The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Oct. 25, 2022
Filed:
Nov. 06, 2020
Global Energy Interconnection Research Institute Co. Ltd, Beijing, CN;
State Grid Corporation of China Co. Ltd, Beijing, CN;
State Grid Jiangsu Electric Power Co., Ltd., Jiangsu, CN;
State Grid Shanxi Electric Power Company, Shandong, CN;
Yingzhong Gu, San Jose, CA (US);
Guanyu Tian, San Jose, CA (US);
Chunlei Xu, San Jose, CA (US);
Haiwei Wu, San Jose, CA (US);
Zhe Yu, San Jose, CA (US);
Di Shi, San Jose, CA (US);
Global Energy Interconnection Research Institute Co. Ltd, Beijing, CN;
State Grid Corporation of China Co. Ltd, Beijing, CN;
State Grid Jiangsu Electric Power Co., Ltd., Jiangsu, CN;
State Grid Shanxi Electric Power Company, Shyandong, CN;
Abstract
Systems and methods for processing measurement data in an electric power system include acquiring the measurement data by a phasor measurement unit (PMU) coupled to a line of the electric power system, and inputting a plurality of the measurement data within a predetermined time window into a K-nearest neighbor (KNN) for identifying bad data among the plurality of the measurement data, wherein when one of the plurality of measurement data contains a bad datum, the machine learning module sends the bad datum to a denoising autoencoder module for correcting the bad datum, wherein the denoising autoencoder module outputs a corrected part corresponding to the bad datum, and when one of the plurality of measurement data contains no bad datum, the machine learning module bypasses the denoising autoencoder module and outputs the one of the plurality of measurement data as an untouched part.