Hydrogenation network distribution planning method and device based on multi-source data, and storage medium

Abstract

The embodiment of the invention relates to the technical field of energy planning, and discloses a hydrogenation network distribution planning method and device based on multi-source data, and a storage medium, and the method comprises the steps: firstly obtaining a preliminarily planned hydrogenation network route (i.e., an initial hydrogenation station topological map), obtaining a plurality of initial candidate hydrogenation station addresses through spatial mapping; adjusting the initial candidate address according to a multi-source data set of industry, traffic, environment, economy, safety and the like to obtain a target candidate address, and screening out a target hydrogenation site address according to preset conditions including rigid (such as distance limitation with a peripheral sensitive area) and flexible (such as single-station service radius limitation) constraints; and finally, generating a hydrogenation network distribution circuit diagram based on the target addresses. Therefore, according to the technical scheme of the invention, multiple factors can be comprehensively considered, so that the site selection of the hydrogenation sites is more scientific and reasonable, the accurate matching of hydrogen energy supply and terminal requirements can be realized, and the efficiency of hydrogenation network distribution planning can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of energy planning, and in particular to a method, device and storage medium for hydrogenation network distribution planning based on multi-source data. Background Art

[0002] As the hydrogen energy industry flourishes, the rational planning and layout of hydrogen refueling networks, as key infrastructure for hydrogen energy applications, plays a vital role in the promotion of hydrogen-powered vehicles and the sustainable development of the hydrogen energy industry. With the continuous advancement of hydrogen energy technology, the market share of hydrogen-powered vehicles has gradually increased, and the demand for hydrogen refueling stations has also increased. Therefore, how to scientifically and efficiently plan the distribution of hydrogen refueling networks has become a pressing issue. Summary of the Invention

[0003] The main purpose of the present invention is to provide a hydrogenation network distribution planning method, device and storage medium based on multi-source data, aiming to solve the technical problem of low efficiency of hydrogenation network distribution planning in the prior art.

[0004] To achieve the above objectives, in a first aspect, an embodiment of the present application provides a method for hydrogenation network distribution planning based on multi-source data, the method comprising: Obtaining an initial hydrogenation site topology map, wherein the initial hydrogenation site topology map is a preliminarily planned hydrogenation network route; Performing spatial mapping on the initial hydrogenation site topology map to obtain multiple initial candidate hydrogenation site addresses; Adjusting each initial candidate hydrogen refueling site address according to a multi-source data set to obtain a plurality of corresponding target candidate hydrogen refueling site addresses, wherein the multi-source data set includes industrial data, traffic data, environmental data, economic data, and safety data; The target hydrogenation site address is obtained by screening the multiple target candidate hydrogenation site addresses according to preset constraints, wherein the preset constraints include at least one of a rigid constraint and a flexible constraint, wherein the rigid constraint includes a distance restriction between the hydrogenation site and surrounding sensitive areas, and the flexible constraint includes a single-site service radius restriction; A hydrogenation network distribution route map is generated based on the multiple target hydrogenation site addresses.

[0005] In one possible implementation, adjusting each initial candidate hydrogenation site address according to the multi-source data set to obtain a plurality of corresponding target candidate hydrogenation site addresses includes: For each initial candidate hydrogen refueling site address, a multi-source data evaluation model is constructed; A search algorithm is used to perform a target search on a preset range area of each initial candidate hydrogenation site address to obtain multiple corresponding target candidate hydrogenation site addresses, wherein the comprehensive score value of each target candidate hydrogenation site address under the multi-source data evaluation model is within a set range.

[0006] In one possible implementation, for each initial candidate hydrogen refueling site address, a multi-source data evaluation model is constructed, including: Obtain the evaluation index weights corresponding to industrial data, traffic data, environmental data, economic data and safety data in multi-source data sets; A multi-source data evaluation model is constructed according to the evaluation index weights; wherein the multi-source data evaluation model satisfies the following expression: S=X*α1*(1+K1*F z )+Y*α2(1+K2*F z )+A*α3(1+K3*F z )+B*α4(1+K4*F z )+C*α5(1+K5*F z ), where S is the comprehensive score, X is the industry data score, Y is the traffic data score, A is the environmental data score, B is the economic data score, C is the safety data score, α1-α5 are the corresponding evaluation index weights, F z is the regional characteristic factor, and k1−k5 are the sensitivity coefficients of each data category weight to the regional characteristic factor.

[0007] In one possible implementation, the method of using a search algorithm to perform a target search within a preset range of each initial candidate hydrogenation site address to obtain multiple corresponding target candidate hydrogenation site addresses includes: Divide the preset range of each initial candidate hydrogen refueling site address into M*N grids, each grid representing a candidate hydrogen refueling site address, where M and N are both greater than or equal to 10; Calculate the comprehensive score of each candidate hydrogen refueling station address under the multi-source data evaluation model; The candidate hydrogenation site addresses with comprehensive score values within the set range are screened out as target candidate hydrogenation site addresses.

[0008] In a possible implementation, the step of screening the plurality of target candidate hydrogenation site addresses according to preset constraints to obtain the target hydrogenation site address includes: For rigid constraints, the distance restrictions between hydrogen refueling stations and surrounding sensitive areas are converted into spatial buffer analysis, and the target candidate hydrogen refueling station addresses located within the buffer zone of sensitive areas are eliminated; For flexible constraints, a service area is constructed with each target candidate hydrogen refueling station address as the center and the single station service radius as the radius. The number of potential hydrogen refueling demand points in each service area is counted, and the target candidate hydrogen refueling station addresses with a corresponding service area where the number of potential hydrogen refueling demand points is less than the preset threshold are eliminated. The final target hydrogen refueling station address is obtained by combining the screening results of rigid constraints and flexible constraints.

[0009] In a possible implementation, counting the number of potential hydrogenation demand points in each service area includes: Determine the basic hydrogen refueling demand point in each service area according to the hydrogen vehicle penetration rate increase index, wherein the basic hydrogen refueling demand point is positively correlated with the hydrogen vehicle penetration rate increase index; Determine additional hydrogen refueling demand points within each service area based on the hydrogen price fluctuation index; Determine the number of potential hydrogenation demand points in each service area based on the basic hydrogenation demand points and additional hydrogenation demand points.

[0010] In one possible implementation, determining the number of potential hydrogenation demand points in each service area based on the basic hydrogenation demand points and the additional hydrogenation demand points includes: Obtain the initial reference weights of the basic hydrogenation demand point and the additional hydrogenation demand point, and the sum of the initial reference weights is 1; Adjusting the initial reference weights according to population density data to obtain target reference weights for basic hydrogenation demand points and additional hydrogenation demand points; The number of potential hydrogenation demand points is obtained according to the basic hydrogenation demand points, the additional hydrogenation demand points and the corresponding target reference weights.

[0011] In one possible implementation, performing spatial mapping on the initial hydrogenation site topology map to obtain multiple initial candidate hydrogenation site addresses includes: Identifying and extracting network nodes in the initial hydrogenation site topology map to obtain a plurality of initial network nodes; Associating the plurality of initial network nodes with a geographic information system, and converting the node coordinates in the topological map into geographic coordinates in the GIS using a coordinate conversion algorithm; According to the converted geographic coordinates, the actual geographic location corresponding to each initial network node is determined in GIS to obtain multiple initial candidate hydrogen refueling site addresses.

[0012] In a second aspect, an embodiment of the present application further provides an electronic device, including: A map acquisition module is used to obtain an initial hydrogenation station topology map; A spatial mapping module is used to perform spatial mapping on the initial hydrogenation site topology map to obtain multiple initial candidate hydrogenation site addresses; An adjustment module, configured to adjust each initial candidate hydrogenation site address according to a multi-source data set to obtain a plurality of corresponding target candidate hydrogenation site addresses; A screening module is used to screen multiple target candidate hydrogenation site addresses according to preset constraints to obtain a target hydrogenation site address; The route map generation module is used to generate a hydrogenation network distribution route map based on the addresses of multiple target hydrogenation stations.

[0013] In a third aspect, an embodiment of the present application further provides a storage medium on which a computer program is stored, and when the computer program is executed by a processor, the steps of the method described in the first aspect are implemented.

[0014] Different from the prior art, the method for hydrogenation network distribution planning based on multi-source data provided in the embodiment of the present application first obtains the preliminary planned hydrogenation network route, i.e., the initial hydrogenation site topology map, obtains multiple initial candidate hydrogenation site addresses through spatial mapping, and then adjusts the initial candidate addresses based on multi-source data sets such as industry, transportation, environment, economy, and safety to obtain target candidate addresses. Then, the target hydrogenation site addresses are screened out based on preset conditions containing rigid (such as distance restrictions from surrounding sensitive areas) and flexible (such as single-station service radius restrictions) constraints, and finally a hydrogenation network distribution route map is generated based on these target addresses. In this way, the technical solution of the present application, based on manual preliminary planning, comprehensively considers multiple factors, and automatically screens out target hydrogenation addresses that meet the conditions, making the site selection of hydrogenation sites more scientific and reasonable, not only achieving a precise match between hydrogen energy supply and terminal demand, but also improving the efficiency of hydrogenation network distribution planning. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the structures shown in these drawings without paying any creative work.

[0016] Figure 1 A schematic diagram of a topological map of an initial hydrogenation station in some embodiments of the present application; Figure 2 This is a flow chart of a method for hydrogenation network distribution planning based on multi-source data in some embodiments of the present application; Figure 3 This is a flow chart of step S300 of the method for planning hydrogenation network distribution based on multi-source data in some embodiments of the present application; Figure 4 This is a schematic diagram of the division of the preset range of initial candidate hydrogen refueling site addresses in some embodiments of the present application; Figure 5 Schematic diagram of the hardware structure of the electronic device in some embodiments of the present application.

[0017] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0018] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0019] It should be noted that all directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of the present invention are only used to explain the relative position relationship, movement status, etc. between the various components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly.

[0020] In addition, the descriptions of "first", "second", etc. in the present invention are only for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In addition, "and / or" in the full text includes three solutions. Taking A and / or B as an example, it includes technical solution A, technical solution B, and technical solution that satisfies both A and B. In addition, the technical solutions between the various embodiments can be combined with each other, but they must be based on the ability of ordinary technicians in this field to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such a combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0021] As the hydrogen energy industry flourishes, the rational planning and layout of hydrogen refueling networks, as key infrastructure for hydrogen energy applications, plays a vital role in the promotion of hydrogen-powered vehicles and the sustainable development of the hydrogen energy industry. With the continuous advancement of hydrogen energy technology, the market share of hydrogen-powered vehicles has gradually increased, and the demand for hydrogen refueling stations has also increased. Therefore, how to scientifically and efficiently plan the distribution of hydrogen refueling networks has become a pressing issue.

[0022] like Figures 1-4As shown, the following takes the hydrogenation network distribution planning system executing the hydrogenation network distribution planning method based on multi-source data as an example for explanation. It should be noted that although the logical order is shown in the flow chart, in some cases, the steps shown or described can be executed in a different order than here. Figure 2 The method includes the following steps S100 to S500: Step S100: obtaining an initial hydrogenation site topology map, wherein the initial hydrogenation site topology map is a preliminarily planned hydrogenation network route; Specifically, relevant planners can customize hydrogen refueling stations in the area to be distributed and planned, that is, they can preliminarily plan hydrogen refueling network routes in the relevant areas. Taking the planning of hydrogen refueling stations on highways as an example, planners customize hydrogen refueling stations along the highway and automatically form an initial hydrogen refueling station topology map through a pre-set map scale. Figure 1 As shown, hydrogen refueling stations Z1-Z4 are network nodes of the initial hydrogen refueling station topology map.

[0023] For example, relevant planners can customize multiple hydrogen refueling stations along the highway based on the total length of the highway and the coverage distance of the stations, such as distributing multiple hydrogen refueling stations at equal distances.

[0024] Step S200: performing spatial mapping on the initial hydrogenation site topology map to obtain multiple initial candidate hydrogenation site addresses; Spatial mapping refers to accurately mapping the nodes on the topological map to the actual space, thereby determining the actual geographical location of each network node.

[0025] In one embodiment, step S200: spatially mapping the initial hydrogen refueling site topology map to obtain multiple initial candidate hydrogen refueling site addresses, includes: identifying and extracting network nodes in the initial hydrogen refueling site topology map to obtain multiple initial network nodes; associating the multiple initial network nodes with a geographic information system, and converting the node coordinates in the topology map into geographic coordinates in GIS through a coordinate conversion algorithm; based on the converted geographic coordinates, determining the actual geographic location corresponding to each initial network node in GIS to obtain multiple initial candidate hydrogen refueling site addresses.

[0026] Specifically, the initial hydrogen refueling site topology map is thoroughly analyzed to accurately identify and extract network nodes, resulting in multiple initial network nodes. These initial network nodes serve as the fundamental building blocks of the topology map and represent the locations of potential hydrogen refueling sites. These extracted initial network nodes are then linked to a geographic information system (GIS). GIS integrates a rich set of geospatial data, providing an accurate geographic reference framework for node coordinate conversion. Using a coordinate conversion algorithm, the node coordinates in the topology map are converted to geographic coordinates in the GIS. This algorithm accounts for differences in coordinate systems between the topology map and the GIS, ensuring through precise calculations that the converted geographic coordinates accurately reflect the node's location in real space. Finally, based on the converted geographic coordinates, the actual geographic location corresponding to each initial network node is precisely determined in the GIS. These actual geographic locations serve as the initial candidate hydrogen refueling site addresses, providing the basis for subsequent adjustment and screening based on multi-source data.

[0027] Step S300: adjusting each initial candidate hydrogen refueling site address according to a multi-source data set to obtain a plurality of corresponding target candidate hydrogen refueling site addresses, wherein the multi-source data set includes industrial data, traffic data, environmental data, economic data, and safety data; It can be understood that the initial candidate hydrogen refueling station address is the location of the hydrogen refueling station obtained by the relevant planners based on experience or demand. It does not take into account factors such as the economic benefits and environmental impact of the hydrogen refueling station. In other words, the initial candidate hydrogen refueling station address does not match the actual demand.

[0028] In order to achieve an accurate match between hydrogen energy supply and actual terminal demand, after obtaining the initial candidate hydrogenation site addresses, this application adjusts each initial candidate hydrogenation site address according to the multi-source data set to obtain multiple corresponding target candidate hydrogenation site addresses. Figure 1 After extracting and spatially mapping the initial candidate hydrogenation site addresses Z1, Z2, Z3, and Z4 from the topological map, it is necessary to adjust each of these initial candidate hydrogenation site addresses to obtain multiple corresponding target candidate hydrogenation site addresses. That is, for initial candidate hydrogenation site address Z1, multiple corresponding target candidate hydrogenation site addresses can be obtained after adjustment. Similarly, for initial candidate hydrogenation site addresses Z2, Z3, or Z4, multiple corresponding target candidate hydrogenation site addresses can also be obtained.

[0029] In this embodiment, a refined adjustment is made to each initial candidate hydrogenation site address to generate multiple corresponding target candidate hydrogenation site addresses. This greatly enriches the range of options for subsequent screening of the final target hydrogenation site address, providing more diverse and high-quality alternatives for scientific decision-making.

[0030] like Figure 3 As shown, in one embodiment, step S300: adjusting each initial candidate hydrogenation site address according to the multi-source data set to obtain multiple corresponding target candidate hydrogenation site addresses includes: S310: Construct a multi-source data evaluation model for each initial candidate hydrogen refueling site address; Specifically, multi-source datasets can include five key categories of information: industrial data, transportation data, environmental data, economic data, and safety data. Industrial data can include existing hydrogen energy industry data (such as the number or location of logistics parks, ports, and heavy truck bases) and future industry planning data (such as site selection data for water electrolysis hydrogen production projects). Transportation data can include highway network topology, traffic flow (by time period), and service area / hub node coordinates. Environmental data can include regional carbon emission intensity, land use type, and ecological protection zone boundaries. Economic data can include land costs, equipment investment (compressor / storage tank unit price), and operating costs (labor / electricity prices). Safety data can include the distribution of sensitive facilities (schools / hospitals) and historical accident data.

[0031] The evaluation index weights represent the importance of the above five types of data in the comprehensive evaluation of the initial candidate hydrogen refueling station addresses. For example, if the hydrogen energy industry in a certain area (i.e., the area where the initial candidate hydrogen refueling station address is located) is developing rapidly, the impact of industrial data on the site selection of the hydrogen refueling station may be greater, and the corresponding evaluation index weight of the industrial data will be relatively high; in some transportation hub areas, the importance of traffic data may be more prominent, and the corresponding evaluation index weight will occupy a larger proportion. The determination of these weights can be based on a comprehensive consideration of multiple factors such as expert experience, historical data analysis, and actual planning needs. After the corresponding weights are determined, they can be stored in the memory and directly retrieved from the memory when needed.

[0032] It is understandable that due to the different actual conditions in different regions (regions where different initial candidate hydrogen refueling station addresses are located), it is necessary to construct a multi-source data evaluation model that is adapted to each initial candidate hydrogen refueling station address.

[0033] When building a multi-source data evaluation model, the corresponding evaluation indicator weights are first obtained from the memory, and then the multi-source data evaluation model is built based on these evaluation indicator weights.

[0034] In the embodiment of the present application, the multi-source data evaluation model satisfies the following expression: S=X*α1*(1+K1*F z )+Y*α2(1+K2*F z )+A*α3(1+K3*F z)+B*α4(1+K4*F z )+C*α5(1+K5*F z ).

[0035] Where S is the comprehensive score, which is the final output of the entire evaluation model and is used to quantify the suitability of each initial candidate hydrogen refueling site after considering multiple data sources. A higher comprehensive score indicates that the initial candidate site is more suitable as a hydrogen refueling site.

[0036] X represents the industry data score, reflecting the suitability of the initial candidate location's industrial development for hydrogen refueling station selection. For example, if the surrounding area is home to a large number of hydrogen production companies and hydrogen refueling equipment manufacturing bases, the industry data score will be high; conversely, if the industrial foundation is weak, the score will be low.

[0037] Y represents the traffic data score, which reflects the accessibility of the address, including road conditions, public transportation coverage, and proximity to major transportation arteries. Good traffic conditions facilitate the transportation of materials and the entry and exit of vehicles at the hydrogen refueling station, so the traffic data score is an important evaluation indicator.

[0038] A represents the environmental data score, which reflects the environmental impact of the hydrogen refueling station's construction and operation. The environmental data score covers aspects such as the surrounding ecological environment, land use planning, and environmental protection requirements. For example, the more fragile the environment in a region, the lower the environmental data score will be.

[0039] B is the economic data score, which mainly evaluates the construction cost, operating cost and expected economic benefits of the site. This includes land prices, construction material costs, energy supply costs, and future market demand and revenue forecasts for hydrogen refueling services.

[0040] C represents the safety data score, which considers safety factors such as the address's distance from surrounding sensitive areas, geological stability, and fire safety facilities. The greater the impact on the safety of surrounding sensitive areas, the lower the score. Alternatively, the worse the geological stability, the lower the score.

[0041] α1-α5 are the evaluation indicator weights corresponding to industrial data, traffic data, environmental data, economic data, and safety data, respectively. They represent the importance of these five types of data in the comprehensive evaluation of the initial candidate hydrogen refueling station locations.

[0042] F z=area characteristic factors. Different regions have different characteristics and development needs, and regional characteristic factors are used to reflect these differences. For example, the regional characteristic factors of urban core areas and suburban areas may be different. Urban core areas may place more emphasis on transportation convenience and economic data, while suburban areas may focus more on environmental data and industrial development potential. For example, the greater the focus on industrial development in a region, the greater the weight of industrial data in the corresponding model.

[0043] Regional characteristic factor F z The value of can be obtained by referring to the preset mapping table. Since different focus points are associated with different regional characteristics, the corresponding regional characteristic factor values will also be different.

[0044] k1-k5 are the sensitivity coefficients of each data category weight to regional characteristic factors. They indicate the sensitivity of each data category weight to changes in regional characteristic factors. For example, in certain regions, the weight of industrial data may be more sensitive to changes in regional characteristic factors, that is, the value of K1 is larger, which means that changes in regional characteristics will significantly affect the weight of industrial data in the comprehensive evaluation.

[0045] For example, Figure 1 As shown in the figure, the area where hydrogenation station Z1 is located pays more attention to industrial development. The characteristic factor F z The value of is 2, and the weight of industrial data is more sensitive to changes in regional characteristic factors. Therefore, K1 can be set to 0.1, K2 can be set to -0.025, K3 can be set to -0.025, K4 can be set to -0.025, and K5 can be set to -0.025.

[0046] In this way, the embodiment of the present application dynamically adjusts the weight according to the regional characteristic factor. When the regional characteristic factor changes, the weight of this type of data will change accordingly through the effect of the sensitivity coefficient K, thereby more accurately reflecting the impact of different regional characteristics on the importance of various types of data.

[0047] In other embodiments, regional differences may not be considered. In this way, the multi-source data evaluation model satisfies the expression: S=X*α1*+Y*α2+A*α3+B*α4+C*α5.

[0048] S320. Use a search algorithm to perform a target search on a preset range area of each initial candidate hydrogenation site address to obtain a plurality of corresponding target candidate hydrogenation site addresses, wherein the comprehensive score value of each target candidate hydrogenation site address under the multi-source data evaluation model is within a set range.

[0049] Specifically, the preset range area of each initial candidate hydrogen refueling site address can be divided into M*N grids, each grid represents a candidate hydrogen refueling site address, where M and N are both greater than or equal to 10; then the comprehensive score value of each candidate hydrogen refueling site address under the multi-source data evaluation model is calculated; finally, the candidate hydrogen refueling site addresses with comprehensive score values within the set range are screened out as the target candidate hydrogen refueling site addresses.

[0050] like Figure 4 As shown, the middle rectangular box is an initial candidate hydrogenation station, and the outermost circle is the preset range area of the initial candidate hydrogenation station (such as a 5-kilometer range). The preset range area is divided into 10*10 grids (for simplicity, Figure 4 (The network is only divided into 4*8 grids). For example, grids W1 and W2 are both candidate hydrogen refueling station addresses.

[0051] In other embodiments, the preset range area of the initial candidate hydrogen refueling site may also be a rectangular area.

[0052] It should be noted that the industrial data score, traffic data score, environmental data score, economic data score, and safety data score corresponding to each grid can be pre-calibrated according to actual conditions.

[0053] Therefore, during the search, the algorithm uses pre-calibrated industry data scores, traffic data scores, environmental data scores, economic data scores, safety data scores, and a multi-source data evaluation model to retrieve grids with comprehensive scores within a set range. In other words, candidate hydrogen refueling station addresses with comprehensive scores within a set range (e.g., between 80 and 95) are selected as target candidate hydrogen refueling station addresses.

[0054] Thus, the embodiment of the present application selects candidate hydrogenation site addresses that meet the preset conditions as target candidate hydrogenation site addresses, for example, selecting candidate hydrogenation site addresses with a comprehensive score between 80 and 95 (corresponding to Figure 4 The grids that meet the comprehensive score in the 3D image are selected as the target candidate hydrogenation site addresses, which provides a basis for the subsequent screening of target hydrogenation sites according to the preset constraints.

[0055] Step S400: Filter the multiple target candidate hydrogenation station addresses according to preset constraints to obtain a target hydrogenation station address, wherein the preset constraints include at least one of a rigid constraint and a flexible constraint, wherein the rigid constraint includes a distance restriction between the hydrogenation station and surrounding sensitive areas, and the flexible constraint includes a single station service radius restriction; It is understood that in step S300, multiple target candidate hydrogenation site addresses that meet the comprehensive scoring criteria are obtained for each initial candidate hydrogenation site address. Therefore, in order to obtain a more accurate target hydrogenation site address, further screening is required among the multiple target candidate hydrogenation site addresses.

[0056] In one embodiment, the step S400 of screening the plurality of target candidate hydrogenation site addresses according to preset constraints to obtain the target hydrogenation site address includes: For rigid constraints, the distance restrictions between hydrogen refueling stations and surrounding sensitive areas are converted into spatial buffer analysis, and the target candidate hydrogen refueling station addresses located within the buffer zone of sensitive areas are eliminated; For flexible constraints, a service area is constructed with each target candidate hydrogen refueling station address as the center and the single station service radius as the radius. The number of potential hydrogen refueling demand points in each service area is counted, and the target candidate hydrogen refueling station addresses with a corresponding service area where the number of potential hydrogen refueling demand points is less than the preset threshold are eliminated. The final target hydrogen refueling station address is obtained by combining the screening results of rigid constraints and flexible constraints.

[0057] Specifically, for rigid constraints, the embodiments of the present application mainly focus on the distance limit between hydrogen refueling stations and surrounding sensitive areas. In actual operation, this distance limit is converted into a spatial buffer analysis. Spatial buffer analysis is a common technology in geographic information systems (GIS), which can create a buffer zone with a certain width around sensitive areas. The width of this buffer zone is the minimum allowable distance between the hydrogen refueling station and the sensitive area. Through spatial buffer analysis, the system can automatically identify the target candidate hydrogen refueling station addresses located in the buffer zone of the sensitive area. These addresses are too close to the sensitive area and may pose potential threats to the safety, environment and other aspects of the sensitive area, so they need to be eliminated. For example, if the sensitive area is a school or hospital, the proximity of the hydrogen refueling station may pose a safety risk, so the distance limit must be strictly observed to ensure that the construction of the hydrogen refueling station will not have an adverse impact on the sensitive area.

[0058] For flexible constraints, the embodiment of the present application takes each target candidate hydrogen refueling station address as the center and constructs a service area with a single station service radius as the radius. The single station service radius is determined based on factors such as the service capacity of the hydrogen refueling station and the surrounding traffic conditions. It represents the range that the hydrogen refueling station can effectively serve. By constructing the service area, the potential service range of each target candidate address can be intuitively understood. The number of potential hydrogen refueling demand points in each service area is counted. Potential hydrogen refueling demand points can be existing hydrogen vehicle concentration areas, planned hydrogen energy industry projects, etc. The number of these demand points reflects the scale of hydrogen refueling demand in the service area. A preset threshold is set. If the number of potential hydrogen refueling demand points in the service area corresponding to a target candidate hydrogen refueling station address is less than this preset threshold, it means that the service demand for the address is insufficient, and the construction of a hydrogen refueling station may cause a waste of resources, so it is eliminated. For example, if the preset threshold is 100 potential demand points, and there are only 50 potential demand points in the service area of a target candidate address, then the address does not meet the requirements of the flexible constraint and needs to be eliminated.

[0059] After eliminating target candidate hydrogen refueling site addresses located in sensitive area buffer zones and eliminating target candidate hydrogen refueling site addresses with insufficient potential service demand, the final target hydrogen refueling site address can be determined from the remaining target candidate hydrogen refueling site addresses, such as randomly selecting one of them as the target hydrogen refueling site address, or the selection authority can be sent to relevant planners, who select one of the remaining target candidate hydrogen refueling site addresses as the target hydrogen refueling site address based on their experience.

[0060] In one embodiment, the number of potential hydrogen refueling demand points in each service area is counted, including: determining basic hydrogen refueling demand points in each service area according to the hydrogen vehicle penetration rate increase index, wherein the basic hydrogen refueling demand points are positively correlated with the hydrogen vehicle penetration rate increase index; determining additional hydrogen refueling demand points in each service area according to the hydrogen energy price fluctuation index; and determining the number of potential hydrogen refueling demand points in each service area according to the basic hydrogen refueling demand points and the additional hydrogen refueling demand points.

[0061] Specifically, the hydrogen vehicle penetration rate increase index reflects the growing popularity of hydrogen vehicles in a specific area. Since a higher hydrogen vehicle penetration rate means more potential users of hydrogen vehicles in the area, the demand for hydrogen refueling will also be greater. Therefore, the basic hydrogen refueling demand points are positively correlated with the hydrogen vehicle penetration rate increase index. For example, within a certain service area, if the hydrogen vehicle penetration rate increase index is high, it means that the number of users using hydrogen vehicles in the area may increase significantly in the future, and the basic hydrogen refueling demand points in the area will be correspondingly higher.

[0062] The hydrogen price volatility index reflects changes in hydrogen prices over a specific period. Large fluctuations in hydrogen prices may affect user demand for hydrogen refueling. For example, if hydrogen prices are expected to fall, some users who originally had less urgent hydrogen refueling needs may increase their demand due to price factors. Conversely, if prices are expected to rise, this may suppress demand from some users.

[0063] For example, a relationship model between basic hydrogen refueling demand points and the hydrogen vehicle penetration rate increase index is established in advance, and a relationship model between additional hydrogen refueling demand points and the hydrogen energy price fluctuation index is established in advance. According to the hydrogen vehicle penetration rate increase index and the hydrogen energy price fluctuation index in the next 1-2 years, the number of basic hydrogen refueling demand points and the number of additional hydrogen refueling demand points can be obtained.

[0064] In one embodiment, the method of determining the number of potential hydrogenation demand points in each service area based on the basic hydrogenation demand points and the additional hydrogenation demand points includes: obtaining initial reference weights of the basic hydrogenation demand points and the additional hydrogenation demand points, and the sum of the initial reference weights is 1; adjusting the initial reference weights according to population density data to obtain target reference weights of the basic hydrogenation demand points and the additional hydrogenation demand points; and obtaining the number of potential hydrogenation demand points according to the basic hydrogenation demand points, the additional hydrogenation demand points and the corresponding target reference weights.

[0065] Specifically, the initial reference weight is a preliminary setting of the relative importance of basic hydrogenation demand points and additional hydrogenation demand points in the number of potential hydrogenation demand points. For example, it can be preliminarily assumed that the importance of basic hydrogenation demand points and additional hydrogenation demand points is equal, so their initial reference weights can both be set to 0.5.

[0066] Population density data reflects the density of the population within the service area. Generally speaking, higher population density areas are likely to have more concentrated and intense demand for hydrogen refueling. For example, in urban core areas, where population density is high and vehicle use is frequent, hydrogen refueling demand may be more strongly influenced by demographic factors. Therefore, the initial reference weights can be adjusted based on population density data. For example, for areas with a population density greater than a certain value, the importance of basic hydrogen refueling demand points (reference weight) can be increased, while the importance of additional hydrogen refueling demand points (reference weight) can be decreased. Finally, the number of potential hydrogen refueling demand points is calculated based on the basic hydrogen refueling demand points, additional hydrogen refueling demand points, and their corresponding target reference weights. The specific calculation formula can be: Number of potential hydrogen refueling demand points = Number of basic hydrogen refueling demand points × Target reference weight of basic hydrogen refueling demand points + Number of additional hydrogen refueling demand points × Target reference weight of additional hydrogen refueling demand points. This formula comprehensively considers the impact of basic hydrogen refueling demand points, additional hydrogen refueling demand points, and population density to determine the number of potential hydrogen refueling demand points within each service area.

[0067] In this way, by counting the number of potential hydrogen refueling demand points through the above method, the scale of hydrogen refueling demand in each service area can be assessed more scientifically and accurately. In the process of hydrogen refueling station site selection, the number of potential hydrogen refueling demand points can be used to screen out target candidate addresses with sufficient service demand, avoid building hydrogen refueling stations in areas with insufficient demand, improve resource utilization efficiency, and optimize the layout of the hydrogen refueling network. For example, when planning a city's hydrogen refueling network, priority should be given to building hydrogen refueling stations in service areas with a large number of potential hydrogen refueling demand points to meet the hydrogen refueling needs of the area and promote the development of the hydrogen energy industry.

[0068] Step S500: Generate a hydrogenation network distribution route map based on the addresses of the multiple target hydrogenation stations.

[0069] Specifically, after screening out multiple target hydrogenation site addresses in step S400, the embodiment of the present application constructs an intuitive and reasonable hydrogenation network distribution route map based on the multiple target hydrogenation site addresses, providing clear guidance for subsequent actual construction and operation.

[0070] Based on this, the embodiment of the present application provides a method for hydrogenation network distribution planning based on multi-source data. First, the preliminary planned hydrogenation network route, i.e., the initial hydrogenation site topology map, is obtained. A plurality of initial candidate hydrogenation site addresses are obtained through spatial mapping. Then, the initial candidate addresses are adjusted based on multi-source data sets such as industry, transportation, environment, economy, and safety to obtain target candidate addresses. Then, the target hydrogenation site addresses are screened out based on preset conditions including rigid (such as distance restrictions from surrounding sensitive areas) and flexible (such as single-station service radius restrictions) constraints. Finally, a hydrogenation network distribution route map is generated based on these target addresses. In this way, the technical solution of the present application, based on manual preliminary planning, comprehensively considers various factors, and automatically screens out target hydrogenation addresses that meet the conditions, making the site selection of hydrogenation sites more scientific and reasonable. It can not only achieve accurate matching of hydrogen energy supply and terminal demand, but also improve the efficiency of hydrogenation network distribution planning.

[0071] like Figure 5 As shown, Figure 5 The present invention provides a hardware structure diagram of an electronic device in some embodiments of the present invention. The electronic device provided in the embodiments of the present invention includes: a map acquisition module 100 for acquiring an initial hydrogenation site topology map; a spatial mapping module 200 for spatially mapping the initial hydrogenation site topology map to obtain multiple initial candidate hydrogenation site addresses; an adjustment module 300 for adjusting each initial candidate hydrogenation site address based on a multi-source data set to obtain multiple corresponding target candidate hydrogenation site addresses; a screening module 400 for screening multiple target candidate hydrogenation site addresses based on preset constraints to obtain a target hydrogenation site address; and a route map generation module 500 for generating a hydrogenation network distribution route map based on the multiple target hydrogenation site addresses.

[0072] An embodiment of the present application also provides a hydrogenation network distribution planning system, which includes a memory 1000 and a processor 2000, wherein the memory 1000 is used to store computer-readable instructions, and the processor 2000 is used to call the computer-readable instructions to execute the hydrogenation network distribution planning method based on multi-source data as described above.

[0073] Among them, the processor 2000 is used to provide computing and control capabilities to control the hydrogenation network distribution planning system to perform corresponding tasks, for example, controlling the hydrogenation network distribution planning system to perform the hydrogenation network distribution planning method based on multi-source data in any of the above method embodiments, the method including: obtaining an initial hydrogenation site topology map, the initial hydrogenation site topology map is a preliminary planned hydrogenation network route; spatially mapping the initial hydrogenation site topology map to obtain multiple initial candidate hydrogenation site addresses; adjusting each initial candidate hydrogenation site address according to the multi-source data set to obtain multiple corresponding target candidate hydrogenation site addresses, wherein the multi-source data set includes industrial data, traffic data, environmental data, economic data and safety data; screening the multiple target candidate hydrogenation site addresses according to preset constraints to obtain target hydrogenation site addresses, the preset constraints including at least one of rigid constraints and flexible constraints, the rigid constraints including the distance limit between the hydrogenation site and the surrounding sensitive areas, and the flexible constraints including the single-station service radius limit; generating a hydrogenation network distribution route map based on the multiple target hydrogenation site addresses.

[0074] Processor 2000 may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), a hardware chip, or any combination thereof; it may also be a digital signal processing (DSP), an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or any combination thereof. The PLD may be a complex programmable logic device (CPLD), a field-programmable gate array (FPGA), a generic array logic (GAL), or any combination thereof.

[0075] Memory 1000, as a non-transitory computer-readable storage medium, may be used to store non-transitory software programs, non-transitory computer-executable programs, and modules, such as the program instructions / modules corresponding to the multi-source data-based hydrogenation network distribution planning method in the embodiments of the present application. Processor 2000, by executing the non-transitory software programs, instructions, and modules stored in memory 1000, may implement the multi-source data-based hydrogenation network distribution planning method in any of the aforementioned method embodiments.

[0076] Specifically, the memory 1000 may include a volatile memory (VM), such as a random access memory (RAM); the memory 1000 may also include a non-volatile memory (NVM), such as a read-only memory (ROM), a flash memory, a hard disk drive (HDD) or a solid-state drive (SSD) or other non-transitory solid-state storage device; the memory 1000 may also include a combination of the above types of memory.

[0077] To sum up, the hydrogenation network distribution planning system of the present application adopts the technical solution of any one of the above-mentioned hydrogenation network distribution planning method embodiments based on multi-source data. Therefore, it has at least the beneficial effects brought by the technical solutions of the above-mentioned embodiments, which will not be described one by one here.

[0078] The present application also provides a computer-readable storage medium, such as a memory device including program code. The program code can be executed by a processor to implement the multi-source data-based hydrogenation network distribution planning method described in the above embodiment. For example, the computer-readable storage medium can be a read-only memory (ROM), a random access memory (RAM), a compact disc read-only memory (CDROM), a magnetic tape, a floppy disk, or an optical data storage device.

[0079] The present application also provides a computer program product comprising one or more program codes stored in a computer-readable storage medium. A processor of the hydrogenation network distribution planning system reads the program code from the computer-readable storage medium and executes the program code to perform the steps of the multi-source data-based hydrogenation network distribution planning method provided in the above embodiment.

[0080] Those skilled in the art will understand that all or part of the steps of implementing the above embodiments can be completed by hardware, or by hardware related to program code, and the program can be stored in a computer-readable storage medium. The above-mentioned storage medium can be a read-only memory, a disk or an optical disk, etc.

[0081] It should be noted that the device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of this embodiment.

[0082] Through the description of the above embodiments, it is clear to those skilled in the art that each embodiment can be implemented by means of software plus a general hardware platform, or of course by hardware. It is understood by those skilled in the art that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. The storage medium can be a magnetic disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM).

[0083] The above description is only a preferred embodiment of the present invention and does not limit the patent scope of the present invention. All equivalent structural transformations made by using the contents of the present invention description and drawings under the inventive concept of the present invention, or direct / indirect application in other related technical fields are included in the patent protection scope of the present invention.

Claims

1. A hydrogenation network distribution planning method based on multi-source data, characterized in that: The method comprises: Obtaining an initial hydrogenation site topology map, wherein the initial hydrogenation site topology map is a preliminarily planned hydrogenation network route; Performing spatial mapping on the initial hydrogenation site topology map to obtain multiple initial candidate hydrogenation site addresses; Adjusting each initial candidate hydrogen refueling site address according to a multi-source data set to obtain a plurality of corresponding target candidate hydrogen refueling site addresses, wherein the multi-source data set includes industrial data, traffic data, environmental data, economic data, and safety data; The target hydrogenation site address is obtained by screening the multiple target candidate hydrogenation site addresses according to preset constraints, wherein the preset constraints include at least one of a rigid constraint and a flexible constraint, wherein the rigid constraint includes a distance restriction between the hydrogenation site and surrounding sensitive areas, and the flexible constraint includes a single-site service radius restriction; A hydrogenation network distribution route map is generated based on the multiple target hydrogenation site addresses.

2. The hydrogenation network distribution planning method based on multi-source data according to claim 1, characterized in that: The adjusting of each initial candidate hydrogenation site address according to the multi-source data set to obtain a plurality of corresponding target candidate hydrogenation site addresses includes: For each initial candidate hydrogen refueling site address, a multi-source data evaluation model is constructed; A search algorithm is used to perform a target search on a preset range area of each initial candidate hydrogenation site address to obtain multiple corresponding target candidate hydrogenation site addresses, wherein the comprehensive score value of each target candidate hydrogenation site address under the multi-source data evaluation model is within a set range.

3. The hydrogenation network distribution planning method based on multi-source data according to claim 2, characterized in that: For each initial candidate hydrogen refueling site address, a multi-source data evaluation model is constructed, including: Obtain the evaluation index weights corresponding to industrial data, traffic data, environmental data, economic data and safety data in multi-source data sets; A multi-source data evaluation model is constructed according to the evaluation index weights; wherein the multi-source data evaluation model satisfies the following expression: S=X*α1*(1+K1*F z )+Y*α2(1+K2*F z )+A*α3(1+K3*F z )+B*α4(1+K4*F z )+C*α5(1+K5*F z ), where S is the comprehensive score, X is the industry data score, Y is the traffic data score, A is the environmental data score, B is the economic data score, C is the safety data score, α1-α5 are the corresponding evaluation index weights, F z is the regional characteristic factor, and k1−k5 are the sensitivity coefficients of each data category weight to the regional characteristic factor.

4. The hydrogenation network distribution planning method based on multi-source data according to claim 3, characterized in that: The method of using a search algorithm to perform a target search on a preset range of each initial candidate hydrogenation site address to obtain a plurality of corresponding target candidate hydrogenation site addresses includes: Divide the preset range of each initial candidate hydrogen refueling site address into M*N grids, each grid representing a candidate hydrogen refueling site address, where M and N are both greater than or equal to 10; Calculate the comprehensive score of each candidate hydrogen refueling station address under the multi-source data evaluation model; The candidate hydrogenation site addresses with comprehensive score values within the set range are screened out as target candidate hydrogenation site addresses.

5. The hydrogenation network distribution planning method based on multi-source data according to claim 1, characterized in that: The step of screening the plurality of target candidate hydrogenation site addresses according to the preset constraint conditions to obtain the target hydrogenation site address includes: For rigid constraints, the distance restrictions between hydrogen refueling stations and surrounding sensitive areas are converted into spatial buffer analysis, and the target candidate hydrogen refueling station addresses located within the buffer zone of sensitive areas are eliminated; For flexible constraints, a service area is constructed with each target candidate hydrogen refueling station address as the center and the single station service radius as the radius. The number of potential hydrogen refueling demand points in each service area is counted, and the target candidate hydrogen refueling station addresses with a corresponding service area where the number of potential hydrogen refueling demand points is less than the preset threshold are eliminated. The final target hydrogen refueling station address is obtained by combining the screening results of rigid constraints and flexible constraints.

6. The hydrogenation network distribution planning method based on multi-source data according to claim 5, characterized in that: The statistics of the number of potential hydrogen refueling demand points in each service area include: Determine the basic hydrogen refueling demand point in each service area according to the hydrogen vehicle penetration rate increase index, wherein the basic hydrogen refueling demand point is positively correlated with the hydrogen vehicle penetration rate increase index; Determine additional hydrogen refueling demand points within each service area based on the hydrogen price fluctuation index; Determine the number of potential hydrogenation demand points in each service area based on the basic hydrogenation demand points and additional hydrogenation demand points.

7. The hydrogenation network distribution planning method based on multi-source data according to claim 6, characterized in that: The number of potential hydrogenation demand points within each service area is determined based on the basic hydrogenation demand points and the additional hydrogenation demand points, including: Obtain the initial reference weights of the basic hydrogenation demand point and the additional hydrogenation demand point, and the sum of the initial reference weights is 1; Adjusting the initial reference weights according to population density data to obtain target reference weights for basic hydrogenation demand points and additional hydrogenation demand points; The number of potential hydrogenation demand points is obtained according to the basic hydrogenation demand points, the additional hydrogenation demand points and the corresponding target reference weights.

8. The hydrogenation network distribution planning method based on multi-source data according to claim 1, characterized in that: The spatial mapping of the initial hydrogenation site topology map to obtain multiple initial candidate hydrogenation site addresses includes: Identifying and extracting network nodes in the initial hydrogenation site topology map to obtain a plurality of initial network nodes; Associating the plurality of initial network nodes with a geographic information system, and converting the node coordinates in the topological map into geographic coordinates in the GIS using a coordinate conversion algorithm; According to the converted geographic coordinates, the actual geographic location corresponding to each initial network node is determined in GIS to obtain multiple initial candidate hydrogen refueling site addresses.

9. An electronic device, characterized in that: include: A map acquisition module is used to obtain an initial hydrogenation station topology map; A spatial mapping module is used to perform spatial mapping on the initial hydrogenation site topology map to obtain multiple initial candidate hydrogenation site addresses; An adjustment module, configured to adjust each initial candidate hydrogenation site address according to a multi-source data set to obtain a plurality of corresponding target candidate hydrogenation site addresses; A screening module is used to screen multiple target candidate hydrogenation site addresses according to preset constraints to obtain a target hydrogenation site address; The route map generation module is used to generate a hydrogenation network distribution route map based on the addresses of multiple target hydrogenation stations.

10. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 8 are implemented.

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