41 results about "System topology" patented technology

The application discloses a kind of wind farm power collection system topology design method and system based on improved genetic algorithm, it is related to system topology design technical field, to solve the core problem of wind turbine grouping and submarine cable connection collaborative optimization under high-dimensional constraint, accurate matching of load flow and cost.The method determines the maximum number of wind turbines and the number range of feeder by parameter calculation module simultaneous equations, grouping connection module constructs initial scheme by polar grouping combined with minimum spanning tree algorithm, cost modeling module calculates cost by exclusive function, iteration optimization module dynamically adjusts grouping and the number of wind turbines based on improved genetic algorithm, constraint screening module excludes illegal scheme by penalty formula, and finally generates optimal and suboptimal topology graph containing core parameters.The application divides high-dimensional optimization problem into layers, considers constraint satisfaction degree and economy, significantly reduces submarine cable investment cost, improves design efficiency and engineering feasibility, and is suitable for various offshore wind farm power collection system topology design.

This invention discloses a planning method and system for a hydrogen-containing integrated energy system. The method includes: constructing equipment instance models of various energy types in the system by configuring parameters; wherein the equipment includes electrolyzer equipment; constructing a load model in the system by configuring the load demand of the area to be planned, the load demand supporting configuration at multiple time scales; obtaining the energy price model of the area to be planned and completing the energy price configuration; constructing a system topology by graphically associating the equipment instance models, load models, and energy price models through a visual configuration interface, and configuring constraint rules on the system topology; wherein the constraint rules include start-up and shutdown optimization constraints for the electrolyzer; transforming the system topology with configured constraint rules into a mixed-integer linear programming model and performing optimization to obtain the configuration scheme and operation strategy of each device in the system. This invention solves the problems of insufficient characterization of equipment operating losses and low modeling efficiency in existing planning methods by introducing refined electrolyzer start-up and shutdown constraints and a visual modeling process, thus achieving efficient and accurate planning for hydrogen-containing integrated energy systems.

The application discloses a kind of management systems and implementation methods of full life cycle operation and maintenance, it is related to full life cycle technical field.Constructs full cycle initial dynamic operation and maintenance hypergraph;Generation represents the dynamic hypergraph time sequence evolution sequence of system topology evolution along with life cycle;Generation full cycle space-time fusion operation and maintenance representation;Output the multidimensional abnormal risk prediction distribution atlas of the future operation trend of representation system;Based on the full life cycle management library, the corresponding resource degradation, isolation or expansion strategy is matched, and the adaptive operation and maintenance scheduling execution instruction set for directly intervening target system is generated.The application makes that when processing the full cycle long sequence data of mass node scale, the time axis resolution of operation and maintenance characteristics is significantly improved, especially in the correlation tracing of long-range latent fault.

This application provides a method, apparatus, medium, and equipment for locating cable defects based on a terminal grounding wire. The method includes: injecting a broadband pulse current signal with a predetermined repetition frequency into the cable grounding wire at the terminal connection of an in-service cable; acquiring the current signal from the cable grounding wire; and analyzing and diagnosing the current signal in the time or frequency domain to locate potential defects in the in-service cable. This application can solve the problems of needing to disconnect the cable system topology, exposing cable cores, and poor on-site anti-interference capabilities when diagnosing faults.

This invention belongs to the technical field of process control and automation, and relates to an intelligent switching system for multi-stage reaction process parameters in a reactor. The system includes: a transient physical sequence generation module to acquire signal-generated variable sequences; a Jacobian tensor array construction module to construct a dynamic heat flux Jacobian tensor array reflecting temporal coupling strength; a system topological singularity identification module to analyze the array and generate eigenvalue reduction mutation flags; a hardware wake-up vector generation module to generate a hardware-level execution clock trigger vector for the wake-up controller in response to the flags; a transient residual data extraction module to extract transient heat flux residual data fragments via a direct memory access mechanism; and a control state overwrite activation module to overwrite the controller state using the fragments and output a disturbance-free control command for the target stage. This invention solves the problem of difficulty in accurately capturing physical phase transition singularities and the initial state of the synchronous controller during multi-stage operation, leading to control disturbances during switching.

The present application relates to the technical field of power system grid loss allocation, in particular to a grid loss allocation method and system based on arbitrary segmentation, comprising the following steps: S1, system topology graph power and loss calculation; S2, system topology graph segmentation and tie line loss calculation; S3, total allocation loss calculation; S4, first loss allocation amount calculation; S5, secondary allocation amount calculation; S6, total loss allocation amount calculation: according to the loss allocation amount of each generator in each segmented area obtained in step S4 and the secondary allocation amount of each generator to tie line loss obtained in step S5, the total loss allocation amount of all generators is obtained. The present application segments the system topology graph based on the principle of Gaussian surface minimization, so that the segmentation method is more scientific and reasonable, which is conducive to subsequent loss calculation and allocation, and improves the calculation efficiency and accuracy.

The application discloses a wireless power transmission system topology optimization method and related device, comprising: selecting a main characteristic mode from the plurality of orthogonal characteristic modes; establishing a material field description model based on series expansion, reconstructing the material distribution of the physical space as a linear combination of the dominant characteristic modes, and taking the weighting coefficients corresponding to each dominant characteristic mode as optimization variables; constructing a multi-objective function; solving the multi-objective function, iteratively solving the weighting coefficients, determining the final material properties of each finite element unit according to the material field function value after optimization convergence through a binary mapping rule, and generating a continuous and smooth magnetic core topology structure according to the final material properties of each finite element unit. The method and related device can optimize the topology of the wireless power transmission system, and can solve the problems of low calculation efficiency, discontinuous results and difficulty in manufacturing.

This application discloses a method, apparatus, and device for constructing a hierarchical domain ontology and knowledge graph. The method includes: acquiring multi-source input data and performing document segmentation processing on the multi-source input data to obtain parsable document fragments. The multi-source input data includes at least one of device service relationships, operating procedures, and system topology. Based on AI, metadata is extracted from the document fragments to construct a metadata hierarchy tree corresponding to multiple semantic levels. Through a semantic alignment engine and adapter module, the introduced open-source external ontology is semantically mapped and aligned with the multiple semantic levels. The aligned metadata and external ontology knowledge are organized, classified and layered according to six semantic levels to form a structured hierarchy tree, and a hierarchical domain ontology and corresponding RDF knowledge graph are generated based on the structured hierarchy tree to improve the support of the knowledge graph for complex mechanism modeling and reasoning, as well as its usability and maintainability.

This invention discloses a power flow optimization control method for a power system with multiple DC shared grounding electrodes, belonging to the field of power system stability and control. The method includes the following steps: S1: Establishing the AC / DC hybrid system topology, constructing an AC / DC equivalent model with shared grounding electrodes, and completing component parameter calculations and per-unit value reduction; S2: Establishing a power flow optimization model under normal operating conditions, setting objective functions, AC / DC power flow equality constraints, inequality constraints, and upper and lower limit constraints for variables; S3: Under unipolar operating conditions, establishing a power flow optimization model with minimum load shedding as the objective, adding grounding electrode current constraints to the original normal operating constraints; S4: Solving the AC / DC hybrid system power flow model with multiple DC shared grounding electrodes based on the actual operating conditions of the system, outputting the optimal operating scheme and control settings for the system under normal or unipolar operating conditions, including generator output, DC control variable setpoints, and DC power distribution. This method can achieve coordinated operation and reasonable distribution of grounding electrode current among multiple DC transmission lines in an AC / DC hybrid system, improving the safety and stability of the AC / DC hybrid system under different operating conditions.

This invention discloses a topology design method for offshore wind farm collection systems based on reinforcement learning, belonging to the field of new energy and power system engineering. This method combines an objective function with various constraints to establish a bilateral ring topology planning model for the offshore wind power collection system. Simultaneously, it constructs an evaluation-improvement iterative framework based on policy gradient reinforcement learning. Furthermore, through policy network evaluation, dynamic parameter updates, and operator orchestration, reward signals guide the model's learning of the mapping between the learning state and the optimal operator. A threshold-triggered global perturbation exploration mechanism is introduced to effectively escape local optima while keeping costs relatively constant. Iterative optimization of the topology is achieved through the evaluation-improvement iterative framework. This method is adaptable to wind farms of different turbine sizes, offering superior optimization performance, solution efficiency, and robustness, providing an economical and reliable topology design solution for offshore wind farm collection systems.

The application provides a multi-modal fusion fault self-diagnosis method for a wind-solar-storage multi-energy complementary system, comprising: collecting operation data of wind power equipment, photovoltaic components and energy storage equipment as observation data for a fault system, and performing alignment processing on each observation data in the time domain, the space domain and the physical domain after unifying the time standard and the space structure; using a fixed-length sliding window to sample the aligned multi-modal observation data to obtain multi-modal fusion data; extracting local features of each modal data and interaction features between each modal, and then fusing them into an operation state expression vector of the system; constructing a fault propagation chain based on a system topology model, finding an abnormal node through a root cause inference method, and identifying a fault equipment by establishing a mapping relationship between the operation state expression vector of the system and the fault propagation chain. The method significantly improves the perception level of early weak faults, and expands the fault diagnosis range from a single point anomaly to the system structure level.

The application provides a high spatial resolution distribution map construction method and device of an electric carbon factor, relates to the field of new energy power generation dynamic monitoring, and comprises the following steps: analyzing the influence of wind and light injection power on the total carbon flow rate of a system according to a system topology structure and system operation parameters, obtaining a branch power flow injection matrix and a unit injection distribution matrix; determining system node carbon potential according to the branch power flow injection matrix, the unit injection distribution matrix and pre-calculated thermal power generation carbon emission intensity; and inserting the system node carbon potential into a layer after substation position fuzzy processing to obtain a high spatial resolution distribution map of the electric carbon factor. The application can calculate the hourly resolution carbon emission intensity of a source side thermal power unit by using the material balance method, obtain the power carbon emission factor of substations at different voltage levels in combination with power flow tracking based on the target regional network structure, further combine the coverage range of substations at different voltage levels, and draw a distribution map of the electric carbon factor by using a spatial allocation technology.

The application discloses a wireless power transmission system topology and a parameter design method thereof. The topology comprises an inverter circuit, a primary side compensation network, a primary side induction coil, a secondary side compensation network and a rectifier circuit. The resonant inductance in the primary side compensation network is connected in series with a first capacitive element to form a first resonant branch, and is connected in parallel with a second capacitive element and a second resonant branch comprising the primary side induction coil through a parallel node. The harmonic impedance characteristics are reconfigured, and the attenuation degree of high-order harmonics is adjustable through the capacitance ratio. The parameters satisfy the zero phase angle condition to realize constant voltage output, and satisfy the soft switching condition to cooperatively optimize harmonic suppression and zero voltage switching. The application actively suppresses high-order harmonics while maintaining constant frequency and constant voltage output, reduces light load loss, realizes full range soft switching, and is suitable for wireless charging scenes such as electric vehicles and industrial automatic guided vehicles.

This invention discloses a method for generating energy storage configuration principles based on LLM and time-series production simulation, belonging to the field of power system planning. This method uses a closed-loop "simulation-analysis-iteration" process to extract interpretable and reusable configuration principles from massive scenarios and configuration schemes. An AI agent globally schedules these principles: based on system topology and operating scenarios, it automatically invokes year-round time-series production simulations to simulate different combinations of energy storage capacity, power, placement location, and control strategies, obtaining key operating indicators. The simulation results are input into the LLM to obtain the optimal energy storage configuration principles, which are then verified and corrected by the AI ​​agent based on effectiveness indicators, thus outputting the final energy storage configuration principles. Furthermore, the year-round simulation employs time-dimensional decomposition, breaking down the overall model into multiple sub-optimization problems, alleviating the difficulty of solving problems caused by excessively large integer variables, and improving computational efficiency and engineering usability.

The present application relates to the technical field of intelligent power distribution equipment and power distribution automation, and particularly relates to an automatic topology identification method of a modular power distribution box; the process comprises: collecting connection behaviors of module interface insertion, mechanical locking and main circuit conduction state to form a connection behavior sequence; generating a structure-derived connection behavior sequence based on the power supply path of the module in the box and the correlation module relationship; checking the time sequence correspondence relationship and state closure relationship between the interface level and the structure-derived level sequence through cross-level consistency rules to form a topology relationship determination result; performing local topology update according to the determination result to update the topology structure mapping of the modular power distribution box; the present application overcomes the recognition dead zone and electromagnetic coupling interference caused by low impedance and high collinear branch, can accurately determine the real physical connection relationship between the modules, supports plug-and-play of the modules and dynamic adjustment of the local topology, and improves the system topology identification precision and operation and maintenance management efficiency.

The application provides a power spot market supply and demand prediction method and system fusing multi-source features and dynamic correction, and relates to the technical field of power market supply and demand prediction. Multi-source heterogeneous power data including demand side data and power supply side data are acquired and preprocessed; the preprocessed multi-source heterogeneous power data are input into a space-time feature extraction model, space-time correlation features of power supply and demand are extracted based on system topological structure and time series; a supply and demand coupling correlation model is used to perform coupling analysis on the space-time correlation features, quantize interactive influence of the power supply side and the demand side, and output supply and demand collaborative prediction results; a dynamic correction prediction strategy based on a rolling time domain is used to perform real-time rolling correction on the supply and demand collaborative prediction results, and finally obtain the supply and demand prediction results. More reliable and timely decision support is provided for power spot market transactions, which helps to improve market operation efficiency and system safety and stability.

This invention relates to a real-time simulation method and system for large-scale cascaded H-bridge applications with full-detail modeling. The method involves equivalently partitioning the topology of the large-scale cascaded H-bridge system into several equivalent circuits, replacing the partitioned cascaded H-bridge topology with controlled voltage sources, and measuring the current of the controlled voltage sources as feedback. The entire main grid circuit is replaced by a controlled current source, and its voltage is measured as feedback. Circuit breakers are added to the main circuit topology, and bypass switches are added to the cascaded H-bridge topology. A logic control program is designed to control the on / off state of each switch. The partitioned equivalent circuits run in the FPGAs of each simulator, and the logic control program runs in the CPU of the simulator. The simulators interact with each other via fiber optic communication. Compared with existing technologies, this invention can achieve accurate simulation of various operating conditions of large-scale cascaded H-bridge systems and realize hardware-in-the-loop testing of controllers with full physical I / O interaction for large-scale cascaded H-bridge applications with full-detail modeling.

This invention provides a three-stage optimization genetic algorithm-based method and system for topology optimization of photovoltaic power plant collection systems, relating to the fields of photovoltaic systems and smart grids. The method includes: acquiring basic data of the photovoltaic power plant collection system, which includes a step-up substation and multiple box-type transformers; initializing a population based on the basic data of the photovoltaic power plant collection system using a hybrid initialization strategy; repeatedly executing genetic operations, a dual repair mechanism, and dynamic penalty evaluation to update the population until preset conditions are met; and determining the optimal topology network from the current population. This method has the advantage of improving the efficiency and quality of topology optimization for photovoltaic power plant collection systems.

This invention discloses an alarm convergence method, apparatus, device, and medium based on heuristic rules and a large language model. The method includes: acquiring alarm data streams from a distributed cloud system; dividing the alarm data streams based on a preset time window to construct a target alarm pair set; calculating a first relevance score for each alarm pair in the target alarm pair set based on heuristic rules; classifying alarm pairs into high-confidence alarm pairs and low-confidence alarm pairs based on the first relevance score; inputting the low-confidence alarm pairs into a large language model; using the large language model to call operation and maintenance knowledge documents and system topology data to perform causal inference on the low-confidence alarm pairs to determine a second relevance score; generating a relevance matrix based on the first and second relevance scores; and aggregating the alarm data streams based on the relevance matrix to generate alarm clusters. This achieves the technical effect of improving the accuracy of alarm aggregation.

The application discloses a multi-modal disaster space-time graph construction method, system, device and storage medium, and relates to the technical field of intelligent water conservancy. The method comprises the following steps: a physical evolution disaster chain field ontology is constructed by relying on a basin water system topology; unstructured disaster text is subjected to zero-sample element extraction, absolute geographic coordinates and high-frequency time stamps are bound as space-time attribute, and micro-dynamic disaster point elements are generated; water body range vectors are extracted based on radar remote sensing images and are vectorized as macro-physical envelope surface elements; under a unified geographic information system, a space-time tolerance alignment mechanism of macro-surface constraint and micro-point interpolation is adopted, a spatial physical buffer tolerance is set, a cross-modal physical trust edge is established when the space-time constraint is met, and finally, a graph is constructed and cross-scale deduction is performed. The application solves the problems that the existing disaster graph is separated from the physical space mapping, the traditional extraction model is prone to chain breakage, and the multi-modal data space-time matching is difficult, and improves the knowledge extraction accuracy.

This application relates to the field of power system automation technology, providing a substation fault control system and method based on remote monitoring. The method generates multiple candidate isolation strategies by acquiring power data of each line in the substation system, load importance classification data, circuit breaker operation rule base, system topology connections, and fault diagnosis results. For each candidate strategy, the correlation characteristics between the total load and importance distribution in the fault area, the impact of circuit breaker operation complexity on the thoroughness of isolation, and the impact range of power supply islanding in non-fault areas after execution are analyzed. Based on the multi-dimensional evaluation results, the isolation effect of each strategy is analyzed through a multi-objective decision model, the optimal strategy is selected, and a circuit breaker control command sequence is generated for execution. This application achieves multi-objective comprehensive optimization and rapid remote execution of fault isolation strategies, significantly improving the intelligence level and processing efficiency of substation fault control.

The application discloses a kind of multi-terminal flexible DC transmission system fault current monitoring methods considering hybrid converter station active current limiting control.First, the equivalent model of DC line and the equivalent model of hybrid converter station in different response stages are established;Then, according to the topological structure of multi-terminal flexible DC transmission system, the spatial state equation set of the whole system is established;Solve the state space equation set, obtain the time domain response of fault current.The application realizes the accurate calculation of the fault current of multi-terminal flexible DC transmission system by fully considering the dynamic response characteristics of converter station active current limiting control, so as to realize the accurate monitoring of the fault current of multi-terminal flexible DC transmission system.

The application discloses a power system transmission section transmission power limit and fault analysis method. A system topology undirected graph capable of representing the topology structure of a power system is constructed, a transmission section parameter model of a standardized operation mode is established, and the sending end and the receiving end of the transmission section are determined. A power system transmission section sending end unit automatic search model based on a topology analysis method is further constructed, and fault cards for transient stability analysis of different elements and fault types are generated in batches. A transmission section transmission power analysis model is constructed based on GRPO, and a transmission section transient stability transmission limit calculation model is constructed by adopting a repeated power flow strategy to determine the transient stability transmission limit of the target transmission section. A transmission section fault identification model considering transient stability constraints is constructed to identify the key fault restricting the transmission capacity of the target transmission section.

This invention relates to the field of fault diagnosis technology for new energy vehicle charging facilities, and discloses a fault detection method and system for charging piles. The method includes: collecting operational and environmental data and performing cleaning and feature extraction; constructing a component topology graph based on data correlation; obtaining historical logs and extracting interaction feature vectors; calculating the dependency strength of adjacent nodes to identify risk transmission chains; matching and analyzing the risk chains with environmental features to obtain interference correlation paths; constructing a propagation model based on the interference paths and simulating cascading propagation to generate a fault propagation graph; tracing the path backward from the propagation graph and matching it with a fault mode library to determine and output fault root cause information. This invention achieves early and accurate localization of hidden and cascading faults in charging piles by constructing system topology and analyzing the coupling effect of dynamic interaction and environmental interference.

The application belongs to the technical field of processors, and particularly relates to a selection and subsystem design method, system and storage medium for SRAM. The selection and subsystem design method comprises the following steps: obtaining system specification information of a target processor storage system, analyzing the system specification information to generate a corresponding access model and a hard constraint set; screening SRAM macros that meet the hard constraint set from a preset storage compiler or PDK macro library, and then simulating and rescreening the screened SRAM macros through the access model, and standardizing macro-level features of the rescreened SRAM macros; matching SRAM macros from an SRAM macro candidate set based on bandwidth requirements and concurrent access requirements in the system specification information, and automatically generating multiple groups of SRAM subsystem topology candidates. Compared with the prior art, the application can realize rapid landing, stable signing and production reuse of the SRAM subsystem.

The present application relates to a kind of offshore new energy access direct current grid multimodal oscillation tracing method and system, belong to wind power generation system technical field, solve the problem of the low positioning accuracy of the existing new energy station through flexible transmission system oscillation source positioning error even positioning problem.The method comprises: the new energy is divided into several energy subsystems by control link and constructs system topology diagram through flexible transmission system;Wherein, the system topology diagram is weighted directed graph, node is each energy subsystem, dynamic energy interaction between each energy subsystem is directed edge, and the edge weight is based on the state variable of each energy subsystem, and the obtained interactive energy weight factor;Based on the interactive energy weight factor between each energy subsystem, the edge betweenness centrality value between each energy subsystem is obtained;Based on the edge betweenness centrality value between each energy subsystem, the system topology diagram is modularized and partitioned, and the energy subsystem of oscillation occurrence is obtained.The accurate positioning of oscillation source is realized.

The embodiment of the application provides a power transmission line engineering material table automatic generation method, which is applied to the technical field of electric power systems and power transmission engineering, and constructs a full-digital derivation engine: firstly, line path and obstacle constraints are obtained through GIS analysis; then, the arrangement of the tower is automatically determined based on an optimization algorithm; then, conductor mechanics simulation and component intelligent matching are carried out; finally, the system topological relationship is constructed, and an accurate engineering bill of materials is automatically generated. The method remolds the traditional discrete mode which depends on manual judgment and manual statistics into a continuous automatic process based on a unified data model and physical laws, ensures design consistency, statistical accuracy and full-process traceability, and significantly improves design efficiency, safety and economy.

The application relates to a kind of multi-modal data analysis methods and systems based on graph neural network, which include pre-processing and extracting features to log, index, call chain and deployment metadata;By constructing a time-series heterogeneous graph that integrates call and deployment relationships, the system topology evolution is dynamically represented;Then load the multi-modal features to the graph nodes, use the heterogeneous graph neural network to aggregate the spatial context, and model the time dependence through the time-series neural network, generate the node feature representation that integrates the space-time information;Finally, taking the index feature as the core, through the cross-modal attention mechanism, adaptively fuse the multi-source features, form the unified joint representation of the system, and accordingly realize the abnormal scoring or root cause sorting. The application effectively reduces the topology lag caused by static graph modeling, solves the problem of insufficient information utilization caused by simple fusion of multi-source data, and significantly improves the operation and maintenance analysis accuracy and robustness in complex dynamic environment.

The application discloses a high anti-interference intelligent servo system topology based on a winding and connecting unit, which comprises a servo driver, an optical fiber encoder and an intelligent control algorithm module connected to the input end of the servo driver, and a key execution component connected to the output end of the servo driver; the intelligent control algorithm module is used for adaptively calculating a time interval for data exchange between the servo driver and an upper controller, and is used for predicting and compensating a servo phase, and simultaneously generating an optimized control instruction after phase prediction and compensation, and the optimized control instruction is issued to the servo driver; the servo driver is used for outputting driving power to the key execution component in response to the optimized control instruction; and the high anti-interference intelligent servo system topology based on the winding and connecting unit can reduce the synchronous error and the failure rate of sudden acceleration and deceleration out-of-step of the winding and connecting unit servo system, improve the signal-to-noise ratio and the phase margin of the encoder, reduce the equipment failure downtime, improve the product qualification rate, and reduce the annual maintenance cost.