1932 results about "Electricity distribution systems" patented technology

The present invention relates to a production and energy system based on a new energy-powered submerged arc furnace, and a related control method. The production and energy system comprises a power transmission and distribution system, a renewable energy power generation system, an energy storage system, and a submerged arc furnace-based production system. The power transmission and distribution system is respectively connected to the renewable energy power generation system, the energy storage system, and the submerged arc furnace-based production system. The production and energy system further comprises an energy control system. The energy control system comprises: an integrated regulation and control system used for performing integrated regulation and control on the production and energy system by means of the power transmission and distribution system; a renewable energy power generation control system used for controlling operation of the renewable energy power generation system; an energy storage control system used for controlling operation of the energy storage system; and a submerged arc furnace-based production control system used for controlling operation of the submerged arc furnace-based production system. Compared with the prior art, the present invention has the advantages of optimizing energy utilization, achieving environmental protection and low-carbon development, improving the stability and reliability of the energy system, etc.

The invention discloses a power distribution equipment state monitoring system and monitoring method based on the Internet of Things technology, and relates to the technical field of power distribution equipment monitoring, the system comprises the following components: a sound acquisition module, a data transmission module, a data processing center and an early warning display module; by combining the Internet of Things technology, the expert system and the feature engineering technology, high-precision acquisition and analysis of operation sound signals of the power distribution equipment are realized, and by constructing the fault voiceprint feature library, the system can quickly recognize and match equipment fault features, so that early warning is given out at the initial stage of the fault, and the fault early warning efficiency is improved. In addition, due to the application of the cross-equipment associated fault prediction model and the fault propagation prediction model, the system can predict the propagation conditions of cascading faults and system-level faults, more comprehensive fault information is provided for operation and maintenance personnel, prevention measures can be taken in advance, and the fault monitoring accuracy and timeliness are improved. The influence of faults on a power distribution system is reduced.

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 power system false data injection attack detection method and system. Measurement data of a power distribution system are acquired; constructing an attack sequence, and injecting the constructed attack sequence into the obtained measurement data to simulate a false data attack; constructing a false data injection attack detection model based on the expansion causal convolution and the recurrent neural network to analyze the state change of the power distribution system; and judging an attack behavior according to the analyzed state of the power distribution system. According to the method, time sequence data can be processed, the long-term dependency relationship and the complex mode can be captured, and the response capability to the complex attack mode can be improved, so that the false data injection attack can be effectively detected and prevented, and the safety and reliability of the power distribution system can be maintained.

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.

The invention relates to the technical field of power distribution system reliability analysis, in particular to a power distribution system reliability analysis method and system. The method comprises the following steps: performing multi-dimensional data acquisition on a power distribution system through a sensor network, and performing multi-dimensional data fusion to obtain multi-dimensional associated data; performing comprehensive operation data set construction on the multi-dimensional associated data to obtain a comprehensive operation data set; performing time sequence data segmentation according to the comprehensive operation data set to obtain a rapid fluctuation characteristic sequence and a slow change long-term trend sequence; performing time sequence decomposition on the rapid fluctuation characteristic sequence and the slow change long-term trend sequence to obtain high-frequency fluctuation characteristic data and long-term trend characteristic data; and performing feature component analysis on the high-frequency fluctuation feature data and the long-term trend feature data to obtain a multi-scale feature set. Through risk factor correlation analysis and reliability network model construction, the reliability analysis precision of the power distribution system is improved.

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 invention discloses an active power distribution network two-stage island division method and system considering flexible resource support. The method comprises the following steps: establishing a first resource allocation model considering energy storage and controllable load, the first resource allocation model comprises energy storage battery charging and discharging upper and lower limit constraints, an energy storage battery degradation cost model, a controllable load model and a controllable load related user protocol; obtaining parameter data of a target power distribution system, wherein the parameter data comprises a line parameter, a load level, a load level, a network topology connection relationship, a system operation voltage level and branch current limitation, a system fault position, a reference voltage and a reference power initial value; and according to the parameter data, establishing a mathematical model for two-stage island power supply recovery based on a first resource allocation model. The method for solving the island is simple and convenient, the island recovery amount can achieve the optimal recovery effect, meanwhile, the search time is greatly shortened, the solving efficiency is higher, and the rapid power supply recovery capacity of the power distribution network is 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 relates to the field of short-term load prediction and power dispatching control of a power system, in particular to an energy output optimization dispatching method and system considering a random source load virtual power plant, and designs a virtual power plant double-layer optimization dispatching model. The lower-layer model constructs a user load prediction model of an improved Transform, and then a renewable energy output model is established by using a scene generation method; the upper layer model takes the power generation cost minimization of the wind-light storage and combustion virtual power plant as a target, considers constraint conditions such as gas turbine output power, ramp rate, energy storage charging and discharging power, electricity storage quantity and power balance, and proposes a single guide target function comparison algorithm considering random source load to carry out optimization solution on a virtual power plant optimization scheduling target function; and planning and deciding the output of each energy source in the next 24 hours. Experiments show that the new energy consumption level can be remarkably improved under the random source load condition, and better economic benefits are obtained while stable operation of a power distribution system is promoted.

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 embodiment of the invention discloses a power distribution system operation optimization method and a related device. The method comprises the following steps: determining meteorological data in a prediction time period and an electrical load of target equipment in a power distribution system; determining a dynamic current threshold value of the target equipment according to the meteorological data and the electrical load; constructing a multi-objective planning model according to the plurality of optimization objectives; determining a new energy consumption strategy according to the dynamic current threshold; according to the multi-target planning model and the new energy consumption strategy, determining an operation strategy of the power distribution system; importing an operation strategy of the power distribution system into the electromagnetic transient simulation model, and performing field-circuit coupling verification to obtain a verification result; and adjusting the multi-target planning model according to the verification result until the verification result indicates that the power distribution system is in a safe operation state. In this way, the problem that static threshold constraint conservative and dynamic threshold technology collaborative optimization capability is insufficient is solved, and the absorption capability and dynamic safety margin of a power distribution system in a new energy high-permeability scene are improved.

The invention discloses a power distribution system fault prediction system and prediction method based on big data analysis, and relates to the technical field of power distribution fault prediction, and the system comprises a data collection module which is used for collecting the real-time operation data of a sensor in a power distribution system; the data storage module is used for adopting a data storage technology; the data preprocessing module is used for carrying out primary processing on the collected data; the feature extraction module is used for applying a data analysis and machine learning algorithm; the big data analysis module is used for performing a learning technology on the extracted features; and the fault prediction and notification module is used for analyzing the result of the model. According to the invention, after the data acquisition module collects the real-time operation data from the sensor in the power distribution system, the data preprocessing module carries out processing operation based on the collected data, so that the interference of errors and inconsistency in the original data on subsequent analysis is avoided, and the accuracy starting point of the whole fault prediction process is effectively improved.

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 embodiment of the invention discloses a multi-virtual power plant energy optimization method and device based on energy-carbon sharing. The method comprises the steps of establishing a master-slave game architecture of a power distribution system operator and each virtual power plant based on a transaction electricity price and a transaction carbon price of the power distribution system operator, and a transaction electricity quantity, a transaction carbon quota and equipment output of each virtual power plant; a dynamic pricing model for maximizing the income of a power distribution system operator is constructed based on a master-slave game architecture, an energy management model for minimizing the operation cost of the virtual power plant is constructed based on the master-slave game architecture, and a master-slave game double-layer optimization model for energy-carbon sharing of the multiple virtual power plants is determined based on the dynamic pricing model and the energy management model; and equivalently converting the master-slave game double-layer optimization model into a single-layer optimization model based on a Carlo-demander-Kuhn-Tuck condition, and solving the single-layer optimization model to obtain a target energy management strategy of each virtual power plant, thereby giving consideration to economic benefits and carbon emission reduction.

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 discloses a primary and secondary collaborative planning method based on a novel power distribution system, and relates to the technical field of power system optimization, and the method comprises the following specific steps: constructing a power distribution network model and fault feature analysis, designing an adaptive protection mechanism, realizing a rapid fault processing mechanism, and performing primary and secondary system collaborative planning. And implementing and verifying: implementing a planning method in the power distribution network, installing and debugging related equipment, carrying out field test, and verifying the effectiveness of an adaptive protection mechanism and a fault rapid processing mechanism, the running state of the power distribution network is monitored in real time, and the protection constant value is automatically adjusted according to the monitored fault characteristic parameters, so that the reliability of the power distribution network is improved. Therefore, the adaptive capacity of the system to a complex and changeable operation environment is remarkably improved, the dynamic adjustment mechanism can quickly respond to dynamic factors of new energy output fluctuation and load change, it is ensured that a protection strategy is always matched with the operation state of the system, and the problem of protection maloperation or operation refusal caused by rigid setting of a fixed value is effectively prevented.

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 provides a coal preparation plant energy storage system and method based on digital twinning, and the system comprises a hybrid energy storage system, a battery management system, a high-voltage DC protection system, a pre-charging / discharging loop, a high-voltage AC power distribution system, a centralized PCS cluster, and a power electronic interface of a power grid. And the battery energy storage array is connected with power consumption equipment in the coal preparation plant. Constructing a digital twinborn model of the power consumption equipment, obtaining a scheduling plan of the coal preparation plant, determining the power consumption equipment required by the technological process under the current scheduling plan, and simulating the workload of all the power consumption equipment under the current scheduling plan through the digital twinborn model; and according to the workload of the power consumption equipment, predicting the electric quantity W required by the peak value of the electricity price under the current production scheduling plan, and configuring the corresponding energy storage capacity. Through full-process efficiency management and control, production efficiency is improved, an electric energy storage system is established, and an optimal power storage and discharge planning plan is given through a digital twin technology and local peak-valley electricity prices, so that the unit power consumption cost is reduced.

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.