Low-carbon path optimization method and device for sustainable aviation fuel supply chain network, equipment and storage medium

Abstract

The invention discloses a low-carbon path optimization method and device for a sustainable aviation fuel supply chain network, equipment and a storage medium. The method comprises the steps that spatial distribution information and carbon emission factors of related objects of the sustainable aviation fuel supply chain network are acquired; clustering based on biomass raw material yield distribution by adopting a yield weighted clustering method, determining the initial position of the biomass raw material collection station, and determining the final position of the biomass raw material collection station based on the initial position and the railway buffer area; constructing a sustainable aviation fuel supply chain network; and constructing a carbon emission model of the sustainable aviation fuel supply chain network on the basis of the sustainable aviation fuel supply chain network, and performing optimization solution on the carbon emission model to obtain an optimal low-carbon path scheme of the sustainable aviation fuel supply chain network. Therefore, a reasonable low-carbon path scheme can be provided, and carbon emission can be further reduced.

Description

Technical Field

[0001] This application relates to the field of low-carbon optimization technology, and in particular to a method, apparatus, equipment and storage medium for low-carbon pathway optimization of a sustainable aviation fuel supply chain network. Background Technology

[0002] With the rapid development of the aviation industry, the massive consumption of traditional fossil aviation fuels has led to a continuous increase in greenhouse gas emissions in the aviation sector, putting significant pressure on the environment. Developing sustainable aviation fuels is an important way to reduce emissions in the aviation sector in the future.

[0003] However, the large-scale application of sustainable aviation fuel still faces multiple challenges, stemming from the collection of biomass feedstocks, the selection of refineries, airport requirements, and constraints on transportation routes. Therefore, optimizing the low-carbon pathways of the sustainable aviation fuel supply chain network is particularly important, but existing technologies are unable to provide reasonable low-carbon pathway solutions. Summary of the Invention

[0004] This application provides a method, apparatus, equipment, and storage medium for optimizing low-carbon pathways in a sustainable aviation fuel supply chain network. It can provide reasonable low-carbon pathway schemes and further reduce carbon emissions.

[0005] In a first aspect, embodiments of this application provide a low-carbon pathway optimization method for a sustainable aviation fuel supply chain network, including:

[0006] Acquire spatial distribution information of relevant objects in the sustainable aviation fuel supply chain network and carbon emission factors at each stage of the sustainable aviation fuel supply chain network's life cycle; wherein, the spatial distribution information includes the distribution of biomass feedstock production in the target area, the distribution of soil carbon sequestration rate at biomass feedstock sites, railway distribution, highway distribution, refined oil pipeline distribution, refinery distribution, and airport distribution;

[0007] A production-weighted clustering method is used to cluster the biomass raw material production distribution to form several preset clusters. The cluster center of each cluster is used as the initial position of the biomass raw material collection station corresponding to the biomass raw material point within the cluster. A railway buffer zone is determined based on the railway distribution, and the final position of the biomass raw material collection station is determined based on the initial position and the railway buffer zone.

[0008] The sustainable aviation fuel supply chain network is constructed based on one of the biomass feedstock production distribution or the soil carbon sequestration rate distribution, the final location of the biomass feedstock collection station, the railway distribution, the highway distribution, the refined oil pipeline distribution, the oil refinery distribution, and the airport distribution;

[0009] A carbon emission model for the sustainable aviation fuel supply chain network is constructed based on the sustainable aviation fuel supply chain network, the carbon emission factor, and the distribution of soil carbon sequestration rate. The carbon emission model is then optimized and solved to obtain the optimal low-carbon pathway scheme for the sustainable aviation fuel supply chain network.

[0010] Secondly, embodiments of this application provide a low-carbon pathway optimization device for a sustainable aviation fuel supply chain network, comprising:

[0011] The acquisition module is used to acquire spatial distribution information of objects related to the sustainable aviation fuel supply chain network and carbon emission factors at each stage of the sustainable aviation fuel supply chain network's life cycle; wherein, the spatial distribution information includes the distribution of biomass feedstock production in the target area, the distribution of soil carbon sequestration rate at biomass feedstock sites, railway distribution, highway distribution, refined oil pipeline distribution, refinery distribution, and airport distribution;

[0012] The location determination module is used to cluster the biomass raw material production distribution based on the production weighting method using a production weighting method to form a number of preset clusters, take the cluster center of the cluster as the initial location of the biomass raw material collection station corresponding to the biomass raw material point within the cluster, determine the railway buffer zone based on the railway distribution, and determine the final location of the biomass raw material collection station based on the initial location and the railway buffer zone.

[0013] The network construction module is used to construct the sustainable aviation fuel supply chain network based on one of the biomass feedstock production distribution or the soil carbon sequestration rate distribution, the final location of the biomass feedstock collection station, the railway distribution, the highway distribution, the refined oil pipeline distribution, the refinery distribution, and the airport distribution;

[0014] The optimization module is used to construct a carbon emission model of the sustainable aviation fuel supply chain based on the sustainable aviation fuel supply chain network, the carbon emission factor, and the distribution of soil carbon sequestration rate, and to optimize and solve the carbon emission model to obtain the optimal low-carbon path scheme of the sustainable aviation fuel supply chain network.

[0015] Thirdly, embodiments of this application provide an electronic device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, it implements the method provided in embodiments of this application.

[0016] Fourthly, embodiments of this application provide a computer-readable storage medium having a computer program stored thereon, which, when executed in a computer, causes the computer to perform the method provided in embodiments of this application.

[0017] The technical solution provided in this application determines the initial location of biomass feedstock collection stations through a production-weighted clustering method. This allows the collection stations to be located closer to areas with higher biomass feedstock production, thereby reducing the average transportation distance from biomass feedstock points to the collection stations and decreasing carbon emissions during the transportation phase. This provides a reasonable spatial basis for low-carbon path planning in a sustainable aviation fuel supply chain network. By introducing a railway buffer zone as a constraint on the location of biomass feedstock collection stations, the stations are preferentially located within railway reach, increasing the utilization of railway transportation when transporting biomass feedstocks to downstream refineries and reducing reliance on road transportation, which has higher emissions per unit, further reducing carbon emissions during transportation and improving the overall efficiency of centralized collection and transportation of biomass feedstocks. This application also considers the distribution of biomass feedstock production or soil carbon sequestration rate, the final location of biomass feedstock collection stations, railway distribution, road distribution, refined oil pipeline distribution, refinery distribution, and airport distribution. This study constructs a sustainable aviation fuel supply chain network and its carbon emission model based on the distribution of the sustainable aviation fuel supply chain network, carbon emission factors, and soil carbon sequestration rates. Solving the carbon emission model yields the optimal low-carbon pathway, making the low-carbon pathway more rational and further reducing carbon emissions. In summary, by using a production-weighted clustering method and introducing railway buffer zones to determine the final location of biomass raw material collection stations, the site selection of these stations becomes more rational. This provides a reasonable spatial basis for the low-carbon pathway planning of the sustainable aviation fuel supply chain network and reduces reliance on road transportation, which has higher emissions per unit, further reducing carbon emissions during transportation. Furthermore, constructing a sustainable aviation fuel supply network based on the final location of biomass raw material collection stations yields a better sustainable aviation fuel supply network, enabling the construction of a more rational carbon emission model and the solution to obtain the optimal low-carbon pathway, making the low-carbon pathway more rational and further reducing carbon emissions. Attached Figure Description

[0018] Figure 1 A flowchart of a method for optimizing a low-carbon pathway in a sustainable aviation fuel supply chain, provided for the implementation of this application;

[0019] Figure 2 A structural block diagram of a low-carbon pathway optimization device for a sustainable aviation fuel supply chain provided in this application embodiment;

[0020] Figure 3 This is a schematic diagram of an electronic device structure provided in an embodiment of this application. Detailed Implementation

[0021] The present application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0022] Figure 1 This application provides a flowchart of a method for optimizing a low-carbon pathway in a sustainable aviation fuel supply chain. The method can be executed by a device for optimizing a low-carbon pathway in a sustainable aviation fuel supply chain. The device can be implemented by software and / or hardware and can be configured in electronic devices such as computers.

[0023] like Figure 1 As shown, the technical solutions provided in this application include:

[0024] S110: Obtain spatial distribution information of objects related to the sustainable aviation fuel supply chain network and carbon emission factors at each stage of the sustainable aviation fuel supply chain network's life cycle; wherein, the spatial distribution information includes the distribution of biomass feedstock production in the target area, the distribution of soil carbon sequestration rate at biomass feedstock sites, railway distribution, highway distribution, refined oil pipeline distribution, refinery distribution, and airport distribution.

[0025] In this embodiment, the sustainable aviation fuel supply chain network may include nodes and logistics between nodes; wherein, nodes may include the locations of biomass feedstock points, biomass feedstock collection stations, refineries, and airports. The target area may be the entire country or a region selected as needed; the distribution of biomass feedstock production may be the distribution of biomass feedstock production on marginal land, and may include the location information and corresponding production information of each biomass feedstock point in the target area; the distribution of soil carbon sequestration rate of biomass feedstock points may be the distribution of soil carbon sequestration rate of biomass feedstock points on marginal land, and may include the location information and corresponding soil carbon sequestration rate information of biomass feedstock points in the target area; wherein, biomass feedstock points may refer to spatial supply units of biomass feedstock; railway distribution may include the location information of railways in the target area; highway distribution information may include the location information of highways in the target area; refined oil pipeline distribution may include the location information of pipelines in the target area; refinery distribution may include the location information of refineries; airport distribution may include the location information of airports in the target area. Among them, the distribution of biomass feedstock production affects the location of candidate biomass feedstock collection stations; the distribution of carbon sequestration rate affects the final carbon negative amount of the sustainable aviation fuel supply chain network; the distribution of railways, highways, and refined oil pipelines affects carbon emissions from transportation routes; and the distribution of refineries and airports affects supply and demand allocation.

[0026] In this embodiment, the carbon emission factors include carbon emission factors of road transportation, carbon emission factors of rail transportation, carbon emission factors of pipeline transportation, carbon emission factors of biomass raw material planting and collection stages, and carbon emission factors of biomass raw materials in the refining stage.

[0027] S120: A production-weighted clustering method is used to cluster the biomass raw material production distribution to form several preset clusters. The cluster center of each cluster is used as the initial position of the biomass raw material collection station corresponding to the biomass raw material point within the cluster. A railway buffer zone is determined based on the railway distribution, and the final position of the biomass raw material collection station is determined based on the initial position and the railway buffer zone.

[0028] In this embodiment, the output-weighted clustering method can be the output-weighted K-means spatial clustering method.

[0029] Optionally, the yield-weighted clustering method clusters based on the biomass raw material yield distribution to form a preset number of clusters, including: determining biomass raw material points and their corresponding yields based on the biomass raw material yield distribution; randomly assigning a preset number of biomass raw material points as current cluster centers, and assigning each biomass raw material point to the nearest current cluster center to form a cluster; determining the yield-weighted average of the biomass raw material points in the clusters using the yield as the weight, updating the current cluster centers based on the yield-weighted average, and returning to the step of assigning each biomass raw material point to the nearest current cluster center, until the iteration termination condition is met, thereby obtaining the preset number of clusters.

[0030] Specifically, biomass feedstock points can have location attributes; determining a biomass feedstock point can be understood as determining its location. The preset quantity can be 100, or it can be other values.

[0031] Specifically, assigning each biomass raw material point to the nearest current cluster center to form a cluster may include clustering based on the following formula:

[0032] ;

[0033] ;

[0034] in, This is the index of the biomass raw material site; The index of the cluster; For iteration rounds; The number of clusters is the preset number; Biomass feedstock point Position coordinates; For the first In the first iteration, the... The location coordinates of the cluster center of a cluster can be regarded as the location coordinates of the current cluster center before the update; For the first In the first iteration, the... The longitude coordinates of the cluster centers of each cluster; For the first In the first iteration, the... The latitudinal coordinates of the cluster centers of each cluster; Biomass feedstock point With the The first iteration in the round The distance between the cluster centers of each cluster; For the first In the round of iteration, biomass raw material points The cluster number to which it belongs.

[0035] In this embodiment, optionally, updating the current cluster centers based on the output-weighted mean includes:

[0036] The current cluster centers are updated based on the following formula:

[0037] ;

[0038] in, In the first In the first iteration, the... The location coordinates of the cluster centers of each cluster, that is, the updated location coordinates of the current cluster centers; Biomass feedstock point The output; For the biomass raw material point Longitude coordinates; For the biomass raw material point Latitude coordinates; In the first In the first iteration, the... A collection of biomass feedstock points in a cluster.

[0039] Specifically, the iteration termination condition can be:

[0040] ;

[0041] in, This is the convergence threshold.

[0042] In this embodiment, after the iteration termination condition is met, several preset clusters are obtained, which can be achieved through the following formula:

[0043] ;

[0044] in, Biomass feedstock point The final cluster number to which it belongs; For the first The coordinates of the final cluster center locations of each cluster. Therefore, by using a production-weighted clustering method based on the distribution of biomass feedstock production, relatively concentrated biomass feedstock points with high production can be grouped into several clusters, allowing for more rational planning of the locations of biomass feedstock collection stations.

[0045] In this embodiment, optionally, determining the railway buffer zone based on the railway distribution includes: determining an area within a first preset distance from the railway based on the railway distribution, and using this area as the railway buffer zone. Determining the final location of the biomass raw material collection station based on the initial location and the railway buffer zone includes: if neither the initial location nor the biomass raw material points within the cluster fall within the railway buffer zone, projecting the initial location along the shortest distance to the boundary of the railway buffer zone, and if the projection distance does not exceed a second preset distance, using the projection point corresponding to the initial location as the final location of the biomass raw material collection station; or if the projection distance is greater than the second preset distance, using the initial location as the final location of the biomass raw material collection station; wherein, the projection distance is the distance between the initial location and the projection point; the second preset distance is greater than the first preset distance; if there are biomass raw material points within the cluster that fall within the railway buffer zone, selecting the biomass raw material point with the highest output as the final location of the biomass raw material collection station.

[0046] Specifically, to improve the transport accessibility of biomass raw material collection stations and reduce transportation carbon emissions, these stations must be located within railway buffer zones. If neither the initial location of the biomass raw material collection station nor the biomass raw material points within the cluster fall within the railway buffer zone, the initial location can be projected to the boundary of the railway buffer zone along the shortest distance principle. This involves calculating the closest point from the initial location to the nearest boundary of the railway buffer zone, which can then be used as the projection point corresponding to the initial location. If the projection distance does not exceed a second preset distance, this closest point is taken as the final location of the biomass raw material collection station to satisfy the constraints of the railway buffer zone. The first preset distance can be 3 km, or it can be selected according to actual needs; the second preset distance can be 15 km, or it can be selected according to actual needs. After determining the final location of the biomass raw material collection station, the biomass raw material points can be redistributed to the nearest collection station according to the shortest distance from each point, forming the final affiliation between the collection station and the biomass raw material points.

[0047] Therefore, by employing a production-weighted clustering method to determine the initial location of biomass feedstock collection stations, these stations are placed closer to areas with higher biomass feedstock production. This reduces the average transportation distance from biomass feedstock points to the collection stations, thereby decreasing carbon emissions during the biomass feedstock transportation phase and providing a reasonable spatial basis for low-carbon path planning in a sustainable aviation fuel supply chain. Simultaneously, introducing a railway buffer zone as a constraint on the location of biomass feedstock collection stations prioritizes their placement within railway reach. This increases the utilization of railway transportation when transporting biomass feedstocks to downstream refineries, reduces reliance on road transportation (which has higher emissions per unit), further reduces carbon emissions during transportation, and improves the overall efficiency of centralized collection and transportation of biomass feedstocks.

[0048] S130: Construct the sustainable aviation fuel supply chain network based on one of the biomass feedstock production distribution or the soil carbon sequestration rate distribution, the final location of the biomass feedstock collection station, the railway distribution, the highway distribution, the refined oil pipeline distribution, the refinery distribution, and the airport distribution.

[0049] In this embodiment, optionally, the construction of a sustainable aviation fuel supply chain network based on one of the biomass feedstock production distribution or the soil carbon sequestration rate distribution, the final location of the biomass feedstock collection station, the railway distribution, the highway distribution, the refined oil pipeline distribution, the refinery distribution, and the airport distribution includes: determining the location of biomass feedstock points based on one of the biomass feedstock production distribution or the soil carbon sequestration rate distribution, and determining the locations of refineries and airports respectively based on the refinery distribution and the airport distribution; using the locations of biomass feedstock points, the final locations of biomass feedstock collection stations, the refinery locations, and the airport locations as nodes of the sustainable aviation fuel supply chain network; establishing a highway transportation connection between the location of the biomass feedstock point and the final location of the biomass feedstock collection station based on the highway distribution, establishing a highway-railway transportation connection between the final location of the biomass feedstock collection station and the refinery location based on the highway distribution and the railway distribution, and establishing a highway, railway, and pipeline transportation connection between the location of the refinery and the airport based on the highway distribution, railway distribution, and refined oil pipeline distribution.

[0050] S140: Construct a carbon emission model for the sustainable aviation fuel supply chain network based on the sustainable aviation fuel supply chain network, the carbon emission factor, and the distribution of soil carbon sequestration rate, and optimize the carbon emission model to obtain the optimal low-carbon path scheme for the sustainable aviation fuel supply chain network.

[0051] In this embodiment, the annual net carbon emissions of a sustainable aviation fuel supply chain can be constructed based on the annual carbon emissions during the biomass raw material planting and collection stage, the annual carbon emissions during the transportation stage, the carbon emissions during the refining stage, and the negative carbon emissions during the soil carbon sequestration stage. An objective function is constructed with the goal of minimizing the annual net carbon emissions of the sustainable aviation fuel supply chain, and a carbon emission model of the sustainable aviation fuel supply chain network is constructed through the objective function and constraints.

[0052] In this embodiment, optionally, the objective function of the carbon emission model is:

[0053] ;

[0054] in, The annual net carbon emissions of a sustainable aviation fuel supply chain network; This refers to the annual carbon emissions during the planting and harvesting of biomass raw materials. This refers to the annual carbon emissions during the transportation phase. Carbon emissions during the refining stage; This refers to the negative carbon emissions during the soil carbon sequestration stage.

[0055] in; ;

[0056] in, An index of biomass raw material types; This is the index of the biomass raw material site; A collection of biomass raw material sites; A set of categories; Biomass feedstock point Types of supplies The amount of biomass raw materials; For type Carbon emission factors during the planting and collection of biomass raw materials;

[0057] in, ;

[0058] in, An index for modes of transport; For the index of the biomass raw material collection station; An index for oil refineries; For airport indexes; For the biomass raw material point To biomass raw material collection station The modes of transportation included The transport arc assembly; among which, biomass raw material collection stations To connect with biological raw material points The nearest biomass raw material collection station; For the biomass raw material point Biomass raw materials are transported via the aforementioned method Transported to the biomass raw material collection station The amount of raw materials; To the biomass feedstock point Biomass raw materials are transported via the aforementioned method Transported to the biomass raw material collection station In the case of the transportation method The transport distance of the transport arc; The transportation method carbon emission factors, , It is a collection of modes of transportation, which includes road transportation, rail transportation and pipeline transportation; For types Biomass feedstock from the biomass feedstock collection station To the refinery The transportation methods included The set of transport arcs; For types Biomass raw materials are transported via the aforementioned method From the biomass raw material collection station Transported to the refinery The amount of raw materials; For the biomass raw materials to be transported by the aforementioned method From the biomass raw material collection station Transported to the refinery In the case of the transportation method The transport distance of the transport arc; For originating from type Sustainable aviation fuel from biomass feedstock from the refinery Arrive at the airport The modes of transportation included The set of transport arcs; For originating from type Sustainable aviation fuel made from biomass feedstock is produced by the refinery. By transportation Transported to the airport The amount of fuel; To ensure sustainable aviation fuel from the refinery via the aforementioned transportation method Transported to the airport In this case, the mode of transportation The transport distance of the transport arc;

[0059] in, ;

[0060] in, For types Carbon emission factors of biomass feedstock during the refining stage;

[0061] in, ;

[0062] in, Indicates the conversion coefficient between carbon and carbon dioxide; For the biomass raw material point Soil carbon sequestration rate; For the biomass raw material point The planting area; For the biomass raw material point The actual supply; For the biomass raw material point The upper limit of the supply of biomass raw materials.

[0063] In this embodiment, optionally, the constraints of the carbon emission model are:

[0064] ;

[0065] ;

[0066] ;

[0067] ;

[0068] ;

[0069] ;

[0070] in, This indicates whether to select a biomass feedstock point. Planting; For distribution to the biomass raw material collection station A collection of biomass feedstock sites; For the biomass raw material collection station Processing capacity; Indicate whether to select the biomass raw material collection station. ; For the refinery Production capacity; Indicate whether to select the refinery. ; For types The conversion rate of biomass feedstock into sustainable aviation fuel; For the airport The demand for sustainable aviation fuel; For the collection of oil refineries; Meet at the airport.

[0071] In this embodiment, the carbon emission model can be solved using Gurobi mathematical programming optimization software to obtain the optimal solution for a low-carbon path in a sustainable aviation fuel supply chain.

[0072] The technical solution provided in this application determines the initial location of biomass feedstock collection stations through a production-weighted clustering method. This allows the collection stations to be located closer to areas with higher biomass feedstock production, thereby reducing the average transportation distance from biomass feedstock points to the collection stations and decreasing carbon emissions during the transportation phase. This provides a reasonable spatial basis for low-carbon path planning in a sustainable aviation fuel supply chain network. By introducing a railway buffer zone as a constraint on the location of biomass feedstock collection stations, the stations are preferentially located within railway reach, increasing the utilization of railway transportation when transporting biomass feedstocks to downstream refineries and reducing reliance on road transportation, which has higher emissions per unit, further reducing carbon emissions during transportation and improving the overall efficiency of centralized collection and transportation of biomass feedstocks. This application also considers the distribution of biomass feedstock production or soil carbon sequestration rate, the final location of biomass feedstock collection stations, railway distribution, road distribution, refined oil pipeline distribution, refinery distribution, and airport distribution. This study constructs a sustainable aviation fuel supply chain network and its carbon emission model based on the distribution of the sustainable aviation fuel supply chain network, carbon emission factors, and soil carbon sequestration rates. Solving the carbon emission model yields the optimal low-carbon pathway, making the low-carbon pathway more rational and further reducing carbon emissions. In summary, by using a production-weighted clustering method and introducing railway buffer zones to determine the final location of biomass raw material collection stations, the site selection of these stations becomes more rational. This provides a reasonable spatial basis for the low-carbon pathway planning of the sustainable aviation fuel supply chain network and reduces reliance on road transportation, which has higher emissions per unit, further reducing carbon emissions during transportation. Furthermore, constructing a sustainable aviation fuel supply network based on the final location of biomass raw material collection stations yields a better sustainable aviation fuel supply network, enabling the construction of a more rational carbon emission model and the solution to obtain the optimal low-carbon pathway, making the low-carbon pathway more rational and further reducing carbon emissions.

[0073] In this embodiment of the application, taking the national region as an example, the yield distribution and soil carbon sequestration rate distribution of four biomass raw materials planted on the marginal land of the country can be obtained. The yield potential, carbon sequestration potential and area are calculated as shown in Table 1. The yield potential is the sum of the unit yield of each biomass raw material point multiplied by the area of ​​the biomass raw material point when planting the four biomass raw materials. The soil carbon sequestration potential is the sum of the soil carbon sequestration rate of each biomass raw material point multiplied by the area of ​​the biomass raw material point.

[0074] Table 1

[0075] Biomass raw materials Production potential (Mt) Soil carbon sequestration potential (Mt C) Area (Mha) Arundodis 1354.36 191.22 76.79 Miscanthus 195.46 17.92 15.82 jatropha 6 2.39 7.26 Flaxseed 20.94 9.45 22.99

[0076] In this embodiment, as shown in Table 2, the sustainable aviation fuel biomass feedstock collection stations can be divided into three categories: small, medium, and large, based on their annual collection volume.

[0077] Table 2

[0078] scale Biomass feedstock collection volume (Mt) small ≤8 medium 8-15 Large 15-25

[0079] The study scenario for this example can be set in 2050, with a national sustainable aviation fuel refueling rate of 70%. The refineries and airports in this example can be considered only as existing facilities. The annual processing capacity of some refineries is shown in Table 3. The projected national sustainable aviation fuel demand in 2050 is 62.204 million tons, further broken down to the sustainable aviation fuel demand of individual airports, with some examples shown in Table 4.

[0080] Table 3

[0081] name Annual production capacity (10,000 tons) Refinery 1 453.822 Refinery 2 108.9408 Refinery 3 125.7323 Refinery 4 317.6799 Refinery 5 90.79156 Refinery 6 136.1421 Refinery 7 1181.603 Refinery 8 452.6 Refinery 9 318.1325 Refinery 10 950.46 Refinery 11 226.9336

[0082] Table 4

[0083] Airport name Sustainable aviation fuel demand (10,000 tons) Airport 1 75.23871 Airport 2 80.25372 Airport 3 74.46467 Airport 4 152.8218 Airport 5 116.0354 Airport 6 102.7148 Airport 7 6.715207 Airport 8 529.2741 Airport 9 181.5711 Airport 10 41.78566 Airport 11 3.853739 Airport 12 60.48166 Airport 13 87.59473

[0084] Under the constraints of production potential, carbon sequestration potential, annual refining capacity, and airport demand for sustainable aviation fuel, the objective function can be solved using Gurobi mathematical programming optimization software to obtain the optimal low-carbon path scheme that meets the needs of airports nationwide and minimizes the annual net carbon emissions of the sustainable aviation fuel supply chain network.

[0085] The results of the optimal low-carbon pathway are summarized in Table 5. Table 5 shows that, under the given scenario, biomass feedstocks have a significant carbon offsetting effect in the soil carbon sequestration stage. The soil carbon sequestration offset from biomass feedstock cultivation exceeds the sum of carbon emissions from the sustainable aviation fuel supply chain network, resulting in a negative minimum net carbon emission for the sustainable aviation fuel supply chain network each year. This result demonstrates that the technical solution provided by the embodiments of this application can not only achieve a supply-demand balance for sustainable aviation fuel on a national scale, but also provide quantifiable decision-making basis for the spatial layout, phased construction, and multimodal transport organization of the sustainable aviation fuel industry by explicitly incorporating carbon sequestration benefits into the optimization framework.

[0086] Table 5

[0087] <![CDATA[Soil carbon sequestration (100 million tons of CO2)]]> 3.44 <![CDATA[Annual minimum carbon emissions in the supply chain (hundred million tons of CO2)]]> -2.94 Number of small-scale biomass raw material collection stations 59 Number of medium-sized biomass raw material collection stations 22 Number of large-scale biomass raw material collection stations 18 Number of refineries in operation 163 Biomass feedstock collection volume (Mt) 735.52 Sustainable aviation fuel production (10,000 tons) 6220.4

[0088] The technical solution provided in this application embodiment can obtain a low-carbon path scheme for a sustainable aviation fuel supply chain network that integrates biomass raw material supply, refining capacity, and airport demand, providing a quantitative decision-making basis for the planning and construction of a sustainable aviation fuel industry.

[0089] Figure 2 This is a structural block diagram of a low-carbon pathway optimization device for a sustainable aviation fuel supply chain network provided in an embodiment of this application, as shown below. Figure 2 As shown, it includes:

[0090] The acquisition module 510 is used to acquire spatial distribution information of objects related to the sustainable aviation fuel supply chain network and carbon emission factors at each stage of the sustainable aviation fuel supply chain network's life cycle; wherein, the spatial distribution information includes the distribution of biomass feedstock production in the target area, the distribution of soil carbon sequestration rate at biomass feedstock sites, railway distribution, highway distribution, refined oil pipeline distribution, oil refinery distribution, and airport distribution.

[0091] The location determination module 520 is used to perform clustering based on the biomass raw material production distribution using a production-weighted clustering method to form a number of preset clusters, take the cluster center of the cluster as the initial location of the biomass raw material collection station corresponding to the biomass raw material point within the cluster, determine the railway buffer zone based on the railway distribution, and determine the final location of the biomass raw material collection station based on the initial location and the railway buffer zone.

[0092] Network construction module 530 is used to construct the sustainable aviation fuel supply chain network based on one of the biomass feedstock production distribution or the soil carbon sequestration rate distribution, the final location of the biomass feedstock collection station, the railway distribution, the highway distribution, the refined oil pipeline distribution, the refinery distribution, and the airport distribution;

[0093] The optimization module 540 is used to construct a carbon emission model of the sustainable aviation fuel supply chain based on the sustainable aviation fuel supply chain network, the carbon emission factor, and the distribution of soil carbon sequestration rate, and to optimize and solve the carbon emission model to obtain a low-carbon path optimization scheme for the sustainable aviation fuel supply chain network.

[0094] like Figure 3 As shown in the figure, this application provides an electronic device, including a processor 111, a communication interface 112, a memory 113, and a communication bus 114, wherein the processor 111, the communication interface 112, and the memory 113 communicate with each other through the communication bus 114.

[0095] Memory 113 is used to store computer programs;

[0096] In one embodiment of this application, when the processor 111 executes a program stored in the memory 113, it implements the method provided in any of the foregoing method embodiments, including:

[0097] Acquire spatial distribution information of relevant objects in the sustainable aviation fuel supply chain network and carbon emission factors at each stage of the sustainable aviation fuel supply chain network's life cycle; wherein, the spatial distribution information includes the distribution of biomass feedstock production in the target area, the distribution of soil carbon sequestration rate at biomass feedstock sites, railway distribution, highway distribution, refined oil pipeline distribution, refinery distribution, and airport distribution;

[0098] A production-weighted clustering method is used to cluster the biomass raw material production distribution to form several preset clusters. The cluster center of each cluster is used as the initial position of the biomass raw material collection station corresponding to the biomass raw material point within the cluster. A railway buffer zone is determined based on the railway distribution, and the final position of the biomass raw material collection station is determined based on the initial position and the railway buffer zone.

[0099] The sustainable aviation fuel supply chain network is constructed based on one of the biomass feedstock production distribution or the soil carbon sequestration rate distribution, the final location of the biomass feedstock collection station, the railway distribution, the highway distribution, the refined oil pipeline distribution, the oil refinery distribution, and the airport distribution;

[0100] A carbon emission model for the sustainable aviation fuel supply chain network is constructed based on the sustainable aviation fuel supply chain network, the carbon emission factor, and the distribution of soil carbon sequestration rate. The carbon emission model is then optimized and solved to obtain the optimal low-carbon pathway scheme for the sustainable aviation fuel supply chain network.

[0101] This application also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of the method provided in any of the foregoing method embodiments.

[0102] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. 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 can be selected to achieve the purpose of this embodiment according to actual needs.

[0103] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented using software plus a general-purpose hardware platform, or of course, using hardware. Based on this understanding, the above technical solutions, in essence or the parts that contribute to the related technology, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0104] The above embodiments are merely illustrative examples and are not intended to limit the implementation. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is neither necessary nor possible to exhaustively list all possible implementations. However, obvious variations or modifications derived therefrom are still within the scope of protection of this application.

Claims

1. A low-carbon pathway optimization method for a sustainable aviation fuel supply chain network, characterized in that, include: Acquire spatial distribution information of relevant objects in the sustainable aviation fuel supply chain network and carbon emission factors at each stage of the sustainable aviation fuel supply chain network's life cycle; wherein, the spatial distribution information includes the distribution of biomass feedstock production in the target area, the distribution of soil carbon sequestration rate at biomass feedstock sites, railway distribution, highway distribution, refined oil pipeline distribution, refinery distribution, and airport distribution; A production-weighted clustering method is used to cluster the biomass raw material production distribution to form several preset clusters. The cluster center of each cluster is used as the initial position of the biomass raw material collection station corresponding to the biomass raw material point within the cluster. A railway buffer zone is determined based on the railway distribution, and the final position of the biomass raw material collection station is determined based on the initial position and the railway buffer zone. The sustainable aviation fuel supply chain network is constructed based on one of the biomass feedstock production distribution or the soil carbon sequestration rate distribution, the final location of the biomass feedstock collection station, the railway distribution, the highway distribution, the refined oil pipeline distribution, the oil refinery distribution, and the airport distribution; A carbon emission model for the sustainable aviation fuel supply chain network is constructed based on the sustainable aviation fuel supply chain network, the carbon emission factor, and the distribution of soil carbon sequestration rate. The carbon emission model is then optimized and solved to obtain the optimal low-carbon pathway scheme for the sustainable aviation fuel supply chain network.

2. The method according to claim 1, characterized in that, The yield-weighted clustering method clusters the biomass feedstock based on its yield distribution, forming several pre-defined clusters, including: The biomass feedstock locations and their corresponding yields are determined based on the biomass feedstock yield distribution. A predetermined number of biomass raw material points are randomly selected as current cluster centers, and each biomass raw material point is assigned to the nearest current cluster center to form a cluster. Using the production output as the weight, determine the weighted average production output of the biomass raw material points in the cluster. Update the current cluster center based on the weighted average production output. Return to the step of assigning each biomass raw material point to the nearest current cluster center. Continue until the iteration termination condition is met to obtain a number of preset clusters.

3. The method according to claim 2, characterized in that, Updating the current cluster centers based on the output-weighted mean includes: The current cluster centers are updated based on the following formula: ； in, This is the index of the biomass raw material site; The index of the cluster; For iteration rounds; in, In the first In the first iteration, the... The location coordinates of the cluster centers of each cluster, that is, the updated location coordinates of the current cluster centers; Biomass feedstock point The output; For the biomass raw material point Longitude coordinates; For the biomass raw material point Latitude coordinates; In the first In the first iteration, the... A set of biomass feedstock points in a cluster.

4. The method according to claim 1, characterized in that, The determination of railway buffer zones based on the railway distribution includes: Based on the railway distribution, an area within a first preset distance from the railway is determined and used as a railway buffer zone; Determining the final location of the biomass raw material collection station based on the initial location and the railway buffer zone includes: If neither the initial position nor the biomass raw material points within the cluster fall within the railway buffer zone, the initial position is projected along the shortest distance to the boundary of the railway buffer zone. If the projection distance does not exceed a second preset distance, the projection point corresponding to the initial position is taken as the final position of the biomass raw material collection station; or if the projection distance is greater than the second preset distance, the initial position is taken as the final position of the biomass raw material collection station. Wherein, the projection distance is the distance between the initial position and the projection point; the second preset distance is greater than the first preset distance. If there are biomass raw material points within the cluster that fall into the railway buffer zone, the biomass raw material point with the largest output is selected as the final location of the biomass raw material collection station.

5. The method according to claim 1, characterized in that, The objective function of the carbon emission model is: ； in, The annual net carbon emissions of the aforementioned sustainable aviation fuel supply chain network; This refers to the annual carbon emissions during the planting and harvesting of biomass raw materials. This refers to the annual carbon emissions during the transportation phase. Carbon emissions during the refining stage; This refers to the negative carbon emissions during the soil carbon sequestration stage. in; ; in, An index of biomass raw material types; This is the index of the biomass raw material site; A collection of biomass raw material sites; A set of categories; Biomass feedstock point Types of supplies The amount of biomass raw materials; For type Carbon emission factors during the planting and collection of biomass raw materials; in, ; in, An index for modes of transport; For the index of the biomass raw material collection station; An index for oil refineries; For airport indexes; For the biomass raw material point To biomass raw material collection station The modes of transportation included The set of transport arcs; For the biomass raw material point Biomass raw materials are transported via the aforementioned method Transported to the biomass raw material collection station The amount of raw materials; To the biomass feedstock point Biomass raw materials are transported via the aforementioned method Transported to the biomass raw material collection station In the case of the transportation method The transport distance of the transport arc; The transportation method carbon emission factors, , It is a collection of modes of transportation, which includes road transportation, rail transportation and pipeline transportation; For types Biomass feedstock from the biomass feedstock collection station To the refinery The transportation methods included The set of transport arcs; For types Biomass raw materials are transported via the aforementioned method From the biomass raw material collection station Transported to the refinery The amount of raw materials; For the biomass raw materials to be transported by the aforementioned method From the biomass raw material collection station Transported to the refinery In the case of the transportation method The transport distance of the transport arc; For originating from type Sustainable aviation fuel from biomass feedstock from the refinery Arrive at the airport The modes of transportation included The set of transport arcs; For originating from type Sustainable aviation fuel made from biomass feedstock is produced by the refinery. By transportation Transported to the airport The amount of fuel; To ensure sustainable aviation fuel from the refinery via the aforementioned transportation method Transported to the airport In the case of the transportation method The transport distance of the transport arc; in, ; in, For types Carbon emission factors of biomass feedstock during the refining stage; in, ; in, Indicates the conversion coefficient between carbon and carbon dioxide; For the biomass raw material point Soil carbon sequestration rate; For the biomass raw material point The planting area; For the biomass raw material point The actual supply; For the biomass raw material point The upper limit of the supply of biomass raw materials.

6. The method according to claim 5, characterized in that, The constraints of the carbon emission model are as follows: ； ； ； ； ； ； in, This indicates whether to select a biomass feedstock point. Planting; For distribution to the biomass raw material collection station A collection of biomass raw material sites; For the biomass raw material collection station Processing capacity; Indicate whether to select the biomass raw material collection station. ; For the refinery Production capacity; Indicate whether to select the refinery. ; For types The conversion rate of biomass feedstock into sustainable aviation fuel; For the airport The demand for sustainable aviation fuel; For the collection of oil refineries; Meet at the airport.

7. The method according to claim 1, characterized in that, The construction of a sustainable aviation fuel supply chain network based on one of the biomass feedstock yield distribution or the soil carbon sequestration rate distribution, the final location of the biomass feedstock collection station, the railway distribution, the highway distribution, the refined oil pipeline distribution, the refinery distribution, and the airport distribution includes: The location of the biomass feedstock point is determined based on either the biomass feedstock yield distribution or the soil carbon sequestration rate distribution, and the locations of the oil refinery and the airport are determined based on the oil refinery distribution and the airport distribution, respectively. The locations of the biomass feedstock points, the final locations of the biomass feedstock collection stations, the oil refineries, and the airports are designated as nodes in the sustainable aviation fuel supply chain network. A road transport connection is established between the locations of the biomass feedstock points and the final locations of the biomass feedstock collection stations based on the road network distribution. A road-rail transport connection is established between the final locations of the biomass feedstock collection stations and the oil refineries based on the road network distribution and the railway network distribution. Furthermore, a road-rail-pipeline transport connection is established between the locations of the oil refineries and the airports based on the road network distribution, railway network distribution, and refined oil pipeline network distribution.

8. A low-carbon pathway optimization device for a sustainable aviation fuel supply chain network, characterized in that, include: The acquisition module is used to acquire spatial distribution information of objects related to the sustainable aviation fuel supply chain network and carbon emission factors at each stage of the sustainable aviation fuel supply chain network's life cycle; wherein, the spatial distribution information includes the distribution of biomass feedstock production in the target area, the distribution of soil carbon sequestration rate at biomass feedstock sites, railway distribution, highway distribution, refined oil pipeline distribution, refinery distribution, and airport distribution; The location determination module is used to cluster the biomass raw material production distribution based on the production weighting method using a production weighting method to form a number of preset clusters, take the cluster center of the cluster as the initial location of the biomass raw material collection station corresponding to the biomass raw material point within the cluster, determine the railway buffer zone based on the railway distribution, and determine the final location of the biomass raw material collection station based on the initial location and the railway buffer zone. The network construction module is used to construct the sustainable aviation fuel supply chain network based on one of the biomass feedstock production distribution or the soil carbon sequestration rate distribution, the final location of the biomass feedstock collection station, the railway distribution, the highway distribution, the refined oil pipeline distribution, the refinery distribution, and the airport distribution; The optimization module is used to construct a carbon emission model of the sustainable aviation fuel supply chain based on the sustainable aviation fuel supply chain network, the carbon emission factor, and the distribution of soil carbon sequestration rate, and to optimize and solve the carbon emission model to obtain a low-carbon path optimization scheme for the sustainable aviation fuel supply chain network.

9. An electronic device, characterized in that, It includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, It stores a computer program that, when executed in a computer, causes the computer to perform the method described in any one of claims 1-7.

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