Wind power plant equipment type selection and arrangement optimization method and system

Abstract

The invention belongs to the technical field of wind power plants, and provides a wind power plant equipment type selection and arrangement optimization method and system. The method comprises the following steps: determining a matched wind turbine generator type according to the wind speed level and trust level requirements of a wind power plant; rasterizing an area in a preset wind power plant boundary, setting each grid vertex as a fan location point, and optimizing a wind turbine generator arrangement scheme of a determined type by taking the maximum power generation capacity of the whole wind power plant as an optimization target to obtain a micro-siting layout scheme; based on a preset noise evaluation model, correcting the post-micrositing layout scheme; taking a site in the boundary of the wind power plant with the lowest total cost as a site selection result of the booster station; and based on related information of a wind power plant site selection map, determining optimal results of a wind power plant road and a current collection line by taking the minimum total cost of road construction and the minimum project amount of the current collection line as targets, and finally obtaining a wind power plant equipment type selection and arrangement optimization scheme.

Description

Technical Field

[0001] The present invention belongs to the technical field of wind farms, and in particular relates to a method and system for optimizing the selection and layout of wind farm equipment. Background Art

[0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art.

[0003] Wind farm planning and design usually starts with wind resource calculation, unit selection and optimal layout, road and collector line design, and finally economic and environmental evaluation. At present, due to the lack of integrated wind farm planning and design technology, each link is carried out relatively independently and optimized separately, without considering the dependencies between the links, sacrificing the potential for overall optimization, and it is difficult to reduce costs and increase efficiency from a global perspective. Summary of the invention

[0004] In order to solve the above technical problems, the present invention provides a method and system for optimizing the selection and layout of wind farm equipment, which integrates the design of various links in wind farm planning and design, improves the overall optimization capability of the wind farm on the premise that there is a dependency relationship between the links, and can achieve global cost reduction and efficiency improvement of the wind farm.

[0005] In order to achieve the above object, the present invention adopts the following technical solution: A first aspect of the present invention provides a method for optimizing the selection and layout of wind farm equipment.

[0006] In one or more embodiments, a method for optimizing wind farm equipment selection and layout is provided, comprising: Determine the matching wind turbine type according to the wind speed level and trust level requirements of the wind farm; The area within the preset wind farm boundary is gridded, and each grid vertex is set as a wind turbine site. Taking the maximum power generation of the wind farm as the optimization goal, the layout plan of wind turbines of a certain type is optimized to obtain a micro-site selection and layout plan; Under the micro-site selection and layout plan, the influence range of each unit is calculated and drawn based on the preset noise assessment model, and a noise cloud map is synthesized. The location of the unit that affects the sensitive area of ​​residents is adjusted based on the noise cloud map, and the protection distance of the sensitive area is reserved to obtain the revised micro-site selection and layout plan; Based on the revised micro-site selection and layout plan, with the wind farm boundary, the locations of each wind turbine, the sensitive area and the farthest distance from the booster station to the location as constraints, the site within the wind farm boundary with the lowest total cost is selected as the booster station site selection result; The substation site selection results and the revised micro-site selection and layout plan are associated with the map within the preset wind farm boundary to construct a wind farm site selection map. Based on the relevant information of the wind farm site selection map, the optimal results of wind farm roads and collector lines are determined with the goals of minimizing the total road construction cost and the minimum collector line engineering volume, and finally the optimization plan for wind farm equipment selection and layout is obtained.

[0007] As an implementation method, in the process of optimizing the layout plan of a certain type of wind turbines, the wind turbines are arranged in a grid shape with a parallelogram as the smallest unit, and the relevant parameters of the parallelogram are iteratively optimized to obtain a regular layout plan of wind turbines with the maximum power generation in the entire wind farm.

[0008] As an implementation method, according to the principle of regular arrangement of wind turbines, a grid enumeration algorithm based on equal spacing or a genetic algorithm based on equal spacing is used to optimize and iterate the relevant parameters of the parallelogram; wherein the relevant parameters of the parallelogram include the azimuth of the long side of the parallelogram, the angle between the long side and the short side, the length of the long side, the length of the short side, the long side offset and the short side offset.

[0009] As an implementation method, a genetic algorithm based on real number coding is used to encrypt the grid in areas where the elevation and wind power density are greater than a set threshold, and determine a regular arrangement plan for wind turbines with the highest power generation in the entire wind farm.

[0010] As an implementation method, the relevant parameters of the parallelogram are optimized and iterated with the non-uniform spacing layout of the wind farm; wherein the relevant parameters of the parallelogram include the azimuth of the long side of the parallelogram, the angle between the long side and the short side, the length of the long side, the length of the short side, the long side offset, the short side offset, the short side distance diffusion coefficient and the long side distance diffusion coefficient.

[0011] As an implementation method, the process of calculating and drawing the influence range of each unit based on the preset noise assessment model is as follows: Discretize the ground near the wind turbine into a number of grids, divide the period to be evaluated into minute-level time periods, and obtain a first horizontal distance between the highest point of the wind turbine rotor and the ground projection point and a second horizontal distance between the lowest point of the wind turbine rotor and the ground projection point according to the azimuth of the sun in each minute-level time period, wherein the first distance and the second distance are both the horizontal distances between the ground projection point and the wind turbine; For any grid to be evaluated, determine whether it coincides with the projection direction at this time according to the direction of the center of the grid to be evaluated relative to the wind turbine rotor. If it coincides, determine whether the horizontal distance from the center of the grid to be evaluated to the wind turbine is between the second horizontal distance and the first horizontal distance. If so, determine that the grid to be evaluated is affected, add a minute-level period to the affected time, and continue to determine until the grid to be evaluated is not affected, so as to obtain the affected time period and / or cumulative affected time of each grid in the entire period to be evaluated, and then construct a noise cloud map.

[0012] As an implementation mode, when the azimuth direction of the sun relative to the wind turbine coincides with the incoming wind direction, the backlit shadow area of ​​the circular surface swept by the wind turbine rotor is a cylinder with an axis L1 and a diameter D, wherein L1 is a straight line from the center of the wind turbine rotor to the ground parallel to the sun's rays, D is the diameter of the wind turbine rotor, and the ground at the interface of the cylinder is the shadow area of ​​the wind turbine rotor; When the sun's azimuth relative to the wind turbine does not coincide with the incoming wind direction, the wind turbine rotor tracks the wind direction and rotates. The backlit shadow area of ​​the circular surface swept by the wind turbine rotor is an elliptical cylinder, and the interface of the ground on the elliptical cylinder is the shadow area projected by the wind turbine rotor.

[0013] As an implementation method, in the process of determining the wind farm road, an objective function of the weighted total road construction cost is constructed based on the road construction cost of each road section, the road longitudinal slope coefficient, the road longitudinal slope gradient, the road turning radius coefficient, the road earthwork cost coefficient, the filling volume, the excavation volume, the unit excavation cost and the unit filling cost.

[0014] A second aspect of the present invention provides a wind farm equipment selection and layout optimization system.

[0015] In one or more embodiments, a wind farm equipment selection and layout optimization system includes: A wind turbine type determination module, which is used to determine the matching wind turbine type according to the wind speed level and trust level requirements of the wind farm; A preliminary determination module for the micro-site selection and layout plan is used to grid the area within the preset wind farm boundary, with each grid vertex set as a wind turbine site. The maximum power generation of the wind farm is taken as the optimization goal, and the arrangement plan of wind turbines of a certain type is optimized to obtain a micro-site selection and layout plan; A micro-site selection and layout scheme correction module is used to calculate and draw the influence range of each unit based on a preset noise assessment model and synthesize a noise cloud map under the micro-site selection and layout scheme, adjust the location of the unit that affects the sensitive area of ​​residents based on the noise cloud map and reserve a protection distance for the sensitive area, and obtain a corrected micro-site selection and layout scheme; The booster station site selection module is used to select the site within the wind farm boundary with the lowest total construction cost as the booster station site selection result based on the revised micro-site selection layout plan, with the wind farm boundary, the site of each wind turbine, the sensitive area and the maximum distance from the booster station to the site as constraints; The wind farm road and collector line determination module is used to associate the booster station site selection results and the revised micro-site selection layout plan with the map within the preset wind farm boundary, construct a wind farm site selection map, and then based on the relevant information of the wind farm site selection map, determine the optimal results of wind farm roads and collector lines with the goals of minimizing the total road construction cost and the collector line engineering volume, and finally obtain the wind farm equipment selection and layout optimization plan.

[0016] A third aspect of the present invention provides a computer-readable storage medium.

[0017] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps in the above-mentioned method for optimizing the selection and layout of wind farm equipment.

[0018] A fourth aspect of the present invention provides an electronic device.

[0019] An electronic device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps in the above-mentioned method for optimizing the selection and layout of wind farm equipment are implemented.

[0020] Compared with the prior art, the present invention has the following beneficial effects: (1) The present invention integrates the wind farm wind turbine selection, micro-site selection and layout, micro-site selection and layout correction after noise assessment, substation site selection, and wind farm road and collector line selection into an integrated design of wind farm planning and design, taking into account the dependencies between the various links, thereby improving the overall optimization capability of the wind farm and achieving overall cost reduction and efficiency improvement of the wind farm.

[0021] (2) In the process of optimizing the arrangement of wind turbines, the present invention iteratively optimizes the relevant parameters of the parallelogram, which can generate a wider range of calculation results during the optimization, so that the optimization algorithm has excellent adaptability and improves the optimization accuracy. The wind energy utilization efficiency and power generation of the wind farm are improved, and the optimization result is applicable to the micro-site selection optimization of wind farms on flat terrain and at sea.

[0022] (3) The present invention simplifies the light and shadow model of the wind turbine rotor at each evaluation moment into a circular surface facing the incoming wind direction, thereby achieving a more accurate evaluation of the wind turbine light and shadow, and further enabling the optimization of the layout of photovoltaic modules near the wind turbine, thereby increasing photovoltaic power generation on the basis of the same photovoltaic module layout area.

[0023] (4) The present invention comprehensively considers the siting requirements of the booster station in a mountain wind farm, optimizes the alternative siting options for the booster station, considers the earthwork weighted algorithm and the total length of the booster station from each unit, and optimizes the siting options for the booster station in a mountain wind farm by comparing the total cost. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The accompanying drawings in the specification, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0025] Figure 1 is a flow chart of a method for optimizing the selection and layout of wind farm equipment according to an embodiment of the present invention; Figure 2 1. It is a schematic diagram of the structure of a wind farm equipment selection and layout optimization system according to an embodiment of the present invention; Figure 3 is a schematic diagram of an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0026] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0027] It should be noted that the following detailed descriptions are all illustrative and intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present invention belongs.

[0028] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit exemplary embodiments according to the present invention. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprising" and / or "including" are used in this specification, it indicates the presence of features, steps, operations, devices, components and / or combinations thereof.

[0029] Figure 1 FIG. 1 is a flow chart of a method for optimizing the selection and layout of wind farm equipment in an embodiment of the present invention. Figure 1 The wind farm equipment selection and layout optimization method in the embodiment shown may include: S101, determining a matching wind turbine type according to the wind speed level and trust level requirements of the wind farm; S102, gridding the area within the preset wind farm boundary, setting each grid vertex as a wind turbine site, optimizing the layout of wind turbines of a certain type with the maximum power generation of the wind farm as the optimization goal, and obtaining a micro-site selection and layout plan; S103, under the micro-site selection and layout plan, based on the preset noise assessment model, the influence range of each unit is calculated and drawn and a noise cloud map is synthesized, and the location of the unit that affects the sensitive area of ​​residents is adjusted based on the noise cloud map and a protection distance for the sensitive area is reserved to obtain a revised micro-site selection and layout plan; S104, based on the revised micro-site selection and layout plan, taking the wind farm boundary, the sites of each wind turbine, the sensitive area and the farthest distance from the booster station to the site as constraints, the site within the wind farm boundary with the lowest total construction cost is selected as the booster station site selection result; S105, the booster station site selection results and the revised micro-site selection layout plan are associated with the map within the preset wind farm boundary to construct a wind farm site selection map, and then based on the relevant information of the wind farm site selection map, the optimal results of the wind farm roads and collector lines are determined with the minimum total road construction cost and the minimum collector line engineering volume as the goals, and finally the wind farm equipment selection and layout optimization plan is obtained.

[0030] This embodiment integrates the wind farm wind turbine selection, micro-site selection and layout, micro-site selection and layout correction after noise assessment, substation site selection, and wind farm road and collector line selection, and wind farm planning and design into an integrated design, taking into account the dependencies between the various links, improving the overall optimization capability of the wind farm, and achieving global cost reduction and efficiency improvement of the wind farm.

[0031] In step S101, under the conditions that the capacity and boundary of the wind farm are known, the type of unit suitable for the wind farm is selected in combination with the rotor diameter, the rated power of a single unit, and the wind speed conditions at the location of the wind farm. For the selected wind turbine types, the values ​​greater than 0.48 in their thrust coefficient curves are evaluated for trust levels, and the product of the trust level coefficients of the corrected values ​​is the trust level of the wind turbine in the final wind turbine type selection scheme.

[0032] In step S102, during the optimization of the wind turbine arrangement scheme of a determined type, the wind turbines are arranged in a grid shape with a parallelogram as the smallest unit, and the relevant parameters of the parallelogram are iteratively optimized to obtain a regular arrangement scheme of wind turbines with the maximum power generation in the entire wind farm.

[0033] In one or more embodiments, according to the principle of regular arrangement of wind turbines, a grid enumeration algorithm based on equal spacing or a genetic algorithm based on equal spacing is used to optimize and iterate the relevant parameters of the parallelogram; wherein the relevant parameters of the parallelogram include the azimuth of the long side of the parallelogram, the angle between the long side and the short side, the length of the long side, the length of the short side, the long side offset and the short side offset. This method is applicable to plain and offshore wind farms.

[0034] In other embodiments, a genetic algorithm based on real number coding is used to encrypt the grid in areas where the elevation and wind power density are greater than a set threshold, and determine a regular arrangement of wind turbines with the largest power generation in the wind farm. Prioritize screening during the iterative process of the genetic algorithm to improve the efficiency of the genetic algorithm.

[0035] In other optional embodiments, the relevant parameters of the parallelogram are optimized and iterated with the non-equidistant layout of the wind farm; wherein the relevant parameters of the parallelogram include the azimuth of the long side of the parallelogram, the angle between the long side and the short side, the length of the long side, the length of the short side, the offset of the long side, the offset of the short side, the diffusion coefficient of the short side distance and the diffusion coefficient of the long side distance. By introducing the two parameters of the diffusion coefficient of the short side distance and the diffusion coefficient of the long side distance, the non-equidistant layout of the wind farm is realized, and the power generation loss caused by the terrain, environmental turbulence, etc. is reduced. After the algorithm iteration is completed, the total power generation, average wake loss, unit cost, wind turbine foundation cost and total hoisting cost calculated by the corresponding model scheme are output.

[0036] Before formulating the wind turbine layout plan, it is necessary to clarify the site boundaries of the wind farm and the scope of the sensitive area, and use polygons to illustrate the wind farm boundaries and sensitive areas; the wind farm boundaries and sensitive area data are extracted from the map data file or directly obtained from the Excel file.

[0037] In the optimal layout of wind turbines in a wind farm, a grid shape with a parallelogram as the smallest unit is set, and the following assumptions are made for the model: the coordinates of the origin of the coordinate system are (Cx, Cy), the azimuth of the long side is θx, the angle between the long side and the short side is θy, the distance between the starting point and the adjacent point on the short side is Lx1, the distance between the starting point and the adjacent point on the long side is Ly1, the short side distance diffusion coefficient is Sx, and the long side distance diffusion coefficient is Sy.

[0038] When the short side distance diffusion coefficient Sx and the long side distance diffusion coefficient Sy are both equal to 1, the grid is arranged evenly and regularly; when Sx and Sy are not 1, the grid is arranged irregularly. When the starting point is at the boundary, the grid is arranged only to this side of the site, and not to the outside of the boundary; when the starting point is at the center of the site, the grid is arranged to both sides.

[0039] Specifically, the present implementation adopts a general model of an eight-variable variable spacing layout method: Cx, Cy, θx, θy, Lx1, Ly1, Sx, and Sy. In the regular layout optimization process of wind turbines, the maximum power generation of the entire wind farm is taken as the optimization goal, and the above eight parameters are iteratively selected to finally obtain a regular layout scheme for wind turbines that meets the above requirements.

[0040] In step S103, the process of calculating and drawing the influence range of each unit based on the preset noise assessment model is as follows: Discretize the ground near the wind turbine into a number of grids, divide the period to be evaluated into minute-level time periods, and obtain a first horizontal distance between the highest point of the wind turbine rotor and the ground projection point and a second horizontal distance between the lowest point of the wind turbine rotor and the ground projection point according to the azimuth of the sun in each minute-level time period, wherein the first distance and the second distance are both the horizontal distances between the ground projection point and the wind turbine; For any grid to be evaluated, determine whether it coincides with the projection direction at this time according to the direction of the center of the grid to be evaluated relative to the wind turbine rotor. If it coincides, determine whether the horizontal distance from the center of the grid to be evaluated to the wind turbine is between the second horizontal distance and the first horizontal distance. If so, determine that the grid to be evaluated is affected, add a minute-level period to the affected time, and continue to determine until the grid to be evaluated is not affected, so as to obtain the affected time period and / or cumulative affected time of each grid in the entire period to be evaluated, and then construct a noise cloud map.

[0041] Specifically, when the azimuth direction of the sun relative to the wind turbine coincides with the incoming wind direction, the backlit shadow area of ​​the circular surface swept by the wind turbine rotor is a cylinder with axis L1 and diameter D, wherein L1 is a straight line from the center of the wind turbine rotor to the ground parallel to the sun's rays, D is the diameter of the wind turbine rotor, and the ground at the interface of the cylinder is the shadow area of ​​the wind turbine rotor; When the sun's azimuth relative to the wind turbine does not coincide with the incoming wind direction, the wind turbine rotor tracks the wind direction and rotates. The backlit shadow area of ​​the circular surface swept by the wind turbine rotor is an elliptical cylinder, and the interface of the ground on the elliptical cylinder is the shadow area projected by the wind turbine rotor.

[0042] The ground near the wind turbine is discretized into many small grids and a year is divided into 10 minutes (i.e. minute-level time periods). In each minute-level time period, whether the small grid is affected by the shadow is determined based on whether the direction of the center of the small grid on the ground relative to the wind turbine coincides with the direction of the shadow at this time, and the horizontal distance from the center of the small grid on the ground to the wind turbine. If affected, the affected time of the small grid will be increased by 10 minutes (i.e. one minute-level time period is added).

[0043] Calculating the solar altitude angle is the basis for studying the light and shadow flicker of wind turbines. The calculation formula for the solar altitude angle is as follows:

[0044] Where: is the local latitude, deg ; is the solar declination angle, deg ; is the solar hour angle, deg .

[0045] Where: Solar declination angle for:

[0046] Where: n To calculate the sequence of days of the year for the current day.

[0047] The specific calculation time and Beijing time can be converted according to the following formula: ; Where: L is the measured local latitude; E To correct the time difference, the calculation formula is as follows:

[0048] In the formula, .

[0049] After calculating the solar altitude angle, the projection length of the wind turbine rotor during this period can be calculated. First, calculate the projection distance of the top of the wind turbine rotor. L1 : ; Wherein, D1 is the sum of the top of the wind turbine rotor and the elevation difference between the sensitive point and the wind turbine coordinates, in meters.

[0050] Then calculate the projection distance of the lower end of the fan rotor L2 : ; in, D2 It is the sum of the lowest point of the wind turbine rotor and the elevation difference between the sensitive point and the wind turbine coordinates, in meters.

[0051] The ground near the wind turbine is discretized into many small grids and a year is divided into 10 minutes. In each 10-minute period, whether it is affected is determined based on whether the direction of the center of the small grid relative to the wind turbine coincides with the shadow direction at that time and whether the distance from the center of the grid to the wind turbine is less than the shadow length calculated according to the formula. If affected, the affected time of the small grid is added with 10 minutes. According to this method, the number of hours the ground around the wind turbine is affected can be calculated.

[0052] In this implementation, the light and shadow effects of the wind turbine wheel can be combined with the light and shadow effects of the tower model. The tower model does not rotate and can be implemented using existing methods. It only needs to superimpose the light and shadow effects of the wind turbine wheel described in this implementation.

[0053] When calculating the area affected by the wind rotor shadow, the implementation method uses the wind turbine to track the wind direction to form a brake disc. The projected area of ​​the brake disc is smaller than that of a sphere, and the sweeping range of the wind rotor is simplified to a circular surface to more accurately simulate the actual situation. This is used as a simplified model of the wind turbine in the geographic coordinates to evaluate and calculate the impact of light and shadow. The wind direction time series is taken into account to make the light and shadow model more accurate, which is beneficial to the optimization of the layout of photovoltaic panels near the wind turbine, such as arranging them in the grid with the least light and shadow area in a year.

[0054] In step S104, during the determination of the site selection of the booster station: Step S1041: Establish a digital elevation model based on the boundary range of the wind farm, the determined wind turbine machine sites and the sensitive areas, and delineate candidate sites for booster stations in the mountainous wind farm area based on the digital elevation model.

[0055] Determine the capacity and geometric dimensions of the booster station in a mountain wind farm. Generally, the capacity of the booster station in a wind farm is equal to the total capacity of the wind turbines connected to it. However, due to factors such as manufacturing specifications and expansion requirements, the design capacity of the booster station is often greater than the installed capacity of the wind farm. In this implementation, it is necessary to determine the capacity of the booster station transformer and land use indicators according to the capacity of the wind farm in accordance with relevant regulations. The power consumption indicator table of a single wind turbine substation is shown in Table 1 as an example.

[0056] Table 1 Electricity consumption index table of substation of single wind turbine

[0057] Sensitive areas include ecosystem protection areas, historical and cultural sites, and residential areas. The site selection of wind farm booster stations should avoid sensitive areas as much as possible to minimize the impact on sensitive areas of wind farms.

[0058] In addition to sensitive areas, the considered wind farm booster station site selection constraints are shown in Table 2.

[0059] Table 2 Limiting factors for site selection of wind farm booster stations

[0060] S1042: connecting adjacent three-dimensional coordinates on the digital elevation model to generate a plurality of triangular pyramids, calculating the earthwork excavation volume of each triangular pyramid, superimposing to obtain the earthwork volume of each candidate site of the mountain wind farm at the design elevation, using an earthwork weighting factor to correct the earthwork volume of the candidate site of the booster station to obtain the final earthwork volume of each candidate site, and obtaining the weighted earthwork cost of each candidate site according to the earthwork volume of each candidate site; The site selection optimization process mainly includes the comparison of earthwork volume and distance engineering volume of the alternative sites. This implementation method designs a weighted earthwork algorithm for the substation. Considering the possible complex terrain conditions in the mountains, the earthwork weighted algorithm mainly adopts the digital ground model method. Through the existing model three-dimensional coordinates (x , y , z ) Adjacent coordinate points are connected to generate a triangulated network to calculate the earthwork excavation volume of each triangular pyramid. The earthwork excavation volume of each triangular pyramid calculated by the software is superimposed to obtain the earthwork volume of the alternative site for the mountain wind farm booster station at the design elevation. Considering the influence of actual engineering factors, it is necessary to use the earthwork weighting factor to correct the calculation results. The earthwork weighting factor of this implementation method is mainly determined by terrain, environmental conditions, engineering requirements, and site factors.

[0061]

[0062] In the formula, e is the earthwork weighting factor; T is the terrain factor, which reflects the influence of different terrain characteristics on the earthwork volume estimation; S is the site factor, reflecting the influence of site factors such as soil type and soil quality; E It is the engineering factor, which reflects the influence of the actual conditions of the project on the earthwork estimate; En It is an environmental factor, which reflects the impact of environmental factors such as temperature and rainfall on earthwork estimation.

[0063] S1043: According to the digital elevation model, automatically selecting a fitting point that meets the conditions from two points that need to be calculated for distance, using a distance fitting method to calculate the total distance between the candidate site and each unit, and calculating the weighted road cost of each candidate site according to the weighted road cost coefficient and the total distance; S1044: The total cost is taken as the sum of the weighted earthwork cost and the weighted road cost of the candidate sites, and the candidate site with the lowest total cost is taken as the final booster station site selection result.

[0064] In the process of determining the wind farm road, an objective function of the weighted total road construction cost is constructed based on the road construction cost of each road section, road longitudinal slope coefficient, road longitudinal slope gradient, road turning radius coefficient, road earthwork cost coefficient, filling volume, excavation volume, unit excavation cost and unit filling cost.

[0065] The calculation points of the distance engineering quantity are fitted with the established DEM model. In order to improve the calculation accuracy, the fitting points that meet the conditions are automatically selected from the two points where the distance calculation is required, and the longer road engineering is fitted into a combination of multiple shorter roads. Taking the road points A and G to be calculated as an example, the fitting points B, C, D, E, and F are inserted in the road calculation process, and the distance calculation of road AE is converted into the sum of the distances of AB, BC, CD, DE, and EF. At the same time, considering the impact of the model accuracy on the distance fitting results, the distance fitting coefficient is added for correction. The fitting distance calculation formula between any two is as follows:

[0066] In the formula, xA , yA,zA are the ordered numerical arrays of the DEM model of point A, xB , yB, zB They are the ordered numerical arrays of the DEM model of point B; l is the distance fitting coefficient.

[0067] This implementation method uses the distance fitting method to calculate the total distance between the booster station site and each unit. To meet the actual project requirements, the distance between the booster station site and each unit should be less than the longest connection distance of the corresponding collector line. On this basis, the road cost is determined by the road weighted cost coefficient and the road distance. The road weighted cost coefficient is the unit distance construction cost of the local road. Considering factors such as land acquisition cost, construction conditions, design cost, labor cost, and material cost, this implementation method sets a benchmark road cost coefficient to reflect the local road construction benchmark cost at the wind farm booster station site. Taking into account the different construction conditions of each section of road, the benchmark road cost coefficient is corrected to determine the road weight for each section of road. According to the distance engineering quantity calculation, this implementation method establishes a road weighted cost model:

[0068]

[0069] In the formula, Q Add weighted cost to roads; qi For the i Weighted cost coefficient of road section; Li For the i Distance of road section; αi For the i The terrain cost coefficient of the road section; βi is the slope cost coefficient of the i-th section of road; γi For the i Cost coefficient of road curvature; c is the base road cost coefficient; ei For the i Earthwork cost coefficient for road section.

[0070] On this basis, this implementation method establishes the optimization processing of alternative plans. This implementation method calculates the total cost according to the weighted earthwork cost model and the weighted road construction cost model, and calculates the unit kilometer cost price according to the ratio of the total cost to the distance engineering volume. Finally, according to the comparison of the total cost, the plan with the lowest total cost is selected as the recommended optimal plan.

[0071] In step S105, the process of determining the optimal result of the wind farm road with the minimum total road construction cost includes: According to the wind farm boundary, prohibited construction area, confirmed machine site, road access point and road delivery point, the area where topographic map needs to be generated is exported from Aowei Map in .kmz or .kml format; the obtained .kmz or .kml format file is imported into Global Mapper, the contour interval value is modified to 10, the topographic map is generated and the horizontal and elevation data are extracted; For the acquired map data, the approximate geodesic method is used to calculate the distance between two points. Specifically, firstly, project points A and E to the ground to generate points A' and E', insert multiple points B', C', D'...M', N' into the line connecting points A'E', and then find the points B, C, E...M, N projected to the actual terrain by these three points. The path length between points AE is approximately converted into the sum of the Euclidean distances between AB, BC, CD, DE...MN. The distance calculation formula between any two points is as follows:

[0072] in xA , y , Z They are A The coordinates and elevation of the point, B I agree.

[0073] A weighted total cost function model for road construction is established, specifically:

[0074]

[0075]

[0076]

[0077]

[0078]

[0079] in, Ct is the weighted total road construction cost; Ci For the i Cost of road construction; αi For the i Longitudinal slope coefficient of section road; si For the i The longitudinal slope of the road section; βi For the i Turning radius coefficient of road section; E , Fi , Vi , , Respectivelyi The earthwork cost coefficient, filling volume, excavation volume, unit excavation cost and unit filling cost of the road section. The optimization goal is to minimize the total weighted road construction cost. minCt .

[0080] Based on the determined unit coordinates and road access points and delivery points, the minimum weighted total road construction cost is optimized.

[0081] In step S105, the process of determining the optimal result of the collector line includes: A clustering algorithm is used to divide the collector line loops of the units and delineate the subordinate booster stations. Taking the wind farm boundary, sensitive area, cable limit area, maximum line voltage drop and other constraints as constraints, a greedy algorithm is used to generate the initial solution of the collector line. The layout plan is matched to the collector line topology structure, and the random forest algorithm or genetic algorithm is further used to optimize the initial solution to obtain the optimal solution for the collector line engineering volume.

[0082] Figure 2 is a schematic diagram of a wind farm equipment selection and layout optimization system structure in an embodiment of the present invention. Figure 1 The wind farm equipment selection and layout optimization method corresponds to Figure 2 As shown, the wind farm equipment selection and layout optimization system in this embodiment may include: A wind turbine type determination module 201 is used to determine a matching wind turbine type according to the wind speed level and trust level requirements of the wind farm; A preliminary determination module 202 for micro-site selection and layout is used to grid the area within the preset wind farm boundary, with each grid vertex set as a wind turbine site, and optimize the arrangement of wind turbines of a certain type with the maximum power generation of the wind farm as the optimization goal, to obtain a micro-site selection and layout plan; The micro-site selection and layout scheme correction module 203 is used to calculate and draw the influence range of each unit based on the preset noise assessment model and synthesize the noise cloud map under the micro-site selection and layout scheme, adjust the unit position that affects the sensitive area of ​​residents based on the noise cloud map and reserve the protection distance of the sensitive area, and obtain the corrected micro-site selection and layout scheme; A booster station site selection module 204 is used to select the site within the wind farm boundary with the lowest total construction cost as the booster station site selection result based on the revised micro-site selection layout plan, with the wind farm boundary, the site of each wind turbine, the sensitive area and the farthest distance from the booster station to the site as constraints; The wind farm road and collector line determination module 205 is used to associate the booster station site selection results and the revised micro-site selection layout plan with the map within the preset wind farm boundary, construct a wind farm site selection map, and then based on the relevant information of the wind farm site selection map, determine the optimal results of the wind farm roads and collector lines with the minimum total road construction cost and the minimum collector line engineering volume as the goals, and finally obtain the wind farm equipment selection and layout optimization plan.

[0083] It should be noted here that Figure 2 Each module in the wind farm equipment selection and layout optimization system is related to Figure 1 Each step in the wind farm equipment selection and layout optimization method in the embodiment corresponds to each other, and the specific implementation process is the same, which will not be repeated here.

[0084] Reference Figure 3 , a schematic diagram of an electronic device is given. It should be noted that, Figure 3 The electronic device 300 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0085] like Figure 3 As shown, the electronic device 300 includes a central processing unit (CPU) 301, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 302 or the program loaded from the storage part 308 to the random access memory (RAM) 303. In the RAM 303, various programs and data required for system operation are also stored. The central processing unit 301, the ROM 302 and the RAM 303 are connected to each other through a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304.

[0086] The following components are connected to the I / O interface 305: an input section 306 including a keyboard, a mouse, etc.; an output section 307 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 308 including a hard disk, etc.; and a communication section 309 including a network interface card such as a local area network (LAN) card, a modem, etc. The communication section 309 performs communication processing via a network such as the Internet. A drive 310 is also connected to the I / O interface 305 as needed. A removable medium 311, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 310 as needed, so that a computer program read therefrom is installed into the storage section 308 as needed.

[0087] When the central processing unit 301 in the electronic device of this embodiment executes the program, the following is achieved: Figure 1 The steps in the wind farm equipment selection and layout optimization method are shown.

[0088] In particular, according to an embodiment of the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present application includes a computer program product, which includes a computer program carried on a computer readable medium, the computer program including a computer program for executing Figure 1 In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 309, and / or installed from the removable medium 311. When the computer program is executed by the central processing unit 301, various functions defined in the apparatus of the present application are executed.

[0089] in, Figure 1 The computer program instructions corresponding to the method shown may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce a product including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0090] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium, and when the program is executed, it can include the processes of the embodiments of the above-mentioned methods. The storage medium can be a disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM), etc.

[0091] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for optimizing the selection and layout of wind farm equipment, characterized in that: include: Determine the matching wind turbine type according to the wind speed level and trust level requirements of the wind farm; The area within the preset wind farm boundary is gridded, and each grid vertex is set as a wind turbine site. Taking the maximum power generation of the wind farm as the optimization goal, the layout plan of wind turbines of a certain type is optimized to obtain a micro-site selection and layout plan; Under the micro-site selection and layout plan, the influence range of each unit is calculated and drawn based on the preset noise assessment model, and a noise cloud map is synthesized. The location of the unit that affects the sensitive area of ​​residents is adjusted based on the noise cloud map, and the protection distance of the sensitive area is reserved to obtain the revised micro-site selection and layout plan; Based on the revised micro-site selection and layout plan, with the wind farm boundary, the locations of each wind turbine, the sensitive area and the farthest distance from the booster station to the location as constraints, the site within the wind farm boundary with the lowest total cost is selected as the booster station site selection result; The substation site selection results and the revised micro-site selection and layout plan are associated with the map within the preset wind farm boundary to construct a wind farm site selection map. Based on the relevant information of the wind farm site selection map, the optimal results of wind farm roads and collector lines are determined with the goals of minimizing the total road construction cost and the minimum collector line engineering volume, and finally the optimization plan for wind farm equipment selection and layout is obtained.

2. The method for optimizing wind farm equipment selection and layout according to claim 1, characterized in that: In the process of optimizing the layout plan of wind turbines of a certain type, the layout is carried out in a grid shape with a parallelogram as the smallest unit, and the relevant parameters of the parallelogram are iteratively optimized to obtain a regular layout plan of wind turbines with the maximum power generation in the entire wind farm.

3. The method for optimizing the selection and layout of wind farm equipment according to claim 2, characterized in that: According to the principle of regular arrangement of wind turbines, a grid enumeration algorithm based on equal spacing or a genetic algorithm based on equal spacing is used to iterate and optimize the relevant parameters of the parallelogram; wherein the relevant parameters of the parallelogram include the azimuth of the long side of the parallelogram, the angle between the long side and the short side, the length of the long side, the length of the short side, the long side offset and the short side offset.

4. The method for optimizing the selection and layout of wind farm equipment according to claim 2, characterized in that: A genetic algorithm based on real number coding is used to encrypt the grid in areas where the elevation and wind power density are greater than the set threshold, and determine the regular arrangement of wind turbines with the highest power generation in the wind farm. Or, the relevant parameters of the parallelogram are optimized and iterated with the non-uniform spacing layout of the wind farm; wherein the relevant parameters of the parallelogram include the azimuth of the long side of the parallelogram, the angle between the long side and the short side, the length of the long side, the length of the short side, the offset of the long side, the offset of the short side, the diffusion coefficient of the short side distance and the diffusion coefficient of the long side distance.

5. The method for optimizing wind farm equipment selection and layout according to claim 1, characterized in that: The process of calculating and drawing the influence range of each unit based on the preset noise assessment model is as follows: Discretize the ground near the wind turbine into a number of grids, divide the period to be evaluated into minute-level time periods, and obtain a first horizontal distance between the highest point of the wind turbine rotor and the ground projection point and a second horizontal distance between the lowest point of the wind turbine rotor and the ground projection point according to the azimuth of the sun in each minute-level time period, wherein the first distance and the second distance are both the horizontal distances between the ground projection point and the wind turbine; For any grid to be evaluated, determine whether it coincides with the projection direction at this time according to the direction of the center of the grid to be evaluated relative to the wind turbine rotor. If it coincides, determine whether the horizontal distance from the center of the grid to be evaluated to the wind turbine is between the second horizontal distance and the first horizontal distance. If so, determine that the grid to be evaluated is affected, add a minute-level period to the affected time, and continue to determine until the grid to be evaluated is not affected, so as to obtain the affected time period and / or cumulative affected time of each grid in the entire period to be evaluated, and then construct a noise cloud map.

6. The method for optimizing the selection and layout of wind farm equipment according to claim 5, characterized in that: When the sun's azimuth direction relative to the wind turbine coincides with the incoming wind direction, the backlit shadow area of ​​the circular surface swept by the wind turbine rotor is a cylinder with axis L1 and diameter D, where L1 is a straight line from the center of the wind turbine rotor to the ground parallel to the sun's rays, D is the diameter of the wind turbine rotor, and the ground at the interface of the cylinder is the shadow area of ​​the wind turbine rotor; When the sun's azimuth relative to the wind turbine does not coincide with the incoming wind direction, the wind turbine rotor tracks the wind direction and rotates. The backlit shadow area of ​​the circular surface swept by the wind turbine rotor is an elliptical cylinder, and the interface of the ground on the elliptical cylinder is the shadow area projected by the wind turbine rotor.

7. The method for optimizing wind farm equipment selection and layout according to claim 1, characterized in that: In the process of determining the wind farm road, an objective function of the weighted total road construction cost is constructed based on the road construction cost of each road section, road longitudinal slope coefficient, road longitudinal slope gradient, road turning radius coefficient, road earthwork cost coefficient, filling volume, excavation volume, unit excavation cost and unit filling cost.

8. A wind farm equipment selection and layout optimization system, characterized in that: include: A wind turbine type determination module, which is used to determine the matching wind turbine type according to the wind speed level and trust level requirements of the wind farm; A preliminary determination module for the micro-site selection and layout plan is used to grid the area within the preset wind farm boundary, with each grid vertex set as a wind turbine site. The maximum power generation of the wind farm is taken as the optimization goal, and the arrangement plan of wind turbines of a certain type is optimized to obtain a micro-site selection and layout plan; A micro-site selection and layout scheme correction module is used to calculate and draw the influence range of each unit based on a preset noise assessment model and synthesize a noise cloud map under the micro-site selection and layout scheme, adjust the location of the unit that affects the sensitive area of ​​residents based on the noise cloud map and reserve a protection distance for the sensitive area, and obtain a corrected micro-site selection and layout scheme; The booster station site selection module is used to select the site within the wind farm boundary with the lowest total construction cost as the booster station site selection result based on the revised micro-site selection layout plan, with the wind farm boundary, the site of each wind turbine, the sensitive area and the maximum distance from the booster station to the site as constraints; The wind farm road and collector line determination module is used to associate the booster station site selection results and the revised micro-site selection layout plan with the map within the preset wind farm boundary, construct a wind farm site selection map, and then based on the relevant information of the wind farm site selection map, determine the optimal results of wind farm roads and collector lines with the goals of minimizing the total road construction cost and the collector line engineering volume, and finally obtain the wind farm equipment selection and layout optimization plan.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps in the method for optimizing the selection and layout of wind farm equipment according to any one of claims 1 to 7 are implemented.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the steps in the method for optimizing the selection and layout of wind farm equipment according to any one of claims 1 to 7 are implemented.

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