Generator Tripping Event Detection and Nadir Frequency Prediction Using Frequency Data Measured by μPMU

• Main Authors: Yu-Chi Lin, 林育琦
• Other Authors: Chih-Wen Liu
• Format: Others
• Language: zh-TW
• Published: 2019
• Online Access: http://ndltd.ncl.edu.tw/handle/dh9ng4

碩士 === 國立臺灣大學 === 電機工程學研究所 === 107 === With the annual demand load increasing in Taiwan, it needs to be more cautious in dispatching generator units to get through the peak load in summer. If the generator units fail and trip unexpectedly at low spinning reserve situation, the frequency of the power system will decline quickly and cause a severe event. The frequency represents the power balance. In case the frequency is too low, the generator units will disconnect from the grid. Finally, it will lead to a power system blackout, like the North America blackout event in 2003. However, if it is treated with the proper load shedding strategy and the emergency control, it will be possible to prevent a blackout event, like the 815 Datan tripping event in Taiwan last year. The problem is that all these emergency strategies are adopted when the frequency has already been too low, so this research tries to detect the tripping event and predict its severity before the frequency drops to nadir frequency. The research hopes that the nadir frequency prediction brings benefit for the emergency control in the future. This thesis will first introduce a detection algorithm for tripping event. The algorithm uses three data points to achieve real-time event detection. Next, considering the system parameter provided by Taipower and the frequency data measured by μPMU to predict the nadir frequency. The detect algorithm can 100% detect the events which nadir frequency lower than 59.8Hz given by Taipower. If the error is lower than 0.1Hz, it represents the success of the prediction. Then 87.1% of the events that found by μPMU can predict the nadir frequency accurately.