Load simulation method and device of wind generating set and storage medium

Abstract

The invention provides a load simulation method and device for a wind generating set and a storage medium. The load simulation method comprises the steps that terrain information of a target wind power plant where a target wind generating set is located and actually-measured wind parameters of a preset observation point are obtained; based on the topographic information, performing simulation processing on the wind parameters of the target wind power plant to obtain wind power plant simulation wind parameters; determining predicted wind parameters of a plurality of points in an impeller surface of the target wind generating set according to the simulated wind parameters and the actually measured wind parameters of the wind power plant to obtain predicted wind parameters of the impeller surface; and performing simulation processing on the load of the target wind generating set based on the impeller surface prediction wind parameter to obtain a set simulation load. According to the method, the predicted wind parameters of a plurality of points in the impeller surface of the target wind generating set are determined by combining the wind power plant simulation wind parameters and the actually measured wind parameters obtained through simulation, the actual wind parameters borne by the set on the whole impeller surface can be predicted, and then the accurate set simulation load is calculated; and simulation measurement deviation caused by wind parameter imbalance of the impeller surface is fully reduced.

Description

Technical Field

[0001] The present disclosure relates to the field of wind turbines, and more specifically, to a load simulation method, device and storage medium for a wind turbine generator set. Background Art

[0002] During the entire life cycle of a wind farm, it is necessary to ensure that the wind turbine has a normal operating life of 20 years. This requires that during the design phase of the wind turbine, the load strength caused by various wind conditions that the unit is subjected to during operation must be considered. Fatigue load and limit load are two important parameters for measuring the safety performance of wind turbines. The traditional method is to calibrate the load of the unit based on the wind turbine design specifications in the IEC (International Electrotechnical Commission) standard. However, in the load test and simulation comparison of the operating unit, it was found that there was a large error between the two, and the maximum fatigue load error reached 30%. This has led to an endless stream of unit failure problems in actual operating wind farms, and unit vibration, blade sweeping towers, tower collapses and other phenomena often occur. How to reduce the simulation deviation, that is, the deviation between the simulation load and the test load, so as to more accurately simulate the wind turbine load, is an urgent problem to be solved within the industry. Summary of the invention

[0003] Therefore, how to reduce the simulation bias is crucial.

[0004] In a general aspect, a method for simulating the load of a wind turbine generator set is provided, the method comprising: acquiring terrain information of a target wind farm where the target wind turbine generator set is located and measured wind parameters at predetermined observation points; simulating the wind parameters of the target wind farm based on the terrain information to obtain simulated wind parameters of the wind farm; determining predicted wind parameters of multiple points within an impeller surface of the target wind turbine generator set based on the simulated wind parameters of the wind farm and the measured wind parameters to obtain predicted wind parameters of the impeller surface; simulating the load of the target wind turbine generator set based on the predicted wind parameters of the impeller surface to obtain a simulated load of the unit.

[0005] Optionally, the wind parameters of the target wind farm are simulated based on the terrain information to obtain the simulated wind parameters of the wind farm, including: determining a plurality of preset sectors, each preset sector representing a wind direction; for each preset sector of the plurality of preset sectors, based on the terrain information, the wind parameters of the target wind farm are simulated to obtain the simulated wind parameters of the wind farm for each preset sector.

[0006] Optionally, the predicted wind parameters of multiple points within the impeller surface of the target wind turbine generator set are determined based on the wind farm simulation wind parameters and the measured wind parameters to obtain the predicted wind parameters of the impeller surface, including: for each preset sector of the multiple preset sectors, taking the direction facing the incoming wind as the impeller surface orientation of the target wind turbine generator set in the preset sector; based on the wind farm simulation wind parameters and the measured wind parameters of each preset sector, the predicted wind parameters of multiple points within the impeller surface of the target wind turbine generator set in each preset sector are determined to obtain the predicted wind parameters of the impeller surface of each preset sector.

[0007] Optionally, the load of the target wind turbine generator set is simulated based on the predicted wind parameters of the impeller surface to obtain the simulated load of the unit, including: based on the predicted wind parameters of the impeller surface of each preset sector, the load of the target wind turbine generator set in each preset sector is simulated to obtain the simulated load of each preset sector; and the simulated loads of multiple preset sectors are combined to obtain the simulated load of the unit.

[0008] Optionally, the predicted wind parameters of multiple points of the impeller surface of the target wind turbine generator set in each preset sector are determined according to the wind farm simulation wind parameters of each preset sector and the measured wind parameters to obtain the predicted wind parameters of the impeller surface of each preset sector, including: statistically processing the measured wind parameters according to the multiple preset sectors and the multiple preset wind speed segments to obtain statistical wind parameters in multiple preset intervals, each of the multiple preset intervals corresponding to a preset sector and a preset wind speed segment; for each preset interval of the multiple preset intervals, determining the predicted wind parameters of multiple points of the impeller surface of the target wind turbine generator set in the preset sector corresponding to the preset interval according to the wind farm simulation wind parameters of the preset sector corresponding to the preset interval and the statistical wind parameters in the preset interval to obtain the predicted wind parameters of the impeller surface of the preset interval.

[0009] Optionally, the load of the target wind turbine generator set in each preset sector is simulated based on the predicted wind parameters of the impeller surface in each preset sector to obtain the simulated load of each preset sector, including: for each preset interval in the multiple preset intervals, determining the interval simulation load of the target wind turbine generator set in the preset interval according to the predicted wind parameters of the impeller surface in the preset interval.

[0010] Optionally, the simulation loads of the multiple preset sectors are combined to obtain the simulation load of the unit, including: combining the interval simulation loads of multiple preset intervals corresponding to the same preset wind speed segment to obtain the simulation load corresponding to each preset wind speed segment in the multiple preset wind speed segments as the simulation load of the unit.

[0011] Optionally, for each preset interval in the multiple preset intervals, based on the wind farm simulation wind parameters of the preset sector corresponding to the preset interval and the statistical wind parameters under the preset interval, the predicted wind parameters of multiple points of the impeller surface of the target wind turbine generator set in the preset sector corresponding to the preset interval are determined to obtain the predicted wind parameters of the impeller surface of the preset interval, including: for each preset sector in the multiple preset sectors, according to the impeller surface orientation of the target wind turbine generator set in the preset sector, constructing the impeller surface grid of the target wind turbine generator set in the preset sector; for each preset sector in the multiple preset sectors, the target wind turbine generator set in the preset sector is positioned at the impeller surface grid; The grid points in the impeller surface grid of the preset sector are taken as multiple points within the impeller surface, and based on the simulated wind parameters of the wind farm in the preset sector, the simulated wind parameters at the predetermined observation points are determined by interpolation method; for each preset interval in the multiple preset intervals, the predicted wind parameters of each grid point in the impeller surface grid of the preset sector corresponding to the preset interval of the target wind turbine generator set and the simulated wind parameters at the predetermined observation point are determined according to the statistical wind parameters under the preset interval, so as to obtain the predicted wind parameters of the impeller surface of the preset interval.

[0012] Optionally, each grid point of the impeller surface grid includes a hub center point and a non-hub center point, wherein, for each preset interval in the multiple preset intervals, according to each grid point in the impeller surface grid of the preset sector corresponding to the preset interval of the target wind turbine generator set and the simulated wind parameters at the predetermined observation point, as well as the statistical wind parameters under the preset interval, the predicted wind parameters of each grid point in the impeller surface grid of the preset sector corresponding to the preset interval of the target wind turbine generator set are determined, and the predicted wind parameters of the impeller surface of the preset interval are obtained, including: for each preset interval in the multiple preset intervals, the predicted wind parameters of the impeller surface of the target wind turbine generator set corresponding to the preset interval in the preset interval are obtained. For each grid point in the impeller surface grid of the preset sector, according to the simulation wind parameters and reference wind parameters of the reference point corresponding to the grid point, the simulation wind parameters of the grid point are corrected to obtain the predicted wind parameters of the grid point; the predicted wind parameters of each grid point in the impeller surface grid of the preset sector corresponding to the preset interval of the target wind turbine generator set are used as the predicted wind parameters of the impeller surface of the preset interval; wherein the reference point corresponding to the hub center point is the predetermined observation point, the reference point corresponding to the non-hub center point is the hub center point, the reference wind parameters of the predetermined observation point are the statistical wind parameters under the preset interval, and the reference wind parameters of the hub center point are the predicted wind parameters of the hub center point.

[0013] Optionally, the wind parameters include wind speed, turbulence intensity and wind direction, wherein the simulated wind parameters of the grid point are corrected according to the simulated wind parameters and reference wind parameters of the reference point corresponding to the grid point to obtain the predicted wind parameters of the grid point, including: based on the respective correction relationships of different wind parameters, the simulated wind parameters of the grid point are corrected according to the simulated wind parameters and reference wind parameters of the reference point corresponding to the grid point to obtain the predicted wind parameters of the grid point, wherein the correction relationship of the wind speed is that the ratio of the predicted wind speed of the grid point to the simulated wind speed is equal to the ratio of the reference wind speed of the reference point corresponding to the grid point to the simulated wind speed; turbulence intensity The correction relationship is that the ratio of the predicted turbulence difference to the simulated turbulence difference is equal to the ratio of the simulated wind speed of the grid point to the simulated wind speed of the reference point corresponding to the grid point, wherein the predicted turbulence difference is the difference between the predicted turbulence intensity of the grid point and the reference turbulence intensity of the reference point corresponding to the grid point, and the simulated turbulence difference is the difference between the simulated turbulence intensity of the grid point and the simulated turbulence intensity of the reference point corresponding to the grid point; the correction relationship of wind direction is that the difference between the predicted wind direction and the simulated wind direction of the grid point is equal to the difference between the reference wind direction and the simulated wind direction of the reference point corresponding to the grid point.

[0014] Optionally, based on the terrain information, simulating the wind parameters of multiple points in the target wind farm to obtain the simulated wind parameters of the wind farm, including: determining a complexity index of the target wind farm based on the terrain information, wherein the complexity index is used to represent the terrain complexity of the target wind farm; when the complexity index is greater than a complexity threshold, simulating the wind parameters of multiple points in the target wind farm based on the terrain information to obtain the simulated wind parameters of the wind farm.

[0015] Optionally, the complexity threshold is a statistical value of a complexity index of a reference wind farm, and the reference wind farm is a wind farm where a fault has occurred.

[0016] In another general aspect, a load simulation device for a wind turbine generator set is provided, the load simulation device comprising: an acquisition unit configured to acquire terrain information of a target wind farm where the target wind turbine generator set is located and measured wind parameters at predetermined observation points; a first simulation unit configured to simulate the wind parameters of the target wind farm based on the terrain information to obtain simulated wind parameters of the wind farm; a determination unit configured to determine predicted wind parameters of multiple points within an impeller surface of the target wind turbine generator set based on the simulated wind parameters of the wind farm and the measured wind parameters to obtain predicted wind parameters of the impeller surface; and a second simulation unit configured to simulate the load of the target wind turbine generator set based on the predicted wind parameters of the impeller surface to obtain a simulated load of the unit.

[0017] Optionally, the first simulation unit is further configured to: determine multiple preset sectors, each preset sector represents a wind direction; for each of the multiple preset sectors, based on the terrain information, simulate the wind parameters of the target wind farm to obtain the simulated wind parameters of the wind farm for each preset sector.

[0018] Optionally, the determination unit is further configured to: for each preset sector of the multiple preset sectors, take the direction of the incoming wind as the direction of the impeller surface of the target wind turbine in the preset sector; determine the predicted wind parameters of multiple points on the impeller surface of the target wind turbine in each preset sector according to the wind farm simulation wind parameters of each preset sector and the measured wind parameters, and obtain the predicted wind parameters of the impeller surface of each preset sector.

[0019] Optionally, the second simulation unit is further configured to: simulate the load of the target wind turbine generator set in each preset sector based on the predicted wind parameters of the blade surface of each preset sector to obtain the simulated load of each preset sector; and merge the simulated loads of the multiple preset sectors to obtain the simulated load of the unit.

[0020] Optionally, the determination unit is further configured to: perform statistical processing on the measured wind parameters according to the multiple preset sectors and the multiple preset wind speed segments to obtain statistical wind parameters under multiple preset intervals, each of the multiple preset intervals corresponds to a preset sector and a preset wind speed segment; for each of the multiple preset intervals, determine the predicted wind parameters of multiple points on the impeller surface of the target wind turbine generator set within the preset sector corresponding to the preset interval based on the wind farm simulation wind parameters of the preset sector corresponding to the preset interval and the statistical wind parameters under the preset interval to obtain the predicted wind parameters of the impeller surface of the preset interval.

[0021] Optionally, the second simulation unit is further configured to: for each preset interval in the multiple preset intervals, determine the interval simulation load of the target wind turbine generator set in the preset interval according to the predicted wind parameters of the impeller surface in the preset interval.

[0022] Optionally, the second simulation unit is further configured to: merge the interval simulation loads of multiple preset intervals corresponding to the same preset wind speed segment, and obtain the simulation load corresponding to each preset wind speed segment in the multiple preset wind speed segments as the unit simulation load.

[0023] Optionally, the determination unit is further configured to: for each preset sector of the multiple preset sectors, construct a wheel surface grid of the target wind turbine generator set in the preset sector according to the wheel surface orientation of the target wind turbine generator set in the preset sector; for each preset sector of the multiple preset sectors, use each grid point in the wheel surface grid of the target wind turbine generator set in the preset sector as a plurality of points within the wheel surface, and determine each grid point in the wheel surface grid and the simulated wind parameters at the predetermined observation point by using an interpolation method based on the wind farm simulation wind parameters of the preset sector; for each preset interval of the multiple preset intervals, determine the predicted wind parameters of each grid point in the wheel surface grid of the preset sector corresponding to the preset interval of the target wind turbine generator set according to each grid point in the wheel surface grid of the preset sector corresponding to the preset interval of the target wind turbine generator set and the simulated wind parameters at the predetermined observation point, as well as the statistical wind parameters under the preset interval, to obtain the predicted wind parameters of the wheel surface of the preset interval.

[0024] Optionally, each grid point of the impeller surface grid includes a hub center point and a non-hub center point, and the determination unit is further configured to: for each preset interval in the multiple preset intervals, for each grid point in the impeller surface grid of the preset sector corresponding to the preset interval of the target wind turbine generator set, correct the simulated wind parameters of the grid point according to the simulated wind parameters and reference wind parameters of the reference point corresponding to the grid point, so as to obtain the predicted wind parameters of the grid point; use the predicted wind parameters of each grid point in the impeller surface grid of the preset sector corresponding to the preset interval of the target wind turbine generator set as the predicted wind parameters of the impeller surface of the preset interval; wherein the reference point corresponding to the hub center point is the predetermined observation point, the reference point corresponding to the non-hub center point is the hub center point, the reference wind parameters of the predetermined observation point are the statistical wind parameters under the preset interval, and the reference wind parameters of the hub center point are the predicted wind parameters of the hub center point.

[0025] Optionally, the wind parameters include wind speed, turbulence intensity and wind direction, and the determination unit is further configured to: based on the respective correction relationships of different wind parameters, correct the simulated wind parameters of the grid point according to the simulated wind parameters and reference wind parameters of the reference point corresponding to the grid point to obtain the predicted wind parameters of the grid point, wherein the correction relationship of wind speed is that the ratio of the predicted wind speed of the grid point to the simulated wind speed is equal to the ratio of the reference wind speed of the reference point corresponding to the grid point to the simulated wind speed; the correction relationship of turbulence intensity is that the ratio of the predicted turbulence difference to the simulated turbulence difference is equal to the ratio of the simulated wind speed of the grid point to the simulated wind speed of the reference point corresponding to the grid point, wherein the predicted turbulence difference is the difference between the predicted turbulence intensity of the grid point and the reference turbulence intensity of the reference point corresponding to the grid point, and the simulated turbulence difference is the difference between the simulated turbulence intensity of the grid point and the simulated turbulence intensity of the reference point corresponding to the grid point; the correction relationship of wind direction is that the difference between the predicted wind direction of the grid point and the simulated wind direction is equal to the difference between the reference wind direction of the reference point corresponding to the grid point and the simulated wind direction.

[0026] Optionally, the first simulation unit is further configured to: determine a complexity index of the target wind farm based on the terrain information, wherein the complexity index is used to represent the terrain complexity of the target wind farm; when the complexity index is greater than a complexity threshold, simulate the wind parameters of multiple points within the target wind farm based on the terrain information to obtain the simulated wind parameters of the wind farm.

[0027] Optionally, the complexity threshold is a statistical value of a complexity index of a reference wind farm, and the reference wind farm is a wind farm where a fault has occurred.

[0028] In another general aspect, a computer-readable storage medium is provided. When instructions in the computer-readable storage medium are executed by at least one processor, the at least one processor is prompted to execute the load simulation method for a wind turbine generator set as described above.

[0029] In another general aspect, a computer device is provided, comprising: at least one processor; and at least one memory storing computer executable instructions, wherein the computer executable instructions, when executed by the at least one processor, cause the at least one processor to execute the load simulation method for a wind turbine generator set as described above.

[0030] The present disclosure provides a load simulation method, device and storage medium for a wind turbine generator set. By combining the simulated wind parameters of the wind farm obtained by simulation and the measured wind parameters, the simulated wind parameters are further refined to determine the predicted wind parameters of multiple points within the impeller surface of the target wind turbine generator set. The actual wind parameters borne by the unit on the entire impeller surface can be predicted, and then a more accurate simulated load of the unit can be calculated, which can fully reduce the simulation measurement deviation caused by the imbalance of the wind parameters on the impeller surface.

[0031] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 is a flow chart showing a load simulation method of a wind turbine generator set according to an embodiment of the present disclosure;

[0033] Figure 2 is a schematic flow chart showing a load simulation method for a wind turbine generator set according to a specific embodiment of the present disclosure;

[0034] Figure 3 is a schematic diagram showing an impeller surface mesh according to a specific embodiment of the present disclosure;

[0035] Figure 4 is a schematic diagram showing the distribution of simulated wind speed on the impeller surface according to a specific embodiment of the present disclosure;

[0036] Figure 5 is a schematic diagram showing the distribution of the simulated turbulence intensity of the impeller surface according to a specific embodiment of the present disclosure;

[0037] Figure 6 is a block diagram showing a load simulation device for a wind turbine generator set according to an embodiment of the present disclosure;

[0038] Figure 7 is a block diagram illustrating a computer device according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0039] The following specific embodiments are provided to help the reader obtain a comprehensive understanding of the methods, devices and / or systems described herein. However, after understanding the disclosure of the present application, various changes, modifications and equivalents of the methods, devices and / or systems described herein will be clear. For example, the order of operations described herein is only an example and is not limited to those orders set forth herein, but can be changed as will be clear after understanding the disclosure of the present application, except for operations that must occur in a specific order. In addition, for greater clarity and simplicity, the description of features known in the art may be omitted.

[0040] The features described herein can be implemented in different forms and should not be construed as being limited to the examples described herein. Rather, the examples described herein have been provided to illustrate only some of the many possible ways to implement the methods, devices, and / or systems described herein, which will be clear after understanding the disclosure of the present application.

[0041] As used herein, the term "and / or" includes any one of the associated listed items and any combination of any two or more.

[0042] Although terms such as "first", "second", and "third" may be used herein to describe various members, components, regions, layers, or portions, these members, components, regions, layers, or portions should not be limited by these terms. Instead, these terms are only used to distinguish one member, component, region, layer, or portion from another member, component, region, layer, or portion. Therefore, without departing from the teachings of the examples described herein, the first member, first component, first region, first layer, or first portion referred to in the examples may also be referred to as the second member, second component, second region, second layer, or second portion.

[0043] In the specification, when an element (such as a layer, a region, or a substrate) is described as being “on”, “connected to”, or “coupled to” another element, the element may be directly “on”, “connected to”, or “coupled to” another element, or one or more other elements may be present therebetween. Conversely, when an element is described as being “directly on”, “directly connected to”, or “directly coupled to” another element, there may be no other elements present therebetween.

[0044] The terms used herein are only used to describe various examples and are not intended to limit the disclosure. Unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. The terms "comprise", "include" and "have" indicate the presence of the described features, quantities, operations, components, elements and / or combinations thereof, but do not exclude the presence or addition of one or more other features, quantities, operations, components, elements and / or combinations thereof.

[0045] Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as those generally understood by a person of ordinary skill in the art to which the present disclosure belongs after understanding the present disclosure. Unless explicitly defined as such herein, terms (such as those defined in a general dictionary) should be interpreted as having a meaning consistent with their meaning in the context of the relevant art and the present disclosure, and should not be interpreted in an idealized or overly formal manner.

[0046] Furthermore, in the description of examples, when it is considered that a detailed description of a well-known related structure or function would cause vague interpretation of the present disclosure, such a detailed description will be omitted.

[0047] Figure 1 is a flow chart showing a load simulation method for a wind turbine generator set according to an embodiment of the present disclosure.

[0048] Reference Figure 1 In step S101, the terrain information of the target wind farm where the target wind turbine generator set is located and the measured wind parameters of the predetermined observation points are obtained.

[0049] It should be understood that the target wind turbine generator set is the wind turbine generator set to be subjected to load simulation, and the target wind farm is the wind farm to which the target wind turbine generator set has or will belong. If the present disclosure is applied to the wind turbine design stage, the target wind turbine generator set and the target wind farm are both under design, and the target wind farm at this time is a virtual wind farm. If the wind farm has been clearly sited, the target wind farm is the site where the wind farm is to be built with the selected address. If the wind farm has only selected an approximate location, or has only determined the applicable area of ​​the unit, and has not completely clarified the site selection, the target wind farm can be a representative regional terrain, or a wind farm that has been built in the area, as a site reference for the target wind farm; if the present disclosure is applied to the wind farm operation stage, the target wind turbine generator set and the target wind farm have been built and put into use, and the target wind farm is a wind farm with a target wind turbine generator set.

[0050] The terrain information may specifically include the terrain data and roughness of the target wind farm. The terrain data is used to describe the terrain of the target wind farm, such as whether it is a plain, mountainous or hilly. As an example, it can be achieved by describing the ground height at various locations in the target wind farm. The roughness is also called ground roughness, which characterizes the interaction between the surface and the atmosphere and reflects the effect of the surface on reducing wind speed. It can be input into the simulation model as a parameter in the subsequent simulation process.

[0051] The measured wind parameters are the wind parameters actually detected, which can be wind tower data or radar data.

[0052] In step S102, based on the terrain information, the wind parameters of the target wind farm are simulated to obtain simulated wind parameters of the wind farm.

[0053] As an example, this step can be implemented using the CFD (Computational Fluid Dynamics) method, including the determination of the simulation area, the setting of boundary conditions, the generation of grids, and the selection of turbulence models. In determining the simulation area, the length and width of the simulation area can be determined according to the area occupied by the target wind farm, and the height of the simulation area can be determined according to the height of the mountain in the target wind farm. For example, the point with a set height above the highest point of the mountain is used as the highest point of the simulation area, and the distance from the lowest point to the highest point of the target wind farm is the height of the simulation area. The boundary condition setting mainly involves the inlet boundary and the ground boundary. The inlet condition can be a three-layer wind profile inlet boundary condition that considers the thermal stability of the atmosphere. The setting of other boundary conditions refers to traditional CFD simulation. In terms of grid generation, the number of grids can be appropriately increased to meet the requirements of refined simulation. The specific increase can be appropriately adjusted according to the simulation results in combination with experience, and the present disclosure is not limited. In the selection of turbulence models, the atmospheric thermal stability information can be combined to select a model that takes the atmospheric thermal stability into consideration, such as the RANS (Reynolds averaged Navier–Stokes) model. Appropriate models can be selected according to different terrains. For example, for mountainous areas, two-equation models can be selected, such as the k-ε model and the SST (Shear Stress Transfer) k-ω model. For plains and hills, DES (Detached-Eddy Simulation) and LES (Large Eddy Simulation) models can be selected.

[0054] In step S103, predicted wind parameters of multiple points within the impeller surface of the target wind turbine generator set are determined according to the simulated wind parameters and the measured wind parameters of the wind farm, and the predicted wind parameters of the impeller surface are obtained.

[0055] In fact, in traditional wind turbine design, engineers construct the wind conditions experienced by the wind turbine through the IEC standard wind model based on the wind parameter input at the hub center, and then use the BEM theory (Blade-element Theory) method to calculate the load of the wind turbine. However, with the advancement of the large-scale trend of the unit, the imbalance of wind parameters on the entire impeller surface has gradually become prominent, especially in complex mountainous terrain. People have analyzed through radar measurement methods and CFD simulation methods that the complexity of the wind conditions actually suffered by the impeller surface far exceeds the complexity of the wind conditions constructed by traditional methods, which leads to great disadvantages in using only the hub center wind parameter as the input of load simulation. The present disclosure further refines the predicted wind parameters of multiple points within the impeller surface of the target wind turbine generator set by combining the simulated wind parameters of the wind farm and the measured wind parameters, and can predict the actual wind parameters borne by the unit on the entire impeller surface, so as to calculate a more accurate unit simulation load in the subsequent step S104, which can fully reduce the simulation deviation caused by the imbalance of the wind parameters on the impeller surface. It should be understood that, since the inlet boundary condition adopted when the simulation processing is performed in step S102 to determine the simulated wind parameters of the wind farm is a single wind condition, including a single inlet wind speed and wind direction, the simulated wind parameters on the impeller surface calculated from the simulated wind parameters of the wind farm also correspond to the single wind condition of the inlet boundary. In step S103, by introducing the measured wind parameters, the simulated wind parameters on the impeller surface under the single wind condition can be adjusted, thereby inferring the predicted wind parameters on the impeller surface that are consistent with the measured wind parameters as the predicted wind parameters of the impeller surface.

[0056] In step S104, based on the predicted wind parameters of the impeller surface, the load of the target wind turbine generator set is simulated to obtain a simulated load of the set.

[0057] It should be understood that regarding the application of unit simulation loads, if the present disclosure is applied to the wind turbine design stage, the structural dimensions of the target wind turbine generator set can be designed based on the obtained unit simulation loads to ensure the safety performance simulation in the wind turbine design stage, thereby reducing quality failure problems in the wind turbine operation stage; if the present disclosure is applied to the wind farm operation stage, the life of the target wind turbine generator set or certain components in the set can be predicted based on the unit simulation load, and maintenance or replacement plans can be made in a timely manner, thereby reducing the risk of safety accidents.

[0058] The following is a further introduction to the above steps.

[0059] In some embodiments, considering that the phenomenon of unbalanced wind parameters on the impeller surface is more likely to occur under complex terrain, the present disclosure adopts different schemes to determine the predicted wind parameters on the impeller surface for different terrains, so as to realize scene-by-scene simulation.

[0060] Specifically, optionally, step S102 includes: determining the complexity index of the target wind farm based on the terrain information, wherein the complexity index is used to represent the complexity of the terrain of the target wind farm; when the complexity index is greater than the complexity threshold, simulating the wind parameters of multiple points in the target wind farm based on the terrain information to obtain the simulated wind parameters of the wind farm. By configuring the complexity index and the complexity threshold, the complexity of the terrain of the target wind farm can be quantitatively represented, and when the complexity index is greater than the complexity threshold, the terrain of the target wind farm is considered to be complex. At this time, the aforementioned solution of first calculating the simulated wind parameters of the wind farm and then refining them to obtain the predicted wind parameters of the impeller surface can meet the simulation needs of complex terrain and fully reduce the simulation deviation caused by the imbalance of the wind parameters on the impeller surface under complex terrain.

[0061] It should be understood that when the complexity index is less than or equal to the complexity threshold, the terrain of the target wind farm can be considered to be relatively simple and flat. At this time, the traditional method is used to construct the wind conditions experienced by the wind turbine based on the wind parameters at the hub center. This can provide a more suitable load assessment scheme for the target wind turbine generator set, which helps to reduce the computational load and improve computational efficiency.

[0062] Optionally, the complexity threshold is a statistical value of the complexity index of a reference wind farm, and the reference wind farm is a wind farm that has experienced a failure. The wind conditions are complex under complex terrain, and the simulation deviation is correspondingly large, making it more likely for failures to occur. By counting the complexity index of the reference wind farm that has experienced a failure, the obtained complexity threshold can more reliably distinguish between complex terrain and simple terrain, which helps to improve the recognition sensitivity of complex terrain. As an example, when determining the complexity threshold, the complexity index of all reference wind farms obtained can be directly counted, and the statistical values ​​are, for example, the mean, median, mode, and quantile of a predetermined probability (for example, the 70% lower quantile); the obtained reference wind farms can also be screened for the second time according to the number and / or severity of the failures, and then the complexity index of the reference wind farms remaining after the second screening can be counted. The statistical values ​​used are the same as those used for direct statistics, and the present disclosure does not limit this.

[0063] In some embodiments, optionally, step S102 includes: determining a plurality of preset sectors, each of which represents a wind direction; for each of the plurality of preset sectors, simulating the wind parameters of the target wind farm based on the terrain information to obtain the wind farm simulation wind parameters of each preset sector. Since the wind direction in the target wind farm varies greatly under complex terrain, the wind parameters on the entire impeller surface of the target wind turbine generator set under different wind directions also vary greatly. By dividing the wind direction of the target wind farm into a plurality of preset sectors, such as 16 sectors, and simulating them separately, the influence of wind from different wind directions can be simulated, thereby achieving refined simulation of multiple sectors and improving simulation accuracy.

[0064] Optionally, in the above-mentioned embodiment of multi-sector refined simulation, step S103 includes: for each preset sector in a plurality of preset sectors, taking the direction facing the incoming wind as the impeller surface orientation of the target wind turbine in the preset sector; determining the predicted wind parameters of multiple points of the impeller surface of the target wind turbine in each preset sector according to the wind farm simulation wind parameters and the measured wind parameters of each preset sector, and obtaining the predicted wind parameters of the impeller surface of each preset sector. Considering that during the actual operation of the wind farm, the yaw direction of the wind turbine will be adjusted according to the incoming wind direction so that the impeller surface faces the incoming wind, by determining the corresponding impeller surface orientation for each preset sector, a more accurate impeller surface position can be determined, which helps to obtain more accurate predicted wind parameters of the impeller surface.

[0065] Optionally, in the above-mentioned embodiment of multi-sector refined simulation, step S104 includes: based on the predicted wind parameters of the impeller surface of each preset sector, simulating the load of the target wind turbine generator set in each preset sector to obtain the simulated load of each preset sector; merging the simulated loads of multiple preset sectors to obtain the simulated load of the unit. On the basis of obtaining the predicted wind parameters of the impeller surface of each preset sector, by continuing to simulate the load corresponding to each preset sector, a more accurate simulated load can be obtained based on the more accurate predicted wind parameters of the impeller surface, and after merging, the simulated load of the unit of the entire target wind turbine generator set can be obtained, which helps to fully reduce the simulation deviation. As an example, the statistical value of the simulated load of multiple preset sectors can be calculated as the simulated load of the unit, and the statistical value is, for example, an average value. For example, the frequency of wind directions corresponding to different preset sectors in the historical wind parameters of the target wind farm can be counted, and the frequency is used as the weight of the corresponding preset sector to calculate the weighted average value of the simulated loads of multiple preset sectors. The present disclosure does not limit this.

[0066] Further optionally, based on the multi-sector refined simulation, the wind speed may be divided into a plurality of preset wind speed segments to achieve multi-wind speed segment simulation.

[0067] Specifically, optionally, the step of determining the predicted wind parameters of multiple points on the impeller surface of each preset sector of the target wind turbine generator set according to the wind farm simulation wind parameters and the measured wind parameters of each preset sector in step S103 to obtain the predicted wind parameters of the impeller surface of each preset sector includes: performing statistical processing on the measured wind parameters according to multiple preset sectors and multiple preset wind speed segments to obtain statistical wind parameters under multiple preset intervals, wherein each of the multiple preset intervals corresponds to a preset sector and a preset wind speed segment, and taking the case where there are 16 preset sectors and 34 preset wind speed segments as an example, 16×34=544 preset intervals can be obtained; for each of the multiple preset intervals, determining the predicted wind parameters of multiple points on the impeller surface of the target wind turbine generator set in the preset sector corresponding to the preset interval according to the wind farm simulation wind parameters of the preset sector corresponding to the preset interval and the statistical wind parameters under the preset interval to obtain the predicted wind parameters of the impeller surface of the preset interval. Since different preset wind speed sections will not affect the wind farm simulation parameters under the same preset sector, a set of wind farm simulation wind parameters can be shared. By combining the statistical wind parameters under the preset interval, that is, the statistical wind parameters of different preset wind speed sections in the corresponding preset sector, the predicted wind parameters of the impeller surface corresponding to the preset interval are determined, which can realize the reliable calculation of the predicted wind parameters of the impeller surface for different preset intervals. It should be understood that the predicted wind parameters of the impeller surface of each preset interval are the predicted wind parameters of the impeller surface of each preset sector under each preset wind speed section. It should be understood that the statistical wind parameters are the statistical values ​​of the measured values ​​of each wind parameter within the preset interval.

[0068] Optionally, the step of simulating the load of the target wind turbine generator set in each preset sector based on the predicted wind parameters of the impeller surface of each preset sector in step S104 to obtain the simulated load of each preset sector includes: for each preset interval in a plurality of preset intervals, determining the interval simulated load of the target wind turbine generator set in the preset interval according to the predicted wind parameters of the impeller surface of the preset interval. By continuing to simulate the corresponding load on the basis of obtaining relatively accurate predicted wind parameters of the impeller surface in each preset interval (i.e., each preset sector in each preset wind speed segment), relatively accurate interval simulated loads can be obtained based on relatively accurate predicted wind parameters of the impeller surface in different preset intervals, which helps to fully reduce the simulation deviation.

[0069] Optionally, the step of merging the simulated loads of multiple preset sectors in step S104 to obtain the simulated load of the unit includes: merging the interval simulated loads of multiple preset intervals corresponding to the same preset wind speed segment, and obtaining the simulated load corresponding to each preset wind speed segment in the multiple preset wind speed segments as the simulated load of the unit. Since the load of the unit is often significantly different under different wind speeds, and different wind directions have little effect on the load of the unit, by merging the interval simulated loads of multiple preset intervals corresponding to the same preset wind speed segment, the simulated loads corresponding to different preset wind speed segments can be obtained, and the refined distinction of the simulated load of the unit can be achieved, which helps to improve the accuracy of the simulated load of the unit, thereby reducing the simulation deviation. As an example, refer to the previous text. When merging the interval simulated loads of multiple preset intervals corresponding to the same preset wind speed segment, the statistical values ​​of the interval simulated loads of multiple preset intervals corresponding to the same preset wind speed segment can be calculated, which will not be repeated here.

[0070] Optionally, regarding the specific determination scheme of the predicted wind parameters of the impeller surface, the step of determining the predicted wind parameters of the impeller surface for each preset interval in step S103 includes: for each preset sector in a plurality of preset sectors, constructing a impeller surface grid of the target wind turbine generator set in the preset sector according to the impeller surface orientation of the target wind turbine generator set in the preset sector; for each preset sector in a plurality of preset sectors, taking each grid point in the impeller surface grid of the target wind turbine generator set in the preset sector as a plurality of points within the impeller surface, and determining each grid point in the impeller surface grid and the simulated wind parameters at the predetermined observation points by using the interpolation method based on the wind farm simulation wind parameters of the preset sector; for each preset interval in a plurality of preset intervals, determining the predicted wind parameters of each grid point in the impeller surface grid of the preset sector corresponding to the preset interval of the target wind turbine generator set according to the simulated wind parameters at the predetermined observation points and the statistical wind parameters under the preset interval, so as to obtain the predicted wind parameters of the impeller surface for the preset interval. As mentioned above, each preset sector can determine the corresponding impeller surface orientation, and under the same preset sector, different preset wind speed sections can share a set of wind farm simulation wind parameters. Based on this, by first constructing an impeller surface grid for each preset sector, and combining the wind farm simulation wind parameters to determine the simulation wind parameters at each grid point in the impeller surface grid and the predetermined observation point, and finally combining the corresponding statistical wind parameters to determine the predicted wind parameters at each grid point, the predicted wind parameters of the impeller surface can be reliably determined.

[0071] Optionally, each grid point of the impeller surface grid includes a hub center point and a non-hub center point. For each preset interval in the plurality of preset intervals described above, according to each grid point in the impeller surface grid of the preset sector corresponding to the preset interval of the target wind turbine generator set and the simulated wind parameters at the predetermined observation point, as well as the statistical wind parameters under the preset interval, the predicted wind parameters of each grid point in the impeller surface grid of the preset sector corresponding to the preset interval of the target wind turbine generator set are determined. The step of obtaining the predicted wind parameters of the impeller surface in the preset interval includes: for each preset interval in the plurality of preset intervals, the predicted wind parameters of the target wind turbine generator set in the preset area are obtained. For each grid point in the impeller surface grid of the preset sector corresponding to the preset interval, according to the simulated wind parameters and reference wind parameters of the reference point corresponding to the grid point, the simulated wind parameters of the grid point are corrected to obtain the predicted wind parameters of the grid point; the predicted wind parameters of each grid point in the impeller surface grid of the preset sector corresponding to the preset interval of the target wind turbine generator set are used as the predicted wind parameters of the impeller surface in the preset interval; wherein, the reference point corresponding to the hub center point is the predetermined observation point, the reference point corresponding to the non-hub center point is the hub center point, the reference wind parameters of the predetermined observation point are the statistical wind parameters under the preset interval, and the reference wind parameters of the hub center point are the predicted wind parameters of the hub center point. Referring to the previous description, it can be seen that the simulated wind parameters of the wind farm correspond to a single wind condition, so the simulated wind parameters on the impeller surface obtained thereby also correspond to the single wind condition. It is necessary to adjust the simulated wind parameters in combination with the measured wind parameters to obtain accurate predicted wind parameters of the impeller surface. By first referring to the statistical wind parameters of the predetermined observation points to determine the predicted wind parameters of the hub center point when adjusting the simulated wind parameters in combination with the measured wind parameters, and then referring to the predicted wind parameters of the hub center point to determine the predicted wind parameters of other grid points, the hub center point that has a closer relationship with other grid points can be used as the reference point for other grid points, rather than uniformly using the predetermined observation points as the reference points, which helps to improve the accuracy of the predicted wind parameters of other grid points.

[0072] Optionally, the wind parameters include wind speed, turbulence intensity and wind direction, and the simulated wind parameters of the grid point are corrected according to the simulated wind parameters and reference wind parameters of the reference point corresponding to the grid point in the previous paragraph to obtain the predicted wind parameters of the grid point, including: based on the respective correction relationships of different wind parameters, the simulated wind parameters of the grid point are corrected according to the simulated wind parameters and reference wind parameters of the reference point corresponding to the grid point to obtain the predicted wind parameters of the grid point, wherein the correction relationship of wind speed is that the ratio of the predicted wind speed of the grid point to the simulated wind speed is equal to the ratio of the reference wind speed of the reference point corresponding to the grid point to the simulated wind speed; turbulence intensity and wind direction, and the simulated wind parameters of the grid point are corrected according to the simulated wind parameters and reference wind parameters of the reference point corresponding to the grid point to obtain the predicted wind parameters of the grid point; The correction relationship of flow intensity is that the ratio of the predicted turbulence difference to the simulated turbulence difference is equal to the ratio of the simulated wind speed of the grid point to the simulated wind speed of the reference point corresponding to the grid point, where the predicted turbulence difference is the difference between the predicted turbulence intensity of the grid point and the reference turbulence intensity of the reference point corresponding to the grid point, and the simulated turbulence difference is the difference between the simulated turbulence intensity of the grid point and the simulated turbulence intensity of the reference point corresponding to the grid point; the correction relationship of wind direction is that the difference between the predicted wind direction and the simulated wind direction of the grid point is equal to the difference between the reference wind direction and the simulated wind direction of the reference point corresponding to the grid point. By configuring different correction relationships according to the physical characteristics of wind speed, turbulence intensity and wind direction, and correcting the simulated wind parameters of each grid point based on the corresponding correction relationships, it is possible to ensure that accurate predicted wind parameters of the impeller surface are obtained.

[0073] Next, combine Figures 2 to 5 A specific embodiment of the present disclosure is introduced.

[0074] This specific embodiment proposes a load simulation method based on CFD impeller surface wind parameters. This method is based on the CFD simulation wind parameter input method, and takes the influence of complex terrain on wind parameter imbalance into account in the load simulation, which can reduce the simulation deviation of the load. The method mainly includes three parts: terrain complexity identification, CFD simulation and impeller surface wind parameter extraction, and load simulation. First, the complexity of the terrain suitable for the designed target wind turbine generator set or the terrain where the target wind turbine generator set in operation is located is identified. For simple terrain with low complexity, the traditional single-point measured wind parameters are used as the input of the load simulation to evaluate the safety performance of the unit. For terrain with high complexity, the corrected distribution of the entire impeller surface wind parameters is obtained through CFD simulation and impeller surface wind parameter extraction, and then used as the input of the load simulation to evaluate the fatigue load and limit load of the unit.

[0075] Reference Figure 2 , the specific embodiment comprises the following steps:

[0076] a) During the unit design and development stage, based on the applicable area of ​​the unit, select a representative regional terrain, or select a built wind farm in the area as the target wind farm, and select a specific unit point as the unit site of the target wind turbine generator unit, and read the terrain information of the target wind farm.

[0077] b) Identify the terrain complexity of the target wind farm. Specifically, the complexity index can be constructed based on the number of mountains, slope, maximum altitude difference, etc. in the target wind farm. For example, the proportion of mountains with a maximum altitude difference exceeding a threshold and the proportion of mountains with a slope exceeding a threshold in the target wind farm can be calculated, and the complexity index can be obtained based on these two proportions by looking up a table.

[0078] c) judging whether the complexity index exceeds a complexity threshold, wherein the complexity threshold is set by statistically processing the complexity indexes of operating wind farms that have experienced fault problems in the terrain database.

[0079] d) If the complexity index of the target wind farm exceeds the complexity threshold, it is judged as complex terrain, and the load simulation process based on the CFD impeller surface wind parameter is started to read the roughness information of the target wind farm, the location information of the target wind turbine generator set, and the designed model information. The model information mainly includes the tower height and the hub diameter.

[0080] e) Determine the wind parameters for wind farm simulation. Set the target wind farm calculation area, generate the grid, and set the boundary conditions. Use the RANS model to perform CFD simulation on 16 preset sectors until the simulation converges. The inlet boundary condition of the target wind farm is the three-layer wind profile inlet boundary condition considering the atmospheric stability. Other boundary conditions are set with reference to the traditional CFD simulation of the wind farm. The RANS models used are the k-ε model and the SST k-ω model considering the atmospheric stability, in order to consider the impact of meteorological laws on the wind farm and ensure the accuracy and reliability of the simulation.

[0081] f) In each preset sector, at the site of the target wind turbine generator set, an N×N impeller surface grid is constructed based on the tower height, hub diameter, and impeller surface orientation of the target wind turbine generator set, such as Figure 3 As shown. Through interpolation methods, such as the inverse distance square interpolation method, the wind farm simulation wind parameters are interpolated to the impeller surface grid, including the average wind speed, turbulence intensity, inflow angle, and wind direction of each grid node. Finally, the simulation wind parameters of the impeller surface grid points and predetermined observation points of the target wind turbine generator set in 16 preset sectors are obtained. Figure 4 and Figure 5 The figure shows the distribution of simulated wind speed and simulated turbulence intensity on the impeller surface. It can be seen that there is an unbalanced distribution.

[0082] g) Read radar data or wind tower data as the measured wind parameters of the predetermined observation point, including wind speed, turbulence intensity, and wind direction. The predetermined observation point is the target point detected by the radar data or the location of the wind tower. Specifically, when the radar data or wind tower data contains wind parameter data of multiple different heights, the wind parameter data of the hub center height can be selected, and the wind parameter data of other height layers can also be selected. The measured wind parameters are processed according to sectors (16 preset sectors) and wind speed sections (cut-in wind speed 3m / s, cut-out wind speed 20m / s, wind speed interval of 0.5m / s, and 34 preset wind speed sections are obtained) to obtain the wind speed average value, turbulence intensity average value, wind direction average value and frequency under different preset sectors and different preset wind speed sections. Since the inflow angle cannot be directly measured, the simulation result of the inflow angle is used later. There are 16 (preset number of sectors) × 34 (preset number of wind speed sections) = 544 preset intervals here.

[0083] h) For each preset interval, the wind speed, turbulence intensity and wind direction at the hub center height of the target wind turbine generator set are corrected by the measured wind parameters at the predetermined observation point. The correction formulas for wind speed and turbulence intensity are as follows:

[0084]

[0085]

[0086] Where v h_p_real 、v h_mast_real are the predicted wind speed at the hub center of the target wind turbine and the measured wind speed at the predetermined observation point; h_p_CFD 、v h_mast_CFD They are the simulated wind speed at the hub center and the predetermined observation point. p_real ,ti mast_real are the predicted turbulence intensity at the hub center and the measured turbulence intensity at the predetermined observation point. p_CFD ,ti mast_CFD They are the simulated turbulence intensity at the hub center and the predetermined observation point. Then, for each preset interval, based on the predicted wind parameters at the hub center, the predicted wind parameters at other grid points on the entire impeller surface are obtained by referring to the above formula. Finally, the predicted wind parameters and frequency distribution of each grid point on the impeller surface in each preset interval are obtained.

[0087] i) Decompose the simulated wind speed, simulated turbulence intensity, and simulated wind direction of each preset sector and each preset wind speed segment, that is, each preset interval, into the three directions of the coordinate system x, y, and z to obtain the components of each predicted wind parameter in the three directions. For a preset interval, the predicted wind parameters of all grid points on the entire impeller surface are obtained as average values, which can be input into the wind model in the IEC standard to generate the time series wind parameters at different times on the entire impeller surface. The 600s time series wind parameters are generally used for load simulation. This method can be used to generate the 600s time series wind parameters of the impeller surface corresponding to each preset interval.

[0088] j) Input the 600s time-series wind parameters of the impeller surface corresponding to each preset interval into the load simulation model. In c), if the complexity index does not exceed the complexity threshold, the influence of the unbalanced wind parameters of the impeller surface caused by the terrain is ignored, and the unit load is calculated by inputting the measured wind parameters at the hub center height. The input wind parameters mainly include the average wind speed at the hub center, turbulence intensity, wind shear, etc. Thereby generating the 600s time-series wind parameters of the entire impeller surface. The present disclosure targets complex terrains, and based on the CFD impeller surface simulation wind parameters and the measured wind parameters at predetermined observation points, the input is the time-series wind parameters of the entire impeller surface generated by the predicted wind parameter constraints of the impeller surface at each grid point, while the traditional method inputs the time-series wind parameters of the entire impeller surface generated by the single-point wind parameters at the hub center combined with the wind shear constraints.

[0089] k) Use the constructed time series wind parameters to simulate loads under various working conditions, and finally solve the fatigue load and limit load of the target wind turbine. For example, for the fatigue load of the unit, the NTM model (Normal Turbulence Model) in the IEC standard is used to obtain the load simulation results of each preset interval, and then according to the frequency distribution of each preset interval, the fatigue load of the entire unit under different preset wind speed sections is finally obtained. The limit load is the maximum value of the load simulation result.

[0090] In addition, regarding the execution subject, in this specific embodiment, the load simulation method is executed by a simulation system independent of the wind farm control system. The simulation system first needs to obtain the terrain information of the target wind farm and the measured wind parameters of the predetermined observation point. Among them, the terrain information can be derived from the actual measurement data of the target wind farm, and the actual measurement data is often stored in a special memory, that is, the actual measurement data of the target wind farm can be obtained from the memory; if there is no actual measurement data, STRM (Shuttle Radar Topography Mission, Shuttle Radar Topography Mission) data can be used. The data is public data and can be obtained from relevant websites, such as EarthExplorer. The measured wind parameters can be radar data or wind tower data, which can be obtained from the corresponding data storage. After completing the data acquisition, the simulation system can perform a series of simulation processing and finally obtain the unit simulation load. Thereafter, the equipment used to perform the design calculation of the wind turbine generator set in the development stage, or the equipment used to perform the remaining life calculation of the wind turbine generator set in the operation stage, such as a workstation, can obtain the unit simulation load from the simulation system to perform the corresponding calculation.

[0091] Figure 6 Detailed description is a block diagram showing a load simulation device for a wind turbine generator set according to an embodiment of the present disclosure.

[0092] Reference Figure 6 The load simulation device 600 of a wind turbine generator set includes an acquisition unit 601 , a first simulation unit 602 , a determination unit 603 , and a second simulation unit 604 .

[0093] The acquisition unit 601 may acquire the topographic information of the target wind farm where the target wind turbine generator set is located and the measured wind parameters of the predetermined observation point.

[0094] The first simulation unit 602 may simulate the wind parameters of the target wind farm based on the terrain information to obtain the simulated wind parameters of the wind farm.

[0095] The determination unit 603 may determine the predicted wind parameters of multiple points within the impeller surface of the target wind turbine generator set according to the simulated wind parameters and the measured wind parameters of the wind farm, and obtain the predicted wind parameters of the impeller surface.

[0096] The second simulation unit 604 can simulate the load of the target wind turbine generator set based on the predicted wind parameter of the impeller surface to obtain the simulated load of the set.

[0097] Optionally, the first simulation unit 602 can also: determine multiple preset sectors, each preset sector represents a wind direction; for each of the multiple preset sectors, based on terrain information, simulate the wind parameters of the target wind farm to obtain the wind farm simulation wind parameters of each preset sector.

[0098] Optionally, the determination unit 603 can also: for each preset sector in a plurality of preset sectors, take the direction facing the incoming wind as the direction of the impeller surface of the target wind turbine generator set in the preset sector; determine the predicted wind parameters of multiple points on the impeller surface of the target wind turbine generator set in each preset sector according to the simulated wind parameters and measured wind parameters of the wind farm in each preset sector, and obtain the predicted wind parameters of the impeller surface of each preset sector.

[0099] Optionally, the second simulation unit 604 can also: simulate the load of the target wind turbine generator set in each preset sector based on the predicted wind parameters of the blade surface of each preset sector to obtain the simulated load of each preset sector; merge the simulated loads of multiple preset sectors to obtain the simulated load of the unit.

[0100] Optionally, the determination unit 603 may also: perform statistical processing on the measured wind parameters according to a plurality of preset sectors and a plurality of preset wind speed segments to obtain statistical wind parameters under a plurality of preset intervals, each of the plurality of preset intervals corresponding to a preset sector and a preset wind speed segment; for each of the plurality of preset intervals, determine the predicted wind parameters of a plurality of points on the impeller surface of the target wind turbine generator set in the preset sector corresponding to the preset interval according to the wind farm simulation wind parameters of the preset sector corresponding to the preset interval and the statistical wind parameters under the preset interval to obtain the predicted wind parameters of the impeller surface of the preset interval.

[0101] Optionally, the second simulation unit 604 may also: for each preset interval in a plurality of preset intervals, determine an interval simulation load of the target wind turbine generator set in the preset interval according to the predicted wind parameters of the impeller surface in the preset interval.

[0102] Optionally, the second simulation unit 604 may also: merge the interval simulation loads of multiple preset intervals corresponding to the same preset wind speed segment to obtain the simulation load corresponding to each preset wind speed segment in the multiple preset wind speed segments as the unit simulation load.

[0103] Optionally, the determination unit 603 may also: for each preset sector in a plurality of preset sectors, construct a wheel surface grid of the target wind turbine generator set in the preset sector according to the wheel surface orientation of the target wind turbine generator set in the preset sector; for each preset sector in a plurality of preset sectors, use each grid point in the wheel surface grid of the target wind turbine generator set in the preset sector as a plurality of points within the wheel surface, and determine each grid point in the wheel surface grid and the simulated wind parameters at the predetermined observation points by using the interpolation method based on the simulated wind parameters of the wind farm in the preset sector; for each preset interval in a plurality of preset intervals, determine the predicted wind parameters of each grid point in the wheel surface grid of the preset sector corresponding to the preset interval of the target wind turbine generator set according to each grid point in the wheel surface grid of the preset sector corresponding to the preset interval and the simulated wind parameters at the predetermined observation points, as well as the statistical wind parameters under the preset interval, to obtain the predicted wind parameters of the wheel surface of the preset interval.

[0104] Optionally, each grid point of the impeller surface grid includes a hub center point and a non-hub center point, and the determination unit 603 may also: for each preset interval in a plurality of preset intervals, for each grid point in the impeller surface grid of a preset sector corresponding to the preset interval of the target wind turbine generator set, according to the simulation wind parameters and reference wind parameters of the reference point corresponding to the grid point, correct the simulation wind parameters of the grid point to obtain the predicted wind parameters of the grid point; use the predicted wind parameters of each grid point in the impeller surface grid of the preset sector corresponding to the preset interval of the target wind turbine generator set as the predicted wind parameters of the impeller surface of the preset interval; wherein the reference point corresponding to the hub center point is the predetermined observation point, the reference point corresponding to the non-hub center point is the hub center point, the reference wind parameters of the predetermined observation point are the statistical wind parameters under the preset interval, and the reference wind parameters of the hub center point are the predicted wind parameters of the hub center point.

[0105] Optionally, the wind parameters include wind speed, turbulence intensity and wind direction, and the determination unit 603 can also: based on the respective correction relationships of different wind parameters, correct the simulated wind parameters of the grid point according to the simulated wind parameters and reference wind parameters of the reference point corresponding to the grid point, to obtain the predicted wind parameters of the grid point, wherein the correction relationship of the wind speed is that the ratio of the predicted wind speed of the grid point to the simulated wind speed is equal to the ratio of the reference wind speed of the reference point corresponding to the grid point to the simulated wind speed; the correction relationship of the turbulence intensity is that the ratio of the predicted turbulence difference to the simulated turbulence difference is equal to the ratio of the simulated wind speed of the grid point to the simulated wind speed of the reference point corresponding to the grid point, wherein the predicted turbulence difference is the difference between the predicted turbulence intensity of the grid point and the reference turbulence intensity of the reference point corresponding to the grid point, and the simulated turbulence difference is the difference between the simulated turbulence intensity of the grid point and the simulated turbulence intensity of the reference point corresponding to the grid point; the correction relationship of the wind direction is that the difference between the predicted wind direction of the grid point and the simulated wind direction is equal to the difference between the reference wind direction of the reference point corresponding to the grid point and the simulated wind direction.

[0106] Optionally, the first simulation unit 602 may also: determine a complexity index of the target wind farm based on terrain information, wherein the complexity index is used to represent the terrain complexity of the target wind farm; when the complexity index is greater than a complexity threshold, simulate the wind parameters of multiple points in the target wind farm based on the terrain information to obtain simulated wind parameters of the wind farm.

[0107] Optionally, the complexity threshold is a statistical value of a complexity index of a reference wind farm, and the reference wind farm is a wind farm where a fault has occurred.

[0108] Regarding the device in the above embodiment, the specific manner in which each unit performs the operation has been described in detail in the embodiment of the method, and will not be elaborated here.

[0109] The load simulation method of a wind turbine generator set according to an embodiment of the present disclosure may be written as a computer program and stored on a computer-readable storage medium. When the instructions corresponding to the computer program are executed by a processor, the load simulation method of the wind turbine generator set as described above may be implemented. Examples of computer-readable storage media include: read-only memory (ROM), random access programmable read-only memory (PROM), electrically erasable programmable read-only memory (EEPROM), random access memory (RAM), dynamic random access memory (DRAM), static random access memory (SRAM), flash memory, non-volatile memory, CD-ROM, CD-R, CD+R, CD-RW, CD+RW, DVD-ROM, DVD-R, DVD+R, DVD-RW, DVD+RW, DVD-RAM, BD-ROM, BD-R, BD-R LTH, BD-RE, Blu-ray or optical disk storage, hard disk drive (HDD), solid state drive (SSD), card storage (such as, multimedia card, secure digital (SD) card or extreme digital (XD) card), magnetic tape, floppy disk, magneto-optical data storage device, optical data storage device, hard disk, solid state disk and any other device, any other device is configured to store computer program and any associated data, data files and data structures in a non-transitory manner and provide the computer program and any associated data, data files and data structures to a processor or computer so that the processor or computer can execute the computer program. In one example, the computer program and any associated data, data files and data structures are distributed on a networked computer system so that the computer program and any associated data, data files and data structures are stored, accessed and executed in a distributed manner by one or more processors or computers.

[0110] Figure 7 is a block diagram illustrating a computer device according to an embodiment of the present disclosure.

[0111] Reference Figure 7 The computer device 700 includes at least one memory 701 and at least one processor 702, wherein the at least one memory 701 stores a set of computer executable instructions. When the set of computer executable instructions is executed by the at least one processor 702, a load simulation method for a wind turbine generator set according to an exemplary embodiment of the present disclosure is executed.

[0112] As an example, the computer device 700 may be a PC, a tablet device, a personal digital assistant, a smart phone, or other device capable of executing the above-mentioned instruction set. Here, the computer device 700 is not necessarily a single electronic device, but may also be any device or circuit collection capable of executing the above-mentioned instructions (or instruction sets) individually or in combination. The computer device 700 may also be part of an integrated control system or a system manager, or may be configured as a portable electronic device interconnected with a local or remote (e.g., via wireless transmission) interface.

[0113] In computer device 700, processor 702 may include a central processing unit (CPU), a graphics processing unit (GPU), a programmable logic device, a dedicated processor system, a microcontroller, or a microprocessor. By way of example and not limitation, the processor may also include an analog processor, a digital processor, a microprocessor, a multi-core processor, a processor array, a network processor, etc.

[0114] The processor 702 may execute instructions or codes stored in the memory 701, which may also store data. Instructions and data may also be sent and received over a network via a network interface device, which may employ any known transmission protocol.

[0115] The memory 701 may be integrated with the processor 702, for example, by placing RAM or flash memory within an integrated circuit microprocessor or the like. In addition, the memory 701 may include a separate device, such as an external disk drive, a storage array, or any other storage device that can be used by a database system. The memory 701 and the processor 702 may be operatively coupled, or may communicate with each other, such as through an I / O port, a network connection, etc., so that the processor 702 can read files stored in the memory.

[0116] In addition, the computer device 700 may also include a video display (such as a liquid crystal display) and a user interaction interface (such as a keyboard, a mouse, a touch input device, etc.) All components of the computer device 700 may be connected to each other via a bus and / or a network.

[0117] The present disclosure provides a load simulation method, device and storage medium for a wind turbine generator set. By combining the simulated wind parameters of the wind farm obtained by simulation and the measured wind parameters, the simulated wind parameters are further refined to determine the predicted wind parameters of multiple points within the impeller surface of the target wind turbine generator set. The actual wind parameters borne by the unit on the entire impeller surface can be predicted, and then a more accurate simulated load of the unit can be calculated, which can fully reduce the simulation measurement deviation caused by the imbalance of the wind parameters on the impeller surface.

[0118] In addition, by configuring the complexity index and complexity threshold, the terrain complexity of the target wind farm can be quantitatively expressed, and when the complexity index is greater than the complexity threshold, the terrain of the target wind farm is considered to be complex. At this time, the aforementioned solution of first calculating the wind farm simulation wind parameters and then refining the predicted wind parameters of the impeller surface can meet the simulation needs of complex terrain and fully reduce the simulation deviation caused by the imbalance of the wind parameters on the impeller surface under complex terrain. For the case where the complexity index is less than or equal to the complexity threshold, it can be considered that the terrain of the target wind farm is relatively simple and flat. At this time, the traditional method is used to construct the wind conditions experienced by the wind turbine based on the wind parameters at the center of the hub, which can provide a more suitable load assessment solution for the target wind turbine generator set, help reduce the calculation load, improve the calculation efficiency, and realize the simulation of different scenarios.

[0119] The specific implementation methods of the present disclosure have been described in detail above. Although some embodiments have been shown and described, those skilled in the art should understand that these embodiments may be modified and varied without departing from the principles and spirit of the present disclosure, the scope of which is defined by the claims and their equivalents. These modifications and variations should also be within the scope of protection of the claims of the present disclosure.

Claims

1. A load simulation method for a wind turbine generator set, characterized in that: The load simulation method comprises: Obtaining terrain information of a target wind farm where a target wind turbine generator set is located and measured wind parameters at a predetermined observation point; Based on the terrain information, the wind parameters of the target wind farm are simulated to obtain simulated wind parameters of the wind farm; Determine predicted wind parameters of multiple points within the impeller surface of the target wind turbine generator set according to the simulated wind parameters of the wind farm and the measured wind parameters, and obtain predicted wind parameters of the impeller surface; Based on the predicted wind parameter of the impeller surface, the load of the target wind turbine generator set is simulated to obtain a simulated load of the set.

2. The load simulation method according to claim 1, characterized in that: The step of simulating the wind parameters of the target wind farm based on the terrain information to obtain simulated wind parameters of the wind farm includes: Determine a plurality of preset sectors, each preset sector represents a wind direction; For each preset sector of the plurality of preset sectors, based on the terrain information, the wind parameters of the target wind farm are simulated to obtain the simulated wind parameters of the wind farm of each preset sector.

3. The load simulation method according to claim 2, characterized in that: The step of determining predicted wind parameters of a plurality of points within the impeller surface of the target wind turbine generator set according to the simulated wind parameters of the wind farm and the measured wind parameters to obtain predicted wind parameters of the impeller surface includes: For each preset sector of the plurality of preset sectors, taking the direction facing the incoming wind as the impeller surface orientation of the target wind turbine generator set in the preset sector; According to the wind farm simulation wind parameters of each preset sector and the measured wind parameters, the predicted wind parameters of multiple points of the target wind turbine generator set within the impeller surface of each preset sector are determined to obtain the predicted wind parameters of the impeller surface of each preset sector.

4. The load simulation method according to claim 3, characterized in that: The method of simulating the load of the target wind turbine generator set based on the predicted wind parameter of the impeller surface to obtain the simulated load of the wind turbine generator set includes: Based on the predicted wind parameters of the impeller surface of each preset sector, the load of the target wind turbine generator set in each preset sector is simulated to obtain the simulated load of each preset sector; The simulated loads of the multiple preset sectors are combined to obtain the simulated load of the unit.

5. The load simulation method according to claim 4, characterized in that: The step of determining predicted wind parameters of a plurality of points on the impeller surface of each preset sector of the target wind turbine generator set according to the wind farm simulation wind parameters of each preset sector and the measured wind parameters, and obtaining predicted wind parameters on the impeller surface of each preset sector, comprises: The measured wind parameters are statistically processed according to the multiple preset sectors and the multiple preset wind speed segments to obtain statistical wind parameters in multiple preset intervals, each of the multiple preset intervals corresponding to a preset sector and a preset wind speed segment; For each preset interval among the multiple preset intervals, based on the wind farm simulation wind parameters of the preset sector corresponding to the preset interval and the statistical wind parameters under the preset interval, the predicted wind parameters of multiple points on the impeller surface of the target wind turbine generator set within the preset sector corresponding to the preset interval are determined to obtain the predicted wind parameters of the impeller surface of the preset interval.

6. The load simulation method according to claim 5, characterized in that: The predicted wind parameters of the impeller surface of each preset sector are used to simulate the load of the target wind turbine generator set in each preset sector to obtain the simulated load of each preset sector, including: For each preset interval of the plurality of preset intervals, the interval simulation load of the target wind turbine generator set in the preset interval is determined according to the predicted wind parameter of the impeller surface in the preset interval.

7. The load simulation method according to claim 6, characterized in that: The combining the simulated loads of the plurality of preset sectors to obtain the simulated load of the unit includes: The interval simulation loads of multiple preset intervals corresponding to the same preset wind speed section are combined to obtain the simulation load corresponding to each preset wind speed section in the multiple preset wind speed sections as the unit simulation load.

8. The load simulation method according to claim 5, characterized in that: For each preset interval of the multiple preset intervals, determining predicted wind parameters of a plurality of points of the impeller surface of the target wind turbine generator set within the preset sector corresponding to the preset interval according to the wind farm simulation wind parameters of the preset sector corresponding to the preset interval and the statistical wind parameters under the preset interval, and obtaining the predicted wind parameters of the impeller surface of the preset interval, comprises: For each preset sector of the plurality of preset sectors, constructing a blade surface grid of the target wind turbine generator set in the preset sector according to the blade surface orientation of the target wind turbine generator set in the preset sector; For each preset sector of the multiple preset sectors, each grid point of the target wind turbine generator set in the impeller surface grid of the preset sector is used as a plurality of points within the impeller surface, and based on the wind farm simulation wind parameters of the preset sector, the simulation wind parameters at each grid point in the impeller surface grid and the predetermined observation point are determined by using an interpolation method; For each preset interval among the multiple preset intervals, based on each grid point in the impeller surface grid of the preset sector corresponding to the preset interval of the target wind turbine generator set and the simulated wind parameters at the predetermined observation point, as well as the statistical wind parameters under the preset interval, the predicted wind parameters of the impeller surface of the target wind turbine generator set are determined to obtain the predicted wind parameters of the impeller surface of the preset interval.

9. The load simulation method according to claim 8, characterized in that: Each grid point of the impeller surface grid includes a hub center point and a non-hub center point, wherein, for each preset interval of the multiple preset intervals, according to each grid point in the impeller surface grid of the preset sector corresponding to the preset interval of the target wind turbine generator set and the simulated wind parameter at the predetermined observation point, and the statistical wind parameter under the preset interval, the predicted wind parameter of each grid point in the impeller surface grid of the preset sector corresponding to the preset interval of the target wind turbine generator set is determined, and the predicted wind parameter of the impeller surface of the preset interval is obtained, including: For each preset interval in the multiple preset intervals, for each grid point in the impeller surface grid of the preset sector of the target wind turbine generator set corresponding to the preset interval, according to the simulated wind parameter and the reference wind parameter of the reference point corresponding to the grid point, the simulated wind parameter of the grid point is corrected to obtain the predicted wind parameter of the grid point; Using the predicted wind parameters of each grid point in the impeller surface grid of the preset sector corresponding to the preset interval of the target wind turbine generator set as the predicted wind parameters of the impeller surface of the preset interval; Among them, the reference point corresponding to the wheel hub center point is the predetermined observation point, the reference point corresponding to the non-wheel hub center point is the wheel hub center point, the reference wind parameter of the predetermined observation point is the statistical wind parameter under the preset interval, and the reference wind parameter of the wheel hub center point is the predicted wind parameter of the wheel hub center point.

10. The load simulation method according to claim 9, characterized in that: The wind parameters include wind speed, turbulence intensity and wind direction, wherein the simulated wind parameters of the grid point and the reference wind parameters corresponding to the grid point are corrected to obtain the predicted wind parameters of the grid point, including: Based on the respective correction relationships of different wind parameters, the simulated wind parameters of the grid point are corrected according to the simulated wind parameters and the reference wind parameters of the reference point corresponding to the grid point to obtain the predicted wind parameters of the grid point. The correction relationship of the wind speed is that the ratio of the predicted wind speed at the grid point to the simulated wind speed is equal to the ratio of the reference wind speed at the reference point corresponding to the grid point to the simulated wind speed; The correction relationship of turbulence intensity is that the ratio of the predicted turbulence difference to the simulated turbulence difference is equal to the ratio of the simulated wind speed of the grid point to the simulated wind speed of the reference point corresponding to the grid point, wherein the predicted turbulence difference is the difference between the predicted turbulence intensity of the grid point and the reference turbulence intensity of the reference point corresponding to the grid point, and the simulated turbulence difference is the difference between the simulated turbulence intensity of the grid point and the simulated turbulence intensity of the reference point corresponding to the grid point; The correction relationship of the wind direction is that the difference between the predicted wind direction and the simulated wind direction of the grid point is equal to the difference between the reference wind direction and the simulated wind direction of the reference point corresponding to the grid point.

11. The load simulation method according to any one of claims 1 to 10, characterized in that: The simulating process of wind parameters of multiple points in the target wind farm based on the terrain information to obtain wind farm simulated wind parameters includes: Based on the terrain information, determining a complexity index of the target wind farm, wherein the complexity index is used to represent the complexity of the terrain of the target wind farm; When the complexity index is greater than a complexity threshold, wind parameters of a plurality of points in the target wind farm are simulated based on the terrain information to obtain simulated wind parameters of the wind farm.

12. The load simulation method according to claim 11, characterized in that: The complexity threshold is a statistical value of a complexity index of a reference wind farm, and the reference wind farm is a wind farm where a fault has occurred.

13. A load simulation device for a wind turbine generator set, characterized in that: The load simulation device comprises: An acquisition unit is configured to acquire terrain information of a target wind farm where a target wind turbine generator set is located and actual wind parameters at a predetermined observation point; A first simulation unit is configured to simulate the wind parameters of the target wind farm based on the terrain information to obtain simulated wind parameters of the wind farm; A determination unit is configured to determine predicted wind parameters of a plurality of points within an impeller surface of a target wind turbine generator set according to the simulated wind parameters of the wind farm and the measured wind parameters, so as to obtain predicted wind parameters of the impeller surface; The second simulation unit is configured to simulate the load of the target wind turbine generator set based on the predicted wind parameter of the impeller surface to obtain a simulated load of the wind turbine generator set.

14. A computer-readable storage medium, characterized in that: When the instructions in the computer-readable storage medium are executed by at least one processor, the at least one processor is prompted to execute the load simulation method for a wind turbine generator set according to any one of claims 1 to 12.

15. A computer device, characterized in that: include: at least one processor; at least one memory storing computer executable instructions, Wherein, when the computer executable instructions are executed by the at least one processor, the at least one processor is prompted to execute the load simulation method for a wind turbine generator set according to any one of claims 1 to 12.

Images