427 results about "Voltage response" patented technology

The invention discloses a battery abnormity identification monitoring method for battery operation and maintenance, and particularly relates to the technical field of battery detection. After a battery enters a station, a temperature difference array, shell micro-deformation, cavity gas indication and end plate near-end temperature are synchronously acquired to form a skin observation vector; applying slight current disturbance and recording voltage response and temperature rise differential to generate a disturbance differential vector; performing event alignment, same-window shadow trajectory depolarization and quantile projection normalization under a unified time reference to obtain a stable and reliable equivalent short window representation vector; performing weighted matching on the vector and historical reference fingerprint quality to obtain a consistency score, calculating a multi-physical disturbance coupling index and a historical trajectory deviation index, outputting a short window credibility coefficient through a discrimination model, generating a risk tag by combining a consistency threshold coefficient after zooming the consistency score, and performing risk identification on the risk tag. And linkage isolation recheck, power limitation and temperature rise limitation or release and archiving are carried out, so that the problem that abnormity in a short time window is easily covered by an environment common mode and artifacts is solved.

The invention relates to the technical field of DC / DC power supplies, and discloses a DC / DC power supply function parameter testing method and system and computer equipment, and the method comprises the steps: injecting a preset disturbance signal into an input end of a tested DC / DC power supply through a signal conditioning circuit, and obtaining output voltage response data and output current response data; adopting a dynamic multi-parameter test system and collecting target test parameter data; calculating a characteristic parameter set, and executing voltage-temperature control model predictive control analysis to obtain a control parameter sequence; and controlling the power output value of the electric heating wire, the rotating speed value of the heat dissipation fan and the position value of the electric push rod in the test box body to obtain an intelligent adjustment test environment and generate an aging test result and a test strategy adjustment instruction, thereby overcoming the problem of parameter detection blind areas in a traditional test method, and improving the test accuracy even under the condition that the output voltage is accurately matched with the set value. And the power supply performance abnormity can be effectively identified, and the reliability and accuracy of the test are obviously improved.

The invention discloses a liquid crystal display screen gray scale control method based on adaptive brightness compensation, which relates to the technical field of liquid crystal display screen control, and comprises the following steps: collecting environmental spectrum distribution information and a pixel gray scale voltage response curve of a liquid crystal display screen in real time, and carrying out fusion processing to form a time sequence joint feature vector; through multi-mode synchronous sampling and time sequence joint feature vector generation, ambient light and screen content changes are accurately captured, target adjustment values of backlight power and gray scale voltage are dynamically predicted, and response lag and overshoot are avoided. Through spectral domain balancing and a self-adaptive damping scheduling mechanism, cooperative control of backlight and gray scale is optimized, high-frequency oscillation is suppressed, and linear response of a low-frequency band is ensured. Meanwhile, Gamma mapping and global color gamut calibration are dynamically refreshed, accurate adjustment of area-level brightness and gray scale is achieved, and continuity of the display effect and visual experience of a user are improved.

The invention relates to the field of battery charging control, in particular to a lithium ion battery equalizing charge control method and system based on a BMS (Battery Management System). The method comprises the following steps: continuously obtaining battery cell monitoring parameters of a battery charging state based on a BMS, and carrying out high-frequency filtering and denoising processing and battery cell charging behavior analysis to obtain a battery cell behavior characteristic time sequence; identifying a charging voltage response signal of each battery cell based on a BMS, performing multi-frequency impedance change trend evolution, performing battery cell charging response characteristic perception based on a battery cell behavior characteristic time sequence, and constructing a plurality of battery cell charging state maps; and carrying out quantitative calculation on charging energy flow affinity according to the battery cell monitoring parameters, carrying out state deviation trend distinguishing by combining the plurality of battery cell charging state maps, constructing a topological connection diagram among the battery cells, and carrying out energy deviation complementary path mining and dynamic deviation balance planning on weak battery cells and strong battery cells. According to the invention, efficient and accurate energy balanced distribution and charging control are realized.

The invention discloses a Fourier transform and S transform combined battery impedance spectroscopy measurement method and device, and aims to improve the precision, speed and reliability of impedance measurement of a battery energy storage system. According to the method, a multi-frequency component excitation signal is generated through a controllable current source, and current and voltage response signals of a battery are synchronously acquired and are respectively input into a Fourier transform module and an S transform module for frequency domain analysis. The Fourier transform module extracts impedance spectrums of low and medium frequency bands, and the S transform module extracts impedance spectrums of medium and high frequency bands through Gaussian window time-frequency analysis. And a data fusion algorithm is adopted to perform composite processing on results of the two modules, including a direct selection method, an arithmetic average method, an amplitude and phase calibration method and a weighted average method, so that smooth transition and optimization between frequency bands are realized, and finally the electrochemical impedance spectrum is generated. Through collaborative analysis of Fourier transform and S transform, parameter optimization and a fusion algorithm, the efficiency and accuracy of impedance spectroscopy measurement are remarkably improved, and the method is suitable for rapid monitoring and diagnosis of the battery state.

The invention discloses a battery pack full life cycle internal resistance evolution tracking method, which belongs to the technical field of battery state monitoring, and comprises the following steps: identifying an operation gap window in the operation process of a battery pack; applying a micro excitation signal to the battery pack in the operation gap window to generate a voltage response signal; orthogonal component extraction and amplitude calculation are carried out on the voltage response signal, and a current internal resistance measurement value is obtained through calculation; jointly storing the current internal resistance measurement value and the corresponding battery state parameter to obtain an internal resistance data sequence; performing trend extraction and deviation modeling on the internal resistance data sequence to obtain an updated internal resistance evolution prediction model; and performing health state mapping analysis on the updated internal resistance evolution prediction model to generate a battery health state evaluation parameter. According to the method, a dynamic excitation adjustment technology is adopted, and a multi-source data time alignment strategy is combined, so that accurate tracking of full life cycle evolution of the internal resistance of the battery pack and accurate evaluation of the battery health state can be realized.

The invention discloses a lithium battery external short circuit fault rapid diagnosis system and method based on PSO-Bayes parameter identification and a thermoelectric coupling model. According to the lithium battery external short circuit fault diagnosis method, the accuracy and the stability of lithium battery external short circuit fault diagnosis are remarkably improved by fusing thermoelectric coupling modeling and a PSO-Bayes parameter identification method. A bidirectional coupling mechanism of an electrical and thermal model can simultaneously capture a voltage dynamic response and a temperature change process, and an intelligent parameter identification algorithm is matched, so that modeling errors under complex working conditions are effectively reduced, and fault feature extraction is more accurate. The fault scoring module integrates multi-dimensional indexes to carry out grading judgment, the capability of distinguishing mild, moderate and severe short circuits is enhanced, the problem of false alarm or missing alarm possibly caused by single parameter judgment is avoided, good response speed and environmental adaptability are shown in practical application, fault detection and grade evaluation can be completed within 4 seconds, and the fault detection efficiency is improved. And the real-time safety protection requirement is met.

The invention discloses an energy storage monitoring method and system, electronic equipment and a storage medium, and relates to the technical field of energy storage. The method comprises the following steps: acquiring voltage data and temperature data of a plurality of different types of battery units; generating a voltage response curve of the corresponding battery unit based on each voltage data, and generating a temperature response curve of the corresponding battery unit based on each temperature data; dividing each battery unit into a plurality of battery packs with different charging and discharging characteristics according to each voltage response curve and each temperature response curve, and calculating the residual electric quantity value of each battery unit in each battery pack; in each battery pack, determining an electric quantity difference value between the battery units in combination with the residual electric quantity value of each battery unit, and taking each battery unit of which the electric quantity difference value is greater than an electric quantity threshold value as a target battery pair; and performing concurrent equalization adjustment on the power parameters of each target battery pair until the electric quantity difference value of each target battery pair is smaller than the electric quantity threshold value. By implementing the technical scheme provided by the invention, the overall energy storage efficiency can be improved.

The invention relates to the technical field of power consumption management, in particular to a pump station unit energy consumption real-time analysis system which comprises a load feature extraction module, a frequency stability recognition module, a start-stop window recognition module, a voltage response regulation and control module and a signal filtering module. According to the method, a sliding trend sequence is constructed through load state data and current increment information, slope abrupt change points are identified, trend direction classification is carried out, accurate identification of a frequency operation stability section is realized in combination with frequency variation amplitude, and a regulation and control time window is constructed through trend consistency judgment of energy consumption and flow in the same time domain. A voltage input strategy is set according to the trend change rate, a mapping table is formed, signal filtering and recovery are achieved through trend continuity judgment in confidence evaluation of energy consumption labels, and the behavior segmentation precision, the adaptability of electric energy input regulation and control and the continuity and controllability of overall operation state recognition in the energy consumption monitoring process are effectively enhanced.

The invention belongs to the technical field of quality detection, and discloses an electrical automation quality detection method and system. The method comprises the steps of collecting original voltage and current signals of a PCC point of a power grid and performing FFT to obtain a background harmonic frequency set and a background harmonic amplitude set; generating an initial frequency grid based on a preset target frequency band, and generating a sparse frequency grid in combination with the background harmonic waves; calculating the estimated signal-to-noise ratio of each candidate frequency, performing ascending sorting to obtain an injection sequence, injecting sinusoidal signals, collecting PCC point voltage response and total current, and calculating a frequency impedance data pair; performing rational function fitting based on the frequency impedance data to obtain a broadband impedance curve; analyzing the curve, extracting quality characteristic parameters, and performing quality judgment according to the parameters; according to the method, the technical problem that the grid-connected stability quality of a single new energy converter cannot be quickly and automatically qualified in a production line offline detection scene in the prior art is effectively solved.

The invention discloses an LED display screen brightness uniformity correction method and system based on current feedback, and relates to the technical field of brightness correction.The method comprises the steps that firstly, a vertical blanking period time sequence empty window is utilized, high-low double-amplitude detection current is injected into LED pixels, and voltage responses in different excitation states are obtained on the premise that normal display is not interfered; then, constructing a state decoupling model based on a reference I-V-T characteristic spectrum, and deeply analyzing coupled electrical signals into independent real-time junction temperature and aging factors by using differential sensitivity characteristics of voltage to temperature and aging; and then, on the basis of the physical state parameters, reverse compensation operation is performed in combination with an original gray instruction and a reference L-I brightness model, and target driving current capable of counteracting thermal quenching and aging attenuation is dynamically deduced. In this way, the correction problem caused by deep coupling of temperature drift and device aging can be effectively solved, and therefore self-adaptive high-precision brightness uniformity correction in the full life cycle of the display screen is achieved.

The invention discloses a voltage sensitivity fitting method and system driven by measurement data of a power distribution network, and the method comprises the steps: constructing a node input feature matrix based on the injection power, measurement voltage and neighborhood features of a power distribution network node in a certain operation state, inputting the node input feature matrix to a variational auto-encoder model, and estimating the node voltage of the whole network; constructing a plurality of groups of micro-power reference disturbance samples around the operation state, and generating corresponding voltage response by using the model again; and finally, calculating a power difference and a voltage difference between each disturbance sample and the reference state, constructing an overdetermined equation set, fitting a voltage sensitivity matrix by adopting a least square method, and averaging fitting results to improve the estimation precision. According to the method, high-precision voltage estimation and voltage sensitivity fitting can still be realized under the conditions of lack of topological structures and line parameters and sparse voltage measurement, and the method is suitable for state estimation, voltage treatment and operation optimization tasks in typical power distribution network scenes of sparse voltage measurement, incomplete topological information and the like.

The invention relates to the technical field of industrial control systems, and discloses an industrial and commercial energy storage battery management system and method.The industrial and commercial energy storage battery management method comprises the steps that a battery main loop switching device is controlled to superpose micro-disturbance signals, a voltage response sequence is collected in real time, the approximate entropy value of the voltage response sequence is calculated, the battery operation mode is determined according to entropy value threshold value comparison, and a corresponding control strategy is executed; according to the method, the electrochemical stability in the battery is directly perceived through order degree analysis of the voltage response sequence, model-free state recognition is achieved, meanwhile, a resource self-adaptive mechanism that macroscopic monitoring triggers microscopic calculation is constructed, the decision reliability is improved through electrochemical and thermodynamic signal cross validation under the complex working condition, and the method is suitable for large-scale popularization and application. And a dynamic control system with both real-time performance and safety is formed.

The invention relates to the technical field of electrical parameter measurement, in particular to an SOC prediction method and system applied to a lithium battery. The method comprises the following steps: collecting an electrical variable parameter set of the lithium battery in a current operation period, and determining an electric quantity change value and a change trend of terminal voltage; dividing a voltage response state of the lithium battery in each operation stage to determine an operation state mapping relation; predicting the state of charge of the lithium battery in the current operation period by using the operation state mapping relation; in response to the first change of the operation condition of the lithium battery, collecting a current electrical variable parameter set of the lithium battery to correct the operation state mapping relation; and predicting the state of charge of the lithium battery after the first change of the operation condition according to the corrected operation state mapping relation. The method is beneficial for dynamically adapting to unsteady state behaviors of the lithium battery in different working states, SOC prediction lag and fluctuation caused by working condition changes are effectively reduced, and the dynamic response capability and reliability of prediction are improved.

A method is provided for pretraining a hyper model configured for use in predicting a state of power (SoP) of a vehicle battery. The method includes performing electrochemical impedance spectroscopy (EIS) scans on a plurality of batteries having a set of similar operating characteristics to the vehicle battery. The EIS scans are performed across various states of the vehicle battery. The method further includes fitting parameters of the hyper model by applying an optimization technique to results of the EIS scans. The hyper model includes a family of models that each define a voltage response of a respective cell from among a plurality of cells of the vehicle battery to a current profile over the various states of the vehicle battery.

The invention relates to the technical field of charging optimization, and discloses a multi-stage charging optimization method based on adaptive identification of a battery, and the method comprises the following steps: S101, in-situ detection and battery type identification; step S102, applying a current step and collecting a voltage response; s103, predicting the change of the terminal voltage along with time; step S104, determining a safe amplitude limiting current; step S105, determining a pre-deceleration factor; and step S106, judging full power, generating a quota recovery instruction, and returning to the step S104 for redistribution. Battery individual parameters are obtained through in-situ detection and micro-pulse identification, current quotas are dynamically distributed based on a constant voltage proportion, a safe target current is determined by combining voltage and power amplitude limiting, current distribution unbalance is avoided, the bus current utilization rate is maximized, voltage overshoot is inhibited by means of a first-order following strategy and a pre-deceleration factor, and the safety of a battery is improved. And stable switching is ensured by matching with constant-voltage inlet current clamping.

The invention provides a battery process simulation test method, which comprises the following steps of: S1, inputting battery model parameters required by a second-order equivalent circuit and an initial state of a battery for pre-processing to obtain a basic second-order equivalent circuit simulation model, and introducing a series of calibration parameters on the basis of the basic second-order equivalent circuit model to obtain a simulation result of the battery model; errors are dynamically corrected in the simulation calculation process, the problem that an original model is insufficient in precision in the aspects of SOC change rate, voltage response and the like is effectively solved, and the accuracy and reliability of simulation results are remarkably improved. Aiming at complex and diversified process requirements in a battery test scene, a process simulation function supporting multiple process steps and multi-condition logic is constructed, an actual test process can be truly restored, and powerful data support is provided for process debugging, test time prediction and electric energy consumption evaluation.

The invention discloses a multi-energy cooperative control method and system with a self-adaptive disturbance discrimination function, and relates to the technical field of energy cooperative control, and the method comprises the following steps: constructing a multi-band phase fingerprint sequence based on the instantaneous voltage response of a photovoltaic array, and forming an initial energy transition baseline through extracting microsecond phase deviation tracks in different bands; and based on the initial energy transition baseline, constructing time series dynamic gradient mapping, converting the phase deviation trajectory into continuous power gradient distribution, and identifying a potential acceleration fragment in the power gradient distribution. According to the method, a high-sensitivity energy identification mechanism is constructed, pre-judgment is carried out in advance before photovoltaic output sharply rises, and power of different frequency bands is guided to enter a layered energy storage path based on a high-risk window, so that energy deposition according to needs is realized, local thermal stress concentration is avoided, and structural damage and energy storage attenuation of a heat storage body are effectively prevented; the stability and safety of electric heating are improved, and the service life of heat storage materials is prolonged.

The invention belongs to the technical field of energy storage system state monitoring, and provides a lithium ion energy storage system abnormal state identification method and system based on impedance spectrum analysis, and the method comprises the steps: carrying out the decoupling of voltage response data and current response data through employing an excitation-response decoupling algorithm under a dynamic working condition, and obtaining an impedance spectrum; obtaining a voltage response component and a current response component; obtaining the total impedance spectrum of the lithium ion energy storage system under the current working condition; constructing a system-level impedance cloud picture; calculating a difference value between the current impedance spectrum and the weighted moving average baseline spectrum based on the system-level impedance cloud atlas to obtain an enhanced difference cloud atlas; and performing non-uniform segmentation and feature extraction on the enhanced difference cloud picture by using a visual Transform model oriented to electrochemical prior to obtain a multi-dimensional abnormal probability vector, and obtaining an abnormal state type of the lithium ion energy storage system based on the multi-dimensional abnormal probability vector. According to the technical scheme, the accuracy, timeliness and reliability of abnormal state recognition of the energy storage system are remarkably improved.

The invention relates to the technical field of energy storage battery module health monitoring, in particular to an energy storage battery module health monitoring method, which comprises the following steps: S1, applying a preset micro-current pulse sequence to each single battery in an echelon utilization energy storage battery module; s2, collecting voltage response data of each single battery under the excitation of the micro-current pulse sequence, and recording current temperature data of each single battery; s3, extracting a first characteristic parameter set and a second characteristic parameter set from the voltage response data; s4, a pre-established reference model is used, the model combines the characteristic parameters, the battery aging state and the temperature corresponding relation, and the real-time influence of historical damage and the current temperature is separated and quantified; and S5, based on the historical damage contribution and the current temperature instant influence contribution, evaluating the inconsistency of each single battery in the echelon utilization battery module. The method has the advantage of improving the accuracy of health state and inconsistency evaluation.

The invention relates to a battery internal resistance testing method and circuit, and the method comprises the steps: sequentially applying alternating current excitation signals of a plurality of frequency points distributed in a specified frequency scanning range to a tested battery in a frequency scanning mode, and enabling the amplitude of the alternating current excitation signals to be smaller than or equal to a preset amplitude, the distribution of the plurality of frequency points is related to an equivalent circuit model adopted by the tested battery; acquiring a voltage response signal generated by the tested battery under the action of the alternating current excitation signal, and acquiring an alternating current signal flowing through the tested battery; acquiring complex impedance data corresponding to each frequency point in the plurality of frequency points based on the voltage response signal and the alternating current signal; and performing parameter fitting on the complex impedance data of the plurality of frequency points and the equivalent circuit model to obtain parameter values related to the internal resistance of the battery, and generating a battery internal resistance test result. The scheme provided by the invention can improve the test efficiency and test precision of the internal resistance of the battery.

The invention relates to the technical field of charge and discharge control, in particular to a V2X charge and discharge cooperative control system based on dynamic multi-objective optimization, which comprises a voltage characteristic identification module, a response capability evaluation module, a scheduling matching mapping module, a task load distribution module and a cooperative regulation and control judgment module. According to the method, rapid adaptive response data acquisition in a voltage regulation dead zone is realized through multi-node transient voltage response identification, a synchronization vector is constructed by using response time, an instability characteristic and a precision grade, vehicle synchronization capability is normalized and measured, and dynamic scheduling layering of multiple vehicles is realized by constructing a difference sorting mechanism in combination with regulation tolerance. A regulation and control mapping relation is established according to a task load regulation rate, consistent matching and dynamic adaptation of vehicle scheduling and load change are realized, the adaptation capability of a vehicle energy response behavior to a dynamic demand of a power grid is remarkably improved, a coordinated discharge task under multi-target constraint is met, and the problems of time lag and unbalanced response are reduced.

The invention discloses a cooperative suppression method for transient overvoltage of a hybrid wind power plant by a network-constructing type direct-driven wind turbine, which is suitable for the hybrid wind power plant comprising a network-constructing type permanent magnet direct-driven wind turbine generator and a network-following type permanent magnet direct-driven wind turbine generator. The method comprises the steps of constructing an electrical equivalent model, extracting key parameters, identifying regulation and control factors, formulating a cooperative control strategy, and executing control response and strategy optimization in an abnormal state of a system. Voltage response characteristics are analyzed through indexes such as self-impedance, mutual impedance and short-circuit ratio, and effective suppression of transient overvoltage and improvement of system voltage supporting capability are realized by combining controller parameter setting and reactive power compensation device control.

The embodiment of the invention provides a DC bus ground insulation degree detection method and device and a medium, and is applied to the technical field of electronic circuits. The method comprises the following steps: acquiring sampling signals of a detected loop corresponding to a target direct-current bus under excitation signals of different frequencies; wherein the sampling signal comprises a voltage response signal and a current response signal of the detected loop; performing frequency domain analysis based on the sampling signal to obtain an amplitude and a phase corresponding to each frequency component; based on the amplitude and the phase of each frequency component, performing fitting calculation to obtain a capacitance value of the measured loop; the capacitance value represents a real ground capacitance value of the target DC bus; and obtaining a ground insulation degree detection result of the target DC bus based on capacitance value analysis. The technical effect of improving the insulation degree detection accuracy is achieved.

The invention relates to the technical field of charging optimization, in particular to a multi-target charging strategy optimization method considering battery health attenuation, and provides the following scheme: firstly, collecting instant state parameters of a battery when the battery is connected to a battery replacement cabinet, and mapping the instant state parameters to a preset battery cluster health model library to obtain an initial health state estimated value; before charging is started, voltage response and impedance characteristics are obtained through disturbance current diagnosis, initial estimation is corrected, and a health state posterior estimation value and a corresponding uncertainty index are obtained; on the basis, a target optimization function is constructed by combining the charging duration, the battery health attenuation cost, the electricity price cost and the heat management cost, and an individual charging strategy adaptive to the battery is generated; according to the method, the health state estimation precision can be improved under the scene of lack of battery historical data, the charging strategy deviation is reduced, and safety, efficiency and economical efficiency are considered.

The invention relates to the technical field of converter control, and provides a self-adaptive virtual impedance optimization method for a grid-forming type energy storage converter under a weak power grid, which comprises the following steps: injecting a multi-frequency-band collaborative disturbance signal into the power grid, acquiring a voltage response signal and a current response signal of the power grid, and carrying out online scanning and identifying the impedance characteristics of the power grid; establishing a power grid impedance model; constructing a real-time digital twinborn model synchronously operating with the physical converter, wherein the real-time digital twinborn model integrates the power grid impedance model and a multi-time scale state space model of the network-constructing type energy storage converter; and downloading the optimized virtual impedance parameter set to the physical networking type energy storage converter for execution, and performing closed-loop control of the adaptive virtual impedance. Therefore, the broadband stability and the dynamic performance of the network-forming type energy storage converter in the time-varying weak power grid environment are improved.

The invention discloses an automatic test method and system for a resistor. The method comprises the following steps: acquiring a to-be-tested resistor; configuring a dynamic impulse voltage gradient parameter and a staged acquisition strategy for the to-be-tested resistor; based on the dynamic impulse voltage gradient parameter and a staged acquisition strategy, acquiring response voltage, response current and temperature data of the to-be-tested resistor under different impulse voltages as target data; performing feature extraction on the target data, and determining an anti-surge index and an impact response consistency index corresponding to the to-be-tested resistor based on the extracted features; generating a test report according to the anti-surge index and the impact response consistency index; the resistor performance data is acquired in multiple dimensions, and the resistor is accurately tested based on a resistor performance evaluation quantification system.

The invention relates to a charge pump circuit, a modulation method of the charge pump circuit and electronic equipment. The charge pump circuit comprises a charge pump module, a driving module, an obtaining module and a frequency adjusting module. The charge pump module is used for connecting a load and is configured to output a target voltage to the load in response to the adjusted target switching frequency based on the power supply voltage. And the driving module is connected with the charge pump module and is configured to respond to the adjusted target switching frequency to drive the charge pump module. The acquisition module is configured to acquire a pre-input signal corresponding to a load. And the frequency regulation module is connected with the acquisition module and the driving module, and is configured to regulate the magnitude of the target switching frequency in real time according to the pre-input signal. The switching frequency of the charge pump can be dynamically regulated and controlled, so that the output efficiency of the charge pump circuit is improved, and electromagnetic interference and switching loss are avoided.

The invention discloses an SVG parameter dynamic setting method and device, electronic equipment and a storage medium, which are used for solving the technical problems of incomplete consideration, low optimization efficiency, easiness in falling into a local optimal solution and poor expansibility when an objective function is constructed in the prior art. The method comprises the following steps: constructing a control model of the SVG, and determining a to-be-optimized parameter set of the control model; voltage response of the control model during transient simulation is considered, and a fitness function based on voltage recovery segmented penalty is constructed; based on the fitness function, performing parameter optimization on the to-be-optimized parameter set through particle swarm optimization to obtain an optimal parameter set; and taking the optimal parameter set as a control parameter set of the SVG in practical application.

The invention provides a charging pile output power control method, a charging pile output power control device, a charging pile and a charging pile system. The charging pile output power control method comprises the steps of acquiring power grid real-time voltage acquired by a power grid monitoring device; determining a power grid voltage deviation degree according to a difference value between the power grid real-time voltage and the power grid rated voltage in response to the condition that the power grid real-time voltage is lower than a first voltage threshold value; obtaining a task priority parameter of a charging task corresponding to the target charging pile and a battery state parameter set of a target battery corresponding to the charging task; according to the power grid voltage deviation degree, the task priority parameters and a battery state parameter set, a charging power adjustment coefficient is calculated through a preset multi-parameter coupling algorithm, and the battery state parameter set comprises battery health state parameters and battery remaining capacity; determining an output power adjustment value of the target charging pile according to the difference value and the charging power adjustment coefficient; and adjusting the output power of the target charging pile according to the output power adjustment value. According to the invention, the flexibility and intelligence of charging pile output power control are improved.