Three-dimensional design method and system for underground powerhouse of pumped storage power station

Abstract

The invention discloses a three-dimensional design method and system for an underground powerhouse of a pumped storage power station, and belongs to the technical field of underground energy engineering design and construction. The method comprises the four stages of GIS quantitative site selection and plant parametric modeling, dynamic three-dimensional geologic structure modeling, three-dimensional geologic attribute body modeling and plant adjustment, and GIM / CAE integrated analysis and scheme optimization. The problems of extensive site selection, fragmentation of geological modeling, disjunction of analysis and design and the like in the prior art are solved. The system comprises a hardware layer and a software layer, the hardware layer provides data acquisition, calculation storage and visual interaction support, and the software layer realizes seamless connection of all links through modular design. According to the method and the system, digitization, integration and intelligentization of the whole process of underground powerhouse design are realized, the safety, the economy and the efficiency of the design are improved, and the method and the system can be applied to underground powerhouse projects under complex geological conditions.

Description

Technical Field

[0001] This invention relates to the field of underground energy engineering design and construction technology, specifically to a three-dimensional design method and system for underground powerhouses of pumped storage power stations. Background Technology

[0002] The design of underground powerhouses for pumped storage power stations requires comprehensive consideration of multiple factors such as topography, regional geology, and surrounding rock stability. Existing technologies often adopt a step-by-step application scheme of "GIS + 3D geological modeling + CAE analysis". The workflow is as follows: use GIS to complete the preliminary site selection of the underground powerhouse and output the 2D site selection area; construct a static 3D geological model based on the initial exploration data; manually organize the geological model parameters into CAE input format and conduct surrounding rock stability analysis; if the analysis results do not meet the requirements, return to the site selection or design stage for manual adjustment and repeat the above steps.

[0003] However, existing GIS site selection technologies lack quantification and dynamism, and can only perform qualitative zoning based on a single threshold. They cannot quantitatively analyze the coupling relationship between "topography-geology-factory demand", and the site selection results cannot be adjusted with subsequent survey data updates. Existing GIS tools do not have a dedicated quantitative assessment module for underground factories, have not established a correlation algorithm between "site selection parameters-geological risks-engineering costs", and are not interconnected with data in the subsequent geological modeling stage. In addition, 3D geological modeling is too fragmented and static, only able to integrate the geometric information of strata and faults, unable to visualize the distribution pattern of groundwater in a synchronous manner, and the model is built based on initial exploration data and cannot be dynamically updated as supplemented by tunnel / borehole test data, resulting in a larger deviation between the model and the actual geological conditions. Existing modeling technology lacks an automatic fusion interface for "multi-source exploration data" and has not designed a real-time update algorithm for attribute data. The disconnect between geological attribute modeling and design results in key attribute data such as surrounding rock quality and geostress field being presented only in the form of tables or reports, which cannot be correlated with the three-dimensional model of the underground powerhouse. When judging the matching between attribute distribution and powerhouse location, the adjustment efficiency is low and errors are easy to occur. Existing technology has not established a spatial mapping relationship between "attribute data and three-dimensional model" and lacks the linkage function between attribute visualization and design adjustment. The low level of integration between GIM and CAE, coupled with the lack of an optimization loop, necessitates the conversion of geological parameters from GIM into a CAE-compatible format. This results in low data transmission efficiency, a high risk of errors, and the need to interpret and feed back analysis results to the design end. The inability to automatically trigger scheme adjustments leads to a long optimization cycle. Summary of the Invention

[0004] The purpose of this invention is to provide a three-dimensional design method and system for underground powerhouses of pumped storage power stations, so as to solve the problems in the prior art.

[0005] To solve the above-mentioned technical problems, the present invention specifically provides the following technical solution: A three-dimensional design method for the underground powerhouse of a pumped storage power station includes the following steps: GIS-based quantitative site selection and parametric modeling of factory buildings, dynamic 3D geological structure modeling, 3D geological attribute volume modeling and factory building adjustment, and integrated GIM / CAE analysis and solution optimization: S1. GIS-based quantitative site selection and parametric modeling of factory buildings include: Import 3D topographic data and regional geological data, including fault distribution maps and stratigraphic lithology maps, and ensure that the coordinate system is consistent with the topographic data; Three types of core quantitative evaluation indicators and their weights are set. The indicators include topographic indicators, geological risk indicators, and engineering convenience indicators. The topographic indicators include the layout of the tunnel entrance, the slope of the tunnel line, and the excavation volume. The topographic indicators reflect the constraints on the layout of the underground powerhouse tunnel entrance and the accessibility of construction. The geological risk indicators include minimum distance from faults and formation stability; The project convenience indicators include the distance to the construction access road and the distance to the water source; The scores of each candidate area are calculated using a comprehensive scoring formula, and areas with a score ≥ 0.8 are selected as preliminary plant sites. The comprehensive scoring formula is: Comprehensive score = (Topographic index score × 0.3) + (Geological risk index score × 0.5) + (Engineering convenience index score × 0.2). The topographic index score is calculated as (1 - actual excavation volume / maximum allowable excavation volume) × (1 - actual average slope / 20°). If the actual average slope is greater than 20°, the score for this item is 0. The geological risk index score = (actual fault distance / 300m) × actual stratum stability coefficient; The project convenience index score = (1 - min(actual access road distance / 1000m, 1)) × (1 - actual water source distance / 500m); Input the plant design parameters, generate a 3D geometric model of the underground plant using parametric methods, and overlay it with the GIS terrain model for display. S2. Dynamic 3D geological structure modeling includes: Based on geological mapping data, an improved Kriging interpolation algorithm was used to generate an initial three-dimensional geological model of the underground powerhouse area, including the main stratigraphic lithology and three-dimensional grid surface of geological structure. Import and merge multi-source exploration data into the geological data center, including borehole data, horizontal tunnel exploration data, and groundwater seepage test data; automatically correct stratigraphic boundaries; generate three-dimensional fracture surfaces through trace-surface mapping algorithm; and mark high-permeability groundwater areas. A multi-feature visualization method is adopted, using different colors / textures to distinguish lithology, transparent surfaces to display groundwater levels, and dashed boxes to mark fault-affected areas; S3, 3D geological attribute modeling and plant adjustment include: Import borehole test data and tunnel rock mass quality test data into the geological data center; Discrete data is converted into a continuous three-dimensional attribute field using a radial basis function interpolation algorithm. The interpolation formula is: U(P)=Σ[λi×φ(||P-Pi||)]+a0+a1x+a2y+a3z, where P(x,y,z) is an arbitrary point in the model space, Pi(x_i,y_i,z_i) is a measured data point, φ(r)=exp(-(εr)^2) is the Gaussian radial basis function (ε is a shape parameter, with a value of 0.1-0.5), and λi, a0, a1, a2, a3 are interpolation coefficients; Construct a three-dimensional geological attribute volume model that integrates geometry and attributes, and visualize the attribute distribution through color gradient; The system automatically analyzes the spatial overlap between the current location of the underground powerhouse and the distribution of three-dimensional geological attributes. Based on the preset surrounding rock quality threshold and the ground stress threshold, it calculates the area ratio of high-risk attribute areas within the powerhouse area. When the area ratio exceeds the corresponding preset ratio threshold, it triggers a powerhouse adjustment prompt. The system adjusts the plan position or axial direction of the underground powerhouse until the area ratio of the high-risk attribute areas meets the design requirements. S4, GIM / CAE integrated analysis and solution optimization include: Read the parameters from the 3D geological property volume model and the geometric parameters of the underground powerhouse, and automatically generate a calculation input file compatible with CAE software; CAE software is used to perform finite element calculations, analyze the distribution of stress, displacement and plastic zone in the surrounding rock, and set evaluation criteria. If the calculation results do not meet the standards, the system will automatically analyze the reasons for the deviation and generate fine-tuning suggestions. After the engineer confirms the suggestions, the 3D model of the factory will be updated, and the data conversion and analysis steps will be repeated until the results meet the requirements. Finally, the optimized solution will be output.

[0006] A preferred solution provided by a three-dimensional design system for underground powerhouses of pumped storage power stations includes a hardware layer and a software layer, which are linked through a data interface: The hardware layer includes data acquisition devices, computing and storage devices, and visualization and interaction devices. The data acquisition devices include borehole core samplers, borehole rock mass quality detectors, geostress measuring instruments, and total stations. The computing and storage devices include high-performance servers and distributed databases. The visualization and interaction devices include graphics workstations and touch screens. The software layer adopts a modular design, including a GIS quantitative site selection and parametric modeling module, a dynamic 3D geological structure modeling module, a 3D geological attribute volume modeling module, and a GIM / CAE integrated analysis and optimization module. The GIS quantitative site selection and parametric modeling module is used to realize topographic-geological coupling analysis and automatic generation of 3D factory models, and includes a quantitative evaluation model and parametric modeling algorithm. The dynamic 3D geological structure modeling module is used to integrate multi-source exploration data and update strata, fault, and groundwater models, and includes an automatic multi-source data fusion interface and a trace-surface mapping algorithm. The 3D geological attribute volume modeling module is used to associate measured data with models, visualize surrounding rock quality and geostress field, and includes a radial basis function interpolation algorithm and an automatic high-risk area overlap analysis algorithm. The GIM / CAE integrated analysis and optimization module is used to realize automatic interaction between geological data and analysis software and closed-loop optimization of schemes, and includes an automatic data conversion interface and automated closed-loop logic.

[0007] Based on a three-dimensional design method for underground powerhouses of pumped storage power stations, step S1, inputting powerhouse design parameters, and parametrically generating a three-dimensional geometric model of the underground powerhouse refers to the automated generation of the underground powerhouse BIM model by inputting parameters controlling the size and shape of the underground powerhouse through development tools in BIM software.

[0008] Based on a three-dimensional design method for underground powerhouses of pumped storage power stations, step S4, which automatically analyzes the overlap between the current location of the powerhouse and the attribute distribution, refers to mapping the attributes in the three-dimensional geological attribute volume model onto the underground powerhouse BIM model and displaying the magnitude of the geological attribute values ​​of various parts of the underground powerhouse. Based on a three-dimensional design method for underground powerhouses of pumped storage power stations, the CAE software mentioned in step S4 includes FLAC3D and ANSYS.

[0009] Based on the preferred scheme provided by a three-dimensional design system for underground powerhouses of pumped storage power stations, in the hardware layer, the data acquisition device and the storage device are connected through a wired or wireless network, the storage device and the computing device are connected through an optical fiber, and the computing device and the visualization or interactive device are connected through an HDMI or DP interface.

[0010] Based on the preferred solution provided by a three-dimensional design system for underground powerhouses of pumped storage power stations, the software layer modules are integrated into the same B / S architecture Web system, and the modules realize data transmission and closed-loop linkage through API interfaces or feedback interfaces.

[0011] Compared with the prior art, the present invention has the following advantages: 1. The present invention has higher site selection accuracy and faster efficiency. It achieves accurate site selection through a quantitative evaluation model of "topography-geology-engineering requirements" and automatically generates a three-dimensional model of the factory building, shortening the site selection and modeling cycle; 2. The geological model of this invention is dynamic and integrated, and can integrate multi-source exploration data in real time, and simultaneously visualize the distribution of strata, faults, groundwater and properties, reduce model deviation, and eliminate the need for manual remodeling. 3. This invention is more closely linked to geological attributes, constructing an integrated "geometry + attribute" model that automatically analyzes the overlap of high-risk areas and triggers adjustment prompts, thereby improving the risk area avoidance rate. 4. This invention analyzes and optimizes closed-loop automation based on GIM / CAE integrated technology, realizing automatic data conversion and automatic result feedback, shortening the iteration cycle and reducing errors caused by manual intervention. Attached Figure Description

[0012] To more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are merely exemplary, and those skilled in the art can derive other embodiments based on the provided drawings without creative effort.

[0013] Figure 1 This is a schematic diagram of the overall process of the present invention; Figure 2 For technology roadmap; Figure 3 A schematic diagram of the automatic generation program for underground powerhouses; Figure 4 A schematic diagram of assigning attributes from a 3D geological attribute volume model to an underground powerhouse BIM model. Detailed Implementation

[0014] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0015] The concepts involved in this application will first be described with reference to the accompanying drawings. It should be noted that the following descriptions of various concepts are only for the purpose of making the content of this application easier to understand and do not constitute a limitation on the scope of protection of this application; furthermore, the embodiments and features in the embodiments of this application can be combined with each other unless otherwise specified. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0016] Example like Figures 1 to 4As shown, this invention provides a three-dimensional design method for the underground powerhouse of a pumped storage power station, comprising the following steps: GIS-based quantitative site selection and parametric modeling of factory buildings, dynamic 3D geological structure modeling, 3D geological attribute volume modeling and factory building adjustment, and integrated GIM / CAE analysis and solution optimization: S1. GIS-based quantitative site selection and parametric modeling of factory buildings include: Import 3D topographic data and regional geological data (DEM, resolution ≥5m). The regional geological data includes fault distribution maps and stratigraphic lithology maps, and the coordinate system is consistent with the topographic data. Three types of core quantitative evaluation indicators and their weights are set. The indicators include topographic indicators (weight 30%), geological risk indicators (weight 50%), and engineering convenience indicators (weight 20%). The topographic indicators include the layout of the tunnel entrance, the slope of the tunnel line, and the excavation volume. The topographic indicators reflect the constraints on the layout of the underground powerhouse entrance and the accessibility of construction. Geological risk indicators include minimum distance to fault (target ≥ 300m, risk coefficient = 1 / (distance × 0.01)) and stratum stability; The project convenience indicators include the distance to the construction access road (target ≤ 1km) and the distance to the water source (target ≥ 500m). The scores of each candidate area were calculated using a comprehensive scoring formula. Areas with a score ≥ 0.8 were selected as preliminary plant sites. The comprehensive scoring formula is: Comprehensive score = (Topographic index score × 0.3) + (Geological risk index score × 0.5) + (Engineering convenience index score × 0.2). Topographic index score = (1 - actual excavation volume / maximum allowable excavation volume) × (1 - actual average slope / 20°). If the actual average slope > 20°, the score for this item is 0. Geological risk index score = (actual fault distance / 300m) × actual stratum stability coefficient, and the geological risk index score ≤ 1; Project convenience index score = (1 - min(actual access road distance / 1000m, 1)) × (1 - actual water source distance / 500m); Input the plant design parameters (length L, width W, height H, burial depth D), parametrically generate a 3D geometric model of the underground plant (format: .dwg / .step), and overlay it with the GIS terrain model for display; S2. Dynamic 3D geological structure modeling includes: Based on geological mapping data, an improved Kriging interpolation algorithm (considering the influence of faults on stratigraphic continuity) was used to generate an initial three-dimensional geological model of the underground powerhouse area, including the main stratigraphic lithology and three-dimensional grid surfaces of geological structure surfaces. Import and merge multi-source exploration data into the geological data center, including borehole data (coordinates X / Y / Z, lithological stratification depth, groundwater level), horizontal tunnel exploration data (horizontal tunnel axis coordinates, tunnel wall fracture traces), and groundwater seepage test data (permeability coefficient). Automatically correct stratigraphic boundaries, generate three-dimensional fracture surfaces through trace-surface mapping algorithm, and mark high groundwater permeability areas. A multi-feature visualization method is adopted, using different colors / textures to distinguish lithology, transparent surfaces to display groundwater levels, and dashed boxes to mark fault-affected areas; S3, 3D geological attribute modeling and plant adjustment include: Import borehole test data (RMR rock mass quality score, rock mass elastic modulus) and tunnel rock mass quality test data (joint spacing, integrity coefficient) into the geological data center. Discrete data is converted into a continuous three-dimensional attribute field using the radial basis function interpolation algorithm. The interpolation formula is: U(P)=Σ[λi×φ(||P-Pi||)]+a0+a1x+a2y+a3z, where P(x,y,z) is an arbitrary point in the model space, Pi(x_i,y_i,z_i) is the measured data point, φ(r)=exp(-(εr)^2) is the Gaussian radial basis function (ε is the shape parameter, with a value of 0.1-0.5), and λi, a0, a1, a2, a3 are the interpolation coefficients; Construct a three-dimensional geological attribute volume model that integrates geometry and attributes, and visualize the attribute distribution through color gradient (RMR value ≥80 is green, 60-80 is yellow, and <60 is red). The system automatically analyzes the spatial overlap between the current location of the underground powerhouse and the distribution of three-dimensional geological attributes. Based on the preset surrounding rock quality threshold and the ground stress threshold, it calculates the area ratio of high-risk attribute areas within the powerhouse area. When the area ratio exceeds the corresponding preset ratio threshold, it triggers a powerhouse adjustment prompt. The system adjusts the plan position or axial direction of the underground powerhouse until the area ratio of the high-risk attribute areas meets the design requirements. S4, GIM / CAE integrated analysis and solution optimization include: Read the parameters (rock mass elastic modulus, Poisson's ratio, geostress value) and underground powerhouse geometric parameters from the three-dimensional geological property model, and automatically generate a CAE software compatible calculation input file (.dat format). CAE software was used to perform finite element calculations to analyze the surrounding rock stress (maximum principal stress, minimum principal stress), displacement (maximum displacement value, displacement trend), and plastic zone distribution, and to set evaluation criteria (maximum displacement ≤ 10 mm, plastic zone volume ratio ≤ 3%). If the calculation results do not meet the standards, the system will automatically analyze the reasons for the deviation and generate fine-tuning suggestions. After the engineer confirms the suggestions, the 3D model of the factory will be updated, and the data conversion and analysis steps will be repeated until the results meet the requirements. Finally, the optimized solution will be output.

[0017] As an advanced solution for the 3D design system of underground powerhouses in pumped storage power stations, it includes a hardware layer and a software layer, which are linked through a data interface. The hardware layer includes data acquisition equipment, computing and storage equipment, and visualization and interaction equipment. Data acquisition equipment includes borehole core samplers (ultrasonic logging tools), borehole rock mass quality testing instruments, geostress measuring instruments (hydraulic fracturing instruments), and total stations; computing and storage equipment includes high-performance servers and distributed databases; visualization and interaction equipment includes graphics workstations and touch screens. The software layer adopts a modular design, including a GIS quantitative site selection and parametric modeling module, a dynamic 3D geological structure modeling module, a 3D geological attribute volume modeling module, and a GIM / CAE integrated analysis and optimization module. The GIS quantitative site selection and parametric modeling module is used to realize topographic-geological coupling analysis and automatic generation of 3D plant models, and includes a quantitative evaluation model and parametric modeling algorithm. The dynamic 3D geological structure modeling module is used to integrate multi-source exploration data and update stratigraphic, fault, and groundwater models, and includes an automatic multi-source data fusion interface and a trace-surface mapping algorithm. The 3D geological attribute volume modeling module is used to associate measured data with models, visualize surrounding rock quality and geostress field, and includes a radial basis function interpolation algorithm and an automatic high-risk area overlap analysis algorithm. The GIM / CAE integrated analysis and optimization module is used to realize automatic interaction between geological data and analysis software and closed-loop optimization of schemes, and includes an automatic data conversion interface and automated closed-loop logic.

[0018] As a three-dimensional design method for underground powerhouses of pumped storage power stations, step S1, which involves inputting powerhouse design parameters and parametrically generating a three-dimensional geometric model of the underground powerhouse, refers to automatically generating a BIM model of the underground powerhouse by inputting parameters that control the size and shape of the underground powerhouse through development tools in BIM software.

[0019] As a 3D design method for underground powerhouses of pumped storage power stations, step S4, which involves automatically analyzing the overlap between the current location of the powerhouse and its attribute distribution, refers to mapping the attributes in the 3D geological attribute volume model onto the underground powerhouse BIM model and displaying the magnitude of the geological attribute values ​​for each part of the underground powerhouse. As a three-dimensional design method for underground powerhouses of pumped storage power stations, the CAE software in step S4 includes FLAC3D and ANSYS.

[0020] As an advanced solution for a 3D design system for underground powerhouses of pumped storage power stations, the data acquisition and storage devices in the hardware layer are connected via wired or wireless networks, the storage devices are connected to the computing devices via optical fibers, and the computing devices are connected to the visualization or interactive devices via HDMI or DP interfaces.

[0021] As an advanced solution for the 3D design system of underground powerhouses of pumped storage power stations, the software modules are integrated into the same B / S architecture web system, and the modules realize data transmission and closed-loop linkage through API interfaces or feedback interfaces.

[0022] As a further explanation of this embodiment of the invention, the specific implementation process of the invention is as follows: 1. Data preparation: Collect 3D topographic DEM data (5m resolution), fault distribution map, and stratigraphic lithology map of the target area to ensure coordinate system consistency; obtain borehole data, rock mass quality data, geostress data, and tunnel coordinate data through equipment such as borehole core samplers, ultrasonic logging tools, hydraulic fracturing instruments, and total stations.

[0023] 2. GIS Quantitative Site Selection and Parametric Modeling: Import topographic and geological data into the GIS quantitative site selection and parametric modeling module, set topographic indicators (target average slope ≤ 20°), geological risk indicators (target fault distance ≥ 300m, granite stability coefficient 0.9), and engineering convenience indicators (target construction access road distance ≤ 1km). Calculate three candidate areas using a comprehensive scoring formula, and select the area with a score of 0.85 as the preliminary plant site. Input the plant design parameters (length 120m, width 25m, height 40m, burial depth 300m), and automatically generate a .dwg format 3D plant model, which is then overlaid on the topographic model.

[0024] 3. Dynamic 3D Geological Structure Modeling: Based on the initial borehole data, an improved Kriging interpolation algorithm is used to generate a 3D surface of the strata; supplementary borehole data (including groundwater level information), horizontal tunnel fault trace data, and groundwater permeability coefficient data are imported, and the module automatically corrects the strata boundaries. A 3D fault surface is generated through a trace-surface mapping algorithm, and high-permeability areas are marked; red is used to display granite, blue to display shale, and a transparent surface to display the groundwater level. Dashed boxes mark the fault-affected areas.

[0025] 4. Three-dimensional geological attribute modeling and plant adjustment: Import borehole RMR score data (range 75-90) and joint spacing data of adit, and generate a three-dimensional RMR value distribution field and geostress distribution field through radial basis function interpolation algorithm (ε=0.3) to construct an integrated attribute model; analysis found that 12% of the initial plant location had RMR < 60, triggering an adjustment prompt. After the plant was laterally offset by 8m, the proportion of high-risk areas was reduced to 8%, meeting the design requirements.

[0026] 5. GIM / CAE Integrated Analysis and Scheme Optimization: The module automatically reads parameters such as rock mass elastic modulus and geostress value from the adjusted model and generates a FLAC3D compatible .dat format input file; calls FLAC3D to perform finite element calculations, obtaining a maximum displacement of 8mm and a plastic zone volume ratio of 2.5%, which meets the evaluation criteria; outputs the final optimized scheme (factory location coordinates, axis direction, geometric dimensions).

[0027] The embodiments and / or implementation methods described above are merely preferred embodiments and / or implementation methods for implementing the technology of the present invention, and are not intended to limit the implementation methods of the technology of the present invention in any way. Any person skilled in the art can make some modifications or alterations to other equivalent embodiments without departing from the scope of the technical means disclosed in the content of the present invention, but they should still be regarded as the technology or embodiments that are substantially the same as the present invention.

[0028] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. The above descriptions are only preferred embodiments of this application. It should be noted that due to the limitations of written expression, while there are objectively infinite specific structures, those skilled in the art can make several improvements, modifications, or changes without departing from the principles of this application, and can also combine the above technical features in an appropriate manner. These improvements, modifications, changes, or combinations, or the direct application of the inventive concept and technical solution to other situations without modification, should all be considered within the scope of protection of this application.

Claims

1. A three-dimensional design method for the underground powerhouse of a pumped storage power station, characterized in that, Includes the following steps: S1. GIS-based quantitative site selection and parametric modeling of factory buildings; S2, Dynamic 3D Geological Structure Modeling; S3, 3D geological attribute volume modeling; S4. Plant adjustment and BIM / CAE integrated analysis and solution optimization.

2. The three-dimensional design method for the underground powerhouse of a pumped storage power station according to claim 1, characterized in that, The GIS-based quantitative site selection and parametric modeling of factory buildings also include: Import 3D topographic data and regional geological data, including fault distribution maps and stratigraphic lithology maps, and ensure that the coordinate system is consistent with the topographic data; Three types of core quantitative evaluation indicators and their weights are set. The indicators include topographic indicators, geological risk indicators, and engineering convenience indicators. The topographic indicators include the layout of the tunnel entrance, the slope of the tunnel line, and the excavation volume. The topographic indicators reflect the constraints on the layout of the underground powerhouse tunnel entrance and the accessibility of construction. The geological risk indicators include minimum distance from faults and formation stability; The project convenience indicators include the distance to the construction access road and the distance to the water source; The scores of each candidate area are calculated using a comprehensive scoring formula, and areas with a score ≥ 0.8 are selected as preliminary plant sites. The comprehensive scoring formula is: Comprehensive score = Topographic index score × 0.3 + Geological risk index score × 0.5 + Engineering convenience index score × 0.

2. The topographic index score is calculated as (1-a / b)×(1-c / 20), where a is the actual excavation volume, b is the maximum allowable excavation volume, and c is the actual average slope. If the actual average slope is greater than 20, the score for this item is 0. The geological risk index score = actual fault distance / 300 × actual stratum stability coefficient, and the geological risk index score ≤ 1; The project convenience index score is calculated as follows: (1-min(d / 1000,1))×(1-f / 500), where d is the actual access road distance and f is the actual water source distance. Input the plant design parameters, generate a parametric 3D geometric model of the underground plant, and overlay it with the GIS terrain model for display.

3. The three-dimensional design method for the underground powerhouse of a pumped storage power station according to claim 1, characterized in that, The dynamic three-dimensional geological structure modeling also includes: Based on geological mapping data, an improved Kriging interpolation algorithm was used to generate an initial three-dimensional geological model of the underground powerhouse area, including the main strata lithology and three-dimensional grid surface of geological structure. Import and merge multi-source exploration data into the geological data center, including borehole data, horizontal tunnel exploration data and groundwater seepage test data, automatically correct stratigraphic boundaries, generate three-dimensional fracture surfaces and mark high groundwater permeability areas through trace-surface mapping algorithm; A multi-feature visualization method is adopted, using different colors / textures to distinguish lithology, transparent surfaces to display groundwater levels, and dashed boxes to mark fault-affected areas.

4. The three-dimensional design method for the underground powerhouse of a pumped storage power station according to claim 1, characterized in that, The three-dimensional geological attribute modeling and plant adjustment also include: Import borehole test data and tunnel rock mass quality test data into the geological data center; Discrete data is converted into a continuous three-dimensional attribute field using a radial basis function interpolation algorithm. The interpolation formula is: U(P)=Σ[λi×φ(||P-Pi||)]+a0+a1x+a2y+a3z, where P(x,y,z) is an arbitrary point in the model space, Pi(x_i,y_i,z_i) is a measured data point, φ(r)=exp(-(εr)^2) is the Gaussian radial basis function (ε is a shape parameter, with a value of 0.1-0.5), and λi, a0, a1, a2, a3 are interpolation coefficients; Construct a three-dimensional geological attribute volume model that integrates geometry and attributes, and visualize the attribute distribution through color gradient; The system automatically analyzes the spatial overlap between the current location of the underground powerhouse and the distribution of three-dimensional geological attributes. Based on preset surrounding rock quality thresholds and geostress thresholds, it calculates the area ratio of high-risk attribute areas within the powerhouse area. When the area ratio exceeds the corresponding preset ratio threshold, it triggers a powerhouse adjustment prompt. The system then adjusts the planar position or axial direction of the underground powerhouse until the area ratio of the high-risk attribute areas meets the design requirements.

5. The three-dimensional design method for the underground powerhouse of a pumped storage power station according to claim 1, characterized in that, The integrated BIM / CAE analysis and solution optimization also includes: Read the parameters from the 3D geological property volume model and the geometric parameters of the underground powerhouse, and automatically generate a calculation input file compatible with CAE software; CAE software is used to perform finite element calculations, analyze the distribution of stress, displacement and plastic zone in the surrounding rock, and set evaluation criteria. If the calculation results do not meet the standards, the system will automatically analyze the reasons for the deviation and generate fine-tuning suggestions. After the engineer confirms the suggestions, the 3D model of the factory will be updated, and the data conversion and analysis steps will be repeated until the results meet the requirements. Finally, the optimized solution will be output.

6. The three-dimensional design method for the underground powerhouse of a pumped storage power station according to claim 1, characterized in that, Step S1 involves inputting the plant design parameters and parametrically generating a 3D geometric model of the underground plant. This means that the BIM model of the underground plant can be automatically generated by inputting parameters that control the size and shape of the underground plant through the development tools in the BIM software.

7. The three-dimensional design method for the underground powerhouse of a pumped storage power station according to claim 1, characterized in that, In step S4, the automatic analysis of the overlap between the current location of the plant and the attribute distribution refers to mapping the attributes in the three-dimensional geological attribute volume model to the underground plant BIM model and displaying the magnitude of the geological attribute values ​​of each part of the underground plant.

8. A system for implementing the three-dimensional design method for the underground powerhouse of a pumped storage power station as described in claim 1, characterized in that, It includes a hardware layer and a software layer, which are linked together through a data interface: The hardware layer includes data acquisition devices, computing and storage devices, and visualization and interaction devices. The data acquisition devices include borehole core samplers, borehole rock mass quality detectors, geostress measuring instruments, and total stations. The computing and storage devices include high-performance servers and distributed databases. The visualization and interaction devices include graphics workstations and touch screens. The software layer adopts a modular design, including a GIS quantitative site selection and parametric modeling module, a dynamic three-dimensional geological structure modeling module, a three-dimensional geological attribute volume modeling module, and a GIM / CAE integrated analysis and optimization module. The GIS quantitative site selection and parametric modeling module is used to realize terrain-geology coupling analysis and automatic generation of three-dimensional models of the plant, and includes a quantitative evaluation model and a parametric modeling algorithm. The dynamic 3D geological structure modeling module is used to integrate multi-source exploration data and update stratigraphic, fault, and groundwater models. It includes an automatic multi-source data fusion interface and a trace-surface mapping algorithm. The 3D geological attribute volume modeling module is used to associate measured data with the model, visualize surrounding rock quality and geostress field, and includes a radial basis function interpolation algorithm and an automatic overlap analysis algorithm for high-risk areas. The GIM / CAE integrated analysis and optimization module is used to realize automatic interaction between geological data and analysis software and closed-loop optimization of schemes. It includes an automatic data conversion interface and automated closed-loop logic.

9. A three-dimensional design system for underground powerhouse of a pumped storage power station according to claim 8, characterized in that, In the hardware layer, the data acquisition device and the storage device are connected via wired or wireless network, the storage device and the computing device are connected via optical fiber, and the computing device and the visualization or interactive device are connected via HDMI or DP interface.

10. A three-dimensional design system for underground powerhouse of a pumped storage power station according to claim 8, characterized in that, The software layer modules are integrated into the same B / S architecture web system, and each module realizes data transmission and closed-loop linkage through API interfaces or feedback interfaces.

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