Hydrogen refueling station site selection and scale determination method and device, electronic equipment and storage medium

Abstract

The invention discloses a hydrogen refueling station site selection and scale determination method and device, electronic equipment and a storage medium, and the method comprises the steps: building a hydrogen demand model and a hydrogen cost model according to the path information of a target region, building a target function according to the hydrogen demand model and the hydrogen cost model, solving the target function through a multi-target optimization function, and determining the site selection and scale of a hydrogen refueling station. A pareto solution set is obtained; according to the pareto solution set, constructing an ideal optimal solution and an ideal worst solution; based on a TOPSIS algorithm, determining a first distance between each solution in the pareto solution set and the ideal optimal solution, and determining a second distance between each solution in the pareto solution set and the understanding most listed solution; and selecting one solution from the pareto solution set as a target solution according to the first distance and the second distance corresponding to each solution in the pareto solution set. And the target solution can simultaneously meet relatively large hydrogen utilization requirements and relatively low hydrogen utilization cost, and is an optimal combination of the site selection and the scale of the hydrogenation station established in the target area, so that the effect of considering the hydrogen utilization requirements and the hydrogen utilization cost of the hydrogenation station is achieved.

Description

Technical Field

[0001] The present application relates to the field of hydrogen energy technology, and in particular to a method, device, electronic equipment and storage medium for site selection and scale determination of a hydrogen refueling station. Background Art

[0002] As a clean, carbon-free and storable secondary energy source, hydrogen energy is one of the important development directions in the field of new energy technology and is regarded as an important way to achieve carbon emission reduction. Hydrogen fuel cell vehicles are the most typical application field of hydrogen energy, and hydrogen refueling stations are supporting infrastructure to ensure the fuel supply of hydrogen fuel cell vehicles.

[0003] Currently, the site selection is mainly carried out manually near the frequently used locations based on the current hydrogen usage situation. The existing method is highly subjective and relies on subjective judgment to select the site, which lacks objectivity. Due to the high cost of building a hydrogen refueling station, subjective judgment of the site selection and the scale of the site construction can easily lead to a mismatch between demand and hydrogen refueling station capacity, resulting in a waste of resources. Therefore, a method for determining the site selection and scale of a hydrogen refueling station is urgently needed. Summary of the invention

[0004] The present application aims to solve at least one of the technical problems existing in the prior art. To this end, the present application proposes a method, device, electronic device and storage medium for determining the site selection and scale of a hydrogen refueling station, which can determine the site selection and scale of a hydrogen refueling station based on path information.

[0005] According to the first aspect of the present application, the method for determining the site and scale of a hydrogen refueling station includes:

[0006] Get the path information of the target area;

[0007] A hydrogen demand model is constructed according to the path information, and the hydrogen demand model is:

[0008]

[0009] Wherein, q represents the shortest path from the starting point to the end point, the set of shortest paths is Q, F represents the number of hydrogenation equipment in the target area every day; f q Characterizes the number of hydrogenation equipment on the shortest path q per day; y q Used to characterize whether hydrogenation has occurred; A i , B j Represent the starting point and the end point respectively; W Ai and are the weights of the starting point and the end point respectively; dq is the distance of the shortest path q; M is an empirical constant; and b is a distance index.

[0010] Construct a hydrogen cost model; the hydrogen cost model is:

[0011]

[0012] Among them, X is the comprehensive hydrogen cost; Pi is the hydrogen cost of the i-th node on the path; Si is the scale of the hydrogen refueling station at the i-th node on the path; n is the total number of nodes on the path;

[0013] An objective function is constructed according to the hydrogen demand model and the hydrogen cost model; the objective function is:

[0014]

[0015] Solving the objective function based on a multi-objective optimization function to obtain a Pareto solution set;

[0016] According to the Pareto solution set, construct an ideal optimal solution and an ideal worst solution;

[0017] Based on the approximate ideal solution sorting algorithm, determining a first distance between each solution in the Pareto solution set and the ideal optimal solution, and determining a second distance between each solution in the Pareto solution set and the ideal optimal solution;

[0018] A solution is selected from the Pareto solution set as a target solution according to the first distance and the second distance corresponding to each solution in the Pareto solution set.

[0019] The method for site selection and scale determination of hydrogen refueling stations according to the embodiment of the present application has at least the following beneficial effects: the method of the present application constructs a hydrogen demand model and a hydrogen cost model according to the path information of the target area, then constructs an objective function according to the hydrogen demand model and the hydrogen cost model, and then uses a multi-objective optimization function to solve the objective function to obtain a Pareto solution set; according to the Pareto solution set, an ideal optimal solution and an ideal worst solution are constructed; based on the TOPSIS algorithm, the first distance between each solution in the Pareto solution set and the ideal optimal solution is determined, and the second distance between each solution in the Pareto solution set and the ideal worst solution is determined; according to the first distance and the second distance corresponding to each solution in the Pareto solution set, a solution is selected from the Pareto solution set as the target solution. The target solution includes the site selection and scale of the hydrogen refueling station in the target area. This application combines a multi-objective optimization function with the TOPSIS algorithm so that the target solution can simultaneously meet a larger hydrogen demand and a lower hydrogen cost. The target solution is the optimal combination of the site selection and scale of a hydrogen refueling station in the target area, so as to achieve the effect of taking into account both the hydrogen demand and the hydrogen cost of the hydrogen refueling station.

[0020] According to some embodiments of the present application, q The expression is:

[0021]

[0022] Among them, i represents the node passed by the shortest path q, and ai represents whether there is a hydrogen refueling station at the i-th node. If there is a hydrogen refueling station at the i-th node, ai is 1; if there is no hydrogen refueling station at the i-th node, ai is 0.

[0023] According to some embodiments of the present application, the expression of the hydrogen cost of the i-th node is:

[0024] P i =P p_h +P t_h +P h ,

[0025] Where Pi is the hydrogen cost of the i-th node on the path, P p_h is the hydrogen production cost, P t_h = The storage and transportation cost of transporting hydrogen energy to the i-th hydrogenation point, P h The cost of hydrogen refueling station.

[0026] According to some embodiments of the present application, the expression of the scale of the hydrogen refueling station at the i-th node is:

[0027]

[0028] Where Si is the scale of the hydrogenation station at the i-th node of the path; fq represents the number of hydrogenation equipment per day on the shortest path q; W i is the weight of the i-th node of the shortest path q; Aq is the average hydrogen consumption of the hydrogenation equipment of the shortest path q; dq is the distance of the shortest path q; ai represents whether there is a hydrogenation station at the i-th node.

[0029] According to some embodiments of the present application, constructing an ideal optimal solution and an ideal worst solution according to the Pareto solution set includes:

[0030] Non-dimensionalizing the pareto solution set;

[0031] According to the dimensionless pareto solution set, the ideal optimal solution and the ideal worst solution are constructed.

[0032] According to some embodiments of the present application, the first distance and the second distance are both Euclidean geometric distances.

[0033] According to some embodiments of the present application, constructing the ideal optimal solution and the ideal worst solution according to the dimensionless Pareto solution set includes:

[0034] Taking hydrogen radiation rate as a target, the ideal optimal solution and the ideal worst solution are generated according to the Pareto solution set by using an approximate ideal solution sorting algorithm.

[0035] The second aspect of the present application provides a device for determining the site selection and scale of a hydrogen refueling station, including:

[0036] An acquisition module is used to obtain path information of a target area;

[0037] The first building module is used to build a hydrogen demand model according to the path information, and the hydrogen demand model is:

[0038]

[0039]

[0040] Wherein, q represents the shortest path from the starting point to the end point, the set of shortest paths is Q, F represents the number of hydrogenation equipment in the target area every day; f q Characterizes the number of hydrogenation equipment on the shortest path q per day; y q Used to characterize whether hydrogenation has occurred; A i , B j Represent the starting point and the end point respectively; W Ai and are the weights of the starting point and the end point respectively; dq is the distance of the shortest path q; M is an empirical constant; and b is a distance index.

[0041] The second building block is used to build a hydrogen cost model; the hydrogen cost model is:

[0042]

[0043] Among them, X is the comprehensive hydrogen cost; Pi is the hydrogen cost of the i-th node on the path; Si is the scale of the hydrogen refueling station at the i-th node on the path; n is the total number of nodes on the path;

[0044] The third building module is to build an objective function according to the hydrogen demand model and the hydrogen cost model; the objective function is:

[0045]

[0046] A solution module, used for solving the objective function based on a multi-objective optimization function to obtain a Pareto solution set;

[0047] A fourth construction module is used to construct an ideal optimal solution and an ideal worst solution according to the Pareto solution set;

[0048] A determination module, configured to determine a first distance between each solution in the Pareto solution set and the ideal optimal solution based on an approximate ideal solution sorting algorithm, and to determine a second distance between each solution in the Pareto solution set and the ideal optimal solution;

[0049] A selection module is used to select a solution from the Pareto solution set as a target solution according to the first distance and the second distance corresponding to each solution in the Pareto solution set.

[0050] The third aspect of the present application provides an electronic device, which includes a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the method for site selection and scale determination of a hydrogen refueling station as described in any one of the first aspect embodiments is implemented.

[0051] The fourth aspect of the present application provides a computer-readable storage medium, which stores a computer program, characterized in that when the computer program is executed by a processor, the method for site selection and scale determination of a hydrogen refueling station described in any one of the first aspect embodiments is implemented.

[0052] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] The present application is further described below with reference to the accompanying drawings and embodiments, wherein:

[0054] Figure 1 A schematic diagram of a process for determining the site and scale of a hydrogen refueling station according to an embodiment of the present application;

[0055] Figure 2 for Figure 1 A specific flow chart of step S160;

[0056] Figure 3 A schematic diagram of the structure of a device for determining the site selection and scale of a hydrogen refueling station according to an embodiment of the present application;

[0057] Figure 4 A schematic diagram of the hardware structure of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0058] The embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present application, and cannot be understood as limiting the present application.

[0059] In the description of the present application, it should be understood that descriptions involving orientation, such as up, down, front, back, left, right, etc., indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present application.

[0060] In the description of this application, "several" means more than one, "more" means more than two, "greater than", "less than", "exceed", etc. are understood to exclude the number itself, and "above", "below", "within", etc. are understood to include the number itself. If there is a description of "first" or "second", it is only used for the purpose of distinguishing technical features, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features or implicitly indicating the order of the indicated technical features.

[0061] In the description of this application, unless otherwise clearly defined, terms such as setting, installing, connecting, etc. should be understood in a broad sense, and technicians in the relevant technical field can reasonably determine the specific meanings of the above terms in this application based on the specific content of the technical solution.

[0062] In the description of the present application, the description with reference to the terms "one embodiment", "some embodiments", "illustrative embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials, or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0063] Reference Figure 1 The method for determining the site selection and scale of a hydrogen refueling station in the first embodiment of the present application includes but is not limited to the following steps:

[0064] Step S110, obtaining path information of the target area;

[0065] Step S120: construct a hydrogen demand model according to the route information. The hydrogen demand model is:

[0066]

[0067] Among them, q represents the shortest path from the starting point to the end point, the set of shortest paths is Q, F represents the number of hydrogen refueling equipment in the target area every day; f q Characterizes the number of hydrogen refueling equipment per day on route q; y q Used to characterize whether hydrogenation has occurred; A i , B jRepresent the starting point and the end point respectively; W Ai and are the weights of the starting point and the end point respectively; dq is the distance of path q; M is the empirical constant; b is the distance index.

[0068] Step S130, constructing a hydrogen cost model; the hydrogen cost model is:

[0069]

[0070] Among them, X is the comprehensive hydrogen cost; Pi is the hydrogen cost of the i-th node on the path; Si is the scale of the hydrogen refueling station at the i-th node on the path; n is the total number of nodes on the path;

[0071] Step S140, constructing an objective function based on the hydrogen demand model and the hydrogen cost model; the objective function is:

[0072]

[0073] Step S150, solving the objective function based on the multi-objective optimization function to obtain a Pareto solution set;

[0074] Step S160, constructing an ideal optimal solution and an ideal worst solution according to the Pareto solution set;

[0075] Step S170, based on the approximate ideal solution sorting algorithm, determining the first distance between each solution in the Pareto solution set and the ideal optimal solution, and determining the second distance between each solution in the Pareto solution set and the ideal optimal solution;

[0076] Step S180, selecting a solution from the Pareto solution set as a target solution according to the first distance and the second distance corresponding to each solution in the Pareto solution set.

[0077] According to the method for determining the site and scale of a hydrogen refueling station according to the embodiment of the present application, there are at least the following beneficial effects: the method of the present application constructs a hydrogen demand model and a hydrogen cost model according to the path information of the target area, then constructs an objective function according to the hydrogen demand model and the hydrogen cost model, and then uses a multi-objective optimization function to solve the objective function to obtain a Pareto solution set; according to the Pareto solution set, an ideal optimal solution and an ideal worst solution are constructed; based on the TOPSIS algorithm, the first distance between each solution in the Pareto solution set and the ideal optimal solution is determined, and the second distance between each solution in the Pareto solution set and the ideal worst solution is determined; according to the first distance and the second distance corresponding to each solution in the Pareto solution set, a solution is selected from the Pareto solution set as the target solution. The target solution includes the site selection and scale of the hydrogen refueling station in the target area. The present application combines the multi-objective optimization function with the TOPSIS algorithm so that the target solution can simultaneously meet the larger hydrogen demand and the lower hydrogen cost. The target solution is the optimal combination of the site selection and scale of the hydrogen refueling station in the target area, so as to achieve the effect of taking into account the hydrogen demand and hydrogen cost of the hydrogen refueling station.

[0078] It is worth noting that in step S110, the target area refers to the area where a hydrogen refueling station needs to be established, which may include multiple roads. The path information includes multiple paths in the target area, each path having multiple nodes. The starting point and the end point are set based on the two ends of the target area, and then the shortest path from the starting point to the end point in the target area is determined. Taking into account symmetry and radiation, for example, a hydrogen refueling station can simultaneously radiate multiple hydrogen power generation equipment at the same distance around it, so the shortest path can have multiple paths, and the shortest path set Q is obtained. And the path information also includes the number of hydrogen refueling equipment per day in each shortest path (such as the number of hydrogen refueling vehicles).

[0079] It should be noted that F represents the number of hydrogenation equipment in the target area every day, and F is also called the radiation rate.

[0080] It should be noted that the path information can be obtained by relevant personnel conducting a survey of the target area in advance. In some embodiments, the city has a smart transportation center, and the smart transportation center stores the path information of the target area. Therefore, the path information of the target area can be obtained through the smart transportation center.

[0081] In step S120, according to different definitions of cargo transportability, M is usually between 0.5 and 3.0. For example, M can be 0.5, 0.7, or 3.0. WAi and WBj are the weights of the starting point and the end point, respectively. Those skilled in the art can set the weights of the starting point and the end point according to actual needs.

[0082] In step S150, the objective function is solved using the gamultiobj multi-objective optimization function of MATLAB to obtain a Pareto solution set. gamultiobj is a genetic algorithm function in MATLAB used to solve multi-objective optimization problems. Multi-objective optimization problems involve multiple objective functions, which usually conflict with each other, that is, the optimization of one objective function may cause the performance of another objective function to degrade. The gamultiobj function uses a genetic algorithm to find a set of compromise solutions, which are called Pareto optimal solution sets. A genetic algorithm is an optimization algorithm that simulates the principles of natural selection and genetics, and iteratively improves the quality of the solution through operations such as selection, crossover, and mutation.

[0083] In step S170, the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) is a commonly used comprehensive evaluation method. Its basic idea is to find the best and worst solutions among the finite solutions for the normalized data set, and use a certain distance calculation method (such as Euclidean distance or cosine method) to calculate the distance between each sample data or each evaluation object data and the best and worst solutions, that is, the degree of proximity.

[0084] In one embodiment, y q The expression is:

[0085]

[0086] Among them, i represents the node that path q passes through, and ai represents whether there is a hydrogen refueling station at the i-th node. If there is a hydrogen refueling station at the i-th node, ai is 1; if there is no hydrogen refueling station at the i-th node, ai is 0.

[0087] In one embodiment, the expression of the hydrogen cost of the i-th node is:

[0088] P i =P p_h +P t_h +P h ,

[0089] Where Pi is the hydrogen cost of the i-th node on the path, P p_h is the hydrogen production cost, in yuan / kg, P t_h The storage and transportation cost of transporting hydrogen energy to the i-th hydrogenation point is RMB / kg, P h is the cost of hydrogen refueling station, in Yuan / kg.

[0090] In one embodiment, the expression of the scale of the hydrogen refueling station at the i-th node is:

[0091]

[0092] Where Si is the scale of the hydrogenation station at the i-th node of the path; fq represents the number of hydrogenation equipment per day on path q; W i is the weight of the i-th node on path q; Aq is the average hydrogen consumption of the hydrogenation equipment on path q; dq is the distance of path q; ai represents whether there is a hydrogenation station at the i-th node.

[0093] In one embodiment, referring to Figure 2 , Figure 2 yes Figure 1 A specific flow chart of step S160 in FIG. 1 is shown in FIG. 1 . Step S160 may include but is not limited to the following steps:

[0094] Step S210, performing dimensionless processing on the Pareto solution set;

[0095] Step S220, constructing an ideal optimal solution and an ideal worst solution according to the dimensionless Pareto solution set.

[0096] Dimensionless processing of the Pareto solution set can eliminate the influence of dimension and order of magnitude. After dimensionless processing, decision makers can more easily identify and understand the characteristics of the Pareto solution set, such as the trade-off relationship between solutions, so as to make decisions more efficiently. Dimensionless processing can improve the convergence speed and stability of the algorithm. The specific dimensionless processing operation can be to normalize the Pareto solution set.

[0097] In one embodiment, the first distance and the second distance are both Euclidean distances. Euclidean distance, also known as Euclidean distance, is a straight-line distance between two points in a multi-dimensional space.

[0098] In one embodiment, step S220 may include but is not limited to the following steps:

[0099] Taking hydrogen radiation rate as the target, the ideal optimal solution and the ideal worst solution are generated according to the Pareto solution set using the approximate ideal solution sorting algorithm.

[0100] Exemplarily, referring to Table 1, Table 1 shows multiple solutions in the Pareto solution set. When using the approximate ideal solution sorting algorithm, an ideal optimal solution and an ideal worst solution in a system composed of all solutions can be constructed based on the Pareto solution set and the TOPSIS algorithm, with the hydrogen radiation rate as the target, that is, a solution with the largest hydrogen radiation rate is constructed as the ideal optimal solution, and a solution with the smallest hydrogen radiation rate is constructed as the ideal worst solution. Then, each solution in the Pareto solution set is sorted according to its hydrogen radiation rate, and the solution with the hydrogen radiation rate closest to the ideal optimal solution can be selected as the target solution.

[0101] Table 1

[0102]

[0103] Reference Figure 3 The second embodiment of the present application provides a device for determining the site selection and scale of a hydrogen refueling station, including:

[0104] An acquisition module 310 is used to acquire path information of a target area;

[0105] The first building module 320 is used to build a hydrogen demand model according to the route information. The hydrogen demand model is:

[0106]

[0107] Among them, q represents the shortest path from the starting point to the end point, the set of shortest paths is Q, F represents the number of hydrogen refueling equipment in the target area every day; f q Characterizes the number of hydrogen refueling equipment per day on route q; y q Used to characterize whether hydrogenation has occurred; A i , B j Represent the starting point and the end point respectively; W Ai and are the weights of the starting point and the end point respectively; dq is the distance of path q; M is the empirical constant; b is the distance index.

[0108] The second building module 330 is used to build a hydrogen cost model; the hydrogen cost model is:

[0109]

[0110] Among them, X is the comprehensive hydrogen cost; Pi is the hydrogen cost of the i-th node on the path; Si is the scale of the hydrogen refueling station at the i-th node on the path; n is the total number of nodes on the path;

[0111] The third building module 340 builds an objective function according to the hydrogen demand model and the hydrogen cost model; the objective function is:

[0112]

[0113] A solution module 350, used to solve the objective function based on the multi-objective optimization function to obtain a Pareto solution set;

[0114] A fourth construction module 360 ​​is used to construct an ideal optimal solution and an ideal worst solution according to the Pareto solution set;

[0115] A determination module 370 is used to determine a first distance between each solution in the Pareto solution set and the ideal optimal solution based on the TOPSIS algorithm, and to determine a second distance between each solution in the Pareto solution set and the ideal optimal solution;

[0116] The selection module 380 is used to select a solution from the Pareto solution set as a target solution according to the first distance and the second distance corresponding to each solution in the Pareto solution set.

[0117] The device of the present application, the acquisition module 310 acquires the path information, then the first construction module 320 constructs the hydrogen demand model according to the path information of the target area, the second construction module 330 constructs the hydrogen cost model, and then the third construction module 340 constructs the objective function according to the hydrogen demand model and the hydrogen cost model, and the solution module 350 uses the multi-objective optimization function to solve the objective function to obtain the Pareto solution set; the fourth construction module 360 ​​constructs the ideal optimal solution and the ideal worst solution according to the Pareto solution set; the determination module 370 determines the first distance between each solution in the Pareto solution set and the ideal optimal solution based on the TOPSIS algorithm, and determines the second distance between each solution in the Pareto solution set and the ideal worst solution; the selection module 380 selects a solution from the Pareto solution set as the target solution according to the first distance and the second distance corresponding to each solution in the Pareto solution set. The target solution includes the site selection and construction scale of the hydrogen refueling station in the target area. This application combines a multi-objective optimization function with the TOPSIS algorithm so that the target solution can simultaneously meet a larger hydrogen demand and a lower hydrogen cost. The target solution is the optimal combination of the site selection and scale of a hydrogen refueling station in the target area, so as to achieve the effect of taking into account both the hydrogen demand and the hydrogen cost of the hydrogen refueling station.

[0118] The third aspect of the present application provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, the method for determining the site and scale of a hydrogen refueling station of any one of the first aspect embodiments is implemented.

[0119] See also Figure 4 , Figure 4 The hardware structure of an electronic device of another embodiment is illustrated, and the electronic device includes:

[0120] The processor 401 may be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (Application Specific Integrated Circuit, ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of the present application;

[0121] The memory 402 can be implemented in the form of a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 402 can store an operating system and other application programs. When the technical solution provided in the embodiment of this specification is implemented by software or firmware, the relevant program code is stored in the memory 402, and the processor 401 calls and executes the robot path planning method of the embodiment of this application;

[0122] Input / output interface 403, used to implement information input and output;

[0123] Communication interface 404, used to realize communication interaction between the device and other devices, which can be realized by wired mode (such as USB, network cable, etc.) or wireless mode (such as mobile network, WIFI, Bluetooth, etc.);

[0124] Bus 405 , which transmits information between various components of the device (e.g., processor 401 , memory 402 , input / output interface 403 , and communication interface 404 );

[0125] The processor 401 , the memory 402 , the input / output interface 403 and the communication interface 404 are connected to each other in communication within the device via the bus 405 .

[0126] The fourth aspect embodiment of the present application provides a computer-readable storage medium, which stores a computer program, characterized in that when the computer program is executed by a processor, the method for site selection and scale determination of a hydrogen refueling station of any one of the first aspect embodiments is implemented.

[0127] The memory, as a non-transient computer-readable storage medium, can be used to store non-transient software programs and non-transient computer executable programs. In addition, the memory may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory may optionally include a memory remotely disposed relative to the processor, and these remote memories may be connected to the processor via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0128] The embodiments described in the embodiments of the present application are intended to more clearly illustrate the technical solutions of the embodiments of the present application and do not constitute a limitation on the technical solutions provided in the embodiments of the present application. Those skilled in the art will appreciate that with the evolution of technology and the emergence of new application scenarios, the technical solutions provided in the embodiments of the present application are also applicable to similar technical problems.

[0129] Those skilled in the art will appreciate that the technical solutions shown in the figures do not constitute a limitation on the embodiments of the present application, and may include more or fewer steps than shown in the figures, or a combination of certain steps, or different steps.

[0130] The device embodiments described above are merely illustrative, and the units described as separate components may or may not be physically separated, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0131] Those skilled in the art will appreciate that all or some of the steps in the methods disclosed above, and the functional modules / units in the systems and devices may be implemented as software, firmware, hardware, or a suitable combination thereof.

[0132] The terms "first", "second", "third", "fourth", etc. (if any) in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0133] It should be understood that in the present application, "at least one (item)" means one or more, and "plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally indicates that the objects associated before and after are in an "or" relationship. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple.

[0134] In the several embodiments provided in the present application, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the system embodiments described above are merely schematic. For example, the division of the above units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0135] The units described above as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0136] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0137] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including multiple instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, referred to as ROM), random access memory (Random Access Memory, referred to as RAM), disk or optical disk and other media that can store programs.

[0138] The preferred embodiments of the present invention are described above with reference to the accompanying drawings, but the scope of the rights of the present invention is not limited thereto. Any modification, equivalent substitution and improvement made by a person skilled in the art without departing from the scope and essence of the present invention should be within the scope of the rights of the present invention.

Claims

1. A method for site selection and scale determination of a hydrogen refueling station, characterized in that: include: Get the path information of the target area; A hydrogen demand model is constructed according to the path information, and the hydrogen demand model is: Wherein, q represents the shortest path from the starting point to the end point, the set of the shortest paths is Q, F represents the number of hydrogenation equipment in the target area every day; f q Characterizes the number of hydrogenation equipment on the shortest path q per day; y q Used to characterize whether hydrogenation has occurred; A i , B j Represent the starting point and the end point respectively; W Ai and are the weights of the starting point and the end point respectively; d q is the distance of the shortest path q; M is an empirical constant; b is the distance index. Construct a hydrogen cost model; the hydrogen cost model is: Among them, X is the comprehensive hydrogen cost; Pi is the hydrogen cost of the i-th node on the path; Si is the scale of the hydrogen refueling station at the i-th node on the path; n is the total number of nodes on the path; An objective function is constructed according to the hydrogen demand model and the hydrogen cost model; the objective function is: Solving the objective function based on a multi-objective optimization function to obtain a Pareto solution set; According to the Pareto solution set, construct an ideal optimal solution and an ideal worst solution; Based on the approximate ideal solution sorting algorithm, determining a first distance between each solution in the Pareto solution set and the ideal optimal solution, and determining a second distance between each solution in the Pareto solution set and the ideal optimal solution; A solution is selected from the Pareto solution set as a target solution according to the first distance and the second distance corresponding to each solution in the Pareto solution set.

2. The method for site selection and scale determination of a hydrogen refueling station according to claim 1, characterized in that: y q The expression is: Among them, i represents the node passed by the shortest path q, and ai represents whether there is a hydrogen refueling station at the i-th node. If there is a hydrogen refueling station at the i-th node, ai is 1; if there is no hydrogen refueling station at the i-th node, ai is 0.

3. The method for site selection and scale determination of a hydrogen refueling station according to claim 1, characterized in that: The expression of hydrogen cost of the i-th node is: P i =P p_h +P t_h +P h , Where Pi is the hydrogen cost of the i-th node on the path, P p_h is the hydrogen production cost, P t_h = The storage and transportation cost of transporting hydrogen energy to the i-th hydrogenation point, P h The cost of hydrogen refueling station.

4. The method for site selection and scale determination of a hydrogen refueling station according to claim 2, characterized in that: The expression of the hydrogen station scale of the i-th node is: Where Si is the scale of the hydrogenation station at the i-th node of the path; fq represents the number of hydrogenation equipment per day on the shortest path q; W i is the weight of the i-th node of the shortest path q; Aq is the average hydrogen consumption of the hydrogenation equipment of the shortest path q; dq is the distance of the shortest path q; ai represents whether there is a hydrogenation station at the i-th node.

5. The method for site selection and scale determination of a hydrogen refueling station according to claim 1, characterized in that: The step of constructing an ideal optimal solution and an ideal worst solution according to the Pareto solution set includes: Non-dimensionalizing the pareto solution set; According to the dimensionless pareto solution set, the ideal optimal solution and the ideal worst solution are constructed.

6. The method for site selection and scale determination of a hydrogen refueling station according to claim 1, characterized in that: The first distance and the second distance are both Euclidean geometric distances.

7. The method for site selection and scale determination of a hydrogen refueling station according to claim 5, characterized in that: The step of constructing the ideal optimal solution and the ideal worst solution according to the dimensionless pareto solution set comprises: Taking hydrogen radiation rate as a target, the ideal optimal solution and the ideal worst solution are generated according to the Pareto solution set by using an approximate ideal solution sorting algorithm.

8. A device for determining the site selection and scale of a hydrogen refueling station, characterized in that: include: An acquisition module is used to obtain path information of a target area; The first building module is used to build a hydrogen demand model according to the path information, and the hydrogen demand model is: Wherein, q represents the shortest path from the starting point to the end point, the set of shortest paths is Q, F represents the number of hydrogenation equipment in the target area every day; f q Characterizes the number of hydrogenation equipment on the shortest path q per day; y q Used to characterize whether hydrogenation has occurred; Ai, B j Respectively represent the starting point and the end point; W Ai and are the weights of the starting point and the end point respectively; d q is the distance of the shortest path q; M is an empirical constant; b is the distance index. The second building block is used to build a hydrogen cost model; the hydrogen cost model is: Among them, X is the comprehensive hydrogen cost; Pi is the hydrogen cost of the i-th node on the path; Si is the scale of the hydrogen refueling station at the i-th node on the path; n is the total number of nodes on the path; The third building module is to build an objective function according to the hydrogen demand model and the hydrogen cost model; the objective function is: A solution module, used for solving the objective function based on a multi-objective optimization function to obtain a Pareto solution set; A fourth construction module is used to construct an ideal optimal solution and an ideal worst solution according to the Pareto solution set; A determination module, configured to determine a first distance between each solution in the Pareto solution set and the ideal optimal solution based on an approximate ideal solution sorting algorithm, and to determine a second distance between each solution in the Pareto solution set and the ideal optimal solution; A selection module is used to select a solution from the Pareto solution set as a target solution according to the first distance and the second distance corresponding to each solution in the Pareto solution set.

9. An electronic device, characterized in that: The electronic device includes a memory and a processor, the memory stores a computer program, and the processor implements the method for site selection and scale determination of a hydrogen refueling station as described in any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method for site selection and scale determination of a hydrogen refueling station according to any one of claims 1 to 7 is implemented.

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