A method, apparatus, equipment, and medium for determining the operating load of a wind turbine generator set.

Abstract

This invention discloses a method, apparatus, equipment, and medium for determining the operating load of a wind turbine, relating to the field of power equipment technology. The method includes: determining target operating data of the wind turbine; determining the cumulative vibration acceleration value and model coefficients of the wind turbine based on the target operating data, wherein the cumulative vibration acceleration value includes the cumulative axial vibration acceleration value and the cumulative lateral vibration acceleration value, and the model coefficients include axial model coefficients and lateral model coefficients; and determining the operating load of the wind turbine based on the cumulative axial vibration acceleration value, the cumulative lateral vibration acceleration value, the axial model coefficients, and the lateral model coefficients. This invention determines the cumulative vibration acceleration value and model coefficients of the wind turbine based on its operating data, thereby determining the operating load of the wind turbine. This method enables simple, rapid, and efficient determination of the operating load of the wind turbine without the need for additional detection equipment, improving the feasibility of the operating load determination process.

Description

Technical Field

[0001] This invention relates to the field of power equipment technology, and in particular to a method, apparatus, equipment and medium for determining the operating load of a wind turbine. Background Technology

[0002] Wind turbine generators (also known as "wind turbines") are high-tech, high-performance products that convert wind energy into rotational mechanical energy through blades, then convert the mechanical energy into electrical energy through a generator, and finally input the electrical energy into the power grid. They are one of the most important pieces of equipment in the power equipment field. Therefore, the usage information and losses of wind turbine generators are among the issues that have received much attention.

[0003] The losses of wind turbines are primarily related to the loads they experience. These loads are transmitted through the hub to components such as the main shaft, generator, frame, and tower, thus affecting the turbine's performance, structure, and lifespan. Currently, the load on a wind turbine is determined using monitoring devices, such as real-time load monitoring systems installed near the turbine. However, installing such systems requires additional budget and may interfere with the turbine's operation. Furthermore, if the load monitoring system malfunctions, the operating load on the wind turbine cannot be determined. Summary of the Invention

[0004] This invention provides a method, apparatus, equipment, and medium for determining the operating load of a wind turbine, which can determine the operating load of a wind turbine simply, quickly, and efficiently without the need for additional testing equipment, thus improving the feasibility of the operating load determination process.

[0005] According to one aspect of the present invention, a method for determining the operating load of a wind turbine generator is provided, the method comprising:

[0006] Determine the target operating data for the wind turbine;

[0007] Based on the target operating data, the cumulative vibration acceleration value and model coefficients of the wind turbine are determined. The cumulative vibration acceleration value includes the cumulative axial vibration acceleration value and the cumulative lateral vibration acceleration value, and the model coefficients include the axial model coefficients and the lateral model coefficients.

[0008] The operating load of the wind turbine is determined based on the cumulative values ​​of axial vibration acceleration, lateral vibration acceleration, axial model coefficients, and lateral model coefficients.

[0009] Optionally, the target operating data for the wind turbine can be determined, including: acquiring historical operating data of the wind turbine; and filtering the historical operating data based on operating data filtering rules to obtain the target operating data.

[0010] Optionally, the target operating data includes the axial vibration acceleration of the wind turbine, the lateral vibration acceleration of the wind turbine, time information, wind direction information, wind speed information, start-up and shutdown information, and yaw information.

[0011] Optionally, based on the target operating data, the cumulative value of vibration acceleration and model coefficients of the wind turbine are determined, including: determining the cumulative value of axial vibration acceleration and the cumulative value of lateral vibration acceleration based on the preset duration, the axial vibration acceleration and the lateral vibration acceleration of the turbine; and determining the axial model coefficients and the lateral model coefficients based on time information, wind direction information, wind speed information, start-up and shutdown information and yaw information.

[0012] Optionally, based on a preset duration, the axial vibration acceleration of the unit, and the lateral vibration acceleration of the unit, the accumulated value of axial vibration acceleration and the accumulated value of lateral vibration acceleration are determined, including: determining the accumulated value of axial vibration acceleration based on a preset duration and the axial vibration acceleration of the unit; and determining the accumulated value of lateral vibration acceleration based on a preset duration and the lateral vibration acceleration of the unit.

[0013] Optionally, based on time information, wind direction information, wind speed information, start-up and shutdown information, and yaw information, the axial model coefficients and lateral model coefficients are determined, including: determining the operating time model coefficients of the wind turbine based on time information and the ideal operating time of the wind turbine; determining the axial wind resource model coefficients and lateral wind resource condition model coefficients of the wind turbine based on wind speed information, wind direction information, and the cut-out wind speed of the wind turbine; determining the start-up and shutdown frequency model coefficients of the wind turbine based on start-up and shutdown information; determining the yaw frequency model coefficients of the wind turbine based on yaw information; determining the axial model coefficients based on the operating time model coefficients, axial wind resource model coefficients, start-up and shutdown frequency model coefficients, and yaw frequency model coefficients; and determining the lateral model coefficients based on the operating time model coefficients, lateral wind resource condition model coefficients, start-up and shutdown frequency model coefficients, and yaw frequency model coefficients.

[0014] Optionally, the operating load of the wind turbine is determined based on the accumulated value of axial vibration acceleration, the accumulated value of lateral vibration acceleration, the axial model coefficient, and the lateral model coefficient, including: determining the axial operating load based on the accumulated value of axial vibration acceleration and the axial model coefficient; determining the lateral operating load based on the accumulated value of lateral vibration acceleration and the lateral model coefficient; and determining the operating load based on the axial operating load and the lateral operating load.

[0015] Optionally, the axial running load is the product of the accumulated axial vibration acceleration and the axial model coefficient; the lateral running load is the product of the accumulated lateral vibration acceleration and the lateral model coefficient; and the running load is the sum of the axial running load and the lateral running load.

[0016] According to another aspect of the present invention, a device for determining the operating load of a wind turbine generator is provided, the device comprising:

[0017] The acquisition module is used to determine the target operating data of the wind turbine.

[0018] The determination module is used to determine the cumulative vibration acceleration value and model coefficients of the wind turbine based on the target operating data. The cumulative vibration acceleration value includes the cumulative axial vibration acceleration value and the cumulative lateral vibration acceleration value, and the model coefficients include the axial model coefficients and the lateral model coefficients.

[0019] The execution module is used to determine the operating load of the wind turbine based on the accumulated values ​​of axial vibration acceleration, lateral vibration acceleration, axial model coefficients, and lateral model coefficients.

[0020] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0021] At least one processor; and a memory communicatively connected to the at least one processor;

[0022] The memory stores a computer program that can be executed by at least one processor, which is then executed by the at least one processor to enable the at least one processor to perform the method for determining the operating load of the wind turbine as described in any embodiment of the present invention.

[0023] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing a processor to execute and implement the method for determining the operating load of a wind turbine generator as described in any embodiment of the present invention.

[0024] The technical solution of this invention involves determining the target operating data of a wind turbine; based on the target operating data, determining the cumulative vibration acceleration value and model coefficients of the wind turbine, wherein the cumulative vibration acceleration value includes the cumulative axial vibration acceleration value and the cumulative lateral vibration acceleration value, and the model coefficients include the axial model coefficient and the lateral model coefficient; and based on the cumulative axial vibration acceleration value, the cumulative lateral vibration acceleration value, the axial model coefficient, and the lateral model coefficient, determining the operating load of the wind turbine. This invention can determine the cumulative axial vibration acceleration value, the cumulative lateral vibration acceleration value, the axial model coefficient, and the lateral model coefficient of the wind turbine based on its historical operating data, and determine the operating load of the wind turbine based on these values. This allows for a simple, fast, and efficient determination of the wind turbine's operating load without the need for additional testing equipment, thus improving the feasibility of the operating load determination process. This solves the problem that determining the load of wind turbines based on monitoring devices not only requires additional budget but may also interfere with the operation of wind turbines. Furthermore, if the wind turbine load monitoring device malfunctions, it will be impossible to determine the operating load of the wind turbine.

[0025] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0026] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0027] Figure 1 This is a flowchart illustrating a method for determining the operating load of a wind turbine generator according to Embodiment 1 of the present invention.

[0028] Figure 2 This is a flowchart illustrating a method for determining the operating load of a wind turbine generator according to Embodiment 2 of the present invention.

[0029] Figure 3 This is a schematic diagram of the structure of a device for determining the operating load of a wind turbine generator provided in Embodiment 3 of the present invention;

[0030] Figure 4 This is a schematic diagram of the structure of an electronic device provided in Embodiment 4 of the present invention. Detailed Implementation

[0031] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0032] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0033] Example 1

[0034] Figure 1 This is a flowchart illustrating a method for determining the operating load of a wind turbine generator according to Embodiment 1 of the present invention. This embodiment is applicable to situations such as determining the operating load of a wind turbine generator. The method can be executed by the wind turbine generator operating load determination device provided by the present invention. This device can be implemented in software and / or hardware. In a specific embodiment, the device can be integrated into an electronic device. The following embodiments will illustrate this using the integration of the device into an electronic device as an example. (Refer to...) Figure 1 The method specifically includes the following steps:

[0035] S101. Determine the target operating data for the wind turbine.

[0036] Among them, the target operating data of the wind turbine can be understood as the data used to determine the load on the wind turbine in the operating data of the wind turbine, that is, the operating data after removing inappropriate parameters. Inappropriate parameters include wind speed, wind turbine failure shutdown, manual shutdown, wind turbine maintenance, incomplete data, power less than or equal to 0, power limit, and operating data in the vortex sector angle.

[0037] Specifically, the target operating data includes the axial vibration acceleration of the wind turbine, the lateral vibration acceleration of the wind turbine, time information, wind direction information, wind speed information, start-up and shutdown information, and yaw information.

[0038] Furthermore, the axial vibration acceleration of the unit can be understood as the axial vibration acceleration of the unit within each unit of data collection time; the lateral vibration acceleration of the unit can be understood as the lateral vibration acceleration of the unit within each unit of data collection time; the time information can be understood as the operating time of the wind turbine; the wind direction information can be understood as the direction of the wind experienced by the wind turbine within each unit of data collection time; the wind speed information can be understood as the speed of the wind experienced by the wind turbine within each unit of data collection time; the start-stop information can be understood as the number of times the wind turbine is turned on and / or turned off; and the yaw information can be understood as the number of times the wind turbine yaws during operation.

[0039] The unit acquisition time can be set and adjusted according to the load requirements, including 30-second, 1-minute, 3-minute, and 5-minute levels, etc. This embodiment does not limit this.

[0040] The advantage of this setup is that it allows the target operating data of the wind turbine to be used to determine the load on the wind turbine, thereby improving the accuracy of the determined load.

[0041] S102. Based on the target operating data, determine the cumulative value of vibration acceleration and model coefficients of the wind turbine.

[0042] The cumulative vibration acceleration values ​​include the cumulative axial vibration acceleration values ​​and the cumulative lateral vibration acceleration values, and the model coefficients include the axial model coefficients and the lateral model coefficients.

[0043] Specifically, determining the cumulative vibration acceleration value and model coefficients of the wind turbine can be understood as determining the sum of the axial vibration acceleration, the sum of the lateral vibration acceleration, the axial model coefficient, and the lateral model coefficient of the wind turbine within the acquisition time. Furthermore, the acquisition time can be set and adjusted according to the load determination requirements, including 6 months, 12 months, 18 months, etc., but this embodiment does not limit this. This invention can determine the load of the wind turbine in units of acquisition time, reducing the frequency of load determination and lowering the workload of the load determination system.

[0044] S103. Based on the cumulative value of axial vibration acceleration, the cumulative value of lateral vibration acceleration, the axial model coefficient, and the lateral model coefficient, determine the operating load of the wind turbine.

[0045] The operating load of a wind turbine can be understood as the external force that the wind turbine bears during operation.

[0046] Specifically, the operating load of a wind turbine is calculated as: cumulative axial vibration acceleration * axial model coefficient + cumulative lateral vibration acceleration * lateral model coefficient.

[0047] The advantage of this setup is that it allows for the quantification of the wind turbine's operating load. By using the wind turbine's operating data to establish a deterministic logic / analysis model for the operating load, the operating load of the wind turbine during the data collection period can be obtained directly from the logic processing results / initial model results. This automates the periodic monitoring and evaluation of the wind turbine's operating load, helping wind farm maintenance personnel understand the operating status of the wind turbine (i.e., the wind turbine unit), predict the damage to components such as the main shaft bearings, gearbox, nacelle front frame tower bolts, and assess the lifespan of the wind turbine.

[0048] The technical solution of this embodiment determines the target operating data of the wind turbine; based on the target operating data, it determines the cumulative vibration acceleration value and model coefficients of the wind turbine, wherein the cumulative vibration acceleration value includes the cumulative axial vibration acceleration value and the cumulative lateral vibration acceleration value, and the model coefficients include the axial model coefficient and the lateral model coefficient; based on the cumulative axial vibration acceleration value, the cumulative lateral vibration acceleration value, the axial model coefficient, and the lateral model coefficient, it determines the operating load of the wind turbine. This invention can determine the cumulative axial vibration acceleration value, the cumulative lateral vibration acceleration value, the axial model coefficient, and the lateral model coefficient of the wind turbine based on its historical operating data, and determine the operating load of the wind turbine based on these values. This allows for a simple, fast, and efficient determination of the wind turbine's operating load without the need for additional testing equipment, improving the feasibility of the operating load determination process. This solves the problem that determining the load of wind turbines based on monitoring devices not only requires additional budget but may also interfere with the operation of wind turbines. Furthermore, if the wind turbine load monitoring device malfunctions, it will be impossible to determine the operating load of the wind turbine.

[0049] Example 2

[0050] Figure 2 This is a flowchart illustrating a method for determining the operating load of a wind turbine generator according to Embodiment 2 of the present invention. This embodiment is applicable to situations such as determining the operating load of a wind turbine generator. The method can be executed by the wind turbine generator operating load determination device provided by the present invention. This device can be implemented in software and / or hardware. In a specific embodiment, the device can be integrated into an electronic device. The following embodiments will illustrate this using the integration of the device into an electronic device as an example. (Refer to...) Figure 2 The method specifically includes the following steps:

[0051] S201. Obtain historical operating data of wind turbine units.

[0052] Historical operating data can be understood as the operating data of wind turbines within a preset time period.

[0053] Specifically, the preset time period can be set and adjusted according to the data acquisition needs, including the operating data of the wind turbine for the past year, the operating data of the wind turbine for the past six months, and all operating data of the wind turbine, etc. This embodiment does not limit this.

[0054] The advantage of this setup is that it allows for the acquisition of comprehensive operational data from the wind turbine, ensuring the integrity of the operational data.

[0055] S202. Based on the operation data filtering rules, filter the historical operation data to obtain the target operation data.

[0056] Historical operating data refers to all operating data of wind turbines within a certain period, including both data that can be used to determine the operating load of wind turbines and data that cannot determine the operating load of wind turbines. Target data can be understood as the data in historical operating data used to determine the operating load of wind turbines. Operating data filtering rules can be understood as the methods for filtering target operating data or removing inappropriate operating data from historical operating data.

[0057] Specifically, the target operating data includes the axial vibration acceleration of the wind turbine, the lateral vibration acceleration of the wind turbine, time information, wind direction information, wind speed information, start-up and shutdown information, and yaw information.

[0058] Furthermore, the operational data screening rules include two types: International Electrotechnical Commission (IEC) standards and analysis of actual wind turbine operation. Based on IEC standards, historical operational data containing information on wind speed, turbine failures, manual shutdowns, and turbine maintenance can be removed. Based on analysis of actual wind turbine operation, historical operational data containing incomplete data, power less than or equal to 0, power limits, and data located in the eddy current sector angle can be removed. After two rounds of screening, the target operational data for determining the operating load of the wind turbine can be obtained.

[0059] The advantage of this setup is that it first processes historical operating data, uses appropriate operating data to determine the operating load of the wind turbine, improves the accuracy of the determined operating load, reduces the amount of operating data processing, and saves data processing resources.

[0060] S203. Based on the preset duration, the axial vibration acceleration of the unit, and the lateral vibration acceleration of the unit, determine the cumulative value of the axial vibration acceleration and the cumulative value of the lateral vibration acceleration.

[0061] The preset duration can be understood as the information collection time. The axial vibration acceleration of the unit can be understood as the axial vibration acceleration of the unit within each unit collection time. The lateral vibration acceleration of the unit can be understood as the lateral vibration acceleration of the unit within each unit collection time. The collection time can be set and adjusted according to the load requirements, including 6 months, 12 months, 18 months, etc. The unit collection time can be set and adjusted according to the load requirements, including 30 seconds, 1 minute, 3 minutes, 5 minutes, etc. This embodiment does not limit this.

[0062] Specifically, determining the cumulative values ​​of axial vibration acceleration and lateral vibration acceleration of a wind turbine can be understood as determining the sum of the axial vibration acceleration and the sum of the lateral vibration acceleration of the wind turbine within the acquisition time.

[0063] In one embodiment, S203 may specifically include: determining the cumulative value of axial vibration acceleration based on a preset duration and the axial vibration acceleration of the unit; and determining the cumulative value of lateral vibration acceleration based on a preset duration and the lateral vibration acceleration of the unit.

[0064] Assuming a unit acquisition time of 1 minute and an acquisition time (preset duration) of 1 year, the cumulative value of axial vibration acceleration... Where i represents the acquisition time corresponding to the unit acquisition time, A xi The axial vibration acceleration corresponds to the acquisition time i, and Δt represents the acquisition time difference, which can be understood as 1 minute in this embodiment; the accumulated value of lateral vibration acceleration. Where i represents the acquisition time corresponding to the unit acquisition time, A yi Δt represents the lateral vibration acceleration at acquisition time i, and Δt represents the acquisition time difference.

[0065] S204. Based on time information, wind direction information, wind speed information, start-stop information, and yaw information, determine the axial model coefficients and lateral model coefficients.

[0066] Among them, time information can be understood as the operating time of the wind turbine, wind direction information can be understood as the direction of the wind experienced by the wind turbine during each unit of data collection time, wind speed information can be understood as the speed of the wind experienced by the wind turbine during each unit of data collection time, start-stop information can be understood as the number of times the wind turbine is turned on and / or turned off, and yaw information can be understood as the number of times the wind turbine yaws during operation.

[0067] Specifically, wind turbines are configured with axial and lateral winds. The wind direction information is different for different directions. Therefore, determining the axial and lateral model coefficients based on time information, wind direction information, wind speed information, start-stop information, and yaw information includes determining the axial model coefficients based on time information, wind speed information, start-stop information, yaw information, and axial wind resources, and determining the lateral model coefficients based on time information, wind speed information, start-stop information, yaw information, and lateral wind resources.

[0068] In one embodiment, S204 may specifically include: determining the operating time model coefficient of the wind turbine based on time information and the ideal operating time of the wind turbine; determining the axial wind resource model coefficient and the lateral wind resource model coefficient of the wind turbine based on wind speed information, wind direction information and the cut-out wind speed of the wind turbine; determining the start-stop frequency model coefficient of the wind turbine based on start-stop information; determining the yaw frequency model coefficient of the wind turbine based on yaw information; determining the axial model coefficient based on the operating time model coefficient, axial wind resource model coefficient, start-stop frequency model coefficient and yaw frequency model coefficient; and determining the lateral model coefficient based on the operating time model coefficient, lateral wind resource model coefficient, start-stop frequency model coefficient and yaw frequency model coefficient.

[0069] Among them, the ideal operating time of a wind turbine can be understood as the design life of the wind turbine, the cut-out wind speed of a wind turbine is related to the model of the wind turbine, and the cut-off wind speed of a wind turbine can be understood as a constant value.

[0070] Specifically, the operating time model coefficients of wind turbine units Among them, t w Represents time information (operating time of the wind turbine), t d This represents the ideal operating time of the wind turbine. The axial wind resource model coefficients for the wind turbine are also mentioned. Model coefficients for lateral wind resources of wind turbines Where i represents the acquisition time corresponding to the unit acquisition time, V mi V represents the wind speed at time i. co α represents the cut-out wind speed of the wind turbine. i This represents the angle between the wind speed and direction at time i and the wind turbine axis. The model coefficients for the number of start-stop cycles of the wind turbine are also included. Where, N s This represents the number of start-ups and shutdowns of the wind turbine. The yaw rate model coefficients for the wind turbine. Where, N d This represents the yaw rate of the wind turbine. Axial model coefficient λ x =λ1·λ 2x ·λ3·λ4, lateral model coefficients λ y =λ1·λ 2y·λ3·λ4, where λ1 represents the operating time model coefficient of the wind turbine, λ 2x λ represents the axial wind resource model coefficient of the wind turbine. 2y λ represents the lateral wind resource condition model coefficient of the wind turbine, λ3 represents the start-stop frequency model coefficient of the wind turbine, and λ4 represents the yaw frequency model coefficient of the wind turbine.

[0071] S205. Based on the cumulative value of axial vibration acceleration, the cumulative value of lateral vibration acceleration, the axial model coefficient, and the lateral model coefficient, determine the operating load of the wind turbine.

[0072] The operating load of a wind turbine can be understood as the external force that the wind turbine bears during operation. Specifically, the operating load of a wind turbine = cumulative axial vibration acceleration * axial model coefficient + cumulative lateral vibration acceleration * lateral model coefficient.

[0073] In one embodiment, S205 may specifically include: determining the axial running load based on the accumulated value of axial vibration acceleration and the axial model coefficient; determining the lateral running load based on the accumulated value of lateral vibration acceleration and the lateral model coefficient; and determining the running load based on the axial running load and the lateral running load.

[0074] Among them, the axial running load is the product of the cumulative value of axial vibration acceleration and the axial model coefficient, the lateral running load is the product of the cumulative value of lateral vibration acceleration and the lateral model coefficient, and the running load is the sum of the axial running load and the lateral running load.

[0075] For example, axial running load A x =λ x ·A xo , where λ x A represents the axial model coefficient. xo This represents the cumulative value of axial vibration acceleration. Lateral running load A y =λ y ·A yo , where λ y A represents the lateral model coefficients. yo This represents the cumulative value of lateral vibration acceleration. Operating load A = A x +A y , where A x Indicates axial running load, A y This indicates a lateral running load.

[0076] The technical solution of this embodiment involves acquiring historical operating data of the wind turbine; filtering the historical operating data based on operating data filtering rules to obtain target operating data; determining the cumulative value of axial vibration acceleration and the cumulative value of lateral vibration acceleration based on a preset duration, the axial vibration acceleration, and the lateral vibration acceleration; determining the axial model coefficient and the lateral model coefficient based on time information, wind direction information, wind speed information, start-up and shutdown information, and yaw information; and determining the operating load of the wind turbine based on the cumulative value of axial vibration acceleration, the cumulative value of lateral vibration acceleration, the axial model coefficient, and the lateral model coefficient. This invention determines the target operating data of a wind turbine based on its historical operating data and operating data filtering rules, reducing the impact of interfering data on the load determination process. Based on the target operating data, it determines the cumulative axial vibration acceleration, cumulative lateral vibration acceleration, axial model coefficient, and lateral model coefficient of the wind turbine. Then, based on these values, it determines the operating load of the wind turbine. This method enables simple, fast, and efficient determination of the wind turbine's operating load without the need for additional detection equipment, improving the feasibility of the load determination process. It solves the problems of determining the wind turbine load based on monitoring devices, which not only requires additional budget but may also interfere with the wind turbine's operation, and cannot determine the operating load if the wind turbine load monitoring device malfunctions.

[0077] Example 3

[0078] Figure 3 This is a schematic diagram of a device for determining the operating load of a wind turbine generator provided in Embodiment 3 of the present invention. Figure 3 As shown, the device includes: an acquisition module 301, a determination module 302, and an execution module 303.

[0079] The acquisition module 301 is used to determine the target operating data of the wind turbine.

[0080] The determination module 302 is used to determine the cumulative vibration acceleration value and model coefficients of the wind turbine based on the target operating data. The cumulative vibration acceleration value includes the cumulative axial vibration acceleration value and the cumulative lateral vibration acceleration value, and the model coefficients include the axial model coefficients and the lateral model coefficients.

[0081] The execution module 303 is used to determine the operating load of the wind turbine based on the accumulated value of axial vibration acceleration, the accumulated value of lateral vibration acceleration, the axial model coefficient, and the lateral model coefficient.

[0082] Optionally, module 301 is used to acquire historical operating data of wind turbine units; and to filter the historical operating data based on operating data filtering rules to obtain target operating data.

[0083] Optionally, the target operating data includes the axial vibration acceleration of the wind turbine, the lateral vibration acceleration of the wind turbine, time information, wind direction information, wind speed information, start-up and shutdown information, and yaw information.

[0084] Optionally, module 302 is specifically used to determine the cumulative value of axial vibration acceleration and the cumulative value of lateral vibration acceleration based on a preset duration, the axial vibration acceleration of the unit and the lateral vibration acceleration of the unit; and to determine the axial model coefficient and the lateral model coefficient based on time information, wind direction information, wind speed information, start-up and shutdown information and yaw information.

[0085] Optionally, module 302 is specifically used to determine the cumulative value of axial vibration acceleration based on a preset duration and the axial vibration acceleration of the unit; and to determine the cumulative value of lateral vibration acceleration based on a preset duration and the lateral vibration acceleration of the unit.

[0086] Optionally, module 302 is specifically used to determine the operating time model coefficients of the wind turbine based on time information and the ideal operating time of the wind turbine; to determine the axial wind resource model coefficients and lateral wind resource model coefficients of the wind turbine based on wind speed information, wind direction information and the cut-out wind speed of the wind turbine; to determine the start-stop frequency model coefficients of the wind turbine based on start-stop information; to determine the yaw frequency model coefficients of the wind turbine based on yaw information; to determine the axial model coefficients based on the operating time model coefficients, axial wind resource model coefficients, start-stop frequency model coefficients and yaw frequency model coefficients; and to determine the lateral model coefficients based on the operating time model coefficients, lateral wind resource model coefficients, start-stop frequency model coefficients and yaw frequency model coefficients.

[0087] Optionally, the execution module 303 is specifically used to determine the axial running load based on the accumulated value of axial vibration acceleration and the axial model coefficient; to determine the lateral running load based on the accumulated value of lateral vibration acceleration and the lateral model coefficient; and to determine the running load based on the axial running load and the lateral running load.

[0088] Optionally, the axial running load is the product of the accumulated axial vibration acceleration and the axial model coefficient; the lateral running load is the product of the accumulated lateral vibration acceleration and the lateral model coefficient; and the running load is the sum of the axial running load and the lateral running load.

[0089] The wind turbine operating load determination device provided in this embodiment of the invention can execute the wind turbine operating load determination method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0090] Example 4

[0091] Figure 4This is a schematic diagram of the structure of an electronic device provided in Embodiment 4 of the present invention. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0092] like Figure 4 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 may also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0093] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0094] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as methods for determining the operating load of a wind turbine.

[0095] In some embodiments, the method for determining the operating load of the wind turbine can be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the method for determining the operating load of the wind turbine described above can be performed. Alternatively, in other embodiments, processor 11 can be configured to perform the method for determining the operating load of the wind turbine by any other suitable means (e.g., by means of firmware).

[0096] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0097] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0098] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0099] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0100] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0101] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0102] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0103] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for determining the operating load of a wind turbine generator set, characterized in that, include: Determine the target operating data for the wind turbine; The target operating data includes the axial vibration acceleration, lateral vibration acceleration, time information, wind direction information, wind speed information, start-up and shutdown information, and yaw information of the wind turbine unit; Based on the target operating data, the cumulative vibration acceleration value and model coefficients of the wind turbine are determined, wherein the cumulative vibration acceleration value includes the cumulative axial vibration acceleration value and the cumulative lateral vibration acceleration value, and the model coefficients include the axial model coefficients and the lateral model coefficients. Based on the accumulated value of axial vibration acceleration, the accumulated value of lateral vibration acceleration, the axial model coefficient, and the lateral model coefficient, the operating load of the wind turbine is determined; The determination of the cumulative vibration acceleration value and model coefficients of the wind turbine based on the target operating data includes: Based on a preset duration, the axial vibration acceleration of the unit, and the lateral vibration acceleration of the unit, the cumulative value of the axial vibration acceleration and the cumulative value of the lateral vibration acceleration are determined. Based on the time information, wind direction information, wind speed information, start-stop information, and yaw information, the axial model coefficients and the lateral model coefficients are determined; The determination of the axial model coefficients and the lateral model coefficients based on the time information, wind direction information, wind speed information, start-stop information, and yaw information includes: Based on the time information and the ideal operating time of the wind turbine, the operating time model coefficients of the wind turbine are determined; Based on the wind speed information, the wind direction information, and the cut-out wind speed of the wind turbine, the axial wind resource model coefficient and the lateral wind resource condition model coefficient of the wind turbine are determined. Based on the start-up and shutdown information, determine the start-up and shutdown frequency model coefficients of the wind turbine unit; Based on the yaw information, determine the yaw frequency model coefficients of the wind turbine. The axial model coefficients are determined based on the running time model coefficients, the axial wind resource model coefficients, the start-stop frequency model coefficients, and the yaw frequency model coefficients. The lateral model coefficients are determined based on the running time model coefficients, the lateral wind resource condition model coefficients, the start-stop frequency model coefficients, and the yaw frequency model coefficients.

2. The method according to claim 1, characterized in that, The determination of the target operating data for the wind turbine includes: Obtain the historical operating data of the wind turbine; The historical operational data is filtered based on operational data filtering rules to obtain the target operational data.

3. The method according to claim 1, characterized in that, The determination of the accumulated values ​​of the axial vibration acceleration and the lateral vibration acceleration based on a preset duration, the axial vibration acceleration of the unit, and the lateral vibration acceleration of the unit includes: The cumulative value of the axial vibration acceleration is determined based on the preset duration and the axial vibration acceleration of the unit; The cumulative value of the lateral vibration acceleration is determined based on the preset duration and the lateral vibration acceleration of the unit.

4. The method according to claim 1, characterized in that, The determination of the operating load of the wind turbine based on the accumulated axial vibration acceleration, the accumulated lateral vibration acceleration, the axial model coefficient, and the lateral model coefficient includes: The axial running load is determined based on the accumulated value of the axial vibration acceleration and the axial model coefficients. Based on the accumulated value of lateral vibration acceleration and the lateral model coefficients, the lateral running load is determined; The operating load is determined based on the axial operating load and the lateral operating load.

5. A device for determining the operating load of a wind turbine generator set, characterized in that, The method for determining the operating load of a wind turbine generator as described in any one of claims 1 to 4, wherein the device for determining the operating load of the wind turbine generator comprises: The acquisition module is used to determine the target operating data of the wind turbine. The determination module is used to determine the cumulative vibration acceleration value and model coefficients of the wind turbine based on the target operating data, wherein the cumulative vibration acceleration value includes the cumulative axial vibration acceleration value and the cumulative lateral vibration acceleration value, and the model coefficients include the axial model coefficients and the lateral model coefficients; The execution module is used to determine the operating load of the wind turbine based on the accumulated value of axial vibration acceleration, the accumulated value of lateral vibration acceleration, the axial model coefficient, and the lateral model coefficient.

6. An electronic device, characterized in that, The electronic device includes: At least one processor; and a memory communicatively connected to said at least one processor; The memory stores a computer program that can be executed by the at least one processor, which is then executed by the at least one processor to enable the at least one processor to perform the method for determining the operating load of the wind turbine as described in any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that are used to cause a processor to execute the method for determining the operating load of the wind turbine as described in any one of claims 1 to 4.

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