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.

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.

公开(公告)号：US12031524B2

公开(公告)日：2024-07-09

申请号：US17410911

申请日：2021-08-24

Applicant: Inventus Holdings, LLC

Inventor： Andres F. Girardot ,  George Alex Pantouris ,  Yi Li

IPC: F03D7/04 ,  F03D7/02 ,  G05B19/042 ,  G06N20/00 ,  G06F113/06

CPC classification number: F03D7/046 ,  F03D7/0224 ,  F03D7/0276 ,  F03D7/045 ,  G05B19/042 ,  G06N20/00 ,  F05B2200/13 ,  F05B2200/14 ,  F05B2200/211 ,  F05B2200/221 ,  F05B2220/30 ,  F05B2240/221 ,  F05B2260/74 ,  F05B2260/84 ,  F05B2270/101 ,  F05B2270/1033 ,  F05B2270/32 ,  F05B2270/323 ,  F05B2270/324 ,  F05B2270/325 ,  F05B2270/402 ,  G05B2219/2619 ,  G06F2113/06

Abstract: A system for generating power includes an environmental engine that determines performance metrics for a plurality of wind turbines deployed at a plurality of windfarms, such that each windfarm includes a corresponding subset of the plurality of windfarms. The performance metrics for a given wind turbine of the plurality of wind turbines characterizes wind flowing over blades of the given wind turbine. The system includes an artificial intelligence (AI) ensemble engine operating on the one or more computing devices that generates a set of models for each wind turbine of the plurality of wind turbines, wherein each model of each set of models is generated with a different machine learning algorithm and selects, for each respective set of models, a model with a highest efficiency metric. The AI engine provides edge computing systems operating at the plurality of windfarms with a selected model and corresponding recommended operating parameters.

公开(公告)号：US11168667B2

公开(公告)日：2021-11-09

申请号：US15776294

申请日：2017-11-06

Applicant: XINJIANG GOLDWIND SCIENCE & TECHNOLOGY CO., LTD.

Inventor： Juan Ao ,  Zhao Liu

IPC: G06F30/20 ,  F03D17/00 ,  G06Q50/06 ,  G01W1/00 ,  G06F111/10 ,  G06F113/06

Abstract: A method and a device for calculating a power generation of a wind farm is provided. The method includes: determining whether a terrain complexity of a wind farm field exceeds a predetermined complexity; determining a representativeness of anemometer tower data in the wind farm field in a case where the terrain complexity exceeds the predetermined complexity; performing a mesoscale numerical simulation of a meteorological variable in the wind farm field in a case where the anemometer tower data is unrepresentative; extracting mesoscale numerical simulation data as virtual anemometer tower data; and calculating the power generation of the wind farm by using the virtual anemometer tower data.

公开(公告)号：US12091985B2

公开(公告)日：2024-09-17

申请号：US17879165

申请日：2022-08-02

Applicant: General Electric Company

Inventor： Gregory Terrence Garay ,  Daniel Endecott Osgood ,  Douglas Gerard Konitzer

IPC: F01D5/14 ,  F01D5/16 ,  F01D21/00 ,  G06F30/17 ,  G06F113/06

CPC classification number: F01D5/147 ,  F01D5/16 ,  G06F30/17 ,  F05D2220/32 ,  F05D2240/30 ,  F05D2250/21 ,  F05D2260/96 ,  F05D2300/605 ,  G06F2113/06

Abstract: An engine component for a turbine engine, the engine component comprising a wall bounding an interior; a panel portion defining a portion of the wall, the panel portion comprising: an outer wall; an inner wall spaced from the outer wall to define a wall gap; and a structural segment formed within the wall gap comprising at least one structural element. The apparatus formed from a method including calculating a factor and adjusting a variable until the factor is between a given range.

公开(公告)号：US11885305B2

公开(公告)日：2024-01-30

申请号：US17514061

申请日：2021-10-29

Applicant: IFP Energies nouvelles

Inventor： Eduardo Bezerra Rufino Ferreira Paiva ,  Hoai-Nam Nguyen ,  Olivier Lepreux

IPC: F03D7/04 ,  F03D17/00 ,  G01P21/02 ,  G01P5/26 ,  G01S17/58 ,  G06F113/06 ,  G06F113/08

CPC classification number: F03D7/045 ,  F03D17/00 ,  G01P21/025 ,  F05B2260/821 ,  F05B2260/84 ,  F05B2270/32 ,  F05B2270/327 ,  F05B2270/328 ,  F05B2270/335 ,  F05B2270/8042 ,  G01P5/26 ,  G01S17/58 ,  G06F2113/06 ,  G06F2113/08

Abstract: The present invention relates to a method of determining the wind speed in the plane of a rotor (PR) of a wind turbine (1), by measuring (MES2) the rotational speed of the rotor, the angle of the blades and the generated power. The method according to the invention uses a wind turbine model (MOD) constructed from wind speed measurements (LID), and by use of measurement clustering (GRO) and regressions (REG).

公开(公告)号：US12159245B2

公开(公告)日：2024-12-03

申请号：US17652681

申请日：2022-02-26

Applicant: Economic and Technological Research Institute of State Grid Liaoning Electric Power Co., Ltd. ,  State Grid Corporation of China ,  Northeast Electric Power University

Inventor： Xiao Pan ,  Mingli Zhang ,  Lin Zhao ,  Na Zhang ,  Zhuoran Song ,  Nantian Huang ,  Jing Gao ,  Xuming Lv ,  Hua Li ,  Mengzeng Cheng ,  Xing Ji ,  Wenying Shang ,  Yixin Hou ,  Suo Yang ,  Bo Yang ,  Yutong Liu ,  Linkun Man ,  Xilin Xu ,  Haifeng Yang ,  Fangyuan Yang ,  Kai Liu ,  Jinqi Li ,  Zongyuan Wang

IPC: G06Q10/04 ,  G06F17/15 ,  G06F18/211 ,  G06F18/2133 ,  G06F18/23213 ,  G06N3/0475 ,  G06Q50/06 ,  G06F113/06

Abstract: A method for predicting a day-ahead wind power of wind farms, comprising: constructing a raw data set based on a correlation between the to-be-predicted daily wind power, the numerical weather forecast meteorological feature and a historical daily wind power; obtaining a clustered data set and performing k-means clustering, obtaining a raw data set with cluster labels, and generating massive labeled scenes based on robust auxiliary classifier generative adversarial networks; determining the cluster label category of the to-be-predicted day based on the known historical daily wind power and numerical weather forecast meteorological feature, and screening out multiple scenes with high similarity to the to-be-predicted daily wind power based on the cluster label category; and obtaining the prediction results of the to-be-predicted daily wind power at a plurality of set times based on an average value, an upper limit value and a lower limit value of the to-be-predicted daily wind power.

公开(公告)号：US20240337249A1

公开(公告)日：2024-10-10

申请号：US18745330

申请日：2024-06-17

Applicant: Inventus Holdings, LLC

Inventor： Andres F. Girardot ,  George Alexander Pantouris ,  Yi Li

IPC: F03D7/04 ,  F03D7/02 ,  G05B19/042 ,  G06F113/06 ,  G06N20/00

CPC classification number: F03D7/046 ,  F03D7/0224 ,  F03D7/0276 ,  F03D7/045 ,  G05B19/042 ,  G06N20/00 ,  F05B2200/13 ,  F05B2200/14 ,  F05B2200/211 ,  F05B2200/221 ,  F05B2220/30 ,  F05B2240/221 ,  F05B2260/74 ,  F05B2260/84 ,  F05B2270/101 ,  F05B2270/1033 ,  F05B2270/32 ,  F05B2270/323 ,  F05B2270/324 ,  F05B2270/325 ,  F05B2270/402 ,  G05B2219/2619 ,  G06F2113/06

Abstract: A system for generating power includes an environmental engine that determines performance metrics for a plurality of wind turbines deployed at a plurality of windfarms, such that each windfarm includes a corresponding subset of the plurality of windfarms. The performance metrics for a given wind turbine of the plurality of wind turbines characterizes wind flowing over blades of the given wind turbine. The system includes an artificial intelligence (AI) ensemble engine operating on the one or more computing devices that generates a set of models for each wind turbine of the plurality of wind turbines, wherein each model of each set of models is generated with a different machine learning algorithm and selects, for each respective set of models, a model with a highest efficiency metric. The AI engine provides edge computing systems operating at the plurality of windfarms with a selected model and corresponding recommended operating parameters.

公开(公告)号：US11714934B2

公开(公告)日：2023-08-01

申请号：US16904959

申请日：2020-06-18

Applicant: The Governors of the University of Alberta

Inventor： Sayed Ali Khajehoddin ,  Ahmadreza Tabesh ,  Navid Shabanikia

IPC: G06F30/20 ,  F03D9/25 ,  G06F113/06

CPC classification number: G06F30/20 ,  F03D9/257 ,  G06F2113/06

Abstract: A method of modeling an equivalent wind turbine generator (WTG) system for a wind farm having a plurality of WTG units includes determining an impact factor of each WTG unit of the plurality of WTG units, determining an equivalent single WTG unit model parameters of the wind farm based on the impact factor of each WTG unit, and determining an effective wind speed of the wind farm to use as the equivalent WTG input wind speed. The method produces a model of static and/or dynamic wind farm behavior. Additionally, a software configured to execute a method of modeling an equivalent wind turbine generator (WTG) system for a wind farm having a plurality of WTG units.

公开(公告)号：US11499431B2

公开(公告)日：2022-11-15

申请号：US17142788

申请日：2021-01-06

Applicant: General Electric Company

Inventor： Gregory Terrence Garay ,  Daniel Endecott Osgood ,  Douglas Gerard Konitzer

IPC: F01D5/14 ,  G06F30/17 ,  G06F113/06

Abstract: An apparatus and method for forming an engine component for a turbine engine, the engine component comprising a wall bounding an interior; a panel portion defining a portion of the wall, the panel portion comprising: an outer wall; an inner wall spaced from the outer wall to define a wall gap; and a structural segment formed within the wall gap comprising at least one structural element. The method including calculating a factor and adjusting a variable until the factor is between a given range.