3145 results about "Heat supply" patented technology

The invention provides a heat supply load prediction and scheduling method based on energy storage peak regulation, and the method comprises the steps: obtaining multi-modal data of a heat supply system, carrying out the preprocessing of the multi-modal data, and constructing a space-time joint feature matrix based on the preprocessed multi-modal data; inputting the spatio-temporal joint feature matrix into a multi-modal depth load prediction model for heat supply load prediction to obtain a heat supply load prediction result; the multi-modal deep load prediction model is obtained by training a deep learning prediction model fused with physical constraints through system historical data; based on the heat supply load prediction result, a distributed energy storage scheduling strategy is generated in combination with a multi-agent reinforcement learning algorithm based on an MADDPG framework, and scheduling operation of the heat supply system is carried out according to the distributed energy storage scheduling strategy; and the energy utilization efficiency and the power grid stability are improved.

The invention discloses a cold and heat supply unit and process capable of deeply utilizing a heat source in the technical field of absorption refrigeration. The cold and heat supply unit comprises a refrigerating unit, a heating unit, a heat source flash tank and a high-pressure absorber. The refrigerating unit utilizes an external heat source to produce cold energy, the heating unit utilizes the heat source used by the refrigerating unit to produce cold energy so as to cool circulating water of the refrigerating unit, and the heat source flash tank utilizes the heat source discharged by the high-pressure absorber to heat; the absorption refrigerating unit is optimally designed, so that the absorption refrigerating unit can deeply utilize a heat source and supply cold and high-level heat energy at the same time, the problem that the heat source utilization rate of the unit is not high is solved, and the requirement for high-temperature heat energy in the production process is met; and low-grade waste heat is converted into cold energy and high-level heat energy, transition and upgrading of energy quality can be achieved, the unit has the cold and heat combined supply function, and the application scene is greatly expanded.

The invention discloses a heat supply system multi-working-condition scheduling control method based on a large model and multiple agents. The method comprises the steps that a heat supply system digital twinborn model is established; the method comprises the following steps: setting a scheduling control center management agent, predicting a thermal load demand by adopting a large language model and combining a thermal load prediction model, dividing a system into a plurality of operation conditions, and setting a plurality of condition sub-agents corresponding to the operation conditions; the dispatching control center management agent judges whether the working condition sub-agents under the corresponding operation working conditions are triggered to start working or not, and meanwhile heat load demand values, predicted through a large language model, of all time periods in the future and the heat production amount of the new energy heat supply unit are transmitted to the corresponding working condition sub-agents; and the working condition sub-agent adopts a large language model to establish a system optimization scheduling control knowledge graph based on the large language model, obtains a scheduling control strategy of each device on the source network load side of the heat supply system, and feeds back the scheduling control strategy to the digital twinborn model for guiding the actual operation management of the heat supply system.

The invention discloses a low-vacuum circulating water heating dynamic load matching method based on AI regulation and control, and the method comprises the following steps: step S100, multi-source data real-time collection: building thermal environment parameters are synchronously collected through a temperature sensor array, a vacuum pressure transmitter, a flowmeter and an environment monitoring unit which are deployed in a distributed manner; according to the method, the control period is compressed to the minute level, compared with traditional PID control, the response speed is increased by several times, the indoor temperature can be controlled more accurately, and meanwhile the failure rate of equipment is reduced. According to the sudden weather coping mechanism, heat supply strengthening can be started 30 minutes ahead of time under extreme weather such as snowstorm weather, and the stability of the system is ensured. The method is characterized in that the prediction advantage of deep learning and the optimization capability of model prediction control are deeply combined, and the control problem of multivariable strong coupling of the low vacuum system is solved through a verification system of multi-source data fusion and virtual-real combination.

The invention relates to the technical field of collaborative optimization, and discloses a gas power generation and heat supply collaborative optimization method and system based on a particle swarm algorithm. The method comprises the following steps: acquiring and preprocessing operation parameters of the gas power generation and heat supply system to obtain state characterization data, constructing gas resource limitation and equipment operation constraints based on the data, and generating an optimization objective function; importing the optimized objective function into a particle swarm algorithm for initialization to obtain an initial particle set; a particle swarm is evolved through a search operation based on a gas energy critical path, near-end strategy optimization is carried out, particle swarm parameters are dynamically adjusted, and a target configuration scheme is obtained. And finally, establishing a multi-level cooperative control structure, executing hierarchical scheduling, and generating a cooperative optimization control instruction. The gas power generation and heat supply system is subjected to collaborative optimization control through an intelligent optimization algorithm, the influence of dynamic factors such as gas concentration fluctuation and energy demand change is overcome, and efficient utilization of gas energy is achieved.

The invention discloses a secondary network heat supply temperature control method and device based on a negative pressure water mixing technology, and relates to the technical field of secondary network heat supply control. The secondary network heat supply temperature control method and device based on the negative pressure water mixing technology comprises the steps that S1, operation data, structure steady state data and thermal environment data in a current heat supply task are collected, and a standardized heat supply working condition data set is constructed after preprocessing; s2, local hydraulic fluctuation characteristics are evaluated, and the water mixing proportion, the water supplementing flow and bypass path configuration are dynamically adjusted; s3, jointly analyzing the temperature difference of supply water and return water, the heat deviation and the valve state, and driving water mixing adjustment and path optimization; s4, evaluating adjustment intensity and heat response deviation, and realizing abnormal disturbance response and adjustment strategy correction; and S5, recording negative pressure, uneven heat and cold and response data for subsequent diagnosis and steady state identification. The problems that a traditional water mixing control means is difficult to effectively inhibit pressure fluctuation of the water return end, local negative pressure is easily formed, and local energy waste and uneven heat distribution are caused are solved.

The invention discloses a dynamic load adaptive charging pile liquid cooling control method, relates to the technical field of thermal management, and solves the problems of temperature prediction deviation, local hot spot leak detection and protective supercooling caused by a simplified thermal model based on fixed parameters and key temperature points under rapid load fluctuation. Parameterization time-varying heat supply network parallel multi-rate observation is constructed, a heat exchange coefficient and node heat capacity are identified and calibrated through recursion with physical constraints, transmission time delay is merged into an extended state in an explicit mode, short-window high-frequency sampling and local temperature field reconstruction are triggered based on residual errors, and the time-varying heat supply network parallel multi-rate observation is achieved. A control sequence is issued in parallel by adopting hierarchical rolling type control with a second-order moment uncertainty constraint; based on the scheme, the short-term temperature field prediction precision and the local hot spot identification capability are improved, and the cooling resource directional utilization efficiency and the charging system operation continuity are remarkably improved.

The multi-energy complementary heat supply system comprises an external basic heat source, a middle-grade synergistic heat source, a high-grade energy storage heat source, an intelligent heating power mixing center and a central controller, and the intelligent heating power mixing center is used for heating heat source equipment of all levels and operation instructions of associated assemblies according to the operation instructions of the heat source equipment of all the levels and the operation instructions of the associated assemblies. Heat energy of different grades is mixed and allocated, and heat loads meeting the grade requirements of heat consumers are output to the heat consumers; the central controller is used for establishing a multi-target optimization model taking the minimum total operation cost of the system as a core target based on the electricity price prediction data and the different-grade thermal load prediction data, solving the multi-target optimization model and generating a system operation strategy under the condition that preset basic guarantee logic, economic operation logic and peak response and power grid interaction logic are met; and the generated system operation strategy is converted into an operation instruction for the heat source equipment of each level and the associated assembly, so that the reliability and the adaptability of operation control of the heat supply system are effectively improved.

The invention provides a heat supply digital twinborn intelligent regulation and control method, and relates to the technical field of intelligent regulation and control, and the method comprises the steps: executing millisecond-level high-concurrency numerical simulation according to a dynamic digital twinborn body, so as to obtain a simulation result; based on the simulation result, coupling the electricity price fluctuation data and the weather prediction data, performing future heat supply system multi-working-condition deduction, and dynamically optimizing a heat source unit start-stop combination and pipe network valve opening strategy to obtain a deduction result and an optimization strategy; generating an equipment regulation and control instruction set according to the deduction result and the optimization strategy; and an equipment regulation and control instruction set is issued to an edge computing node, a variable-frequency circulating pump and an electric control valve executing mechanism are controlled, and dynamic closed-loop regulation of the flow and the pressure of the heat supply pipe network is achieved. According to the invention, the pipe network flow and pressure regulation response time can be shortened to a second level.

The invention discloses an intelligent building heating and ventilation automatic control method and system based on digital twinning, and relates to the technical field of intelligent heat supply. The method comprises the specific steps that entity data of a building and a heat supply system are obtained, a building heat supply system twinborn model is constructed, and a digital twinborn automatic control system is constructed based on the building heat supply system twinborn model; deploying a multi-modal sensing network, and constructing a distributed data monitoring system; real-time data collected by the distributed data monitoring system is input into the digital twin automatic control system, and a dynamic control strategy is generated in combination with historical data; and the heat supply system is controlled to execute actions based on the dynamic control strategy, and feedback data are sent to the digital twin automatic control system for control strategy optimization. According to the invention, the response speed of the system is obviously improved, and the adaptability to complex and changeable environments is enhanced.

The invention relates to the technical field of heat transmission, in particular to a heat transmission data storage and management system based on an industrial big data platform, and the system comprises a self-adaptive acoustic baseline modeling module which generates a self-adaptive baseline model library for storing the mapping relation between a working condition area and a model; the abnormal deviation degree calculation module is used for calculating and generating an abnormal deviation degree; the health state evaluation module is used for generating a comprehensive health index representing the long-term service performance of the pipe network; and the closed-loop correction and scheduling module is used for determining a comprehensive risk level according to the comprehensive health index and the change trend thereof, generating an operation and maintenance scheduling instruction for dynamically adjusting an abnormal deviation degree calculation process and pipe network operation parameters, and realizing closed-loop feedback control. According to the invention, accurate identification and positioning of abnormal events such as leakage, third-party damage and the like are realized.

The invention discloses an analogue simulation system for operation of a ground source heat pump and a gas boiler in a severe cold area. The analogue simulation system comprises a heat supply correction model building module, a ground source / gas heat supply estimation module, a heat supply dispatching distribution module and a correction model optimization module. According to historical operation data of a ground source heat pump subsystem, heat supply correction models associated with soil geology and environmental climate are constructed based on a single variable principle, a heat supply amount estimated value of the ground source heat pump subsystem is dynamically corrected, heat supply amount of a gas boiler subsystem and heat load required by a building group are estimated, heat supply output of the two subsystems is intelligently distributed, and heat supply efficiency is improved. And the heat supply amount correction model is optimized through the actual heat supply amount deviation. The method can effectively overcome the problem of ground source heat pump heat supply amount deviation caused by soil heat unbalance and climate fluctuation in a severe cold area, further improves the energy efficiency estimation precision of a heat supply system, facilitates optimization of a scheduling strategy, has dynamic compensation and model self-evolution capabilities, and can adapt to complex environmental changes.

A clothes drying device, including an air channel, an air path switching assembly, multiple clothes drying apparatuses, and multiple heating apparatuses. The air path switching assembly includes a first multi-position switching component and a second multi-position switching component. The first multi-position switching component and the second multi-position switching component are respectively provided between a hot air input section and intermediate heat source sections and between a hot air output section and the intermediate heat source sections; the first multi-position switching component and the second multi-position switching component have the same number of switching positions and are configured to work in conjunction to each other so that at least one clothes drying apparatus is selectively communicated with the corresponding hot air input section, the hot air output section, and the intermediate heat source sections so as to form a circulation loop.

The invention relates to the technical field of data processing, and discloses a heat supply network heat supply system control method based on a prediction model, and the method comprises the steps: S1, collecting historical operation data and real-time operation data of a heat supply network heat supply system, S2, carrying out the preprocessing of the historical operation data and the real-time operation data, and generating a standardized heat supply data set; by constructing a prediction model based on historical data and real-time data, the thermal load demand change in a future time period can be dynamically predicted, the problem of adjustment lag caused by dependence on a static model in a traditional control method is solved, the response ability of a heat supply system to extreme weather and user demand sudden change is improved, and the heat supply efficiency is improved. The stability and reliability of heat supply quality are guaranteed, the time hysteresis between a regulation and control instruction and the actual heat supply effect is reduced by analyzing the heat transmission characteristic and the delay effect of each node of the pipe network in real time, the phenomena of insufficient heat supply and energy waste caused by untimely regulation of the system are avoided, and the energy consumption is reduced. And the operation efficiency and the energy utilization rate of the heat supply system are improved.

Methods and apparatus for anti-ice heat supply from waste heat recovery systems are disclosed. An apparatus for an aircraft, the apparatus comprising a fuel heat exchange system, an anti-ice heat exchanger, a waste heat recovery heat exchanger, and a conduit coupled to the fuel heat exchange system, the anti-ice heat exchanger, and the waste heat recovery heat exchanger, the conduit including a first portion and a second portion distinct from the first portion, wherein the first portion of the conduit carries a first portion of a thermal transfer fluid from the waste heat recovery heat exchanger to the anti-ice heat exchanger in which the thermal transfer fluid supplies anti-ice heat to a portion of the aircraft, wherein the second portion of the conduit carries a second portion of the thermal transfer fluid from the waste heat recovery heat exchanger to the fuel heat exchange system.

The invention discloses an offshore multi-energy combined supply system based on constant-pressure compressed carbon dioxide energy storage and an operation method of the offshore multi-energy combined supply system. The system comprises a working medium storage device, a heat energy storage device, a charging process module, a gas-liquid conversion loop, a discharging process module, a cold energy supply module and a heat energy supply module. By improving the energy release process structure of the compressed carbon dioxide energy storage system, the pressure of high-pressure carbon dioxide is reduced to normal pressure after primary expansion, so that low-temperature cold energy is generated while power is generated, consumption of stored heat is saved, residual stored heat is used for heat supply, the comprehensive utilization rate of energy is increased, and combined supply of cooling, heating and power is achieved; the system further comprises an integrated thermally-driven combined cooling and power supply subsystem capable of switching power generation / refrigeration modes, organic Rankine cycle and jet refrigeration cycle are highly integrated, investment cost and space occupation are reduced, redundant heat energy is flexibly and efficiently converted into electric energy or cold energy, and the flexibility of multi-energy combined supply of the system is improved.

The invention discloses a circulating water waste heat recovery and air cooling collaborative optimization method which is used for solving the problems that an existing air cooling system, an existing waste heat recovery system and an existing water treatment system normally operate independently and lack a unified coordination mechanism, when environment parameters or operation working conditions change, all the systems cannot respond collaboratively, and the overall energy efficiency is difficult to achieve. The method comprises the following steps: generating a system state data set according to acquired environment parameters, unit operation parameters, heat supply network parameters and whole-plant multi-water-source water quality parameters; according to the system state data set, a nozzle array operation strategy is determined through a preset total spraying amount calculation model; according to the unit operation parameters and the heat supply network parameters, waste heat recovery power is determined; determining a water source distribution strategy according to the multi-water-source water quality parameters; according to the nozzle array operation strategy, the waste heat recovery power and the water source distribution strategy, a waste heat recovery-air cooling collaborative optimization strategy is generated; and a cooperative control instruction set is generated according to the waste heat recovery-air cooling cooperative optimization strategy.

The invention relates to a physical-data dual-drive heat supply system heat demand prediction and optimization control method and system, and belongs to the technical field of intelligent regulation and control of regional energy systems. A multivariable time sequence is given, the forward LSTM and the backward LSTM respectively process the multivariable time sequence, and bidirectional hidden state splicing is output; constructing a decoder layer by using a multi-head self-attention mechanism, and parallelizing attention heads; the re-attention module dynamically adjusts attention distribution based on physical constraints derived from fluid thermodynamics, realizes deep learning to pay attention to related key physical parameters in a prediction process, and generates a physical vector P through heat flux Q and inertial delay tau; and fusing and outputting the predicted temperature of the secondary return water. According to the method, physical knowledge and depth sequential modeling are combined, prediction precision and physical interpretability are combined, and the interpretability, robustness and generalization of thermal dynamics of a heat supply system in an actual area are enhanced.

The invention discloses a heat supply pipeline welding seam detection device, and relates to the technical field of heat supply pipeline processing, the heat supply pipeline welding seam detection device comprises a transmission mechanism 1 and a detection bin, the transmission mechanism 1 is provided with an inverted U-shaped support, the bottom wall of the horizontal section of the inverted U-shaped support is slidably connected with magnetization members in a front-back symmetrical manner, and the inverted U-shaped support is provided with a clamping member and a pretreatment mechanism; a detection bin is arranged on the left side of the first conveying mechanism, and a transferring mechanism, a marking mechanism and a second conveying mechanism are arranged on the detection bin. Through cooperation of the driving assembly and the brushing assembly, the outer wall of the to-be-detected pipe fitting is brushed, the situation that magnetic powder, oxide skin, burrs and the like adhere to the surface of the pipe fitting, the magnetic powder gathering phenomenon caused by non-defect factors is caused, and misjudgment occurs in the detection process is avoided, through cooperation of the driving assembly and the flushing assembly, the pipe fitting is flushed, and the detection efficiency is improved. The scraped impurities are prevented from being attached to the outer wall of the to-be-detected pipe fitting, and meanwhile, the pre-wetting treatment can be carried out, so that the fluorescent magnetic suspension is helped to cover the surface of the pipe fitting more uniformly.

The invention relates to the technical field of heat supply control, in particular to a heat supply secondary network branch line intelligent hydraulic equilibrium method and device, a medium and a product. The method comprises the following steps: constructing a branch topological graph of a heat supply secondary network in a target heat supply area; the environment temperature is obtained in real time, the heat supply station is controlled to supply heat to each heating single body in the target heat supply area based on the dynamic flow control strategy, and the node flow and the node temperature of each node in the branch topological graph are collected; constructing a branch heat supply loss model of the branch topological graph based on the environment temperature, the node flow and the node temperature; the monomer temperature and heat supply backflow data of each heating monomer are obtained, and a monomer heating model is constructed for each heating monomer based on the environment temperature, the monomer temperature and the heat supply backflow data; and determining a flow regulation and control strategy based on the monomer heating model and the branch line heat supply loss model, and adjusting the monomer heat supply flow of the heat supply secondary network based on the flow regulation and control strategy. According to the method, heat supply hydraulic balance can be achieved through precise flow regulation and control precision.

The invention belongs to the technical field of energy system scheduling, and particularly discloses a multi-time-scale dynamic optimization scheduling method and system for an integrated energy system, and the method comprises the steps: collecting the operation data and topological parameters of each energy device in the integrated energy system, constructing an initial energy flow model, and mapping the initial energy flow model to a discrete time domain from a Laplacian domain, establishing a linear dynamic energy flow model; calculating the inertia time of the system according to the normalized step response of the heat supply network and the natural gas network, and constructing a multi-time scale scheduling framework with double-layer intra-day rolling optimization according to the inertia time; and setting different optimization objective functions in three scheduling levels, namely a day-ahead scheduling level, an intra-day upper layer scheduling level and an intra-day lower layer scheduling level, so as to realize dynamic optimization of the running state and load adjustment of the coupling equipment. The problems of time scale separation, discontinuous state, poor adaptability of heterogeneous network inertia difference and the like in an existing scheduling method are solved, and the scheduling stability and the operation economy of the comprehensive energy system under the high permeability of renewable energy sources are improved.

The invention relates to the technical field of heat supply unit peak regulation capacity optimization, in particular to a heat supply unit heat storage peak regulation strategy construction method and device and a storage medium, and the method comprises the steps: carrying out the hourly prediction of a day-ahead electrical load and a day-ahead thermal load through a target BO-ResNet-AM neural network prediction model, obtaining a day-ahead hourly electric load predicted value and a day-ahead hourly thermal load predicted value; based on a power supply balance constraint, a heat supply balance constraint, a unit ramp rate constraint and a target function, taking pipe network heat storage / release, actual power supply power and actual heat supply as decision variables, and constructing an initial source network load storage collaborative interaction mode optimization scheduling model; and converging the initial source network load storage collaborative interaction mode optimization scheduling model to a globally optimal solution through an adaptive weight learning factor particle swarm optimization algorithm. By accurately predicting the electric heating load and quantifying the heat storage capacity of the pipe network, peak clipping and valley filling of the electric load and space-time translation of the thermal load are achieved, and the deep adjustment and peak capacity of the unit is improved.

The invention discloses a photovoltaic photo-thermal energy storage multi-element coupled all-weather self-adaptive building energy system and method, and belongs to the crossing field of solar comprehensive utilization and building energy saving. The system integrates a Fresnel lens, a frequency division film, a photovoltaic power generation unit, a thermoelectric power generation unit and a multi-temperature-zone phase change energy storage device, and the surface of the photovoltaic and thermoelectric unit is covered with an aerogel heat collection and insulation layer. Sunlight is focused by a Fresnel lens and then is separated into short-wave light and long-wave light by a frequency division film, and power generation waste heat is stored in a cascade mode through a phase change energy storage device; the intelligent control unit switches a heat supply season mode or a cold supply season mode according to seasons and energy consumption requirements. The system improves the solar spectrum utilization rate, achieves all-weather self-adaptive supply of electricity and heat of the building, is compact in structure, low-carbon and efficient, and is suitable for various building energy scenes.

According to the data center cluster two-stage energy sharing method based on the multi-element load comprehensive demand response, the first stage is a day-ahead optimization stage, uncertainty probability distribution of wind power, photovoltaic power generation and loads is fully considered in the stage, and a shared energy storage (SES) optimization scheduling method based on a conditional worst-at-risk value (WCVaR) is constructed. The second stage is a real-time optimization stage: firstly, designing a novel point-to-point (P2P) transaction mechanism based on an electricity and heat supply-demand ratio so as to realize joint sharing of electricity and heat between DCPs; then, a refined IDR model is provided, the model considers the space-time transferability of data loads and the flexibility, the thermal hysteresis effect and the thermal comfort of the household appliances, and indexes such as the efficiency improvement ratio are introduced to evaluate the IDR model; and finally, constructing a benefit function of the DCCO and the DCPs.

The invention provides a centralized heating method and system based on room temperature feedback regulation, and the method comprises the steps: collecting and verifying real-time room temperature data, and generating a room temperature feedback signal; the signals are transmitted to a central control unit for sequential processing, and a temperature-time two-dimensional data matrix is generated; a preset dynamic compensation algorithm is used for calculating a heat demand correction value of each heat supply pipe network key node; the heat supply pipeline flow is dynamically adjusted according to the correction value; and verifying the effect through a closed-loop feedback mechanism and optimizing algorithm parameters. According to the method, a network is constructed to realize multi-node synchronous acquisition and verification, and heat distribution heterogeneity and fluctuation characteristics are captured in combination with matrix processing and interpolation completion. Compared with a traditional single-point sensor, according to the scheme, through two-dimensional mapping and anomaly detection, the adjustment response time is shortened to the sampling period level, the temperature deviation calculation precision is improved to + / -0.1 DEG C level, the overheating-underheating alternating phenomenon is solved, and accurate dynamic matching of the heat demand correction value is achieved.

The invention discloses a heat pump waste heat recovery cooperative heat supply method and system, and relates to the technical field of intelligent heat supply control, and the method comprises the steps: collecting environment data and heat pump operation data through a sensor, and carrying out the data preprocessing; modeling the operation state of the heat pump system by using a gradient lifting tree algorithm, constructing a heat pump load prediction model, and outputting load prediction; in combination with the load prediction result and the heat pump operation data, a collaborative heat supply strategy is obtained through an optimization algorithm; and waste heat recovery scheduling is carried out according to the load prediction result and the current waste heat recovery condition. According to the method, the accuracy and the real-time performance of load prediction can be remarkably improved, heat source configuration and heat supply requirements are highly matched, the waste heat utilization rate is improved to the maximum extent, power consumption is reduced, meanwhile, the indoor comfort degree and the system operation stability are guaranteed, finally, the operation cost is remarkably reduced, and the service life of equipment is prolonged.

The invention provides a coal mine multi-source waste heat intelligent utilization system and method based on cross-seasonal heat storage, and relates to the technical field of coal mine waste heat utilization, and the system comprises the steps that a heat prediction module monitors and obtains a plurality of historical redundant heat sequences of a plurality of coal mine waste heat sources, and carries out heat prediction in a preset time window; a heat supply demand prediction module reads the heat use characteristic sequence and the associated heat use characteristic sequence and performs heat supply demand prediction; a heat storage scheme optimization module performs heat storage scheme optimization and outputs an optimal heat storage proportion sequence by taking a heat supply quantity sequence meeting a predicted demand as a conditional constraint, taking the maximum capacity of heat storage equipment as an equipment constraint and taking the minimum heat loss as a target; and the heat storage management and control module executes heat storage management and control in a preset time window according to the optimal heat storage proportion sequence. The technical problem that in the prior art, waste heat cannot be effectively stored can be solved, the technical target of intelligent regulation and control system construction is achieved, and the technical effect of improving the waste heat utilization efficiency is achieved.

The invention discloses a high-pressure combustion combined heat and power generation energy storage system and method for hydrogen and oxygen production through electrolysis, and relates to the field of hydrogen energy storage. After the electrolytic cell produces high-pressure hydrogen and oxygen, the high-pressure hydrogen and oxygen are stored in the hydrogen / oxygen storage tank, the system can operate in a hydrogen / oxygen mode, and in the oxygen mode operation, the hydrogen and oxygen steam mixed gas from the oxygen storage tank and the hydrogen / oxygen evaporation compressor are combusted in the high-pressure combustion chamber to generate superheated steam, and then the superheated steam enters the expansion turbine to do work; due to excessive oxygen, dead steam after acting is separated into two working media through a gas-liquid separator, that is, gas enters a cooler to be cooled and then returns to a combustion chamber through a hydrogen / oxygen evaporation compressor, drainage water generated after liquid enters a heat supply heat exchanger is pressurized through a water pump and then enters a high-temperature combustion chamber, and therefore clean utilization of hydrogen energy and cyclic regeneration of the working media are achieved. The system can realize high power generation efficiency and excellent environmental protection performance, and is suitable for regions requiring stable consumption of fluctuating renewable energy sources, power and heat supply and the like.

The invention relates to the field of uranium concentration, and discloses an energy-saving device and method for drying a first-batch centrifugal unit. According to the device, an inlet of a centrifugal machine is connected with an outlet of an evaporator through a pipeline provided with a fourth cooling valve and an eighth cooling valve and is connected to the secondary side of a cooling plate heat exchanger and the secondary side of a heating plate heat exchanger respectively; an outlet of the centrifugal machine is connected with an inlet of the evaporator through a sixth cold valve, a first cold valve and a second water pump. An inlet of the sixth cold valve is connected with the secondary side of the heat supply plate heat exchanger through a first water pump. The primary side of the cold supply plate heat exchanger is connected with a newly-built cooling tower loop, and the primary side of the heat supply plate heat exchanger, the condenser and the newly-built cooling tower form circulation. By optimizing system connection and a heat energy circulation path, the energy utilization efficiency and the equipment utilization rate are effectively improved, and the investment and operation cost is remarkably reduced.

The application provides a heat supply network adjusting method and device, which comprises the following steps: determining the proportion of resident users in a heat supply area; when the proportion of resident users is less than a proportion threshold, predicting the heat supply load of the heat supply area to obtain the predicted heat supply load of the heat supply area; when the proportion of resident users is greater than or equal to the proportion threshold, determining the area type of the heat supply area; determining the heat supply satisfaction degree based on the area type of the heat supply area; predicting the load of resident users and industrial users to obtain the predicted resident load and the predicted industrial load; correcting the predicted resident load by the heat supply satisfaction degree, and determining the predicted heat supply load of the heat supply area by the predicted industrial load and the corrected predicted resident load; comparing the predicted heat supply load with the actual heat supply load of the heat supply network, and controlling the distributed energy storage system to adjust the heat supply network according to the comparison result, so that the time lag of the heat supply network regulation is shortened, and the response capacity of the heat supply network is improved.