128 results about "Power model" patented technology

The invention relates to the technical field of network security, and particularly discloses an edge device network threat detection method and system based on an electric power large model, and the method comprises the steps: capturing a network message sequence in real time, extracting a time sequence randomness feature and a semantic deviation feature from a time dimension and a protocol dimension, and carrying out the fusion to form a comprehensive threat feature vector; performing multi-dimensional feature analysis and time sequence modeling by adopting a lightweight electric power large model to realize millisecond-level threat assessment; establishing a multi-level response mechanism, dynamically triggering a differential protection strategy according to the threat level, and ensuring the reliability and consistency of response actions through digital signature and collaborative verification; according to the method, the complex network attack in the power edge equipment can be effectively identified, the threat detection accuracy and the system defense capability are improved, and the strict requirements of a power system on real-time performance and reliability are met.

The invention discloses a flood storage and detention area flood diversion process simulation method and device based on a hydrodynamic model, and the method comprises the steps: obtaining the landform, river section, dike engineering parameters, and real-time hydrological and meteorological data of a flood storage and detention area, constructing a basic parameter library, and storing the basic parameter library in a data input module; constructing a hydrodynamic model calculation module by taking a hydrodynamic equation as a theoretical basis on the basis of the basic database, and combining a finite element volume method; receiving a numerical calculation result, analyzing real-time parameters through a dynamic simulation module so as to match actual hydrological parameters, and performing comparison under multiple scenes; and transmitting the hydrological parameters and the comparison data to a result output module, and outputting key parameters of the flood diversion process and a risk assessment result. The method has the advantages that high-frequency coupling of a hydrodynamic model, multi-source dynamic data, a cross-domain model and an engineering control system is achieved, and the problems of data lag, model isolation and control disjunction in traditional simulation are solved.

The invention provides a distributed scheduling method for railway traction stations and peripheral micro-energy grids, and belongs to the technical field of energy supply of micro-energy grid groups containing the railway traction stations, and the method comprises the steps: building a micro-energy grid sharing mutual aid grid structure containing the railway traction stations, obtaining a power model of each railway traction station, and optimally configuring energy storage equipment, obtaining operation constraints of the energy storage equipment; constructing an energy sharing benefit function by taking each micro-energy network agent as a game main body and taking individual benefit maximization as a target, setting constraint conditions, and establishing an energy sharing non-cooperative game model; and solving the energy sharing non-cooperative game model by adopting an alternating direction multiplier algorithm to obtain a distributed energy transaction behavior result and a price result. According to the method, distributed solution is carried out on the micro-energy network energy sharing non-cooperative game model based on the alternating direction multiplier method, original centralized optimization is converted into coupling optimization among a plurality of micro-energy network agents through interactive variables, the efficiency of the whole iteration process is guaranteed, and the privacy of each energy network is protected.

The application provides a highway charging load prediction method and control system based on traffic flow power. Through a second-by-second specific power model of different electric vehicle types on the highway, factors such as road slope, vehicle load, electric vehicle braking recovery characteristics, instantaneous speed and acceleration can be considered to achieve more accurate energy consumption modeling. By establishing a specific power operation mode distribution library of different vehicle types, using a shock wave model and a cellular transmission model to solve, quantifying the congestion propagation process, dynamically correcting the specific power calculation parameters, only the road section parameters and average speed are needed to calculate the energy consumption under complex road conditions. The driver's range anxiety is quantified as a dynamic variable, and charging decision rules are established for different scenarios. The charging probability is dynamically corrected based on the queue length, weather, and driver type, and an electric vehicle charging time prediction model is established based on different service area charging scenarios.

The invention discloses a wind, light and green power coupled pumping unit well group operation collaborative optimization method. The method comprises the following steps: acquiring field data of a multi-energy micro-grid pumping unit well group; establishing a wind and light output uncertainty model, an energy storage battery model, a pumping unit power model and bidirectional AC / DC converter equipment; based on each model, establishing a multi-objective optimization scheduling model for the intermittent pumping operation of the multi-energy micro-grid pumping unit well group; an NSGA-II method is adopted to solve the established multi-objective optimization scheduling model, and a Pareto optimal scheduling scheme is obtained; and carrying out comprehensive evaluation and decision analysis based on an entropy weight TOPSIS method, and selecting an optimal scheme from a Pareto optimal scheduling scheme set obtained by NSGA-II. According to the multi-energy micro-grid rod-pumped well group off-peak interval pumping operation multi-objective optimization method based on NSGA-II and entropy weight TOPSIS, the power utilization requirement of the rod-pumped well group can be met, the working system of rod-pumped well group interval pumping operation is optimized, the economical efficiency and stability of the operation of a rod-pumped well interval pumping system under a wind-solar storage micro-grid are ensured, and the green power consumption capability of the system is enhanced.

The invention discloses a power system cascading failure chain modeling and blocking method, device and system considering source-load double-end uncertainty, and a medium. The method comprises the steps of constructing source-load uncertainty input distribution (wind power introduces Weibull distribution based on a wind speed segmented power model, photovoltaic introduces Beta distribution based on an irradiance output model, and a load side introduces a normal distribution fluctuation model); an MSFF method is adopted to construct a unified source-load stochastic power flow model, and a multi-scene power flow state set is obtained; introducing a power flow out-of-limit criterion and a hidden fault probability function, building a cascading fault propagation model fusing wind-solar load uncertainty, and dynamically simulating fault chain evolution; and formulating a staged collaborative blocking strategy (cutting off non-critical load emergency control, quickly responding a battery energy storage system and dynamically adjusting a critical line protection constant value) to realize real-time fault suppression. Simulation shows that the method is suitable for power system security defense in a high-proportion new energy penetration scene, and has good engineering adaptability and dynamic control performance.

The invention discloses a polar region environment-oriented two-stage micro-siting optimization method for a wind generating set, and relates to the technical field of polar region renewable energy planning and wind power generation, the optimization method comprises the following steps: polar region environment parameter initialization and scene modeling; the first stage is grid primary selection based on mixed integer linear programming; the second stage is coordinate refinement based on a multi-population genetic algorithm; and scheme output and efficiency evaluation. According to the method, a sector reweighting mechanism of extremely cold correction parameters is realized through reweighting of biochemical parameters and scenes in an environment special for a polar region, the extremely cold correction parameters are directly embedded into a wind regime scene set and a power model, and the problem that a conventional land model can obviously underestimate or overestimate single-machine power and wake flow propagation distance under extremely low temperature and low roughness conditions, so that the reliability of the model is improved is solved. Therefore, the power prediction and wake flow loss evaluation are more practical under the polar region conditions such as the south pole, so that the engineering reliability of site selection decision and the accuracy of generating capacity prediction are improved.

The invention relates to the field of fish habitat evaluation, in particular to a spawning migration type fish full life history stage suitable habitat inversion method based on a hydrodynamic model, and the method mainly comprises the steps: (1) collecting spawning migration type fish data, hydrological data and topographic data; (2) determining life history stages of the fishes and the actual number of the fishes; (3) establishing one-dimensional hydrodynamic models of different life history stages; (3) grouping the water depth and the flow velocity of each life history stage, and calculating the number frequency of fishes in each interval; (4) constructing a habitat suitability curve of water depth and flow velocity; and (5) evaluating a suitable habitat. According to the method, the suitable habitat of the spawning migration type fish in the whole life history stage can be efficiently and accurately evaluated, and protection strategy formulation and measure implementation of aquatic organisms are facilitated.

The invention discloses a multi-source heterogeneous meteorological data adaptive fusion photovoltaic power prediction method, and belongs to the technical field of photovoltaic power generation prediction and meteorological data processing. The method comprises the following steps: acquiring regional meteorological data, site micro-meteorological data and wind cloud satellite secondary cloud picture data, and carrying out preprocessing and feature screening on the regional meteorological data, the site micro-meteorological data and the wind cloud satellite secondary cloud picture data; defining a coupling coefficient vector; calculating fusion temperature, wind speed and irradiance based on the coupling coefficient, and constructing an input feature vector; performing preliminary power prediction by using a time sequence prediction photovoltaic short-term power model and the input feature vector; optimizing a coupling coefficient by adopting a genetic algorithm; and performing final power prediction based on the global optimal coupling coefficient and the time sequence prediction photovoltaic short-term power model. According to the invention, through an adaptive weight optimization mechanism, the problem of insufficient adaptability of fixed weight fusion under different meteorological conditions is effectively overcome, and the engineering landing performance is high.

The invention discloses an urban fine pipe network drainage effect simulation method based on a nonlinear reservoir method, and the method comprises the steps: obtaining the rainfall, terrain, underlying surface and trunk pipe network data of a research region, building a two-dimensional hydrodynamic model and a one-dimensional pipe network model based on the obtained data, dividing a control region for each rainwater node, and carrying out the calculation of the control region. Establishing a coupling relationship between a ground surface grid in the control area and a corresponding rainwater node; calculating the rainfall and infiltration process of the research area to judge whether the rainwater nodes overflow or not, if overflow occurs, performing overflow calculation, if overflow does not occur, deducting a certain amount of water from each earth surface grid, counting the water amount, adding the water amount into the corresponding rainwater nodes respectively, and correcting the water amount by adopting a nonlinear reservoir method; and performing data updating according to the calculation result until the set operation time is reached, and outputting the final calculation result of the research area. The problem that the drainage capacity of the pipe network is difficult to generalize in the absence of fine pipe network data in the prior art is solved.

The invention provides a hydrodynamic model-based mountain river flood diversion tunnel line and scale optimization design method, which comprises the following steps of: constructing a one-dimensional hydrodynamic mathematical model of a research area drainage basin by adopting MIKE11 software, and constructing a one-dimensional hydrodynamic model of the research area drainage basin according to the one-dimensional hydrodynamic mathematical model of the drainage basin, boundary conditions and calibrated comprehensive roughness; and calculating designed flood water surface lines of different frequencies of the urban section. According to the actual situation of a city, aiming at urban flood causes and main problems existing in a current flood control system, engineering measure schemes such as flood control reservoir construction, beach retreating and river returning, river regulation, embankment heightening and flood diversion channel building are proposed, and a flood diversion tunnel route and planning optimization research is developed on the basis of a hydrodynamic model. Numerical simulation of flood disasters is completed by means of the modern information technology, a complete disaster prevention and control system is established for achieving the purposes of scientization, high efficiency and automation of disaster prevention and relief decision, the urban flood prevention capacity can be comprehensively improved, and the life and property safety of the masses is guaranteed.

The invention discloses a cascade reservoir backwater jacking influence quantification and tail water level prediction method based on hydrodynamic simulation and regression analysis. The method comprises the following steps: step 1, data collection and preprocessing; 2, constructing a one-dimensional hydrodynamic model, simulating water surface lines under different constant flow conditions by taking the upstream reservoir outlet flow as an upper boundary and the downstream reservoir dam front water level as a lower boundary, and calculating the upstream reservoir tail water level; 3, multiple groups of upstream reservoir outlet flow and downstream reservoir dam front water level combinations are set, the corresponding tail water level is calculated through a hydrodynamic model, and a data table is formed; 4, establishing a function relation model among the tail water level, the reservoir outlet flow and the dam front water level by using a multivariate nonlinear regression method; step 5, performing significance test and error analysis on the regression model; 6, a calculation page rule of the influence of the downstream reservoir backwater jacking on the upstream reservoir tail water level under different working conditions is developed; the method is beneficial for improving the refined scheduling level of the cascade reservoirs.

The invention discloses a fuel cell output power regulation and control method and a control system thereof. The regulation and control method comprises the following steps: dividing an environment temperature into a plurality of temperature intervals, and setting a power constraint of each temperature interval based on a pre-established temperature power model; based on a pre-established altitude power model, quantifying compensation coefficients of the altitude and the output power; establishing a multi-dimensional linkage rule according to the power constraint, the compensation coefficient and the running state of the fuel cell; and dynamically adjusting the output power of the fuel cell according to the linkage rule. According to the technical scheme, the output power can be effectively stabilized, the operation efficiency of the fuel cell is improved, the service life is prolonged, and the safety is improved.

The invention discloses a joint control method and device of a robot and a nonvolatile storage medium. The method comprises the steps that the environment temperature and the current temperature of a target joint of the robot are collected; inputting the current temperature and the environment temperature into a preset joint loss power model of the robot, and determining the maximum joint loss power of the robot; determining the maximum output power corresponding to the target joint based on the maximum joint loss power; and based on the maximum output power, the target joint output power is controlled. The technical problem that due to the fact that temperature rise of part of joints is too large, the collaborative robot may be directly suspended or shut down, and risks are brought to production operation of a terminal user is solved.

The invention provides a heterogeneous computing power model scheduling method and device, electronic equipment and a storage medium, and relates to the technical field of heterogeneous computing power resource dynamic scheduling. The heterogeneous computing resource demand parameter can be automatically analyzed, the real-time heterogeneous resource state of each computing node in the cluster is obtained, and the target computing node meeting the demand is accurately determined through the preset multi-dimensional resource matching strategy. Then, a containerized task instance is automatically started on the target node, heterogeneous computing resources are distributed according to requirements, the corresponding model mirror image is loaded, and the execution instruction is executed. The problems that in the prior art, due to the fact that a model mirror image management system and a scheduling system are separated, a scheduling strategy cannot sense the heterogeneous computing power requirement of an AI model, task definition lacks a reusable template and is tedious in operation, nodes are appointed manually, efficiency is low, errors are prone to occurring, and the resource utilization rate is low can be solved.

The invention discloses a method for extracting parameters of a (subtropical) eucalyptus man-made forest based on an unmanned aerial vehicle laser radar. The method comprises the following steps: investigating a sample plot, and measuring and calculating actual forest parameters such as average diameter, average height, sectional area, stand volume and the like; acquiring and preprocessing high-density unmanned aerial vehicle laser radar point cloud data, and extracting three types of feature variables of height, density and vertical structure; deducing a model structural formula on the basis of a stock different-speed growth equation, and screening variables according to rules; constructing a power model by using a regular exhaustion method; the optimal model is screened out through model parameter estimation, inspection, significance analysis and the like. According to the method, the variable synergistic effect is mined through the exhaustion method, the multi-dimensional test system is constructed, and the exclusive model is customized, so that the problems of one-sided variable screening, insufficient model reliability and poor specific forest stand adaptability in the prior art are solved, high-precision estimation of core forest parameters is realized, and the method is suitable for large-scale popularization and application. And scientific and effective technical support is provided for refined management and sustainable operation of eucalyptus man-made forest resources.

A power supply apparatus (100) comprises an inverter (110), voltage and current measuring devices (120a, 120b), a temperature sensor (130), and an operation circuit (140). The inverter (110) comprises change-over switches (SW1-SW6). The voltage and current measuring devices (120a, 120b) are configured to measure the voltage (V1) and the current (I1) on the change-over switches (SW1-SW6). The temperature sensor (130) is configured to measure an initial temperature (T[0]) in an initial state. The operation circuit (140) is coupled to the voltage and current measuring devices (120a, 120b) and the temperature sensor (130). The operation circuit (140) is configured to: execute a power model (142), and calculate a first transient power of the change-over switches (SW1-SW6) on the basis of the initial temperature (T[0]), the voltage (V1), and the current (I1); and execute a thermal model (144), and calculate a first transient ideal temperature of the change-over switches (SW1-SW6) on basis of the first transient power. The power supply apparatus (100) calculates, in real time, the transient temperature of channel interfaces of the change-over switches (SW1-SW6) by measuring the voltage (V1) and the current (I1) on the change-over switches (SW1-SW6) of the inverter (110). The present invention also relates to a temperature measurement method (500) for a power supply apparatus, and an electrical system (ES1).

This invention relates to the field of sediment prediction technology, specifically to a method for predicting sediment deposition in waterways based on a hydrodynamic model. The method includes the following steps: correcting the critical initiation velocity of sediments using the biomass, metabolic rate, and biofilm thickness of the microbial community to obtain a corrected critical initiation velocity; calculating the actual suspended sediment concentration in the waterway based on the corrected critical initiation velocity, combined with the turbulence intensity, propagation distance, and draft of the ship's wake; and calculating the sediment deposition volume in the waterway based on the suspended sediment concentration, combined with the cementation strength, water content, and organic matter decomposition rate of the surface sediments. This invention comprehensively considers ecological and navigation-related influencing factors and improves prediction accuracy in complex scenarios.

The invention relates to the technical field of energy-saving control of central air-conditioning systems, and discloses an energy-saving control method of a central air-conditioning system based on a data-driven proxy model, which comprises the following steps: collecting and preprocessing field data; establishing a digital twin platform; predicting a tail end load; establishing a power model of each device; carrying out physical information projection of self-adaptive weight; carrying out model linearization and accelerated solution; and integrating, solving and verifying the model. According to the energy-saving control method for the central air-conditioning system of the data-driven proxy model, high-precision simulation is achieved through digital twinning, energy conservation is ensured through self-adaptive projection, solution is accelerated through the improved Big-M method, and global optimal control and energy consumption reduction are achieved.

The invention discloses a power electronic equipment cascade stability optimization control method based on a BP neural network, and relates to the field of intelligent control, and the method comprises the steps: building a mathematical model according to the topology and operation characteristics of a DC / DC converter cascade structure employing a dual-active bridge as a core; obtaining three phase-shifting angle parameters, classifying operation modes based on a triple phase-shifting control thought, and constructing a transmission power model; designing a BP neural network for each operation mode, sorting historical operation data of each operation mode into a training set, and performing offline training on the BP neural network through an error back propagation and gradient descent algorithm; the trained BP neural networks are deployed in an actual control system, operation data are collected in real time, the current mode is recognized, the corresponding BP neural networks are called to generate optimization control parameters, the phase shift angle, the voltage and the current are dynamically adjusted, and online optimization control over the stability of the cascade system is achieved.

This invention discloses an intelligent planning method and system for aircraft transportation missions based on real-time power prediction. The method includes: constructing a full-physics power model that couples the dynamic characteristics of the inertial measurement unit, the environmental wind field vector, and battery characteristics, and completing offline calibration; during mission execution, using an extended Kalman filter to jointly estimate the load mass and wind field vector in real time, and dynamically solving for the optimal cruise speed that minimizes energy consumption per unit distance; predicting the aircraft's remaining support distance based on the real-time calculated state and "energy bucket" model; and automatically triggering a hierarchical closed-loop strategy—prioritizing waypoint elimination, replanning the route, or immediate return—when energy is insufficient by continuously monitoring and comparing with mission requirements. This invention achieves accurate endurance prediction and autonomous mission adjustment under load changes and wind field disturbances, significantly improving the safety, adaptability, and completion efficiency of aircraft in multi-point transportation missions such as express delivery.

The present application relates to the technical field of mobile communication, in particular to a smart on-demand service method and device for vehicle networking deterministic delay guarantee. The method comprises: establishing a deterministic delay model under a multi-mode link; modeling a wireless channel, introducing a stochastic network calculus (SNC) theory, and deducing a general formula of delay violation probability under different channel conditions; dynamically establishing a transmission power model according to link characteristics, and giving a minimum power threshold value that meets the required channel conditions; taking the maximization of the number of successful vehicles as the optimization objective, and determining the constraint conditions; using an LA2C reinforcement learning algorithm improved based on an A2C mechanism to perform strategy learning and solving, and completing the smart on-demand service for vehicle networking deterministic delay guarantee. The present application adaptively configures key communication parameters such as transmission mode, access mode, resource allocation, and semantic compression ratio, thereby significantly improving the task completion rate and meeting the development trend of the future communication network towards intelligentization and adaptive evolution.

The invention relates to an adjustable potential analysis method for adjustable load resources in a building park. The method comprises the following steps: constructing an adjustable load resource adjustment power model in the building park; calculating the dynamic carbon emission of the adjustable load resource; establishing an adjustable load resource multi-target aggregation model; and calculating the comprehensive adjustment potential of the adjustable load resources in the building park. The low-carbon contribution of each adjustment behavior of the park is accurately quantified, and the load resources are promoted to be upgraded from one-way economic response to multi-dimensional collaborative response; the accuracy and credibility of potential evaluation are remarkably improved, the problem of deviation caused by extensive aggregation is solved, and a reliable data basis is provided for power grid demand response and marketization transaction; a key decision basis is provided for the park to participate in power grid interaction, the transformation of the building park to a flexible resource polymer is powerfully promoted on the premise of ensuring the safety and comfort of energy consumption, and a solid support is provided for the construction of a novel power system and the digital transformation of park energy.

The invention discloses a river and lake hydrodynamic model reduced-order inversion initialization method for intelligent water conservancy, and the method comprises the steps: dividing a computational domain into a plurality of sub-domains according to hydraulic characteristics, building a physical constraint equation represented by reduced-order description parameters, and determining an independent to-be-inverted parameter set through the analysis of the degree of freedom; estimating an initial state of a part of sub-domains by using observation information or a priori value at a starting moment; determining an inversion window according to the hydraulic disturbance propagation time; constructing an agent model, and performing joint inversion on the to-be-inverted parameters and the boundary process line parameters to minimize the cost function; and driving the proxy model to generate a global initial state by using the optimal parameter obtained by inversion, mapping the global initial state to a basic model grid, and taking the global initial state as an initial condition after free evolution and boundary smoothing processing. According to the method, actual measurement data are fused through order reduction-inversion, global initial field construction can be rapidly and accurately completed, and the requirement of an intelligent water conservancy system for cold start of a hydrodynamic model is met.

The invention provides a functional module and a mobile device, the functional module comprises a temperature sensor, a processor and a memory, the processor establishes a mapping relation between a voltage sampling value at a voltage sampling port and a power value of the functional module through a set voltage detection model and a power supply voltage value of the functional module; the memory stores a power model for determining a power value; the power model represents a mapping relation between a power value of the functional module and a temperature detection value of the functional module under each operation condition, and the temperature detection value is determined based on temperature values collected by at least part of the temperature sensors; the processor is set to act a first temperature detection value of the functional module at the first sampling time on the power model to obtain a first power value of the functional module at the first sampling time, and act the first power value and a first voltage sampling value of the voltage sampling port at the first sampling time on the voltage detection model to obtain a second power value of the functional module at the second sampling time; and obtaining a first power supply voltage value of the functional module in the first sampling time.

The application discloses a simulation and dispatching control method and system for urban flood process. The application belongs to the technical field of urban water conservancy system control. The method comprises the following steps: collecting and constructing a specific type of basic data set, respectively constructing a hydrological runoff model, a one-dimensional water power model of a drainage pipe network, a river network mixed water power model and an engineering dispatching model; performing three-dimensional dynamic coupling to form a water resource full-space dynamic model; using at least one historical flood event in historical flood data to calibrate parameters and verify accuracy of the water resource full-space dynamic model; after verification, using the water resource full-space dynamic model to build a digital simulation platform to simulate flood and determine a dispatching scheme. The technical scheme can realize multi-scenario dynamic simulation, automatic comparison and selection after generation of a dispatching scheme, enhance system adaptability and response timeliness under extreme weather, and provide an efficient and accurate flood control and drainage scheme generation mechanism for urban area flood control and drainage.

The invention relates to a power model security detection method, device and equipment, a medium and a program product. The method comprises the following steps: adding different types of basic trigger patterns to each image in an image database to obtain a plurality of candidate trigger images, calling a target power model to identify each candidate trigger image, and determining the probability that the target power model is attacked; calling a target power model to identify images in the first image set, and determining abnormal sample proportion information in the first image set; and adding different types of disturbances to the images in the second image set, calling the target power model to identify each disturbance sample image, and determining anti-interference quantization information of the target power model, and finally, fusing the attacked probability of the target power model, the abnormal sample proportion information and the anti-interference quantitative information to obtain a security detection result of the target power model. By adopting the method, the accurate detection of the potential safety hazard of the target power model can be realized.

The invention belongs to the technical field of energy regulation and control, and provides an energy storage regulation and control decision method and system based on energy dynamic balance, and the method comprises the steps: constructing an energy storage equipment feature set, carrying out the numerical conversion of state features in the energy storage equipment feature set, and obtaining key energy storage features; the method comprises the following steps: constructing an equivalent state-of-charge model, an intra-day time-phased capacity measurement and calculation model and a system power model of an energy storage system, setting balance conditions of the energy storage system, and carrying out quantitative solution on key energy storage characteristics to obtain quantitative data of energy storage nodes; according to the quantized data and an energy balance grading rule, an alternative regulation and control scheme is determined through a multi-energy storage system regulation and control model; and setting regulation and control constraint conditions, constructing a regulation and control cost model of the energy storage system participating in the power grid, and screening the alternative regulation and control schemes to obtain an energy storage regulation and control decision scheme. According to the scheme, the regulation and control precision is effectively improved, the energy dynamic balance of the energy storage node network is realized, and the regulation and control effect is better.

Embodiments of the present application provide a power resource allocation method and device, electronic equipment and storage medium, the method comprises: acquiring the computing power information corresponding to each computing node, the computing power information at least includes logical operation capability, parallel computing capability and neural network computing capability; according to the logical operation capability, parallel computing capability and neural network computing capability corresponding to each computing node, a hybrid control system is constructed, and the hybrid control system is configured with a computing power model; through the hybrid control system, the power demand information corresponding to the power consumption equipment and the historical resource configuration information are acquired, and the computing power model is used to operate the power demand information and the historical resource configuration information, and output the output power reference value corresponding to the power supply system; through the power supply system, the corresponding power resource is output to the power consumption equipment based on the output power reference value.

The invention discloses a helicopter demand power model calculation method and system, and belongs to the technical field of helicopter control, and the method comprises the steps: constructing a T-S fuzzy model, and dividing flight modes on a flight envelope based on the constructed T-S fuzzy model, so as to obtain a flight mode set; obtaining time sequence data in the flight process of the helicopter, and determining a current flight mode in the flight mode set based on the obtained time sequence data; and calculating the required power of the helicopter based on the determined current flight mode. A flight mode set is divided on a flight envelope through the constructed T-S fuzzy model, the required power of an engine can be well estimated by recognizing flight modes and calculating the required power in the flight process, power matching with the engine is achieved, and a basis is provided for subsequent high-speed helicopter control.