【讲座题目】Synchronous Phasor Data Quality Enhancement and an Online Method for Thevenin Equivalent Estimation

【讲座时间】2018年7月17日（星期二）15：00

【讲座地点】北京校部主楼D260

【主 讲 人】Joe   H. Chow  美国工程院院士

【主讲人简介】 Joe   H. Chow教授在伊利诺伊大学厄巴纳-香槟分校获得电气工程硕士、博士学位。1987年加入伦斯勒理工学院前，他曾在通用电气电力系统部门工作。目前，他是伦斯勒理工学院电子与计算机系统工程学院教授，NSF/DOE工程研究中心的校园主任，负责超广域弹性电能传输网络（CURENT ERC）。研究方向包括大型电力系统的建模和控制以及同步相量测量技术。同时，他是IEEE Fellow和美国工程院院士，曾获美国自动控制委员会的Donald Eckman奖，IEEE控制系统学会控制系统技术奖和IEEE电力能源学会的Charles Concordia电力系统工程奖。

【内容简介】 This talk consists of two parts. The first part is entitled “Recovery of Missing Synchrophasor Data via Adaptive Filtering.” This is an ongoing research topic at RPI to improve the data quality of PMU data, so that the synchrophasor data can be used reliably by control room applications.  In previous research, RPI has proposed the use of low-rank matrix completion to recovery missing PMU data, from information available in neighboring substations.  (Low-rank matrix completion methods have been developed for video processing and consensus analysis.) In this new approach, the low-rank property is translated into an adaptive filter based on windows lasting seconds.  A stability condition has also been established for the filter.  The second part is entitled “an On-line Thevenin Equivalent Estimation Algorithm.” This is a continuation of our research on developing equivalent circuit models from power system measured data for voltage stability analysis.  Thevenin Equivalent model estimation using measured data from real systems is fraught with problems and can yield inconsistent results.  During periods in which the load and generator pattern does not change much, the estimated parameters will be driven mostly by measurement noise.  In this new online method, a thresholding method and a forgetting factor method are used to reduce the variations of the Thevenin Equivalent model parameters.