Electric power material storage, distribution and management system

Abstract

The invention relates to the technical field of electric power material management and logistics distribution, and particularly discloses an electric power material storage, distribution and management system, which comprises a storage layering and grading management module, an active distribution scheduling module, a multi-scene inventory balance model module and an informatization integrated management module. A three-level storage framework of a distribution center, a branch library and a terminal library is constructed, and a hierarchical and hierarchical optimization model is adopted to plan and optimize the layout based on 0-1 integers; driving active delivery based on demand prediction, and making an active delivery strategy combining primary delivery and secondary delivery; establishing an inventory balance model of three scenes of arrival pre-arrangement, inventory optimization and inventory overstock, and realizing cost optimization and inventory balance through a quantification formula; and real-time sharing and monitoring of data are realized based on informatization integrated management. The system is suitable for various regional power systems, can effectively improve the storage capacity utilization rate, reduce the distribution cost and enhance the supply chain toughness, and solves the problems of layout imbalance, passive distribution, inventory misalignment and the like in the prior art.

Description

Technical Field

[0001] This invention relates to the field of power material management and logistics distribution technology, specifically to a power material warehousing, distribution and management system applicable to power grids of various voltage levels and power companies of different sizes, integrating hierarchical management and proactive distribution mechanisms. Background Technology

[0002] As a core support for power grid construction, operation and maintenance, and emergency response, the efficiency of power material warehousing, distribution, and management directly determines the stability of power grid operation and the reliability of power supply. It is a crucial link for power companies to achieve intensive operation and enhance the resilience of the industrial and supply chains. Currently, the systemic problems facing the power material warehousing and distribution sector are becoming increasingly prominent, making it difficult to meet the refined and intelligent management needs of modern power systems. These problems manifest themselves as follows: The warehouse layout is unbalanced and resource utilization is low: power material warehouses are mostly scattered according to administrative regions. Although some areas have built large-scale warehousing networks (such as some areas with dozens or even hundreds of warehouses, covering a total area of ​​hundreds of thousands of square meters), the hierarchical division and functional positioning are unclear, resulting in a serious uneven distribution of warehouse capacity resources. On the one hand, core warehousing nodes often face the pressure of "warehouse overload," while on the other hand, a large number of warehouse locations are idle. For example, the utilization rate of some warehouse yards is less than 10%, or even 0%. The utilization rate of warehouse spaces such as racks and temporary storage areas is also generally low, and the role of the "reservoir" for inventory is not fully utilized. At the same time, the hardware configuration of warehouses is uneven, and the coverage of modern equipment is low. Only a few warehouses are equipped with intelligent equipment such as three-dimensional racks, AGV / RGV, and RFID radio frequency identification. Most warehouses still rely on traditional manual operations, resulting in low warehousing efficiency.

[0003] The traditional power supply distribution model is passive and lacks timely response: It primarily operates on a passive "demand-supplier response" model. Demanders submit their needs in advance, and suppliers then organize procurement, allocation, and distribution, lacking accurate forecasting and proactive allocation capabilities. Under this model, the timeliness of emergency supplies delivery and fault repair material replenishment is difficult to guarantee, and the pressure on supply security continues to increase due to external factors such as geographical location, climate, and transportation conditions. Furthermore, the distribution process contains redundant steps, requiring some materials to undergo multiple transfers before reaching the demand site, increasing logistics costs and reducing delivery reliability.

[0004] Inaccurate inventory management and a significant imbalance between storage and demand: Power supply materials are diverse (including infrastructure materials, operation and maintenance materials, and emergency supplies), with significantly different storage requirements and demand characteristics for different types. However, existing inventory management lacks targeted and precise models to support this. On the one hand, some materials suffer from inventory backlogs due to inaccurate demand forecasts and rigid replenishment mechanisms; others have excessively long inventory ages and slow turnover, consuming substantial storage space and capital. On the other hand, insufficient inventory or untimely allocation of some operation and maintenance and emergency supplies affects normal power grid operation and fault repair, making it difficult to maintain a dynamic balance between storage and demand.

[0005] The level of informatization is lagging behind and data silos are obvious: data collection in warehousing, distribution, and inventory relies heavily on manual recording or decentralized systems, lacking a unified integrated management platform. This makes it difficult to collect and share data throughout the entire lifecycle of materials in real time. There are significant data barriers between warehouses and between supply and demand sides. Information such as inventory status, demand plans, and delivery progress is not synchronized in a timely manner, which not only affects decision-making efficiency but also leads to insufficient management precision, failing to provide data support for warehouse layout optimization and distribution strategy adjustments.

[0006] These problems not only increase the construction costs of power companies' warehousing, logistics, and capital costs, but also weaken the resilience of the power supply chain and hinder the digital transformation and high-quality development of power companies. Therefore, it is urgent to build an integrated system that takes into account layout optimization, proactive delivery, inventory balancing, and intelligent management to solve the industry's pain points. Summary of the Invention

[0007] The purpose of this invention is to solve the technical problems of unbalanced layout, passive delivery, inaccurate inventory, and inefficient management in the existing power material warehousing, distribution, and management. It provides an integrated system based on a hierarchical management architecture, an active delivery mechanism, and a multi-scenario inventory balancing model to achieve optimized power material warehousing layout, efficient delivery response, dynamic inventory balancing, and full-process management visibility, thereby improving the overall operational efficiency and resilience of the power material supply chain.

[0008] To achieve the above objectives, this invention provides a power material warehousing, distribution, and management system, including a tiered warehousing management module, an active distribution scheduling module, a multi-scenario inventory balancing model module, and an information integration management module. These modules work together to achieve intelligent management of power materials throughout their entire lifecycle. The specific technical solution is as follows: The tiered warehouse management module is used to construct a three-tiered warehouse architecture: distribution center, branch warehouses, and terminal warehouses. Distribution centers are the core regional warehouse nodes, responsible for the storage of critical materials, overall material allocation, and management. Branch warehouses are supplementary regional warehouse nodes, responsible for material storage, terminal warehouse replenishment, and localized distribution within their respective regions. Terminal warehouses are the basic warehouse nodes, responsible for localized material storage and distribution to nearby demand points. The number and coverage radius of each level of nodes can be flexibly adjusted based on regional scope and electricity demand. A tiered evaluation index system is established, employing a combination of qualitative and quantitative screening methods to select the best warehouses for each level from existing warehousing resources. Screening criteria include: branch warehouses must have a warehouse area ≥ 1000 square meters, complete warehousing facilities and equipment, and terminal warehouses whose storage capacity is not nearing saturation; priority should be given to locations with convenient transportation (close to highways, railways, national roads, etc.) and in urban areas to attract technical personnel, avoiding redundant construction and reducing layout costs; a tiered optimization model is adopted, using 0-1 integer programming to optimize the tiered layout and material allocation. The proactive delivery scheduling module includes a demand forecasting unit, a delivery decision-making unit, and a route and capacity optimization unit. The demand forecasting unit forecasts material demand based on multi-source data. The delivery decision-making unit formulates a proactive delivery strategy that combines primary and secondary deliveries based on a three-tier warehousing architecture and the inventory status and capacity threshold of each warehouse. The route and capacity optimization unit optimizes delivery routes and coordinates the allocation of transportation resources. The multi-scenario inventory balancing model module includes an arrival pre-arrangement inventory balancing model, an inventory optimization inventory balancing model, and an inventory backlog resolution model, which are adapted to the inventory allocation needs of material arrival, daily operation and maintenance, and inventory backlog scenarios, respectively. The arrival pre-arrangement inventory balancing model, the inventory optimization inventory balancing model, and the inventory backlog resolution model all aim to minimize the overall cost. The information integration management module is used to collect data from the entire process, including warehousing, distribution, and inventory. It relies on the smart supply chain platform to achieve data sharing, real-time monitoring, and anomaly warning, supporting the balanced utilization of warehouse capacity across the entire domain.

[0009] As a further description of the above technical solution: the hierarchical evaluation index system takes into account various factors such as politics, economy, environment, labor force, and supporting facilities, specifically covering policy adaptability, economic cost, transportation conditions, warehousing capacity, and operation and maintenance resources. Among them, the policy adaptability dimension refers to the national and provincial construction policies and economic development strategies; the economic cost dimension covers warehouse construction costs, distribution costs, and operating costs; the transportation conditions dimension includes the coverage of transportation lines such as highways, railways, and national highways; the warehousing capacity dimension involves warehouse area, facility and equipment configuration, and storage capacity; and the operation and maintenance resources dimension includes human resource supply and the operational level of technical personnel.

[0010] As a further description of the above technical solution: the hierarchical optimization model aims to minimize the sum of transportation costs, operation and maintenance costs, and time penalty costs. The constraints include the matching constraint between the inflow and demand of terminal warehouses, the upper limit constraint of warehouse capacity, and the non-negative constraint of service radius exceeding distance. The hierarchical evaluation index system adopts a screening method that combines qualitative and quantitative methods, and the warehouses are selected from terminal warehouses with a warehouse area of ​​≥1000 square meters, complete warehousing facilities and equipment, and warehouse capacity that is not close to saturation.

[0011] As a further description of the above technical solution: The demand forecasting unit of the active delivery scheduling module uses a time series forecasting algorithm or machine learning algorithm supported by big data analysis to forecast material demand (including material demand type, quantity and time window). The input data includes historical requisition data, power project progress data, equipment operation and maintenance plan data, emergency event early warning data and material consumption trend data. The focus is on forecasting "high-frequency" demand materials based on big data analysis.

[0012] As a further description of the above technical solution: Based on the hierarchical warehousing architecture, the distribution decision unit formulates an active distribution strategy that combines primary and secondary distribution, taking into account factors such as the inventory status, storage capacity threshold, and distribution costs of each warehouse. After the supplier produces materials, based on the monthly demand plan and current inventory status, and based on the functions of each warehouse and distribution optimization principles, the production materials are divided into two parts. One part of the materials is prioritized for distribution to the sub-warehouse (primary distribution). When the inventory in the terminal warehouse is lower than the safety threshold, the distribution center or sub-warehouse initiates replenishment distribution (secondary distribution). At the same time, it supports cross-level allocation and distribution of backlogged materials.

[0013] As a further description of the above technical solution: the route and capacity optimization unit comprehensively considers constraints such as transportation distance, road conditions, vehicle load, and carbon emission costs, and uses operations research optimization algorithms to generate the optimal delivery route and dynamically allocate transportation resources to reduce transportation losses and costs and improve delivery timeliness.

[0014] As a further description of the above technical solution: the comprehensive cost of the pre-arrangement inventory balancing model includes fixed costs, transportation costs and carbon emission costs, which are calculated by a quantitative formula that includes vehicle load capacity, driving distance, fuel consumption coefficient and carbon emission coefficient. The constraints include distribution center capacity threshold constraints, demand matching degree constraints and vehicle load limit constraints. The distribution center threshold is obtained by simulation model data based on historical storage data.

[0015] As a further description of the above technical solution: the comprehensive cost of the inventory optimization and inventory balancing model includes fixed costs, transportation costs, carbon emission costs, and delivery delay penalty costs. It adopts a strategy of continuous inventory counting of safety stock and reserve stock, and sets a safety stock threshold and a maximum reserve threshold. When the inventory of the terminal warehouse is lower than the safety threshold, a replenishment instruction is automatically triggered. The delivery delay penalty cost is calculated based on the matching relationship between the delivery time and the preset optimal service time window and acceptable time window. When the acceptable time window is exceeded, a high penalty cost is triggered. The safety stock threshold and the maximum reserve threshold are determined by each terminal warehouse based on inventory management theory, combined with historical inventory status and inbound / outbound information.

[0016] As a further description of the above technical solution: The inventory backlog resolution model includes an inventory age early warning unit and a usable inventory resource pool. For inventory backlog scenarios, an inventory age early warning mechanism and a usable inventory resource pool are established. Backlogged materials are screened based on inventory age, and priority matching of target demand points is constructed based on the urgency of demand, delivery distance, and inventory capacity. Active delivery of backlogged materials is triggered through first-in-first-out (FIFO) requisition rules, cross-regional inventory balancing, and project-based matching. Simultaneously, inventory backlog is avoided by optimizing the accuracy of power material demand planning. Optimization measures include fully utilizing big data and cloud computing, real-time monitoring of material data, clarifying responsibilities and establishing reward and punishment methods, establishing an information exchange platform, improving the comprehensive quality of professional personnel, strengthening daily management, strictly controlling approval processes, meticulous management, and ensuring the uniqueness of material codes.

[0017] As a further description of the above technical solution: the information integration management module includes a data acquisition unit, a data sharing and collaboration unit, and a monitoring and early warning unit. The data acquisition unit collects data throughout the entire process through RFID radio frequency identification equipment, mobile operation terminals, positioning equipment, and WMS system; the data sharing and collaboration unit supports the data flow of the two-stage delivery business of "warehouse to warehouse, warehouse to warehouse, and warehouse to site"; and the monitoring and early warning unit realizes warehouse age warning, warehouse capacity threshold warning, and delivery delay warning.

[0018] Compared with the prior art, the present invention has the following beneficial effects: 1. Optimize warehouse layout: By adopting a hierarchical and layered architecture and a scientific site selection mechanism, the limitations of decentralized management of warehouse resources are broken, the overall warehouse capacity utilization rate is improved, resource waste is reduced, and the construction and operation and maintenance costs of warehouses are lowered; 2. Improve delivery efficiency: The proactive delivery model, combined with accurate demand forecasting, transforms the traditional passive model of "demand application - supplier response" into a proactive model of "forecasting and prediction - proactive allocation", shortening delivery response time and especially improving the timeliness of emergency supplies delivery; 3. Achieve inventory balance: The multi-scenario inventory balance model covers all scenarios, including arrival, daily operation and maintenance, and backlog resolution, effectively controlling the risks of inventory backlog and shortage, improving inventory turnover efficiency, and reducing capital occupation costs. 4. Enhance the precision of management: Information-integrated management enables real-time data collection, sharing, and monitoring, providing data support for management decisions and improving the intensive, refined, and intelligent level of power material management; 5. Enhance supply chain resilience: The system is flexible and adaptable, and its architecture and parameters can be adjusted according to the power demand scale, geographical conditions and warehousing resources of different regions. It is suitable for various regional power systems and improves the stability and risk resistance of the power material supply chain. Attached Figure Description

[0019] Figure 1 This is a diagram of a three-tiered warehousing structure for power materials.

[0020] Figure 2 It is a hierarchical structure and material flow diagram of the power grid material warehouse.

[0021] Figure 3 This is a diagram illustrating the strategy of continuous inventory checks for safety stock and reserve stock.

[0022] Figure 4 It is an inventory status diagram with safety stock set. Detailed Implementation

[0023] The claims of the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments, but this does not constitute any limitation on the present invention. Any limited modifications made by any person within the scope of protection of the claims of the present invention shall still be within the scope of protection of the claims of the present invention.

[0024] This invention provides a power material warehousing, distribution, and management system, including a tiered warehousing management module, an active distribution scheduling module, a multi-scenario inventory balancing model module, and an information integration management module. These modules work together to achieve intelligent management of power materials throughout their entire lifecycle. The specific technical solution is as follows: The tiered warehouse management module is used to construct a three-tiered warehouse architecture: distribution center - sub-warehouse - terminal warehouse. The three-tiered warehouse architecture is as follows: Figure 1 As shown, the main functions of warehouses at each level are as follows: Distribution center: A primary warehouse, it is the central part of the warehouse. According to the supply plan, it is responsible for regional storage and mainly has the functions of storing important materials, controlling material information, supplying and allocating materials. Sub-warehouses: These are secondary warehouses and constitute the main part. They serve as a supplement to the distribution center, responsible for regional storage. Considering the balance with the distribution center, excessive diversion should be avoided. Their main functions include storing materials within the region, supplying materials to meet demand, and distributing materials to terminal warehouses or demand sites. Terminal warehouse: This is a three-level warehouse and a basic component. In principle, it only stores self-procured materials and does not store regional materials. Its main functions are to store local materials and distribute materials to the demand site.

[0025] The transportation of power grid materials mainly falls into the following categories: When transporting infrastructure materials, the materials are transported directly from the supply point to the demand point. Generally, suppliers transport these materials directly to the power project's location without going through warehouses. However, when power material companies transport key materials such as production and maintenance components, or spare parts, a distribution center is required for allocation. The materials are first transported from the supplier to the distribution center, then allocated to branch warehouses or terminal warehouses, and finally transported to the demand location. Figure 2 As shown.

[0026] A tiered evaluation index system will be established, covering multiple factors such as politics, economy, environment, labor force, and supporting facilities. A selection method combining qualitative and quantitative approaches will be used to preferentially select warehouses at each level from existing warehousing resources. Selection criteria include: warehouses must have an area of ​​≥1000 square meters, complete warehousing facilities and equipment, and a storage capacity not nearing saturation; priority will be given to locations with convenient transportation (close to highways, railways, national roads, etc.) and in urban areas to attract technical personnel, avoiding redundant construction and reducing layout costs; and a management model combining centralized management and tiered authorization will be supported, with higher-level nodes coordinating material procurement, inventory allocation, and data monitoring. The lower-level nodes are responsible for localized warehousing operations, demand feedback, and material requisition, achieving a balance between unified scheduling of resources across the entire region and flexible local operations. The hierarchical evaluation index system includes policy adaptability, economic cost, transportation conditions, warehousing capacity, and operation and maintenance resources. The policy adaptability dimension refers to national and provincial construction policies and economic development strategies. The economic cost dimension covers warehouse construction costs, distribution costs, and operating costs. The transportation conditions dimension includes the coverage of transportation routes such as highways, railways, and national roads. The warehousing capacity dimension involves warehouse area, facility and equipment configuration, and storage capacity. The operation and maintenance resources dimension includes human resource supply and the operational level of technical personnel.

[0027] The hierarchical optimization model mentioned above uses transportation costs ( TC 1) Operation and maintenance costs ( TC 2) Time penalty cost ( TC 3) The goal is to minimize the sum, specifically: Transportation costs Transportation costs constitute a significant portion of a company's overall costs. The location, distance, and volume of the warehouse from supply and demand points determine the transportation methods and means a company uses to reduce costs. Therefore, transportation costs include the costs of transporting goods from the distribution center to the sub-warehouse, from the distribution center to the terminal warehouse, and from the sub-warehouse to the terminal warehouse. in,c For transportation rates, Q oi For from the distribution center o Transported to the branch warehouse i The volume of transport, d oi For from the distribution center o Transported to the branch warehouse i distance, Q oj For from the distribution center o Transported to terminal warehouse j The volume of transport, d oj For from the distribution center o Transported to terminal warehouse j distance, Q ij To shard the database i Terminal warehouse j The volume of transport ( ), d ij To shard the database i Terminal warehouse j distance ( ).

[0028] Operation and maintenance costs Warehouse operation and maintenance costs refer to the maintenance expenses for warehouse material management. These costs are usually related to the quantity of materials; the larger the quantity, the higher the operation and maintenance costs. in, α Storage fee rate for materials in a unit's warehouse. Q i For database partitioning i The demand, Q j For terminal library j The demand.

[0029] Time penalty cost In the transportation of power grid materials, the primary focus is on safety and reliability. While time-sensitive delivery is less critical in routine transport, the demands for timely delivery and customer satisfaction are increasing with the development of modern logistics. In the event of an emergency power outage, timely delivery to the site is crucial. Therefore, to make the hierarchical strategy model more comprehensive, time penalty costs are considered during model construction. When the demand from the location is low and far from the warehouse, the timeliness of warehouse delivery typically decreases. Since power grid warehouse delivery lacks time-based measurement, delivery time is converted into the warehouse's service radius. That is, when the distance from the demand location to the warehouse exceeds the warehouse's service radius, a penalty cost needs to be calculated for the selected warehouse location. in, Penalty rate per unit distance; For distances from the distribution center to the sub-warehouse that exceed the service radius of the distribution center, ; For distances from the distribution center to the terminal warehouse that exceed the service radius of the distribution center, ; This is because the distance from the shard to the terminal shard exceeds the shard's service radius. , r o The service radius of the distribution center r i The service radius of the sub-database.

[0030] In summary, this results in a total overall cost across the entire region. TC The smallest specific expression is as follows: The constraints include the matching constraint between terminal warehouse inflow and demand, the warehouse capacity limit constraint, and the non-negative constraint on service radius exceeding distance. Specifically: The inflow to the terminal library equals the demand: The outflow from the distribution center is less than the inventory capacity: in, S o For the capacity of the distribution center; The sum of outflow from distribution warehouses and demand is less than the inventory capacity. For database partitioning capacity, ; The inflow to the terminal warehouse is less than the inventory capacity: For terminal library The capacity; The distance from the distribution center to the sub-warehouse exceeds the service radius of the distribution center by 0 or more. The distance from the distribution center to the terminal warehouse that exceeds the service radius of the distribution center is greater than or equal to 0: The distance from the distribution center to the terminal warehouse that exceeds the service radius of the distribution center is greater than or equal to 0: .

[0031] The proactive delivery scheduling module includes a demand forecasting unit, a delivery decision-making unit, and a route and capacity optimization unit. The demand forecasting unit uses a time series forecasting algorithm or machine learning algorithm supported by big data analysis to forecast material demand (including material demand type, quantity, and time window). Input data includes historical requisition data, power project progress data, equipment operation and maintenance plan data, emergency event early warning data, and material consumption trend data. The delivery decision-making unit, based on the hierarchical warehousing architecture, and combined with factors such as the current inventory status, capacity utilization threshold, and delivery costs of each warehouse, formulates a combined delivery strategy of "first-time delivery + second-time delivery": after the supplier produces materials, according to the monthly demand plan and current inventory status, based on the functions of each warehouse and delivery optimization principles, the produced materials are divided into two parts. One part of the materials is prioritized for delivery to the branch warehouse (i.e., first-time delivery), and the remaining materials are delivered to the distribution center or branch warehouse, reducing the capacity pressure of the distribution center while increasing the capacity utilization of the branch warehouse. When the terminal warehouse inventory falls below the safety threshold, the distribution center or branch warehouse initiates replenishment and delivery (i.e., secondary delivery), while also supporting cross-level allocation and delivery of backlogged materials. The route and capacity optimization unit comprehensively considers constraints such as transportation distance, road conditions, vehicle load, and carbon emission costs, and uses operations research optimization algorithms to generate the optimal delivery route and dynamically allocate transportation resources to reduce transportation losses and costs and improve delivery timeliness.

[0032] The multi-scenario inventory balancing model module includes an arrival pre-arrangement inventory balancing model, an inventory optimization inventory balancing model, and an inventory backlog resolution model, which are adapted to the inventory allocation needs of material arrival, daily operation and maintenance, and inventory backlog scenarios, respectively.

[0033] The pre-arrival inventory balancing model is designed for supplier arrival scenarios. With the goal of "lowest overall cost", it constructs an optimization model that includes fixed costs, transportation costs, and carbon emission costs. Constraints include warehouse capacity thresholds, demand matching degree, and vehicle load limits. This model enables the reasonable allocation of arriving goods between distribution centers and sub-warehouses, avoiding backlog in a single warehouse.

[0034] The objective function is: in, These are fixed costs. Fixed costs in the material distribution process mainly include vehicle wear and tear costs and driver wages, etc. These costs are constants unrelated to the vehicle's load or distance traveled during the logistics and distribution process. Assume there are a total of... m Delivery vehicle, No. k The fixed cost of the vehicle is The total fixed costs in the logistics and distribution process for: ; The transportation cost, which mainly includes fuel consumption during vehicle operation and corresponding vehicle maintenance costs, is the cost of transporting goods. Indicates the first k The cost incurred by a vehicle traveling a unit distance. Indicate demand points a With demand points b The distance between them determines the transportation costs incurred during the logistics and distribution process. for: , Carbon emission costs: The carbon emission costs during goods delivery are related to many factors, including vehicle model, load capacity, speed, distance traveled, and road conditions. For ease of calculation, we only consider the vehicle's load capacity and the distance traveled during delivery. The fuel consumption per unit distance is related to the vehicle's load capacity as follows: Indicates load capacity Fuel consumption per unit distance traveled by the vehicle. Indicates the vehicle's cargo capacity. This indicates the vehicle's own weight. and This represents a constant related to carbon emissions.

[0035] Assuming the vehicle's maximum load capacity is Q The fuel consumption per unit distance traveled by a fully loaded vehicle is The fuel consumption per unit distance traveled by the vehicle when it is unloaded is Then the following relationship exists: The relationship between fuel consumption per unit distance and vehicle load capacity can be obtained as follows: As can be seen from the above formula, during the material distribution process, when the vehicle's cargo capacity is... At that time, from the delivery point a Drive to the delivery point b carbon emission costs for: The carbon emission cost during the entire material distribution process for: in, Indicates the cost of carbon emissions per unit mass. This indicates the conversion of fuel consumption into greenhouse gas emissions. d ab Indicates delivery point a to delivery point b The distance between them; The objective function of the pre-arrangement inventory equilibrium model is, even if the overall cost is... C The smallest specific expression is: The constraints specifically include: The cargo on each delivery vehicle must not exceed the vehicle's load capacity. , in, Q b Indicates delivery point b Demand; Each delivery point can only be visited and delivered by one vehicle once. Each vehicle starts from the starting point and eventually returns to the starting point: .

[0036] The inventory optimization and inventory balancing model is designed for routine operation and maintenance scenarios, and sets a safety stock, such as... Figure 3 As shown, using Figure 4 The continuous inventory management strategy for safety stock and reserve stock, as shown, performs continuous inventory checks. When the inventory drops to the safety stock level (which can be determined by each terminal warehouse based on inventory management theory, combined with historical inventory status and inbound / outbound information), an active replenishment instruction is automatically triggered to keep the reserve stock (which can be determined by each terminal warehouse based on inventory management theory, combined with historical inventory status and inbound / outbound information) constant. The model also incorporates the cost of delivery delay penalties to ensure that inventory levels dynamically match demand. Its objective function is: in, It is a fixed cost. It is transportation cost, It is the cost of carbon emissions, Penalties for delivery delays.

[0037] Delivery delay penalty cost In the process of goods delivery, if a vehicle's delivery time exceeds the expected time due to various reasons, a penalty cost is incurred. This cost is calculated based on the matching relationship between the delivery time and the preset optimal service time window and acceptable time window. Exceeding the acceptable time window triggers a higher penalty cost. The penalty cost mainly includes the additional costs incurred when the delivery vehicle cannot arrive at the expected delivery point time, including waiting costs incurred when the vehicle arrives earlier than the expected delivery point time and late costs incurred when the vehicle arrives later than the expected delivery point time. Customers typically set two time windows: the optimal service time window and the acceptable time window. Completing the customer's request within the optimal service time window will not incur penalty costs; completing the delivery outside the optimal service time window but within the acceptable time window will incur a small penalty cost; delivering the goods outside the acceptable time window will result in the customer refusing service and incurring a larger penalty cost.

[0038] assumed, t bk Indicates vehicle Arrival at delivery point b Time, P e This represents the cost per unit of time that a vehicle is waiting for. P l This represents the unit time cost of a vehicle being late. M This indicates the penalty cost for vehicles arriving outside of the acceptable time, and the inability to accept delivery activities outside of the acceptable time. M It was set to a very large number. For delivery points b The desired time window For delivery points b An acceptable time window. Delivery point. b The cost of punishment is : The constraints are the same as those in the pre-arrangement inventory equilibrium model.

[0039] The inventory backlog resolution model includes an inventory age warning unit and a usable inventory resource pool. For inventory backlog scenarios, an inventory age warning mechanism and a usable inventory resource pool are established. Backlogged materials are screened by inventory age, and priority matching of target demand points is constructed based on the urgency of demand, delivery distance, and inventory capacity. Through "first-in, first-out" requisition rules, cross-regional inventory balancing, and project adaptation matching, the proactive distribution of backlogged materials is triggered to achieve inventory revitalization and supply-demand balance.

[0040] The information integration management module includes a data acquisition unit, a data sharing and collaboration unit, and a monitoring and early warning unit. The data acquisition unit uses equipment and software such as RFID radio frequency identification, mobile operation terminals (PDAs), and WMS warehouse management systems to collect information such as the inbound, outbound, inventory, and age of warehouse materials in real time, as well as data such as location and status during the delivery process, realizing data visualization of the entire life cycle of materials. The data sharing and collaboration unit builds a full-domain material information sharing platform, breaking down data barriers between distribution centers, branch warehouses, terminal warehouses, suppliers, and demand units, and realizing real-time synchronization of information such as inventory status, demand forecasts, and delivery plans. The monitoring and early warning unit monitors key indicators such as warehouse capacity utilization, inventory turnover efficiency, and delivery timeliness in real time. When abnormal situations such as exceeding capacity limits, inventory shortages, or delivery delays occur, an early warning is automatically triggered and pushed to relevant management nodes.

[0041] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit them; those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions will not cause the essence of the corresponding technical solutions to deviate from the protection scope of the present invention.

Claims

1. A power material warehousing, distribution, and management system, characterized in that: It includes a tiered and hierarchical warehouse management module, an active delivery scheduling module, a multi-scenario inventory balancing model module, and an information integration management module, with each module communicating with each other; The warehousing hierarchical management module is used to construct a three-level warehousing architecture of distribution center-sub-warehouse-terminal warehouse, establish a hierarchical evaluation index system to screen warehouses at each level, and use a hierarchical optimization model to optimize hierarchical layout and material allocation. The proactive delivery scheduling module includes a demand forecasting unit, a delivery decision-making unit, and a route and capacity optimization unit. The demand forecasting unit forecasts material demand based on multi-source data. The delivery decision-making unit formulates a proactive delivery strategy that combines primary and secondary delivery based on a three-tier warehousing architecture and the inventory status and capacity threshold of each warehouse. The route and capacity optimization unit optimizes delivery routes and coordinates the allocation of transportation resources. The multi-scenario inventory balancing model module includes an arrival pre-arrangement inventory balancing model, an inventory optimization inventory balancing model, and an inventory backlog resolution model, which are adapted to the inventory allocation needs of material arrival, daily operation and maintenance, and inventory backlog scenarios, respectively. The arrival pre-arrangement inventory balancing model, the inventory optimization inventory balancing model, and the inventory backlog resolution model all aim to minimize the overall cost. The information integration management module is used to collect data from the entire process, including warehousing, distribution, and inventory. It relies on the smart supply chain platform to achieve data sharing, real-time monitoring, and anomaly warning, supporting the balanced utilization of warehouse capacity across the entire domain.

2. The power material warehousing, distribution and management system according to claim 1, characterized in that: The tiered evaluation index system includes policy adaptability, economic cost, transportation conditions, warehousing capacity, and operation and maintenance resources.

3. The power material warehousing, distribution and management system according to claim 1, characterized in that: The hierarchical optimization model aims to minimize the sum of transportation costs, operation and maintenance costs, and time penalty costs. The constraints include matching the inflow and demand of terminal warehouses, upper limit constraints on warehouse capacity, and non-negative constraints on service radius exceeding distance.

4. The power material warehousing, distribution and management system according to claim 1, characterized in that: The demand forecasting unit of the proactive delivery scheduling module uses a time series forecasting algorithm or machine learning algorithm supported by big data analysis to forecast material demand. The input data includes historical requisition data, power project progress data, equipment operation and maintenance plan data, emergency event early warning data, and material consumption trend data.

5. The power material warehousing, distribution and management system according to claim 1, characterized in that: The combined distribution strategy is as follows: after the supplier produces materials, based on the monthly demand plan and current inventory status, and based on the functions of each warehouse and distribution optimization principles, the produced materials are divided into two parts, and one part of the materials are given priority to be distributed to the sub-warehouse. When the inventory in the terminal warehouse falls below the safety threshold, the distribution center or branch warehouse will initiate replenishment and distribution; at the same time, it supports cross-level allocation and distribution of backlogged materials.

6. The power material warehousing, distribution and management system according to claim 1, characterized in that: The comprehensive cost of the pre-arrangement inventory balancing model includes fixed costs, transportation costs, and carbon emission costs, which are calculated using a quantitative formula that includes vehicle load capacity, travel distance, fuel consumption coefficient, and carbon emission coefficient. The constraints include distribution center capacity threshold constraints, demand matching degree constraints, and vehicle load limit constraints. The distribution center threshold is derived from historical storage data through simulation model data.

7. The power material warehousing, distribution and management system according to claim 1, characterized in that: The comprehensive cost of the inventory optimization and inventory balancing model includes fixed costs, transportation costs, carbon emission costs, and delivery delay penalty costs. It adopts a strategy of continuous inventory counting of safety stock and reserve stock, and sets a safety stock threshold and a maximum reserve threshold. When the inventory of the terminal warehouse is lower than the safety threshold, a replenishment instruction is automatically triggered. The delivery delay penalty cost is calculated based on the matching relationship between the delivery time and the preset optimal service time window and acceptable time window. When the acceptable time window is exceeded, a high penalty cost is triggered. The safety stock threshold and the maximum reserve threshold are determined by each terminal warehouse based on inventory management theory, combined with historical inventory status and inbound / outbound information.

8. The power material warehousing, distribution and management system according to claim 1, characterized in that: The inventory backlog resolution model includes an inventory age warning unit and a resource pool of available inventory. For inventory backlog scenarios, an inventory age warning mechanism and a resource pool of available inventory are established. By combining the first-in-first-out (FIFO) requisition rule and cross-regional balancing inventory, the backlog of materials can be allocated across warehouses.

9. The power material warehousing, distribution and management system according to claim 1, characterized in that: The information integration management module includes a data acquisition unit, a data sharing and collaboration unit, and a monitoring and early warning unit. The data acquisition unit collects data throughout the entire process through RFID radio frequency identification equipment, mobile operation terminals, positioning equipment, and the WMS system. The data sharing and collaboration unit supports the data flow of the two-stage delivery business of "warehouse to warehouse, warehouse to warehouse, and warehouse to site". The monitoring and early warning unit realizes warehouse age warning, warehouse capacity threshold warning, and delivery delay warning.

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