Offshore wind plant wind resource assessment method and device, electronic equipment and readable storage medium

Abstract

The invention discloses an offshore wind power plant wind resource assessment method and device, electronic equipment and a readable storage medium, is applied to the technical field of offshore wind power development, and aims to solve the problem that wind resources of an offshore wind power plant cannot be accurately assessed in the prior art. The method comprises the following steps: acquiring measured data of each anemometer tower in a preset range around an area to be subjected to wind measurement; performing wind resource prediction on a target point location in the area to be subjected to wind measurement by using each group of wind measurement tower actual measurement data to obtain a first predicted average wind speed corresponding to each group of wind measurement tower actual measurement data; determining a wind speed correction coefficient of the target point location according to each first predicted average wind speed; determining a target anemometer tower from each anemometer tower, and correcting the anemometer tower actual measurement data of the target anemometer tower by adopting a correction coefficient to obtain annual wind speed data of a target point location in the area to be subjected to wind measurement; according to the invention, the accuracy of offshore wind plant wind resource assessment can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of offshore wind power development, and in particular to a method, device, electronic equipment and computer-readable storage medium for evaluating wind resources in an offshore wind farm. Background Art

[0002] Wind power generation is the fastest growing green energy technology in the world. Due to the abundant offshore wind energy resources and the feasibility of current technology, the ocean will become a rapidly developing wind power market. As the development of offshore wind power is gradually accelerated, the project cycle is compressed to be shorter. In the early stage of the project wind resource assessment, for projects without wind measurement data or the length of wind measurement data does not meet a full year, it is impossible to objectively and accurately assess the wind resources of the project. Currently, the more commonly used methods for dealing with projects without wind towers are as follows:

[0003] One method is to use WRF (Weather Research and Forecasting) to simulate the meteorological characteristics of the target area, establish multiple virtual wind towers, extract the corresponding wind resource data, and determine the final target location wind resources based on the excellent correlation between the actual wind tower data in the target area and the virtual tower to be determined. The disadvantage of this method is that the calculation efficiency is extremely low and the turbulence level cannot be accurately assessed.

[0004] Another method is to use an artificial intelligence network model to generate wind measurement data at the target location based on the data from adjacent wind farm wind towers. The disadvantage of this method is that the artificial intelligence model requires a large amount of measured data for training, and the accuracy of the model directly affects the reliability of the results.

[0005] Another method is to use mesoscale data to calculate the ratio of the wind speed at the target location to the measured location, and use this as a correction factor to extrapolate the wind speed at a single known wind tower location to the wind speed at the target location. The disadvantage of this method is that the prediction results are greatly affected by the accuracy of the data at a single known wind tower location.

[0006] In view of this, how to improve the accuracy of wind resource assessment in offshore wind farms has become a problem that technical personnel in this field need to solve. Summary of the invention

[0007] The purpose of the embodiments of the present invention is to provide a method, device, electronic device and computer-readable storage medium for evaluating wind resources in an offshore wind farm, which can improve the accuracy of wind resource evaluation in an offshore wind farm during use.

[0008] To solve the above technical problems, the embodiments of the present invention provide the following technical solutions:

[0009] In one aspect, the present invention provides a method for evaluating wind resources in an offshore wind farm, comprising:

[0010] Obtaining the measured data of wind towers of each wind tower within a preset range around the wind area to be measured;

[0011] Using each group of the wind tower measured data, respectively, to predict the wind resources of the target points in the wind area to be measured, and obtain the first predicted average wind speed corresponding to each of the wind tower measured data;

[0012] Determining a wind speed correction coefficient for each target point according to each of the first predicted average wind speeds;

[0013] A target wind tower is determined from each of the wind towers, and the wind tower measured data of the target wind tower is corrected by using the correction coefficient to obtain the annual wind speed data of the target point in the wind area to be measured.

[0014] In one embodiment, using each group of the wind tower measured data to respectively predict wind resources for target points in the wind area to be measured to obtain a first predicted average wind speed corresponding to each of the wind tower measured data, includes:

[0015] For each group of wind tower measured data, an average wind speed of the wind tower at a preset hub height of the corresponding wind tower is obtained according to the wind tower measured data;

[0016] Acquire the mesoscale data of the wind tower and the mesoscale data of the wind area to be measured;

[0017] A first predicted average wind speed of a target point in the wind area to be measured at the preset hub height is determined according to the average measured wind speed of the wind measuring tower, the mesoscale data of the wind measuring tower and the mesoscale data of the wind area to be measured.

[0018] In one embodiment, determining the wind speed correction coefficient of the target point according to each of the first predicted average wind speeds includes:

[0019] Determine the measured average wind speed at the target point according to each of the first predicted average wind speeds;

[0020] Obtaining an average wind speed of the target wind tower at a preset hub height;

[0021] The ratio of the measured average wind speed at the target point to the average wind speed of the target wind tower at a preset hub height is determined as the wind speed correction coefficient of the target point.

[0022] In one embodiment, the step of obtaining the measured data of wind towers of each wind tower within a preset range around the wind area to be measured includes:

[0023] Detect whether there is a wind tower within a first preset range around the wind area to be measured, and if so, obtain the wind tower measured data of each wind tower within the first prediction range;

[0024] If not, detect whether there is a wind measuring tower within a second preset range around the wind area to be measured. If so, obtain the actual measured data of the wind measuring towers of each wind measuring tower within the second prediction range, wherein the distance between the first preset range and the wind area to be measured is smaller than the distance between the second preset range and the wind area to be measured.

[0025] In one embodiment, the target point is the center point of the wind area to be measured, and the first preset range is a range within a first distance from the center point of the wind area to be measured;

[0026] Then, when there is a wind tower within the first preset range, determining the measured average wind speed at the target point according to each of the first predicted average wind speeds includes:

[0027] The average wind speed of each of the first predicted average wind speeds is used as the measured average wind speed at the central point of the wind area to be measured.

[0028] In one embodiment, the target point is the center point of the wind area to be measured, and the second preset range is a range between a first distance and a second distance from the center point of the wind area to be measured; the first distance is smaller than the second distance;

[0029] Then, when there is no wind tower within the first preset range and there are multiple wind towers within the second preset range, determining the measured average wind speed of the target point according to each of the first predicted average wind speeds includes: obtaining the weight of each of the wind towers;

[0030] For each of the first predicted average wind speeds, multiplying the first predicted average wind speed by the weight of the corresponding wind tower to obtain a corrected wind speed;

[0031] The corrected wind speeds are summed to obtain the measured average wind speed at the target point.

[0032] In one implementation, obtaining the weight of each of the wind towers includes:

[0033] The weight of each wind tower is determined according to the wind tower measured data corresponding to each wind tower.

[0034] In one embodiment, determining the weight of each wind tower according to the wind tower measured data corresponding to each wind tower includes:

[0035] For each of the wind towers, the wind speed of other wind towers is estimated by using the wind tower measured data of the wind tower, so as to obtain the estimated wind speed of other wind towers estimated by the wind tower;

[0036] For each of the estimated wind speeds, based on the wind speed actually measured by the wind tower of the wind tower and the estimated wind speed, determine the deviation rate of the wind speed estimated by the wind tower from the estimated wind speeds of other wind towers;

[0037] Sum the deviation rates of the wind speed estimated by the wind measuring tower from other wind measuring towers, and combine the total number of other wind measuring towers to obtain a first average deviation rate corresponding to the wind measuring tower;

[0038] Sum the first average deviation rates corresponding to each of the wind measurement towers to obtain a total average deviation rate;

[0039] For each of the wind towers, according to the first average deviation rate of the wind tower and the total average deviation rate, a deviation ratio corresponding to the wind tower is obtained;

[0040] Sum the deviation proportions corresponding to each of the wind measurement towers to obtain a total deviation proportion;

[0041] For each of the wind towers, a ratio of the deviation proportion of the wind tower to the total deviation proportion is used as the weight of the wind tower.

[0042] In one embodiment, determining a target wind tower from each of the wind towers includes:

[0043] A wind measuring tower that is closest to the target point in the wind measuring area among the wind measuring towers is determined as a target wind measuring tower.

[0044] Another aspect of the present invention provides a wind resource assessment device for an offshore wind farm, comprising:

[0045] An acquisition module is used to acquire the measured data of wind towers of each wind tower within a preset range around the wind area to be measured;

[0046] A prediction module, used to use each group of measured data of the wind tower to predict the wind resources of the target points in the wind area to be measured, and obtain a first predicted average wind speed corresponding to each measured data of the wind tower;

[0047] A determination module, used to determine the wind speed correction coefficient of the target point according to each of the first predicted average wind speeds;

[0048] The correction module is used to determine a target wind tower from each of the wind towers, and use the correction coefficient to correct the wind tower measured data of the target wind tower to obtain the annual wind speed data of the target point in the wind area to be measured.

[0049] Another aspect of the present invention provides an electronic device, comprising:

[0050] Memory for storing computer programs;

[0051] A processor is used to implement the steps of the offshore wind farm wind resource assessment method as described above when executing the computer program.

[0052] Another aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of the offshore wind farm wind resource assessment method as described above are implemented.

[0053] It can be seen from the above technical solutions that the beneficial effects of the embodiments of the present invention are:

[0054] An embodiment of the present invention provides a method for evaluating wind resources in an offshore wind farm, comprising: obtaining measured data of wind towers of each wind tower within a preset range around a wind area to be measured; using each group of measured data of wind towers to respectively predict wind resources for target points in the wind area to be measured, and obtaining first predicted average wind speeds corresponding to the measured data of each wind tower; determining wind speed correction coefficients for target points according to the first predicted average wind speeds; determining a target wind tower from each wind tower, and using the correction coefficient to correct the measured data of the wind tower of the target wind tower, and obtaining annual wind speed data for the target points in the wind area to be measured.

[0055] It can be seen that in the embodiment of the present invention, when calculating the correction coefficient of the target point in the wind area to be measured, the first predicted average wind speed is calculated by respectively extrapolating the wind speed of the target point based on the measured data of the wind towers of each wind tower within a preset range around the wind area to be measured, rather than being obtained based on the data of a single wind tower. Therefore, the obtained correction coefficient is more accurate. In the present invention, a target wind tower is determined from multiple wind towers, and then the measured data of the wind tower of the target wind tower is corrected using the correction coefficient, so as to obtain more accurate annual wind speed data of the target point in the wind area to be measured. The present invention can improve the accuracy of wind resource assessment in offshore wind farms.

[0056] In addition, the present invention also provides corresponding implementation devices, electronic devices and computer-readable storage media for the offshore wind farm wind resource assessment method, further making the method more practical, and the devices, electronic devices and computer-readable storage media have corresponding advantages. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the prior art and the drawings required for use in the embodiments are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0058] Figure 1 A schematic flow chart of a method for evaluating wind resources in an offshore wind farm provided by an embodiment of the present invention;

[0059] Figure 2 A table of various parameters for determining a weight coefficient of a wind tower provided in an embodiment of the present invention;

[0060] Figure 3 A position relationship diagram of a wind tower and target points provided in an embodiment of the present invention;

[0061] Figure 4 A target point wind speed estimation parameter table diagram provided by an embodiment of the present invention;

[0062] Figure 5 A schematic structural diagram of a wind resource assessment device for an offshore wind farm provided by an embodiment of the present invention;

[0063] Figure 6 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention;

[0064] Figure 7 A schematic diagram of the structure of a computer-readable storage medium provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0065] The embodiments of the present invention provide a method, device, electronic device and computer-readable storage medium for evaluating wind resources in an offshore wind farm, which can improve the accuracy of wind resource evaluation in an offshore wind farm during use.

[0066] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0067] Please refer to Figure 1 , Figure 1 A flow chart of a method for evaluating wind resources in an offshore wind farm provided by an embodiment of the present invention. The method comprises:

[0068] S110: Acquire the wind tower measured data of each wind tower within a preset range around the wind area to be measured;

[0069] It should be noted that when conducting wind resource assessment for a wind area to be measured (i.e., a field area to be measured), a preset range around the wind area to be measured can be determined, and each wind tower within the preset range can be determined, and the wind tower measured data of each wind tower can be obtained. The preset range can be determined with the target point of the wind area to be measured as the center.

[0070] In actual applications, it is possible to detect whether there is a wind measurement tower within a first preset range around the wind area to be measured. If there is a wind measurement tower within the first preset range, the actual measured data of the wind measurement tower of each wind measurement tower within the first prediction range is obtained; if there is no wind measurement tower within the first preset range, it is detected whether there is a wind measurement tower within a second preset range around the wind area to be measured. If there is a wind measurement tower within the second preset range, the actual measured data of the wind measurement tower of each wind measurement tower within the second prediction range is obtained, wherein the distance between the first preset range and the wind area to be measured is smaller than the distance between the second preset range and the wind area to be measured.

[0071] S120: using each group of wind tower measured data to respectively perform wind resource prediction for target points in the wind area to be measured, to obtain a first predicted average wind speed corresponding to each wind tower measured data;

[0072] Specifically, after obtaining the measured data of each wind tower, for each wind tower, the measured data of the wind tower of the wind tower can be used to infer the wind resources of the target point in the wind area to be measured, and the first predicted average wind speed of the center point of the wind area to be measured inferred by the measured data of the wind tower of the wind tower can be obtained, so that the first predicted average wind speed inferred by the measured data of each wind tower can be obtained, that is, one wind tower corresponds to one group of measured data of the wind tower and one first predicted average wind speed. In practical applications, for each wind tower, the wind tower can be used as a reference point, so as to infer the first predicted average wind speed of the target point in the wind area to be measured based on the measured data of the wind tower at the reference point.

[0073] Furthermore, the implementation process of the above S120 can be implemented in the following manner:

[0074] For each set of wind tower measured data, the average measured wind speed of the wind tower at the preset hub height of the corresponding wind tower is obtained according to the wind tower measured data;

[0075] Obtain mesoscale data of the wind tower and the mesoscale data of the wind area to be measured;

[0076] A first predicted average wind speed at a target point in the wind area to be measured at a preset hub height is determined according to the average measured wind speed of the wind measuring tower, the mesoscale data of the wind measuring tower and the mesoscale data of the wind area to be measured.

[0077] It should be noted that the measured data of the wind tower collected in actual applications are annual data. The preset hub height can be determined according to the height of the wind turbine set at the target point in the wind area to be measured, and then the annual measured data of the preset hub height of the wind tower can be inferred based on the measured data of the wind tower. Further, based on the annual measured data of the preset hub height of the wind tower, the average measured wind speed of the wind tower at the preset hub height of the wind tower can be obtained.

[0078] It can be understood that after obtaining the average measured wind speed of the wind tower at the preset hub height of the wind tower (i.e., the reference point), the mesoscale data of the wind tower (such as mesoscale contemporaneous data and mesoscale long-term data) can be further obtained, and the mesoscale data of the target point in the wind area to be measured (such as mesoscale contemporaneous data and mesoscale long-term data) can be obtained. Then, according to the average measured wind speed of the wind tower, the mesoscale data of the wind tower and the mesoscale data of the wind area to be measured, the first predicted average wind speed of the target point in the wind area to be measured at the preset hub height can be calculated in combination with the first relationship, wherein the first relationship is: V 目标点位中尺度 / V 参考点位中尺度 =V 目标点位实测 / V 参考点位实测 , V 目标点位中尺度 Represents the mesoscale data of the target point in the wind area to be measured, V 参考点位中尺度 Represents the mesoscale data of the wind tower, V 参考点位实测 represents the average measured wind speed of the wind tower. According to the first relational expression, the first predicted average wind speed V at the target point at the preset hub height in the wind area to be measured can be obtained. 目标点位实测 .

[0079] S130: determining a wind speed correction coefficient of a target point according to each first predicted average wind speed;

[0080] Specifically, when there are multiple wind measuring towers within a preset range around the wind area to be measured, taking into account that different wind measuring towers have different representativeness of the wind conditions in the wind area to be measured, after obtaining the first preset average wind speed estimated by each wind measuring tower, the wind speed correction coefficient of the target point in the wind area to be measured can be further determined in combination with each first predicted average wind speed.

[0081] S140: Determine a target wind tower from each wind tower, and use a correction coefficient to correct the wind tower measured data of the target wind tower to obtain the annual wind speed data of the target point in the wind area to be measured.

[0082] It should be noted that, in the embodiment of the present invention, a target wind tower is determined from each wind tower, and then the wind speed correction coefficient is used to correct the wind tower measured data of the target wind tower to obtain the corrected target point time series data, and the corrected target point time series data is used as the annual wind speed data of the target point in the wind area to be measured.

[0083] In practical applications, the wind tower closest to the target point in the wind area to be measured among the wind towers can be determined as the target wind tower (that is, the adjacent wind tower), wherein the target point can be the center point, that is, the wind tower closest to the center point of the wind area to be measured among the wind towers can be selected as the target wind tower.

[0084] Furthermore, the process of determining the wind speed correction coefficient of the target point according to each first predicted average wind speed in S130 may include:

[0085] Determine the measured average wind speed at the target point according to each first predicted average wind speed;

[0086] Obtaining an average wind speed of a target wind tower at a preset hub height;

[0087] The ratio of the measured average wind speed at the target point to the average wind speed of the target wind tower at the preset hub height is determined as the wind speed correction coefficient of the target point.

[0088] It can be understood that after obtaining the first predicted average wind speeds estimated by each wind tower for the target position of the wind area to be measured, the measured average wind speed of the wind area to be measured can be further determined according to each first predicted average wind speed. After obtaining the measured average wind speed of the wind area to be measured, the average wind speed of the wind tower at the preset hub height of the target wind tower can be further obtained, and then combined with the relationship ƒ = V 目标点 / V 实测点 , we can get the wind speed correction coefficient f of the target point, where V 目标点 Represents the measured average wind speed at the target point, V 实测点 Represents the average wind speed at the wind tower at a preset hub height adjacent to the wind tower.

[0089] Furthermore, the process of obtaining the measured data of each wind tower in a preset range around the wind area to be measured in S110 may include:

[0090] Detect whether there is a wind tower within a first preset range around the wind area to be measured, and if so, obtain the wind tower measured data of each wind tower within the first prediction range;

[0091] If not, detect whether there is a wind measuring tower within a second preset range around the wind area to be measured. If so, obtain the actual measured data of the wind measuring towers of each wind measuring tower within the second prediction range, wherein the distance between the first preset range and the wind area to be measured is smaller than the distance between the second preset range and the wind area to be measured.

[0092] In practical applications, the first preset range in the embodiment of the present invention can be a range within a first distance from the target point of the wind area to be measured, and the second preset range can be a range between the first distance and the second distance from the center point of the wind area to be measured; wherein the first distance is smaller than the second distance.

[0093] Specifically, it is possible to first detect whether there is a wind tower within a preset range within a first distance from the target point of the wind area to be measured, and if so, obtain the wind tower measured data of each wind tower, and enter the subsequent wind resource forecast for the wind area to be measured. If not, further detect whether there is a wind tower within a preset range between the first distance and the second distance from the target point of the wind area to be measured, and if so, obtain each wind tower within the range and incorporate it into the subsequent wind resource forecast for the wind area to be measured.

[0094] It should be noted that in the embodiment of the present invention, the target point is the center point of the wind area to be measured. For different preset ranges, the process of determining the measured average wind speed of the target point is different according to each first predicted average wind speed, which is described in detail below:

[0095] When there is a wind tower within the first preset range, the process of determining the measured average wind speed at the target point according to each first predicted average wind speed may include:

[0096] The average wind speed of each first predicted average wind speed is used as the measured average wind speed at the center point of the wind area to be measured.

[0097] It can be understood that the first distance can be 10km, and it can be detected whether there is a wind measuring tower within the first distance range from the center point of the wind area to be measured. If so, the measured data of the wind measuring tower of each wind measuring tower is obtained, and the corresponding first predicted average wind speed is inferred respectively, and then the average wind speed of each first predicted average wind speed is calculated, and the average wind speed is used as the measured average wind speed of the center point of the wind area to be measured.

[0098] Of course, if there is only one wind measuring tower detected within a preset range within the first distance from the center point of the wind area to be measured, after the first predicted average wind speed of the center point of the wind area to be measured is inferred based on the actual measured data of the wind measuring tower, the first predicted average wind speed can be directly used as the measured average wind speed of the center point of the wind area to be measured.

[0099] In addition, when there is no wind tower within the first preset range and there are multiple wind towers within the second preset range, the process of determining the measured average wind speed at the target point according to each first predicted average wind speed may include:

[0100] Get the weight of each wind tower;

[0101] For each first predicted average wind speed, multiply the first predicted average wind speed by the weight of the corresponding wind tower to obtain a corrected wind speed;

[0102] Sum up each corrected wind speed to get the measured average wind speed at the target point.

[0103] It should be noted that in actual applications, the second distance can be 80km, and it can be understood that each wind tower located between the first distance and the second distance from the center point of the wind area to be measured is generally representative of the wind area to be measured. At this time, it is necessary to use long-term data to determine the weight of each wind tower. Specifically, the weight of each wind tower can be determined according to the measured data of the wind towers corresponding to each wind tower. For each first predicted average wind speed, the first predicted average wind speed is multiplied by the weight of the corresponding wind tower to obtain the corrected wind speed, thereby obtaining the corrected wind speed corresponding to each first preset average wind speed, and then the corrected wind speeds are summed to obtain the measured average wind speed of the target point.

[0104] In one implementation, the process of determining the weight of each wind tower according to the wind tower measured data corresponding to each wind tower may include:

[0105] For each wind tower, the wind speed of other wind towers is estimated by using the wind tower measured data of the wind tower, and the estimated wind speed of other wind towers is obtained;

[0106] For each estimated wind speed, based on the wind speed actually measured by the wind tower and the estimated wind speed, determine the deviation rate of the wind tower's estimated wind speed from other wind towers;

[0107] Sum the deviation rates of the wind speeds estimated by the wind tower from other wind towers, and combine the total number of other wind towers to obtain a first average deviation rate corresponding to the wind tower;

[0108] The first average deviation rate corresponding to each wind measurement tower is summed to obtain a total average deviation rate;

[0109] For each wind tower, the deviation ratio corresponding to the wind tower is obtained according to the first average deviation rate and the total average deviation rate of the wind tower;

[0110] Sum the deviation percentages corresponding to each wind tower to obtain the total deviation percentage;

[0111] For each wind tower, the ratio of the deviation proportion of the wind tower to the total deviation proportion is used as the weight of the wind tower.

[0112] It should be noted that when there are multiple reference wind towers, it is necessary to consider the representativeness of wind conditions in the field area from different wind towers. The evaluation of different representativeness is based on the deviation judgment of the wind speed at each point with measured data. The larger the deviation, the worse the representativeness, and the smaller the deviation, the better the representativeness. Among them, the various parameters determined by the wind tower weight coefficient are as follows Figure 2 shown.

[0113] Below Figure 3 Taking the wind area to be measured and each wind tower as an example, the weight calculation process of each wind tower is explained:

[0114] Figure 3 The middle circular area in the figure is the wind area to be measured, and the center of the wind area to be measured is the target point T. There is no wind tower within a radius of 10 km (i.e., a first preset range) of the target point. There are 6 wind towers within a radius of 10 km to a radius of 80 km (i.e., a second preset range), which can be respectively determined as wind tower A, wind tower B, wind tower C, wind tower D, wind tower E, and wind tower F. In the embodiment of the present invention, one wind tower is taken as an example for detailed description:

[0115] For example, the wind tower measured data of wind tower A (that is, the wind speed measured by the wind tower) is recorded as V A实 , based on the wind tower measured data V of wind tower A A实 The first predicted average wind speed at the target point T is estimated to be V A,T Based on the first relational expression, the estimated wind speeds at the other five wind towers are estimated from the wind tower A. For example, the estimated wind speed at the wind tower B estimated by the wind tower A is V A,B , the estimated wind speed at tower A is V A,C , the estimated wind speed at wind tower A is V A,D , the estimated wind speed at wind tower A is V A,E , the estimated wind speed at tower A is V A,F .

[0116] For wind tower A, the estimated wind speed at other wind towers (V A,B ,V A,C ,……V A,F ), based on the wind speed V measured by other wind towers i实 , estimated wind speed V A，i , determine the deviation rate of wind speed estimated by wind tower A from other wind towers. Specifically, the deviation rate P of wind speed estimated by wind tower A at other locations (wind tower i) is A,i =|V i实-V A,i |, where N is the total number of wind towers within the second preset range from the target point, i=B,C...F, based on the above deviation rates combined with the total number of other wind towers N-1, the first average deviation rate P can be obtained. A,aver =(P A,B + P A,C + P A,D + P A,E + P A,F ) / (N-1).

[0117] According to the above method, the first average deviation rate P corresponding to the wind tower B can be obtained respectively. B,aver , the first average deviation rate P corresponding to the wind tower C C,aver , the first average deviation rate P corresponding to the wind tower D D,aver , the first average deviation rate P corresponding to the wind tower E E,aver , the first average deviation rate P corresponding to the wind tower F F,aver Then the first average deviation rate P corresponding to each wind tower is j,aver Sum and get the total average deviation rate , j = A,B,C……F.

[0118] For each wind tower, the relationship P is calculated based on the first average deviation rate and the total average deviation rate of the wind tower and the deviation ratio. j,prop =1-P j,aver / , and obtain the deviation proportion P corresponding to the wind tower j j,prop For example, the deviation of wind tower A accounts for P A,prop For: P A,prop =1-P A,aver /

[0119] Sum the deviation proportions corresponding to each wind tower j j,prop , and get the total deviation ratio ; For each wind tower j, the deviation proportion P of wind tower j is j,prop Percentage of total deviation The ratio of is taken as the weight P of the wind tower j,factor , that is, P j,factor =P j,prop / For example, the weight of wind tower A is P A,factor =P A,prop / .

[0120] After obtaining the weights of each wind tower, the measured average wind speed V at the target point T can be calculated based on the first predicted average wind speed of each wind tower combined with the corresponding weight. 目标点 , where V 目标点 = V A,T P A,factor +V B， T P B,factor +……+V F,T P F,factor .

[0121] The values ​​of each parameter can be found in Figure 4 The target position wind speed calculation table shown in the figure is as follows. After the above wind speed calculation, the measured average wind speed V at the target point T is obtained. 目标点 Since the wind tower C is closest to the target point, the wind tower C can be selected as the target wind tower, and the measured data of the wind tower C is used as the original wind data to be corrected, and it is corrected according to the wind speed level of 8.170m / s at the target point, that is, the original wind data to be corrected is corrected to the average wind speed level of 8.170m / s through the correction coefficient. After the correction, the distribution characteristics of the turbulence intensity in the area changing with wind direction and the distribution characteristics of the turbulence intensity changing with seasons are not affected.

[0122] It can be seen that in the embodiment of the present invention, when calculating the correction coefficient of the target point in the wind area to be measured, the first predicted average wind speed is calculated by respectively extrapolating the wind speed of the target point based on the measured data of the wind towers of each wind tower within a preset range around the wind area to be measured, rather than being obtained based on the data of a single wind tower. Therefore, the obtained correction coefficient is more accurate. In the present invention, a target wind tower is determined from multiple wind towers, and then the measured data of the wind tower of the target wind tower is corrected using the correction coefficient, so as to obtain more accurate annual wind speed data of the target point in the wind area to be measured. The present invention can improve the accuracy of wind resource assessment in offshore wind farms.

[0123] The present invention also provides a corresponding device for the offshore wind farm wind resource assessment method, which further makes the method more practical. Among them, the device can be described from the perspective of functional modules and hardware. The offshore wind farm wind resource assessment device provided by the present invention is introduced below. The device is used to implement the offshore wind farm wind resource assessment method provided by the present invention. In this embodiment, the offshore wind farm wind resource assessment device may include or be divided into one or more program modules, and the one or more program modules are stored in a storage medium and executed by one or more processors to complete the offshore wind farm wind resource assessment method disclosed in the above embodiment. The program module referred to in the present invention refers to a series of computer program instruction segments that can complete specific functions, which is more suitable for describing the execution process of the offshore wind farm wind resource assessment device in the storage medium than the program itself. The following description will specifically introduce the functions of each program module of this embodiment. The offshore wind farm wind resource assessment device described below and the offshore wind farm wind resource assessment method described above can be referenced to each other.

[0124] From the perspective of functional modules, see Figure 5 , Figure 5 A structural diagram of a wind resource assessment device for an offshore wind farm provided by the present invention in a specific embodiment, the device may include:

[0125] An acquisition module 11 is used to acquire the measured data of each wind tower within a preset range around the wind area to be measured;

[0126] A prediction module 12 is used to use each group of wind tower measured data to perform wind resource prediction on the target points in the wind area to be measured, and obtain a first predicted average wind speed corresponding to each wind tower measured data;

[0127] A determination module 13 is used to determine a wind speed correction coefficient of a target point according to each first predicted average wind speed;

[0128] The correction module 14 is used to determine a target wind tower from various wind towers, and use a correction coefficient to correct the wind tower measured data of the target wind tower to obtain the annual wind speed data of the target point in the wind area to be measured.

[0129] In one embodiment, the prediction module 12 includes:

[0130] A first calculation unit is used to obtain, for each group of wind tower measured data, an average measured wind speed of the wind tower at a preset hub height of the corresponding wind tower according to the wind tower measured data;

[0131] A first acquisition unit is used to acquire the mesoscale data of the wind tower and the mesoscale data of the wind area to be measured;

[0132] The second calculation unit is used to determine a first predicted average wind speed at a target point in the wind area to be measured at a preset hub height based on the average measured wind speed of the wind tower, the mesoscale data of the wind tower and the mesoscale data of the wind area to be measured.

[0133] In one embodiment, the determination module 13 includes:

[0134] A first determining unit, configured to determine the measured average wind speed at the target point according to each first predicted average wind speed;

[0135] A second acquisition unit is used to acquire an average wind speed of a wind tower at a preset hub height of a target wind tower;

[0136] The third calculation unit is used to determine the ratio of the measured average wind speed at the target point to the average wind speed of the target wind tower at a preset hub height as the wind speed correction coefficient of the target point.

[0137] In one implementation, the acquisition module 11 includes:

[0138] The first detection unit is used to detect whether there is a wind measuring tower within a first preset range around the wind area to be measured, and if so, trigger the third acquisition unit; if not, trigger the second detection unit;

[0139] A third acquisition subunit is used to acquire the wind tower measured data of each wind tower within the first prediction range;

[0140] A second detection unit is used to detect whether there is a wind measurement tower within a second preset range around the wind area to be measured, and if so, trigger a fourth acquisition unit;

[0141] The fourth acquisition unit is used to acquire the measured data of each wind tower of each wind tower within the second prediction range, wherein the distance between the first preset range and the wind area to be measured is smaller than the distance between the second preset range and the wind area to be measured.

[0142] In one embodiment, the target point is the center point of the wind area to be measured, and the first preset range is a range within a first distance from the center point of the wind area to be measured;

[0143] Then, when there is a wind tower within the first preset range, the first determining unit is used to:

[0144] The average wind speed of each first predicted average wind speed is used as the measured average wind speed at the center point of the wind area to be measured.

[0145] In one embodiment, the target point is the center point of the wind area to be measured, and the second preset range is a range between a first distance and a second distance from the center point of the wind area to be measured; the first distance is smaller than the second distance;

[0146] Then, when there is no wind tower within the first preset range and there are multiple wind towers within the second preset range, the first determining unit includes:

[0147] The first acquisition subunit is used to obtain the weight of each wind tower;

[0148] A first calculation subunit is used for multiplying the first predicted average wind speed by the weight of the corresponding wind tower for each first predicted average wind speed to obtain a corrected wind speed;

[0149] The second calculation subunit is used to sum up the corrected wind speeds to obtain the measured average wind speed at the target point.

[0150] In one implementation, the first acquisition subunit is configured to:

[0151] The weight of each wind tower is determined according to the measured data of each wind tower.

[0152] In one implementation, the first acquisition subunit includes:

[0153] The first inference subunit is used to, for each wind tower, use the wind tower measured data of the wind tower to respectively infer the wind speed of other wind towers, so as to obtain the inferred wind speed of other wind towers estimated by the wind tower;

[0154] A third calculation subunit is used to determine, for each estimated wind speed, a deviation rate of the wind speed estimated by the wind tower from the estimated wind speeds of other wind towers based on the wind speed actually measured by the wind tower and the estimated wind speed of the wind tower;

[0155] A fourth calculation subunit is used to sum the deviation rates of the wind speeds estimated by the wind tower from other wind towers, and obtain a first average deviation rate corresponding to the wind tower in combination with the total number of other wind towers;

[0156] a fifth calculation subunit, configured to sum the first average deviation rates corresponding to each wind tower to obtain a total average deviation rate;

[0157] a sixth calculation subunit, configured to obtain, for each wind tower, a deviation ratio corresponding to the wind tower according to the first average deviation rate and the total average deviation rate of the wind tower;

[0158] A seventh calculation subunit is used to sum the deviation proportions corresponding to each wind measurement tower to obtain a total deviation proportion;

[0159] The eighth calculation subunit is configured to use, for each wind tower, a ratio of the deviation proportion of the wind tower to the total deviation proportion as the weight of the wind tower.

[0160] In one embodiment, the correction module 14 is configured to include:

[0161] The wind tower closest to the target point in the wind area to be measured is determined as the target wind tower, and the correction coefficient is used to correct the measured data of the target wind tower to obtain the annual wind speed data of the target point in the wind area to be measured.

[0162] It should be noted that the offshore wind farm wind resource assessment device in the embodiment of the present invention has the same beneficial effects as the offshore wind farm wind resource assessment method provided in the above embodiment, and for the specific introduction of the offshore wind farm wind resource assessment method involved in the embodiment of the present invention, please refer to the above embodiment, and this application will not go into details here.

[0163] The offshore wind farm wind resource assessment device mentioned above is described from the perspective of functional modules. Furthermore, the present invention also provides an electronic device, which is described from the perspective of hardware. Figure 6 A structural diagram of an electronic device provided in an embodiment of the present application, such as Figure 6 As shown, the electronic equipment includes:

[0164] A memory 20, for storing computer programs;

[0165] The processor 21 is used to implement the steps of the offshore wind farm wind resource assessment method of the above embodiment when executing the computer program.

[0166] The electronic device provided in this embodiment may include but is not limited to a smart phone, a tablet computer, a laptop computer or a desktop computer.

[0167] Among them, the processor 21 may include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor 21 can be implemented in at least one hardware form of DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), and PLA (Programmable Logic Array). The processor 21 may also include a main processor and a coprocessor. The main processor is a processor for processing data in the awake state, also known as a CPU (Central Processing Unit); the coprocessor is a low-power processor for processing data in the standby state. In some embodiments, the processor 21 may be integrated with a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content to be displayed on the display screen. In some embodiments, the processor 21 may also include an AI (Artificial Intelligence) processor, which is used to process computing operations related to machine learning.

[0168] The memory 20 may include one or more computer-readable storage media, which may be non-transitory. The memory 20 may also include a high-speed random access memory, and a non-volatile memory, such as one or more disk storage devices, flash memory storage devices. In some embodiments, the memory 20 may be an internal storage unit of an electronic device, such as a hard disk of a server. In other embodiments, the memory 20 may also be an external storage device of an electronic device, such as a plug-in hard disk equipped on a server, a smart memory card (Smart Media Card, SMC), a secure digital (SecureDigital, SD) card, a flash card (Flash Card), etc. Further, the memory 20 may also include both an internal storage unit of an electronic device and an external storage device. The memory 20 may not only be used to store application software and various types of data installed in the electronic device, such as: the code of the program in the process of executing the offshore wind farm wind resource assessment method, but also be used to temporarily store data that has been output or is to be output. In this embodiment, the memory 20 is at least used to store the following computer program 201, wherein, after the computer program is loaded and executed by the processor 21, the relevant steps of the offshore wind farm wind resource assessment method disclosed in any of the aforementioned embodiments can be implemented. In addition, the resources stored in the memory 20 may also include an operating system 202 and data 203, etc., and the storage method may be temporary storage or permanent storage. The operating system 202 may include Windows, Unix, Linux, etc. The data 203 may include but is not limited to (data corresponding to the wind resource assessment results of the offshore wind farm), etc.

[0169] In some embodiments, the electronic device may further include a display screen 22, an input / output interface 23, a communication interface 24, a power supply 25, and a communication bus 26. Among them, the display screen 22 and the input / output interface 23, such as a keyboard, belong to the user interface, and the optional user interface may also include a standard wired interface, a wireless interface, and the like. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, and an OLED (Organic Light-Emitting Diode) touch device, and the like. The display may also be appropriately referred to as a display screen or a display unit, which is used to display information processed in the electronic device and to display a visual user interface. The communication interface 24 may optionally include a wired interface and / or a wireless interface, such as a WI-FI interface, a Bluetooth interface, and the like, which are generally used to establish a communication connection between the electronic device and other electronic devices. The communication bus 26 may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, and the like. The bus may be divided into an address bus, a data bus, a control bus, and the like. For ease of representation, Figure 6 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0170] Those skilled in the art will understand that Figure 6 The structure shown in the figure does not constitute a limitation on the electronic device, and may include more or fewer components than shown in the figure.

[0171] It is understandable that if the offshore wind farm wind resource assessment method in the above embodiment is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium to execute all or part of the steps of each embodiment method of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), electrically erasable programmable ROM, register, hard disk, removable disk, CD-ROM, magnetic disk or optical disk and other media that can store program code.

[0172] Based on this, Figure 7As shown, an embodiment of the present invention further provides a computer-readable storage medium, on which a computer program 31 is stored. When the computer program 31 is executed by a processor, the steps of the offshore wind farm wind resource assessment method as described above are implemented.

[0173] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0174] It should also be noted that, in this specification, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "comprise", "include" or any other variants thereof are intended to cover non-exclusive inclusion, so that the process, method, article or equipment including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or equipment. In the absence of further restrictions, the elements defined by the statement "comprise a ..." do not exclude the presence of other identical elements in the process, method, article or equipment including the elements.

[0175] The above description of the disclosed embodiments enables one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for evaluating wind resources in an offshore wind farm, characterized in that: include: Obtaining the measured data of wind towers of each wind tower within a preset range around the wind area to be measured; Using each group of the wind tower measured data, respectively, to predict the wind resources of the target points in the wind area to be measured, and obtain the first predicted average wind speed corresponding to each of the wind tower measured data; Determining a wind speed correction coefficient for each target point according to each of the first predicted average wind speeds; A target wind tower is determined from each of the wind towers, and the wind tower measured data of the target wind tower is corrected by using the correction coefficient to obtain the annual wind speed data of the target point in the wind area to be measured.

2. The offshore wind farm wind resource assessment method according to claim 1, characterized in that: The method of using each group of measured data of the wind tower to respectively predict wind resources for target points in the wind area to be measured to obtain a first predicted average wind speed corresponding to each measured data of the wind tower comprises: For each group of wind tower measured data, an average wind speed of the wind tower at a preset hub height of the corresponding wind tower is obtained according to the wind tower measured data; Acquire the mesoscale data of the wind tower and the mesoscale data of the wind area to be measured; A first predicted average wind speed of a target point in the wind area to be measured at the preset hub height is determined according to the average measured wind speed of the wind measuring tower, the mesoscale data of the wind measuring tower and the mesoscale data of the wind area to be measured.

3. The offshore wind farm wind resource assessment method according to claim 2, characterized in that: Determining the wind speed correction coefficient of the target point according to each of the first predicted average wind speeds includes: Determine the measured average wind speed at the target point according to each of the first predicted average wind speeds; Obtaining an average wind speed of the target wind tower at a preset hub height; The ratio of the measured average wind speed at the target point to the average wind speed of the target wind tower at a preset hub height is determined as the wind speed correction coefficient of the target point.

4. The offshore wind farm wind resource assessment method according to claim 3, characterized in that: The step of obtaining the measured data of wind towers of each wind tower within a preset range around the wind area to be measured includes: Detect whether there is a wind tower within a first preset range around the wind area to be measured, and if so, obtain the wind tower measured data of each wind tower within the first prediction range; If not, detect whether there is a wind measuring tower within a second preset range around the wind area to be measured. If so, obtain the actual measured data of the wind measuring towers of each wind measuring tower within the second prediction range, wherein the distance between the first preset range and the wind area to be measured is smaller than the distance between the second preset range and the wind area to be measured.

5. The offshore wind farm wind resource assessment method according to claim 4, characterized in that: The target point is the center point of the wind area to be measured, and the first preset range is a range within a first distance from the center point of the wind area to be measured; Then, when there is a wind tower within the first preset range, determining the measured average wind speed at the target point according to each of the first predicted average wind speeds includes: The average wind speed of each of the first predicted average wind speeds is used as the measured average wind speed at the central point of the wind area to be measured.

6. The offshore wind farm wind resource assessment method according to claim 4, characterized in that: The target point is the center point of the wind area to be measured, and the second preset range is a range between a first distance and a second distance from the center point of the wind area to be measured; the first distance is smaller than the second distance; Then, when there is no wind tower within the first preset range and there are multiple wind towers within the second preset range, determining the measured average wind speed at the target point according to each of the first predicted average wind speeds includes: Obtaining the weight of each of the wind towers; For each of the first predicted average wind speeds, multiplying the first predicted average wind speed by the weight of the corresponding wind tower to obtain a corrected wind speed; The corrected wind speeds are summed to obtain the measured average wind speed at the target point.

7. The offshore wind farm wind resource assessment method according to claim 6, characterized in that: The obtaining of the weight of each wind tower comprises: The weight of each wind tower is determined according to the wind tower measured data corresponding to each wind tower.

8. The offshore wind farm wind resource assessment method according to claim 7, characterized in that: Determining the weight of each wind tower according to the wind tower measured data corresponding to each wind tower includes: For each of the wind towers, the wind speed of other wind towers is estimated by using the wind tower measured data of the wind tower, so as to obtain the estimated wind speed of other wind towers estimated by the wind tower; For each of the estimated wind speeds, based on the wind speed actually measured by the wind tower of the wind tower and the estimated wind speed, determine the deviation rate of the wind speed estimated by the wind tower from the estimated wind speeds of other wind towers; Sum the deviation rates of the wind speed estimated by the wind measuring tower from other wind measuring towers, and combine the total number of other wind measuring towers to obtain a first average deviation rate corresponding to the wind measuring tower; Sum the first average deviation rates corresponding to each of the wind measurement towers to obtain a total average deviation rate; For each of the wind towers, according to the first average deviation rate of the wind tower and the total average deviation rate, a deviation ratio corresponding to the wind tower is obtained; Sum the deviation proportions corresponding to each of the wind measurement towers to obtain a total deviation proportion; For each of the wind towers, a ratio of the deviation proportion of the wind tower to the total deviation proportion is used as the weight of the wind tower.

9. The offshore wind farm wind resource assessment method according to any one of claims 1 to 8, characterized in that: The step of determining a target wind tower from each of the wind towers comprises: A wind measuring tower that is closest to the target point in the wind measuring area among the wind measuring towers is determined as a target wind measuring tower.

10. A wind resource assessment device for an offshore wind farm, characterized in that: include: An acquisition module is used to acquire the measured data of wind towers of each wind tower within a preset range around the wind area to be measured; A prediction module, used to use each group of measured data of the wind tower to predict the wind resources of the target points in the wind area to be measured, and obtain a first predicted average wind speed corresponding to each measured data of the wind tower; A determination module, used to determine the wind speed correction coefficient of the target point according to each of the first predicted average wind speeds; The correction module is used to determine a target wind tower from each of the wind towers, and use the correction coefficient to correct the wind tower measured data of the target wind tower to obtain the annual wind speed data of the target point in the wind area to be measured.

11. An electronic device, characterized in that: include: Memory for storing computer programs; A processor is used to implement the steps of the offshore wind farm wind resource assessment method as claimed in any one of claims 1 to 9 when executing the computer program.

12. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the offshore wind farm wind resource assessment method according to any one of claims 1 to 9 are implemented.

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