24 results about "Grid management" patented technology

The invention provides a micro-grid management method and system based on source grid load storage, and relates to the technical field of micro-grids, and the method comprises the steps: S1, obtaining renewable energy power generation data in a micro-grid, the state of charge (SOC) of an energy storage device, a load demand, and power grid operation state information; and S2, performing real-time prediction on the load demand by using an intelligent algorithm and generating a load scheduling plan. According to the micro-grid management method and system based on source grid load storage, load prediction is carried out by introducing an intelligent algorithm, power scheduling between renewable energy sources and an energy storage device is optimized by a dynamic coordination mechanism, and resources are allocated by a multi-objective optimization algorithm, so that efficient management of the micro-grid is successfully realized. By acquiring various data in the micro-grid in real time and combining with a dynamic adjustment scheduling strategy, the method can effectively deal with the uncertainty of load fluctuation and renewable energy output, optimize the operation efficiency of the power grid, and ensure the stability and economy of the system.

A grid management platform is disclosed for predicting and mitigating peak electricity demand events using probabilistic modeling and cost-optimized control. The system includes a likelihood model that evaluates the probability of each remaining day within an evaluation interval being the peak load day. This is achieved through a Monte Carlo simulation engine that generates multiple stochastic realizations of future load trajectories based on historical data, forecast data, and forecast error profiles derived from back testing. The system computes likelihood scores and classifies days using optimized bin thresholds that minimize operational cost, considering demand charges, available distributed energy resources, and forecast uncertainty. Based on the predicted likelihoods, the platform generates actionable insights and transmits control signals to grid-connected assets such as batteries, HVAC systems, and electric vehicle chargers to shift or reduce load during predicted peak periods.

The invention provides an intelligent video security monitoring method and system based on grid management and control, and relates to the technical field of video security monitoring. According to the method, firstly, a monitoring area is divided into a plurality of management grids, and secondly, for each management grid, the activity state of a dynamic target in the management grid is determined according to collected video data; under the condition that a physical communication path exists between at least two management grids, whether a cross-grid flow event exists or not is judged according to the activity state of the corresponding dynamic target; and finally, when a cross-grid flow event exists, generating gridding linkage alarm information. According to the technical scheme provided by the invention, the monitoring area is divided into the grids and the space-time activity association of the dynamic target between the adjacent grids is cooperatively analyzed, so that accurate perception and structured alarm of cross-regional flow behaviors are realized, and the linkage and refinement level of regional safety monitoring are effectively improved.

The invention relates to the technical field of electric power marketing digitization, and discloses an electric power marketing digitization grid management platform based on a virtual number technology, and the platform comprises the steps: generating a coverage potential field through entropy index analysis, automatically segmenting a line according to a trace gradient, and forming a corresponding relation between a slice and a responsibility subject; a virtual number pool is configured and the service life is bound in combination with historical call data, so that number source dynamic allocation and synchronous effectiveness are realized; and calling routing is completed through space coordinate mapping. According to the platform, the problems of communication mismatching and service cross-lattice in the mountainous area are effectively solved, and the refinement and intelligence level of marketing management is improved.

The application belongs to the technical field of city planning, and provides a city planning application method based on grid management, which comprises the following steps: obtaining current city management data, dividing a target management area into multiple basic management grids; presetting a reserved virtual sub-grid that can be dynamically enabled for each basic management grid through modular design, wherein the reserved virtual sub-grid is in an inactivated state in an initial state and has self-configuration and adjustment capabilities; continuously monitoring dynamic operation data of each basic management grid, analyzing a current data mode by using a decision tree model, and generating a grid adjustment trigger signal. Through dynamic monitoring and the design of the elastic reserved virtual sub-grid, the division and management of the grid are more flexible, the city changes can be responded in a timely manner, and the management efficiency and adaptability are improved.

1. The name of the design product: grid marketing operation management graphical user interface for electronic equipment. 2. The use of the design product: for an electronic device. 3. The design points of the design product: in the graphical user interface content. 4. The picture or photo that best indicates the design points: front view. 5. The rear view is the conventional design, and the rear view is omitted; the left view is the conventional design, and the left view is omitted; the right view is the conventional design, and the right view is omitted; the top view is the conventional design, and the top view is omitted; the bottom view is the conventional design, and the bottom view is omitted. 6. The use of the graphical user interface: the graphical interface of the design product is used for the graphical user interface of grid management, wherein the "add grid" button in the upper right corner of the front view is clicked to enter the interface change state diagram 1; the mouse is moved to the map anchor icon in the interface change state diagram 1, and the related anchor information content is displayed in a floating window to enter the interface change state diagram 2; after entering the information in the interface change state diagram 2, any area on the map is clicked to draw a region box to enter the interface change state diagram 3.

The invention belongs to the technical field of city planning, and provides a grid management-based city planning application method, which comprises the following steps of: acquiring current city management data, and dividing a target management area into a plurality of basic management grids; a reserved virtual sub-grid capable of being dynamically started is preset for each basic management grid through modular design, and the reserved virtual sub-grid is in an inactive state in an initial state and has self-configuration and adjustment capacity; and continuously monitoring dynamic operation data of each basic management grid, analyzing a current data mode by adopting a decision tree model, and generating a grid adjustment trigger signal. Through the design of dynamic monitoring and elastic reservation of the virtual sub-grids, grid division and management are more flexible, city changes can be responded in time, and the management efficiency and the adaptive capacity are improved.

The application provides a user-side micro-grid load regulation method, system and equipment based on artificial intelligence, and relates to the technical field of micro-grid management.The method comprises the following steps: analyzing multi-dimensional heterogeneous data to obtain load time series data, and determining the demand weight of each user according to power demand data through an analytic hierarchy process; processing the load time series data through empirical mode decomposition to obtain intrinsic mode function components; dynamically predicting the intrinsic mode function components, and obtaining a multi-modal load prediction result by weighting and fusing the prediction results through an attention mechanism; optimizing the multi-modal load prediction result in combination with the operation target of a micro-grid cluster to generate a basic load regulation strategy of the micro-grid cluster; and generating a final regulation strategy corresponding to each user in combination with the demand weight corresponding to the user according to the basic load regulation strategy, and regulating the final regulation strategy. The application significantly improves the regulation accuracy of the user-side micro-grid load.

The invention discloses a method and a system for grid management of energy consumption of an industrial control link of a multi-agent system. The method comprises the following steps: extracting multi-agent system data, and based on agent feature classification, generating a training matrix by adopting a Pareto optimal solution algorithm; calculating a grid segmentation index of the industrial control link to carry out adaptive grid segmentation; a Minimax-Q algorithm is adopted to obtain an optimal matrix training result set; and acquiring memory and CPU resource data of each sub-link through a PLC program, comparing the memory and CPU resource data with the optimal set, if a condition is met, mapping the data as a Socket service request and sending a control signal to execute optimization, otherwise, continuously monitoring and recording. The system comprises a data aggregation and training matrix generation module, an intelligent industrial control grid segmentation module, a reinforcement learning optimization module and an energy consumption monitoring execution module. The method can achieve the optimal energy consumption of the system, optimizes the resource distribution through the self-adaptive grid segmentation, and improves the quality of decision data.

A system and method for dynamic energy grid management with centralized intelligence and distributed edge execution is disclosed. An energy grid optimization computer continuously receives operational data from edge units distributed throughout an energy distribution network. The computer monitors the data to detect trigger events such as renewable generation fluctuations or predicted grid congestion, performs system-wide analysis to identify affected edge units, calculates updated parameters accounting for variable fault current contributions from renewable sources, generates lightweight configuration packages, and deploys them to edge units through secure communication networks. Edge units receive configurations, perform validation, execute atomic rolling updates without interrupting operations, continuously sample measurements, autonomously execute protection and control algorithms, coordinate actions using GPS / PTP synchronized timing, and stream filtered operational data back to the central platform. The continuous configuration update methodology enables dynamic adaptation to variable renewable generation and changing grid conditions while maintaining millisecond-level autonomous protection response.

Computer device for grid management with integrated real-time analytics interface

The invention discloses a micro-grid demand side management method and system based on group enhancement strategy optimization, and belongs to the technical field of micro-grid management, and the method comprises the steps: building an environment model based on the charge state of a battery energy storage system, and enabling a state space to be composed of real-time system state data; constructing a self-adaptive reward function including economic rewards and security punishment; training an intelligent agent in the environment model by using a reinforcement learning algorithm based on group enhancement, and obtaining an optimal energy storage scheduling strategy network model based on an adaptive reward function; and the intelligent agent takes real-time system state data of the environment model as input and outputs optimal energy storage charging and discharging actions at the moment, so that intelligent management of a micro-grid demand side is realized. On the premise of not depending on prediction, real-time, self-adaptive and high-precision optimization control over the energy storage system is achieved, and the operation stability, safety and control intelligence level of the system facing renewable energy fluctuation and load change are improved.

The application discloses an engineering construction emergency call grid command management system, and relates to the technical field of data management, comprising: mapping the physical space and organizational responsibility relationship of the engineering project into a digital grid management structure; integrating various risk perception devices to construct a digital twin model; real-time analysis of original stress wave signals to identify potential risk events and perform forward-looking dynamic deduction to predict the chain influence area of the risk; spatial superposition analysis of the chain influence area and the grid management structure to determine the affected target grid, generate predictive emergency instructions, initiate targeted pre-call to the responsibility terminal of the affected target grid, and receive execution feedback information. The application solves the technical problems that the existing technology is difficult to identify the stress mutation inside the key temporary structure and the possible chain risk caused thereby in the engineering construction, and lacks forward-looking and precision in emergency response, and achieves the technical effects of predicting the risk influence range in advance and realizing predictive and targeted emergency response.

The invention relates to the technical field of micro-grid operation management, and discloses a data-driven micro-grid management optimization scheduling method, system, device and medium, and the method comprises the steps: collecting the predicted power and actual power data of renewable energy in a micro-grid system in real time; based on historical data, a denoising probability diffusion model is adopted to learn probability distribution of prediction errors, and a plurality of uncertainty scenes are generated; quantifying the risk cost in the scheduling process in the optimization model by using a conditional value-at-risk method; and constructing an optimal scheduling model aiming at minimizing economic cost and risk cost, and solving an optimal scheduling decision. According to the method, the wind and light uncertainty is accurately described in a data driving mode, balance optimization of economy and operation risks is achieved, and the reliability and economy of micro-grid dispatching are effectively improved.

The application discloses a traffic construction engineering safety production grid management system and relates to the related field of traffic management, which comprises the following steps: a collection module collects multi-dimensional parameters of a construction site and constructs a collection data set; a division module establishes an initial grid unit, performs boundary self-adaptive updating, and establishes a grid division result; an establishment module configures safety management equipment, performs real-time monitoring inside the grid, and establishes a grid monitoring data set; an identification module performs risk identification inside the grid and establishes a grid-level risk index; and an early warning module configures grid correlation, performs risk sharing of the grid-level risk index, utilizes the risk sharing result to perform risk global reconstruction of the grid division result, and performs early warning management. The application solves the technical problems of the existing safety production management, such as incomplete monitoring coverage, lack of flexibility in regional management, and weak cross-regional risk prediction capability, and achieves the technical effects of global monitoring coverage, dynamic regional management, and accurate cross-regional risk prediction.

The invention relates to the technical field of grassroots statistical work and enterprise regulation-lifting and unified management, in particular to an enterprise regulation-lifting and unified dynamic monitoring system based on grid management and department collaboration. Comprising a grid management module, a tax data comparison module, an enterprise monitoring and cultivation module, an efficient regulation-lifting integration module and a leader decision reference module. A grid management mode and a department division cooperation mode are fused, a modern information technology is fully utilized, and multi-source data are gathered for comparison and analysis. The grid management module is used for establishing an enterprise basic information database; the tax data comparison module forms a standard enterprise database and a seed enterprise database; the enterprise monitoring cultivation module is used for a department to carry out dynamic monitoring cultivation; the high-efficiency regulation-lifting and integration module is used for automatically discriminating the enterprises reaching the regulations and realizing high-efficiency regulation-lifting and integration; and the leader decision reference module provides a visual interface for decision reference.

The invention relates to the technical field of campus digital health management, in particular to an intelligent health campus management system and method based on gridding management, and the system comprises a gridding space and personnel organization mapping module which is used for carrying out the gridding of a campus physical space, so as to obtain a multi-level management grid, mapping is carried out according to an administrative organization so as to generate a campus space digital management platform; the multi-source heterogeneous health data acquisition and fusion module is used for acquiring multi-source heterogeneous data in the platform so as to construct a personal health electronic file; the health risk assessment and hospital guide module is used for predicting a health risk prediction result and personalized triage suggestions of each individual according to the personal health electronic archives; and the service touch and intervention module is used for pushing health knowledge or activities and sending personalized triage suggestions to a grid responsible person or a corresponding professional institution. Therefore, the problems of data islands, service passivity and fragmentation and the like in existing college health management are solved.

The invention discloses a heterogeneous transplantation and parallel optimization method for multiphase flow numerical simulation software, and belongs to the technical field of heterogeneous parallel calculation of computational fluid mechanics. According to the method, cross-language adaptation is realized by establishing a cross-language calling interface, unifying an array storage access mode, adapting a function interface format and reconstructing a core calculation function module; computing deployment is completed through efficient management of a storage space of a device end, directional copying and synchronization of data, optimization and definition of a kernel function, thread scheduling optimization, result return and parallel communication. In combination with a grid management scheme of double-layer boundary expansion, grid data interaction efficiency is optimized; efficient parallel scheduling and expansibility optimization are realized by dividing computational domains, allocating processes, cooperatively dividing tasks and formulating a weak expansibility optimization strategy. Software seamless transplantation and efficient interoperation can be achieved, the single-step iteration throughput rate and the speed-up ratio are improved, the communication transmission bottleneck is relieved, and good expansibility and engineering practicability are achieved.

The invention discloses a data-driven home-based care collaborative nursing scheduling method, and particularly relates to the technical field of home-based care collaborative nursing. The method comprises the following steps of: 1, constructing an associated grid database based on a dynamic data fusion and real-time updating mechanism of grid management and multi-source data acquisition and preprocessing; 2, utilizing historical data and real-time information in the associated grid database, combining a deep learning model and an XGBoost algorithm, and performing accurate pre-judgment on material demands and service demands possibly generated by the old; and step 3, dividing the community into a plurality of dynamic neighborhood cooperation units by adopting a DBSCAN density clustering algorithm and comprehensively considering factors of geographic distance and service demand complementarity. According to the home-based care collaborative nursing scheduling method, more accurate and efficient care service can be provided for old people through integration and deep analysis of multi-dimensional data, so that comprehensive upgrading of community and city care service systems is promoted.

The application relates to the technical field of containerization, in particular to a distributed computing method and system based on a service grid, which comprises the following steps: a grid management center is used as a central controller of the whole service grid, and is used for managing and controlling the functions of the service network; a grid agent is used for taking over the request and response of services, and realizes the routing and flow control of the request; the distributed computing method and system based on the service grid have the beneficial effects that through automatic service registration and discovery, the grid management center can monitor the creation and deletion of service instances in real time, and automatically distributes the latest service instance information to the grid agent, and the whole process is transparent and non-perceptual to the service instances.

The invention provides a user side micro-grid load regulation and control method, system and device based on artificial intelligence, and relates to the technical field of micro-grid management, and the method comprises the steps: carrying out the analysis according to multi-dimensional heterogeneous data, obtaining load time sequence data, and determining the demand weight of each user according to the power demand data through an analytic hierarchy process; processing the load time sequence data through empirical mode decomposition to obtain an intrinsic mode function component; carrying out dynamic prediction according to the intrinsic mode function component, and carrying out weighted fusion on a prediction result through an attention mechanism to obtain a multi-mode load prediction result; according to the multi-modal load prediction result, optimization is carried out in combination with an operation target of the micro-grid cluster, and a basic load regulation and control strategy of the micro-grid cluster is generated; and according to the basic load regulation and control strategy, in combination with the demand weights corresponding to the users, generating a final regulation and control strategy corresponding to each user, and carrying out regulation and control. According to the invention, the regulation and control precision of the user-side micro-grid load is obviously improved.

The invention discloses a park micro-grid regulation and control system and method based on a fusion terminal. The system comprises a micro-grid management and control system and the fusion terminal. The method comprises the steps that a fusion terminal collects and preprocesses multi-source data; the micro-grid management and control system receives the real-time operation state data uploaded by the fusion terminal, constructs a multi-target optimization model for optimization, and constructs a full-dimensional constraint condition; the micro-grid management and control system executes multi-target optimization scheduling to generate a regulation and control strategy; and the fusion terminal issues and executes the regulation and control instruction, and carries out closed-loop feedback adjustment at the same time. Multi-protocol data fusion is realized through the fusion terminal, a'source network load storage and charging 'island is broken, and global + real-time regulation and control are realized through cloud-edge collaboration; through multi-objective optimization scheduling, the operation cost is effectively reduced, the network loss is reduced, the new energy consumption rate is improved, the capability of coping with distributed energy fluctuation of the micro-grid is enhanced, and the operation reliability of the system is improved.

The application discloses a micro-grid demand side management method and system based on group enhancement strategy optimization, belongs to the technical field of micro-grid management, and comprises the following steps: constructing an environment model based on the state of charge of a battery energy storage system, and the state space is composed of real-time system state data; constructing an adaptive reward function including economic rewards and safety penalties; training an intelligent agent in the environment model by using a group enhancement-based reinforcement learning algorithm, obtaining an optimal energy storage scheduling strategy network model based on the adaptive reward function; and inputting the real-time system state data of the environment model into the intelligent agent, outputting optimal energy storage charging and discharging actions at a time, and realizing intelligent management of the micro-grid demand side. The application realizes real-time, adaptive and high-precision optimal control of the energy storage system without relying on prediction, and improves the operation stability, safety and control intelligent level of the system in the face of renewable energy fluctuation and load change.

The invention discloses a hydrogen refueling station integrity data management method and system, and belongs to the technical field of hydrogen energy infrastructure safety management, and the method comprises the following steps: (1) constructing a three-level grid system; (2) defining grid attributes; (3) implementing integrity data gridding integration; (4) establishing a cross-grid collaborative management mechanism; and (5) optimizing resource collaborative scheduling based on the grid data. The system comprises a hardware architecture and a software system. The hardware architecture comprises a sensing layer deployed in each grid, a cross-grid transmission layer and a distributed storage layer; the software system comprises a grid management module, a data integration module, a collaborative analysis module, a visualization module and a decision support module. According to the method, association integration of multi-source data is realized through space grid division, a cross-professional cooperation mechanism is established, the data utilization efficiency and the integrity management and control level are improved, and the problems of fragmentation, poor collaboration and weak space association of existing hydrogen refueling station integrity data management are solved.