Invention Grant
- Patent Title: Wind turbine control based on reinforcement learning
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Application No.: US17639925Application Date: 2020-08-13
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Publication No.: US12110867B2Publication Date: 2024-10-08
- Inventor: Bert Gollnick
- Applicant: Siemens Gamesa Renewable Energy A/S
- Applicant Address: DK Brande
- Assignee: Siemens Gamesa Renewable Energy A/S
- Current Assignee: Siemens Gamesa Renewable Energy A/S
- Current Assignee Address: DK Brande
- Agency: Schmeiser, Olsen & Watts LLP
- Priority: EP 197556 2019.09.16
- International Application: PCT/EP2020/072731 2020.08.13
- International Announcement: WO2021/052686A 2021.03.25
- Date entered country: 2022-03-03
- Main IPC: F03D7/04
- IPC: F03D7/04

Abstract:
Methods, systems, and devices for wind turbine control based on reinforcement learning are disclosed. The method comprises receiving data indicative of a current environmental state of the wind turbine, determining one or more controlling actions of the wind turbine based on the current environmental state of the wind turbine and a reinforcement learning algorithm, and applying the determined one or more controlling actions to the wind turbine.
Public/Granted literature
- US20220325696A1 WIND TURBINE CONTROL BASED ON REINFORCEMENT LEARNING Public/Granted day:2022-10-13
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