50 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 discloses a new energy base power supply game optimization planning method and system, and the method is characterized in that the method comprises the steps: building a new energy base power supply operation model containing field station side energy storage and shared energy storage based on the priority of a flexible resource power storage and discharge calling sequence when the new energy power is residual and insufficient; obtaining power supply investment basic parameters of a new energy base to be planned, and establishing participants, strategy space and a revenue function of the new energy base game model; formulating game rules and game equilibrium conditions based on the new energy base game model; solving by adopting a discrete integer genetic algorithm, carrying out game iteration and recording to obtain a Nash equilibrium point of decision capacity of each participant; a strategy space and a revenue function in the game model consider a decision-making mode of configuring station-side exclusive energy storage by a new energy investor; the game planning method provided by the invention can consider the decision-making motivation and benefit demand of each power supply investor, and is used for solving the new energy base power supply planning problem considering the interests of multiple parties.

The invention discloses a self-adaptive generator set load adjustment and coal optimized supply control method, and the method achieves the accurate prediction of short-term and medium-and-long-term load demands through the building of a self-adaptive generator set load adjustment and coal optimized supply control method, and a deep learning load prediction model of multi-dimensional data. And a hierarchical response mechanism and a real-time control algorithm are combined, so that the load response speed and the adjustment efficiency are improved. The dynamic coal purchase and supply plan is combined with the reinforcement learning algorithm, the coal inventory can be dynamically adjusted according to the load demand, and the supply efficiency and economy are optimized. Coal quality monitoring equipment is introduced, high-calorific-value coal is distributed to a high-load unit in a targeted mode, the combustion efficiency is improved, and coal consumption and equipment abrasion are reduced. A closed-loop feedback system and a self-learning mechanism realize real-time monitoring and automatic adjustment, and the prediction precision and adaptability are improved.

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.

The invention relates to a method for generating a provision plan (30) for at least one tool (18), comprising the steps of: (S1) receiving a production plan (32) by means of the electronic computing device (28); (S2) determining the at least one required tool (18) depending on the production plan (32); (S3) determining a first position (P1) of a tool storage (16) for the tool (18) relative to a second position (P2) of the production machine (12, 14); (S4) determining a provision time (34) for the tool (18) depending on the relative positions (P1, P2); and (S5) generating the provision plan (30) for the at least one tool (18) depending on the determined provision time (34). The invention further relates to a computer program product, a computer-readable storage medium, and an electronic computing device (10).

The invention discloses a bulk commodity supply chain management system, and relates to bulk commodity supply chain management, and the system comprises a digital supply chain module which carries out supply chain business process examination and approval management and online business management and control; the coaling business management module is used for generating a supply plan according to user requirements and the station coal inventory information, controlling vehicles to enter and unload coal, collecting coal unloading data and updating the station coal inventory information; the station cargo control module controls the vehicles to enter and exit the station according to the supply plan and collects cargo loading and unloading metering data of the vehicles; the field short-time transfer business module is used for obtaining coal transfer starting quantity and stopping quantity data through interaction with belt scale Internet of Things equipment at a loading port and an unloading port, and forming coal transfer data in combination with the collected vehicle loading and unloading cargo metering data; processing the coal circulation data by using a flow calculation framework, and predicting the time and quantity of coal circulation through a data mining algorithm; aiming at low management efficiency of bulk commodity supply chains in the prior art, the efficiency is improved.

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.

Successful supply chain optimization must mitigate imbalances between supply and demand over time. To successfully perform supply planning for optimal and viable execution, the predictability for both demand and supply is essential. However, in complex supply chain networks with numerous nodes and edges, accurate supply predictions are challenging due to dynamic node interactions, cascading supply delays, resource availability, production, and logistic capabilities. Consequently, supply executions often deviate from their initial plans. A Graph-based Supply Prediction (GSP) probabilistic model is presented. The attention-based graph neural network (GNN) model predicts supplies, inventory, and imbalances using graph-structured historical data, demand forecasting, and original supply plan inputs. The experiments, conducted using historical data from a global consumer goods company's large-scale supply chain, demonstrate that GSP significantly improves supply and inventory prediction accuracy, potentially offering supply plan corrections to optimize executions.

The invention relates to the field of big data management and control, in particular to a supply chain group meal management and control system based on big data, which comprises a dish information module used for collecting delivery time of a plurality of dishes, a train information module used for collecting train information of a plurality of trains, a collection module used for collecting the delivery time and preprocessing the delivery time to generate corresponding preprocessing data, and a management and control module used for managing the corresponding preprocessing data. The system comprises a preprocessing module used for preprocessing data, a learning module used for selecting a plurality of index characteristics of the preprocessing data for learning and generating a standard distribution time length of dishes, and a planning module used for generating a group meal supply plan according to the standard distribution time length and train information, adjusting the learning module according to the group meal supply plan, and visualizing a group meal supply chain by using the learning module. The difficulty of management and control in the distribution process is reduced, the freshness of the food materials in the distribution process is guaranteed, the problem that the food production amount is not easy to control is effectively solved, the problem of information lag of a food supply chain is further avoided, and the practicability of the group meal supply chain is improved.

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.

The present disclosure proposes a method, device, electronic device and medium for planning fluid supply for an automated working face in a coal mine. The method comprises: obtaining an original fluid supply curve corresponding to the coal mining process of the working face; obtaining at least one original fluid supply process data from a comprehensive mining big data platform; and processing the original fluid supply curve according to at least one original fluid supply process data to obtain a flow prediction curve. Through the present disclosure, the fluid supply effect of the automated working face in a coal mine can be effectively improved, and the practicality of fluid supply for the automated working face in a coal mine can be improved.

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).

To provide a supply and demand plan development support device that is capable of developing a supply and demand plan that takes into account the uncertainty of renewable energy power sources and demand, and a lead time for countermeasures.SOLUTION: A supply and demand planning support device 100 includes: a scenario creation unit 21 that creates a forecast error scenario including time-series data of a forecast error and an occurrence probability thereof, using forecast error data, which is a difference between forecast values and actual values of demand and renewable energy power sources for a past specified period; a reserve margin evaluation unit 22 that evaluates a supply reserve margin using the forecast error scenario created by the scenario creation unit 21 and power generation plan data; and an additional supply plan development unit 23 that develops an additional supply plan using the evaluation result of the supply reserve margin by the reserve margin evaluation unit 22 and data on candidate additional supply measures to compensate for supply capacity shortages.SELECTED DRAWING: Figure 2

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.

The invention discloses a demand processing method, computing equipment and a computer readable storage medium. The method comprises the following steps: acquiring at least one piece of demand information of a target country for a target engineering machine in a future preset duration; the demand information comprises configuration information, demand quantity and demand delivery time; according to the demand delivery time and a preset logistics cycle and / or production cycle, determining a goods source demand type corresponding to the target engineering machinery required by each piece of demand information; according to the goods source demand type, the demand information and a preset goods source pool, goods source scheduling operation is executed on the target engineering machinery; the goods source pool comprises local warehouse goods source information and transportation in-transit goods source information of the target engineering machinery in the target country and local factory goods source information. Therefore, overall planning and scheduling of goods sources can be realized, the risk that customers are lost or demands cannot be satisfied due to regional stockout is reduced, and the inventory turnover rate and the coordination efficiency of market demands are improved.

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.

To enable efficient power supply and demand management.SOLUTION: A power supply and demand management device 100 includes a supply management unit 111 that receives a power supply plan including a supply plan value that is a time slot for scheduled power supply and an amount of power to be supplied from a power supply system 510, a memory unit 130 that stores past power supply plans and actual supply values that are amounts of power actually supplied in the time slots of the power supply plan, and a supply reliability calculation unit 114 that calculates supply reliability of the supply plan value included in the power supply plan on the basis of the supply plan value and actual supply value included in the past power supply plan and the supply plan value included in the power supply plan.SELECTED DRAWING: Figure 1

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 present application relates to a supply chain optimization method and system based on digital rights products, the method includes obtaining the product collection quantity and product write-off quantity of digital rights products, and performing product supply planning for digital rights products, obtaining supply plan data, obtaining supply plans and supply operation data of all suppliers, matching each supplier with a supply plan and selecting the supplier with the highest matching degree, obtaining supplier data related to the supply plan data, analyzing the supply association relationship between supplier data and supply plan data, and combining peer marketing data of similar products to build a supply chain management model for digital rights products, obtaining the supply performance data of each supplier in the supply process, inputting the supply performance data into the supply chain management model to evaluate the supply capacity, and performing supply optimization processing according to the evaluation results. The present application has the effect of improving the timeliness of supply of digital rights products.