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CN-122022515-A - Wind power plant automatic site selection system and method based on multi-index scoring such as terrain constraint and wake flow threshold check

CN122022515ACN 122022515 ACN122022515 ACN 122022515ACN-122022515-A

Abstract

The invention discloses an automatic wind farm site selection system and method based on multi-index scoring such as terrain constraint and wake flow threshold check, and belongs to the technical field of wind farm planning. The system comprises a data acquisition and processing module, an interactive visualization module, a wind direction analysis module, an automatic arrangement module, a multi-constraint check module, a result generation module, a traceability module and the like. The method comprises the steps of uniformly processing wind resources and terrain data, obtaining and aggregating wind direction weights, constructing a multi-index scoring model integrating terrain ridge degree, directivity, windward exposure degree and wind power score, adopting greedy strategy iteration to screen candidate points, executing minimum-distance-based hard constraint check and Jensen model-based wake rapid threshold check in parallel, and determining final machine position after local micro-movement optimization of passing points. The invention realizes automation and standardization of the site selection flow, solves the problems of different data apertures, large manual error and wake flow evaluation missing, and remarkably improves site selection efficiency, objectivity and traceability of the scheme.

Inventors

  • PENG HAO
  • ZHANG CHI
  • LIU YUHAO
  • YAN MIN
  • LIANG YANAN

Assignees

  • 瑞科同创电力工程设计有限公司

Dates

Publication Date
20260512
Application Date
20260123

Claims (10)

  1. 1. A wind farm automatic site selection system based on multi-index scoring such as terrain constraint and wake flow threshold check is characterized by comprising: The data acquisition and unified processing module is used for acquiring and uniformly processing wind resource data and digital elevation model data in a designated analysis area and generating a grid wind resource layer and a topographic layer with uniform coordinates and resolution; The interactive visual module is connected with the data acquisition and unified processing module and is used for visually rendering the grid wind resource layer and the topographic layer and providing a graphical user interface for parameter configuration and interaction; The wind direction rose acquisition and analysis module is used for acquiring wind direction frequency data of a plurality of representative points from the analysis area, carrying out normalization aggregation and generating direction weight data for machine position layout; The automatic arrangement and multi-constraint checking module is connected with the data acquisition and unified processing module, the interactive visualization module and the wind direction rose acquisition and analysis module and is used for screening candidate grids in the analysis area through a multi-index scoring model combining land ridge degree, directional fluctuation, windward exposure and wind power score based on the grid wind resource layer and the land map layer, carrying out iterative screening on the candidate grids by adopting a greedy strategy, carrying out equivalent distance hard constraint checking on candidate points in each iteration based on minimum distance multiple, and carrying out fast threshold checking on wake effects based on the Jensen engineering model and the direction weight data so as to determine final machine position layout; and the result generation and tracing module is used for exporting a result file containing the final machine position geographic information and recording system operation parameters and process logs.
  2. 2. The automatic wind farm location system based on multi-index scoring such as terrain constraint and wake threshold check as claimed in claim 1, wherein the data acquisition and unified processing module comprises: the data loading unit is used for loading the boundary file of the analysis area and acquiring the average wind speed raster data for a plurality of years Cutting the digital elevation model data; A unified gridding unit for cutting the wind speed raster data And the digital elevation model data are unified to a preset fixed resolution through interpolation On the calculation grid of (2), ensuring that grid pixels of two layers of data are completely aligned under metric coordinates; a terrain deriving unit for calculating gradient based on the digital elevation model data And according to a preset gradient Usable range A terrain availability zone mask is generated.
  3. 3. The automatic wind farm location system based on multi-index scoring such as terrain constraint and wake threshold verification according to claim 1, wherein the wind direction rose acquisition and analysis module comprises: the parallel grabbing unit is used for selecting representative grid points in the analysis area according to a preset sampling step length, and calling a wind direction service to obtain multi-sector wind direction frequency data of each representative grid point; The multi-level cache unit comprises a disk cache for persistent storage and a memory cache for current session acceleration, wherein the disk cache is optionally arranged, when the multi-level cache unit is started, the multi-level cache unit is used for persistent storage of wind direction rose data representing grid points, the unique identification of a cache entry is at least related to position coordinates and data height, and the cache entry comprises coordinates, height, wind speed and wind direction/wind energy sector frequency; And the direction weight aggregation unit is used for carrying out normalization processing on all wind direction frequency data representing grid points to obtain direction-weight pairs for arrangement and check.
  4. 4. The automatic site selection system for wind farm based on multi-index scoring such as terrain constraint and wake threshold check as set forth in claim 1, wherein in the automatic arrangement and multi-constraint check module, the multi-index scoring model pairs candidate grids Is of (1) The calculation formula of (2) is as follows: Wherein: For candidate grids Is a composite score of (2); 、 、 And The land ridge score, the directivity fluctuation score, the windward exposure score and the wind power score are respectively, and are normalized dimensionless components; A penalty term associated with the grade; 、 、 And Is the weight coefficient of the corresponding item.
  5. 5. The automatic wind farm location system based on the multi-index scores of terrain constraint, wake threshold check and the like according to claim 4, wherein the wind power score z is calculated according to the following formula: Wherein: To take into account the current effective wind speed after the wake effects of the dropped point; The mean value of the third power of the wind speed of the free incoming flow in the analysis area; is the standard deviation of the third power of the free incoming wind speed (V 0 3 ) in the analysis area.
  6. 6. The automatic wind farm location selection system based on terrain constraint, wake threshold check and the like according to claim 4, wherein the slope deduction term is characterized in that The calculation of (2) employs piecewise linear functions, the formula is as follows: Wherein: The gradient value of the current grid; And The lower limit and the upper limit of the gradient available range are respectively; a break point gradient value for deduction and penalty gradient change; 、 And Respectively, the deduction and penalty coefficients.
  7. 7. The automatic wind farm location selection system based on the multi-index scores of terrain constraint, wake threshold check and the like according to claim 1, wherein in the automatic arrangement and multi-constraint check module, the condition of the minimum-interval hard constraint check is that for any selected machine position With the position of the machine to be selected The following inequality needs to be satisfied: Wherein: And The plane rectangular coordinate is under metric coordinates, D is the diameter of the impeller; Is a preset minimum pitch multiple.
  8. 8. The automatic wind farm location system based on the multi-index scoring such as terrain constraint and wake threshold check, as set forth in claim 1, wherein in the automatic arrangement and multi-constraint check module, the fast wake effect threshold check based on the Jensen engineering model includes: for upstream machine position In the wind direction sector If the point to be selected Located at its wake cone Internally, calculate the speed loss ratio : Wherein: Is a thrust coefficient; Is the wake expansion coefficient; Point to be selected Relative to the upstream machine position In a sector A distance in an axially downstream direction; Is an indication function; Is a wake cone section; Calculating the composite loss ratio of sector k ; Calculating the effective wind speed for sector k Wherein: the free incoming wind speed for sector k; synthesizing a deficit ratio for the sector; If it meets The candidate point is denied, wherein: For sectors Direction weights of (2); and overrules the threshold value for the preset wake.
  9. 9. The wind farm automatic site selection system based on multi-index scoring such as terrain constraint and wake threshold check, as set forth in claim 1, wherein the automatic arrangement and multi-constraint check module further comprises a local micro-moving optimization unit for checking candidate machine positions passing through constraint and wake, the radius around the metric projection plane coordinates of the candidate machine positions is Randomly sampling the neighborhood of jitter_three times, and selecting the comprehensive score on the premise of not violating the boundary and constraint The maximum location serves as the final drop point for the machine.
  10. 10. An automatic wind farm site selection method based on multi-index scoring such as terrain constraint and wake threshold check is characterized by being realized by adopting the automatic wind farm site selection system based on multi-index scoring such as terrain constraint and wake threshold check according to any one of claims 1-9, and the method comprises the following steps: loading the boundary of an analysis area of a target wind power plant, acquiring and uniformly processing annual average wind speed grid data and digital elevation model data in the analysis area, and generating an aligned grid wind resource layer and a topography layer; sampling wind direction frequency data in the analysis area, and aggregating to generate multi-sector direction weights for machine position layout; Thirdly, screening out initial candidate grids in a gradient available area based on the grid wind resource layer and the terrain layer through a multi-index scoring model combining terrain ridge degree, directional fluctuation, windward exposure degree and wind power score; Step four, adopting a greedy iteration strategy, and executing the following substeps from the initial candidate grid until the target number of machine bits is reached or the candidate is exhausted: 41 Selecting the candidate grid with the highest current score as a to-be-fixed point; 42 Performing equivalent distance hard constraint inspection based on minimum distance multiple on the to-be-fixed point; 43 If the distance check is passed, carrying out wake effect fast threshold check on the model based on the Jensen engineering model and the multi-sector direction weight; 44 If the wake flow check is passed, carrying out local neighborhood random micro-moving optimization on the point, determining the final drop point position, and updating the scores of the effective wind speed field and the residual candidate grids; And fifthly, outputting longitude and latitude information of the final machine position layout, and generating a traceability log containing operation parameters and key steps.

Description

Wind power plant automatic site selection system and method based on multi-index scoring such as terrain constraint and wake flow threshold check Technical Field The invention belongs to the technical field of wind power plant planning, in particular to an automatic wind power plant site selection system and method based on multi-index scoring such as terrain constraint and wake threshold check, which are particularly suitable for a macroscopic primary site selection stage of a wind power plant. Background Wind power generation is a mature renewable energy technology with the transition of global energy structures to clean low carbon, and the installed scale thereof continues to grow rapidly. In the whole life cycle of wind farm development, site selection planning is a key link for determining project investment benefit, power generation capacity and long-term operation and maintenance feasibility. Conventional wind farm addressing is generally divided into two stages, primary addressing (macro addressing) and detailed addressing (micro addressing). The primary site selection aims at rapidly identifying candidate areas and capacity levels with rich wind energy resources, proper terrain conditions and certain development potential in a wide area of tens to hundreds of square kilometers, and provides a basis and a direction for subsequent fine investigation, microscopic layout and economic benefit evaluation. Currently, the industry generally relies on Geographic Information System (GIS) software, mesoscale wind resource data, digital Elevation Model (DEM) and engineer experience judgment when performing preliminary site selection of wind farms. Typical conventional workflow can be summarized by firstly acquiring wind speed, wind direction map and topography data of a target area from different data sources (such as public database, commercial analysis data and company internal database), secondly manually overlaying wind resource map layers, topography gradient map layers, project boundaries and the like in GIS software, roughly defining a potential strip which can be suitable for fan arrangement by visual interpretation and combination of dominant wind directions, then manually arranging a small number of candidate machine positions in the potential strip according to empirical rules (such as 7 times impeller diameter of main wind direction interval and 5 times impeller diameter of side wind direction interval), and finally deriving the result in KML/KMZ and the like, and carrying out capacity estimation by assistance of a table. However, the above conventional method relying on manual operation and multi-tool combination has many inherent drawbacks, which seriously affect the efficiency, objectivity and traceability of the preliminary site selection, and mainly manifest in the following aspects. (1) The data caliber is not uniform, the comparability of the result is poor, wind resource data and topographic data can come from different institutions, and the wind resource data and the topographic data have differences in space projection, coordinate units, data resolution, statistical years and even color code representation. Engineers use inconsistent data apertures in different projects or different stages of the same project, so that the generated site selection scheme is difficult to objectively and fairly compare transversely, and the subjectivity of the scheme is strong in judging the quality of the scheme. (2) The process is split, the manual operation error is outstanding, the site selection process involves a plurality of links such as data downloading, format conversion, GIS analysis, visual interpretation, manual punctuation, table recording and the like, and the process needs to be frequently switched and imported and exported among different software platforms. This process is extremely prone to human errors, such as distance and area calculation distortion caused by misuse of the coordinate system, confusion of longitude and latitude coordinate sequences, transcription errors occurring when data are manually input, and the like. In addition, by means of engineers to visually recognize the topographic features such as 'long mountain ridge', 'gentle slope bench', the subjectivity is strong, and different people can possibly draw quite different conclusions. (3) The automation degree is low, the working efficiency is low, and a great deal of work depends on repeated manual operation from data preparation to candidate machine position scheme generation. Especially when multiple comparison schemes under different pitch parameters and different terrain constraint conditions need to be evaluated, the traditional method is time-consuming and labor-consuming, and is difficult to realize rapid iteration and scheme optimization, and the requirement of rapid decision of the current period cannot be met. (4) The core site selection rule is not strictly executed, and a rapid checking mechanism is lacking, s