Method for site selection of wind power generation based on ancient storm deposition background

Abstract

The application discloses a wind power generation site selection method based on ancient storm deposition background and relates to the field of power generation site selection, which comprises the following steps: setting a unified space reference, forming an input data set, performing wind source basin assimilation fusion, generating modern wind field three types of grids, and configuring a modern wind field deposition response calibration reference domain. Long-term wind direction and wind speed prior are established by using storm deposition records and direction evidence, annual uncertainty caused by only relying on short-term wind measurement is reduced, hard constraint filtering is formed by using soft sediment deformation risk coding and boundary stability marking, a penalty term is introduced into scoring, ground investigation and construction stage risks are reduced, candidate area output synchronously gives evidence chain index and uncertainty level, short-term wind measurement review, ground investigation review and deviation backwriting self-calibration iteration are performed, and finally, site selection achievement package containing superimposed graph and evidence chain list is solidified, so that site selection decision transparency and landing efficiency are improved.

Description

Technical Field

[0001] This invention relates to the field of power generation site selection, and in particular to a wind power generation site selection method based on paleostorm depositional background. Background Technology

[0002] Wind farm site selection typically revolves around wind speed, wind direction stability, wind energy density, grid connection, and transportation conditions. A wind field evaluation grid is constructed based on field wind measurements, topographic elevation, and surface roughness information. Candidate areas are delineated and ranked by overlaying constraints in a GIS environment. For topographic-water transition zones such as the periphery of lakes, the wind field is significantly affected by the effective wind distance and wave action. Extreme wind events will directly change the unit load spectrum and operation and maintenance costs. Therefore, it is necessary to quantify wind resources and engineering constraints simultaneously under a unified spatial benchmark.

[0003] However, existing site selection processes primarily rely on short-term wind measurements and modern meteorological statistics, lacking prior constraints on dominant wind direction and speed levels over longer timescales. Wind resource benefit assessments are susceptible to instability due to interannual fluctuations. Furthermore, empirical judgments are often used for two types of geological safety factors: soft sediment deformation and storm sandbar boundary stability, making it difficult to establish enforceable hard constraints. Moreover, the candidate area output stage lacks evidence chain indexes and uncertainty grading, making it difficult to write back and update model parameters with subsequent verification data, resulting in insufficient decision auditability and verifiability. Summary of the Invention

[0004] The purpose of this invention is to address the shortcomings of existing technologies by providing a wind power site selection method based on paleostorm sedimentary background. The method aims to construct a storm event sedimentary record library under a unified spatial benchmark and extract a set of directional evidence. Based on the validity threshold of directional evidence and the credibility of sedimentary records, a directional evidence credibility weight is established. Then, paleoprevailing wind direction and paleowind stability indices are calculated to form a long-term wind resource reliability prior. Furthermore, information from ancient and modern times is integrated across time scales to generate a set of parameters for future wind energy assessment. A candidate area list is output by combining geological safety constraints and comprehensive scoring rules. Evidence chain indexes and uncertainty levels are bound to the candidate area entries, enabling traceability and quantification of site selection results.

[0005] Therefore, this application provides a wind power generation site selection method based on paleostorm depositional background, including the following steps:

[0006] Step S100: Set a unified spatial reference and form an input data set, perform wind source basin assimilation and fusion, generate three types of modern wind field grids, and configure the modern wind field deposition response calibration reference domain.

[0007] Step S200: Obtain the set of outcrop profile measurement records and the set of core sampling records, determine the storm event sedimentary records, configure the storm event sedimentary record library, perform sedimentary structure interpretation, restore the paleogeographic feature set and paleowater depth variation curve, output the effective wind path partition grid and wave energy attenuation boundary, form the geological safety constraint factor, and configure the hard constraint filtering conditions for wind power generation site selection.

[0008] Step S300: Configure the directional evidence set and complete the directional evidence storage, set the directional evidence validity threshold, calculate the directional evidence credibility weight, calculate the ancient dominant wind direction based on the directional evidence credibility weight, calculate the ancient wind direction stability index, and form the stability threshold judgment result.

[0009] Step S400: Form a set of storm sediment dynamics proxy parameters, set the inverted paleowind speed mean parameters, form paleowind speed levels, configure the sedimentary tectonic wind field relationship model, perform paleowater depth-wind path coupling correction, perform cross-timescale fusion, and output a set of future wind energy assessment parameters.

[0010] Step S500: Configure hard constraint filtering, generate candidate region input set, configure comprehensive scoring rules, output preferred region boundary, output candidate region list, and bind evidence chain index and uncertainty level.

[0011] Step S600: Configure short-term wind measurement verification and foundation investigation verification, form a verification data set, calculate the verification deviation, write back and update the inversion coefficients and risk penalty terms, configure the iteration termination conditions, and solidify the final site selection result package.

[0012] In some specific embodiments, step S100 specifically includes:

[0013] Step S100.1: Set a unified spatial benchmark and form an input data set, perform wind source basin assimilation and fusion, and generate three types of modern wind field grids.

[0014] Step S100.2: Configure the modern wind field deposition response calibration reference domain.

[0015] The criteria for determining a modern storm event are set, which include a 10-minute average wind speed threshold and a duration threshold. The 10-minute average wind speed threshold is set to 13.9 m / s, and the duration threshold is set to 120 minutes.

[0016] When any grid cell within the spatial grid of the study area meets the criteria for determining a modern storm event, the modern wind field parameter vector for the corresponding time period is extracted. The modern wind field parameter vector includes the average wind speed of the storm event, the prevailing wind direction of the storm event, and the wind direction stability during the storm event.

[0017] In some specific embodiments, step S200 specifically includes:

[0018] Step S200.1: Obtain the set of outcrop profile measurement records and the set of core sampling records, determine the storm event sedimentary records, configure the storm event sedimentary record library, perform sedimentary structure interpretation, and restore the paleogeographic feature set and paleowater depth variation curve.

[0019] Step S200.2: Output the effective wind path partition grid and wave energy attenuation boundary to form the geological safety constraint factor, and configure the hard constraint filtering conditions for wind power generation site selection.

[0020] In some specific embodiments, step S300 specifically includes:

[0021] Step S300.1: Configure the directional evidence set, complete the directional evidence entry into the database, set the directional evidence validity threshold, and calculate the directional evidence credibility weight.

[0022] Step S300.2: Calculate the ancient prevailing wind direction based on the credible weight of directional evidence, calculate the ancient wind direction stability index, and form a stability threshold judgment result.

[0023] In some specific embodiments, step S400 specifically includes:

[0024] Step S400.1: Form a set of storm sediment dynamics proxy parameters, set the inversion paleowind speed mean parameters, and form paleowind speed levels.

[0025] Step S400.2: Configure the sedimentary tectonic wind field relationship model, perform paleowater depth-wind path coupling correction, perform cross-timescale fusion, and output the set of future wind energy assessment parameters.

[0026] In some specific embodiments, step S500 specifically includes:

[0027] Step S500.1: Configure hard constraint filtering, generate candidate region input set, configure comprehensive scoring rules, and output preferred region boundary.

[0028] Step S500.2: Output the candidate region list and bind the evidence chain index and uncertainty level.

[0029] In some specific embodiments, step S600 specifically includes:

[0030] Step S600.1: Configure short-term wind measurement verification and foundation investigation verification, form a verification data set, calculate the verification deviation, and write back to update the inversion coefficients and risk penalty items.

[0031] Step S600.2: Configure the iteration termination conditions and solidify the final site selection result package.

[0032] The maximum number of model self-calibration iterations is set to 3. The root mean square error threshold for wind speed verification is set to 0.8 m / s. The stability threshold for the boundary vector of the preferred area is set to an area change ratio of no more than 5%. When the root mean square error for wind speed verification is no more than 0.8 m / s and the area change ratio of the boundary vector of the preferred area is no more than 5%, the final candidate area list is output. The final candidate area list is output when the number of model self-calibration iterations reaches 3.

[0033] The final site selection result package is generated, which includes a wind rose overlay map, a wind energy zoning map, a geological risk overlay map, a candidate area boundary map, and an evidence chain list. The evidence chain list fields include a set of storm event sedimentary record numbers, a set of directional evidence numbers, modern wind field-sedimentary response calibration benchmark field entry numbers, paleodominant wind direction, paleowind direction stability index, and uncertainty level. The final site selection result package and the final candidate area list are then bound and output.

[0034] In summary, the wind power site selection method based on paleostorm depositional background provided in this application establishes long-term wind direction and speed priors using storm depositional records and directional evidence, reducing interannual uncertainties caused by relying solely on short-term wind measurements. It uses soft sediment deformation risk coding and boundary stability marking to form hard constraint filtering and introduces penalty terms in the scoring to reduce risks during the foundation investigation and construction stages. The candidate area output simultaneously provides evidence chain indexes and uncertainty levels, and performs short-term wind measurement verification, foundation investigation verification, and deviation write-back self-calibration iteration. Finally, it solidifies a site selection result package containing overlay maps and evidence chain lists, improving the transparency and efficiency of site selection decisions. Attached Figure Description

[0035] Figure 1 This is an overall flowchart of the wind power generation site selection method based on paleostorm deposition background provided in the embodiments of this application. Detailed Implementation

[0036] Please refer to Figure 1 This illustrates the flow of one embodiment of a wind power generation site selection method based on paleostorm depositional background according to the present disclosure.

[0037] like Figure 1 As shown, the wind power site selection method based on paleostorm depositional background includes the following steps:

[0038] Step S100: Set a unified spatial reference and form an input data set, perform wind source basin assimilation and fusion, generate three types of modern wind field grids, and configure the modern wind field deposition response calibration reference domain.

[0039] Step S200: Obtain the set of outcrop profile measurement records and the set of core sampling records, determine the storm event sedimentary records, configure the storm event sedimentary record library, perform sedimentary structure interpretation, restore the paleogeographic feature set and paleowater depth variation curve, output the effective wind path partition grid and wave energy attenuation boundary, form the geological safety constraint factor, and configure the hard constraint filtering conditions for wind power generation site selection.

[0040] Step S300: Configure the directional evidence set and complete the directional evidence storage, set the directional evidence validity threshold, calculate the directional evidence credibility weight, calculate the ancient dominant wind direction based on the directional evidence credibility weight, calculate the ancient wind direction stability index, and form the stability threshold judgment result.

[0041] Step S400: Form a set of storm sediment dynamics proxy parameters, set the inverted paleowind speed mean parameters, form paleowind speed levels, configure the sedimentary tectonic wind field relationship model, perform paleowater depth-wind path coupling correction, perform cross-timescale fusion, and output a set of future wind energy assessment parameters.

[0042] Step S500: Configure hard constraint filtering, generate candidate region input set, configure comprehensive scoring rules, output preferred region boundary, output candidate region list, and bind evidence chain index and uncertainty level.

[0043] Step S600: Configure short-term wind measurement verification and foundation investigation verification, form a verification data set, calculate the verification deviation, write back and update the inversion coefficients and risk penalty terms, configure the iteration termination conditions, and solidify the final site selection result package.

[0044] In some specific embodiments, step S100 specifically includes:

[0045] Step S100.1: Set a unified spatial benchmark and form an input data set, perform wind source basin assimilation and fusion, and generate three types of modern wind field grids.

[0046] The spatial extent of the study area was defined as the buffer zone extending outward from the shoreline of the modern lake. The width of the buffer zone was set to 5 km. A spatial grid was established for the study area, with a resolution of 100 m.

[0047] A set of field wind measurement records is formed, which includes the coordinates of the wind measurement points, sampling timestamps, 10-minute average wind speed, and 10-minute average wind direction. A set of topographic and geomorphological constraint grids is also formed, which includes topographic elevation grids and surface roughness grids. Integrity constraints are applied to the set of field wind measurement records, with a missing measurement ratio threshold set to 5%. Field wind measurement records with a missing measurement ratio exceeding 5% are not included in the assimilation and fusion.

[0048] A wind source basin assimilation and fusion solution model is established. This model takes a set of field wind measurement records and a set of topographic and geomorphological constraint grids as input, and outputs a modern wind vector grid on the spatial grid of the study area. The assimilation and fusion expression for the modern wind vector grid is defined as follows:

[0049]

[0050] In the formula: The coordinates of the center of the grid within the spatial grid of the study area are: Modern style vector, The grid center coordinates are The surface roughness correction factor is calculated from the surface roughness grid. This indicates the field wind measurement record number that participated in the assimilation and integration. This indicates the number of field wind measurement records that participated in the assimilation and integration process. The field wind measurement record number is indicated as follows. The spatial weighting coefficient is determined based on the attenuation of the distance between the wind measurement point and the center of the grid. The field wind measurement record number is indicated as follows. The measured wind vector is obtained by converting the 10-minute average wind speed and the 10-minute average wind direction.

[0051] Modern wind speed and direction parameters are calculated from modern wind vector grids. The statistical window for wind direction stability is set to 1 hour. The consistency of wind vector synthesis within the 1-hour window is defined as wind direction stability. The formula for calculating wind direction stability is set as follows:

[0052]

[0053] In the formula: Indicates wind direction stability. This indicates the sampling sequence number within the 1-hour window, 10 minutes. This indicates the number of 10-minute sampling periods within a 1-hour window. Indicates the first Wind vectors in 10-minute sampling periods Indicates the first Wind vector magnitude in a 10-minute sampling period This represents the magnitude of the sum of wind vectors within a 1-hour window.

[0054] Wind stability The wind direction stability parameter grid is generated by mapping the spatial grid of the study area. The wind direction stability threshold is set to 0.65. Grid cells with a wind direction stability of not less than 0.65 are marked as stable wind direction grid cells.

[0055] Step S100.2: Configure the modern wind field deposition response calibration reference domain.

[0056] The criteria for determining a modern storm event are set, which include a 10-minute average wind speed threshold and a duration threshold. The 10-minute average wind speed threshold is set to 13.9 m / s, and the duration threshold is set to 120 minutes.

[0057] When any grid cell within the spatial grid of the study area meets the criteria for determining a modern storm event, the modern wind field parameter vector for the corresponding time period is extracted. The modern wind field parameter vector includes the average wind speed of the storm event, the prevailing wind direction of the storm event, and the wind direction stability during the storm event.

[0058] A set of sedimentary response parameters is established, which includes event layer thickness, median grain size of the event layer, and erosion bottom interface morphology level. The modern wind field parameter vector and the set of sedimentary response parameters are bound in the same spatial location to form a modern wind field-sedimentary response calibration reference domain.

[0059] The output of the modern wind field-depositional response calibration baseline domain serves as the parameter calibration input. This input is used as the spatial weighting coefficient for the source basin assimilation and fusion solution model in subsequent paleowind field inversion. Value selection strategy and surface roughness correction coefficient Value retrieval strategy calibration update.

[0060] In some specific embodiments, step S200 specifically includes:

[0061] Step S200.1: Obtain the set of outcrop profile measurement records and the set of core sampling records, determine the storm event sedimentary records, configure the storm event sedimentary record library, perform sedimentary structure interpretation, and restore the paleogeographic feature set and paleowater depth variation curve.

[0062] A set of outcrop profile measurement records was obtained, which included the spatial coordinates of the outcrop profile, the bedding thickness sequence, the bedding attitude sequence, the morphological parameters of the erosion bottom interface, and the set of sedimentary structure image evidence. The set of sedimentary structure image evidence was calibrated with a scale and the spatial resolution of the set of sedimentary structure image evidence was set to 0.5 mm.

[0063] Obtain a core sampling record set, which includes the coordinates of the core sampling points, the core depth sequence, the grain size analysis results, and the sequence number. The lower limit of the core sampling depth is set to 6m.

[0064] The storm event sedimentary record is introduced, which consists of an event layer, an erosion floor, and directional sedimentary structures. The event layer is defined as a sedimentary segment in the vertical sequence that has a sudden increase in thickness and is accompanied by a sudden change in grain size.

[0065] Set an event layer judgment threshold, an event layer thickness threshold of 0.12m, an event layer median particle size mutation threshold of no less than 0.15mm between adjacent layers, and an erosion bottom interface judgment threshold of 0.03m.

[0066] A credibility score for storm event deposition records is constructed, and the formula for calculating the credibility score is set as follows:

[0067]

[0068] In the formula: This indicates the reliability score of the storm event deposition record. This indicates the event layer thickness. A value of 1 indicates an event layer thickness that is not less than the event layer thickness threshold, while a value of 0 indicates an event layer thickness that is less than the event layer thickness threshold. This represents the median particle size mutation indicator at the event layer. A value of 1 is assigned if the median particle size change is not less than the event layer median particle size mutation threshold, and a value of 0 is assigned if the median particle size change is less than the event layer median particle size mutation threshold. This indicates the erosion interface indicator. The value is 1 if the erosion cutting depth is not less than the erosion cutting depth threshold, and 0 if the erosion cutting depth is less than the erosion cutting depth threshold.

[0069] A confidence threshold for storm event deposition records was set to 0.70. Depositional layers with a thickness of not less than 0.70 are written into the storm event sedimentary record library, leading to the identification of storm sandbars and beach bars. Storm sandbars are defined as sand body units controlled by storm event sedimentary records and exhibiting continuous long-axis distribution, while beach bars are defined as sand body units exhibiting a strip-like distribution near the shore and modified by waves.

[0070] The lower limit of the long axis length of storm sandbars is set at 200m, and the lower limit of the width of beach bars is set at 80m. Sand body units that meet the lower limit conditions are vectorized at their boundaries and written into the storm event deposition record library.

[0071] The sedimentary tectonic interpretation results are presented, which include the long axis azimuth of sand bodies and the cross-bedding dip azimuth. The long axis azimuth of sand bodies is calculated from the storm bar boundary and the beach bar boundary, and the cross-bedding dip azimuth is extracted from the bedding occurrence sequence.

[0072] Ancient shoreline orientation parameters are constructed, which are obtained by taking the statistical main peak direction of the azimuth of the major axis of the sand body. The ancient shoreline orientation parameters are written into the ancient geomorphological feature set.

[0073] A paleodepth variation curve was constructed, which was jointly constrained by the facies migration distance sequence in the outcrop profile measurement record set and the layer thickness variation sequence in the core sampling record set. The paleodepth variation curve was fitted using piecewise linear fitting, with a segment length set to 50m and a root mean square threshold for the fitting residual set to 0.25m. Segments with a root mean square residual exceeding 0.25m were marked as low confidence segments and written into the paleodepth variation curve marking field.

[0074] Step S200.2: Output the effective wind path partition grid and wave energy attenuation boundary to form the geological safety constraint factor, and configure the hard constraint filtering conditions for wind power generation site selection.

[0075] The effective wind path is derived, defined as the continuous water distance along the normal direction of the ancient shoreline strike parameter. The specific calculation settings are as follows:

[0076]

[0077] In the formula: The grid center coordinates are Effective wind path Indicates the grid number of the normal direction. This represents the cumulative number of grid cells extending to the shoreline boundary. Indicates the spatial raster resolution of the study area. The value is 100m This indicates the water area indicator; the value of a water area grid cell is 1, and the value of a non-water area grid cell is 0.

[0078] Set effective wind path partitioning thresholds, with effective wind path partitioning thresholds set to 10km and 30km. Effective wind paths less than 10km are written into the short wind path partitioning field, effective wind paths not less than 10km and less than 30km are written into the medium wind path partitioning field, and effective wind paths not less than 30km are written into the long wind path partitioning field, forming an effective wind path partitioning grid.

[0079] Wave energy attenuation boundary is derived. The wave energy attenuation boundary is determined by the effective wind path zoning grid and the paleodepth variation curve. The wave energy attenuation judgment threshold is set to an energy attenuation ratio of not less than 0.60. The outer edge of the connected grid cell with an energy attenuation ratio of not less than 0.60 is extracted as the wave energy attenuation boundary and the vector boundary line is output.

[0080] Soft sedimentary deformation structures were identified, and their types were labeled and individual structure thicknesses were measured in the sedimentary structure image evidence set. A soft sedimentary deformation risk code was constructed, with the set of values ​​set as 0, 1, 2, and 3. A soft sedimentary deformation risk code of 0 indicates that the soft sedimentary deformation structure was not identified, a soft sedimentary deformation risk code of 1 indicates that the thickness of the individual structure is less than 0.10 m, a soft sedimentary deformation risk code of 2 indicates that the thickness of the individual structure is not less than 0.10 m and less than 0.30 m, and a soft sedimentary deformation risk code of 3 indicates that the thickness of the individual structure is not less than 0.30 m.

[0081] Geological safety constraint factors are formed, which include soft sediment deformation risk coding and storm sandbar boundary stability markers. The storm sandbar boundary stability markers are determined by the continuous length of the storm sandbar boundary, with a continuous length threshold set at 500m. Continuous lengths less than 500m are written as low-stability boundary markers.

[0082] Configure hard constraint filtering conditions for wind power generation site selection, set the soft deposition deformation risk coding threshold to 1, remove grid cells with soft deposition deformation risk codes greater than 1 from the candidate area input set, and remove grid cells covered by low stability boundary markers from the candidate area input set.

[0083] In some specific embodiments, step S300 specifically includes:

[0084] Step S300.1: Configure the directional evidence set, complete the directional evidence entry into the database, set the directional evidence validity threshold, and calculate the directional evidence credibility weight.

[0085] A set of directional evidence was extracted based on the outcrop profile measurement record set and the sedimentary structure image evidence set. The directional evidence set includes the cross-bedding dip azimuth, the sand body major axis azimuth, and the ripple mark normal azimuth. The cross-bedding dip azimuth was calculated from the bedding attitude sequence, the sand body major axis azimuth was calculated from the storm bar boundary vector and the beach bar boundary vector, and the ripple mark normal azimuth was obtained by rotating the ripple mark peak line azimuth in the sedimentary structure image evidence set by 90°.

[0086] Set a threshold for the validity of directional evidence. The threshold for the validity of directional evidence includes a spatial continuity length threshold and an azimuth dispersion threshold. The spatial continuity length threshold is set to 10m, and the azimuth dispersion threshold is set to 20°.

[0087] When the set of directional evidence appears continuously on the outcrop profile for a length of not less than 10m and the azimuth dispersion within the same outcrop profile is not greater than 20°, the directional evidence validity marker corresponding to the set of directional evidence is set to 1. When the directional evidence validity marker does not meet the requirements, the directional evidence validity marker is set to 0.

[0088] A credibility weight for directional evidence is constructed, which is jointly determined by the validity marker of directional evidence and the credibility score of storm event sedimentary records. The formula for calculating the credibility weight of directional evidence is set as follows:

[0089]

[0090] In the formula: The evidence number indicating the direction is The credibility weight of directional evidence, The evidence number indicating the direction is The reliability score of the storm event sedimentary record corresponding to the sedimentary interval. The evidence number indicating the direction is The directional evidence validity marker has values ​​of 0 and 1. Indicates the direction of the evidence number.

[0091] Step S300.2: Calculate the ancient prevailing wind direction based on the credible weight of directional evidence, calculate the ancient wind direction stability index, and form a stability threshold judgment result.

[0092] The ancient dominant wind direction is introduced, defined as the statistical main peak direction of the directional evidence set under the constraint of the directional evidence credibility weight. The formula for calculating the ancient dominant wind direction is set as follows:

[0093]

[0094] In the formula: Indicates the prevailing wind direction in ancient times The evidence number indicating the direction is The azimuth angle is taken from one of the following: the azimuth angle of cross-bedding dip direction, the azimuth angle of the major axis of the sand body, and the azimuth angle of the ripple mark normal direction. The evidence number indicating the direction is directional evidence credibility weight This indicates the number of directional evidence pieces involved in the calculation within the directional evidence set. This represents a two-parameter arctangent function and outputs the azimuth angle.

[0095] This leads to the paleowind stability index, defined as the strength of the synthetic consistency of the directional evidence set under the constraint of the directional evidence credibility weight. The formula for calculating the paleowind stability index is set as follows:

[0096]

[0097] In the formula: Indicators representing the stability of ancient wind direction. The evidence number indicating the direction is The credibility weight of directional evidence, The evidence number indicating the direction is azimuth angle, This indicates the number of directional evidence pieces involved in the calculation within the directional evidence set.

[0098] A paleowind stability threshold is set to 0.70. When the paleowind stability index is not less than 0.70, a high stability marker is written, and when the paleowind stability index is less than 0.70, a low stability marker is written. The high stability marker and the low stability marker are written to the paleowind stability marker field of the storm event deposition record library.

[0099] The ancient prevailing wind direction, ancient wind direction stability index, and high stability and low stability markers are bound to the spatial grid of the study area to form a long-term wind resource reliability prior input set. The long-term wind resource reliability prior input set is used for the ancient wind speed inversion and sedimentary structure and wind field coupled wind energy assessment of S400.

[0100] In some specific embodiments, step S400 specifically includes:

[0101] Step S400.1: Form a set of storm sediment dynamics proxy parameters, set the inversion paleowind speed mean parameters, and form paleowind speed levels.

[0102] The event layer thickness, median grain size of the event layer, sorting coefficient corresponding to the grain size analysis results, and bottom interface roughness index corresponding to the erosion bottom interface morphology parameters were extracted from the storm event sedimentary record library. The bottom interface roughness index was calculated using a statistical window length of 10m.

[0103] Minimum and maximum normalization were applied to the event layer thickness, median particle size of the event layer, sorting coefficient, and bottom interface roughness index. The lower limit of the median particle size of the event layer was set to 0.06 mm and the upper limit of the median particle size of the event layer was set to 0.60 mm. The lower limit of the event layer thickness was set to 0.05 μm and the upper limit of the event layer thickness was set to 0.50 μm. The lower limit of the sorting coefficient was set to 0.50 and the upper limit of the sorting coefficient was set to 2.00. The lower limit of the bottom interface roughness index was set to 0.010 and the upper limit of the bottom interface roughness index was set to 0.080.

[0104] Normalization results less than 0 are treated as 0, and normalization results greater than 1 are treated as 1. Storm sediment dynamics surrogate parameters are constructed, and the calculation formula for these parameters is set as follows:

[0105]

[0106] In the formula: The storm event deposition record number is indicated as Storm sediment dynamics proxy parameters, This represents the normalized value of the median particle size in the event layer. This represents the normalized value of the event layer thickness. This represents the normalized value of the sorting coefficient. This represents the normalized value of the bottom interface roughness index. This indicates the number of the storm event deposition record.

[0107] Based on the modern wind field-sedimentary response calibration benchmark domain, a calibration mapping relationship is established from storm sediment dynamic surrogate parameters to paleowind speed mean parameters. The calculation formula for paleowind speed mean parameters is set as follows:

[0108]

[0109] In the formula: The storm event deposition record number is indicated as The paleowind speed mean parameters, in m / s. The storm event deposition record number is indicated as Storm sediment dynamics proxy parameters.

[0110] The threshold values ​​for ancient wind speed classification are set at 13.9 m / s, 17.2 m / s, and 24.5 m / s. Ancient wind speeds with a mean value less than 13.9 m / s are classified as Level 1, those with a mean value not less than 13.9 m / s and less than 17.2 m / s are classified as Level 2, those with a mean value not less than 17.2 m / s and less than 24.5 m / s are classified as Level 3, and those with a mean value not less than 24.5 m / s are classified as Level 4.

[0111] The parameter set for the probability distribution of paleowind speed is expressed using a log-normal distribution. The log-normal mean parameter is taken as the natural logarithm of the paleowind speed mean parameter, and the log-normal standard deviation parameter is obtained by linear scaling of the paleowind direction stability index. The baseline value of the log-normal standard deviation parameter is set to 0.35. When the paleowind direction stability index increases, the log-normal standard deviation parameter decreases proportionally, and the reduction coefficient is set to 0.5.

[0112] Step S400.2: Configure the sedimentary tectonic wind field relationship model, perform paleowater depth-wind path coupling correction, perform cross-timescale fusion, and output the set of future wind energy assessment parameters.

[0113] A paleodepth parameter grid is derived, which is generated by interpolating the paleodepth variation curve within the spatial grid of the study area. An effective wind path partition grid and a wave energy attenuation boundary are derived, and a sedimentary tectonic wind field relationship model is constructed. The sedimentary tectonic wind field relationship model performs three types of corrections on the paleowind speed mean parameter, including: effective wind path correction, paleodepth correction, and wave energy attenuation correction.

[0114] Effective wind path correction: When the effective wind path is not less than 30km, the upper limit of the enhancement is taken, and the upper limit of the enhancement is set to 15%. When the effective wind path is less than 30km, the enhancement is linearly increased according to the proportion of the effective wind path.

[0115] Paleowater depth correction: When the paleowater depth is not less than 5m, the upper limit of the reduction is taken, and the upper limit of the reduction range is set to 10%. When the paleowater depth is less than 5m, the reduction is linearly reduced according to the proportion of paleowater depth.

[0116] Wave energy attenuation correction: The correction factor is 1.00 inside the wave energy attenuation boundary and 0.85 outside the wave energy attenuation boundary.

[0117] The total coefficient of the coupling correction is configured to be the product of the three types of correction coefficients. The lower limit of the total coefficient of the coupling correction is set to 0.80 and the upper limit is set to 1.20. If the total coefficient of the coupling correction is less than 0.80, it is taken as 0.80. If the total coefficient of the coupling correction is greater than 1.20, it is taken as 1.20. The mean paleowind speed parameter after coupling correction is written into the spatial grid of the study area.

[0118] A cross-timescale fusion weight parameter is introduced. The cross-timescale fusion weight parameter is the arithmetic mean of the grid value of the wind direction stability parameter and the wind direction stability index. The lower limit of the cross-timescale fusion weight parameter is set to 0.30 and the upper limit is set to 0.70. The lower limit constraint and the upper limit constraint are used to suppress the dominant influence of a single timescale anomaly on the future equivalent wind speed mean parameter.

[0119] The future equivalent wind speed mean parameter is constructed. The future equivalent wind speed mean parameter is the weighted average of the modern wind speed parameter grid value and the coupled and corrected ancient wind speed mean parameter. The weighting coefficient adopts the cross-time scale fusion weight parameter.

[0120] A set of future wind energy assessment parameters is formed, which includes wind energy density, effective hours, and extreme wind risk tail intensity. Wind energy density is calculated according to the rule that the air density is 1.225 kg / m³ and is proportional to the cube of the mean parameter of the future equivalent wind speed. Effective hours are calculated according to the rule that the lower limit of the power generation wind speed window is 3 m / s and the upper limit of the power generation wind speed window is 25 m / s. The calculation method is to use the log-normal distribution parameter set to perform interval probability estimation and conversion for 8760 hours throughout the year. Extreme wind risk tail intensity is calculated according to the exceedance probability of future wind speeds exceeding 25 m / s and the value range is limited to 0 to 1. An increase in the value of extreme wind risk tail intensity indicates an increase in extreme wind risk.

[0121] In some specific embodiments, step S500 specifically includes:

[0122] Step S500.1: Configure hard constraint filtering, generate candidate region input set, configure comprehensive scoring rules, and output preferred region boundary.

[0123] This paper introduces a set of parameters for future wind energy assessment, a raster for wind direction stability parameters, a paleowind direction stability index, and a geological safety constraint factor. The thresholds are set as follows: wind energy density threshold: 220 W / m³; effective hours threshold: 2600 h; extreme wind risk tail intensity threshold: 0.03; wind direction stability threshold: 0.65; paleowind direction stability threshold: 0.70; and soft sediment deformation risk coding threshold: 1.

[0124] Within the spatial grid of the study area, grid cells simultaneously satisfy the following conditions: wind energy density not less than 220 W / m³, effective hours not less than 2600 h, extreme wind risk tail intensity not greater than 0.03, wind direction stability parameter grid value not less than 0.65, wind direction stability index not less than 0.70, soft deposition deformation risk code not greater than 1, and low stability boundary marker not covered, and are written into the candidate area input set.

[0125] The wind resource benefit score is derived by normalizing the wind energy density and effective hours and then weighting the sum by 0.6 and 0.4 respectively. The wind direction stability benefit score is derived by normalizing the grid values ​​of the wind direction stability parameter and the wind direction stability index and then weighting the sum by 0.5 and 0.5 respectively.

[0126] The project accessibility benefit score is derived. The project accessibility benefit score is jointly determined by the road access distance and the grid connection distance. The road access distance is defined as the shortest horizontal distance from the candidate area input set grid cell to the centerline of the existing road. The grid connection distance is defined as the shortest horizontal distance from the candidate area input set grid cell to the boundary of the existing power transmission and distribution line corridor.

[0127] The road access distance threshold is set at 8km, and the grid connection distance threshold is set at 15km. When the road access distance is no more than 8km and the grid connection distance is no more than 15km, the project accessibility benefit score is 1. When the road access distance is greater than 8km or the grid connection distance is greater than 15km, the project accessibility benefit score is 0.

[0128] The geological risk penalty score is derived from the soft sediment deformation risk code. When the soft sediment deformation risk code is 0, the geological risk penalty score is 0, and when the soft sediment deformation risk code is 1, the geological risk penalty score is 0.5.

[0129] The comprehensive score is calculated using a weighted summation rule, taking the comprehensive score as 0.45 × wind resource benefit score + 0.30 × wind direction stability benefit score + 0.20 × engineering accessibility benefit score - 0.05 × geological risk penalty score. This comprehensive score is written into the comprehensive score raster. The comprehensive score threshold is set to 0.65. Connected raster cells with a comprehensive score of not less than 0.65 are aggregated into a set of connected domains in the preferred area. The area threshold for the connected domains in the preferred area is set to 0.80 km². Connected domains with an area of ​​not less than 0.80 km² in the preferred area are output as the boundary vector of the preferred area.

[0130] Step S500.2: Output the candidate region list and bind the evidence chain index and uncertainty level.

[0131] The threshold for the number of entries in the candidate region list is set to 20. The set of connected components of the preferred regions is sorted according to the average comprehensive score. The boundary vectors of the top 20 preferred regions with the highest average comprehensive score are output as the candidate region list.

[0132] The evidence chain index table is established item by item according to the candidate area list. The fields of the evidence chain index table include the set of storm event sedimentary record numbers, the set of directional evidence numbers, the entry number of the modern wind field sedimentary response calibration benchmark domain, the paleodominant wind direction, the paleowind direction stability index, and the low confidence segment coverage ratio of the paleowater depth change curve.

[0133] The uncertainty level is determined by the ancient and modern wind direction deviation angle, the stability fusion index, and the low-confidence segment coverage ratio of the ancient water depth variation curve: when the ancient and modern wind direction deviation angle is not greater than 30°, the stability fusion index is not less than 0.70, and the low-confidence segment coverage ratio of the ancient water depth variation curve is not greater than 0.20, it is written into the first level of uncertainty.

[0134] When the deviation angle between ancient and modern wind direction is greater than 30° but not greater than 60°, or the stability fusion index is less than 0.70 but not less than 0.60, or the low-confidence segment coverage ratio of the paleowater depth variation curve is greater than 0.20 but not greater than 0.40, it is classified as a Level 2 uncertainty.

[0135] When the ancient and modern wind direction deviation angle is greater than 60°, the stability fusion index is less than 0.60, or the low-confidence segment coverage ratio of the ancient water depth variation curve is greater than 0.40, it is written into the third level of uncertainty.

[0136] Level 1 uncertainty, Level 2 uncertainty, and Level 3 uncertainty are bound to the candidate area list and output along with the candidate area list.

[0137] In some specific embodiments, step S600 specifically includes:

[0138] Step S600.1: Configure short-term wind measurement verification and foundation investigation verification, form a verification data set, calculate the verification deviation, and write back to update the inversion coefficients and risk penalty items.

[0139] A candidate area list is generated, forming a short-term wind measurement verification point set. The short-term wind measurement verification point set is deployed within the boundary vector of the preferred area corresponding to the candidate area list. The minimum number of short-term wind measurement verification points is set to 2, and the minimum spacing between short-term wind measurement verification points is set to 500m.

[0140] A short-term wind measurement verification record set is formed, which includes the coordinates of the wind measurement point, the sampling timestamp, the 10-minute average wind speed, and the 10-minute average wind direction. The lower limit of the short-term wind measurement verification period is set to 30 days, and the threshold for the missing measurement ratio of the short-term wind measurement verification record set is set to 5%.

[0141] A set of foundation investigation verification points is formed, which corresponds to the set of short-term wind measurement verification points, forming a set of foundation investigation verification records. The set of foundation investigation verification records includes the coordinates of the investigation points, the borehole depth, the bearing capacity characteristic value, and the groundwater depth. The lower limit of the borehole depth is set to 15m, the threshold of the bearing capacity characteristic value is set to 180kPa, and the threshold of the groundwater depth is set to 1.5m.

[0142] Within the short-term wind measurement verification period, the 10-minute average wind speed is calculated as the equivalent wind speed mean parameter for short-term wind measurement verification. The equivalent wind speed mean parameter for short-term wind measurement verification is registered with the future equivalent wind speed mean parameter to form a wind speed verification deviation sequence. The root mean square error of wind speed verification is calculated using the following formula:

[0143]

[0144] In the formula: It is the root mean square error of wind speed verification. This refers to the number of short-term wind measurement verification sites participating in the review. This is the serial number of the short-term wind measurement verification point. The short-term wind measurement verification point number is The deviation in wind speed verification.

[0145] The spatial weight coefficients of the wind speed verification deviation sequence are then written back to update the wind source basin assimilation and fusion solution model. Value selection strategy and surface roughness correction coefficient The value retrieval strategy and write-back update adopt the inversion coefficient self-calibration parameter. The self-calibration parameters of the inversion coefficients are expressed as follows:

[0146]

[0147] In the formula: It is the first The self-calibration parameters of the inversion coefficients in the self-calibration iteration of the wheel model. It is the first The self-calibration parameters of the inversion coefficients in the self-calibration iteration of the wheel model. This is the proportional write-back factor, which is set to 0.35. This is the lower limit of the inversion coefficient self-calibration parameter, which is set to 0.90. This is the upper limit of the self-calibration parameter for the inversion coefficients. The upper limit of the self-calibration parameter for the inversion coefficients is set to 1.10. It is a limiting operator and restricts the result within the parentheses to... scope.

[0148] The set of foundation investigation and verification records is mapped to the update value of geological risk penalty score. When the bearing capacity characteristic value is less than 180 kPa, the geological risk penalty score is updated to 1.0. When the groundwater depth is less than 1.5 m, the geological risk penalty score is updated to 1.0. When the bearing capacity characteristic value is not less than 180 kPa and the groundwater depth is not less than 1.5 m, the original value of the geological risk penalty score is maintained. After the geological risk penalty score update is completed, the comprehensive score grid is recalculated and the candidate area list is updated.

[0149] Step S600.2: Configure the iteration termination conditions and solidify the final site selection result package.

[0150] The maximum number of model self-calibration iterations is set to 3. The root mean square error threshold for wind speed verification is set to 0.8 m / s. The stability threshold for the boundary vector of the preferred area is set to an area change ratio of no more than 5%. When the root mean square error for wind speed verification is no more than 0.8 m / s and the area change ratio of the boundary vector of the preferred area is no more than 5%, the final candidate area list is output. The final candidate area list is output when the number of model self-calibration iterations reaches 3.

[0151] The final site selection result package is generated, which includes a wind rose overlay map, a wind energy zoning map, a geological risk overlay map, a candidate area boundary map, and an evidence chain list. The evidence chain list fields include a set of storm event sedimentary record numbers, a set of directional evidence numbers, modern wind field-sedimentary response calibration benchmark field entry numbers, paleodominant wind direction, paleowind direction stability index, and uncertainty level. The final site selection result package and the final candidate area list are then bound and output.

[0152] In practical application, a unified spatial benchmark is set for the study area. The 5km buffer zone extending outward from the modern lake shoreline is defined as the study area, and a spatial grid with a resolution of 100m is established to form a set of field wind measurement records. The 10-minute average wind speed and 10-minute average wind direction are recorded. Records with a missing rate of more than 5% are removed. Wind direction stability is calculated using a 1-hour statistical window, and a wind direction stability parameter grid is generated. Grid cells with a wind direction stability of not less than 0.65 are marked as stable wind direction grid cells. The criteria for judging modern storm events are set as a 10-minute average wind speed of not less than 13.9m / s and a duration of not less than 120min. Wind field parameter vectors are extracted and bound to event layer thickness, median grain size, and erosion bottom interface morphology level to form a modern wind field-deposition response calibration benchmark domain.

[0153] Outcrop profile measurement records and core sampling records were acquired. Event layer thickness of 0.12m, median grain size abrupt change of 0.15mm, and erosion cutting depth of 0.03m were used as criteria for judging storm event sedimentary records. A sedimentary record reliability threshold of 0.70 was used for database entry. A root mean square threshold of 0.25m for the residual of paleodepth variation curve fitting was used to mark low reliability segments. Effective wind path zoning thresholds of 10km and 30km were used to generate zoning grids. A wave energy attenuation ratio threshold of 0.60 was used to extract wave energy attenuation boundaries. Soft sediment deformation risk coding was graded according to structural thickness of 0.10m and 0.30m. A storm sandbar boundary continuity length threshold of 500m was used to generate low stability boundary markers. The soft sediment deformation risk coding threshold of 1 and the low stability boundary markers constituted the geological safety constraint factor and were used for hard constraint filtering.

[0154] Configure the directional evidence set and complete the directional evidence database entry. The validity threshold of the directional evidence is set to a spatial continuous length of not less than 10m and an azimuth dispersion of not more than 20°. The credibility weight of the directional evidence is jointly determined by the directional evidence validity label and the credibility score of the storm event sedimentary record. Under the credibility weight constraint, the direction of the main peak is statistically obtained to obtain the paleoprevailing wind direction. The synthetic consistency intensity is calculated to obtain the paleoprevailing wind direction stability index. The paleoprevailing wind direction stability threshold is set to 0.70. A paleoprevailing wind direction stability index of not less than 0.70 is written as a high stability label, and a paleoprevailing wind direction stability index of less than 0.70 is written as a low stability label. The label field is output with the storm event sedimentary record database and used for subsequent inversion and site selection.

[0155] The system generates storm sediment dynamic surrogate parameters and inverts paleowind speed mean parameters. The bottom interface roughness index is statistically analyzed using a 10m window. The normalized boundary is set with a lower limit of 0.06mm for the median grain size of the event layer, a sorting coefficient of 0.50–2.00, and a bottom interface roughness index of 0.010–0.080. The result range is limited to 0–1. The paleowind speed level thresholds are 13.9, 17.2, and 24.5 m / s. The coupling correction includes three factors: effective wind path, paleowater depth, and wave energy attenuation. The effective wind path is not less than 30km, with an upper limit of 15% enhancement. The paleowater depth is not less than 5m, with an upper limit of 10% reduction. The boundary correction is 1.00, and the boundary correction is 0.85. The total coefficient of the coupling correction is limited to 0.80–1.20, and the fusion weight is limited to 0.30–0.70. The system generates the future equivalent wind speed mean parameters and outputs the future wind energy assessment parameter set.

[0156] Configure hard constraint filtering and generate a candidate area input set. Raster cells with wind energy density ≥220W / m³, effective hours ≥2600h, extreme wind risk tail intensity ≤0.03, wind direction stability ≥0.65, paleowind direction stability index ≥0.70, soft sediment deformation risk code ≤1 and low stability boundary marker not covered are included in the database. The accessibility benefit score is determined by the road access distance ≤8km and the grid connection distance ≤15km. The comprehensive score is calculated with 0.45, 0.30, and 0.20 plus a geological risk penalty of 0.05. The boundary vector of the preferred area is output when the area of ​​the connected domain of the comprehensive score raster is ≥0.80km². The threshold for the number of candidate area entries is 20. The output is sorted by the average comprehensive score and bound with the evidence chain index and uncertainty level.

[0157] Configure a short-term wind measurement verification point set and deploy it within the boundary of the preferred area. The number of points should be ≥2 and the spacing should be ≥500m. The verification period should be ≥30 days and the missing measurement ratio should be ≤5%. Configure foundation investigation verification records, with a borehole depth ≥15m, a bearing capacity characteristic value threshold of 180kPa, and a groundwater burial depth threshold of 1.5m. Write back the wind speed verification deviation sequence to update the spatial weight coefficient strategy and the surface roughness correction coefficient strategy. The proportion of the write-back coefficient is 0.20 and the self-calibration parameter of the inversion coefficient is limited to 0.90–1.10. The upper limit of the number of model self-calibration iterations is 3. The root mean square error threshold of wind speed verification is 0.8m / s. The proportion threshold of the area change ratio of the preferred area boundary is 5%. After meeting the termination conditions, solidify the final site selection result package and output the wind rose overlay map, wind energy zoning map, geological risk overlay map, candidate area boundary map, and evidence chain list.

Claims

1. A wind power generation site selection method based on paleostorm depositional background, characterized in that, Includes the following steps: S100, set a unified spatial benchmark and form an input data set, perform wind source basin assimilation and fusion, generate three types of modern wind field grids, and configure the modern wind field deposition response calibration benchmark domain; S200: Obtain the set of outcrop profile measurement records and core sampling records, determine the storm event sedimentary records, configure the storm event sedimentary record library, perform sedimentary structure interpretation, restore the paleogeographic feature set and paleowater depth variation curve, output the effective wind path partition grid and wave energy attenuation boundary, form the geological safety constraint factor, and configure the hard constraint filtering conditions for wind power generation site selection. S300: Configure the directional evidence set and complete the directional evidence storage, set the directional evidence validity threshold, calculate the directional evidence credibility weight, calculate the ancient dominant wind direction based on the directional evidence credibility weight, calculate the ancient wind direction stability index, and form the stability threshold judgment result. S400, forming a set of storm sediment dynamics proxy parameters, setting the inversion paleowind speed mean parameters, forming paleowind speed levels, configuring a sedimentary tectonic wind field relationship model, performing paleowater depth-wind path coupling correction, performing cross-timescale fusion, and outputting a set of future wind energy assessment parameters. S500: Configure hard constraint filtering, generate candidate region input set, configure comprehensive scoring rules, output preferred region boundary, output candidate region list, and bind evidence chain index and uncertainty level; S600 configures short-term wind measurement verification and foundation investigation verification, forms a verification data set, calculates verification deviation, writes back and updates inversion coefficients and risk penalty terms, configures iteration termination conditions, and solidifies the final site selection result package.

2. The wind power generation site selection method based on paleostorm depositional background according to claim 1, characterized in that, S100 specifically includes: S100.

1. Set a unified spatial benchmark, form an input data set, perform wind source basin assimilation and fusion, and generate three types of modern wind field grids; The spatial extent of the study area is defined as the buffer zone extending outward from the shoreline of the modern lake. The width of the buffer zone is set to 5 km. A spatial grid for the study area is established, and the resolution of the spatial grid is set to 100 m. A set of field wind measurement records is formed, which includes the coordinates of the wind measurement points, sampling timestamps, 10-minute average wind speed, and 10-minute average wind direction. A set of topographic and geomorphological constraint grids is also formed, which includes topographic elevation grids and surface roughness grids. Integrity constraints are applied to the set of field wind measurement records, with a missing measurement ratio threshold set to 5%. Field wind measurement records with a missing measurement ratio exceeding 5% are not included in the assimilation and fusion. A wind source basin assimilation and fusion solution model is established. The wind source basin assimilation and fusion solution model takes the set of field wind measurement records and the set of topographic and geomorphological constraint grids as inputs and outputs modern wind vector grids on the spatial grid of the study area. Modern wind speed parameter grid and modern wind direction parameter grid are calculated from modern wind vector grid. The statistical window for wind direction stability is set to 1 hour. The consistency of wind vector synthesis within the 1-hour window is defined as wind direction stability. Wind stability The wind direction stability parameter grid is generated by mapping the spatial grid of the study area. The wind direction stability threshold is set to 0.

65. Grid cells with a wind direction stability of not less than 0.65 are marked as stable wind direction grid cells. S100.2, Configure a modern wind field deposition response calibration reference domain; The criteria for determining a modern storm event are set, which include a 10-minute average wind speed threshold and a duration threshold. The 10-minute average wind speed threshold is set to 13.9 m / s, and the duration threshold is set to 120 minutes. When any grid cell within the spatial grid of the study area meets the criteria for determining a modern storm event, the modern wind field parameter vector for the corresponding time period is extracted. The modern wind field parameter vector includes the average wind speed of the storm event, the prevailing wind direction of the storm event, and the wind direction stability during the storm event. A set of sedimentary response parameters is established, which includes event layer thickness, median grain size of event layer, and erosion bottom interface morphology level. The modern wind field parameter vector and the set of sedimentary response parameters are bound in the same spatial location to form a modern wind field-sedimentary response calibration reference domain. The output of the modern wind field-depositional response calibration baseline domain serves as the parameter calibration input. This input is used as the spatial weighting coefficient for the source basin assimilation and fusion solution model in subsequent paleowind field inversion. Value selection strategy and surface roughness correction coefficient Value retrieval strategy calibration update.

3. The wind power generation site selection method based on paleostorm depositional background according to claim 1, characterized in that, S200 specifically includes: S200.

1. Obtain the set of outcrop profile measurement records and core sampling records, determine the storm event sedimentary records, configure the storm event sedimentary record library, perform sedimentary structure interpretation, and restore the paleogeographic feature set and paleowater depth variation curve; A set of outcrop profile measurement records was obtained, which included the outcrop profile spatial coordinates, bedding thickness sequence, bedding attitude sequence, erosion bottom interface morphology parameters, and sedimentary structure image evidence set. The sedimentary structure image evidence set was calibrated with a scale and the spatial resolution of the sedimentary structure image evidence set was set to 0.5 mm. Obtain a core sampling record set, which includes the coordinates of the core sampling points, the core depth sequence, the grain size analysis results, and the sequence number. The lower limit of the core sampling depth is set to 6m. The storm event sedimentary record is introduced, which consists of an event layer, an erosion floor, and directional sedimentary structures. The event layer is defined as a sedimentary segment in the vertical sequence that has a sudden increase in thickness and is accompanied by a sudden change in grain size. Set an event layer judgment threshold, an event layer thickness threshold of 0.12m, an event layer median particle size mutation threshold of no less than 0.15mm between adjacent layers, and an erosion bottom interface judgment threshold of 0.03m. Construct a credibility score for storm event deposition records; A confidence threshold for storm event deposition records was set to 0.

70. Depositional layers with a thickness of not less than 0.70 are written into the storm event sedimentary record library, leading to the identification of storm sandbars and beach bars. Storm sandbars are defined as sand body units controlled by storm event sedimentary records and exhibiting continuous long-axis distribution, while beach bars are defined as sand body units exhibiting a strip-like distribution near the shore and modified by waves. The sedimentary tectonic interpretation results are presented, which include the long axis azimuth of sand bodies and the dip azimuth of cross-bedding. The long axis azimuth of sand bodies is calculated from the storm bar boundary and the beach bar boundary, and the dip azimuth of cross-bedding is extracted from the bedding attitude sequence. Ancient shoreline orientation parameters are constructed. The ancient shoreline orientation parameters are taken from the statistical main peak direction of the azimuth of the major axis of the sand body. The ancient shoreline orientation parameters are written into the ancient geomorphological feature set. A paleodepth variation curve was constructed, which was jointly constrained by the facies migration distance sequence in the outcrop profile measurement record set and the layer thickness variation sequence in the core sampling record set. The paleodepth variation curve was fitted using piecewise linear fitting, with the segment length set to 50m and the root mean square threshold of the fitting residual set to 0.25m. Segments with a root mean square of the fitting residual exceeding 0.25m were marked as low confidence segments and written into the paleodepth variation curve marking field. S200.2 Output effective wind path partition grid and wave energy attenuation boundary to form geological safety constraint factor, and configure hard constraint filtering conditions for wind power generation site selection; The effective wind path is defined as the continuous water distance along the normal direction of the ancient shoreline strike parameter. Set effective wind path partition thresholds. The effective wind path partition thresholds are set to 10km and 30km. Effective wind paths less than 10km are written into the short wind path partition field. Effective wind paths not less than 10km and less than 30km are written into the medium wind path partition field. Effective wind paths not less than 30km are written into the long wind path partition field, forming an effective wind path partition grid. Soft sedimentary deformation structures were identified, and their types were labeled and individual structure thicknesses were measured in the sedimentary structure image evidence set. A soft sedimentary deformation risk code was constructed, with the set of values ​​set to 0, 1, 2, and 3. A soft sedimentary deformation risk code of 0 indicates that the soft sedimentary deformation structure was not identified; a soft sedimentary deformation risk code of 1 indicates that the thickness of the individual structure is less than 0.10 m; a soft sedimentary deformation risk code of 2 indicates that the thickness of the individual structure is not less than 0.10 m and less than 0.30 m; and a soft sedimentary deformation risk code of 3 indicates that the thickness of the individual structure is not less than 0.30 m. Geological safety constraint factors are formed, which include soft sediment deformation risk coding and storm sandbar boundary stability markers. The storm sandbar boundary stability markers are determined by the continuous length of the storm sandbar boundary, with a continuous length threshold set at 500m. Continuous lengths less than 500m are marked as low-stability boundaries. Configure hard constraint filtering conditions for wind power generation site selection, set the soft deposition deformation risk coding threshold to 1, remove grid cells with soft deposition deformation risk codes greater than 1 from the candidate area input set, and remove grid cells covered by low stability boundary markers from the candidate area input set.

4. The wind power generation site selection method based on paleostorm depositional background according to claim 1, characterized in that, The S300 specifically includes: S300.1 Configure the directional evidence set, complete the directional evidence entry into the database, set the directional evidence validity threshold, and calculate the directional evidence credibility weight. A set of directional evidence was extracted based on the outcrop profile measurement record set and the sedimentary structure image evidence set. The directional evidence set includes the cross-bedding dip azimuth, the sand body major axis azimuth, and the ripple mark normal azimuth. The cross-bedding dip azimuth was calculated from the bedding attitude sequence, the sand body major axis azimuth was calculated from the storm bar boundary vector and the beach bar boundary vector, and the ripple mark normal azimuth was obtained by rotating the ripple mark peak line azimuth in the sedimentary structure image evidence set by 90°. Set a threshold for the validity of directional evidence. The threshold for the validity of directional evidence includes a spatial continuity length threshold and an azimuth dispersion threshold. The spatial continuity length threshold is set to 10m, and the azimuth dispersion threshold is set to 20°. A credibility weight for directional evidence is constructed, which is jointly determined by the validity label of directional evidence and the credibility score of storm event sedimentary records. S300.2 Calculate the ancient prevailing wind direction based on the credible weight of directional evidence, calculate the ancient wind direction stability index, and form a stability threshold judgment result; The ancient dominant wind direction is introduced, which is defined as the statistical main peak direction of the set of directional evidence under the constraint of the credibility weight of directional evidence. This leads to the ancient wind direction stability index, which is defined as the strength of the synthetic consistency of the set of directional evidence under the constraint of the directional evidence credibility weight. A paleowind stability threshold is set to 0.

70. When the paleowind stability index is not less than 0.70, a high stability flag is written, and when the paleowind stability index is less than 0.70, a low stability flag is written. The high stability flag and the low stability flag are written into the paleowind stability flag field of the storm event deposition record library. The ancient prevailing wind direction, ancient wind direction stability index, and high stability and low stability markers are bound to the spatial grid of the study area to form a long-term wind resource reliability prior input set. The long-term wind resource reliability prior input set is used for the ancient wind speed inversion and sedimentary structure and wind field coupled wind energy assessment of S400.

5. The wind power generation site selection method based on paleostorm depositional background according to claim 1, characterized in that, The S400 specifically includes: S400.

1. Form a set of storm sediment dynamics proxy parameters, set the parameters for inverting paleowind speed mean, and form paleowind speed levels; The event layer thickness, median grain size of the event layer, sorting coefficient corresponding to the grain size analysis results, and bottom interface roughness index corresponding to the erosion bottom interface morphology parameters were extracted from the storm event sedimentary record library. The bottom interface roughness index was calculated using a statistical window length of 10m. A calibration mapping relationship between storm sediment dynamic surrogate parameters and paleowind speed mean parameters was established based on the modern wind field-sediment response calibration benchmark domain. The parameter set for the probability distribution of paleowind speed is expressed using a log-normal distribution. The log-normal mean parameter is taken as the natural logarithm of the paleowind speed mean parameter, and the log-normal standard deviation parameter is obtained by linear scaling of the paleowind direction stability index. The baseline value of the log-normal standard deviation parameter is set to 0.

35. When the paleowind direction stability index increases, the log-normal standard deviation parameter decreases proportionally, and the reduction coefficient is set to 0.

5. S400.2 Configure the sedimentary tectonic wind field relationship model, perform paleowater depth-wind path coupling correction, perform cross-timescale fusion, and output a set of future wind energy assessment parameters; A paleodepth parameter grid is introduced, which is generated by interpolating the paleodepth variation curve into the spatial grid of the study area. An effective wind path partition grid and wave energy attenuation boundary are introduced. A sedimentary tectonic wind field relationship model is constructed. The sedimentary tectonic wind field relationship model performs three types of corrections on the paleowind speed mean parameter, including: effective wind path correction, paleodepth correction and wave energy attenuation correction. The total coefficient of the coupling correction is configured to be the product of the three types of correction coefficients. The lower limit of the total coefficient of the coupling correction is set to 0.80 and the upper limit is set to 1.

20. If the total coefficient of the coupling correction is less than 0.80, it is taken as 0.

80. If the total coefficient of the coupling correction is greater than 1.20, it is taken as 1.

20. The mean paleowind speed parameter after coupling correction is written into the spatial grid of the study area. A cross-timescale fusion weight parameter is introduced. The cross-timescale fusion weight parameter is the arithmetic mean of the grid value of the wind direction stability parameter and the wind direction stability index. The lower limit of the cross-timescale fusion weight parameter is set to 0.30 and the upper limit is set to 0.

70. The lower limit constraint and the upper limit constraint are used to suppress the dominant influence of a single timescale anomaly on the future equivalent wind speed mean parameter. The future equivalent wind speed mean parameter is constructed. The future equivalent wind speed mean parameter is the weighted average of the modern wind speed parameter grid value and the coupled and corrected ancient wind speed mean parameter. The weighting coefficient adopts the cross-time scale fusion weight parameter. A set of future wind energy assessment parameters is formed, which includes wind energy density, effective hours, and extreme wind risk tail intensity. Wind energy density is calculated according to the rule that the air density is 1.225 kg / m³ and is proportional to the cube of the mean parameter of the future equivalent wind speed. Effective hours are calculated according to the rule that the lower limit of the power generation wind speed window is 3 m / s and the upper limit of the power generation wind speed window is 25 m / s. The calculation method is to use the log-normal distribution parameter set to perform interval probability estimation and conversion for 8760 hours throughout the year. Extreme wind risk tail intensity is calculated according to the exceedance probability of future wind speeds exceeding 25 m / s and the value range is limited to 0 to 1. An increase in the value of extreme wind risk tail intensity indicates an increase in extreme wind risk.

6. The wind power generation site selection method based on paleostorm depositional background according to claim 1, characterized in that, The S500 specifically includes: S500.1 Configure hard constraint filtering, generate a candidate region input set, configure comprehensive scoring rules, and output the preferred region boundary; This study introduces a set of future wind energy assessment parameters, a wind direction stability parameter grid, a paleowind direction stability index, and a geological safety constraint factor. The wind energy density threshold is set to 220 W / m³, the effective hours threshold is set to 2600 h, the extreme wind risk tail intensity threshold is set to 0.03, the wind direction stability threshold is set to 0.65, the paleowind direction stability threshold is set to 0.70, and the soft sediment deformation risk coding threshold is set to 1. Within the spatial grid of the study area, grid cells simultaneously satisfy the following conditions: wind energy density not less than 220 W / m³, effective hours not less than 2600 h, extreme wind risk tail intensity not greater than 0.03, wind direction stability parameter grid value not less than 0.65, wind direction stability index not less than 0.70, soft deposition deformation risk code not greater than 1, and low stability boundary marker not covered, and are written into the candidate area input set. The wind resource benefit score is derived by normalizing the wind energy density and effective hours and then weighting the sum by 0.6 and 0.4 respectively. The wind direction stability benefit score is derived by normalizing the grid value of the wind direction stability parameter and the wind direction stability index and then weighting the sum by 0.5 and 0.5 respectively. The project accessibility benefit score is derived. The project accessibility benefit score is jointly determined by the road access distance and the grid connection distance. The road access distance is defined as the shortest horizontal distance from the candidate area input set grid cell to the centerline of the existing road. The grid connection distance is defined as the shortest horizontal distance from the candidate area input set grid cell to the boundary of the existing power transmission and distribution line corridor. The comprehensive score is calculated using a weighted summation rule, taking the comprehensive score as 0.45 × wind resource benefit score + 0.30 × wind direction stability benefit score + 0.20 × engineering accessibility benefit score - 0.05 × geological risk penalty score. This comprehensive score is written into the comprehensive score raster. The comprehensive score threshold is set to 0.

65. Connected raster cells with a comprehensive score of not less than 0.65 are aggregated into a set of connected domains in the preferred area. The area threshold for the connected domains in the preferred area is set to 0.80 km². Connected domains with an area of ​​not less than 0.80 km² in the preferred area are output as the boundary vector of the preferred area. S500.2 Output the candidate region list and bind the evidence chain index and uncertainty level; The threshold for the number of items in the candidate area list is set to 20. The set of connected components of the preferred area is sorted according to the average comprehensive score. The boundary vectors of the top 20 preferred areas with the highest average comprehensive score are output as the candidate area list. The evidence chain index table is established item by item according to the candidate area list. The fields of the evidence chain index table include the set of storm event sedimentary record numbers, the set of directional evidence numbers, the entry number of the modern wind field sedimentary response calibration benchmark domain, the paleodominant wind direction, the paleowind direction stability index, and the low confidence segment coverage ratio of the paleowater depth change curve. The uncertainty level is determined by the ancient and modern wind direction deviation angle, the stability fusion index, and the coverage ratio of the low-confidence segment of the ancient water depth variation curve: when the ancient and modern wind direction deviation angle is not greater than 30°, the stability fusion index is not less than 0.70, and the coverage ratio of the low-confidence segment of the ancient water depth variation curve is not greater than 0.20, it is written as a first-level uncertainty level; When the deviation angle between ancient and modern wind direction is greater than 30° but not greater than 60°, or the stability fusion index is less than 0.70 but not less than 0.60, or the low-confidence segment coverage ratio of the paleowater depth variation curve is greater than 0.20 but not greater than 0.40, it is classified as a Level 2 uncertainty. When the ancient and modern wind direction deviation angle is greater than 60°, the stability fusion index is less than 0.60, or the low-confidence segment coverage ratio of the ancient water depth variation curve is greater than 0.40, it is written into the third level of uncertainty. Level 1 uncertainty, Level 2 uncertainty, and Level 3 uncertainty are bound to the candidate area list and output along with the candidate area list.

7. The wind power generation site selection method based on paleostorm depositional background according to claim 1, characterized in that, The S600 specifically includes: S600.1 Configure short-term wind measurement verification and foundation investigation verification, form a verification data set, calculate verification deviation, and write back to update the inversion coefficients and risk penalty items; A candidate area list is drawn up to form a short-term wind measurement verification point set. The short-term wind measurement verification point set is deployed within the boundary vector of the preferred area corresponding to the candidate area list. The lower limit of the number of short-term wind measurement verification points is set to 2, and the lower limit of the spacing between short-term wind measurement verification points is set to 500m. A short-term wind measurement verification record set is formed, which includes the coordinates of the wind measurement point, sampling timestamp, 10-minute average wind speed, and 10-minute average wind direction. The lower limit of the short-term wind measurement verification period is set to 30 days, and the threshold for the missing measurement ratio of the short-term wind measurement verification record set is set to 5%. A set of foundation investigation verification points is formed, which corresponds to the set of short-term wind measurement verification points, forming a set of foundation investigation verification records. The set of foundation investigation verification records includes the coordinates of the investigation points, the borehole depth, the bearing capacity characteristic value, and the groundwater depth. The lower limit of the borehole depth is set to 15m, the threshold of the bearing capacity characteristic value is set to 180kPa, and the threshold of the groundwater depth is set to 1.5m. Within the short-term wind measurement verification period, the 10-minute average wind speed is calculated as the equivalent wind speed mean parameter for short-term wind measurement verification. The equivalent wind speed mean parameter for short-term wind measurement verification is registered with the future equivalent wind speed mean parameter to form a wind speed verification deviation sequence. The spatial weight coefficients of the wind speed verification deviation sequence are then written back to update the wind source basin assimilation and fusion solution model. Value selection strategy and surface roughness correction coefficient The value retrieval strategy and write-back update adopt the inversion coefficient self-calibration parameter. Express; The set of foundation investigation and verification records is mapped to the update value of geological risk penalty score. When the bearing capacity characteristic value is less than 180 kPa, the geological risk penalty score is updated to 1.

0. When the groundwater depth is less than 1.5 m, the geological risk penalty score is updated to 1.

0. When the bearing capacity characteristic value is not less than 180 kPa and the groundwater depth is not less than 1.5 m, the original value of the geological risk penalty score is maintained. After the geological risk penalty score update is completed, the comprehensive score grid is recalculated and the candidate area list is updated. S600.2 Configure the iteration termination conditions and solidify the final site selection result package; Configure the model self-calibration iteration limit to 3, configure the root mean square error threshold of wind speed verification to 0.8 m / s, configure the boundary vector stability threshold of the preferred area to be no more than 5% of the area change ratio. When the root mean square error of wind speed verification is no more than 0.8 m / s and the boundary vector area change ratio of the preferred area is no more than 5%, the final candidate area list is output. When the model self-calibration iteration reaches 3, the final candidate area list is output. The final site selection result package is generated, which includes a wind rose overlay map, a wind energy zoning map, a geological risk overlay map, a candidate area boundary map, and an evidence chain list. The evidence chain list fields include a set of storm event sedimentary record numbers, a set of directional evidence numbers, modern wind field-sedimentary response calibration benchmark field entry numbers, paleodominant wind direction, paleowind direction stability index, and uncertainty level. The final site selection result package and the final candidate area list are then bound and output.

Images