A gis-based mountain compressed air energy storage power station site selection method and system

Abstract

The present application relates to the technical field of electric power energy storage, and discloses a GIS-based mountain compressed air energy storage power station site selection method and system, comprising: obtaining first-level data, second-level data and third-level data in a target mountain area; obtaining a candidate area based on the first-level data; obtaining a geologically available area based on the second-level data; screening out qualified mountains based on the second-level data, constructing the contour and main ridge line of the qualified mountains; determining a mountain reference area, calculating the area of the reference area; solving the optimal internal rectangle of the mountain reference area, determining whether the mountain reference area meets the optimal internal rectangle requirement, and determining a target available mountain; and determining the score of the target available mountain by comprehensively considering the second-level and third-level data, and taking the area with a high score as the final site selection.

Description

Technical Field

[0001] This invention relates to the field of power energy storage technology, and in particular to a GIS-based method and system for site selection of mountain compressed air energy storage power stations. Background Technology

[0002] According to statistics from CNESA DataLink's global energy storage database, by the end of 2024, the cumulative installed capacity of operational power storage projects in China reached 137.9 GW, accounting for 37.1% of the global market, representing a year-on-year increase of 59.9%. The cumulative installed capacity of new energy storage reached 78.3 GW, accounting for 57%, surpassing pumped hydro storage for the first time. New energy storage is increasingly becoming the mainstream technology for addressing the large-scale grid integration and consumption of new energy sources and improving the power system's security and supply capabilities. Compressed air energy storage is one such new energy storage method. Its construction can effectively alleviate the "randomness," "intermittency," and "fluctuation" problems of new energy sources, and it has advantages such as short construction cycles, large construction scale, safety and reliability, and greater environmental friendliness. It is a promising long-term, large-scale energy storage form among new energy storage methods. However, to achieve a reasonable layout and orderly construction of compressed air energy storage power stations, site selection and planning are the "most critical link" and the "first step," serving as an important prerequisite and fundamental guarantee for the overall construction work.

[0003] Currently, the planning and site selection for compressed air energy storage (CAES) primarily relies on traditional manual map-based methods. This approach is inefficient and struggles to systematically assess site conditions, often leading to the overlooking of potentially high-quality sites. Furthermore, the site selection results lack effective systematic integration and spatial visualization, hindering informed decision-making. With the rapid development of the energy storage industry, CAES site selection demands higher quality and efficiency. Traditional methods, lacking accuracy, timeliness, and visualization, are ill-suited to current requirements. This is particularly true for complex mountainous terrain, where traditional methods struggle to provide high-quality and efficient solutions. Therefore, a new CAES power plant site selection method is urgently needed to address the shortcomings of current methods and rapidly promote the scientific and orderly development of CAES. Summary of the Invention

[0004] This invention provides a GIS-based method and system for site selection of mountain compressed air energy storage power stations, in order to solve the problems of insufficient accuracy, low timeliness, and poor visualization in existing site selection methods.

[0005] To achieve the above objectives, the present invention employs the following technical solution: In a first aspect, the present invention provides a GIS-based method for site selection of mountain compressed air energy storage power stations, comprising: Acquire primary, secondary, and tertiary data for the target mountainous region; Based on the primary data, the target mountainous area is subjected to erasure analysis, and the target mountainous area containing the primary data is erased is used as a candidate area. Based on the secondary data, the candidate areas are filtered to select areas whose geological conditions meet the engineering requirements, thus obtaining geologically usable areas. Contour lines are constructed in the geologically available area. Mountains in the geologically available area are identified based on the contour lines. Mountains that meet the height requirements are selected, and the outlines and main ridge lines of the mountains that meet the requirements are constructed. Based on the relevant parameters of the compressed air energy storage power station, the reference area of ​​the mountain is determined in the mountain outline, and the area of ​​the reference area is calculated. The optimal internal rectangle of the mountain's baseline region is determined using a geometric algorithm. The determination of whether the mountain's baseline region meets the requirements for the optimal internal rectangle is then used to identify the target usable mountain. Based on the secondary and tertiary data, the scores of the target available mountains are determined, and the areas with high scores are selected as the final sites.

[0006] Optionally, the primary data includes: data on the three zones and three lines, data on mineral resources covered by the land, and data on military facilities; The secondary data includes: geological data and topographic data; The three levels of data include: river system data, road traffic data, power grid corridor data, substation data, wind farm and photovoltaic power station data, existing energy storage power station data, and residential area data.

[0007] Optionally, the step of filtering the candidate areas based on the secondary data to select areas whose geological conditions meet the engineering requirements and thus obtain geologically usable areas includes: Based on the geological data in the secondary data, the candidate areas are screened, and areas with igneous rocks, a distance greater than a certain range from active faults, and relatively low seismic intensity are selected as geologically usable areas.

[0008] Optionally, the step of constructing contour lines in the geologically available area and identifying mountains in the geologically available area based on the contour lines includes: Contour lines are generated in the geologically available area using a digital elevation model, and the highest closed contour line is found among the generated contour lines. Internal representative points are generated in the highest closed contour lines, and all closed contour lines containing internal representative points are identified as mountains in the geologically available area.

[0009] Optionally, the step of selecting mountains that meet the height requirements and constructing the outline and main ridgeline of the mountains that meet the requirements includes: Determine the required mountain height, and based on this requirement, select suitable mountains from the geologically available area. In mountains that meet the requirements, the lowest contour line is used as the mountain outline; Flow direction analysis is performed on suitable mountain slopes to calculate the flow direction. Based on the flow direction, cumulative flow analysis is conducted to generate a cumulative flow grid and identify flow convergence areas. The river network is determined based on the flow convergence areas to obtain the watershed boundary line, and the ridgeline is determined based on the watershed boundary line.

[0010] Optionally, the relevant parameters of the compressed air energy storage power station are used to determine the mountain reference area in the mountain contour, and the area of ​​the reference area is calculated, including: Based on the relevant parameters of the compressed air energy storage power station, the mountain contour is analyzed horizontally, vertically, and overlay to determine the mountain reference area. The lateral analysis includes: based on the burial depth requirements in the relevant parameters of the compressed air energy storage power station, performing an inward shrinkage analysis on the mountain outline to obtain the area that meets the lateral burial depth requirements; The longitudinal analysis includes: based on the burial depth requirements in the relevant parameters of the compressed air energy storage power station, finding contour lines that meet the burial depth requirements upwards from the contour lines where the mountain outline is located, and obtaining the area that meets the longitudinal burial depth requirements; Overlay analysis includes: performing overlay analysis on areas that meet the burial depth requirements laterally and areas that meet the burial depth requirements longitudinally to obtain the mountain reference area; The area of ​​the reference area is calculated based on the aforementioned mountain reference area, wherein the area is calculated using the following formula: ; In the formula, Indicates the area of ​​the reference region. The number of vertices of the polygon. For the first The x-coordinates of the vertices, For the first The y-coordinates of the vertices, For the first The x-coordinates of the vertices, For the first The ordinates of each vertex.

[0011] Optionally, the step of solving for the optimal internal rectangle of the mountain reference area using a geometric algorithm, determining whether the mountain reference area meets the requirements of the optimal internal rectangle, and identifying the target usable mountain includes: Determine the total volume of the cavern in the relevant parameters of the compressed air energy storage power station. Length of the cavern Base multiple of cavern length Spacing between caverns , diameter of the cavern Require; Calculate the optimal inner rectangle length , =Cavity length Determine whether the length of the mountain body perpendicular to the main ridge line is greater than or equal to the length of the optimal internal rectangle. ×The length of the cavern is a multiple of the baseline. If the conditions are met, then the mountain meets the requirement for the optimal internal rectangular length. Calculate the number of caverns , , And based on the number of caverns Calculate the optimal inner rectangle width , = +( ) ; Determine if the width of the mountain body parallel to the main ridge line is greater than or equal to the optimal internal rectangle width. If the conditions are met, then the mountain body meets the requirement for the optimal internal rectangle width; If the length of the mountain perpendicular to the main ridge line and the width parallel to the main ridge line both meet the requirements of the optimal internal rectangle, then the mountain is a target usable mountain.

[0012] Optionally, the step of determining the score of the target usable mountain based on the secondary and tertiary data, and using the area with the highest score as the final site selection, includes: The scores of usable mountains for a target are determined by analyzing geological data, topographic data, river system data, and road traffic data. The location score is calculated according to the following formula: ； , = 0.5, = 0.3, = 0.1, = 0.1; ； In the formula, For geological scores, The baseline area of ​​the mountain is scored. The score is based on the distance from the river system. Scoring is based on distance from road traffic. For lithology score, The score is based on the distance from the active fracture. To score the earthquake intensity, , which are the corresponding weights; The area with the highest location score will be selected as the final location.

[0013] Secondly, embodiments of this application provide a GIS-based mountain compressed air energy storage power station site selection system, characterized in that it includes a processor and a memory; Memory, used to store computer programs; When a processor executes a program stored in memory, it implements any of the steps of the method described in the first aspect.

[0014] Beneficial effects: This invention provides a GIS-based site selection method for compressed air energy storage power stations in mountainous areas. It introduces GIS spatial analysis methods into the field of compressed air energy storage site selection, significantly improving site selection accuracy and effectively shortening the selection cycle. Furthermore, by employing a weighted assignment method for in-depth analysis of compressed air energy storage sites, the optimal mountain locations can be scientifically and efficiently selected, providing a precise decision-making basis for site selection. Attached Figure Description

[0015] Figure 1 This is a flowchart of a preferred embodiment of the present invention: a GIS-based site selection method for a mountain compressed air energy storage power station. Figure 2 This is a schematic diagram of the mountain identification process according to a preferred embodiment of the present invention; Figure 3 This is a schematic diagram of the ridgeline generation process according to a preferred embodiment of the present invention; Figure 4 This is a schematic diagram of the reference region generation process according to a preferred embodiment of the present invention; Figure 5 This is a flowchart of a GIS-based site selection method for a mountain compressed air energy storage power station, which is a preferred embodiment of the present invention. Detailed Implementation

[0016] The technical solution of the present invention will be clearly and completely described below. 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.

[0017] Unless otherwise defined, the technical or scientific terms used in this invention shall have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "first," "second," and similar terms used in this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Similarly, the terms "an" or "a," and similar terms do not indicate a quantity limitation, but rather indicate the presence of at least one. The terms "connected" or "linked," and similar terms, are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. "Up," "down," "left," "right," etc., are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship also changes accordingly.

[0018] Example 1 Please see Figure 1 This application provides a GIS-based site selection method for mountain compressed air energy storage power stations, including: Acquire primary, secondary, and tertiary data for the target mountainous region; Based on the primary data, the target mountainous area is subjected to erasure analysis, and the target mountainous area containing the primary data is erased is used as a candidate area. Based on the secondary data, the candidate areas are filtered to select areas whose geological conditions meet the engineering requirements, thus obtaining geologically usable areas. Contour lines are constructed in the geologically available area. Mountains in the geologically available area are identified based on the contour lines. Mountains that meet the height requirements are selected, and the outlines and main ridge lines of the mountains that meet the requirements are constructed. Based on the relevant parameters of the compressed air energy storage power station, the reference area of ​​the mountain is determined in the mountain outline, and the area of ​​the reference area is calculated. The optimal internal rectangle of the mountain's baseline region is determined using a geometric algorithm. The determination of whether the mountain's baseline region meets the requirements for the optimal internal rectangle is then used to identify the target usable mountain. Based on the secondary and tertiary data, the scores of the target available mountains are determined, and the areas with high scores are selected as the final sites.

[0019] Optional, primary data includes: data on the three zones and three lines, data on mineral resources covered by the land, and data on military facilities; Secondary data includes: geological data and topographic data; Level 3 data includes: river system data, road traffic data, power grid corridor data, substation data, wind farm and photovoltaic power station data, existing energy storage power station data, and residential area data.

[0020] In the above embodiments, a multi-source spatial database is constructed and hierarchically classified. Various data types are collected and acquired, forming primary, secondary, and tertiary data. Primary data consists of decisive data, including data on the three zones and three lines (referring to waterways, railway lines, and highways), mineral resources, and military facilities. Secondary data consists of restrictive data, including geological and topographical data. Tertiary data consists of impact data, including river system data, road traffic data, power grid corridor data, substation data, wind farm and photovoltaic power station data, existing energy storage power station data, and residential data.

[0021] The data on the three zones and three lines, mineral resources, and military facilities in the first-level data, the geological data and topographic data in the second-level data, and the river system data, road traffic data, grid corridor data, substation data, wind farm and photovoltaic power station data, existing energy storage power station data, and residential data in the third-level data are only examples here and are not limited. Under other conditions or needs, the data types included in the first-level, second-level, and third-level data can be added according to the actual situation.

[0022] Optionally, based on secondary data, the candidate areas are filtered to select areas whose geological conditions meet the engineering requirements, thus obtaining geologically usable areas, including: Based on the geological and topographic data in the secondary data, candidate areas are screened. Areas with igneous rocks, a distance greater than a certain range from active faults, and relatively low seismic intensity are selected as geologically usable areas.

[0023] Optionally, contour lines are constructed within the geologically available area, and mountains within the geologically available area are identified based on these contour lines, including: Contour lines are generated in geologically available areas using digital elevation models, and the highest closed contour line is found among the generated contour lines. Internal representative points are generated in the highest closed contour lines, and all closed contour lines containing internal representative points are identified as mountains in the geologically usable area.

[0024] In the above embodiments, such as Figure 2 As shown, within the geologically usable area, contour lines are generated using a digital elevation model (with an accuracy better than 30m), and the mountains are identified through these contour lines.

[0025] Optionally, select mountains that meet the height requirements, and construct the outline and main ridgeline of the mountains that meet the requirements, including: Determine the required mountain height, and based on the required mountain height, select suitable mountains from the geologically available area; In mountains that meet the requirements, the lowest contour line is used as the mountain outline; Calculate the water flow direction in the qualified mountains, generate a flow accumulation grid based on the water flow direction, identify the water flow convergence area through the flow accumulation grid, determine the river network based on the water flow convergence area to obtain the watershed boundary line, and determine the ridge line based on the watershed boundary line.

[0026] In the above embodiments, such as Figure 3 As shown, by inputting the required mountain height, mountains within the region that meet the height requirement are selected. For the mountains that meet the height requirement, the mountain outline and main ridgeline are drawn. The mountain outline is the lowest contour line in mountain identification. The main ridgeline needs to be generated by combining database data and using the GIS hydrological analysis module, sequentially executing flow direction analysis, flow accumulation, and the watershed tool.

[0027] Optionally, based on relevant parameters of the compressed air energy storage power station, a reference region of the mountain is determined in the mountain profile, and the area of ​​the reference region is calculated, including: Based on the relevant parameters of the compressed air energy storage power station, the mountain contour is analyzed horizontally, vertically, and overlay to determine the benchmark area of ​​the mountain. The lateral analysis includes: based on the burial depth requirements in the relevant parameters of the compressed air energy storage power station, performing an inward shrinkage analysis on the mountain outline to obtain the area that meets the lateral burial depth requirements; The longitudinal analysis includes: based on the burial depth requirements in the relevant parameters of the compressed air energy storage power station, finding contour lines that meet the burial depth requirements upwards from the contour lines where the mountain outline is located, and obtaining the area that meets the longitudinal burial depth requirements; Overlay analysis includes: performing overlay analysis on areas that meet the burial depth requirements laterally and areas that meet the burial depth requirements longitudinally to obtain the mountain reference area; The area of ​​the benchmark region is calculated based on the mountain benchmark region, where the area calculation satisfies the following relationship: ; In the formula, Indicates the area of ​​the reference region. The number of vertices of the polygon. For the first The x-coordinates of the vertices, For the first The y-coordinates of the vertices, For the first The x-coordinates of the vertices, For the first The ordinates of each vertex.

[0028] In the above embodiments, such as Figure 4As shown, by inputting relevant limiting parameters (such as total cave volume, cave length, cave length benchmark multiple, cave spacing, cave diameter, and cave burial depth), and based on the cave burial depth requirements, the mountain contour is analyzed laterally, longitudinally, and superimposed to obtain the benchmark area. The area of ​​the benchmark area is then calculated using the shoelace formula.

[0029] Optionally, the optimal internal rectangle of the mountain's reference area is solved using a geometric algorithm to determine whether the mountain's reference area meets the requirements for the optimal internal rectangle, thus identifying the target usable mountain, including: The optimal internal rectangle of the mountain reference region is determined using a geometric algorithm based on the area and shape of the mountain reference region. Determine the total volume of the cavern in the relevant parameters of the compressed air energy storage power station. Length of the cavern Base multiple of cavern length Spacing between caverns , diameter of the cavern Require; Calculate the optimal inner rectangle length , =Cavity length Determine whether the length of the mountain body perpendicular to the main ridge line is greater than or equal to the length of the optimal internal rectangle. ×The length of the cavern is a multiple of the baseline. If the conditions are met, then the mountain meets the requirement for the optimal internal rectangular length. Calculate the number of caverns , , And based on the number of caverns Calculate the optimal inner rectangle width , = +( ) ; Determine if the width of the mountain body parallel to the main ridge line is greater than or equal to the optimal internal rectangle width. If the conditions are met, then the mountain body meets the requirement for the optimal internal rectangle width; If the length of the mountain perpendicular to the main ridge line and the width parallel to the main ridge line both meet the requirements of the optimal internal rectangle, then the mountain is a target usable mountain.

[0030] Optionally, based on secondary and tertiary data, the scores of available target hills are determined, and areas with high scores are selected as the final site selection, including: The scores of usable mountains for a target are determined by analyzing geological data, topographic data, river system data, and road traffic data. The location score is calculated according to the following formula: ; , = 0.5, = 0.3, = 0.1, = 0.1; ; In the formula, For geological scores, The baseline area of ​​the mountain is scored. The score is based on the distance from the river system. Scoring is based on distance from road traffic. For lithology score, The score is based on the distance from the active fracture. To score the earthquake intensity, , which are the corresponding weights; The area with the highest location score will be selected as the final site.

[0031] Example 2 like Figure 5 The diagram shows a schematic flow chart of the method of the present invention. The calculation results of this embodiment 1 are shown in Tables 1 and 2.

[0032] Step 1: In the site selection planning of compressed air energy storage in a certain area, retrieve data from the database on the three zones and three lines, mineral resources covered by the area, military facilities, geological data, topographic data, river system data, transportation data, grid corridor data, substation data, wind farm and photovoltaic power station data, existing energy storage power station data, and residential area data.

[0033] Step 2: Through erasure analysis, exclude areas involving data related to the three zones and three lines, mineral resources, and military facilities.

[0034] Step 3: In the areas selected in Step 2, use open-source geological data to select areas with granite lithology, a distance greater than 1 km from active faults, and seismic intensity of 6 or 7 degrees.

[0035] Step 4: Using terrain data (accuracy better than 30m), generate contour lines at 10m intervals, and identify mountains using these contour lines. Input a mountain height of 200m, identify mountains within the area, and filter out mountains with a height greater than 200m.

[0036] Step 5: For mountains with a height greater than 200m, draw the mountain outline and main ridgeline.

[0037] Step 6: Input the relevant limiting parameters, namely the total volume of the cavern: 300,000 m³ 3The cavern length is 600m, the baseline multiple of the cavern length is 2, the cavern spacing is 100m, the cavern diameter is 10m, and the cavern depth is 150m. Based on the 150m cavern depth requirement, the mountain contour is analyzed laterally, longitudinally, and through superposition, to determine the baseline area and calculate its area.

[0038] Step 7: Based on the total volume of the caverns, the length of the caverns, the reference multiple of the cavern length, the distance between caverns, and the required diameter of the caverns, solve for the ideal optimal internal rectangle using a geometric algorithm, and determine whether the optimal internal rectangle of the mountain meets the requirements (① determine whether the length perpendicular to the main ridge line is greater than or equal to the reference multiple of the cavern length; ② determine whether the width parallel to the main ridge line is greater than or equal to the calculated minimum width). If the requirements are met, then the mountain is the target usable mountain.

[0039] Step 8: Use impact data, such as river system data and road traffic data, to conduct spatial analysis. The analysis target can be the mountain and its distance. Use weighting methods to optimize the final site selection.

[0040] Table 1. Partial Parameter Table of Example 2

[0041] Table 2 Calculation Results of Example 2

[0042] The site accuracy rate was: ,in The total number of stations, This refers to the number of sites that do not meet the criteria during manual review.

[0043] The calculation results show that the program can greatly improve the site selection speed, and the site selection accuracy meets the requirements of engineering applications.

[0044] This application also provides a GIS-based mountain compressed air energy storage power station site selection system, characterized in that it includes a processor and a memory; Memory, used to store computer programs; When the processor executes a program stored in memory, it implements any of the steps described in the GIS-based mountain compressed air energy storage power station site selection method.

[0045] The aforementioned GIS-based mountain compressed air energy storage power station site selection system can implement various embodiments of the aforementioned GIS-based mountain compressed air energy storage power station site selection method and achieve the same beneficial effects, which will not be elaborated here.

[0046] The preferred embodiments of the present invention have been described in detail above. It should be understood that those skilled in the art can make numerous modifications and variations based on the concept of the present invention without creative effort. Therefore, all technical solutions that can be obtained by those skilled in the art based on the concept of the present invention through logical analysis, reasoning, or limited experimentation on the basis of existing technology should be within the scope of protection defined by the claims.

Claims

1. A GIS-based site selection method for mountain compressed air energy storage power stations, characterized in that, include: Acquire primary, secondary, and tertiary data for the target mountainous region; wherein, the primary data includes: data on the three zones and three lines, data on mineral resources covered by the land, and data on military facilities; the secondary data includes: geological data and topographic data; the tertiary data includes: river system data, road traffic data, grid corridor data, substation data, wind farm and photovoltaic power station data, data on existing energy storage power stations, and residential data; Based on the primary data, the target mountainous area is subjected to erasure analysis, and the target mountainous area containing the primary data is erased is used as a candidate area. Based on the secondary data, the candidate areas are filtered to select areas whose geological conditions meet the engineering requirements, thus obtaining geologically usable areas. Contour lines are constructed in the geologically available area. Mountains in the geologically available area are identified based on the contour lines. Mountains that meet the height requirements are selected, and the outlines and main ridge lines of the mountains that meet the requirements are constructed. Based on the relevant parameters of the compressed air energy storage power station, the reference area of ​​the mountain is determined in the mountain outline, and the area of ​​the reference area is calculated. The optimal internal rectangle of the mountain's baseline region is determined using a geometric algorithm. The determination of whether the mountain's baseline region meets the requirements for the optimal internal rectangle is then used to identify the target usable mountain. Based on the secondary and tertiary data, the scores of the target usable mountains are determined, and the areas with high scores are selected as the final sites. The parameters of the compressed air energy storage power station determine the mountain reference area in the mountain contour, including: Based on the relevant parameters of the compressed air energy storage power station, the mountain contour is analyzed horizontally, vertically, and overlay to determine the mountain reference area. The lateral analysis includes: based on the burial depth requirements in the relevant parameters of the compressed air energy storage power station, performing an inward shrinkage analysis on the mountain outline to obtain the area that meets the lateral burial depth requirements; The longitudinal analysis includes: based on the burial depth requirements in the relevant parameters of the compressed air energy storage power station, finding contour lines that meet the burial depth requirements upwards from the contour lines where the mountain outline is located, and obtaining the area that meets the longitudinal burial depth requirements; The overlay analysis includes: performing overlay analysis on areas that meet the burial depth requirements laterally and areas that meet the burial depth requirements longitudinally to obtain the mountain reference area.

2. The GIS-based site selection method for mountain compressed air energy storage power stations according to claim 1, characterized in that, The process of filtering the candidate areas based on the secondary data to select areas whose geological conditions meet the engineering requirements and thus obtain geologically usable areas includes: Based on the geological data in the secondary data, the candidate areas are screened, and areas with igneous rocks, a distance greater than a certain range from active faults, and a relatively low seismic intensity compared to the regional average are selected as geologically usable areas.

3. The GIS-based site selection method for mountain compressed air energy storage power stations according to claim 1, characterized in that, The process of constructing contour lines in the geologically usable area and identifying mountains in the geologically usable area based on the contour lines includes: Contour lines are generated in the geologically available area using a digital elevation model, and the highest closed contour line is found among the generated contour lines. Internal representative points are generated in the highest closed contour lines, and all closed contour lines containing internal representative points are identified as mountains in the geologically available area.

4. The GIS-based site selection method for mountain compressed air energy storage power stations according to claim 1, characterized in that, The process of selecting mountains that meet the height requirements and constructing their outlines and main ridgelines includes: Determine the required mountain height, and based on this requirement, select suitable mountains from the geologically available area. In mountains that meet the requirements, the lowest contour line is used as the mountain outline; Flow direction analysis is performed on the qualified mountain to calculate the water flow direction. Based on the water flow direction, flow accumulation analysis is performed to generate a flow accumulation grid, identify the water flow convergence area, determine the river network based on the water flow convergence area to obtain the watershed boundary line, and determine the ridge line based on the watershed boundary line.

5. The GIS-based site selection method for mountain compressed air energy storage power stations according to claim 1, characterized in that, The area of ​​the reference area is calculated based on the aforementioned mountain reference area, wherein the area is calculated using the following formula: ； In the formula, Indicates the area of ​​the reference region. The number of vertices of the polygon. For the first The x-coordinates of the vertices, For the first The y-coordinates of the vertices, For the first The x-coordinates of the vertices, For the first The ordinates of each vertex.

6. The GIS-based site selection method for mountain compressed air energy storage power stations according to claim 1, characterized in that, The process of solving for the optimal internal rectangle of the mountain's reference area using geometric algorithms, determining whether the mountain's reference area meets the requirements for the optimal internal rectangle, and identifying the target usable mountain includes: Determine the total volume of the cavern in the relevant parameters of the compressed air energy storage power station. Length of the cavern Base multiple of cavern length Spacing between caverns , diameter of the cavern Require; Calculate the optimal inner rectangle length , =Cavity length Determine whether the length of the mountain body perpendicular to the main ridge line is greater than or equal to the length of the optimal internal rectangle. ×The length of the cavern is a multiple of the baseline. If the conditions are met, then the mountain meets the requirement for the optimal internal rectangular length. Calculate the number of caverns , , And based on the number of caverns Calculate the optimal inner rectangle width , = +( ) ; Determine if the width of the mountain body parallel to the main ridge line is greater than or equal to the optimal internal rectangle width. If the conditions are met, then the mountain body meets the requirement for the optimal internal rectangle width; If the length of the mountain perpendicular to the main ridge line and the width parallel to the main ridge line both meet the requirements of the optimal internal rectangle, then the mountain is a target usable mountain.

7. The GIS-based site selection method for mountain compressed air energy storage power stations according to claim 1, characterized in that, The process of determining the score of the target usable mountain based on the secondary and tertiary data, and selecting the area with the highest score as the final site selection, includes: The scores of usable mountains for a target are determined by analyzing geological data, topographic data, river system data, and road traffic data. The location score is calculated according to the following formula: ； ， = 0.5， = 0.3， = 0.1， = 0.1； ； In the formula, For geological scores, The baseline area of ​​the mountain is scored. The score is based on the distance from the river system. Scoring is based on distance from road traffic. For lithology score, The score is based on the distance from the active fracture. To score the earthquake intensity, , which are the corresponding weights; The area with the highest location score will be selected as the final location.

8. A GIS-based site selection system for mountain compressed air energy storage power stations, characterized in that, Including processor and memory; Memory, used to store computer programs; A processor, when executing a program stored in memory, implements the steps of the method described in any one of claims 1-7.

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