Siemens Gamesa Renewable Energy A/s

Siemens Gamesa Renewable Energy Gmbh & Co. Kg

Bert Gollnick

Xavier Vives Jaume

Fabian Walz

Julien Berbach

Simon Slapka

Jon Gould

Vinay Kumar Manjunatha

Uffe Sjølund Freiberg

A method of operating a wind turbine is provided. The wind turbine is operable in plural different operating modes that differ by at least one of lifetime consumption of the wind turbine and energy production by the wind turbine. A sequence of operating modes is determined for a future period of time, wherein an optimization parameter is estimated based on at least one estimated external parameter. The method further includes obtaining a current value for the at least one external parameter and determining an actual operating mode for the wind turbine for a current point in time, wherein the determining of the actual operating mode comprises estimating an adjusted optimization parameter for plural sequences and for the current value of the at least one external parameter, and selecting the actual operating mode based on the estimated adjusted optimization parameters. The wind turbine is operated in the determined actual operating mode.

Method of operating a wind turbine

A method for a renewable energy generating system is provided. The renewable energy generating system includes the following steps: —determining, by a first energy meter, a produced energy amount of the renewable energy generating system in the predetermined period of time; —verifying the produced energy amount of the renewable energy generating system in the predetermined period of time; —issuing, by a computing unit, an energy certificate for the renewable energy generating system for the predetermined period of time, where the energy certificate at least comprises a time stamp indicating the predetermined period of time, an identifier indicating the one or group of renewable energy generators having produced the energy amount, and the produced energy amount; —encrypting, by the computing unit, the energy certificated; and —adding, by the computing unit, the encrypted energy certificate to a block of a blockchain or a distributed ledger application as a digital output.

Method and apparatus for computer-implemented monitoring of energy production of a renewable energy generating system

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.

Wind turbine control based on reinforcement learning

A method of controlling plural wind turbines is provided, wherein each wind turbine is operable in different operating modes, wherein operating parameters and/or operating features are set differently in the different operating modes. For at least a first of the plural wind turbines, at least some of the different operating modes have a different impact on a residual lifetime of at least a second of the plural wind turbines. In embodiments, the method includes providing at least one candidate operating scheme and estimating a residual lifetime and/or at least one optimization parameter. Estimating of the residual lifetime and/or the optimization parameter considers the impact of the operating mode of the first wind turbine specified in the candidate operating scheme on the residual lifetime of the second wind turbine. The plural wind turbines are then operated in accordance with an operating scheme selected from the candidate operating schemes.

Controlling the operation of plural wind turbines

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

Wind turbine yaw offset control based on reinforcement learning

Provided is a method for monitoring one or more wind turbines in a wind farm, each wind turbine having a rotor with rotor blades which are rotatable around a rotor axis, wherein one or several times during the operation of the wind farm a process is performed that includes

Method and an apparatus for computer-implemented monitoring of one or more wind turbines in a wind farm

A method and system of controlling operation of wind turbines is provided, the method including (a) receiving a parameter value which is based on at least one sensor signal, (b) determining a difference between the received parameter value and a predetermined value, (c) comparing the difference with a threshold value, and (d) if the difference is below the threshold value, operating the wind turbines in a first mode of operation, (e) if the difference is not below the threshold value, incrementing an alert counter, comparing the alert counter with an alert threshold value, operating the wind turbines in a second mode of operation if the alert counter is smaller than the alert threshold value or if the alert counter exceeds the second threshold value and the difference is decreasing, triggering an alarm if the alert counter exceeds the alert threshold value and the difference is not decreasing.

Method and system for controlling operation of wind turbines

Provided is a method for computer-implemented monitoring of wind turbines in a wind farm each wind turbine including, an upper section being pivotable around a vertical yaw axis wherein the following steps are performed:

Provided is a warning light apparatus for at least one wind turbine including: at least one warning light, at least one sensor for detecting the presence of an object, a presence acquisition device connected to the at least one sensor the presence acquisition device being configured for: triggering the capturing of data through the at least one sensor, analysing the data captured through the at least one sensor for detecting the presence of objects, a warning controller connected to the at least one warning light and the presence acquisition device, the warning controller being configured for: receiving information about the detection of objects from the presence acquisition device, sending function signals depending on the information received from the presence acquisition device for activating or deactivating the at least one warning light.

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Hamburg, Germany

Bert Gollnick