348 results about "Power system security" patented technology

The invention discloses an electric power system safety early warning method and system based on multi-modal cooperation, and relates to the technical field of electric power system safety early warning, and the method comprises the steps: collecting multi-source operation data, carrying out the preprocessing, carrying out the multi-modal feature extraction and fusion based on the preprocessed data, and carrying out the multi-modal feature extraction and fusion. Inputting an edge detection model and outputting an abnormal confidence score in combination with an attention mechanism; and performing alarm grading according to the abnormal confidence score, constructing a causal diagram for alarms with high risk levels in combination with associated security events, and performing future attack path prediction by adopting a time sequence diagram neural network. According to the method, multi-scale convolution and a channel attention mechanism are fused, the extraction capability of the multi-source data time sequence features of the power system is enhanced, the anomaly detection precision is improved, dynamic attack path prediction is realized in combination with RMTPP and causal atlas topological constraints, sequence modeling is enhanced through self-attention and position coding, and the detection accuracy is improved. And the perspectiveness and the reliability of the safety early warning of the power system are obviously enhanced.

The invention discloses a switch equipment performance aging intelligent diagnosis method and device based on multi-parameter fusion, relates to the technical field of power equipment abnormal defect diagnosis, and solves the problem of low precision of aging judgment of switch equipment depending on a single temperature and humidity threshold value or a single gas parameter in the prior art. The method comprises the following steps: acquiring internal and external humiture and internal gas characteristic parameters of equipment; constructing multi-channel standardized monitoring data through time synchronization, filtering and de-noising and exception elimination processing; calculating an absolute humidity difference inside and outside the cabinet, constructing a humidity expectation model, and obtaining a standardized residual error; performing offset detection and trend smoothing processing on the standardized residual error to obtain a cumulant and a smoothing trend quantity, and fusing the cumulant and the smoothing trend quantity to calculate an offset index; outputting a moisture seepage risk score, and triggering early warning when the moisture seepage risk score and the characteristic gas concentration exceed a threshold value. According to the invention, real-time high-precision evaluation of the aging state of the equipment is realized, early hidden dangers are effectively identified, and the safety and reliability of a power system are improved.

The invention relates to the technical field of electrical equipment detection, and discloses a terahertz time-domain spectroscopy-based GIS insulating material nondestructive testing method, which comprises the following steps: acquiring GIS insulating material time-domain signals by using a reflection-type terahertz time-domain spectroscopy (THz-TDS), and separating and reconstructing defect echoes based on electromagnetic simulation modeling in combination with wavelet transform, STFT and a transmission matrix method; multi-dimensional features are extracted, SVM and RBFNN are trained after dimensionality reduction, and a classification and quantitative regression model fusing physical constraints is constructed; and inputting a signal of a sample to be detected into the model to realize rapid, non-contact and accurate detection on the type, size and depth of the defect. The method overcomes the defects that traditional detection is low in efficiency, has damage or is difficult to quantify, the signal-to-noise ratio, the sensitivity and the automation level are remarkably improved, the method can be widely applied to GIS production quality control, installation acceptance, operation and maintenance monitoring, health assessment and life prediction, and powerful support is provided for safe and reliable operation of an electric power system.

The invention discloses a power load prediction method, and the method comprises the steps: firstly solving an extreme event data sparsity problem through a generative adversarial network, and constructing an event time sequence library through a time sequence anomaly detection algorithm; then analyzing the causal relationship between the event and the load by applying a causal discovery algorithm, and converting prediction output into probability distribution by adopting a Bayesian neural network to quantify uncertainty; constructing a prediction model triggered by an event, and generating a multi-time scale probability prediction interval; and finally, generating a multi-scene prediction result through Monte Carlo simulation, quantifying the system recovery capability in combination with a toughness index, and integrating the system recovery capability to a decision support system to generate a risk response scheme. According to the method, the accuracy and robustness of load prediction under the extreme climate are remarkably improved, full-chain risk insight from early warning to recovery is realized, and prospective decision support is provided for safe operation of a power system.

The invention relates to the technical field of power systems and automation thereof, in particular to a generative adversarial network-based source-load joint scene generation method, which comprises the following steps of: constructing a multi-source time sequence database and extracting weather, time, space and historical state driving factors; establishing a joint probability distribution model based on a vine connection function; taking a numerical weather forecast path and a date type as conditional input, constructing a generative adversarial network embedded with a physical constraint microloss function of the power system, and forming a physical information generator; performing dependent structure fidelity verification on the generated scene by using the joint probability distribution model; generator parameters are fixed, potential space vectors are optimized through a gradient ascending method to maximize power grid risk indexes, and a high-risk source-load joint scene set is generated. According to the technical scheme, accurate generation of the source-load joint scene which is physically feasible and reasonable in statistics and focuses on the high-risk working condition is realized, and the safe operation toughness and the risk early warning capability of the novel power system are remarkably improved.

The invention relates to the technical field of power system safe operation safety and intelligent monitoring, and discloses a vegetation intrusion risk assessment method and system for a power transmission corridor and electronic equipment, and the method comprises the steps: obtaining multi-source remote sensing data and meteorological data of vegetation in a preset range of a target power transmission corridor; performing data fusion on the multi-source remote sensing data to obtain fused data; extracting a vegetation height change sequence based on the fused data, and performing prediction based on the vegetation height change sequence and the meteorological data to obtain a future time sequence height change curve; obtaining engineering parameters of a target power transmission corridor, and calculating a vegetation invasion risk value based on the engineering parameters and a future time sequence height change curve; and performing risk assessment based on the vegetation invasion risk value. The method breaks through the limitation of traditional static monitoring, integrates InSAR time sequence analysis and a machine learning algorithm, realizes vegetation growth dynamic modeling and future trend prediction, realizes risk level quantitative evaluation in combination with power transmission line structure parameters, and can provide technical support for power grid risk early warning.

The invention relates to the technical field of power system safety and stability control, and discloses a new energy field station broadband oscillation risk early warning method based on voltage dynamic indications, which comprises the following steps: acquiring instantaneous value data in a new energy electric field station to obtain electric quantity time sequence data; processing the electrical quantity time sequence data according to the target sliding window and outputting risk characteristic quantity; performing nonlinear normalization processing on the risk characteristic quantity by using a weighted fusion technology, and generating a single broadband oscillation risk index reflecting the broadband oscillation level of the new energy station according to a normalization processing result; and carrying out difference comparison on the single broadband oscillation risk index and a dynamic risk early warning threshold, and triggering an oscillation risk early warning signal and implementing oscillation risk early warning when a difference result meets a target warning requirement. According to the method, the defense gateway is moved forward by capturing the dynamic symptoms before oscillation occurs, so that the fundamental conversion from post-event to beforehand is realized, and a precious decision window period is won for operation adjustment.

The invention relates to the technical field of power system security, and particularly discloses a ground wire management operation system based on ground wire cabinet monitoring, which comprises a physical sensing layer, an edge computing layer, a block chain consensus layer and an application service layer. The physical sensing layer collects the identity, the in-place state and the electrical parameters of the grounding wire; the edge calculation layer carries out local data processing and event judgment; the block chain consensus layer realizes data credible evidence storage and cross-domain sharing through an intelligent contract and a distributed account book; and the application service layer provides asset panoramic display, cooperative verification and risk early warning services. Through the above architecture, unified management and safety collaboration of data of the whole life cycle of the grounding wire are realized, and the safety operation and maintenance level of a power grid is improved.

The invention discloses a power target damage propagation path modeling method based on an attack chain atlas, and the method comprises the steps: collecting multi-source heterogeneous data of a power system, and carrying out the standardized structure mapping and data quality optimization, thereby obtaining standardized behavior metadata; performing heterogeneous node extraction on the standardized behavior metadata, defining an association relationship between heterogeneous nodes to construct an initial atlas, optimizing the initial atlas in combination with manual verification and an automatic duplicate removal mechanism to obtain a heterogeneous atlas, and performing attack time sequence anchoring on attack behavior nodes in the heterogeneous atlas, the incidence relation of attack behaviors, system components and service logic in time and topology dimensions is mined, an attack path is reconstructed in a cross-layer mode, then a potential high-risk attack mode is identified, damage propagation prediction is carried out, and adaptive optimization is carried out on a damage propagation prediction result in combination with service priorities. The method has the effects of realizing structured restoration and damage propagation reasoning of the attack path and providing comprehensive technical support for safety protection of the power system.

The invention discloses a power system cascading failure chain modeling and blocking method, device and system considering source-load double-end uncertainty, and a medium. The method comprises the steps of constructing source-load uncertainty input distribution (wind power introduces Weibull distribution based on a wind speed segmented power model, photovoltaic introduces Beta distribution based on an irradiance output model, and a load side introduces a normal distribution fluctuation model); an MSFF method is adopted to construct a unified source-load stochastic power flow model, and a multi-scene power flow state set is obtained; introducing a power flow out-of-limit criterion and a hidden fault probability function, building a cascading fault propagation model fusing wind-solar load uncertainty, and dynamically simulating fault chain evolution; and formulating a staged collaborative blocking strategy (cutting off non-critical load emergency control, quickly responding a battery energy storage system and dynamically adjusting a critical line protection constant value) to realize real-time fault suppression. Simulation shows that the method is suitable for power system security defense in a high-proportion new energy penetration scene, and has good engineering adaptability and dynamic control performance.

The invention relates to the technical field of power system safety, and discloses a safety early warning method and system for a power system data center. The method comprises the steps that a safety monitoring period threshold value is set, when the continuous operation duration of the data center reaches the standard, historical and real-time safety state summaries are synchronously obtained, the historical operation duration comprises historical operation duration and configuration parameters, and the real-time safety state summaries comprise current operation duration and configuration parameters. And searching a security data fluctuation set by calculating security difference measurement of corresponding parameters of the two types of summary. And when the set variation degree is greater than or equal to a variation threshold value, taking the time distance ratio between the data storage starting point and the historical acquisition point as well as between the data storage starting point and the current time point as an early warning trigger factor, and starting a safety data early warning response from the data storage starting point according to the factor. According to the method, historical and real-time data comparison is combined, accurate monitoring of the safety state is achieved, timely risk identification is assisted, and a safety barrier is built for operation of the data center.

The invention discloses a power distribution network toughness dynamic evaluation and decision support method, and relates to the technical field of power system safety protection. The method comprises the following steps: constructing a dynamic risk field, fusing an external threat trajectory and equipment vulnerability, and calculating a node time-varying fault probability; key weights are set according to topology and user values, and value loads are formed; a large number of fault evolution sequences are generated through Monte Carlo simulation, impact speed and impact quantity characteristics are extracted for intelligent clustering screening, and an effective fault evolution sequence is obtained; fine time-step simulation is carried out, a toughness curve is drawn, and multi-dimensional dynamic toughness indexes such as robustness depth and loss area are extracted; and finally, performing adaptive classification on the scene based on the impact index and the robustness depth, and generating a sorted decision support information packet. According to the invention, the transformation from static and passive evaluation to dynamic, active prediction and scientific decision is realized, and the toughness of the power distribution network to cope with extreme events is effectively improved.

The invention discloses a power transmission line icing trend time sequence prediction method and system based on multi-source data, and relates to the technical field of power system safety monitoring and disaster prevention and mitigation, and the method comprises the steps: collecting the meteorological information, line state information and geographic space information of a to-be-predicted power transmission line in real time, forming a multi-source space-time heterogeneous sequence data set, preprocessing the data set; based on the physical process of icing, extracting time sequence features, cross-modal features and spatial features in the preprocessed data set, and constructing a high-dimensional feature vector; the cross modal characteristics comprise wet bulb temperature, wind-cold index and supercooling water gas flux; and inputting the time sequence high-dimensional feature vector into a CNN-BiLSTM hybrid prediction model based on an attention mechanism, and outputting the icing thickness and the icing change trend in a future preset time step length through a multi-step rolling prediction or direct multi-output prediction mode. According to the invention, accurate, real-time and quantitative prediction of the long-time icing thickness and the change trend can be realized.

The invention discloses a wind power prediction model double-target countermeasure attack method, which belongs to the technical field of crossing of power system security and artificial intelligence, and comprises the following steps: S1, collecting original data and determining parameters; s2, training a time sequence diagram auto-encoder detection model; s3, constructing and training a wind power prediction model; s4, constructing a dual-objective optimization function; s5, iteratively generating a confrontation sample; and S6, adversarial sample injection and detection. According to the wind power prediction model dual-target countermeasure attack method, through dual-target weighting function and reconstruction loss item coefficient adjustment, joint adjustment and optimization of attack destructiveness and concealment are realized, the detection probability is reduced, and bias selection is supported; through the improved GAE structure, the time sequence dependence is captured, artificial feature design is avoided, and the accuracy of detecting the time sequence adversarial sample is improved.

The invention relates to the technical field of image recognition, and discloses a violation recognition method and system for safe operation of an electric power system. The method comprises the following steps: collecting a power operation video and preprocessing to establish a violation sample library; extracting skeleton joint points by using a regional multi-person posture estimation algorithm to construct time sequence data; converting into a space-time diagram structure and generating violation feature enhancement data in combination with an attention mechanism; and carrying out feature learning and classification by adopting a space-time diagram convolutional neural network, and outputting a violation recognition result. According to the method, the technical problems that the traditional manual supervision efficiency is low, the coverage rate is insufficient and the dynamic violation behavior characteristics cannot be accurately captured by the existing image recognition method are solved, and the accuracy and the real-time monitoring capability of power operation violation behavior recognition are remarkably improved.

The invention discloses a large-scale power dispatching optimization method and system based on agent collaboration, and the method comprises the steps: collecting parameters such as power generation side unit output, power transmission side line transmission, power utilization side load, market side electricity price and the like through an energy Internet intelligent decision platform, and carrying out the dynamic processing of the parameters, and obtaining a power utilization main body market response coefficient; combining the coefficient and a multi-side parameter construction model to determine a multi-agent initial bargaining scheme, inputting the scheme into a reinforcement learning model, and setting a state, action and reward related element training optimization game strategy; and adjusting parameters according to the optimization strategy to generate scheduling plans such as unit start-stop, output distribution and line power flow control, feeding back the scheduling plans to a platform for simulation, outputting indexes such as a network loss rate and a load satisfaction rate, and performing iterative adjustment if a threshold value is not met. According to the system construction method, corresponding functional units operate cooperatively, multi-side parameters can be fully integrated, a closed-loop optimization process is formed, market adaptability and scheduling accuracy are improved, and safe and stable operation of a large-scale power system is guaranteed.

The invention relates to the technical field of power system safety monitoring, and discloses a power monitoring safety protection control system and method, and the system comprises a main station safety controller, a terminal safety verification unit, and a safety verification channel. The master station safety controller responds to a control instruction of the monitoring master station, carries out prospective simulation on the instruction, and generates a verification data packet containing a physical state expected vector; the terminal security verification unit receives the original control instruction and the verification data packet, and performs collaborative arbitration; the collaborative arbitration process comprises the following steps: the terminal security verification unit performs localized consequence simulation based on a built-in local physical micro-model to generate a local prediction state vector; comparing the vector with a physical state expected vector issued by the master station; and according to the comparison result, the terminal security verification unit generates and executes permission or blocking decisions for the control instruction. According to the invention, through cooperative verification of the physical layers of the master station and the terminal, malicious control instructions having physical harm to the power system are effectively protected.

The invention relates to the technical field of power system safety and stability analysis and operation control, and discloses a CVAE-GAN-based power system high-risk operation scene generation method, system and device and a medium, and the method comprises the steps: considering the uncertainty of wind and light output, and employing a Monte Carlo method to generate an original sample; calculating a node betweenness index and a power transmission betweenness, and taking the first three nodes and branches as key nodes and key branches; according to key node voltage and key branch power flow out-of-limit conditions, judging whether the risk is high, generating an original sample, setting different high-risk operation scene labels, and converting the labels into one-hot codes; the original samples and one-hot codes are input into a CVAE-GAN model at the same time for training; cVAE pre-training is carried out before formal training, and a good initial value is obtained; after training is completed, operation scenes with different high risks are generated by selecting labels, and finally advantages and disadvantages of generated samples are analyzed and evaluated by utilizing t-SNE.

The invention relates to the technical field of large-scale power system safety guarantee and intelligent scheduling, and discloses a new energy power system optimization scheduling method and system, and the method comprises the steps: carrying out the internal processing steps before economic scheduling, and carrying out the self-adaptive correction of a frequency change rate safety threshold value based on the overall completeness of a power defense system, real-time data closed-loop verification is carried out based on a wide-area measurement system, and an inertia contribution constant of a started unit is selected; and then generating a minimum system inertia base line constraint based on the corrected frequency change rate safety threshold and the inertia contribution constant selected after verification, and implanting the minimum system inertia base line constraint into the economic dispatching optimization model for execution. According to the method, a closed-loop information interaction path is established between power system safety analysis logic and an economic dispatching model, and verified physical safety requirements are preposed as constraint conditions which must be obeyed by the economic model.

The invention relates to the technical field of power system safety measures, and particularly provides a method for constructing a safety measure generation model based on a graph theory and a large language model, and the method comprises the following steps: constructing a power grid knowledge graph according to a power grid topological graph, and a sequential rule and a restrictive rule of equipment operation; inputting the structured text instruction of the power grid knowledge graph into the large language model, and generating an initial work ticket through the large language model; generating a training sample according to topological features extracted from the power grid topological graph and the initial work ticket, and training the large language model to obtain a topological perception enhancement model; and according to the multi-modal auxiliary data and the topological features, generating a multi-modal feature vector, and re-training the topological perception enhancement model to obtain a security measure generation model, so as to solve the technical problems that the security measure generation model cannot process image data and the generated security measure is easy to violate equipment operation security requirements.

The invention relates to the technical field of power system safety assessment, and discloses an optical storage and charging micro-grid power distribution network safety assessment method, system and device based on continuous loading capacity assessment and a medium, and the method comprises the steps: building a probability distribution model of an optical storage and charging micro-grid through data preprocessing; calculating a continuous loading capacity index considering the time sequence characteristics; establishing a power flow model of the power distribution network, and performing voltage, thermal and transient stability analysis; carrying out probability safety evaluation by adopting Monte Carlo simulation; and optimizing the acceptance capability of the optical storage and charging micro-grid based on the security constraint. Accurate and efficient evaluation of the safety level of the power distribution network is achieved, and effective technical support is provided for safe operation of the power distribution network under high-proportion new energy access.

The invention relates to the technical field of power systems, and provides an inertia optimization control method and device for a photovoltaic power station containing energy storage, a medium and equipment, and the method comprises the steps: monitoring the power grid voltage frequency of a grid-connected point of the photovoltaic power station in real time, and calculating the frequency deviation and the frequency change rate in real time based on a monitoring result; when the frequency deviation is larger than a frequency dead zone threshold value and the frequency change rate is larger than a frequency change rate dead zone threshold value, inertia optimization control is started, and the inertia optimization control comprises the steps that a photovoltaic virtual inertia power component and an energy storage virtual inertia power component are calculated based on the frequency deviation, the frequency change rate and the real-time charge state of the energy storage system; adjusting the output power of the photovoltaic system based on the photovoltaic virtual inertia power component; and controlling the charging and discharging power of the energy storage system based on the energy storage virtual inertia power component. The inertia supporting capacity of the photovoltaic power station is effectively improved, when the power grid frequency fluctuates, rapid response can be achieved, effective inertia compensation can be provided, the stability of the power grid is enhanced, and safe and stable operation of a power system is guaranteed.

The application discloses a kind of substation flood intelligent monitoring method and system, it is related to electric power system safety monitoring field.The method is by building the multi-dimensional influence factor library including the bottom elevation of discharge port and pipe network permeation loss, combined with rainfall forecast executes dynamic water balance deduction, deduce according to the dynamic correction soil infiltration capacity of early rainless days, and according to the effective pressure difference of water level and the bottom of discharge port calculates net drainage capacity;Based on the deduction result, water level height field is generated by combining three-dimensional digital model for waterlogging overflow distribution;According to water level height field and equipment elevation, determine the flooding risk, and generate dispatching instruction by taking water center as target and combining prohibited operation area to optimize equipment layout coordinates;Through man-machine interaction correction parameter and trigger GPU acceleration recalculation to realize model online evolution.The application realizes the physical mechanism simulation and space intelligent scheduling under the microscale of substation, changes passive alarm into active risk deduction.

The application discloses a kind of energy storage collaborative control method and device for power grid primary frequency modulation and secondary frequency modulation, method includes: the regional equivalent frequency response model of multi-region interconnected power grid is constructed;According to the command of energy storage primary and secondary frequency modulation of regional tie-line exchange power and regional equivalent frequency response model same direction condition is obtained, and based on fuzzy logic and centroid defuzzification obtains energy storage response priority;According to energy storage response priority and command same direction condition distribution primary and secondary frequency modulation power.The method of the application can make full use of the multi-scene output characteristics of energy storage, optimize its output under the premise of meeting the safe operation of power system, and improve the economy.

The utility model discloses a multifunctional early-warning intelligent monitoring device for a cable trench of a transformer substation. The multifunctional early-warning intelligent monitoring device comprises a main control chip, a sensor, a communication module, a control module, a relay, danger elimination equipment, a transformer and a power supply, the communication module, the control module and the transformer are respectively connected with the main control chip; the relay is connected with the danger eliminating device and the control module. The power supply is respectively connected with the relay and the transformer; the sensors comprise a liquid level sensor, an ultrasonic sensor, a temperature and humidity sensor and a combustible gas sensor; the liquid level sensor, the ultrasonic sensor, the temperature and humidity sensor and the combustible gas sensor are respectively connected with the main control chip. According to the utility model, monitoring and rapid early warning of water level, temperature and humidity, combustible gas concentration and animal activity in the cable trench can be realized, operation and maintenance cost and risk of the cable trench are reduced, and stable operation of the cable trench and safety and reliability of an electric power system are guaranteed.

The present application relates to power industry safety domain boundary fitting technology, in particular to a kind of high-dimensional static security domain boundary fitting method of power system, considering system generator output constraint, node load value sampling is carried out, through power flow calculation, the sample in the security domain is filtered out, and initial sample set is formed.Boundary sample search algorithm is proposed, for each sample in initial sample set, find a sample in the security domain, a sample outside the security domain, and satisfy the distance between the two is less than the set distance threshold value.The data in the boundary sample set in the original power injection space is converted to new three-dimensional feature space by deep neural network model.Extract the boundary in feature space by the weighted tilt decision tree algorithm based on information gain ratio, and evaluate the boundary performance, select the optimal boundary.The method can realize the fitting of high-dimensional boundary of power system security domain, and reduce the error with actual boundary.

A comprehensive energy system toughness improvement method considering road network traffic uncertainty belongs to the technical field of power system safety planning operation, and comprises the following steps: constructing a dual uncertainty model containing wind power output uncertainty, photovoltaic output uncertainty and traffic network traffic uncertainty; based on the dual uncertainty model, a two-stage robust optimization method is adopted, pre-disaster resource pre-deployment decision is carried out, and resources comprise fixed electricity-hydrogen-storage resources and mobile hydrogen energy resources; in the disaster occurrence process, on the basis of a pre-disaster resource pre-deployment decision result and system state information obtained in real time, a model prediction control MPC rolling optimization method is adopted, and scheduling and operation strategies of mobile hydrogen energy resources are dynamically adjusted. Through cooperative scheduling of fixed and mobile electricity-hydrogen-storage resources, optimal configuration of hydrogen energy resources before disasters and dynamic response of mobile hydrogen energy in disasters are realized, so that survival and recovery capabilities of the system in extreme weather events are remarkably enhanced.

The invention relates to the technical field of electric power meteorological disaster prediction, and particularly provides a power grid extreme freezing rain quantitative short-term and temporary early warning method and device, and the method comprises the steps: taking the meteorological element data, topographic feature data and freezing rain cumulative prediction amount of a region as the input of a pre-trained physical constraint deep learning model; obtaining a freezing rain accumulated correction output by a pre-trained physical constraint deep learning model; determining a freezing rain cumulative forecast quantity of the region based on the freezing rain cumulative correction quantity; and performing power grid extreme freezing rain quantitative short-term and temporary early warning on the region based on the freezing rain accumulated forecast quantity of the region. According to the technical scheme provided by the invention, the early warning precision and response efficiency of the power grid under the extreme freezing rain condition can be remarkably improved, and a scientific decision basis is provided for power system safety scheduling, emergency ice melting and equipment risk management and control.

The invention provides a panoramic monitoring method and system for a remote control process of an electric power system, and the method comprises the steps: integrating remote control information which is collected by secondary equipment at a plant station end in a scattered manner in time and space dimensions; a remote control operation panoramic record report capable of comprehensively reflecting a transmission state of a remote control instruction in a plant-station end communication network and a processing result in each device is constructed, and panoramic monitoring of the whole remote control operation process can be realized by acquiring and visually displaying the remote control operation panoramic record report in real time at a dispatching master station or a plant-station end. On one hand, a remote control operation panoramic record report is constructed, and comprehensive data support can be provided for remote control operation timeliness evaluation and remote control operation abnormal reason analysis and positioning; on the other hand, on-line panoramic monitoring of the remote control operation process is achieved, the sensing capacity of remote control operators for the operation condition of field equipment can be greatly improved, then the efficiency of power grid remote control operation is improved, and safe, stable and economical operation of a novel power system is supported.

The invention discloses a power equipment USB interface monitoring method and system, and belongs to the technical field of power system safety monitoring. The power equipment USB interface monitoring method comprises the following steps: acquiring a target USB interface message sent by a client; according to the target USB interface message, determining corresponding USB equipment attribute information; performing matching identification on the attribute information of the USB equipment and associated information in a pre-established security knowledge base; and if the identification is successful, outputting associated information corresponding to the target USB interface to give an alarm. According to the method and the device, the corresponding USB equipment attribute information is determined according to the target USB interface message sent by the client, and the USB equipment attribute information and the associated information in the pre-established safety knowledge base are matched and identified, so that the associated information corresponding to the target USB interface can be determined, and the externally inserted USB equipment can be identified and alarmed; the problem that the current power system is easily stolen by external USB equipment and transmits viruses is solved.