46 results about "Energy matching" patented technology

The invention belongs to the cross technical field of artificial intelligence and environmental protection engineering, particularly relates to a denitration catalyst microwave regeneration optimization method based on machine learning, and aims to solve the problems of inaccurate energy matching, large structural damage and low efficiency of a traditional regeneration method. The method comprises the following steps: constructing a catalyst multi-dimensional feature database, establishing a microwave regeneration multi-physics field coupling simulation model, and training an integrated learning prediction model to associate input features with a regeneration effect; in the regeneration process, infrared thermal imaging, microwave reflection and gas sensing equipment are integrated, temperature field, energy absorption and tail gas data are collected in real time, and microwave power, frequency and atmosphere parameters are dynamically regulated and controlled. Accurate energy release and closed-loop intelligent regulation and control are achieved, the activity recovery rate after regeneration exceeds 92%, the specific surface area retention rate exceeds 85%, the regeneration period is shortened to one third of that of a traditional method, energy consumption is reduced by 40%, full-life-cycle intelligent management of the catalyst is supported, and economical efficiency and sustainability of environmental protection equipment are remarkably improved.

The invention discloses a multi-view fisheye camera real-time look-around image splicing method and device, and relates to the technical field of image processing, the method generates a lookup table (LUT) based on calibration parameters, converts a fisheye image distortion removal correction process into a table lookup operation, avoids real-time calculation one by one pixel, significantly reduces the operation overhead, and improves the image quality. And the system can keep low-delay processing under the condition of high-resolution input. According to the method, self-adaptive feathering weight distribution is introduced into a seam band, local energy matching and a multi-band fusion method are combined, and the width and the weight of a splicing area are dynamically adjusted according to scene brightness and contrast difference, so that ghosting and brightness abrupt change at the seam are effectively reduced, and the smoothness of splicing transition is ensured.

The invention discloses a GEO and SSO cross-platform satellite high-energy proton data collaborative calibration method based on a solar proton event, and the method comprises the steps: obtaining high-energy proton observation data and space environment disturbance parameter data of GEO and SSO, and carrying out the preprocessing, and obtaining high-energy proton data, satellite space-time position data and environment parameters of a unified flux type; screening high-energy proton data during the event period according to the sun proton event definition to obtain a plurality of event data sets and grouping the event data sets; performing alignment processing on the screened high-energy proton data of the GEO and the SSO; based on the power law spectrum characteristics of the solar proton event, constructing the energy matching relation of each energy channel of GEO and SSO, and determining the effective energy and energy interval of each energy channel of SSO through point-by-point spectrum fitting and statistical inversion; and recalculating the differential flux of the GEO in a corresponding energy channel by using the calibrated effective energy, establishing a point-by-point scatter matrix of the two types of satellite data, and performing linear fitting and correlation analysis to realize calibration.

This invention discloses an intelligent resource allocation method for energy-aware partitions, belonging to the field of computer architecture and operating system task scheduling technology. The method divides computing resources into multiple independent energy-aware partitions based on the processor cores. It then monitors the energy status parameters of each partition in real time. By parsing the instruction code stream of the tasks to be assigned, the proportion of arithmetic and logical instructions is extracted as instruction mixing features, and the address span of memory access instructions is analyzed to obtain cache access density features. Based on the energy status of the partitions and the computation and memory access characteristics of the tasks, a suitability score for the task relative to each partition is generated, comprehensively reflecting the energy matching degree and hardware resource matching degree. Based on the suitability score and the remaining task acceptance capacity of the partitions, a two-dimensional assignment strategy is used to dynamically map tasks to the core execution in the optimal energy-aware partition. This invention achieves fine-grained matching of computing resources and energy status, optimizing system energy utilization efficiency.

The invention discloses an ultrasonic therapeutic instrument and an energy matching control system and method thereof, and relates to the field of medical equipment, and the system comprises a main controller which is used for outputting a frequency control signal corresponding to a target working mode to a frequency control module, and outputting a matching control signal corresponding to the target working mode to a control module; the driving power module is used for controlling the electric energy output by the direct-current power supply to be converted into frequency electric energy; the control module is used for matching the frequency electric energy to the target matching circuit module so as to transmit the frequency electric energy to the corresponding ultrasonic transducer through the target matching circuit module; the main controller can control the frequency of the frequency electric energy, so that skin physiques with different dielectric constants are effectively met; and the main controller can control and select the matching circuit module by outputting a matching control signal, so that the power electric energy and the ultrasonic transducer are better matched, the requirements of different users and groups are met, and the user experience is improved.

The invention relates to the technical field of cross-layer cooperative scheduling, and particularly discloses a multi-energy complementary energy storage EMS cross-layer cooperative scheduling method and system. The method comprises the following steps: S1, acquiring energy data of each layer in real time; S2, carrying out collaborative optimization on the energy data of each layer; S3, matching an energy quantity with energy storage capacity; S4, matching the energy quantity with energy consumption, S5, generating a cross-layer collaborative scheduling strategy, and S6, optimizing the cross-layer collaborative scheduling strategy. Through establishing a three-layer cooperation mechanism of an energy supply layer, a storage layer and a demand layer, optimization and matching of energy data are realized, an electric energy quality parameter is introduced as a scheduling strategy adjustment basis, a formed closed-loop optimization mechanism solves the problems of insufficient inter-layer information interaction, poor scheduling flexibility and the like in a traditional method, the energy utilization efficiency is improved, and the scheduling cost is reduced. The adaptive capacity of the system to renewable energy fluctuation is enhanced, and technical support is provided for efficient operation of the multi-energy complementary system.

This invention discloses a stable combustion control system based on a multi-dimensional furnace combustion measurement method, specifically relating to the field of furnace combustion measurement. This includes multi-dimensional sensor data acquisition, feature parameter quantification and extraction, combustion stability modeling, intelligent graded stable combustion control, iterative optimization of control effect, and dynamic evaluation of combustion state. Multi-dimensional sensor data acquisition involves synchronously acquiring data through an array of sensors. Feature parameter quantification and extraction involves preprocessing the acquired data to extract key feature parameters. Combustion stability modeling involves constructing a quantitative evaluation model of the combustion stability index based on the key feature parameters. Intelligent graded stable combustion control involves triggering a three-stage direct injection response mechanism for the fuel gun based on the combustion stability index, combined with an adaptive energy matching algorithm to dynamically adjust the stable combustion energy injection. This invention, through a multi-dimensional sensor array and feature extraction algorithm, achieves advanced identification of early combustion deterioration, solving the problem of lag in single flame detector monitoring.

The invention relates to the technical field of rotary mechanical vibration analysis, in particular to a water turbine vibration data analysis method and system, which establishes a frequency and energy matching relation table through feature updating and synchronism screening, so that coupling analysis of a frequency domain and a time domain has pertinence and fineness, and energy features of key frequency responses among structures are highlighted; through feature similarity calculation and an updating mechanism of a low-similarity label, the dynamic adaptability of the frequency energy mode under the variable working condition clearly reflects a risk transmission link of frequency energy features between nodes, the dynamic adaptability of the frequency energy mode under the variable working condition is improved, and the reliability of the frequency energy mode under the variable working condition is improved. Through processing logic and organic connection of signal multi-scale feature extraction and key component frequency energy difference analysis, pertinence of frequency energy feature extraction, dynamic nature of working condition adaptation and fineness of risk transfer description are realized, and thus early abnormity capture precision and fault evolution path identification capability are improved.

The invention relates to the technical field of submerged arc smelting furnace control, in particular to a three-phase layered combined electrode submerged arc smelting furnace control system based on wireless networking, which comprises a data acquisition unit, a data processing unit and a data processing unit, the actual electrical apparent parameters and the smelting process data are combined into actual observable output; the mechanism model prediction unit is used for resolving predicted observable output; the state fusion observation unit is used for correcting and updating to obtain optimal state estimation; the furnace condition risk assessment unit is used for calculating to obtain an energy matching index, a crusting risk index and a material collapse risk index; the closed-loop control execution unit is used for generating a control strategy corresponding to the first-level response, the second-level response or the conventional response so as to correct control input; according to the method, the level of actively predicting and avoiding internal risks is improved, and the safety, stability and energy efficiency of operation of the smelting furnace are remarkably improved.

The present invention relates to the technical field of offshore wind turbine generator set installation equipment, and more particularly to a fuel-electric hybrid drive system and a hybrid wind power installation vessel with an energy matching function. The fuel-electric hybrid drive system includes an energy supply assembly. The energy supply assembly includes generator sets, emergency generator sets, and battery packs. Different numbers of generator sets can be started to supply energy to the wind power installation vessel under different loads. When the generator sets provide sufficient energy, excess electrical energy is stored in the battery pack. When the energy supply is insufficient, the battery packs are used to supply energy to the wind power installation vessel. In the event of a generator failure, the battery packs provide energy until the emergency generator sets start. When the wind power installation vessel is operating, a dynamic positioning system receives environmental signals from sensors, and the fuel-electric hybrid drive system adjusts the number of propeller start-ups, rotation speed, and direction angle to keep the vessel in a predetermined position. The energy supply assembly ensures sufficient power for the wind power installation vessel, solving the energy supply problem in harsh conditions and improving the stability of the wind power installation vessel.

The invention discloses a photovoltaic power generation energy storage optimization system, method and device, and belongs to the technical field of photovoltaic power generation. The method comprises the following steps: deploying a photovoltaic array comprising a plurality of photovoltaic cell panels, connecting the photovoltaic array with an electric energy management system through a connecting line, and adjusting the inclination angle of the cell panels according to a real-time illumination angle; configuring an energy storage device comprising a plurality of battery packs connected in parallel and a battery management system, wherein the battery packs are connected with an electric energy management system through a bidirectional DC / DC converter; through illumination, power and environment temperature and humidity sensors, power generation and energy storage data such as photovoltaic array power generation power, illumination intensity and temperature and humidity of an area where the photovoltaic array is located are collected; determining an optimization scheme based on the data, wherein the optimization scheme covers an energy matching relation between photovoltaic power generation and energy storage, a photovoltaic power generation priority supply strategy and an energy storage charging and discharging power adjustment parameter; the energy flow is optimized according to the scheme. According to the invention, illumination fluctuation and load requirements are efficiently adapted, dynamic balance of photovoltaic power generation and energy storage is realized, and the energy utilization efficiency and the power supply stability are improved.

The application discloses a kind of fluid delivery control systems based on operating condition perception, it is related to fluid delivery automatic control technical field, system includes operating condition multi-source perception module, condition migration boundary identification module, equivalent delivery resistance identification module, delivery stability scoring module and pump valve collaborative buffer control module;Based on continuous sliding time window extraction pressure, flow, pump load, valve action, unit delivery energy consumption and equivalent delivery resistance variation characteristics, delivery trend verification, energy matching verification and migration contribution analysis are carried out, and equivalent delivery resistance parameters are calculated and corrected, and delivery stability score is calculated, and according to control mode suggestion, total regulation demand quantity calculation, pump valve regulation contribution distribution and actuator limiting control are carried out.Above-mentioned mode, the application can reduce pressure impact and equipment damage risk under the condition of demand change, resistance increase, valve disturbance or low flow high pressure, improve the operating stability of fluid delivery system.

The application relates to the field of intelligent meal matching, and discloses a modular precise nutrition intelligent meal box and a self-adaptive meal matching device. The self-adaptive meal matching device comprises a clustering module, a calculation module and a construction module. The clustering module is used for clustering a user feature vector based on a fuzzy C-means clustering algorithm. The calculation module is used for calculating a meal energy target and a macro-nutrient target according to a membership vector. The construction module is used for constructing a multi-objective optimization model comprising an energy matching degree, a macro-nutrient balance degree, a taste preference satisfaction degree and a dish diversity gain target function. The decision module is used for visualizing and displaying a Pareto optimal solution set for user selection. By constructing a multi-dimensional user feature vector, generating a personalized meal energy target and a macro-nutrient target according to a membership weight, establishing a multi-objective optimization model and outputting a Pareto optimal solution set by using a multi-objective evolutionary algorithm, the Pareto optimal trade-off and hierarchical constraint management of multiple conflict targets are realized.

This invention provides a method and system for optimizing train timetables using virtual train formation and regenerative braking energy, relating to the field of data processing technology. The method includes: calculating the time overlap area of ​​the running curves of traction and braking trains within the same power supply zone based on an updated passenger flow allocation scheme and the new solution to quantify the recoverable amount of regenerative braking energy, thus obtaining a quantification result; calculating the traction energy consumption in operating costs based on the quantification result to obtain a performance evaluation value for the new solution; and determining whether to accept the new solution based on the performance evaluation value of the new solution and the performance evaluation value of the current solution, thereby updating the current solution. This invention enhances the opportunity for energy matching between trains.

This invention discloses a method and apparatus for small-sample bearing fault diagnosis based on digital twin assistance. The method collects basic parameters of the target bearing, establishes a dynamic simulation model, and obtains simulated vibration signals under different fault states. Variational mode decomposition is performed on labeled measured data to screen fault characteristic modes and background components. Mode replacement and energy matching are used to fuse the simulated signals with the background components of the measured signals, generating twin data that combines physical mechanisms and real distribution characteristics. The twin data and a small amount of labeled measured signals are used as the source domain, while a large amount of unlabeled measured signals are used as the target domain input to the diagnostic model. The model sequentially performs feature extraction, graph structure construction and node weight adjustment, classifier classification, and domain discriminator differentiation, and incorporates contrastive loss to achieve cross-domain feature alignment. This invention can improve fault diagnosis accuracy and generalization performance in small-sample scenarios with limited measured fault data, solving the problem of insufficient training data.

The invention relates to the technical field of power distribution, in particular to a hill and mountain agricultural machine chassis distributed battery BMS current distribution method and system based on dynamic state estimation. Comprising the following steps: S1, acquiring parameters of a plurality of battery compartments and working condition parameters of a chassis; s2, constructing a state vector based on the working condition parameters of the chassis, performing fusion estimation on the dynamic state of the vehicle based on the state vector and extended Kalman filtering to obtain a state estimation result, and determining a current working condition type based on the state estimation result; s3, calculating the real-time power of the whole vehicle based on the current working condition type; and S4, the output power of each battery compartment is calculated based on the real-time power of the whole vehicle, and then distributed battery BMS current distribution is achieved. According to the invention, the output power of each battery compartment is dynamically adjusted based on real-time estimation results of states such as gradient, load, speed and the like, so that accurate energy matching is realized; the problems of energy waste and response delay caused by fixed output of a traditional hilly and mountainous agricultural machine operation scheme are avoided.

The utility model discloses a monitoring and compensating structure for eliminating the influence of EX spectrum fluctuation of a fluorospectro photometer, and particularly relates to the technical field of fluorescence analysis and detection, which comprises an EM light energy beam splitter, an EM wavelength energy matching tuner, a monitoring multiplier tube, an electronic negative feedback compensation control module and a measurement multiplier tube, the EM light energy beam splitter is arranged between a sample pool in the fluorescence spectrophotometer and the EM light energy beam splitter I, the EM light energy beam splitter splits EX light energy into two paths, the light beam I in the horizontal direction enters the fluorescence measurement channel to complete fluorescence testing, and the light beam II in the vertical direction enters the EX light energy monitoring channel to monitor the fluctuation of the EX light energy. According to the utility model, a monitoring light path structure of which the photoelectric characteristic of a monitoring light path is consistent with that of a measuring light path detector is designed to be embedded into a measuring light path and a circuit of an instrument, so that the correction compensation quantity of fluctuation quantity which is equal to sample fluorescence in quantity ratio and same in phase and synchronization is obtained in time to eliminate the error influence caused by EX energy fluctuation in a fluorescence test.

The invention belongs to the technical field of communication. The invention provides a TOA (Time of Arrival) and carrier phase joint estimation method for an eLoran receiver. According to the embodiment of the invention, bench chain identification and GRI locking are repeatedly completed by using a pulse group period, the effective signal-to-noise ratio is improved through epoch folding, and sub-sampling level TOA observation is constructed by adopting energy matching rough estimation-coherent correlation refining-peak parabola interpolation; and meanwhile, baseband phase observation is formed by coherent down-conversion accumulation, and phase ambiguity branch selection and unwrapping are carried out. A unified state space model including TOA deviation, drift rate, baseband phase and frequency deviation is established, TOA and phase joint Kalman filtering recursion is realized, multi-model adaptive Kalman filtering and innovative likelihood adaptive weighting are introduced, and noise expansion is measured to suppress outlier observation.

The invention discloses a cleaning method for a semiconductor photoetching mask substrate, and belongs to the technical field of semiconductor manufacturing. According to the method, dynamic cleaning logic of step cooperation and energy matching is adopted, and the steps of interface wetting and pre-cleaning, chemical soft interface construction, low-damage mechanical stripping and synchronous washing, targeted reaction clearing, microstructure deep cleaning, interface dehydration and modification and final energy-assisted drying are sequentially executed. The method is characterized in that through the dependency relationship of chemical interface softening and low-damage mechanical stripping in sequence, the rotation speed of a substrate in each step is strictly controlled to meet the specific dynamic relationship (V2 < V1 < V4 < V3 < V5 < V6), and precise cooperation of chemical action, physical stripping and energy field cleaning is achieved. The contradiction between efficiency and substrate damage in a traditional cleaning process is effectively solved, full-scale pollutants from micron-scale particles to nano-scale molecular contamination can be removed without dead corners, and a clean, stable and secondary pollution resistant surface state is actively reconstructed at a cleaning end point; and the cleanliness and the service life of the mask substrate and the yield of a downstream photoetching process are remarkably improved.

The invention discloses a debris flow flexible protective net design method based on cooperation of energy matching and force balance, and belongs to the technical field of geological disaster prevention and control engineering. According to the method, debris flow impact energy is distributed to energy dissipaters at all parts according to a preset proportion, and scientific preliminary selection and matching of structural components are achieved; a continuous impact process is dispersed into a plurality of dynamic stages, solid-liquid separation and blocking effects are considered, and the load of each stage is finely calculated; establishing a finite element model for multi-stage nonlinear analysis to obtain a structure response peak value; and performing double verification on the strength of the component and the performance of the energy dissipater, and iteratively optimizing the design scheme. According to the method, the spanning from experience design to theoretical and refined design is realized, and the scientificity, the safety and the economical efficiency of the design of the single protective net are remarkably improved.

This invention discloses a waste heat generation and SCO2 energy storage collaborative scheduling platform based on energy level matching. Belonging to the field of waste heat recovery and SCO2 energy storage, it addresses the problems of poor energy matching between waste heat and energy storage systems, high reliance on manual intervention, and lack of economical scheduling in existing technologies. It achieves full-dimensional parameter acquisition and fusion through a multi-source sensing module, and constructs a dynamic energy flow scheduling system based on an intelligent decision-making central module and a production-storage tiered optimization module. This enables economical time-segmented scheduling, maintaining production load while reducing high-priced electricity consumption, balancing production and revenue. Combined with a tiered self-healing interlocking module, it achieves fault classification and self-healing control, enabling rapid fault response and self-healing. In the event of network interruption or central dispatch command failure, the edge control engine module activates a local governance mode to maintain normal platform operation, improving system stability and security, and reducing the need for manual intervention.

The present application belongs to the field of artificial intelligence and rail transit intelligent operation and maintenance technology, and specifically relates to a subway intelligent maintenance system for collaborative optimization of braking energy consumption, aiming to solve the problems of low braking energy recovery efficiency, equipment perception lag and passive maintenance strategy. The system realizes the determination of regenerative braking energy absorbability and the quantitative evaluation of component health state by constructing a whole-network train dynamic topology and energy-health coupling analysis engine. Combined with a four-quadrant decision matrix, the system generates a hierarchical maintenance instruction and uses a rolling time domain optimization algorithm to coordinate train group operation time to improve energy matching degree. The system integrates a self-adaptive learning hub to continuously calibrate model parameters. The system realizes the collaborative optimization of braking energy efficiency improvement and key component life extension, and reduces the measured resistance energy consumption by more than 28% and the sudden failure rate by 41%.

The invention provides an elevator energy recovery and energy saving method and system.The method comprises the following steps that elevator groups located in different building facilities and emergency energy units connected with the elevator groups are determined, and a power supply network for connecting all the emergency energy units is established based on a common direct current bus; in response to the power failure state of any elevator group, the emergency energy quantity corresponding to each emergency energy unit located in the power supply network is compared with the group energy quantity of the corresponding elevator group, and the emergency energy units having the energy adaptation relation with the elevator group are determined as energy supply units based on the comparison result; and the energy supply unit is controlled to supply energy to the elevator group, and supply information determined based on energy supply is sent to the visual unit corresponding to the elevator group to be displayed. The method at least improves the energy scheduling flexibility.

The invention discloses an extreme wave spectrum calculation method based on a wave element co-occurrence recurrence period, and belongs to the technical field of coast and ocean engineering. Comprising the following steps: acquiring significant wave height and spectral peak period length time sequence data of a certain station, constructing an annual extreme value sample pair, and mapping the annual extreme value sample pair to a unified probability space; based on the Copula theory, quantitative characterization is carried out on a dependent structure among wave elements, and optimal selection is carried out on candidate Copula models according to an AIC information criterion; determining a joint exceeding target probability according to the co-occurrence recurrence period definition, and determining a joint design point based on a maximum probability density criterion; and based on the joint design points, inversely calculating spectral scale parameters through zero-order spectral moment energy matching and finishing effective wave height consistency checking, and further calculating an extreme wave spectral density function curve meeting the co-occurrence recurrence period constraint. According to the method, the co-occurrence recurrence period design sea condition is determined, wave spectrum calculation self-consistency is achieved, and the rationality and engineering applicability of an extreme wave spectrum calculation result are improved.

The present application relates to a kind of based on path energy matching's no baseline ultrasonic Lamb defect positioning method, comprising the following steps: S1, on aluminum plate arrangement circular sensor array and construct sector area, simulate defect by punching on plate, gather the damage signal of sector scanning area;S2, pre-processing is carried out to damage signal, and all signals are normalized according to boundary echo signal;S3, according to sensor path length, all signals are grouped, and the first arrival wave packet energy ratio is calculated according to group;S4, the two paths of the lowest energy ratio in each sector scanning area are found out, and the intersection of path straight line is calculated, to further determine the defect position, draw defect positioning chart.Compared with prior art, the present application has the advantages of rapid and accurate detection and positioning of defect, clear imaging result and the like.

The invention discloses a working state monitoring and energy matching method and system for a press machine, and relates to the related field of data prediction and intelligent optimization technologies in the production field. A multi-task prediction model based on a neural network is established and trained to process and analyze a large amount of historical data, and a pre-training model is obtained and used for processing press operation data, stamping part parameters and production environment data which are collected in real time and outputting an abnormal detection result of a working state and a stamping part deformation work prediction result; and according to the stamping part deformation work output by the model, an objective function and constraint conditions are established, and the optimal press parameter combination configuration is obtained by adopting an intelligent optimization algorithm, so that the working energy of the press is reasonably matched with the stamping part deformation work. The problems that an existing press machine working state monitoring and energy matching method is poor in flexibility and insufficient in precision are solved, the data monitoring real-time performance is improved, and the system data analysis capacity and the intelligent level are improved.

The invention relates to a combined experiment method for improving ECC performance test success probability, and belongs to the technical field of civil engineering material test and design. Aiming at the problems of low trial and error efficiency, large discreteness of experimental results and the like in the research and development of the existing high-strength and ultrahigh-ductility engineering cementitious composites (ECC), the invention provides a closed-loop experimental system based on the combination of micromechanics matching screening and macroscopic accurate verification. The method mainly comprises two stages: in a screening stage (step 1), respectively through a pure matrix three-point bending experiment and a single fiber bundle drawing experiment, acquiring matrix fracture toughness and interface bonding strength parameters, verifying an energy matching relationship according to a micromechanics criterion, if the energy matching relationship is not matched, feeding back and guiding fiber modification or matrix adjustment, and if the energy matching relationship is not matched, feeding back and guiding the interface bonding strength parameters; reverse design and pre-screening of the mix proportion are realized; in the verification stage (step 2), a special dumbbell test piece designed with a specific long scale distance (80mm effective observation area) is adopted to perform a uniaxial tensile test on the all-component material meeting the matching requirement, and end damage interference is avoided. By applying the method, the research and development period can be shortened by 40% or above, the high-performance ECC with the compressive strength larger than 135 MPa, the tensile strength larger than 10.0 MPa and the tensile strain capacity of 10%-12% is successfully guided, prepared and verified, and the test success rate and the data authenticity are remarkably improved.

The application relates to the technical field of solar irrigation, and discloses a solar irrigation method and system based on data fusion, which comprises the following steps: collecting and preprocessing environmental data, soil data, crop growth stage data, irrigation water quantity, solar energy and electricity consumption data; predicting crop water demand based on the fusion data, calculating solar energy supply capacity and energy required for irrigation, selecting an energy supply strategy after matching; selecting an irrigation mode in combination with the crop stage and water demand, comprehensively evaluating and selecting an optimal scheme for the combination of the energy supply strategy and the irrigation mode based on preset indexes; recording real-time electricity consumption, water discharge and soil response data during the irrigation process, and dynamically updating a data fusion model based on the data, so that adaptive optimization of the strategy combination is realized, and thus the collaborative and efficient operation of irrigation control and energy scheduling is realized. The application can realize dynamic collaboration and efficient regulation and control of the irrigation strategy and the energy supply path.

The application provides a hydraulic wind-driven reverse osmosis seawater desalination control method based on double-layer cooperative optimization, relates to the technical field of renewable energy utilization and seawater desalination equipment control, and comprises the following steps: S1, acquiring hydraulic wind turbine unit parameters and historical wind speed data to obtain the optimal wind wheel rotating speed of the hydraulic wind turbine; S2, determining the real-time energy supply performance of the hydraulic transmission chain and outputting dynamic equivalent energy parameters; S3, generating an energy supply relationship matched with dynamic characteristics and solving an optimal water production steady-state characteristic vector; S4, constructing an outer ring wind wheel rotating speed backstepping sliding mode controller and outputting a motor displacement control signal; and S5, establishing an inner ring motor rotating speed backstepping sliding mode controller and outputting a feed water pressure regulation signal. Through the double-layer cooperative architecture of the upper-layer dynamic target programming and the lower-layer double backstepping sliding mode tracking, the application solves the energy matching and dynamic tracking problems of wind power seawater desalination and improves the wind energy utilization rate and water production stability.

This application discloses a photovoltaic air conditioning energy control method, device, equipment, and storage medium, relating to the field of photovoltaic air conditioning power control technology. The method includes: establishing a probability model for the activation of photovoltaic air conditioners at different times based on the activity patterns, dwell time, and number of people in different rooms; calculating a target real-time indoor temperature corresponding to a preset main activity area room based on the power of each photovoltaic air conditioner and indoor / outdoor conditions, combined with the activation probability model, when all photovoltaic air conditioners operate using only the electricity generated by real-time photovoltaic power generation; and controlling the power of the photovoltaic air conditioners based on a preset thermal comfort temperature range, the target real-time indoor temperature, and the activation probability model. In this way, this application can establish an activation probability model for air conditioning behavior based on information such as the activity patterns of people in different rooms, allowing for flexible control of air conditioning operation, improving the local consumption rate of photovoltaic power generation, increasing energy matching efficiency, and reducing investment costs.