1633 results about "Power factor" patented technology

The invention relates to the technical field of online calibration, in particular to a multi-parameter fusion intelligent electric energy meter online calibration method and system, and the method comprises the following steps: collecting voltage waveforms, current harmonics and active power data, dividing windows, calculating a covariance matrix, and generating a feature set; a power factor curvature extreme value and a temperature inflection point offset are analyzed to generate an interference identifier, current density distribution and a voltage distortion spectrum are jointly analyzed to extract a harmonic energy ratio to generate a feature vector, and phase compensation is performed on a pulse sequence to generate a calibration instruction set. According to the method, the covariance matrix is constructed by synchronously collecting voltage and current power parameters, the abnormal mark section is generated by combining the temperature change and the covariance difference value, the environment disturbance and the real deviation are effectively distinguished, and the temperature hysteresis effect is identified through the power factor curvature extreme value and the temperature inflection point offset. And combining current density and voltage distortion spectrum analysis to extract a fundamental wave and harmonic wave energy ratio, establishing a composite calibration reference, and dynamically adjusting a pulse duty ratio to realize harmonic wave energy compensation.

The invention provides a single-tube boost PFC circuit control method and system for single-cycle control, and relates to the technical field of data processing, and the method comprises the steps: generating a self-adaptive PWM control signal according to a duty ratio adjustment amount and a frequency compensation factor, and dynamically limiting the pulse current amplitude of a power switch tube through a peak current prediction algorithm, a load current change rate is generated based on the real-time relevance between the pulse current amplitude and the load current; setting a first monitoring point in a dynamic duty ratio change path of the PWM control signal, and extracting a duty ratio change rate and a switching frequency fluctuation parameter in real time; setting a second monitoring point in a feedback path of a load current change rate, and extracting a load current slope characteristic and a transient change amplitude in real time; and based on the parameters of the first monitoring point and the second monitoring point, generating a correction factor through a dynamic response correlation model. According to the invention, a high power factor can be realized under wide input voltage and load fluctuation.

The invention relates to a V2G-based alternating current charging power adjusting method and device. The method comprises the following steps: carrying out multi-scale data acquisition and preprocessing on a V2G alternating current charging system to obtain a standardized system state data set; constructing a system dynamic model comprising a power grid voltage characteristic and a charging power characteristic; carrying out decomposition to obtain a power output mapping relation calculation, and obtaining a power modulation control parameter; establishing a fast and slow time scale coordination control framework, and designing a power regulation agent and a voltage regulation agent to obtain a coordination control strategy; checking a charging power limit value constraint, a voltage limit value constraint and a power factor constraint to obtain a constraint violation judgment result, and executing constraint projection calculation to obtain a target control instruction; and controlling a power conversion circuit of the charging pile to execute power regulation operation. According to the invention, a hierarchical control structure is adopted, the control complexity of the system is reduced, and the robustness and the adaptive ability of the control strategy are improved.

The invention relates to the technical field of intelligent control of transformer substations, in particular to a standardized intelligent control system of a transformer substation, which realizes real-time response to the running state of equipment by acquiring the current, voltage, power factor, temperature and humidity, operation state, insulation state and environment temperature and humidity of a power transformation unit in real time. A gradient boosting decision tree is combined with a variational auto-encoder and a self-attention mechanism, state vector features are extracted, complex abnormal states are accurately recognized, potential faults are detected in an early stage, and the monitoring efficiency and the early warning precision are greatly improved. The future power demand is accurately predicted by combining the long-short-term memory network model with historical and real-time load data, and the limitation of traditional static load management is overcome. Based on the predicted power demand, the reinforcement learning model is adopted to dynamically adjust the operation number of the power transformation units, optimal configuration of resources is achieved while the demand is met, and the overall operation efficiency of the transformer substation is remarkably improved.

The invention discloses an intelligent diagnosis system of a power distribution network fault self-judgment switch device, and relates to the technical field of power system automation and intelligent power grids, and the intelligent diagnosis system comprises an intelligent diagnosis system interconnection hub which is in communication connection with a power parameter monitoring module, an intelligent fault detection module and a visual decision support module; the electric power parameter monitoring module monitors the state of a power distribution network in real time through a mutual inductor, voltage, current, power factors and harmonic data are collected through an intelligent electric meter, the intelligent fault detection module achieves fault recognition, trend prediction and anomaly detection through an LSTM neural network, and the decision support module provides a graphical interface and automatically generates a fault response strategy. According to the method, autonomous judgment and quick response of the power distribution network fault are achieved, the accuracy and efficiency of fault detection are remarkably improved, the false alarm rate and the missing report rate are reduced, meanwhile, the decision support module of the graphical interface simplifies the fault processing flow, and the stability and safety of power grid operation are improved.

The invention provides a frequency converter dynamic fault diagnosis method and system based on a multi-brand load test platform. According to the method, multiple real-time operation parameter sets are acquired, the amplitude attenuation threshold and the frequency fluctuation interval of a voltage waveform fragment are dynamically adjusted according to a load mode configuration file, the dynamic voltage reference parameter corresponding to the current load mode is generated, and then the actual waveform and an expected current phase curve are compared frame by frame; the method comprises the following steps: firstly, calculating to obtain a phase offset, then constructing a multi-dimensional operation characteristic spectrum, then carrying out time sequence cross validation on a sudden change time node of a power factor jump trajectory and an abnormal waveform position in a harmonic distortion incidence matrix, outputting an abnormal mode code, and finally, matching a load adaptation grade constraint condition to generate a diagnosis report; according to the technical scheme provided by the invention, the fault diagnosis precision and the cross-brand system adaptation capability in a complex load scene are remarkably improved, and the problem of misjudgment of a single brand threshold rule in a multi-device scene is effectively solved.

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 relates to the technical field of electric power reactive power compensation, in particular to a novel static dynamic reactive power compensation device and a control method thereof, and the device comprises a power grid state monitoring module, a reactive power demand calculation module, a compensation control execution module, a harmonic suppression module and a dynamic energy storage support module. According to the method, through real-time extraction and segmented analysis of the dynamic operation parameters of the power grid, accurate perception of the state of the power grid is realized, the transient characteristics of operation are represented, an accurate basis is provided for subsequent compensation, decomposition and classified accumulation of reactive power requirements are realized, inductive and capacitive power differences are accurately identified, the calculation accuracy and efficiency are improved, and load adaptation is optimized; in harmonic suppression, resolution and response speed are enhanced through signal separation and frequency correction, energy storage and compensation linkage is improved through dynamic energy storage optimization, dynamic response capability is enhanced, loss is reduced, voltage stability and power factors are improved, stable guarantee is provided for complex fluctuation scenes, and electric energy is saved.

The invention provides a single-stage AC / DC converter for realizing high-frequency isolation power factor correction, and relates to the technical field of converters. The AC-DC converter comprises an AC module with a transformer, an H4 full-bridge module, a third switch and a switch group satisfying a bidirectional current path. The alternating current module with the transformer comprises a first inductor, an intermediate capacitor, a second inductor and the transformer. The first end of the switch group satisfying the bidirectional current path is connected to the common end of the first inductor and the intermediate capacitor, and the second end is connected to the common end of the external AC power supply and the transformer. When the single-stage AC / DC converter works, the switch group satisfying the bidirectional current path is in complementary conduction with the third switch. Compared with equipment such as a two-stage energy conversion configuration, the AC / DC converter provided by the embodiment of the invention is equivalent to an isolated single-stage SEPIC-PFC converter for one-stage energy conversion, the circuit structure is simple, the control is easy to realize, a one-stage architecture is adopted, and the efficiency is improved.

The invention relates to the technical field of electric energy management, and discloses a hybrid control method and system based on distributed power supply electric energy quality management, and the method comprises the steps: obtaining a total capacity value needing grid connection and electric energy data of a plurality of distributed power supply stations in an area range; distributing the distributed capacity to the distributed power station according to a first distribution algorithm, and controlling the distributed power station to output electric energy; calculating a current power factor value, calculating a difference value between the current power factor value and a target power factor value as a power factor difference value in real time, and controlling the number of switching intelligent capacitors according to the power factor difference value; adjusting the output of the SVG according to the variation amplitude of the power factor difference value; and calculating a harmonic current step change slope based on a first detection algorithm, calculating a difference value between the harmonic current step change slope and a harmonic distortion target value as a harmonic distortion adjustment value, and adjusting the output of the APF according to the harmonic distortion adjustment value. According to the invention, the electric energy quality of the novel power grid-connected power system can be improved.

The invention relates to the technical field of photovoltaic voltage regulation, and discloses a distributed photovoltaic power distribution network voltage control system and method. According to the system and the method, voltage and power information of each measurement point is acquired through a data acquisition module, related data of the photovoltaic inverter is collected, and a communication module receives the data and transmits the data to a control module and a monitoring management module; the control module calculates voltage-power sensitivity, a power factor, voltage deviation, power loss and reactive power compensation requirements according to the data, evaluates the running state of the current power grid and judges whether reactive voltage regulation is needed or not, and the monitoring and management module calculates system response time and fault occurrence probability and controls the system response time and the fault occurrence probability. And judging whether the control effect reaches the expectation or not, analyzing faults and abnormities, providing an adjustment strategy for the voltage stability and the photovoltaic power generation efficiency by the optimization scheduling module, acting on the control module again, optimizing system operation by issuing a new control signal, generating a system optimization report and sending the system optimization report to a display end.

The invention discloses an electric energy quality comprehensive treatment method and device based on multilevel collaborative optimization, and belongs to the technical field of electric energy quality treatment of an electric power system. According to the method, voltage and current data of a power grid are collected in real time and multi-parameter monitoring is performed; processing the data by using an adaptive wavelet transform and singular value decomposition combined algorithm, extracting disturbance characteristics and identifying the type and position of a disturbance source; a multi-objective optimization function including harmonic suppression, voltage stabilization, three-phase balance and power factor improvement is constructed, a Pareto optimal solution set is solved, and an optimal solution is selected; and according to an optimization result, generating and executing a cooperative control strategy of each type of electric energy quality treatment equipment. Cooperative treatment of various electric energy quality problems and cooperative control of various treatment devices are realized, the accuracy, self-adaptability and economical efficiency of electric energy quality treatment are improved, and the reliability and stability of an electric power system are enhanced.

The invention discloses a micro-grid power control method, system and device based on fuzzy modulation and a storage medium, and relates to the technical field of intelligent grid integration of a photovoltaic system and a micro-grid, and the method comprises the steps: firstly obtaining the real-time power data of a photovoltaic system, carrying out the control processing through fuzzy logic, and calculating a reference instruction; according to the reference instruction, hysteresis time is dynamically adjusted through modulation hysteresis control, and an inverter switching signal is generated; converting direct current into alternating current based on the switching signal and a power switching device, injecting the alternating current into the micro-grid, calculating active and reactive power reference values, ensuring that the system operates according to a unit power factor, and giving active power to the reference value; according to the method, the power control precision and adaptability of the micro-grid are improved, excessive switching of the inverter is avoided, loss is reduced, the service life is prolonged, power matching and stable transmission are achieved, reactive loss is reduced, bus voltage is stabilized, harmonic waves can be reduced, the electric energy quality is improved, and efficient and stable operation of the micro-grid is guaranteed.

The invention discloses a flexible control method for new energy grid connection, and relates to the technical field of new energy grid connection control. The method comprises the steps of obtaining grid-connected point electrical parameters through a self-measurement mode or a communication interface mode, performing harmonic feature extraction and compensation based on a deep learning network, and adopting a state estimation method to fuse multi-source data to estimate power grid parameters; and constructing a multi-objective optimization function including voltage quality, a power factor and harmonic suppression, dynamically adjusting a weight coefficient of the optimization function by using a swarm intelligence algorithm, and realizing inverter switching sequence optimization through multi-objective model prediction control. Through a dual-mode communication redundancy mechanism and local intelligent control, while a communication function of a traditional main link is reserved, a standby wireless communication link is introduced to realize real-time backup transmission of a control instruction, and through a local autonomous decision-making capability, the problem of control failure caused by a communication problem in a traditional scheme is fundamentally solved.

The invention relates to the technical field of power system monitoring, and provides a power grid data fault diagnosis method and device based on an intelligent power monitoring instrument, and the method comprises the steps: collecting the operation data of a power grid through the intelligent power monitoring instrument, and generating a fault feature vector containing the multi-dimensional feature parameters of voltage, current and power factor; matching and comparing the feature vector with a preset fault criterion; determining a specific fault type based on a comparison result of the characteristic parameters and a threshold value, including identifying voltage abnormity through a voltage deviation rate, identifying harmonic exceeding through a current harmonic total distortion rate, and identifying a three-phase imbalance fault through a three-phase imbalance degree; for judgment of the three-phase unbalance degree, mean square error statistic calculation is adopted, and a safety coefficient is introduced for threshold comparison; and the fault influence priority is evaluated by quantifying the degree of deviation of each characteristic parameter from the threshold. The fault diagnosis efficiency and reliability can be improved, and intelligent decision support is provided for safe operation of a power grid.

The invention discloses an optimal control method for a single-phase high-frequency chain AC-DC non-electrolytic capacitor converter, and belongs to the technical field of power electronics. In order to realize power factor correction and soft switching without a closed-loop control circuit, the circuit comprises a converter and a controller, and the converter and the controller are connected through a signal; the controller collects a signal of the converter as a feedback signal, and generates a driving pulse signal of the converter in an SPWM mode. A phase shift control method and a dead zone self-adaptive control method are adopted to control a first series switch tube, a second series switch tube, a third series switch tube and a fourth series switch tube in a primary side matrix converter and a secondary side first switch tube and a secondary side second switch tube of a secondary side rectifier; and the frequency and the pulse width of the secondary-side third switch tube and the secondary-side fourth switch tube are optimally controlled. The driving pulse signal of the pre-stage matrix converter is generated, a direct-current link energy storage capacitor of a traditional two-stage rectifying circuit is eliminated, the size is reduced, and the hardware cost is saved.

The invention relates to the technical field of energy efficiency monitoring, in particular to a load and energy efficiency monitoring method and system for a four-fusible integrated terminal, and the method comprises the steps: taking any historical sampling moment except the historical sampling moment as a comparison moment at the historical sampling moment which belongs to the same time point as the current sampling moment in any historical period; according to the data correlation degree between the historical sampling moment and the comparison moment in each historical period, obtaining the correlation reference credibility between the historical sampling moment and the comparison moment; obtaining the correlation reference credibility between the historical sampling moment and each comparison moment, and obtaining the abnormality early warning index of the power factor at the current sampling moment in combination with the data correlation degree between the current sampling moment and each comparison moment in each historical period, so as to carry out the abnormality monitoring and early warning of an electrical system. Accurate identification and early warning of power factor abnormity under dynamic load change are realized.

The present invention relates to the field of intelligent power distribution technology, specifically to an intelligent city power distribution method and system, including the following steps: counting the instantaneous power output values ​​and current power flow directions of all regional power supply units in the urban power grid, calculating the power increments within adjacent time intervals, judging the power increment change trend, and screening the power supply nodes to obtain the periodic power increment trend analysis results. In the present invention, by counting the instantaneous power output values ​​and power flow directions of the power supply units, an accurate judgment of the power change trend is achieved, the impact of sudden load fluctuations is reduced, and the problems of load overload or redundant scheduling in the traditional mode are avoided according to the calculated load growth rate. By analyzing the power flow direction to adjust the path, the load units are sorted according to the real-time demand, power factor and load change rate, and the power redundancy of non-critical areas is reduced in combination with the optimization calculation of the power supply scheduling path, and the responsiveness of the power grid in emergency situations is improved.

The invention discloses an optimized reactive power control and fault ride-through method and system for a hybrid commutation converter, and the method comprises the steps: introducing reactive power control and considering the constant voltage control of negative turn-off angle limitation, achieving the control of an extremely low turn-off angle through the active turn-off of a full-control device in the converter under a steady-state working condition, and further meeting the demands of a high power factor; the investment of passive filter equipment is reduced; under the alternating current fault working condition, forced commutation and negative turn-off angle operation are achieved through active turn-off of a full-control device, the receiving end power grid voltage is effectively supported while commutation failure of a half-control thyristor in the hybrid commutation converter is avoided, and the active power transmission level during the fault period is improved. The full-control characteristic of the reverse blocking type integrated gate commutation thyristor in the hybrid commutation converter is fully utilized, reactive power control under the steady-state working condition and stable power transmission under the alternating-current fault are achieved by optimizing active turn-off control, and the method has wide applicability and good application prospects.

The invention discloses a method and system for testing the electrical performance of a semiconductor chip, and the method comprises the steps: building a mapping relation between dielectric loss and loss frequency through obtaining the dielectric loss data, internal material characteristics and dynamic load power factors of the chip under each frequency band, recognizing a loss abnormal region, and analyzing the influence of the loss abnormal region on the performance of the chip; correcting test data by adopting a minimum mean square error algorithm, and optimizing the impedance of the power supply network and the dynamic switching characteristic of a functional module; calculating the breakdown voltage distribution of each layer in the chip, identifying a high-voltage risk region, optimizing the voltage distribution by using a gradient descent algorithm, and dynamically adjusting the working voltage and current; power factor fluctuation is analyzed through a sliding window algorithm, an abnormal area is identified, a power factor is optimized through a PID algorithm, and the working state and transient response of a chip in a dynamic load are improved. According to the method, the problems of nonlinearity of high-frequency dielectric loss, non-uniform breakdown voltage distribution and unstable power factor response under a dynamic load are solved, and comprehensive and accurate evaluation and optimization of chip performance are realized.

The invention provides a regional power supply stability determination method, medium and system, and belongs to the technical field of regional power supply, and the method comprises the steps: collecting the power supply data of each node in a region in real time, including power supply parameters such as voltage, current and power factor, load parameters such as load power and change rate, and environmental parameters such as temperature and humidity; through data cleaning and feature extraction, a regional power supply stability judgment equation set considering all features is established, and a stability evaluation vector is calculated. And performing parameter fitting on the equation set by using historical data to obtain a stability evaluation vector at the current moment, and inputting the stability evaluation vector into a pre-trained stability judgment model to obtain a power supply stability evaluation result. According to the method, the medium and the system provided by the invention, mathematical modeling and machine learning technologies are adopted, and the technical problem that the power supply stability state of the regional power grid is difficult to accurately judge in real time due to the lack of deep analysis on a power supply stability formation mechanism in the existing power supply stability evaluation method is solved.

The invention relates to the technical field of electric power engineering automation, in particular to a low-voltage equipment power factor automatic adjusting system and method based on end compensation, and the system comprises a load monitoring module, a compensation strategy generation module, an end compensation execution module, a dynamic balance correction module and an effect evaluation module. According to the invention, the sequential relationship between the load fluctuation and the compensation demand can be accurately identified by continuously monitoring the current waveform, the voltage waveform and the phase difference change trend of the low-voltage equipment, and the compensation strategy is dynamically formulated in combination with the response duration and the compensation demand matching rule, so that the compensation response agility and the matching property of the fluctuating load are improved; dynamic scheduling is carried out according to the capacitor switching capacity and the combination relation in compensation execution, switching weight configuration is analyzed and optimized through the power factor change rate before and after compensation and the load synchronization characteristic, the dynamic balance of the compensation process is enhanced, the power factor stability and the load fluctuation matching capacity after compensation are effectively improved, and the compensation efficiency is improved. And the adaptability and continuity of the adjusting effect are enhanced.

The invention discloses an optimization control method and system for an ultra-large fan intelligent speed regulator, and relates to the technical field of fan intelligent control, and the method comprises the steps: obtaining the current operation environment parameters of a fan, including but not limited to a wind speed signal, a motor input current, a voltage, a power factor, a rotating speed, an environment temperature and atmospheric pressure; monitoring whether the wind speed fluctuation amplitude exceeds a set threshold or not in a continuous sampling period; judging whether the current system enters a critical hysteresis zone state or not, wherein the critical hysteresis zone state is a working condition when the wind speed data of the sensor does not have stability and fan output has current fluctuation abnormity and a differential pressure rapid change trend; when the system enters a critical hysteresis zone state, the collected wind speed signal is paused as a speed regulation basis, an air volume estimation model based on current, voltage, rotating speed, temperature, humidity and air pressure is constructed, and equivalent air volume is output as a pseudo feedback signal; the problem that the fan speed regulation accuracy and the system stability are reduced in the plateau low-pressure environment is solved.

The invention relates to a coordination method and device for harmonic suppression and reactive power compensation in a power distribution network. The method comprises the steps of obtaining power grid operation parameter information of a power distribution network; according to the power grid operation parameter information, the total current harmonic distortion rate, the power factor and each harmonic current information of the power distribution network are detected; detecting to-be-optimized parameters of the power distribution network according to the total current harmonic distortion rate, the power factor and the current information of each harmonic, the to-be-optimized parameters including at least one of each harmonic and reactive power; and according to the to-be-optimized parameters, suppressing each harmonic in the power distribution network and compensating reactive power in the power distribution network. The method can accurately perform cooperative control on harmonic suppression and reactive power compensation in the power distribution network.

The invention provides an intelligent household electrical appliance type identification method and system based on a neural network, and relates to the technical field of intelligent household electrical appliance identification. The method comprises the following steps: acquiring electrical parameters of the household appliance in stable operation; cleaning the electrical parameters by using a mixed algorithm based on statistics and signal processing, and performing normalization processing on the cleaned voltage data and the cleaned current data; constructing voltage and current track curves, and combining the voltage and current track curves in the same two-dimensional plane coordinate system to form a track image; establishing a mapping relation between the power factor and an image pixel gray value, and based on the track image and the mapping relation, constructing a two-dimensional track image containing gray information corresponding to the operation state of the electric appliance; carrying out feature vector extraction on the two-dimensional track image containing the gray scale information; and performing electric appliance classification and identification based on the convolutional neural network model. According to the invention, the accuracy of electrical identification and classification can be improved.

The invention discloses an automatic feeder fault processing method based on a 5G network, and the method improves the fault processing capability of a power distribution network through the high speed, low delay and high safety of the 5G communication network, can quickly position a fault region through the information exchange between power distribution terminals in combination with the fault signals of the power distribution terminals and adjacent terminals, and improves the fault processing efficiency. Therefore, quick isolation of a fault section is achieved, when a fault occurs, the power failure range is controlled within the minimum range, the power failure time is shortened, fault positioning and control decision making are completely and autonomously completed by the power distribution terminal, the whole processing process does not depend on a power distribution main station, and the main station only needs to receive a fault processing result afterwards; according to the method, the network topology structure can be automatically updated when part of power distribution terminals have communication faults, the operation states of all nodes and circuit breakers in a power distribution line can be monitored in real time, remote measurement can be conducted on voltage, current, power factors and the like, and operation parameter curves of all the nodes can be displayed in real time.

The invention discloses an optimized operation method and system for a network-constructed converter. The minimum voltage amplitude deviation of a common coupling point, the maximum new energy power generation power, the maximum network-side power factor and the minimum line loss serve as nonlinear multiple targets in optimized operation of the network-constructed converter. The non-linear multi-target constraints comprise a common coupling point voltage constraint, a network side minimum power factor constraint, a converter output current constraint, a converter apparent power constraint, a photovoltaic output constraint and an energy storage state constraint; according to the priority of each target, determining a target function and a constraint condition of each priority target; according to the priority order, the optimal solutions of the target functions of the priority targets under the constraint condition are solved in sequence, and the optimal solutions serve as input data of the proxy model; and according to the output data of the agent model, optimizing the operation of the network construction type converter. Cooperative control of convergence speed, global optimization capability and dynamic adaptability is considered, and power supply quality and operation efficiency of an active power distribution area are improved.

The invention discloses a variable frequency driving device energy recovery control system based on direct power supply of a high-voltage power grid, and relates to the technical field of electrical transmission and energy recovery control. Updating the power grid impedance model in real time by using a complex impedance calculation method; load operation state parameters are dynamically adjusted in combination with motor end output power, rotating speed change and torque calculation; according to the method, regenerative energy is accurately calculated, a feedback path is adjusted according to voltage fluctuation and frequency deviation of a power grid, a feedback current fluctuation ratio and a power factor are monitored, a feedback path conduction proportion is optimized in real time, when the current is unstable or the power factor is abnormal, a suboptimal path is automatically switched, and continuous and stable operation of a system is guaranteed; according to the invention, the energy feedback efficiency and the power grid compatibility of the high-voltage power grid variable-frequency driving device are effectively improved, and the method is suitable for energy feedback application of a high-power motor driving system.

The invention discloses a transformer area low-voltage cause analysis method and device and a medium. The method comprises the following steps: acquiring acquisition information of a transformer area in real time; determining a low-voltage event of the transformer area according to the acquired information; the causes of the low-voltage event are analyzed through the collected information to obtain the low-voltage cause, and the low-voltage cause comprises single-phase disconnection, single-phase grounding, three-phase imbalance, distribution transformer outlet metering device fault, low power factor, unreasonable transformer gear and low-voltage abnormity; and performing intelligent decision according to the low-voltage cause to obtain conclusion information. By acquiring the acquisition information of the existing power distribution automation system and determining the low-voltage event and the specific low-voltage cause according to the acquisition information, low-voltage monitoring and cause analysis can be realized without additional equipment, the cause of the low voltage in the transformer area can be analyzed and judged in real time, the analysis cost is low, the applicability is wide, and the method is suitable for popularization and application. The method can be widely applied to the technical field of power distribution networks.

The invention provides a P-type AgBi Se2 thermoelectric material and a preparation method thereof, and relates to the technical field of thermoelectric materials. According to the P-type AgBi Se2 thermoelectric material and the preparation method thereof, the chemical composition of a compound of the P-type AgBi Se2-based thermoelectric material is AgBi (1-x) MnxSe2, 0lt, xlt; and 0.7, the compound is a P-type thermoelectric material. The AgBi Se2-based thermoelectric material with P-type conductivity in a room temperature region is prepared by doping Mn element at the position of B element in a displacement manner and combining melting with a spark plasma sintering technology, and Mn atoms replace B lattice feeding points in a solid solution doping manner to cause mass and stress field changes, so that the lattice heat conductivity is further reduced, and the room temperature Seebeck coefficient of AgB Se2 can be changed from negative to positive. The increase of the doping amount of the manganese element can cause the improvement of the carrier concentration, and the power factor is remarkably improved, so that the ZT value of the P-type thermoelectric material in the room temperature region is remarkably improved, and the room temperature thermoelectric performance of the material is further improved. The invention is used for the P-type AgBi Se2 semiconductor material and the preparation method thereof.