8645 results about "Low voltage" patented technology

The invention discloses a high and low voltage power distribution cabinet operation monitoring system based on data analysis, and relates to the technical field of power distribution cabinet operation monitoring, the system comprises an operation monitoring platform, the operation monitoring platform is in communication connection with a data acquisition module, a fault risk analysis module, a fault risk diagnosis module, a fault positioning module and a monitoring early warning module, the modules are in electric signal connection; the data acquisition module is used for collecting and preprocessing power distribution equipment data of the high-low voltage power distribution cabinet. According to the invention, through integration of the data acquisition module, the fault risk analysis module, the diagnosis module and the positioning module, comprehensive monitoring of the operation state of the high-low voltage power distribution cabinet is realized, a fault risk diagnosis model is established by using a deep learning algorithm, and potential fault risks are accurately identified in combination with real-time data and historical cases, so that the accuracy and timeliness of early warning are significantly improved, and the working efficiency of the high-low voltage power distribution cabinet is improved. And operation and maintenance personnel can intervene in advance according to the early warning information and take preventive measures, thereby effectively avoiding faults and ensuring stable operation of the power system.

The invention discloses an intelligent centralized control and protection integrated system for a high-low voltage switch cabinet, relates to the technical field of electric power automation, and solves the problems that an existing centralized control system is lagged in data processing, incompatible in communication protocol and difficult in fault positioning. Running parameters and equipment state parameters of each high-low voltage switch cabinet are monitored in real time through a distributed data acquisition module; different communication protocols are automatically identified and adapted through the communication transmission module; real-time data analysis, fault early warning and state evaluation are carried out through a deep analysis module, and an early warning mechanism is triggered when a potential fault is early warned; the fault diagnosis module is used for quickly positioning a fault source and generating a maintenance suggestion, and the remote interaction module is used for providing a graphical user interface, displaying the real-time state of the system and allowing a user to remotely monitor and operate; according to the invention, the performance, compatibility and usability of the system are obviously improved.

Systems and apparatus are provided for a high-power microwave sensor using an unmanned aerial vehicle. The unmanned aerial vehicle may include a central body, at least one electric motor, and a barometric pressure feedthrough. The central body may include a first enclosure housing a plurality of low voltage components, a voltage feedthrough connector, and a second enclosure housing a plurality of high voltage components. The low voltage components may include a first signal processing system, a first radio transceiver, a flight controller, a second signal processing system, a second radio transceiver, and a navigation system. The high voltage components may include a plurality of electronic speed controllers, a power distribution module, an input power interface, and a plurality of high power filters. The components of each enclosure may be segregated such that the high voltage components do not create electromagnetic interference with the low voltage components.

The invention discloses a direct-current arc fault diagnosis method and device with adaptive capacity. The method comprises the following steps: 1) collecting a current alternating-current component when a current direct-current system normally works; 2) extracting time-frequency domain characteristics of a current AC component, wherein the time-frequency domain characteristics comprise a current peak-to-peak value, a standard deviation and an amplitude reconstruction harmonic power sum; 3) performing multi-time-frequency-domain feature fusion based on mahalanobis distance to obtain arc detection features; 4) calculating an arc fault judgment threshold value based on a box plot method; 5) collecting a current AC component in real time to calculate a Mahalanobis distance, comparing the Mahalanobis distance with an arc fault determination threshold, and recording an arc event; the method has the advantages that the system adaptability is high, the detection rate is high, the false alarm rate is low, and the method can be widely applied to high-voltage and low-voltage direct-current power distribution systems such as airplanes, vehicles and ships.

The invention provides a test method and device for a motor active short-circuit relay, and a storage medium. The method includes the steps: performing the zero speed detection of a motor after a motor controller completes a low-voltage power-on operation, wherein when the motor controller is powered down, a first relay and a second relay are both switched on; controlling the second relay to be turned on if the motor passes the zero speed detection, and injecting a first excitation signal at the control ends of a first phase winding and a third phase winding through the motor controller; performing injection detection of the first excitation signal to determine whether the first excitation signal is successfully injected or not; controlling the first relay to be turned on if the first excitation signal is successfully injected, and obtaining a voltage across two ends of the first relay; and judging whether the power-on test of the first relay is successful or not according to the voltage across two ends of the first relay. The method can realize the turn-on test of the short-circuit relay, and ensures the reliability of the active short-circuit function of the vehicle motor duringdriving.

The invention relates to the technical field of power distribution cabinet detection, and discloses an intelligent detection system and method for a high-low voltage power distribution cabinet, and the system comprises a data collection module, a feature extraction module, a network construction and updating module, a fault positioning module, a positioning map generation module, and a self-healing control module. The method comprises the following steps: generating a multi-physical field coupling data set by synchronously collecting electromagnetic radiation spectrum and cabinet vibration waveform, performing time-frequency domain conjoint analysis to extract fault feature vectors, constructing and dynamically updating a fault propagation network, identifying key fault sources by combining betweenness centrality and historical case matching, and generating a fault positioning map; accurate self-healing control is realized by applying reverse electromagnetic pulse and adjusting contact pressure based on the atlas; according to the invention, the problems of low positioning precision and mechanical self-healing control means during detection of the high-low voltage power distribution cabinet are solved, and the fault detection efficiency and reliability are significantly improved.

The invention relates to the technical field of electric power system safety early warning, and discloses a fault risk sensing early warning method for a high-low voltage switchgear assembly, and the method carries out the data preprocessing and feature extraction through collecting the state monitoring data, environmental parameters and basic attribute information of a device in historical operation. And based on the feature data sets, constructing a fault risk prediction model to predict the fault risk probability of the equipment in a period of time in the future, obtaining the operation state data and environmental parameters of the equipment in real time, and inputting the prediction model to obtain the fault risk probability. Meanwhile, the equipment is monitored in real time, original monitoring data is cleaned, abnormal values are removed, real-time monitoring data is compared with prediction data, whether the difference exceeds a threshold value or not is judged according to a preset risk threshold value, and risk points are marked. And evaluating the equipment fault risk according to the risk point and the evaluation strategy, and sending a result to related personnel to take prevention measures.

A system includes: an AC-DC converter; and a DC-DC converter, the DC-DC converter including: a first high voltage buck-boost converter having a secondary side connectable to a first high voltage battery; a second high voltage buck-boost converter having a secondary side connectable to a second high voltage battery; a first low voltage buck-boost converter having a secondary side connectable to a first low voltage battery; a second low voltage buck-boost converter having a secondary side connectable to a second low voltage battery; and one or more transformers having a primary side connected to the AC-DC converter and a secondary side connected to each of a primary side of the first high voltage buck-boost converter, a primary side of the second high voltage buck-boost converter, a primary side of the first low voltage buck-boost converter, and a primary side of the second low voltage buck-boost converter.

The present invention relates to the technical field of low-voltage electrical appliances, and discloses an intelligent safety protection and fault prevention method for low-voltage electrical appliances, including: obtaining the working state parameters of the target low-voltage electrical appliance, performing filtering processing, obtaining accurate working state parameters, inputting the accurate working state parameters into a fault analysis model, obtaining a fault analysis result, and if the fault analysis result is an operating fault, generating a safety protection scheme based on the fault type and the working state parameters. By implementing the present invention, a variety of protection strategies are adopted to comprehensively reduce the risk of functional failure caused by faults of intelligent low-voltage electrical appliances, extend the normal operation time of the equipment, and solve the problem in the related technology that the existing protection methods are difficult to effectively monitor and prevent these emerging faults due to the unique fault modes caused by the integration of multiple advanced modules in intelligent low-voltage electrical appliances.

The present disclosure provides a method and device for calculating fault measurement impedance of a hybrid-connected grid-following and grid-forming wind power system. The method includes: obtaining characteristics of the grid-following and grid-forming converters and a corresponding low voltage ride-through control strategy; establishing an equivalent circuit under a corresponding fault state; conducting a simplified analysis on the wind power system to obtain an equivalent network diagram; obtaining a sub-circuit diagram of each power source excitation acting alone; obtaining short-circuit currents on both sides of the corresponding system and a grid connection point voltage; superimposing to obtain total short-circuit current on both sides of the wind power system and total grid connection point voltage; and obtaining a measurement impedance at a protection installation location on the new energy source side. The method can accurately calculate the measurement impedance value at the protection installation location after the wind power system has fault.

The invention discloses an anti-fracture low-voltage power cable, and relates to the technical field of low-voltage cables, the anti-fracture low-voltage power cable comprises three core bodies, the surfaces of the three core bodies are all sleeved with shielding layers, the surfaces of the shielding layers are wrapped with insulating layers, the outer sides of the three core bodies are sleeved with an inner protection layer, the surface of the inner protection layer is sleeved with a thermal insulation layer, and the thermal insulation layer is wrapped with an outer protection layer. The outer side of the thermal insulation layer is sleeved with an outer protection layer, the surface of the outer protection layer is provided with a sliding protection mechanism, and the inner side of the outer protection layer is provided with a reinforcing anti-breaking mechanism in an embedded manner. And when the cable slides, the outer protection layer is not rubbed with the ground, so that the outer protection layer of the cable is prevented from being rubbed and scraped to influence subsequent normal use, the cable is protected to a certain degree, and impurities such as dust and soil adhered to the surface of the cable in the cable transportation and laying process can be scraped.

The invention discloses a high-low voltage switch cabinet feeder fault positioning method and system based on transient traveling waves, and belongs to the technical field of power system fault detection and positioning, and the method comprises the steps: synchronously collecting electric and acoustic multi-mode signals, and generating a weighted transient synchronization feature matrix; performing time-frequency transformation and feedback optimization on the matrix, and outputting a multi-scale time-frequency feature set; analyzing the feature set by using an integrated learning network, and outputting a layered preliminary positioning result; convergence to an accurate fault section is carried out through iteration calibration; and finally, fusing multi-model calculation and outputting a comprehensive fault positioning report. According to the method, a technical path of combining multi-modal signal fusion and a physical model is adopted, convergence from fuzzy region division to an accurate position can be realized in stages, and the accuracy, the speed and the anti-interference capability of switch cabinet feeder line fault positioning are remarkably improved.

The invention relates to the technical field of intelligent power distribution system state monitoring, in particular to a cable connection state online monitoring method for a low-voltage cable branch box, which comprises the following steps of: applying a disturbance excitation signal to a connection node of the cable branch box, and acquiring transient voltage, current and phase response parameters of the node in different excitation periods; establishing a mapping relation between the node electrical characteristics and the connection state; performing dynamic reference calibration on the acquired signals based on a multi-node space-time coupling matrix to form an adaptive judgment reference of electrical coupling between nodes; a connection degradation sensitive index is extracted through feature sequence differential calculation, a connection state quantitative evaluation result is generated, and real-time updating and anomaly recognition are carried out according to the state change trend; according to the method, the problems of misjudgment and delay caused by a monitoring mode depending on indirect parameters such as temperature and current are solved, high environmental adaptability and degradation identification precision are achieved, and the operation safety and monitoring reliability of the low-voltage power distribution system are greatly improved.

The invention discloses a source load distributed scheduling system based on medium and low voltage power distribution network carbon flow tracking, and relates to the technical field of power distribution network scheduling. The source-load distributed scheduling system comprises a data acquisition module, a carbon flow tracking module, a load prediction module, a distributed power source scheduling module, a source-load matching module, a collaborative scheduling module and a carbon emission monitoring module, and all the modules are connected through electric signals. The data acquisition module is used for collecting operation data of each node and branch in the middle and low voltage power distribution network. By monitoring the carbon emission condition of each distributed power supply and combining load prediction and a source-load matching strategy, a low-carbon scheduling scheme is accurately formulated, output adjustment of the power supply is considered, load reduction and transfer are also considered, collaborative optimization of the source side and the load side is realized, and the scheduling efficiency of the distributed power supply can be improved according to the carbon emission intensity of each power supply. And the overall carbon emission of the power distribution network is effectively reduced while the load requirement is met.

The invention discloses a low-voltage cable branch box with protection structures at wire inlets, and belongs to the technical field of cable branch boxes, the low-voltage cable branch box comprises a box body, the interior of the box body is fixedly connected with a mounting rack for mounting electrical appliance elements through bolts, the bottom of the box body is provided with a plurality of wire inlets distributed in a linear array, and the wire inlets are arranged in the box body. The bottom of the inner wall of the box body is fixedly connected with a fixing frame corresponding to each wire inlet, and the front and back surfaces of the fixing frame are movably provided with plugging plates in a penetrating manner. The plugging plate is arranged to plug the wire inlet, and the gap sealing mechanism is arranged to fill and seal the gap between the cable and the plugging plate, so that external humid gas cannot enter the box body from the wire inlet, and when the sealing door of the box body is in a closed state, the whole branch box can be in a totally closed state; dust or humid gas in external air is prevented from entering the branch box, and electronic components in the branch box are well protected.

The invention discloses a middle and low voltage distribution network cooperative regulation and control method and device based on reliability evaluation, and belongs to the technical field of power system optimization. According to the method, a zone area in the low-voltage power distribution network is projected into a feasible space to obtain a feasible region, flexible resources such as distributed photovoltaic, electric heating loads and distributed energy storage of the zone area of the low-voltage power distribution network are projected and aggregated into constraint conditions of virtual load nodes in the medium-voltage power distribution network, and a medium-voltage power distribution network model and a corresponding objective function are constructed based on the constraint conditions. And obtaining a switching action sequence corresponding to the medium-voltage power distribution network after solving the objective function. According to the method, a medium and low voltage power distribution network cooperative reliability improvement strategy considering the virtual load nodes is provided, all flexible resources of a low voltage power distribution network zone area are represented through the virtual load nodes, and the variable dimension and the calculation complexity of medium and low voltage power distribution network reliability evaluation are reduced; the linkage between the flexible resources of the transformer area and the medium-voltage power distribution network switch is realized, and the reliability of the medium-low voltage power distribution network is effectively improved.

The invention relates to the technical field of cable preparation, in particular to an extruded insulation low-voltage power cable and a preparation method thereof.The preparation method comprises the steps that metal wires are twisted into a conductor according to preset twisting parameters, and the conductor is preprocessed; extruding an insulating layer on the surface of the pretreated conductor by using a screw extruder to obtain an insulated wire core; monitoring the diameter of the insulated wire core in real time by using a laser diameter measuring instrument, and determining the fluctuation characteristic type of the diameter of the wire core under a first preset condition; obtaining the eccentricity of the insulating layer and the void ratio between the insulating layer and the conductor; judging the qualification of the extrusion process according to the extrusion comprehensive quality index; under the condition that the extrusion process is unqualified, the qualification of the extrusion process is secondarily judged according to the insulation performance evaluation value; under the condition that the extrusion process is judged to be unqualified for the second time, an adjustment strategy of the extrusion process is determined; and after the insulated wire cores qualified in the extrusion process are twisted into a cable, an outer protective sleeve is extruded. The production efficiency and the product stability of the cable are improved.

An automotive power system includes an AC / DC power converter, a transformer, a switching bridge connected between the AC / DC power converter and transformer, and a switch bank connected with a secondary side of the transformer. The switch bank connects the secondary side between an electric machine and another switching bridge such that the electric machine, first switching bridge, transformer, and second switching bridge form an isolated DC / DC power converter. The system further includes one or more switches configured to directly connect the traction battery between the AC / DC power converter and second switching bridge.

The invention relates to a low-voltage motor insulation resistance online monitoring and early warning method, system and device and a medium. The method comprises the following steps: firstly, acquiring multi-dimensional operation data through a data acquisition link to form an original monitoring data set; preprocessing the original monitoring data set, and focusing core information through dimension reduction processing to obtain a key parameter set; and then inputting the key parameter set into a dynamic correlation model constructed based on a long short-term memory network, and outputting a prediction result of the variation trend of the insulation resistance value along with time and the deterioration degree quantification. And finally, carrying out early warning analysis based on a prediction result, and generating early warning fault features in combination with a real degradation judgment process. According to the method, the insulation resistance trend and the degradation degree are accurately predicted, the defect of insufficient real-time performance of off-line detection is overcome, the accuracy and the pertinence of fault early warning are improved, and equipment shutdown and safety risks caused by insulation faults are effectively reduced.

The invention discloses an intelligent dehumidification and heat dissipation type high-low voltage switch cabinet, and belongs to the technical field of switch cabinets, the intelligent dehumidification and heat dissipation type high-low voltage switch cabinet comprises a cabinet body, a sealing strip is fixedly installed on the front side of the cabinet body, a sealing cabinet door is hinged to the front side of the cabinet body, and a temperature sensor, a humidity sensor, a controller and a control assembly are arranged in the cabinet body; a ventilation assembly, a condensation mechanism, a water collection mechanism and a heat exchange mechanism are sequentially arranged on one side of the cabinet body from top to bottom, and a ventilation assembly is arranged at the bottom of the other side of the cabinet body. Forced ventilation can be achieved through the arranged ventilation mechanism, the ventilation speed can be adjusted according to the temperature, the flow direction of air in the switch cabinet can be changed according to needs, uniform and controllable heat dissipation is achieved, heat dissipation is achieved while dehumidification is achieved through the arranged condensation mechanism, heat dissipation work is further conducted through condensate water, and the dehumidification and heat dissipation effect is improved.

A system includes: an alternating current (AC) to direct current (DC) converter (AC-DC converter), the AC-DC converter connectable to a line voltage; and a DC to DC converter (DC-DC converter) connected to the AC-DC converter, the DC-DC converter including: a high voltage buck-boost converter having a secondary side connectable to a high voltage battery; a low voltage buck-boost converter having a secondary side connectable to a low voltage battery; and one or more transformers having a primary side connected to the AC-DC converter, a secondary side connected to a primary side of the high voltage buck-boost converter, and a tertiary side connected to a primary side of the low voltage buck-boost converter.

The invention discloses a new energy voltage ride-through parameter optimization method considering polymorphic voltage stability constraint, a storage medium and equipment, and belongs to the technical field of power system safety and stability improvement. In order to solve the problem that an existing new energy voltage ride-through parameter optimization method is only suitable for a single fault scene and only aims at a voltage stable form to optimize a new energy voltage ride-through parameter, the invention provides a new energy voltage ride-through parameter optimization method. Based on the dynamic characteristics of the new energy during the power grid fault period, the new energy general control model is established so as to determine the dominant control parameters influencing the dynamic characteristics of the new energy during the high / low voltage penetration period, the influence of the dominant control parameters on the voltage stability under different faults is considered, and the voltage regulation capability and the power regulation cost of the new energy are considered. A new energy voltage ride-through parameter optimization model considering polymorphic voltage stability constraints is established, and the optimization model is solved by adopting a particle swarm optimization algorithm. The method is used for voltage ride-through parameter optimization of new energy.

The invention discloses a multi-new energy station low voltage ride through control parameter coordinated optimization method, system, device and medium, and the method comprises the steps: evaluating the coupling influence degree of the reactive power change of each new energy station on the grid-connected point voltage of other new energy stations in a target region; obtaining the reactive voltage influence coupling degree index value of the grid-connected point of each new energy station; setting the value range of the reactive current proportionality coefficient in the low voltage ride through control of each new energy station based on the reactive voltage influence coupling degree index value of the grid-connected point of each new energy station; and within the value range of the reactive current proportionality coefficient in the low-voltage ride-through control of each new energy station, performing coordinated optimization on the reactive current proportionality coefficient in the low-voltage ride-through control of each new energy station. Compared with the prior art, the overall deviation of the grid-connected point voltage of the multiple new energy stations can be reduced, and the voltage stability of the power grid is improved.

The invention relates to the technical field of fault detection, in particular to a low-voltage distribution network electric leakage fault detection method and system, and the method comprises the steps: obtaining a residual current and zero-sequence current data set according to the three-phase current data and neutral current data of a low-voltage distribution network; performing opening and closing operation on the residual current and zero-sequence current data set by using a mathematical morphology method to obtain current signal local-global feature data; obtaining a leakage current change signal based on the current signal local-global feature data; based on a sparrow optimization algorithm fusing a sine and cosine search strategy and a Cauchy variation mechanism, constructing a low-voltage distribution network electric leakage fault detection model; and based on the current change signal, performing fault identification by using a low-voltage distribution network electric leakage fault detection model to obtain an electric leakage fault identification result. According to the invention, high-precision identification of the electric leakage fault of the low-voltage power distribution network is realized through the sparrow optimization algorithm fusing the sine and cosine search strategy and the Cauchy variation mechanism, and the accuracy and efficiency of electric leakage detection are effectively improved.

The invention discloses a fault ride-through test method for an offshore wind power flexible direct output system, and the method comprises the steps: building a fault equivalent circuit of the offshore wind power flexible direct output system, analyzing the operation characteristics of an AC power grid side under a low-voltage fault, and determining the incidence relation between the DC side excess energy and the power grid voltage drop; establishing a model representing each component in the fault equivalent circuit, wherein the components at least comprise a machine-side converter, a grid-side converter, a direct-current capacitor and an unloading resistor; when a low-voltage fault of an alternating-current power grid side is detected, executing the following cooperative control based on the model: synchronously starting unloading resistance control and reactive power support control, wherein an unloading resistor dissipates excess energy of a direct-current side through a direct-current chopper; the grid-side converter injects a capacitive reactive current which is deeply matched with the voltage drop of the power grid so as to improve the voltage of a grid-connected point; and if the direct-current voltage continuously exceeds the preset threshold value, starting power prompt drop control, and reducing the output power of the unit according to a gradient until the system recovers to be stable.

This application relates to the technical field of electric vehicles, and in particular, to charging systems and methods. An example charging system includes: a low-voltage battery capable of supplying power to a low-voltage electrical device of a vehicle; a power battery module; a direct current-to-direct current (DC-DC) converter capable of receiving a voltage supplied by the power battery module in response to at least that a positive relay and a negative relay of the power battery module are closed, and converting the voltage into a charging voltage of the low-voltage battery to charge the low-voltage battery; and a DC-DC controller electrically connected to the low-voltage battery and capable of monitoring a voltage of the low-voltage battery in response to at least that the vehicle is in a dormant state.

The invention discloses an intelligent sensing network connection monitoring method and system for a high-low voltage switch cabinet, and belongs to the technical field of electrical monitoring. The method comprises the following steps: acquiring physical quantity data of the high-low voltage switch cabinet according to an adaptive data acquisition period; generating a high-precision original data set through a signal processing algorithm and a data fusion algorithm; according to the high-precision original data set, the operation state of the high-low voltage switch cabinet is evaluated through a state evaluation algorithm, and a state evaluation result set is generated; and outputting a prediction result set of the high-low voltage switch cabinet through a state prediction method according to the state evaluation result set. According to the invention, on the basis of self-adaptive data acquisition, a state prediction method is adopted to accurately predict the fault occurrence probability of the high-low voltage switch cabinet according to the state evaluation result set, so that the effects of planning an operation and maintenance strategy in advance and ensuring stable operation of a power system are realized; the problem that the high-low voltage switch cabinet state prediction precision is low in the prior art is solved.

The invention relates to the technical field of electrical parameter testing, in particular to a high-low voltage frequency converter testing system which comprises a sampling point calibration module, a frequency cross-grade identification module, a current response re-sequencing module, a dynamic interference blocking module and an operation parameter output module. According to the method, the amplitude of the voltage sampling point is mapped into the trigonometric function curve, the waveform trend is deduced in combination with the amplitude change angle, a time delay calibration mechanism based on periodic trend identification is established, and the sampling point time sequence precision in different gear switching scenes can be effectively adapted. According to a combined judgment mode of the current rise rate direction and the frequency jump amplitude, a cross-cycle dynamic judgment path is constructed, a frequency jump index can be identified from a non-stable operation state, and the perception capability of a non-linear operation behavior is improved. A current response sorting reconstruction process is introduced, and the sorting matching capability of inconsistent response sequences is enhanced through cross analysis of frequency gears, current response directions and load states.

The invention relates to the technical field of remote monitoring, and discloses an intelligent AI-based fault detection method and system for a high-low voltage power distribution cabinet, and the method comprises the steps: constructing an LSTM-Attention hybrid network of a multi-modal data flow, extracting the time sequence characteristics of the multi-modal data flow, extracting the non-stationary signal frequency domain characteristics of the multi-modal data flow, and carrying out the fault detection of the multi-modal data flow. The method comprises the following steps: constructing a fault knowledge graph of a high-low voltage power distribution cabinet, analyzing a topological correlation feature vector of the high-low voltage power distribution cabinet, training a pre-constructed power distribution cabinet fault global model to obtain a trained power distribution cabinet fault global model, and analyzing a fault probability matrix of the high-low voltage power distribution cabinet by using the trained power distribution cabinet fault global model. And establishing a digital twinborn body of the high-low voltage power distribution cabinet, analyzing a fault evolution path of the high-low voltage power distribution cabinet by using the digital twinborn body, and analyzing a fault detection report of the high-low voltage power distribution cabinet. The maintenance efficiency of the high-low voltage power distribution cabinet can be improved.

The invention discloses a response control method for a charging station participating in a low-voltage treatment scene, and the method comprises the following steps: S1, collecting the voltage data of a charging pile, calculating a deviation, and judging a low-voltage grade; s2, when the deviation is in a light interval, outputting reactive power support voltage in proportion; s3, when the deviation exceeds a heavy threshold value, reducing active power and starting V2G feedback; s4, constructing a graph structure model, and extracting inter-node power coupling and user behavior factors; s5, inputting the model into an improved prediction controller, predicting a future voltage state, and optimizing and outputting a current period power control value; s6, power adjustment is executed, and feedback power is slowly output in the V2G stage; and S7, comparing the control deviation with the behavior factor change, updating the node control priority, and feeding back for rolling optimization of the next period. According to the invention, while the charging regulation and control precision is improved, the user experience and the voltage stability are effectively considered, and the method is suitable for various low-voltage treatment scenes.