Xinjiang Goldwind Science & Technology has filed a patent for a load control method and apparatus for wind turbine generator systems. The method involves obtaining feature parameters for load prediction, using a virtual load sensor to estimate the load, and adjusting the control strategy based on the estimated load. This allows for real-time monitoring and adjustment of the wind turbine generator system based on the load. GlobalData’s report on Xinjiang Goldwind Science & Technology gives a 360-degree view of the company including its patenting strategy. Buy the report here.

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According to GlobalData’s company profile on Xinjiang Goldwind Science & Technology, Ram air turbine was a key innovation area identified from patents. Xinjiang Goldwind Science & Technology's grant share as of September 2023 was 49%. Grant share is based on the ratio of number of grants to total number of patents.

Load control method for wind turbine generator system

Source: United States Patent and Trademark Office (USPTO). Credit: Xinjiang Goldwind Science & Technology Co Ltd

A recently filed patent (Publication Number: US20230265832A1) describes a load control method for a wind turbine generator system. The method involves obtaining feature parameters of the wind turbine generator system for load prediction, obtaining a load estimation value by inputting the feature parameters into a virtual load sensor, and adjusting the control strategy of the wind turbine generator system based on the obtained load estimation value.

The feature parameters used for load prediction include a configuration parameter, a control parameter, an operation parameter, and a preset flag. The preset flag can indicate a preset event flag and/or a preset fault flag.

The load estimation value consists of a real-time load estimation value at the current moment and a load prediction value after a predetermined duration. The control strategy adjustment involves controlling the wind turbine generator system to perform a shutdown control strategy or a load reduction control strategy based on the real-time load estimation value and the load prediction value.

The method includes comparing the real-time load estimation value to a load risk threshold and controlling the wind turbine generator system accordingly. If the real-time load estimation value is not less than the load risk threshold, the system performs a shutdown control strategy and sends an alarm signal. If the real-time load estimation value is less than the load risk threshold, the system compares it to a load warning threshold. If the load prediction value is not less than the load risk threshold, the system performs a load reduction control strategy.

The virtual load sensor used in the method is trained using simulation data of the wind turbine generator system under all operating conditions. The training involves building a feature matrix and a target matrix based on the simulation data, where the feature matrix consists of the feature parameters for load prediction and the target matrix consists of real-time load values. The virtual load sensor is then trained using the feature matrix as input and the target matrix as output.

The patent also describes a load control apparatus for a wind turbine generator system, which includes modules for obtaining feature parameters, obtaining load estimation values, and adjusting the control strategy based on the load estimation values.

Additionally, the patent mentions a controller with a processor and memory that stores a computer program implementing the load control method, as well as a computer-readable storage medium storing the same program.

Overall, this patent presents a load control method and apparatus for wind turbine generator systems that utilizes feature parameters, virtual load sensors, and control strategy adjustments to optimize the performance and safety of the system.

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