Inventory control method and device of intelligent electric meter

Abstract

The invention provides an inventory control method and device for intelligent electric meters, and belongs to the technical field of supply chain management. The method comprises the steps of obtaining a predicted demand quantity of a target type of intelligent electric meter; correcting the predicted demand quantity based on the substitution relationship between the intelligent electric meter of the related model and the intelligent electric meter of the target model to obtain a corrected demand quantity; and based on the supply chain parameters and the corrected demand quantity of the target type of intelligent electric meter, determining the inventory of the target type of intelligent electric meter, and performing inventory control on the target type of intelligent electric meter based on the inventory. According to the invention, the inventory amount is closer to the actual demand amount of the target type of intelligent electric meter, and the situation that the target type of intelligent electric meter cannot be provided for the user in time is avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of supply chain management, and in particular to an inventory control method and device for a smart electric meter. Background Art

[0002] The demand for smart meters is usually related to the growth of electricity consumption, grid upgrades, intelligent needs, and government policy promotion. With the development of new technologies such as intelligent control technology, sensor technology, communication technology, and artificial intelligence, the functions of smart meters are constantly enhanced, such as customer load identification, two-way metering, and tiered electricity prices. These technological advances have promoted the market demand for smart meters. With the global emphasis on energy conservation and emission reduction and smart grid construction, the demand for smart meters has shown a steady growth trend. For example, according to data from the China Economic Industry Research Institute, as of the end of December 2022, China's smart meter holdings have exceeded 650 million, with an average annual replacement of about 80 million.

[0003] At present, in order to meet the needs of users to replace smart meters in a timely manner and formulate a reasonable production and procurement plan, the demand for smart meters is usually predicted based on the installation volume of smart meters over the years, and a certain amount of additional inventory is maintained as a buffer considering demand fluctuations and supply chain uncertainties. However, the additional inventory used as a buffer is usually set based on experience, which is difficult to respond to rapidly changing demand fluctuations, resulting in the need to improve the accuracy of the current smart meter inventory planning. Summary of the invention

[0004] The embodiments of the present invention provide a method and device for controlling inventory of a smart meter, so as to solve the problem of improving the accuracy of inventory planning of the smart meter.

[0005] In a first aspect, an embodiment of the present invention provides an inventory control method for a smart meter, comprising:

[0006] Obtain the predicted demand for the target model of smart meters;

[0007] The predicted demand is corrected based on the substitution relationship between the related model smart meter and the target model smart meter to obtain the corrected demand;

[0008] The inventory quantity of the target model smart meters is determined based on the supply chain parameters and the revised demand quantity of the target model smart meters, so as to perform inventory control on the target model smart meters based on the inventory quantity.

[0009] In a possible implementation, the substitution relationship includes an inherent substitution relationship and a demand substitution relationship; based on the substitution relationship between the related model smart meter and the target model smart meter, the predicted demand is corrected to obtain the corrected demand, including:

[0010] For each relevant model of smart meter, based on the inherent substitution relationship and demand substitution relationship of the relevant model of smart meter, calculate the substitution rate of the relevant model of smart meter for the target model of smart meter;

[0011] Determine the demand correction amount of the target model smart meter based on the replacement rate of various related models of smart meters for the target model smart meter;

[0012] The predicted demand quantity is corrected based on the demand correction amount to obtain a corrected demand quantity.

[0013] In a possible implementation, before calculating the replacement rate of each related model of smart electric meter for the target model of smart electric meter based on the inherent replacement relationship and demand replacement relationship of the related model of smart electric meter for each related model of smart electric meter, the method further includes:

[0014] For each relevant model of smart meter, the cross-price elasticity between the relevant model of smart meter and the target model of smart meter is calculated as the inherent substitution relationship between the relevant model of smart meter and the target model of smart meter;

[0015] Based on the importance index of each meter function under each demand generation reason, determine the function duplication rate of each related model smart meter with the target model smart meter under each demand generation reason; where the demand generation reasons include function upgrade, new meter installation and replacement of old meter with new one;

[0016] For the first relevant model smart meter, based on the historical proportion of each demand generation reason, the function repetition rate of the first relevant model smart meter and the target model smart meter under each demand generation reason is weighted summed to obtain the demand substitution relationship between the first relevant model smart meter and the target model smart meter; wherein the first relevant model smart meter is any relevant model smart meter.

[0017] In a possible implementation, the function duplication rate is calculated as follows:

[0018]

[0019] in, is the function repetition rate, ω i is the importance index of function i, i is the function that both the relevant model smart meter and the target model smart meter have, j is the function that the relevant model smart meter has but the target model smart meter does not have, and k is the function that the relevant model smart meter does not have but the target model smart meter has.

[0020] In a possible implementation, the calculation formula of the demand correction amount is:

[0021] Δ d =ζd Q d ∑Q n ω n (k 1 ε n +k 2 θ n )

[0022] Among them, Δ d is the demand correction, d is the adjustment factor, Q d is the predicted demand for the target model smart meter, Q n is the predicted demand for the relevant model of smart meter n, ω n is the historical proportion of the relevant model of smart meter n, ε n is the inherent substitution relationship between the relevant model smart meter n and the target model smart meter, θ n is the demand substitution relationship between the related model smart meter n and the target model smart meter, k 1 and k 2 The preset weights.

[0023] In a possible implementation, before determining the function duplication rate of each related model of smart electric meter with the target model of smart electric meter under each demand generation reason based on the importance index of each electric meter function under each demand generation reason, the method further includes:

[0024] For each demand generating reason, the importance index of each meter function of the first relevant model smart meter under the demand generating reason is determined based on the hierarchical analysis method.

[0025] In a possible implementation, the supply chain parameters include demand standard deviation, production efficiency, and supply chain efficiency; and the inventory of the target model smart meter is determined based on the supply chain parameters of the target model smart meter and the corrected demand, including:

[0026] Calculate the inventory safety margin of the target model smart meter based on the demand standard deviation, production efficiency and supply chain efficiency of the target model smart meter;

[0027] The sum of the inventory safety margin and the predicted demand is calculated as the inventory of the target model smart meter. In a possible implementation, the calculation formula for the inventory safety margin is:

[0028] M=σ d (1-sc)(1-ce)

[0029] Among them, M is the inventory safety margin, σ d is the standard deviation of the demand for the target model smart meter, sc is the production efficiency, and ce is the supply chain efficiency.

[0030] In a second aspect, an embodiment of the present invention provides an inventory control device for a smart meter, comprising:

[0031] An acquisition module, used to acquire the predicted demand of the target model smart meter;

[0032] A demand correction module, used to correct the predicted demand based on the substitution relationship between the relevant model smart meter and the target model smart meter to obtain a corrected demand;

[0033] The inventory determination module is used to determine the inventory of the target model smart meter based on the supply chain parameters and the revised demand of the target model smart meter, so as to perform inventory control on the target model smart meter based on the inventory.

[0034] The embodiment of the present invention provides an inventory control method and device for smart meters. The method and device evaluate the substitution relationship between related model smart meters and target model smart meters by analyzing overlapping functions and difference functions, and thereby quantify the influence of related model smart meters on the demand fluctuation of target model smart meters, determine a more accurate revised demand, and then consider the influence of supply chain parameters of target model smart meters on the inventory effect. The inventory is determined based on the revised demand, so that the inventory is closer to the actual demand of target model smart meters, thereby avoiding the situation where the target model smart meters cannot be provided to users in a timely manner. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0036] Figure 1 is a flow chart of an implementation of an inventory control method for a smart meter provided by an embodiment of the present invention;

[0037] Figure 2 It is a structural schematic diagram of an inventory control device for a smart meter provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0038] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present invention. However, it should be clear to those skilled in the art that the present invention may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present invention.

[0039] In order to make the purpose, technical solutions and advantages of the present invention more clear, specific embodiments will be described below in conjunction with the accompanying drawings.

[0040] Figure 1 The implementation flow chart of the inventory control method of the smart meter provided by the embodiment of the present invention is detailed as follows:

[0041] Step 101, obtaining the predicted demand of the target model smart meter.

[0042] In this embodiment, the demand for smart meters is usually related to the growth of electricity consumption, grid upgrades, intelligent demand, and government policy promotion. With the global emphasis on energy conservation and emission reduction and smart grid construction, the demand for smart meters has shown a steady growth trend. Accurate market demand forecasting can help companies arrange production plans reasonably to avoid overproduction leading to inventory backlogs or underproduction leading to stockouts.

[0043] This embodiment can be applied to inventory control of enterprise production plans or inventory control of power operating organizations. Smart meters are mainly for home users and usually have functions such as remote meter reading, real-time monitoring, fault diagnosis, prepayment, peak and valley electricity prices, etc. In order to meet the uncertainty of user demand for smart meters, power operating organizations need to ensure a certain amount of inventory to avoid shortages when users need to replace or install smart meters.

[0044] In this embodiment, the inventory and predicted demand of the target model smart meter are set for a period of time in the future, and the specific period can be determined according to actual demand.

[0045] Step 102: correct the predicted demand based on the substitution relationship between the related model smart meter and the target model smart meter to obtain a corrected demand.

[0046] In this embodiment, as a high-tech electricity metering device, the smart meter has the characteristics of high technical content and diverse functions. With the development of technology, smart meters of different models and different functional characteristics continue to be launched. Therefore, as users have different needs for replacing smart meters, there will be differences in the selection of smart meter models. When two or more models of smart meters have the functions required by users, users may choose from them because of the differences in other functions or parameters between these types of meters. In this embodiment, the smart meters with such a relationship are called related model smart meters of the target model smart meter.

[0047] The functions of the related model smart meter overlap with the target model smart meter. In some scenarios, users may choose to purchase the related model smart meter instead of the target model smart meter, resulting in a decrease in the actual demand for the target model smart meter compared to the predicted demand. Similarly, in some scenarios, users may choose to purchase the target model smart meter instead of the related model smart meter, resulting in an increase in the actual demand for the target model smart meter compared to the predicted demand. In this embodiment, the fluctuation characteristic of the predicted demand of the target model smart meter is described through the substitution relationship between the related model smart meter and the target model smart meter, so as to obtain a more accurate predicted demand.

[0048] Step 103: determining the inventory of the target model smart meters based on the supply chain parameters and the revised demand of the target model smart meters, so as to perform inventory control on the target model smart meters based on the inventory.

[0049] In this embodiment, the impact of the production efficiency and supply chain efficiency of smart meters on inventory is mainly reflected in the following aspects:

[0050] 1) Demand forecast accuracy: The supply chain can help companies arrange production plans reasonably through accurate market demand forecasts, avoiding inventory backlogs caused by overproduction or shortages caused by insufficient production.

[0051] 2) Raw material supply stability: The stability of the supply chain directly affects the production of smart meters. For example, if the supply of chips and other key components is unstable, it may cause production delays, which in turn affects inventory levels.

[0052] 3) Production efficiency: An efficient production process can shorten the production cycle, reduce the inventory of work-in-progress, and ensure a quick response to market demand.

[0053] 4) Logistics and delivery speed: The logistics and delivery efficiency in the supply chain determines the speed at which smart meters are delivered from the production line to the end user. Efficient logistics can reduce inventory in transit and speed up inventory turnover.

[0054] 5) Inventory Management: Inventory control strategies in supply chain management, such as just-in-time replenishment system (JIT) and economic order quantity (EOQ), can help companies optimize inventory levels and reduce the risk of overstocking or stockouts.

[0055] 6) Ability to respond to market changes: The flexibility and responsiveness of the supply chain are critical to responding to market changes. For example, if the market demand for smart meters suddenly increases, the supply chain needs to be able to quickly adjust production and distribution plans to meet demand.

[0056] 7) Technology and Automation Application: The level of technology and automation applied in the supply chain, such as the use of IoT technology for real-time inventory monitoring, can improve the transparency and efficiency of the supply chain.

[0057] 8) Supply Chain Partnership: Good partnerships with suppliers and logistics service providers can enhance the synergy of the entire supply chain, thereby improving the efficiency of inventory management.

[0058] Therefore, the quantitative evaluation of the supply chain efficiency parameters of smart meters and their impact on inventory can be carried out through the following key indicators, so as to obtain the inventory that can meet user needs:

[0059] 1) Capacity utilization: measures the ratio between actual production and maximum production capacity. High capacity utilization means that production equipment and resources are fully utilized, which helps to reduce unit costs.

[0060] 2) Production cycle time: the time required from the input of raw materials to the output of finished products. The shorter the cycle time, the higher the production efficiency and the faster the response to market demand.

[0061] 3) Inventory turnover rate: It measures the ratio of the number of smart meters sold in a certain period to the average inventory, reflecting the liquidity of inventory. The higher the turnover rate, the more effective the inventory management.

[0062] 4) Order fulfillment cycle: The time required for the entire process from customer order placement to order fulfillment. The shorter the cycle, the stronger the supply chain's ability to respond to the market.

[0063] 5) Supply chain response time: the entire cycle time from raw material procurement to finished product delivery. The shorter this time is, the more efficient the supply chain is.

[0064] 6) Inventory accuracy: The consistency between actual inventory and recorded inventory. The higher the accuracy, the lower the uncertainty in inventory management.

[0065] 7) Supply chain costs: including procurement costs, production costs, transportation costs, inventory holding costs, etc. The lower the cost, the higher the supply chain efficiency is generally considered to be.

[0066] 8) Service level: including on-time delivery rate, order accuracy, etc., reflecting the extent to which the supply chain meets customer needs.

[0067] 9) Demand forecast accuracy: The consistency between forecasted demand and actual demand. The more accurate the forecast, the better inventory management can avoid excess or shortage.

[0068] 10) Supply chain flexibility: The ability of the supply chain to adapt to market changes, including the speed of response to demand fluctuations and the ability to recover from supply disruptions.

[0069] 11) Information technology application: the application degree of systems such as ERP and WMS, which can improve the transparency and coordination of the supply chain.

[0070] 12) Supply chain integration: the degree of coordination and integration between various links in the supply chain, including information sharing, process docking, etc.

[0071] The embodiment of the present invention analyzes overlapping functions and difference functions, evaluates the substitution relationship between the related model smart meters and the target model smart meters, and quantifies the influence of the related model smart meters on the demand fluctuation of the target model smart meters, determines a more accurate revised demand, and then considers the influence of the supply chain parameters of the target model smart meters on the inventory effect, determines the inventory based on the revised demand, so that the inventory is closer to the actual demand of the target model smart meters, avoiding the situation where the target model smart meters cannot be provided to users in a timely manner.

[0072] In a possible implementation, the substitution relationship includes an inherent substitution relationship and a demand substitution relationship; based on the substitution relationship between the related model smart meter and the target model smart meter, the predicted demand is corrected to obtain the corrected demand, including:

[0073] For each relevant model of smart meter, based on the inherent substitution relationship and demand substitution relationship of the relevant model of smart meter, calculate the substitution rate of the relevant model of smart meter for the target model of smart meter;

[0074] Determine the demand correction amount of the target model smart meter based on the replacement rate of various related models of smart meters for the target model smart meter;

[0075] The predicted demand quantity is corrected based on the demand correction amount to obtain a corrected demand quantity.

[0076] In this embodiment, since there may be multiple related models of smart meters, the impact on the demand of the target model smart meter is the sum of the impacts of these related models of smart meters, and the specific impact degree of each related model of smart meters is different. Therefore, each related model of smart meter can be analyzed separately, and then combined to determine the demand correction amount of the target model smart meter.

[0077] The inherent substitution relationship in this embodiment refers to the possibility that users purchase related models of smart meters instead of purchasing the target model of smart meters when user needs are not classified, which can be represented by cross-price elasticity.

[0078] Demand substitution relationship refers to the possibility that users, when they have specific needs, will purchase related models of smart meters instead of the target model of smart meters. This relationship is affected by the specific functions and parameters of smart meters. For example, for home users, they may prefer products with high cost performance, especially the initial installation cost and long-term use cost, and prefer smart meters with energy-saving reminders and energy efficiency analysis functions. For industrial users, they may have high requirements for the metering accuracy of the meter in order to accurately grasp the production energy consumption. Therefore, based on the classification of user needs and purchase scenarios, and analyzing the demand substitution relationship separately, a more accurate demand correction can be obtained.

[0079] After determining the replacement rates of various related models of smart meters for the target model of smart meters, the technology for predicting demand can be increased or decreased in corresponding proportions to obtain the corrected demand.

[0080] In a possible implementation, before calculating the replacement rate of each related model of smart electric meter for the target model of smart electric meter based on the inherent replacement relationship and demand replacement relationship of the related model of smart electric meter for each related model of smart electric meter, the method further includes:

[0081] For each relevant model of smart meter, the cross-price elasticity between the relevant model of smart meter and the target model of smart meter is calculated as the inherent substitution relationship between the relevant model of smart meter and the target model of smart meter;

[0082] Based on the importance index of each meter function under each demand generation reason, determine the function duplication rate of each related model smart meter with the target model smart meter under each demand generation reason; where the demand generation reasons include function upgrade, new meter installation and replacement of old meter with new one;

[0083] For the first relevant model smart meter, based on the historical proportion of each demand generation reason, the function repetition rate of the first relevant model smart meter and the target model smart meter under each demand generation reason is weighted summed to obtain the demand substitution relationship between the first relevant model smart meter and the target model smart meter; wherein the first relevant model smart meter is any relevant model smart meter.

[0084] In this embodiment, the cross-price elasticity between smart meters is calculated, that is, the impact of price changes of one meter on the demand for another meter. If the cross-price elasticity is high, it indicates that the two are good substitutes.

[0085] As for demand substitution, after analysis, the reasons for demand generation, i.e., the reasons why users purchase smart meters, are divided into function upgrade, new installation of meters, and replacement of old meters with new ones. The user preferences for the three situations of function upgrade, new installation of meters, and replacement of old meters with new ones are as follows:

[0086] 1. Function upgrade

[0087] Advanced Technology: Preference for having the latest technology, such as Internet of Things (IoT) connectivity, more accurate metering algorithms, etc.

[0088] Value-added services: Hope to obtain more value-added services, such as energy consumption analysis reports, energy-saving suggestions, etc.

[0089] Compatibility: You want your new meter to be compatible with your existing smart home systems or other devices.

[0090] User interface: Preference is given to better user interfaces and more intuitive data presentation.

[0091] Remote control: More emphasis is placed on remote monitoring and control functions so that electricity usage can be understood and managed at any time.

[0092] 2. New electricity meter

[0093] Cost-effectiveness: Since it is a new installation, users may pay more attention to the initial installation cost and long-term use cost.

[0094] Easy installation: The preferred installation process is simple and quick, reducing the impact of installation on daily life.

[0095] Ease of use: The meter should be simple to operate, easy to understand and use.

[0096] Energy saving and environmental protection: Pay attention to the energy-saving effect of the electricity meter and whether it meets environmental protection standards.

[0097] Smart functions: They have high expectations for smart functions, such as automatic meter reading and remote bill payment.

[0098] 3. Replace the old with the new

[0099] Reliability: As the original electricity meter ages, users may be more concerned about the reliability and stability of the new meter.

[0100] Safety: Pay attention to the safety of the new electricity meter to avoid safety accidents caused by meter problems.

[0101] Maintenance cost: Prefer products with low maintenance costs to reduce additional expenses in long-term use.

[0102] Convenient upgrade: It is hoped that the new electricity meters will have better upgrade space in the future to adapt to technological development.

[0103] Policy support: Electricity meters that enjoy government subsidies or policy support may be preferred.

[0104] In addition, the reasons for the demand can be divided according to user portraits. The following are the preferences of various types of users:

[0105] 1. Home users

[0106] Energy saving and environmental protection: prefer smart meters with energy-saving reminders and energy efficiency analysis functions.

[0107] Remote control: It is hoped that the electric meter supports remote control via mobile phone APP, such as turning the power on and off, checking the power consumption, etc.

[0108] Price sensitive: They prefer products with high cost performance, especially the initial installation cost and long-term use cost.

[0109] Ease of use: Prefer smart meters with simple operation and user-friendly interface, which can be used by the elderly and children.

[0110] Security: Pay attention to the data security and electrical safety of the electricity meter.

[0111] 2. Commercial Users

[0112] Data management: Preference for electricity meters with detailed electricity usage data recording and analysis capabilities to enable energy consumption management and optimization.

[0113] Prepayment function: For rented shops, etc., the prepayment function can reduce the risk of arrears.

[0114] Peak and valley electricity prices: For commercial users with high electricity consumption, smart meters that support peak and valley electricity prices can help save electricity bills.

[0115] Scalability: It is hoped that the electricity meter will be compatible with existing business management systems (such as building automation systems).

[0116] 3. Industrial users

[0117] High-precision measurement: High measurement accuracy is required for the electricity meter to accurately grasp the production energy consumption.

[0118] Fault diagnosis: Preference is given to smart meters that can monitor the status of the power grid in real time and provide fault diagnosis.

[0119] Customization service: It may be necessary to customize the meter functions according to the specific production environment.

[0120] Stability and reliability: There are higher requirements for the stability and reliability of the meter operation.

[0121] 4. Government and Utilities

[0122] Remote meter reading: Preference is given to smart meters that can realize remote automatic meter reading to improve work efficiency.

[0123] Policy support: Meters that meet national or local policy requirements may be preferred, such as those that support specific subsidy policies.

[0124] Large-scale deployment: The electric meter needs to have good batch deployment capabilities and centralized management functions.

[0125] 5. Smart home enthusiasts

[0126] Smart home integration: Preference is given to meters that can be seamlessly integrated with smart home systems.

[0127] Technological innovation: There is a high interest and acceptance of new technologies and new functions of electricity meters.

[0128] User experience: Focus on the interactive experience between the electricity meter and other smart home devices.

[0129] 6. Environmentalist

[0130] Green certification: Preference is given to smart meter products that have obtained environmental certification.

[0131] Sustainable development: Pay attention to whether the production process of electric meters complies with the principles of sustainable development.

[0132] Based on the above-mentioned user preferences, the demand substitution relationship corresponding to each relevant model of smart meter can be analyzed for each cause of demand based on the functional configuration characteristics of each relevant model of smart meter and the adaptability to the causes of each demand, and then integrated.

[0133] In a possible implementation, the function duplication rate is calculated as follows:

[0134]

[0135] in, is the function repetition rate, ω i is the importance index of function i, i is the function that both the relevant model smart meter and the target model smart meter have, j is the function that the relevant model smart meter has but the target model smart meter does not have, and k is the function that the relevant model smart meter does not have but the target model smart meter has.

[0136] In this embodiment, It represents the proportion of the functions of the relevant model smart meter and the target model smart meter in the total functions of both, which is used as the benchmark and (∑ω j -∑ω k ) to express the influence of the functions of the relevant model smart meter over the target model smart meter on the user's purchase choice. Among them, the functions of the smart meter may include accurate metering, remote meter reading, fault diagnosis, etc. If the two models of smart meters have different metering accuracies, the higher-precision metering is regarded as a new function.

[0137] In this embodiment, for the first related model smart meter, based on the historical proportion of each demand generation reason, the formula for weighted summation of the function repetition rate of the first related model smart meter and the target model smart meter under each demand generation reason is:

[0138]

[0139] Among them, θ n is the replacement rate of the relevant model smart meter n to the target model smart meter, is the functional duplication rate between the relevant model smart meter n and the target model smart meter under the demand generation reason m, ω m It is the historical proportion of demand generation reason m.

[0140] In a possible implementation, the calculation formula of the demand correction amount is:

[0141] Δ d =ζ d Q d ∑Q n ω n (k 1 ε n +k 2 θ n )

[0142] Among them, Δ d is the demand correction, d is the adjustment factor, Q d is the predicted demand for the target model smart meter, Q n is the predicted demand for the relevant model of smart meter n, ω n is the historical proportion of the relevant model of smart meter n, ε m is the inherent substitution relationship between the relevant model smart meter n and the target model smart meter, θ n is the demand substitution relationship between the related model smart meter n and the target model smart meter, k 1 and k 2 The preset weights.

[0143] In this embodiment, the demand correction is based on the predicted demand, so it needs to be multiplied by the predicted demand. The adjustment factor is used to convert the substitution relationship into the demand correction, k 1 and k 2 It is used to integrate the inherent substitution relationship and demand substitution relationship of each relevant model of smart meter, which can be set according to actual conditions. (k 1 ε n +k 2 θ n ) represents the replacement rate of the relevant model smart meter n for the target model smart meter, and is respectively compared with Q n ,ω n By multiplying and summing based on n, the replacement rates of the target model smart meters for the relevant models can be integrated to obtain the total replacement rate of the target model smart meters.

[0144] In a possible implementation, before determining the function duplication rate of each related model of smart electric meter with the target model of smart electric meter under each demand generation reason based on the importance index of each electric meter function under each demand generation reason, the method further includes:

[0145] For each demand generating reason, the importance index of each meter function of the first relevant model smart meter under the demand generating reason is determined based on the hierarchical analysis method.

[0146] In this embodiment, under different purchase scenarios and user needs, the influence of each meter function on the user's choice of smart meter model varies. Through the hierarchical analysis method, the importance of each meter function can be first qualitatively analyzed and then quantitatively analyzed. A hierarchical structure model is constructed, and the importance weights of indicators are determined through pairwise comparison. Time series analysis and cross-validation are used to verify the accuracy of the weights through historical data in different time periods as the importance indicators of each meter function, so as to accurately calculate the function duplication rate of each related model of smart meter with the target model of smart meter under each demand generation reason.

[0147] In a possible implementation, the supply chain parameters include demand standard deviation, production efficiency, and supply chain efficiency; and the inventory of the target model smart meter is determined based on the supply chain parameters of the target model smart meter and the corrected demand, including:

[0148] Calculate the inventory safety margin of the target model smart meter based on the demand standard deviation, production efficiency and supply chain efficiency of the target model smart meter;

[0149] The sum of the inventory safety margin and the predicted demand is calculated as the inventory quantity of the target model smart meter.

[0150] In this embodiment, the inventory safety margin is used to compensate for the uncertainty of demand. The demand standard deviation is used to describe the volatility of demand, the production efficiency is used to describe the efficiency of the production facilities of the target model smart meter and the stability of production capacity, and the supply chain efficiency includes the raw material logistics efficiency, product logistics efficiency, information flow efficiency, etc. The production efficiency and supply chain efficiency are used together to indicate the volatility of the supply chain and quantify the uncertainty factors that affect the supply chain efficiency. Therefore, by combining the above three parameters, a reasonable inventory safety margin can be calculated to ensure the accuracy of the inventory.

[0151] In one possible implementation, the formula for calculating the inventory safety margin is:

[0152] M=σ d (1-sc)(1-ce)

[0153] Among them, M is the inventory safety margin, σ d is the standard deviation of the demand for the target model smart meter, sc is the production efficiency, and ce is the supply chain efficiency.

[0154] In this embodiment, the capacity efficiency can be measured by indicators such as on-time delivery rate, order accuracy, capacity utilization rate, production efficiency, etc., and one or more of them can be selected for weighted summation as the capacity efficiency value. Supply chain efficiency can be measured by the following indicators:

[0155] Order fulfillment rate: The ratio of orders completed on time to the total number of orders.

[0156] Inventory Turnover Ratio: The ratio of cost of goods sold to average inventory levels.

[0157] Transportation efficiency: the ratio of transportation cost to transportation volume.

[0158] If both capacity efficiency and supply chain efficiency are high, then (1-sc) and (1-ce) will be small, reducing the need for inventory safety margin.

[0159] It should be understood that the order of execution of the steps in the above embodiment does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention.

[0160] The following is an embodiment of the device of the present invention. For details not described in detail therein, reference may be made to the corresponding method embodiment described above.

[0161] Figure 2 The following is a schematic diagram showing the structure of the inventory control device of the smart meter provided by the embodiment of the present invention. For the convenience of explanation, only the parts related to the embodiment of the present invention are shown, which are described in detail as follows:

[0162] like Figure 2 As shown, the inventory control device 2 of the smart meter includes:

[0163] An acquisition module 21 is used to acquire the predicted demand of the target model smart meter;

[0164] The demand correction module 22 is used to correct the predicted demand based on the substitution relationship between the relevant model smart meter and the target model smart meter to obtain a corrected demand;

[0165] The inventory determination module 23 is used to determine the inventory of the target model smart meters based on the supply chain parameters and the modified demand of the target model smart meters, so as to perform inventory control on the target model smart meters based on the inventory.

[0166] In a possible implementation, the substitution relationship includes an inherent substitution relationship and a demand substitution relationship; the demand correction module 22 is specifically used to:

[0167] For each relevant model of smart meter, based on the inherent substitution relationship and demand substitution relationship of the relevant model of smart meter, calculate the substitution rate of the relevant model of smart meter for the target model of smart meter;

[0168] Determine the demand correction amount of the target model smart meter based on the replacement rate of various related models of smart meters for the target model smart meter;

[0169] The predicted demand quantity is corrected based on the demand correction amount to obtain a corrected demand quantity.

[0170] In a possible implementation, the demand modification module 22 is further configured to:

[0171] Before calculating the replacement rate of the smart meter of the relevant model for the target model smart meter based on the inherent substitution relationship and demand substitution relationship of the smart meter of the relevant model for each smart meter of the relevant model, the cross price elasticity between the smart meter of the relevant model and the target model smart meter is calculated for each smart meter of the relevant model as the inherent substitution relationship between the smart meter of the relevant model and the target model smart meter;

[0172] Based on the importance index of each meter function under each demand generation reason, determine the function duplication rate of each related model smart meter with the target model smart meter under each demand generation reason; where the demand generation reasons include function upgrade, new meter installation and replacement of old meter with new one;

[0173] For the first relevant model smart meter, based on the historical proportion of each demand generation reason, the function repetition rate of the first relevant model smart meter and the target model smart meter under each demand generation reason is weighted summed to obtain the demand substitution relationship between the first relevant model smart meter and the target model smart meter; wherein the first relevant model smart meter is any relevant model smart meter.

[0174] In a possible implementation, the function duplication rate is calculated as follows:

[0175]

[0176] in, is the function repetition rate, ω i is the importance index of function i, i is the function that both the relevant model smart meter and the target model smart meter have, j is the function that the relevant model smart meter has but the target model smart meter does not have, and k is the function that the relevant model smart meter does not have but the target model smart meter has.

[0177] In a possible implementation, the calculation formula of the demand correction amount is:

[0178] Δ d =ζ d Q d ∑Q n ω n (k 1 ε n +k 2 θ n )

[0179] Among them, Δ d is the demand correction, d is the adjustment factor, Q d is the predicted demand for the target model smart meter, Q n is the predicted demand for the relevant model of smart meter n, ω n is the historical proportion of the relevant model of smart meter n, ε n is the inherent substitution relationship between the relevant model smart meter n and the target model smart meter, θ n is the demand substitution relationship between the related model smart meter n and the target model smart meter, k 1 and k 2 The preset weights.

[0180] In a possible implementation, the demand modification module 22 is further configured to:

[0181] Before determining the function duplication rate of each related model of smart meter with the target model of smart meter under each demand cause based on the importance index of each meter function under each demand cause, for each demand cause, determine the importance index of each meter function of the first related model of smart meter under that demand cause based on the analytic hierarchy process.

[0182] In a possible implementation, the supply chain parameters include demand standard deviation, production capacity efficiency and supply chain efficiency; the inventory determination module 23 is specifically used to:

[0183] Calculate the inventory safety margin of the target model smart meter based on the demand standard deviation, production efficiency and supply chain efficiency of the target model smart meter;

[0184] The sum of the inventory safety margin and the predicted demand is calculated as the inventory of the target model smart meter. In a possible implementation, the calculation formula for the inventory safety margin is:

[0185] M=σ d (1-sc)(1-ce)

[0186] Among them, M is the inventory safety margin, σ dis the standard deviation of the demand for the target model smart meter, sc is the production efficiency, and ce is the supply chain efficiency.

[0187] The embodiment of the present invention analyzes overlapping functions and difference functions, evaluates the substitution relationship between the related model smart meters and the target model smart meters, and quantifies the influence of the related model smart meters on the demand fluctuation of the target model smart meters, determines a more accurate revised demand, and then considers the influence of the supply chain parameters of the target model smart meters on the inventory effect, determines the inventory based on the revised demand, so that the inventory is closer to the actual demand of the target model smart meters, avoiding the situation where the target model smart meters cannot be provided to users in a timely manner.

[0188] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0189] Those of ordinary skill in the art will appreciate that the templates, units, and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. 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.

[0190] If the module / 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 present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor, the steps of the above-mentioned inventory control method embodiments of each smart meter can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device that can carry the computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory, random access memory, electrical carrier signal, telecommunication signal and software distribution medium.

[0191] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A method for controlling inventory of a smart meter, characterized in that: include: Obtain the predicted demand for the target model of smart meters; Correcting the predicted demand based on a substitution relationship between a related model smart meter and the target model smart meter to obtain a corrected demand; The inventory quantity of the target model smart meters is determined based on the supply chain parameters of the target model smart meters and the corrected demand quantity, so as to perform inventory control on the target model smart meters based on the inventory quantity.

2. The inventory control method of the smart meter according to claim 1, characterized in that: The substitution relationship includes an inherent substitution relationship and a demand substitution relationship; The step of correcting the predicted demand based on the substitution relationship between the related model smart meter and the target model smart meter to obtain the corrected demand includes: For each related model of smart electric meter, based on the inherent substitution relationship and demand substitution relationship of the related model of smart electric meter, calculate the substitution rate of the related model of smart electric meter for the target model of smart electric meter; Determining a demand correction amount of the target model smart meter based on a replacement rate of various related models of smart meters for the target model smart meter; The predicted demand quantity is corrected based on the demand correction amount to obtain a corrected demand quantity.

3. The inventory control method of the smart meter according to claim 2, characterized in that: Before calculating the replacement rate of the smart meter of the relevant model for the smart meter of the target model based on the inherent replacement relationship and the demand replacement relationship of the smart meter of the relevant model for each smart meter of the relevant model, the method further includes: For each relevant model of smart electric meter, the cross price elasticity between the relevant model of smart electric meter and the target model of smart electric meter is calculated as the inherent substitution relationship between the relevant model of smart electric meter and the target model of smart electric meter; Based on the importance index of each meter function under each demand generation reason, determine the function duplication rate of each related model smart meter with the target model smart meter under each demand generation reason; wherein the demand generation reason includes function upgrade, new meter installation and replacement of old meter with new one; For the first related model smart meter, based on the historical proportion of each demand generation reason, the function repetition rate of the first related model smart meter and the target model smart meter under each demand generation reason is weighted summed to obtain the demand substitution relationship between the first related model smart meter and the target model smart meter; wherein the first related model smart meter is any related model smart meter.

4. The inventory control method of the smart meter according to claim 3, characterized in that: The formula for calculating the function duplication rate is: in, is the function repetition rate, ω i is the importance index of function i, i is the function that both the relevant model smart meter and the target model smart meter have, j is the function that the relevant model smart meter has but the target model smart meter does not have, and k is the function that the relevant model smart meter does not have but the target model smart meter has.

5. The inventory control method of the smart meter according to claim 3, characterized in that: The formula for calculating the demand correction is: D d =ζ d Q d ∑Q n oh n (ω1e n +k2θ n ) Among them, Δ d is the demand correction, d is the adjustment factor, Q d is the predicted demand for the target model smart meter, Q n is the predicted demand for the relevant model of smart meter n, ω n is the historical proportion of the relevant model of smart meter n, ω n is the inherent substitution relationship between the relevant model smart meter n and the target model smart meter, θ n is the demand substitution relationship between the related model smart meter n and the target model smart meter, and k1 and k2 are preset weights.

6. The inventory control method of the smart meter according to claim 3, characterized in that: Before determining the function duplication rate of each related model of smart electric meter with the target model of smart electric meter under each demand generation reason based on the importance index of each electric meter function under each demand generation reason, the method further includes: For each demand generating reason, the importance index of each meter function of the first relevant model smart meter under the demand generating reason is determined based on the hierarchical analysis method.

7. The inventory control method of the smart meter according to claim 1, characterized in that: The supply chain parameters include demand standard deviation, production efficiency and supply chain efficiency; the determining the inventory of the target model smart meter based on the supply chain parameters of the target model smart meter and the corrected demand includes: Calculate the inventory safety margin of the target model smart meter based on the demand standard deviation, production efficiency and supply chain efficiency of the target model smart meter; The sum of the inventory safety margin and the predicted demand is calculated as the inventory of the target model smart meter.

8. The inventory control method of the smart meter according to claim 7, characterized in that: The formula for calculating the inventory safety margin is: M=σ d (1-sc)(1-ce) Among them, m is the inventory safety margin, σ d is the standard deviation of the demand for the target model smart meter, sc is the production efficiency, and ce is the supply chain efficiency.

9. An inventory control device for a smart meter, characterized in that: include: An acquisition module, used to acquire the predicted demand of the target model smart meter; A demand correction module, used to correct the predicted demand based on the substitution relationship between the relevant model smart meter and the target model smart meter to obtain a corrected demand; The inventory determination module is used to determine the inventory of the target model smart meter based on the supply chain parameters of the target model smart meter and the corrected demand, so as to perform inventory control on the target model smart meter based on the inventory.

10. The inventory control device of the smart meter according to claim 9, characterized in that: The substitution relationship includes an inherent substitution relationship and a demand substitution relationship; the demand correction module is specifically used for: For each related model of smart electric meter, based on the inherent substitution relationship and demand substitution relationship of the related model of smart electric meter, calculate the substitution rate of the related model of smart electric meter for the target model of smart electric meter; Determining a demand correction amount of the target model smart meter based on a replacement rate of various related models of smart meters for the target model smart meter; The predicted demand quantity is corrected based on the demand correction amount to obtain a corrected demand quantity.

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