1572 results about "Electricity distribution systems" patented technology

The invention relates to a power distribution system optimization method considering a space-time game under vehicle-station-network interaction, and the method employs a double-layer optimization framework integrating the space-time game and dynamic electricity price, an upper decision maker is a power distribution system operator, and the power distribution system operation cost is minimized and the renewable energy consumption rate is maximized. Generating a dynamic electricity price signal in a time-sharing and partition manner; the lower-layer main body comprises an electric vehicle user and a charging station operator, and the electric vehicle user optimizes a charging time period and a charging station and forms charging demand distribution through a non-cooperative game based on a dynamic electricity price signal and a charging service charge by taking the maximum self-charging decision utility as a target; and a charging station operator optimizes and adjusts a charging service fee decision by taking charging demand distribution as input and taking revenue maximization as a target. Compared with the prior art, the method can collaboratively optimize the economic operation of the power grid and the consumption of renewable energy sources, promotes the efficient flow and balanced distribution of resources among regions, and provides decision support for the dispatching of the power distribution network.

The invention discloses a self-adaptive management method and system for intelligent terminal equipment of a distributed power distribution network. According to the method, a self-organizing peer-to-peer communication network covering the whole network is constructed, and neighbor discovery and information sharing among intelligent terminal devices are achieved; the terminal independently completes control instruction calculation based on the local electrical parameters and a preset multi-objective function and optimizes an area control effect through a cooperation mechanism; introducing a self-adaptive adjustment strategy of a control algorithm; when abnormal operation is detected, the terminal can autonomously complete fault positioning and isolation, and power supply recovery is realized based on standby path judgment or micro-grid switching; the central management unit periodically carries out acceptance capacity evaluation, and terminal model parameters are aggregated in a federated learning mode; the terminal has an edge autonomous capability, and can maintain local control and data retention when communication is interrupted. The system has the characteristics of quick response, flexible structure, intelligent cooperation, high adaptability and the like, and is suitable for intelligent operation and management and control scenes of various types of power distribution systems.

This invention pertains to an intelligent electronic device designed for sophisticated monitoring and analysis of electrical power distribution. The device integrates at least one sensor for detecting electrical parameters from a distribution system to a load, coupled with an analog-to-digital converter to transform sensed analog signals into digital data. A processing module, linked to the converter, employs customized moving average filters to calculate the frequency of electrical power distribution, enhancing measurement accuracy by adjusting for transient fluctuations. It retrieves frequency threshold settings from memory to define operational bounds, logging frequency data around identified deviation events when measurements surpass these thresholds. This system facilitates precise frequency analysis and robust event logging, providing a comprehensive solution for maintaining electrical power distribution within defined standards.

The invention discloses a power distribution system flexible regulation and control system based on load side behavior recognition and a method thereof, and relates to the technical field of power distribution of power systems. The method comprises the following steps: acquiring power utilization power, equipment state, environment parameters and power utilization preference information of a user side in real time; dynamically generating and updating behavior inertia factor data, and reporting high-frequency change data when the behavior inertia factor data exceeds a preset threshold; receiving regional load feature abstract data, and uploading the abstract data when the change of the abstract data exceeds a threshold value; historical period abstract data are fused, and a prediction matrix containing the partition load trend and the peak probability in the T time window is generated through a behavior inertia dynamic evolution model; and when the load rate of the system exceeds a safety threshold value, calculating an individual adjustment amplitude, and generating a regulation and control instruction containing a time-phased target and a flexible adjustment amplitude. Accurate prediction and flexible regulation and control of the load of the power distribution system are realized, and the operation stability and the power supply quality of the system are remarkably improved.

The present invention relates to the technical field of power systems and operations research. Disclosed are a method and system for coordinated source-grid-load-storage dispatch optimization during post-disaster restoration of a power distribution system. The method comprises: acquiring network topology constraint data for a power distribution system, wherein network topology constraints for the power distribution system comprise a virtual network topology constraint for the power distribution system, a geometric network topology constraint for the power distribution system, and an electrical network topology constraint for the power distribution system; on the basis of fault situations of a power source device, a load device and an energy storage device that are caused by a disaster, generating operational characteristic constraint data for devices in the power distribution system, wherein the operational characteristic constraint data for the devices in the power distribution system comprises operational characteristic constraints for the power source device, the load device and the energy storage device; and inputting the network topology constraint data for the power distribution system and the operational characteristic constraint data for the devices in the power distribution system into a pre-established coordinated source-grid-load-storage dispatch optimization model for power distribution systems in a post-disaster restoration scenario, such that a coordinated dispatch optimization result is output.

The invention provides a smart park power distribution equipment intelligent operation and maintenance method and system based on big data, and relates to the technical field of smart park operation and maintenance management.The method comprises the steps that firstly, a structured expression mode of operation behaviors of a multi-park power distribution system is constructed, and the relationship between common operation characteristics of parks and equipment behaviors is extracted; rapid modeling and migration prediction of the new park are realized; secondly, an intelligent layered response mechanism based on abnormal event triggering is constructed, and an adaptive analysis and diagnosis strategy can be dynamically selected according to the type and grade of an abnormal event; meanwhile, a closed-loop process from event triggering to fault tracing, equipment positioning and response strategy making is realized in combination with a data driving and structured reasoning method; in addition, various heterogeneous data sources are fused, an information barrier is broken through, the comprehensive judgment of the system is improved, the output of the AI model is verified by introducing electrical physical constraint conditions, and it is ensured that the result logic is reasonable.

The invention relates to the technical field of power distribution cabinet detection, and discloses an intelligent power distribution cabinet state dynamic monitoring method and system, and the method comprises the following steps: collecting multi-source data generated in the operation process of a power distribution cabinet; preprocessing the multi-source data to generate a standardized data set; a random field model is constructed and used for describing the spatial relevance between units in the power distribution cabinet and the relation between the state of each unit and multi-source data, and model parameters are estimated through the maximum logarithmic posterior probability. An intelligent power distribution simulation model and a multi-source data acquisition technology are adopted, multi-dimensional parameters are acquired in real time through a high-precision sensor, monitoring efficiency and decision accuracy are remarkably improved, data analysis integrity and model sensitivity are ensured through dynamic time modeling and capturing of space and time relevance of the power distribution cabinet, and the power distribution cabinet can be monitored more accurately. And the state distribution visualization and maintenance priority strategy generation module optimizes the maintenance plan, reduces the operation and maintenance cost, and guarantees the stability of the power distribution system.

The invention discloses a power distribution switchgear remote monitoring and maintenance method based on the Internet of Things, relates to the technical field of power system operation and maintenance, and solves the problems that in an existing power distribution system, the edge anomaly recognition capability is weak, a control feedback chain is not closed, and multi-terminal control conflicts occur frequently. According to the scheme, a structured time sequence index of multi-source data is constructed on edge equipment, and equipment state drift is judged based on residual function included angle change; a control command management mechanism of a unique transaction identifier is introduced, a dual-channel feedback structure and a control mutual exclusion stack are combined, and a remote command consistency control chain is established; a hidden danger propagation chain is constructed on the cloud based on the abnormal Boolean bitmap and the topological relation, and a multi-node state linkage analysis and risk priority intervention strategy is achieved; according to the invention, the abnormity identification accuracy, the remote control stability and the system-level operation and maintenance response efficiency of the power distribution switch equipment are obviously improved.

The invention discloses a power distribution topology dynamic reconstruction risk assessment method, system and device and a medium, and relates to the technical field of data processing. The method comprises the following steps: acquiring real-time state data of an intelligent component to construct an initial topological structure, and identifying a changed target node by sending a detection signal; and then carrying out dynamic reconstruction on the topological structure in the three logic layers. And performing electrical characteristic verification on the reconstructed topological structure. And after the electrical characteristic verification is passed, determining a connection relationship of upstream and downstream power distribution cabinets and a component association link based on the target node, and calculating a risk level in combination with historical operation parameters. And formulating a temporary coping strategy according to the risk level, and generating a risk assessment report containing the topological influence range, the risk level and the coping strategy. Real-time monitoring and risk early warning of topological change of the power distribution system are realized in the whole process. By implementing the technical scheme provided by the invention, the risk assessment accuracy of the dynamic reconstruction of the power distribution topology can be improved.

The invention relates to the technical field of power distribution management, in particular to an intelligent UPS power distribution management method and system based on dynamic load balance, and the method comprises the steps: monitoring the energy consumption parameters of each load in real time, and generating a multi-dimensional energy consumption data set based on the energy consumption parameters; inputting the multi-dimensional energy consumption data set into a preset power prediction model, and predicting a power demand prediction result of each load in future time; dynamically generating a load priority queue based on the power demand prediction result of each load and the real-time capacity state of the UPS, and adjusting the power distribution strategy of the UPS to each load in real time; and acquiring working data of the UPS system under the current power distribution strategy, acquiring abnormal data based on the working data of the UPS system, and updating the load power distribution strategy according to the abnormal data. According to the invention, the energy efficiency of the UPS power distribution system is improved, the stability of the system is enhanced, and the output power distribution of the UPS is dynamically adjusted.

The invention relates to a power distribution network voltage partition control method and system based on a hierarchical K-means clustering algorithm, and belongs to the technical field of power distribution system voltage partition optimization. According to the technical scheme, power distribution network node parameters are collected in a self-adaptive partition mode, a node sensitivity coefficient and an eigenvector of an electrical distance are constructed, and then a K-means algorithm is used for fine region division; selecting a dominant node: solving a Jacobi matrix through load flow calculation, extracting a voltage sensitivity coefficient, and selecting a node with the maximum sensitivity as a dominant node in each partition; multi-objective optimization: constructing an optimization model with minimum network loss, minimum voltage deviation and highest voltage stability as objectives; and partition cooperative control: accessing wind power and photovoltaic power to the dominant node, adjusting reactive power output in real time according to an optimization result, and realizing partition autonomy and global cooperation. According to the invention, voltage fluctuation and out-of-limit are inhibited, system network loss is reduced, control efficiency and economy are improved, and the method is suitable for complex topology and high permeability scenes.

The invention discloses a power distribution system fault analysis method and system. The method comprises the steps of collecting operation related data of a power distribution system in real time through various sensors and intelligent metering equipment; preprocessing the collected operation related data to remove noise and interference signals, and establishing a multi-dimensional feature set of the real-time operation state of the power distribution system; extracting potential fault features from the multi-dimensional feature set by using a convolutional neural network, and generating a fault feature vector; performing time sequence analysis on the fault feature vector by using a recurrent neural network, and identifying a possible fault type in the current power distribution system; and in combination with the topological structure and the electrical model of the power distribution system, spatial positioning is performed on the identified fault type based on the graph neural network, and specific nodes of the fault and corresponding fault severity levels are output. According to the embodiment of the invention, the fault detection capability and response speed of the power distribution system can be remarkably improved, and the power distribution system is promoted to develop towards intelligentization and automation directions.

In an approach to a state of health for grid applications, a system includes one or more battery energy storage systems having a plurality of batteries; energy sources; power distribution systems; and computing devices. The computing devices are configured to: for each of the battery energy storage systems: receive battery parameters for each of the batteries from the battery energy storage systems; determine a lithium plating state, a solid electrolyte interface (SEI) thickness, and a dendrite length for each of the plurality of batteries; determine a battery state of health (SOH) for each of the batteries based on at least one of the lithium plating state, the SEI thickness, and the dendrite length; determine a battery charge profile to mitigate aging for each of batteries based on the SOH; and send updated battery parameters and control thresholds for each of batteries to each of the battery energy storage systems.

The embodiment of the invention provides a digital simulation modeling method and device of a tandem type hybrid electric propulsion system, computer equipment and a medium, and relates to the technical field of simulation modeling, and the method comprises the following steps: constructing a turboshaft prime mover model, constructing a generator model, connecting the turboshaft prime mover model and the generator model in series to generate a generator set, the power generation groups are connected in parallel to construct a turbine power generation system; constructing a propulsion system; constructing a battery energy storage system; constructing a power transmission and distribution system, and respectively connecting the power transmission and distribution system with a turbine power generation system, a propulsion system and a battery energy storage system; and constructing a comprehensive control and energy management system, and outputting a digital simulation modeling result through a turbine power generation system, a power transmission and distribution system and a battery energy storage system. According to the scheme, a simulation modeling method based on multi-physics field coupling double-power-source dynamic response and energy flow regulation and control provides reliable modeling technical support for engineering application of a tandem type hybrid electric propulsion system.

The invention relates to the technical field of electric energy quality monitoring, and discloses an electric energy quality monitoring method and system for a low-voltage power distribution system, which are used for acquiring parameter fluctuation information in a dynamic power grid environment and performing data quality evaluation and adaptive adjustment. According to the method, feature extraction and systematic deviation correction are performed on the acquired power grid operation data, a parameter change trend prediction model is constructed, and the potential influence of future short-term power grid parameter fluctuation on the operation stability is analyzed. According to the prediction result, the service influence level is evaluated, the quality monitoring report is generated, and the monitoring precision improvement scheme is determined. By updating the complex scene adaptation module, adaptation to different power grid operation environments is achieved. The method can effectively improve the accuracy and prediction capability of power grid operation state monitoring, and provides important support for safe and stable operation of a power grid.

The invention provides a charging pile cluster power coordination method, device and equipment and a storage medium, relates to the technical field of charging pile optimization, and is applied to a charging pile power distribution system which comprises a plurality of charging piles. The method comprises the following steps: acquiring current state data, historical use data and position data of each charging pile in different time periods, and determining corresponding priority weight data according to the position data and the historical use data; based on a preset prediction model, obtaining use probability data of the corresponding charging pile according to the historical use data and the corresponding current state data; obtaining corresponding power reference data according to the power grid dispatching plan data, the current state data and the use probability data; and obtaining a power adjustment strategy of each charging pile according to the current state data, the priority weight data and the power reference data based on a deep reinforcement learning model. According to the method, the prediction model and the deep reinforcement learning technology are combined, and intelligent and efficient power coordination is realized.

A device, method, and non-transitory computer readable medium for controlling a power distribution system includes an islanded microgrid and a control system. The islanded microgrid includes battery energy storage systems (BESSs) that operate as a primary energy source, and a decentralized consensus-based virtual synchronous generator (VSG). The control system simultaneously, emulates inertial response of a synchronous generator by the virtual synchronous generator during grid disruptions to regulate and stabilizes frequency of the islanded microgrid, and maintain consensus among the plurality of battery energy storage systems (BESSs).

The invention discloses a flood disaster scene-oriented urban power distribution network toughness evaluation method and system, and belongs to the technical field of power distribution network toughness evaluation, and the method comprises the steps: obtaining rainfall data, land utilization data, elevation data and the like, and inputting the data into a waterlogging simulation module; the waterlogging simulation module simulates rainfall runoff production and runoff convergence to generate ponding distribution; the disaster judgment module obtains the fault probability of the power distribution equipment and the line in combination with the power distribution equipment and line disaster fault model, and generates a system disaster scene under the flood disaster; the load reduction optimization module constructs a power distribution system load reduction optimization model, and takes the minimization of the total load reduction amount of the power distribution system as a target; and the system toughness evaluation module measures the overall toughness of the power distribution system in the flood disaster scene. According to the method, the overall toughness level is quantitatively evaluated based on the system load reduction amount, the node load importance degree and the ponding condition are combined to recognize the weak links of the system, reference is provided for differential reinforcement and operation and maintenance strategies, and subsequent waterlogging prevention planning and operation and maintenance management are guided.

The present application provides a decision-making method and system for emergency frequency control optimization in an off-grid process of a power distribution system, and relates to the technical field of frequency control of the power distribution system. An average system frequency response model of the power distribution system is established; a frequency deviation is approximated as a quadratic function under a reasonable assumption that an increase in active power generation of the system increases approximately linearly with time, to perform open-loop processing on the frequency response model, so as to obtain an open-loop model; decisions are made on control quantities of fast power control resources within the power distribution system, and an emergency frequency control optimization model of the power distribution system is established; and the emergency frequency control optimization model is solved to obtain a decision-making emergency control scheme with a minimum cost of emergency control measures.

The invention discloses a multi-mode self-learning diagnosis and early warning method and system for a power distribution system, and relates to the technical field of intelligent operation and maintenance of power systems. According to the method, a visible light image, an infrared thermal image, a sound signal, an environmental parameter and an electrical parameter of the power distribution equipment are collected through a multi-mode sensor, and time synchronization and feature extraction are carried out; multi-modal features are constructed into a hypergraph structure, and cross-modal feature fusion is realized by using a graph attention mechanism; adopting a strategy of combining self-supervised pre-training and supervised fine tuning to carry out multi-objective joint optimization on the fused features to obtain a self-learning diagnosis model; the system inputs multi-modal data in real time during operation, outputs an equipment operation state and a health degree index, and realizes early warning and fault alarm through threshold comparison. According to the method, deep fusion and adaptive learning of multi-source information can be realized, high-precision diagnosis, real-time early warning and online updating capabilities are realized, and the intelligence and safety of a power distribution system are remarkably improved.

The invention discloses a power distribution control method and device for an optical storage DC flexible power distribution system, and relates to the technical field of power distribution control methods, and the method comprises the steps: determining a power consumption path of each power distribution region based on a power load and a photovoltaic power generation path of each power distribution region, and an energy storage path corresponding to the optical storage DC flexible power distribution system; and the power distribution balance event of each power distribution area is determined according to each power consumption path, the power distribution level of each power distribution area and the power distribution control relationship among the power distribution areas, so that the accuracy of the power distribution balance event of each power distribution area is improved. Therefore, the dynamic restoration event of the power distribution area is determined based on the autonomous management and control system and the abnormal power distribution position of the power distribution area, and the flexible regulation and control event of the optical storage direct-current flexible power distribution system is determined based on each dynamic restoration event, the working process of the optical storage direct-current flexible power distribution system and the flexible management and control path. And the autonomous flexible regulation and control effect of the optical storage direct-current flexible power distribution system is ensured.

The invention relates to the technical field of power distribution automation operation and maintenance, in particular to a power distribution automation operation and maintenance method based on electric power big data. The method comprises the following steps: collecting and processing power distribution operation data, calling a fault feature rule set to analyze the power distribution operation data, and identifying and detecting a power distribution fault event; based on the electrical topological structure, the protection action information and the power distribution node on-off state of the current power distribution network, a fault feeder line and a fault section are identified, a switching value logic relation and a topological accessibility model are used for power distribution positioning of a fault event area, and a fault diagnosis result data set is output; and generating a fault isolation operation and maintenance strategy and an overhaul task priority list by using an operation and maintenance scheduling model based on the fault diagnosis result data set and the load transfer capacity, the field operation capacity and the historical overhaul resource distribution information of the power distribution station. According to the method, fault diagnosis and an intelligent scheduling mechanism are fused, and the fault response speed and the operation and maintenance cooperation efficiency of the power distribution system under complex working conditions are improved.

The invention aims to provide an on-line monitoring device and a detection method for an electrical loop, and relates to a method and a system for dynamically calculating a conductor or contact resistance value and predicting a conductor or connection point degradation risk by acquiring current and voltage data of a conductor or an electrical connection point in real time, and a method and a system for dynamically analyzing a resistance change trend to determine a conductor or connection point degradation risk. Early warning of the health state of the conductor or the connection point is achieved, and the electrical fire prevention and control capability can be improved. The system comprises an electrical loop, a current detection module and a voltage detection module, the current detection module is arranged in the electrical loop to be detected, the voltage detection module is connected to the two ends of the electrical loop, and the current detection module and the voltage detection module are both in communication connection with a server through a data processing module and a networking module. The method is applied to the technical field of AC / DC power supply and distribution system electrical equipment / line resistance and electrical connection point contact state monitoring.

The invention relates to the field of power distribution system simulation, in particular to a power distribution and micro-grid coordination wide-area balance regulation and control method and system in a multi-micro-grid access scene, and the method comprises the steps: carrying out the cluster division of a plurality of micro-grids based on the electrical coupling degree and net power between the micro-grids; using a pre-constructed multi-energy coupling source load prediction model to cluster resources of an area where the micro-grid is located, and performing load prediction on the divided clusters based on the clustered resources to obtain a group composed of the clusters, the resources and corresponding loads; based on the group, a target cascade method is adopted to solve a pre-constructed zone area or micro-grid layer optimization model, a feeder line level optimization model and a region layer optimization model to realize dispatching optimization of the power distribution network and the micro-grid; by constructing the multi-layer optimization model, the power exchange cost, the power generation cost and the environment cost between the micro-grid and the power distribution network can be optimized, and economic operation of the system is achieved.

Accurate real-time monitoring of distribution networks becomes increasingly pivotal to ensure reliable and optimal operation of grid. Existing joint parameter-state estimation techniques predominantly focus on transmission systems, making their applicability to distribution systems challenging due to variations in available input data. Furthermore, the joint estimation techniques significantly suffer from computational complexity. Present disclosure provides a method and a system for personalized multi-subject text to image generation. The system first uses lossy Distflow equations and an inverse Physics-Informed Neural Network (iPINN) architecture for learning network voltage dynamics, drift matrix and network bus voltages from real-time bus power injection data and historical voltage data. Thereafter, the system determines a plurality of line parameters from the learnt drift matrix using a least-square optimization technique. Finally, the system calculates line power flows and line currents using the lossy Distflow equations.

The invention relates to the technical field of electric energy distribution, in particular to an intelligent power distribution system and a power distribution method.According to the intelligent power distribution system and method, power flow paths and load density distribution are defined by collecting load distribution values of nodes of a power distribution network and calculating power flow, line transmission loss and load value density of load transmission paths among the nodes; according to the method, a data foundation is laid for subsequent dynamic adjustment, partition node power requirements and transmission path characteristics are integrated by adopting an alternating direction multiplier method, a dynamic partition model is established, a global problem is decomposed into a local optimization sub-problem in a partition optimization process, partition boundary adjustment and power balanced distribution are realized through iterative calculation, and a partition node is optimized. A greedy algorithm is adopted to screen load priorities and demanded quantities, the electric energy guarantee capability of high-priority loads is improved, through adjustment of a voltage offset range and dynamic adjustment of reactive power compensation equipment, the influence of voltage fluctuation on power balance between partitions is effectively reduced, the voltage stability is improved, and the energy consumption and the power loss are reduced.

The invention provides a ship power battery state monitoring method and system based on multi-sensor data fusion, and relates to the technical field of batteries, and the method comprises the steps: interactively obtaining multi-mode monitoring data of a ship power battery in a ship matched intelligent power distribution system; generating a mapping confidence score by using the expected output prediction of the reliable twin of the sensor and the residual error of the multi-modal monitoring data; the method comprises the following steps of: after preprocessing multi-modal monitoring data, respectively extracting transient, trend and accumulation characteristics based on a multi-time scale sliding window; inputting the multi-modal feature set into a hierarchical fusion model, executing coupling fusion analysis in a module layer and a cabin ship layer, and outputting comprehensive operation state features; constructing an abnormal probability value according to a multi-dimensional abnormal index calculation result and the mapping confidence score; and monitoring and managing the state of the ship power battery according to the abnormal probability value. According to the invention, the technical problem of low monitoring efficiency of the state of the ship power battery in the prior art can be solved.

The invention discloses a two-stage fault recovery method for improving the elasticity of a power distribution system, and the method comprises the steps: constructing a typhoon space-time evolution model, and generating a prediction fault scene; simulating the distribution line in the predicted fault scene by using a Monte Carlo simulation method to generate a plurality of fault scenes; based on the information entropy value of the fault scene and the fault multiple number, an uncertainty set is constructed, and then a robust optimization model is constructed; solving the robust optimization model, and determining a pre-layout scheme of the mobile energy storage system and the static var compensator in a pre-disaster worst fault scene; a multi-source collaborative post-disaster multi-period multi-target fault recovery model is constructed; the fault recovery model realizes recovery of a power-loss load and a fault line of a power distribution system through network reconstruction and optimal scheduling of a mobile energy storage system, a static var compensator, a maintenance team and an electric vehicle. According to the invention, the overall elasticity of the power distribution system is obviously improved, the capability of resisting disasters is enhanced, and the capability of rapidly recovering power supply is also improved.

The invention discloses a power distribution system planning operation collaborative optimization method integrated with multi-flexibility resources. Comprising the steps of obtaining a reference data set of a power distribution system, and fitting wind power and photovoltaic edge distribution to construct a joint probability model; and fitting the relationship between the energy storage discharge depth and the capacity attenuation, establishing a full life cycle cost model, and outputting equivalent operation cost parameters changing along with the operation strategy. Based on wind-solar combined distribution parameters, operation cost parameters and load electricity price prediction, a multi-temporal-spatial-scale scene set is generated by adopting Latin hypercube sampling, and a typical scene is obtained through clustering and scene reduction. And constructing a two-stage robust capacity planning model in combination with the typical scene and the equivalent operation cost. The model is solved through a main-sub problem decomposition coordination strategy, an installation and capacity configuration scheme is obtained, and integrated collaborative optimization of long-term planning and short-term operation of the power distribution system is achieved. According to the invention, the safety, economy and flexibility of the power distribution system in a high-volatility environment can be effectively improved.

The invention belongs to the technical field of smart power grids, and discloses an anti-explosion power distribution control system and control method based on the Internet of Things, and the method comprises the steps: obtaining the working parameters and environment data of a target power distribution network, and constructing an anti-explosion safety feature model based on the working parameters and environment data; performing electromagnetic interference sensitivity analysis based on the constructed explosion-proof safety feature model to obtain corresponding electromagnetic sensitive nodes, performing anti-interference analysis on the electromagnetic sensitive nodes, and updating the explosion-proof safety feature model based on the electromagnetic sensitive nodes to obtain a corresponding power distribution protection model; inputting the obtained working parameters into a power distribution protection model to obtain corresponding power distribution operation state information, and performing power grid topology optimization based on the corresponding power distribution operation state information to obtain a corresponding power distribution regulation and control strategy; monitoring the state of the power distribution network based on the power distribution regulation and control strategy, and generating an explosion-proof power distribution safety evaluation result; the safety and the stability of the power distribution system are remarkably improved.