3247 results about "Cold storage" patented technology

The invention relates to an energy management method, device and equipment based on an air conditioning system and a medium. The method comprises the steps that in a preset period, a target cold storage capacity calculation model matched with the current working condition is selected from a plurality of candidate cold storage capacity calculation models according to the pre-obtained photovoltaic power generation power, the air conditioner system load and the change trend of the environment temperature; the environment temperature and the electric energy are input into the target cold storage capacity calculation model, and the cold storage capacity, output by the target cold storage capacity calculation model, of a phase change cold storage material in the air conditioner system is obtained; based on the cold storage capacity, the photovoltaic power generation power and pre-obtained planned electricity consumption probability distribution, analysis processing is conducted, and an energy management strategy of the air conditioning system is obtained; the energy management strategy is used for guiding the air conditioning system to adopt commercial power supply or photovoltaic power supply, whether to utilize the phase change cold storage material for cold storage or not and whether to start a compressor to assist in executing the cold storage process or not. By adopting the method, the power consumption cost can be reduced.

The invention belongs to the technical field of cold chain warehouse management, and particularly relates to a cold storage dynamic scheduling cooperative control method and system based on the Internet of Things, and the method comprises the steps: obtaining operation parameters and environment parameters; according to the operation parameters and the environment parameters, an E-LSTM model is used for analyzing the operation state of the refrigeration equipment, an analysis result is generated, and through a TFT neural network model, the environment parameters and the current time and production plan are combined, and the refrigeration demand change trend is predicted; based on the analysis result and the refrigeration demand change trend, a dynamic scheduling strategy of the refrigeration equipment is generated by combining a scheduling rule and an optimization target and utilizing a PPO algorithm; the scheduling strategy is sent to the PLC control end of the refrigeration equipment through the Internet of Things communication network, the PLC control end performs cooperative control on the refrigeration equipment according to the scheduling strategy, and meanwhile, the execution state of the equipment is fed back to the cloud server. Therefore, the problems of rigid scheduling mode, serious energy waste, insufficient emergency capability and the like in the prior art are solved.

The invention belongs to the technical field of intelligent building energy management, and particularly discloses and provides a dual-mode cold storage air conditioning system based on human flow dynamic cooperative regulation, which comprises the following steps: acquiring dynamic human flow thermodynamic diagram data in real time, and accurately calculating a multi-region linkage cold load demand value based on a density change correlation coefficient and a heat conduction model; the real-time sensing of the flow density fluctuation and the dynamic refrigeration demand matching are realized; the phase change state of the coolant of the cold storage tank and the power consumption data of the refrigerating unit are collected in real time, the cold storage release proportion, the refrigerating power increment and other key parameters are dynamically adjusted, and the energy utilization rate is increased; the inherent defect of non-uniform cold and heat in zone control is overcome by calculating inter-zone cooling capacity migration parameters; temperature feedback data and a people flow thermodynamic diagram are collected in real time, the proportionality coefficient of the fan rotating speed and the air valve opening degree is dynamically adjusted, a closed-loop learning mechanism is formed, and the matching precision of a temperature control strategy and people flow distribution is continuously optimized.

The invention relates to the technical field of cold storage spraying, and discloses a cold storage spraying polyurethane real-time monitoring system based on temperature and humidity feedback, and the system comprises an environment collection module, a state analysis module, a parameter regulation and control module, a dynamic fusion module, a mode matching module and a feedback execution module. The environment acquisition module acquires temperature and humidity data and sets a monitoring interval; the state analysis module divides coating detection nodes and generates feature vectors; the parameter regulation and control module is used for separating influence factors, establishing control rules and acquiring process parameters; the dynamic fusion module identifies the equipment state, performs dynamic compensation and calculates the parameter difference degree; the mode matching module deduces an optimal curing threshold value and generates a deviation sequence; and the feedback execution module analyzes the deviation sequence and generates an adjustment instruction. The system realizes real-time monitoring and accurate regulation and control of the process of spraying polyurethane on the refrigeration house, improves the quality stability of the coating and the construction efficiency, is suitable for refrigeration house construction and maintenance scenes, and has the advantages of high environmental adaptability, accurate parameter regulation and control and the like.

The invention relates to the technical field of cold storage door control, and discloses a cold storage door opening and closing control method which comprises the following steps: acquiring multi-mode sensing information related to operation of a cold storage door system; driving a digital twinborn model based on the multi-mode sensing information, and analyzing the current state and predicting the future state of the cold storage door system by using the digital twinborn model; based on the multi-mode sensing information and the analysis and prediction result of the digital twinborn model, a deep reinforcement learning algorithm is adopted to generate a cooperative control instruction for the cold storage door opening and closing motion and the operation of at least one energy-saving device; and executing the cooperative control instruction. Energy flow is accurately simulated and predicted by using a high-fidelity digital twinborn model, and the actual traffic demand is accurately judged in combination with multi-modal perception, so that a deep reinforcement learning agent can generate a cooperative control instruction with the lowest comprehensive energy consumption as a target, and active intelligent energy saving is realized.

The invention relates to the technical field of electric power intelligent judgment, in particular to an AI-based intelligent electric energy meter fault diagnosis system, which comprises an operation data acquisition module, a jump correlation judgment module, an operation deviation judgment module, a current waveform diagnosis module and an abnormity alarm module. According to the invention, through synchronous acquisition of the current data and the operation data of the refrigeration storage, whether the current jump is related to the gating action is judged, and the refrigeration performance abnormity of the refrigeration storage and the fault type of the intelligent electric meter are effectively identified by further combining multiple cross validation of baseline energy consumption and temperature change; an ideal current waveform is constructed through an AI algorithm and is compared with an actually measured waveform, so that intelligent judgment and classification of fault types are realized; meanwhile, the diagnosis result is linked with the operation and maintenance system, the response efficiency is improved, and the method is particularly suitable for scenes with high requirements on the stability of the electric meter, such as cold chain storage, and has good practical value and popularization prospect.

The invention relates to the technical field of forklift control, and discloses a refrigeration house unmanned forklift anti-skid control method and system based on multi-sensor fusion, and the method comprises the steps: synchronously collecting wheel angular velocity, vehicle body inertia data, motor current, vibration and acoustic signals through a multi-mode sensor, and carrying out the time alignment and feature extraction; inputting a time-space diagram neural network to estimate the friction coefficient and the optimal slip rate of each wheel in real time; and in combination with model predictive control, four-wheel independent torque distribution is optimized in a rolling manner under the condition that physical constraints are met, so that high-precision tracking and dynamic stability are realized. The system comprises a data acquisition module, a data processing module, a friction estimation module, a torque distribution module and an execution module. The attachment change can be sensed in advance, and the safety, efficiency and operation precision of the unmanned forklift in the wet and slippery refrigeration house environment are improved.

The invention discloses a server liquid cooling cabinet group heat dissipation system with phase change energy storage, which comprises two linear array type server liquid cooling cabinet groups, two cooling capacity distribution units, two heat pipe air conditioner all-in-one machines, a multi-channel cold liquid distributor, a multi-channel hot liquid backflow device and the like, the all-in-one machine comprises a heat pipe natural cold source refrigerating loop and a compressor mechanical refrigerating loop, the two refrigerating loops independently or jointly provide an outdoor cold source, heat of all the liquid cooling cabinets is transmitted to the all-in-one machine in the cold capacity distribution unit, and therefore the heat is transmitted out of the machine room. A phase change energy storage flow channel is preferably arranged on the primary side of the intermediate heat exchanger in parallel, cold storage and buffering are achieved by switching a channel, a cold storage and cold release intelligent control strategy based on a lag temperature difference threshold value is constructed, a main cold source linkage and cold source switching smooth transition mechanism is achieved, the thermal stability, operation continuity and response capacity of the system are improved, and the system reliability is improved. The liquid cooling heat dissipation device is suitable for data center liquid cooling heat dissipation scenes with high heat density, high energy efficiency and high reliability requirements.

The invention discloses a pressure storage and heat storage coupled regenerative heat pump power storage system and a regulation and control method thereof. The system is composed of an electric-power generation integrated unit, an energy storage compression and energy release expansion integrated unit, an energy storage expansion and energy release compression integrated unit, a high-temperature heat exchanger, a backheating heat exchanger, a cold energy absorption heat exchanger, a heat storage and cold storage storage tank, a high-pressure gas storage tank and the like. And an energy storage / energy release loop, a heat storage / heat release loop, a cold storage / cold release loop and a pressure heat coupling loop are formed by connecting pipelines. In the energy storage mode, the compressor unit is driven by electric energy to conduct multi-stage compression, and compression heat and expansion cold are stored in the high-temperature storage tank and the low-temperature storage tank correspondingly. In the energy release mode, the heat storage medium and the cold storage medium are sequentially released to supply heat or cold to the circulating working medium, and the expansion unit is driven to drive the generator to generate electricity. According to the method, bidirectional operation of energy storage and energy release is achieved through valve switching and circulation control, and power output and load change are adjusted within a second level through a pressure-heat coupling mechanism.

The invention discloses an air conditioner resource allocation method and system based on a cold accumulation prediction algorithm, and relates to the field of air conditioner cold accumulation, and the method comprises the steps: collecting historical load operation data of an air conditioner, analyzing the historical load operation data through employing a grey relational analysis algorithm, and constructing a cold load prediction model in combination with the cold accumulation prediction algorithm; training the cold load prediction model by using a back propagation neural network algorithm, inputting load operation data collected in real time into the trained cold load prediction model, and outputting a cold load prediction result; and in combination with the cooling load prediction result and the electricity price information, an air conditioner resource allocation strategy is formulated, and a model prediction control algorithm is used for optimizing the allocation strategy. Through integration of the load prediction technology and the real-time electricity price information, the cold load demand of the whole day can be accurately predicted, energy waste is reduced, the energy utilization efficiency is improved, the dynamic electricity price market can be responded, and economic maximization is achieved.

The invention relates to the technical field of intelligent control of refrigeration equipment, in particular to an artificial intelligence-based screw compressor running state control system and method, which comprises a signal acquisition unit, a disturbance identification unit and a compressor control unit, the signal acquisition unit acquires a refrigeration house door opening and closing state time sequence signal and three-dimensional temperature field change data, the disturbance identification unit synchronously locks the door opening moment through a timestamp, divides a core influence area and a stable conduction area, analyzes the correlation between the temperature change rate and the door opening angle and the temperature fluctuation amplitude, and determines the temperature change rate of the door opening angle. And the door opening disturbance or equipment abnormity identification factor is output, and the compressor control unit executes differential regulation according to the door opening disturbance or equipment abnormity identification factor, so that the problems of disturbance misjudgment and regulation rigidity in traditional control are solved, and the operation stability and energy consumption control precision of the compressor are improved.

The invention discloses a cold storage temperature optimization control system and method for a chilled water storage air conditioning system, and relates to the technical field of chilled water storage air conditioning management.The method comprises the steps that 1, a plurality of operation parameters in the system operation process are collected; performing time synchronization and abnormal value elimination on the operation parameters to form a dynamic operation data set; and 2, judging the current hydraulic circulation state based on the dynamic operation data set, and outputting a circulation deviation signal when any index of the total flow of the system, the flow distribution of each branch or the temperature difference change rate of the supplied water and the returned water exceeds a set corresponding threshold value. By constructing the dynamic operation data set and monitoring key parameters such as the system temperature, the flow and the water pump operation state in real time, a unified multi-dimensional data basis is established, support is provided for follow-up operation state recognition and control strategy execution, and the real-time performance and accuracy of control are remarkably improved.

The invention provides a big data information processing method and system based on deep learning. According to the method, an energy distribution model is generated by combining a building information model with infrared thermal imaging data, and a dynamic thermal balance equation set is constructed according to the model so as to generate three-dimensional temperature field reconstruction data. Then, thermal resistance parameters in the energy distribution model, heat flow abnormal area coordinates in the three-dimensional temperature field reconstruction data and air conditioning unit current data are analyzed through a deep learning algorithm, and space-time coupling characteristics of equipment power consumption and thermal environment parameters are extracted; then, a priority regulation and control chain of the temperature control equipment is formulated, and multi-stage linkage rules of the fresh air exchange rate, illumination dimming and cold release of the cold storage tank are covered; finally, the chilled water pump phase difference, the air conditioner group operation mode and the emergency lighting power limiting value are dynamically adjusted, and power load stabilization is achieved. According to the technical scheme provided by the invention, the data information processing efficiency and stability of the large building can be improved.

The invention discloses a novel energy storage vehicle-mounted refrigerator and a control method, and relates to the technical field of refrigeration. The device comprises a box body, a novel energy storage heat exchange system and a control system, the novel energy storage heat exchange system comprises an energy storage body containing a cold storage medium; the cooling channel penetrates through the air duct system of the energy storage body; the heat exchange part is communicated with the vehicle-mounted refrigerating system and comprises a first heat exchange structure in contact with the cold storage medium; and the air guide part drives air to flow through the cooling channel. The first heat exchange structure is provided with a channel and / or a heat exchange piece used for circulating a refrigerant of the vehicle-mounted refrigerating system, and the first heat exchange structure is used for efficiently transmitting the cooling capacity of the refrigerant of the vehicle-mounted refrigerating system to the cold storage medium and / or transmitting the cooling capacity to air through the wall of the cooling channel. Optionally, a second heat exchange structure is arranged in the cooling channel to further strengthen heat exchange of the air. By optimizing the heat exchange structure, the efficiency of refrigerating and cold accumulation by using the vehicle-mounted refrigerating system is improved.

The invention provides an intelligent control method and system for a refrigeration house, and relates to the field of control. A refrigeration house space thermodynamic diagram model is constructed based on temperature measuring points, and a historical temperature sequence, a house door opening and closing state sequence, cargo warehouse-in and warehouse-out records and external environment parameters are obtained; predicting a temperature change track of each node in a future control time domain by using a space-time diagram convolutional network; establishing an equipment health state evaluation model based on a hidden Markov model, evaluating the health state of each refrigeration compressor unit and quantifying the health state into an equipment health index; and solving the rolling optimization objective function in the control time domain to obtain an optimal start-stop time sequence and operation power combination instruction of each refrigeration compressor unit and auxiliary equipment, and issuing the combination instruction to a corresponding field controller for execution. The temperature change of each area in the refrigeration house can be accurately predicted, the operation load can be reasonably distributed according to the health condition of the unit, the service life of equipment is effectively prolonged, and the sudden failure risk and the maintenance cost of the whole life cycle are reduced.

The invention relates to the technical field of cold storage equipment, in particular to intelligent regulation and control phase change cold storage equipment, an energy-saving refrigeration house and an intelligent regulation and control method of the energy-saving refrigeration house. The cold storage equipment comprises a plurality of phase change cold storage modules and an intelligent adjusting module, the phase change cold storage modules are all arranged at the top of the refrigeration house, the multiple phase change cold storage modules are divided into the fixed phase change cold storage modules and the movable phase change cold storage modules, and the intelligent adjusting module comprises a processor, a temperature sensing module and a driving mechanism. The driving mechanism is used for driving the movable phase change cold storage module to move up and down in the vertical direction. The energy-saving refrigeration house comprises a refrigerating unit, a goods shelf and the intelligent regulation and control phase change cold storage equipment. On the basis of an existing fixed PCM technology, position adjustability and intelligent feedback serve as the core, in the night cold charging stage, the phase change cold storage module descends to the optimal cold charging position according to a feedback signal of a temperature probe, the cold charging speed of the phase change cold storage module is increased, and efficient and intelligent operation of a cold storage system of the refrigeration house is ensured.

The invention discloses an energy storage and release double-closed cycle carbon dioxide electric heating energy storage system and an energy storage method, and belongs to the technical field of energy storage. The energy storage system comprises an energy storage closed circulation system, an energy release closed circulation system, a heat storage system and a cold storage system; the energy storage closed circulation system and the energy release closed circulation system share the same set of heat exchanger A and heat exchanger B which are connected in series, and the flowing directions of carbon dioxide working media in the heat exchanger A and the heat exchanger B are opposite to the flowing directions of media in the heat storage system and the cold storage system; the heat storage system exchanges energy with a carbon dioxide working medium in the energy storage closed circulation system through a heat exchanger A and a heat exchanger B; the heat storage system exchanges energy with the carbon dioxide working medium in the energy release closed circulation system through the heat exchanger A and the heat exchanger B. The energy storage system can meet the energy storage construction requirements under diversified scenes such as the power supply side, the power grid side and the user side. The method can adapt to energy storage construction requirements in diversified scenes such as a power supply side, a power grid side and a user side.

According to the data center evaporation cold total heat recovery double-energy-storage air conditioning system and the control method, the obvious energy efficiency improvement and economic optimization effects are achieved, the future server heat load, environment parameters and electricity price changes are accurately pre-judged through a composite prediction model of the central control module, and the real-time charge state of the double-energy-storage module is combined, so that the energy efficiency is improved. A collaborative operation instruction with the optimal cost is generated; by means of deep coupling of the evaporative cooling module and the total heat recovery module, a natural cold source is utilized to the maximum extent, and the running time of a conventional refrigeration module is shortened; through cooperative scheduling of the cold energy storage unit and the heat storage unit, efficient cold / heat storage is achieved in the electricity price valley value period, stored energy is released preferentially in the peak value period, and frequent starting and stopping of equipment are avoided; and on the basis of the multi-dimensional constraint optimization decision model, the total operation cost is minimized on the premise that the system meets the safety temperature and humidity requirements of the data center.

The invention discloses a dynamic energy-saving control method and system for a cold storage based on deep learning and multi-source data fusion, and relates to the technical field of cold storage energy-saving control, and the method comprises the steps: constructing a thermal field sensing network through a fixed sparse sensor array and a mobile thermal field scanning robot, and collecting temperature, humidity and thermal imaging data; reconstructing a three-dimensional thermal pixel field through registration, interpolation and other processing, and performing space-time alignment on the three-dimensional thermal pixel field, equipment parameters and inventory thermal physical properties; constructing digital twinborn deduction thermal field evolution based on a physical information neural network, and recognizing a high-temperature hot spot and a low-temperature safe area in combination with a space-time diagram attention network; the method comprises the following steps: by taking power consumption cost minimization and over-temperature risk controllability as targets, solving an optimal control strategy containing tuyere parameters and compressor frequency by using a multi-agent depth deterministic strategy gradient algorithm, driving equipment to execute targeted cold supply, and enabling a system to comprise a thermal field sensing layer, a data fusion layer, a digital twinning and prediction layer, a decision optimization layer and an execution layer. And accurate temperature control and energy conservation are realized.

The invention discloses a linkage control system and method for cold energy storage and release in an energy storage low-temperature interval, belongs to the technical field of energy storage system temperature control, and aims to solve the problems that traditional energy storage cold energy regulation is lagged, cold energy waste is serious, and dynamic changes of working conditions are difficult to adapt. According to the system and method, cold release judgment is triggered based on the environment temperature and the temperature of an energy storage module, a cold release interval is defined by predicting the environment temperature and the temperature of the energy storage module in a fitting mode, a temperature prediction curve is dynamically corrected in combination with real-time working conditions, cold release subintervals are divided, and a cold release control instruction is generated; and meanwhile, the temperature of the energy storage module is monitored in real time to correct the cooling capacity release control instruction, and a cooling capacity recovery instruction is generated by monitoring the temperature of the cooling liquid. Accurate steady-state control over the temperature of the energy storage module and efficient circulation of the cooling capacity are achieved, and the operation economical efficiency and safety of the energy storage system are remarkably improved.

The invention relates to a liquid air energy storage and terrestrial heat coordinated underground space air regulation and control system and method. Comprising a first-stage compressor, a second-stage compressor, a third-stage compressor, an expansion refrigerator, a first-stage compression heat exchanger, a second-stage compression heat exchanger, a third-stage compression heat exchanger, a cold box, a separator, a liquid air storage tank, a cryogenic pump, an evaporator, a cold storage circulating pump, a cold storage box, a compression heat exchange circulating pump, a compression heat storage box, a first heater, a second heater and a third heater. The system comprises a first air expander, a second air expander, a third air expander and a generator. The regeneration heater is used for guiding the compression heat generated by the compressor into the regeneration heater for regeneration and / or guiding the geothermal energy output by the geothermal energy output end into the regeneration heater for regeneration; the rotary wheel dehumidification device is used for performing cryogenic drying on the wet air; the fresh air processing unit is composed of a fresh air filter, a regeneration fan, a regeneration filter and an air supply fan.

The invention provides a distributed cold chain load and photovoltaic consumption multi-target cooperative regulation and control method and system, and the method comprises the steps: inputting the operation data of a cold chain load into a pre-constructed cold chain load time-space characteristic model, obtaining the fluctuation of the cold chain load, and carrying out the optimization with the minimization of the fluctuation of the cold chain load as a target, and obtaining a cold storage time window; the method comprises the following steps: inputting current operation data of cold chain-energy storage-photovoltaic into a pre-constructed cold chain-energy storage-photovoltaic multi-target aggregation regulation and control model, taking a cold storage time window as a constraint boundary, and adopting a third-generation non-dominated sorting genetic algorithm and a distributed alternating direction multiplier method for solving; a multi-target cooperative regulation and control result with the maximization of the photovoltaic consumption rate, the minimization of the operation cost and the optimization of the fresh-keeping quality of the agricultural products as targets is obtained; the economical efficiency, the reliability and the environmental protection property of the distributed energy system are remarkably improved, and an efficient, reliable and low-cost cooperative regulation and control scheme is provided for the cold chain energy system under the permeation of high-proportion renewable energy sources.

The invention provides a refrigeration house multi-fan intelligent cooperative defrosting control system and method. The refrigeration house multi-fan intelligent cooperative defrosting control system comprises an air-cooled condenser, a throttling valve, a compressor, a refrigerating chamber, a bypass valve, an air speed sensor, a temperature and humidity sensor, a temperature sensor, a pressure sensor, a flow meter, an air cooler tail end evaporator, data acquisition equipment, a central processing unit and a control output port. According to the cold storage scene that hot gas bypass defrosting is adopted, and one refrigerating unit is provided with a plurality of air coolers, the ratio (COP) of the accumulated refrigerating capacity to the total energy consumption in the operation period of each air cooler is calculated. And a comprehensive performance coefficient dynamic model of the air cooler is constructed by combining the temperature difference between the air supply and the air return, so that optimal energy efficiency of the air cooler and multi-fan defrosting control are realized. Compared with the prior art, the defrosting control logic is reconstructed from the perspective of the performance coefficient of the air cooler, the frosting condition of the surface of the evaporator at the tail end of the multiple fans of the refrigeration house can be accurately judged, it is ensured that the unit maintains high efficiency in the operation process, and development of the efficient and energy-saving control technology of a refrigeration house refrigerating system is facilitated.

The invention provides a penaeus vannamei quality prediction and grade evaluation method and system, and belongs to the field of penaeus vannamei cold-chain transportation process quality prediction, and the method comprises the steps: S1, constructing a penaeus vannamei data set, and carrying out the dynamic time-varying coupling correlation graph generation, convection-diffusion cooperative information propagation, multi-task joint optimization and end-to-end MLP prediction to obtain a penaeus vannamei data set; obtaining a prediction result of the quality of the penaeus vannamei; s2, splicing is performed according to the prediction result and the actual quality data, and a feature matrix is constructed; clustering the feature matrix by using a rule fusion K-means + + clustering method to obtain an optimal clustering center set; and S3, based on the prediction result and the clustering center set, carrying out dynamic prediction and evaluation on the quality of the penaeus vannamei in the refrigeration state in a period of time in the future. According to the invention, an intelligent solution is provided for quality monitoring in cold-chain logistics, and economic loss caused by quality deterioration is significantly reduced.

The utility model provides a liquid carbon dioxide energy storage refrigerating system. The liquid carbon dioxide energy storage refrigerating system comprises an energy storage system, a refrigerating system and a heat circulation system. The energy storage system comprises a low-pressure liquid storage tank, a first throttling pressure reducing valve, a first heat exchanger, a compressor, a second heat exchanger and a high-pressure liquid storage tank which are sequentially connected in a sealed mode. The refrigerating system comprises a high-pressure liquid storage tank, a second throttling pressure reducing valve, a third heat exchanger, a fourth heat exchanger and a low-pressure liquid storage tank which are sequentially connected in a sealed mode. The heat circulation system comprises a cold storage tank, the cold storage tank is coupled with the first heat exchanger through a circulation pipeline, and the cold storage tank is coupled with the fourth heat exchanger through a circulation pipeline. In the low peak period of electricity utilization, the electric energy is stored in the form of high-pressure liquid carbon dioxide. And the liquid carbon dioxide is gasified and cooled through pressure reduction of the second throttling pressure reducing valve so as to provide cold energy. And meanwhile, cold energy generated in the refrigeration process can be stored through the heat circulation system and used for cooling carbon dioxide in the energy storage process.

The invention provides an intelligent transportation device for fish fry keep-alive transportation and a water treatment process, and the device comprises a heat preservation box body, an environment sensor, a fish fry state indirect monitoring sensor, and a flexible buffer type self-adaptive isolation device, an intelligent environment regulation and control module and a dynamic buffer device which are detachably connected with the heat preservation box body, the intelligent environment regulation and control module comprises a water temperature regulation module, a water quality regulation module and a gradient environment adaptation module, the gradient environment adaptation module automatically regulates values of all parameters according to a preset environment parameter change curve, and meanwhile, the change rate and the water treatment process of the environment parameters are regulated in real time according to data fed back by the water quality regulation module; and the dynamic buffer device dynamically adjusts the damping coefficient of the buffer unit according to the pressure and acceleration data in the cold storage transportation device. The device can accurately match the optimal fish fry transportation environment with the adaptive rhythm of the marine ranching environment, greatly reduces the stress damage of the fish fry in the transportation process, and improves the adaptive capacity of the fish fry to the target environment after transportation.

The invention discloses a solid-phase and liquid-phase double-coupled liquid air energy storage and cold storage system. Comprising an air liquefaction storage module used for cooling, liquefying and storing compressed air, a liquid phase cold storage / release module used for storing and releasing high-quality cooling capacity of liquid air, and a solid phase cold storage / release module used for storing and releasing medium-low-quality cooling capacity of the liquid air. The liquid phase cold storage / release module and the solid phase cold storage / release module are connected to the rear end of the air liquefaction storage module in series, and heat exchange is conducted between the liquid phase cold storage / release module and the air liquefaction storage module and between the solid phase cold storage / release module and the air liquefaction storage module. And an outlet pipeline of the solid-phase cold storage / release module is connected to the heater. High-quality cooling capacity in the power generation process of the liquid air energy storage system is stored in a liquid-phase cold storage mode, medium-low-quality cooling capacity in the power generation process of the liquid air energy storage system is stored in a solid-phase cold storage mode, the defect of large exergy loss caused by solid-phase cold storage is overcome, and the cold storage efficiency of the energy storage system is improved.

The invention discloses a recombinant C factor protein protective agent and application thereof. The recombinant factor C protein protective agent is prepared from the following components according to the final concentration of each component: 0.05 to 0.2 percent (w / v) of ProClin 300, 100 to 300 mM of sodium chloride, 1 to 10 mg / mL of bovine serum albumin, 5 to 20 percent (w / v) of trehalose, 10 to 50 percent (v / v) of glycerol, 0.1 to 0.5 percent (w / v) of tween-20 and 0.1 to 1 mM of ethylene glycol diethyl ether diamine tetraacetic acid with the pH value of 8.0. The invention also discloses an application of the recombinant factor C protein protective agent in refrigerated preservation of recombinant factor C protein. After the recombinant C-factor protein protective agent and the recombinant C-factor protein are mixed, the recombinant C-factor protein is prevented from being influenced by conditions such as aggregation, oxidation, freeze thawing and metal ion dependent inactivation, the stability of the recombinant C-factor protein in refrigeration storage is improved, and the activity retention rate of the recombinant C-factor protein after refrigeration storage for 12 months is greater than or equal to 90%; and the accuracy and sensitivity of endotoxin detection are maintained.

The invention relates to the technical field of refrigeration houses for storage, and provides a refrigeration house for fruit storage and a storage method.The refrigeration house for fruit storage comprises a refrigeration house body, a plurality of independent refrigeration house box bodies are arranged in the refrigeration house body, refrigeration equipment is installed in the refrigeration house body, and the air inlet end of the refrigeration equipment communicates with the outside through a pipeline; the output end of the refrigeration equipment communicates with a ventilation pipeline, the multiple storage racks are arranged in each refrigeration storage box, the ventilation box bodies are fixedly installed in each storage rack, each ventilation box body is provided with a ventilation structure, the air uniformizing assembly is installed at the top of each refrigeration storage box body, and the air uniformizing assembly is connected with the storage racks. By means of the technical scheme, the technical problems that in the related technology, when fruits stored in a refrigeration house are taken out, the phenomenon of local cold damage is likely to occur in the temperature returning process, temperature returning is difficult to conduct on part of fruits in batches according to the requirements, and consequently high-value fruits are difficult to supply according to the requirements in a graded mode are solved.

The utility model discloses a refrigeration house defrosting system which comprises a refrigeration house body and a dehumidification device, the dehumidification device is provided with a dehumidification rotating wheel, the dehumidification rotating wheel is provided with a processing area and a regeneration area, and the dehumidification device reduces internal moisture of the refrigeration house body through the dehumidification rotating wheel and removes internal frost of the refrigeration house body. Wherein the dehumidification device is provided with a treatment air inlet and a treatment air outlet, the treatment air inlet can extract gas to be treated from the interior of the refrigeration house body, and the treatment air outlet can convey dry gas adsorbed and dehumidified by the dehumidification rotating wheel to the refrigeration house body again. According to the refrigeration house defrosting system, no condensate water is generated in the whole dehumidification process of the refrigeration house, water does not need to be drained in the refrigeration house, the problem that cold water generated due to the fact that electric defrosting, hot fluorine defrosting and other defrosting modes are used is inconvenient to drain is solved, the residual cold water in the refrigeration house is not completely drained and can be condensed again, and the dehumidification and defrosting effects of the refrigeration house are not thorough; no obvious temperature fluctuation exists in the refrigeration house in the operation process of the refrigeration house defrosting system.