Method and system for obtaining parameters of a site for an offshore wind farm
By employing an optimization method to select representative sampling points in offshore wind farms, and combining static pressure sampling and Kriging, the problems of unreasonable sampling point distribution and inaccurate soil strength calculation were solved, resulting in more accurate site parameter assessment and reduced construction costs.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- SHANGHAI JIAOTONG UNIV
- Filing Date
- 2023-12-13
- Publication Date
- 2026-06-23
AI Technical Summary
Existing technologies are not sufficiently efficient in terms of the number and distribution of sampling points during offshore wind farm surveys, resulting in large deviations in test data. Traditional sampling methods cause significant soil disturbance, and the calculation of the undrained shear strength Su of the soil is not accurate enough, affecting the reliability and cost of wind farm construction.
Representative sampling points were selected using an optimization method. Low-disturbance in-situ samples were obtained through static pressure sampling and advanced geotechnical tests. Combined with static cone penetration tests and Kriging, the interpretation parameters were extended to all wind turbine locations to obtain more accurate site parameters.
It improves the accuracy of offshore wind farm site parameter assessment, reduces the risk of foundation settlement and overturning, lowers construction and maintenance costs, and improves construction quality and efficiency.
Smart Images
Figure CN117744208B_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the fields of engineering survey and marine engineering, and more specifically, to a method and system for obtaining site parameters of offshore wind farms. Background Technology
[0002] Marine geotechnical investigation, a crucial component of offshore wind power construction, differs from traditional onshore engineering investigation. Due to limitations in domestic investigation technology, marine geotechnical investigation yields soil samples with higher levels of disturbance and incurs higher costs. Since my country launched its offshore wind power construction in 2009, domestic offshore wind power geotechnical engineering investigations have widely adopted extensive investigation methods such as drilling.
[0003] In current engineering practice, firstly, the number and distribution of sampling points are often unreasonable and lack representativeness. For example, the sampling process may be affected by geological heterogeneity, which can lead to significant deviations in test data. Secondly, traditional sampling methods often employ the heavy-hammer, low-impact sampling method, which causes significant disturbance to the in-situ soil, resulting in considerable uncertainty in the collected site data. Furthermore, traditional geotechnical testing methods are often not precise enough.
[0004] Undrained shear strength S of soil u It is an important mechanical property of cohesive soil, referring to the ultimate ability of soil to resist shear failure under a certain stress state. The undrained shear strength S of soil u Undrained shear strength cannot be directly measured by CPT tests, but can be obtained through empirical correlation. Calibration is required through indoor geotechnical tests such as direct shear or triaxial compression. However, since the parameters in the undrained shear strength calculation formula usually change with site variations, it is necessary to make corrections based on different geographical conditions to obtain accurate undrained shear strength. In existing studies, generally only one point is taken for each wind turbine location, and the undrained shear strength S of the soil is obtained by combining conventional empirical formulas. u Using this method to calibrate the interpretation parameters of all points results in unreliable results.
[0005] A search revealed no reports that are identical or similar to the subject matter of this invention. Summary of the Invention
[0006] The purpose of this invention is to provide a method and system for obtaining site parameters of offshore wind farms. By obtaining representative sampling points, static cone penetration data and soil strength interpretation parameters can be obtained, which can effectively improve the accuracy of site parameter prediction and evaluation.
[0007] A first aspect of the present invention provides a method for obtaining site parameters of an offshore wind farm, comprising:
[0008] The distribution and number of wind turbine locations in the overall wind farm are planned, and representative sampling points are selected using optimization methods;
[0009] Static pressure sampling was performed at the representative sampling points to obtain low-disturbance in-situ samples.
[0010] Static cone penetration tests were conducted on all planned wind turbine locations to obtain static cone penetration data for all locations.
[0011] The soil strength interpretation parameters of the representative sampling points were obtained by testing the low-disturbance in-situ samples.
[0012] Using the Kriging method, the interpretation parameters of a limited number of representative sampling points are extended to all wind turbine locations, thereby interpreting the static cone penetration test data and obtaining the site parameters for all wind turbine locations.
[0013] Optionally, the planning of the distribution and number of wind turbine locations in the overall wind farm, and the selection of representative sampling points using an optimization method, includes:
[0014] The number and distribution of wind turbine locations across the entire site are planned, and one static penetration test borehole is installed at each wind turbine location.
[0015] The optimization method is used to select representative sampling points. An optimization problem is constructed with the goal of selecting several representative points from all wind turbine locations so that the sum of the "influence" of these points on other locations is maximized.
[0016] Optionally, the step of selecting representative sampling points using an optimization method, implemented using the K-means clustering algorithm in combinatorial optimization, includes:
[0017] Define the distance function as Euclidean distance;
[0018] n points are selected from all fan locations as static pressure sampling points for thin-walled tubes. These sampling points are the initial cluster centers, i.e., cluster centers.
[0019] Calculate the Euclidean distance from each wind turbine location to the initial cluster center;
[0020] Based on the Euclidean distance calculated for each wind turbine location, each wind turbine location is assigned to the class corresponding to the cluster center closest to it according to the criterion of minimum distance, and the global extreme value is calculated.
[0021] The distance to the group is recalculated with each wind turbine location in each group as a candidate cluster center, and the candidate cluster center corresponding to the minimum total distance of each group is taken as the new generation cluster center.
[0022] Repeat the above clustering process until the cluster centers no longer change or the maximum number of iterations is reached;
[0023] Find a set containing n cluster centers such that the sum of the distances from these n cluster centers to all other wind turbine locations is minimized. These n cluster centers are the locations of the selected n sampling points.
[0024] Optionally, the precise testing of the low-disturbance in-situ samples to obtain soil strength interpretation parameters at representative sampling points includes:
[0025] Prepare soil samples for testing using low-disturbance samples, and use advanced geotechnical tests to determine key soil strength benchmark values.
[0026] By verifying the static cone penetration data from the corresponding location, the interpretation parameter N is obtained. kt N kt =10.5-4.6ln(B) q +0.1); where B q This refers to the pore water pressure parameter.
[0027] Optionally, the determination of key soil strength benchmark values using advanced geotechnical testing includes:
[0028] The undrained shear strength S was obtained from advanced geotechnical tests. u Using the undrained shear strength as the benchmark value, compare N... kt The calibration is performed to obtain the interpretation parameters N. kt ;
[0029] By interpreting parameter N kt Correcting static cone penetration test data to predict the continuous undrained shear strength S on the regional stratigraphic profile. u The undrained shear strength S of the soil samples from the entire site was obtained. u .
[0030] Optionally, the use of Kriging to extend the interpretation parameters of a finite number of representative sampling points to all wind turbine locations includes:
[0031] The interpretation parameters of representative points were analyzed and processed using the Kriging method to obtain the numerical values of the soil strength interpretation parameters of all wind turbine locations in the entire site.
[0032] Based on the distribution of the interpretation parameters and the static cone penetration test data, the undrained shear strength S of the soil samples throughout the site is interpreted. u .
[0033] A second aspect of the present invention provides a system for acquiring site parameters of an offshore wind farm, comprising:
[0034] Representative sampling point determination unit: Plan the distribution and number of wind turbine locations in the overall wind farm, and select representative sampling points using optimization methods;
[0035] Static pressure sampling unit: Performs static pressure sampling at the representative sampling points to obtain low-disturbance in-situ samples;
[0036] Static cone penetration test unit: Perform static cone penetration tests on all planned wind turbine locations and obtain static cone penetration data for all locations;
[0037] Soil strength interpretation parameter determination unit: Tests the low-disturbance in-situ sample to obtain the soil strength interpretation parameters of the representative sampling point;
[0038] Site parameter determination unit: Using the Kriging method, the interpretation parameters of a limited number of representative sampling points are extended to all wind turbine locations, thereby interpreting the static cone penetration test data and obtaining the site parameters of all wind turbine locations.
[0039] Compared with the prior art, the present invention has at least one of the following beneficial effects:
[0040] The method and system for obtaining offshore wind farm site parameters provided in this invention, by acquiring representative sampling points, can obtain static cone penetration test data and soil strength interpretation parameters, thereby obtaining more accurate seabed geological data and improving the accuracy of parameter assessment for wind farm construction sites. This method can reduce problems caused by inaccurate geological data, such as foundation settlement and overturning, thus reducing the construction and maintenance costs of wind farms.
[0041] The method and system for obtaining offshore wind farm site parameters provided in this invention are applicable and economical. Sampling from sampling points determined by clustering methods can improve sampling and testing efficiency, shorten the construction cycle, reduce unnecessary waste and repetitive work, thereby reducing the construction cost of wind farms and ultimately achieving the goal of improving the quality and economy of wind farm construction. For other marine engineering projects, the data can be recalibrated based on the results of on-site borehole laboratory tests and then applied to the static cone penetration test (CPT) interpretation of soil sample strength to improve site parameters. Attached Figure Description
[0042] Other features, objects, and advantages of the present invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings:
[0043] Figure 1 This is a flowchart of a method for obtaining offshore wind farm site parameters according to an embodiment of the present invention;
[0044] Figure 2 This is a schematic diagram of an in-situ static cone penetration test in a preferred embodiment of the present invention;
[0045] Figure 3This is a flowchart illustrating the selection of static pressure sampling points using the K-means clustering algorithm in a preferred embodiment of the present invention. Detailed Implementation
[0046] The present invention will now be described in detail with reference to specific embodiments. These embodiments will help those skilled in the art to further understand the present invention, but do not limit the invention in any way. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention. These all fall within the scope of protection of the present invention.
[0047] Currently, in-situ testing methods such as static cone penetration test (CPT), thin-walled sampling tube static pressure sampling technology, and optimization methods are gradually being widely applied in marine geotechnical investigation. In addition, in existing technologies, generally only one point is taken at each wind turbine location, and the undrained shear strength S of the soil is obtained using conventional empirical formulas. u However, using this method to calibrate the interpretation parameters of all points is not reliable enough. To improve the reliability of the assessment of offshore wind farm site parameters, this invention has studied this issue and provides a method for obtaining offshore wind farm site parameters. This method involves selecting representative points for static pressure sampling to obtain soil samples from the site using an optimization method. Advanced indoor geotechnical tests are then conducted to obtain interpretation parameters more suitable for the site. The site parameters for all wind turbine locations are obtained using the Kriging method, allowing for parameter adjustments based on spatial variations. This method allows for obtaining more reliable parameters with fewer sampling attempts.
[0048] Reference Figure 1 The diagram shown is a flowchart of a method according to an embodiment of the present invention. Specifically, the method for obtaining offshore wind farm site parameters provided in this embodiment includes the following steps S100 to S500:
[0049] S100 plans the distribution and number of wind turbine locations in the overall wind farm and selects representative sampling points using an optimization method.
[0050] In this step, to better improve the final effect, in some embodiments, the number and distribution of wind turbine locations across the entire site are planned, and one static cone penetration test (CPT) borehole is arranged at each turbine location. Furthermore, to obtain more accurate seabed geological data and improve the accuracy of parameter assessment for the wind farm construction site, an optimization method is used to select representative sampling points. Specifically, an optimization problem is constructed with the goal of selecting several representative points from all turbine locations such that the sum of the "influence" of these points on other points is maximized. The sampling points of the representative points can be located at a certain distance from the corresponding turbine location's CPT borehole; this distance is selected based on the actual conditions of the offshore wind farm.
[0051] To achieve the required representative sampling points and improve the efficiency of sampling and testing, in some embodiments, an optimization method is used to select representative sampling points, which is implemented using the K-means clustering algorithm in combinatorial optimization.
[0052] Specifically, including:
[0053] S101, define the distance function as Euclidean distance;
[0054] S102, select n points from all fan locations as static pressure sampling points for thin-walled tubes. These sampling points are the initial cluster centers, i.e., cluster centers.
[0055] S103, Calculate the Euclidean distance from each wind turbine location to the initial cluster center;
[0056] S104. Based on the Euclidean distance calculated for each wind turbine location, each wind turbine location is assigned to the class corresponding to the cluster center closest to it according to the criterion of minimum distance, and the global extreme value is calculated.
[0057] S105, recalculate the distance of the group with each wind turbine position in each group as the candidate cluster center, and take the candidate cluster center corresponding to the minimum total distance of each group as the new generation cluster center;
[0058] S106, repeat the clustering process of S104-S105 above until the cluster centers no longer change or the maximum number of iterations is reached;
[0059] S107, find a set containing n cluster centers such that the sum of the distances from these n cluster centers to the locations of all other wind turbines is minimized. These n cluster centers are the locations of the selected n sampling points.
[0060] The above methods can obtain representative sampling points, overcoming the problems that the number and distribution of sampling points in existing technologies are often unreasonable and lack representativeness, and may be affected by geological heterogeneity during the sampling process, which can lead to large deviations in test data.
[0061] S200, static pressure sampling is performed at representative sampling points to obtain low-disturbance in-situ samples;
[0062] In this step, for the selected representative sampling points, low-disturbance static pressure sampling technology is employed. Static pressure sampling is performed using thin-walled sampling tubes to obtain low-disturbance in-situ samples. Traditional sampling methods often use the heavy-weight, low-impact method, which causes significant disturbance to the in-situ soil, resulting in considerable uncertainty in the collected site data. The static pressure sampling method used in this step avoids these problems and effectively improves the reliability of the collected site data.
[0063] S300 performs static cone penetration tests on all planned wind turbine locations to obtain static cone penetration data for all locations;
[0064] In this step, in-situ static cone penetration tests are used to acquire static cone penetration data for all locations. In one embodiment, the following steps can be followed:
[0065] S301: Place the probe of the static cone penetrometer on the test point, apply vertical pressure, and press the probe into the soil sample at a uniform speed. Record the strain gauge data in real time during the penetration process.
[0066] S302, the obtained test data is processed to obtain the cone tip resistance q. c pore water pressure u2, sidewall friction f s A curve of penetration resistance as a function of depth was plotted to obtain static cone penetration data for all locations.
[0067] The static cone penetration test equipment can use existing technology. Other test operations not detailed in the description can also refer to the existing static cone penetration test operation, and are not limited here.
[0068] S400 tests low-disturbance in-situ samples to obtain soil strength interpretation parameters at representative sampling points;
[0069] Based on the above-mentioned low-disturbance in-situ samples, precise testing is conducted to obtain soil strength interpretation parameters for representative sampling points, which may include:
[0070] S401 involves preparing low-disturbance samples into soil samples for testing, and using advanced geotechnical tests to determine key soil strength benchmark values.
[0071] S402, using the static cone penetration data from the corresponding location for verification, obtain the interpretation parameter N. kt N kt =10.5-4.6ln(B) q +0.1); where B q This refers to the pore water pressure parameter.
[0072] Undrained shear strength S of soil u It is an important mechanical property of cohesive soil, and as an interpretable parameter for offshore wind farm site parameters, it depends to some extent on the undrained shear strength S of the cohesive soil. u Therefore, advanced geotechnical testing is required to calibrate the undrained shear strength based on high-quality (low-disturbance) clay samples. Furthermore, since the parameters in the undrained shear strength calculation formula typically change with site variations, it is necessary to make corrections based on different geographical conditions to obtain accurate undrained shear strength.
[0073] In some embodiments, determining key soil strength benchmark values using advanced geotechnical tests can be performed by following these steps: obtaining the undrained shear strength S from the advanced geotechnical tests. u Using the undrained shear strength as the benchmark value, compare N... kt The calibration is performed to obtain the interpretation parameters N. kt By interpreting parameter N kt Correcting static cone penetration test data to predict the continuous undrained shear strength S on the regional stratigraphic profile. u This step allows for the calculation of corrected undrained shear strength based on different geographical location conditions, resulting in an accurate undrained shear strength.
[0074] In the above embodiments, the soil mechanical properties of different soil layers in the sea area obtained by experiment can be obtained by existing experiments, such as triaxial compression. The specific experiment can be determined and selected according to the mechanical property parameters to be obtained.
[0075] S500 uses the Kriging method to extend the interpretation parameters of a limited number of representative sampling points to all wind turbine locations, thereby interpreting the static cone penetration test data and obtaining the site parameters for all wind turbine locations.
[0076] Specifically, this step utilizes the Kriging method to extend the interpretation parameters of a finite number of representative sampling points to all wind turbine locations, which may include:
[0077] S501, using the Kriging method to analyze and process the interpretation parameters of representative points, the numerical values of the soil strength interpretation parameters of all wind turbine locations in the entire site are obtained.
[0078] S502, Based on the values of the interpretation parameters and the static cone penetration test data, interpret the undrained shear strength S of the soil samples from the entire site. u This allows for the optimization of the overall parameters of the offshore wind farm site, specifically the undrained shear strength S of the soil samples from the entire site. u .
[0079] Better still, in a preferred embodiment, the analysis and processing of interpretation parameters at representative points using the Kriging method to obtain numerical values of soil strength interpretation parameters for all wind turbine locations across the entire site includes:
[0080] S5011, Establish the wind farm area boundaries and calculate the interpretation parameters N for n representative sampling points. kt The initial data is formed, which includes the regionalized variable Z(x), and the known data are Z(x1), Z(x2), ..., Z(x...). n );
[0081] S5012, gridded offshore wind farm area, analysis and interpretation of parameter Nkt The spatial distribution characteristics of the values;
[0082] S5013, interprets the parameters N of representative points. kt As a regionalization variable, a semivariance model was chosen, and kriging was used for spatial interpolation to calculate the kriging difference at the unknown point x0. The result is Z. ※ (x0) is a known sampling point Z(x i The weighted sum of ), i = 1, 2, ..., n;
[0083] S5014, Plot the field interpretation parameters N kt The contour map is used, and cross-validation is performed using the known data. This involves removing one or more measured sample data points at a time and then using data from other locations to predict related data. This process is repeated, and finally, statistical regression analysis is performed on the actual and estimated values for each data point.
[0084] S5015, based on the results of statistical regression analysis, obtain the accuracy evaluation of the semivariogram model, estimate the error and reliability of the interpolation results, and obtain the numerical values of the soil strength interpretation parameters of all wind turbine locations in the entire site.
[0085] The method for obtaining offshore wind farm site parameters in the above embodiments of the present invention is based on finite static pressure sampling and precise testing technology. It is simple and reliable to operate, and can effectively improve the accuracy of site parameter prediction and evaluation. The undrained shear strength S of the soil sample throughout the site is obtained by interpreting the parameters. u This allows for the determination of more reasonable construction plans and material selection, improving construction efficiency and quality, shortening the construction cycle, thereby reducing the construction cost of wind farms and reducing potential risks and uncertainties in engineering design and construction in areas such as offshore wind power construction.
[0086] To better understand the present invention, a preferred embodiment is provided below. Specifically, the method for obtaining offshore wind farm site parameters in this embodiment includes the following detailed steps:
[0087] S1, to carry out necessary preliminary treatment of the offshore wind farm site to ensure the operability and rationality of the survey and sampling process;
[0088] S2, plan the number and distribution of wind turbine locations throughout the site, and arrange one static cone penetration test (CPT) borehole at each wind turbine location;
[0089] S3. Construct an optimization problem with the goal of selecting several representative points from all wind turbine locations to maximize the sum of the "influence" of these points on other locations. The sampling point of the representative point is about 5m away from the CPT hole of the corresponding turbine location.
[0090] Reference Figure 3As shown, this step uses the K-means clustering algorithm from combinatorial optimization to solve the problem. The following are the steps implemented in this embodiment:
[0091] (1) Define the distance function as the Euclidean distance, which is the straight-line distance between two points;
[0092] (2) Select n points from all fan locations as static pressure sampling points for thin-walled tubes, and use them as initial cluster centers, i.e., cluster centers;
[0093] (3) Calculate the Euclidean distance from each fan location to the cluster center (sampling point);
[0094] (4) Calculate the distance based on each wind turbine location, and assign each wind turbine location to the class corresponding to the cluster center (sampling point) closest to them according to the criterion of minimum distance, and calculate the global extreme value.
[0095] (5) Recalculate the distance of the group with each wind turbine position in each group as the candidate cluster center (candidate sampling point), and take the candidate cluster center corresponding to the minimum total distance of each group as the new generation cluster center (sampling point).
[0096] (6) Repeat steps (4) and (5) until the cluster center (sampling point) no longer changes or the maximum number of iterations is reached;
[0097] (7) Find a set containing n cluster centers such that the sum of the distances from these n cluster centers to the other wind turbine locations is minimized;
[0098] (8) These n cluster centers are the locations of the selected n sampling points, and the sum of their distances to other sampling points will be the minimum.
[0099] Through the above steps, this embodiment can obtain relatively uniformly distributed and representative sampling points, providing a prerequisite for improving data accuracy and sampling effect in the future.
[0100] S4. For the selected representative sampling points, low-disturbance static pressure sampling technology is used to take static pressure samples through thin-walled sampling tubes and seal them with wax before transporting them back to the indoor laboratory; at the same time, in-situ CPT technology is used to conduct static penetration tests on all fan locations.
[0101] Reference Figure 2 The diagram shown is a schematic diagram of the in-situ static cone penetration test in this preferred embodiment. In this embodiment, the method is applied in practice using 100 conventional offshore wind farm sites as examples. An in-situ static cone penetration test is carried out at each wind turbine site, and a schematic diagram of selecting a point for static pressure sampling of thin-walled tubes is shown.
[0102] In this step, CPT, or in-situ static cone penetration test, is a method for testing the mechanical properties of soil layers in situ. The following are the basic steps for accurately testing the mechanical properties of soil samples using in-situ CPT testing in this embodiment:
[0103] (1) Prepare static cone penetration testing equipment, including cone probe, cone rod and measuring instruments, etc. The cone angle of the cone probe is 60°, and the measuring instruments are strain gauges and matching acquisition equipment.
[0104] (2) Place the probe on the test point and apply a certain vertical pressure so that the probe is pressed into the soil sample at a uniform speed. During the penetration process, record the strain gauge data in real time.
[0105] (3) The data recorded by the measuring instrument is processed to obtain the cone tip resistance q. c pore water pressure u2, sidewall friction f s A curve showing the change in penetration resistance with depth was plotted.
[0106] S5. Appropriately process the obtained low-disturbance samples to prepare the soil samples required for the test. Conduct advanced geotechnical tests to determine the key soil strength benchmark values, and use the corresponding CPT data from the corresponding location for calibration to obtain accurate interpretation parameters N. kt =10.5-4.6ln(B) q +0.1);
[0107] The advanced geotechnical tests in step S5, namely the indoor triaxial UU, consolidated rapid shear (CQ), and triaxial CU tests, are commonly used methods for testing the mechanical properties of soil samples. The following is the basic content of using advanced geotechnical tests to accurately test the mechanical properties of soil samples:
[0108] (1) Based on the results of indoor triaxial unconsolidated undrained UU, consolidated fast shear CQ, and triaxial consolidated undrained CU tests, the soil mechanical properties of different soil layers in the sea area were obtained.
[0109] (2) S obtained through experimental results u For the reference value N kt The calibration is performed to obtain the interpretation parameters N. kt ;
[0110] (3) By interpreting parameter N kt Correcting CPT data to predict the continuous undrained shear strength S on the stratigraphic profile in this region. u .
[0111] S6, using the Kriging method to analyze N at representative points. kt Analysis and processing were performed to provide the strength interpretation parameters N for soil samples from all wind turbine locations across the entire site. ktThe numerical value, combined with CPT test data, can effectively interpret the undrained shear strength S of the soil samples throughout the site. u This improves the accuracy of predictions and assessments;
[0112] In step S6, the Kriging method considers the positional relationship between sampling points and non-sampling points, as well as the relative positional relationship between wind turbine locations. By analyzing the spatial correlation between sampling points, the Kriging method can more accurately predict the geological parameters of non-sampling points, i.e., the soil sample strength interpretation parameter N. kt This method considers not only the distance between data points but also their spatial relationships, thereby improving the accuracy and reliability of predictions.
[0113] In one embodiment, the Kriging method is used to analyze the N of representative points. kt The basic steps for analysis and processing include:
[0114] (1) Establish the wind farm area and calculate the interpretation parameters N for n representative sampling points. kt This forms the initial data, namely the regionalized variable Z(x), with known data being Z(x1), Z(x2), ..., Z(x... n );
[0115] (2) Gridded offshore wind farm area, analysis of N kt The spatial distribution characteristics of the values;
[0116] (3) N of the representative points kt As a regionalization variable, a suitable semivariogram model is selected, and ordinary kriging is used for spatial interpolation to calculate the kriging difference at the unknown point x0. The result is Z. ※ (x0) is a known sampling point Z(x i The weighted sum of (i = 1, 2, ..., n), i.e.
[0117] (4) Plot the field interpretation parameters N kt The contour map is used, and cross-validation is performed using known data. This involves removing one or more measured samples at a time and then using data from other locations to predict related data. This process is repeated, and finally, statistical regression analysis is performed on the actual and estimated values for each data point.
[0118] (5) Obtain the accuracy evaluation of the semivariogram model, estimate the error and reliability of the interpolation results, and obtain the numerical values of the strength interpretation parameters of soil samples at all wind turbine locations in the entire site.
[0119] The site parameters obtained from steps S1-S6 above can be applied to fields such as offshore wind power construction to guide engineering design and construction processes and reduce potential risks and uncertainties.
[0120] Based on the same technical concept described above, another embodiment of the present invention also provides a system for obtaining site parameters of an offshore wind farm, comprising:
[0121] Representative sampling point determination unit: Plan the distribution and number of wind turbine locations in the overall wind farm, and select representative sampling points using optimization methods;
[0122] Static pressure sampling unit: Performs static pressure sampling at the representative sampling points to obtain low-disturbance in-situ samples;
[0123] Static cone penetration test unit: Perform static cone penetration tests on all planned wind turbine locations and obtain static cone penetration data for all locations;
[0124] Soil strength interpretation parameter determination unit: Tests the low-disturbance in-situ sample to obtain the soil strength interpretation parameters of the representative sampling point;
[0125] Site parameter determination unit: Using the Kriging method, the interpretation parameters of a limited number of representative sampling points are extended to all wind turbine locations, thereby interpreting the static cone penetration test data and obtaining the site parameters of all wind turbine locations.
[0126] Each unit in this system embodiment corresponds to each step in the above-described method embodiment for obtaining offshore wind farm site parameters. The specific implementation techniques can be found by referring to the implementation of each step in the method embodiment for obtaining offshore wind farm site parameters, and will not be repeated here.
[0127] In the above embodiments of the present invention, by acquiring more accurate geological data and optimizing overall site parameters, problems encountered during construction can be reduced, construction efficiency and quality can be improved, and site utilization can be increased, further increasing power generation revenue. By improving the accuracy and rationality of geological data, the construction and maintenance costs of offshore wind farms can be reduced, thereby bringing economic benefits and better adapting to market demands and economic development needs. The implementation of the present invention can bring innovative technological means, providing better technical support and guarantees for future offshore wind farm construction.
[0128] Specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the specific embodiments described above, and those skilled in the art can make various modifications or variations within the scope of the claims, which do not affect the essence of the present invention. The above preferred features can be used in any combination without conflict.
Claims
1. A method for obtaining site parameters of an offshore wind farm, characterized in that, include: The distribution and number of wind turbine locations in the overall wind farm are planned, and representative sampling points are selected using optimization methods; Static pressure sampling was performed at the representative sampling points to obtain low-disturbance in-situ samples. Static cone penetration tests were conducted on all planned wind turbine locations to obtain static cone penetration data for all locations. The soil strength interpretation parameters of the representative sampling points were obtained by testing the low-disturbance in-situ samples. Using the Kriging method, the interpretation parameters of a limited number of representative sampling points are extended to all wind turbine locations, thereby interpreting the static cone penetration data and obtaining the site parameters of all wind turbine locations. The method of using kriging extends the interpretation parameters of a finite number of representative sampling points to all wind turbine locations, including: The interpretation parameters of representative points were analyzed and processed using the Kriging method to obtain the numerical values of the soil strength interpretation parameters of all wind turbine locations in the entire site. Based on the values of the interpretation parameters and the static cone penetration test data, the undrained shear strength of the soil samples from the entire site is interpreted. The undrained shear strength of the soil samples from the entire site was obtained. .
2. The method for obtaining offshore wind farm site parameters according to claim 1, characterized in that, The planning of the distribution and number of wind turbine locations in the overall wind farm, and the selection of representative sampling points using an optimization method, includes: The number and distribution of wind turbine locations across the entire site are planned, and one static penetration test borehole is installed at each wind turbine location. The optimization method is used to select representative sampling points. An optimization problem is constructed with the goal of selecting several representative points from all wind turbine locations so that the sum of the "influence" of these points on other locations is maximized.
3. The method for obtaining offshore wind farm site parameters according to claim 2, characterized in that, The selection of representative sampling points using an optimization method, implemented using the K-means clustering algorithm in combinatorial optimization, includes: Define the distance function as Euclidean distance; n points are selected from all fan locations as static pressure sampling points for thin-walled tubes. These sampling points are the initial cluster centers, i.e., cluster centers. Calculate the Euclidean distance from each wind turbine location to the initial cluster center; Based on the Euclidean distance calculated for each wind turbine location, each wind turbine location is assigned to the class corresponding to the cluster center closest to it according to the criterion of minimum distance, and the global extreme value is calculated. The distance to the group is recalculated with each wind turbine location in the group as a candidate cluster center, and the candidate cluster center corresponding to the minimum total distance of each group is taken as the new generation cluster center. Repeat the above clustering process until the cluster centers no longer change or the maximum number of iterations is reached; Find a set containing n cluster centers such that the sum of the distances from these n cluster centers to all other wind turbine locations is minimized. These n cluster centers are the locations of the selected n sampling points.
4. The method for obtaining offshore wind farm site parameters according to claim 1, characterized in that, The process of performing hydrostatic sampling at the representative sampling points to obtain low-disturbance in-situ samples includes: For the selected representative sampling points, the low-disturbance static pressure sampling technique was adopted, and low-disturbance in-situ samples were obtained by static pressure sampling through thin-walled sampling tubes.
5. The method for obtaining offshore wind farm site parameters according to claim 1, characterized in that, The static cone penetration test was conducted on all planned wind turbine locations to obtain static cone penetration data for all locations, including: Place the probe of the static cone penetrometer on the test point and apply vertical pressure to make the probe penetrate into the soil sample at a uniform speed. Record the strain gauge data in real time during the penetration process. The obtained test data is processed to obtain the cone tip resistance. pore water pressure Side wall friction A curve of penetration resistance as a function of depth was plotted to obtain static cone penetration data for all locations.
6. The method for obtaining offshore wind farm site parameters according to claim 1, characterized in that, The testing of the low-disturbance in-situ samples to obtain soil strength interpretation parameters at representative sampling points includes: Prepare soil samples for testing using low-disturbance samples, and use advanced geotechnical tests to determine key soil strength benchmark values. Interpretation parameters were obtained by verifying the static cone penetration test data from the corresponding positions. ,in, This refers to the pore water pressure parameter.
7. The method for obtaining offshore wind farm site parameters according to claim 6, characterized in that, The determination of key soil strength benchmark values using advanced geotechnical testing includes: The undrained shear strength was obtained from advanced geotechnical tests. Using the undrained shear strength as the benchmark value for... Calibration is performed to obtain the interpretation parameters. ; By interpreting parameters Correcting static cone penetration test data to predict the continuous undrained shear strength of the regional stratigraphic profile. .
8. The method for obtaining offshore wind farm site parameters according to claim 1, characterized in that, The Kriging method is used to analyze and process the interpretation parameters of representative points to obtain the numerical values of soil strength interpretation parameters for all wind turbine locations in the entire site, including: Establish the wind farm site area and calculate the interpretation parameters for n representative sampling points. This forms the initial data, which includes the regionalized variable Z(x), and the known data is Z(x). ), Z( ), ..., Z( ); Gridded offshore wind farm area, parameter analysis and interpretation The spatial distribution characteristics of the values; Interpretation parameters of representative points As a regionalization variable, a semivariance model was chosen, and Kriging was used for spatial interpolation to calculate the location of unknown points. The Kriging difference, the result is ( ), is a known sampling point Z( The weighted sum of ), i=1,2,…,n; Plotting field interpretation parameters The contour map is used to perform cross-validation with the known data, that is, one or more measured sample data are removed each time, and then the data from other locations are used to predict the data related to them; the operation is repeated, and finally the true value and the estimated value of each data point are subjected to statistical regression analysis. Based on the results of the statistical regression analysis, the accuracy evaluation of the semivariogram model is obtained, the error and reliability of the interpolation results are estimated, and the numerical values of the strength interpretation parameters of soil samples at all wind turbine locations in the entire site are obtained.
9. A system for improving the reliability of site parameter assessment for offshore wind farms, characterized in that, include: Representative sampling point determination unit: Plan the distribution and number of wind turbine locations in the overall wind farm, and select representative sampling points using optimization methods; Static pressure sampling unit: Performs static pressure sampling at the representative sampling points to obtain low-disturbance in-situ samples; Static cone penetration test unit: Perform static cone penetration tests on all planned wind turbine locations and obtain static cone penetration data for all locations; Soil strength interpretation parameter determination unit: Tests the low-disturbance in-situ sample to obtain the soil strength interpretation parameters of the representative sampling point; Site parameter determination unit: Using the kriging method, the interpretation parameters of a finite number of representative sampling points are extended to all wind turbine locations, thereby interpreting the static cone penetration test data and obtaining the site parameters for all wind turbine locations; wherein, the step of using the kriging method to extend the interpretation parameters of a finite number of representative sampling points to all wind turbine locations includes: The interpretation parameters of representative points were analyzed and processed using the Kriging method to obtain the numerical values of the soil strength interpretation parameters of all wind turbine locations in the entire site. Based on the values of the interpretation parameters and the static cone penetration test data, the undrained shear strength of the soil samples from the entire site is interpreted. The undrained shear strength of the soil samples from the entire site was obtained. .