1119 results about "Heat power" patented technology

The invention belongs to the technical field of intelligent home control, and particularly relates to an electric blanket intelligent temperature control system, which analyzes the matching relationship between the heating power and the temperature response in the historical operation cycle of a plurality of independent subareas of an electric blanket, fuses the thermal coupling effect between the subareas, and independently quantifies the dynamic thermal inertia parameter of each subarea. Based on the independent temperature change trend and the real-time temperature deviation of each partition, a control state including a steady state, a transient state or a strong compensation state is decided and maintained for each partition, the dynamic thermal inertia parameter, the real-time temperature deviation and the current control state are integrated, differentiated feed-forward compensation amounts are generated and superposed to the output of a PID controller of the corresponding partition, and the control state of the corresponding partition is calculated. A final power control instruction is generated after amplitude limiting and smooth filtering, temperature response lag caused by thermal inertia is actively predicted and counteracted, precise control is achieved in combination with partition state recognition, and the system response speed and control stability are remarkably improved.

The invention discloses an active prediction type modular battery thermal management system, which comprises the following steps: a liquid path and electrical connection module, a data acquisition module, a communication transmission module, a working condition identification module, a feedback control module, a cooperative control module, an execution adjustment module, a state feedback module, an exception handling module, a redundancy switching module and the like. A prediction control instruction is generated by combining a working condition recognition result, a fusion control quantity is formed by the prediction control instruction and temperature feedback, amplitude limiting control is conducted according to thermal power evaluation and a set threshold value, coordinated adjustment of a pump, a valve and a bypass assembly is achieved, and if recognition fails or data is abnormal, the system automatically freezes prediction control and executes closed-loop adjustment only depending on feedback. And the standby device takes over the fault after fault judgment, so that continuous operation and safety maintenance of the system are guaranteed. The system has a modular structure and complete maintenance process support.

The invention relates to the technical field of data processing, and provides a multi-mode water-cooling heat dissipation system and method.The thermal load urgency degree is generated by obtaining the temperature change rate and the thermal power density of a component in real time, the running state of the component is monitored, and a user scene identifier is output; comparing the temperature difference value of the cooling liquid at the inlet and outlet of the radiator with the cooling liquid flow to estimate the instantaneous heat dissipating capacity; predicting a temperature change track based on the thermal load urgency degree and the user scene identifier, calibrating the temperature change track in combination with the instantaneous heat dissipation amount, determining a candidate mode set and an optimization weight through the user scene identifier, and selecting a target heat dissipation mode; temperature distribution of different areas of the radiator is obtained according to the target heat dissipation mode so as to distribute the target rotating speed of the fan, respond to the local high heat load, control the multi-way valve to dynamically adjust the topological structure of the cooling liquid flowing path and distribute the cooling liquid flow, and deep cooperation of the fan and the cooling liquid is achieved.

The invention discloses a regulation and control system and method based on heat energy of an energy storage cabinet, and belongs to the technical field of intelligent heat management. Temperature data in the energy storage cabinet are collected, a temperature distribution matrix is constructed, and a thermal gradient vector and an overheating risk area are extracted based on a difference algorithm; further establishing a thermal power load mapping model, and dynamically generating an air circulation path optimization diagram; the opening angle of a flow deflector and the rotating speed of a fan are adjusted in combination with an optimized path, and self-adaptive regulation and control of a thermal field in the cabinet body are achieved; meanwhile, a machine learning model is trained by utilizing historical operation data, an optimal regulation and control strategy is output, and an execution layer is driven to realize collaborative response of a fan and a flow deflector; the method has the advantages of high regulation and control precision, high response speed, low energy consumption and the like, and is suitable for heat management requirements of various types of energy storage cabinets.

The invention relates to the technical field of thermal field modeling and control, and particularly provides a molecular beam epitaxy substrate temperature field control method and system based on artificial intelligence, and the method comprises the following steps: obtaining the all-region temperature data of the surface of a substrate, and the heating power and environment parameters of each region of a heating cavity; inputting the heating power and the environmental parameters into the temperature field model, and outputting a temperature distribution matrix and temperature gradient data of the surface of the substrate; predicting temperature prediction data according to the temperature distribution matrix, the heating power and the sequence data of the environmental parameters in the historical time period; and inputting a state vector formed by the temperature distribution matrix, the temperature gradient data, the heating power data and the temperature prediction data into a deep reinforcement learning model, and then outputting the heating power adjusting quantity of each area to control a temperature field. According to the invention, the problems of insufficient prediction precision and real-time performance of the substrate temperature in the prior art are solved, the influence of environmental factors and heating power on the substrate temperature is considered, and the temperature field control capability is improved.

The invention relates to the technical field of intelligent sintering, and discloses a rare earth magnet intelligent sintering production line and a control system, and the system comprises a temperature data collection module, a temperature gradient evaluation module, a temperature change rate fitting module, a heating power adjustment module, a directional heat energy compensation module and an optimized heating instruction generation module. Temperature distribution information in the sintering furnace is obtained; evaluating real-time temperature gradients of different positions in the sintering furnace, and comparing the real-time temperature gradients with a preset gradient threshold value to identify a temperature abnormal region in the sintering furnace; fitting the temperature change rate of the temperature abnormal area; the material phase change critical parameters of the rare earth magnet in the current sintering stage are combined to adjust the heating power of the temperature abnormal area; performing directional heat energy compensation on the temperature abnormal region to obtain a power compensation amount; superposing the power compensation amount and the reference power of the sintering furnace to generate an optimized heating instruction; the intelligent sintering control efficiency of the rare earth magnet can be improved.

The invention relates to the technical field of industrial production control, in particular to a polyurethane raw material preheating control method and system. The method comprises the following steps: acquiring tank body temperature, environment temperature, batch temperature rise, tank body structure and raw material liquid data, constructing a thermal resistance-thermal capacitance series-parallel model to represent system thermal inertia characteristics, then identifying an initial value drift resistance section, a main temperature rise section and a disturbance absorption section in a segmented manner, and implementing power back-stepping based on segmented data, so as to obtain the thermal inertia characteristic of the system. Dynamically generating a heating power track; and a heating track is replanned in combination with real-time change data, so that precise modeling and self-adaptive control of a temperature rise process are realized, and the temperature control precision and energy efficiency response capability of the preheating system under different raw material batches and different working conditions are effectively improved.

The invention discloses a fused salt heat storage and Carnot cell combined coal-fired unit peak-load regulation operation method, device and equipment, a medium and a product, and relates to the field of unit peak-load regulation operation. Acquiring information data; based on a power regulation demand prediction model, performing peak regulation demand prediction according to the information data to obtain a prediction result; the power regulation demand prediction model is obtained by adopting a multi-objective optimization model and performing time sequence analysis on a long-short-term memory network model; determining an energy scheduling strategy based on the prediction result; the energy scheduling strategy comprises a heat storage power coordination instruction and a heat release power coordination instruction; and according to the energy scheduling strategy, operation adjustment is conducted on the coal-fired unit, the fused salt heat storage subsystem and the Carnot battery subsystem based on the control system. The invention aims to improve the peak regulation performance of the coal-fired unit.

The invention relates to the technical field of process control, in particular to a polyphenylene sulfide polymerizer temperature self-adaptive control method, which comprises the following steps: acquiring melt viscosity, heat release power and residence time deviation of a polymerizer in real time, and constructing a normalized multi-dimensional time sequence input vector by using a sliding window technology; and then, through fusing a weight control model of a long short-term memory network and an attention mechanism, combining static working condition characteristics, and analyzing and outputting adaptive weight coefficients for different deviation dimensions in real time. Meanwhile, based on the shear heat effect and the reaction accumulation effect, specific temperature compensation components for the inlet of the heating medium jacket are calculated, and independent amplitude limiting processing is carried out on all the components. And finally, a target set temperature is synthesized through weighting, and an execution mechanism is driven to act accurately by utilizing cascade PID control and a valve flow characteristic inverse mapping model. According to the invention, through deep fusion and mechanism compensation, accurate steady-state control of the polymerization reaction is realized.

The invention relates to the technical field of crossing of artificial intelligence and intelligent manufacturing, discloses a position self-adaptive AI regulation and control method and system for continuous heat treatment of a fastener, and aims to solve the problems of non-uniform temperature field, high hardness dispersion, increase of quenching cracking rate and the like caused by lack of position perception and dynamic compensation lag in the prior art. According to the method, in-furnace coordinates of fasteners are tracked in real time through a high-speed visual positioning device, a thermal demand prediction neural network model with space-time convolution mixed with a gating circulation unit is constructed in combination with the conveying speed, thermal environment parameters and material characteristics, and an instantaneous thermal power instruction is output; the system comprises a high-speed visual positioning module, a motion state monitoring module, a thermal environment sensing module, a thermal demand prediction module and the like, and drives a high-density partitioned infrared heating array to realize millisecond-level local thermal compensation. According to the method, the temperature deviation of the junction of the temperature zones can be controlled within + / -8 DEG C, the hardness dispersion and the cracking rate are remarkably reduced, and the heat treatment consistency and the finished product yield are improved.

The invention provides an electric kettle heating control method and system based on intelligent temperature control, and relates to the technical field of household appliances. A multi-dimensional temperature measurement module is introduced, a plurality of high-precision temperature sensors are distributed at different positions in an electric kettle, and temperature distribution information of the different positions in the kettle can be obtained in real time; and local temperature misjudgment caused by a single sensor is effectively avoided. Meanwhile, the water level detection module can accurately measure the real-time water volume. On the basis, the system can dynamically distribute contribution indexes of all temperature measurement point positions according to the real-time water quantity, the heating power is adjusted in real time in combination with a PID algorithm, the temperature control precision and stability are remarkably improved, temperature misjudgment is reduced, accurate control over the heating process is achieved, and it is ensured that the water temperature can accurately reach the target temperature set by a user.

The invention discloses a rotating wheel dehumidification system operation control method and system. The dehumidification system comprises a dehumidification rotating wheel, a treatment air circulation unit arranged on the treatment side of the dehumidification rotating wheel and a regeneration air circulation unit arranged on the regeneration side of the dehumidification rotating wheel. The regenerated air circulating unit comprises an air heat exchanger, an electric heater and a heat pump heater; the heat pump heater comprises an evaporator, a condenser and a compressor; the control method comprises the steps that the temperature of regeneration air entering the dehumidification rotating wheel is detected to obtain the regeneration temperature; according to the regeneration temperature and a preset regeneration temperature threshold value, the heating power of the electric heater is dynamically adjusted, and the heating power is larger than or equal to zero and smaller than or equal to rated power. According to the scheme, regeneration exhaust heat can be recycled to the maximum extent, the energy efficiency ratio of the system is remarkably increased, dependence on a high-energy-consumption electric heater is reduced, the operation cost is saved, the regeneration temperature is dynamically controlled, and stable operation under different working conditions is ensured.

The invention discloses a hydraulic mechanical heat dissipation device in the field of hydraulic heat dissipation equipment. The hydraulic mechanical heat dissipation device comprises a heat dissipation pipe, a collection unit and a control unit. A liquid cooling mechanism is communicated in the heat dissipation pipe, and an air cooling mechanism is arranged outside the heat dissipation pipe; the acquisition unit is used for acquiring temperature of hydraulic oil in two ends of the radiating pipe; and the control unit is used for controlling the cooling amplitude of the liquid cooling mechanism and / or the air cooling mechanism based on the temperature acquired by the acquisition unit. According to the scheme, the heat dissipation power can be automatically and flexibly adjusted according to the actual temperature condition of the hydraulic system, so that the heat dissipation accuracy is improved.

The invention relates to a vertical baking oven control system for biscuit production, which comprises an intelligent scheduling module, the output end of the intelligent scheduling module is electrically connected with a multi-mode sensing module, and the output end of the multi-mode sensing module is electrically connected with a self-adaptive wind field control module. And the output end of the self-adaptive wind field control module is electrically connected with a thermodynamic compensation module. According to the application, the baking tray three-dimensional space optimization layout is realized through the intelligent scheduling module, a precise thermal field distribution model is constructed in combination with multi-modal sensing data, and the system adopts a self-adaptive wind field control and thermodynamic compensation technology to dynamically adjust the heating power and the airflow distribution, so that the baking uniformity is ensured; the digital twin central control module optimizes a control strategy through virtual simulation to realize intelligent iteration of process parameters, the intelligent early warning system predicts the drying quality and the equipment state based on machine learning and establishes a grading alarm mechanism, and the energy optimization module reduces energy consumption through a load balancing strategy.

The invention discloses a high-heat-power thermoelectric cell hydrogel for low-grade heat energy collection and a preparation method thereof, and belongs to the technical field of heat energy recovery. The polyacrylamide hydrogel is selected as a substrate of the thermoelectric cell hydrogel, so that a hydrogel internal structure which is easy to regulate and control can be obtained; excellent hydrogel stretchability is obtained by using a cross-linking agent and an initiator with relatively low concentration; potassium ferricyanide and potassium ferrocyanide are used as redox ions to generate a thermoelectric effect, so that stable P-type thermal power is obtained; by using guanidine hydrochloride, the solvation entropy difference between potassium ferricyanide and potassium ferrocyanide is enlarged, and the thermal power of the hydrogel in the thermoelectric cell is greatly improved; sodium pyrrolidone carboxylate is used, so that the concentration of ions in the hydrogel is further improved, the conductivity of the thermoelectric cell hydrogel is improved, meanwhile, a hydrogen bond network between water molecules is destroyed, and the water-retaining property of the thermoelectric cell hydrogel is improved.

The invention discloses an air conditioner evaporator anti-freezing self-adaptive control method, and relates to the technical field of air conditioner evaporator anti-freezing, and the method comprises the steps: S1, data collection: obtaining an evaporator temperature field, environment temperature and humidity and compressor operation parameters through a distributed sensor array, S2, feature extraction: calculating a regional temperature difference gradient and a frosting rate prediction value based on temperature field data, s3, risk grade division, S4, intelligent decision generation, S5, driving execution, S6, real-time monitoring, S7, parameter iteration, and S8, mode switching. Through the steps S1, S2, S6 and S7, a self-learning system for data acquisition, feature analysis, effect feedback and model optimization is constructed, so that the system can continuously adapt to complex scenes such as evaporator performance attenuation and long-term environment change; through the steps S3, S4, S5 and S8, refined hierarchical management and control of risks and dynamic optimization of control parameters are realized, and cooperative adjustment of heating power and fan rotating speed and adaptive reduction of sampling frequency at low risk are combined.

The invention relates to the technical field of photovoltaic photo-thermal heating, and discloses a photovoltaic photo-thermal heat pump heating control method based on a dynamic load. The method comprises the steps that the solar irradiation intensity, the environment temperature, the relative humidity and the building heat load requirement of a target heating area are measured and recorded, and environment load data are formed; on the basis of the data, the connection topology of a photovoltaic photo-thermal heat collector array and a heat pump unit is optimized through a multi-source heat supply assembly collaborative configuration method, and a system structure configuration scheme is determined; according to the scheme, the output thermal power of the heat collector array is dynamically predicted through a photo-thermal conversion efficiency prediction method, and a predicted thermal power distribution scheme is obtained; and finally, on the basis of the predicted heat power distribution scheme, a circulation path of a heat medium between the heat collector array and the heat pump unit is independently controlled through a heat medium directional scheduling method, and a heat medium scheduling instruction is generated. According to the method, dynamic cooperation of all assemblies of the heating system can be achieved, the method adapts to building heat load changes, and the flexibility and adaptability of system operation are improved.

The invention discloses an induction heating path optimization method suitable for a heterogeneous noise elimination structure, and particularly relates to the field of induction heating path optimization of the heterogeneous noise elimination structure, and the method comprises the steps: building a grid coordinate in a target region, collecting the heat conductivity coefficient, the specific heat capacity, the thermal resistance value and the induction coil gap value of each grid node in the grid coordinate, generating a thermal response model; and performing heat conduction calculation on the thermal response model and a preset heating power curve, calculating a temperature rise value of each grid node in a fixed preset heating time, marking the grid nodes of which the temperature rise values reach or exceed a safe temperature threshold and the adjacent grid nodes as heat concentration areas, and generating risk area data after gathering the heat concentration areas. A risk assessment and dynamic reordering mechanism based on local thermal characteristic difference is introduced in a heating path planning process, so that advanced identification and real-time avoidance of a heat concentration area are realized.

The invention provides an anode tail gas recovery and tail gas combustion combined SOFC (Solid Oxide Fuel Cell) combined cooling heating and power system and method. The system comprises an SOFC power generation module, an input system and a tail gas treatment and energy recovery module, the SOFC power generation module is respectively connected or disconnected with the input system and the tail gas treatment and energy recovery module; according to the anode tail gas recovery and tail gas combustion combined SOFC combined cooling heating and power system and method, the structure of the system can be optimized, anode tail gas shunting and intelligent circulation are achieved, and catalytic combustion cooperative treatment is guaranteed; a multi-grade energy cascade recovery system is realized; and an intelligent cooperative control system is realized.

The invention relates to the technical field of textile bio-manufacturing and industrial process automation control, in particular to a bio-based fabric production temperature and humidity intelligent regulation and control system which comprises a data acquisition unit used for acquiring temperature and humidity sensor values in a fermentation curing workshop in real time and reading current heating power of an actuator and a fan rotating speed instruction; the reference state reconstruction unit is used for receiving the input state vector and generating an interference-free reference vector; the disturbance simulation unit is used for generating a theoretical damaged state vector representing a specific fault mode; the double-track difference unit is used for generating a real difference feature vector and a theoretical difference feature vector; the coupling regulation and control unit is used for calculating a similarity value of the real difference feature vector and the theoretical difference feature vector in a number domain space; according to the method, non-ideal factor interference is effectively eliminated, and the physical interpretability and numerical traceability of the reference data are ensured.

The invention relates to the field of oil field heating furnace control, and discloses an oil field heating furnace intelligent digital implementation method and control method.The control method comprises the following steps that S1, a temperature sensor is used for monitoring the temperature of an oil field heating furnace in real time; s2, calculating a temperature error between the upper limit and the lower limit of the real-time temperature and the set temperature according to the monitoring data of the temperature sensor; s3, a self-adaptive PID control algorithm is applied, and heating power is calculated based on the temperature error; and S4, dynamically adjusting the heating power to control the temperature of the oil field heating furnace. The precision and stability of temperature control can be improved, the oil field heating furnace can control the target temperature more accurately, and the production efficiency is improved. Meanwhile, the self-adaptive PID control algorithm can automatically adjust parameters according to actual working conditions and environment changes, the adaptability and robustness of the system are improved, and the requirements for manual intervention and adjustment are reduced. In addition, the stable and efficient heating process can be achieved by dynamically adjusting the heating power, and energy and cost are saved.

The invention relates to the technical field of hot-dip galvanized steel pipe surface treatment, and discloses a hot-dip galvanized steel pipe internal blowing steam electric heating control method and system. The method comprises the steps that the outer diameter, the wall thickness, the surface temperature and steel type information of a galvanized steel pipe are collected, a steam temperature demand value is calculated, the input number and the power duty ratio of sectional type electric heating pipes are dynamically adjusted according to the temperature rise demand, and the heating power is corrected in real time through a cascade closed-loop control system; and calculating the solidification speed of the zinc liquid according to the wall thickness, and processing the thin-walled pipe in a pulse injection mode. The technical problems that in the prior art, steam temperature control precision is insufficient, heating power distribution lacks dynamic adaptation, temperature closed-loop control response lags behind, and a zinc layer on the inner wall of the thin-walled pipe is uneven are solved.

The invention relates to the technical field of vehicle power systems, in particular to a solid hydrogen storage device containing a low-temperature cold-start hydrogen storage cylinder and a fuel cell collaborative power assembly, and the device comprises a heat flow modulation module, a balance driving module, a release coordination module, a power matching module and a power assembly control module. In the hydrogen storage process, through real-time linkage judgment of the interface temperature difference and the heat flux change, directional feedback of energy in different areas is achieved, the stable hydrogen release condition of the hydrogen storage material is maintained, differentiated distribution is conducted on heating power according to the heat flux density deviation, invalid energy consumption and local energy accumulation are avoided, and the energy storage efficiency is improved. Dynamic balance is constructed between the hydrogen release rate and the phase change medium energy absorption rate, the hydrogen supply process is corrected through filtering estimation, the release flow is more stable and controllable, finally, the hydrogen supply stability and the load requirement are combined in the power output link, dynamic matching of the galvanic pile power and the external working condition is achieved, and the energy efficiency is improved. And the response flexibility and the energy conversion efficiency of the power system are improved.

A method and system for preventing condensation of an ultrasonic liquid level meter. The method comprises: connecting a heat tracing unit to an ultrasonic liquid level meter, and deploying a temperature monitoring module; on the basis of a measurement result of the monitoring module, calculating the dew point of the surface of a probe of the ultrasonic liquid level meter; and comparing the dew point with the surface temperature of the liquid level meter measured by the monitoring module and, on the basis of a heating control execution module, performing dynamic temperature control. By means of deploying the heating unit and the temperature monitoring module, the present invention measures the surface temperature of the probe in real time and, on the basis of the calculated dew point, dynamically adjusts heating power, such that the surface temperature of the probe is higher than the dew point temperature, thus effectively avoiding condensation and solving the effect of environment temperature and humidity on the precision of liquid level measurement.

The invention belongs to the technical field of electric control cabinet heat dissipation structure data processing, and particularly relates to an electric control cabinet heat dissipation structure parameter optimization method and system based on a genetic algorithm, and the method comprises the steps: obtaining the multi-source dynamic thermal load data of a to-be-optimized electric control cabinet in a complete process period, and constructing a transient heating power function; constructing a transient thermal resistance network model containing flow field coupling characteristics, defining a to-be-optimized structure parameter vector, and determining flow field thermal resistance coupling efficiency; based on the transient thermal resistance network model, utilizing a genetic algorithm to carry out iterative optimization on the structure parameter vector, calculating a transient thermal shock response index of the key component, and constructing a fitness function according to the transient thermal shock response index to evaluate individual advantages and disadvantages; and when the genetic algorithm meets a preset termination condition, outputting an optimal structure parameter combination, and generating a heat dissipation structure model based on the optimal structure parameter combination. According to the invention, transient thermal shock and dustproof requirements can be effectively balanced.

The invention provides a battery charging strategy determination method and apparatus, an electronic device and a medium. The method comprises the steps of constructing a multi-physical field coupling model of a battery system; simulation is carried out based on an electrochemical model in the multi-physics field coupling model, fast charging characteristic maps of the battery in different temperature intervals are generated, and the fast charging characteristic maps are used for representing the mapping relation among the charging current of the battery, the temperature rise of the battery and the lithium precipitation boundary; setting a maximum self-heating power limit value of the battery in a low-temperature environment based on the fast charging characteristic map; according to a preset low-temperature fast charging index and the maximum self-heating power limit value, reversely solving and determining the lowest initial charging temperature of the battery meeting the low-temperature fast charging index; and based on the lowest initial charging temperature, solving a parameter solution set containing the thickness and the heat conductivity coefficient of the external thermal insulation layer. According to the invention, the charging efficiency of the power battery in a low-temperature environment is improved.

The invention provides a symmetrical clamped micro-beam electric power sensing device based on MEMS resonators, and belongs to the technical field of MEMS sensing. The sensing device comprises a sensing assembly. The sensing assembly comprises a vibration beam, an excitation electrode, a tuning electrode and an auxiliary electrode. The two ends of the vibration beam in the axial direction of the vibration beam are connected with the auxiliary electrodes, and the exciting electrodes and the tuning electrodes are arranged at intervals in the length direction of the vibration beam and arranged on the same side of the vibration beam. Excitation voltage is applied to the excitation electrode so that the excitation electrode can excite the vibration beam to generate resonance. Tuning voltage is applied to the tuning electrode so that the tuning electrode can adjust the rigidity of the vibration beam according to the environment temperature, and the thermal power corresponding to the heat source can be inverted. The two sensing assemblies are arranged in a central symmetry mode, so that interference of electrostatic fields generated by the excitation electrodes and the tuning electrodes corresponding to different vibration beams can be weakened mutually. According to the invention, high-precision power inversion in a wide temperature range can be realized.

The invention discloses a liquid cooling case overload monitoring method based on an intelligent sensor. The method comprises the following steps: deploying a sensor network at a key node of a cooling flow channel of a liquid cooling case; all the sensors are connected with an edge computing gateway; the edge computing gateway synchronously collects data of the sensor and generates a time sequence data set; dynamically calculating the overall heat dissipation power P (t), the system flow resistance coefficient K (t) and a parameter eta (t) representing the cooling efficiency based on the time sequence data set; comparing the calculated value with a reference value, and performing overload risk assessment by applying a preset judgment logic; when the evaluation result exceeds a preset risk threshold value, triggering overload early warning, and generating a control instruction; and according to historical operation data of the system, carrying out periodic self-adaptive calibration on the reference value. By deploying the sensor network at the key node of the liquid cooling case and analyzing the collected data through the edge computing gateway, the response speed and the control precision of the system to the dynamic change of the heat source power are improved.

The invention relates to the technical field of power distribution network toughness demand response, in particular to a power distribution network toughness improvement optimization method, system and device based on response prediction and a storage medium. Training an integrated decision tree model based on historical data to predict a response intention value of the cooling and heating load user, and determining a temperature regulation boundary and a response frequency upper limit according to the response intention value; generating an initial scene set through source load uncertainty sampling, extracting a typical scene by adopting a transportation distance scene reduction method, and introducing an overall offset constraint and a single-point extreme value constraint to perform two-dimensional limitation on scene probability distribution; a scene probability combination enabling the load recovery value to be minimum is searched in a probability distribution domain, and a scheduling scheme enabling the key load recovery value to be maximum is solved under the condition that the power flow constraint, the cold and heat power balance constraint and the temperature regulation boundary constraint are met; and carrying out probability weighting on the load recovery values of different scenes to obtain a toughness evaluation value, and carrying out sensitivity analysis.

The invention provides a chopped chilli fermentation jar temperature remote regulation and control system and method based on supervision and control, and relates to the technical field of temperature remote regulation and control. The abnormal confidence coefficient of the temperature of the chopped chilli fermentation jar in the current chopped chilli fermentation period is determined; calibrating the temperature value of each temperature sensor; further generating temperature regulation and control instructions of a heating rate control section and a constant temperature maintaining section in the current chopped chilli fermentation period; when the abnormal confidence exceeds a set threshold value, a semiconductor temperature control module on the outer wall of the chopped hot pepper fermentation jar body is remotely controlled to execute a temperature regulation and control instruction, temperature gradient distribution in the chopped hot pepper fermentation jar is continuously monitored in the instruction execution process, and then the distribution proportion of the heating power and the refrigerating power of the semiconductor temperature control module is adjusted. According to the application, the internal temperature of the chopped chilli fermentation jar can be remotely and accurately regulated and controlled in a high-acid, high-salt and high-humidity chopped chilli fermentation environment, so that the uniform distribution of the internal temperature of the fermentation jar is improved.