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:
May. 03, 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);
Qibing Zhang, San Jose, CA (US);
Ruisheng Diao, San Jose, CA (US);
Di Shi, San Jose, CA (US);
Global Energy Interconnection Research Institute Co. Ltd, Beijing, CN;
State Grid Coporation of China Co. Ltd, Beijing, CN;
State Grid Jiangsu Electric Power Co., LTD., Nanjing, CN;
State Grid ShanXi Electric Power Company, Jinan, CN;
Abstract
State estimation in an electric power system includes acquiring electrical measurements from the electric power system at a reporting rate of the electrical measurements, processing the electrical measurements into sequence data including positive sequence data, processing positive sequence data by an observable state estimator to generate a plurality of estimated states including a plurality of estimated observable states, parameters of the observable state estimator being updated by a first training module in a first time thread, processing the plurality of estimated states by an unobservable state estimator to generate a plurality of estimated unobservable states, parameters of the unobservable state estimator being updated by a second training module in a second time thread independent of the first time thread, and outputting a plurality of final estimated states generated by concatenating the plurality of estimated observable states and the plurality of estimated unobservable states.