30 results about "Supply planning" patented technology

The invention discloses a new energy medium and long term stochastic programming method and system coupled with an electro-hydrogen water regulation power supply, and the method comprises the steps: building a power supply planning model with the minimum planning operation cost as an optimization target; bringing the new energy power supply and energy storage adjusting equipment operation model and the new energy consumption rate upper and lower limit constraint expression into a power supply planning model; in consideration of the randomness of fluctuation at two sides of a source and a load in power supply planning, based on the obtained power system operation scene set S and the power supply planning model, dividing into an investment decision-making layer and an operation simulation layer according to a time period influenced by a decision, and constructing a power supply planning two-stage stochastic optimization model based on a typical scene; and solving the power supply planning two-stage stochastic optimization model under a medium and long term planning framework, and determining the investment planning installed capacity of the adjusting power supply and the new energy in the planning level year. According to the invention, economy of medium and long term planning and power supply capacity configuration of new energy can be improved, and reasonable consumption and flexible adjustment of new energy electric power are promoted.

The invention belongs to the technical field of order management, and particularly relates to a production order supply planning management system based on data analysis, and the system comprises an order data collection module which is used for collecting customer order data, and the customer order data comprises historical order data and current order data; the order data analysis module is used for calculating the demand quantity of product orders in M periods in the future based on the obtained historical order data; the supply chain data collection module is used for collecting data of each production line in a supply chain; the supply chain data analysis module is used for calculating the actual order demand quantity of the product in the M periods in the future based on the product order demand quantity and the data of the production line in the supply chain; and based on the data of the production line in the supply chain and the actual demand of the product, the delivery time index of the order product required by the current customer is calculated.

A demand and supply planning method generates a supply-demand plan including information that specifies operation of an energy generation unit for each unit time in a microgrid having energy generation units being connected to an external energy supply system and generating energy while consuming fuel, an energy storage unit, and a load unit; by calculating an optimization problem related to an objective function including terms related to energy transfer from the external energy supply system in the microgrid and terms related to fuel consumption in the microgrid by using a constraint condition related to a relationship between information related to an operating duration time in each of the one or more energy generation units at a start time for generating the supply-demand plan and a minimum operation time constraint of the energy generation unit; and outputting the supply-demand plan based on a calculation result of the optimization problem.

The invention discloses a distributed power supply deployment method and system based on risk assessment. The method comprises the following steps: constructing a distributed power supply planning model taking the annual minimum total cost of a power distribution network as a target function, wherein the model integrates the investment operation cost, the network loss cost, and the output uncertainty operation risk cost and the flexibility insufficient risk cost of a newly constructed distributed power supply; and solving the model by adopting an improved particle swarm algorithm to obtain an optimal site selection and constant volume scheme of the distributed power supply and the energy storage system. By quantifying the two types of risks, the problem of insufficient risk consideration in the existing planning method is solved, and the planning result is more economical and reliable. In addition, the improved algorithm improves the optimization solution efficiency and the global optimization capability.

By supplying hydrogen gas in conjunction with other hydrogen gas supply systems besides hydrogen production equipment, we can meet a certain volume of hydrogen demand and supply hydrogen gas under better supply conditions. [Solution] The supply plan management device 10 manages the gas supply plan when supplying hydrogen gas by a hydrogen gas supply device that includes a water electrolysis hydrogen production device that produces hydrogen gas using electricity from renewable energy, commercial power, or storage batteries, and a gas supply source configured to obtain hydrogen gas by a method other than water electrolysis. The management device 10 includes a selection unit 10b that receives information on which of a plurality of operating modes, including a CO2 reduction mode and a cost reduction mode, to execute, and a planning unit 10d that creates a supply plan according to the hydrogen gas demand according to the operating mode received by the selection unit 10b.

The present disclosure relates to determining acceptability of a remedy for a supply plan deviation with a machine learning model. A system for analyzing a supplier communication regarding a deviation from a supply plan is described. The system can determine a severity of the deviation and determine an impact on a supply chain or inventory level caused by the deviation. A remedy in the supplier communication can be identified, and the system can determine whether the remedy is acceptable to address the deviation. The analysis of the supply plan deviation, the severity of the deviation, the acceptability of the remedy, and / or other factors can be used to generate a supplier score.

A supply chain supply planning device (1) is characterized by comprising: a distribution calculation unit (11) that calculates, on the basis of record information pertaining to supply and demand activities of a supply chain, a distribution pertaining to record information pertaining to each process constituting the supply chain; a distribution influence degree calculation unit (123) that, when information pertaining to an incident that influences the supply chain is input, calculates, on the basis of the record of a change in a distribution of record information pertaining to each past process due to the influence of a past incident similar to the incident, the degree of influence on the distribution of the record information pertaining to each process; and a distribution estimation unit that estimates a future distribution on the basis of the degree of influence on the distribution of the record information pertaining to each process calculated by the distribution influence degree calculation unit (123).

The invention provides a power distribution network supply chain dynamic scheduling method considering internal and external lead period time lag, and relates to the technical field of supply chain management. The method comprises the following steps: according to a preset lead feature library, obtaining lead feature data of various electric power material supply links in a supply chain; according to the conduction characteristic data, predicting conduction probability distribution of each type of electric power material supply links, and according to the conduction probability distribution, generating multiple groups of future conduction scenes of each type of electric power materials through a Monte Carlo method; establishing a day-ahead scheduling model and solving the day-ahead scheduling model according to multiple groups of future lead scenes of each type of electric power materials to obtain a day-ahead scheduling scheme of each scheduling period of the next day; and based on the day-ahead scheduling scheme, in each scheduling period of the next day, establishing an intra-day scheduling model considering the demand scene priority and solving the intra-day scheduling model to obtain a period-level dynamic scheduling scheme. According to the invention, accurate real-time matching between the material supply plan and the power grid demand can be realized, and the problem of plan failure caused by conduction uncertainty and time-varying characteristics is solved.

A material supply plan generation method and device, a storage medium and a server, the method comprising: obtaining material demand details and material supply details, the material demand details comprising a plurality of pieces of material demand information, the material demand information comprising: a demand material identifier, a demand document number and a demand quantity; the material supply details comprise a plurality of pieces of material supply information, and the material supply information comprises a supply material identifier, a supply document number and a supply quantity; determining the supplied quantity in the demand quantity, and / or determining the occupied quantity in the supply quantity; updating the demand quantity based on the supplied quantity, and / or updating the supply quantity based on the occupied quantity; and generating at least one occupancy record for each piece of material demand information, and writing the at least one occupancy record into an occupancy record table. Through the scheme provided by the invention, the accurate material supply plan can be generated.

The present application belongs to the field of network-structured energy storage planning, and provides a network-structured energy storage black start power supply planning method and system, generates a candidate start path set; extracts path associated lines, estimates line condition failure probability according to historical line failure records and power failure time conditions, forms a representative power failure scenario set by using a scenario generation model; comprehensively discriminates candidate path availability, network-structured energy storage power energy satisfaction relationship and transient process safety margin, and constructs an index; based on the candidate path, the representative power failure scenario and the planning evaluation index, organizes candidate objects, scenario information, capacity boundaries and planning constraints, forms input data required by the main problem and the scenario sub-problem; iteratively solves the main problem and the scenario sub-problem, and determines a network-structured energy storage planning scheme that meets the black start reliability requirements and has the optimal recovery support capability. The present application can improve the black start success rate and the recovery support capability of the units to be started after a large-scale power failure.

The application provides a multi-objective power supply planning method based on Pareto front shape optimization and a related device, including obtaining a multi-objective power supply planning model of a project to be planned, and extracting investment decision variables and operation variables from the multi-objective power supply planning model; continuously optimizing solutions composed of the investment decision variables and the operation variables by using a genetic algorithm until the optimization is stopped after a stop condition is met, and a solution set is obtained; selecting a compromise solution meeting a requirement based on a Pareto front shape of the solution set, so as to determine a final multi-objective power supply planning scheme. The application optimizes the investment decision variables and the operation variables by using the genetic algorithm, minimizes conflict relationships between different objectives, selects a balanced compromise solution, and finally determines the multi-objective power supply planning scheme. The method not only considers uniformity and convergence of the Pareto front, but also particularly focuses on influences of the power supply planning on conflict relationships of operation objectives, and improves accuracy and reliability of decision-making.

The invention relates to the technical field of power supply planning of an electric power system, and discloses a power supply planning method, system and device and a medium, and the method comprises the steps: obtaining key parameters of the electric power system, and generating a plurality of source-load random scenes; based on these scenarios, an uncertain set of component faults is constructed, thereby establishing power disturbance and system frequency response equations, including frequency balance constraints. And constructing a power supply planning model including an objective function and constraint conditions, and solving the model to optimize power supply configuration. According to the method, the reliability, the stability and the adaptability of the power system are improved by considering the uncertainty and the frequency stability. Stable operation of the system under various conditions is ensured, the optimal power supply configuration is rapidly determined through the planning model, the planning efficiency is improved, resource waste is reduced, and sustainable development is promoted.

The invention discloses a distributed power supply planning method and system, relates to the technical field of distributed power supplies, and solves the problems that in the prior art, whether a distributed power supply is additionally installed or not mainly depends on experience judgment of workers, quantitative data support is lacked, the working efficiency is low, and misjudgment is prone to occurring. The method comprises the following steps: firstly, collecting historical voltage data of a current area to judge whether the voltage has a voltage quality problem, if the deviation is greater than a limited range, recording the occurrence frequency and duration of the deviation, otherwise, collecting historical voltage data of a next area, and judging again; then, in an area where a voltage quality problem occurs, an optimal scheme is obtained by adopting a mode of solving an objective function, and the objective function comprehensively considers voltage quality benefits, benefits brought by residual electric quantity after voltage deviation is flattened, and power generation cost of the distributed power supply; the optimal scheme solved based on the method can provide a data reference for a manager to make a final decision.

Provide a system. 【Solution means】 As an information acquisition means, means for acquiring environmental information and regional event information via a communication network, Means for acquiring past transaction records from a recording medium, As an analysis means, means for executing an intelligent algorithm for prediction based on the acquired environmental information, regional event information, and past transaction records, As an optimization means, means for creating an optimal supply plan based on the prediction result and the held information, As a notification means, means for reporting the optimized supply plan to the administrator, Means for transmitting information to the administrator using a real-time notification function, Equipped with an adjustable user interface, means for the administrator to modify the supply plan, A system including.

The application provides a distributed power supply planning method and device, electronic equipment and storage medium, and belongs to the field of distribution network planning. The method comprises the following steps: screening the optional nodes of the distributed power supply to be planned based on the small world theory to obtain the candidate nodes, and determining the solution space according to the candidate nodes; constructing an optimization objective function and a constraint condition, initializing the to-be-planned variable of the distributed power supply to be planned to obtain an initial Onomarchus population, improving the Onomarchus algorithm of the initial Onomarchus population through an adaptive weight and a Levy flight strategy to obtain a child population, determining the population fitness of the child population according to the optimization objective function and screening to obtain a new round of Onomarchus population, and iteratively optimizing to obtain optimal planning variables. The important node screening through the small world theory can effectively reduce the solution dimension, the adaptive weight and the Levy flight strategy can improve the convergence speed and the global search ability of the algorithm, and the fast and accurate solution of the distributed power supply planning problem is realized.

It is intended to reduce errors related to an energy supply plan to be formulated. An energy supply plan formulation device includes an acquisition unit for acquiring a change of a base load of energy equipment, a determination unit for determining whether to need correction of at least one of an equipment model and a load model on the basis of the change of the base load, a correction unit for correcting at least one of the equipment model and the load model on the basis of a determination result, a demand forecasting unit for forecasting the amount of energy demand, and a supply plan formulation unit for formulating an energy supply plan on the basis of the equipment model and the amount of energy demand.

A matching support device which achieve matching between demand information and supply information, quickly and accurately reflecting changes in information. The matching support device acquires supply information and / or demand information, performs a matching between the demand information and the supply information, and transmits results of the matching to a supplier terminal and a consumer terminal. The matching support device, during a period specified from the supplier terminal and / or the consumer terminal, continues reception of the supply information and / or the demand information to reflect the changes in information and to continue matching. The matching support device may calculate, based on information of matchings, a schedule-to-result difference ratio of the supply plan information and / or the demand plan information.

The invention relates to the technical field of supply chain management, in particular to a supply chain management method and system based on data analysis processing. Comprising the following steps: S1, acquiring events of each supply chain node, and dividing the events into basic events and sudden events; the supply chain nodes are clustered according to the time proportion of the supply starting time and the supply ending time of the basic event and the sudden event at the supply chain nodes, and a clustering result is obtained; s2, based on the clustering result, extracting material flow, information flow and fund flow information in each supply chain node; and taking the circulation relation of the material flow, the information flow and the fund flow as the first attention degree of each supply chain node. According to the method, supply chain risk distribution is identified through time difference proportion clustering, adaptive adjustment and early warning prompt of a supply plan are realized by combining circulation relation deviation and exponential function dynamic analysis, and the response speed and the cooperation efficiency are improved.

The invention discloses a power system multi-time-space-guarantee power supply planning research method considering extreme weather influence, and relates to the technical field of power system planning and operation, and the method comprises the following steps: collecting plum rain irradiation data and hurricane path data; obtaining the rainfall intensity based on the Weber distribution, calculating a rainfall attenuation coefficient, and obtaining the actual irradiance according to the rainfall attenuation coefficient and the plum rain irradiation data; calculating node wind speed in combination with hurricane path data and preset terrain correction parameters; screening the actual irradiance and the node wind speed to obtain a typical meteorological year, and generating new energy output scene data; and according to the new energy output scene data, constructing a two-stage guarantee power supply planning model, and generating an optimal guarantee power supply planning scheme based on the two-stage guarantee power supply planning model. The method is used for solving the problem that extreme weather space-time characteristics and multi-source collaborative optimization are difficult to consider in the prior art.

The system according to this embodiment aims to efficiently supply ingredients from local farmers and producers. [Solution] The system according to the embodiment comprises a collection unit, a planning unit, and a supply unit. The collection unit collects data from local farmers and producers. The planning unit creates a supply plan based on the data collected by the collection unit. The supply unit supplies local ingredients based on the supply plan created by the planning unit.

The invention relates to a power supply planning method considering boundary uncertainty. The method comprises the following steps: step 1, inputting power supply construction and load conditions of original partitions in long-term planning as basic parameters of a model; 2, sampling uncertainty according to a Monte Carlo simulation method to generate a scene tree of future electricity consumption and load, and generating a possible value set under different time nodes in the future; 3, establishing a rolling optimization power supply structure planning model based on a model prediction control thought; the method has the advantages that the power supply structure planning model is constructed, model prediction control is introduced, pre-planning is realized, and the influence is reduced through an online rolling strategy.

The invention discloses a full-link logistics system, which is used for forming a logistics plan from a plurality of suppliers to a production factory. Comprises: a processing device comprising: an order management module configured to generate an order and a supplier supply plan; the goods taking configuration module is configured to distribute circulation goods taking or zero-load goods taking according to the physical form and the historical transportation frequency of the goods; the path planning module is configured to generate a first planned logistics path for transporting the cargoes distributed to take the cargoes from the suppliers to a central cargo picking bin; a second planned logistics path is generated and is used for transporting the goods distributed to be taken circularly from the supplier to a central goods picking bin; generating a multimodal transport planning path which is used for transporting the goods in the central goods package warehouse to a supply management warehouse; and generating a terminal transportation planning path for transporting the goods in the supply management warehouse to a production factory. The method is suitable for a multi-supplier mode of a large-scale production enterprise, and the flexibility and stability of a supply chain are ensured.

The invention discloses a power system carbon emission boundary making and resource allocation method and system, and belongs to the technical field of power supply planning. The method comprises the steps of obtaining power system planning data; constructing a power supply investment operation model taking the minimum total cost net present value as a target, wherein the model comprises investment constraint and operation constraint; establishing a carbon emission boundary dynamic formulating model based on double-layer optimization, formulating a carbon emission boundary sequence at the upper layer, optimizing power supply investment operation at the lower layer, and realizing boundary optimization through iterative feedback; and solving the model, and outputting a carbon emission boundary sequence and a corresponding power supply investment operation scheme. Through an innovative double-layer optimization model, the technical problem that static carbon emission constraint is difficult to adapt to long-term transformation requirements is solved, scientific formulation of carbon emission boundaries and efficient allocation of resources are realized, and reliable technical support is provided for low-carbon transformation of a power system.

The invention relates to the technical field of electronic manufacturing workshop production scheduling, in particular to an intelligent scheduling method for SMT production line remodeling and material collaboration. According to the method, order and resource information is acquired through data acquisition, a multi-target dynamic scheduling model is established, an equipment white list and a candidate solution set are generated by applying large-field search, an initial production sequence is constructed, a variety sequence is dynamically adjusted, a material supply plan is trimmed by adopting linear programming, and an optimal production scheduling scheme is obtained based on iterative optimization of a column generation algorithm. According to the invention, collaborative optimization of production line remodeling and material supply is realized, and the scheduling efficiency and quality are improved.

The application provides a multi-source supply smoothing scheduling decision method, system, device and storage medium based on cross-period allocation operators, and relates to the technical field of supply chain planning and operation optimization. The method comprises the following steps: acquiring basic business data of a multi-source supply network; using a preset demand distribution weight vector in a week to discretely decompose the total demand of a sales area in each logical week into a daily demand sequence; performing time sequence backtracking on each demand day in the daily demand sequence based on a transportation cycle to determine the corresponding production factory delivery day and the production logical week to which the demand day belongs; generating a cross-period allocation operator according to the attribution relationship; constructing a linear programming model containing the operator and solving the model to generate an optimal supply plan. The application solves the problem of capacity planning distortion caused by non-integer week transportation cycles.

The present invention is an outcome of the "2024 Service BM Overseas Expansion Support Project" managed by KOTRA, and the objective thereof is to provide an integrated system for inventory sharing and sales of products expanding into overseas markets, and, more particularly, the system comprises: a web server linked to a database constructed by collecting and storing, by a company terminal, information about products that can be distributed overseas from among products sold by domestic sellers; a website generation unit that, upon receipt of a sourcing cooperation request from a partner terminal located overseas through the web server, replicates the database, and then generates a replicated database-based partner-dedicated website by using a pre-established website template; a website deployment unit that, before deploying the partner-dedicated website generated by the website generation unit, configures sales products by requesting, from the partner terminal, a selection input for products to be handled from among the products in the database, and deploys, through a specialized hosting company, the partner-dedicated website on which the sales products are configured; and a product supply planning unit that, upon receipt of a purchase request for at least one product from a local buyer terminal overseas through the partner-dedicated website, establishes a product supply plan by identifying the inventory status of the product stored in a domestic logistics storage warehouse and a logistics storage warehouse of a partner company by using an integrated inventory management system.

This invention provides a dynamic scheduling method for distribution network supply chains that considers internal and external conduction time lags, relating to the field of supply chain management technology. The method includes: acquiring conduction time characteristic data for various power material supply links in the supply chain based on a pre-set conduction time characteristic library; predicting the conduction time probability distribution for various power material supply links based on the conduction time characteristic data, and generating multiple sets of future conduction time scenarios for each type of power material using the Monte Carlo method based on the conduction time probability distribution; establishing and solving a day-ahead scheduling model based on the multiple sets of future conduction time scenarios for each type of power material to obtain a day-ahead scheduling scheme for each scheduling period of the next day; and establishing and solving an intraday scheduling model considering the priority of demand scenarios for each scheduling period of the next day based on the day-ahead scheduling scheme to obtain a time-period-level dynamic scheduling scheme. This invention enables accurate real-time matching between material supply plans and grid demand, solving the problem of plan failure caused by conduction time uncertainty and time variability.

The invention relates to the technical field of power supply full-life-cycle cost calculation, in particular to a power supply full-life-cycle cost calculation method based on capacity adequacy, and the calculation method comprises the steps: building a cost optimization model based on the investment cost; cost prediction of the power supply life cycle is completed based on the distributed power supply area node data; determining the cost of the full life cycle of the power supply based on the capacity adequacy; according to the invention, the cost prediction of the power supply life cycle is carried out based on the distributed power supply area node data, and the real-time monitoring and prediction of the power supply operation state are realized; by introducing a calculation formula of a whole life cycle cost minimum value, calculation of an optimal planning scheme of a distributed power supply planning model is realized; the cost prediction of the power supply life cycle is carried out based on the distributed power supply area node data, and the real-time monitoring and prediction of the power supply operation state are realized.

Depending on the uncertainties surrounding the supply chain and the existence of countermeasures, it becomes possible to estimate the future distribution of historical information related to the supply chain. [Solution] The supply chain supply planning device 1 is characterized by comprising: a distribution calculation unit 11 that calculates the distribution of performance information for each process constituting the supply chain based on performance information of supply and demand activities of the supply chain; a distribution impact calculation unit 123 that, when information of an incident affecting the supply chain is input, calculates the degree of impact on the distribution of performance information for each process based on the past changes in the distribution of performance information for each process due to the impact of past incidents similar to the incident; and a distribution estimation unit that estimates the future distribution based on the degree of impact on the distribution of performance information for each process calculated by the distribution impact calculation unit 123.