38 results about "Smart substation" patented technology

The application relates to the technical field of power system automation, and particularly discloses an intelligent substation automation management system. The system comprises a digital twin synchronous management module, a multi-engine collaborative deduction module, an online strategy optimization and simulation module, and an instruction safety checking and feedback module. The system builds a digital twin synchronized with a physical station as a unified analysis environment; multiple professional analysis engines interacting through a shared cognitive state library are run in the twin, interwoven evaluation and joint deduction of equipment state, protection logic and network reliability are realized; based on the deduction result, online simulation iteration is used to search for a multi-step optimization control plan in the twin environment; and after safety checking of the plan instruction, the instruction is executed, and feedback data is collected to drive the closed-loop evolution of the model and the strategy. The application realizes multi-source data fusion, dynamic collaboration of cross-professional analysis and adaptive optimization of control strategies, and improves the integrity and autonomy of intelligent substation management.

The application discloses an interactive adaptive generation method and device for a substation main wiring diagram, and belongs to the technical field of intelligent substations. The method comprises the following steps: loading a pre-constructed substation typical design framework template and a bus branch interval template; instantiating the substation typical design framework template and the bus branch interval template to generate a typical design template instance and a branch interval template instance; respectively performing graph module association on the typical design template instance and the branch interval template instance to generate the graph module associated typical design template instance and the graph module associated branch interval template instance; expanding a arrangeable interval according to the graph module associated typical design template instance and the number and form of the branch interval; and based on an interactive diagramming configuration mechanism, arranging the graph module associated branch interval template instance to the arrangeable interval to generate a substation main wiring diagram. The application can solve the problems of non-standard, low efficiency, easy-to-make errors in graph module association and difficult-to-control diagramming effect in automatic diagramming.

The application relates to the technical field of power system automation, and discloses a smart substation electrical equipment state monitoring and diagnosing system and method, which comprises a four-layer cooperative architecture of a process perception layer, a bay control layer, a station control and cloud platform layer and an execution interaction layer. The process perception layer collects multi-dimensional equipment state data through standardized monitoring IEDs; an edge intelligent diagnosis unit of the bay control layer runs improved D-S evidence theory and LSTM algorithm to perform local fusion diagnosis and trend prediction, realizes rapid diagnosis within 50 ms and linkage control based on GOOSE; the station control and cloud platform layer realizes plug-and-play and panoramic monitoring of equipment based on SCD files; the cloud platform performs deep analysis and model training, and improves the diagnosis capability through cloud-edge cooperative iteration; the application solves the problems of protocol heterogeneity, data island, diagnosis lag and poor linkage of the traditional monitoring system, and realizes standardized, real-time and intelligent monitoring and active early warning of the equipment state.

The application provides a remote intelligent operation monitoring method and system of a smart substation, relates to the technical field of intelligent operation and maintenance of a substation, and relates to multi-source heterogeneous sensing, deep feature modeling, fault prediction evaluation and model self-optimization.The application collects electrical, environmental and meteorological data through heterogeneous sensors, constructs a structured original data set, carries out time series prediction in combination with a convolution-LSTM model, and outputs a fault probability and a confidence interval by using a Transformer fusion network, so that online early warning and response control are realized, and the application has the self-adaptive updating capacity driven by federated learning.

The application provides an intelligent substation anomaly detection method based on meta-learning technology, first, a multi-working condition task library is constructed for meta-training. Secondly, a double meta-knowledge learning framework is designed to learn task-level model initialization parameters suitable for rapid adaptation. Subsequently, online reconstruction error driven anomaly detection is deployed, and the adapted model is used to calculate data reconstruction error in real time, and combined with the adaptive threshold to accurately distinguish and alarm grading. Finally, the system supports a dynamic updating mechanism, which continuously collects verified samples and periodically triggers meta-updating. The application significantly reduces the data dependence and deployment cost in new scenarios, improves the model's generalization ability to multiple working conditions and sensitivity to rare anomalies through meta-knowledge sharing, and ensures the long-term effectiveness of the detection system through online learning mechanism, providing an efficient, adaptive and evolutionary security protection solution for intelligent substations.

The application relates to the technical field of smart grid communication, and discloses a smart substation path controllable network system and method based on IPv6 and white box switching. A centralized controller is used to gather link state information of each white box switch to construct a global topology view. Based on the view and a service demand vector, network service flow is optimized and evaluated to generate a path planning table. Then, the path planning table is translated and coded by a rule conversion module, and is sent to a programmable data plane of the switch through a southbound interface and is solidified into a hardware forwarding table. According to the path planning table, an access side switch matches a received original service packet, generates an IPv6 encapsulated packet with a path strategy expansion header, and finally performs destination address overwrite and hop-by-hop controllable forwarding along the path indicated by the expansion header to obtain a target service packet. In this way, the closed architecture of traditional underlying equipment is broken, and accurate control and high-reliability deterministic flexible transmission of the end-to-end path of massive service in a substation are realized.

The present application relates to the technical field of substation automation testing, and particularly relates to a substation automation testing method and system, the method comprising the following steps: constructing a digital test message for simulating a power grid operating state, the digital test message conforming to internal processing specifications of an intelligent terminal; non-invasively injecting the digital test message into an internal logic processing path of the intelligent terminal through a diagnostic interface reserved by the intelligent terminal or an internal communication network of the intelligent substation; using a time synchronization mechanism of the intelligent substation to synchronize the time of the digital test message; receiving response data returned by the intelligent terminal through the internal communication network of the intelligent substation; wherein a testing process is isolated from main function logic of the intelligent terminal, and the testing process comprises injection of the digital test message, time synchronization and acquisition of the response data. Through the above scheme, testing efficiency and reliability are improved.

The transformer fault early warning method based on multi-modal data fusion and dynamic weight relates to the technical field of transformer fault early warning, and solves the problems of single data, fixed weight, poor fusion generalization, and insufficient early warning adaptability and accuracy of traditional methods. The method first collects real-time operation, environment, and historical maintenance multi-modal heterogeneous data of the transformer and performs differential preprocessing accordingly; then constructs a multi-branch feature extraction architecture to extract fault-related features of the three types of data; then builds a dynamic weight distribution module based on an improved sparrow search algorithm to weight and fuse the features to obtain a multi-modal fusion matrix; finally, the matrix is input into an optimized extreme learning machine model to output the fault probability and specific type, and the weight is dynamically updated and the model is iterated when the working condition parameter changes exceed the threshold. The present application greatly improves the accuracy, reliability and adaptability of fault early warning, significantly reduces the false alarm and missed alarm rate, provides support for transformer operation and maintenance decision-making, and is suitable for intelligent substation equipment health management.

This invention relates to the field of relay protection technology for intelligent substations, and discloses a method, system, device, and medium for automatically constructing a relay protection business model and generating virtual circuits. The method includes: acquiring substation configuration files and primary system diagrams and performing data parsing to construct a unified data model; constructing a graph database model based on node type sets and edge relationship type sets to achieve node instantiation and relationship linking; automatically generating and completing virtual circuits using a two-stage strategy combining rule inference and intelligent graph neural network completion to obtain complete virtual circuit connection relationships; and visualizing the virtual circuit connection relationships, supporting hierarchical navigation and viewing based on voltage level, wiring method, and bay. This invention significantly reduces modeling time and error probability. The generated business model and its visualization provide a solid and reliable model foundation for subsequent protection logic verification, intelligent operation and maintenance, and digital twin applications.

This invention discloses a nano-silicon-based special transformer cooling oil and its preparation method. The cooling oil comprises the following components by mass percentage: 85%–90% modified silicone oil base oil, 2%–3% spherical nano-silicon particles, 1%–5% composite antioxidant, 0.5%–2% polyether-modified silicone oil dispersant and stabilizer, and the balance being functional additives. This invention constructs a three-dimensional thermally conductive network using surface-modified nano-silicon, synergistically combining composite antioxidants, low-temperature flow improvers, and anti-cavitation additives. This allows the cooling oil to maintain high insulation performance while achieving a thermal conductivity increase of ≥50%, good low-temperature fluidity at -80℃, partial discharge ≤5pC, cavitation inhibition rate ≥78%, overload capacity up to 200%, and service life extended to 40 years. This product is particularly suitable for extreme environments with altitudes ≥5000 meters and temperature differences ranging from -80℃ to +120℃, meeting the requirements of ultra-high voltage DC converter transformers and intelligent substations in cold regions for efficient heat dissipation and long-term stable operation.

This invention relates to the field of intelligent substation commissioning, and more particularly to an intelligent substation commissioning method based on the CMS protocol. The commissioning master station loads the system configuration description file, and through semantic pre-parsing, logical model parsing, and communication configuration parsing, generates the topology of all substation equipment. Subsequently, it collects equipment operating status data in real time, performs normalization processing, and constructs equipment operating status vectors. Based on these vectors, a dynamic state entropy flow collaborative algorithm is used to calculate the basic disturbance energy of a single device, and the coupling propagation strength between devices is introduced to generate a dynamic state entropy flow. This flow is compared with a set stability threshold range, and the CMS commissioning path and commissioning priority are adjusted in real time. This method solves the technical problems of low SCD configuration parsing efficiency, inability to uniformly model the communication and control relationships between devices, separation between operating status and protocol commissioning process, difficulty in identifying equipment anomaly propagation relationships, and the inability of fixed commissioning sequences to adapt to complex operating conditions.

This invention discloses a waveform recording method, apparatus, electronic device, and storage medium based on UDP multicast, to solve the problems of low communication efficiency, poor synchronization, and poor coordination in current smart substation waveform recording. Applied to a smart substation, the method involves multiple waveform acquisition units joined to a specified multicast address; acquiring the smart substation's SCD file and generating station-wide waveform recording mapping information accordingly; for any first waveform acquisition unit that initiates waveform recording, generating linked waveform recording information based on the station-wide waveform recording mapping information and sending it via multicast message; for each second waveform acquisition unit that receives the multicast message, if it is determined based on the multicast message that it meets the waveform recording initiation conditions, then initiating waveform recording and synchronously generating waveform recording files according to the multicast message; grouping all waveform recording files to obtain multiple waveform recording file groups; and performing waveform time stamp and boundary alignment on each waveform recording file group before merging the waveforms to obtain the station-wide waveform recording file.

The application discloses a power system station automation protocol conversion method and device based on docker virtualization, belongs to the technical field of power automation, adopts an isolated deployment mode of one device one container, creates an independent running container for each physical 103 protocol device, internally embeds a 103 protocol analysis, data mapping engine and a virtual 61850 IED Server, and builds a high-fidelity virtual 61850 IED Server digital twin body consistent with the real device; the data semantic recovery and intelligent bidirectional mapping are realized through the mapping engine, the whole life cycle management and standardized configuration of the virtual 61850 IED Server cluster are completed in combination with a centralized configuration and management platform and a container arrangement tool, the device-level and semantic protocol conversion is realized, the information islands of new and old devices are broken, the system reliability and operation and maintenance efficiency are improved, the technical life cycle of the stock device is prolonged, a smooth transition path is provided for the digitalization and twinning upgrade of the power system, and the full-scene construction demand of the intelligent substation is adapted.

The application discloses a prefabricated optical cable fiber connector mechanical performance enhancement system of a smart substation, relates to the technical field of optical communication of the smart substation, and comprises a data acquisition module, an environmental stress modeling module, a risk simulation module and a strategy fusion module. The system collects connector parameters and in-station environmental data, constructs a comprehensive stress model, analyzes vibration interference spectrum and natural frequency by using a modal matching device, generates a resonance avoidance strategy, analyzes periodic thermal stress and connector structure by using a thermodynamic simulator, generates a deformation compensation scheme, and finally fuses and outputs a composite enhancement strategy. The system can accurately predict and avoid the resonance risk of the connector and a specific electromagnetic vibration source, effectively compensate the cumulative deformation caused by the periodic thermal stress, and thus improve the long-term mechanical reliability and optical transmission stability of the connector in a complex in-station environment before deployment.

This invention relates to the field of power grid safety technology, and in particular to a modular intelligent substation monitoring risk assessment system. The system includes collecting substation environmental data, subdividing load arrays by unit load time, calculating data deviation values, and determining the steady-state and fluctuating states for each time period. This aligns with the dynamic characteristics of modular substation compartmentalized operation. Then, using historical environmental data from steady-state periods, combined with external and internal data and power load influence parameters, the system uses a function simulation model to perform multiple simulations to determine the internal steady-state function. Next, it compares the similarity between load and temperature change curves during fluctuating periods to obtain load correlation values. Finally, it combines the internal steady-state function, load correlation values, and real-time load to assess risk coefficients and generate abnormal states. This system effectively addresses the shortcomings of existing systems such as separate monitoring and coarse load analysis, accurately matches the compartmentalized operation characteristics of modular substations, and further improves the targeting of risk assessment.

The application discloses a kind of substation secondary system online monitoring devices, it is related to substation secondary system online monitoring technical field, and monitoring terminal protection mechanism includes installation shell, the top of the installation shell is provided with opening, and the front side of installation shell is provided with front through slot, and front through slot is step groove, and the position of the front side in installation shell is provided with mesh placing plate at the bottom of front through slot, and secondary system online monitoring terminal is placed on mesh placing plate, monitoring terminal fastening mechanism is installed in installation shell, and the top rear side of secondary system online monitoring terminal is matched with monitoring terminal fastening mechanism and is clamped;Cable inner end limiting mechanism is arranged in installation shell.The substation secondary system online monitoring device, secondary equipment is overall coordinated smoothly, beneficial to give full play to the technical advantage of intelligent substation, can realize the modularization of secondary equipment installation, and the line after wiring is easy to arrange, and secondary system online monitoring terminal can be quickly air supply heat dissipation.

This application provides a method and system for processing physical interaction data of power grid equipment. The method constructs flow description information for each periodic data stream based on the message transmission period and message length of each intelligent electronic device (IED) in the process layer. Based on the flow description information, worst-case arrival analysis is performed for each output port in the TSN. Based on the results of the worst-case arrival analysis, a gating schedule for each output port in the TSN is generated or adjusted. Based on the generated gating schedule, a transmission phase offset parameter is assigned to each IED. During the operation of the TSN network, delay measurement is performed on the periodic data streams to obtain delay statistics. Based on the delay statistics, the gating schedule is adaptively adjusted to maintain message transmission delay jitter within a preset upper threshold, thereby improving the determinism and reliability of critical periodic data stream transmission in the process layer of the intelligent substation.

This invention provides a backup and recovery system, method, electronic device, and storage medium for substation equipment software systems based on LVM snapshots. The backup and recovery system includes: an LVM partitioning component, which creates LVM partitions on the hard disk using the LVM thin pool format and formats the partitions into the required file system format; a snapshot management tool, used to back up the existing system state and recover corrupted files; and a bootloader and liveCD recovery tool, where the bootloader displays a list of snapshots on the LVM partitions, the liveCD is launched to execute the snapshot management tool, and the LVM partitions are recovered using snapshots selected in the snapshot management tool. This invention, based on LVM snapshots, enables backup and recovery of software systems for intelligent substation equipment without requiring additional backup equipment, achieving standalone system backup and recovery functionality; the backup speed is fast, and it has minimal impact on the production and operation of the substation equipment.

The application provides a kind of intelligent substation protection device soft pressure plate state inspection method, including monitoring system start remote control, judge whether the communication of the protection device to be operated is normal;Based on the normal communication of the protection device to be operated, judge whether the soft pressure plate of protection device is remotely controlled to be put into;Based on the soft pressure plate of protection device is remotely controlled to be put into, judge whether the management CPU return information is normal;Based on the management CPU return information is normal, judge whether the protection device operation record is correct;Based on the protection device operation record is correct, judge whether the protection CPU setting value printing is started;Based on the protection CPU setting value printing is started, judge whether the soft pressure plate information in printing setting value is consistent with monitoring system.The application realizes the proofreading of the remote control result of soft pressure plate by monitoring system, so as to avoid the problem that the pressure plate state displayed by monitoring system is inconsistent with the actual under the abnormal situation such as communication interruption between each CPU in protection equipment.

This invention discloses a multi-algorithm fusion identification method and system for substation inspection based on positive and negative sample collaboration, relating to the field of substation inspection technology. The method includes: acquiring historical images of equipment in multiple substation scenarios; constructing a positive and negative sample dual-database collaborative iterative pool; collecting substation inspection images; eliminating interference features in the collected substation inspection images using an adaptive collaborative anti-interference algorithm based on multi-scenario acquisition interference factors; performing initial screening of equipment status anomalies using a hierarchical parallel fusion identification algorithm based on the positive and negative sample dual-database collaborative iterative pool and the substation inspection images; outputting equipment defect assessment conclusions; dynamically calibrating the equipment defect assessment conclusions based on the substation's scenario environment characteristics; outputting equipment defect identification reports; and optimizing the positive and negative sample dual-database collaborative iterative pool based on equipment defect identification reports within a preset period. This invention can provide strong technical support for the safe operation and maintenance of smart substations, reduce manual operation and maintenance costs, and improve the reliability of power grid operation.

The present application relates to the technical field of electrical sensor, in particular to a distributed relay protection test method and system for smart substation, comprising: acquiring current signals, voltage signals of nodes, spatial distances between nodes, spatial distances between nodes and busbars; according to current signals and voltage signals of nodes at adjacent time, acquiring current mutation degree, voltage mutation degree and fault characteristics of each node at each time, so as to acquire influencing time and each suspected fault node; according to current mutation degree of suspected fault nodes at all influencing time, combining fault characteristics of each suspected fault node at each fault time, acquiring possibility of each suspected fault node to occur fault at each fault time, and combining spatial distances between nodes and busbars, giving priority to each node. The present application gives priority to each node by analyzing the node most likely to occur fault first, so as to improve fault response speed.

This invention relates to the field of optical cable thermal aging simulation and optimization technology, specifically a method for optimizing the optical transmission performance of prefabricated optical cables in smart substations under high-temperature aging. The method includes: establishing a simulation model based on material thermodynamics and geometry to simulate the distribution and evolution of the internal temperature field of the optical cable at high temperatures; calculating the micro-variation field of the thermally induced refractive index of the fiber core material based on the temperature field, and then analyzing the mode coupling and additional loss characteristics of the optical signal; based on this, deriving the inverse refractive index modulation distribution function used to compensate for performance degradation, and converting it into a scheme for adjusting the physical parameters of the prefabricated optical cable structure. This method, through a combination of simulation modeling and reverse design, achieves active compensation and optimization for the decline in optical transmission performance caused by thermal aging, improving the transmission stability and service life of prefabricated optical cables under long-term high-temperature environments.

The application provides a kind of intelligent distributed direct-current power supply control method and system based on neural network, it is related to neural network technical field, wherein, the method comprises: obtaining bus voltage, direct-current power module output current, battery pack state of charge, load power demand and cabinet key node temperature data in intelligent substation direct-current microgrid;Fusion the output current, state of charge and load data to generate power supply capability distribution map, while based on temperature data inversion hotspot distribution and calculate fault risk index;Based on power supply capability distribution map and risk index, through the strategy coordination and Q value interaction between power intelligent agent dynamically adjusts power distribution weight and generates dispatching instruction;Combined with bus voltage correction signal, power output and bus voltage are adjusted, and the intelligent stable control of intelligent substation direct-current microgrid is realized.The application improves the operation stability and power supply scheduling efficiency of intelligent substation direct-current microgrid under fluctuation condition.

This invention relates to the field of snow removal equipment technology, specifically a smart substation snow removal robot for power plants. It includes a main controller, an automatic path planning and scanning system, a hot air snow removal and retractable duct device, and an intelligent scheduling system. The main controller receives data, plans the snow removal path based on the substation layout diagram and a preset algorithm, controls the start and stop of the hot air generator, and determines whether to call the robot for snow removal based on the received data. The automatic path planning and scanning system includes lidar and vision sensors to collect environmental and snow accumulation area data. The hot air snow removal and retractable duct device includes a hot air generator and a retractable air outlet duct to achieve hot air snow removal. The intelligent scheduling system includes temperature and humidity sensors to provide data for snow removal decisions. This invention can automatically plan paths, accurately remove snow, ensure the safe operation of substations, improve snow removal efficiency, and reduce labor costs and safety risks.

The application discloses a network intrusion detection method, system and device based on multi-dimensional features and a storage medium, relates to the technical field of network security, and comprises the following steps: capturing MMS, GOOSE and SV protocol messages from an intelligent substation network and synchronously collecting device state data; preprocessing the collected data; counting time sequence features, analyzing protocol features and calculating behavior features from the device data; dynamically calculating the weights of the three types of features through an attention mechanism network, and performing weighted fusion; inputting the fused features into a multi-layer perception classifier, calculating the probabilities of belonging to various attacks, determining whether an intrusion occurs and the attack type according to a probability threshold; outputting a detection result with a time stamp and a confidence degree, generating an alarm and sending the alarm to a monitoring system, and recording feature weights for analysis and optimization. The application can identify hidden attack behaviors across industrial protocols in the intelligent substation by introducing a multi-dimensional feature dynamic fusion method based on an attention mechanism.

The application is suitable for the technical field of electrical equipment state monitoring, and provides a smart substation fault detection method and system, which comprises the following steps: collecting oil temperature, oil chromatographic data and electric parameter signals of a target electrical equipment in real time; based on a method of fusing physical mechanism and data driving, the oil chromatographic data is adaptively corrected according to the oil temperature to obtain corrected gas concentration data; a dynamic multi-dimensional fault feature set is constructed according to the corrected gas concentration data, the oil temperature and the electric parameter signals; based on a preset fault prediction model, the dynamic multi-dimensional fault feature set is taken as input, and a fault probability prediction result is output; based on a preset dynamic threshold, fault early warning information is generated according to the fault probability prediction result. Through the construction of the dynamic multi-dimensional fault feature set containing electric-thermal correlation features and the like, the application can sensitively capture early fault weak signs, thereby facilitating timely maintenance of electrical equipment of a substation.

A sample data generation method, a model training method, a device fingerprint classification method and device, the sample data generation method comprising: grabbing smart substation messages; analyzing the smart substation messages, and using the analyzed message fields, combining with the smart substation structure information stored in the SCD file, obtaining a device type label and updating a device label table; based on the updated device label table, obtaining a device type label value and a message feature field and encapsulating them as a PTD data set to serve as sample data of a smart substation measurement and control device fingerprint classification model. The model training using the sample data generated by the method provided in the embodiment of the application can improve the feature extraction effect and the generalization of the model, and thus the recognition and classification of the smart substation measurement and control device by the model can be realized.

The application discloses a kind of intelligent substation suitable for electric power system, it is related to electric power system technical field. Including: data convergence fusion module, to real-time acquisition and receive from the inside and outside of substation, the operation data of multi-source heterogeneous, operation data includes sensor data, SCADA data, relay protection data, environmental monitoring data and historical operation data, and to multi-source heterogeneous operation data carry out data cleaning, format standardization, space-time alignment and associated fusion.The application is collected multi-source heterogeneous operation data by data convergence fusion module and completes cleaning, standardization, space-time alignment and associated fusion, forms unified intelligent data model, effectively solves the problem that equipment state perception is not accurate in prior art due to insufficient multi-source data fusion;Rely on state perception evaluation module accurately analyzes equipment state and identifies fault mode, combined with intelligent early warning decision module realizes early fault prediction alarm using big data and machine learning.