Point location information determination method and device, equipment, storage medium and product

Abstract

The invention belongs to the technical field of wind power plants, and discloses a point location information determination method and device, equipment, a storage medium and a product. The method comprises the following steps: clustering a plurality of to-be-queried point locations in an available land parcel of a wind power plant to obtain a target clustering center, then constructing a triangulation network by taking the target clustering center as a vertex, and determining an affiliation relationship between the plurality of to-be-queried point locations and triangles in the triangulation network; and determining wind speed and wind direction information corresponding to the plurality of to-be-queried point locations according to the target wind speed and wind direction information corresponding to the target clustering center and the affiliation relationship. The multiple to-be-queried points are clustered, the number of the points needing to be queried through the wind resource interface is reduced, then the wind speed and wind direction information corresponding to the multiple to-be-queried points is determined according to the target wind speed and wind direction information corresponding to the target clustering center and the affiliation relation, and therefore under the condition that the number of query times of the wind resource interface is limited, the query efficiency of the wind resource interface is improved. The wind speed and wind direction information of a large number of to-be-queried point locations in available plots is effectively and accurately determined through a clustering center query method.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of wind farms, in particular to a point information determination method and device, equipment, storage medium and product. BACKGROUND

[0002] In the micro-siting process of a wind farm, the selection of wind turbine points is an important link, which is related to the subsequent selection of power collection lines, roads and booster stations in the wind farm. The selection of wind turbine points in the micro-siting stage needs to be combined with factors such as wind direction, wind speed distribution and terrain, among which the wind speed and wind direction information of each available point is crucial and directly related to the power generation yield and the wake influence range between points. How to obtain the wind speed and wind direction information of the points to be queried is a problem that must be solved in the micro-siting stage. Generally, the wind resource interface provided by a third-party company is used to query the wind resource of each point in the region. However, there is often a limit on the number of queries, and the limit cannot meet the demand for the total number of queries. Therefore, how to effectively and accurately determine the wind speed and wind direction information of a large number of points in the available land block under the condition that the number of wind resource interface queries is limited has become a problem to be solved. SUMMARY

[0003] The main purpose of the present application is to provide a point information determination method, device, equipment, storage medium and product, which aims to solve the technical problem of how to effectively and accurately determine the wind speed and wind direction information of a large number of points in the available land block under the condition that the number of wind resource interface queries is limited.

[0004] To achieve the above-mentioned purpose, the present application provides a point information determination method, which comprises the following steps:

[0005] Clustering a plurality of points to be queried in an available land block of a wind farm to obtain a target clustering center;

[0006] Taking the target clustering center as a vertex, constructing a triangular mesh, and determining the attribution relationship between the plurality of points to be queried and the triangles in the triangular mesh;

[0007] Determining the wind speed and wind direction information corresponding to the plurality of points to be queried according to the target wind speed and wind direction information corresponding to the target clustering center and the attribution relationship.

[0008] Optionally, the step of clustering a plurality of points to be queried in an available land block of a wind farm to obtain a target clustering center specifically comprises:

[0009] Determining the maximum number of point queries corresponding to the wind farm, and selecting an initial point set with a number equal to the maximum number of point queries from the plurality of points to be queried;

[0010] each initial point in the initial point set is taken as an initial clustering center;

[0011] adjusting the initial clustering center to obtain a target clustering center.

[0012] Optionally, the step of adjusting the initial clustering center to obtain a target clustering center specifically comprises:

[0013] calculating the Euclidean distance between each to-be-queried point and each initial clustering center, and constructing a distance set;

[0014] determining a to-be-queried clustering center corresponding to each to-be-queried point according to the distance set;

[0015] clustering the plurality of to-be-queried points according to the to-be-queried clustering center to obtain an initial class with a number of the maximum point query times;

[0016] determining a target clustering center according to all to-be-queried points in the initial class.

[0017] Optionally, the step of determining a target clustering center according to all to-be-queried points in the initial class specifically comprises:

[0018] determining the point coordinates corresponding to all to-be-queried points in each initial class, and determining a new clustering center according to the point coordinates;

[0019] returning to the step of calculating the Euclidean distance between each to-be-queried point and each initial clustering center, and constructing a distance set, until a preset iteration number is reached or the position of the obtained clustering center meets a preset condition, and taking the obtained clustering center as a target clustering center.

[0020] Optionally, the step of determining the wind speed and direction information corresponding to the plurality of to-be-queried points according to the target wind speed and direction information corresponding to the target clustering center and the attribution relationship specifically comprises:

[0021] for each triangle in the triangular net, obtaining the vertex coordinates of the triangle, and determining the vertex wind speed and direction information of the triangle according to the target wind speed and direction information corresponding to the target clustering center;

[0022] calculating the plane fitting coefficient of the triangle according to the vertex coordinates and the vertex wind speed and direction information;

[0023] determining the wind speed and direction information corresponding to the plurality of to-be-queried points according to the plane fitting coefficient and the attribution relationship.

[0024] Optionally, the step of determining the wind speed and direction information corresponding to the plurality of query points based on the plane fitting coefficients and the attribution relationship specifically includes:

[0025] When the attribution relationship indicates that the point to be queried belongs to the triangle, wind speed and wind direction information are calculated based on the plane fitting coefficient and the coordinates corresponding to the point to be queried.

[0026] When the attribution relationship is that the point to be queried does not belong to any triangle, determine the point cluster center corresponding to the point to be queried;

[0027] The wind speed and direction information of the points corresponding to the cluster centers of the points are used as the wind speed and direction information of the points to be queried.

[0028] Optionally, before the step of clustering multiple query points in the available land parcels of the wind farm to obtain the target cluster center, the method further includes:

[0029] Determine all boundary points corresponding to the available land parcels for wind farms in the initial land parcel set, and determine the center of the circumcircle corresponding to the available land parcels for wind farms;

[0030] Calculate the Euclidean distance between each boundary point and the center of the circumcircle to form a set of Euclidean distances;

[0031] Determine the maximum distance in the set of Euclidean distances, and use the point corresponding to the maximum distance as the target point.

[0032] Multiple query points are determined based on the target point.

[0033] Optionally, the step of determining multiple query points based on the target point specifically includes:

[0034] Using the target point as the center, construct an initial circle based on the diameter of the wind turbine impeller;

[0035] Determine the difference between the initial set of land parcels and the initial circle;

[0036] The initial set of land parcels is updated based on the difference set to obtain a new set of land parcels. The steps of determining all boundary points corresponding to the available land parcels for wind farms in the initial set of land parcels are returned until the new set of land parcels is empty. All the obtained target points are used as multiple query points.

[0037] Furthermore, to achieve the above objectives, this application also provides a location information determination device, the location information determination device comprising:

[0038] The point clustering module is used to cluster multiple query points in the available land parcels of wind farms to obtain the target cluster center;

[0039] A triangulation construction module is used to construct a triangulation network with the target cluster center as the vertex, and to determine the attribution relationship between the multiple query points and the triangles in the triangulation network;

[0040] The location information determination module is used to determine the wind speed and direction information corresponding to the multiple locations to be queried based on the target wind speed and direction information corresponding to the target cluster center and the attribution relationship.

[0041] In addition, to achieve the above objectives, this application also proposes a location information determination device, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the location information determination method described above.

[0042] In addition, to achieve the above objectives, this application also proposes a storage medium, which is a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the steps of the point information determination method described above.

[0043] In addition, to achieve the above objectives, this application also provides a computer program product, which includes a computer program that, when executed by a processor, implements the steps of the point information determination method described above.

[0044] This application clusters multiple query points within available wind farm land parcels to obtain target cluster centers. Then, using these target cluster centers as vertices, a triangular network is constructed, and the affiliation of each query point with a triangle within the network is determined. Finally, based on the target wind speed and direction information corresponding to the target cluster centers and their affiliation, the wind speed and direction information corresponding to each query point is determined. This application first clusters multiple query points, replacing single-point queries in existing technologies with cluster center queries, reducing the number of points that need to be queried through the wind resource interface. Simultaneously, the calculation of the target cluster centers ensures sufficiently broad query coverage and high accuracy. By determining the wind speed and direction information corresponding to multiple query points based on the target wind speed and direction information corresponding to the target cluster centers and their affiliation, this application can effectively and accurately determine the wind speed and direction information of a large number of query points within available land parcels, even with limited wind resource interface query attempts. Attached Figure Description

[0045] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0046] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0047] Figure 1 This is a flowchart illustrating the first embodiment of the method for determining location information in this application;

[0048] Figure 2 A schematic diagram of the location to be queried and the target cluster center, which is an embodiment of the location information determination method of this application;

[0049] Figure 3 This is a schematic diagram illustrating the determination of multiple query points according to an embodiment of the point information determination method of this application;

[0050] Figure 4 A schematic diagram of a triangulation network for one embodiment of the point information determination method of this application;

[0051] Figure 5 This is a flowchart illustrating the second embodiment of the method for determining location information in this application;

[0052] Figure 6 This is a flowchart illustrating the third embodiment of the point location information determination method of this application;

[0053] Figure 7 A schematic diagram of plane fitting of points within a triangular mesh in one embodiment of the point location information determination method of this application;

[0054] Figure 8 This is a structural block diagram of the first embodiment of the location information determination device of this application;

[0055] Figure 9 This is a schematic diagram of the device for determining the location information of the hardware operating environment involved in the embodiments of this application.

[0056] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0057] It should be understood that the specific embodiments described herein are merely illustrative of the technical solutions of this application and are not intended to limit this application.

[0058] To better understand the technical solution of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.

[0059] The main solution of this application embodiment is: to cluster multiple query points in the available land of the wind farm to obtain a target cluster center; to construct a triangular network with the target cluster center as the vertex, and to determine the belonging relationship between the multiple query points and the triangles in the triangular network; and to determine the wind speed and wind direction information corresponding to the multiple query points according to the target wind speed and wind direction information corresponding to the target cluster center and the belonging relationship.

[0060] In the micro-site selection process of wind farms, the selection of wind turbine locations is a crucial step, affecting the site selection of subsequent power collection lines, roads, and substations. The selection of wind turbine locations during the micro-site selection phase needs to consider factors such as wind direction, wind speed distribution, and topography. Among these, the wind speed and direction information for each available location is critical, directly impacting power generation revenue and the wake influence range between locations. Therefore, obtaining the wind speed and direction information for the desired location is a problem that must be solved during the micro-site selection phase. Generally, wind resource interfaces provided by third-party companies are used for single-point queries to obtain wind resource information for each point in the area. However, there are often limitations on the number of queries, and these limits are far from meeting the total demand for queries.

[0061] This application clusters multiple query points within available wind farm land parcels to obtain target cluster centers. Then, using these target cluster centers as vertices, a triangular network is constructed, and the affiliation of each query point with a triangle within the network is determined. Finally, based on the target wind speed and direction information corresponding to the target cluster centers and their affiliation, the wind speed and direction information corresponding to each query point is determined. This application first clusters multiple query points, replacing single-point queries in existing technologies with cluster center queries, reducing the number of points that need to be queried through the wind resource interface. Simultaneously, the calculation of the target cluster centers ensures sufficiently broad query coverage and high accuracy. By determining the wind speed and direction information corresponding to multiple query points based on the target wind speed and direction information corresponding to the target cluster centers and their affiliation, this application can effectively and accurately determine the wind speed and direction information of a large number of query points within available land parcels, even with limited wind resource interface query attempts.

[0062] It should be noted that the executing entity of this application can be a computing service device with data processing, network communication, and program execution functions, such as a computer, or an electronic device or location information determination device capable of performing the above functions. The following description uses a location information determination device as an example to illustrate this embodiment and the subsequent embodiments.

[0063] Based on this, embodiments of this application provide a method for determining location information, referring to... Figure 1 , Figure 1 This is a flowchart illustrating the first embodiment of the method for determining location information in this application.

[0064] In this embodiment, the method for determining location information includes the following steps:

[0065] Step S10: Cluster multiple query points in the available land parcels of the wind farm to obtain the target cluster center.

[0066] Understandably, multiple query points in the available land parcels of wind farms can be clustered. Clustering algorithms can be used to obtain several classes and determine the target cluster center for each class.

[0067] In the specific implementation, refer to Figure 2 , Figure 2 This is a schematic diagram of the query point and the target cluster center in one embodiment of the point information determination method of this application, as shown below. Figure 2 As shown, the red dots represent the points to be queried, and the green dots represent the target cluster centers.

[0068] Furthermore, in order to determine multiple query points in the available land parcels of the wind farm, in this embodiment, before step S10, the method further includes: determining all boundary points corresponding to the available land parcels of the wind farm in the initial land parcel set, and determining the center of the circumcircle corresponding to the available land parcels of the wind farm; calculating the Euclidean distance between each boundary point and the center of the circumcircle to form a set of Euclidean distances; determining the maximum distance in the set of Euclidean distances, and taking the point corresponding to the maximum distance as the target point; and determining multiple query points based on the target point.

[0069] It should be understood that this embodiment can obtain multiple query points in the available land parcels of a wind farm through a greedy strategy. The input of the greedy strategy can be the available land parcels and the diameter of the wind turbine rotor, and the output can be multiple query points in the available land parcels.

[0070] Understandably, referring to Figure 3 , Figure 3 This is a schematic diagram illustrating the determination of multiple query points according to an embodiment of the point information determination method of this application, as shown below. Figure 3 As shown, the initial set of land parcels can be set as S, such as... Figure 3 The first image in the diagram includes three available land parcels. The initial set of query points T is an empty set. Then, all boundary points corresponding to the available land parcels of the wind farm in the initial set of land parcels S are determined, and the center of the circumcircle corresponding to the available land parcels of the wind farm is determined. This circumcircle can contain all available land parcels of the wind farm. Then, the Euclidean distance between each boundary point and the center of the circumcircle is calculated, and the Euclidean distances between all boundary points and the center of the circumcircle are used to form a set of Euclidean distances.

[0071] In practical implementation, the maximum distance in the Euclidean distance set can be determined, and the point corresponding to the maximum distance can be used as the target point, such as... Figure 3The purple dots in the second image are used to determine multiple query points based on the target point.

[0072] Furthermore, in order to accurately determine multiple query points, in this embodiment, the step of determining multiple query points based on the target point specifically includes: constructing an initial circle with the target point as the center and based on the wind turbine rotor diameter; determining the difference between the initial land parcel set and the initial circle; updating the initial land parcel set based on the difference to obtain a new land parcel set, and returning to the step of determining all boundary points corresponding to the available land parcels of the wind farm in the initial land parcel set, until the new land parcel set is an empty set, and using all the obtained target points as multiple query points.

[0073] Understandably, after obtaining the target point p, p can be added to t, and an initial circle O can be constructed with the target point p as the center and D / 2 as the radius, as follows. Figure 3 The second image shows a purple hollow circle, where D is the diameter of the wind turbine impeller, which can be set to 200 meters. Then, the difference between each available plot in the initial plot set S and the initial circle O is calculated. The initial plot set is then updated based on this difference, i.e., S is updated to the set containing this difference, resulting in a new plot set. The process then returns to the previous steps of retrieving the boundary points of available plots in the updated plot set, resulting in several initial circles, such as... Figure 3 The third, fourth, and fifth images in the dataset, until the new set of land parcels becomes empty, are used to treat all target locations as multiple query locations, such as... Figure 3 The red dot in the last picture.

[0074] Step S20: Construct a triangular network with the target cluster center as the vertex, and determine the attribution relationship between the multiple query points and the triangles in the triangular network.

[0075] It should be understood that this embodiment can use all target cluster centers as vertices and call the Delaunay algorithm to generate a triangular mesh, referring to... Figure 4 , Figure 4 A schematic diagram of a triangulated network for one embodiment of the point information determination method of this application, as shown below. Figure 4 As shown, a triangulation network can contain several triangles, and there may be some query points that are outside the triangulation network. The relationship between each query point and the triangles in the triangulation network can include whether the query point is inside a triangle or outside a triangle.

[0076] Step S30: Determine the wind speed and direction information corresponding to the multiple query points based on the target wind speed and direction information corresponding to the target cluster center and the attribution relationship.

[0077] It is understood that in this embodiment, the target cluster center can query the target wind speed and direction information through the wind resource interface. The number of target cluster centers can be the same as the number of wind resource interfaces. Then, the wind speed and direction information corresponding to each query point is determined according to the target wind speed and direction information and the affiliation relationship.

[0078] This embodiment clusters multiple query points within available wind farm land parcels to obtain target cluster centers. Then, using these target cluster centers as vertices, a triangular network is constructed, and the affiliation of each query point with a triangle within the network is determined. Finally, based on the target wind speed and direction information corresponding to the target cluster centers and their affiliation relationships, the wind speed and direction information corresponding to each query point is determined. This embodiment first clusters multiple query points, replacing single-point queries in existing technologies with cluster center queries, reducing the number of points that need to be queried through the wind resource interface. Simultaneously, the calculation of the target cluster centers ensures sufficiently broad query coverage and high accuracy. By determining the wind speed and direction information corresponding to multiple query points based on the target wind speed and direction information corresponding to the target cluster centers and their affiliation relationships, this method effectively and accurately determines the wind speed and direction information of a large number of query points within available land parcels, even when the number of wind resource interface queries is limited.

[0079] refer to Figure 5 , Figure 5 This is a flowchart illustrating the second embodiment of the method for determining location information in this application.

[0080] Based on the first embodiment described above, in this embodiment, step S10 includes:

[0081] Step S101: Determine the maximum number of times the location can be queried for the wind farm, and select an initial set of locations from the plurality of locations to be queried, the number of which is equal to the maximum number of times the location can be queried.

[0082] Understandably, the maximum number of query times n for a wind farm can be the number of wind resource interfaces, and the number of query points can be set to m, where m >> n. Let P be the number of m query points. i Let i = 1, 2, ..., m, and its coordinates be (x1, y1), (x2, y2), ..., (x m ,y m ).

[0083] It should be understood that the location of the cluster center can be calculated using the K-means clustering algorithm. Specifically, an initial set of points can be selected from the m points to be queried, with the number of points equal to the maximum number of queries required. That is, n points to be queried can be selected as the initial set of points.

[0084] Step S102: Use each initial point in the initial point set as the initial cluster center.

[0085] Understandably, the initial point set can contain n initial points, which can be used as initial cluster centers, and the number of initial cluster centers is also n.

[0086] Step S103: Adjust the initial cluster centers to obtain the target cluster centers.

[0087] Furthermore, in order to effectively adjust the initial cluster centers, in this embodiment, step S103 includes: calculating the Euclidean distance between each query point and each of the initial cluster centers, and constructing a distance set; determining the query cluster center corresponding to each query point based on the distance set; clustering the multiple query points based on the query cluster centers to obtain an initial class with a number equal to the maximum number of query times; and determining the target cluster center based on all query points in the initial class.

[0088] It should be understood that the Euclidean distances between m query points and n initial cluster centers can be calculated, and all Euclidean distances can be constructed into a distance set. Then, the corresponding query cluster centers for the m query points can be determined based on the distance set. Specifically, the m query points can be assigned to the nearest cluster center, i.e., the query cluster center. Then, the m query points are clustered according to the query cluster centers to obtain n initial clusters, each with k cluster centers. i There are n points to be queried, i = 1, 2, ..., n, and they satisfy: That is, the sum of the number of query points in all n initial classes is m, and it is guaranteed that each query point belongs to one and only one initial class.

[0089] Furthermore, in this embodiment, the step of determining the target cluster center based on all query points in the initial class specifically includes: determining the coordinates of all query points in each initial class, and determining new cluster centers based on the coordinates; returning to the step of calculating the Euclidean distance between each query point and each initial cluster center, and constructing a distance set, until a preset number of iterations is reached or the position of the obtained cluster center meets a preset condition, and the obtained cluster center is used as the target cluster center.

[0090] Understandably, after obtaining n initial classes, for each initial class k i Given a query point, its coordinates can be determined, and a new cluster center can be determined based on these coordinates. The coordinates of the new cluster center can be: x i ′ Let y be the x-coordinate of the new cluster center. i ′ The ordinate is the y-coordinate of the new cluster center.

[0091] It should be understood that after obtaining the sum of new cluster centers, the steps of calculating the Euclidean distance between each query point and each of the initial cluster centers and constructing the distance set can be returned until a preset number of iterations is reached or the positions of the obtained cluster centers meet a preset condition. The preset condition may be that the positions of the obtained cluster centers remain almost unchanged. All cluster centers obtained during the loop can be used as the target cluster center, denoted as C. i , i=1,2,…,n, that is Figure 2 The green dots in the middle.

[0092] This embodiment determines the maximum number of queries required for a wind farm and selects an initial set of points from multiple query points, with the number of points equal to the maximum number of queries. Each initial point in this set is then used as an initial cluster center, and these initial cluster centers are adjusted to obtain the target cluster center. By using each initial point in the initial set as the initial cluster center, the wind speed and direction information of the initial cluster center can be obtained through the wind resource query interface, reducing the number of points that need to be directly queried through the wind resource interface. The calculation of the target cluster center ensures that the query coverage for wind speed and direction is sufficiently broad and the accuracy is sufficiently high.

[0093] refer to Figure 6 , Figure 6 This is a flowchart illustrating the third embodiment of the method for determining location information in this application.

[0094] Based on the above embodiments, in this embodiment, step S30 includes:

[0095] Step S301: For each triangle in the triangulation network, obtain the vertex coordinates of the triangle, and determine the vertex wind speed and direction information of the triangle based on the target wind speed and direction information corresponding to the target cluster center.

[0096] Understandably, for each triangle T in the triangular network... j The coordinates of the vertices of the triangle (x1, y1), (x2, y2), and (x3, y3) can be obtained. Since the vertices of the triangle are the target cluster centers, and the target wind speed and direction information corresponding to the target cluster centers is obtained through the wind resource query interface, the wind speed and direction information of the vertices of the triangle can be obtained. The vertex wind speed information is denoted as s1, s2, s3, and the vertex wind direction information is denoted as a1, a2, a3.

[0097] Step S302: Calculate the plane fitting coefficient of the triangle based on the vertex coordinates and the vertex wind speed and direction information.

[0098] It should be understood that this embodiment uses the calculation of wind speed information corresponding to the point to be queried as an example for explanation. The method for calculating wind direction information corresponding to the point to be queried is the same as the method for calculating wind speed information, and this embodiment will not elaborate on it further.

[0099] Understandably, the vertex coordinates and corresponding vertex wind speed information are integrated into three-dimensional point coordinates (x1, y1, s1), (x2, y2, s2), (x3, y3, s3). The equation of the plane passing through these three points is calculated as follows: Let the equation of the plane passing through these three points be Ax + By + Cz = 1, where A, B, and C are plane fitting coefficients, then:

[0100]

[0101] Step S303: Determine the wind speed and direction information corresponding to the multiple query points based on the plane fitting coefficients and the attribution relationship.

[0102] Furthermore, to accurately obtain the wind speed and direction information corresponding to the point to be queried, in this embodiment, step S303 includes: when the attribution relationship is that the point to be queried belongs to the triangle, calculating the wind speed and direction information based on the plane fitting coefficient and the coordinates corresponding to the point to be queried; when the attribution relationship is that the point to be queried does not belong to any triangle, determining the point cluster center corresponding to the point to be queried; and using the point wind speed and direction information corresponding to the point cluster center as the wind speed and direction information corresponding to the point to be queried.

[0103] It should be understood that for m points P to be queried i Determine its relationship with triangle T. j The attribution relationship, if P i ∈T j If the attribution relationship is that the point to be queried belongs to the triangle, then P i The wind speed at point is:

[0104]

[0105] In the formula, A j B j C j Triangle T j The coefficients of the fitted plane equation, x i y i Let P be the point i The coordinates. (Refer to...) Figure 7 , Figure 7 This is a schematic diagram of plane fitting of points within a triangular mesh in one embodiment of the point location information determination method of this application.

[0106] Understandably, if point P i Not belonging to any Tj If the queried point does not belong to any triangle, the cluster center of the queried point can be determined. This cluster center is one of the target cluster centers, and the wind speed corresponding to this cluster center is used as the wind speed information corresponding to the queried point.

[0107] In practical implementation, the calculation of wind direction information for the location to be queried can be performed by considering all the s values ​​from the above steps. i Replace with wind direction a i By performing the same process, the wind direction information corresponding to the queried point can be obtained. In this embodiment, actual tests show that the average difference between the fitting result of this method and the actual query result in mountainous scenarios with variable wind speed and direction is within two per thousand, which basically meets the requirements for querying wind speed and direction at multiple points over a large area.

[0108] This embodiment obtains the vertex coordinates of each triangle in the triangulation network, and determines the vertex wind speed and direction information of the triangle based on the target wind speed and direction information corresponding to the target cluster center. Then, it calculates the plane fitting coefficient of the triangle based on the vertex coordinates and vertex wind speed and direction information, and determines the wind speed and direction information corresponding to multiple query points based on the plane fitting coefficient and the attribution relationship. This embodiment uses a triangulation network plus plane fitting method, which can make full use of the wind speed and direction information of the queried points, and at the same time considers the gradual change trend of wind speed and direction between different points, making the fitting results more accurate, and thus accurately determining the wind speed and direction information of a large number of query points within the available land area.

[0109] Reference Figure 8 , Figure 8 This is a structural block diagram of the first embodiment of the location information determination device of this application.

[0110] like Figure 8 As shown, the location information determination device proposed in this application includes:

[0111] The point clustering module 10 is used to cluster multiple points to be queried in the available land plots of the wind farm to obtain the target cluster center;

[0112] The triangulation construction module 20 is used to construct a triangulation network with the target cluster center as the vertex, and to determine the belonging relationship between the multiple query points and the triangles in the triangulation network;

[0113] The location information determination module 30 is used to determine the wind speed and direction information corresponding to the multiple locations to be queried based on the target wind speed and direction information corresponding to the target cluster center and the attribution relationship.

[0114] This embodiment clusters multiple query points within available wind farm land parcels to obtain target cluster centers. Then, using these target cluster centers as vertices, a triangular network is constructed, and the affiliation of each query point with a triangle within the network is determined. Finally, based on the target wind speed and direction information corresponding to the target cluster centers and their affiliation relationships, the wind speed and direction information corresponding to each query point is determined. This embodiment first clusters multiple query points, replacing single-point queries in existing technologies with cluster center queries, reducing the number of points that need to be queried through the wind resource interface. Simultaneously, the calculation of the target cluster centers ensures sufficiently broad query coverage and high accuracy. By determining the wind speed and direction information corresponding to multiple query points based on the target wind speed and direction information corresponding to the target cluster centers and their affiliation relationships, this method effectively and accurately determines the wind speed and direction information of a large number of query points within available land parcels, even when the number of wind resource interface queries is limited.

[0115] It should be noted that the workflow described above is merely illustrative and does not limit the scope of protection of this application. In practical applications, those skilled in the art can select some or all of it to achieve the purpose of this embodiment according to actual needs, and no restrictions are imposed here.

[0116] In addition, for technical details not described in detail in this embodiment, please refer to the point information determination method provided in any embodiment of this application, which will not be repeated here.

[0117] Based on the first embodiment of the location information determination device described in this application, a second embodiment of the location information determination device of this application is proposed.

[0118] In this embodiment, the point clustering module 10 is further configured to determine the maximum number of point queries corresponding to the wind farm, and select an initial point set from the plurality of points to be queried with a number equal to the maximum number of point queries; use each initial point in the initial point set as an initial cluster center; and adjust the initial cluster center to obtain a target cluster center.

[0119] Furthermore, the point clustering module 10 is also used to calculate the Euclidean distance between each point to be queried and each of the initial cluster centers, and construct a distance set; determine the cluster center to be queried corresponding to each point to be queried based on the distance set; cluster the multiple points to be queried based on the cluster centers to be queried to obtain an initial class with a number equal to the maximum number of point queries; and determine the target cluster center based on all points to be queried in the initial class.

[0120] Furthermore, the point clustering module 10 is also used to determine the point coordinates corresponding to all query points in each initial class, and determine new cluster centers based on the point coordinates; return to the step of calculating the Euclidean distance between each query point and each initial cluster center, and constructing a distance set, until a preset number of iterations is reached or the position of the obtained cluster center meets the preset conditions, and use the obtained cluster center as the target cluster center.

[0121] Furthermore, the point information determination module 30 is also used to obtain the vertex coordinates of each triangle in the triangulation network, and determine the vertex wind speed and direction information of the triangle according to the target wind speed and direction information corresponding to the target cluster center; calculate the plane fitting coefficient of the triangle according to the vertex coordinates and the vertex wind speed and direction information; and determine the wind speed and direction information corresponding to the multiple query points according to the plane fitting coefficient and the attribution relationship.

[0122] Furthermore, the point information determination module 30 is also used to calculate wind speed and direction information based on the plane fitting coefficient and the coordinates corresponding to the point to be queried when the attribution relationship is that the point to be queried belongs to the triangle; and to determine the point cluster center corresponding to the point to be queried when the attribution relationship is that the point to be queried does not belong to any triangle; and to use the point wind speed and direction information corresponding to the point cluster center as the wind speed and direction information corresponding to the point to be queried.

[0123] Furthermore, the point clustering module 10 is also used to determine all boundary points corresponding to the available wind farm plots in the initial plot set, and determine the center of the circumcircle corresponding to the available wind farm plots; calculate the Euclidean distance between each boundary point and the center of the circumcircle to form an Euclidean distance set; determine the maximum distance in the Euclidean distance set, and take the point corresponding to the maximum distance as the target point; and determine multiple points to be queried based on the target point.

[0124] Furthermore, the point clustering module 10 is also used to construct an initial circle with the target point as the center and based on the diameter of the wind turbine rotor; determine the difference between the initial land parcel set and the initial circle; update the initial land parcel set based on the difference to obtain a new land parcel set, and return the step of determining all boundary points corresponding to the available land parcels of the wind farm in the initial land parcel set, until the new land parcel set is an empty set, and use all the obtained target points as multiple query points.

[0125] Other embodiments or specific implementations of the location information determination device of this application can be found in the above-described method embodiments, and will not be repeated here.

[0126] This application provides a location information determination device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the location information determination method in the above embodiment 1.

[0127] The following is for reference. Figure 9 The diagram illustrates a structural schematic of a location information determination device suitable for implementing embodiments of this application. The location information determination device in these embodiments may include, but is not limited to, mobile terminals such as mobile phones, laptops, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Description), PMPs (Portable Media Players), and in-vehicle terminals (e.g., in-vehicle navigation terminals), as well as fixed terminals such as digital TVs and desktop computers. Figure 9 The location information determination device shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of this application.

[0128] like Figure 9As shown, the point information determination device may include a processing unit 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1002 or a program loaded from a storage device 1003 into a random access memory (RAM) 1004. The RAM 1004 also stores various programs and data required for the operation of the point information determination device. The processing unit 1001, ROM 1002, and RAM 1004 are interconnected via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to the I / O interface 1006: input devices 1007 including, for example, touchscreens, touchpads, keyboards, mice, image sensors, microphones, accelerometers, gyroscopes, etc.; output devices 1008 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 1003 including, for example, magnetic tapes, hard disks, etc.; and communication devices 1009. Communication device 1009 allows the location information determining device to communicate wirelessly or wiredly with other devices to exchange data. Although the figure shows location information determining devices with various systems, it should be understood that implementation or possession of all the systems shown is not required. More or fewer systems may be implemented alternatively.

[0129] Specifically, according to the embodiments disclosed in this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device, or installed from storage device 1003, or installed from ROM 1002. When the computer program is executed by processing device 1001, it performs the functions defined in the methods of the embodiments disclosed in this application.

[0130] The location information determination device provided in this application, employing the location information determination method described in the above embodiments, can solve the technical problem of effectively and accurately determining wind speed and direction information for a large number of locations within available land parcels when the number of wind resource interface queries is limited. Compared with the prior art, the beneficial effects of the location information determination device provided in this application are the same as those of the location information determination method provided in the above embodiments, and other technical features of this location information determination device are the same as those disclosed in the method of the previous embodiment, and will not be repeated here.

[0131] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0132] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0133] This application provides a computer-readable storage medium having computer-readable program instructions (i.e., a computer program) stored thereon, the computer-readable program instructions being used to execute the point information determination method in the above embodiments.

[0134] The computer-readable storage medium provided in this application may be, for example, a USB flash drive, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, system, or device. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.

[0135] The aforementioned computer-readable storage medium may be included in the location information determination device; or it may exist independently and not be assembled into the location information determination device.

[0136] The aforementioned computer-readable storage medium carries one or more programs. When the aforementioned one or more programs are executed by the location information determining device, the location information determining device: clusters multiple queried locations in the available land parcels of the wind farm to obtain target cluster centers; constructs a triangular network with the target cluster centers as vertices, and determines the affiliation relationship between the multiple queried locations and the triangles in the triangular network; and determines the wind speed and direction information corresponding to the multiple queried locations based on the target wind speed and direction information corresponding to the target cluster centers and the affiliation relationship.

[0137] Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a Local Area Network (LAN) or a Wide Area Network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0138] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0139] The modules described in the embodiments of this application can be implemented in software or hardware. The names of the modules do not necessarily limit the functionality of the unit itself.

[0140] The readable storage medium provided in this application is a computer-readable storage medium that stores computer-readable program instructions (i.e., a computer program) for executing the above-described point information determination method. This solves the technical problem of effectively and accurately determining wind speed and direction information for a large number of points within available land parcels when the number of wind resource interface queries is limited. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as those of the point information determination method provided in the above embodiments, and will not be elaborated upon here.

[0141] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the point information determination method described above.

[0142] The computer program product provided in this application can solve the technical problem of effectively and accurately determining wind speed and direction information of a large number of points within available land parcels when the number of wind resource interface queries is limited. Compared with the prior art, the beneficial effects of the computer program product provided in this application are the same as those of the point information determination method provided in the above embodiments, and will not be repeated here.

[0143] The above description is only a part of the embodiments of this application and does not limit the patent scope of this application. All equivalent structural transformations made under the technical concept of this application and using the contents of the specification and drawings of this application, or direct / indirect applications in other related technical fields, are included in the patent protection scope of this application.

Claims

1. A method for determining location information, characterized in that, The method for determining location information includes the following steps: Cluster multiple query points in the available land parcels of wind farms to obtain the target cluster centers; Using the target cluster center as the vertex, a triangular network is constructed, and the attribution relationship between the multiple query points and the triangles in the triangular network is determined; The wind speed and direction information corresponding to the multiple query points is determined based on the target wind speed and direction information corresponding to the target cluster center and the attribution relationship.

2. The method for determining location information as described in claim 1, characterized in that, The step of clustering multiple query points in available land parcels for wind farms to obtain target cluster centers specifically includes: Determine the maximum number of times a location can be queried for a wind farm, and select an initial set of locations from the plurality of locations to be queried, the number of which is equal to the maximum number of times a location can be queried. Each initial point in the initial point set is used as the initial cluster center; The initial cluster centers are adjusted to obtain the target cluster centers.

3. The method for determining location information as described in claim 2, characterized in that, The step of adjusting the initial cluster centers to obtain the target cluster centers specifically includes: Calculate the Euclidean distance between each query point and each of the initial cluster centers, and construct a distance set; The cluster center corresponding to each of the query points is determined based on the distance set. Cluster the multiple query points according to the cluster center to be queried, and obtain an initial class with a number equal to the maximum number of query times for the maximum point; The target cluster center is determined based on all the query points in the initial class.

4. The method for determining location information as described in claim 2, characterized in that, The step of determining the target cluster center based on all query points in the initial class specifically includes: Determine the coordinates of all query points in each initial class, and determine new cluster centers based on the coordinates. Return to the steps of calculating the Euclidean distance between each query point and each initial cluster center, and constructing a distance set, until a preset number of iterations is reached or the position of the obtained cluster center meets a preset condition, and the obtained cluster center is used as the target cluster center.

5. The method for determining location information as described in claim 1, characterized in that, The step of determining the wind speed and direction information corresponding to the multiple query points based on the target wind speed and direction information corresponding to the target cluster center and the attribution relationship specifically includes: For each triangle in the triangulation network, obtain the vertex coordinates of the triangle, and determine the vertex wind speed and direction information of the triangle based on the target wind speed and direction information corresponding to the target cluster center; The plane fitting coefficient of the triangle is calculated based on the vertex coordinates and the vertex wind speed and direction information; The wind speed and direction information corresponding to the multiple query points is determined based on the plane fitting coefficients and the attribution relationship.

6. The method for determining location information as described in claim 5, characterized in that, The step of determining the wind speed and direction information corresponding to the multiple query points based on the plane fitting coefficients and the attribution relationship specifically includes: When the attribution relationship indicates that the point to be queried belongs to the triangle, wind speed and wind direction information are calculated based on the plane fitting coefficient and the coordinates corresponding to the point to be queried. When the attribution relationship is that the point to be queried does not belong to any triangle, determine the point cluster center corresponding to the point to be queried; The wind speed and direction information of the points corresponding to the cluster centers of the points are used as the wind speed and direction information of the points to be queried.

7. The method for determining location information as described in any one of claims 1 to 6, characterized in that, Before the step of clustering multiple query points in the available land parcels of the wind farm to obtain the target cluster center, the method further includes: Determine all boundary points corresponding to the available land parcels for wind farms in the initial land parcel set, and determine the center of the circumcircle corresponding to the available land parcels for wind farms; Calculate the Euclidean distance between each boundary point and the center of the circumcircle to form a set of Euclidean distances; Determine the maximum distance in the set of Euclidean distances, and use the point corresponding to the maximum distance as the target point. Multiple query points are determined based on the target point.

8. The method for determining location information as described in claim 7, characterized in that, The step of determining multiple query points based on the target point specifically includes: Using the target point as the center, construct an initial circle based on the diameter of the wind turbine impeller; Determine the difference between the initial set of land parcels and the initial circle; The initial set of land parcels is updated based on the difference set to obtain a new set of land parcels. The steps of determining all boundary points corresponding to the available land parcels for wind farms in the initial set of land parcels are returned until the new set of land parcels is empty. All the obtained target points are used as multiple query points.

9. A device for determining location information, characterized in that, The location information determination device includes: The point clustering module is used to cluster multiple query points in the available land parcels of wind farms to obtain the target cluster center; A triangulation construction module is used to construct a triangulation network with the target cluster center as the vertex, and to determine the attribution relationship between the multiple query points and the triangles in the triangulation network; The location information determination module is used to determine the wind speed and direction information corresponding to the multiple locations to be queried based on the target wind speed and direction information corresponding to the target cluster center and the attribution relationship.

10. A device for determining location information, characterized in that, The device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the location information determination method as described in any one of claims 1 to 8.

11. A storage medium, characterized in that, The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, it implements the steps of the point information determination method as described in any one of claims 1 to 8.

12. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the steps of the location information determination method as described in any one of claims 1 to 8.

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