1116 results about "Chilled water" patented technology

The invention relates to the technical field of air conditioner chilled water control, in particular to an air conditioner chilled water control method and system based on deep learning, and the method comprises the following steps: collecting states of an air conditioner water chilling unit, including water pump frequency and valve opening feedback, and pipe network water supply temperature, return water temperature, flow and differential pressure operation readings; according to the method, the state parameters of the water chilling unit are dynamically collected, the system operation state feature set is constructed, real-time fusion and standardization processing of multi-source heterogeneous data are achieved, the problem of time sequence dislocation caused by sensor sampling frequency differences is solved, the heat load change key input quantity is recognized based on the feature set, and the system operation state feature set is established. And the performance attenuation trend of the water pump is accurately pre-judged in combination with prediction calculation, and extra energy consumption caused by lagging adjustment is reduced. A layered optimization framework with total energy consumption minimization as a target is introduced, water supply temperature, pressure difference setting and unit operation combination are decoupled into independent optimization sub-problems, and invalid work of a water pump is reduced on the premise that the tail end heat requirement is met.

The invention discloses an integrated cold station intelligent control system based on multi-modal data fusion, and relates to the technical field of data fusion, an intelligent decision and optimization module adopts reinforcement learning and model prediction control based on fused data to realize dynamic optimization of start and stop of a water chilling unit, chilled water temperature setting and water pump frequency adjustment; the fault detection and adaptive optimization module evaluates the data fusion accuracy by calculating an environment entropy value and cold station dynamic response delay time, and dynamically adjusts a control strategy based on a prediction deviation rate and the data fusion accuracy; the closed-loop feedback module analyzes and adjusts control parameters through operation data, intelligent control models between different cold stations are optimized through transfer learning, intelligent deployment of a new cold station is accelerated, and the generalization ability of the models is improved. More accurate, more energy-saving and more stable intelligent control of the cold station is realized, and the operation efficiency and reliability of the cold station system are improved.

The invention discloses a central air conditioner load self-adaptive regulation and control method based on artificial intelligence, which relates to the technical field of heating ventilation air conditioner automatic regulation and control, and comprises the steps of edge end data preprocessing, deep learning load prediction and self-adaptive updating, intelligent control strategy, closed-loop feedback and continuous optimization and fault diagnosis and remote operation and maintenance. Through edge end denoising and feature labeling, the data transmission pressure is remarkably reduced, and the response speed is increased; the deep learning model is combined with online iteration and reinforcement learning, key parameters such as chilled water temperature and water pump frequency are accurately regulated and controlled, and energy consumption and comfort are considered; according to the method, prediction errors and equipment states are monitored, a model and a control strategy are synchronously updated when abnormity is detected, fault early warning is triggered in combination with health assessment, energy consumption is effectively reduced, the service life of equipment is prolonged, and finally an efficient and stable self-adaptive regulation and control system capable of being operated and maintained online in a long period is constructed.

The invention relates to a chilled water system of a central air conditioner and an energy-saving optimization control method. The energy-saving optimization method comprises the following steps: S1, establishing an energy consumption model of the chilled water system of the central air conditioner; s2, firstly performing correlation analysis on the selected cooling load influence factors by adopting a grey correlation analysis method, screening out strong correlation influence factors, and establishing a central air conditioner cooling load prediction model based on PSO-LSSVM (Particle Swarm Optimization-Least Square Support Vector Machine); s3, optimizing the energy consumption model parameters of the chilled water system of the central air conditioner while predicting the cooling load value of the next point by using an improved white whale algorithm, and enabling the output result of the energy consumption model to reach the minimum value; the system comprises an energy consumption modeling module, a cooling load prediction module and an energy-saving optimization module. According to the method, the energy consumption model and the cooling load prediction model are established, the cooling load value of the next point is predicted, parameter optimization is performed, and an optimization structure is output; the energy consumption model and the cold load prediction model can be updated periodically, and the problem of performance reduction caused by long-time equipment operation is avoided.

The invention provides a distributed intelligent cooperative energy-saving control method and device for an industrial air conditioner, electronic equipment and a computer readable storage medium, and is applied to the field of data processing application. The method comprises the following steps: acquiring industrial air conditioner operation related data including environment parameters and equipment state data; an intelligent cooperative control mechanism is constructed based on multi-device cooperation and hierarchical adjustment requirements, and the intelligent cooperative control mechanism comprises a multi-device linkage strategy for dynamically distributing refrigeration resources according to regional cooling and heating loads and a hierarchical adjustment algorithm of a chilled water system and a cooling system, and a control framework for achieving global optimization is formed; processing the environment parameters and the equipment state data to generate a dynamic control strategy; generating target energy-saving control information based on the data analysis result and the dynamic control strategy; and all operation data and control effects generated based on the target energy-saving control information are integrated, a high-energy-consumption link optimization scheme is generated, energy consumption data credible tracing is achieved, and the distributed air conditioning system is aggregated to participate in power grid frequency modulation.

The invention relates to the technical field of industrial control, and discloses an energy-saving air conditioner intelligent control system which comprises an edge computing node, a dynamic load prediction module, a self-adaptive control module, an energy consumption optimization evaluation module and a fault diagnosis module. A data acquisition module, a real-time control module and a communication interface are integrated; based on the historical environment data and the air conditioner operation log, a long-short-term memory network model is adopted to predict the expected load demand in 2-4 hours in the future; dynamically adjusting the operation number of chilled water units, the frequency conversion frequency of water pumps and the opening degree of fresh air valves according to the expected load requirement; the unit cold energy consumption of a single air conditioner is calculated in real time, and a global optimization instruction is generated in combination with a time-of-use electricity price strategy; motor current harmonic characteristics are collected through the edge calculation nodes, the abnormity of the air conditioner is recognized, graded response is conducted, the intelligent control efficiency of the energy-saving air conditioner is improved, and the overall energy consumption cost of the air conditioner is reduced.

The invention provides a high-efficiency control method and system for a central air conditioner refrigeration machine room, and relates to the technical field of automatic control, and the method comprises the steps: 1, obtaining chilled water supply and return water temperature difference and flow data, and calculating the dynamic cold load demand of a building in combination with the personnel distribution thermal imaging data of each floor; and 2, on the basis of the dynamic cooling load requirement, a dynamic adjustment model for the number of running water chilling units is built, matching degree calculation is conducted on the actual cooling load value and the single refrigerating capacity of the water chilling units through a fuzzy PID control algorithm, and a final unit running combination scheme is generated. By calculating the cooling load requirement, dynamically adjusting the operation parameters of the water chilling unit, the chilled water pump and the cooling tower and balancing the equipment operation time, the system energy efficiency is effectively improved, the energy consumption and the operation and maintenance cost are reduced, and stable operation of the refrigerating system is guaranteed.

The invention discloses an all-air air conditioner regulation and control method based on indoor number of people and meteorological parameter changes, and belongs to the field of air conditioner control. The method comprises the following steps that meteorological parameters of an area where a building is located are obtained, building envelope parameters, indoor equipment power and the number of real-time personnel are determined, the needed fresh air volume and the load of an air conditioning unit are calculated, the air supply volume and the air supply temperature are determined, and the air supply volume is fed into an air conditioning space for airflow organization simulation. A PMV value is calculated according to the simulation result, when the PMV meets the requirement, regulation and control parameters of a fresh air valve and an air return valve of the air supply system are output, and the chilled water amount needed by the air volume and the water valve opening degree are calculated; and when the PMV does not meet the requirement, the opening degree of the air return valve is adjusted, and the model is re-established for iterative calculation until the PMV reaches a target value. Based on an air conditioning unit control mechanism, building dynamic load changes are combined, the PMV is used as an evaluation index, an air valve and a water valve are adjusted, the indoor design environment requirement is met, and support is provided for optimization design of a building air conditioner air and water system.

The invention discloses an energy-saving economic dispatching method for a data center energy system based on a prediction model. The method comprises the following steps: establishing a digital twinborn model of the data center energy system; dividing the data center into a plurality of energy consumption partitions, and installing a temperature acquisition device in each energy consumption partition; after a cooling capacity demand prediction model of the data center under each time period partition is established, target combination parameters and target energy efficiency indexes PUE of the chilled water temperature and the air supply temperature of a refrigeration subsystem under each time period are obtained through calculation; establishing a data center energy efficiency index PUE prediction model, and establishing an upper-layer refrigeration subsystem optimization scheduling model by taking the minimum deviation between an energy efficiency index PUE prediction value and a target energy efficiency index PUE, the minimum deviation between actual combined parameters of chilled water temperature and air supply temperature and target combined parameters and the minimum cold capacity supply and demand deviation of each partition as targets; and establishing a lower-layer data center optimization scheduling model by taking the minimum power utilization operation cost of the system and the minimum load migration cost of the IT equipment as a target.

The invention discloses a machine room water-cooled air conditioner adaptive control method based on big data analysis, which relates to the technical field of adaptive regulation and control, is used for improving the problem of overlong response time caused by fixed thermal inertia, and comprises the following steps of: performing network deployment on distributed optical fiber sensing, screening environmental data in a water-cooled air conditioner adaptive system by utilizing a sliding time window algorithm, and determining the response time of the water-cooled air conditioner. Noise is suppressed, a thermal inertia compensation mechanism is entered, an LSTM neural network is constructed based on initial system thermal inertia to predict thermal disturbance of a plurality of subsequent control periods, and a space-time alignment compensation matrix is introduced to suppress harmonic oscillation in the thermal inertia compensation mechanism; the predicted thermal disturbance and the chilled water flow in the air conditioner are integrated, a double-closed-loop correction method is used for generating thermal compensation correction, gain switching is conducted on the double-closed-loop correction method, and synchronous alignment correction is conducted on asynchronously-collected data packets through a time sequence alignment engine; and setting a bending window and carrying out characterization fusion to judge an environment data acquisition point and an abnormal acquisition response rate thereof.

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 relates to an air conditioner temperature and humidity independent control system and method based on two-stage coil chilled water. On the basis of the existing chip plant temperature and humidity independent control based on a fresh air processing unit, a return air drying and cooling coil and a fan filtering unit, low-temperature chilled water outlet of a water chilling unit firstly passes through a fresh air re-cooling coil; return water obtained after the temperature of the fresh air re-cooling coil pipe rises serves as water supply of the fresh air pre-cooling coil pipe and the return air cooling dry coil pipe, so that two-stage coil pipe chilled water is formed, and the return water of the fresh air pre-cooling coil pipe and the return water of the return air cooling dry coil pipe are mixed and then serve as chilled water return water of the water chilling unit. By increasing the return water temperature of the water chilling unit, the average evaporation temperature of an evaporator of the water chilling unit is increased. A bypass is arranged between an inlet and an outlet of the return air cooling dry coil, and the air temperature in the plant is controlled by adjusting the bypass flow through an electric two-way adjusting valve and a PID controller. Compared with the prior art, the invention has the advantages of high unit energy efficiency ratio, low refrigeration energy consumption, simplified system and the like.

The invention relates to an air conditioner chilled water PID parameter optimization method based on an improved sparrow search algorithm. The method comprises the steps that population initialization, a discoverer updating formula and a follower updating formula in the sparrow search algorithm are improved; a return water temperature difference signal of the air conditioner chilled water system is detected and input to the improved sparrow search algorithm optimization PID controller, and the improved sparrow search algorithm dynamically adjusts the proportionality coefficient, the integral coefficient and the differential coefficient of the PID controller; and the improved sparrow search algorithm iteratively calculates an optimal parameter combination, and the PID controller performs optimal control of the chilled water system based on the optimal parameter combination. The improved sparrow search algorithm carries out population initialization by introducing a reverse learning strategy optimized by a refraction principle so as to enhance the diversity of an initial population; respectively introducing sine and cosine transform and a Cauchy variation mechanism in a position updating stage of the discoverer and the follower; and the PID controller dynamically adjusts Kp, Ki and Kd based on an improved algorithm so as to realize optimal parameter setting.

The invention discloses a medical water chilling unit internet-of-things edge control method, which comprises the steps of obtaining water chilling unit operation parameters, cooling tower operation parameters and environmental parameters of different types of areas of a hospital, and inputting the water chilling unit operation parameters, the cooling tower operation parameters and the environmental parameters of the different types of areas into a cooling load prediction model, future cooling load prediction values of different types of regions are obtained; inputting the running parameters of the water chilling unit, the running parameters of the cooling tower and the future cooling load predicted values of the different types of regions into a deep reinforcement learning model to obtain adjustment strategies of the water chilling unit and the cooling tower of the different types of regions; dynamically adjusting distribution paths and distribution priorities of cooling water and chilled water according to different types of regions, future cooling load predicted values and adjustment strategies of a water chilling unit and a cooling tower; and controlling the operation of the water chilling units and the cooling towers in the corresponding regions through the adjustment strategies of the water chilling units and the cooling towers in the different types of regions, the cooling water and chilled water region distribution paths and the distribution priorities thereof.

The invention discloses a heat allocation system based on a heat pump. The heat allocation system comprises a water tank; a water source heat pump; an air source heat pump; a cooling tower; a cooling water circulation system; a hot water circulation system; a chilled water circulation system; an exhaust heat recovery system; wherein the water tank, the water source heat pump, the air source heat pump, the cooling tower, the cooling water circulation system, the hot water circulation system, the chilled water circulation system and the exhaust heat recovery system are connected with one another to realize heat allocation, especially heat allocation of a coating pretreatment electrophoresis production line of a vehicle body or parts forming the vehicle body; according to the system, heat generated when the heat pump / refrigerating unit produces chilled water and / or heat taken away in exhaust air can be recycled and used for heating the heat using tail end. Therefore, the heat which is wasted originally can be fully utilized, the energy consumption is reduced, and the utilization efficiency of energy is improved.

The invention relates to a data center equipment type selection method based on electrical and heating ventilation load linkage, and belongs to the technical field of data center infrastructure design. The model selection method comprises the steps of setting basic data, obtaining the number of machine rooms and the number of IT devices in a single machine room, obtaining the total power of the IT devices, setting an energy efficiency index set value, obtaining the project power consumption scale, obtaining the total cooling load, selecting models of air conditioners at the tail ends of the machine rooms and substations, selecting models of water chilling units, selecting models of heat exchangers, selecting models of cooling water pumps and chilled water pumps and selecting models of cooling towers. And obtaining the total power of the air conditioner, obtaining an energy efficiency index accounting value, and carrying out PUE verification. According to the method, through closed-loop iteration of electrical load-heating and ventilation load-PUE, model selection and quantity selection of all key equipment are completed at a time; professional splitting, repeated adjustment and modification and capacity redundancy caused by traditional serial design are avoided, the design period is remarkably shortened, and initial investment is reduced.

The invention relates to an urban rail transit station ventilation and air conditioning system cooperative control method, device and equipment based on dynamic energy efficiency optimization and a medium. Constructing an energy efficiency model of the ventilation and air conditioning system by combining the energy efficiency curved surface characteristics of the water chilling unit and the cubic law power consumption characteristics of the frequency conversion equipment; an intelligent optimization algorithm is adopted, a dynamic scaling temperature feasible domain of chilled water of a water chilling unit and a frequency interaction limitation domain of frequency conversion equipment are constructed, the feasibility of a temperature set value is kept, meanwhile, coupling constraints in the frequency conversion equipment are decoupled, and an optimal parameter combination is solved; and the optimal parameter combination is issued to an execution layer, the actual energy efficiency ratio deviation of the system is monitored in real time, and energy efficiency model parameter re-calibration or iterative optimization is triggered according to a deviation threshold. Therefore, the overall energy efficiency of the ventilation air conditioning system is stably improved, and efficient operation under the dynamic working condition is achieved.

The invention discloses a chilled water system operation control method, a chilled water system and a storage medium. Relates to the technical field of refrigeration equipment, and the method comprises the steps that according to obtained operation parameters of a chilled water system, predicted chilled water flow is obtained, the predicted chilled water flow corresponds to a preset time period, and the preset time period is a preset time period after the current time; on the basis of the predicted chilled water flow and system configuration information, initial operation parameters in the preset time period are determined; and according to the operation initial parameter and the predicted chilled water flow, an operation target parameter is determined, and the chilled water system is controlled to operate by adopting the operation target parameter in the preset time period. And fine control of the chilled water system in the preset time period is realized. On the premise of meeting system operation requirements, energy consumption is reduced, operation efficiency is improved, and meanwhile system instability caused by parameter adjustment lag is reduced.

The utility model provides a heat exchanger assembly and an air conditioner, the heat exchanger assembly comprises an evaporator assembly and a surface air cooler assembly, refrigerant is introduced into a heat exchange tube of the evaporator assembly, chilled water is introduced into a heat exchange tube of the surface air cooler assembly, and the evaporator assembly and the surface air cooler assembly are connected into a whole. The evaporator assembly is located at the upstream position of the surface air cooler assembly in the air flowing direction, when chilled water is mainly used for refrigeration, the surface air cooler assembly works, the evaporator assembly does not work, and air passes through the evaporator assembly to be not cooled and then passes through the surface air cooler assembly to be cooled. According to the utility model, the refrigeration effect is not worsened under the condition that the energy efficiency and the refrigeration performance are considered at the same time, and the required refrigeration effect is ensured.

The utility model discloses a system for producing hydrogen by electrolyzing water. The system comprises an alkali liquor electrolysis device, a gas-liquid separation device and an interlocking control device, the alkali liquor electrolysis device comprises an electrolytic bath and an alkali liquor circulating pump, the gas-liquid separation device comprises a gas-liquid separator, and the interlocking control device comprises an electromagnetic valve; the gas-liquid separation device further comprises a U-shaped pipe for separating gas and liquid by utilizing gravity and a jacketed pipe for separating gas and liquid by utilizing condensation; the U-shaped pipe is arranged between the electrolytic bath and the gas-liquid separator, and the alkali liquor self-flowing pipe is arranged between the low point of the U-shaped pipe and the alkali liquor circulating pump; the jacketed pipe is arranged between the U-shaped pipe and the gas-liquid separator, and an interlayer of the jacketed pipe is communicated with a chilled water pipeline. According to the water electrolysis hydrogen production system, the U-shaped pipe and the jacketed pipe are arranged, so that the gas-liquid separation efficiency of the water electrolysis hydrogen production system is improved, and the hydrogen production efficiency is improved; a washer and a cooler are removed, the whole equipment is simple, the occupied space is small, and the manufacturing cost is low; through regulation and control of the interlocking control device, the safety of the water electrolysis hydrogen production system is improved, and unattended operation can be achieved.

The utility model discloses a flue gas waste heat recovery system, and belongs to the field of heat energy recovery equipment. Comprising TEG equipment, a first heat exchanger, a generator, a condenser, a second heat exchanger, an absorber, an evaporator and a cold storage tower, the hot end inlet of the TEG equipment is connected with external high-temperature flue gas, and the flue gas sequentially passes through the first heat exchanger and the generator and then is discharged to the external environment or subsequent flue gas treatment equipment; refrigerant water is introduced into a cold end inlet of the TEG equipment, the refrigerant water is obtained by liquefying refrigeration steam generated by the generator in the condenser, and the refrigerant water discharged from a cold end outlet of the TEG equipment enters the absorber to be absorbed after being treated by the evaporator. A cooling water inlet of the first heat exchanger is connected with high-temperature cooling water, the high-temperature cooling water is obtained after medium-temperature cooling water from the absorber absorbs heat in the condenser, a cooling water outlet of the first heat exchanger is connected with the absorber, and the absorber is connected with the generator through the second heat exchanger; and the evaporator and the cold storage tower form chilled water circulation.

The invention provides a data center cascade refrigeration system control method and device, and the method comprises the steps: obtaining an outdoor wet bulb temperature to determine a first target temperature, obtaining an indoor return air temperature to determine a second target temperature, and calculating the temperature difference between the first target temperature and the second target temperature; the data center cascade refrigeration system is controlled to enter a first refrigeration mode, a second refrigeration mode or a third refrigeration mode according to preset conditions, and only the chilled water refrigeration system is started in the first refrigeration mode; in the second refrigeration mode, the chilled water refrigeration system and the evaporation cold and heat pipe refrigeration system are started at the same time; and in the third refrigeration mode, only the evaporation cold and heat pipe refrigeration system is started. In different modes, the system optimizes the refrigeration effect by adjusting the compressor frequency, the water pump frequency, the water supply valve opening, the fan frequency, the fluorine pump frequency, the expansion valve opening and other parameters, and the problems that in an existing refrigeration system in the prior art, the water side natural cooling time is short due to the fact that the temperature difference between the air side and the water side is inconsistent are solved. And more energy is consumed to meet the refrigeration requirement.

A manufacturing plant water-cooling air conditioner energy-saving control method based on load prediction comprises the steps that a heat load mechanism model of a water-cooling air conditioner system is constructed, and the heat load mechanism model comprises a wall heat transfer transient heat conduction model, a solar radiation heat model, a device heat dissipation heat model and a fresh air latent heat model; and establishing a thermal load maximum flow graph model. And establishing a refrigeration mechanism model of the water-cooling air conditioning system, wherein the refrigeration mechanism model comprises a water chilling unit model, a chilled water pipeline heat loss model, a cooling tower model, an air handling unit model and an air duct heat loss model. And establishing a refrigeration maximum flow graph model. And training the thermal load maximum flow graph model and the refrigeration maximum flow graph model through an attention mechanism to obtain a thermal load graph feature matrix and a refrigeration graph feature matrix. And according to the heat load diagram characteristic matrix and the refrigeration diagram characteristic matrix, current operation data of the water-cooling air conditioning system are predicted, and an energy-saving control strategy of the water-cooling air conditioning system is output.

The invention provides a multi-target control strategy optimization method for intelligent cold release scheduling of a chilled water storage system. The method comprises the following steps: acquiring chilled water storage system data; constructing a multi-input time sequence regression model to obtain a cold load prediction mean value and a standard deviation sequence; acquiring a corresponding electricity price per hour and a building cold and hot inertia coefficient sequence, and generating a weighted risk score value; constructing an optimization objective function with the lowest electricity price cost and the lowest risk to generate an optimal cold release strategy sequence; and executing the optimal cold release strategy sequence, deploying the optimal cold release strategy sequence into a real chilled water storage system, and performing boundary management and limited optimization fine tuning on the strategy according to the real-time state of the system in the operation process. According to the method, the problems of multi-link splitting, poor strategy robustness, execution disjunction and the like in the current cold and heat scheduling system are solved, and the method has good implementability and systematic innovation value.

The invention relates to the field of coal gasification chilled water, in particular to a coal gasification chilled water filtering system which comprises at least two filter bodies connected into a coal gasification chilled water system and arranged in parallel, and each filter body comprises a shell, a V-shaped sieve plate, a sieve plate flushing assembly and a shell flushing assembly. According to the coal gasification chilled water filtering system, on-line automatic dual cleaning of the filter body can be achieved, under the condition that normal operation of the filtering system is not affected, high-pressure grey water of a coal gasification grey water system is used for cleaning the sieve plate from the upper portion through the top flushing spray head, the inner wall of the shell is flushed through the combination of the side flushing pipe, and the filtering effect is good. The flushing effect of the filter body is improved, the service life of the filter body is prolonged, recycling of the filter body is achieved, the problems that at present, ash blocks the filter, chilled water supply is insufficient, and a gasification furnace cannot operate for a long period are solved, the working intensity of workers is reduced, and the production investment cost is saved.

A cold plunge water generation assembly for a tub enclosure that is capable of receiving water from an outside water source, chilling said water with an electric water cooling system to a temperature within a range of 33-45° F. and delivering said chilled water to a cold water storage tank for storage. The assembly includes a cold water pump fluidly coupled to the cold water storage tank and an electric controller communicatively coupled to the cold water pump, the electric water cooling system, and an electric display on the assembly, wherein the electric controller is operably configured to selectively initiate the water cooling system to chill incoming liquid for storage in the cold water storage tank and cause the cold water pump to induce a flow of the chilled liquid to the cold water supply conduit and out through the faucet coupled to the tub enclosure.

The invention relates to a combined control method based on chilled water storage and phase change cold storage in a cold supply system, and the method comprises the steps: obtaining electricity price fluctuation information and weather information, and inputting the information into a prediction model for trend prediction when user demand information is received; equipment state information is obtained, and a corresponding federated cold storage strategy model is matched; inputting a trend feature set output by the prediction model and equipment state information into a federated cold storage strategy model to generate a cold storage strategy; solving a cold storage strategy generated by the federated cold storage strategy model to output an optimal cold storage strategy set; through the application of the combined control method and the federated cold storage strategy model, efficient combined control of chilled water storage and phase change cold storage equipment is achieved; by deploying the federated cold storage strategy model, the cold supply system can be quickly matched with the federated cold storage strategy model when facing a new cold storage demand, so that a highly personalized and precise cold storage strategy is generated, and the effectiveness and high efficiency of the strategy are ensured.

The present application relates to a system and method for supplying cascade energy using waste heat from a power plant during production. The waste heat from the power plant during production is connected to a heat source inlet of a lithium-bromide absorption chiller and to a waste water inlet of a waste water heat exchanger, and a heat source outlet of the lithium-bromide absorption chiller is connected to the waster water inlet of the waste water heat exchanger and to a water return port of the waste heat from the power plant during production; the lithium-bromide absorption chiller is connected to a chilled water intake line, a chilled water output line, a cooled water intake line and a cooled water discharge line, the cooled water discharge line is connected to a clean water side inlet of the waste water heat exchanger, and a clean water side outlet of the waste water heat exchanger is sequentially connected to a water purification device and a hot water tank; the clean water side inlet of the waste water heat exchanger is connected to a heating water return line, and the clean water side outlet of the waste water heat exchanger is connected to a heating water supply line; and a water outlet of the waste heat from the power plant during production is further connected to a heat source inlet of a solution regenerator, and a waste water outlet of the solution regenerator is connected to the water return port of the waste heat from the power plant during production. The system of the present application has high energy utilization efficiency, thus effectively expanding the range of waste-water waste heat utilization.

The utility model discloses a semi-closed type air separation precooling device which comprises a circulating water pipe network, a water cooling tower and an air cooling tower, a normal temperature water dry type heat exchanger, a normal temperature water sprayer, a first heat exchange filler and a cooling water heat exchange coil pipe are arranged in the water cooling tower from top to bottom, and a chilled water wet type heat exchange system and a cooling water spraying system are arranged in the air cooling tower. The system further comprises a pipeline which is circularly connected with the circulating water pipe network, the normal-temperature water dry-type heat exchanger, the cooling water heat exchange coil and the chilled water wet-type heat exchange system, and the lower portion of the water cooling tower is provided with a cooling water pump and is connected with the cooling water spraying system through the cooling water pump. The heat exchanger is designed at the top of the water cooling tower to recover the cooling capacity of discharged waste nitrogen; chilled water adopts closed circulation so as to eliminate a chilled water pump; the composite means of step-by-step heat exchange of the air cooling tower to improve the cooling efficiency is adopted, the tail end temperature of compressed air is reduced more efficiently, residual cold and residual pressure of all stages of systems are fully utilized, and the operation energy consumption of the pre-cooling system can be effectively saved.

The invention discloses a fuzzy algorithm-based control method and system for parallel variable-frequency water pumps of a refrigerating unit. The method comprises the following steps of: acquiring operation data of the refrigerating unit; and determining an input variable according to the operation data, determining an output variable through a fuzzy algorithm based on the input variable, and adjusting the refrigerating unit parallel variable frequency water pump according to the output variable. The fuzzy algorithm is adopted to control the refrigerating unit parallel variable frequency water pump, and the chilled water supply and return water temperature difference, the chilled water flow deviation, the cooling water supply and return water temperature difference, the cooling water flow deviation and the refrigerating unit load rate serve as input variables; the chilled water pump frequency adjustment amount and the cooling water pump frequency adjustment amount are used as output variables, so that the chilled water pump frequency adjustment amount and the cooling water pump frequency adjustment amount can be smoothly adjusted according to the current state and the change trend of the system, oscillation and overshoot are effectively reduced, the system runs more stably, and the service life of equipment is prolonged.