US 11,841,387 B2
Cloud-end collaborative system and method for load identification
Xingqi Liu, Beijing (CN); Enguo Zhu, Beijing (CN); Heping Zou, Beijing (CN); Fantao Lin, Beijing (CN); Min Lei, Beijing (CN); Yinghui Xu, Beijing (CN); Hao Chen, Beijing (CN); Zhongxing Wu, Beijing (CN); Yupeng Zhang, Beijing (CN); Zixu Zhu, Beijing (CN); and Yue Han, Beijing (CN)
Assigned to CHINA ELECTRIC POWER RESEARCH INSTITUTE, Beijing (CN); and STATE GRID CORPORATION OF CHINA, Beijing (CN)
Appl. No. 17/759,769
Filed by CHINA ELECTRIC POWER RESEARCH INSTITUTE, Beijing (CN); and STATE GRID CORPORATION OF CHINA, Beijing (CN)
PCT Filed Jan. 29, 2022, PCT No. PCT/CN2022/075039
§ 371(c)(1), (2) Date Jul. 29, 2022,
PCT Pub. No. WO2022/111741, PCT Pub. Date Jun. 2, 2022.
Claims priority of application No. 202011395279.X (CN), filed on Nov. 30, 2020.
Prior Publication US 2023/0070173 A1, Mar. 9, 2023
Int. Cl. G01R 19/25 (2006.01); G16Y 10/35 (2020.01)
CPC G01R 19/2513 (2013.01) [G16Y 10/35 (2020.01)] 9 Claims
OG exemplary drawing
 
1. A cloud-end collaborative system for load identification, comprising:
an intelligent Internet-of-Things watt-hour meter assembly, configured to identify load characteristic data of a user electrical device, perform characteristic vector data extraction on the load characteristic data by a preset load characteristic vector extraction algorithm, match extracted characteristic vector data with a first load characteristic library of the intelligent Internet-of-Things watt-hour meter assembly, and determine load characteristic data corresponding to characteristic vector data that is not matched in the extracted characteristic vector data as target load characteristic data;
a user power information pre-loading/acquisition assembly, configured to call the target load characteristic data and transmit the target load characteristic data to a master station load identification assembly; and
the master station load identification assembly, configured to receive the target load characteristic data, perform data orientation processing on the target load characteristic data to obtain to-be-identified characteristic vector data, and identify a target intelligent Internet-of-Things watt-hour meter assembly and a type of a target load characteristic extraction algorithm from the to-be-identified characteristic vector data; and store matching information and determine an optimal matching strategy matching the to-be-identified characteristic data when it is determined that the target load characteristic extraction algorithm matches the target intelligent Internet-of-Things watt-hour meter assembly, and identify an optimal matching solution corresponding to the to-be-identified characteristic vector data from a second load characteristic library according to the optimal matching strategy, to complete a matching between the to-be-identified characteristic vector data and the second load characteristic library.