An intelligent online site selection method, device and storage medium for multiple elements and multiple objectives of a pumped storage power station

Abstract

The present invention provides a multi-factor and multi-objective intelligent online site selection method, device and storage medium for pumped storage power stations: extracting the midpoints of each river network line segment as candidate points to construct a candidate point set; screening the set according to the diversion distance and head parameters to obtain a set; using a multi-objective constraint model to verify the dam length, dam height, reservoir capacity and reservoir surface morphology of the candidate points in the set to obtain a set; selecting a candidate point from the set, screening out the candidate points in the set that match the candidate point to obtain a set; and obtaining the candidate point in the set that is optimally matched with the candidate point through suitability analysis. The present invention optimizes the online site selection method for pumped storage power stations in terms of site selection efficiency, reservoir capacity calculation, optimization of homogeneous sites, and comprehensive evaluation of sites.

Description

Technical Field

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

[0002] In the process of traditional pumped - storage power station planning and site selection, it mainly relies on manual on - site investigation, data processing and analysis and calculation, 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 the demand for pumped - storage power stations and the progress of science and technology, many scholars have carried out research on qualitative and quantitative methods for site - selection planning from the perspectives of technology, algorithms, evaluation indicators, etc. However, there are mostly some deficiencies, such as: ① The site - selection speed is relatively slow, and the improvement of site - selection efficiency is limited; ② The number of potential sites selected is huge, the potential points have strong homogeneity, and there is a lack of targeted guidance for the actual site - selection work; ③ There is a lack of comprehensive qualitative and quantitative evaluation of the screened sites.

[0003] Currently, there is no unified and scientific guidance plan for pumped - storage power stations. In actual projects, there are problems such as random site selection and difficulty in carrying out. 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 prior art. 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 pumped - storage power stations, which optimizes the online site - selection method for pumped - storage power stations from aspects such as site - selection efficiency, reservoir capacity calculation, optimization of homogeneous sites, and comprehensive evaluation of sites. The specific technical solutions are as follows:

[0005] A multi - factor and multi - objective intelligent online site - selection method for pumped - storage power stations includes:

[0006] S1. Obtain the contour line layer data and river system data of the research area;

[0007] S2. Extract the mid - points of each river network segment as candidate points to construct a candidate point set ;

[0008] S3. Screen the candidate points in the set according to the water diversion distances of the upper and lower reservoirs and the head parameters to obtain a new candidate point set

[0009] S4. Use a multi - objective constraint model to verify the dam length, dam height, reservoir capacity and reservoir surface morphology of the candidate points in the set , and the set Put the candidate points that meet the multi-objective constraint model into the set ;

[0010] S5. Select any candidate point from the set , and screen out the candidate points from the set that can form the upper reservoir or the lower reservoir with the candidate point , to obtain the set formed by all candidate points ; ; ; ;

[0011] S6. Conduct a suitability analysis on each candidate point in the set to obtain the candidate point that is the best match with the candidate point in the set .

[0012] Preferably, in S3, according to the water diversion distances of the upper and lower reservoirs and the head parameters , the specific screening of the candidate points in the set is as follows:

[0013] Traverse and calculate the Euclidean distance between any two candidate points and in the set , as well as the elevation difference . If it satisfies , then it is considered that the candidate point and can form the upper and lower reservoirs, and put the candidate points and into the set ; where , is the water diversion distance, is the head parameter, is the set , and

[0014] Preferably, use the multi-objective constraint model to verify the dam length, dam height, reservoir capacity, and reservoir surface morphology of the candidate points in the set . The specific method is as follows:

[0015] S4.1. Obtain the set of dam lines that meet the dam line length constraint for the candidate point ; where , is the total number of dam lines of the candidate point ;

[0016] ​S4.2. Set to an initial value of 1;

[0017] S4.3. Verify whether the dam height corresponding to the th dam line in the dam line set is qualified. If it is qualified, proceed to step S4.4; if it is unqualified, determine whether is equal to k . If it is not equal, take = k = k + 1 and repeat step S4.3. If it is equal, end the verification of the candidate points ;

[0018] S4.4. Obtain the reservoir surface coordinate strings corresponding to all dam lines in the dam line set whose elevations are less than or equal to the elevation of the th dam line; verify whether the reservoir capacity corresponding to the th dam line is qualified. If it is qualified, proceed to step S4.5; if it is unqualified, end the verification of the candidate points ;

[0019] S4.5. Verify whether the reservoir surface shape corresponding to the th dam line is qualified. If it is qualified, put the candidate points into the set ; if it is unqualified, determine whether k is equal to . If it is not equal, take k = k + 1 and repeat step S4.3. If it is equal, end the verification of the candidate points ;

[0020] Preferably, before executing step S4, it also includes: traversing and calculating the Euclidean distance between any two candidate points and in the set . If is less than the set sampling distance S , then delete any one of the candidate points and , from the set until the Euclidean distance between any two candidate points in the set is greater than the sampling distance and , both belong to , is the number of candidate points in the set ; where,

[0021] Preferably, in step S4.1, obtaining the candidate points Set of dam lines satisfying the dam line length constraint Specifically:

[0022] S4.1.1. According to the set of candidate points in terms of elevation , filter to obtain the contour line set that satisfies ; among them, represents the th contour line, is an integer and 1, w , is the number of contour lines in the set , represents the elevation of the contour line , is the set elevation tolerance;

[0023] S4.1.2. Draw a perpendicular segment from the candidate point to the river network segment where the candidate point is located. Among them, the length of the perpendicular segment is set as the maximum dam length parameter , the candidate point is located at the midpoint of the perpendicular segment , and the two endpoints of the perpendicular segment are respectively denoted as and ;

[0024] S4.1.3. Perform an intersection calculation between the perpendicular segment and the contour lines in the set . If the perpendicular segment intersects the same contour line at two or more intersection points, then extract the connection line between adjacent two intersection points, and select the connection line that intersects the river network segment as the reservoir dam line;

[0025] S4.1.4. Sort the obtained reservoir dam lines in descending order according to the elevation of their respective endpoints to obtain the dam line set .

[0026] Preferably, the specific method for obtaining the intersection points of the perpendicular segment and the contour line in step S4.1.3 is as follows:

[0027] A41. Obtain the set of node coordinate strings of the contour line , where represents the contour line The coordinates of the

[0028] A42. Using the line segment between the coordinates of two adjacent nodes on the contour line as an element, construct a set of line segments of the contour line ; where represents the s th line segment, u represents 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 ;

[0029] A43. By calculating the intersection of line segments, find all elements in the set of line segments that intersect with the vertical line segment to obtain the set ;

[0030] A44. Calculate the intersection points of each element in the set with the vertical line segment .

[0031] Preferably, the specific method for obtaining the library surface coordinate string in S4.4 is:

[0032] Assume that the endpoint of the th dam line is located on the line segment of the contour line , and the other endpoint is located on the line segment of the contour line ; where: the set of node coordinate strings of the contour line is represented as , is represented as , is represented as , , , and all belong to the set of node coordinate strings , and , both belong to ;

[0033] When the contour line is a non-closed contour line, then the library surface coordinate string is:

[0034]

[0035] When the contour line is a closed contour line, the contour line and the th dam line form two closed polygons, and the coordinate strings of the two closed polygons are respectively expressed as:

[0036]

[0037] (17),

[0038] Obtain the starting coordinate of the river network segment where the candidate point is located, and judge whether there is an inclusion relationship between the starting coordinate of the river network segment and the 、 shown closed polygon. Select the coordinate string corresponding to the closed polygon with an inclusion relationship as the reservoir surface coordinate string ; if there is no inclusion relationship between the starting coordinate of the river network segment and the 、 shown closed polygons, then use the starting coordinate of the river network segment and the candidate point as the two endpoints of the line segment to generate a new vector line feature, solve the intersection points of the vector line feature and the two closed polygons, and select the coordinate string corresponding to the closed polygon with the number of intersection points greater than or equal to 2 as the reservoir surface coordinate string .

[0039] Preferably, the specific method for verifying whether the reservoir capacity is qualified in S4.4 is:

[0040] Obtain the contour line set in which the elevation value is less than or equal to of the contour line set , , and calculate the reservoir capacity value corresponding to the th dam line according to formula (18). If then the verification is qualified;

[0041] Among them, the contour line set is the set of contour lines intersecting with each dam line in the dam line set , the contour line set is , is the contour line intersecting with the dam line in the dam line set , is the elevation of the contour line intersecting with the th dam line, is the minimum reservoir capacity allowed by the project;

[0042] The The storage capacity value corresponding to the dam line is:

[0043]

[0044] Among them: when , ; is the reservoir surface area enclosed by the t th contour line and the dam line, is the elevation of the t th contour line.

[0045] Preferably, in S4.5, verifying whether the reservoir surface shape is qualified is specifically:

[0046] If it satisfies and , then the reservoir surface shape is qualified; among them, the reservoir surface shape parameters , are respectively expressed as:

[0047]

[0048] Among them, is the perimeter of the reservoir surface corresponding to the th dam line, is the length of the th dam line, is the farthest Euclidean distance between the reservoir surface coordinates and the candidate point , 、 are all set reservoir shape threshold values.

[0049] The present invention also provides a multi-factor and multi-objective intelligent online site selection device for a pumped storage power station, including a storage medium and a processor. A computer program is stored in the storage medium. When the processor runs the computer program, it executes the multi-factor and multi-objective intelligent online site selection method for the pumped storage power station.

[0050] The present invention also provides a storage medium, in which a computer program is stored. When the computer program runs, it executes the multi-factor and multi-objective intelligent online site selection method for the pumped storage power station.

[0051] Applying the technical solution of the present invention has the following beneficial effects:

[0052] The present invention combines online zoning and parameter setting methods to preliminarily select suitable site addresses, and based on the set multi-objective constraint conditions, selects high-quality upper and lower reservoirs. The method of the present invention improves the site selection efficiency to a certain extent, reduces the probability of misselection and omission, and has scientificity and convenience, belonging to the field of site selection planning for pumped storage power stations.

[0053] The present invention takes into account the influence of various geographical elements such as terrain, water system, geology, and ecological red line, and under the constraints of a multi-objective model of dam height, dam length, reservoir capacity, matching of upper / lower reservoirs, reservoir surface morphology, etc., intelligently solves all candidate points that meet the conditions within the region. On the basis of the preliminarily selected sites, designers can select candidate points of interest to generate reservoirs, and based on the set construction conditions of the upper and lower reservoirs, preliminarily select the matching reservoirs.

[0054] The present invention combines remote sensing image data and DEM data. Through online site selection and result visualization, it can not only view the distribution of the geographical locations of the upper / lower reservoirs as a whole, but also evaluate the geographical conditions around the reservoirs in detail, providing more detailed data references 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.

[0055] In addition to the purposes, features and advantages described above, the present invention has other purposes, features and advantages. The present invention will be further described in detail below with reference to the drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] The drawings constituting a part of this application are used to provide a further understanding of the present invention. The schematic embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation to the present invention. In the drawings:

[0057] Figure 1 is a flowchart of the multi-factor multi-objective intelligent online site selection method for a pumped storage power station in Embodiment 1;

[0058] Figure 2 is the schematic diagram of the candidate points in the research area of Embodiment 2 and the result of the preliminarily selected matching reservoir in ;

[0059] Figure 3 is Figure 2 the enlarged view of the result of the preliminarily selected matching reservoir in DETAILED DESCRIPTION OF THE EMBODIMENTS

[0060] To facilitate the understanding of the present invention, the present invention will be described more comprehensively below, and preferred embodiments of the present invention are given. 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 content of the present invention more thorough and comprehensive.

[0061] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the technical field to which this invention belongs. The terms used in the description of the present invention herein are for the purpose of describing specific embodiments only and are not intended to limit the present invention.

[0062] Example 1:

[0063] As Figure 1 shown, this embodiment provides a multi-factor and multi-objective intelligent online site selection method for pumped storage power stations, which optimizes the online site selection method for pumped storage power stations from aspects such as site selection efficiency, reservoir capacity calculation, optimization of homogeneous sites, and comprehensive site evaluation, and mainly includes the following steps:

[0064] S1. Obtain the contour layer data and river system data of the research area, specifically:

[0065] According to the vector data of the defined research area, the given initial contour elevation value, contour interval, and flow threshold parameters, use DEM data to extract the contour layer data and river system data of the research area.

[0066] S2. Extract the midpoints of each river network segment as candidate points to construct a candidate point set ;

[0067] Specifically, according to the river system data obtained in S1, traverse the river network segments, extract the midpoints of each river network segment and put them into the candidate point set , and at the same time, record the river identification ID where each candidate point is located, and calculate the elevation of each candidate point according to the terrain data , where represents the th candidate point in the set , represents the elevation of the th candidate point in the set , is the number of candidate points in the set .

[0068] S3. Screen the candidate points in the set according to the water diversion distances of the upper and lower reservoirs and the head parameter to obtain a new candidate point set ;

[0069] Specifically, in order to improve the efficiency of site selection, first conduct a preliminary screening of the candidate points in the set based on the water diversion distance and the head parameter, specifically:

[0070] Traverse and calculate the set Any two candidate points and the candidate point The Euclidean distance and the elevation difference , if it satisfies , then the candidate point and the candidate point can form the dam sites of the upper reservoir and the lower reservoir. The candidate point and the candidate point are put into the set ; among them, , is the diversion distance, is the head parameter, and the set , is the number of candidate points in the set .

[0071] Furthermore, the Euclidean distance between the candidate point and the candidate point and the elevation difference are calculated respectively as follows:

[0072]

[0073]

[0074] Among them, represents the Euclidean distance, represents taking the absolute value, represents the elevation of the candidate point , represents the elevation of the candidate point .

[0075] S4. Use the multi-objective constraint model to verify the dam length, dam height, reservoir capacity, and reservoir surface morphology of the candidate points in the set . Put the candidate points that meet the multi-objective constraint model in the set into the set ;

[0076] Considering the construction conditions of the pumped-storage power station and the impact of the economic benefits of the power station, in this embodiment, the multi-objective constraint model is used to screen out the power station locations with good conditions and high benefits; specifically, the multi-objective constraint model is:

[0077] (3),

[0078] Among them, is the reservoir dam line length of the candidate point , is the candidate point of the reservoir dam height, is the candidate point of the reservoir storage capacity, is the candidate point of the ratio of the reservoir surface perimeter to the dam line length, is the candidate point of the ratio of the farthest distance to the reservoir surface to the dam line length, is the maximum allowable reservoir dam length for the project, is the maximum allowable reservoir dam height for the project, is the minimum allowable reservoir storage capacity for the project, 、 is the set storage capacity form threshold.

[0079] Preferably, before performing step S4, it also includes a screening step of removing homogeneous sites, specifically: traverse and calculate the set any two candidate points in and the Euclidean distance between them, if is less than the set sampling distance S , then delete the candidate point from the set either or until the Euclidean distance between any two candidate points in the set is greater than the sampling distance ; where and and both belong to ; by removing homogeneous sites, the number of candidate points in the set can be reduced, improving the calculation efficiency (if the screening step of removing homogeneous sites is not performed, although it does not affect the subsequent screening results, it will lead to a decrease in calculation efficiency).

[0080] Furthermore, use a multi-objective constraint model to verify the dam length, dam height, storage capacity, and reservoir surface shape of the candidate point in the set , specifically:

[0081] S4.1. Obtain the dam line set that satisfies the dam line length constraint for the candidate point , where , is the total number of dam lines of the candidate point , and satisfying the dam line length constraint means that each dam line in the dam line set satisfies ;

[0082] Preferably, in step S4.1, the candidate points are obtained A set of dam lines that satisfy the dam line length constraint Specifically:

[0083] S4.1.1. According to the set The candidate points in Elevation , filter to obtain the contour line set that satisfies ; among them, ; where Represents the th contour line, Is an integer and 1, w , Is the number of contour lines in the set , Represents the elevation of the contour line , Is the set elevation tolerance;

[0084] S4.1.2. Draw a perpendicular line segment to the river network segment where the candidate point is located through the candidate point . Among them, the length of the perpendicular line segment is set to the maximum dam length parameter , and the candidate point is located at the midpoint of the perpendicular line segment . The two endpoints of the perpendicular line segment are respectively denoted as and and ;

[0085] S4.1.3. Perform an intersection calculation between the perpendicular line segment and the contour line in the set . If the perpendicular line segment intersects the same contour line at two or more points, then extract the connection line between adjacent two points and select the connection line that intersects the river network segment as the reservoir dam line; among them, the two endpoints of the reservoir dam line are denoted as , , and (that is, the candidate point does not coincide with the two endpoints of the dam line);

[0086] S4.1.4. Sort the obtained reservoir dam lines in descending order according to the elevation of their respective endpoints to obtain the dam line set ;

[0087] Specifically, the dam line set , the corresponding contour line set is , indicating the perpendicular line segment and the k th contour line in , and respectively represent the two endpoints of the dam line , and the number of dam lines in the set is the same as the number of contour lines in , both being .

[0088] Furthermore, the calculation method for the length of each dam line in the dam line set is as follows:

[0089]

[0090] Furthermore, the specific method for obtaining the intersection point of the perpendicular line segment and the contour line in step S4.1.3 is as follows:

[0091] A41. Obtain the set of node coordinate strings of the contour line , indicating the th node coordinate on the contour line

[0092] A42. Take the line segment between two adjacent node coordinates on the contour line as an element to construct the line segment set of the contour line ; if the contour line is a closed contour line, then ; if the contour line is a non-closed contour line, then ; where represents the s th line segment, u indicating the number of line segments;

[0093] A43. Find all elements in the line segment set that intersect with the perpendicular line segment to obtain the set ;

[0094] Specifically, in this embodiment, the method for determining whether the element in the line segment set (i.e., the line segment) intersects with the perpendicular line segment is as follows:

[0095] Hypothetical line segment set The elements in are represented as , where: both belong to the set of node coordinate strings ; First, a straddle test is performed on the two line segments. The mathematical expression for the straddle test is:

[0096]

[0097] where, is a quick rejection test for quickly excluding non-intersecting line segments; represents the point 's coordinates, represents the point 's coordinates, represents the point 's x coordinates, represents the point 's x coordinates, represents the point 's y coordinates, represents the point 's y coordinates, represents the point 's y coordinates, represents the point 's y coordinates.

[0098] After meeting the straddle test conditions, a line segment intersection determination based on vector cross product is performed. The mathematical expression is:

[0099] (6),

[0100] (7),

[0101] where, represents the vector 、 cross product; 、 、 、 are the numerical results of four groups of vector cross products respectively, represents the multiplication operation.

[0102] A44. Calculate the set The elements in each element and the vertical line segment The intersection point.

[0103] Furthermore, calculate the intersection points of the elements in the set with the vertical line segment , specifically:

[0104] Suppose the element in the set is represented as , where both belong to the set of node coordinate strings ; Denote the intersection point of the element with the vertical line segment as . In this embodiment, the solution method of

[0105] is as follows: Suppose there exists a parameter satisfying formula (8):

[0106]

[0107] Then the right - hand sides of the two equalities in formula (8) are equal, that is: x, y The coordinates are also equal, and then formula (9) is obtained:

[0108] (9),

[0109] Further solve the system of binary linear equations of formula (9) to obtain formula (10):

[0110] (10),

[0111] Among them, the denominator in formula (10) is not zero, which is expressed as:

[0112]

[0113] After obtaining the value of through formula (10), substitute into the first equality of formula (8) to obtain formula (12), or substitute into the second equality of formula (8) to obtain formula (13), then the value of can be solved:

[0114]

[0115] (13),

[0116] Among them, and are the two endpoints of the vertical line segment respectively; represents the point of coordinates representing the coordinates of point representing the coordinates x of point representing the coordinates x of point representing the coordinates of point; representing the coordinates y of point representing the coordinates y of point representing the coordinates y of point representing the coordinates y of point representing the coordinates of point indicating a multiplication operation.

[0117] S4.2. Set the initial value of to 1;

[0118] S4.3. Check whether the dam height corresponding to the th dam line in the dam line set is qualified. If it is qualified, go to step S4.4; if it is unqualified, judge whether is equal to k . If it is not equal, take = k = k +1 and repeat step S4.3. If it is equal, end the verification of the candidate point ;

[0119] Specifically, the dam height corresponding to the th dam line is specifically:

[0120]

[0121] wherein, is the elevation of the end point of the th dam line, that is, the elevation of the th contour line in the contour line set , and is the elevation of the candidate point .

[0122] Further, substitute the dam height into formula (3) for dam height verification. If it satisfies then the dam height verification is qualified; otherwise, it is unqualified.

[0123] S4.4. Obtain the dam line set All the reservoir surface coordinate strings corresponding to the dam lines with elevations less than or equal to the elevation of the th dam line; verify whether the reservoir capacity corresponding to the th dam line is qualified. If it is qualified, proceed to step S4.5; if it is unqualified, end the verification of the candidate points .

[0124] Specifically, the size of the reservoir capacity directly determines the water storage capacity of the reservoir. To select a suitable reservoir location, in this embodiment, the closed surface formed by the intersection of the dam line and the contour line is used as the reservoir surface. First, obtain the set of contour lines with elevation values less than or equal to , , , and then calculate the reservoir surface coordinate strings formed by each contour line in the contour line set and the corresponding dam line respectively, where is the elevation of the contour line that intersects with the th dam line. Considering that there are two types of contour lines in the study area, non-closed contour lines and closed contour lines, it is necessary to calculate the reservoir surface coordinate strings in different cases:

[0125] Assume that the endpoint of the th dam line is located on the line segment of the contour line , and the other endpoint is located on the line segment of the contour line ; where: the set of node coordinate strings of the contour line is represented as , is represented as , is represented as , , , and all belong to the set of node coordinate strings , and , both belong to ;

[0126] When the contour line is a non-closed contour line, it means that the contour line If the starting and ending coordinates are inconsistent, the reservoir surface coordinate string is:

[0127]

[0128] When the contour line is a closed contour line, the contour line and the th dam line form two closed polygons, and the coordinate strings of the two closed polygons are respectively expressed as:

[0129]

[0130] (17),

[0131] Considering that the reservoir should be located in the upstream area of the dam line, this embodiment introduces the river water system direction to determine the reservoir surface coordinate string corresponding to the current candidate point. Specifically: Obtain the starting coordinate of the river network line segment where the candidate point is located, and use the overlay analysis algorithm to judge whether there is an inclusion relationship between the starting coordinate of the river network line segment and the 、 shown closed polygons, and select the coordinate string corresponding to the closed polygon with an inclusion relationship as the reservoir surface coordinate string ; if there is no inclusion relationship between the starting coordinate of the river network line segment and the 、 shown closed polygons, then use the starting coordinate of the river network line segment and the candidate point as the two endpoints of the line segment to generate a new vector line feature, and use the overlay analysis algorithm to solve the intersection points of the vector line feature and the two closed polygons. The coordinate string of the closed polygon with the number of intersection points greater than or equal to 2 is the reservoir surface coordinate string .

[0132] Furthermore, in order to obtain a more accurate reservoir capacity value, this embodiment introduces a layered reservoir capacity calculation method. Specifically:

[0133] Obtain the set in which the elevation value is less than or equal to of the contour line set , , and calculate and accumulate the reservoir capacity values enclosed by the adjacent contour lines and the dam line in the set respectively to obtain the reservoir capacity value corresponding to the th dam line. If , then enter step S4.5, otherwise end the verification of the candidate point , and reselect the candidate point to start the verification from step S4.1; The The elevations of the contour lines where the two endpoints of the dam line are located;

[0134] Further, The reservoir capacity value corresponding to the th dam line is:

[0135]

[0136] Where: when , ; is the reservoir surface coordinate string The reservoir capacity of the corresponding reservoir, is the t th reservoir surface area enclosed by the contour line and the dam line (which can be obtained according to the reservoir surface coordinate string), is the elevation of the t th contour line.

[0137] S4.5. Check whether the reservoir surface shape is qualified. If it is qualified, put the candidate point into the set ; if it is unqualified, judge whether k is equal to . If it is not equal, take k = k +1 and repeat step S4.3. If it is equal, end the verification of the candidate point ;

[0138] Specifically, in order to describe the reservoir surface shape and find a dam site with a shorter dam length and a larger reservoir surface, introduce the reservoir surface shape parameters , to distinguish the quality of the reservoir surface; if and are satisfied, the reservoir surface shape is qualified, and the candidate point is put into the set , and all verification steps for the current candidate point are exited, and return to step S4.1 to calculate the next candidate point in the set ; if and are not satisfied, judge whether the current k is equal to . If it is not equal, take k = k +1 and repeat step S4.3. If it is equal, end the verification of the candidate point ;

[0139] Further, the reservoir surface shape parameters , are expressed as:

[0140]

[0141] Among them, is the perimeter of the reservoir surface corresponding to the th dam line, is the length of the th dam line, is the farthest Euclidean distance between the reservoir surface coordinates and the candidate point . Here, the reservoir surface coordinates refer to any coordinate point in the reservoir surface coordinate string .

[0142] S5. Select any candidate point from the set , and screen out the candidate points from the set that can form the upper reservoir or the lower reservoir with the candidate point to obtain the set formed by all candidate points ;

[0143] Specifically, based on the screening results of step S4, the designer can randomly select a candidate point of interest from the set to generate a reservoir, and then screen out all candidate points from the set that can form the upper reservoir or the lower reservoir with the candidate point for subsequent output of the optimal matching site.

[0144] Furthermore, in this embodiment, according to formula (21), screen out the candidate points from the set that can form the upper reservoir or the lower reservoir with the candidate point :

[0145]

[0146] Among them:

[0147]

[0148]

[0149]

[0150] Among them, is the distance between the reservoir corresponding to the candidate point and the reservoir corresponding to the candidate point , is the water head of the reservoir corresponding to the candidate point and the reservoir corresponding to the candidate point , is the candidate point Corresponding reservoir and candidate points Distance-height ratio of the corresponding reservoir, is the elevation of the candidate point ; is the elevation of the candidate point ; is the maximum diversion distance (default configuration parameter), is the minimum head (default configuration parameter), is the maximum distance-height ratio (default configuration parameter), is the set the number of candidate points in.

[0151] S6. For each candidate point in the set perform a suitability analysis to obtain the candidate point with the best match to the candidate point.

[0152] 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 issues such as whether the water source is sufficient, whether the geological conditions are suitable for construction, and whether the ecological red line is damaged. In this embodiment, by analyzing the key influencing factors of the pumped-storage power station site, suitability evaluation indicators are screened out, and the pumped-storage power station site is evaluated by the analytic hierarchy process.

[0153] Specifically, the suitability evaluation indicators in this embodiment include topographic condition indicators, geological condition indicators, external environment indicators, and water source condition indicators. Among them, the topographic condition indicators include head, distance-height ratio, reservoir surface area, traffic conditions, and construction conditions; the geological condition indicators include geological stability, geotechnical engineering characteristics, and material source conditions; the external environment indicators include the number of immigrants involved in the project area, cultivated land area, area of ecological environment sensitive areas, and distance from the new energy enrichment area or the power grid load center; the water source condition indicators include the annual average runoff and the annual average sediment content.

[0154] Furthermore, the specific method for performing a suitability analysis on each candidate point in the set is as follows:

[0155] S6.1. According to the 1-9 scale method, compare each evaluation indicator pairwise to construct an indicator matrix ;

[0156]

[0157] Among them, represents the importance degree of the evaluation indicator i with respect to the evaluation indicator j , is the number of evaluation indicators. ​​

[0158] Further, the 1-9 scale method is defined as:

[0159] (26),

[0160] S6.2. Determine whether the established index matrix has consistency according to the random consistency ratio. If it does not have consistency, the index matrix needs to be re-established A , where A is the consistency index of the index matrix , and A is the random consistency index of the index matrix ; A Specifically, determining whether the index matrix

[0161] has consistency is specifically as follows: A where

[0162]

[0163]

[0164] where is the maximum eigenvalue of the index matrix A .

[0165] Further, the random consistency index A of the index matrix can be directly obtained by those skilled in the art based on the existing technology, where has a corresponding relationship with . In this embodiment, some values corresponding to the values are given:

[0166]

[0167] S6.3. Use expert scoring to perform fuzzy evaluation on each candidate point in the set to obtain the candidate point that best matches the candidate point ;

[0168] S6.3.1. According to the scoring results of experts on each evaluation index, calculate the comprehensive weight of each evaluation index, and construct the fuzzy comprehensive evaluation matrix R of the candidate point , specifically as follows:

[0169]

[0170]

[0171] where is the evaluation result of the m th expert on the i th evaluation index, m , is the number of experts; is the comprehensive score of the i th index, ;

[0172] S6.3.2. Based on the fuzzy comprehensive evaluation matrix R , the score of the candidate point is obtained through fuzzy comprehensive evaluation operation, specifically:

[0173]

[0174] Among them, is the weight matrix of each evaluation index of the candidate point , and is the weight corresponding to the n th evaluation index.

[0175] S6.3.3. Based on the scores of each candidate point , the candidate point that best matches the candidate point is output;

[0176] Preferably, according to the construction and operation management conditions of the pumped-storage power station, the scores of the selected pumped-storage power station (candidate point ) are divided into 5 levels: excellent, good, average, poor, and very poor. At the same time, a 5-level goodness degree is introduced to quantify qualitative indicators:

[0177]

[0178] (33),

[0179] According to the score of the candidate point , the rating of the pumped-storage site can be judged, and thus the candidate point that best matches the candidate point can be found from the set .

[0180] The site selection method of this embodiment takes into account various geographical factors such as terrain, water system, geology, and ecological red line. Under the constraints of multi-objective models such as dam height, dam length, reservoir capacity, matching upper / lower reservoirs, and reservoir surface morphology, all candidate points that meet the conditions within the region are intelligently solved. Based on the general election sites, designers can select candidate points of interest to generate reservoirs, and based on the set construction conditions of the upper and lower reservoirs, the most optimally matched reservoirs are generally selected. The method of this embodiment combines remote sensing image data and DEM data. Through online site selection and result visualization, it can not only view the distribution of the geographical locations of the upper / lower reservoirs as a whole, but also evaluate the geographical conditions around the reservoirs in detail, providing more detailed data references for the site selection and planning of pumped-storage power stations. Compared with manual site selection, it greatly improves the efficiency, accuracy, scientificity, and convenience of site selection.

[0181] Embodiment 2:

[0182] In this embodiment, the global 30-meter DEM data is used to further illustrate the site selection method in Embodiment 1.

[0183] S1. Online draw the study area 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, use image processing technology to merge the tiles, and use the vector polygon layer to perform image clipping on the merged tile data to obtain the terrain raster data within the study area; then based on the terrain raster data, use GIS analysis algorithms to generate contour lines and river water system data. The initial contour elevation value used in this embodiment is 0 meters, the contour interval is 20 meters, and the flow threshold is 300. The extracted contour layer contains 7771 line data, and the water system layer contains 4120 line data.

[0184] S2. According to the river water system data generated in S1, traverse the river network line segments, extract the midpoints of the river network line segments and put them into the candidate point set , and calculate the elevation of each candidate point based on the terrain raster data; in this embodiment, the set is obtained, and the corresponding elevation set of each candidate point is .

[0185] S3. Traverse the candidate point set , calculate the Euclidean distance between any two candidate points and the candidate point and the elevation difference , filter out the candidate points where the upper (lower) reservoir cannot be found, and obtain a new candidate point set . The diversion distance used in this embodiment is 5000 meters, and the water head is 150 meters.

[0186] S4. Use the multi-objective constraint model to check the dam length, dam height, reservoir capacity, and reservoir surface morphology of the candidate points in the set , and put the candidate points that meet the multi-objective constraint model in the set into the set ;

[0187] In this embodiment, the multi-objective constraint model is set as:

[0188] 1) Dam length constraint: ;

[0189] 2) Dam height constraint: ;

[0190] 3) Reservoir capacity constraint: ;

[0191] 4) Reservoir surface morphology constraint: .

[0192] Screen homogeneous sites: Traverse and calculate the Euclidean distance between any two candidate points and in the set . If is less than the set sampling distance S , then delete any one of the candidate points from the set , until the Euclidean distance between any two candidate points in the set is greater than the sampling distance ; where and , both belong to , is the number of candidate points in the set ;

[0193] In this embodiment, the sampling distance S is set to 500 meters, and candidate points are selected from the filtered set for subsequent detailed description. The Euclidean distance between the candidate point and all candidate points in the set is greater than S .

[0194] S4.1. Obtain the dam line set where the candidate points meet the dam line length constraint. Specifically:

[0195] S4.1.1. The elevation of the candidate point ​ = 525 m, set = 200 m, filter the contour lines that meet to obtain a set of contour lines .

[0196] S4.1.2. Draw a perpendicular line segment to the river segment where the candidate point is located (in this embodiment, the river segment ID is 529);

[0197] S4.1.3. Calculate the intersection points of the perpendicular line segment and the set of all contour lines to obtain a dam line formed by three contour lines in the set ;

[0198] S4.1.4. The elevation of the endpoints of each dam line is 580 m, 560 m, and 540 m from large to small, corresponding to the contour lines , and the dam line set .

[0199] S4.2. Set the initial value of to 1;

[0200] S4.3. Verify whether the dam height corresponding to the th dam line in the dam line set is qualified; calculate that the length of the th dam line = m, and the dam height = m, which meets the dam length and dam height constraints, and enter step S4.4; m, satisfying the dam length and dam height constraints, enter step S4.4;

[0201] S4.4. Calculate that the line segments intersecting the contour line are respectively ; , . In this embodiment, is a non-closed contour line. Therefore, the reservoir surface coordinate string is .

[0202] Furthermore, calculate the corresponding reservoir capacity value as:

[0203] ;

[0204] is greater than , so it meets the reservoir capacity constraint.

[0205] S4.5. In this embodiment, calculate that = 5011.18 m, = 1785.51 m, then ≈20.54, ≈7.32, satisfying and , that is, satisfying the reservoir surface shape constraint conditions; therefore, the candidate point is put into the set to obtain the final set as Figure 2 shown.

[0206] S5. General election to match the reservoir: Select the candidate points in the set (corresponding to the in the above set ). According to the constraint calculation of formula (21), it is obtained that there are 19 candidate points corresponding to the reservoirs in the study area that satisfy the constraint conditions, that is, ; in this embodiment, m is set, = m, = 15, and the general election result is as Figure 3 shown;

[0207] S6. Conduct suitability analysis on each candidate point in the set . Through fuzzy comprehensive evaluation operation, the candidate point has the highest score of 96 points; that is, the candidate point is the optimal match for the candidate point .

[0208] Embodiment 3:

[0209] This embodiment provides an intelligent online site selection device for a pumped storage power station with multiple elements and multiple objectives, including a storage medium and a processor. A computer program is stored in the storage medium. When the processor runs the computer program, it executes the intelligent online site selection method for a pumped storage power station in Embodiment 1.

[0210] The above is only the preferred embodiment of the present invention and is not used to limit the present invention. For those skilled in the art, the present invention can have various changes and modifications. 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; 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 Verification of 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 .

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 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.

4. The multi-factor and multi-objective intelligent online site selection method for a pumped storage power station according to any one of claims 1 to 3, characterized in that: 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 intersecting 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 1 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.

7. 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: 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.

8. 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 7.

9. 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 7 is executed.

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