743 results about "Current load" patented technology

The invention relates to the technical field of intelligent control, in particular to an intelligent power optimization scheduling method in a new energy grid-connected scene, which comprises the following steps of: acquiring a current load, a rated load, an adjustment rate and a temperature rise value through a data interface, and normalizing to generate a characteristic parameter matrix; the product of the adjusting rate and the temperature rise value is used for calculating the correlation degree with the aging factor to obtain an elastic weight, extracting the voltage stability and the weight, inputting the voltage stability and the weight into a Dijkstra algorithm to screen a path meeting the safety margin, monitoring the slope of an inertia change curve, adjusting a compensation coefficient through fuzzy PID control, and feeding back the compensation coefficient to correlation degree calculation. According to the method, multi-source parameters are fused through a rule tree structure, the load regulation rate and the aging factor weight are dynamically distributed, bus voltage stability and elastic weight path optimization are combined, a synchronous inertia margin safety correction system is constructed, the system response precision, the state cooperation efficiency and robustness are improved, local optimum is avoided, and the system reliability is improved. And the standby capacity configuration and the frequency advance correction capability are optimized.

The invention discloses a secondary frequency modulation optimization control method under a low-load working condition, relates to the technical field of power grid resource optimization, and is used for solving the problem that a control strategy under the low-load working condition is not fully considered in the prior art. The current load interval is recognized, and control parameter correction is conducted on the unit located in the low load interval; calculating a total output power reference value; carrying out calculation by adopting a self-adaptive optimization algorithm, and carrying out power fine distribution to obtain an optimal charging and discharging instruction of each energy storage unit; and the output power is adjusted in real time through double-closed-loop control. The invention further discloses a secondary frequency modulation optimization control device under the low-load working condition, electronic equipment and a computer storage medium. By dynamically correcting the control parameters of the low-load thermal power generating unit and cooperatively distributing the hybrid energy storage power in combination with the adaptive optimization algorithm, the safety and economical efficiency of the energy storage system are guaranteed.

The invention provides an optical storage parallel network control method, which comprises the following steps: calculating the current load rate percentage of each residual unit according to the connection relation and electrical path information of the residual units after isolation; evaluating the available margin capacity and the frequency regulation bearing capacity of the remaining units, matching the available margin capacity and the frequency regulation bearing capacity with a specific power value and a frequency regulation requirement which need to be compensated, and determining a feasible unit combination scheme for fault recovery; generating a power redistribution list and a frequency adjustment responsibility distribution table according to the direct current bus connection mode of the optimal unit recombination, and obtaining an output power set value and a frequency adjustment parameter of each unit after adjustment; and extracting the continuous power supply time value of the optical storage parallel network, updating the total power supply capacity value of the optical storage parallel network, and maintaining the continuous power output and frequency stability after the fault of the optical storage parallel network.

The invention discloses a factory equipment predictive maintenance scheme optimization method based on reinforcement learning, and relates to the technical field of equipment maintenance scheme prediction, and the method comprises the steps: carrying out the fusion through employing a space-time attention mechanism based on an equipment health index, equipment operation duration and a current load level, generating an equipment state vector, constructing a reinforcement learning framework, and carrying out the optimization of a factory equipment predictive maintenance scheme. A multi-target reward function is embedded in the reinforcement learning framework, a PPO algorithm is adopted for optimization, a reinforcement learning model is generated, the reinforcement learning model is trained by using the equipment state vector, the trained reinforcement learning model is obtained, the trained reinforcement learning model is deployed to an actual industrial control unit, the latest equipment state vector is received in real time, and the final equipment state vector is obtained. And obtaining an optimal maintenance strategy. And converting the optimal maintenance strategy into a specific maintenance instruction and executing the specific maintenance instruction. Through the factory equipment predictive maintenance method, rapid response to emergencies is facilitated, greater loss is avoided, resource allocation is optimized, and enterprise competitiveness is enhanced.

The invention provides a charging pile power distribution method and system based on dynamic load balancing, and the method comprises the following steps: obtaining the local state information of each charging pile, the state information at least comprises the charging queuing length, the current vehicle charge state, the current load power, the battery health state, the predicted residence time, the electricity price information and the power grid load state; based on the historical charging behavior, the electricity price fluctuation and the traffic flow data, the vehicle access frequency, the electricity price trend and the power demand of each charging pile in the future time period are predicted through a time sequence neural network; a prediction model is constructed; according to the method, forward-looking power planning is realized by entering a multi-dimensional prediction mechanism; the power distribution efficiency is improved by adopting a local collaborative game; the self-adaption and generalization ability is realized through reinforcement learning, and the robustness of a scheduling strategy in multiple scenes is enhanced; through a multi-target scheduling index, the electricity price, the battery life, the waiting time and the power grid load are optimized at the same time.

The invention provides an intelligent optimization control method for the energy consumption of a packaging production line, and the method comprises the steps: collecting the processing data of the production of products of two specifications of vacuum can sealing and normal pressure can sealing, extracting the load change of a conveying belt during the switching of different specifications, and obtaining the fluctuation range of the load of the conveying belt; predicting the operation power scheduling of the equipment according to the instantaneous peak value and high-frequency fluctuation characteristics of the power demand, and outputting energy consumption peak value prediction data of the equipment during specification switching; determining and outputting an operation time sequence plan according to the energy consumption peak prediction data of the equipment during specification switching; monitoring the dynamic change of the conveyor belt load in real time according to the operation time sequence plan, obtaining the deviation value of the current load and the predicted load, and judging whether the deviation value affects the energy consumption distribution mode of the whole production line or not; and through the new energy consumption distribution result, generating and executing an equipment cooperative operation control instruction in combination with the operation time sequence plan.

The invention discloses a regulation and control method and device for a load power supply loop, equipment, a medium and a program product, and relates to the technical field of servers, and the method comprises the steps: obtaining the current change rate, the contact temperature rise rate and the voltage change rate of a load interface when a hot plug event occurs, so as to comprehensively reflect the rapid change condition of a circuit state at the hot plug moment; then, inputting the data into a surge probability prediction model to obtain a surge occurrence probability so as to pre-judge a surge risk in advance; and when the surge occurrence probability is greater than or equal to a first preset probability, the resistance-capacitance parameters of the load power supply loop are calculated according to the monitored load interface current, load interface voltage and load interface temperature, so that when a hot plug event occurs, the circuit can be rapidly adjusted according to the resistance-capacitance parameters, abnormal changes of the current and the voltage are inhibited in time, and the reliability of the hot plug event is improved. The protection response speed is improved, equipment damage caused by untimely protection is effectively avoided, and the server is ensured to stably operate under complex conditions such as load hot plug.

A LED circuit with a sequence function includes a load component, a capacitive component, a current load, and a voltage processor. The load component provides a resistance value. The capacitive component is connected to the load component in series at anode. The capacitive component provides a capacitance value, and generates an inner voltage at the node. The current load is connected in parallel to the load component and the capacitive component to provide a current path. The voltage processor receives the inner voltage and a threshold voltage, and compares the inner voltage with the threshold voltage to generate a comparison signal. The LED circuit counts time to acquire a time value from a starting time when the voltage processor starts to generate the comparison signal to a time when a level of the comparison signal changes, and uses the time value for sequencing.

The invention provides a robust control automatic setting method for a constant-pressure water supply system, and the method comprises the steps: obtaining a system working condition in real time, and extracting multi-dimensional state parameters including real-time flow, pressure deviation, current deviation and power deviation; the current load working condition is judged according to the pressure deviation, disturbance characteristics are analyzed by integrating all parameters, and the disturbance grade and type are determined. On the basis, robust control parameters are automatically set in combination with real-time working conditions, load conditions and disturbance characteristics of the system. And finally, performing multi-stage cooperative control on the system by using the set parameters, so that the constant-pressure water supply system is automatically set. According to the robust control automatic setting method for the constant-pressure water supply system, load working conditions and disturbance characteristics are recognized based on multi-dimensional state parameters, robust control parameters are self-set in a targeted mode, and automatic setting of the constant-pressure water supply system is achieved through multi-stage cooperative control. Therefore, the intelligent level of the constant-pressure water supply system and the adaptability in different operation environments are effectively improved.

A modular and scalable AC / DC substation transforms AC voltage to DC voltage for driving a high-voltage and high-current load, such as a heavy work machine. Sized to fit within a standard high-cube ISO shipping container, the substation includes a main transformer attached at a center of a rectangular base with a pair of controlled rectifiers positioned on the base downstream from the main transformer, aligned parallel to a lateral axis of the base, and substantially symmetrical to a longitudinal axis of the base. The arrangement of these components on the base, together with lowpass filters and switchgear, achieves high power density for the substation, provides balanced mass for stability during shipment and placement, and helps protect personnel from accidental electrical arcing.

The invention discloses a self-adaptive transformation ratio adjustment electric quantity metering method and device, the device comprises a high-voltage metering device and a control center, and the high-voltage metering device is composed of a voltage transformer, a current transformer and an electric energy meter. The core innovation point is that the current transformer is provided with a plurality of secondary windings, each winding is respectively connected with a relay with a multi-gang switch contact, the output end of the relay is connected with the electric energy meter, and the relay and the control center realize linkage control. The control center drives a multi-gang switch contact of the relay to be automatically switched to a secondary winding adaptive to the current load by monitoring the current state of the load in real time; factors such as temperature, humidity and the year of a home-entry power grid are introduced to correct a current measured value, and the accuracy of electric quantity metering is improved. Meanwhile, the control center records transformation ratio switching data in real time, reliable support is provided for time-of-use electricity price execution, demand side response and electric quantity tracing, and the intelligence and refinement level of electric power metering is remarkably improved.

The invention discloses high-voltage wiring harness connector terminal fretting wear test equipment which comprises an equipment base, a high-frequency vibration exciter and a lifting platform are mounted on the equipment base, and a mounting platform is arranged at the top of the lifting platform; a left test piece mounting loading mechanism and a right test piece mounting force measuring device are arranged on the mounting platform. The device can realize a multi-physics field coupling test, current-carrying friction and arc erosion of an electric contact surface in a real working condition are simulated by combining a current load with high-frequency mechanical wear, and the electric-mechanical coupling wear characteristic of a new energy automobile charging terminal is accurately reproduced. The device supports the dynamic adjustment of normal load, simulates the contact pressure change of the left and right test samples of the test terminal in the plugging process through the test sample pin and the test sample jack, can be used for researching the relevance between the fretting wear and the contact resistance of the test terminal under different loads, and realizes the test of the terminal under complex working conditions in a laboratory environment. The test process is convenient, efficient and accurate, and the test cost and the test period are greatly reduced.

The invention belongs to the technical field of AGV path planning, and particularly relates to an AGV path planning method and system for a production line, and the method comprises the steps: obtaining an instantaneous speed sequence, a planning speed sequence, a current remaining electric quantity, a current load mass, a rated load, and a safe electric quantity of a single transportation task of an AGV; calculating the weight of the current land parcel where the AGV is located in the warehouse area divided into the plurality of land parcels; obtaining the current passing resistance; calculating an electric quantity risk factor; the load condition and the electric quantity risk of the AGV are integrated, the situation passing cost is calculated, the comprehensive cost is calculated based on the geometric distance between the adjacent land parcels and the fluctuation condition of the situation passing cost, and the optimal path is obtained; and performing trajectory interpolation on the optimal path, generating a smooth motion trajectory to control the AGV to run, and feeding back operation data to the central scheduling system to realize optimization. The technical problems of low path planning efficiency and high energy consumption in the prior art are solved.

The present invention relates to the field of storage, and specifically to a PCIe dual-port SSD low-power control device and method. The device includes a load prediction unit and a power consumption control unit. The load prediction unit uses the PCIe power management module (ASPM)'s judgment result on the link idle state and the margin value of the receive / transmit buffer as input to calculate the current load state of each of the two ports and output a load level value. The power consumption control unit uses the load level output by the load prediction unit to timely adjust the operating state of each SSD module to achieve SSD power consumption control. The present invention detects the business pressure and load conditions of the two ports and adaptively adjusts the operating state of each SSD module to achieve dynamic adjustment of SSD power consumption. While ensuring timely and accurate data response, it minimizes the power consumption of the entire disk and improves the energy saving effect of the data center.

The invention provides a comprehensive energy self-adaptive scheduling method based on meteorological prediction, and aims to solve the problems that an existing energy system lags in response to meteorological disturbance and is insufficient in load regulation precision, and the comprehensive energy self-adaptive scheduling method comprises the following steps: fusing second-level meteorological disturbance data, electrical load power data, energy storage device charge state data and power grid boundary power flow data; constructing a disturbance response feature set, and establishing a time correlation mapping structure between a disturbance variable and a load variable; according to the method, a disturbance trend is predicted based on a mapping structure, an index set of disturbance direction, intensity and sensitive sections is formed, a dynamic regulation capability vector is generated in combination with a current load state, a scheduling optimization model meeting multiple operation constraints is constructed on the basis, a cooperative control strategy set is output, and the dynamic regulation capability vector is obtained. Finally, the control strategy is converted into a control instruction, the control instruction is accurately acted on a power generation device, an energy storage device and a load device, second-level dynamic self-adaptive scheduling of the comprehensive energy system on meteorological disturbance is achieved, and the system response capacity, stability and energy utilization efficiency are improved.

The invention is suitable for the technical field of energy storage control, and provides a direct current energy storage control system of a distributed sodium ion battery, which comprises a distributed energy storage unit, a direct current bus network, an intelligent monitoring unit and an energy management unit, the distributed energy storage unit is connected with the direct current bus network; the intelligent monitoring unit is connected with the sodium ion battery module in the distributed energy storage unit, and transmits monitored data to the energy management unit through the CAN communication module; the energy management unit is connected with the non-isolated bidirectional DC converter in the distributed energy storage unit, performs fault analysis based on the received parameters, generates a duty ratio adjustment instruction, and dynamically adjusts the duty ratio of the non-isolated bidirectional DC converter according to the duty ratio adjustment instruction. And the bus voltage of the direct-current bus network is adaptively adjusted within the preset range. According to the method, the loss in the energy conversion process is reduced, and the energy utilization efficiency is improved by flexibly configuring the energy storage capacity in a direct-current load scene.

The invention discloses a control method and device of a photovoltaic air conditioner and a computer readable storage medium. The method comprises the following steps: acquiring a plurality of historical generated powers of the photovoltaic air conditioner in a historical time period; inputting the plurality of historical power generation powers into a power prediction model so as to predict a plurality of predicted power generation powers of the photovoltaic air conditioner in the future time period by using the power prediction model according to the plurality of historical power generation powers; generating a control strategy for controlling the photovoltaic air conditioner at each sampling time point in the future time period according to each predicted generation power and the current load power of the photovoltaic air conditioner; and the photovoltaic air conditioner is controlled to operate at the sampling time points according to the corresponding control strategies in sequence. According to the invention, the technical problem that the photovoltaic power generation power cannot be accurately predicted under the environment that the weather data is difficult to obtain due to the fact that networking cannot be carried out or network signals are poor in the prior art is solved.

The invention relates to the technical field of data processing, in particular to an AI large model multivariate data fusion method and system based on multiple modalities, and the method comprises the steps: collecting multi-source data; performing classification abnormity judgment; abnormal type identification; calculating severity; switching fusion modes; and outputting an alarm. According to the method, parameters such as the spindle temperature, the rotating speed fluctuation rate, the vibration acceleration, the current load, the acoustic emission energy spectrum peak value, the cutting force variance and the cooling liquid metal particle concentration are acquired and fused step by step in multiple dimensions in the machining process of the numerical control machine tool, so that the running state of the machine tool is dynamically sensed from multiple angles; furthermore, the physical essence of tool wear and material peeling is revealed through the coupling relationship between the cutting force variance and the metal particle concentration, and meanwhile, the dynamic stability change of the machine tool structure is captured by combining the spindle rotating speed fluctuation ratio; the problem that state monitoring is not accurate in the numerical control machining process due to data isolation and fusion strategy staticization is effectively solved.

The invention relates to the technical field of manufacturing execution systems, in particular to an intelligent scheduling method integrating demand prediction and supply matching, which comprises the following steps of: acquiring to-be-scheduled order information and a workshop real-time resource state in a manufacturing execution system, constructing an order demand feature vector, the method comprises the following steps: acquiring an equipment precision retentivity value, a current load rate value, an energy consumption level value and an operator skill proficiency value, and constructing a resource supply capability vector; according to the method, when an urgent order insertion instruction is received, a clear decision basis is provided, a rigid scheduling locking block which must be kept unchanged and an adjustable liquid adjustable scheduling block which can be adjusted can be distinguished, only the latter is subjected to accurate splitting and backward moving operation, and the target-clear local adjustment mode is adopted, so that the operation efficiency is greatly improved. The huge calculation overhead and the violent fluctuation of the production plan caused by the traditional global rescheduling are avoided, and the agility of the manufacturing system to deal with the market change is enhanced.

The invention discloses a thermal power generating unit dynamic coupling compensation coordination control system, which belongs to the technical field of thermal power generating units, and comprises a dynamic coupling compensation module, a self-adaptive sliding pressure optimization module and a coordination control execution module, the dynamic coupling compensation module is used for receiving a load instruction sent by a preset control terminal and generating a dynamic compensation signal; the self-adaptive sliding pressure optimization module is used for correcting a preset initial sliding pressure curve in real time based on the time-varying characteristics of the actual operation parameters of the thermal power generating unit, superposing the current load demand of the thermal power generating unit and the heat storage capacity change of the boiler in the initial sliding pressure curve, and dynamically generating an optimal operation initial pressure target value; and the coordination control execution module is used for integrating the dynamic compensation signal and the optimal operation initial pressure target value into a unified control instruction. The dynamic coupling compensation module, the self-adaptive sliding pressure optimization module and the coordination control execution module are arranged, so that the manual intervention requirement is remarkably reduced.

The invention discloses a cross-cabinet power scheduling method, device and system applied to a charging station, the cross-cabinet power scheduling method can be applied to the technical field of energy management of the charging station, and the method comprises the following steps: when the charging demand of a first power cabinet exceeds the rated total power thereof, the first power cabinet is switched to the second power cabinet; obtaining dynamic schedulable power of at least one second power cabinet and a peak power demand in a future time window; wherein the first power cabinet is any one power cabinet of the charging station, and the second power cabinets are other power cabinets; the dynamic dispatchable power is determined based on the rated total power of the power cabinet, the current load power and the safety margin adjusted according to the real-time state of the charging gun in the power cabinet; determining a resource occupation priority of each second power cabinet based on the dynamic schedulable power and the peak power demand; and calling the power resource of the corresponding second power cabinet through the corresponding cross-cabinet contactor group according to the priority. The operation stability and the power resource utilization rate of the charging station are improved.

The invention discloses a motor state monitoring method and device based on a multi-modal sensor, and the method comprises the steps: firstly, carrying out the comprehensive analysis of the current and rotating speed data of a motor, and explicitly constructing a working condition vector which can accurately represent the current load and rotating speed state of the motor; then, self-adaptive adjustment and reconstruction are carried out on original vibration frequency spectrum features and current frequency spectrum features through modes such as an attention mechanism by taking a working condition vector as guidance, so that feature components introduced by working condition changes are stripped, and pure features which are highly related to a fault state and basically irrelevant to a working condition state are extracted; and furthermore, the decoupled pure features are fused to effectively excavate the complementary relationship between vibration and current information, and finally, accurate fault diagnosis is realized. In this way, the accuracy and reliability of motor state monitoring are improved.

A system includes a plurality of power modules connected in parallel and a variable current load controller coupled to the plurality of power modules. The input terminals of the plurality of power modules are configured to be coupled to an output of a fuel cell stack, and the output terminals of the plurality of power modules are configured to supply power to a forklift. The plurality of power modules is further configured to provide electrical isolation between the fuel cell stack and the forklift. The variable current load controller is configured to regulate power distribution among the plurality of power modules.

The invention relates to the technical field of energy-saving optimization control, in particular to an MAU energy-saving optimization control method and system based on model prediction, and the method comprises the following steps: obtaining the current operation state parameters of an MAU, defining an air supply temperature range and an equipment limit, and the operation disturbance integration degree is calculated by combining the current load. According to the method, MAU operation state parameters are obtained in real time, the incidence relation between the equipment limit of the air supply temperature and the current load is defined, and the internal influence rule between the actual operation of the equipment and the disturbance condition is described; meanwhile, the filter pressure difference and the coil pipe dirt coefficient aging index are clearly recognized, direct quantization correlation with the accumulated operation time and the average load rate is established, the regularity of aging state change is fully excavated, and therefore the accuracy of state parameter prediction is improved.

The invention discloses an intelligent control method for power distribution and efficiency optimization of an energy storage power station, and the method comprises the steps: obtaining real-time operation data and historical load records of all PCS units in the energy storage power station, and obtaining a current load change trend through data fusion processing; according to the current load change trend, a fuzzy logic algorithm is adopted to analyze the performance state and the output proportion of the PCS unit, and the initial load distribution weight of each unit is determined; aiming at the optimized distribution scheme, generating a self-adaptive priority ranking rule by adopting a genetic algorithm, judging whether the rule covers real-time state change or not, and obtaining a dynamic ranking list; extracting a high-priority PCS unit from the dynamic sorting list, obtaining an equipment loss index of the high-priority PCS unit, and determining an output increase proportion of a low-loss unit through index comparison processing; and according to the output increase proportion, fusing the resource utilization rate data, and if the utilization rate is lower than a preset threshold value, redistributing idle unit power to obtain overall efficiency improvement configuration.

The invention discloses a power supply test method for simulating an equipment load and electronic equipment, and relates to the technical field of electronics, and the method comprises the steps: transmitting test current information to a first control part through a management controller, the test current information being used for indicating a to-be-simulated specified load current of a first load module; according to the specified load current, the first control part controls the first load module to carry out current pumping on a power supply of the first load module; voltage data of the power supply of the first load module and current data of the power supply of the first load module are obtained through the first control part, and a first test result is obtained. The technical problem of insufficient accuracy and comprehensiveness of the power supply test method of the equipment load in the related technology is solved, and the technical effect of improving the accuracy and comprehensiveness of the power supply test method of the equipment load is achieved.

The invention discloses a heat conduction type heat dissipation cable, and relates to the technical field of heat dissipation cables, the heat conduction type heat dissipation cable comprises a central capillary main pipe, a plurality of conductor strands are arranged on the outer side of the central capillary main pipe, a heat dissipation ring is arranged on the other side of each conductor strand, and a plurality of first heat dissipation holes are integrally formed in the heat dissipation ring; according to the invention, heat generated by the conductor strands is quickly transmitted through the heat conducting column, and the magnetic conductive sheet and the magnetocaloric material sheet are matched to generate magnetocaloric effect by utilizing magnetic field intensity fluctuation caused by current change: when the current is increased, heat is released to strengthen evaporation of a working medium, and when the current is reduced, heat is absorbed to directly cool, so that a self-adaptive heat adjusting mechanism is formed; heat can be quickly transferred through evaporation-condensation of low-boiling-point fluid through phase change circulation of the central capillary main pipe and the branch capillary pipes, and multi-path heat dissipation of the heat dissipation ring and the fins is combined, so that the heat dissipation efficiency under different current loads is improved, and the problem of local overheating is effectively avoided.

A microgrid controller of a microgrid includes a communication interface configured to receive load information corresponding to a current load demand of a plurality of loads connected to the microgrid and output control signals for controlling energy resource systems associated with the microgrid, which include a non-stabilizing group and a stabilizing group; and one or more processors, coupled to the one or more memories, configured to execute a load stabilization algorithm to generate the one or more control signals based on the load information. Executing the load stabilization algorithm includes generating, based on the load information, one or more first control signals to dynamically control an amount of total output power provided by the stabilizing group to a power distribution network of the microgrid in order to stabilize one or more cyclic loads on the power distribution network and to maintain the non-stabilizing group at a substantially constant load.

The invention provides a new energy automobile battery pack temperature abnormity real-time monitoring and fault diagnosis method, and relates to the technical field of new energy automobile battery management, and the method comprises the steps: building a temperature gradient field and heat flow conduction path topological relation through obtaining the temperature and current load values of a battery unit, and carrying out the temperature field reconstruction; a theoretical temperature response value is calculated based on a current load, correction is carried out in combination with a space thermal coupling strength distribution matrix to obtain a temperature reference value, a dynamic characteristic quantity is extracted to determine an abnormal evolution mode by calculating a deviation degree between a measured value and the reference value and a time evolution trajectory thereof, and finally a fault source position is positioned. According to the invention, the battery abnormity detection accuracy and the fault diagnosis efficiency can be improved.

The invention is suitable for the technical field of computers, and particularly relates to a dynamic adjustment method and device for server power consumption and a storage medium. The dynamic adjustment method comprises the following steps: acquiring a current load value of a server in a current sampling period; judging whether the fluctuation of the working state of the server generates a preset number of times in a preset time period or not according to the current load value, and adjusting a preset load threshold value of the server and the CPU frequency drop time delay; whether the current load value is larger than a preset load threshold value or not is judged; if yes, the CPU frequency of the server is set to be the maximum value; if not, the target CPU frequency of the server in the next sampling period is calculated, and the CPU frequency of the server is adjusted to the target CPU frequency. Compared with the prior art, the method has the advantages that short periodic task characteristics can be captured, the CPU frequency reduction time delay and the preset load threshold value can be automatically changed, and dynamic frequency modulation is performed on the CPU, so that the power consumption can be reduced, and the maximum performance of the server in various load scenes can be exerted.