation detection is to observe the phenomenon of partial discharge of equipment, which is the earliest characteristic. Prevention can be carried out in advance, and trend observation is better than periodic inspection. Long-term observation can effectively reduce the probability of misjudgment. This project intends to develop a high-speed data-acquisition device to acquire the original discharge waveform data of partial discharge for noise suppression. In order to improve the diagnostic efficiency and accuracy of the diagnostic system, it is necessary to suppress the noise of the measurement data, so as to carry out the fault identification of the discharge type. Through this method, the actual operating data of the system can be recorded as the original discharge waveform, in order to understand the original discharge waveform conditions of the power transmission and transformation equipment in multiple partial discharge measurements, and then after noise suppression, it can be regarded as a type of partial discharge identification.
- Open Access
- 18 January 2024
- Published by MDPI AG in Applied Sciences
- Vol. 14 (2) , 814
Estimation of Energy Storage Requirements in an Independent Power System from an Energy Perspective
Taiwan’s power system operates as an isolated grid, preventing the export of surplus energy. Excess electricity is either stored or discarded (curtailed). This study aims to estimate the energy storage requirement for the day with the most extreme electricity consumption behavior in a year without energy curtailment. Based on the installed capacity and actual power generation of renewable energy sources in 2022, this research estimates the power generation per GW of the installed capacity at full load. Integrating the government’s annual installation capacity plans, this study forecasts the annual power generation of renewable sources. Using the electrical load during the 2023 Spring Festival as a baseline and assuming an annual electricity consumption growth rate of 2%, combined with a minimum gas power output of approximately 6 GW, this study calculates the unused power generation, which represents the pumped-storage hydroelectricity and battery energy storage systems requirements for that day under a no-curtailment scenario. Considering the semi-annual adjustments in installation planning, this study’s code is open-sourced and designed to provide updated results with new planning data input, facilitating ongoing adjustments.
- 18 January 2024
- Published by MDPI AG in Applied Sciences
- Vol. 14 (2) , 814
Open AccessEstimation of Energy Storage Requirements in an Independent Power System from an Energy Perspective
Taiwan’s power system operates as an isolated grid, preventing the export of surplus energy. Excess electricity is either stored or discarded (curtailed). This study aims to estimate the energy storage requirement for the day with the most extreme electricity consumption behavior in a year without energy curtailment. Based on the installed capacity and actual power generation of renewable energy sources in 2022, this research estimates the power generation per GW of the installed capacity at full load. Integrating the government’s annual installation capacity plans, this study forecasts the annual power generation of renewable sources. Using the electrical load during the 2023 Spring Festival as a baseline and assuming an annual electricity consumption growth rate of 2%, combined with a minimum gas power output of approximately 6 GW, this study calculates the unused power generation, which represents the pumped-storage hydroelectricity and battery energy storage systems requirements for that day under a no-curtailment scenario. Considering the semi-annual adjustments in installation planning, this study’s code is open-sourced and designed to provide updated results with new planning data input, facilitating ongoing adjustments.