Electric power material distribution method, system and equipment based on long period and medium

Abstract

The invention is suitable for the technical field of electric power material distribution, and provides an electric power material distribution method, system and device based on a long period, and a medium, and the method comprises the steps: obtaining a first material inventory of each power supply station in a first preset time, and the material consumption of each power supply station in a second preset time; calculating a second material inventory of each power supply station within a second preset time according to the first material inventory and the material consumption; judging whether the second material stock of each power supply station is lower than a preset safety stock level, if so, determining a target power supply station of which the second stock is lower than the safety stock level, and calculating the material capacity, required by the target power supply station, delivered by the central warehouse; and determining a corresponding target distribution scheme based on the material capacity distributed by the central warehouse required by the target power supply. According to the method, the distribution path is optimized by comprehensively considering the material demand and the distance of the station, and through long-period simulation deduction, the distribution efficiency is improved and the distribution cost is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of power material distribution, and in particular to a method, system, equipment and medium for long-cycle power material distribution. Background Art

[0002] In terms of material distribution for large power grid enterprises, due to their large scale and numerous sites, power grid enterprises have an urgent need to optimize material distribution. Reducing costs and improving efficiency is a crucial link. Although existing vehicle routing problem solutions have made some progress in single-time distribution, they lack the ability to monitor and track the distribution system in the long term, and fail to take into account dynamic factors such as material consumption and inventory levels. This makes the long-term material distribution route planning and logistics optimization of power materials not automated and comprehensive enough, and even errors occur.

[0003] In view of this, a method, system, equipment and medium for long-term power material distribution are needed. Summary of the invention

[0004] The embodiment of the present application provides a long-cycle power material distribution method, which is used to solve the problem that the long-cycle material distribution route planning and logistics optimization level of power materials are not automated and comprehensive enough.

[0005] A first aspect of an embodiment of the present application provides a long-cycle power material distribution method, comprising:

[0006] Obtaining a first material inventory of each power supply station within a first preset time and a material consumption of each power supply station within a second preset time;

[0007] Calculate the second material inventory of each power supply station within a second preset time according to the first material inventory and material consumption;

[0008] Determine whether the second material inventory of each power supply station is lower than the preset safety stock level, and if so, determine the target power supply station whose second inventory is lower than the safety stock level, and calculate the material capacity required by the central warehouse for distribution of the target power supply station;

[0009] A corresponding target distribution plan is determined based on the materials that the target power supply needs to distribute from the central warehouse.

[0010] Furthermore, the obtaining of the first material inventory of each power supply station within the first preset time and the material consumption of each power supply station within the second preset time includes:

[0011] The material monitoring systems of the power supply stations are associated, and the first material inventory within the first preset time and the material consumption within the second preset time are collected according to the identification information of each power supply station.

[0012] Furthermore, the calculation formula for calculating the second material inventory of each power supply station within the second preset time according to the first material inventory and material consumption is as follows:

[0013] S i,t =S i,t―1 ―C i,t―1 +I i,t―1 ;

[0014] Where: S i,t is the inventory balance of materials in each power supply station from the first preset time t-1 to the second preset time t, S i,t―1 is the inventory of materials in each power supply station within the first preset time t-1, C i,t―1 is the material consumption of each power supply station within the first preset time t-1, I i,t―1 The first preset time is the material inventory of each power supply station within t-1.

[0015] Furthermore, the target distribution plan corresponding to the materials required to be distributed by the central warehouse based on the target power supply is determined, including:

[0016] The objective function is constructed with the goal of minimizing the total cost of distributing materials from the central warehouse;

[0017] Determine constraints, wherein the constraints include a constraint that each power station is served by one vehicle, a site constraint, a vehicle entry center constraint, a secondary cycle elimination condition constraint, and a time window constraint;

[0018] A distribution plan for the target power supply station is determined according to the optimal solution of the objective function.

[0019] Furthermore, the objective function is expressed as follows:

[0020]

[0021]

[0022] Where: C T is the total delivery cost of all vehicles, C j is the unit distance transportation cost of the jth vehicle, R j [i+1] is the distance between the i-th node and the i+1-th node on the route of the j-th vehicle, n j is the number of stations on the line, P j is the unit distance transportation cost of the jth vehicle.

[0023] Furthermore, the expressions of the constraints are as follows:

[0024] Each power station is served by one vehicle:

[0025]

[0026] Site constraints:

[0027]

[0028] Secondary cycle elimination conditions:

[0029]

[0030] Time window constraints:

[0031]

[0032] Where: the directed graph G = (V, E) represents the distribution network, V = {0, 1, ..., N} represents the node set, node 0 represents the starting power supply station, V\{0} represents the distribution site, E = {(i, j)i, j∈V, i≠j} represents the arc set, K = {1, ..., M} represents the distribution vehicle set, M represents the number of vehicles required, Q represents the vehicle load, d i represents the demand of node i, AT ki represents the arrival time of vehicle k at node i, WT ki represents the waiting time of vehicle k at node i, s i represents the service time of vehicle k at node i, t ij represents the travel time of vehicle k between node i and node j, [e i ,l i ] represents the time window of node i, x ijk is a binary variable indicating whether the vehicle travels from node i to node j, and p3 is a constant used to ensure that the constraint condition is ijk =0.

[0033] Furthermore, the determining whether the second material inventory of each power supply station is lower than a preset safety inventory level includes:

[0034] If not, the third material inventory of each power supply station within the third preset time is calculated.

[0035] A second aspect of the embodiment of the present application provides a long-cycle power material distribution system, including:

[0036] An inventory and consumption acquisition unit, used to acquire a first material inventory of each power supply station within a first preset time and a material consumption of each power supply station within a second preset time;

[0037] A second material inventory calculation unit, used to calculate the second material inventory of each power supply station within a second preset time according to the first material inventory and material consumption;

[0038] A second material inventory determination unit, used to determine whether the second material inventory of each power supply station is lower than a preset safety inventory level;

[0039] The target power supply station determination unit is used to determine the target power supply station whose second inventory is lower than the safety inventory level when the second material inventory of each power supply station is lower than the preset safety inventory level, and calculate the material capacity required by the central warehouse for distribution of the target power supply station;

[0040] The target distribution plan determining unit is used to determine the corresponding target distribution plan based on the materials that the central warehouse needs to distribute to the target power supply.

[0041] A third aspect of the embodiments of the present application provides a computer device, including:

[0042] memories, transceivers, processors, and bus systems;

[0043] Wherein, the memory is used to store programs;

[0044] The processor is used to execute the program in the memory, including executing the long-cycle-based power material distribution method according to any one of claims 1 to 7;

[0045] The bus system is used to connect the memory and the processor so that the memory and the processor can communicate with each other.

[0046] A fourth aspect of an embodiment of the present application provides a readable storage medium, including instructions, which, when executed on a computer, enables the computer to execute any of the long-cycle-based power material distribution methods described above.

[0047] It can be seen from the above technical solutions that the embodiments of the present application have the following advantages:

[0048] This application obtains the material inventory of each power supply station in a certain month and the material consumption of each power supply station in the previous month, and calculates the material inventory of this month based on the material inventory and material consumption; then determines whether the material inventory of this month is lower than the preset safety inventory level. If so, the power supply stations that are lower than the safety inventory level are determined, and the material capacity that these power supply stations need to distribute from the central warehouse is calculated. Finally, the corresponding target distribution plan is determined based on the material capacity that needs to be distributed from the central warehouse. This application determines the power supply stations and material capacity that need to be distributed by setting the safety inventory level, comprehensively considers the material demand and distance of the site to optimize the distribution path, and improves the distribution efficiency and reduces the distribution cost through long-term simulation and deduction. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 It is a schematic diagram of an embodiment of a method for distributing electric power materials based on a long period in the present invention;

[0050] Figure 2 It is a structural block diagram of an embodiment of a long-cycle power material distribution system in the present invention;

[0051] Figure 3 The figure is a structural block diagram of a computer device in the present invention. DETAILED DESCRIPTION

[0052] The embodiments of the present application provide a method, system, equipment and medium for long-term distribution of electric power materials, which solve the problem that the long-term material distribution route planning and logistics optimization level of electric power materials are not automated and comprehensive enough.

[0053] The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims 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, for example. In addition, the terms "including" and "corresponding to" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0054] Embodiment 1

[0055] The implementation method in this embodiment can be implemented in the system, can be implemented in the server, and can also be implemented in the terminal, and there is no specific limitation. The following will introduce the long-term power material distribution method in this application from the perspective of the system. Figure 1 , the method provided in this application comprises the following steps:

[0056] S11. Obtain the first material inventory of each power supply station within the first preset time and the material consumption of each power supply station within the second preset time;

[0057] In this embodiment, obtaining the first material inventory of each power supply station within the first preset time and the material consumption of each power supply station within the second preset time includes:

[0058] The material monitoring systems of the power supply stations are associated, and the first material inventory within the first preset time and the material consumption within the second preset time are collected according to the identification information of each power supply station.

[0059] Specifically, the first preset time refers to the time period from the first month to the beginning of the next month, the first material inventory is the inventory of the first month, and the second preset time is the time period from the last month to the first month. For example, if May is taken as the first month, the consumption of April needs to be obtained. The power material inventory of each power supply station is collected by the system through the material monitoring system of each power supply station, and the material inventory within a certain period of time and the material consumption of the last month based on the time point are collected according to the identification information of each power supply station. The identification information includes the area or project number where the power supply station is located. The associated data includes the data monitored and analyzed by the material monitoring system, which mainly comes from the inventory-related detailed table. For example, a certain time range is intercepted to obtain the physical inventory and virtual inventory in May. The inventory table includes inventory material information such as storage location, storage location description, factory attributes, materials, material description, project type, quantity and amount. When the system is associated with the data, it is associated through key fields such as regional number or project number, extracts key information based on key fields, and then regenerates the material inventory table based on the key information. In addition to identification information such as number, it also includes inventory and consumption.

[0060] S12. Calculate the second material inventory of each power supply station within the second preset time according to the first material inventory and material consumption;

[0061] First, the geographical distance between power stations is accurately measured to determine the longitude and latitude coordinates (x i ,y i ), through the map software, determine the transportation distance d(i,j) and time consumption t(i,j) between power station i and power station j, where t(i,j) includes the unloading time.

[0062] Secondly, the initial inventory of each power supply station is dynamically simulated. Assume that the power material consumption of the ith power supply station in the tth month is C i,t , the inventory is I i,t , the materials that need to be distributed from the central warehouse are Di,t At that time, t = 1, that is, the starting storage S of power supply station i in the first month i,1 for:

[0063] S i,1 =I i,1 ;

[0064] The inventory balance S at the end of the first month and the beginning of the second month can be obtained i,2 :

[0065] S i,2 =S i,1 ―C i,1 +I i,1 ;

[0066] By analogy, the inventory balance at the end of February and the beginning of March is S i,3 :

[0067] S i,3 =S i,2 ―C i,2 +I i,2 ;

[0068] By analogy, the balance at the end of month t-1, i.e. the beginning of month t, is:

[0069] S i,t =S i,t―1 ―C i,t―1 +I i,t―1 ;

[0070] Where: S i,t is the inventory balance of materials in each power supply station from the first preset time t-1 to the second preset time t, S i,t―1 is the inventory of materials in each power supply station within the first preset time t-1, C i,t―1 is the material consumption of each power supply station within the first preset time t-1, I i,t―1 The first preset time is the material inventory of each power supply station within t-1.

[0071] If within a year until the 12th month:

[0072] S i,4 =S i,3 ―C i,3 +I i,3 ;

[0073] S i,5 =S i,4 ―C i,4 +I i,4 ;

[0074] …

[0075] S i,12 =S i,11―C i,11 +I i,11 ;

[0076] The above deduction dynamically simulates the changes in inventory, warehousing, and consumption. The above long-term deduction algorithm can take into account dynamic long-term cost changes. The algorithm can reduce the risk of excess or shortage by optimizing inventory levels.

[0077] S13. Determine whether the second material inventory of each power supply station is lower than the preset safety inventory level;

[0078] S14. When the second material inventory of each power supply station is lower than the preset safety stock level, the target power supply station whose second inventory is lower than the safety stock level is determined, and the material capacity required for distribution from the central warehouse of the target power supply station is calculated;

[0079] In the above, it is determined whether the material inventory of each power supply station obtained based on the calculation is lower than the preset safety inventory level. If so, it is necessary to calculate the material capacity required for distribution from the central warehouse. If not, the third material inventory of each power supply station within the third preset time is calculated, that is, the material inventory for the next month. Here, the third material inventory will be used as the basic data for calculating the inventory of the first month, similar to steps S11 and S12, through long-term simulation of changes in inventory, warehouses, and consumption.

[0080] S15. Determine a corresponding target distribution plan based on the materials that the target power supply station needs to distribute from the central warehouse.

[0081] In this embodiment, determining the corresponding target distribution plan based on the materials that the target power supply needs to distribute from the central warehouse includes the following steps:

[0082] 1. Construct the objective function with the goal of minimizing the total cost of distributing materials from the central warehouse;

[0083] 2. Determine the constraints, which include the constraint that each power supply station is served by one vehicle, site constraints, vehicle entry constraints, secondary cycle elimination constraints, and time window constraints;

[0084] 3. Determine the distribution plan for the target power supply station based on the optimal solution of the objective function.

[0085] Specifically, based on the distribution demand, the path planning algorithm of the Vehicle Routing Problem (VRP) is used to further optimize the logistics distribution process. The VRP algorithm is a combinatorial optimization problem that aims to assign distribution tasks to a group of vehicles and determine the distribution route of each vehicle to minimize the total distribution cost, including time cost, transportation cost and vehicle use cost.

[0086] Objective function:

[0087]

[0088] Where: C T is the total delivery cost of all vehicles, C j is the unit distance transportation cost of the jth vehicle, R j [i+1] is the distance between the i-th node and the i+1-th node on the route of the j-th vehicle, n j is the number of stations on the line, P j is the unit distance transportation cost of the jth vehicle.

[0089] Constraints:

[0090] Each power station is served by one vehicle:

[0091]

[0092] Site constraints:

[0093]

[0094] Secondary cycle elimination conditions:

[0095]

[0096] The time window constraints include that the vehicle’s arrival time must not exceed the user’s latest service start time, the user’s service start time must be between the earliest service start time and the latest service start time, and the time relationship between the predecessor node and the successor node, which are as follows:

[0097]

[0098] Where: the directed graph G = (V, E) represents the distribution network, V = {0, 1, ..., N} represents the node set, node 0 represents the starting power supply station, V\{0} represents the distribution site, E = {(i, j)i, j∈V, i≠j} represents the arc set, K = {1, ..., M} represents the distribution vehicle set, M represents the number of vehicles required, Q represents the vehicle load, d i represents the demand of node i, AT ki represents the arrival time of vehicle k at node i, WT ki represents the waiting time of vehicle k at node i, s i represents the service time of vehicle k at node i, t ij represents the travel time of vehicle k between node i and node j, [e i ,l i ] represents the time window of node i, x ijkis a binary variable indicating whether the vehicle travels from node i to node j, and p3 is a very large constant used to ensure that the constraint condition is ijk =0 is always true.

[0099] The above embodiment has a long-term deduction algorithm for power material distribution and has strong long-term planning capabilities, which can predict and plan material demand and distribution plans for months or even years. By comprehensively considering the dynamic changes in time during the distribution process, as well as key factors such as distance and time, the lowest cost solution and the highest efficiency solution under a variety of factors are obtained.

[0100] Embodiment 2

[0101] See also Figure 2 , an embodiment of a long-cycle power material distribution system in the present invention comprises the following steps:

[0102] An inventory and consumption acquisition unit, used to acquire a first material inventory of each power supply station within a first preset time and a material consumption of each power supply station within a second preset time;

[0103] A second material inventory calculation unit, used to calculate the second material inventory of each power supply station within a second preset time according to the first material inventory and the material consumption;

[0104] A second material inventory determination unit, used to determine whether the second material inventory of each power supply station is lower than a preset safety inventory level;

[0105] The target power supply station determination unit is used to determine the target power supply station whose second inventory is lower than the safety inventory level when the second material inventory of each power supply station is lower than the preset safety inventory level, and calculate the material capacity required by the central warehouse for distribution to the target power supply station;

[0106] The target distribution plan determination unit is used to determine the corresponding target distribution plan based on the materials that the target power supply needs to distribute from the central warehouse.

[0107] For the specific definition of the system, please refer to the definition of the method above, which will not be repeated here. Each module in the above system can be implemented in whole or in part by software, hardware and a combination thereof. The above modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory in the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0108] Embodiment 3

[0109] See also Figure 3The present invention provides a computer device, including a memory, a processor, and computer-readable instructions stored in the memory and executable on the processor. When the processor executes the computer-readable instructions, the steps of the above method are implemented.

[0110] Those of ordinary skill in the art will appreciate that the units of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition of each example has been generally described in terms of function in the above description. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0111] In the embodiments provided by the present invention, it should be understood that the division of units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units can be combined into one unit, one unit can be split into multiple units, or some features can be ignored. In addition, each functional unit in each embodiment of the present invention can be integrated into a processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units.

[0112] 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 invention, in essence, 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, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-0nlyMemory), random access memory (RAM, RandomAccessMemory), mobile hard disk, magnetic disk or optical disk, etc., which can store program code.

[0113] It can be understood that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or replace some or all of the technical features therein by equivalents. These modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be included in the scope of the claims and specification of the present invention.

Claims

1. A method for distributing electric power materials based on a long cycle, characterized in that: include: Obtaining a first material inventory of each power supply station within a first preset time and a material consumption of each power supply station within a second preset time; Calculate the second material inventory of each power supply station within a second preset time according to the first material inventory and material consumption; Determine whether the second material inventory of each power supply station is lower than the preset safety stock level, and if so, determine the target power supply station whose second inventory is lower than the safety stock level, and calculate the material capacity required by the central warehouse for distribution of the target power supply station; The corresponding target distribution plan is determined based on the material capacity required by the central warehouse for distribution of the target power supply.

2. The long-cycle power material distribution method according to claim 1 is characterized in that: The obtaining of the first material inventory of each power supply station within the first preset time and the material consumption of each power supply station within the second preset time includes: The material monitoring systems of the power supply stations are associated, and the first material inventory within the first preset time and the material consumption within the second preset time are collected according to the identification information of each power supply station.

3. The long-cycle power material distribution method according to claim 1 is characterized in that: The calculation formula for calculating the second material inventory of each power supply station within the second preset time according to the first material inventory and material consumption is as follows: S i，t =S i，t-1 -C i，t-1 +I i，t-1 ; Where: S i，t is the inventory balance of materials in each power supply station from the first preset time t-1 to the second preset time t, S i，t-1 is the inventory of materials in each power supply station within the first preset time t-1, C i，t-1 is the material consumption of each power supply station within the first preset time t-1, I i，t-1 The first preset time is the inventory of materials at each power supply station within t-1.

4. The long-cycle power material distribution method according to claim 1 is characterized in that: The determining of the corresponding target distribution plan based on the materials required to be distributed by the central warehouse for the target power supply includes: The objective function is constructed with the goal of minimizing the total cost of distributing materials from the central warehouse; Determine constraints, wherein the constraints include a constraint that each power station is served by one vehicle, a site constraint, a vehicle entry center constraint, a secondary cycle elimination condition constraint, and a time window constraint; A distribution plan for the target power supply station is determined according to the optimal solution of the objective function.

5. The long-cycle power material distribution method according to claim 4 is characterized in that: The expression of the objective function is as follows: Where: C T is the total delivery cost of all vehicles, C j is the unit distance transportation cost of the jth vehicle, R j [i+1] is the distance between the i-th node and the i+1-th node on the route of the j-th vehicle, n j is the number of stations on the line, P j is the unit distance transportation cost of the jth vehicle.

6. The long-cycle power material distribution method according to claim 4 is characterized in that: The expressions of the constraints are as follows: Each power station is served by one vehicle: Site constraints: Secondary cycle elimination conditions: Time window constraints: Where: the directed graph G = (V, E) represents the distribution network, V = {0, 1, ..., N} represents the node set, node 0 represents the starting power supply station, V\{0} represents the distribution site, E = {(i, j)i, j∈V, i≠j} represents the arc set, K = {1, ..., M} represents the distribution vehicle set, M represents the number of vehicles required, Q represents the vehicle load, d i represents the demand of node i, AT ki represents the arrival time of vehicle k at node i, WT ki represents the waiting time of vehicle k at node i, s i represents the service time of vehicle k at node i, t ij represents the travel time of vehicle k between node i and node j, [e i , l i ] represents the time window of node i, x ijk is a binary variable indicating whether the vehicle travels from node i to node j, and p3 is a constant used to ensure that the constraint condition is ijk =0.

7. The long-cycle power material distribution method according to claim 1 is characterized in that: The determining whether the second material inventory of each power supply station is lower than a preset safety inventory level includes: If not, the third material inventory of each power supply station within the third preset time is calculated.

8. A long-cycle power material distribution system, characterized in that: include: An inventory and consumption acquisition unit, used to acquire a first material inventory of each power supply station within a first preset time and a material consumption of each power supply station within a second preset time; A second material inventory calculation unit, used to calculate the second material inventory of each power supply station within a second preset time according to the first material inventory and material consumption; A second material inventory determination unit, used to determine whether the second material inventory of each power supply station is lower than a preset safety inventory level; The target power supply station determination unit is used to determine the target power supply station whose second inventory is lower than the safety inventory level when the second material inventory of each power supply station is lower than the preset safety inventory level, and calculate the material capacity required by the central warehouse for distribution of the target power supply station; The target distribution plan determining unit is used to determine the corresponding target distribution plan based on the materials that the central warehouse needs to distribute to the target power supply.

9. A computer device, characterized in that: include: memories, transceivers, processors, and bus systems; Wherein, the memory is used to store programs; The processor is used to execute the program in the memory, including executing the long-cycle-based power material distribution method according to any one of claims 1 to 7; The bus system is used to connect the memory and the processor so that the memory and the processor can communicate with each other.

10. A readable storage medium, characterized in that: The method comprises instructions which, when executed on a computer, enable the computer to execute the long-cycle-based power material distribution method according to any one of claims 1 to 7.

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