3288 results about "Cooling tower" patented technology

The invention belongs to the technical field of intelligent control of heating, ventilation and air conditioning systems, and particularly relates to an intelligent optimizing and energy-saving control method for a central air conditioner based on deep learning, which comprises the following steps of: acquiring operation data of a central air conditioning system in real time through an internet of things technology; the operation data comprises operation parameters of cold and heat source equipment, flow and lift parameters of a water pump, fan frequency parameters of a cooling tower, temperature and humidity data of an air conditioner terminal, environment temperature and humidity data, weather forecast data and the like. Through deep integration of Internet of Things perception, deep learning prediction and a multi-objective optimization technology, the limitation of a traditional control framework is broken through, meanwhile, accurate prediction of building cooling and heating loads is realized through construction of a hybrid deep learning model, an optimization objective of a full life cycle perspective is established in combination with an equipment performance degradation model, and the system performance is improved. A federal learning framework is innovatively introduced into region-level energy efficiency management, and the model generalization ability is improved on the premise of ensuring data privacy.

The invention relates to an ice crystal evaporator and an ice crystal water cooling device producing from the same, belonging to the technical field of refrigeration. The ice crystal evaporator is characterized in that a liquid inlet channel is formed by an evaporator tube, a liquid inlet and a liquid outlet in a tubular casing; and the outer channel of the evaporator tube of the tubular casing is divided into more than one S-shaped channel forming a water return channel through a water inlet of a water divider and a water outlet of a water collector. The ice crystal water cooling device is characterized in that the return air inlet of the ice crystal evaporator is communicated with a compressor, a condenser, a liquid feeding valve, a dry filter, a liquid feeding electromagnetic valve anda thermostatic expansion valve in sequence, and then is communicated with the liquid inlet of the ice crystal evaporator; a cooling water inlet / outlet of the condenser is connected with a cooling tower in series; and a water inlet / outlet of the ice crystal evaporator is communicated with a water circulating pump and an ice crystal energy storage tank in series. The invention has the advantages ofhigh cooling efficiency, no icing and low cooling temperature and is suitable for production of energy storage central air-conditioning, marine fishing, seafood processing, fruit, vegetable or meat processing, and the like; the cooled medium is municipal water.

The invention provides an intelligent monitoring system of a liquid cooling cabinet and processing equipment thereof, and relates to the technical field of data processing, and the system comprises a cold source self-control module which is used for dynamically adjusting the operation state of a cooling tower of primary side circulation and the flow of a circulating water pump according to cooling water parameters, and achieving the variable flow control of cooling water; the dynamic environment monitoring module is used for monitoring the secondary side pipeline state and the cabinet environment in real time through the cooling capacity distribution unit and the distributed sensor network; and the comprehensive monitoring sub-module is used for realizing leakage positioning through a built-in liquid leakage sensor, a temperature sensor and a pressure sensor, and automatically supplementing liquid by using a liquid storage tank. Through multi-mode sensor fusion, dynamic threshold value self-adaption and multi-parameter collaborative analysis, accurate leakage positioning and graded alarm are achieved, automatic liquid supplementing closed-loop control and variable flow adjustment are combined, the system reliability is improved, and energy consumption is reduced.

The invention discloses a cold station multi-equipment combination energy efficiency optimization method and system, relates to the field of cold station energy efficiency optimization, and aims to solve the problems of low energy efficiency and response lag caused by manual adjustment. The method comprises the following steps: S1, acquiring key operation data (power, state, temperature, flow and frequency) of a water chilling unit, a cooling tower and a water pump and external environment data (temperature and humidity, wind speed and load prediction) in real time; s2, constructing an equipment energy efficiency model based on historical data, and quantifying the change of the equipment efficiency along with the load rate, the temperature difference and the environment temperature; s3, according to the current load and environment prediction, simulating and traversing the energy consumption of the equipment start-stop combination and the water pump frequency combination by applying a Monte Carlo algorithm, and screening a combination strategy with the lowest total energy consumption of the system; s4, converting the optimization strategy into a control instruction, and issuing the control instruction to equipment for execution; and S5, comparing the actual energy consumption with the predicted value, and if the deviation exceeds 5%, correcting model parameters by adopting a least square regression algorithm to realize closed-loop optimization. And the energy efficiency and the response speed of the cold station are obviously improved.

The invention relates to a gas leakage early warning method and system for a chemical industry park. The early warning method comprises the following steps: acquiring real-time temperature and pressure data of a reaction kettle area and a storage tank area; obtaining a historical leakage record of a pipeline joint, and determining a diffusion path prediction boundary; extracting a wind direction and a wind speed in a diffusion path prediction boundary, and determining space-time distribution characteristics; analyzing space-time distribution characteristics, determining an overlapping region and setting concentration monitoring nodes; identifying the concentration contribution ratio of the reaction kettle area diffusion characteristic and the storage tank area diffusion characteristic; integrating the operation data of the pipeline joint diffusion characteristics and the loading and unloading area diffusion characteristics, and determining a diffusion path deviation correction coefficient; combining the deviation correction coefficient with the humidity data of the peripheral diffusion characteristics of the cooling tower; and updating diffusion parameters of the separation tower area diffusion characteristics and the public engineering area diffusion characteristics according to a source intensity estimation result. According to the invention, accurate prediction and early warning of gas diffusion in a complex chemical device area are realized, and the safety management level is improved.

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.

According to the cooling tower early fault early warning method based on vibration state monitoring, vibration signals and working condition labels of key parts of the cooling tower are synchronously collected through multiple channels, and data quality is improved through preprocessing operation such as band-pass filtering and normalization; time-frequency features are extracted in a multi-scale mode through self-adaptive variational mode decomposition and wavelet packet transformation, signal complexity is quantized through energy entropy, and weak fault detection capacity is enhanced; the obtained features are input into a deep belief network after being subjected to principal component analysis dimensionality reduction, and automatic classification and recognition of the equipment operation state are achieved; dynamic early warning grade adaptation is carried out according to an identification result in combination with a working condition label, the environmental adaptability and stability of early warning are effectively improved, the method further has the functions of early warning sample recording and periodic model iterative optimization, and the fault identification precision and robustness in a complex noise environment are remarkably improved.

The invention relates to the technical field of industrial control, and discloses a dry-wet combined cooling tower operation state prediction and diagnosis system comprising a load prediction module used for obtaining production plan data and environment information, constructing a basic heat load prediction model, and outputting a total prediction heat load; the thermal modeling module is used for establishing a heat transfer model and an energy consumption model, the heat transfer model outputs cooling amounts in different operation modes, and the energy consumption model outputs total predicted power; the dry-wet decision module is used for constructing a multi-objective optimization function and solving the multi-objective optimization function to obtain a dry-wet switching strategy; and the control execution module is used for executing the dry-wet switching strategy. According to the method, the basic thermal load prediction model is established, so that the prediction precision of the thermal load is improved, and differentiated cooling strategies are provided for different production stages; on the basis of real-time load requirements and environmental conditions, a dry mode or a wet mode is intelligently selected for operation, and a multi-objective optimization function is constructed, so that the balance between cooling requirement meeting and system energy consumption minimization is realized.

The invention relates to the field of factory intelligent cooling, and discloses an MPC-based large factory intelligent cooling system and a cooling control method, the system comprises a data acquisition module, an AI control module, a cooling tower control module, a cooling water pump control module and a cooling-water machine control module; the data acquisition module acquires outdoor environment temperature and humidity, cooling tower outlet water temperature, cooling water pump inlet and outlet water temperature difference and flow and water chiller operation state data in real time. The AI control module constructs a system model through real-time data, predicts and optimizes by using an MPC algorithm, and calculates optimal values of the running frequency of a cooling tower fan, the running frequency of a cooling water pump and the power of a cooling-water machine compressor by adopting sequential quadratic programming, so as to realize cooperative dynamic control of equipment in the system; the overall operation efficiency of the cooling system under the outdoor temperature and humidity change condition is effectively improved, and the overall energy consumption of the system is minimized in real time.

The invention provides a system-level collaborative water-cooling energy-saving control device and method based on AI fusion refrigeration, and the device comprises an edge calculation unit which is used for receiving the operation working condition parameters, the output working condition and refrigerating capacity prediction information of a refrigeration system, and a water-cooling system control strategy; the cooperative control unit is used for receiving the control strategy pushed by the edge computing unit and performing cooperative control on each device of the water cooling system; the collecting unit is used for collecting operation parameters of the refrigerating system. By establishing the complete system energy consumption model and the multi-constraint optimization algorithm, global optimization control over equipment such as a water chilling unit, a water pump and a cooling tower is achieved.

The invention discloses a cooling tower fault tracing method based on a knowledge graph, and the method comprises the steps: collecting all kinds of operation, fault symptoms and environment condition data of a cooling tower in a distributed manner, carrying out the abnormal value processing, missing completion and normalization, and constructing a knowledge graph which takes equipment components, fault modes and symptoms as nodes and causes and effects and association as edges; a fault propagation path is generated in a knowledge graph by using a structured symptom vector, a semantic feature and a historical statistical feature are combined to dynamically evaluate a path weight, and multi-round iterative optimization and sorting are realized, so that a key path with a significant weight is identified as a final fault traceability basis, and a maintenance decision is further supported. According to the invention, the traceability accuracy of complex faults of the cooling tower and the adaptive capability of the knowledge graph are effectively improved.

The invention discloses a cooling tower operation state monitoring method and system based on big data analysis, and relates to the technical field of data processing, and the method comprises the steps: obtaining water temperature data of an inlet and an outlet of a cooling tower, calculating a cooling temperature difference, and carrying out the cooling efficiency evaluation based on a time sequence temperature relation; analyzing the relationship between the control parameters of each level of the cooling tower in combination with historical operation data and a field big data sample, and establishing a level control analysis path; and on the basis of the cooling target of the heat source equipment, analyzing control parameters of each level through the time sequence cooling efficiency, identifying the running state of the cooling tower, and sending state feedback information. The technical problems that existing cooling tower operation state monitoring depends on simple static measurement, dynamic optimization and real-time adjustment of control parameters of all levels are lacked, and the operation efficiency of the cooling tower is affected are solved, and the purposes that the control parameters are dynamically optimized in real time through big data analysis and multi-level control analysis, and the operation efficiency of the cooling tower is improved are achieved. And the operation efficiency of the cooling tower is improved.

The invention belongs to the technical field of cooling towers, and particularly relates to a circulating spraying system and a cooling tower comprising the same, the circulating spraying system comprises a water pipe, a water tank arranged below the water pipe; the pressure control assembly is arranged in the water tank and comprises a sealing block, a connecting ring is arranged on the outer surface of the sealing block, and a connecting hole is formed in the lower surface of the connecting ring. During use, the water pump is started to feed water in the water tank into the atomizing nozzles through the water conveying pipe and the flow dividing pipe. Water flow firstly makes contact with the flow guide strips, impacts the flow guide pieces after drainage and drives the connecting plate and the transmission rod to rotate. The transmission rod penetrates through the first linear bearing and is matched with the second linear bearing to drive the cleaning support to rotate, the first spring buffers, the second spring pushes the cleaning support to enable the cleaning brush to be attached to the inner wall of the nozzle, and the inner wall is cleaned rotationally. After passing through the kinetic energy conversion assembly, the water flow is atomized and sprayed out through the spray orifice plate. The flexible nanofiber brush can remove dirt to avoid blockage, the inner wall is not damaged, and uniform atomization is guaranteed.

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 intercooling tower shutter control system and method have the characteristics of self-adaption and high precision in the control strategy, the system can automatically adjust the control parameters in the actual operation, and the dependence on manual intervention is reduced. The complexity of operation and maintenance is reduced, and errors and faults caused by manual operation are reduced. And the problem of hysteresis or over-regulation possibly caused by a single controller is effectively avoided. By means of double-layer control, more stable control response can be provided when complex and changeable operation conditions are processed, and system instability caused by environment or load fluctuation is reduced. Through the double-layer fuzzy controller, more accurate temperature adjustment can be realized. The first-layer fuzzy controller is responsible for processing macroscopic temperature and wind speed changes, and the second-layer fuzzy controller is used for further finely adjusting the opening error and the change rate.

The invention discloses a data center low-carbon control method and system, and relates to the technical field of data centers, and the method comprises the steps: collecting the environment parameters and equipment operation data of a data center in a hot-summer and warm-winter region in real time based on a multi-mode sensor network; constructing a climate-adaptive space-time diagram convolutional network, taking a server rack, a cooling tower and a power distribution cabinet as nodes, taking a cold and hot flow path as a dynamic weighted edge, embedding climate feature vectors, and generating a thermal load prediction map; a dynamic refrigeration strategy and a server load migration strategy are generated by taking a thermodynamic equation and a fluid dynamic model as strategy optimization boundary conditions through a physical constraint reinforcement learning framework and combining a thermal load prediction map; and based on the dynamic refrigeration strategy, the air conditioning system is controlled to start a hybrid refrigeration mode according to the real-time climate type, the water cooling main cycle and indirect evaporative cooling standby loop are synchronously operated, and the cold charging and discharging logic of the chilled water storage system is switched according to the electricity price time period.

The invention belongs to the technical field of closed cooling towers, and discloses a countercurrent closed cooling tower and a cooling method.The countercurrent closed cooling tower comprises a tower body, a draught fan is fixedly connected to the top of the tower body, an air inlet is formed in the side wall of the bottom of the tower body, a water collecting tank is formed in the bottom of the tower body, and a pair of coil pipes is fixedly connected to the middle of the tower body; through cooperation of structures such as an annular shell, an annular spraying pipe and a concave panel, the possibility that scale is generated by the coil pipe is reduced, the heat exchange effect can be improved, during heat exchange, water in a collecting groove of the annular spraying pipe moving in a reciprocating mode is pumped and pressurized, the surface of the coil pipe is scoured in an annular mode, and the scale forming risk is reduced; and meanwhile, the sliding columns continuously extrude the wave-shaped grooves, so that the whole annular shell rotates in a reciprocating mode, close-distance washing can be more uniform, and therefore the heat exchange effect and durability of the coil pipe are efficiently improved.

The invention discloses a thermal power plant intelligent circulating water energy-saving optimization system control method, relates to the technical field of thermal power plant automatic control, and aims to solve the technical problems of low control precision and large energy consumption of a traditional thermal power plant cold end system and realize optimization control by constructing an intelligent control system based on a Transform deep learning architecture. An intelligent weather data acquisition network is established, meteorological data, satellite meteorological data and a local microclimate sensor network are integrated, and high-precision space-time meteorological information is obtained; according to the method, a Transform encoder-decoder architecture is adopted, multi-source data is converted into a standardized token for representation, and complex association analysis is realized through a multi-head self-attention mechanism; a multi-objective collaborative optimization framework with an objective function as a core is constructed, a steam turbine-condenser-cooling tower-circulating water pump control closed loop is established, and seasonal adaptive control and robust optimization are achieved; providing decision transparent analysis, and explaining a control decision process through attention weight distribution.

The invention belongs to the technical field of locomotive equipment maintenance, and provides an automatic inspection system and method for a locomotive cooling tower, and the method comprises the steps: obtaining the basic information of the locomotive cooling tower, planning an inspection path for an inspection machine, controlling the inspection machine to inspect along the inspection path, and collecting the visual information of the locomotive cooling tower, the method comprises the following steps: constructing a local three-dimensional grid map in real time, detecting obstacles, evaluating a collision risk between the obstacles and an inspection machine, if the collision risk is high, triggering the inspection machine to avoid obstacles, constructing a global three-dimensional grid map when the inspection machine completes an inspection path, and determining an inspection blind area under the global three-dimensional grid map. And judging whether the current inspection time period is ended or not, if not, triggering supplementary inspection, otherwise, planning an inspection path for the next inspection time period, and after the inspection time period is ended, performing anomaly detection and positioning on each part of the locomotive cooling tower based on visual information acquired by an inspection machine through a machine learning algorithm.

The invention relates to the technical field of industrial data storage, in particular to an industrial data storage method and system based on a knowledge graph, and the method comprises the following steps: obtaining cooling tower operation data and binding identification information, constructing a time sequence node and a graph path, extracting a relationship between an attribute tag and a behavior type labeling direction, classification fields belong to path channels in sequence, and structural area additional labels are filled in to write into node relations. According to the method, multi-field synchronous collection is completed through a binding mode of operation data and identification content, an information flow path is constructed according to a time sequence, and paths consistent in sequence are screened according to a field change rule in combination with a transmission direction between attribute labels and behavior type labeling nodes to perform channel division and attribution arrangement. A structural region is filled through unified arrangement of paths and node contents, and label information is added, so that organization association, process continuity and structural logic among data are enhanced, and path stability, node orderliness and data coordination in map construction are improved.

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 utility model relates to a capillary tube energy wall ground source heat pump air-conditioning system for a subway station. A traditional underground station air-conditioning system water chilling unit usually adopts a ground cooling tower to eliminate unit condensation heat, and the problems that the cooling tower is difficult to expropriate land and arrange, influences urban landscapes and the like exist. The system comprises a capillary energy wall close to the soil side and used for eliminating condensation heat, and the capillary energy wall sequentially comprises a structural wall, a capillary mesh buried pipe layer, a heat preservation layer, an aluminum tin film, an air interlayer, an aluminum tin film and a wall separation wall from the soil side to the station side; the capillary mesh buried pipe layer comprises a capillary mesh laid on the inner side of the structural wall. According to the utility model, station waste heat is transferred to surrounding soil through the capillary tube mesh grid laid on the inner surface of the structural wall, underground renewable energy sources are extracted for cooling, and a traditional cooling tower is reduced or replaced. The underground heat exchanger is combined with an underground station supporting structure, cold energy in soil can be extracted, heat can also be extracted, and the occupied space of the underground heat exchanger is effectively reduced.

The invention provides a cooling tower floating water loss prediction analysis method, which comprises the following steps: acquiring and cleaning multi-dimensional operation data of a cooling tower, performing working condition label classification, feature normalization and derivative feature extension, and constructing a deep neural network model to realize floating water loss prediction after dynamically adjusting a feature weight based on a working condition classification clustering result. And in the online stage, real-time working condition labels and historical error feedback are combined, and the feature weights and model parameters are dynamically optimized, so that the generalization ability and prediction accuracy of the model under variable working conditions are improved, the engineering applicability and the online adaptive optimization ability are high, and water saving and intelligent operation management of the cooling tower system are effectively supported.

The utility model discloses a pilot plant for producing fulvic acid by a pyrolysis method. The pilot plant comprises a conduction oil boiler, a grinding machine, a reaction kettle, a sleeve cooler, a buffer tank, a circulating cooling tower and a circulating cooling water pump, wherein the heat-conducting oil boiler is circularly connected with the reaction kettle; the grinding machine is sequentially connected with the reaction kettle and the buffer tank; the sleeve cooler is arranged on a pipeline between the reaction kettle and the buffer tank in a sleeving manner; the sleeve cooler is further connected with a circulating cooling tower, a circulating cooling water pump and a buffer tank in sequence; and the buffer tank is also respectively connected with the sleeve cooler and the circulating cooling tower.

The invention relates to the field of electric power systems, in particular to an energy storage dynamic optimization scheduling method and system of an electric power system and a storage medium, and the method comprises the steps: S1, building an energy storage dynamic calculation model; s3, energy consumption models of a water chilling unit, an air source heat pump, a water pump and a cooling tower are established respectively, and instantaneous energy consumption under different working conditions is calculated by considering operation working conditions and environmental parameter correction; and S4, outputting the utilization rate, the maximum adjusting power, the average adjusting power, the maximum adjusting capacity proportion and the accumulative adjusting electric quantity proportion of the energy storage device, and carrying out quantitative evaluation. According to the method, supply and demand state changes such as valley load, flat load, peak load, peak load and the like of the power system can be identified in real time / quasi-real time, the time periods and power of energy storage and energy release are adjusted, dynamic power distribution of a host in each load time period is realized, and the overall energy efficiency level and operation stability of the system are improved.

The invention relates to the technical field of flue gas treatment, in particular to a gas rising cap assembly, a gas cooling tower and a flue gas purification system. The gas rising cap assembly comprises a plurality of gas rising cap units, the gas rising cap units are arranged in parallel at intervals, and each gas rising cap unit comprises a guide cylinder and a first gas rising cap; the guide cylinder is used for guiding gas to rise for cooling; the first gas rising cap is arranged above the guide cylinder and at least covers the upper part of the guide cylinder; in the axial direction of the guide cylinder, a gap through which gas in the guide cylinder overflows is formed between the first gas rising cap and the upper part of the guide cylinder; at least part of the adjacent gas rising cap units share one first gas rising cap, and an opening is formed in the shared first gas rising cap and located between the upper portions of the adjacent guide cylinders; according to the gas lifting cap assembly, the gas-liquid separation efficiency can be improved, and the problem of low-load liquid leakage can be avoided or reduced.

The invention relates to the technical field of ocean engineering, in particular to a test method suitable for an ORC system performance test. The method comprises the following steps that a heat medium boiler, an air cooling tower and an ORC system are connected, a heat source pipeline and a cold source pipeline are established, and temperature parameters are set; the air cooling tower is started to exhaust air and exchange heat with refrigerant water, organic working medium condensation is accelerated, and it is guaranteed that the cooling efficiency reaches the standard; electrical, instrument, logic and safety protection tests are completed; the system is started and continuously operates for 120 minutes, and whether the temperature, the electrical parameters and the mechanical state are normal or not is monitored in real time; a dry type load device is connected to simulate power generation, and the output performance and stability of the ORC system under the load are verified; and closing the equipment and recovering the original pipeline, and simulating all actions before the ORC system is started. Coolant water and an air cooling tower are used for forced ventilation and cooperative heat exchange, and working medium condensation is accelerated. A cable health degree model is introduced, the cable insulation performance is dynamically evaluated by combining parameters such as temperature and load fluctuation, and the test logic is optimized.

A cooling tower for evaporative cooling of water is contained within an ISO-compliant shipping container frame, permitting stacking of cooling towers for transport and for certain industrial applications. A volume of fill media is contained within the frame. Spaced apart troughs underlie the fill media, running substantially the length of the fill media and connecting to a basin. Baffles are connected to one upper edge of the troughs, while an air flow space is positioned over the other upper trough edge. A water distribution system, with variable flow nozzles positioned closely above the fill media, sprays water over the upper surface of the fill media, where it moves by gravity down into the troughs. Fans atop the fill media move air vertically upward through the fill media.

The invention relates to the technical field of waste heat recovery and comprehensive utilization, in particular to an air compressor waste heat recovery cooling and heating load control method and system and a storage medium. According to the temperature data, the heat pump load is adjusted; obtaining a cooling water temperature trend of the air compressor; according to the air compressor cooling water temperature trend, whether the air compressor cooling water temperature exceeds an early warning value and continues to rise or not is judged; when it is judged that the temperature of the cooling water of the air compressor exceeds the early warning value and continues to rise, the opening degree of a three-way valve is adjusted according to the trend of the temperature of the cooling water of the air compressor; and adjusting the rotating speed of a cooling tower fan according to the temperature trend of the cooling water of the air compressor. Through cooperative regulation and control of the heat pump and the cooling tower, it can be ensured that the temperature of the cooling water is always stabilized in the optimal working interval, and the waste heat utilization rate is maximized on the premise that the operation stability of the air compressor system is guaranteed.