A micro-terrain coupling-based site selection method for a mountain photovoltaic field area booster station

Abstract

The application provides a mountain photovoltaic field area step-up station site selection method based on micro-terrain coupling. The method specifically comprises the following steps: obtaining field area digital surface model data, selecting four indexes of slope, slope length, rock exposure rate and catchment characteristics by combining with field reconnaissance related data for K-means clustering, determining the partition of various types of micro-terrain units, establishing a mapping relationship table of various types of micro-terrain units and six types of cost coefficients, establishing a total construction cost coupling model, generating a step-up station candidate site selection area under multiple constraint conditions, comprehensively scoring the step-up station site selection candidate area, and taking the site selection area with the highest comprehensive score as the optimal site selection of the step-up station. According to the terrain differentiated cost coefficient, the application reduces the cost accounting deviation, reflects the real investment benefit by establishing the cost coupling model, solves the problem of single site selection screening standard and insufficient landing of the prior art through the comprehensive evaluation of the site selection area, and improves the rationality and economy of site selection.

Description

Technical Field

[0001] This invention relates to the field of photovoltaic power plant engineering design technology, specifically to a method for selecting a substation site in a mountainous photovoltaic field based on micro-topography coupling, which precisely adapts costs by dividing the terrain into micro-topographic units and coordinates the cost control of power collection lines and roads. Background Technology

[0002] With the development of the photovoltaic industry, photovoltaic resources in plains are becoming increasingly scarce, and mountain photovoltaic systems are being widely promoted in mountainous areas. As the core hub of mountain photovoltaic sites, the rationality of the site selection of the booster station directly determines the project's construction costs and operational benefits, making it a key aspect of engineering design.

[0003] Compared to photovoltaic (PV) fields in plains areas, mountainous PV fields are characterized by complex terrain, diverse micro-topographical units (such as gentle terraces, gentle slopes, steep slopes, valleys, and exposed rock areas), and a larger distribution range of PV arrays. These characteristics present challenges for the site selection of booster substations. Currently, booster substation site selection often combines experience with on-site surveys, considering single-dimensional cost indicators such as earthwork and distance, and has not yet formed a systematic site selection scheme that couples terrain features with cost. Summary of the Invention

[0004] This invention addresses the shortcomings of existing technologies by providing a method for selecting substation locations in mountainous photovoltaic fields based on micro-topography coupling. This method precisely divides the mountainous micro-topography into units, establishes a quantitative mapping relationship between micro-topography and cost, constructs a cost coupling model, and combines scientific ranking and evaluation rules to achieve the optimal location for the substation.

[0005] To achieve the above technical objectives, this invention provides a method for selecting a substation location in a mountainous photovoltaic field based on micro-topography coupling, the specific steps of which are as follows:

[0006] S1. Obtain digital surface model data of the site with a resolution of 0.1-0.5m through drone aerial survey, and combine it with the data on the characteristics of gully water runoff and soil thickness recorded by on-site reconnaissance. The data coverage area must extend more than 500m beyond the red line of the photovoltaic site.

[0007] S2. Select four indicators from the data obtained in step S1: slope, slope length, rock exposure rate, and water catchment characteristics, and perform K-means clustering. Input the obtained topographic data into the K-means clustering model, complete the clustering division according to the threshold, and output the distribution map of micro-topographic units in the field area. Clarify the boundary range and area of ​​each type of micro-topographic unit. The micro-topographic classification includes gentle terraces, gentle slope areas, steep slope areas, valley areas, and rock exposure areas.

[0008] S3. By analyzing the cost data of historical mountain photovoltaic projects, establish a mapping relationship table between various micro-topographic units and 6 types of cost coefficients; the 6 types of cost coefficients include conductor cross-section enlargement coefficient k1, tower foundation reinforcement cost coefficient k2, roadbed excavation difficulty coefficient k3, slope support cost coefficient k4, terrain leveling coefficient k5, and cost sharing coefficient k6 for parallel laying of lines and roads.

[0009] S4. Establish a total construction cost coupling model, the objective function of which is mathematically expressed as follows:

[0010] S5. Generate candidate site selection areas for the booster station under the constraints of photovoltaic array partition range, booster station area, straight distance from the center of each array partition, terrain slope, and ecological protection red line.

[0011] S6. The candidate sites for the substation are comprehensively scored, taking into account the total construction cost and construction accessibility as evaluation indicators. All candidate sites for the substation are ranked from high to low based on their comprehensive scores, and the site with the highest comprehensive score is selected as the optimal site for the substation.

[0012] The preferred technical solution of this invention: In step S2, the clustering threshold is determined using historical mountain photovoltaic projects as follows:

[0013] Gentle terraces: slope ≤ 5° and slope length ≥ 50m, rock exposure rate < 20%;

[0014] Gentle slope areas: 5° < slope ≤ 15° and slope length ≥ 30m, rock exposure rate < 30%;

[0015] Steep slope areas: 15° < slope ≤ 30° and slope length < 30m, rock exposure rate < 40%;

[0016] Valley areas: slope ≤ 5° and slope length < 20%, with water catchment characteristics;

[0017] Rock-exposed areas: Rock exposure rate ≥ 70%, slope is not limited.

[0018] The preferred technical solution of this invention is as follows: the mapping relationship between various micro-terrain units and 6 types of cost coefficients in step S3 is as follows:

[0019]

[0020] A further technical solution of the present invention: cost of the collector line in step S4 The mathematical expression is as follows:

[0021]

[0022] in: For the first The length of the segmented power line in the corresponding micro-topographic unit; Cost per unit length of basic conductor; For the first The conductor cross-section magnification factor of the micro-topography where the line segment is located; The unit cost of a standard tower base; For the first The cost coefficient for tower foundation reinforcement based on the micro-topography of the section's tower foundation; Cost per unit area of ​​slope protection installed separately for the line; For the first The slope support cost coefficient of the micro-topography where the section of the line is located; For the first The slope protection height of the section of the line; For the first The cost of crossing the intersection of a section of track and a road.

[0023] A further technical solution of the present invention: S4 step, construction cost of the central road The mathematical expression is as follows:

[0024]

[0025] in: For the first The length of the access road to the station within the corresponding micro-topographic unit; For the first The length of the maintenance road within the corresponding micro-topographic unit. The unit cost of basic roadbed excavation; For the first The difficulty coefficient of roadbed excavation in the micro-topography of the section of road; The unit cost of road paving; The unit area cost of slope protection constructed separately for roads; For the first The slope support cost coefficient of the micro-topography where the road section is located; For the first The slope height of the access road to the station; For the first The slope height of the section of road under maintenance.

[0026] A further technical solution of the present invention: the cost of site leveling for the booster station in step S4. The mathematical expression is as follows:

[0027]

[0028] in: The total area of ​​the substation includes the designed area and the area reserved for future expansion, in square meters; The cost per unit area for leveling the site is taken as the benchmark, and the cost of leveling gentle terraces is uniformly used. This is the terrain flatness coefficient.

[0029] A further technical solution of the present invention: Collaborative sharing of redundant costs in step S4. The mathematical expression is as follows:

[0030]

[0031] in: For the first The parallel length of the section of track to the road; The unit cost of slope protection for separately laid lines; The unit area cost of slope protection constructed separately for roads; To obtain the higher of the two support costs; For the first Cost sharing coefficient for parallel laying of lines and roads in the micro-topography of the parallel section area; For the first The shared slope height of parallel sections, that is, the slope height where the line and the road overlap.

[0032] The preferred technical solution of the present invention is as follows: The constraints of the candidate site selection area for the booster station in step S5 are: ① The straight-line distance from the center of each array partition is ≤8km; ② The terrain slope is ≤15°; ③ Avoid areas with high incidence of geological disasters; ④ The area of ​​usable flat land is ≥ the designed land area of ​​the booster station; ⑤ Areas with extremely high engineering difficulty, such as areas with exposed rocks and gully catchment areas, as well as areas within the ecological protection red line, are excluded.

[0033] A further technical solution of the present invention: The specific process of the comprehensive scoring in step S6 is as follows:

[0034] ① Identify the target micro-topographic unit type and match the corresponding coefficients from the mapping table between various micro-topographic units and 6 types of cost coefficients. ;

[0035] ② Combining the photovoltaic array planning map and the micro-topographic unit distribution map, extract the core parameters corresponding to the unit, specifically including the length of the collection line, the length of the site road, the length of the collinear parallel lines, and the total land area of ​​the step-up substation. ;

[0036] ③ Substitute the parameters of each candidate region into the objective function of the cost coupling model to obtain the total construction cost of each candidate region. ;

[0037] ④ Record the lowest total construction cost among all candidate areas as Total score for construction in a candidate area Points less than 0 will be recorded as 0.

[0038] ⑤ Construction accessibility score The scoring criteria are as follows:

[0039] Large equipment entry conditions: 10 points are awarded if the candidate area is ≤2km from the main road of the site, 6 points are awarded if the distance is 2-3km, and 0 points are awarded if the distance is >3km.

[0040] Material transportation route: 10 points for transportation routes with a slope greater than 30° that have no continuous steep slopes or large gullies; 4 points for the presence of one such obstacle; 0 points for the presence of two or more such obstacles.

[0041] ⑥ Overall Score All candidate areas are sorted from highest to lowest comprehensive score, and the area with the highest comprehensive score is selected as the optimal site for the booster station. If the comprehensive scores of two or more candidate areas differ by ≤2, the area with the lower total construction cost is selected.

[0042] The present invention has the following beneficial effects:

[0043] (1) Improve the accuracy of cost accounting and reflect the true investment cost: This invention divides the photovoltaic field terrain into different micro-topographic units through the K-means clustering algorithm and establishes a mapping relationship table between different micro-topographic units and cost coefficients, thereby avoiding cost accounting distortion caused by different terrains, accurately calculating project costs, and providing reliable support for investment decisions.

[0044] (2) Improve site selection efficiency and eliminate repetitive workload: The present invention adopts a process of screening first and then calculating and sorting. It filters the candidate areas for site selection through constraints such as micro-topography type, distance, and area, and only evaluates the candidate areas that meet the requirements, which greatly improves the site selection efficiency and shortens the design cycle.

[0045] (3) Enhance the feasibility of project implementation and ensure smooth construction and subsequent operation and maintenance: The present invention comprehensively considers the construction accessibility index in the comprehensive scoring stage, ensuring that the selected site area can safely and smoothly transport large equipment and materials, while also reducing the later operation and maintenance costs and risks.

[0046] (4) Improve universality and be applicable to different mountain photovoltaic scenarios: The cost coefficient mapping table of the present invention can be finely adjusted according to the topographic map of the project site, and can be adapted to a variety of mountain photovoltaic projects with different terrain conditions.

[0047] This invention combines basic data of photovoltaic field sites to divide the field sites into five types of micro-topographic units, establishes corresponding cost coefficient mapping relationships, and reduces cost accounting deviations based on topographically differentiated cost coefficients. By establishing a cost coupling model, the cost accounting logic chain is improved, and redundant costs of repeated support are deducted to reflect the true investment benefits. Through comprehensive evaluation of the site selection area, a systematic assessment considering cost and construction accessibility is conducted to solve the problems of single site selection criteria and insufficient feasibility in existing technologies, thereby improving the rationality and economy of site selection. Attached Figure Description

[0048] Figure 1 This is a flowchart of the present invention. Detailed Implementation

[0049] This invention provides a method for selecting the location of a booster station in a mountainous photovoltaic field based on micro-topography coupling. By accurately dividing the mountainous micro-topography into units, establishing a quantitative mapping relationship between micro-topography and cost, constructing a cost coupling model, and combining scientific ranking and evaluation rules, the optimal location of the booster station is achieved. The specific implementation steps are as follows:

[0050] S1. Obtain digital surface model (DSM) data of the site with a resolution of 0.1-0.5m through drone aerial survey, and supplement the data with supplementary data such as gully water catchment characteristics and soil layer thickness recorded by on-site reconnaissance. The data coverage area must extend more than 500m beyond the red line of the photovoltaic site.

[0051] S2. Based on the data, four indicators—slope, slope length, rock exposure rate, and water catchment characteristics—are selected for K-means clustering. The clustering threshold is determined using historical mountain photovoltaic projects.

[0052] Gentle terraces: slope ≤ 5° and slope length ≥ 50m, rock exposure rate < 20%;

[0053] Gentle slope areas: 5° < slope ≤ 15° and slope length ≥ 30m, rock exposure rate < 30%;

[0054] Steep slope areas: 15° < slope ≤ 30° and slope length < 30m, rock exposure rate < 40%;

[0055] Valley areas: slope ≤ 5° and slope length < 20%, with water catchment characteristics;

[0056] Rock-exposed areas: Rock exposure rate ≥ 70%, slope is not limited.

[0057] The acquired terrain data is input into the K-means clustering model, and the clustering is completed according to the threshold. The distribution map of micro-topographic units in the field area is output, and the boundary range and area of ​​each type of micro-topographic unit are clearly defined.

[0058] S3. By analyzing historical cost data of mountain photovoltaic projects, a mapping table between various micro-topographical units and six types of cost coefficients is established. The coefficients can be fine-tuned according to the actual terrain characteristics of the site:

[0059]

[0060] S4. Establish a total construction cost coupling model, the objective function of which is mathematically expressed as follows:

[0061]

[0062] Collection line cost The mathematical expression is as follows:

[0063]

[0064] in: For the first The length of the segmented power line in the corresponding micro-topographic unit; Cost per unit length of basic conductor; For the first The conductor cross-section magnification factor of the micro-topography where the line segment is located; The unit cost of a standard tower base; For the first The cost coefficient for tower foundation reinforcement based on the micro-topography of the section's tower foundation; Cost per unit area of ​​slope protection installed separately for the line; For the first The slope support cost coefficient of the micro-topography where the section of the line is located; For the first The slope protection height of the section of the line; For the first The cost of crossing the intersection of a section of track and a road.

[0065] Site road construction costs The mathematical expression is as follows:

[0066]

[0067] in: For the first The length of the access road to the station within the corresponding micro-topographic unit; For the first The length of the maintenance road within the corresponding micro-topographic unit. The unit cost of basic roadbed excavation; For the first The difficulty coefficient of roadbed excavation in the micro-topography of the section of road; The unit cost of road paving; The unit area cost of slope protection constructed separately for roads; For the first The slope support cost coefficient of the micro-topography where the road section is located; For the first The slope height of the access road to the station; For the first The slope height of the section of road under maintenance.

[0068] Leveling cost of booster station site The mathematical expression is as follows:

[0069]

[0070] in: The total area of ​​the substation includes the designed area and the area reserved for future expansion, in square meters; The cost per unit area for leveling the site is taken as the benchmark, and the cost of leveling gentle terraces is uniformly used. The terrain smoothing coefficient is k5, which varies depending on the terrain, representing the change in the cost of smoothing different terrains.

[0071] Collaborative sharing of redundant costs The mathematical expression is as follows:

[0072]

[0073] in: For the first The parallel length of the section of track to the road; The unit cost of slope protection for separately laid lines; The unit area cost of slope protection constructed separately for roads; To obtain the higher of the two support costs; For the first Cost sharing coefficient for parallel laying of lines and roads in the micro-topography of the parallel section area; For the first The shared slope height of parallel sections, that is, the slope height where the line and the road overlap.

[0074] Collaborative sharing of redundant costs The mathematical expression is as follows:

[0075]

[0076] in: For the first The parallel length of the section of track to the road; The unit cost of slope protection for separately laid lines; The unit area cost of slope protection constructed separately for roads; To obtain the higher of the two support costs; For the first The collaborative sharing coefficient of the micro-topography in the parallel area of ​​the segment; For the first The shared slope height of the parallel section (i.e., the slope height where the line coincides with the road).

[0077] S5. Generate candidate site selection areas based on constraints such as the photovoltaic array zoning range, the area occupied by the booster station, the straight-line distance from the center of each array zone, the terrain slope, and the ecological protection red line. The constraints for the candidate site selection areas of the booster station are as follows: ① Straight-line distance from the center of each array zone ≤ 8km; ② Terrain slope ≤ 15°; ③ Avoid areas with a high incidence of geological disasters; ④ The area of ​​usable flat land is ≥ the designed area of ​​the booster station; ⑤ Areas with extremely high engineering difficulty, such as areas with exposed rock and gully catchment areas, as well as areas within the ecological protection red line, are excluded.

[0078] S6. Conduct a comprehensive evaluation of the candidate sites for the booster station, considering two evaluation indicators: total construction cost and construction accessibility. The comprehensive evaluation steps are as follows:

[0079] ① Identify the target micro-terrain unit type and match the corresponding one from the cost factor table. coefficient;

[0080] ② Combining the photovoltaic array planning map and the micro-topographic unit distribution map, extract the corresponding unit's collection line length, site road (access + maintenance) length, collinear parallel length, and total substation area. Core parameters, etc.

[0081] ③ Substitute the parameters of each candidate region into the objective function of the cost coupling model to obtain the total construction cost of each candidate region. .

[0082] ④ Record the lowest total construction cost among all candidate areas as Total score for construction in a candidate area (A score less than 0 is recorded as 0).

[0083] ⑤ Construction accessibility score The scoring criteria are as follows: Large equipment entry conditions: 10 points for the candidate area being ≤2km from the main road of the site, 6 points for 2-3km, and 0 points for >3km; Material transportation route: 10 points for the transportation route having no continuous steep slopes (slope >30°) and no large gullies crossing, 4 points for the presence of 1 such obstacle, and 0 points for the presence of 2 or more obstacles.

[0084] ⑥ Overall Score All candidate areas are sorted from highest to lowest comprehensive score, and the area with the highest comprehensive score is selected as the optimal site for the booster station. If the comprehensive scores of two or more candidate areas differ by ≤2, the area with the lower total construction cost is selected.

[0085] The above description is merely one embodiment of the present invention, and while it is detailed and specific, it should not be construed as limiting the scope of the invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the appended claims.

Claims

1. A method for selecting a substation location in a mountainous photovoltaic power plant area based on micro-topographic coupling, characterized in that, The specific steps are as follows: S1. Obtain digital surface model data of the site with a resolution of 0.1-0.5m through drone aerial survey, and combine it with the data on the characteristics of gully water runoff and soil thickness recorded by on-site reconnaissance. The data coverage area must extend more than 500m beyond the red line of the photovoltaic site. S2. Select four indicators from the data obtained in step S1: slope, slope length, rock exposure rate, and water catchment characteristics, and perform K-means clustering. Input the obtained topographic data into the K-means clustering model, complete the clustering division according to the threshold, and output the distribution map of micro-topographic units in the field area. Clarify the boundary range and area of ​​each type of micro-topographic unit. The micro-topographic classification includes gentle terraces, gentle slope areas, steep slope areas, valley areas, and rock exposure areas. S3. By analyzing the cost data of historical mountain photovoltaic projects, establish a mapping relationship table between various micro-topographic units and 6 types of cost coefficients; the 6 types of cost coefficients include conductor cross-section enlargement coefficient k1, tower foundation reinforcement cost coefficient k2, roadbed excavation difficulty coefficient k3, slope support cost coefficient k4, terrain leveling coefficient k5, and cost sharing coefficient k6 for parallel laying of lines and roads. S4. Establish a total construction cost coupling model, the objective function of which is mathematically expressed as follows: ； S5. Generate candidate site selection areas for the booster station under the constraints of photovoltaic array partition range, booster station area, straight distance from the center of each array partition, terrain slope, and ecological protection red line. S6. The candidate sites for the substation are comprehensively scored, taking into account the total construction cost and construction accessibility as evaluation indicators. All candidate sites for the substation are ranked from high to low based on their comprehensive scores, and the site with the highest comprehensive score is selected as the optimal site for the substation.

2. The method for selecting a substation location in a mountainous photovoltaic field based on micro-topography coupling according to claim 1, characterized in that, In step S2, the clustering threshold was determined using historical mountain photovoltaic projects as follows: Gentle terraces: slope ≤ 5° and slope length ≥ 50m, rock exposure rate < 20%; Gentle slope areas: 5° < slope ≤ 15° and slope length ≥ 30m, rock exposure rate < 30%; Steep slope areas: 15° < slope ≤ 30° and slope length < 30m, rock exposure rate < 40%; Valley areas: slope ≤ 5° and slope length < 20%, with water catchment characteristics; Rock-exposed areas: Rock exposure rate ≥ 70%, slope is not limited.

3. A method for selecting a substation location in a mountainous photovoltaic field based on micro-topography coupling, as described in claim 1 or 2, characterized in that... The mapping relationships between various micro-terrain units and the six cost coefficients in step S3 are as follows: 。 4. A method for selecting a substation location in a mountainous photovoltaic field based on micro-topography coupling, as described in claim 1 or 2, characterized in that... Cost of collector lines in step S4 The mathematical expression is as follows: ； in: For the first The length of the segmented power line in the corresponding micro-topographic unit; Cost per unit length of basic conductor; For the first The conductor cross-section magnification factor of the micro-topography where the line segment is located; The unit cost of a standard tower base; For the first The cost coefficient for tower foundation reinforcement based on the micro-topography of the section's tower foundation; Cost per unit area of ​​slope protection installed separately for the line; For the first The slope support cost coefficient of the micro-topography where the section of the line is located; For the first The slope protection height of the section of the line; For the first The cost of crossing the intersection of a section of track and a road.

5. A method for selecting a substation location in a mountainous photovoltaic field based on micro-topography coupling, as described in claim 1 or 2, characterized in that... S4 Step Central Area Road Construction Cost The mathematical expression is as follows: ； in: For the first The length of the access road to the station within the corresponding micro-topographic unit; For the first The length of the maintenance road within the corresponding micro-topographic unit. The unit cost of basic roadbed excavation; For the first The difficulty coefficient of roadbed excavation in the micro-topography of the section of road; The unit cost of road paving; The unit area cost of slope protection constructed separately for roads; For the first The slope support cost coefficient of the micro-topography where the road section is located; For the first The slope height of the access road to the station; For the first The slope height of the section of road under maintenance.

6. A method for selecting a substation location in a mountainous photovoltaic field based on micro-topography coupling, as described in claim 1 or 2, characterized in that, The cost of site leveling for the booster station in step S4 The mathematical expression is as follows: ； in: The total area of ​​the substation includes the designed area and the area reserved for future expansion, in square meters; The cost per unit area for leveling the site is taken as the benchmark, and the cost of leveling gentle terraces is uniformly used. This is the terrain flatness coefficient.

7. A method for selecting a substation location in a mountainous photovoltaic field based on micro-topography coupling, as described in claim 1 or 2, characterized in that... In step S4, collaborative sharing of redundancy costs The mathematical expression is as follows: ； in: For the first The parallel length of the section of track to the road; The unit cost of slope protection for separately laid lines; The unit area cost of slope protection constructed separately for roads; To obtain the higher of the two support costs; For the first Cost sharing coefficient for parallel laying of lines and roads in the micro-topography of the parallel section area; For the first The shared slope height of parallel sections, that is, the slope height where the line and the road overlap.

8. A method for selecting a substation location in a mountainous photovoltaic field based on micro-topography coupling, as described in claim 1 or 2, characterized in that, The constraints for the candidate sites of the booster station in step S5 are as follows: ① The straight-line distance from the center of each array partition is ≤8km; ② The terrain slope is ≤15°; ③ Avoid areas with high incidence of geological disasters; ④ The area of ​​usable flat land is ≥ the designed area of ​​the booster station; ⑤ Areas with extremely high engineering difficulty, such as areas with exposed rocks and gully catchment areas, as well as areas within the ecological protection red line, are excluded.

9. A method for selecting a substation location in a mountainous photovoltaic field based on micro-topography coupling, as described in claim 1 or 2, characterized in that, The specific process of the comprehensive scoring in step S6 is as follows: ① Identify the target micro-topographic unit type and match the corresponding coefficients from the mapping table between various micro-topographic units and 6 types of cost coefficients. ; ② Combining the photovoltaic array planning map and the micro-topographic unit distribution map, extract the core parameters corresponding to the unit, specifically including the length of the collection line, the length of the site road, the length of the collinear parallel lines, and the total land area of ​​the step-up substation. ; ③ Substitute the parameters of each candidate region into the objective function of the cost coupling model to obtain the total construction cost of each candidate region. ; ④ Record the lowest total construction cost among all candidate areas as Total score for construction in a candidate area Points less than 0 will be recorded as 0. ⑤ Construction accessibility score The scoring criteria are as follows: Large equipment entry conditions: 10 points are awarded if the candidate area is ≤2km from the main road of the site, 6 points are awarded if the distance is 2-3km, and 0 points are awarded if the distance is >3km. Material transportation route: 10 points for transportation routes with a slope greater than 30° that have no continuous steep slopes or large gullies; 4 points for the presence of one such obstacle; 0 points for the presence of two or more such obstacles. ⑥ Overall Score All candidate areas are sorted from highest to lowest comprehensive score, and the area with the highest comprehensive score is selected as the optimal site for the booster station. If the comprehensive scores of two or more candidate areas differ by ≤2, the area with the lower total construction cost is selected.

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