Pumped storage power station multi-element multi-target intelligent online site selection method and device and storage medium

Abstract

The invention provides a pumped storage power station multi-element multi-target intelligent online site selection method and device and a storage medium. The method comprises the following steps: extracting a midpoint of each river network line segment as a candidate point to construct a candidate point set # imgabs0 #; the set # imgabs3 # is screened according to the water diversion distance # imgabs1 # and the water head parameter # imgabs2 #, and a set # imgabs4 # is obtained; verifying the dam length, the dam height, the reservoir capacity and the reservoir surface form of the candidate points in the set # imgabs5 # by using a multi-target constraint model to obtain a set # imgabs6 #; a candidate point # imgabs8 # is selected from the set # imgabs7 #, a candidate point # imgabs11 # matched with the candidate point # imgabs10 # in the set # imgabs9 # is screened out, and a set # imgabs12 # is obtained; and obtaining a candidate point, which is optimally matched with the candidate point # imgabs14 #, in the set # imgabs13 # through suitability analysis. The pumped storage power station online site selection method is optimized from the aspects of site selection efficiency, reservoir capacity calculation, homogeneous site optimization, site comprehensive evaluation and the like.

Description

Technical Field

[0001] The present invention relates to the technical field of site selection for pumped storage power stations, and in particular to a multi-factor and multi-objective intelligent online site selection method, device and storage medium for pumped storage power stations. Background Art

[0002] In the traditional planning and site selection process of pumped storage power stations, manual on-site surveys, data processing and analysis and calculation are mainly relied on, which has high professional requirements for staff, and there are problems such as large workload, low efficiency, long time consumption, and missed selection. In recent years, with the growth of demand for pumped storage power stations and the advancement of science and technology, many scholars have conducted qualitative and quantitative methods research on site selection planning from the perspectives of technology, algorithms, and evaluation indicators. However, most of them have some shortcomings, such as: ① The site selection speed is slow and the efficiency of site selection is limited; ② The number of potential sites selected is huge, the potential sites are highly homogeneous, and there is a lack of targeted guidance for the actual site selection work; ③ There is a lack of comprehensive and comprehensive qualitative and quantitative evaluation of the selected sites.

[0003] At present, there is no unified and scientific guidance plan for pumped-storage power stations. In actual projects, there are problems such as arbitrary site selection and difficulty in implementation. There is an urgent need for a unified, scientific and efficient multi-factor and multi-objective intelligent online site selection method, device and storage medium for pumped-storage power stations to solve the problems existing in the existing technology. Summary of the invention

[0004] The purpose of the present invention is to provide a multi-factor and multi-objective intelligent online site selection method for a pumped storage power station, which optimizes the online site selection method for a pumped storage power station from aspects such as site selection efficiency, reservoir capacity calculation, optimization of homogeneous sites, and comprehensive evaluation of sites. The specific technical scheme is as follows: A multi-factor and multi-objective intelligent online site selection method for a pumped storage power station, comprising: S1. Obtain the contour layer data and river system data of the study area; S2. Extract the midpoints of each river network segment as candidate points to construct a candidate point set ; S3. According to the water diversion distance between the upper and lower reservoirs and head parameters Pair Collection Filter the candidate points in to get a new set of candidate points ; S4. Using multi-objective constraint model to The dam length, dam height, reservoir capacity and reservoir surface shape of the candidate points are verified. The candidate points that satisfy the multi-objective constraint model are put into the set middle; S5. From the collection Select any candidate point , and from the set Select candidate points Candidate points that can form upper or lower reservoirs , get all candidate points The set of ; S6. Pair collection The candidate points in Perform suitability analysis and obtain the set Center and candidate points The best matching candidate point.

[0005] Preferably, in S3, the water diversion distance between the upper and lower reservoirs is and head parameters Pair Collection The specific screening of candidate points is: Traverse the calculation collection Any two candidate points and The Euclidean distance between And elevation difference , if satisfied , then the candidate point is considered and Can form upper and lower libraries, and the candidate points and Add to collection Among them, , is the water diversion distance, is the water head parameter, For collection The number of candidate points.

[0006] Preferably, a multi-objective constraint model is used to Candidate point The dam length, dam height, reservoir capacity and reservoir surface shape are verified, specifically: S4.1. Obtaining candidate points The set of dam lines that satisfy the dam line length constraint ;in, ], Candidate point Total number of dam lines; S4.2. Settings The initial value of is 1; S4.3, check dam line collection Middle Whether the dam height corresponding to the dam line is qualified, if qualified, proceed to step S4.4; if unqualified, judge k Is it equal to If not equal, take k = k +1 Repeat step S4.3, if equal, end the candidate point Verification of S4.4. Obtain dam line set Medium elevation is less than or equal to The reservoir surface coordinate strings corresponding to all dam lines of the dam line elevation; check the Whether the reservoir capacity corresponding to the dam line is qualified, if qualified, go to step S4.5; if not qualified, end the candidate point Verification of S4.5. Verify Whether the reservoir surface shape corresponding to the dam line is qualified, if qualified, the candidate point Add to collection If unqualified, judge k Is it equal to If not equal, take k=k +1 Repeat step S4.3, if equal, end the candidate point Verification.

[0007] Preferably, before executing step S4, the method further includes: traversing the calculation set Any two candidate points and The Euclidean distance between ,like Less than the set sampling distance S , then from the set Delete candidate points , Any one of them, until the set The Euclidean distance between any two candidate points in is greater than the sampling distance ;in, and , All belong to , For collection The number of candidate points.

[0008] Preferably, in step S4.1, candidate points are obtained The set of dam lines that satisfy the dam line length constraint Specifically: S4.1.1. According to the collection Candidate point Elevation , the screening is satisfied A collection of contour lines ;in, Indicates Contour lines, is an integer and 1, w ], For collection The number of contour lines in Contour lines The elevation of The elevation tolerance is set; S4.1.2. Passing candidate points Draw a perpendicular line to the candidate point The perpendicular line segment of the river network segment , where the vertical line segment The length is set as the maximum dam length parameter , candidate points On the vertical line At the midpoint of The two endpoints of and ; S4.1.3. The vertical line segment With Collection Contour lines in Perform intersection calculations. If the vertical line segment With the same contour line If there are two or more intersection points, the line between the two adjacent intersection points is extracted, and the line that intersects with the river network segment is selected as the reservoir dam line; S4.1.4. Sort the obtained dam lines of each reservoir according to their endpoint elevations from high to low to obtain the dam line set .

[0009] Preferably, in step S4.1.3, the vertical line segment is obtained With contour lines The specific method of intersection is: A41. Obtaining Contour Lines The node coordinate string set ],in Contour lines On Node coordinates; A42, Contour Line The line segment between the coordinates of two adjacent nodes is used as an element to construct the contour line. The line segment set ;in, Indicates s Line segment, u Indicates the number of line segments; if the contour line is a closed contour line, then If the contour line is a non-closed contour line, then ; A43. Find the line segment set by calculating the intersection of line segments Median and perpendicular segments All the elements that intersect get the set ; A44. Calculation Set The elements and vertical segments in The intersection of .

[0010] Preferably, the storage surface coordinate string obtained in S4.4 is specifically: Assume End point of the dam line Located on the contour Line segment On the other end Located on the contour Line segment Above; Among them: Contour lines The node coordinate string set is expressed as ], Expressed as , Expressed as , , , and All belong to the node coordinate string set , and , All belong to ; When the contour line If it is a non-closed contour line, the library surface coordinate string for: When the contour line When it is a closed contour line, the contour line With The dam line forms two closed polygons, and the coordinate strings of the two closed polygons are expressed as: ] (17), Get candidate points The starting point coordinates of the river network segment where the river network segment is located are determined by 、 Check whether the closed polygons shown have a containment relationship. Select the coordinate string corresponding to the closed polygons with a containment relationship as the library surface coordinate string. ; If the starting coordinates of the river network segment are 、 If there is no inclusion relationship between the closed polygons shown, the starting point coordinates of the river network segment and the candidate point Generate a new vector line feature as the two endpoints of the line segment, solve the intersection of the vector line feature and the two closed polygons, and select the coordinate string corresponding to the closed polygon with more than or equal to 2 intersection points as the library surface coordinate string .

[0011] Preferably, the verification of whether the storage capacity is qualified in S4.4 is specifically: Get the contour line collection Medium elevation value is less than or equal to A collection of contour lines , , calculated according to formula (18) The reservoir capacity corresponding to each dam line ,like The verification is qualified; Among them, the contour line set To meet the dam line The set of contour lines formed by the intersection of the dam lines in the dam is , To meet the dam line Zhongba Line Intersecting contour lines, For the The elevation of the contour lines where the dam lines intersect, The minimum reservoir capacity allowed by the project; No. The reservoir capacity corresponding to each dam line for: Among them: hour, ; It is t The reservoir area enclosed by the contour lines and the dam line, For the t The elevation of a contour line.

[0012] Preferably, the verification of whether the reservoir surface morphology is qualified in S4.5 is specifically: If satisfied and , then the reservoir surface morphology is qualified; among them, the reservoir surface morphology parameters , Respectively expressed as: in, It is The dam line corresponds to the perimeter of the reservoir. For the The length of the dam line, is the coordinates of the reservoir surface and the candidate points The maximum Euclidean distance, 、 All are set reservoir capacity morphology thresholds.

[0013] The present invention also provides a multi-factor, multi-objective, intelligent online site selection device for a pumped-storage power station, comprising a storage medium and a processor, wherein the storage medium stores a computer program, and when the processor runs the computer program, it executes the multi-factor, multi-objective, intelligent online site selection method for a pumped-storage power station.

[0014] The present invention also provides a storage medium, in which a computer program is stored. When the computer program is running, the multi-factor and multi-objective intelligent online site selection method for a pumped-storage power station is executed.

[0015] The application of the technical solution of the present invention has the following beneficial effects: The present invention combines online zoning and parameter setting methods to pre-select suitable station sites, and selects high-quality upper and lower reservoirs based on set multi-objective constraints. The method of the present invention improves the efficiency of site selection to a certain extent, reduces the probability of wrong selection and missed selection, is scientific and convenient, and belongs to the field of site selection planning for pumped storage power stations.

[0016] The present invention takes into account the influence of multiple geographical factors such as topography, water system, geology, and ecological red line, and intelligently solves all candidate points that meet the conditions in the region under the constraints of multi-objective models such as dam height, dam length, reservoir capacity, matching upper / lower reservoirs, and reservoir surface morphology. On the basis of the general selection of sites, designers can select candidate points of interest to generate reservoirs, and general select matching reservoirs based on the set upper and lower reservoir construction conditions.

[0017] The present invention combines remote sensing image data and DEM data, through online site selection and result visualization, can not only view the distribution of the geographical location of the upper / lower reservoir in general, but also evaluate the geographical conditions around the reservoir in detail, and provide more detailed data reference for the site selection planning of pumped storage power stations. Compared with manual site selection, it greatly improves the efficiency, accuracy, scientificity and convenience of site selection.

[0018] In addition to the above-described purposes, features and advantages, the present invention has other purposes, features and advantages. The present invention will be further described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The drawings constituting a part of this application 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 an improper limitation of the present invention. In the drawings: Figure 1 is a flow chart of the multi-factor and multi-objective intelligent online site selection method for a pumped storage power station in Example 1; Figure 2 The study area of ​​Example 2 is a collection Schematic diagram of candidate points and general election matching reservoir results; Figure 3 yes Figure 2 A zoomed in picture of the results of the Chinese general election matching reservoir. DETAILED DESCRIPTION

[0020] In order to facilitate the understanding of the present invention, the present invention will be described more fully below, and preferred embodiments of the present invention are provided. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. On the contrary, the purpose of providing these embodiments is to make the understanding of the disclosure of the present invention more thorough and comprehensive.

[0021] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used in the specification of the present invention herein are only for the purpose of describing specific embodiments and are not intended to limit the present invention.

[0022] Embodiment 1: like Figure 1 As shown, this embodiment provides a multi-factor and multi-objective intelligent online site selection method for a pumped storage power station, which optimizes the online site selection method for a pumped storage power station from aspects such as site selection efficiency, reservoir capacity calculation, optimization of homogeneous sites, and comprehensive evaluation of sites, and mainly includes the following steps: S1. Obtain the contour layer data and river system data of the study area, specifically: According to the vector data of the designated study area and the given initial contour elevation value, contour interval and flow threshold parameters, the contour layer data and river system data of the study area are extracted using DEM data.

[0023] S2. Extract the midpoints of each river network segment as candidate points to construct a candidate point set ; Specifically, according to the river system data obtained by S1, traverse the river network segments, extract the midpoints of each river network segment and put them into the candidate point set At the same time, record the river ID of each candidate point and calculate the elevation of each candidate point based on the terrain data. ,in, Representing a collection The Candidate points, Representing a collection Middle The elevation of the candidate points, For collection The number of candidate points.

[0024] S3. According to the water diversion distance between the upper and lower reservoirs and head parameters Pair Collection Filter the candidate points in to get a new set of candidate points ; Specifically, in order to improve the efficiency of point selection, firstly, based on the water diversion distance and water head parameter set The candidate points in are initially screened, specifically: Traverse the calculation collection Any two candidate points With candidate points The Euclidean distance between And elevation difference , if satisfied , then the candidate point is considered With candidate points Can form the dam site of upper reservoir and lower reservoir, and the candidate point With candidate points Add to collection Among them, , is the water diversion distance, is the head parameter, set , For collection The number of candidate points.

[0025] Furthermore, the candidate points With candidate points The Euclidean distance between And elevation difference The calculations are: in, represents the Euclidean distance, Indicates taking the absolute value, Indicates candidate points The elevation of Indicates candidate points elevation.

[0026] S4. Using multi-objective constraint model to The dam length, dam height, reservoir capacity and reservoir surface shape of the candidate points are verified. The candidate points that satisfy the multi-objective constraint model are put into the set middle; Taking into account the construction conditions of pumped storage power stations and the impact of the economic benefits of power stations, in this embodiment, a multi-objective constraint model is used to screen out power station locations with good conditions and high benefits; specifically, the multi-objective constraint model is: (3), in, Candidate point The length of the reservoir dam line, Candidate point The reservoir dam is high. Candidate point The reservoir capacity, Candidate point The ratio of the reservoir perimeter to the dam line length, Candidate point The ratio of the maximum distance to the reservoir surface to the length of the dam line, is the maximum reservoir dam length allowed by the project, is the maximum reservoir dam height allowed by the project, is the minimum reservoir capacity allowed by the project, 、 is the set storage capacity morphology threshold.

[0027] Preferably, before executing step S4, a screening step of removing homogenized sites is also included, specifically: traversing the calculation set Any two candidate points and The Euclidean distance between ,like Less than the set sampling distance S , then from the set Delete candidate points , Any one of them, until the set The Euclidean distance between any two candidate points in is greater than the sampling distance ;in, and , All belong to ; By removing homogenous sites, the collection can be reduced The number of candidate points in the selection process is increased to improve the calculation efficiency (if the homogenization site screening step is not performed, it will not affect the subsequent screening results, but it will reduce the calculation efficiency).

[0028] Furthermore, the multi-objective constraint model is used to Candidate point The dam length, dam height, reservoir capacity and reservoir surface shape are verified, specifically: S4.1. Obtaining candidate points The set of dam lines that satisfy the dam line length constraint ,in, ], Candidate point The total number of dam lines, satisfying the dam line length constraint means that the dam line set Each dam line in ; Preferably, in step S4.1, candidate points are obtained The set of dam lines that satisfy the dam line length constraint Specifically: S4.1.1. According to the collection Candidate point Elevation , the screening is satisfied A collection of contour lines ;in, Indicates Contour lines, is an integer and 1, w ], For collection The number of contour lines in Contour lines The elevation of The elevation tolerance is set; S4.1.2. Passing candidate points Draw a perpendicular line to the candidate point The perpendicular line segment of the river network segment , where the vertical line segment The length is set as the maximum dam length parameter , candidate points On the vertical line At the midpoint of The two endpoints of and ; S4.1.3. The vertical line segment With Collection Contour lines in Perform intersection calculations. If the vertical line segment With the same contour line If there are two or more intersection points, the line between the two adjacent intersection points is extracted, and the line intersecting with the river network segment is selected as the reservoir dam line; the two endpoints of the reservoir dam line are recorded as , , and (i.e. candidate points The two endpoints of the dam line do not coincide with each other); S4.1.4. Sort the obtained dam lines of each reservoir according to their endpoint elevations from high to low to obtain the dam line set ; Specifically, the dam line collection ], the corresponding contour line set is , Represents a vertical line segment and Middle k The dam line formed by the intersection of contour lines, , and Respectively represent the dam line The two endpoints of the set The number of middle dam lines and The number of medium-high lines is consistent, both .

[0029] Furthermore, the dam line collection The length of each dam line is calculated as follows: Further, in step S4.1.3, the vertical line segment is obtained With contour lines The specific method of intersection is: A41. Obtaining Contour Lines The node coordinate string set ], Contour lines On Node coordinates; A42, Contour Line The line segment between the coordinates of two adjacent nodes is used as an element to construct the contour line. The line segment set If the contour line is a closed contour line, then If the contour line is a non-closed contour line, then ;in, Indicates s Line segment, u Indicates the number of line segments; A43. Find the line segment set by calculating the intersection of line segments Median and perpendicular segments All the elements that intersect get a set ; Specifically, in this embodiment, the line segment set is determined Elements in (i.e. line segment) and perpendicular segment The way to determine whether they intersect is: Assuming a line segment set Elements in Expressed as ,in: All belong to the node coordinate string set ; First, a straddle experiment is performed on the two line segments. The mathematical expression of the straddle experiment is: in, It is a fast rejection experiment, used to quickly exclude non-intersecting line segments; Indicate point of coordinate, Indicate point of coordinate, Indicate point of x coordinate, Indicate point of x coordinate, Indicate point of y coordinate, Indicate point of y coordinate, Indicate point of y coordinate, Indicate point of y coordinate.

[0030] After the straddling test conditions are met, the line segment intersection judgment based on vector cross multiplication is performed, and the mathematical expression is: (6), (7), in, Representation vector , Cross product; 、 、 、 They are four sets of vector cross multiplication numerical results, Represents a multiplication operation.

[0031] A44. Calculation Set The elements and vertical segments in The intersection of .

[0032] Furthermore, the calculation set Middle element and perpendicular segment The intersection points are: Hypothesis set Medium Element Expressed as ,in, All belong to the node coordinate string set ; The element With perpendicular line segment The intersection point is recorded as In this embodiment The solution is: Assume that there are parameters Satisfies formula (8): Then the right-hand sides of the two equations in formula (8) are equal, that is: x, y The coordinates are also equal, and we can get formula (9): (9), Further solving the two-variable linear equation system of formula (9) yields formula (10): (10), Among them, the denominator in formula (10) is not zero, which is expressed as: According to formula (10), After the value of Substituting the first equation into equation (8) yields equation (12), or, Substituting the second equation of formula (8) into formula (13), we can solve it and get : (13), in, and Perpendicular segments The two endpoints of Indicate point of coordinate, Indicate point of coordinate, Indicate point of x coordinate, Indicate point of x coordinate, Indicate point of coordinate; Indicate point of y coordinate, Indicate point of y coordinate, Indicate point of y coordinate, Indicate point of y coordinate, Indicate point of coordinate, Represents a multiplication operation.

[0033] S4.2. Settings The initial value of is 1; S4.3, check dam line collection Middle Whether the dam height corresponding to the dam line is qualified, if qualified, proceed to step S4.4; if unqualified, judge k Is it equal to If not equal, take k = k +1 Repeat step S4.3, if equal, end the candidate point Verification of Specifically, Dam height corresponding to each dam line Specifically: in, For the The elevation of the endpoints of the dam line, that is, the set of contour lines Middle Contour lines The elevation of Candidate point elevation.

[0034] Furthermore, the dam height Substitute into formula (3) to check the dam height. If it satisfies If the dam height verification is successful, the dam height verification is successful; otherwise, it is unqualified.

[0035] S4.4. Obtain dam line set Medium elevation is less than or equal to The reservoir surface coordinate strings corresponding to all dam lines of the dam line elevation; check the Whether the reservoir capacity corresponding to the dam line is qualified, if qualified, go to step S4.5; if not qualified, end the candidate point Verification of Specifically, the size of the reservoir directly determines the water storage capacity of the reservoir. In order to select a suitable reservoir location, this embodiment uses the closed surface formed by the intersection of the dam line and the contour line as the reservoir surface. First, obtain the set Medium elevation value is less than or equal to A collection of contour lines , Then calculate the contour line sets separately The reservoir surface coordinate string formed by each contour line and the corresponding dam line in With The elevation of the contour lines where the dam lines intersect. Considering that there are two types of contour lines in the study area, open contour lines and closed contour lines, it is necessary to calculate the reservoir surface coordinate string for each case: Assume End point of the dam line Located on the contour Line segment On the other end Located on the contour Line segment Above; Among them: Contour lines The node coordinate string set is expressed as ], Expressed as , Expressed as , , , and All belong to the node coordinate string set , and , All belong to ; When the contour line When it is a non-closed contour line, it means that the contour line If the starting and ending coordinates are inconsistent, the library surface coordinate string for: When the contour line When it is a closed contour line, the contour line With The dam line forms two closed polygons, and the coordinate strings of the two closed polygons are expressed as: ] (17), Considering that the reservoir should be located in the upstream area of ​​the dam line, this embodiment introduces the direction of the river system to determine the reservoir surface coordinate string corresponding to the current candidate point, specifically: Get the candidate point The starting point coordinates of the river network segment are determined by using the overlay analysis algorithm. 、 Check whether the closed polygons shown have a containment relationship. Select the coordinate string corresponding to the closed polygons with a containment relationship as the library surface coordinate string. ; If the starting coordinates of the river network segment are 、 If there is no inclusion relationship between the closed polygons shown, the starting point coordinates of the river network segment and the candidate point Generate a new vector line feature as the two endpoints of the line segment, and use the overlay analysis algorithm to solve the intersection of the vector line feature and the two closed polygons. The coordinate string corresponding to the closed polygon with more than or equal to 2 intersection points is the library surface coordinate string. .

[0036] Furthermore, in order to obtain a more accurate storage capacity value, this embodiment introduces a layered storage capacity calculation method, specifically: Get Collection Medium elevation value is less than or equal to A collection of contour lines , , respectively calculate the set The reservoir capacity values ​​enclosed by the adjacent contour lines and the dam line are accumulated to obtain the The reservoir capacity corresponding to each dam line ,like Then go to step S4.5, otherwise end the candidate point Verification, reselect candidate points and start verification from step S4.1; No. The elevation of the contour lines where the two end points of the dam line are located; Further, The reservoir capacity corresponding to each dam line for: Among them: hour, ; is the library surface coordinate string The corresponding reservoir capacity, It is t The reservoir area enclosed by the contour lines and the dam line (which can be obtained based on the reservoir surface coordinate string), For the t The elevation of a contour line.

[0037] S4.5. Check whether the reservoir surface shape is qualified. If qualified, the candidate point Add to collection If unqualified, judge k Is it equal to If not equal, take k=k +1 Repeat step S4.3, if equal, end the candidate point Verification of Specifically, in order to describe the reservoir surface morphology and find the dam site with a shorter dam length to obtain a larger reservoir surface, the reservoir surface morphology parameter is introduced. , To judge the quality of the library; if it meets and , then the reservoir surface morphology is qualified, then the candidate point Add to collection And exit all verification steps for the current candidate point, return to step S4.1 to enter the set The next candidate point is calculated; if it does not meet and , then judge the current k Is it equal to If not equal, take k=k +1 Repeat step S4.3, if equal, end the candidate point Verification.

[0038] Furthermore, the surface morphology parameters , It is expressed as: in, It is The dam line corresponds to the perimeter of the reservoir. For the The length of the dam line, is the coordinates of the reservoir surface and the candidate points The farthest Euclidean distance, where the warehouse surface coordinates refer to the warehouse surface coordinate string Any coordinate point in .

[0039] S5. From the collection Select any candidate point , and from the set Select candidate points Candidate points that can form upper or lower reservoirs , get all candidate points The set of ; Specifically, based on the screening results of step S4, the designer can select Randomly select candidate points of interest from The generated reservoir is then collected Filter out all candidate points Candidate points that can form upper or lower reservoirs , so that the best matching site can be output later.

[0040] Furthermore, in this embodiment, according to formula (21), from the set Select candidate points Candidate points that can form upper or lower reservoirs : in: in, Candidate point Corresponding reservoirs and candidate points Corresponding to the distance of the reservoir, Candidate point Corresponding reservoirs and candidate points Corresponding to the reservoir head, Candidate point Corresponding reservoirs and candidate points Corresponding to the distance-to-height ratio of the reservoir, Candidate point The elevation of Candidate point The elevation of is the maximum water diversion distance (default configuration parameter), is the minimum water head (default configuration parameter), is the maximum distance-to-height ratio (default configuration parameter), For collection The number of candidate points.

[0041] S6. Pair collection The candidate points in Perform suitability analysis and obtain the candidate points The best matching candidate point.

[0042] Preferably, when planning a pumped storage power station, in addition to considering important influencing factors such as dam height, dam length, and reservoir capacity, it is also necessary to consider whether the water source is sufficient, whether the geological conditions are suitable for construction, and whether the ecological red line is damaged. This embodiment analyzes the key influencing factors of the pumped storage power station site, selects suitability evaluation indicators, and evaluates the pumped storage site through the hierarchical analysis method.

[0043] Specifically, the suitability evaluation indicators in this embodiment include terrain condition indicators, geological condition indicators, external environment indicators and water source condition indicators. Among them, terrain condition indicators include water head, distance-to-height ratio, reservoir surface area, traffic conditions and construction conditions; geological condition indicators include geological stability, geotechnical engineering characteristics, and material source conditions; external environment indicators include the area of ​​immigrants involved in the project area, cultivated land area, ecological and environmental sensitive areas, and the distance from new energy-rich areas or power grid load centers; water source condition indicators include multi-year average runoff and multi-year average sediment content.

[0044] Furthermore, for the set The candidate points in The specific aspects of suitability analysis are: S6.1. Compare each evaluation index pairwise according to the 1-9 scale method to construct an index matrix ; in, Indicates evaluation index i For evaluation indicators j The importance of is the number of evaluation indicators.

[0045] Furthermore, the 1~9 scale is defined as: (26), S6.2. According to the random consistency ratio Indicator matrix for judgment formulation A Is there consistency? If not, the indicator matrix needs to be re-formulated. A ,in The indicator matrix A The consistency index, The indicator matrix A Random consistency index of Specifically, the judgment indicator matrix A Whether there is consistency is specifically: in, The indicator matrix A The maximum eigenvalue of .

[0046] Furthermore, the indicator matrix A Random consistency index Those skilled in the art can directly obtain it based on the existing technology, where The value of There is a corresponding relationship. In this embodiment, some The value corresponding to value: S6.3. Using expert scoring to assemble The candidate points in Perform fuzzy evaluation and obtain the candidate points The best matching candidate points; S6.3.1. Calculate the comprehensive weight of each evaluation index based on the expert's scoring results and construct the candidate points. Fuzzy comprehensive evaluation matrix R , specifically: in, For the m Experts on i The evaluation results of the evaluation indicators are m , is the number of experts; For the i The comprehensive score of the indicators, ; S6.3.2. Based on fuzzy comprehensive evaluation matrix R , the candidate points are obtained through fuzzy comprehensive evaluation operation Score , specifically: in, Candidate point The weight matrix of each evaluation index is: For the n The weight corresponding to the evaluation index.

[0047] S6.3.3, based on each candidate point The score, output and candidate point The best matching candidate points; Preferably, according to the construction and operation management conditions of the pumped storage power station, the selected pumped storage power station (candidate point ) is divided into five levels: excellent, good, average, poor, and bad. At the same time, a five-level grade is introduced to quantify the qualitative indicators: (33), According to the candidate point The score of the pumped storage site can be used to determine the rating of the pumped storage site. Find the candidate points The best matching candidate point.

[0048] The site selection method of this embodiment takes into account the influence of multiple geographical factors such as topography, water system, geology, and ecological red line, and intelligently solves all candidate points that meet the conditions in the region under the constraints of multi-objective models such as dam height, dam length, reservoir capacity, matching upper / lower reservoirs, and reservoir surface morphology. On the basis of the general election site, designers can select candidate points of interest to generate reservoirs, and select the best matching reservoir based on the set upper and lower reservoir construction conditions. The method of this embodiment combines remote sensing image data and DEM data, and through online site selection and result visualization, it can not only view the distribution of the geographical location of the upper / lower reservoirs as a whole, but also evaluate the geographical conditions around the reservoir in detail, providing more detailed data reference for the site selection planning of pumped storage power stations. Compared with manual site selection, the efficiency, accuracy, scientificity and convenience of site selection are greatly improved.

[0049] Embodiment 2: In this embodiment, global 30-meter DEM data is used to further illustrate the site selection method in Example 1.

[0050] S1. Draw the study area online to generate a vector polygon layer, obtain the global 30-meter DEM online tile data (.hgt) within the range according to the circumscribed rectangle of the layer, merge the tiles using image processing technology, and use the vector polygon layer to perform image cropping on the merged tile data to obtain the terrain raster data in the study area; then based on the terrain raster data, use the GIS analysis algorithm to generate contour lines and river system data. The initial contour line elevation value used in this embodiment is 0 meters, the contour line interval is 20 meters, and the flow threshold is 300. The extracted contour line layer contains 7771 line data and the water system layer contains 4120 line data.

[0051] S2, based on the river system data generated by S1, traverse the river network segments, extract the midpoints of the river network segments and put them into the candidate point set , and calculate the elevation of each candidate point based on the terrain grid data; in this embodiment, the set , the elevation set corresponding to each candidate point is .

[0052] S3. Traverse the candidate point set , calculate any two candidate points With candidate points The Euclidean distance between And elevation difference , filter out the candidate points that cannot be found in the upper (lower) library, and get a new set of candidate points The water diversion distance used in this embodiment is 5000 meters, water head is 150 meters.

[0053] S4. Using multi-objective constraint model to The dam length, dam height, reservoir capacity and reservoir surface shape of the candidate points are verified. The candidate points that satisfy the multi-objective constraint model are put into the set middle; In this embodiment, the multi-objective constraint model is set as: 1) Dam length constraints: ; 2) Dam height constraints: ; 3) Storage capacity constraints: ; 4) Reservoir surface morphology constraints: .

[0054] Filtering homogeneous sites: traversing the calculation set Any two candidate points and The Euclidean distance between ,like Less than the set sampling distance S , then from the set Delete candidate points , Any one of them, until the set The Euclidean distance between any two candidate points in is greater than the sampling distance ;in, and , All belong to , For collection The number of candidate points; In this embodiment, the sampling distance is set S = 500 meters, from the filtered set Select candidate points For subsequent detailed description, candidate points With Collection The Euclidean distance of all candidate points in S .

[0055] S4.1. Obtaining candidate points The set of dam lines that satisfy the dam line length constraint , specifically: S4.1.1. Candidate points Elevation =525 meters, set = 200 meters, screening meets Contour lines of .

[0056] S4.1.2. Passing candidate points A vertical line segment is formed to be a vertical line segment of the river segment where the river segment is located (in this embodiment, the river segment ID is 529); S4.1.3. Calculation of vertical segments and sets The intersection of all contour lines, get the vertical line segment and the set The three middle contour lines form the dam line; S4.1.4. The elevations of the endpoints of each dam line are 580m, 560m, and 540m respectively, from the largest to the smallest, and the corresponding contour lines are: , dam line collection ].

[0057] S4.2. Settings The initial value of is 1; S4.3, check dam line collection Middle Whether the dam height corresponding to the dam line is qualified; Length of dam line = Meters, dam height = Meters, satisfying the dam length and dam height constraints, and proceeding to step S4.4; S4.4, calculated With contour lines The intersecting line segments are ]、 ]. In this embodiment, is a non-closed contour line, so the coordinate string of the storage surface is ].

[0058] Further, the corresponding storage capacity value is calculated for: ; Greater than , thus satisfying the storage capacity constraint.

[0059] S4.5, calculated in this embodiment =5011.18 meters, =1785.51 meters, then ≈20.54, ≈7.32, satisfying and , that is, it satisfies the reservoir surface morphology constraint; therefore, the candidate point Add to collection In the final set like Figure 2 shown.

[0060] S5. Universal Selection Matching Reservoir: Selecting a Set Candidate points in (corresponding to the above set In ), according to the constraint calculation of formula (21), it is found that there are 19 candidate points corresponding to the reservoirs in the study area that meet the constraint conditions, namely In this embodiment, rice, = rice, =15, the general election results are as follows Figure 3 As shown; S6. Pair collection The suitability of each candidate point in the fuzzy comprehensive evaluation operation is carried out to obtain the candidate point The highest score is 96 points; that is, the candidate point Candidate point The best match of .

[0061] Embodiment 3: This embodiment provides a multi-factor, multi-objective, intelligent online site selection device for a pumped-storage power station, including a storage medium and a processor. The storage medium stores a computer program. When the processor runs the computer program, it executes the multi-factor, multi-objective, intelligent online site selection method for a pumped-storage power station in Example 1.

[0062] 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 multi-factor and multi-objective intelligent online site selection method for a pumped storage power station, characterized in that: include: S1. Obtain the contour layer data and river system data of the study area; S2. Extract the midpoints of each river network segment as candidate points to construct a candidate point set ; S3. According to the water diversion distance between the upper and lower reservoirs and head parameters Pair Collection Filter the candidate points in to get a new set of candidate points ; S4. Using multi-objective constraint model to The dam length, dam height, reservoir capacity and reservoir surface shape of the candidate points are verified. The candidate points that satisfy the multi-objective constraint model are put into the set middle; S5. From the collection Select any candidate point , and from the set Select candidate points Candidate points that can form upper or lower reservoirs , get all candidate points The set of ; S6. Pair collection The candidate points in Perform suitability analysis and obtain the set Center and candidate points The best matching candidate point.

2. The multi-factor and multi-objective intelligent online site selection method for a pumped storage power station according to claim 1 is characterized in that: In S3, the water diversion distance between the upper and lower reservoirs is and head parameters Pair Collection The specific screening of candidate points is: Traverse the calculation collection Any two candidate points and The Euclidean distance between And elevation difference , if satisfied , then the candidate point is considered and Can form upper and lower libraries, and the candidate points and Add to collection Among them, , is the water diversion distance, is the water head parameter, For collection The number of candidate points.

3. The multi-factor and multi-objective intelligent online site selection method for a pumped storage power station according to claim 1 is characterized in that: Using multi-objective constraint model to Candidate point The dam length, dam height, reservoir capacity and reservoir surface shape are verified, specifically: S4.

1. Obtaining candidate points The set of dam lines that satisfy the dam line length constraint ;in, ], Candidate point Total number of dam lines; S4.

2. Settings The initial value of is 1; S4.3, check dam line collection Middle Is the dam height corresponding to the dam line qualified? If qualified, proceed to step S4.4; if unqualified, judge k Is it equal to If not equal, take k = k +1 Repeat step S4.3, if equal, end the candidate point Verification of S4.

4. Obtain dam line set Medium elevation is less than or equal to The reservoir surface coordinate strings corresponding to all dam lines of the dam line elevation; check the Whether the reservoir capacity corresponding to the dam line is qualified, if qualified, go to step S4.5; if not qualified, end the candidate point Verification of S4.

5. Verify Whether the reservoir surface shape corresponding to the dam line is qualified, if qualified, the candidate point Add to collection If unqualified, judge k Is it equal to If not equal, take k=k +1 Repeat step S4.3, if equal, end the candidate point of verification.

4. The multi-factor and multi-objective intelligent online site selection method for a pumped storage power station according to claim 3 is characterized by: Before executing step S4, it also includes: traversing the calculation set Any two candidate points and The Euclidean distance between ,like Less than the set sampling distance S , then from the set Delete candidate points , Any one of them, until the set The Euclidean distance between any two candidate points in is greater than the sampling distance ;in, and , All belong to , For collection The number of candidate points; Obtain candidate points in step S4.1 The set of dam lines that satisfy the dam line length constraint Specifically: S4.1.

1. According to the collection Candidate point Elevation , the screening is satisfied A collection of contour lines ;in, Indicates Contour lines, is an integer and 1, w ], For collection The number of contour lines in Contour lines The elevation of The elevation tolerance is set; S4.1.

2. Passing candidate points Draw a perpendicular line to the candidate point The perpendicular line segment of the river network segment , where the vertical line segment The length is set as the maximum dam length parameter , candidate points On the vertical line At the midpoint of The two endpoints of and ; S4.1.

3. The vertical line segment With Collection Contour lines in Perform intersection calculations. If the vertical line segment With the same contour line If there are two or more intersection points, the line between the two adjacent intersection points is extracted, and the line that intersects with the river network segment is selected as the reservoir dam line; S4.1.

4. Sort the obtained dam lines of each reservoir according to their endpoint elevations from high to low to obtain the dam line set .

5. The multi-factor and multi-objective intelligent online site selection method for a pumped storage power station according to claim 4 is characterized in that: Obtain the vertical line segment in step S4.1.3 With contour lines The specific method of intersection is: A41. Obtaining Contour Lines The node coordinate string set ],in Contour lines On Node coordinates; A42, Contour Line The line segment between the coordinates of two adjacent nodes is used as an element to construct the contour line. The line segment set ;in, Indicates s Line segment, u Indicates the number of line segments; if the contour line is a closed contour line, then If the contour line is a non-closed contour line, then ; A43. Find the line segment set by calculating the intersection of line segments Median and perpendicular segments All the elements that intersect get a set ; A44. Calculation Set The elements and vertical segments The intersection of .

6. The multi-factor and multi-objective intelligent online site selection method for a pumped storage power station according to claim 3 is characterized in that: The specific method for obtaining the library surface coordinate string in S4.4 is: Assume End point of the dam line Located on the contour The line segment On the other end Located on the contour The line segment Above; Among them: Contour lines The node coordinate string set is expressed as ], Expressed as , Expressed as , , , and All belong to the node coordinate string set , and , All belong to ; When the contour line If it is a non-closed contour line, the library surface coordinate string for: When the contour line When it is a closed contour line, the contour line With The dam line forms two closed polygons, and the coordinate strings of the two closed polygons are expressed as: ] （17）， Get candidate points The starting point coordinates of the river network segment where the river network segment is located are determined by 、 Check whether the closed polygons shown have a containment relationship. Select the coordinate string corresponding to the closed polygons with a containment relationship as the library surface coordinate string. ; If the starting coordinates of the river network segment are 、 If there is no inclusion relationship between the closed polygons shown, the starting point coordinates of the river network segment and the candidate point Generate a new vector line feature as the two endpoints of the line segment, solve the intersection of the vector line feature and the two closed polygons, and select the coordinate string corresponding to the closed polygon with more than or equal to 2 intersection points as the library surface coordinate string .

7. The multi-factor and multi-objective intelligent online site selection method for a pumped storage power station according to claim 6 is characterized in that: The specific steps for checking whether the storage capacity is qualified in S4.4 are: Get the contour line collection Medium elevation value is less than or equal to A collection of contour lines , , calculated according to formula (18) The reservoir capacity corresponding to each dam line ,like The verification is qualified; Among them, the contour line set To meet the dam line The set of contour lines formed by the intersection of the dam lines in the dam is , To meet the dam line Zhongba Line Intersecting contour lines, For the The elevation of the contour lines where the dam lines intersect, The minimum reservoir capacity allowed by the project; No. The reservoir capacity corresponding to each dam line for: Among them: hour, ; It is t The reservoir area enclosed by the contour lines and the dam line, For the t The elevation of a contour line.

8. The multi-factor and multi-objective intelligent online site selection method for a pumped storage power station according to claim 6 is characterized in that: The specific verification of whether the reservoir surface shape is qualified in S4.5 is: If satisfied and , then the reservoir surface morphology is qualified; among them, the reservoir surface morphology parameters , Respectively expressed as: in, It is The dam line corresponds to the perimeter of the reservoir. For the The length of the dam line, is the coordinates of the reservoir surface and the candidate points The maximum Euclidean distance of 、 All are set reservoir capacity morphology thresholds.

9. A multi-factor and multi-objective intelligent online site selection device for a pumped storage power station, characterized in that: It comprises a storage medium and a processor, wherein the storage medium stores a computer program, and when the processor runs the computer program, it executes the multi-factor and multi-objective intelligent online site selection method for a pumped-storage power station as described in any one of claims 1 to 8.

10. A storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is run, the multi-factor and multi-objective intelligent online site selection method for a pumped-storage power station as described in any one of claims 1 to 8 is executed.

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