A Novel Power System Transient Stability Prediction Method

一种新型电力系统暂态稳定预测方法

• 批准号: 0095179
• 负责人: George Karady
• 金额: $ 5万
• 依托单位: Arizona State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-06-15 至 2003-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0095179&HistoricalAwards=false
• 关键词: Novel; Power; System; Transient; Stability

This proposal suggests a new fast learning, on line method for the prediction of powersystem transient instability and an example of its application to a single machine andinfinite bus. The proposed algorithm is adapted from a proven robotic ball-catchingalgorithm, which includes fast learning. For instability prediction, the ball location isreplaced by the measured relative generator rotor angle. Using the measured relative rotorangle, the control algorithm predicts the rotor angle at a future time. The relative rotorangle is sampled at a rate of 600 times per second. This new fast learning algorithm willpredict the rotor angle 500-1000 milliseconds into the future. The increase of thepredicted generator relative rotor angle beyond a predetermined threshold is a predictionthat loss of synchronism will occur. When loss of synchronism is predicted a protectionscheme can initiate a stability aid such as generator tripping, braking resistor and/or fastvalving.Preliminary investigation shows that the ball-catching algorithm may be applied fortransient stability prediction. This proposal requests funding to prove the feasibility ofthis method.

提出了一种新的电力系统暂态失稳预测的快速在线学习方法，并给出了该方法在单机和无穷大节点上的应用实例。该算法是从一种成熟的机器人接球算法改编而来的，该算法包括快速学习。对于失稳预测，用实测的发电机转子相对转角来代替滚珠位置。利用测量的相对旋转角，控制算法预测未来时刻的转子角度。以每秒600次的速率对相对旋转角进行采样。这种新的快速学习算法将预测未来500-1000毫秒后的转子角度。当预测的发电机相对转子角度超过预定阈值时，就预示着将会发生失步。当预测失步时，保护方案可启动诸如发电机跳闸、制动电阻和/或快速阀等辅助稳定措施。初步研究表明，捕球算法可用于暂态稳定预测。这项提案要求提供资金，以证明这种方法的可行性。