Patents by Inventor Xingwei CHEN

Xingwei CHEN has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Power system risk assessment methods and systems considering deep feature mining under extreme weather conditions
    Patent number: 12717801
    Abstract: A method for risk assessment of a power system in extreme weather conditions considering deep feature mining for risk assessment of a power system. The risk assessment method includes: dividing the entire power system into regions based on geographical locations; combining historical wind speed data to construct a correlation model for strong wind extreme weather in multiple regions of the power system; constructing a strong wind scenario sample set for each region based on the correlation model; obtaining the probability of transmission line failure in the corresponding region under each strong wind scenario in the strong wind scenario sample set; randomly assigning a power system operating condition to each strong wind scenario in each region, and obtaining the operating risk value of the power system under the corresponding operating condition; constructing and training a risk assessment model; and using the model to provide a power system operating risk score assessment.
    Type: Grant
    Filed: October 11, 2024
    Date of Patent: August 25, 2026
    Assignees: State Grid Henan Electric Power Company Electric Power Science Research Institute, Harbin Institute of Technology, Weihai
    Inventors: Di Zhang, Mingyang Liu, Ze Gao, Chunsun Tian, Chenghao Li, Ji Han, Hua Wang, Guangjie Zhu, Wei Liu, Fangbing Liu, Guanyu Zhang, Xingwei Chen, Xueqing Pan, Zhou Fang, Xiaolu Cao, Hua Zhao, Kun Gao, Yuanyang Ma, Hao Zhang
  • POWER SYSTEM RISK ASSESSMENT METHODS AND SYSTEMS CONSIDERING DEEP FEATURE MINING UNDER EXTREME WEATHER CONDITIONS
    Publication number: 20260079951
    Abstract: A method for risk assessment of a power system in extreme weather conditions considering deep feature mining for risk assessment of a power system. The risk assessment method includes: dividing the entire power system into regions based on geographical locations; combining historical wind speed data to construct a correlation model for strong wind extreme weather in multiple regions of the power system; constructing a strong wind scenario sample set for each region based on the correlation model; obtaining the probability of transmission line failure in the corresponding region under each strong wind scenario in the strong wind scenario sample set; randomly assigning a power system operating condition to each strong wind scenario in each region, and obtaining the operating risk value of the power system under the corresponding operating condition; constructing and training a risk assessment model; and using the model to provide a power system operating risk score assessment.
    Type: Application
    Filed: October 11, 2024
    Publication date: March 19, 2026
    Applicants: STATE GRID HENAN ELECTRIC POWER COMPANY ELECTRIC POWER SCIENCE RESEARCH INSTITUTE, HARBIN INSTITUTE OF TECHNOLOGY, WEIHAI
    Inventors: Di ZHANG, Mingyang LIU, Ze GAO, Chunsun TIAN, Chenghao LI, Ji HAN, Hua WANG, Guangjie ZHU, Wei LIU, Fangbing LIU, Guanyu ZHANG, Xingwei CHEN, Xueqing PAN, Zhou FANG, Xiaolu CAO, Hua ZHAO, Kun GAO, Yuanyang MA, Hao ZHANG