Logistics network layout method for electric power emergency material dispatching

Abstract

The invention discloses a logistics network layout method for electric power emergency material dispatching, and the method can optimize the layout of emergency materials through constructing a network layout model, can make a timely response more quickly when a sudden fault occurs in an electric power system, and guarantees the recovery of the electric power system as soon as possible. Moreover, the time and cost of material distribution are comprehensively considered, so that the cost can be reduced as much as possible while the emergency materials of the power system meet the requirements. According to the method disclosed by the invention, a data-driven emergency logistics network basic model is constructed by combining the current situation of emergency management of a power system and taking the maximization of the emergency service level as a target. According to the method, social benefits are created in the field of electric power emergency, an existing electric power system emergency management method is improved, influences and losses are reduced to the maximum extent, the efficiency and flexibility of emergency material dispatching in an electric power system are further improved, and the emergency response cost is effectively controlled.

Description

Technical Field

[0001] The present invention belongs to the field of logistics network layout, and in particular relates to a logistics network layout method for power emergency material dispatching. Background Art

[0002] Traditional power grid emergency management methods often rely on manual judgment and experience, resulting in slow response times and unscientific decision-making. Furthermore, the specialized nature of power emergency supplies requires high standards for storage and maintenance. The lack of effective cost control mechanisms makes it difficult to effectively reduce overall operating costs. Efficiently allocating grid resources, optimizing material dispatch, and ensuring timely and cost-effective dispatch have become pressing challenges in the power industry.

[0003] In recent years, with the development of technologies such as big data and the Internet of Things, most power companies have established relatively comprehensive emergency material storage and distribution networks. These networks typically include multiple regional warehouses and a central control center to coordinate resources across regions. Modern information technologies, such as GIS (Geographic Information Systems) and ERP (Enterprise Resource Planning) systems, have been widely used in the management of power emergency materials to improve the efficiency and accuracy of material dispatch. Based on a new data-driven perspective, domestic and foreign scholars have also devoted themselves to research on emergency management and achieved certain research results. Li Wei et al. (2023) used an agent-based modeling approach to study the coordination of emergency logistics in power systems. By simulating the behavior and interactions of different agents, they explored methods to improve logistics efficiency. Wang Hua et al. (2020) explored how to use dynamic programming methods to optimize emergency resource allocation in power grids. Their solution can effectively cope with dynamic changes in resource demand. Zhang Li et al. (2019) proposed a multi-objective optimization model for emergency logistics management during power system restoration. The model aims to minimize restoration time and cost while ensuring that all damaged areas receive timely service. It can be seen from this that the research on emergency material dispatch in the big data era will gradually shift its focus to data-driven modeling, paying more attention to the efficiency and timeliness of material dispatch. Summary of the Invention

[0004] To solve the problems existing in the prior art, the present invention proposes a logistics network layout method for power emergency material dispatch. This method comprehensively considers the demand satisfaction time and the total cost of emergency power supply in each region, takes the maximization of emergency service level as the goal, and constructs a 0-1 mixed nonlinear integer programming model to optimize the logistics network layout in the emergency power supply process.

[0005] The technical solutions of the present invention are as follows:

[0006] A logistics network layout method for power emergency material dispatching, wherein the emergency materials in the logistics network are dispatched from material storage warehouses and dispatched to power outage areas via regional distribution centers, including

[0007] A logistics network layout model that maximizes the comprehensive emergency service level is constructed. The logistics network layout model aims to achieve the optimal coordination between the time required to meet emergency material needs and the total cost of power emergencies. The model uses the location of the regional distribution center, the service relationship between the regional distribution center and the power outage area, and the material transportation volume between the material storage depot and the regional distribution center, as well as between the regional distribution center and the power outage area, as decision variables. The model also uses the service uniqueness constraint between the power outage area and the regional distribution center, the supply and demand balance constraint, the total resource constraint, the regional distribution center service constraint, the regional distribution center quantity constraint, and the storage depot capacity constraint as constraints.

[0008] Solve the logistics network layout model to obtain a logistics network layout plan.

[0009] Furthermore, the objective function of the logistics network layout model is:

[0010] max ESL=αESL1+(1-α)ESL2

[0011] Where ESL is the comprehensive emergency service level; ESL1 is the time indicator for meeting emergency material demand; ESL2 is the total cost indicator for power emergency; and α is the weight parameter for the emergency service level.

[0012] Furthermore, the expression of the emergency material demand satisfaction time indicator ESL1 is:

[0013]

[0014] Where K is the total number of power outage areas; h k is the proportion of unmet demand in the kth power outage area; p(h k ) is the impact of the proportion of unmet demand in the kth power outage area on ESL1; ω k is the proportion of the population of power outage area k to the total population of all power outage areas, ε jk is a 0-1 variable, indicating whether the j-th regional distribution center provides power emergency supplies services to the k-th circuit interruption area. If so, ε jk =1, otherwise 0, the same applies to other sub-labels; J is the total number of regional distribution centers; x jk is the amount of supplies that the j-th regional distribution center can provide to the k-th circuit interruption area; d k is the total material demand in the kth circuit interruption area.

[0015] Furthermore, the expression of the total cost indicator ESL2 of power emergency is:

[0016]

[0017] Where C TL and C LTL are the unit transportation costs from the material storage warehouse to the distribution center and from the distribution center to the material supply area; j is a 0-1 variable, indicating whether the j-th regional distribution center is set. If set, then z j =1, otherwise z j =0;y ij and D ij are the quantity and distance of materials that the i-th storage warehouse can provide to the j-th distribution center, and the same applies to other sub-labels; x ij is the amount of materials that the i-th distribution center can provide to the j-th region; VC j is the operating cost of the j-th material distribution center; Ω min is the minimum value of the emergency budget; Ω max is the maximum emergency budget; f is the total cost of emergency supplies; λ and b are the first and second intermediate parameters respectively; C j is the operating cost of the j-th regional distribution center; D jk is the distance from the jth distribution center to the kth interruption area.

[0018] Furthermore, the expression of the service uniqueness constraint between the power outage area and the regional distribution center is:

[0019]

[0020] Furthermore, the expression of the supply and demand balance constraint is:

[0021]

[0022] Furthermore, the expression of the total resource constraint is:

[0023]

[0024] Furthermore, the expression of the regional distribution center service constraint is:

[0025]

[0026] Furthermore, the expression for the number constraint of regional distribution centers is:

[0027]

[0028] Furthermore, the expression of the reserve capacity constraint is:

[0029]

[0030] Compared with the prior art, the present invention has the following beneficial effects:

[0031] The present invention provides a logistics network layout method for dispatching power emergency materials. By constructing a network layout model, the method can optimize the layout of emergency materials, respond more quickly to sudden failures in the power system, and ensure the recovery of the power system as soon as possible. Moreover, by comprehensively considering the time and cost of material distribution, the method can reduce costs as much as possible while ensuring that the power system emergency materials meet demand.

[0032] This method, based on the current state of power system emergency management and aiming to maximize emergency service levels, constructs a data-driven foundational model for emergency logistics networks. This approach has created social benefits in the field of power emergencies. It improves existing power system emergency management methods, minimizing impacts and losses, further enhancing the efficiency and flexibility of emergency material dispatch within the power system, and effectively controlling emergency response costs. It also provides support for emergency material storage and deployment for power grid emergencies.

[0033] The method of the present invention dynamically optimizes material distribution paths and network layouts through a data-driven 0-1 mixed nonlinear integer programming model, thereby shortening emergency response time. The present invention comprehensively weighs time and cost weights, minimizes total costs while meeting emergency needs, and improves resource utilization efficiency. The present invention introduces a dynamic setting mechanism for regional distribution centers (RDCs) to adapt to differences in demand density in different regions and improve the adaptability of network layout. The present invention quantifies demand satisfaction rates and cost impacts through mathematical modeling, providing a scientific and systematic decision-making basis for power emergency management. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 A flow chart of a logistics network layout method for power emergency material dispatching;

[0035] Figure 2 Flowchart for constructing a logistics network layout model to maximize the comprehensive emergency service level. DETAILED DESCRIPTION

[0036] The present invention is further illustrated below with reference to the accompanying drawings and specific embodiments. It should be understood that these embodiments are only used to illustrate the present invention and are not used to limit the scope of the present invention. After reading the present invention, various equivalent modifications of the present invention by those skilled in the art fall within the scope defined by the claims attached to this application.

[0037] Example 1:

[0038] The present invention provides a logistics network layout method for power emergency material dispatching, wherein the logistics network adopts a two-level logistics network, wherein emergency materials in the two-level logistics network are issued from material storage depots and dispatched to power outage areas via regional distribution centers (also known as "RDCs"), and is characterized by including:

[0039] A logistics network layout model that maximizes the comprehensive emergency service level is constructed. The logistics network layout model aims to achieve the optimal coordination between the time situation of meeting the demand for emergency materials in a rapid response and the total cost situation of the power emergency in a cost-controlled manner. The model uses the location of the regional distribution center, the service relationship between the regional distribution center and the power outage area, and the material transportation volume between the material storage depot and the regional distribution center, as well as between the regional distribution center and the power outage area, as decision variables. The model also uses the service uniqueness constraint between the power outage area and the regional distribution center, the supply and demand balance constraint, the total resource constraint, the regional distribution center service constraint, the regional distribution center quantity constraint, and the storage depot capacity constraint as constraint conditions.

[0040] Solve the logistics network layout model to obtain a logistics network layout plan.

[0041] Furthermore, the material reserve warehouse, as the source storage facility for emergency materials, is usually located in a strategic location and is responsible for the centralized storage of large quantities of power emergency materials (such as transformers, cables, maintenance equipment, etc.). The regional distribution center is the intermediate node of the logistics network and is dynamically set according to the optimization model. The power outage area is the terminal demand area where power failure occurs and needs to receive emergency materials to restore power supply. The power emergency material dispatch path is material reserve warehouse ~ regional distribution center ~ power outage area. The method of the present invention aims to build an efficient and low-cost emergency material dispatch network by optimizing the site selection, service relationship and material distribution volume of the regional distribution center to quickly respond to sudden failures in the power system.

[0042] In one embodiment, the objective function of the logistics network layout model is:

[0043] max ESL=αESL1+(1-α)ESL2

[0044] Where ESL is the comprehensive emergency service level; ESL1 is the time indicator for meeting emergency material demand; ESL2 is the total cost indicator for power emergency; and α is the weight parameter for the emergency service level.

[0045] In one embodiment, the expression of the emergency material demand satisfaction time indicator ESL1 is:

[0046]

[0047] Where K is the total number of power outage areas, and h represents the set of power outage areas; kis the proportion of unmet demand in the kth power outage area; p(h k ) is the impact of the proportion of unmet demand in the kth power outage area on ESL1; ω k is the proportion of the population of power outage area k to the total population of all power outage areas, ε jk is a 0-1 variable, indicating whether the j-th regional distribution center provides power emergency supplies services to the k-th circuit interruption area. If so, ε jk =1, otherwise 0, the same applies to other sub-labels; J is the total number of regional distribution centers; x jk is the amount of supplies that the j-th regional distribution center can provide to the k-th circuit interruption area; d k is the total demand for emergency supplies in the kth power outage area.

[0048] In one embodiment, the total cost indicator ESL2 of the power emergency is expressed as:

[0049]

[0050] Where C TL and C LTL are the unit transportation costs from the material storage warehouse to the distribution center and from the distribution center to the material supply area; j is a 0-1 variable, indicating whether the j-th regional distribution center is set. If set, then z j =1, otherwise z j =0;y ij and D ij are the quantity and distance of materials that the i-th storage warehouse can provide to the j-th distribution center, and the same applies to other sub-labels; x ij is the amount of materials that the i-th distribution center can provide to the j-th region; VC j is the operating cost of the j-th material distribution center; Ω min is the minimum value of the emergency budget; Ω max is the maximum emergency budget; f is the total cost of emergency supplies; λ and b are the first and second intermediate parameters respectively; C j is the operating cost of the j-th regional distribution center; D jk is the distance from the jth distribution center to the kth interruption area.

[0051] In one embodiment, the service uniqueness constraint between the power outage area and the regional distribution center indicates that the emergency supplies demand in each region is only provided by one distribution center. The expression of the service uniqueness constraint is:

[0052]

[0053] In one embodiment, the supply-demand balance constraint indicates that the amount of emergency supplies supplied to each region must not exceed the demand in that region. The supply-demand balance constraint is expressed as:

[0054]

[0055] In one embodiment, the total resource constraint indicates that the demand for emergency supplies should be met as much as possible. The expression for the total resource constraint is:

[0056]

[0057] In one embodiment, the regional distribution center service constraint indicates that the emergency material distribution service is provided by a designated material center. The expression of the regional distribution center service constraint is:

[0058]

[0059] In one embodiment, the regional distribution center quantity constraint indicates that the number of regional distribution centers is limited. The expression for the regional distribution center quantity constraint is:

[0060]

[0061] In one embodiment, the reserve capacity constraint indicates that the supply capacity of each reserve is limited. The expression of the reserve capacity constraint is:

[0062]

[0063] The present invention solves the 0-1 mixed nonlinear integer programming model to ultimately obtain an optimal layout plan for the power emergency logistics network, which specifically includes:

[0064] The location of the regional distribution center is determined by the candidate locations (j) where the regional distribution center is set up. j The value of is determined;

[0065] The service relationship between the regional distribution center and the power outage area, that is, the material distribution relationship, is represented by ε jk The value of is determined;

[0066] Material distribution volume: the amount of material transported from the storage warehouse to the regional distribution center ij , and the amount of material transported from the regional distribution center to the power outage area x jk .

[0067] Example 2:

[0068] This embodiment further illustrates the construction of the logistics network layout model based on the first embodiment. The specific steps are as follows:

[0069] Step 1: Parameter setting

[0070] Set the emergency service level weight parameter α.

[0071] Set the minimum emergency budget Ω min .

[0072] Set the maximum value of the emergency budget Ω max .

[0073] Step 2: Calculate the emergency service level index

[0074] Calculate the time indicators for meeting emergency material needs

[0075] Let ESL1 be the first indicator of the power emergency service level standard, which represents the time of meeting the demand for emergency supplies. The impact of the demand on ESL1 is calculated by the proportion of unmet demand in each region. ESL1 is the sum of the impact of unmet demand in each region. The specific calculation formula is as follows

[0076]

[0077] In the above formula, K is the set of power outage areas, h k is the proportion of unmet demand in the kth power outage area, p(h k ) is the impact of the proportion of unmet demand in the kth power outage area on ESL1. k is the proportion of the population of power outage area k to the total population of all power outage areas, ε jk is a 0-1 variable, indicating whether the jth RDC provides power emergency supplies services to the kth circuit interruption area. If so, ε jk =1, otherwise it is 0, and the same applies to other sub-labels.

[0078] (2) Calculate the total cost of power emergency

[0079] Let ESL2 be the second standard indicator of power emergency service level, which represents the total cost of power emergency. The specific description is as follows:

[0080]

[0081] The calculation formulas for λ and b in formula (4) are:

[0082]

[0083] f is the total cost of emergency supplies, and the calculation process is:

[0084]

[0085] Among them, C TL and CLTL are the unit transportation costs from the material storage warehouse to the distribution center and from the distribution center to the material supply area; j Is a 0-1 variable, whether to set the jth RDC, if set, then z j =1, otherwise z j =0;y ij and D ij are the quantity and distance of materials that the i-th storage warehouse can provide to the j-th distribution center, and the same applies to other sub-labels; x ij is the amount of materials that the i-th distribution center can provide to the j-th region; VC j is the operating cost of the j-th material distribution center.

[0086] ESL is the emergency service level of the entire power system. The value of the emergency service level (ESL) is calculated by summing the time to meet power emergency material demand (ESL1) and the total emergency cost (ESL2).

[0087] Step 3: Construct the objective function

[0088] The emergency service level of the power system is comprehensively characterized from two aspects: the time to meet the demand for emergency materials (ESL1) and the total cost of power emergency (ESL2). Combining the time and cost weights, the objective function of the model is given as follows:

[0089] max ESL=αESL1+(1-α)ESL2 (7)

[0090] Step 4: Construct model constraints

[0091] Taking into account the differences in economic development between regions, more developed regions tend to have denser populations. When the logistics of power emergency supplies fail to meet demand, the impact is greater and the consequences are more serious. k To measure severity.

[0092] The following constraints are given based on the actual power supply:

[0093] (1) Each region's emergency supplies are provided by only one distribution center, i.e.

[0094] (2) The amount of emergency supplies supplied to each region does not exceed the demand of the region, that is,

[0095] (3) The demand for emergency supplies should be met as much as possible, i.e.

[0096] (4) Emergency material distribution services are provided by designated material centers, namely

[0097] (5) There is a certain limit on the number of regional distribution centers, i.e.

[0098] (6) Each reserve has a limited supply capacity, i.e.

[0099] Step 5: Build a material layout optimization model

[0100] According to the second and third steps, the following optimization model is constructed:

[0101] max ESL=αESL1+(1-α)ESL2

[0102]

[0103] The above description is only a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by a technician familiar with this technical field within the technical scope disclosed by the present invention should be covered by the scope of protection of the present invention.

Claims

1. A logistics network layout method for dispatching power emergency supplies, wherein emergency supplies in the logistics network are dispatched from a material reserve warehouse and dispatched to power outage areas via a regional distribution center, characterized in that: The method includes constructing a logistics network layout model that maximizes the comprehensive emergency service level, wherein the logistics network layout model aims to optimize the coordination between the time for meeting emergency material demand and the total cost of power emergency, and uses the location of the regional distribution center, the service relationship between the regional distribution center and the power outage area, and the material transportation volume between the material storage depot and the regional distribution center, and between the regional distribution center and the power outage area as decision variables, and uses the service uniqueness constraint between the power outage area and the regional distribution center, the supply and demand balance constraint, the total resource constraint, the regional distribution center service constraint, the regional distribution center quantity constraint, and the storage depot capacity constraint as constraint conditions; Solve the logistics network layout model to obtain a logistics network layout plan.

2. The logistics network layout method for power emergency material dispatching according to claim 1 is characterized in that: The objective function of the logistics network layout model is: max ESL=αESL1+(1-α)ESL2 Where ESL is the comprehensive emergency service level; ESL1 is the time indicator for meeting emergency material demand; ESL2 is the total cost indicator for power emergency; and α is the weight parameter for the emergency service level.

3. The logistics network layout method for power emergency material dispatching according to claim 2 is characterized in that: The expression of the emergency material demand satisfaction time indicator ESL1 is: Where K is the total number of power outage areas; h k is the proportion of unmet demand in the kth power outage area; p(h k ) is the impact of the proportion of unmet demand in the kth power outage area on ESL1; ω k is the proportion of the population of power outage area k to the total population of all power outage areas, ε jk is a 0-1 variable, indicating whether the j-th regional distribution center provides power emergency supplies services to the k-th circuit interruption area. If yes, then ε jk =1, otherwise 0, the same applies to other sub-labels; J is the total number of regional distribution centers; x jk is the amount of supplies that the j-th regional distribution center can provide to the k-th circuit interruption area; d k is the total demand for emergency supplies in the kth power outage area.

4. The logistics network layout method for power emergency material dispatching according to claim 3 is characterized in that: The expression of the total cost indicator ESL2 of the power emergency is: Where C TL and C LTL The unit transportation costs are from the material storage warehouse to the distribution center and from the distribution center to the material supply area respectively; z j is a 0-1 variable, indicating whether the j-th regional distribution center is set. If set, then z j =1, otherwise z j =0;y ij and D ij are the quantity and distance of materials that the i-th storage warehouse can provide to the j-th distribution center, and the same applies to other sub-labels; x ij is the amount of materials that the i-th distribution center can provide to the j-th region; VC j is the operating cost of the j-th material distribution center; Ω min is the minimum value of the emergency budget; Ω max is the maximum emergency budget; f is the total cost of emergency supplies; λ and b are the first and second intermediate parameters respectively; C j is the operating cost of the j-th regional distribution center; D jk is the distance from the jth distribution center to the kth interruption area.

5. The method for logistics network layout for power emergency material dispatching according to claim 4 is characterized in that: The expression of the service uniqueness constraint between the power outage area and the regional distribution center is:

6. The method for logistics network layout for power emergency material dispatching according to claim 5 is characterized in that: The expression of the supply and demand balance constraint is:

7. The method for logistics network layout for power emergency material dispatching according to claim 6, characterized in that: The expression of the total resource constraint is:

8. The method for logistics network layout for power emergency material dispatching according to claim 7 is characterized in that: The expression of the regional distribution center service constraint is:

9. The method for logistics network layout for power emergency material dispatching according to claim 8, characterized in that: The expression for the regional distribution center quantity constraint is:

10. The method for logistics network layout for power emergency material dispatching according to claim 9, characterized in that: The expression of the reserve capacity constraint is:

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