2593 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 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 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 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 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 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 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 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 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 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 belongs to the technical field of power supply transmission, and relates to a POE-POF power supply transmission method and system, and a storage medium. The method comprises the following steps: collecting electric quantity data of POE-POF power supply transmission network nodes in real time, and extracting a dynamic power feature set; identifying an abnormal power loss event based on the feature set and extracting an abnormal mode feature; abnormal path nodes are positioned by combining a POE-POF power supply transmission network topological structure, voltage and current distribution parameters are optimized, and an optimized power distribution scheme is generated; dynamically adjusting voltage and current values of a power supply path, evaluating an energy consumption trend and generating a trend data set; and adaptively adjusting the electric quantity acquisition parameters according to the energy consumption trend, updating the acquisition configuration and circularly executing the steps. According to the invention, intelligent detection, accurate positioning and dynamic optimization of abnormal loss of the power grid are realized, the stability and energy efficiency of the power supply network are improved, and the method is suitable for fine management and energy-saving optimization of the intelligent power grid.

The invention provides an electro-hydraulic servo pump control method and system for controlling hydrogen compression based on fuzzy nerve, and relates to the technical field of hydrogen compression, and the method comprises the steps that the current state of a hydraulic cylinder controlled by an electro-hydraulic servo pump is determined, and an input control variable is obtained; determining an output control variable, establishing a fuzzy control rule, and dividing a basic discourse domain; performing composite defuzzification, and obtaining a corrected weight coefficient through a feedforward neural network; the discrete rule amplitude correction factor and the weight coefficient correction are dynamically optimized and corrected; neural network training is established, a loss function evaluation model is utilized, and hydrogen compression control is achieved through a double-buffering mechanism. Fuzzy PID control is adopted, composite defuzzification is carried out according to the real-time state change of a system in combination with fuzzy logic, a membership function output by the fuzzy PID is divided according to regions, a control signal of a driver is synthesized, and hydrogen compression control is achieved; system output is adjusted according to different working conditions, power loss is reduced, and system control precision is improved.

The invention discloses an intelligent control cooling fan driving method, relates to the technical field of intelligent cooling, and solves the problems that the working mode of a traditional fan is irrelevant to an electric control working state, the fan always runs at the maximum rotating speed after electric control is started, and electric energy is wasted. The cooling fan driving method comprises the steps that the controller conducts power sampling and dynamic calibration on the direct-current side and the alternating-current side of the inverter circuit respectively, and voltage and current are obtained; calculating corresponding power and a power loss value according to the corresponding voltage and current on the two sides, performing temperature compensation on the power loss value according to the junction temperature of the field effect transistor to obtain real-time power loss, and recording loss duration; according to the environment temperature, a loss power threshold value and a loss time threshold value are preset and compared with the real-time power loss and the loss duration time, and meanwhile the real-time power loss and the loss duration time are stored to the controller; and establishing a nonlinear mapping model of the PWM duty ratio and the voltage of the electric control high-power output port, and regulating and controlling the rotating speed of the fan in combination with a multi-stage speed regulation mechanism so as to complete the driving control of the fan.

The invention relates to the technical field of cables, and discloses a power shielding cable stranding device for a top drive of an oil platform and a production process, the power shielding cable stranding device comprises a supporting assembly, the upper part of the supporting assembly is provided with a wire feeding assembly, a stranding assembly, a guide assembly and a traction assembly, and the wire feeding assembly is located at the side part of the upper part of the supporting assembly; the stranding assembly, the guiding assembly and the traction assembly are transversely arranged on the upper portion of the supporting assembly along the supporting assembly, the supporting assembly comprises a bottom plate, and a first driving motor is installed on the upper portion of the bottom plate. By arranging an adjusting plate, the problem that a stranded wire is locally bent due to improper storage and carrying or material rigidity difference can be solved. Precise correction is achieved by sensing local deformation of the stranded wire and applying extrusion and drawing force, the situation that the cross section structure of the cable is not uniform due to deflection of a bent part after stranding is avoided, the structural strength of the cable is guaranteed, electric energy loss is reduced, the power transmission efficiency is improved, and the structural stability and transmission performance of the stranded cable are guaranteed.

The invention discloses a distribution network low-voltage extension type direct-current ice melting method and an ice melting management system, and relates to the field of disaster prevention and reduction of an electric power system, and the method comprises the steps: obtaining an electrical characteristic signal, an icing thickness value and weather forecast data of each target line; calculating power loss distribution of each target line, and dividing the target line into a plurality of electron supply zones; inputting the icing thickness value and the weather forecast data into an icing prediction model to obtain an icing development trend; carrying out correlation operation on the icing development trend and the corresponding power loss distribution to obtain an ice melting priority and an ice melting current value; generating a power supply execution sequence and a direct-current power supply output parameter; and generating an ice melting execution scheme based on the power supply execution sequence and the DC power supply output parameters, and implementing ice melting power supply according to the ice melting execution scheme and the power supply execution sequence. According to the invention, ice melting planning can be carried out, and electric energy waste is avoided.

The invention discloses a two-stage fault recovery method for improving the elasticity of a power distribution system, and the method comprises the steps: constructing a typhoon space-time evolution model, and generating a prediction fault scene; simulating the distribution line in the predicted fault scene by using a Monte Carlo simulation method to generate a plurality of fault scenes; based on the information entropy value of the fault scene and the fault multiple number, an uncertainty set is constructed, and then a robust optimization model is constructed; solving the robust optimization model, and determining a pre-layout scheme of the mobile energy storage system and the static var compensator in a pre-disaster worst fault scene; a multi-source collaborative post-disaster multi-period multi-target fault recovery model is constructed; the fault recovery model realizes recovery of a power-loss load and a fault line of a power distribution system through network reconstruction and optimal scheduling of a mobile energy storage system, a static var compensator, a maintenance team and an electric vehicle. According to the invention, the overall elasticity of the power distribution system is obviously improved, the capability of resisting disasters is enhanced, and the capability of rapidly recovering power supply is also improved.

The present invention discloses a BMS battery remote monitoring and data analysis system based on a cloud platform, which relates to the technical field of remote monitoring and is used to solve the problems in the prior art that due to the lack of detailed data monitoring, it is impossible to deeply analyze the performance and loss of each part of the battery, thereby affecting the overall health assessment and management of the battery. Moreover, the battery state of the battery is usually a fixed and static value, ignoring the dynamic impact of the management frequency and power loss of different functional parts on the battery state; by combining the management frequency and power loss, the battery state of each functional part can be accurately allocated, the battery usage strategy can be optimized according to the actual situation of different modules, and unnecessary energy loss can be reduced. Unnecessary interference with the battery can be reduced. Through an automated monitoring and adjustment mechanism, manual intervention in battery management can be reduced, making battery management more intelligent and efficient.

The invention discloses a fan variable pitch anti-stall control method, device and system based on temperature scheduling, and the method comprises the steps: calculating a minimum anti-stall pitch angle under different environment temperatures and fan output powers, and taking the minimum anti-stall pitch angle as an optimal pitch angle amplitude limiting value; constructing a corresponding relation among the environment temperature, the fan output power and the optimal pitch angle amplitude limiting value; in the operation process of the controlled fan, the temperature of the environment where the controlled fan is located and the output power of the controlled fan are collected in real time; and according to the environment temperature and the fan output power which are collected in real time and the stored corresponding relation, the real-time optimal pitch angle amplitude limiting value is obtained, so that the real-time pitch angle of the controlled fan is controlled to be lower than the real-time optimal pitch angle amplitude limiting value. According to the method, the operation safety of the unit can be improved, the control stability is improved, and the power loss can be minimized while stall is prevented.

The invention relates to the technical field of electric energy loss analysis, and discloses a power grid electric energy loss analysis system, method and device based on machine learning and a medium. Acquiring electric energy loss data of each power transmission line of the power grid in the target area in the current monitoring period, and respectively comparing and analyzing the electric energy loss data with the electric energy loss data of each power transmission line in each historical monitoring period in the current year and the electric energy loss data of each power transmission line in each historical same period in a preset historical year period; obtaining a first electric energy loss increase evaluation index and a second electric energy loss increase evaluation index, evaluating the electric energy loss increase condition, constructing an electric energy loss discrimination vector, and discriminating whether the electric energy loss meets the standard through a logistic regression model, thereby improving the evaluation accuracy of the electric energy loss of the power transmission line. The subjectivity and uncertainty of manual judgment are reduced, a manager can quickly know the electric energy loss trend of the power transmission line, the electric energy loss of the power transmission line is reduced, and normal operation of a power grid is ensured.

The invention discloses an elevator energy-saving control system based on an auxiliary power supply module, which relates to the field of elevator energy-saving control and comprises a battery module, the auxiliary power supply module and an energy-saving control module, the battery module is connected with a circuit breaker, the circuit breaker is connected with at least one contactor set used for being connected with at least one elevator in a one-to-one correspondence mode, the same bypass contactor is connected between the circuit breaker and all the contactor sets, and the bypass contactor is connected with an anti-reverse diode in parallel. The mains supply and the battery module are respectively connected with the auxiliary power supply module; the auxiliary power supply module is connected with the energy-saving control module; and the energy-saving control module is respectively in communication connection with the circuit breaker, the contactor group, the bypass contactor, the battery module and the auxiliary power supply module. The charging and discharging energy balance of the battery module can be realized, and the problems of conversion electric quantity loss and high cost caused by the use of a conversion module are avoided.

The invention discloses a high-voltage discharge circuit suitable for a storage battery power supply and an electric flame stove. The high-voltage discharge circuit comprises an inversion driving module, a boosting transformer T1, at least three groups of active bridge rectifier modules and discharge modules corresponding to the active bridge rectifier modules. Through combination of driving of the active bridge rectifier module, voltage / current double-closed-loop feedback and real-time PWM signal output control of the control chip U1, current difference of each discharge branch is eliminated, the problem of uneven branch current is solved, and ring current and reactive power loss between branches are eliminated; a diode in a voltage doubling rectifying circuit and a bleeder resistor of a resonance circuit in the prior art are abandoned, an active bridge type rectifying module is adopted for driving, a PWM signal is dynamically adjusted through the low ESR characteristic of a capacitor C1 and closed-loop control, extra power loss is avoided, the working temperature of the circuit is controlled to be below 85 DEG C, and the service life of the circuit is prolonged. And the continuous service life of components in the circuit is prolonged.

The invention discloses a fault reconstruction method and device for a power distribution network, terminal equipment and a storage medium, and belongs to the technical field of power grid reconstruction, and the method comprises the steps: obtaining the power data of a fault period of the power distribution network in real time, and the number of time periods between the current moment and the fault occurrence moment; then, according to the power data and the time period number, with the purpose of minimizing the sum of the load power loss amount and the power failure cost, a line recovery optimization model and corresponding constraint conditions are constructed; and finally, under each constraint condition, solving the line recovery optimization model to obtain the line switch state of each line when the sum of the load power loss and the power failure cost is minimum, and performing fault reconstruction on the current power distribution network according to the line switch state. Through the implementation of the method and the device, the problem that the obtained reconstruction scheme is unreasonable due to the fact that the loss of the load in the power failure period cannot be accurately evaluated when the static constant load power failure loss is used for power grid reconstruction in the prior art can be solved.

A method for estimating friendly metal losses associated with wireless power transfer from a wireless power transmitter to a wireless power receiver can include obtaining an indication of received power including rectifier voltage and rectifier current of the wireless power receiver and computing a friendly metal power loss based on the indication of rectifier voltage and rectifier current of the wireless power receiver and one or more coefficients corresponding to a baseline wireless power transmission between the wireless power transmitter and the wireless power receiver. The rectifier voltage can be a rectifier output voltage, and the rectifier current can be a rectifier output current. Computing the friendly metal power loss can use an equation having a formPl⁢o⁢s⁢s=a·IT⁢X2+b·Irect2+c·Vrect2,where b is a coefficient relating to the rectifier current, c is a coefficient relating to the rectifier voltage, a is a coefficient relating to transmitter current ITX.

The invention relates to the technical field of engines, and discloses a dynamic control method, device and equipment for the angle of an adjustable guide vane of a gas compressor, and the method comprises the steps that when it is detected that an anti-icing valve is opened, the initial anti-icing air entraining amount is obtained, and the anti-icing air entraining amount is continuously obtained; determining a first angle offset based on the initial anti-icing air entrainment amount and the current anti-icing air entrainment amount; surge margin verification is carried out based on a surge margin compensation model, and a second angle offset is obtained; determining a target angle offset based on the first angle offset and the second angle offset; and controlling the angle of the adjustable guide vane of the gas compressor to adjust the target angle offset. According to the method, the target angle offset is obtained from the first angle offset based on the anti-icing air entraining amount and the second angle offset based on the surge margin, the anti-icing requirement and the surge safety are both considered, and accurate dynamic control over the adjustable guide vane of the gas compressor is achieved based on the target angle offset. The power loss caused when the anti-icing valve is opened is effectively compensated, and the power requirement of the helicopter is met.

The invention discloses a transmission mechanism and an all-terrain vehicle using the transmission mechanism, the transmission mechanism comprises a linkage assembly, an output shaft, two sets of transmission parts, a sensor module and a controller, the linkage assembly is connected with the output shaft, and the two sets of transmission parts are arranged on the two sides of the linkage assembly respectively; each transmission part comprises a first transmission part, a second transmission part, a supporting part, a first friction part, a second friction part, an extrusion module and a driving unit, the first transmission parts are connected with the output shaft, the second transmission parts are rotationally connected with the supporting parts, and the first friction parts are connected with the first transmission parts; the second friction piece is connected with the second transmission piece and abuts against the first friction piece, the extrusion module abuts against the first friction piece or the second friction piece, the driving unit is connected with the extrusion module, and the controller is electrically connected with the driving unit and the sensor module. According to the transmission mechanism, the power loss is reduced, the all-terrain vehicle is helped to escape, and the control stability of a driver is improved.

The invention discloses a near-infrared flexible polarized photoelectric detector and a preparation method thereof. The photoelectric detector comprises an Sb2Se3 micron wire, a PET flexible substrate, a metal Ag electrode, a silver wire and polydimethylsiloxane (a PDMS mixture). According to the preparation method, an effective metal-semiconductor-metal (M-S-M) structure is constructed by combining the Sb2Se3 micron wire and the Ag electrode, curing packaging is carried out by adopting a PDMS mixture, the incident light transmittance is improved, meanwhile, the response speed of a device can be greatly improved through ohmic contact formed by the micron wire and the Ag electrode, and the power loss of the device is remarkably reduced. Compared with the prior art, the detector provided by the invention still keeps a stable and high extinction ratio under mechanical bending deformation, and realizes sensitive polarization, quick response and stable performance of a near-infrared band at the same time.

The invention discloses a vehicle-mounted power supply short-circuit heat prediction method based on big data analysis, and the method comprises the following steps: collecting real-time operation data, and storing the data in a data cache, thereby obtaining a cache time sequence signal; filtering the cached time sequence signal, and extracting a basic feature sequence; constructing an RC network model based on the basic feature sequence, and converting a fractional order operator into an equivalent integer order model; performing parameter estimation on the equivalent integer order model to generate a thermal prediction model; taking the thermal prediction model and the basic feature sequence as joint input and output power loss features; inputting the power loss characteristics into a quantile regression forest model to form a heat prediction result; comparing the heat prediction result with a heat threshold value and a temperature rise threshold value, and outputting a control trigger signal; and calling parameters in a control strategy library according to the control trigger signal to generate a control strategy. According to the invention, vehicle-mounted power supply short-circuit heat prediction is realized.

The invention provides an EMS-based multi-source cooperative switching and interlocking control method and system and a storage medium, and the method comprises the steps: firstly, monitoring the state of a power grid in real time, and achieving the quick switching operation through an STS if the power grid is abnormal; then, photovoltaic power supply is started preferentially, when photovoltaic power supply is not available, phase difference is detected in real time through a DZZB-A module, the rotating speed is dynamically adjusted based on the phase difference so as to meet dynamic grid-connected control of an oil engine (diesel generator), and impact-free grid connection is achieved; finally, based on the power supply power and the load power, a PCS charging and discharging mode is intelligently switched, and the stability of the power supply system is improved; meanwhile, through a double-path auxiliary power redundancy mechanism, a working power supply of the STS cabinet is ensured, and a power loss blind area of a control circuit is eliminated; in addition, through safety interlocking logic, automatic breaking of the power grid and the oil engine is achieved, and the problem of short circuit caused by parallel connection of power sources is prevented. The power supply system reliability is improved.