Intelligent design method and system for water delivery system of pumped storage power station

Abstract

The present invention relates to the field of underground engineering technology for pumped storage power stations, and discloses an intelligent design method and system for a water delivery system for a pumped storage power station. The method comprises: digitizing the administrative area scope, river network data, sensitive area data, regional geological data, hydrological data and traffic network data in a pumped storage power station project and forming a GIS platform layer; integrating the data layer into a data scene and publishing it to the cloud; obtaining the business logic and distance-to-height ratio requirements of the pumped storage power station in the pumped storage power station project, and constructing a multi-dimensional multi-factor association logic model; integrating the multi-dimensional multi-factor association logic model with the GIS platform to obtain potential data of a library location; generating a plane design control point based on the analysis results, and integrating the geological data to obtain a plane layout combination scheme; the system comprises a basic information data module, an analysis data module, and a scheme combination module. The present invention realizes the intelligent design of a water delivery system for a pumped storage power station.

Description

Technical Field

[0001] The present invention relates to the technical field of underground engineering of pumped storage power stations, and in particular to an intelligent design method and system for a water delivery system of a pumped storage power station. Background Art

[0002] At present, the site selection of pumped storage power stations is mainly based on planning, focusing on macro-site selection research, and generating site selection planning reports as design deliverables. There is a lack of coordination with downstream construction professionals, and a lack of extended application of planning data to engineering project design and construction. The site selection of pumped storage power stations is based on the GIS system, professional scheme design, model establishment and design drawing, and BIM system. Different professional designers use different systems and independent design software platforms, resulting in poor collaborative modification capabilities and easy data fragmentation. The GIS system, BIM system and design data are relatively isolated, and there is a lack of data-driven integrated design solutions. In the design of the plane layout of the water transmission system, it is necessary to consider the influence of the layout of the surge tank, the layout of the plant and the layout of the upper and lower reservoirs at the same time. The design boundaries are complex and there are many scheme combinations. At present, there is a lack of a method model for the design of integrated macro-site selection of pumped storage power stations and optimization of the plane layout of the water transmission system.

[0003] The modeling of water conveyance system tunnels has two degrees of freedom: one is the plane and spatial changes of the tunnel line, and the other is the geometric shape constraint changes of the cavern itself. Because the axis of the underground powerhouse is usually dynamically adjusted according to the ground stress conditions and fault distribution. The plane layout of the water diversion system needs to be dynamically adjusted according to the axis of the powerhouse and the location of the water inlet, and the plane design usually includes plane turns. When designing the water conveyance system, there are plane turns in the two-dimensional plane layout and elevation turns in the longitudinal section layout. The random coupling of plane turns and elevation turns can easily lead to a large number of spatial turns, which increases the difficulty of construction and installation and affects the construction period.

[0004] BIM models have high application value in guiding high-pressure pipeline excavation and support design, finite element calculation, and refined installation of steel pipelines. However, in terms of water supply system model generation, compared with highway transportation systems and long-distance water diversion buildings, water supply systems have complex longitudinal sections and high requirements for matching plan layout and longitudinal section layout. There is a lack of effective methods and procedures for the longitudinal section characteristics of water supply systems, such as inclined well / data layout, surge well selection, and complex three-dimensional centerline fitting and BIM model generation.

[0005] In summary, the site selection and water delivery system design of pumped storage power stations have a significant impact on project investment. The design boundary is complex, and the design optimization and multiple scheme comparison requirements are high, which is inconsistent with the current two-dimensional design based on a single design software. At present, there is a lack of research on the plane layout line selection model of pumped storage power stations and the generation of horizontal and longitudinal section designs based on GIS system site selection schemes. Since the longitudinal section design is more complex than the water diversion project, the design head is higher, and the project cost is higher, the digital design research on pumped storage power stations is of high urgency.

[0006] Prior art 1, Chinese patent, patent number: 202410227878.2 discloses a method for comparing water transmission and power generation system schemes in the early design stage of a pumped storage power station, including establishing a parametric template for the reference range of the first-level transition and second-level transition axes of the water transmission pipeline skeleton and the outline of the plant and the outlet of the auxiliary cavern, combining the terrain surface to perform a three-dimensional design of the water transmission and power generation system scheme and generate a three-dimensional model, reading the three-dimensional model to calculate the engineering quantity and investment of the water transmission pipeline, surge chamber, plant and auxiliary cavern, deriving the calculation results, establishing multiple water transmission and power generation system design schemes for comparison, and selecting the scheme with the smallest sum of investment in the water transmission pipeline, surge chamber, plant and auxiliary cavern as the recommended scheme for the water transmission and power generation system. Although the method for comparing water transmission and power generation system schemes in the early design stage of a pumped storage power station can improve the design efficiency and optimality of the early scheme of the intelligent design and power generation system of the water transmission system of the pumped storage power station, it has the characteristics of rapid response to design changes and convenient quantitative comparison; however, its model is relatively simple and the comparison process is cumbersome, which affects the efficiency of the scheme comparison results to a certain extent.

[0007] Prior art 2, Chinese patent, patent number: 202311271645.4 provides a cascade pumped storage power station, including a reservoir, a water delivery system, a power generation system and a pump-turbine; a water delivery system, a power generation system and a pump-turbine are arranged between every two upper and lower adjacent reservoirs; every two upper and lower adjacent reservoirs, and the water delivery system, power generation system and pump-turbine that connect them, form a first-level pumped storage power station, thereby forming an N-1 level pumped storage power station. Make full use of reservoirs and power station supporting facilities. Although the reservoirs in the middle layers are both the lower reservoirs of the upper-level pumped storage power station and the upper reservoirs of the lower-level pumped storage power station, they greatly broaden the site selection range of pumped storage power stations, save engineering investment, and have broad guidance and promotion significance; however, its structure is relatively simple, the degree of intelligence is low, and the environmental impact is not taken into account, so that the performance of the energy storage power station needs to be further improved.

[0008] Prior art three, Chinese patent, patent number: 202410519591.7 relates to a method, device, computer equipment, storage medium and computer program product for selecting a project management scheme for a pumped storage power station, which can be used in the field of computer technology. The method includes: obtaining data of candidate project management schemes for a pumped storage power station; performing prediction processing on the data of the candidate project management schemes through multiple project management scheme prediction models to obtain multiple prediction results of the candidate project management schemes; fusing multiple prediction results of the candidate project management schemes to obtain a comprehensive prediction result of the candidate project management schemes; performing feature decomposition and feature extraction processing on the comprehensive prediction results to obtain a comprehensive prediction feature result of the candidate project management schemes; and selecting the target project management scheme for the pumped storage power station from the candidate project management schemes based on the comprehensive prediction feature result. Although the adoption can improve the efficiency of selecting project management schemes for pumped storage power stations; however, the model considers many factors, resulting in insufficient response speed and flexibility of the prediction model, making it difficult to cope with instantaneous fluctuations in power grid load.

[0009] At present, the existing technologies 1, 2 and 3 do not consider geographical restrictions, environmental impacts, and have insufficient response speed and flexibility, making it difficult to cope with instantaneous fluctuations in grid load. To solve the above problems, the present invention provides an intelligent design method and system for a water delivery system of a pumped storage power station. Summary of the invention

[0010] The main purpose of the present invention is to provide an intelligent design method and system for the water delivery system of a pumped storage power station, so as to solve the problems in the prior art that geographical restrictions, environmental impacts, response speed and flexibility are insufficient, and it is difficult to cope with instantaneous fluctuations in power grid load.

[0011] To achieve the above object, the present invention provides the following technical solutions:

[0012] An intelligent design method for a water delivery system of a pumped storage power station, the intelligent design method for a water delivery system of a pumped storage power station comprising:

[0013] The terminal sends the pumped storage power station project, digitizes the administrative area scope, river network data, sensitive area data, regional geological data, hydrological data and traffic network data of the pumped storage power station project and forms a GIS platform layer; integrates the data layer into a data scene and publishes it to the cloud;

[0014] The GIS platform layer is used to calculate the regional slope, the area that can be formed into a reservoir by damming, the natural depression and the peak vertex as the site selection data layer; the business logic and distance-to-height ratio requirements of the pumped-storage power station in the pumped-storage power station project are obtained, and a multi-dimensional and multi-factor association logic model is constructed;

[0015] The multi-dimensional and multi-factor correlation logic model is integrated with the GIS platform to obtain the potential reservoir location data; the potential reservoir location data is analyzed, and the plane design control points are generated based on the analysis results, and the geological data is integrated to obtain the plane layout combination plan.

[0016] As a further improvement of the present invention, the process of integrating data layers into data scenes and publishing them to the cloud includes:

[0017] Acquire the pumped storage power station project sent by the terminal, and classify the acquired pumped storage power station project according to the geological data into plane area address data, three-dimensional geological body model, two-dimensional geological surface model and structured geological data;

[0018] Select a site for the classified data, and digitize the classified data into a GIS platform layer based on the administrative area of ​​the site, river network data, sensitive area data, regional geological data, hydrological data, and transportation network data;

[0019] Publish the GIS platform layer to the cloud, and users can view the GIS platform layer through the cloud to make decisions and design solutions.

[0020] As a further improvement of the present invention, the process of constructing a multi-dimensional multi-factor association logic model includes:

[0021] The GIS platform layer is used to calculate the regional slope, the area that can be formed into a reservoir by damming, the natural depression and the peak vertex as the site selection data layer;

[0022] Obtain the business logic and distance-to-height ratio requirements of the pumped-storage power station project, and build a multi-dimensional and multi-factor association logic model; the multi-dimensional and multi-factor association logic model divides the site selection data layer into a small-scale site selection area and a large-scale site selection area;

[0023] For small-scale site selection areas, reservoir site comparison is carried out; for large-scale site selection areas, water transmission routes are selected and the site selection area is divided into at least one area; calculations are performed based on each area to obtain a standard distance-to-height ratio range combination.

[0024] As a further improvement of the present invention, the process of obtaining the standard distance-to-height ratio range combination includes:

[0025] Build a design scenario and conduct a comparison of reservoir sites; select reservoir condition areas as the key, take the regional commanding heights as the upper reservoir, and combine the reservoir area and the natural depression as the lower reservoir for multi-dimensional association combination; in the site selection area, traverse and combine the dam area and the dam area, the dam area and the natural depression, and the mountain top and the natural depression in pairs to obtain all the site selection combinations;

[0026] According to the characteristics of pumped storage power stations, the site selection area is divided into at least one region according to the administrative area connection and natural river distribution; within a single site selection area, the dammed reservoir area and the mountain peak are set as the upper reservoir selection set;

[0027] For each sub-region, calculate the distance-to-height ratio value of the combination in the region, extract the combination that meets the requirement of distance-to-height ratio less than 10 to create a data object; based on the calculation results, draw a vertical line of the river channel along the direction of the steep mountain; select the standard distance-to-height ratio range combination based on the upper and lower reservoir sites.

[0028] As a further improvement of the present invention, the process of fusing geological data to obtain a plan layout combination scheme includes:

[0029] Integrate the multi-dimensional and multi-factor association logic model into the GIS platform, perform calculations based on the site selection layer data, merge the upper and lower database groups that meet the calculation standards, and output the site selection auxiliary layer;

[0030] Generate a visual diagram of the plane layout design from the data output by the multi-dimensional and multi-factor association logic model; output the geological structure data into a standard unified format and make adjustments; obtain a plane layout combination plan;

[0031] Generate address structure surface data corresponding to the route according to the plane layout combination scheme; call the longitudinal section generation algorithm to generate section design data; analyze the section design data, compare the analysis results, and obtain the performance indicator data set of the evaluation scheme; fit the plane data, fit the section data, and fuse the longitudinal data.

[0032] As a further improvement of the present invention, the process of calculating and merging the upper and lower library groups that meet the standard and outputting the site selection auxiliary layer includes:

[0033] The business logic of the power station and the distance-to-height ratio requirements are used to build a multi-dimensional and multi-factor association logic model; the business logic of the power station and the distance-to-height ratio requirements are divided into a training set, a test set, and a verification set, and the training set is used to train the multi-dimensional and multi-factor association logic model;

[0034] Input various indicators in the pumped storage power station project into the multi-dimensional multi-factor association logic model for response, and obtain the relationship between various indicators; collect and filter the required time of various indicators in the multi-dimensional multi-factor association logic model, and integrate the multi-dimensional multi-factor association logic model into the system for calculation;

[0035] Calculations are performed based on the site selection layer data, and the upper and lower library groups that meet the calculation standards are merged and output as the site selection auxiliary layer.

[0036] As a further improvement of the present invention, the process of integrating the multi-dimensional multi-factor association logic model into the system for calculation includes:

[0037] Standardize the response data output by the model to obtain standardized data, and vectorize the standardized data to obtain vectorized classification data;

[0038] Extract the data from the GIS platform and integrate it with the standard data and vectorized classification data to obtain a standard multi-source data set; reorganize the standard multi-source data set into a high-dimensional tensor based on a multi-dimensional combination structure; each dimension represents a data response, and obtain an initial high-dimensional tensor;

[0039] The initial high-dimensional tensor is decomposed to obtain a reduced-dimensional high-dimensional tensor. The missing elements in the reduced-dimensional high-dimensional tensor are evaluated and filled based on the tensor completion algorithm to obtain the target high-dimensional tensor.

[0040] As a further improvement of the present invention, the process of obtaining the plan layout combination scheme includes:

[0041] Visualize the plane design control points as a piecewise function composed of arc segment and straight line segment feature control points; interactively draw through the GIS platform, pick up all feature control points to complete the object-oriented modeling of the plane layout route;

[0042] Export geological structure data into a unified format, and transform geological structure data into geological structure families through secondary development; transform geological structure families into corresponding coordinates and import them into the project environment for arranging pumped storage power stations;

[0043] Users dynamically adjust parameters to determine the axis of the environmental pumped-storage power station project; combine different plane layout control points to obtain the plane layout combination cold protection; and store the line plane layout plan feature point set to the cloud.

[0044] As a further improvement of the present invention, the process of plane data fitting, cross-section data fitting and longitudinal data fusion includes:

[0045] Call the address data to convert the geological structure data into the corresponding underlying surface, and give the address structure information to form a surface-based three-dimensional geological model; obtain the preliminary plane layout line data and generate the plane layout line primitives; generate the layout route object of the corresponding route based on the plane layout line primitives, and obtain the terrain line data along the plane layout design route according to the layout route formation;

[0046] Cut the three-dimensional geological surface model along the plane layout route to generate geological structure surface data corresponding to the route; derive the longitudinal section form by controlling the number of slope points, elevation of slope change points, and slope between slope change points;

[0047] Analyze the cross-section design data, compare the analysis results, and obtain the performance indicator data set of the evaluation scheme; fit the plane data, fit the cross-section data, and fuse the longitudinal data.

[0048] To achieve the above object, the present invention also provides the following technical solutions:

[0049] A pumped storage power station water delivery system intelligent design system, which is applied to the pumped storage power station water delivery system intelligent design method, the pumped storage power station water delivery system intelligent design system comprises:

[0050] The basic information data module is used to obtain the pumped storage power station project sent by the terminal, digitize the administrative area scope, river network data, sensitive area data, regional geological data, hydrological data and traffic network data of the pumped storage power station project and form a GIS platform layer; integrate the data layer into a data scene and publish it to the cloud;

[0051] The data analysis module is used to calculate the regional slope, the reservoir area formed by the dam, the natural depression and the peak vertex of the mountain as the site selection data layer of the GIS platform layer; obtain the business logic and distance-to-height ratio requirements of the pumped-storage power station project, and build a multi-dimensional and multi-factor association logic model;

[0052] The scheme combination module is used to integrate the multi-dimensional and multi-factor correlation logic model with the GIS platform to obtain the potential location data of the reservoir; analyze the potential location data of the reservoir, generate the plane design control points according to the analysis results, and integrate the geological data to obtain the plane layout combination scheme.

[0053] The data acquisition and digitization of the present invention digitizes various data in the pumped storage power station project (such as the administrative area of ​​site selection, river network data, sensitive area data, regional geological data, hydrological data and traffic network data), and integrates them into GIS platform layers to form data scenes and publish them to the cloud. GIS platform layer analysis and model construction, analyze the GIS platform layer, calculate the regional slope, dam-forming reservoir area, natural depressions and peak vertices, and build a multi-dimensional and multi-factor association logic model in combination with the business logic and distance-to-height ratio requirements of the pumped storage power station. Model fusion and graphic design integrate the multi-dimensional and multi-factor association logic model with the GIS platform to obtain potential reservoir location data, analyze it, generate graphic design control points, and obtain a plane layout combination plan in combination with geological data. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 A schematic diagram of the steps of an embodiment of the intelligent design method for a water delivery system of a pumped storage power station of the present invention;

[0055] Figure 2 A schematic diagram of the steps of an embodiment of the intelligent design method for a water delivery system of a pumped storage power station of the present invention;

[0056] Figure 3A schematic flow chart of the steps of integrating data layers into data scenes and publishing them to the cloud in one embodiment of the intelligent design method for a water delivery system of a pumped storage power station of the present invention;

[0057] Figure 4 A schematic flow chart of the steps of constructing a multi-dimensional and multi-factor association logic model for an embodiment of the intelligent design method for a water delivery system of a pumped storage power station of the present invention;

[0058] Figure 5 A schematic flow chart of steps for obtaining a standard distance-to-height ratio range combination according to an embodiment of an intelligent design method for a water delivery system of a pumped-storage power station of the present invention;

[0059] Figure 6 A schematic flow chart of the steps of fusing geological data to obtain a planar layout combination scheme in one embodiment of an intelligent design method for a water delivery system of a pumped storage power station of the present invention;

[0060] Figure 7 This is a model generation effect diagram of an embodiment of the intelligent design method for the water delivery system of a pumped storage power station of the present invention;

[0061] Figure 8 This is a data fitting effect diagram of an embodiment of the intelligent design method for the water delivery system of a pumped storage power station of the present invention;

[0062] Fig. 9 A schematic diagram of functional modules of an embodiment of an intelligent design system for a water delivery system of a pumped storage power station according to the present invention;

[0063] Fig.10 It is a structural schematic diagram of an embodiment of an electronic device of the present invention;

[0064] Fig.11 It is a schematic structural diagram of an embodiment of the storage medium of the present invention. DETAILED DESCRIPTION

[0065] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0066] The terms "first", "second" and "third" in the present invention are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the number of indicated technical features. Therefore, the features defined as "first", "second" and "third" may explicitly or implicitly include at least one of the features. In the description of the present invention, the meaning of "multiple" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined. All directional indications (such as up, down, left, right, front, back...) in the embodiments of the present invention are only used to explain the relative position relationship, movement, etc. between the components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication also changes accordingly. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally also includes steps or units that are not listed, or optionally also includes other steps or units inherent to these processes, methods, products or devices.

[0067] Reference to an "embodiment" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiment may be included in at least one embodiment of the present invention. The appearance of the phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0068] like Figure 1 As shown, this embodiment provides an embodiment of an intelligent design method for a water delivery system of a pumped storage power station. In this embodiment, the intelligent design method for a water delivery system of a pumped storage power station specifically includes the following steps:

[0069] Step S1: Obtain the pumped storage power station project sent by the terminal, digitize the administrative area scope, river network data, sensitive area data, regional geological data, hydrological data and traffic network data in the pumped storage power station project and form a GIS platform layer; integrate the data layer into a data scene and publish it to the cloud;

[0070] Step S2: Calculate the regional slope, the reservoir area formed by the dam, the natural depression and the peak of the mountain for the GIS platform layer as the site selection data layer; obtain the business logic and distance-to-height ratio requirements of the pumped storage power station in the pumped storage power station project, and construct a multi-dimensional and multi-factor association logic model;

[0071] Step S3: Integrate the multi-dimensional and multi-factor correlation logic model with the GIS platform to obtain the potential reservoir location data; analyze the potential reservoir location data, generate plane design control points based on the analysis results, and integrate the geological data to obtain a plane layout combination plan.

[0072] Preferably, in step S1 of this embodiment, data acquisition and digitization are used to digitize various types of data in the pumped storage power station project (such as the scope of the administrative area for site selection, river network data, sensitive area data, regional geological data, hydrological data and traffic network data), and integrated into a GIS platform layer to form a data scene and publish it to the cloud. Significance: Through digitization and GIS platform integration, centralized management and visualization of data are realized, providing a solid foundation for analysis and decision-making. Step S2 GIS platform layer analysis and model construction, the GIS platform layer is analyzed to calculate the regional slope, the dam-forming reservoir area, the natural depression and the peak vertex, and the multi-dimensional multi-factor association logic model is constructed in combination with the business logic and distance-to-height ratio requirements of the pumped storage power station. Significance: Through the construction of the multi-dimensional multi-factor association logic model, various factors can be comprehensively considered, the scientificity and accuracy of the site selection can be improved, and a basis for the plane design can be provided. Step S3 Model fusion and plane design integrates the multi-dimensional multi-factor association logic model with the GIS platform to obtain the potential reservoir location data, analyze it, generate the plane design control points, and obtain the plane layout combination plan in combination with the geological data. Significance: Through model fusion and analysis, the plane design can be optimized, the rationality and feasibility of the design can be ensured, and the operating efficiency and safety of the pumped storage power station can be improved (for specific principles, please refer to the attached Figure 2 ).

[0073] In summary, this embodiment realizes the intelligent design of the water delivery system of the pumped storage power station through data digitization, GIS platform analysis, model construction and fusion, improves the scientificity, accuracy and efficiency of the design, and has important engineering application value.

[0074] Furthermore, if Figure 3 As shown, the process of integrating the data layers into a data scene and publishing it to the cloud in step S1 specifically includes the following steps:

[0075] Step S11: obtaining the pumped storage power station project sent by the terminal, and classifying the obtained pumped storage power station project according to the geological data into plane area address data, three-dimensional geological body model, two-dimensional geological surface model and structured geological data;

[0076] Step S12: Select a site for the classified data, and digitize the classified data into a GIS platform layer according to the administrative area of ​​the site selection, river network data, sensitive area data, regional geological data, hydrological data and traffic network data;

[0077] Step S13: Publish the GIS platform layer to the cloud, where users can view the GIS platform layer and make decisions and design solutions.

[0078] Preferably, step S11 of this embodiment acquires and classifies the data of the pumped storage power station project. By classifying the geological data of the pumped storage power station project, the complex data can be decomposed into more manageable parts, including plane area address data, three-dimensional geological body model, two-dimensional geological surface model and structured geological data; the classified data is easier to standardize and process, which is convenient for site selection and analysis. The significance achieved: the classified data is easier to manage and process, reducing data redundancy and confusion, and improving the efficiency of data processing; through classification, different types of geological data can be analyzed more accurately, providing higher quality data support for subsequent site selection and decision-making. Step S12 selects the site for the classified data and digitizes it to form a GIS platform layer, and integrates the classified data according to the administrative area scope of the site selection, river network data, sensitive area data, regional geological data, hydrological data and traffic network data to form a unified GIS platform layer; through the GIS platform, the complex geological and environmental data are visualized in the form of layers, which is convenient for users to intuitively understand and analyze. Significance achieved: By integrating multi-source data, the suitability of the site selection can be evaluated more comprehensively, the site selection decision can be optimized, and the environmental impact and engineering risks can be reduced; the visualization of the GIS platform layer allows users to view and analyze data more intuitively, improves the interactivity between users and data, and facilitates decision-making and scheme design. Step S13 publishes the GIS platform layer to the cloud. By publishing the GIS platform layer to the cloud, remote access and sharing of data are realized, and users can view and analyze data without local storage; cloud publishing allows data to be updated in real time and supports multi-user collaboration, which improves the flexibility and efficiency of data management. Significance achieved: Cloud publishing breaks the geographical limitations of data, promotes data sharing and collaboration, and facilitates multi-party participation in decision-making and scheme design; through cloud access, users can view and analyze data anytime and anywhere, which improves the efficiency and flexibility of decision-making and supports faster response and adjustment.

[0079] In summary, this embodiment achieves efficient management and utilization of data through data classification, integration, visualization and cloud publishing, improves the quality and efficiency of decision-making, promotes data sharing and collaboration, and provides strong technical support for the site selection and construction of pumped-storage power station projects.

[0080] Further, if Figure 4 As shown, the process of constructing a multi-dimensional multi-factor association logic model in step S2 specifically includes the following steps:

[0081] Step S21: Calculate the slope of the area, the area that can be formed into a reservoir by damming the GIS platform layer, the natural depression and the peak vertex as the site selection data layer;

[0082] Step S22: obtaining the business logic and distance-to-height ratio requirements of the pumped-storage power station in the pumped-storage power station project, and constructing a multi-dimensional multi-factor association logic model; the multi-dimensional multi-factor association logic model divides the site selection data layer into a small-scale site selection area and a large-scale site selection area;

[0083] Step S23: For a small-scale site selection area, perform reservoir site comparison and selection; for a large-scale site selection area, perform water transmission route selection and divide the site selection area into at least one area; perform calculations based on each area to obtain a standard distance-to-height ratio range combination.

[0084] Preferably, step S21 of this embodiment calculates the slope of the area, the area where the dam can be used as a reservoir, the natural depression and the peak of the mountain as the site selection data layer of the GIS platform layer; through the GIS platform, integrate and analyze geographic information data, such as slope, the area where the dam can be used as a reservoir, the natural depression and the peak of the mountain, to form a site selection data layer; these data help to accurately locate the potential site selection area of ​​the pumped storage power station, and provide a basis for subsequent detailed analysis. Significance: Through GIS technology, qualified areas can be quickly screened out, greatly improving the efficiency of site selection; based on scientific analysis of geographic information, the scientificity and rationality of site selection are ensured, and blindness is reduced. Step S22 obtains the business logic and distance-to-height ratio requirements of the pumped storage power station in the pumped storage power station project, constructs a multi-dimensional and multi-factor association logic model, and combines the business logic and distance-to-height ratio requirements of the pumped storage power station to construct a multi-dimensional and multi-factor association logic model, and divides the site selection data layer into a small-scale site selection area and a large-scale site selection area; the model can comprehensively consider multiple factors, such as topography, hydrology, engineering technology, etc., and conduct a comprehensive analysis. Significance: Through multi-dimensional and multi-factor analysis, the best site selection area can be determined more accurately and resource allocation can be optimized; comprehensive consideration of multiple factors can be taken to improve the feasibility and economic benefits of the project. Step S23: For a small-scale site selection area, a reservoir site comparison is performed; for a large-scale site selection area, a water transmission route is selected, and the site selection area is divided into at least one area; calculations are performed based on each area to obtain a standard distance-to-height ratio range combination; for a small-scale site selection area, a reservoir site comparison is performed to ensure the accuracy of the site selection; for a large-scale site selection area, a water transmission route is selected to optimize the water transmission route and reduce the project cost; calculations are performed based on each area to obtain a standard distance-to-height ratio range combination to ensure the standardization and normalization of the site selection. Significance: Through refined site selection and route optimization, the accuracy and rationality of site selection can be improved; through standardized calculations, the standardization and controllability of the site selection process can be ensured, which is convenient for subsequent management and evaluation.

[0085] In summary, in order to ensure the scientificity, rationality and efficiency of the site selection of the pumped storage power station, this embodiment uses GIS technology, the construction of a multi-dimensional and multi-factor associated logic model, and refined site selection and route optimization to ultimately achieve the optimal site selection and efficient implementation of the project.

[0086] Furthermore, if Figure 5 As shown, the process of obtaining the standard distance-to-height ratio range combination in step S23 specifically includes the following steps:

[0087] Step S231: Build a design scenario and conduct a reservoir site comparison; select a reservoir condition area for multiple key points, take the regional commanding heights as the upper reservoir, and combine the reservoir area and the natural depression as the lower reservoir for multi-dimensional association combination; in the site selection area, traverse and combine the dam area and the dam area, the dam area and the natural depression, and the peak top and the natural depression in pairs to obtain all the site general selection combinations;

[0088] Step S232: according to the characteristics of the pumped storage power station, the site selection area is divided into at least one area according to the administrative area connection and the natural river distribution; within a single site selection area, the dammed reservoir area and the mountain peak are set as the upper reservoir selection set;

[0089] Step S233: For each sub-area, calculate the distance-to-height ratio value of the combinations within the area, extract the combinations that meet the requirement of a distance-to-height ratio less than 10, and create data objects; based on the calculation results, draw a vertical line of the river channel along the direction of the steep mountain; and select a standard distance-to-height ratio range combination based on the upper and lower reservoir sites.

[0090] Preferably, step S231 of this embodiment builds a design scenario and conducts a reservoir site comparison. By building a design scenario, the actual reservoir site comparison environment is simulated to ensure the scientificity and rationality of the site selection; the reservoir condition area is selected, the regional commanding heights are used as the upper reservoir, and the reservoir area and the natural depression are combined as the lower reservoir to perform multi-dimensional association combination; within the site selection area, the dam area and the dam area, the dam area and the natural depression, and the peak top and the natural depression are traversed and combined in pairs to obtain all the site general selection combinations. Significance: Through multi-dimensional association combination and traversal combination, the site combination that meets the conditions is comprehensively screened out to ensure the comprehensiveness and scientificity of the site selection; by simulating the actual environment, the accuracy and rationality of the site selection are improved, and blindness is reduced. Step S232: According to the characteristics of the pumped storage power station, the administrative area connection and the natural river distribution, the site selection area is divided into at least one area. According to the characteristics of the pumped storage power station, the site selection area is divided into at least one area according to the administrative area connection and the natural river distribution; in a single site selection area, the dammed reservoir area and the peak are set as the upper reservoir selection set to ensure the rationality of the upper reservoir selection. Significance: Through regional division, the management and analysis of the site selection area are optimized and the management efficiency is improved; by setting the upper reservoir selection set, the rationality and scientificity of the upper reservoir selection are ensured, and the feasibility of the project is improved. Step S233: For each sub-area, the distance-to-height ratio value of the combination in the area is calculated, and the combination that meets the requirement of the distance-to-height ratio less than 10 is extracted to create a data object. For each sub-area, the distance-to-height ratio value of the combination in the area is calculated to ensure the rationality of the site selection; the combination that meets the requirement of the distance-to-height ratio less than 10 is extracted to create a data object, which is convenient for subsequent analysis and management; according to the calculation results, a vertical line of the river channel is made along the direction of the steep mountain to ensure the scientific nature of the site selection. Significance: By calculating the distance-to-height ratio and creating data objects, the standardization and regularization of site selection can be ensured, and the scientific nature of site selection can be improved; by drawing the vertical line of the river channel, the site selection plan can be optimized, and the feasibility and economic benefits of the project can be improved.

[0091] In summary, this embodiment ensures the scientificity, rationality and efficiency of the site selection of the pumped storage power station. By designing scenario construction, multi-dimensional association combination, regional division, distance-to-height ratio calculation and data object creation, the optimal site selection and efficient implementation of the project are finally achieved. This not only improves the accuracy and rationality of the site selection, but also optimizes the site selection plan, and improves the feasibility and economic benefits of the project.

[0092] Furthermore, if Figure 6 As shown, the process of fusing geological data to obtain a plan layout combination scheme in step S3 specifically includes the following steps:

[0093] Step S31: Integrate the multi-dimensional and multi-factor association logic model into the GIS platform, perform calculations based on the site selection layer data, merge the upper and lower library groups that meet the calculation standards, and output the site selection auxiliary layer;

[0094] Step S32: Generate a visual diagram of the plane layout design from the data output by the multi-dimensional multi-factor association logic model; output the geological structure data into a standard unified format and make adjustments; and obtain a plane layout combination plan;

[0095] Step S33: Generate address structure surface data corresponding to the route according to the plane layout combination scheme; call the longitudinal section generation algorithm to generate section design data; analyze the section design data, compare the analysis results, and obtain the performance indicator data set of the evaluation scheme; fit the plane data, fit the section data, and fuse the longitudinal data.

[0096] Among them, the expression of the longitudinal section generation algorithm is:

[0097]

[0098] In the formula, Represents the generated cross-section design data, which is represented by the parameterized variables t Coordinates of the cross-section points at ; Represents the point coordinates in the plan layout combination scheme, which represents the parameterized variable t The coordinates of the original cross-section point at ; Represents the point coordinates in geological structure data, expressed in parameterized variables t Coordinates of geological structure points at; Weight factor, dimensionless, used to adjust the impact of geological structure data on section design; Smoothing factor, dimensionless, used to adjust the smoothness of the cross-section design; Constraint factors are dimensionless and are used to adjust the constraints of the cross-section design; Fourier transform operator, used to convert time domain data into frequency domain data operator (Fourier transform operator The main purpose of the time domain data (i.e. the original geological structure data) is to and floor plan data The conversion process plays a vital role in the longitudinal section generation algorithm for the following reasons: In the frequency domain, the different frequency components of the data can be separated and analyzed; through Fourier transform, the complex time domain signal can be decomposed into a series of simple sine waves, each sine wave corresponds to a specific frequency, and the decomposition helps to better understand the frequency characteristics of the data, so as to perform more precise operations and optimization in the frequency domain; in the longitudinal section generation algorithm, geological structure data and floor plan data Fusion needs to be performed at some stage. Fusion directly in the time domain may result in distorted or inaccurate data; , can capture the rate of change of geological structure data, thereby adjusting the smoothness of cross-section design. Fourier transform makes it easier to process these high-order derivatives in the frequency domain, thereby obtaining a smoother cross-section design in the time domain. C ( u ) to perform integration , ensuring that the cross-section design meets engineering requirements (such as terrain constraints, engineering specifications, etc.); the Fourier transform and inverse transform processes ensure that this integration operation is seamlessly connected between the frequency domain and the time domain, thereby generating accurate cross-section design data that meets all constraints.

[0099] In summary, The second derivative of the geological structure data, expressed in terms of parameterized variables t The rate of change of geological structures at the location; C ( u ) constraint vector, indicating the parameterization of variables t The constraints of the cross-section design (such as terrain, engineering requirements, etc.); t A parameterized variable representing the dimensionless position of the section point along the route direction; u The integration variable represents the dimensionless path of integration along the route direction; The second-order derivative representing the geological structure data is used to capture the rate of change of geological structure and thus adjust the smoothness of cross-section design; Represents the constraint vector C ( u ) to ensure that the cross-section design meets engineering requirements (such as terrain constraints, engineering specifications, etc.); through Fourier transform and inverse transform, the geological structure data and the plane layout data are integrated in the frequency domain and then converted back to the time domain to generate more accurate cross-section design data; through the second-order derivative , adjust the smoothness of the cross-section design to avoid sudden changes or discontinuities in the cross-section design; , ensure that the cross-section design meets engineering requirements, such as terrain constraints, engineering specifications, etc.

[0100] Preferably, step S31 of this embodiment integrates the business logic of the pumped storage power station and the distance-to-height ratio requirements to construct a logic model that can comprehensively consider multiple factors (for effects, refer to the attached Figure 7); the model can handle complex geological and environmental data to ensure the scientificity and rationality of site selection; the model is integrated into the GIS platform, and the site selection layer data is used for calculation, which can efficiently screen out the upper and lower library combinations that meet the standards and output the site selection auxiliary layer. Significance: Through multi-dimensional data analysis, it is ensured that the site selection not only meets the technical requirements, but also maximizes resource utilization and environmental benefits; the automated calculation and screening process greatly reduces manual intervention and improves the efficiency and accuracy of site selection decisions. Step S32 generates a visual diagram of the plane layout design and adjusts the geological structure data, visualizes the output data of the multi-dimensional and multi-factor correlation logic model, and facilitates designers to intuitively understand and optimize the plane layout; converts the geological structure data into a standard unified format to facilitate subsequent adjustments and analysis, and ensures data compatibility and consistency. Significance: Through visualization tools, designers can more intuitively adjust and optimize the plane layout, improve the rationality and aesthetics of the design; the unified data format ensures the compatibility of different data sources, and provides a solid foundation for subsequent analysis and application. Step S33 generates address structure surface data and performs cross-section design data analysis. According to the plane layout combination scheme, the corresponding address structure surface data is generated to provide a basis for subsequent route design and analysis; the longitudinal section generation algorithm is called to generate cross-section design data to ensure the scientificity and accuracy of the cross-section design; the plane data, cross-section data and longitudinal data are integrated to form a complete design data set for comprehensive analysis and evaluation. Significance: By generating detailed address structure surface data and cross-section design data, comprehensive support is provided for engineering design, ensuring that every link of the design is scientifically analyzed; through comparative selection and analysis, the performance index data set of the evaluation scheme is obtained, which provides a scientific basis for the final scheme selection and ensures the maximization of the performance and benefits of the project.

[0101] In summary, this embodiment not only realizes data processing and optimization in technology through multi-dimensional data fusion and analysis, but also provides important support for engineering design and decision-making in practical applications, thereby ensuring the scientificity, rationality and efficiency of the final plan layout combination scheme.

[0102] Furthermore, the process of calculating and merging the upper and lower library groups that meet the standards and outputting the site selection auxiliary layer in step S31 specifically includes the following steps:

[0103] Step S311: construct a multi-dimensional and multi-factor association logic model based on the business logic of the power station and the distance-to-height ratio requirements; divide the business logic of the power station and the distance-to-height ratio requirements into a training set, a test set, and a validation set, and use the training set to train the multi-dimensional and multi-factor association logic model;

[0104] Step S312: inputting various indicators in the pumped storage power station project into the multi-dimensional multi-factor association logic model for response, and obtaining the relationship between various indicators; collecting and filtering the required time of various indicators in the multi-dimensional multi-factor association logic model, and integrating the multi-dimensional multi-factor association logic model into the system for calculation;

[0105] Step S313: Perform calculations based on the site selection layer data, merge the upper and lower library groups that meet the calculation standards, and output the site selection auxiliary layer.

[0106] Preferably, in step S311 of this embodiment, a multi-dimensional multi-factor association logic model is constructed and trained. By converting the business logic of the power station and the distance-to-height ratio requirements into a multi-dimensional multi-factor association logic model, complex data relationships can be systematically analyzed and processed; the data is divided into a training set, a test set, and a validation set to ensure that the performance of the model on different data sets is stable and improve the generalization ability of the model; the model is trained using the training set so that the model can learn the intrinsic connection between the factors and provide a basis for subsequent prediction and analysis. Significance: By training the model, the impact of different factors on site selection can be more accurately predicted and evaluated, and the scientificity and accuracy of site selection can be improved; based on the analysis results of the model, more data-driven decisions can be made to reduce the interference of human factors. Step S312 inputs the index items and performs calculations, inputs the index items in each direction into the model, obtains the relationship between the index items, and helps understand the interaction between different indicators; collects and filters the required time of each index item to ensure the accuracy and effectiveness of the model in the time dimension; integrates the multi-dimensional multi-factor association logic model into the system to realize automatic calculation and analysis and improve efficiency. Significance: Through system integration, data can be analyzed and processed in real time, changes can be responded to quickly, and the timeliness of decision-making can be improved; by analyzing the relationship between various indicators, all aspects of site selection can be comprehensively evaluated to ensure the rationality and feasibility of site selection. Step S313 calculates and outputs the site selection auxiliary layer based on the site selection layer data, calculates based on the site selection layer data, and screens out the upper and lower library combinations that meet the standards to ensure the scientificity and rationality of the site selection; outputs the calculation results as a site selection auxiliary layer to intuitively display all aspects of site selection, which is convenient for decision makers to understand and use. Significance: Through layer output, all aspects of site selection can be intuitively displayed, which is convenient for decision makers to quickly understand and evaluate; provides a scientific site selection auxiliary layer to help decision makers make more reasonable and effective decisions and improve the success rate of the project.

[0107] In summary, this embodiment ensures the scientificity, accuracy and timeliness of site selection through systematic model construction, data analysis and layer output, and provides solid data support and decision-making basis for the successful implementation of the project.

[0108] Furthermore, in step S312, the process of integrating the multi-dimensional multi-factor association logic model into the system for calculation specifically includes the following steps:

[0109] Step S3121: normalizing the response data output by the model to obtain standardized data, and vectorizing the standardized data to obtain vectorized classification data;

[0110] Step S3122: extracting data from the GIS platform, integrating it with standard data and vectorized classification data, and obtaining a standard multi-source data set; reorganizing the standard multi-source data set into a high-dimensional tensor based on a multi-dimensional combination structure; wherein each dimension represents a data response, and obtaining an initial high-dimensional tensor;

[0111] Step S3123: Decompose the initial high-dimensional tensor to obtain a reduced-dimensional high-dimensional tensor, evaluate and fill in the missing elements in the reduced-dimensional high-dimensional tensor based on a tensor completion algorithm, and obtain a target high-dimensional tensor.

[0112] Among them, the expression of the tensor completion algorithm is:

[0113]

[0114] Constraints:

[0115]

[0116] In the formula, represents the target high-dimensional tensor, and represents the complete tensor after completion; represents the initial high-dimensional tensor, represents the original tensor with missing elements, Represents the projection operator, which means that only the observed elements in the tensor are retained and the rest are set to 0; Represents the observation set, which represents the index set of known elements in the tensor; Represents the tensor decomposition factor matrix, which represents the decomposition factors of different dimensions; represents the nuclear norm regularization parameter, which is used to control the low-rank property of the tensor. , , represents the factor matrix regularization parameter, which is used to control the smoothness of the decomposition factor. represents the nuclear norm, which indicates the low-rank property of the tensor; represents the Frobenius norm, which represents the sum of the squares of the matrix; The tensor multiplication operator represents the i Tensor multiplication over dimensions; d Indicates the number of dimensions of the tensor and the rank of the tensor; The tensor is in i Dimensional size; It represents the rank of tensor decomposition and the dimension of decomposition factors. The tensor completion algorithm combines tensor decomposition, nuclear norm regularization, factor matrix regularization and constraints to effectively process missing elements in high-dimensional tensors and generate high-quality completion results. By adjusting the regularization parameters, the performance and robustness of the algorithm can be flexibly controlled.

[0117] Preferably, step S3121 of this embodiment standardizes the response data output by the model so that it has the same scale, thereby facilitating subsequent analysis and processing. Standardization is usually achieved by methods such as normalization or Z-score standardization, which helps to improve the accuracy of similarity or difference measurement. In addition, the unit also vectorizes the standardized data and converts quantitative data into qualitative data for further analysis and classification. Step S3122 extracts data from the GIS platform and integrates it with the standardized data and vectorized classified data to form a standard multi-source data set. This process involves a multi-dimensional combination structure, which reorganizes these data into a high-dimensional tensor, where each dimension represents a data response, thereby obtaining an initial high-dimensional tensor. This integration method can effectively fuse data from different sources and provide a unified data view for subsequent analysis. Step S3123 is to decompose the initial high-dimensional tensor to obtain a reduced-dimensional high-dimensional tensor. Through the tensor completion algorithm, the missing elements in the reduced-dimensional high-dimensional tensor are evaluated and filled, and the target high-dimensional tensor is finally obtained. Tensor completion technology is particularly important when dealing with missing values ​​in high-dimensional data. It restores the complete tensor by optimizing the model to improve the integrity and accuracy of the data. For example, the low-rank tensor completion method based on tensor chain decomposition can effectively solve the completion problem in high-dimensional data, with high data compression capability and computational efficiency.

[0118] Furthermore, the process of obtaining the plane layout combination scheme in step S32 specifically includes the following steps:

[0119] Step S321: Visualize the plane design control points as a piecewise function composed of arc segment and straight line segment feature control points; through interactive drawing on the GIS platform, pick up all feature control points to complete the object modeling of the plane layout route;

[0120] Among them, the plane design control points include the water supply line import point, import turning control point, diversion layout point, factory entry turning point, etc.; the straight line segment is generated by the starting point and end point control, and the arc segment is generated by the starting point, end point and arc radius control;

[0121] Table 1. Characteristic control points of water transmission line layout

[0122]

[0123] Step S322: output the geological structure data into a unified format, convert the geological structure data into a geological structure family through secondary development; convert the geological structure family into corresponding coordinates, and import them into the project environment for arranging the pumped storage power station;

[0124] Step S323: The user dynamically adjusts parameters to determine the axis of the environmental pumped storage power station project; combines different plane layout control points to obtain a plane layout combination for cold protection; and stores a line plane layout plan feature point set to the cloud.

[0125] Preferably, step S321 of this embodiment visualizes the plane design control points as a piecewise function composed of arc segment and straight line segment feature control points; interactive drawing through the GIS platform allows the user to pick up all feature control points, thereby completing the object-oriented modeling of the plane layout route; specifically, the plane design control points include the water supply line import point, import turning control point, diversion layout point, factory entry turning point, etc. The straight line segment is generated by the starting point and the end point control, while the arc segment is generated by the starting point and the end point and the arc radius control; this embodiment realizes the accurate modeling of complex plane graphics, and through the interactivity of the GIS platform, the user can flexibly adjust and optimize the plane design to improve the accuracy and efficiency of the design. In addition, through object-oriented modeling, the design data can be better managed and stored, which is convenient for subsequent modification and analysis. Step S322 outputs the geological structure data into a unified format, and converts the geological structure data into a geological structure family through secondary development; then, the geological structure family is converted into corresponding coordinates and imported into the project environment of the pumped storage power station; this embodiment realizes the standardization and integrated processing of geological data. By converting geological structure data into a unified format and importing it into the pumped storage power station project environment, geological analysis and design decisions can be effectively supported, and the overall coordination and accuracy of the pumped storage power station project can be improved. In addition, this data processing method is also convenient for sharing and reusing geological data between different pumped storage power station projects, improving work efficiency. Step S323 allows users to dynamically adjust parameters to determine the axis of the environmental pumped storage power station project; it also supports combining different plane layout control points to obtain a plane layout combination cold protection, and stores the line plane layout scheme feature point set to the cloud; this embodiment provides a flexible parameter adjustment function, allowing users to dynamically optimize the design scheme according to actual needs; this embodiment can achieve more complex design requirements by combining different plane layout control points, and store the design data to the cloud for remote access and collaboration; this embodiment enhances the flexibility and scalability of the design, while also improving the security and accessibility of the data.

[0126] Furthermore, the process of plane data fitting, cross-section data fitting and longitudinal data fusion in step S33 specifically includes the following steps:

[0127] Step S331: calling the address data to convert the geological structure data into the corresponding underlying surface, and assigning the address structure information to form a surface-based three-dimensional geological model; obtaining the preliminary plane layout line data, generating the plane layout line primitive; generating the layout route object of the corresponding route based on the plane layout line primitive, and obtaining the terrain line data along the plane layout design route according to the layout route formation;

[0128] Step S332: cutting the three-dimensional geological surface model along the plane layout route to generate geological structural surface data corresponding to the route; deriving the longitudinal section form by controlling the number of slope points, the elevation of the slope change points, and the slope between the slope change points;

[0129] Step S333: Analyze the cross-sectional design data, compare the analysis results, and obtain the performance indicator data set of the evaluation scheme; fit the plane data, fit the cross-sectional data, and fuse the longitudinal data.

[0130] Preferably, in this embodiment, step S331 is used to call address data, convert geological structure data into corresponding underlying curved surface, and assign address structure information to form a three-dimensional geological model based on surface; in this embodiment, classification data is established by collecting geological exploration data, and a three-dimensional geological model expressing each layer is generated by applying the curved surface construction method on the basis of generating a large number of two-dimensional profiles; in this embodiment, data under complex geological conditions can be effectively processed to improve the adaptability and accuracy of the three-dimensional geological model. By converting the profile data sets of two-dimensional lines, two-dimensional surfaces, three-dimensional lines and three-dimensional surfaces into three-dimensional models, users can obtain the analysis results of different profiles in real time, thereby improving the efficiency and accuracy of geological research. Step S 332 is used to section the three-dimensional geological surface model along the plane layout route to generate geological structure surface data corresponding to the route. It controls the derivation of the longitudinal section form by the number of slope points, the elevation of the slope change point, and the slope between the slope change points; it can quickly and accurately extract the required specific geological structure surface data from the three-dimensional geological model, and provide reliable basic data support for subsequent engineering design. In addition, it can also intuitively understand the internal structure of the geological body and the relationship between the layers through flexible sectioning functions. Step S 333 is used to analyze the cross-section design data, compare the analysis results, and obtain the performance index data set of the evaluation scheme. It fits the plane data, cross-section data and longitudinal data; in this embodiment, by fusing and analyzing different types of geological data, the unit can provide a comprehensive performance index data set to help engineers optimize the design scheme. This multi-source data fusion method improves the quality and reliability of the model and provides a scientific basis for subsequent surveys and designs. Plane design control point generation: including water supply line inlet point, inlet turning control point, diversion layout point, factory entry turning point, etc., as shown in Table 1. The plane layout design can be regarded as a piecewise function composed of arc segment and straight line segment feature control points. Among them, the straight line segment is generated by the starting point and the end point control, and the arc segment is generated by the starting point and the end point and the arc radius control. Through interactive drawing on the GIS platform, picking up all feature control points can complete the object modeling of the plane layout route. Each control point is controlled by a clamp point, and can be dynamically adjusted according to specific circumstances in the later stage.

[0131] Furthermore, generating geological structure surface data corresponding to the route in step S332 specifically includes the following steps:

[0132] Step S3321: deriving the control longitudinal section form through the number of slope points, elevation of slope change points, and slope between slope change points; deriving the preliminary scheme of longitudinal section classification and length of each level section; generating longitudinal section data in the form of reducing the length of steel lining section;

[0133] Among them, the methods of reducing the steel lining section include increasing the length of the low-pressure upper flat section and reducing the length of the high-pressure tunnel section of the lower flat section;

[0134] Step S3322: setting a first-level inflection point based on the maximum length of the upper flat section burial depth that meets the standard according to terrain calculation, setting a width change step to derive different flat section layout plans; setting a water diversion and pressure regulating well according to different plant layouts;

[0135] Step S3323: Compare the position of the water diversion and surge tank with the position of the first-level fold point, take the first-level fold point as the starting point, and derive the starting point of the middle flat section according to the slope increment and the height increment respectively; on the basis of the starting point of the middle flat section, derive the end point of the middle flat section according to the width increment; based on the end point of the middle flat section, derive the layout of the lower flat section according to the slope increment and the height increment to form a longitudinal section layout plan.

[0136] Preferably, in this embodiment, step S3321 controls the derivation of the longitudinal section form by the number of slope points, the elevation of the slope change point, and the slope between the slope change points. This method allows the longitudinal section to be graded and a preliminary plan for the length of each level of flat section is formulated. Its main purpose is to reduce the length of the steel lining section, specifically by increasing the length of the low-pressure upper flat section and reducing the length of the high-pressure tunnel section of the lower flat section. This design strategy helps to optimize the engineering structure and reduce the material usage and construction cost. Step S3322 calculates the maximum length of the upper flat section burial depth that reaches the standard according to the terrain, and sets the first-level folding point on this basis. By setting the width change step, different flat section layout schemes are derived. In addition, the subunit also considers the needs of different plant layouts to set up a water diversion and surge tank. This design method can effectively utilize terrain conditions, improve the safety and stability of the project, and simplify the structure to reduce costs. Step S3323 compares the position of the water diversion and surge tank with the position of the first-level folding point, takes the first-level folding point as the starting point, and derives the starting point of the middle flat section according to the slope increment and height increment. Based on the starting point of the middle flat section, the end point of the middle flat section is derived according to the width increment; based on the end point of the middle flat section, the layout of the lower flat section is derived according to the slope increment and height increment to form a longitudinal section layout plan. This modular design method improves the flexibility and adaptability of the design and ensures the feasibility of the project under complex terrain conditions. Geological data fusion design: The geological structure data is output as a standard XML file. Different modeling software can convert the geological structure data into an object-oriented model in the design platform by calling the structure data. Call the geological data interface in Revit software and convert the geological structure data into a geological structure family through secondary development. Call the Revit software API to generate a family file based on the geological structure data, convert it into relative coordinates and import it into the underground plant layout pumped storage power station project environment. Import field experimental data through the user interface. For example, read the minimum geostress direction and the main structural data as auxiliary axis selection data, and express them visually through the user interface. Encapsulate the user interface UI control to couple the read geostress, plant axis, and main structural trend with a rose diagram. Assuming that the relative position of the powerhouse remains unchanged, the hydraulic designer can directly observe the intersection of the powerhouse structure and the geological structure caused by the fine-tuning of the powerhouse axis by adjusting the position and rotation angle of the geological model. By dynamically adjusting the parameters through the user interface, the visualization and parametric interactive design of the powerhouse axis based on the geological model can be realized. Based on the determined powerhouse axis, different plane layout control points are combined to obtain a plane layout combination plan. Design data export: The feature point set of the reviewed line plane layout plan is stored in the platform, and data can be interacted with the design software through the XML interface to form a layout drawing product.Lightweight generation of Civil3D geological profiles based on XML interface: Through secondary development in Civil3D, based on XML data communication, geological data is called to convert geological structure data into corresponding stratigraphic surfaces, and geological structure information is given to form a surface-based three-dimensional geological model. Call the GIS platform data interface, interpret the XML file, obtain the preliminary plane layout line data, and call the Civild graphic interface to generate the plane layout line primitives. Based on the plane layout line primitives, call the API interface to generate the layout route object in Civil3D for the corresponding line. Based on the generated layout route, call the API interface to cut the terrain surface to obtain the terrain line data along the plane layout design route. Cutting the three-dimensional geological surface model along the plane layout route can generate the geological structure surface data corresponding to the route.

[0137] Furthermore, in step S333, the plane data fitting, cross-section data fitting and longitudinal data fusion specifically include the following steps:

[0138] Step S3331: Analyze the values ​​such as the line length, the number of intersections between the line and the geological structure surface, and the intersection angle; compare and select the generated longitudinal section data to preliminarily determine the number of inclined shafts and control point locations of the water delivery system; arrange the geometric data of each level of layout plan and calculate based on the design; use the calculation results as the performance indicator data set for the evaluation plan; and store the data set in the cloud;

[0139] Among them, the calculation results obtained are the length of water transmission lines at all levels, head loss, unit regulation performance Tw time, steel lining section length, support data, width and scale of the fault fracture zone crossed by the scheme, and the intersection angle between the tunnel axis and the fault trend;

[0140] Step S3332: The arc segments in the plane design route are screened into at least eight short arc segments and approximated with straight lines. As the length of the arc increases, the required segmentation data increases; by calculating the node tree of the plane layout line, the multiple broken lines are segmented at the nodes to obtain a set of straight line segments and arc segments; each segment line is equally divided according to the data, and the coordinate values ​​of the equally divided points are recorded; a fitting data dictionary object is constructed, and the x value and y value of the point coordinates are respectively passed into the data dictionary;

[0141] Step S3333: A three-dimensional space coordinate point set is formed by combining the x value, y value of the plane data control point and the z value of the longitudinal section data control point; Revit API is called to perform BIM modeling based on the generated three-dimensional centerline fitting data, and different grouped data are modeled in the corresponding geometric section form.

[0142] Preferably, step S3331 in this embodiment is used to analyze the line length of the water transmission line, the number of intersections between the line and the geological structure surface, and the intersection angle. Through these analyses, the number of inclined shafts and the position of the control points of the water transmission system can be preliminarily determined. In addition, it is also responsible for generating geometric data for each level of the layout plan and performing calculations based on the design. The calculation results are used as a data set for evaluating the performance indicators of the scheme and stored in the cloud. These data include the length of the water transmission line, head loss, unit regulation performance Tw time, steel lining section length, support data, width and scale of the fault fracture zone, intersection angle between the tunnel axis and the fault strike, etc. Step S3332 is used to screen the Hu line segment in the plane design route into at least eight short fox fairy segments and approximate them with straight lines. As the length of the arc increases, the required segmentation data also increases accordingly. By calculating the node trees of the plane layout line, the multi-broken line is segmented at the node to obtain a collection of straight line segments and arc segments. Each segment line is divided equally according to the data, and the coordinate values ​​of the equal division points are recorded. Construct a fitting data dictionary object, and pass the x value and y value of the point coordinates into the data dictionary respectively. Step S3333 forms a three-dimensional space coordinate point set by combining the x value, y value of the plane data control point and the z value of the longitudinal section data control point. Use Revit API to perform BIM modeling based on the generated three-dimensional centerline fitting data, and use the corresponding geometric section form to model different grouped data. Derivative generation of longitudinal section layout of water supply system: The derivation of longitudinal section form is controlled by the number of slope points, the elevation of the slope change point, and the slope between the slope change points. When designing the longitudinal section, the preliminary scheme of longitudinal section classification and the length of each level of flat section is derived first. When generating longitudinal section data in the derivative form, the principle is to minimize the length of the steel lining section and avoid adverse geological conditions. Ways to reduce the steel lining section include increasing the length of the low-pressure upper flat section and reducing the length of the high-pressure tunnel section of the lower flat section. For the upper flat section design, a first-level folding point is set based on the maximum length that meets the upper flat section burial depth calculated according to the terrain, and the width change step is set to derive different upper flat section layout schemes within a certain range. For the tail and middle powerhouse layouts, a water diversion and pressure regulating well needs to be set up. Compare the position of the water diversion and pressure regulating well with the position of the first-level folding point. If the pile number of the water diversion and pressure regulating well position is less than the first-level folding point, the first-level folding point is used as the starting point, and the middle flat section starting point is derived according to the slope increment and height increment respectively; based on the middle flat section starting point, the middle flat section end point is derived according to the width increment; finally, based on the middle flat section end point, the lower flat section layout is derived according to the slope increment and height increment, and finally the longitudinal section layout plan is formed. Add longitudinal section slope change points through the user interface, define the slope change point values, the height of the flat section of each vertical / inclined shaft section, the width of the platform, and the slope of the inclined section. Calculate the corresponding longitudinal section layout, and use the set platform width step and platform height as variables in turn, and derive according to the set step. By inputting the elevation of each control point and the slope of each section of the vertical / inclined shaft, call the longitudinal section generation algorithm of the water supply system to generate the longitudinal section design data.For the derived longitudinal section data, the analysis includes values ​​such as line length, number of intersections between the line and the geological structure surface, and intersection angle. Based on the design line values, the generated longitudinal section data are compared and selected to preliminarily determine the number of inclined shafts and control point locations of the water supply system. The geometric data of the layout schemes at all levels and the calculated data based on the design include: the length of the water supply line at all levels, head loss, unit regulation performance Tw time, steel lining section length, support data, the width and scale of the fault fracture zone crossed by the scheme, and the intersection angle between the tunnel axis and the fault strike. They are all stored in the cloud platform as performance indicator data sets for the evaluation scheme (see the attached for the effect). Figure 8 ).

[0143] Furthermore, the process of forming the three-dimensional space coordinate point set in step S3333 specifically includes the following steps:

[0144] Step S33331: normalize the line length len divided by the control points in the longitudinal section design line and project it into the plane layout data; normalize the line length len2 divided by the control points in the plane layout line and project it into the longitudinal section layout design data;

[0145] Step S33332: The ratio ra of len and the length LEN of the calculated plane layout route is used. By using the geometric solution method, the GetPointsAtParameter method is called to pass in the length ratio ra, and the projection point position of the longitudinal section control point on the plane layout route can be obtained; the longitudinal section design polyline is passed in to obtain the coordinates of the control points at the start and end of the longitudinal section nodes, including: the flat section, arc section, and inclined section;

[0146] Step S33333: record the coordinate values ​​of the projection points, and pass the coordinate values ​​into the fitting data dictionary object Dictionary; sort the x values, y values, and z values ​​in the Dictionary in ascending order according to the size of the x value, and combine them into a three-dimensional space coordinate point set that can be composed of the x value, y value of the plane data control point and the z value of the longitudinal section data control point.

[0147] Preferably, in this embodiment, step S3331 is used to project the line length len divided by the control points in the longitudinal section design line into the plane layout data through normalization processing; the line length len2 divided by the control points in the plane layout line is projected into the longitudinal section layout design data through normalization processing; through normalization processing, the influence of different scales or dimensions can be eliminated, so that the data can be compared and processed on a unified scale; so that the data between the longitudinal section design line and the plane layout line can be better matched and integrated, thereby improving the accuracy and efficiency of data processing. Step S33332 calculates the ratio ra of the length LEN of the plane layout route and the length len of the longitudinal section design line. By using the geometric solution method, calling the GetPointsAtParameter method and passing in the length ratio ra, the projection point position of the longitudinal section control point on the plane layout route can be obtained; passing in the longitudinal section design polyline, and finding the control point coordinates of the longitudinal section nodes including: the start and end of the flat section, arc section, and inclined section; by calculating the length ratio ra, the position of the longitudinal section control point on the plane layout route can be accurately determined; this embodiment can efficiently find the projection point position through geometric solution and calling the GetPointsAtParameter method, thereby improving the accuracy and speed of calculation; and by finding the control point coordinates of the longitudinal section node, the design details of the longitudinal section can be better understood, providing support for subsequent analysis and design. Step S33333 is used to record the coordinate values ​​of the projection point and pass the coordinate values ​​into the fitting data dictionary object Dictionary; the x value, y value, and z value in the Dictionary are expanded and sorted in ascending order according to the size of the x value; and by combining into a three-dimensional space coordinate point set that can be composed of the x value, y value of the plane data control point and the z value of the longitudinal section data control point. This embodiment can conveniently store and access data by recording and managing the coordinate values ​​of the projection points; sorting the coordinate values ​​can ensure the orderliness and consistency of the data, which is convenient for subsequent data processing and analysis; this embodiment can better represent and analyze the geometric relationship in space by combining into a three-dimensional space coordinate point set, providing support for three-dimensional modeling and spatial analysis. Plane data fitting: The plane design route contains polyline segments and arc segments of plane turns. The arc segment is split into more than 8 short arc segments and approximated with straight lines, and the number of required segments increases as the length of the arc increases. By calculating the number of nodes of the plane layout line, the polyline is segmented at the node, and a set of line sets containing straight line segments and arc segments will be obtained after segmentation. Traverse each segmented line and divide the line segment into equal parts according to the given number, and record the coordinate values ​​of the equal-divided points. Construct a fitting data dictionary object Dictionary{List x, List y, List z}, and pass the recorded point coordinate x value and y value into the data dictionary respectively.Longitudinal section data fitting: The horizontal axis of the longitudinal section is the line length l, the vertical axis is the z value at the corresponding stake number, and the functional relationship of the longitudinal section layout is g(x). Therefore. The plane layout data cannot be directly merged with the longitudinal section data. The line length len divided by the control points in the longitudinal section design line is normalized and projected into the plane layout data; the line length len2 divided by the control points in the plane layout line is normalized and projected into the longitudinal section layout design data. The ratio ra of len and the length LEN of the plane layout route is calculated. Using the geometric solution method, call the GetPointsAtParameter method to pass in the length ratio ra, and you can get the projection point position of the longitudinal section control point on the plane layout route. Use the same method to pass in the longitudinal section design polyline, and find the coordinates of the control points at the start and end of the longitudinal section nodes, including the flat section, arc section, and inclined section. Record the coordinate values ​​of the projection points and pass the coordinate values ​​into the fitting data dictionary object Dictionary. The x value, y value, and z value in the Dictionary are sorted in ascending order according to the size of the x value, and a three-dimensional space coordinate point set can be formed by combining the x value, y value of the plane data control point and the z value of the longitudinal section data control point. For example, the data in the Dictionary are grouped to form grouped fitting data points consisting of upper flat section line, upper flat turn + upper inclined section + middle flat turn section, middle flat section, middle flat turn + middle inclined section + lower flat turn section, and lower flat section. RevitAPI is called to perform BIM modeling based on the generated three-dimensional centerline fitting data, and the corresponding geometric section form is used to model different grouped data.

[0148] like Fig. 9 As shown, this embodiment also provides an embodiment of an intelligent design system for a water delivery system of a pumped storage power station. In this embodiment, the intelligent design system for a water delivery system of a pumped storage power station is applied to the intelligent design method for a water delivery system of a pumped storage power station in the above embodiment. The intelligent design system for a water delivery system of a pumped storage power station includes a basic information data module 1, an analysis data module 2, and a scheme combination module 3 which are electrically connected in sequence;

[0149] Among them, the basic information data module 1 is used to obtain the pumped-storage power station project sent by the terminal, digitize the administrative area scope, river network data, sensitive area data, regional geological data, hydrological data and traffic network data in the pumped-storage power station project and form a GIS platform layer; integrate the data layer into a data scene and publish it to the cloud; the analysis data module 2 is used to calculate the regional slope aspect, dam-type reservoir area, natural depression and peak apex of the GIS platform layer as the site selection data layer; obtain the business logic and distance-to-height ratio requirements of the pumped-storage power station in the pumped-storage power station project, and construct a multi-dimensional and multi-factor correlation logic model; the scheme combination module 3 is used to integrate the multi-dimensional and multi-factor correlation logic model into the GIS platform to obtain potential reservoir location data; analyze the potential reservoir location data, generate plane design control points based on the analysis results, and integrate the geological data to obtain a plane layout combination scheme.

[0150] Preferably, the basic information data module 1 of this embodiment is responsible for digitizing the pumped storage power station project information sent by the terminal, including the administrative area scope of the site selection, river network data, sensitive area data, regional geological data, hydrological data and traffic network data, etc.; the data in this embodiment is formed into layers through the GIS platform to realize the visualization and management of spatial data. The digitized data layers are integrated into data scenes and published to the cloud for easy access and use by different users. The digitization and integration of data improve the efficiency of data management and enable data to be quickly accessed and updated; this embodiment enhances the comprehensiveness and accuracy of data analysis by integrating multiple types of data into one platform. The analysis data module 2 uses the GIS platform to calculate the regional slope, the reservoir area of ​​the dam, the natural depression and the peak, and constructs a multi-dimensional and multi-factor association logic model; according to the business logic of the pumped storage power station and the distance-to-height ratio requirements in the pumped storage power station project, the site selection analysis is performed; through calculation and analysis, the analysis data module 2 in this embodiment can provide more accurate site selection suggestions and help decision makers make more reasonable site selection decisions. The application of the multi-dimensional and multi-factor model enhances the analysis ability of complex geographical environments and improves the scientificity and accuracy of site selection. The scheme combination module 3 combines the multi-dimensional and multi-factor association logic model with the GIS platform to generate data on potential reservoir locations; analyzes the data on potential reservoir locations to generate plane design control points; combines geological data with the plane layout plan to form the final plane layout combination plan; by integrating multiple data and models, the scheme combination module in this embodiment can provide a more accurate and smooth design plan; the generation of the plane layout combination plan provides an important reference basis for subsequent engineering design and construction, and supports application needs in multiple fields. The data types integrated by the GIS platform include three types: basic information data, GIS analysis data, and site selection model analysis data. The three types of data are integrated into an online visual GIS scene to support designers in making decisions and designing solutions. For basic information data, the administrative area scope, river network data, sensitive area data, regional geological data, hydrological data and traffic network data of the site selection are digitized and formed into GIS platform layers during the site selection stage. Based on the pumped storage power station project, the required data layers are integrated into data scenes and published to the cloud to provide basic information services. For GIS analysis data, GIS spatial analysis capabilities are supported to calculate regional slope, dam-forming reservoir area, natural depressions and peak vertices as site selection data layers, and site selection analysis services are provided based on the GIS platform. For site selection model analysis data, based on the business logic of the pumped storage power station and the distance-to-height ratio requirements, a logical model of the layout of the multi-dimensional and multi-factor associated pumped storage power station is constructed. The logical model is integrated into the GIS platform, and calculations are performed in the background based on the site selection layer data, and the upper and lower reservoir combinations that meet the requirements are output as site selection auxiliary layers.In the proposed site selection area, the potential storage location data are generated based on GIS spatial analysis to calculate the regional mountain slope, mountain areas with reservoir conditions, natural depressions, and regional commanding heights.

[0151] like Fig.10 As shown, this embodiment provides an embodiment of an electronic device. In this embodiment, the electronic device 4 includes a processor 41 and a memory 42 coupled to the processor 41.

[0152] The memory 42 stores program instructions for implementing the intelligent design method for the water delivery system of a pumped storage power station according to any of the above-mentioned embodiments.

[0153] The processor 41 is used to execute program instructions stored in the memory 42 to perform intelligent design of the water delivery system of the pumped storage power station.

[0154] The processor 41 may also be referred to as a CPU (Central Processing Unit). The processor 41 may be an integrated circuit chip having the ability to process signals. The processor 41 may also be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0155] Further, Fig.11 The schematic diagram of the structure of the storage medium of an embodiment of the present application is that the storage medium 5 of the embodiment of the present application stores program instructions 5 that can implement all the above methods, wherein the program instructions 5 can be stored in the above storage medium in the form of a software product, including several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) or a processor to execute all or part of the steps of the methods described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, or terminal devices such as a computer, a server, a mobile phone, and a tablet.

[0156] In the several embodiments provided by the present invention, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0157] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above integrated unit may be implemented in the form of hardware or in the form of software functional units. The above is only an implementation mode of the present invention, and does not limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made by using the contents of the present invention specification and drawings, or directly or indirectly used in other related technical fields, is also included in the patent protection scope of the present invention.

[0158] The specific implementation methods of the invention are described in detail above, but they are only examples, and the invention is not limited to the specific implementation methods described above. For those skilled in the art, any equivalent modification or substitution of the invention is also within the scope of the invention, therefore, the equalization, modification, improvement, etc. made without departing from the spirit and principle of the invention should be included in the scope of the invention.

Claims

1. An intelligent design method for a water delivery system of a pumped storage power station, characterized in that: The intelligent design method for the water delivery system of a pumped storage power station comprises: The terminal sends the pumped storage power station project, digitizes the administrative area scope, river network data, sensitive area data, regional geological data, hydrological data and traffic network data of the pumped storage power station project and forms a GIS platform layer; integrates the data layer into a data scene and publishes it to the cloud; The GIS platform layer is used to calculate the regional slope, the area that can be formed into a reservoir by damming, the natural depression and the peak vertex as the site selection data layer; the business logic and distance-to-height ratio requirements of the pumped-storage power station in the pumped-storage power station project are obtained, and a multi-dimensional and multi-factor association logic model is constructed; The multi-dimensional and multi-factor correlation logic model is integrated into the GIS platform to obtain the potential reservoir location data; the potential reservoir location data is analyzed, and the plane design control points are generated according to the analysis results, and the geological data is integrated to obtain the plane layout combination plan; The process of fusing geological data to obtain a plan layout combination plan includes: Integrate the multi-dimensional and multi-factor association logic model into the GIS platform, perform calculations based on the site selection layer data, merge the upper and lower database groups that meet the calculation standards, and output the site selection auxiliary layer; Generate a visual diagram of the plane layout design from the data output by the multi-dimensional and multi-factor association logic model; output the geological structure data into a standard unified format and make adjustments; obtain a plane layout combination plan; Generate address structure surface data corresponding to the route according to the plane layout combination scheme; call the longitudinal section generation algorithm to generate section design data; analyze the section design data, compare the analysis results, and obtain the performance index data set of the evaluation scheme; fit the plane data, fit the section data, and fuse the longitudinal data; The process of obtaining a plan layout combination scheme includes: Visualize the plane design control points as a piecewise function composed of arc segment and straight line segment feature control points; interactively draw through the GIS platform, pick up all feature control points to complete the object-oriented modeling of the plane layout route; Export geological structure data into a unified format, and transform geological structure data into geological structure families through secondary development; transform geological structure families into corresponding coordinates and import them into the project environment for arranging pumped storage power stations; Users dynamically adjust parameters to determine the axis of the environmental pumped storage power station project; combine different plane layout control points to obtain a plane layout combination plan; and store the line plane layout plan feature point set to the cloud.

2. The intelligent design method for the water delivery system of a pumped storage power station according to claim 1 is characterized in that: The process of integrating data layers into a data scene and publishing it to the cloud includes: Acquire the pumped storage power station project sent by the terminal, and classify the acquired pumped storage power station project according to the geological data into plane area address data, three-dimensional geological body model, two-dimensional geological surface model and structured geological data; Select a site for the classified data, and digitize the classified data into a GIS platform layer based on the administrative area of ​​the site, river network data, sensitive area data, regional geological data, hydrological data, and transportation network data; Publish the GIS platform layer to the cloud, and users can view the GIS platform layer through the cloud to make decisions and design solutions.

3. The intelligent design method for water delivery system of pumped storage power station according to claim 1, characterized in that: The process of building a multi-dimensional and multi-factor association logic model includes: The GIS platform layer is used to calculate the regional slope, the area that can be formed into a reservoir by damming, the natural depression and the peak vertex as the site selection data layer; Obtain the business logic and distance-to-height ratio requirements of the pumped-storage power station project, and build a multi-dimensional and multi-factor association logic model; the multi-dimensional and multi-factor association logic model divides the site selection data layer into a small-scale site selection area and a large-scale site selection area; For small-scale site selection areas, reservoir site comparison is carried out; for large-scale site selection areas, water transmission routes are selected and the site selection area is divided into at least one area; calculations are performed based on each area to obtain a standard distance-to-height ratio range combination.

4. The intelligent design method for the water delivery system of a pumped storage power station according to claim 3 is characterized in that: The process of deriving the standard distance-to-height ratio range combination includes: Build a design scenario and conduct a comparison of reservoir sites; select reservoir condition areas as the key, take the regional commanding heights as the upper reservoir, and combine the reservoir area and the natural depression as the lower reservoir for multi-dimensional association combination; in the site selection area, traverse and combine the dam area and the dam area, the dam area and the natural depression, and the mountain top and the natural depression in pairs to obtain all the site selection combinations; According to the characteristics of pumped storage power stations, the site selection area is divided into at least one region according to the administrative area connection and natural river distribution; within a single site selection area, the dammed reservoir area and the mountain peak are set as the upper reservoir selection set; For each sub-region, calculate the distance-to-height ratio value of the combination in the region, extract the combination that meets the requirement of distance-to-height ratio less than 10 to create a data object; based on the calculation results, draw a vertical line of the river channel along the direction of the steep mountain; select the standard distance-to-height ratio range combination based on the upper and lower reservoir sites.

5. The intelligent design method for water delivery system of pumped storage power station according to claim 1, characterized in that: The process of calculating the upper and lower storage groups that meet the standards and outputting the site selection auxiliary layer includes: The business logic of the power station and the distance-to-height ratio requirements are used to build a multi-dimensional and multi-factor association logic model; the business logic of the power station and the distance-to-height ratio requirements are divided into a training set, a test set, and a verification set, and the training set is used to train the multi-dimensional and multi-factor association logic model; Input various indicators in the pumped storage power station project into the multi-dimensional multi-factor association logic model for response, and obtain the relationship between various indicators; collect and filter the required time of various indicators in the multi-dimensional multi-factor association logic model, and integrate the multi-dimensional multi-factor association logic model into the system for calculation; Calculations are performed based on the site selection layer data, and the upper and lower library groups that meet the calculation standards are merged and output as the site selection auxiliary layer.

6. The intelligent design method for the water delivery system of a pumped storage power station according to claim 5 is characterized in that: The process of integrating the multi-dimensional and multi-factor correlation logic model into the system for calculation includes: Standardize the response data output by the model to obtain standardized data, and vectorize the standardized data to obtain vectorized classification data; Extract the data from the GIS platform and integrate it with the standard data and vectorized classification data to obtain a standard multi-source data set; reorganize the standard multi-source data set into a high-dimensional tensor based on a multi-dimensional combination structure; each dimension represents a data response, and obtain an initial high-dimensional tensor; The initial high-dimensional tensor is decomposed to obtain a reduced-dimensional high-dimensional tensor. The missing elements in the reduced-dimensional high-dimensional tensor are evaluated and filled based on the tensor completion algorithm to obtain the target high-dimensional tensor.

7. The intelligent design method for water delivery system of pumped storage power station according to claim 1, characterized in that: The process of fitting plane data, section data and longitudinal data includes: Call the address data to convert the geological structure data into the corresponding underlying surface, and give the address structure information to form a surface-based three-dimensional geological model; obtain the preliminary plane layout line data and generate the plane layout line primitives; generate the layout route object of the corresponding route based on the plane layout line primitives, and obtain the terrain line data along the plane layout design route according to the layout route formation; Cut the three-dimensional geological surface model along the plane layout route to generate geological structure surface data corresponding to the route; derive the longitudinal section form by controlling the number of slope points, elevation of slope change points, and slope between slope change points; Analyze the cross-section design data, compare the analysis results, and obtain the performance indicator data set of the evaluation scheme; fit the plane data, fit the cross-section data, and fuse the longitudinal data.

8. An intelligent design system for a water delivery system of a pumped storage power station, which is applied to the intelligent design method for a water delivery system of a pumped storage power station as claimed in any one of claims 1 to 7, characterized in that: The intelligent design system for the water delivery system of the pumped storage power station comprises: The basic information data module is used to obtain the pumped storage power station project sent by the terminal, digitize the administrative area scope, river network data, sensitive area data, regional geological data, hydrological data and traffic network data of the pumped storage power station project and form a GIS platform layer; integrate the data layer into a data scene and publish it to the cloud; The data analysis module is used to calculate the regional slope, the reservoir area formed by the dam, the natural depression and the peak vertex of the mountain as the site selection data layer of the GIS platform layer; obtain the business logic and distance-to-height ratio requirements of the pumped-storage power station project, and build a multi-dimensional and multi-factor association logic model; The scheme combination module is used to integrate the multi-dimensional and multi-factor correlation logic model with the GIS platform to obtain the potential location data of the reservoir; analyze the potential location data of the reservoir, generate the plane design control points according to the analysis results, and integrate the geological data to obtain the plane layout combination scheme.

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