21results about How to "Increase risk resistance" patented technology

The invention provides a multi-modal large model construction and operation method and system for reservoir dam safety. The method comprises the following steps: constructing a training set, wherein the training set comprises a single sample; multi-modal data as model input: sensor data arranged on the dam, historical hidden danger records, engineering technology documents formed in various stages of planning, design, construction and operation of the dam, information resources related to dam safety, geometric and material information of the BIM model, timestamps and spatial position information; the probability value of occurrence of the hidden danger event serving as the training label is obtained; the training set is adopted to train a multi-mode pre-training model based on a Transform framework; performing real-time prediction and early warning on potential safety hazards of the dam; and calculating the actual influence degree, the comprehensive risk score, the dynamically set early warning threshold and the emergency measure suggestion of the hidden danger event according to the probability value of whether the hidden danger event occurs or not output by the model. The scientificity and effectiveness of dam safety monitoring are comprehensively improved.

The invention provides a power grid frequency modulation cooperative control method considering a tie line section, and relates to the field of power system automatic scheduling, and the method comprises the steps: obtaining a load characteristic parameter, a transmission capacity parameter and a stability margin parameter of a section spanned by a tie line; solving the multi-objective optimization model by adopting an improved particle swarm optimization algorithm to obtain an optimal tie line electric power distribution curve meeting various constraint conditions; discretizing the optimal tie line electric power distribution curve, and converting the discretized optimal tie line electric power distribution curve into an active power instruction value of a tie line control system; and the tie line control system adjusts the electric power of the tie line in real time according to the active power instruction value. According to the invention, the reasonable distribution of the electric power of the tie line is realized, the frequency modulation demand and transmission capacity limitation of each section are balanced, and the safety and stability of power grid operation are improved. Through a differential scheduling strategy and a real-time optimization mechanism, load fluctuation can be effectively coped with, and safe and stable operation of a power grid is guaranteed.

The invention discloses a novel distribution network multi-virtual power plant distributed resource aggregation and optimization operation method. The method comprises the following steps: 1, solving a virtual power plant feasible region based on a vertex enumeration method; 2, realizing multi-virtual power plant cooperative operation optimization based on a binary consistency algorithm; 3, based on the virtual power plant feasible region solving method based on the vertex enumeration method and the multi-virtual power plant cooperative operation optimization method based on the binary consistency algorithm, constructing a resource aggregation and aggregate optimization operation framework process; in the process, firstly, distributed resources are aggregated through a vertex enumeration method to obtain a virtual power plant feasible region; and carrying out collaborative operation optimization on the multiple virtual power plants by utilizing a binary consistency algorithm. By means of the method, efficient aggregation and optimized operation of distributed resources are achieved, the operation efficiency and economical efficiency of the power distribution network are improved, and the method has important economic and social benefits.

The invention discloses an intelligent charging management system and method based on edge computing, and relates to the field of edge computation.The method comprises the steps that 1, an edge computing node module is arranged, the edge computing node module comprises a data acquisition unit and a data processing unit, data of a charging pile is acquired based on the data acquisition unit and the data processing unit, and the data of the charging pile is acquired; by introducing an edge computing node, computing and control part data of the charging pile are moved to the local; step 2, the edge computing node module uploads the collected data to a central control platform; 3, the central control platform receives and processes the data uploaded by the edge computing node, and based on the reservation time of the user, the current power grid load and the real-time electricity price, cyclic charging optimization scheduling is carried out in a cyclic iteration mode; and 4, after the edge computing node detects that charging is completed or the target electric quantity set by the user is reached, charging is automatically cut off, a charging record is uploaded to the central control platform, and long-term data analysis and strategy optimization are carried out.

The invention provides a wind, light, fire and nuclear storage integrated scheduling architecture based on a complex and uncertain environment of a cold region power grid, and relates to the technical field of power grid system processing, the architecture comprises a data acquisition and monitoring layer, an analysis and decision layer, a control execution layer and an evaluation and optimization layer, the anti-freezing and deicing technology of the power transmission line effectively improves the reliability of equipment in severe environments such as low temperature and ice and snow, guarantees the stability of power transmission of a power grid, reduces equipment faults and power failure accidents caused by cold environment factors, enhances the anti-risk capability of the whole power grid, and improves the safety of the whole power grid. According to the method, characteristics and complementary relations of multiple energy sources of wind, light, fire and nuclear storage are comprehensively considered, peak regulation and frequency modulation analysis and decision making and integrated regulation and control analysis and decision making are carried out, and by constructing a reasonable operation scene and a scheduling model, optimal configuration and cooperative operation of power generation resources can be achieved under different operation conditions.

The invention relates to the technical field of water level, and particularly discloses a farmland water level environment monitoring and alarming device, which comprises a water level acquisition module for acquiring a water level value in real time, comparing a water level range value, sending an early warning prompt when the range is exceeded, and an early warning analysis module for obtaining a water level early warning value through numerical calculation based on the water level value, an alarm signal is sent if the water level early-warning value exceeds a threshold value, the water level early-warning value needs to be predicted and analyzed if the water level early-warning value does not exceed the threshold value, a trend prediction module carries out linear regression on the multi-cycle water level early-warning value, water level over-limit time is obtained through calculation, an AI analysis module combines historical water level values, the early-warning value, rainfall and farmland displacement, and the water level early-warning value is obtained. The device can comprehensively monitor the water level of the farmland, early warns and predicts the change of the water level in time, and provides an effective decision basis for the management of the water level of the farmland.

The invention discloses a two-stage space-time diagram network and multi-source information fusion time sequence probability prediction method and device, and relates to the technical field of artificial intelligence and big data analysis. The method comprises the following steps: acquiring historical wind speed sequence data and corresponding target variable sequence data; preprocessing the data, and constructing a training sample according to a preset time sliding window; constructing a time sequence probability prediction framework of the two-stage space-time diagram network and multi-source information fusion; based on the fluctuation correlation of the historical sequence data, constructing an adjacent matrix between nodes; inputting the training sample and the adjacent matrix between the nodes into a wind speed prediction model, training the model through a designed threshold perception loss function of a wind speed-power nonlinear relationship, and outputting a multi-node wind speed prediction probability of a first stage; and inputting the multi-node wind speed prediction probability and the multi-source environmental factor data into the gradient boosting tree model for second-stage prediction, and outputting a multi-node wind power prediction result. According to the invention, prediction errors can be reduced.

The invention provides a shelter equipment remote power supply monitoring method and system based on the Internet of Things. The method comprises the following steps: monitoring each electric device in real time, and sending monitoring data to a cloud server to obtain real-time monitoring data; generating an accurate power demand prediction report according to the real-time monitoring data; based on the power demand prediction report, when power supply and demand imbalance is predicted, starting an optimization scheduling strategy based on a particle swarm optimization algorithm, dynamically adjusting the output power of a generator set or the working schedule of electric equipment, and evaluating potential risk points by using a fault tree analysis technology; generating an emergency response plan and an optimal scheduling result; and carrying out automatic management on a power resource shortage condition based on the optimal scheduling result, ensuring normal operation of high-priority equipment, and generating a power management decision suggestion. According to the technical scheme provided by the invention, the flexibility of power supply monitoring can be improved.

The invention relates to a battery cluster parallel operation control method and device, an energy storage system, electronic equipment and a medium, the energy storage system comprises n battery clusters, data interaction is carried out between battery monitoring units based on a preset communication bus, and the method comprises the following steps: receiving battery pack parameters returned by the battery monitoring units according to a first time interval, obtaining battery cluster parameters according to a second time interval; calculating parallel operation rating scores of the battery clusters according to the battery pack parameters and the battery cluster parameters; determining the parallel operation level of the battery according to the parallel operation rating score; if the battery parallel operation level is greater than or equal to a preset level threshold value, sending a parallel operation channel occupation command to a preset communication bus; and if the parallel operation channel is successfully occupied, executing a preset parallel operation program. The battery parallel operation control scheme provided by the invention does not depend on an electric energy management system in the energy storage system, and a host and a slave do not need to be arranged in the battery cluster, so that the anti-risk capability of the energy storage system and the battery cluster parallel operation power-on robustness can be greatly improved.

The invention belongs to the technical field of electrical monitoring, and particularly relates to a railway traction substation three-dimensional visual monitoring system, which comprises a data acquisition unit, a data processing unit and a data feedback interaction unit, and is characterized in that the data acquisition unit is used for acquiring working condition data of electrical equipment in a railway traction substation; comprising a fixed acquisition module and a mobile acquisition module; according to the invention, image information acquisition is carried out on dead corners which are difficult to cover by the fixed acquisition module through the mobile trolley, comprehensive coverage and full monitoring of the railway traction substation are realized under dynamic and static cooperation mutual verification, and the safety and reliability degree of information acquisition is improved; moreover, when the information acquisition devices corresponding to the fixed acquisition modules in part of the areas break down, the mobile trolley can be controlled to go to the fault area as a supplement, so that the blank of a monitoring network is filled, and the anti-risk capability of the whole railway traction substation monitoring system is improved.

The invention discloses a supply chain node toughness dynamic evaluation method based on information entropy, and belongs to the field of supply chain network toughness research. The method comprises the steps of calculating efficiency and redundancy of enterprise nodes in supply and demand directions based on an information entropy theory; according to the roles of the enterprise nodes in the supply chain network, performing weighted fusion to obtain the total efficiency and the total redundancy of the enterprise nodes; by comprehensively considering efficiency and redundancy, dynamic quantification of enterprise node toughness is realized. In addition, node toughness driving mechanism diagnosis based on an internal structure is further introduced, and internal structure factors for driving node toughness fluctuation are accurately recognized through exponential decomposition and sensitivity analysis. According to the method disclosed by the invention, dynamic quantification and attribution analysis of the fine-grained toughness of the enterprise node level based on the supply and demand bidirectional dependency relationship are realized, and powerful decision support is provided for accurately positioning the fragile link of the supply chain, optimizing the structure of the supply chain and improving the overall anti-risk capability of the supply chain.

The invention provides an engineering information data management method based on a block chain, and relates to the technical field of block chains, the method is applied to a first server, and the method comprises the following steps: obtaining to-be-processed engineering information data; the synchronous broadcast is sent to the plurality of node servers, reply information sent by a second server in the plurality of node servers is received, and the reply information comprises a second public key of the second server and equipment information; respectively sending the equipment information of each second server to other second servers for verification; after the information that the plurality of second servers pass the verification of the equipment information is obtained, encrypting each piece of engineering information data by adopting a second public key to obtain encrypted data, so that the encrypted data can be decrypted by adopting a second private key corresponding to each second public key; and sending the encrypted data to the second server according to the communication address of each second server. According to the invention, the security of engineering information data management can be improved.

The application relates to a smart scheduling method and system for power grid safety guarantee based on multi-source data analysis, relates to the technical field of power grid scheduling, builds a high-precision space-time evolution digital twin power grid model, fuses four-dimensional multi-source fusion data sets generated by five types of data such as power grid operation, equipment health and extreme weather, adopts a space-time attention graph convolutional neural network to perform multi-scale safety situation assessment, and outputs node-level, regional-level and system-level safety margins and progressive risk prediction results in the future 1-72 hours; a dynamic weight generator driven by a safety situation is constructed to automatically adjust the weights of five optimization objectives; a constraint self-adaptive multi-objective optimization model is solved to obtain a Pareto optimal solution set, an optimal scheme is selected after multi-scenario robustness simulation, and a closed-loop self-adaptive mechanism is established to continuously optimize the core model. The application solves the problems of single traditional scheduling target and poor adaptability, and significantly improves the safety, economy and anti-risk ability of power grid operation.

The application discloses a cross-regional environment collaborative governance data management system and method based on data analysis, relates to the technical field of environmental data management, and comprises the following steps: obtaining cross-regional environmental monitoring data and collaborative governance behavior data, constructing a pollution transmission topology graph and predicting the arrival time and peak intensity; generating early warning information by combining the affected nodes with the sensitive targets and upstream early warning levels in a bidirectional association; based on the topology graph and the early warning information, generating a task arrangement scheme with minimum global damage by scheduling game; performing uncertainty stress testing on the scheme, and if the scheme is lower than the robustness threshold, then cyclically adjusting the scheme until it meets the standard and is issued; receiving execution time and effect data, triggering topology graph re-prediction and early warning information updating when deviation occurs, and performing local or global task re-arrangement; comparing the actual pollution evolution curve with the predicted curve, calibrating the pollution transmission parameters, and updating the evaluation value of the emergency response efficiency of each region.

This application discloses a method and system for stable hydrogen supply planning in a hydrogen production system considering electrolyzer failures, relating to the field of new energy hydrogen production. The method includes acquiring parameter data, historical new energy output data, and historical hydrogen load data of a new energy hydrogen production system containing multiple electrolyzers; constructing multi-state switching models for the electrolyzers, an electrolyzer operation model, an energy storage battery operation model, and a hydrogen storage tank operation model; then constructing a mathematical model for planning the new energy hydrogen production system; and finally, using clustering algorithms and a two-layer iterative solution algorithm to solve the mathematical model for planning the new energy hydrogen production system, determining the optimal capacity planning scheme for each electrolyzer, energy storage battery, and hydrogen storage tank in the new energy hydrogen production system. This application can incorporate the uncertainty of electrolyzer failures into the hydrogen production system planning model, improve the multi-state characterization of the electrolyzers, achieve optimal capacity planning for each device in the new energy hydrogen production system, and ensure a stable and reliable supply of green hydrogen.

The invention provides a multi-source data fused power equipment fault root cause analysis method and system. The method comprises the steps of performing credibility evaluation on multi-source power equipment data; the power equipment comprises sensing monitoring data, operation and maintenance record data and power grid topology data; calculating a fusion weight according to a credibility evaluation result; fusing the power equipment data by using the fusion weight to obtain an equipment fault feature vector; performing correlation calculation on the fault root causes and the key features to obtain a correlation matrix; performing root cause matching degree calculation and screening according to the incidence matrix and the equipment fault feature vector to obtain candidate root causes; constructing a Bayesian network according to the candidate root causes and the corresponding key features, dynamically initializing the conditional probability of the Bayesian network by using real-time data update factors according to an incidence matrix, and adjusting the Bayesian network by using fault reasoning knowledge of a fault knowledge graph; and performing root cause screening on the equipment fault feature vector by adopting a Bayesian network to obtain a power equipment matching fault root cause and a corresponding confidence coefficient. Through the scheme, the accuracy and the disposal efficiency of fault root cause analysis in a complex scene can be improved, and the operation and maintenance cost is reduced.

The application discloses an AI digital customer service device based on an offline large model and an intelligent interaction method. The device is deployed on a user terminal device. The device can complete intelligent interaction without cloud and network, ensuring the continuity and stability of customer service. A lightweight offline large model is used for running, without occupying high server computing power and storage space. It can be directly adapted to various ordinary user terminal devices, and is convenient to deploy and has strong hardware adaptability. Through a knowledge base management module, standardized and structured enterprise customer service knowledge can be stored and managed, and business-related enterprise customer service knowledge can be called as needed, which is beneficial to realize the standardized output of user instruction data and response speech, get rid of the dependence on personal experience of customer service personnel, accurately locate the core problem of customers and formulate a scientific solution method. With the help of the thinking chain technology, the related enterprise customer service knowledge is integrated, combed and logically deduced, and the standardized answer with clear logic and unified format is output.

The utility model relates to the technical field of pipeline beveling machine locking, and provides a pipeline beveling machine locking device which comprises a limiting table, and a fixing shaft is fixedly connected to the side wall of the limiting table. The side wall of the fixing shaft is slidably connected with a sliding cylinder. The side wall of the sliding cylinder is rotationally connected with rotating blocks, and the side walls of the multiple rotating blocks are rotationally connected with limiting blocks. The end part of the limiting block is fixedly connected with a clamping block; a push block is fixedly connected to the side wall of the sliding cylinder. A hydraulic cylinder is arranged on the side wall of the push block; the bottoms of the two hydraulic cylinders are fixedly connected with hydraulic tables correspondingly. The hydraulic cylinder is arranged to drive the sliding barrel, so that the multiple clamping blocks are clamped on the side wall of the pipeline, automatic rapid locking of the pipeline is facilitated, convenience is provided for pipeline locking actions of workers, physical exhaustion of the workers is reduced, and working efficiency is improved.

The application relates to an adaptive direct-current input interface circuit and a driving method thereof. The circuit comprises a voltage comparison module, an adaptive protection module and a voltage reference module. The voltage reference module performs voltage stabilization processing on a target direct-current power supply to obtain a reference direct-current power supply and transmits the reference direct-current power supply to the voltage comparison module. The voltage comparison module divides the voltage of two types of power supplies to obtain a to-be-detected voltage and a reference voltage and obtains a voltage comparison result according to the difference between the to-be-detected voltage and the reference voltage. The adaptive protection module performs polarity detection on the target direct-current power supply to obtain a power supply polarity detection result. According to the two types of results, if the target direct-current power supply is of a positive polarity and is within a voltage control range, the adaptive protection module turns on the connection between the target direct-current power supply and a subsequent circuit; if the target direct-current power supply is of the positive polarity and is not within the voltage control range, the adaptive protection module blocks the corresponding connection; and if the target direct-current power supply is of a reverse polarity, the adaptive protection module blocks the corresponding connection. The method can realize adaptive identification and protection control of a direct-current input interface under an abnormal power supply scene.

The invention discloses an advertisement type photovoltaic energy-saving outdoor garbage can. The advertisement box comprises a base, a shell is arranged at the top of the base, advertisement frames and sliding grooves are arranged on the two sides of the two ends of the shell, push-pull plates are arranged on the two sides of the shell in a sliding mode, and inner barrels are arranged at the top ends of the push-pull plates. According to the outdoor garbage can advertising machine, the outdoor garbage can advertising machine is divided into the shell and the lifting shell, in the carrying and assembling process of installation personnel, due to the fact that the shell is sleeved with the lifting shell, the size of the outdoor garbage can advertising machine is reduced, the installation personnel can carry and assemble the outdoor garbage can advertising machine conveniently, and in case of severe weather, the installation personnel can unlock the clamping pieces; when the outdoor garbage can advertising machine is used, the bolts at the round holes are removed, an installer can contract the shell and the lifting shell, the disaster area of the outdoor garbage can advertising machine in severe weather is reduced, the anti-risk effect of the outdoor garbage can advertising machine in severe weather is improved, and therefore the outdoor garbage can advertising machine is prevented from being damaged in severe weather.

The invention provides a hydropower station project group dynamic investment decision-making method considering uncertainty, and relates to the technical field of hydropower project investment decision-making, and the method comprises the steps: S1, constructing a dynamic element perception and iteration engine, and obtaining a basic decision-making data source of a hydropower project group according to the dynamic element perception and iteration engine; extracting a plurality of decision-making elements from the basic decision-making data source, and dividing the plurality of decision-making elements into static basic elements and dynamic sensitive elements; according to the dynamic sensitive elements, through a real-time data and high-frequency feature analysis technology, an evaluation threshold interval is dynamically calculated and corrected, and a real-time iterative dynamic element library is formed. A multi-dimensional static evaluation system fused with expert experience can be upgraded into a decision support system capable of embedding a key uncertainty dynamic evolution model and performing adaptive simulation and optimization according to time sequence information input, so that a dynamic portfolio strategy with higher anti-risk capability is output.