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Wind turbine yaw offset control based on reinforcement learning

A technology for wind turbines and reinforcement learning, which is applied in the control of wind turbines, the monitoring of wind turbines, and wind turbines, etc. It can solve problems such as the reduction of power generation of upstream wind turbines and the impact on the power output of wind turbines.

Pending Publication Date: 2022-04-12
SIEMENS GAMESA RENEWABLE ENERGY AS
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Changing the yaw offset from zero degree positioning deflects the wake behind the wind turbine and further affects the power output of the wind turbine
[0007] Although the impact of the wake of the upstream wind turbine on the downstream wind turbine can be mitigated or even eliminated by setting the yaw offset of the upstream wind turbine, the power generation of the upstream wind turbine will be reduced at the same time
Therefore, it is challenging and difficult to achieve the optimum (maximum) total power output of the wind farm by adjusting the yaw offset of some or all of the wind turbines in the wind turbine farm

Method used

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  • Wind turbine yaw offset control based on reinforcement learning
  • Wind turbine yaw offset control based on reinforcement learning
  • Wind turbine yaw offset control based on reinforcement learning

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Embodiment Construction

[0027] Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings. It should be understood that the following description of the embodiments should not be construed as limiting. The scope of the present invention is not intended to be limited by the embodiments or drawings described below, which are to be considered as illustrative only.

[0028] The drawings are to be regarded as schematic representations and elements illustrated in the drawings, which are not necessarily shown to scale. Rather, various elements are represented so that their functions and general purpose will become apparent to those skilled in the art. Any connection or coupling between functional blocks, devices, components or other physical or functional units shown in the figures or described herein may also be through an indirect connection or coupling. Coupling between components can also be established via wireless connections. Functiona...

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Abstract

Methods, systems, and apparatus are disclosed for controlling a yaw offset of an upstream wind turbine based on reinforcement learning. The method includes receiving data indicative of a current state of a first wind turbine and a current state of a second wind turbine adjacent to the first wind turbine downstream along a wind direction, one or more control actions associated with a yaw offset of the first wind turbine are determined based on the current state of the first wind turbine, the current state of the second wind turbine, and a reinforcement learning algorithm, and the determined one or more control actions are applied to the first wind turbine.

Description

technical field [0001] Various embodiments of the invention relate to methods and apparatus for controlling yaw offset of one or more wind turbines by utilizing reinforcement learning. Background technique [0002] Wind turbines have been used for many years as a more environmentally friendly energy source. More and more onshore and offshore wind turbine farms are being built around the world. Currently, wind parks are operated in such a way that each wind turbine of the wind park operates at its respective optimum operating point according to the Bates limit. [0003] This technique of making each wind turbine of a wind farm operate at its respective optimum operating point faces certain limitations and drawbacks. The interaction between nearby wind turbines in a wind farm changes the power output compared to that of an isolated wind turbine. For example, along the wind direction, an upstream wind turbine generates a wake that affects a downstream wind turbine. Such eff...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): F03D7/04F03D17/00G05B13/02
CPCF03D7/048F03D7/0204F03D7/046F05B2270/20F05B2270/404F05B2270/709G05B13/027G05B2219/2619Y02E10/72F05B2270/204F05B2270/32F05B2270/321F05B2270/329G06N20/00
Inventor B·戈尔尼克
Owner SIEMENS GAMESA RENEWABLE ENERGY AS