4599 results about "Three-phase electric power" patented technology

The invention relates to the technical field of power system fault monitoring, and discloses a 10kV voltage transformer ground fault real-time monitoring method and system, and the system comprises a ground fault data collection module, a waveform distortion analysis module, a transient signal detection module and the like. Three-phase current, zero-sequence current and voltage waveform data are collected, a current harmonic component proportion, a zero-sequence current high-frequency transient energy value and the like are analyzed, a fault type is determined by combining a phase difference, and a fault position is positioned according to topological parameters and line impedance. And the temperature of the grounding down lead can be monitored, and the fault probability is evaluated and the threshold value is dynamically adjusted by machine learning. According to the invention, real-time accurate monitoring can be realized, fault types and positions can be accurately diagnosed, potential hidden dangers can be comprehensively monitored, the intelligence of a monitoring system is improved, the operation and maintenance cost and risks are effectively reduced, and safe and stable operation of the 10kV power distribution network is ensured.

The invention discloses a power distribution management system of an intelligent charging pile, and belongs to the technical field of electric vehicle charging facilities and intelligent power grids. The load prediction module carries out space-time alignment fusion on historical data and real-time monitoring data to generate a power distribution demand prediction value, and the edge calculation controller executes a model prediction control algorithm based on multi-source data to generate a real-time control strategy containing relay time sequence parameters and a capacitance compensation scheme. And the dynamic power distribution adjustment module executes strategy parameters through the solid-state relay array and the parallel compensation capacitor bank. Self-adaptive adjustment of the power distribution network is achieved through a real-time monitoring-prediction-optimization closed-loop control mechanism, the harmonic content of the power grid is effectively reduced, the energy distribution efficiency of the charging pile group is improved, and the method is suitable for intelligent electric energy management of public charging stations and other scenes.

The invention relates to the technical field of power operation and maintenance, in particular to a power system operation and maintenance method and system of an intelligent power distribution cabinet for weak current control. The method comprises the following steps: acquiring power operation data and sensing data of a power distribution cabinet, and analyzing a topological structure of a power system to obtain a dynamic topological structure of the power system; performing potential load anomaly analysis on the sensing data of the power distribution cabinet to obtain load anomaly node data of the power system; performing load anomaly influence structure division based on the load anomaly node data of the power system to obtain load anomaly influence nodes; performing abnormal node classification on the load abnormal influence nodes according to the sensing data of the power distribution cabinet to obtain three-phase power load offset nodes and three-phase power improper wiring nodes; and performing power distribution reconstruction on the three-phase power load offset node and the three-phase power improper wiring node to obtain abnormal node power distribution data. According to the invention, the weak current control efficiency and the power distribution energy efficiency can be improved.

The invention relates to a multi-source data electric energy quality energy-saving operation monitoring method and device based on AI Internet of Things, and the method comprises the steps: obtaining a transient electromagnetic signal of a permanent magnet operating mechanism circuit breaker, and extracting a time sequence characteristic parameter of the transient electromagnetic signal; judging whether a harmonic problem caused by an inverter exists or not and whether voltage suddenly rises or drops or not, and determining whether the time sequence characteristic parameters are associated with power quality disturbance or not; acquiring a voltage jump amplitude and a voltage swell rate to obtain a voltage fluctuation degree, and outputting a discharge strategy of the energy storage system through a pre-established discharge optimization model; respectively calculating to obtain a voltage distortion rate and a three-phase voltage unbalance degree, and selecting a charging strategy of the energy storage system through a pre-established charging optimization model; predicting a sudden rise rate and a sudden drop rate of the sample to obtain a prediction result, and forming an energy-saving optimization scheme of an energy storage charging and discharging strategy according to the prediction result; the charging and discharging power of the energy storage pool is automatically adjusted, an energy-saving optimization scheme is formed, and the stability of a power grid is effectively improved.

The invention relates to the technical field of CT induction power supplies, in particular to a CT induction power supply system based on cooperative control and distributed optimization and a control method. According to the technical scheme, the CT induction power supply control method based on cooperative control and distributed optimization comprises the following steps: S1, deploying a multi-mode sensing array, and synchronously collecting a three-phase current harmonic spectrum of a power supply node, an iron core magnetostriction vibration waveform and a radiator surface infrared thermal image; generating a digital twinborn body with space-time relevance through multi-physics field coupling modeling; and S2, constructing a data fusion engine driven by a space-time attention mechanism at an edge computing node, and carrying out LSTM feature extraction on the output of the step S1 and a historical operation log under physical constraint. According to the method, through collaborative innovation of multi-mode federated learning and physical embedded edge calculation, a multi-physical field dynamic modeling mechanism under privacy protection is constructed, and the correlation precision and information security of electromagnetic-vibration-thermodynamic data are effectively balanced.

The invention discloses an automatic anchor point searching and processing method for grid-connected test data of a photovoltaic inverter, and belongs to the technical field of automatic test of a power system. According to the method, a three-phase voltage and current signal output by a power grid simulator and an inverter power instruction signal are aligned through a high-precision time synchronization device; wavelet transform multi-scale noise reduction and moving average filtering combined preprocessing is adopted to improve the signal-to-noise ratio; identifying a voltage zero crossing point candidate set, a drop starting point candidate set and a recovery termination point candidate set based on a self-adaptive dynamic threshold value; transient energy characteristic verification is introduced for a voltage drop starting point; effective anchor points are confirmed through time window association of power instruction step changes. According to the method, the problems of low efficiency of manual key event point identification, misjudgment caused by noise interference, grid event and inverter response time sequence correlation missing and the like are solved, and the automation degree of test data analysis, anchor point positioning precision and control response time sequence analysis reliability are remarkably improved.

The invention relates to the technical field of power electronics, in particular to a control method for a low-voltage intelligent reactive compensation system of a submerged arc furnace. Comprising the following steps: acquiring three-phase voltage, current, power factor, harmonic content and temperature parameters of the low-voltage side of the submerged arc furnace through a sensor network; the load fluctuation of the submerged arc furnace in the future 1-5 minutes is predicted based on a deep learning algorithm, and a compensation demand pre-judgment value is generated; according to a load prediction result and a real-time working condition, performing dynamic switching from three modes of fixed compensation, grouped switching and continuous adjustment; harmonic component dynamic tracking compensation is carried out by combining an active power filter (APF) and a static var generator (SVG); the system overvoltage, overcurrent and temperature parameters are monitored in real time, and a grading protection mechanism is triggered and fed back to the compensation strategy adjusting module. The invention provides a control method for a low-voltage intelligent reactive compensation system of a submerged arc furnace so as to improve the response speed of the system, prolong the service life of equipment and guarantee the electric energy quality of a power grid.

The invention discloses a low-voltage ride-through control method of a flywheel energy storage system, which is based on a low-voltage ride-through control strategy of model predictive current control (MPCC) so as to improve the low-voltage ride-through capability of the flywheel energy storage system when a power grid fails. A future current value is predicted through system modeling and a prediction algorithm, so that effective control is realized. The MPCC-based machine side-power grid side coordination control strategy can quickly respond to the voltage sag of the power grid, provide reactive power support, stabilize the voltage of the direct current bus, and ensure the safe and reliable operation of the flywheel energy storage system during the voltage sag period of the power grid. A traditional pulse width modulation (PWM) technology is abandoned, the optimal switching state is directly selected through a limited control set, and hardware implementation of a power grid side converter is simplified. A differential control strategy aiming at a power grid symmetric fault (three-phase voltage sudden drop) and an asymmetric fault (single-phase grounding) is provided, the method is suitable for a complex power grid fault scene, and the system universality is improved.

The invention relates to the technical field of adaptive control, in particular to an electrical automation adjustment method and system, and the method comprises the following steps: obtaining a three-phase current signal, collecting single-cycle high-frequency sampling, extracting an instantaneous extreme point, recording a time coordinate and an amplitude value, calculating a time interval and a change rate, screening the distribution of the extreme point, and obtaining a harmonic distortion characteristic parameter. According to the method, on the basis of high-frequency sampling, instantaneous extreme point extraction, time interval and change rate calculation, harmonic distortion feature description enhancement, extreme value growth rate and phase drift rate are utilized, time periods with prominent fluctuation amplitude are screened, harmonic change trend prediction precision is improved, and the harmonic change trend prediction precision is improved through zero-sequence component and phase offset calculation in combination with periodic change features. The harmonic source is accurately separated, the harmonic cause identification capability is improved, the compensation current is calculated based on the harmonic source, the injection opportunity is optimized, the compensation parameter is adjusted before the harmonic peak value, and the compensation response speed and the matching precision are improved.

The invention relates to the technical field of electrical detection, in particular to an electricity meter load monitoring method and system based on an electric energy quality analyzer, and the method comprises the following steps: extracting three-phase voltage phase deviation characteristics in a disturbance period, combining with the comparison of a frequency band change trend and fundamental frequency power, recognizing an interference coupling section, and analyzing a jump frequency point; and outputting an ammeter load monitoring result. According to the method, the phase deviation angle of the three-phase voltage is extracted in the voltage disturbance period, and the cross-phase synchronization index is constructed, so that the synchronous response characteristics of different loads to disturbance can be accurately revealed, and the accuracy of load response attribution judgment is enhanced. On the basis of cross-phase synchronous analysis, a corresponding relation between frequency band characteristics and response attribution is constructed, so that load response subdivision has a phase difference identification capability and a frequency behavior calibration capability, and the discrimination robustness under a multi-source interference background is improved.

The invention relates to the technical field of inverter control, and discloses an inverter output power control method and device, equipment and a storage medium. The method comprises the following steps: performing power frequency fundamental wave extraction and multi-band band-pass filtering on acquired voltage and current sampling data; performing phase compensation, first coordinate transformation and positive and negative sequence decoupling operation on the filtered fundamental wave principal component data; on the basis of a synchronous phase angle and a power grid fundamental wave frequency obtained by positive and negative sequence decoupling operation, carrying out second coordinate transformation, moving average and harmonic power delay difference operation on three-phase current and voltage data of an alpha-beta coordinate system; performing multi-level power calculation, power capacity distribution, error characteristic evaluation and decoupling operation on the inversion fundamental component and the inversion harmonic component subjected to the difference operation; and performing output signal modulation on the inversion power control quantity of the decoupling operation based on the fundamental wave synchronization phase angle, and generating a power control result. According to the invention, the control performance of the inverter on the output power in actual operation is improved.

The invention relates to the technical field of electrical performance testing, in particular to a water supply equipment electrical performance detection system based on artificial intelligence, which comprises an electrical parameter acquisition module, an energy efficiency analysis module, an insulation performance evaluation module and a comprehensive diagnosis module. According to the invention, a three-phase voltage and current root-mean-square value is dynamically calculated through a broadband current transformer and a sliding window integration method, a 50Hz fundamental component amplitude is extracted to separate power frequency and high frequency harmonic waves, a continuous period energy efficiency ratio standard deviation triggers an insulation detection threshold value, and a parameter fluctuation and insulation degradation response mechanism is established. Harmonic interference correction synchronous processing energy efficiency ratio and leakage current integration, the detection error being lower than 5%, temperature rise rate linear regression and bearing current threshold value cooperative determination, winding aging cross validation, fault misjudgment rate reduction to 26%, closed-loop detection fusion transient capture, dynamic threshold value triggering and multi-parameter diagnosis, early warning success rate reaching 92%, and positioning response being reduced to 3 seconds.

The invention discloses a power distribution network three-core cable fault distance measurement analysis method and system, and relates to the technical field of fault distance measurement, and the key points of the technical scheme are that the method comprises the steps: carrying out the empirical mode decomposition of three-phase voltage and current signals; generating a dynamic correction wave velocity based on the cable type, the environment temperature and the soil humidity parameter; determining the first arrival time of the wave head of the initial traveling wave according to the instantaneous frequency abrupt change point of the alpha-mode component, screening the second arrival time of the first reflected wave by using the amplitude gradient of the zero-mode component, and calculating the arrival time difference; and calculating an initial fault distance, and calling the impedance matrix to iteratively correct the initial fault distance. According to the method, the dynamic wave velocity is coupled with multiple factors, the limitation of single parameter correction is broken through, and the problem of transient drift of the wave velocity is solved; and the STFT high-frequency resolution and the wavelet low-frequency stability are fused, and the ridge continuity is optimized in combination with dynamic programming, so that the traveling wave head detection precision can be improved.

The invention discloses an electric energy metering method under power grid waveform distortion, and particularly relates to the technical field of electric energy metering. The problems of false triggering of an energy compensation mechanism, metering deviation and electricity price settlement risks caused by zero-sequence current or false phase drift easily generated in a multipoint grounding or grounding fault power system in the prior art are solved. According to the anomaly identification and control method integrating zero-sequence current frequency domain characteristic analysis and three-phase phase deviation trend consistency judgment, the false phase deviation state is accurately identified through synchronous sampling, frequency domain analysis and trend consistency evaluation of three-phase voltage, three-phase current and neutral line current, and the false phase deviation state is accurately identified. The error compensation behavior is shielded in real time, the fundamental wave power metering mode is switched to, the electric energy metering accuracy is guaranteed through an error backtracking correction mechanism after recovery, and the anti-interference capability and metering reliability of the electric meter under complex working conditions are effectively improved.

The invention provides an electric energy quality device power smooth flexible capacity expansion method for a new energy access scene. The method comprises the following steps: acquiring three-phase voltage, current and power signals, obtaining standardized three-dimensional tensor data through multi-dimensional tensor spectrum projection decomposition, calculating a characteristic value and a characteristic tensor base, and generating a dynamic characteristic vector and a weight coefficient set; a multi-layer probability graph matrix is constructed, a feature mapping matrix and a hierarchical contribution coefficient are obtained through iterative calculation, a fluctuation feature tensor is constructed, and a multi-time scale prediction model is established; constructing a control manifold space and a measurement tensor, calculating a topological connection matrix, designing a multi-dimensional control law and performing stability optimization; and constructing an embedded feature matrix and an inter-module distance matrix, calculating a capacity expansion weight and a power distribution scheme, and performing spectral domain equalization control and grid-connected coordination control. According to the invention, the power smoothing effect is obviously improved, and the system capacity expansion flexibility is enhanced.

The invention belongs to the technical field of circuit monitoring, and particularly relates to an AI fault identification method and system for an electric power circuit, and the method comprises the steps: constructing a cross-modal data flow with a space-time mark through the synchronous collection of a thermal imaging sequence and a three-phase current waveform, extracting the characteristics of a multi-physical field through combining the characteristics of a wire material, and carrying out the recognition of an AI fault. And establishing a thermal-electric coupling relationship by using space-time alignment convolution, further analyzing and calculating correlation strength between temperature anomaly and current fluctuation through a sliding window, constructing a dynamic threshold model, generating a fault probability thermodynamic diagram, and finally outputting a graded early warning signal. Compared with the prior art, the method has the advantages that deep fusion analysis of thermal imaging and electrical signals is realized, the recognition precision and response speed of potential fault points are improved, the abnormal state of the wire joint can be found and accurately positioned earlier, the misjudgment rate is effectively reduced, and the safety and stability of power grid operation are improved.

The invention relates to a multi-branch power distribution network double-end traveling wave fault positioning method and system, and the method comprises the steps: deploying a plurality of measurement points based on the head and tail ends of a radial power distribution network and branch terminals, collecting topological information, and calculating the linear mode wave velocity; using the three-phase voltage data after the fault to extract traveling wave line mode and zero mode components through modulus decoupling; a line mode component with the strongest global mutation is selected as a reference, and a wave head time sequence table is generated through wavelet decomposition and mutation detection; and correcting the zero-mode wave velocity by combining the topology, the time sequence table and the line-mode wave velocity, and determining a fault interval and outputting a fault position after compensation and correction by using the line-mode and zero-mode wave head time difference. According to the invention, through a wave head time sequence analysis and time difference compensation mechanism based on cooperation of multiple measuring points, positioning errors caused by clock asynchronization and parameter disturbance are effectively overcome, accurate distance measurement which is not influenced by clock errors is realized, and the distance measurement precision is significantly improved; and meanwhile, the point distribution requirement is simplified, accurate judgment and positioning of a fault interval can be realized only by a branch single measuring point, and high economy and deployment flexibility are both achieved.

The invention relates to the technical field of crane line fault diagnosis, in particular to a crane line fault diagnosis system and method based on multi-source data fusion, which comprises a data acquisition and processing unit, a mechanical and electrical coupling characteristic unit and a characteristic fusion and fault quantification unit, the three-axis vibration acceleration and the three-phase current waveform of the track are obtained through the data collecting and processing unit, the mechanical and electrical coupling characteristic unit conducts three-dimensional vector synthesis and wavelet packet decomposition on vibration data, and a time-space incidence matrix of harmonic distortion and vibration is constructed. And the feature fusion and fault quantification unit outputs coupling factors by using a bidirectional long-short-term memory network and an attention mechanism, and outputs a fault probability value through a dynamic time warping matching algorithm after time-frequency domain analysis and sample entropy judgment, so that time-space correlation modeling and dynamic fault matching of multi-source data are realized. And the fault positioning precision and the diagnosis accuracy are improved.

A method for testing sheath impedance in a high-voltage cable cross-bonding system. Three-phase current data and three-phase grounding circulating current data from a first cable body segment and a last cable body segment in cross-bonding units, and three-phase current data, three-phase grounding circulating current data, and three-phase induced voltage data from a cable body at a cross-bonding box are detected and collected, thereby directly calculating three-phase sheath impedance of the three cable segments and determining whether the three-phase sheath impedance is abnormal (step 5), thus determining whether the tested cross-bonding units have a defect. The present invention involves a simple operation, achieves an accurate testing result, and can achieve energized testing without an external excitation source. By performing real-time testing on the cross-bonding units and calculating the sheath impedance of the three cable segments in the cross-bonding units in real time, the states of the cross-bonding units can be determined in real time, which makes it possible to detect a cable fault immediately, thereby preventing a loss caused due to the cable fault.

The invention relates to the technical field of prediction algorithms, and discloses a high-precision active power filtering and prediction algorithm for a three-phase ammeter, which comprises the following steps: acquiring original signals of three-phase voltage and current for baseline correction, performing time-frequency analysis on non-stationary harmonic waves and noise of the original signals, and dynamically adjusting filtering parameters; voltage and current phase alignment is carried out through FIR phase shift and zero crossing point detection, a phase-locked loop is constructed by using GRU to track the frequency of a power grid, the sampling frequency is dynamically adjusted, and frequency mutation is detected; iapFFT transformation is optimized to suppress spectrum leakage, a phase error is corrected through a deep learning network, and weak harmonic detection is enhanced by using an attention mechanism; classifying harmonic waves, and adaptively calculating total active power; dimensionality reduction is carried out on historical power and environmental parameters through an auto-encoder, and future active power is predicted; low-power-consumption hardware is adapted, and training efficiency and data security are optimized; three-phase signals are processed in parallel, and FPGA storage and FFT / FIR cores are optimized for filtering processing; and dynamically adjusting parameters of the phase-locked loop.

The invention provides an open-circuit fault diagnosis method for a three-phase interleaving three-level DC-DC converter, which comprises the following steps of: establishing a mathematical model of the three-phase interleaving three-level DC-DC converter by taking the sum of three-phase inductive current iL1 + iL4, iL2 + iL5 and iL3 + iL6 of inductive current iL1-iL6 of the three-phase interleaving three-level DC-DC converter as state variables; on the basis, designing an improved sliding-mode observer of the three-phase interleaving three-level DC-DC converter, and combining an observation value output by the improved sliding-mode observer with an actual value of the sum of inductive currents of upper and lower bridge arms of the same phase to construct a fault detection variable Mx (x = A, B and C) based on a residual gamma (t); a fault detection variable Nj based on the difference value between the inductive current iL1-iL6 and the current mean value is constructed by utilizing the characteristic that the corresponding inductive current declines at the fastest speed after the open-circuit fault of the switching tube, and j is equal to 1-6; and judging whether the corresponding switch tube has an open-circuit fault or not by comparing the two fault detection variables with a set threshold value.

The invention relates to the technical field of fault diagnosis, in particular to a pole-mounted circuit breaker fault diagnosis method based on multi-information fusion, and the method comprises the steps: firstly obtaining electric quantity modal data such as three-phase current and coil current and mechanical quantity modal data such as mechanism vibration and voiceprint, and constructing a time-frequency domain alignment feature tensor; then, through a graph space-time attention fusion model, deeply mining physical structure association and time sequence evolution laws among heterogeneous data, and generating a dynamic space-time feature matrix; then, respectively constructing a mechanical evidence body for representing the state of the transmission chain of the operating mechanism and an electrical evidence body for representing the working condition of the vacuum arc-extinguishing chamber by adopting a feature level-decision level mixed framework; an improved D-S evidence theory is applied for fusion, when high-conflict evidences are detected, a self-adaptive arbitration mechanism is automatically triggered, conflict weights are dynamically attenuated or distributed to uncertain items, misjudgment is effectively avoided, and high-robustness collaborative diagnosis of the electromechanical state is achieved.

The invention relates to the technical field of cable short-circuit fault detection, in particular to a power distribution network cable short-circuit fault detection method combined with a power supply network topological relation, and the method comprises the steps: collecting the three-phase current and three-phase voltage of each node at each moment in a power distribution network, and the impedance of each node; determining the current abrupt change rate of each node at each moment; obtaining primary fault features of each node at each moment; obtaining an attenuation coefficient of each node at each moment; determining each fault isolation area in the power distribution network according to the connection state of a circuit breaker in the power distribution network; determining the propagation attenuation weight of each node at each moment; and performing weighting processing on the primary fault features through the reciprocal of the propagation attenuation weight, and detecting the short-circuit fault of the power distribution network cable by using a hybrid classifier by using the weighted primary fault features of all nodes at each moment and combining the node adjacency matrix of the power distribution network and the three-phase current and the three-phase voltage of all the nodes. According to the invention, the accuracy of cable short-circuit fault detection is improved.

The invention relates to the technical field of data center power supply, and discloses a transient voltage treatment control method based on a data center flywheel energy storage system. The method comprises the following steps: firstly, acquiring three-phase voltage, current and frequency signals of a power supply bus of a data center and rotating speed and energy storage power signals of a flywheel energy storage system, and calculating a transient voltage characteristic matrix; then, a dynamic threshold value is quantified, a multi-layer cascade evaluation network structure is constructed to carry out voltage transient evaluation, and energy storage control evaluation parameters are generated; then establishing a transient constraint function, and calculating a dynamic stability boundary of the flywheel energy storage system; and finally, iteratively optimizing energy storage control parameters according to the result to obtain a flywheel energy storage power regulation sequence. Through closed-loop adjustment, energy storage power is dynamically adjusted according to load requirements and voltage deviation, transient fluctuation of power supply bus voltage is effectively treated, and power supply stability and reliability of the data center are improved.

The invention discloses a power grid voltage fluctuation suppression method and system based on dynamic voltage regulation, and the method comprises the steps: synchronously collecting a three-phase voltage signal through a sensor array, generating a multi-dimensional feature vector through Park transformation, and extracting a time-frequency joint feature through a mixed multi-scale decomposition algorithm, and inputting a model fusing fuzzy reasoning and a space-time diagram neural network, generating a cooperative adjustment strategy in combination with power grid topology and equipment constraints, and optimizing model parameters through a closed-loop correction mechanism driven by a dynamic forgetting factor. The system comprises a signal acquisition module, a characteristic decomposition module, an intelligent decision module and a closed loop correction module. According to the method, high-precision suppression of power grid voltage fluctuation is realized, the multi-node cooperative adjustment capability is improved, the method can be adaptive to power grid operation state changes, technical feasibility and economic rationality are considered, and an effective scheme is provided for modern power grid voltage stable control.

The invention relates to the technical field of servo control, in particular to a high-precision current closed-loop control system and method for a servo driver, and the method comprises the steps: collecting three-phase current, rotor position, winding temperature and bus voltage, and constructing a state data set; constructing a parameter identification model fusing physical prior and an attention mechanism, deducing inductance and flux linkage parameters influenced by temperature, saturation and cross coupling, and correcting a motor model in real time; the correction parameters are injected into an FOC decoupling and feedforward link, and a self-adaptive PI regulator is linked to set the gain of a current loop on line; calculating a d-q axis voltage command according to the update model to respectively control excitation and torque components; an extended state observer is introduced to estimate load abrupt change and parameter disturbance, feed-forward compensation is carried out, and three-phase PWM is generated through anti-Parker and SVPWM; and an inverter nonlinear compensation model of a dead zone and switch delay is constructed, PWM is pre-distorted and output to a power device, and robust and low-ripple current closed-loop control of the servo motor is realized.

The invention belongs to the technical field of power electronics of power supply or power distribution, and provides a control method of a three-phase four-wire inverter, a controller and an inversion control system. A first control component is generated by using a phase angle, an inversion side three-phase current sampling value and a proportional integral compensator; a second control component and a third control component are generated by using a power grid voltage angular frequency, a neutral line current sampling value, a repetitive controller and a proportional resonance controller, the three control components are combined to control an inverter power switch tube, a proportional integral compensator is still adopted, the algorithm is simple, parameters are easy to design, and the reliability is high. And meanwhile, a repetitive-proportional resonance (RC-PR) composite controller is utilized to realize suppression of neutral line fundamental wave and harmonic current, and the method has faster dynamic response to load abrupt change, so that optimization of dynamic performance and steady-state performance is realized.

The invention provides a brushless motor multi-axis cooperative control method and system for an industrial robot, and relates to the technical field of control, and the method comprises the steps: processing the real-time parameters of a brushless motor of each joint axis through constructing an extended dynamic model, and obtaining a temperature drift coefficient and a load inertia parameter; a self-adaptive pre-compensation model, a neural network compensator and a recurrent neural network prediction model are combined, a torque control instruction is output, a three-phase current prediction value is calculated, a distributed model prediction controller is adopted to generate an optimal switching sequence, multi-axis cooperative control is achieved, and the system stability and the response speed can be effectively improved.

The invention provides an impedance scanning device based on network side voltage dynamic compensation under a three-phase voltage imbalance working condition, and relates to the technical field of new energy station power electronic converter topology and control, the device comprises a three-phase rectifier, a direct current bus capacitor, an inverter, a voltage compensation device, a frequency sweeping device, a circuit breaker and a series transformer part, the three-phase rectifier is connected in series with inverters of the voltage compensation device and the frequency sweep device, a secondary side of a series transformer of the voltage compensation device is connected in series with a network side, a secondary side of a series transformer of the frequency sweep device is connected in series with a grid-connected point, and a primary side of the series transformer is connected to the inverters and is coupled to a secondary side of the series transformer; according to the device, the power grid side voltage is rectified through the voltage compensation unit and is compensated to the grid side after being subjected to single-stage inversion transformation, voltage compensation is achieved through the energy of a power grid when the voltage is unbalanced, and an external energy source or an interference source does not need to be introduced. After compensation, the accuracy of the frequency sweeping result is obviously improved.

The invention discloses a power system inertia estimation method based on multi-mode decomposition and reconstruction, and belongs to the technical field of power system inertia identification control, and the method comprises the steps: obtaining a system frequency deviation signal and three-phase voltage and current data in real time; inputting the frequency deviation signal into a signal processing algorithm, extracting a multi-mode oscillation signal, and reconstructing the multi-mode oscillation signal into an equivalent single oscillation mode signal; the frequency change rate of the reconstructed signal is calculated, and the frequency change rate is obtained and analyzed; after a fault occurs, analyzing the moment corresponding to the maximum value of the frequency change rate, and combining power deviation to trigger inertia constant calculation; according to the frequency change rate and the power deviation, calculating a system inertia constant through a dynamic equation at a triggering moment, and converting the system inertia constant into a per unit value; and reconstructing a frequency signal of a non-measurement node by adopting a weighted least square method to finish inertial estimation. Through a synchronous phasor data dynamic decomposition and reconstruction technology, high-precision online sensing of inertial parameters under complex working conditions is realized.