25 results about "Grid resources" patented technology

The invention discloses a new energy electric vehicle ordered charging method considering multiple factors, which realizes ordered charging through a closed-loop framework of data driving, multi-objective optimization, intelligent scheduling and dynamic feedback based on multi-dimensional data such as user demand, power grid stability, economical efficiency and renewable energy utilization, and can improve the charging efficiency on the basis of meeting the charging demand of a user. Peak clipping and valley filling of power grid loads, efficient utilization of renewable energy sources and user charging cost optimization are achieved, power grid load fluctuation is reduced, the electric energy quality is improved, the renewable energy sources are utilized to the maximum extent, it is ensured that the requirements of new energy electric vehicle users are met, and meanwhile the economical efficiency and stability of a power grid are achieved. Meanwhile, through an intelligent scheduling system and load prediction, charging tasks are uniformly distributed to night valley periods, so that a power grid load curve is more stable, and the utilization efficiency of power grid resources is optimized; and meanwhile, through an intelligent algorithm and a big data technology, the charging demand prediction accuracy is improved, and charging scheduling is more intelligent and accurate.

The invention relates to the technical field of power management, and discloses a power grid resource visual display method for a business expansion scheme. According to the method, by collecting and processing the power grid operation data, the power grid topological data and the user power load historical data in real time, high-quality and more accurate fusion analysis of the data is guaranteed, static data is converted into dynamic information, the limitation that a traditional visualization tool can only provide outdated information is overcome, and the method is suitable for popularization and application. By means of calculation of short-term and long-term load prediction, the influence of a newly added load on the overall safety and stability of an existing power grid is effectively evaluated, and a user can visually observe voltage distribution of each node of the power grid, a branch current state and a real-time load condition through a visual display module, so that the user experience is improved. According to the comprehensive display scheme, the intelligence level of power resource configuration is improved, important support is provided for optimization management decision of power grid operation, and efficient utilization and further sustainable development of power grid resources can be achieved.

The invention provides a three-dimensional flow field simulation method and system based on a clean air conditioner. The method comprises the following steps: constructing a grid historical database of an electronic plant; according to the grid historical database, an AI pre-judgment model is trained, and the AI pre-judgment model is based on a random forest algorithm superposition space attention mechanism; obtaining dynamic scene features of the electronic plant, inputting the dynamic scene features into the trained AI pre-judgment model, and outputting high-risk area coordinates and partition grid parameters; then generating a three-layer multi-scale grid of a macroscopic layer, a mesoscopic layer and a microscopic layer, and coupling and transmitting data by adopting an overlapping grid technology to obtain a grid; the method comprises the following steps: performing independence verification on a grid, and outputting a final grid file, specifically, through AI learning and a multi-scale technology, realizing distribution of grid resources according to needs, not only solving the contradiction that the traditional grid is too dense to waste computing power and too sparse to be insufficient in precision, but also capturing the association of microscopic airflow and macroscopic airflow.

A low-altitude corridor intelligent management and control system comprises a three-dimensional grid resource pool construction module and a resource scheduling module, the three-dimensional grid resource pool construction module is used for constructing a three-dimensional dynamic grid resource pool of a low-altitude airspace, dividing the low-altitude airspace into three-dimensional grid units, and associating the three-dimensional grid units with aircraft parameters; the resource scheduling module is internally provided with a resource pointer, and the resource pointer is used for scheduling the right to use the three-dimensional grid units of the three-dimensional dynamic grid resource pool; the resource scheduling module is further provided with a first time threshold judgment unit, and when the three-dimensional grid unit is in an occupied state and is not used after exceeding a first time threshold, the three-dimensional grid unit is released to be in an allocable state through a resource pointer. Through airspace dynamic scheduling, real-time data fusion, intelligent rendering optimization and a cross-airspace cooperation mechanism, the problems of low airspace utilization rate, scheduling lag, insufficient visualization efficiency and the like in the prior art are effectively solved.

A low-altitude corridor intelligent management and control system comprises a three-dimensional grid resource pool construction module and a resource scheduling module, the three-dimensional grid resource pool construction module is used for constructing a three-dimensional dynamic grid resource pool of a low-altitude airspace, dividing the low-altitude airspace into three-dimensional grid units, and associating the three-dimensional grid units with aircraft parameters; the resource scheduling module is internally provided with a resource pointer, the resource pointer is used for scheduling the use right of the three-dimensional grid units of the three-dimensional dynamic grid resource pool; the resource scheduling module is further provided with a first time threshold judgment unit, when a three-dimensional grid unit is in an occupied state and is not used for more than a first time threshold, the three-dimensional grid unit is released as a distributable state through the resource pointer. Through airspace dynamic scheduling, real-time data fusion, intelligent rendering optimization and cross-airspace collaborative mechanism, the present application effectively solves the problems of low airspace utilization, scheduling lag, insufficient visualization efficiency and the like in the prior art.

The invention relates to the technical field of three-dimensional data processing, and discloses a three-dimensional grid data processing and multiplexing method and system, and the method comprises the steps: S1, obtaining and analyzing grid data, obtaining three-dimensional grid original data, and carrying out the format recognition, geometric analysis and topology analysis of the three-dimensional grid original data; s2, carrying out reuse-oriented standardization processing; s3, constructing multiplexing description information; s4, grid resource storage and index management; s5, determining a subset based on the request; s6, on-demand conversion and result generation; and S7, unified scheduling control. By constructing multiplexing description information containing a unique identifier, a hierarchy mapping relationship, a block mapping relationship, version information and a service adaptation mark, unified management and efficient multiplexing of grid data under different hierarchy and service scenes are realized, and unified data semantic support is provided for hierarchical retrieval, on-demand extraction and multi-service collaboration; therefore, the reusability of the three-dimensional grid data and the system cooperation efficiency are remarkably improved.

The invention provides a power grid investment intelligent decision-making method, system and device and a medium, and the method comprises the steps: generating a power grid resource efficiency distribution index through a resource distribution evaluation model based on the resource data of a power grid; based on the equipment operation data of the power grid, the operation feasibility analysis engine outputs a power grid reliability index; based on the electric energy data and the equipment operation data of the power grid, calculating an environmental influence index by using an environmental influence calculation unit; performing multi-dimensional index fusion calculation on the power grid resource efficiency distribution index, the power grid reliability index and the environmental influence index, and generating an investment strategy of a power grid investment project in combination with the power market data and the resource data of the power grid; executing the investment strategy of the power grid investment project, and driving the power grid to perform operation strategy adjustment. According to the method, comprehensive evaluation of the power grid investment project from all aspects is facilitated, the decision accuracy of the power grid investment project can be improved, and safe and reliable operation of the power grid is ensured.

The invention discloses a regional power grid resource optimization scheduling method based on multi-time scale closed-loop feedback, and the method comprises the steps: firstly constructing a day-ahead scheduling model, and carrying out the prediction through the day-ahead scheduling model, and generating a day-ahead scheduling plan; constructing an intra-day rolling scheduling optimization model to perform rolling scheduling on the day-ahead scheduling plan in real time at the resolution of 15 minutes to form a dynamic scheduling scheme; constructing a multi-dimensional flexibility evaluation index system, and carrying out quantitative analysis and evaluation on the adjustment capability of the dynamic scheduling scheme through a multi-dimensional flexibility index; and an evaluation result is fed back to the intra-day scheduling optimization model to correct the next rolling scheduling, continuous iterative optimization of the rolling window is realized, and an actual optimization scheduling scheme of the regional power grid resources is obtained. According to the method, the problems that a single time scale optimization framework is mostly adopted by an existing scheduling model, a day-ahead plan and real-time scheduling are separated, and a cross-time scale collaboration mechanism is lacked are solved.

The application discloses a kind of protection device signal classification and method of hanging, belong to the technical field of power system relay protection, the protection device signal classification and method of hanging, comprising the following steps: obtaining the protection signal provided by protection device, the protection signal is hung to corresponding primary equipment, and matches grid resource service middle station resource ID;Read the measurement name of the protection signal, according to the keyword mapping table, the measurement name is classified, and the classification result is mapped to grid resource service middle station, to obtain the signal type corresponding to the protection signal in grid resource service middle station.The relationship between the protection signal and primary equipment is hung, and the protection signal is classified, which greatly improves the processing efficiency, solves the problem of protection signal hanging main device and protection signal telesignalling data classification in centralized control system.

This application provides a method, apparatus, electronic device, and storage medium for processing art resources. The method includes: acquiring mesh resources created by DCC software, the mesh resources including multiple mesh models; determining mesh groups corresponding to each of the multiple mesh models based on the vertex data of each mesh model; classifying each mesh model into its corresponding mesh group according to the determined mesh group; and exporting the mesh models in each mesh group according to the export format required by the corresponding mesh group. This achieves automatic classification of mesh models in art resources and exports different types of mesh models according to their respective format requirements, which can improve the efficiency of DCC software in exporting art resources and reduce the probability of errors.

The application provides a three-dimensional flow field simulation method and system based on a clean air conditioner, a grid historical database of an electronic workshop is constructed; an AI prediction model is trained according to the grid historical database, the AI prediction model is based on a random forest algorithm and superimposes a space attention mechanism; dynamic scene features of the electronic workshop are acquired, and the dynamic scene features are input into the trained AI prediction model, and high-risk area coordinates and partition grid parameters are output; then, a macroscopic layer, a mesoscopic layer and a microscopic layer of three-layer multi-scale grids are generated, data is coupled and transmitted by using an overlapping grid technology, and a grid is obtained; the grid is verified for independence, and a final grid file is output; specifically, grid resources are allocated on demand by AI learning and multi-scale technology, so that the contradiction between waste of computing power caused by too dense traditional grids and insufficient accuracy caused by too sparse traditional grids is solved, and the correlation between micro air flow and macro air flow can be captured.

The invention discloses a fixed contour layout planning method considering right-angle polygon soft modules, which comprises the following steps of: (1) according to a given circuit netlist, initially setting each module into a point shape; (2) if the area of the soft module does not reach the minimum required area, gradually increasing the area of the soft module; (3) optimizing overlapping among the modules by adopting a global layout planning model based on an electrostatic field until the density overflow value is reduced to a preset target value; (4) dividing the layout area into a plurality of grids, wherein the soft module competes for residual grid resources; (5) calculating a negotiation sequence of the soft modules; (6) updating the corresponding grid congestion penalty cost; and (7) updating the historical cost of the grids after completing the grid occupation of all modules. And (8) executing soft module movement to optimize the line length. According to the method, the position and the shape of the right-angle polygon soft module can be determined under the conditions of fixed contour constraint and existence of the pre-placed hard module, the line length is effectively reduced, and the requirements of the current layout planning stage can be met.

The invention relates to the technical field of digital twinning three-dimensional visualization, and discloses a beverage production line digital twinning three-dimensional scene lightweight and real-time rendering optimization method, which comprises the following steps: constructing each grid grouping candidate gear set; determining a candidate quality parameter finally adopted by the grid group in the candidate gear of each grid group; performing QEM edge folding iteration simplification based on accumulative error constraint on the shared grid resource corresponding to each grid group to generate a group simplification grid, and setting an equipment function domain identifier for representing an equipment function domain to which the object belongs for the simplified renderable grid object, taking the equipment function domain identifier as a merging boundary constraint of grid merging; and performing grid merging on the renderable grid objects in each merging group, and replacing a plurality of rendering objects in the same merging group with a single rendering object to realize rendering optimization. According to the invention, a complex digital twinning scene can be smoothly operated in a low-configuration hardware environment.

This invention provides a method and related apparatus for flexible resource regulation based on a novel aggregator framework, belonging to the field of distributed energy resource aggregation management. Firstly, this invention solves the multi-market joint optimization scheduling problem using a pre-constructed first planning model. This fully explores the trading value and arbitrage space of different electricity markets, maximizes the overall market revenue of the aggregator, effectively shortens the investment return cycle of flexible resources, and optimizes the spatiotemporal allocation of grid resources. Based on this, a second planning model is introduced to solve the altruistic revenue allocation problem, aiming to minimize the cost allocation differences among all participants in the community. This fairly and reasonably redistributes the market revenue maximized in the first stage among community participants, fundamentally solving the problem of community revenue imbalance, enhancing the enthusiasm and sustainability of users participating in flexible resource regulation, and ultimately achieving the synergistic development of improved energy system economic efficiency and fair community user revenue.

The present invention belongs to the field of converter stations in power systems, and discloses a method and system for verifying a converter station model. The physical database tables of the converter station are obtained, and the physical table naming, physical table attributes, non-empty elements, physical table primary keys, and physical table enumerated values of the database physical tables are verified according to a preset physical model rule file to obtain a physical model verification result. The information model configuration file of the converter station is obtained and parsed to obtain a parsed file. Then, according to a preset logical model rule file, the version number, syntax, semantics, grid resource asset rules, boundary model, and topology of the parsed file are verified to obtain a logical model verification result. The physical model verification result and the logical model verification result are used as the converter station model verification result and output. Through the preset physical model rule file and logical model rule file, deeper verification of the converter station model is realized, thereby ensuring the stable and efficient operation of the converter station.

Embodiments of the present invention disclose a phase-controlled, favorable oil and gas exploration zone classification and evaluation method, device, and medium. The phase-controlled favorable oil and gas exploration zone classification and evaluation method includes: determining a favorable oil and gas exploration zone and dividing the zone into multiple grids; establishing a phase-controlled favorable zone classification and evaluation standard to obtain a grid standard; establishing an uncertainty simulation model based on small-cell control; simulating the grid resource volume based on the grid standard and the small-cell control-based uncertainty simulation model; and evaluating the favorable oil and gas exploration zone based on the simulated resource volume. This method reduces errors and accurately predicts the location of the favorable oil and gas exploration zone.

The application discloses a kind of multi-temporal main and microgrid resource collaborative control method and system, based on the main and micro all application scene main demand, research station line variable house topology multi-scene resource intelligent aggregation technology, support mass resource classification aggregation and multi-scene flexible aggregation, combined with the main and micro integration model and each level regulation resource and regulation capacity, establish the main and micro integration balance analysis model, for the local adequacy in main and microgrid, new energy consumption and other application scenes, research main and micro multi-level collaborative optimization decision technology, establish the main and micro collaborative forward-looking optimization model, propose main and micro ultra-short-term real-time correction strategy, provide accurate decision support for power grid dispatching, it has important significance in the main and micro integration balance analysis and early warning capability.

The invention relates to a cloud server deployment method and device, computer equipment, a storage medium and a computer program product. The embodiment of the invention can be applied to various scenes such as cloud technology, artificial intelligence, intelligent traffic, auxiliary driving and the like. The method comprises the following steps: in response to a cloud server creation request, determining request resource group information indicated by the cloud server creation request; determining grid resource group information adapted to the request resource group information, the grid resource group information indicating grid resources pre-divided from the first physical server, and the grid resources indicating available resources on the first physical server; and creating the cloud server on the first physical server indicated by the grid resource group information by using the available resources indicated by the grid resource group information. When the method is used for deploying the cloud server, various types of resources in the physical server can be effectively utilized.

The invention provides a plant station three-dimensional model digital-analog fusion method and system based on homologous maintenance, and aims to realize plant station three-dimensional homologous maintenance upgrading by expanding a two-dimensional homologous maintenance tool, bind a three-dimensional model and business data in a homologous manner, and accurately map a two-dimensional wiring diagram and the three-dimensional model. Through the power equipment nameplate text recognition method based on deep learning, equipment signboard detection, text detection and text recognition are carried out, equipment nameplate text information associated with an equipment model is obtained, text similarity matching with an account in a power grid resource service is carried out, and efficient association of equipment information and account data is realized. The function design of the system comprises functions of equipment structure tree query, station building three-dimensional model list query, preview, addition, service enabling and the like, and functions of one-key matching, digital-analog association, equipment type screening, association loading, to-be-handled and handled information lists and the like, and supports efficient data maintenance and management of operation and maintenance teams.

The invention discloses a regional power grid resource collaborative analysis method, system, equipment and medium, and relates to the technical field of power grid dispatching, and the method comprises the steps: obtaining a region and sub-regional power grid model data and plan data contained in the region; a first resource scheduling model is established, the first resource scheduling model is a mathematical model for optimizing the balance margin of the sub-region, and the balance margin refers to the power capable of being provided by the sub-region or the power obtained by the sub-region; a second resource scheduling model is established with the sub-region balance margin as a boundary, and the second resource scheduling model is an optimized region balance margin mathematical model; and solving the first resource scheduling model and the second resource scheduling model to obtain regional and sub-regional balance margins, taking the regional and sub-regional balance margins as power capable of being provided or obtained by regional or sub-regional equivalent nodes, and taking the regional and sub-regional balance margins as input of a power grid resource large-range optimization configuration module, thereby realizing resource optimization configuration considering network security.

The invention relates to the technical field of micro-grid resource scheduling, in particular to a micro-grid resource aggregation capability prediction method and system, and the method comprises the steps: obtaining the source load storage load data of a micro-grid, and enabling the data to be used for representing the operation states of a distributed power supply, a flexible load and an energy storage device; constructing an overall aggregation feasible interval according to the individual feasible intervals of the three types of resources, and creating an aggregation power energy boundary model according to the overall aggregation feasible interval; and inputting the model into an ultra-short-term prediction framework of a deep neural network, predicting a future dynamic evolution trend by the framework, outputting a prediction aggregation feasible interval, accurately describing a power-energy combined feasible region of the source-load-storage integrated micro-grid in a minute-level scale, quantifying a nonlinear cumulative effect of the micro-grid evolved along with time, and calculating a power-energy combined feasible region of the micro-grid. And the reliability and timeliness of subsequent scheduling decisions are improved.

The invention belongs to the technical field of engineering machinery automatic driving, and provides an engineering machinery collaborative operation control method and system based on multi-thread simulation, each machine is abstracted into an independent thread, the path of each engineering machine is planned, and a time window occupied by map grid resources is pre-calculated; dividing dynamic grids according to the landform complexity; resource competition and lock allocation are judged according to the time window, for a conflict scene, high-priority engineering machinery is allowed to occupy resources preferentially, and low-priority engineering machinery adjusts the time window; modeling the space resources into a shared memory, constructing a resource allocation diagram according to the lock state of the grid after lock allocation, and generating an occupation and request relation diagram of the engineering machinery and the grid; deadlocks in the source distribution diagram are detected, and for engineering machines with different priorities, the machines with the low priorities are forced to release locks and re-planned; the problem of potential conflicts in a future time window is solved, and the problem of circular waiting of a traditional priority preemption strategy is avoided.

The application relates to the technical field of administrative management and dispatching, and discloses an old-age care service system based on the Internet, which comprises a data acquisition unit, a logic operation unit and a resource configuration unit. The system divides a target area into a business management grid and determines a grid resource pre-occupancy weight by extracting service demand distribution characteristics and calculating demand distribution entropy. When the weight is out of limit, a resource node is locked and a virtual dispatching voucher is generated. A response preparation degree deviation is calculated based on the length of time that the node is static, a pre-displacement task is generated, and the resource node is driven to move to a high-probability demand area before a formal work order, the management and dispatching logic is reconstructed from passive response to a pre-displacement mechanism based on prediction, the resource state is locked by using the virtual voucher, and the starting hysteresis effect is eliminated, so that the response certainty of the system in response to sudden demand is synergistically enhanced.

The present invention discloses a method for allocating power-related appeal tasks, specifically related to the field of power grid management, and is used to solve the problems of resource optimization and balance in the allocation of power-related appeal tasks. First of all, the segmented adaptive filtering algorithm effectively removes seasonal interference in historical task data, making the data more stable, thereby clearly revealing the long-term trend of resource allocation and laying a scientific analysis foundation. Subsequently, the transient pressure absorption potential index is used to evaluate the resource adaptability and elasticity of each grid in coping with sudden tasks, ensuring the rapid response and stability of resource allocation in a high-pressure environment. The structural resource allocation bias index further identifies and quantifies potential biases and imbalances in resource allocation, providing a basis for optimization. Finally, through the generation of the spiral resonance index, the rationality and coordination of resource allocation in each grid are comprehensively evaluated, significantly improving the efficiency of power-related appeal task allocation and the stability of the system.