1211 results about "Heat balance" patented technology

The invention provides a die-casting die heat balance distribution optimization method and system based on an energy model, and relates to the technical field of die-casting dies, and the method comprises the steps: collecting heat distribution data, and building a heat energy transfer mapping relation; extracting space-time correlation features by using a graph attention network; constructing a heat distribution dynamic evolution model; constructing a temperature field predictor based on a deep belief network; training a predictor by using a multi-agent coevolution algorithm; constructing a temperature field optimization strategy network; generating an optimal temperature field control sequence; establishing a regional adaptive control strategy; constructing a temperature field controller based on deep reinforcement learning; and a dynamic fuzzy immune optimization algorithm is adopted to adjust cooling control parameters, and intelligent optimization control over heat distribution of the die-casting die is achieved.

The invention provides an intelligent scheduling and control method and device for an integrated energy system. According to the method, power, gas and heat resource operation data are acquired, multi-scale layered modeling is performed according to a time scale and a space scale, and a power resource state space model, a gas resource flow continuity model, a heat resource heat balance model and a multi-energy coupling characteristic constraint model are established; carrying out feature extraction and dimension reduction representation by adopting a deep auto-encoder network; cooperative training of multiple groups of cognitive models is carried out through a split hierarchical federal learning framework, and a global intelligent model is obtained; constructing a neural architecture search network with a hybrid bionic learning rule, setting a hierarchical scheduling target, and generating a hierarchical intelligent scheduling strategy; and a fault-tolerant control mechanism is constructed, and error detection and correction of operation deviation are realized. According to the invention, multi-time scale collaboration, collaborative learning under multi-device group privacy protection and high-reliability fault-tolerant control are realized, and the operation efficiency and reliability of the integrated energy system are remarkably improved.

The invention relates to the technical field of photovoltaic power generation, and discloses a BAPV-based roof photovoltaic intelligent monitoring system and a dynamic tuning method and device. The method comprises the following steps: scanning a preset BAPV assembly through three-dimensional laser, constructing a surface point cloud model, and establishing a three-dimensional coordinate system comprising BAPV assembly installation base points; acquiring a real-time environment parameter set corresponding to the BAPV component; calculating an optimal working angle of the BAPV component according to the real-time environment parameter set based on an improved particle swarm algorithm; simulating an all-weather shadow movement track according to the optimal working angle based on a Monte Carlo method, and generating a component shielding influence weight matrix; establishing a heat balance equation according to the component shielding influence weight matrix so as to calculate a spacing optimization parameter of the BAPV component; a control instruction is generated according to the spacing optimization parameters, and dynamic tuning of the BAPV assembly is completed according to the control instruction; the control instruction comprises a support rotation angle compensation amount, an inverter parameter adjustment amount and an abnormal component isolation instruction. And the pain points of modeling errors, static optimization limitation, thermal runaway risks and the like are solved.

The invention relates to the technical field of reaction kettle temperature control, and discloses a fine chemical engineering reaction kettle temperature intelligent control method based on self-adaptive search, which comprises the following steps: S1, data acquisition: acquiring operation data of a reaction kettle, including temperature in the kettle, jacket inlet and outlet temperature, fluid flow and valve opening signals; s2, heat balance calculation: establishing a heat balance equation based on the collected data, and calculating reaction heat release and an equivalent heat transfer coefficient; s3, updating the model; s4, predictive control solution is carried out; s5, performing adaptive search; s6, carrying out security constraint; s7, stage identification; and S8, performing control execution. The reaction heat release amount and the equivalent heat transfer coefficient are calculated in real time through linkage of a heat balance calculation module and a model updating module, online parameter identification is achieved through a recursive least square algorithm, a heat model can be dynamically corrected along with working condition changes, it is ensured that a prediction model is consistent with the actual reaction process, and the prediction efficiency is improved. And the temperature prediction precision and the reliability of control response are obviously improved.

The invention relates to the field of industrial automation and intelligent control, and discloses an intelligent temperature automatic control system for a digital glass mold. The method comprises the following steps: acquiring mold surface temperature and heat flow data through a thermocouple array and a thermal infrared imager, and constructing heat flux and a disturbance coefficient; forming state vectors are established in combination with the forming process parameters and the heat flow distribution, and forming stability levels are generated through support vector regression; building a heat balance deviation model based on the thermophysical parameters and the environment variables, and predicting a temperature trend; a temperature control instruction is generated through the fuzzy neural controller, and temperature dynamic closed-loop control is achieved. The system improves the temperature control precision and thermal field balance of the glass mold, and is suitable for intelligent temperature control management in the glass container forming process.

The invention provides a cross-seasonal heat storage coupling solar ground source heat pump combined heating system. The cross-seasonal heat storage coupling solar ground source heat pump combined heating system mainly comprises a solar heat collector, a valve, a heat storage water tank, a heating tail end, a buried phase change heat storage water tank, a buried pipe and a heat pump. Solar radiation heat in non-heating seasons is collected and stored through cross-seasonal heat storage, and the stored heat is extracted in the heating period in winter and is used for heating a building together with a solar ground source heat pump combined heating system. The system has the beneficial effects that the system efficiency is improved, and the use of thermal insulation materials is reduced, so that the cost is reduced; the buried pipe absorbs and inhibits heat diffusion of the heat storage water tank, heat balance of a soil temperature field around the buried phase change heat storage water tank is guaranteed, and efficient operation of a heat pump unit is maintained. The invention has six control methods: solar energy-soil heat storage, solar energy direct heating, solar energy coupling buried phase change heat storage water tank heating, buried phase change heat storage water tank direct heating, solar energy ground source heat pump combined heating and ground source heat pump independent heating.

The invention discloses an axial flux motor temperature prediction method based on equivalent thermal circuit method calculation, and the method comprises the following steps: 1, motor thermal circuit unit division: decomposing a motor into a stator unit, a rotor unit, an air gap unit and a housing unit, and constructing an equivalent thermal network through a node-branch method; 2, calculating a multi-physics coupling heat source; 3, thermal resistance parameter dynamic calculation and CFD coupling optimization: calculating conduction thermal resistance, convection thermal resistance and contact thermal resistance; and 4, parameter self-calibration based on machine learning: constructing a PINN model according to a physical law and known physical parameters, introducing a Bayesian optimization algorithm on the basis of the PINN model, adjusting and optimizing the parameters of the PINN model by using Bayesian optimization, designing a reinforcement learning algorithm, and carrying out self-calibration on the parameters of the PINN model. Enabling the reinforcement learning algorithm to dynamically adjust parameters according to the real-time operation data of the system and the prediction result of the PINN model; 5, constructing and solving a heat balance equation; and step 6, visualizing and verifying the temperature field.

The invention provides a multi-section collaborative dynamic adjustment temperature control system and method, and relates to the technical field of multi-section temperature adjusting.According to the multi-section collaborative dynamic adjustment temperature control system and method, division and data acquisition of a screw rod section, a barrel section and a machine head section are achieved through the thermodynamic state of materials of all sections, and after thermodynamic state data of all the sections are obtained, the temperature of the materials of all the sections is obtained; based on shear heat modeling of a compression section, heat source distribution and axial temperature change of a screw area are obtained, a two-dimensional heat conduction model of a barrel section is established, heat flux density in an axial partition structure is continuously solved, flow coupling calculation is further introduced into a machine head area, outlet temperature fluctuation characteristics are extracted, and a heat flow distribution model is established. And finally, by uniformly fusing the output parameters of each section, a dynamic thermal potential energy function is constructed, and the system can realize overall quantification and uniform expression of the thermal state of each temperature control section. The real-time responsiveness and the global heat balance level of the multi-section temperature control system are effectively improved.

The invention provides a permafrost region ventilation pipe foundation design method based on a heat balance principle, and aims to keep heat balance of permafrost on the lower portion of a foundation and ensure long-term heat stability of the foundation. According to the method, meteorological data, soil physical parameters and permafrost upper limit and ground temperature distribution information are collected so as to evaluate whether additional protection measures are needed or not and determine the burying height of the ventilation pipe foundation. And based on the selected ventilation pipe configuration, the air speed in the pipe is calculated by using a corresponding air speed calculation formula, and the convective heat transfer coefficient is determined accordingly. And determining the diameter of the pipeline by combining the convective heat transfer coefficient and the economical efficiency. And the cooling radius and the optimal operation mode of the ventilation pipe foundation are further determined, so that heat balance at the bottom of the foundation is ensured, and permafrost at the lower part of the foundation is effectively protected. The design method is simple, convenient, rapid and accurate, and has important engineering application value and wide applicability.

The invention provides a sensorless motor stator temperature protection method, device and equipment, and relates to the technical field of motor control, and the protection method comprises the steps: obtaining the current voltage, current and rotating speed of a motor when the motor in a motor control system is in a running state, determining a corresponding temperature rise coefficient and a heat balance temperature according to the current voltage, the current current and the current rotating speed; obtaining a current estimated temperature according to the current voltage, the current current and the current rotating speed; determining a current predicted temperature according to the current estimated temperature, the heat balance temperature, the last estimated temperature and the corresponding temperature rise coefficient; and comparing the current predicted temperature with a preset protection threshold value, and performing temperature protection control on the motor according to a comparison result. A temperature sensor does not need to be installed in the motor, so that the installation difficulty and cost are reduced, the reliability and durability of the system are improved, and the risk that the sensor breaks down or is damaged is avoided.

The invention relates to a simulation and optimization method and device for a battery thermal management system, and belongs to the technical field of battery simulation. The method comprises the following steps: constructing a battery thermal simulation model based on physical characteristics of a battery; establishing a heat conduction model and a heat balance equation of the battery, substituting the heat conduction model and the heat balance equation into the battery thermal simulation model, and simulating temperature distribution of the battery under different working conditions by using a numerical solution method to obtain a simulation result; optimizing the design scheme of the battery thermal management system based on the simulation result; verifying the optimized battery thermal management system based on an actual test environment to obtain a verification result so as to determine whether a design scheme of the optimized battery thermal management system is modified or not, and performing thermal management on the battery based on the optimized battery thermal management system under the condition of determining that the design scheme is not modified; the stability and safety of the battery system under the extreme temperature condition can be effectively improved, the service life of the battery is prolonged, and the energy utilization efficiency of the battery is improved.

The invention relates to the technical field of intelligent building heat load prediction and heat balance regulation and control, and discloses an intelligent building heat balance dynamic regulation and control method and system based on load prediction, and the method comprises the steps: constructing a time-frequency causal double-flow analysis network, mutual enhancement of the time-frequency characteristics and the causal relationship is realized; designing a hierarchical causal discovery algorithm, and mining a multilevel causal structure; developing a causal enhanced time-frequency representation learning method, and fusing time-frequency and causal information; establishing an intervention decision framework based on anti-fact analysis, and evaluating an intervention effect; an abnormal mode self-evolution recognition system is realized, and new abnormal modes are continuously learned; an interpretable abnormity diagnosis mechanism is developed, and a clear diagnosis report is provided; according to the method, the thermal load prediction accuracy is improved, the abnormal early warning capability is enhanced, the intervention efficiency is improved, the system interpretability is enhanced, and the optimization of the energy utilization efficiency is realized.

The invention discloses a roof radiant cooling and independent fresh air dehumidification system mixed operation comprehensive control method, and belongs to the technical field of building environment control and heating ventilation air conditioning. The method comprises the steps that the radiant cooling capacity and the dehumidification capacity of a surface air cooler are calculated through a heat balance equation, and an optimization objective that a top plate radiation system bears 70% sensible heat load and a fresh air system bears 90% humidity load is set; an anti-condensation strategy is triggered by combining dew point temperature monitoring, a control variable is adjusted by taking minimization of energy consumption as a target in a rolling time domain, and it is ensured that the indoor temperature ranges from 23 DEG C to 26 DEG C, the humidity ranges from 40% to 60%, the black ball temperature difference is smaller than or equal to 2 DEG C, and the condensation risk is smaller than or equal to 6%. The method is suitable for energy-saving temperature and humidity regulation and control of large public buildings, and efficient cooperative processing of sensible heat and latent heat loads is achieved.

The invention discloses an energy-saving ground source heat pump control method and system, and the method comprises the steps: building a ground source heat pump system dynamic model which comprises an indoor heat balance model, a ground source heat pump unit model and a soil heat exchange model, obtaining a topological network through coupling, designing a distributed control and fault-tolerant operation strategy according to the topological network structure, and carrying out the control of the ground source heat pump system. Each node is locally controlled according to the position and adjacent node information, a state space model is constructed, an optimal control action sequence is solved through quadratic programming to balance energy consumption and an indoor and outdoor temperature deviation objective function, the optimal operation state is obtained, and the mapping relation between the optimal operation state and environment parameters is learned through a neural network; a ground source circulation flow control algorithm is designed, and circulation pump flow distribution and unit working parameter automatic adjustment are achieved. According to the method, the control precision and stability of the ground source heat pump system can be effectively improved, reliable operation of the ground source heat pump system under complex working conditions is ensured, the energy utilization efficiency is remarkably improved, energy conservation and consumption reduction are achieved, and meanwhile good interpretability is achieved.

The invention discloses an excavator heat dissipation control method and system based on environment temperature and operation working conditions. The excavator heat dissipation control method comprises the steps that S1, the operation working conditions of an excavator are divided into five working conditions including the super-heavy load working condition, the heavy load working condition, the medium load working condition, the light load working condition and the super-light load working condition; s2, the external environment temperature is divided into 10 gears; s3, according to the environment temperature and the operation working condition, the heat dissipation requirement is divided into 10 gears; s4, the rotating speed of the cooling fan is adjusted according to the cooling requirement gear, so that the cooling requirement is accurately matched with the rotating speed of the cooling fan; and S5, whether the temperature of the working medium in the excavator is larger than a high-temperature threshold value or not is judged, if yes, heat dissipation is conducted according to the corresponding heat dissipation fan rotating speed obtained through the heat balance test, and if not, heat dissipation is conducted according to the actual heat dissipation requirement gear standard. The problem of heat dissipation redundancy caused by single parameter control is solved, and dynamic matching of the rotating speed of the fan and the composite heat dissipation requirement is achieved. And the energy consumption under the low-load working condition and the cold environment is reduced, and the risk of insufficient heat dissipation under the high-temperature heavy-load working condition is avoided.

The invention discloses a multi-strategy collaborative heat supply balance control method based on virtual heat supply network grouping, which relates to the technical field of virtual heat supply networks and comprises the following steps: dividing a heat supply network into a plurality of virtual heat supply network groups according to the similarity of a first parameter set in the heat supply network; estimating the thermal load demand and the heat supply capacity of each virtual heat supply network group through a dynamic thermodynamic model and a thermal load prediction model; calculating a heat load characteristic parameter set based on the heat load demand and the heat supply capacity, and selecting a heat supply strategy of each virtual heat supply network group; and performing coordination control on the heat supply network based on the heat supply strategy. Through real-time monitoring and a dynamic grouping mechanism, abnormal nodes can be quickly identified and adjusted, and the flexibility and adaptability of a heat supply network are ensured.

The invention is suitable for the technical field of air conditioner regulation and control, and provides an air conditioner flexible regulation and control method and device, computer equipment and a computer program product. The method comprises the following steps: when an indoor air temperature predicted value reaches an indoor comfortable temperature upper limit value, giving a comfort level alarm; in response to the comfort level alarm, adjusting the indoor set temperature of the air conditioner and the set value of the air conditioner operation power according to the building heat balance model until the comfort level alarm is stopped; when the comfort level alarm stops, the set values of the indoor set temperature of the air conditioner and the operation power of the air conditioner serve as latest set values, and the air conditioner is operated according to the latest set values; the building heat balance model comprises the corresponding relation of the outdoor heat transfer amount, the indoor heat disturbance amount, the virtual battery charging and discharging heat and the air conditioner refrigerating / heating amount. The comfort level warning is performed based on the indoor air temperature predicted value, and the air conditioner indoor set temperature and the air conditioner operation power are adjusted according to the building heat balance model, so that the air conditioner power and the indoor temperature can be accurately controlled.

The invention provides a lithium ion battery core temperature prediction method based on a finite element model, and the method comprises the following steps: 1, designing an electrochemical test experiment, and constructing a one-dimensional electrochemical model containing a lithium ion battery electrochemical heat production mechanism; 2, designing a lithium ion battery temperature test experiment, obtaining electrochemical parameters, heat transfer characteristic parameters, internal thermophysical parameters and environmental parameters of the battery under different working conditions, and obtaining a temperature change curve of the center position and the surface of the battery; and step 3, based on the heat balance equation, establishing a three-dimensional heat transfer model having the same geometric characteristics as the battery used in the experiment. According to the experimental result in the step 2, the three-dimensional heat transfer model is subjected to non-uniform region division, each region corresponds to one one-dimensional electrochemical model, and the heat production rate per unit volume is calculated by the one-dimensional electrochemical model in the step 1; introducing the heat production rate of each area into a three-dimensional heat transfer model to calculate the temperature distribution of the battery, and designing an experiment to correct a one-dimensional electrochemical model; 4, modifying the operation conditions and heat dissipation conditions of the battery, and calculating and analyzing the temperature difference delta T between the center position and the surface position of the battery under different operation conditions and heat dissipation conditions by using the three-dimensional heat transfer model in the step 3; and 5, measuring the surface temperature of the battery, and calculating the temperature of the center of the battery according to the working condition of the battery in the step 4 and the delta T corresponding to the environment temperature, thereby realizing monitoring of the temperature of the center position of the battery. According to the method, a high-precision algorithm model is constructed and verified by utilizing data accumulated in an earlier-stage experiment, the central point temperature which is difficult to directly measure in the battery is predicted only through real-time and easily-acquired battery surface temperature information, operation condition parameters and heat dissipation conditions, key thermal state information is provided for a battery management system, and the battery management efficiency is improved. The method is used for real-time safety monitoring and thermal management optimization.

The invention discloses a hybrid model driving-based space-time consistency regulation and control method for a central heating system, which comprises the following steps of: performing hydraulic equilibrium analysis on the central heating system, and performing hydraulic analysis on a space structure of a heating pipe network by using a graph theory method based on an energy conservation law, simulating the hydraulic working condition of the official website by using a basic loop analysis method; based on an energy conservation and mass conservation heat balance equation, a heat source and a heat user are indirectly connected through heat exchanger transition, a dynamic physical model of each subsystem is established based on a lumped heat capacity method, a refined model of the heat supply system is established, and the thermal dynamic characteristics of the system are researched and analyzed; based on a Pearson's correlation function, considering thermal inertia of equipment such as a pipe network of the central heating system and a building fence structure, and determining a regulation and control period and time of the regulation and control model; according to the method, by controlling the opening degree of the regulating valve of the heat exchange station, the suitability degree of the room temperature of a heat user is guaranteed.

The invention belongs to the technical field of crude oil electric heating furnaces, and relates to a crude oil electric heating furnace control system and a crude oil electric heating furnace. Temperature feature vectors of multiple independent heating sections are collected, a dynamic weight matrix used for representing the thermal inertia unbalance degree is generated, and temperature control compensation gains are generated through real-time analysis in combination with crude oil viscosity-temperature data; performing adaptive adjustment by combining corresponding element values of the dynamic weight matrix to output a segmented power regulation instruction, preferentially calling redundant power of the main and auxiliary coils for cooperative heating, starting adjacent segment compensation heating when the main and auxiliary power is insufficient, and setting heat balance constraint and deviation monitoring termination conditions at the same time; local over-coking is avoided while the power resource utilization rate of the crude oil electric heating furnace is remarkably improved, the viscosity is rapidly converged to a steady-state range through closed-loop feedback of viscosity data after heating and iterative optimization of a regulation instruction, and the stability of long-term operation of the system and the achievement speed of a control target are remarkably improved.

The invention relates to the technical field of building energy conservation, in particular to an edge computing cooperative communication method for multiple heat pumps and a photovoltaic system, which comprises an edge server, a cloud server, multiple heat pumps, a variable frequency pump and an indoor and outdoor heat supply device, and is characterized in that the edge server realizes time synchronization of equipment through an OPC UA over TCSN protocol, a multi-level energy topology network is established, and the multi-level energy topology network is connected with the cloud server; in combination with physical energy flow and information flow, based on a building heat balance equation, an edge server controls a heat pump to work at an energy-saving operation point according to indoor and outdoor temperatures and user requirements, and the flow of a variable frequency pump is adjusted. In addition, multi-mode state sensing is achieved through the distributed sensor network, a layered self-adaptive control strategy is executed, photo-thermal collaborative optimization and heat pump group collaborative control are achieved, the system collaborative control precision is remarkably improved through the method, the time synchronization error is reduced by three orders of magnitude, and the system response speed reaches the millisecond level and is 10 times faster than that of a traditional system.

An electrothermal coupling probabilistic load flow calculation method considering time correlation characteristics of an input variable comprises the following steps: introducing an adaptive window width reflection kernel density estimation method to fit wind speed data, and establishing an uncertainty model of the input variable; a Sobol random sequence obeying [0, 1] uniform distribution is generated, a random number sequence considering time correlation is generated by using a position sorting method according to input actual measurement data, and finally a wind speed sequence sample is obtained through a cubic spline interpolation method. Inputting structural parameters of a power system, introducing a heat balance equation, and establishing an electrothermal coupling probabilistic load flow calculation model by being combined with a probabilistic load flow calculation model; and initializing the model, inputting a wind temperature sequence of each scene, and carrying out electrothermal coupling probabilistic load flow calculation by utilizing a Monte Carlo simulation method distribution based on a Sobol sequence. Uncertainty modeling is carried out according to a model output result, the result is evaluated and analyzed, and a conclusion is obtained. The method is of great significance in analyzing the operation condition of the power system and further guaranteeing safe and stable operation of the power system.

The invention relates to a ground source heat pump control method and device, air conditioning equipment and a medium, total recharge heat of a ground source heat pump within cooling time is determined on the basis of historical record information corresponding to the ground source heat pump, and heat compensation load calculation of all time periods is carried out on the basis of the total recharge heat in combination with load prediction data corresponding to the ground source heat pump; the method comprises the steps of obtaining predicted heat compensation amount corresponding to a current time period, then performing heat compensation load correction based on the predicted heat compensation amount in combination with data acquisition information corresponding to the ground source heat pump to obtain to-be-compensated heat of the ground source heat pump in the current time period, and controlling the ground source heat pump to perform heat compensation in the current time period according to the to-be-compensated heat. According to the control method, the heat required to be injected into the soil in the current time period is completed, the time-phased heat storage control mode of the ground source heat pump is achieved, and therefore annual cold and heat balance control over the ground source heat pump is achieved, and the problem that in the prior art, the ground source heat pump is used for energy conversion, and consequently cold and heat of underground soil are unbalanced is solved.

The invention belongs to the technical field of intelligent heat supply, and provides a green power consumption heat storage and release matching control method and system based on a water heat storage boiler, and the method comprises the steps: firstly obtaining a heat load prediction sequence and an electric power spot market price prediction sequence of a heat supply system; secondly, regarding the heat supply network as a graph structure composed of nodes and pipelines, and establishing a pipe network dynamic model for describing the hydraulic and thermal characteristics of the heat supply pipe network; and finally, with the purpose of minimizing the comprehensive operation cost of the heat supply system in the whole scheduling period, and with the whole network heat balance, heat source operation, centralized heat storage device operation, heat supply network safety and user comfort as constraint conditions, solving to obtain a source network load storage cooperative control strategy. The purpose of integrated collaborative optimization of the heat source, the energy storage, the pipe network and the load is achieved, a scheduling strategy with better economical efficiency can be generated, and the problems that the absorption capacity is insufficient, and the overall operation economical efficiency of the system is not high are solved.

The invention relates to the technical field of orchard meteorological disaster prevention and reduction frost prevention, and provides a surface layer disturbance temperature inversion frost prevention method. According to the method, the frost rate of the orchard can be effectively reduced and the frost loss can be reduced through the processes of constructing the orchard air temperature prediction model, determining the frost disaster threshold value, installing fan pipe tower equipment in the orchard, collecting temperature data in real time based on a sensor network of an Internet of Things monitoring system and optimizing fan parameters through the heat balance model.

The invention provides an integrated energy system operation optimization method considering a source-load fusion scene, and relates to the technical field of energy optimization, and the method comprises the steps: constructing a typical output scene based on historical renewable energy output data; fusing the typical output scene with the electric-thermal load data in the corresponding time period to generate a typical scene sequence representing source-load correlation; taking the comprehensive operation cost as a target, establishing a scheduling optimization model for simultaneously constraining the electricity-heat balance, the equipment output and the energy storage state, and embedding the typical scene sequence into the scheduling optimization model; solving the optimization model to obtain a multi-period optimal scheduling strategy; and controlling energy supply and storage equipment in the integrated energy system according to the scheduling strategy. According to the method, the optimal energy supply scheme of the comprehensive energy system capable of effectively avoiding the uncertainty of the source load is generated for a typical source load fusion scene, the economic benefit of the system is effectively improved on the basis of ensuring energy supply safety, and multi-target balance of economy and reliability is realized.

The invention provides a battery system regulation and control method and system based on an SOX algorithm. The method comprises the following steps: acquiring an SOC value and an SOH value of each battery monomer, determining whether to perform equalization adjustment on the battery pack in combination with the SOC value and the SOH value of the battery pack, performing performance test on the battery pack after equalization adjustment to obtain performance test data, including equalization performance test data and heat balance performance test data, processing to obtain a battery pack balance evaluation index and a heat balance state evaluation index, testing the battery pack under different loads to obtain response stability test data, and processing to obtain a response stability evaluation index; and processing according to the battery pack balance evaluation index, the heat balance state evaluation index and the response stability evaluation index to obtain a battery system comprehensive evaluation index, and obtaining corresponding battery system regulation and control strategy data. Therefore, the technology of accurately regulating and controlling the battery system is realized.

A heat balance optimal satellite sun orientation control method comprises the following steps: firstly, determining sun orientation target parameters according to a sun vector direction calculated by an orbit, using preset sun orientation target parameters when regular preset parameters are set, and then calculating a sun orientation target attitude angle and angular velocity by using a formula provided by the method, and finally, the sun orientation of the satellite to the target attitude angle and angular velocity is realized according to the measurement of the terahertz gyroscope and the plane control of the jet phase.

The invention discloses a pump station unit state comprehensive evaluation method, and belongs to the technical field of pump station unit detection. The method comprises the following steps: acquiring multi-source monitoring data and generating a standardized monitoring data set; time-varying mutual information between indexes is calculated, a dynamic threshold value is determined in combination with current working condition parameters and a water level difference correction term, and a dynamic association network is constructed; performing physical mechanism characteristic decoupling on the data, including stripping a vibration signal working condition drift component based on a reference curve to obtain a vibration residual error, and calculating an equivalent standard working condition temperature based on a heat balance principle; respectively calculating a first weight based on data statistics and a second weight based on network topology, and adaptively generating a comprehensive coupling weight according to a consistency coefficient of the first weight and the second weight; and finally, judging a health state level by using a cloud model. Through deep fusion of a physical mechanism and data driving, the problems that fault features are difficult to extract and the model robustness is poor under variable working conditions are solved, and accurate evaluation of the unit state is achieved.

The invention relates to the technical field of ground source heat pumps, and discloses a ground source heat pump buried pipe zoning layout and cold and heat balance control method which comprises the following steps that the current three-dimensional ground temperature field state of the area where a ground source heat pump buried pipe is located is obtained; predicting a future state sequence of the ground temperature field under different control strategies in a future prediction time domain; solving to obtain an optimal control sequence based on a multi-objective optimization function which aims at minimizing the comprehensive operation cost of the system in the prediction time domain; the multi-objective optimization function at least comprises an energy consumption item representing system short-term operation energy consumption and a balance item representing a ground temperature long-term balance state; and executing the first control action in the optimal control sequence. The prediction model constructed by the invention can combine a physical rule with a data residual continuously learned from actual operation, and ensures that prediction information on which a control decision depends always keeps high fidelity in long-term operation of the system.