1608 results about "Energy conservation" patented technology

The invention provides a reusable rocket landing stage starting height prediction method, a guidance system and a processor, and aims to dynamically and accurately determine the ignition time of an engine by constructing a real-time online starting height prediction model based on an energy conservation principle and combining multiple safety thresholds (including an allowable starting height upper limit and a standby starting height lower limit) so as to predict the starting height of the rocket in a landing stage. And the safety and fuel optimality in the whole flight envelope are ensured, so that the reliability, accuracy and economical efficiency of the reusable rocket landing are remarkably improved. The problems that in the prior art, engine starting height prediction precision and robustness are insufficient, online adaptation to uncertainty of a complex flight environment cannot be achieved, and safety margin consideration is insufficient are solved, and potential safety risks are thoroughly eliminated.

The invention relates to the technical field of refrigeration house energy-saving control and digital twinning, in particular to a refrigeration house fan energy-saving operation method and system, and the method achieves the whole-field temperature deduction of a sensor-free area by constructing a CFD reference model and simulating and predicting the three-dimensional transient airflow and temperature distribution in a refrigeration house. Model parameters are calibrated through measured data, and the order of the model is reduced by adopting intrinsic orthogonal decomposition and Galerkin projection, so that the calculation amount is remarkably reduced, and online optimization is supported. And in combination with a data assimilation algorithm, the prediction result of the reduced-order model is continuously corrected, and the adaptability to environment change and system aging is improved. The optimization control stage takes minimization of the total energy consumption of a fan as a target, solves an optimal fan control sequence under the hard constraint that the whole-field temperature does not exceed the cargo safety upper limit and does not exceed the cargo safety lower limit, and adopts a rolling time domain mode for execution to realize collaborative optimization of safety and energy conservation.

The invention belongs to the technical field of electronic equipment thermal management, and discloses an electronic equipment thermal field rapid prediction method for multi-physical field strong coupling. According to the method, a layered heat source intensity distribution model is constructed, a grid mapping relation topological graph technology and a boundary node energy conservation compensation mechanism are developed, a multi-time scale coupling transfer function is designed, and a dynamic adjustment strategy based on phase deviation analysis is introduced. According to the method, the non-uniform heat source distribution and thermal diffusion dynamic characteristics under the high-frequency condition are accurately captured, the energy consistency of multi-physical field coupling is ensured, the thermal field prediction precision is improved, particularly, the method has outstanding advantages in the aspect of phase and amplitude prediction of transient thermal response, and meanwhile calculation resource consumption is greatly reduced.

The invention discloses a temperature and humidity cooperative control method for an air source heat pump drying room, and relates to the technical field of energy conservation, environmental protection and intelligent manufacturing. The method comprises the following steps: acquiring gas heat state parameters and material and environment characteristic parameters in an air source heat pump drying room, and constructing a multi-source state vector; calculating a dynamic response coefficient group and a material evaporation influence coefficient based on continuous sampling data, and establishing a cross response model; a control compensation signal is generated and corrected according to the disturbance estimator, and the comprehensive control quantity is input into an execution module of the air source heat pump system; a dynamic response coefficient group and a lag correction parameter are updated through a periodic feedback data set, and dynamic coordination between temperature and humidity variables is achieved; the response stability of temperature and humidity control can be maintained under the condition that the material moisture content, the stacking density and the external environment condition change, system oscillation and energy consumption deviation are reduced, and the energy efficiency level of the air source heat pump drying process and the product drying uniformity are improved.

The invention discloses a public building cold load short-time prediction method fusing physical information, and the method comprises the steps: collecting and preprocessing the historical cooling capacity, indoor environment, outdoor weather and equipment operation state data of a public building at a fixed time interval, and obtaining multi-dimensional input features; respectively establishing a workday sub-model and a holiday sub-model according to workday and holiday scene division; the workday sub-model and the holiday sub-model jointly form a cold load prediction model, the workday sub-model adopts a long short-term memory (LSTM) network, and the holiday sub-model adopts a light gradient elevator (Light GBM); a physical constraint loss function based on building energy balance and heat conduction residual error is introduced in the training process, and the physical constraint loss is fused into a total loss function according to a weighting coefficient so as to constrain that the output of each sub-model accords with the law of energy conservation and thermal inertia; monitoring the prediction error MAPE in real time and performing online calibration; and outputting a short-time cold load prediction result.

The invention discloses a low-carbon transformation method, system and device for a building air conditioning system. The objective of the invention is to solve the problems of static model, single target, one-sided evaluation and non-standardized process in the existing reconstruction technology. According to the method, building multi-dimensional data are collected; constructing a building energy consumption prediction physical simulation model coupled with a user behavior prediction model based on machine learning to dynamically reflect a real operation condition; a multi-dimensional objective function is defined, and a Pareto optimal transformation scheme set is generated; constructing an evaluation model based on an analytic hierarchy process and a fuzzy comprehensive evaluation method, and calculating a comprehensive evaluation value of each scheme; and selecting an optimal scheme according to the comprehensive evaluation value, and generating a detailed implementation report. The method can scientifically and efficiently determine the global optimal transformation strategy considering energy conservation, carbon reduction, comfort and economy, and significantly improves the scientificity and comprehensive benefits of building transformation decision.

The invention discloses an LED (Light Emitting Diode) energy-saving street lamp system self-adaptive to an ambient light effect and an illumination adjusting method thereof, and belongs to the technical field of novel illumination control and green energy conservation. The system comprises a light environment sensing module, a traffic flow monitoring module, an LED driving power supply and an electroluminescent illumination module composed of a plurality of light emitting diodes. The main control module is configured to execute active lighting effect decoupling logic, namely, when the electroluminescent lighting module keeps steady-state lighting, the driving power supply is controlled to inject a micro-disturbance modulation signal which cannot be perceived by human vision into output current, and illuminance response data of the light environment perception module are synchronously collected; the road surface reflectivity coupling coefficient is obtained in real time by calculating the change ratio of the response data to the modulation signal, then the reflected light component excited by the street lamp itself is accurately removed from the total illumination value, and the pure environment background illumination is decoupled. The problems of misoperation and energy waste caused by self-luminous interference of a traditional light-operated street lamp are solved.

The invention discloses a control method for steam condensate waste heat recovery and waste water heating, a control device for steam condensate waste heat recovery and waste water heating, control equipment and a computer readable storage medium. The thermal load and the logarithmic average temperature difference are calculated based on the energy conservation principle, and the needed heat exchange area is calculated through a logarithmic average temperature difference method. A flow combination scheme of the plate heat exchanger is determined according to the heat exchange area and the flow parameters, a steam condensate side adopts a single flow, and a waste water side adopts asymmetric configuration of double flows or multiple flows so as to adapt to the flow difference of the two sides. In addition, a real-time monitoring mechanism is further established, when the total heat transfer coefficient is decreased by more than 10%, a cleaning program is automatically triggered, continuous and stable operation of the system is guaranteed, and efficient utilization of waste heat resources is achieved.

The invention relates to the technical field of electric energy metering of a low-voltage power distribution system, and provides an EM algorithm-based district metering device misalignment identification method and system. The method comprises the following steps: establishing a theoretical misalignment value model of each outgoing line in different metering misalignment states, and determining a mapping relation between the different misalignment states and actual electric quantity data; the method comprises the following steps: constructing theoretical deviation values of each outgoing line metering device in different misalignment states on the basis of a transformer area incoming and outgoing line electric energy data and energy conservation relationship, estimating an initial attribution probability of a line state in combination with an index normalization mapping method, and obtaining a posterior attribution probability of each outgoing line line through Gaussian mixture distribution modeling under dynamic prior guidance; and based on the posterior affiliation probability of each outgoing line, constructing an objective function of joint observation value fitting quality, time continuity and misalignment amplitude balance, solving the objective function, and quantifying the electric quantity misalignment proportion of each outgoing line at each moment so as to judge classification and identification of misalignment behaviors.

The invention relates to the technical field of industrial automation control and dynamic simulation, and discloses a centralized control console and 3D model linkage virtual-real simulation system, which comprises a control signal sampling interface, a load response modulation unit, a dynamic model evolution unit and a virtual-real closed-loop feedback unit, the load response modulation unit performs energy consumption weight accumulation on all the virtual controlled objects in transient action to generate a global time scaling factor so as to correct an inertia time constant of the system in real time; the dynamic model evolution unit introduces a hard limiting boundary by using an amplitude limiting link and calculates a process variable; the virtual-real closed-loop feedback unit extracts a control deviation signal and drives a physical instrument to generate a nonlinear damping action, and by establishing a global load modulation model based on energy constraint, a discrete control system spontaneously emerges a nonlinear hysteresis characteristic conforming to physical energy conservation under the low calculation power condition without complex fluid network solution.

The invention discloses a carbon emission flow analysis method for carbon emission evaluation in multiple application scenes, belongs to the technical field of power system carbon emission modeling and evaluation, constructs a connection relationship among nodes, branches and a power supply in a power system, and collects output data and type information of a power generation power supply and a power flow result in multiple operation conditions. The method comprises the following steps: calculating carbon emission of a power generation node, distributing the carbon emission to a load node according to a power flow path, identifying a carbon emission source of the load node by adopting a power tracking method, and calculating carbon emission intensity and a carbon potential index; a transmission structure of carbon emission in a power grid is defined, step-by-step distribution and flow direction tracking of the carbon emission are realized, and the defect that a carbon emission path is unobservable in the prior art is overcome; the identification precision of the carbon emission composition is improved, and a basis is provided for the priority division of energy-saving and emission-reducing measures; a carbon emission path mapping matrix and a transition probability matrix are constructed, dynamic identification of path changes is realized, and discovery of key paths and nodes is facilitated.

The invention belongs to the technical field of electricity markets and low-carbon clearing, and discloses a novel subject participated electricity spot market day-ahead two-stage clearing method under electricity-carbon coupling. The method comprises the following steps: firstly, designing a two-stage clearing mechanism comprising preliminary clearing and multi-target robust optimization; secondly, a unit carbon quota accounting and transaction cost model and a multi-energy power generator model considering marginal cost and carbon emission are constructed based on regional power grid carbon emission factors; then the above models are fused, a non-parameterized uncertain set is adopted to describe new energy fluctuation, a day-ahead two-stage clearing model based on a min-max-min three-layer robust optimization framework is constructed, and the model fuses stepped quotation and dynamic carbon emission factors; finally, the model is converted into a mixed integer linear programming problem, and Camp is adopted; and solving by a CG algorithm. According to the method, the comprehensive clearing cost can be effectively reduced, energy conservation and carbon reduction are promoted, meanwhile, the robustness of the clearing plan to deal with extreme scenes is improved, and the system operation safety is guaranteed.

The invention provides an intelligent collaborative regulation and control method and system for photo-thermal equipment, which give consideration to comfort, health and energy conservation. The method comprises the following steps: acquiring operation state parameters and first outdoor meteorological data of a field to be regulated and controlled; establishing a target function taking the minimum comprehensive energy consumption of the to-be-regulated place as a target, and constraining the target function by adopting a plurality of constraint conditions to obtain an optimization target; taking the operation state parameters of each device at the current moment as one individual to generate a population and taking the first outdoor meteorological data as initial input, and performing iterative optimization on each individual in the population under the limitation of an optimization target by utilizing a pre-trained prediction model and combining a particle swarm optimization algorithm, an optimal regulation and control strategy integrating the light environment, the thermal environment and the comprehensive energy consumption is obtained; and controlling the operation state of each corresponding device in the to-be-regulated place according to the optimal regulation strategy. According to the invention, comfortable, healthy and energy-saving intelligent regulation and control can be considered, and efficient construction and intelligent operation and maintenance of a low-carbon and healthy environment of a building are realized.

The invention discloses a loading lap joint device for cold chain transportation and sorting and a using method thereof, and relates to the technical field of cold chain transportation, the loading lap joint device comprises a drawing cold storage module, a cold storage module, a cold storage module, a cold storage module, a cold storage module, a cold storage module and a cold storage module, the drawing cold storage module is slidably mounted on a sliding groove in the bottom of a cold chain vehicle compartment, and a cold storage cavity is formed in the drawing cold storage module; the linkage defrosting mechanism comprises a frame type defrosting scraping plate arranged above the drawing cold storage module, a frost collecting groove is formed in the side edge of the cold storage cavity, and scraped frost water is guided into the frost collecting groove through the defrosting scraping plate; the lap joint interface module is arranged at the front end of the drawing cold storage module and comprises a conveying plate and a temperature adjusting air curtain which are movably hinged, and the temperature adjusting air curtain communicates with the cold storage cavity and the frost collecting groove through an air duct and releases cold air; the control unit is used for monitoring the temperature in the compartment and the platform position and adjusting the air speed of the air curtain to control the cold air circulation amount. The system not only can automatically remove the frost layer in the carriage and effectively reduce the environment temperature during loading, but also can be flexibly butted with a sorting line, so that energy conservation, high efficiency and temperature control guarantee of a cold chain loading link are realized.

The invention discloses a multi-mode-based self-adaptive air conditioner control method and device and a related medium, and the method comprises the steps that user parameters in a multi-source sensor are collected, and a multi-mode original data set is obtained; performing feature extraction on the multi-modal original data set to obtain a multi-modal fusion feature set; performing parametric fitting by using the multi-modal fusion feature set to construct an individual comfort mapping model; the individual comfort mapping model is controlled and solved, and an air conditioner operation parameter set is obtained; dynamic parameter correction processing is conducted on the air conditioner operation parameter set, and an optimized instruction set is obtained; and performing energy-saving adjustment on the individual comfort mapping model based on the optimization instruction set, and outputting energy-saving control parameters. According to the method, the individual comfort mapping model is controlled and solved, then dynamic parameter correction processing and corresponding energy-saving adjustment are carried out, and finally the energy-saving control parameters are output, so that the individual adaptability of the air conditioner operation parameters is improved, and meanwhile, the energy efficiency is optimized.

The invention provides a deep learning-based ultrasonic-assisted CMT welding process parameter optimization method, which comprises the following steps of: acquiring process parameters, ultrasonic parameters, multi-modal sensing data and result quality labels, and constructing a fusion data set containing numerical simulation and actual measurement samples; and introducing physical consistency constraints of energy conservation, mass conservation and temperature-solid phase fraction evolution into a learning target, and establishing a micro-proxy model comprising a spatial-temporal feature encoder, a layer channel adjacency graph network and a physical consistency output head, so as to realize end-to-end prediction from process / ultrasonic parameters and sensing data to multiple quality indexes. According to the uncertainty of the agent model and the distance between the candidate point and the Pareto frontier, the problems that in the prior art, multi-target / multi-constraint / cross-material migration and online disturbance self-adaption are difficult to solve, and the test cost is difficult to systematically reduce under the small sample condition are solved.

The invention relates to the technical field of power system regulation and control, in particular to a park multi-resource intelligent flexible control method and device considering energy and carbon consumption collaboration, and the method comprises the steps: obtaining historical energy consumption data and historical carbon emission data in a target park; training the historical energy consumption data and the historical carbon emission data based on a feature-level constraint preference optimization algorithm to obtain a park multi-energy prediction model based on feature-level constraint preference optimization so as to predict energy demands in a future time period; constructing a park multi-resource optimization scheduling model according to the energy demand in the future time period; and based on a preset energy storage equipment charging and discharging strategy and a preset flexible load control strategy of the target park, generating a multi-resource energy-carbon cooperative flexible control strategy of the target park according to the park multi-resource optimization scheduling model. Therefore, the problem that an existing cooperative control method cannot meet the comprehensive requirements of the modern park in the aspects of energy conservation, carbon reduction, cost optimization and system stability is solved.

The invention discloses efficient energy-saving reciprocating type integrated ultrafiltration equipment which comprises an ultrafiltration membrane group box body and a circulating pipeline, the ultrafiltration membrane group box body internally comprises a plurality of membrane assembly membrane collecting frames, and a driving assembly for driving each membrane assembly membrane collecting frame to synchronously reciprocate is arranged behind each of two sides of the top of the ultrafiltration membrane group box body. According to the efficient energy-saving reciprocating type integrated ultrafiltration equipment, reciprocating motion of the low-power motor is adopted as an anti-pollution measure of the ultrafiltration membrane, operation energy consumption is effectively reduced, meanwhile, the efficient energy-saving reciprocating type integrated ultrafiltration equipment is matched with a high-quality ultrafiltration membrane material, so that the efficient energy-saving reciprocating type integrated ultrafiltration equipment has high filtering efficiency, a water treatment task can be rapidly completed, and the water treatment efficiency is improved. And the requirements of modern industrial production on high efficiency, energy conservation and environmental protection are met.

The invention relates to the technical field of complex industrial equipment monitoring and digital twinning, and discloses a gas turbine data visualization and intelligent interaction system which comprises a sensor array, a computing unit, a force feedback device, an eye tracker and a display terminal. The system constructs a three-dimensional physical field and corrects a velocity vector by using Kriging interpolation and Euler equation momentum balance, and generates a variable radius flow tube reflecting the compressibility of fluid; calculating mass, momentum and energy conservation residual errors to construct a generalized potential energy field, and generating gradient guide force and self-adaptive damping force by driving force feedback equipment; and dynamically adjusting solving precision and rendering parameters through sight tracking. According to the method, the flow field is reconstructed through physical constraint, multi-modal feedback is introduced, the problem that discrete data feature distortion and single visual interaction are difficult to perceive physical consistency is solved, and high-fidelity reduction of the gas turbine flow field and visual touch synchronous accurate diagnosis of fault types are achieved.

The invention discloses a novel bionic arc-shaped reinforced re-entry honeycomb structure and a platform stress theoretical model, and arc-shaped supports are embedded into traditional re-entry unit cells by utilizing a bionic principle to trigger coupling deformation of multiple plastic hinges, so that the strength, rigidity, stability and energy absorption of the structure are remarkably improved. A platform stress theoretical model of the novel structure is provided based on an energy conservation principle, so that the cost of time, workload and the like of numerical simulation and experiments in a preliminary optimization design stage of the structure is remarkably reduced. Under the parameters of the invention, the platform stress and the specific energy absorption of the reentrant honeycomb structure are up to 10.4 times that of the traditional reentrant honeycomb structure, the rigidity and the stability of the reentrant honeycomb structure are improved to 11.7 times and 1.7 times, and the stable deformation mode and the crushing force efficiency of the reentrant honeycomb structure are superior to those of the traditional reentrant honeycomb structure. The composite material is suitable for scenes requiring high energy absorption and stable impact resistance, such as the protection fields of equipment such as pier collision resistance, canal collision resistance gates, automobile collision resistance, aircraft wing buffer layers and run-flat tires in civil engineering.

The invention discloses a device and a method for simulating heat exchange and friction resistance measurement of an aviation high-speed motor under different working conditions, and relates to the field of heat management of high-speed rotating equipment. An additional heating sheet is attached to the outer surface of the inner rotor, and different surface structures are detachably assembled on the outer rotor to form a stator and rotor slit flow channel boundary; cooling liquid forms one-inlet and one-outlet forced convection through the radial through hole of the end cover. The rotating speed larger than or equal to 20,000 rpm, runner pressure drop and temperature data are synchronously collected through an axle load type sensor, and the heat exchange coefficient, the flow resistance coefficient and the friction resistance coefficient are calculated in real time based on energy conservation, a Darcy formula and a torque empirical formula. A real rotor surface structure is reproduced under the condition of high-speed rotation, working medium leakage is restrained through mechanical sealing, and runner blockage caused by centrifugal deformation of the surface structure is prevented through the outer rotor designed in an integrally-formed mode; the obtained convective heat transfer-resistance coefficient-friction resistance coefficient all-parameter curved surface database can guide optimization of the cooling flow channel of the aviation motor.

The invention discloses an electric energy metering error evaluation method and system for a direct current charging pile, equipment and a medium, and the method comprises the steps: constructing an electric energy disturbance response function based on transient voltage and transient current, and effectively quantifying the transient metering deviation caused by measurement lag, voltage drop, current peak and other factors in the actual operation of the direct current charging pile. Error reconstruction modeling has higher dynamic adaptive capacity and physical rationality, the limitation that in the prior art, the influence of the high-variable-load working condition on metering cannot be reflected is broken through, and the accuracy and timeliness of direct-current charging pile error monitoring are greatly improved. Besides, a standard error is introduced to carry out fitting calibration on a reconstruction error and carry out energy conservation verification, thereby realizing verifiability on a physical level and controllability in engineering implementation, enhancing credibility and authority of an evaluation result, constructing a closed-loop analysis mechanism from error evaluation to metering correction and then to conservation verification, and improving reliability and reliability of the evaluation result. And the closeness and the adaptive capability of the overall error evaluation are improved.

The invention belongs to the technical field of electrode material preparation, and particularly relates to a preparation method of boric acid-assisted low-temperature sintered porous aluminum foil. The preparation method comprises the following steps: dispersing aluminum powder, boric acid and binder raw materials in a solvent to form dispersed slurry; and coating a matrix with the dispersed slurry, drying, sintering at 450-600 DEG C under protective gas, reacting boric acid with aluminum oxide on the surface of the aluminum powder to form low-melting-point aluminoborate, reducing the sintering temperature, promoting aluminum atom diffusion, increasing sintering neck formation, and sintering to obtain the porous aluminum foil. Boron oxide generated by decomposition of boric acid is added to react with aluminum oxide to form low-melting-point aluminoborate, the sintering liquidus temperature is reduced, aluminum atom diffusion is promoted, and low-temperature sintering at 450-600 DEG C is achieved. The aluminum powder sintered foil is suitable for energy storage devices such as an aluminum electrolytic capacitor and a lithium ion battery, has the advantages of low-temperature energy conservation, high porosity and strong mechanical property, and solves the problems of aluminum oxide obstruction and high high-temperature energy consumption of the traditional aluminum powder sintered foil.

The invention discloses a regenerative braking energy recovery method combining dynamic planning and model predictive control, which relates to the technical field of vehicle energy conservation, and comprises the following steps: establishing a dynamic model of a vehicle braking process, performing global energy recovery optimization based on dynamic planning, generating a global optimal reference trajectory, and adopting model predictive control rolling optimization. The reference trajectory is tracked to maximize energy recovery efficiency. According to the method, global optimum is guaranteed through dynamic planning, and meanwhile, the energy recovery efficiency of the regenerative braking process is improved by utilizing model predictive control.

The invention discloses a window cleaning robot cleaning liquid supply and recovery control system and method based on intelligent perception, and belongs to the technical field of intelligent cleaning equipment. The problems that in the prior art, the supply and recovery process of cleaning liquid is extensive, self-adaption to the stain degree cannot be achieved, energy consumption is high, and potential safety hazards exist are solved. According to the technical principle, the visual detection module recognizes the grade of stains on the surface of glass, the recovery sensing module monitors the state of waste liquid and feeds back mop state signals through the negative pressure adjusting module, and the central controller adjusts the spraying amount of cleaning liquid according to the grade of the stains, judges the sewage load according to the state of the waste liquid and controls the recovery pump to operate in a continuous, intermittent or closed mode. And adjusting the rotating speed of the fan according to the mop state signal to maintain the optimal adsorption force. Intelligent cooperation of cleaning liquid supply and recovery and negative pressure adjustment is achieved, precise cleaning, energy conservation and consumption reduction are achieved, safety and reliability are improved, and control parameters are continuously optimized through the self-learning function.

The utility model relates to a self-heating check gate steel gate based on combination of solar energy and an electrothermal film, which comprises a gate body, a groove is arranged on the upstream face of the gate body, a flexible electrothermal film is laid in the groove, an electric control cavity is arranged on the gate body above the groove, and the flexible electrothermal film is arranged in the electric control cavity. A cover body is arranged at the top of the electric control cavity, a solar panel is arranged on the cover body, a rubber sealing plate is arranged outside the flexible electrothermal film, a fixing edge is formed on the edge of the rubber sealing plate, the rubber sealing plate is fixed on the gate body outside the groove through a plurality of connecting pieces, and an embedded convex part matched with the groove is arranged on one side of the rubber sealing plate; an energy storage battery and a controller are arranged in the electric control cavity, an on-off switch connected with the controller is arranged between the energy storage battery and the flexible electrothermal film, and a temperature sensor connected with the controller is arranged on the gate body. According to the self-heating steel gate of the check gate, the problems of difficult opening and closing, gate deformation and the like caused by icing and freezing of a gate in a cold region can be solved; the characteristics of high efficiency, energy conservation, stable operation and the like are realized.

The invention belongs to the field of building environment control, and provides a thermal comfort dynamic adaptive control method based on multi-modal wave analysis and AI driving. According to the method, environmental parameters, user physiological signals (HRV) and subjective thermal comfort data are synchronously collected in real time, time-frequency characteristics of the physiological signals are extracted through continuous Morlet wavelet transform, high-order dynamic characteristics are constructed, the thermal comfort state is predicted in combination with deep learning, a deep reinforcement learning strategy is optimized through an NSGA-II algorithm, a multi-target optimal strategy set is generated, and the optimal thermal comfort state is obtained. And finally, a multi-arm bandit model with Bayesian inference is utilized to realize strategy online adaptive updating. By applying the method, the thermal comfort prediction precision can be expected to be greater than or equal to 90%, the net energy conservation is greater than or equal to 32%, the limitation of the existing thermal comfort regulation and control method in a dynamic situation is effectively solved, and the dynamic balance of personalized thermal comfort and system energy conservation is realized.

The invention relates to a direct current furnace machine-furnace coordination system dynamic modeling method suitable for a wet condition. Based on the law of mass conservation and energy conservation, a lumped parameter method is adopted to construct a dynamic model comprising a coal pulverizing system, a coal economizer-water wall system, a water storage tank system, a superheater system and a steam turbine system; identifying parameters are optimized step by step by only utilizing unit variable load dynamic operation data and combining with the mechanism constraint that the heat absorption capacity of a working medium is monotonically increased along with the coal quantity as fired: static parameters are determined through dynamic data regression, nonlinear parameters are optimized based on a preset water-cooled wall outlet flow and dryness function structure, and the heat absorption capacity of the working medium is calculated. And finally, identifying dynamic parameters step by step by adopting an immune genetic algorithm. The dynamic characteristics and the physical consistency of the established model are verified through open-loop simulation, and the technical problems that dynamic description of the water level of the water storage tank is missing and the modeling precision is low under the wet working condition are solved.

The invention discloses a throttling device movable high-temperature and high-pressure hydrodynamic test system and method, and belongs to the field of high-temperature and high-pressure hydrodynamic tests. The system comprises a cold module, a hot module and a test section module which are connected into a circulation loop through detachable pipelines. The cold module provides and drives a working medium; the heat module comprises a heat regenerator and a preheater, and preheating is carried out by utilizing residual heat of a working medium after the test, so that energy conservation is realized; the parallel flow channel design is adopted in the test section module, and a plurality of throttling device test pieces can be installed at the same time for synchronous testing. The problem that a traditional test bed is heavy and cannot be moved is solved through modular design, the test efficiency and energy efficiency are greatly improved through parallel test and efficient heat recovery, a test system can be conveniently deployed on site, high-precision and batch hydrodynamic characteristic calibration is conducted on multiple throttling elements under the highest pressure of 25 MPa and the flow of 1.2 t / h, and the test bed is suitable for large-scale popularization and application. And rapid research, development and verification of key equipment in the fields of nuclear energy, heat energy and the like are effectively supported.

The invention discloses an intelligent calibration method and system for the electric quantity of an instrument, and relates to the technical field of electric energy metering of an electric power system.The intelligent calibration method comprises the steps that an electric meter network diagram with a main meter and sub-meters as nodes is constructed, and robust composite correlation indexes are calculated on the basis of reading increments in a sliding time window; the interference of common background load and instantaneous noise is suppressed by using a threshold clipping and main table purification mechanism, so that the depiction capability of the correlation graph on a physical connection relationship is improved fundamentally, and the phase to which the sub-table belongs can be identified more accurately in a stock area with unknown phase or incomplete topology; a graph neural network model is introduced based on the network graph, electric meter embedding representation with physical meaning is obtained through neighborhood information aggregation, phase grouping is achieved in combination with unsupervised clustering, split-phase energy balance loss is designed in the training stage, and the difference between the reading of a main meter and the sum of the reading of sub-meters in each phase group is used as a constraint. Alignment of the embedding space and the energy conservation relation is pushed in a self-supervised mode.