3558 results about "Power loss" patented technology

The invention relates to the technical field of operation prediction, in particular to an optical storage flexible direct current operation prediction method based on deep learning, and the method achieves the precise evaluation of photovoltaic power fluctuation through the analysis of historical operation data and the combination of a power state conversion matrix, guarantees that the energy storage charging and discharging rate can be matched with the load demand distribution, and improves the prediction precision. Power scheduling is optimized, topology analysis and power flow path identification are carried out, topology weight calculation is carried out by using a graph convolutional network, power flow can be dynamically adjusted, the adaptability of an operation mode is improved, the influence of power fluctuation on system stability is reduced, power matching is carried out by adopting an adversarial generative network, photovoltaic output is optimized, and the system stability is improved. The energy storage release path is more reasonable, the power loss is reduced, the overall power distribution efficiency is improved, and the load compensation strategy is optimized through short-period fluctuation detection and long-period trend fitting. And variable correction is performed based on error calculation and anomaly detection, so that the reliability of regulation and control response is improved.

The invention discloses an emergency power supply quick access method based on scene recognition, which relates to the technical field of emergency power supplies, and comprises the following steps: in an emergency power supply system, firstly obtaining electrical input parameter information through a preset detection frequency; by introducing a load change evaluation mechanism based on machine learning, the system can identify load fluctuation in real time and dynamically adjust the detection frequency, and the response speed to the rapid change of the load is improved. Compared with a traditional detection method, the load state is intelligently evaluated and accurately divided, it is ensured that the power factor is adjusted in time when the load fluctuates violently, and power loss and waste are reduced. Correction is carried out according to the traditional frequency during stable load fluctuation, the frequency is dynamically adjusted during rapid fluctuation, the electric energy use is optimized, the electric power quality is improved, and harmonic distortion and overload risks are reduced.

The invention relates to the technical field of motor control, in particular to a variable frequency motor dynamic adaptive control method and system based on multi-parameter analysis. The method comprises the following steps: collecting a multi-dimensional electrical operation monitoring parameter flow of a variable frequency motor, carrying out multi-parameter nonlinear correlation analysis and parameter topological correlation reconstruction, and constructing a multi-dimensional feature topological correlation network; a variable frequency motor multi-working-condition travel history database is obtained, multi-working-condition disturbance transient response analysis is carried out, multi-modal behavior prediction evolution is carried out based on the multi-dimensional feature topological association network, and a dynamic multi-modal behavior prediction engine is constructed; and acquiring multi-part electromagnetic sensing parameters of the motor, and performing abnormal electromagnetic intensity fluctuation detection and abnormal part power loss calculation to obtain abnormal part power loss characteristics. The self-adaptive real-time parameter motor control is realized, the energy efficiency of the motor is improved, the maintenance frequency and cost are reduced, and the full-life-cycle optimal control of the motor is realized.

The invention relates to the technical field of power system engineering, in particular to a power distribution network safety assessment method and system based on an optical storage and charging system, and the method comprises the steps: collecting three types of key data of the optical storage and charging system; based on the three types of key data, establishing a power generation prediction model, constructing an energy storage scheduling strategy, and generating a load characteristic curve; calculating a node voltage deviation value and a branch power loss value of the power distribution network to form a network state evaluation index; performing comparative analysis on the network state evaluation index and a preset safety threshold value, and when the node voltage deviation value or the branch power loss value exceeds the preset safety threshold value, marking an abnormal node position; and for the abnormal nodes, adjusting the charging and discharging power of the energy storage system and the operation mode of the charging facility, and outputting optimized operation parameters of the optical storage and charging system. Through cooperative operation of the photovoltaic power generation system, the energy storage system and the charging facility, accurate evaluation and dynamic regulation and control of the node voltage and the line power loss of the power distribution network are realized, and the operation safety and the energy complementation efficiency of the power distribution network are improved.

The invention discloses an intelligent energy scheduling method and system for a flow battery, and relates to the technical field of flow batteries, and the method comprises the following steps: collecting energy operation parameters of the flow battery in real time, and dynamically estimating an electrolyte state to obtain multiple pieces of energy state information; a target to be dispatched is set, and a fuzzy control strategy is formulated through retrograde multi-target optimization; executing a fuzzy control strategy to generate a regulation and control signal set and scheduling; and finally, according to a scheduling result, performing reverse tracing to optimize a fuzzy control strategy, and updating a regulation signal set to obtain a multi-stage regulation instruction to perform intelligent scheduling on the energy of the flow battery. The method solves the technical problems of low matching degree between a scheduling strategy and an actual demand, large power loss and fast battery life attenuation caused by difficulty in accurately capturing an energy state in real time in a traditional flow battery scheduling method, and achieves the purposes of intelligent flow battery energy scheduling, power loss reduction, battery life prolonging and energy conservation. And the matching degree between the scheduling and the actual demand is improved.

The invention relates to the technical field of vehicle charging station operation and maintenance management, and particularly discloses a new energy vehicle charging station operation and maintenance management system and method based on the Internet of Things, and the method comprises the steps: collecting high-frequency harmonic characteristic data in a charging process in real time, and generating harmonic-impedance spectrum combined monitoring data; extracting dynamic attenuation gradient data of the line characteristic impedance; when the dynamic attenuation gradient data is lower than a preset critical safety threshold value, triggering a charging mode switching instruction; the charging piles are controlled to be switched into a charging mode, the phase difference parameters of the multiple charging piles are dynamically optimized, and a phase difference dynamic adjustment instruction set is generated; and finally, self-adaptive correction of the impedance compensation amount is carried out through the MEC equipment, and by self-adaptive correction of the impedance compensation amount, the system can maintain that the overall impedance is constantly greater than a critical safety threshold value, and power loss and equipment damage caused by impedance mismatch are avoided. The real-time feedback mechanism is helpful for improving the energy efficiency of the system, reducing the operation cost and ensuring the long-term reliability of the charging infrastructure.

The invention relates to the technical field of emergency mobile power supplies, and discloses a control method of an emergency mobile power supply and the emergency mobile power supply, and the method comprises the steps: carrying out the operation parameter data collection and adaptive wavelet transform noise reduction of the emergency mobile power supply, and obtaining a standardized feature matrix; performing hierarchical feature extraction through an extended convolutional capsule network to obtain global power supply features and local power supply features; establishing a deep deterministic strategy network for power supply state scoring to obtain a state scoring result; inputting historical data in the experience playback pool into an action generation module, performing optimization iteration on the control action to obtain a first control strategy, and recording state transition data in a control process; and carrying out power loss compensation control analysis to obtain compensation control quantity, superposing the compensation control quantity to obtain a second control strategy, carrying out PWM (Pulse Width Modulation), and generating a charging and discharging control signal. According to the invention, accurate power regulation and energy storage unit control are realized, and stable operation of the system is ensured.

The invention relates to the technical field of active damping control, and discloses a bidirectional DC-DC power supply active damping control system and method, and the system comprises a front-end AC input rectification module, an LLC resonant circuit, and a Buck converter module: the front-end AC input rectification module is used for converting an AC input voltage into a DC voltage; the LLC resonance circuit is used for inverting the rectified direct current voltage into alternating current with a set frequency and transmitting the alternating current to a secondary side through a transformer; and the Buck converter module is used for rectifying an alternating current signal and adjusting the alternating current signal into a required direct current output voltage, and further comprises an LC filter and an active damping control module. By adopting the active damping control method, the resonance peak caused by the LC filter can be effectively suppressed without additionally adding a physical resistor, so that the fluctuation of the output voltage is limited. According to the control strategy, the problems of power loss and heating caused by a traditional passive damping method are avoided, and the energy efficiency of the system is remarkably improved.

The invention relates to an active and reactive collaborative optimization control method for a photovoltaic energy storage system based on a network-forming inverter, and the method achieves the effective control of active and reactive power through simulating the characteristics of a synchronous generator. And then collaborative optimization of active and reactive power control parameters is carried out. A system frequency response model is utilized to describe dynamic response of system frequency, and a dynamic equation of the system is converted into a discrete form in combination with the dynamic equation of the energy storage unit. Meanwhile, the optimization model is solved by considering system capacity limitation, so that transient frequency characteristics are improved, and frequency deviation after system disturbance is reduced. In addition, the minimum active power loss is taken as an optimization target, the voltage deviation is taken as a penalty term to be substituted into a target function, and a reactive power optimization target function is established. A PSO algorithm is adopted to solve a reactive power optimization function, and reactive power output of photovoltaic and energy storage is adjusted by adjusting VSG control parameters, so that the economical efficiency of a power grid is improved on the premise of ensuring qualified voltage.

The invention provides an electric energy quality compensation method and system based on power electronics, and relates to the technical field of power grid dispatching, and the method comprises the steps: collecting the voltage, current, harmonic content, reactive power, three-phase unbalance degree and other real-time multi-mode data of a power grid, and extracting key frequency spectrum features through wavelet transform denoising and windowing interpolation Fourier transform; and constructing a power quality feature vector. A self-adaptive fuzzy logic algorithm and power grid operation parameters are combined, a threshold value of a power quality index is dynamically adjusted, a multi-stage optimization strategy is divided based on the number of standard-exceeding indexes and importance analysis, and a dynamic compensation priority and a compensation strategy are generated. An improved particle swarm optimization algorithm is introduced, an inertia weight is dynamically adjusted, a constraint penalty function is introduced, output parameters of a power electronic compensation device are optimized, and effective compensation of power quality is realized by taking minimization of total active loss as a target.

The invention relates to a method for setting power loss of a mountain photovoltaic array. The method comprises the following steps of: establishing a coupling causal spectrum of multi-source factors including terrain, angle, sunlight, temperature, dust and wiring mode to component output; identifying a dominant loss path based on an identification method of a Bayesian network; outputting a structure weight matrix of the power loss, and identifying an inclination angle gt; a temperature gt; a set of influence factors of the wiring topology pair setting; calculating a power loss response index of each component based on the loss path weight; forming a response index thermodynamic diagram by using a space weight interpolation algorithm, and performing array space sensitive partitioning; the high response area is used as a preferential setting target, and the low response area enters an observation maintenance mechanism; by constructing the response index and the correction response potential function based on multi-factor coupling, the power response potential of the component to the setting operation can be accurately identified, the problems of average adjustment and low-efficiency resource allocation in a traditional setting method are effectively avoided, and it is ensured that setting resources are intensively input into a high-response area.

The invention discloses a battery capacity analysis and prediction method and system of a storage battery, and relates to the technical field of data processing. The method comprises the following steps: acquiring operation data of a target storage battery in a preset time period, wherein the operation data comprises a voltage sequence, an internal resistance sequence, a temperature sequence and a charge-discharge cycle number sequence; determining a time interval corresponding to the plurality of operation conditions according to the operation data; calculating a temperature influence factor, a power loss factor and a cyclic aging factor of each time interval based on the sub-operation data in each time interval; receiving the battery capacity attenuation amount of the target storage battery in each time interval; generating a capacity attenuation curve of the target storage battery by combining the battery capacity attenuation amount, the temperature influence factor, the power loss factor and the cyclic aging factor of each time interval; and predicting the battery capacity in the next time period based on the capacity change curve. By implementing the technical scheme provided by the invention, the effect of improving the accuracy of battery capacity analysis and prediction of the storage battery is achieved.

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 a multistage safety response control method of an industrial and commercial liquid cooling energy storage system, and relates to the technical field of electric energy storage systems, a sensor network collects an operation state data time sequence matrix, and abnormal data cleaning is carried out on the time sequence matrix; the method comprises the following steps: preprocessing a vibration signal of a cooling system, extracting characteristic data of abnormal vibration through Fourier transform and energy distribution analysis, and positioning a time-frequency distribution abnormal region; generating a time sequence multivariable data set according to the characteristic data of the abnormal vibration, determining a cause label according to the fused time sequence multivariable data set, obtaining the inherent frequency and the resonant frequency of the cooling system in combination with simulation analysis, and matching and determining the cause of the abnormal vibration; an LSTW neural network is used for predicting the abnormal resonance risk, and corresponding countermeasures are taken for the cooling network according to the prediction result; unnecessary vibration caused by error adjustment is avoided, the relation between cooling efficiency and safety is balanced, and unnecessary power loss is reduced.

The invention provides a photovoltaic system-based generating capacity loss intelligent evaluation method, which comprises the following steps of: 1, acquiring optical parameters in real time, and synchronously acquiring predicted irradiation data of a meteorological station; step 2, performing feature extraction on the current and voltage curve, identifying abnormal inflection points in the curve, dividing mismatch types, determining theoretical output power of each group of strings, and generating a future theoretical generating capacity baseline; 3, obtaining a group cascade stage power loss rate, and determining a current loss reason in combination with a mismatch type; 4, identifying a current system-level fault area; and step 5, based on a historical fault case library, extracting a group cascade power loss rate, a mismatch type and spatial distribution characteristics of a system-level fault area, matching a loss mode of a current system with a historical fault type, generating an evaluation report including a loss quantized value, a fault position and a repair priority, and carrying out fault recovery. And an optimization operation and maintenance instruction including a personnel scheduling scheme and a spare part demand list is generated. And the operation efficiency and the maintenance effect of the photovoltaic system are improved.

The invention discloses a high-power all-gallium nitride LED driving power supply circuit which comprises an EMI filtering and rectifying circuit, a GaN active power factor correction circuit, a GaN half-bridge LLC resonant converter circuit and a GaN synchronous rectifying and filtering circuit. The PFC and LLC combined control module integrates a power factor correction function and a resonance circuit frequency regulation function, the GaN active power factor correction circuit is connected with the PFC and LLC combined control module to realize power factor correction, and the GaN half-bridge LLC resonant converter circuit is connected with the PFC and LLC combined control module to realize output power regulation; and a constant-current voltage-limiting feedback circuit for outputting current and voltage detection feedback is arranged between the GaN synchronous rectification filter circuit and the PFC and LLC combined control module. The advantages of high efficiency of the GaN switching tube and high working frequency of the circuit are utilized, so that power loss and heat dissipation requirements are reduced, and the efficiency and power density of the LED power supply are improved. The invention has the advantages of high efficiency, high power density, high reliability and the like.

The invention discloses a feeder voltage adjustable potential multi-target evaluation method and device considering a flexible resource operation domain. The method comprises the following steps: constructing a flexible resource adjustment operation constraint model; establishing a deterministic model of node flexible resource operation domain evaluation considering the adjustment cost; in consideration of output of renewable energy sources in nodes and source load uncertainty of loads, a multi-scene stochastic optimization method is adopted to convert a deterministic model into a node flexible resource operation domain stochastic evaluation model, and upper and lower adjustable ranges of node power, baseline power and segmented unit adjustment cost after flexible resource aggregation are obtained; and finally, comprehensively considering feeder network constraint, adjustment cost after flexible resource aggregation and feeder source load prediction, and constructing a multi-target evaluation stochastic optimization model of the adjustable potential of the feeder voltage with minimum node voltage deviation and network power loss to obtain a quantized adjustable range of the feeder voltage.

The invention relates to the technical field of radio frequency signal management, in particular to a radio frequency power supply output power amplification coefficient analysis method and system, and the method comprises the following steps: obtaining the input power, voltage and current parameters of a radio frequency power supply amplifier, calculating the average value of the power supply output power, and analyzing the change trend of the power in a load state. Determining the operation state of the amplifier, and establishing a power output data set. According to the method, the running state of the amplifier is adjusted and optimized in real time by continuously tracking the average value of power output and carrying out detailed analysis on different load states, in addition, accurate adjustment of the amplification coefficient is ensured by quantitatively analyzing the power loss and the fluctuation range, and therefore the amplification effect is optimized, and the reliability of the amplifier is improved. The energy efficiency and the response capability of equipment are remarkably improved, challenges in a complex operation environment are effectively dealt with through fine power stability analysis and dynamic adjustment of an amplification coefficient, and continuous stability and high efficiency of power output are ensured.

The invention discloses a multi-source power distribution network energy-saving optimization scheduling method, system, equipment and storage medium based on big data processing, and relates to the technical field of power systems and big data processing. After power distribution network multi-source data is collected, through preprocessing and feature extraction, loads are predicted and classified through a long and short-term memory network; the load dynamic optimization module combines cost, network loss and photovoltaic consumption, generates a scheduling instruction through a mixed integer programming model, compares power loss before and after scheduling after CPLEX solution, and generates a difference thermodynamic diagram. According to the scheme, accurate load prediction and dynamic optimization scheduling of the multi-source power distribution network are realized through big data processing, the cost and energy efficiency are effectively improved, the consumption capability of photovoltaic energy is enhanced, the energy-saving effect is visually displayed through the power loss difference thermodynamic diagram before and after scheduling, and powerful support is provided for intelligent management of the power distribution network.

The invention relates to the technical field of electric driving system energy-saving control, and discloses a multi-motor driving system torque optimal distribution method and system, and the method comprises the steps: building a single power unit power loss model of a multi-motor driving system; constructing a fitting straight line segment; constructing a torque-current mapping relation curve; a train speed prediction model, a multi-motor driving system power unit motor rotating speed prediction model, a multi-motor driving system total torque reference value prediction model and a multi-motor driving system power unit power loss prediction model are constructed; establishing a multi-motor driving system energy efficiency evaluation function, a multi-motor driving system stability evaluation function, a multi-motor driving system total torque following evaluation function and a system optimization objective function; designing a learning rate of a control vector; and updating the control vector according to the learning rate, and obtaining an optimized torque distribution coefficient and an optimized torque reference value distributed by each power unit. Therefore, the torque optimization distribution of the multi-motor driving system is realized, and the energy utilization efficiency of the system is improved.

The invention relates to the technical field of power grid data analysis, in particular to a power consumer anomaly detection and risk assessment method, system and device based on spatial-temporal feature fusion and a storage medium. The method comprises the following steps: acquiring multi-source power consumption data of various power consumers, constructing a space-time correlation feature extraction model, and establishing a user behavior space-time coupling relationship through time sequence analysis and spatial distribution characteristic analysis; constructing a multi-dimensional risk mapping model based on a long short term memory network and a convolutional neural network, establishing a nonlinear mapping relation from feature information to a risk assessment result, and identifying an abnormal power consumption behavior; establishing a distributed node credibility evaluation system, and performing credibility quantitative analysis on the data nodes in combination with a fuzzy comprehensive evaluation method; and based on an abnormal detection result and credibility evaluation, intelligent analysis and dynamic early warning of the electric charge management and control risk are realized. The time-space coupling characteristic of power consumption data can be fully mined, and high-precision identification of abnormal power consumption behaviors and accurate detection of non-technical power loss are realized.

The invention discloses a power-saving device and method for high-voltage power utilization, and relates to the technical field of power grid control, a self-adaptive dynamic control strategy and a load prediction function are introduced, and a reactive compensation module can adjust the compensation amount according to the real-time change of the load demand; when the load fluctuates violently, a response can be quickly made, unnecessary energy consumption is reduced, the main line and the load end are respectively provided with compensation equipment, and distributed compensation and main line compensation are dynamically matched through load fluctuation prediction and a self-adaptive control technology; when the load changes, the load end equipment preferentially and quickly responds, the coordination of compensation is effectively improved, redundant power loss is avoided, and the harmonic management module realizes accurate harmonic suppression through real-time harmonic data monitoring and parameter adaptive adjustment of the intelligent filter; the intelligent filter automatically adjusts the damping coefficient and the frequency gain according to the frequency and the power density of each harmonic component, and the harmonic component of the specific frequency is inhibited in time; and the harmonic wave fluctuation coping capability of the system is improved.

The invention relates to the technical field of comprehensive energy systems, and particularly discloses a multi-source cooperative fault recovery control method for an electricity-gas comprehensive energy system, which aims at minimizing the sum of weighted power-loss load capacity, weighted gas-loss load capacity and network loss. A remote controllable switch of a power distribution network, opening and closing of a pipeline valve in a natural gas network and distributed energy output of an electricity-gas integrated energy system are used as control variables, corresponding constraint conditions are constructed for the power distribution network, the natural gas network and electrical coupling equipment, and a multi-source cooperative fault recovery problem is constructed. And an optimal recovery strategy is obtained by solving the multi-source collaborative fault recovery problem. According to the method, the characteristics of flexibility and coordination of the power-gas internet and the pipeline storage characteristic of the gas network are fully utilized, the power and gas load recovery state and the output of each distributed energy source are optimized in time, the system source load fluctuation can be effectively resisted, continuous supply of key loads is guaranteed, and the new energy utilization rate is increased.

The invention discloses a hollow shaft motor and a cleaning water circulating filtration scrubber using the same, and belongs to the technical field of hollow shaft motors. Provided is a hollow shaft motor. A hollow shaft is driven by an output shaft of a motor body. A cover body is arranged outside; a first connecting part and a second connecting part are arranged at two ends of the hollow shaft; the first connecting part is of a mechanical fixed connecting structure; the second connecting part is of a split type connector structure comprising a static ring part, a movable ring part and a pressing device. According to the invention, the hollow shaft is externally arranged, and the hollow shaft and the hollow shaft are not coaxial, so that the motor cannot be damaged even if water leaks from the occlusion part of the hollow shaft, power loss is avoided, and maintenance is convenient; a split type connector structure is adopted, through the contact type sealing design of the static ring part and the movable ring part and the introduction of the pressing device, relative rotation between the hollow shaft and external connection can be achieved, the sealing requirement can be met, and water leakage is effectively avoided; in the cleaning water circulating filtration scrubber applying the motor, a connecting water pipe is effectively prevented from being wound.

The invention relates to the technical field of solar cells, and discloses a solar cell module which comprises a plurality of back contact cells and a plurality of welding strips. The back contact battery comprises a battery substrate and a grid line arranged on the surface of the battery substrate, a plurality of Pad points are arranged on the grid line, each welding strip is connected with the grid line through the Pad points, each welding strip is further connected with the grid line through a welding point, and the welding point is a non-Pad point; the total number of welding points and Pad points, connected with the grid line, of each welding strip is x, the main grid power loss of the back contact battery is y, x and y meet the following formula I: y = a * xb, and a and b are constants. According to the invention, the transmission loss of current carriers can be reduced, and the CTM loss of the assembly can be reduced.

The invention relates to an airflow jet heat dissipation, dehumidification and dust removal system of a power device, and belongs to the technical field of power supply and distribution. Comprising an electric power device and a protection box body of the electric power device, the electric power device is arranged in the protection box body, at least one airflow ejector is installed in the protection box body, an air outlet nozzle of a jet flow nozzle of the airflow ejector corresponds to the surface of the electric power device, and the jet flow nozzle is in a wedge shape. Jet air generated by the airflow ejector efficiently and uniformly performs heat dissipation, dehumidification and dust removal on the electric power device, so that the purposes of saving air consumption, reducing energy consumption, preventing electric leakage and short circuit of electric appliances, reducing power loss, prolonging the service life of the electric power device and improving the safety and operation stability of the electric power device are achieved.

The invention belongs to the field of soft magnetic ferrite, and discloses a high-frequency low-loss manganese zinc ferrite material and a preparation method thereof, and the manganese zinc ferrite material comprises main components and auxiliary components. The main components comprise ferric oxide, zinc oxide, manganese oxide and cobaltosic oxide. The auxiliary components comprise calcium carbonate, silicon dioxide and tantalum pentoxide. The preparation method of the manganese zinc ferrite material comprises the following steps: proportioning, drying and ball-milling; pre-sintering is performed; performing secondary ball milling; performing granulation; forming is conducted; sintering is performed; and performing thermal aging. The manganese-zinc ferrite prepared by the invention has relatively low power loss under a high-frequency condition, and can be applied to the field of electronic materials related to power conversion, such as transformers and inductors.

The invention provides a method for identifying a power grid frequency signal assessment standard, and the method comprises the steps: constructing a system architecture composed of a master station, a substation and a communication network, and achieving the initialization of equipment through a finite-state machine; the method comprises the following steps: collecting power grid frequency, power generation side frequency difference and communication state multi-dimensional data, processing signals by applying median filtering, a sliding window and an EWMA algorithm, introducing fuzzy logic to evaluate a system state, and dynamically adjusting a response strategy; an improved PID algorithm is adopted to track frequency change, feed-forward compensation and PSO parameter optimization are combined, a hidden Markov model is utilized to predict a communication fault, and local mode switching is triggered in advance; main station, mixing and local three-state switching is carried out according to communication states and load changes, and a frequency modulation dead zone is automatically adjusted according to power grid loads through a dynamic threshold value self-adaptive algorithm; the control effect is verified by using a digital twinning technology; and the safety and reliability of the system are guaranteed by optional quantum encryption and active-active redundancy design. The whole scheme effectively reduces the power loss of power generation enterprises, and maintains the safe and stable operation of a power grid.

The invention discloses a thermal coupling IGBT static real-time model modeling method and a related device, and the method comprises the steps: carrying out the modeling of an electrical characteristic part of an IGBT according to an equipment data table of the IGBT, and the electrical characteristic part comprises an electrical element and power loss; according to the equipment data table and in combination with a power loss thermal resistance circuit, modeling is carried out on the electric heating characteristic part of the IGBT, and the power loss thermal resistance circuit comprises an in-module series thermal resistor, a thermal conductive adhesive thermal resistor, a radiator thermal resistor and an environment temperature voltage bias; an interaction portion of the electrical characteristic portion and the electrothermal characteristic portion is modeled. According to the method, thermal coupling refined modeling of the IGBT is realized, and the calculation efficiency can achieve a real-time effect, so that the requirements of behavior-level modeling and real-time simulation can be met in the absence of semiconductor physical parameters, and the hardware-in-the-loop test requirements of normal working on-state and closed-state power consumption requirements are met.

The utility model relates to the field of circuit protection, in particular to a contactor integrated with an excitation function, and an excitation ignition assembly, a first piston, a first conductive part, an auxiliary contact system, a push rod, a melt, an air passage, a second piston and an elastic part are integrated in the contactor. The melt and the auxiliary contact system are connected in series and then are connected in series between the two static contacts. In a normal working state, the auxiliary contact system is insulated and disconnected, when an overload current, a short-circuit current or an abnormal condition occurs, the ignition assembly is excited to act to drive the first piston and the first conductive piece to move, the first conductive piece enables the auxiliary contact system to be conducted and closed, and the melt is connected into a main loop in a parallel connection mode; and then the second piston and the elastic piece are driven to displace through the air passage, so that the contact system is switched off, the elastic piece generates irreversible deformation, and the first piston and the first conductive piece push the push rod to disconnect the melt. According to the invention, the power loss is low, zero-current cut-off of a main loop can be realized, and the breaking capacity and the breaking reliability are improved.