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    Method for determining a wind turbine layout
    2.
    发明授权
    Method for determining a wind turbine layout 有权

    公开(公告)号：US12118275B2

    公开(公告)日：2024-10-15

    申请号：US17270355

    申请日：2019-08-08

    Applicant: VESTAS WIND SYSTEMS A/S

    Inventor： Juan Pablo Murcia

    IPC: G06F30/13 ,  F03D80/00 ,  G06F111/04 ,  G06F111/08 ,  G06F113/06

    CPC classification number: G06F30/13 ,  F03D80/00 ,  F05B2260/84 ,  G06F2111/04 ,  G06F2111/08 ,  G06F2113/06

    Abstract: The invention provides a method for determining a wind turbine layout in a wind power plant comprising a plurality of wind turbines. The method comprises the steps of generating a plurality of random layout candidates fulfilling a set of basic requirements, and then performing a pre screening process on each of the plurality of random layout candidates. Based on the pre-screening process, a subset of layout candidates is selected and detailed optimization is performed on the layout candidates of the selected subset of layout candidates. Based on the detailed optimization, an optimized layout for the wind power plant is selected among the optimized layout candidates of the subset of layout candidates.

    METHOD OF DETERMINING AN INOPERABLE TIME PERIOD FOR AN ASSET
    3.
    发明公开
    METHOD OF DETERMINING AN INOPERABLE TIME PERIOD FOR AN ASSET 审中-公开

    公开(公告)号：US20240354468A1

    公开(公告)日：2024-10-24

    申请号：US18137015

    申请日：2023-04-20

    Applicant: Renew-Risk Limited

    Inventor： Subhamoy Bhattacharya ,  Gaurav Chawla ,  Joshua Macabuag ,  Ashima Gupta

    IPC: G06F30/23

    CPC classification number: G06F30/23 ,  G06F2111/10 ,  G06F2113/06

    Abstract: A method of determining an average duration for a time period that the at least one first asset, or a second asset operatively connected to the at least one first asset, is inoperable is described. The method comprises obtaining a location of at least one first asset associated with energy generation, transmission or storage. The method comprises obtaining a first probability of a natural adverse event occurring at the location of the at least one first asset. The method comprises obtaining a second probability of a non-natural adverse event occurring at the location of the at least one first asset. The method comprises determining a third probability of at least one damage state of the at least one first asset from the first and second probabilities. The method comprises determining an average duration for a time period that the at least one first asset, or a second asset operatively connected to the at least one first asset, is inoperable based on the third probability of the at least one damage state of the first asset.

    Wind turbine layout optimization method combining with dispatching strategy for wind farm
    4.
    发明授权
    Wind turbine layout optimization method combining with dispatching strategy for wind farm 有权

    公开(公告)号：US11669663B2

    公开(公告)日：2023-06-06

    申请号：US17953382

    申请日：2022-09-27

    Applicant: ZHEJIANG UNIVERSITY

    Inventor： Xiaoyu Tang ,  Kunwei Lin

    IPC: G06F30/28 ,  F03D7/04 ,  G06F113/06

    CPC classification number: G06F30/28 ,  F03D7/048 ,  F05B2270/204 ,  G06F2113/06

    Abstract: Disclosed is a wind turbine layout optimization method combining with a dispatching strategy for the wind farm. In the wind farm micro-siting stage, the installed wind turbines number and the arrangement positions are optimized. In this method, the dispatching strategy of wind turbines is considered during the layout optimization of wind turbines, and the axial induction factor of each wind turbine is introduced into the layout optimization variables. The dispatching strategy of maximizing the wind farm power generation is combined with the layout optimization of wind turbines in the construction stage of the wind farm, so that the wake effect is effectively reduced and the capacity cost is reduced, which meet the requirement of actual wind farm. A hybrid optimization algorithm is proposed in this method, with a greedy algorithm to optimize the turbine number and a particle swarm optimization (PSO) algorithm to refine the turbine layout scheme.

    Site Planning for Wind Turbines Using Sensor Networks
    8.
    发明公开
    Site Planning for Wind Turbines Using Sensor Networks 审中-公开

    公开(公告)号：US20240271600A1

    公开(公告)日：2024-08-15

    申请号：US18438401

    申请日：2024-02-10

    Applicant: VayuAl Corp.

    Inventor： James Kiles ,  Patrick Hompe ,  August Kiles ,  Gelu Vrabie

    IPC: F03D7/04 ,  F03D7/02 ,  F03D13/25

    CPC classification number: F03D7/048 ,  F03D7/0204 ,  F03D13/25 ,  G06F2113/06

    Abstract: A computer system optimizes site planning for turbines at a wind farm site, by obtaining land-based characteristics of the wind farm site, wind-based characteristics of the wind farm site, including a distribution of wind velocity and wind direction across the wind farm site over time; a number of turbines to be added; and characteristics for each of the turbines. For each turbine, the system simulates a plurality of wakes at a plurality of locations based on the wind-based characteristics and the turbine-based characteristics; determines power outputs based on the simulated wakes and aforementioned characteristics, determines successive locations of the turbine locations according by applying a gradient descent to the power outputs. The system aggregates the maximum power outputs of each turbine and displays an optimized location and final yaw angle corresponding to each turbine.

    METHOD FOR PLANNING A LAYOUT OF A RENEWABLE ENERGY SITE
    9.
    发明公开
    METHOD FOR PLANNING A LAYOUT OF A RENEWABLE ENERGY SITE 审中-公开

    公开(公告)号：US20240054267A1

    公开(公告)日：2024-02-15

    申请号：US17766504

    申请日：2020-09-14

    Applicant: VESTAS WIND SYSTEMS A/S

    Inventor： Martin QVIST ,  Ana Maria Martinez FERNANDEZ ,  Hans Harhoff ANDERSEN ,  Hjalte Vinther KIEFER

    IPC: G06F30/27 ,  H02J3/00

    CPC classification number: G06F30/27 ,  H02J3/004 ,  G06F2113/06

    Abstract: Correlated sets of historical meteorological data and terrain data are obtained for at least one geographical area. A data model is derived based on the basis of the correlated sets, by training the data model. The trained data model is adapted to identify coherence between meteorological data and terrain data relating to the same geographical area. Meteorological data and terrain data related to the renewable energy site are fed to the trained data model, the terrain data having a higher resolution than the meteorological data. Using the trained model, meteorological data related to the renewable energy site with increased resolution is estimated by downscaling the meteorological data. The estimated meteorological data with increased resolution for the renewable energy site is then used for planning a layout of the renewable energy site.

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