中科微点-全球专利检索

  1. Login
  2. Sign Up

Search Results

10 records (took 0.018 seconds)

    Method and device for generating wind turbine generator set simulation model, equipment, and medium
    2.
    发明授权
    Method and device for generating wind turbine generator set simulation model, equipment, and medium 有权

    公开(公告)号：US12197828B2

    公开(公告)日：2025-01-14

    申请号：US18400389

    申请日：2023-12-29

    Applicant: NORTH CHINA ELECTRIC POWER UNIVERSITY

    Inventor： Yang Hu ,  Maofeng Shao ,  Haonan Wang ,  Fang Fang ,  Jizhen Liu

    IPC: G06F30/20 ,  F03D17/00

    Abstract: A method and device for generating a wind turbine generator set simulation model, equipment and a medium, wherein the method includes: clustering a plurality of pieces of historical operation data of a wind turbine generator set, so as to obtain a predetermined number of target data sets, wherein wind speeds contained in each piece of the historical operation data in a target data set fall within a wind speed range corresponding to the target data set; different target data sets correspond to different wind speed ranges; training an initial simulation model by using each target data set, so as to obtain a segmented pneumatic simulation model corresponding to each target data set; constructing a transmission generation simulation model for a transmission system and a generator system, based on the historical operation data; concatenating the segmented pneumatic simulation model corresponding to each wind speed range and the transmission generation simulation model.

    Federated Learning-Based Regional Photovoltaic Power Probabilistic Forecasting Method and Coordinated Control System
    3.
    发明申请
    Federated Learning-Based Regional Photovoltaic Power Probabilistic Forecasting Method and Coordinated Control System 有权

    公开(公告)号：US20230080737A1

    公开(公告)日：2023-03-16

    申请号：US18055414

    申请日：2022-11-15

    Applicant: North China Electric Power University

    Inventor： Fang Fang ,  Xiaoning Zhang ,  Yajuan Liu ,  Le Wei ,  Jizhen Liu

    IPC: G06N3/04 ,  G06N3/08 ,  G06Q50/06 ,  G06Q10/04 ,  H02J3/00

    Abstract: Disclosed is a federated learning-based regional photovoltaic power probability forecasting method, mainly comprising steps of: pinpointing all photovoltaic power stations in a region which participate in a federated learning framework for probability forecasting, collecting information within a period of time and corresponding photovoltaic power variables, and sampling the variables according to time sequence into a sample dataset; processing missing values and outliers in the sample dataset resulting from the step; splitting the sample data set of the photovoltaic power stations into a training set and a testing set according to a preset proportion; normalizing the training set and the testing set, respectively; creating a federated learning framework; building, by a central server, a global forecasting model based on forecast requirements, defining a training error function and a precision requirement, and distributing the network architecture and initialized parameters to all photovoltaic power stations.

    Frequency modulation dynamic modeling method and device for wind farm, and electronic device
    6.
    发明授权
    Frequency modulation dynamic modeling method and device for wind farm, and electronic device 有权

    公开(公告)号：US11847530B1

    公开(公告)日：2023-12-19

    申请号：US18199156

    申请日：2023-05-18

    Applicant: North China Electric Power University

    Inventor： Yang Hu ,  Fang Fang ,  Xinran Yao ,  Ziqiu Song ,  Jizhen Liu

    IPC: G06N3/08 ,  G06N3/0442

    CPC classification number: G06N3/08 ,  G06N3/0442

    Abstract: The present invention provides a frequency modulation dynamic modeling method and device for a wind farm, and an electronic device. The method includes: acquiring first frequency modulation data measured at a grid-connected point of the wind farm under a plurality of preset working conditions; establishing a state space model corresponding to each of the plurality of working conditions according to the first frequency modulation data; measuring the nonlinearity between the state space models corresponding to each two of the plurality of working conditions by using a gap measurement method; combining the first frequency modulation data according to the nonlinearity to obtain second frequency modulation data; and training a preset initial LSTM neural network according to the second frequency modulation data until a preset training requirement is met, and obtaining a trained frequency modulation dynamic model of the wind farm.

    Optimized regulating and controlling method and system for integrated electricity and heat system with heat pumps
    7.
    发明授权
    Optimized regulating and controlling method and system for integrated electricity and heat system with heat pumps 有权

    公开(公告)号：US12140332B2

    公开(公告)日：2024-11-12

    申请号：US17472866

    申请日：2021-09-13

    Applicant: North China Electric Power University

    Inventor： Fang Fang ,  Shunping Jin ,  Xinmeng Zhong ,  Jizhen Liu ,  Yang Hu

    IPC: F24F11/63 ,  F24F11/46 ,  G05B13/04 ,  G06F30/25 ,  G06Q10/04 ,  G06Q10/0631 ,  G06Q50/06 ,  H02J3/32 ,  H02J3/38 ,  H02J3/46 ,  F24F140/60 ,  G06Q10/20

    Abstract: The present application provides an optimized regulating and controlling method and system for an integrated electricity and heat system with heat pumps, relating to the technical field of energy operation. According to the present application, regulating and controlling can be performed by regarding units as different agents and taking maximization of the self-interest of each agent as the objective, so that the load demands of heat and power consumers can be met, and each unit agent can be satisfied with its payoff to the greatest extent. The method includes: S1. establishing a composition and structure framework of the integrated electricity and heat system with heat pumps, and establishing an output model of each unit; S2. establishing a payoff function model of each unit in the integrated electricity and heat system with heat pumps; S3. establishing a non-cooperative game model of the integrated electricity and heat system with heat pumps; and S4. solving the game model by using a particle swarm optimization algorithm to obtain a heat and power scheduling optimization scheme of each unit. The technical solution provided by the present application is applicable to a process of regulating an integrated electricity and heat system with heat pumps.

    COOPERATIVE OPERATION OPTIMIZATION CONTROL METHOD FOR WIND TURBINE GROUPS
    8.
    发明公开
    COOPERATIVE OPERATION OPTIMIZATION CONTROL METHOD FOR WIND TURBINE GROUPS 审中-公开

    公开(公告)号：US20240309843A1

    公开(公告)日：2024-09-19

    申请号：US18608645

    申请日：2024-03-18

    Applicant: North China Electric Power University

    Inventor： Yang Hu ,  Fang Fang ,  Chong ZHANG ,  Jizhen Liu

    IPC: F03D7/04

    CPC classification number: F03D7/049 ,  F05B2260/84 ,  F05B2270/204

    Abstract: A cooperative operation optimization control method for wind turbine groups, including: dividing wind turbine groups based on a digital model and an improved Jensen wake model; performing multi-degree-of-freedom controller design on wind turbines; calculating an ultimate load of the wind turbines jointly by using two methods, and constructing a safe load constraint and a yaw angle constraint for wind turbine operation in conjunction with a safe load coefficient; establishing a collaborative optimization problem model of the wind turbine groups by taking the maximum generating power of the wind turbine groups as an optimization objective, a yaw angle of an upstream wind turbine as a decision variable, and the safe load constraint, the yaw angle constraint and a power change range of the upstream wind turbine as constraint conditions; and determining a cooperative operation optimization algorithm for the wind turbine groups, and optimizing the yaw angle of the wind turbines.

Patent Agency Ranking