Air conditioner control method and device and electronic equipment

Abstract

The invention provides an air conditioner control method and device and electronic equipment. The method comprises the steps that operation environment data and equipment parameters of all air conditioner equipment are obtained; according to the operation environment data and the equipment parameters, current energy consumption reference values of all the air conditioning equipment are determined; according to the current energy consumption reference value and the rated energy consumption reference value of each air conditioner, determining an energy consumption abnormal value of each air conditioner; according to the energy consumption abnormal value of each air conditioner device, the regulation and control priority of each air conditioner device is determined; and the air conditioning equipment is regulated and controlled according to the regulation and control priorities of the air conditioning equipment. According to the method, the device and the equipment, the high-energy-consumption equipment can be regulated and controlled in a targeted mode, the operation efficiency of the air conditioning system is improved, and unnecessary energy loss is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of air conditioning, and in particular to an air conditioning control method, device and electronic equipment. Background Art

[0002] In the cooling system of the data center computer room, multiple variable frequency refrigeration air conditioners are usually used to form a cooling unit to cool the entire computer room. When the temperature sensor in the data center computer room detects that the temperature rises, it will send a temperature increase trigger signal to the control system, and then the control system will indiscriminately control multiple variable frequency air conditioners to reduce the temperature in the data center computer room to the preset threshold.

[0003] However, as the equipment usage time increases, the energy consumption of some variable frequency refrigeration air conditioners will increase abnormally. If all air conditioners continue to be controlled indiscriminately, it will lead to a significant increase in refrigeration expenses and waste of resources. Summary of the invention

[0004] The technical problem to be solved by the present invention is to provide an air conditioning control method, device and electronic equipment for improving the refrigeration efficiency of the air conditioning system in view of the above-mentioned deficiencies in the prior art.

[0005] In a first aspect, the present invention provides an air conditioning control method, which is applied to a data center computer room, wherein the data center computer room includes a plurality of air conditioning devices, and the method includes:

[0006] Acquire the operating environment data and equipment parameters of each air-conditioning device, wherein the operating environment data is various environment and equipment status information collected in real time during the operation of the air-conditioning system;

[0007] Determine a current energy consumption reference value of each of the air-conditioning devices according to the operating environment data and the device parameters, wherein the current energy consumption reference value is used to characterize the energy consumption level of the air-conditioning device in the current operating state;

[0008] Determine an abnormal energy consumption value of each air-conditioning device according to a current energy consumption reference value and a rated energy consumption reference value of each air-conditioning device, wherein the abnormal energy consumption value is used to characterize the energy consumption degree of the air-conditioning device;

[0009] Determine the control priority of each air-conditioning equipment according to the abnormal energy consumption value of each air-conditioning equipment;

[0010] Each air-conditioning device is regulated according to its regulation priority.

[0011] Furthermore, the operating environment data includes the air volume of the air conditioner fan, and the equipment parameters include the wind resistance of the air supply pipe network and the efficiency of the air conditioner fan.

[0012] Determining the current energy consumption reference value of each of the air-conditioning devices according to the operating environment data and the device parameters specifically includes:

[0013] The current energy consumption reference value is calculated by the following formula (1):

[0014]

[0015] Among them, P fg Indicates the power of the air conditioner fan, Q fg Indicates the air volume of the air conditioner fan, H fg Indicates the wind pressure on both sides of the air conditioner fan, η fg represents the air conditioning fan efficiency, and R represents the wind resistance of the air supply pipe network of the air conditioning.

[0016] Furthermore, the regulating and controlling each air-conditioning device according to the regulating and controlling priority of each air-conditioning device specifically includes:

[0017] Determine the target air-conditioning equipment according to the control priority and control target of each air-conditioning equipment;

[0018] Obtaining current operating environment parameters of the target air conditioner;

[0019] Based on the current operating environment parameters, using a preset optimal operating parameter prediction model, predicting the optimal operating parameters of the target air-conditioning equipment;

[0020] Using a preset composite air conditioning system model, the optimal operating parameters are converted into control parameters;

[0021] The target air-conditioning equipment is controlled according to the control parameters.

[0022] Furthermore, the method further comprises:

[0023] Constructing the optimal operating parameter prediction model;

[0024] The constructing of the optimal operating parameter prediction model specifically includes:

[0025] Acquiring historical operating environment data and historical operating parameters of each of the air-conditioning devices;

[0026] Based on the historical operating environment data and historical operating parameters, a neural network model is trained to obtain the optimal operating parameter prediction model.

[0027] Furthermore, the method further comprises:

[0028] Construct a composite air conditioning system model;

[0029] The optimal operating parameters include the evaporation temperature of the evaporator, the condensation temperature of the condenser, and the compressor frequency of the compressor.

[0030] The method of converting the optimal operating parameters into control parameters by using the preset composite air conditioning system model specifically includes the following steps:

[0031] Step 1: Calculate the target parameters of the evaporator according to the evaporation temperature of the evaporator, the refrigerant superheat at the evaporator outlet, the refrigerant enthalpy at the evaporator inlet, the evaporator inlet pressure and the cooling capacity of each branch evaporator;

[0032] Step 2: determining the target parameters of the compressor according to the compressor frequency of the compressor, the refrigerant flow rate of the compressor, the condensing temperature of the condenser and the target parameters of the evaporator, wherein the target parameters of the compressor include the refrigerant flow rate in the compressor;

[0033] Step 3: when the refrigerant flow rate of the throttle valve of the condenser is greater than the refrigerant flow rate in the compressor, the condensing temperature is increased by a preset unit, the condensing temperature is updated, and the step 1 is returned to be executed;

[0034] When the refrigerant flow rate of the throttle valve of the condenser is equal to the refrigerant flow rate in the compressor, executing step 4;

[0035] Step 4: Determine the target parameters of the condenser according to the condensation temperature of the condenser, the condenser mechanism parameters, and the heat exchange medium inlet parameters;

[0036] Step 5: When the refrigerant enthalpy value at the outlet of the electronic expansion valve is not equal to the refrigerant enthalpy value at the inlet of the evaporator, the refrigerant enthalpy value at the inlet of the evaporator is updated according to the refrigerant enthalpy value at the outlet of the electronic expansion valve, and the process returns to execute step 1;

[0037] When the refrigerant enthalpy at the outlet of the electronic expansion valve is equal to the refrigerant enthalpy at the inlet of the evaporator, executing step six;

[0038] Step 6: When the calculated value of the refrigerant charge amount of the electronic expansion valve is greater than the actual value, the opening of the electronic expansion valve is increased by a preset unit, the opening of the electronic expansion valve is updated, and the process returns to step 1;

[0039] When the calculated value of the refrigerant charge amount of the electronic expansion valve is equal to the actual value, a target parameter of the evaporator, a target parameter of the compressor, a target parameter of the condenser, and a target parameter of the electronic expansion valve are output.

[0040] Furthermore, the evaporator is a parallel evaporator.

[0041] The step 1: calculating the target parameters of the evaporator according to the evaporation temperature of the evaporator, the refrigerant superheat at the evaporator outlet, the refrigerant enthalpy at the evaporator inlet, the evaporator inlet pressure and the cooling capacity of each branch evaporator, specifically includes:

[0042] S11, obtaining the refrigerant superheat at the outlet of the parallel evaporator by thermodynamic calculation;

[0043] S12, when the superheat of the refrigerant at the outlet of the parallel evaporator is greater than a preset superheat, increasing the evaporation temperature by a preset unit and updating the evaporation temperature;

[0044] S13, obtaining reference branch input parameters and non-reference branch input parameters of the parallel evaporators;

[0045] S14, calculating output parameters of the reference branch according to the reference branch input parameters;

[0046] S15, calculating output parameters of the non-reference branches according to input parameters of each non-reference branch, wherein the input parameters of the non-reference branches include the opening of the regulating valve of the non-reference branch;

[0047] S16, when the refrigerant pressure at the reference branch outlet is greater than the refrigerant pressure at the non-reference branch outlet, adjusting the opening of the regulating valve of the non-reference branch to decrease by a preset unit, and returning to execute S15;

[0048] When the refrigerant pressure at the reference branch outlet is equal to the refrigerant pressure at the non-reference branch outlet, executing S17;

[0049] S17. Calculate the target parameters of the evaporator according to the output parameters of the reference branch and the output parameters of each non-reference branch.

[0050] In a second aspect, the present invention provides an air conditioning system control device, comprising:

[0051] Applied to a data center room, the data center room includes multiple air conditioning equipment, and the device includes:

[0052] An acquisition module is used to acquire operating environment data and equipment parameters of each air-conditioning device, wherein the operating environment data is various environment and equipment status information collected in real time during the operation of the air-conditioning system;

[0053] A first determination module, connected to the acquisition module, for determining a current energy consumption reference value of each of the air-conditioning devices according to the operating environment data and device parameters, wherein the current energy consumption reference value is used to characterize the energy consumption level of the air-conditioning device in the current operating state;

[0054] A second determination module, connected to the first determination module, is used to determine an abnormal energy consumption value of each air-conditioning device according to a current energy consumption reference value and a rated energy consumption reference value of each air-conditioning device, wherein the abnormal energy consumption value is used to characterize the energy consumption degree of the air-conditioning device;

[0055] A third determination module, connected to the second determination module, for determining the control priority of each air-conditioning device according to the abnormal energy consumption value of each air-conditioning device;

[0056] The control module is connected to the third determination module and is used to regulate each air-conditioning device according to the regulation priority of each air-conditioning device.

[0057] In a third aspect, the present invention provides an electronic device comprising a processor, a memory, and a program or instruction stored in the memory and executable on the processor, wherein the program or instruction, when executed by the processor, implements the air conditioning control method as described in the first aspect.

[0058] The air conditioning control method, device and electronic device provided by the present invention collect the operating environment data and equipment parameters of the air conditioning equipment in real time, accurately calculate the current energy consumption reference value, and compare it with the rated energy consumption to determine the abnormal energy consumption value. The control priority is determined based on the abnormal energy consumption value, so that the manager can regulate the high-energy consumption equipment in a targeted manner, improve the operating efficiency of the air conditioning system, and reduce unnecessary energy consumption. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 This is a flow chart of an air conditioning control method according to Embodiment 1 of the present invention;

[0060] Figure 2 This is a schematic structural diagram of an air conditioning control device according to Embodiment 2 of the present invention;

[0061] Figure 3 This is a schematic diagram of the structure of an electronic device according to Embodiment 3 of the present invention. DETAILED DESCRIPTION

[0062] In order to enable those skilled in the art to better understand the technical solution of the present invention, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.

[0063] It should be understood that the specific embodiments and drawings described herein are only used to explain the present invention rather than to limit the present invention.

[0064] It can be understood that, in the absence of conflict, the various embodiments of the present invention and the various features in the embodiments can be combined with each other.

[0065] It can be understood that, for the convenience of description, the drawings of the present invention only show the parts related to the present invention, while the parts irrelevant to the present invention are not shown in the drawings.

[0066] It can be understood that each unit and module involved in the embodiments of the present invention may correspond to only one physical structure, or may be composed of multiple physical structures, or multiple units and modules may be integrated into one physical structure.

[0067] It can be understood that the terms "first", "second", etc. in the embodiments of the present invention are used to distinguish different objects, or to distinguish different processing of the same object, rather than to describe a specific order of objects.

[0068] It can be understood that, without conflict, the functions and steps marked in the flowcharts and block diagrams of the present invention may occur in an order different from that marked in the drawings.

[0069] It is understood that the flowcharts and block diagrams of the present invention illustrate the possible architectures, functions, and operations of the systems, devices, equipment, and methods according to the various embodiments of the present invention. Each box in the flowchart or block diagram may represent a unit, module, program segment, or code, which contains executable instructions for implementing the specified functions. Moreover, each box or combination of boxes in the block diagram and flowchart may be implemented by a hardware-based system that implements the specified functions, or may be implemented by a combination of hardware and computer instructions.

[0070] It can be understood that the units and modules involved in the embodiments of the present invention can be implemented by software or hardware. For example, the units and modules can be located in a processor.

[0071] It should be noted that the scenario diagram described in the embodiment of the present application is for the purpose of more clearly illustrating the technical solution of the embodiment of the present application, and does not constitute a limitation on the technical solution provided in the embodiment of the present application. A person of ordinary skill in the art can know that with the evolution of network architecture and the emergence of new business scenarios, the technical solution provided in the embodiment of the present application is also applicable to similar technical problems.

[0072] At present, some data center computer rooms are usually built with multiple variable frequency refrigeration air conditioners to form a cooling unit, and then the cooling unit cools the data center computer room. (Cooling the entire data center computer room, rather than the precise direct blowing of the air duct to the server) When the temperature sensor in the data center computer room detects that the temperature rises, it will send a temperature increase trigger signal to the control system, and then the control system will indiscriminately control multiple variable frequency air conditioners to reduce the temperature in the data center computer room to the preset threshold.

[0073] As the usage time increases (most old equipment has been used for many years), the energy consumption of variable frequency refrigeration air conditioners will gradually increase (the reasons for the increase in energy consumption: compressor aging, filter blockage, internal component power loss, etc.), and some variable frequency refrigeration air conditioners will have abnormal energy consumption. Assuming that multiple variable frequency air conditioners are continuously controlled to cool down without distinction, some abnormal energy consumption will cause additional energy loss to the cooling unit, causing a significant increase in the cooling expenses of the data center computer room.

[0074] Based on the problems existing in the prior art, the present application provides an air conditioning control method to reduce air conditioning energy consumption and improve energy utilization efficiency.

[0075] Embodiment 1:

[0076] This embodiment provides an air conditioning control method. Figure 1 As shown, the method includes the following steps S101 to S1:5:

[0077] S101: Acquire operating environment data and equipment parameters of each air-conditioning equipment.

[0078] Operating environment data refers to various environmental and equipment status information collected in real time during the operation of the air conditioning system. It may include:

[0079] Environmental parameters: temperature, humidity, air quality, etc. in the computer room.

[0080] Equipment status: air conditioner operating mode, wind speed, compressor frequency, outlet air temperature, return air temperature, etc.

[0081] Equipment parameters are the technical specifications and performance parameters of the air-conditioning equipment itself, such as cooling capacity, energy efficiency ratio (COP), equipment model and configuration, etc.

[0082] S102: Determine the current energy consumption reference value of each air-conditioning device according to the operating environment data and device parameters.

[0083] Among them, the current energy consumption reference value is used to characterize the energy consumption level of the air-conditioning equipment in the current operating state.

[0084] The collected operating environment data and equipment parameters are used to calculate the current energy consumption reference value of each air-conditioning device through a calculation model or algorithm. This provides quantitative indicators for identifying air-conditioning devices with abnormal energy consumption and determines the energy consumption changes of air-conditioning devices under different operating conditions.

[0085] S103: Determine the abnormal energy consumption value of each air-conditioning device according to the current energy consumption reference value and the rated energy consumption reference value of each air-conditioning device.

[0086] Among them, the energy consumption abnormal value is used to characterize the energy consumption degree of the air-conditioning equipment.

[0087] The rated energy consumption reference value is the energy consumption value of the air-conditioning equipment under standard working conditions, which is usually provided by the manufacturer or calculated through equipment parameters. The larger the energy consumption abnormality value, the more the energy consumption of the air-conditioning equipment deviates from the normal level, and the more serious the potential energy loss.

[0088] Abnormal energy consumption values ​​can be used to identify high-energy-consuming equipment and identify air-conditioning equipment with possible problems (such as reduced efficiency, failure, etc.). This provides a basis for regulatory decisions and focuses on equipment with abnormal energy consumption.

[0089] In an example, the energy consumption abnormal value = the current energy consumption reference value - the rated energy consumption reference value. A positive value indicates that the energy consumption is higher than the rated value and an abnormality exists. A negative value indicates that the energy consumption is lower than the rated value and may be in a normal or energy-saving state.

[0090] S104: Determine the control priority of each air-conditioning device according to the abnormal energy consumption value of each air-conditioning device.

[0091] The control priority can be determined by sorting according to the size of the energy consumption abnormality value, or by setting a threshold or classification.

[0092] For example, sort the air conditioning equipment according to the energy consumption abnormality value from large to small. The equipment with large energy consumption abnormality value has a high priority. When the demand decreases, the equipment with large energy consumption abnormality value will be shut down or the power will be reduced first; the equipment with large energy consumption abnormality value has a low priority. That is, when the demand increases, the equipment with small energy consumption abnormality value will be turned on or the power will be increased first.

[0093] You can also set thresholds or classifications, for example:

[0094] High priority: The abnormal energy consumption value exceeds the set upper limit, and it is necessary to give priority to shutting down or reducing the power. Medium priority: The abnormal energy consumption value is within the set range. Low priority: The energy consumption is normal, and it is necessary to give priority to turning on or increasing the power.

[0095] Therefore, when resources are limited, regulatory resources can be reasonably allocated to improve regulatory efficiency.

[0096] S105: Control each air-conditioning device according to the control priority of each air-conditioning device.

[0097] It can reduce abnormal energy consumption of air-conditioning equipment, save energy, maintain a stable environment in the data center room, and ensure normal operation of equipment.

[0098] In the embodiment of the present application, by real-time collection and analysis of operating data, the equipment with abnormal energy consumption is determined, and targeted regulation is performed according to priority, which effectively reduces the overall energy consumption of the air-conditioning system and improves energy utilization efficiency.

[0099] Optionally, the operating environment data includes air volume supplied by the air conditioner fan, and the equipment parameters include wind resistance of the air supply pipe network and efficiency of the air conditioner fan.

[0100] The above S102 may specifically include the following steps:

[0101] The current energy consumption reference value is calculated by the following formula (1):

[0102]

[0103] Among them, P fg Indicates the power of the air conditioner fan. The actual power consumption of the fan is calculated using the air supply volume, wind pressure difference and fan efficiency.

[0104] Q fg It indicates the air delivery of the air conditioner fan, which refers to the volume of air delivered by the air conditioner fan per unit time, usually expressed in cubic meters per second (m3 / s) or cubic meters per hour (m3 / h).

[0105] H fg It indicates the wind pressure on both sides of the air conditioning fan. The pressure difference that the fan needs to overcome is calculated based on the air supply volume and the wind resistance of the pipe network.

[0106] η fg Indicates the efficiency of the air conditioner fan, the efficiency of the fan in converting electrical energy into kinetic energy, between 0 and 1. The higher the efficiency, the smaller the energy loss when the fan is running, and the better the energy saving effect.

[0107] R represents the wind resistance of the air supply pipe network of the air conditioner. The resistance of the air supply pipe system to the air flow is related to factors such as pipe length, diameter, number of elbows, surface roughness, etc. The greater the wind resistance, the greater the resistance that the fan needs to overcome, and the higher the power consumption.

[0108] In this embodiment, the power consumption of the air conditioner fan is calculated through an accurate mathematical model, taking into account key parameters such as air supply volume, air pressure, fan efficiency and pipe network wind resistance, and the actual energy consumption of the air conditioner can be accurately evaluated. Taking into account key factors such as fan air supply volume, pipe network wind resistance and fan efficiency, the energy consumption of the fan can be accurately reflected, which helps to discover energy waste and potential equipment abnormalities, thereby providing a reliable basis for subsequent energy-saving optimization.

[0109] Optionally, the above S105 may specifically include the following steps:

[0110] Determine the target air-conditioning equipment according to the control priority and control target of each air-conditioning equipment;

[0111] Obtain the current operating environment parameters of the target air conditioner;

[0112] Based on the current operating environment parameters, the optimal operating parameters of the target air-conditioning equipment are predicted using the preset optimal operating parameter prediction model;

[0113] Using the preset composite air conditioning system model, the optimal operating parameters are converted into control parameters;

[0114] The target air-conditioning equipment is controlled according to the control parameters.

[0115] Among them, the control objectives can be reducing energy consumption, improving ambient temperature distribution, equipment maintenance, etc., which can be determined according to actual conditions and are not limited in this application.

[0116] The optimal operating parameter prediction model can be an algorithm based on machine learning (such as neural network) or physical model, which is used to input the current operating environment parameters and output the optimal operating parameters (such as fan speed, air supply volume, temperature setting value, etc.).

[0117] The composite air conditioning system model is a model that describes the operating characteristics of the entire air conditioning system, taking into account the interaction between components and the system response. It is used to convert theoretical optimal operating parameters into actual executable control commands. By inputting the predicted optimal operating parameters into the composite model, specific control parameters (such as the fan frequency and valve opening that actually need to be adjusted) can be calculated.

[0118] Specifically, based on the priority and specific energy-saving or operating goals, the air-conditioning equipment that needs to be regulated is selected; the operating status of the target air-conditioning equipment is obtained, including parameters such as temperature, humidity, pressure, and equipment load; the current environmental parameters are input into the model to obtain the predicted optimal operating parameters; the predicted optimal operating parameters are input into the composite model to calculate the specific control parameters (such as the fan frequency and valve opening that actually need to be adjusted), that is, the theoretical optimal operating parameters are converted into actual executable control commands; finally, control instructions are sent to the air-conditioning equipment to adjust its operating status so as to adjust the hardware settings or control system parameters of the air-conditioning equipment.

[0119] In this embodiment, by using real-time environmental data and model prediction, the most suitable operating parameters for the current environment can be obtained, and the operating efficiency of the air conditioning system can be maximized. At the same time, through the conversion of the composite system model, the accuracy and executability of the control instructions are ensured, and control deviation is avoided. The energy utilization efficiency and the stability of the computer room environment are improved.

[0120] Optionally, the above method may further include the following steps:

[0121] Construct a prediction model for optimal operating parameters.

[0122] Constructing the optimal operating parameter prediction model includes the following steps:

[0123] Obtain the historical operating environment data and historical operating parameters of each air-conditioning equipment;

[0124] Based on the historical operating environment data and historical operating parameters, the neural network model is trained to obtain the optimal operating parameter prediction model.

[0125] In this embodiment, a neural network-based optimal operating parameter prediction model is constructed by utilizing a large amount of historical operating data. The model can capture the complex nonlinear relationship between the operating parameters of the air-conditioning equipment and the environmental conditions, and achieve accurate prediction of the optimal operating parameters.

[0126] In one example, the optimal operating parameter prediction model construction process is as follows:

[0127] (1) Data collection: Collect the operating data of air-conditioning equipment at different times and under different environmental conditions. Historical operating environment data may include temperature, humidity, external weather conditions, equipment load, etc. Historical operating parameters may include fan speed, air volume, compressor frequency, valve opening, etc.

[0128] (2) Data preprocessing:

[0129] Clean the data to remove outliers and noise. Standardize or normalize the data to improve the model training effect.

[0130] (3) Select the model structure:

[0131] Determine the number of neural network layers, the number of neurons in each layer, the activation function and other hyperparameters.

[0132] (4) Model training:

[0133] Use historical data sets for training and adjust model weights through back-propagation algorithms. Use cross-validation to prevent overfitting and improve the generalization ability of the model.

[0134] (5) Model evaluation:

[0135] Use the test data to evaluate the prediction accuracy of the model and adjust the model structure or retrain if necessary.

[0136] Optionally, the above method further includes:

[0137] Construct a composite air conditioning system model;

[0138] The optimal operating parameters include the evaporation temperature of the evaporator, the condensation temperature of the condenser, and the compressor frequency of the compressor.

[0139] Using the preset composite air conditioning system model, converting the optimal operating parameters into control parameters specifically includes the following steps:

[0140] Step 1: Calculate the target parameters of the evaporator according to the evaporation temperature of the evaporator, the refrigerant superheat at the evaporator outlet, the refrigerant enthalpy at the evaporator inlet, the evaporator inlet pressure and the cooling capacity of each branch evaporator;

[0141] Step 2: determining target parameters of the compressor according to the compressor frequency of the compressor, the refrigerant flow rate of the compressor, the condensing temperature of the condenser and the target parameters of the evaporator, wherein the target parameters of the compressor include the refrigerant flow rate in the compressor;

[0142] Step 3: When the refrigerant flow rate of the throttle valve of the condenser is greater than the refrigerant flow rate in the compressor, the condensing temperature is increased by a preset unit, the condensing temperature is updated, and the execution of step 1 is returned;

[0143] When the refrigerant flow rate of the throttle valve of the condenser is less than the refrigerant flow rate in the compressor, the condensing temperature is reduced by a preset unit, the condensing temperature is updated, and the execution returns to step 1;

[0144] When the refrigerant flow rate of the throttle valve of the condenser is equal to the refrigerant flow rate in the compressor, execute step 4;

[0145] Step 4: Determine the target parameters of the condenser according to the condensing temperature of the condenser, the condenser mechanism parameters, and the heat exchange medium inlet parameters;

[0146] Step 5: When the refrigerant enthalpy value at the outlet of the electronic expansion valve is not equal to the refrigerant enthalpy value at the inlet of the evaporator, the refrigerant enthalpy value at the inlet of the evaporator is updated according to the refrigerant enthalpy value at the outlet of the electronic expansion valve, and the process returns to step 1;

[0147] When the refrigerant enthalpy value at the outlet of the electronic expansion valve is equal to the refrigerant enthalpy value at the inlet of the evaporator, execute step 6;

[0148] Step 6: When the calculated value of the refrigerant charge amount of the electronic expansion valve is greater than the actual value, the opening of the electronic expansion valve is increased by a preset unit, the opening of the electronic expansion valve is updated, and the process returns to step 1;

[0149] When the calculated value of the refrigerant charge amount of the electronic expansion valve is equal to the actual value, a target parameter of the evaporator, a target parameter of the compressor, a target parameter of the condenser, and a target parameter of the electronic expansion valve are output.

[0150] In this embodiment, the composite air-conditioning system model is used to convert the optimal operating parameters into specific control parameters to achieve precise control of the air-conditioning equipment.

[0151] Step 1: Calculate the target parameters that need to be controlled through the known evaporator operating conditions and design parameters to adjust the operating state of the evaporator to meet the actual load demand; Step 2: Adjust the operating parameters of the compressor to coordinate the refrigerant flow rate output with the operating states of the evaporator and condenser to maintain the refrigeration cycle balance of the system; Step 3: When it is found that the refrigerant flow rate does not match, change the pressure and flow rate in the system by adjusting the operating parameters (such as condensation temperature) to achieve balance; Step 4: Determine the operating parameters of the condenser by calculating its thermodynamic process in detail to meet the heat dissipation requirements of the system and ensure the normal operation of the refrigeration cycle; Step 5: Adjust the expansion valve so that the thermodynamic state of the refrigerant after throttling meets the operating requirements of the evaporator, thereby ensuring the coordination of the entire refrigeration cycle; Step 6: Adjust the amount of refrigerant entering the system by accurately controlling the opening of the electronic expansion valve to ensure that the system operates in the best state.

[0152] In this embodiment, by constructing a composite air-conditioning system model, the process of converting the optimal operating parameters into specific control parameters is described in detail. This method ensures that the refrigerant flow and thermodynamic state inside the system are balanced and matched by iteratively calculating and adjusting the parameters of key components such as the evaporator, compressor, condenser and electronic expansion valve. Ultimately, precise control of the air-conditioning equipment is achieved, the operating efficiency and reliability of the air-conditioning system are improved, and the technical effects of energy saving, consumption reduction and performance optimization are achieved. .

[0153] Optionally, the evaporator is a parallel evaporator,

[0154] Step 1: Calculate the target parameters of the evaporator based on the evaporation temperature of the evaporator, the refrigerant superheat at the evaporator outlet, the refrigerant enthalpy at the evaporator inlet, the evaporator inlet pressure and the cooling capacity of each branch evaporator, including:

[0155] S11, obtaining the refrigerant superheat at the outlet of the parallel evaporator by thermodynamic calculation;

[0156] S12, when the superheat of the refrigerant at the outlet of the parallel evaporator is greater than the preset superheat, the evaporation temperature is increased by a preset unit to update the evaporation temperature;

[0157] When the superheat of the refrigerant at the outlet of the parallel evaporator is less than the preset superheat, the evaporation temperature is reduced by a preset unit and the evaporation temperature is updated;

[0158] When the refrigerant superheat degree at the outlet of the parallel evaporator is equal to the preset superheat degree, continue to execute S13;

[0159] S13, obtaining reference branch input parameters and non-reference branch input parameters of the parallel evaporators;

[0160] S14, calculating the output parameters of the reference branch according to the input parameters of the reference branch;

[0161] S15, calculating the output parameters of the non-reference branches according to the input parameters of each non-reference branch, wherein the input parameters of the non-reference branches include the opening of the regulating valve of the non-reference branches;

[0162] S16, when the refrigerant pressure at the reference branch outlet is greater than the refrigerant pressure at the non-reference branch outlet, adjusting the opening of the regulating valve of the non-reference branch to decrease by a preset unit, and returning to S15;

[0163] When the refrigerant pressure at the reference branch outlet is lower than the refrigerant pressure at the non-reference branch outlet, the opening of the regulating valve of the non-reference branch is increased by a preset unit, and the process returns to step S15;

[0164] When the reference branch outlet refrigerant pressure is equal to the non-reference branch outlet refrigerant pressure, executing S17;

[0165] S17. Calculate target parameters of the evaporator according to the output parameters of the reference branch and the output parameters of each non-reference branch.

[0166] Among them, the parallel evaporator is composed of multiple parallel branches, and the refrigerant flows and evaporates simultaneously in each branch. Each branch needs to be coordinated and controlled to ensure the optimization of the overall performance.

[0167] Superheat refers to the degree to which the refrigerant temperature exceeds the saturation temperature. Appropriate superheat can prevent liquid refrigerant from entering the compressor and avoid damage.

[0168] Specifically, step S11 calculates the outlet superheat in order to determine the state of the refrigerant at the outlet of the evaporator.

[0169] Step S12: If the superheat is too high, it may lead to reduced energy efficiency. Increasing the evaporation temperature can reduce the superheat and make the system run at a higher efficiency. If the superheat is too low, it means that the evaporation temperature is relatively high. Lowering the evaporation temperature can increase the superheat, which can prevent liquid refrigerant from entering the compressor and prevent liquid hammer.

[0170] Step S13: Obtaining accurate input parameters is the basis for subsequent calculations.

[0171] Step S14 calculates the output parameters of the reference branch such as the outlet pressure, temperature, and refrigerant enthalpy. These parameters will be used to adjust the non-reference branches to achieve balance among the branches.

[0172] The regulating valve opening of the non-reference branch in step S15 is an adjustable control variable. By calculation, the output parameter of the non-reference branch under the current valve opening can be determined.

[0173] The purpose of step S16 is to adjust the pressure of the non-reference branch to match that of the reference branch. Reducing the valve opening will increase the resistance of the non-reference branch, thereby increasing its outlet pressure. This process may require multiple iterations until the pressure is balanced.

[0174] Step S17: When the outlet pressures of each branch are balanced, the operation state of the entire parallel evaporator is optimized. The target parameters may include the overall cooling capacity, outlet temperature, superheat, etc. These parameters will be used for overall control and optimization of the system.

[0175] In this embodiment, the overall performance of the evaporator is optimized by accurately calculating and adjusting the operating parameters of each branch of the parallel evaporator. By adjusting the evaporation temperature and the opening of each branch regulating valve, the outlet superheat and pressure of each branch reach a preset equilibrium state, ensuring that the refrigerant is evenly distributed between the branches, and improving the heat transfer efficiency of the evaporator and the stability of the system. This method effectively reduces energy loss, improves the operating efficiency of the air-conditioning system, and achieves the technical effect of energy saving and consumption reduction.

[0176] An embodiment of the present invention provides an air conditioning system control method.

[0177] In a specific embodiment, the air conditioning system control method may include the following steps:

[0178] Step 1: Build a power consumption calculation model to generate the corresponding instant power consumption value

[0179] The specific steps to build the air conditioning energy consumption model are as follows:

[0180] (1) Data Collection

[0181] Various sensors are installed on each variable frequency refrigeration and air conditioner, and various parameters of each refrigeration and air conditioner per unit time are read.

[0182] Specifically, they may include:

[0183] Wind speed data:

[0184] A sensor is set at the total return air outlet of the air conditioner to measure the wind speed at the return air outlet for calculating the air volume flow rate.

[0185] Area data includes:

[0186] The total filter area (S) is the total area of ​​the return air filter of the air conditioner. The filter permeability (η) characterizes the ventilation performance of the filter, which is the ratio of the area of ​​the return air passing through the filter to the total area of ​​the filter. The above area data is obtained by calculating the rated air volume under the rated power frequency operation state.

[0187] Temperature and humidity data: Sensors are installed at the return air vents and supply air vents to detect the return air temperature (T1), supply air temperature (T2) and humidity to calculate the air density and cooling capacity.

[0188] Pressure data:

[0189] Air pressure (P) at a specific state, used to calculate air density.

[0190] (2) Calculation of air volume flow

[0191] Calculation of volume flow:

[0192] The air volume flow is the product of wind speed and area. To measure the return air volume, the wind speed and area at the total return air outlet of the air conditioner are required. The total filter area permeability is preset to be η. The η value can be calculated by the rated air volume under the rated power frequency operation state. It can be calculated by the following formula (1):

[0193]

[0194] Among them, V e It represents the volume flow rate at rated operation, η represents the ratio of the area of ​​return air passing through the filter to the total area of ​​the filter, S represents the total area of ​​the filter, It represents the average wind speed (unit: m / s). 3600 means converting the flow rate from per second to per hour, that is, 1 hour = 3600 seconds.

[0195] (3) Calculation of air mass flow rate.

[0196] (a) Calculation of air density:

[0197] Air density is affected by temperature and pressure, and its calculation formula is as follows (2):

[0198]

[0199] Where ρ is the air density under specific conditions (unit: kg / m3).

[0200] ρ0 is the density of dry air under standard conditions (1.293kg / m3).

[0201] P is the air pressure under a specific state (unit: Pa).

[0202] P0 is standard atmospheric pressure (101325Pa).

[0203] T is the thermodynamic temperature under a specific state (unit: K, absolute temperature, T = t ° C + 273.15).

[0204] T0: standard temperature (273.15K).

[0205] (b) Calculation of air mass flow:

[0206] The air mass flow rate is the product of the air volume flow rate and the air density, and is calculated using the following formula (3):

[0207] F c =ρ*V e (3)

[0208] Among them, F c is the return air mass flow rate, that is, the air mass flow rate, ρ represents the density of air under a specific state, V e Indicates the volume flow rate at rated operation.

[0209] (4) Calculation of cooling capacity.

[0210] The cooling capacity refers to the cooling capacity provided by the air conditioner. The air cooling capacity represents the degree of air cooling. After heat exchange at the air conditioner terminal, cold air is provided to the computer room. The cold air enters the IT equipment in the computer room for heat exchange and then returns to the air return port of the air conditioner. The cooling capacity of the cold air is calculated during the heat exchange process of the cold air.

[0211] The heat absorbed by the cold air when it enters the computer room and returns to the return air outlet is calculated using the following formula (4):

[0212] Q=c p m p Δt (4)

[0213] Among them, Q represents the cooling capacity of the air supply, that is, the cooling capacity;

[0214] c p represents the specific heat capacity of cold air;

[0215] m p Indicates the cooling air quality, by c Convert from kg / h to kg / s to get m p , that is, m p =F c ÷3600.

[0216] Δt represents the temperature difference between the return air temperature and the supply air temperature, that is, Δt = return air temperature (T1) - supply air temperature (T2).

[0217] (5) Establishment of energy consumption model

[0218] The energy consumption model of the air conditioning fan is based on the air supply volume and fan power of the fan. The model expression is as follows:

[0219]

[0220] Among them, P fgIndicates the power of the air conditioner fan, Q fg Indicates the air volume of the air conditioner fan, H fg Indicates the wind pressure on both sides of the air conditioner fan, η fg represents the air conditioning fan efficiency, and R represents the wind resistance of the air supply pipe network of the air conditioning, which can be obtained through experimental measurement, computational fluid dynamics simulation or reference to pipeline design parameters.

[0221] Step 2: Compare the instantaneous energy consumption value corresponding to each air conditioner with the rated value pre-stored in the database to obtain the energy fluctuation difference, and perform dynamic energy consumption coding on each air conditioner in turn according to the energy consumption fluctuation difference.

[0222] 1. Obtain the rated energy consumption of each air conditioning equipment

[0223] Obtain an algorithm model (or visual chart) of the energy consumption growth of the variable frequency refrigeration air conditioner over time from the database or manufacturer, bring the actual usage time into the algorithm model, and obtain the rated energy consumption value (use the visual chart to find the rated energy consumption value corresponding to the usage time).

[0224] 2. Compare the instantaneous energy consumption value corresponding to each air conditioner with the rated energy consumption value to obtain the energy fluctuation difference.

[0225] 3. Dynamically encode the energy consumption of each air conditioner in turn according to the energy consumption fluctuation difference.

[0226] Step 3: When the system dynamically controls the overall temperature of the data center computer room, the control priority of each air-conditioning device is determined according to the energy consumption code.

[0227] Dynamically call the variable frequency refrigeration air conditioner to perform temperature adjustment operations according to priority.

[0228] When cooling is required, variable frequency refrigeration air conditioners with smaller energy consumption fluctuations are preferred; when the temperature is low enough, variable frequency refrigeration air conditioners with larger energy consumption fluctuations are preferred to reduce their loads.

[0229] Step 4: Create the optimal operating parameter prediction model

[0230] (1) Obtain the operating environment data in the data center computer room, transmit the operating environment data to the background database, and the background database pre-processes the operating environment data to obtain the data to be trained.

[0231] (2) Feature extraction is performed on the training data to obtain the input parameters of the algorithm model, and the input parameters are input into the neural network for model training to obtain the optimal operating parameter prediction model.

[0232] The optimal operating parameters are directly predicted by inputting input parameters (such as operating environment parameters) into the trained optimal operating parameter prediction model.

[0233] Step 5: Predict the optimal operating parameters of the regulated air-conditioning equipment according to the optimal operating parameter prediction model.

[0234] (1) Collect the current operating environment parameters of the air-conditioning equipment.

[0235] (2) Based on the current operating environment parameters of the air-conditioning equipment, the optimal operating parameters of the controlled air-conditioning equipment are predicted using the optimal operating parameter prediction model.

[0236] Step 6: Create a composite air conditioning system model.

[0237] The optimal operating parameters are converted into control instructions for the computer room air conditioner and saved in the background database. A composite air conditioning system model of the computer room air conditioner is constructed based on the control instructions and the optimal operating parameters.

[0238] The operation process of the composite air-conditioning system model is as follows:

[0239] Obtain the basic structure and optimal operating parameters of the air conditioning system, environmental parameters, evaporator outlet refrigerant superheat Δt′ and evaporator cooling capacity Q i .

[0240] The basic structure of the air conditioning system (the air conditioning system here is equivalent to the single air conditioning equipment mentioned above) includes: evaporator, compressor, electronic expansion valve and condenser. It is determined according to the system design configuration and the actual situation of the equipment.

[0241] Environmental parameters: can be obtained through real-time monitoring by sensors.

[0242] The optimal operating parameters, i.e., the optimal operating parameters corresponding to the current environmental conditions, are predicted by the above-mentioned optimal operating parameter prediction model. Specifically, they may include: the evaporation temperature of the evaporator, the condensation temperature of the condenser, and the compressor frequency of the compressor. They are obtained by the above-mentioned optimal operating parameter prediction model.

[0243] The refrigerant superheat Δt′ at the evaporator outlet (preset target superheat) can be preset according to the system safety operation requirements to avoid compressor liquid hammer.

[0244] Evaporator cooling capacity Q i , can be determined based on the load demand or design load of each evaporator branch.

[0245] S1. Calculate the parallel evaporator modules.

[0246] The preset evaporation temperature is t e , enthalpy of refrigerant at the evaporator inlet H ri And the opening degree K of the electronic expansion valve.

[0247] Among them, the evaporation temperature t eIt is predicted by the optimal operating parameter prediction model.

[0248] Evaporator inlet refrigerant enthalpy H ri Refers to the thermodynamic state parameter of the refrigerant at the evaporator inlet, usually expressed as enthalpy (kJ / kg). Enthalpy is the internal energy of a substance plus the product of pressure and volume, indicating the energy state of the substance. The initial value of the enthalpy of the refrigerant at the evaporator inlet can be estimated based on the enthalpy change of the throttling process.

[0249] The electronic expansion valve uses the electrical signal generated by the regulated parameter to control the voltage or current applied to the expansion valve, thereby achieving the purpose of regulating the liquid supply. The initial opening degree K of the electronic expansion valve can be set based on experience or historical data, and is usually preset at an intermediate value.

[0250] The specific calculation process is as follows:

[0251] S11. The actual superheat degree is obtained by thermodynamic calculation to obtain the refrigerant superheat degree Δt1 at the evaporator outlet.

[0252] Optionally, the evaporator outlet temperature and the evaporation temperature t e The difference is calculated.

[0253] S12, judging whether the calculated refrigerant superheat degrees Δt1 and Δt′ at the evaporator outlet are equal, if they are equal, executing S13;

[0254] If Δt1>Δt′, then increase t e That is, adjust the evaporation temperature to make Δt1 equal to Δt′, and obtain the updated evaporation temperature t e , execute S13.

[0255] S13. Obtain reference branch input parameters and non-reference branch input parameters.

[0256] Including the enthalpy and pressure of the inlet refrigerant of the parallel evaporator and the cooling capacity of each branch evaporator.

[0257] S14. Calculate the reference branch.

[0258] The reference branch input parameters include:

[0259] Reference branch inlet refrigerant enthalpy H in,5 =H ri ;

[0260] Reference branch evaporator inlet pressure P in,5 : Corresponding evaporation temperature t e Saturation pressure P r ;

[0261] The opening degree of the reference branch refrigerant flow regulating valve K5 = 1, indicating that the reference branch valve is fully open, which is used as a reference;

[0262] The reference branch evaporator cooling capacity Q5 is determined according to load demand or system design.

[0263] According to the above reference branch input parameters, the following calculations are performed:

[0264] The refrigerant enthalpy H at the base branch outlet is obtained by energy balance calculation out,5 ;

[0265] The reference branch outlet pressure P is obtained by calculating the fluid resistance or assuming it as the reference pressure. out,5 ;

[0266] According to H in,5 , H out,5 and Q5, calculate the refrigerant flow m r,5 .

[0267] S15. Calculate the non-reference branch.

[0268] The opening degree K of the regulating valve of the non-reference branch i Preset (based on experience or initial estimation), opening K i The upper limit is 1, the opening degree K i The lower limit is 0;

[0269] Non-reference branch input parameters include:

[0270] Enthalpy value of refrigerant at the inlet of non-reference branch H in,i =H ri ;

[0271] Non-reference branch inlet refrigerant pressure P in,i ;

[0272] Non-reference branch regulating valve opening K i , the initial value is the preset value;

[0273] Non-reference branch evaporator cooling capacity Q i , corresponding to the cooling capacity of the branch.

[0274] According to the above non-reference branch input parameters, the non-reference branch output parameters are calculated, including the refrigerant enthalpy value H at the reference branch outlet. out,i 、Pressure P out,i and refrigerant flow rate m r,i ;

[0275] S16, determine whether the refrigerant pressure at the reference branch outlet is equal to the refrigerant pressure at the non-reference branch outlet. If the non-reference refrigeration outlet pressure P out,i With the reference branch outlet pressure Pout,5 If they are equal, execute S17.

[0276] If P out,i >P out,5 , then reduce K i That is, adjust the opening K of the corresponding regulating valve i , and return to execute step S15;

[0277] By adjusting the opening degree K of each branch regulating valve i , so that the outlet pressure of each branch is consistent and stable operation is achieved.

[0278] S17. Calculate the enthalpy value H of the mixed refrigerant at the end outlet of the parallel evaporator ro 、Pressure P ro And total refrigerant flow m r,t .

[0279] According to the output parameters of each branch, the mass-weighted average is used to obtain the mixed refrigerant enthalpy H at the end outlet of the parallel evaporator. ro and pressure P ro ; Calculate the total refrigerant flow m according to the refrigerant flow of each branch r,t .

[0280] S18, output parallel evaporator end outlet refrigerant enthalpy value H ro 、Pressure P ro and refrigerant flow rate m r,t .

[0281] S2. Calculate compressor module.

[0282] The compressor works on the refrigerant, increasing its pressure and enthalpy in preparation for the condensation process. c (preset according to the optimal operating parameters or environmental conditions) and compressor frequency f (initial preset value, set according to system requirements), as well as the refrigerant enthalpy value H at the end outlet of the parallel evaporator ro and refrigerant flow rate m r,t As compressor input parameter.

[0283] S21, according to the compressor characteristic curve, determine the refrigerant flow m in the compressor through the compressor frequency f r,c .

[0284] S22, determine the refrigerant flow rate m in the compressor r,c Refrigerant flow rate required for refrigeration at the end of the parallel evaporator m r,t Are they equal? ​​If they are equal, execute S23;

[0285] If m r,c <m r,t, then increase f, that is, adjust the compressor frequency, and return to execute S21.

[0286] By adjusting the compressor frequency f, the refrigerant flow rate m is changed rc , making it equal to the evaporator demand m r,t Matching to ensure supply and demand balance.

[0287] S23, output compressor outlet parameters

[0288] Refrigerant flow rate in compressor m r,c , compressor frequency f, compressor outlet pressure P out,c Among them, P out,c =P c , P c Corresponding to the condensation temperature t c The corresponding saturation pressure.

[0289] S3. Calculate the condenser module.

[0290] Condenser input parameters:

[0291] Condenser structural parameters: including fin-tube heat exchanger size, material, piping layout, etc., and filler characteristics (if there is evaporative cooling function).

[0292] S31. Determine the refrigerant flow rate m of the throttle valve of the condenser r,e .

[0293] S32, determine the refrigerant flow m through the throttle valve of the condenser r,e The refrigerant flow rate in the compressor m r,c Are they equal? ​​If they are equal, execute S33;

[0294] If m r,c >m r,e , then increase t c That is, after adjusting the condensing temperature, the process returns to execute S1.

[0295] S33. The specific steps for calculating the condenser are as follows:

[0296] ① Input the structural parameters of the condenser and the heat exchange medium inlet parameters.

[0297] ② Determine whether to turn on the evaporative cooling function:

[0298] Determine whether to turn on the evaporative cooling function according to the ambient temperature (when the ambient temperature is higher than a certain set value, such as 24°C, turn on the evaporative cooling function.

[0299] If necessary, calculate the packing model to obtain its outlet air dry bulb temperature, that is, calculate the temperature of the air after passing through the wet film or packing according to the wet air heat and moisture exchange equation and heat and mass transfer theory;

[0300] Otherwise, directly go to step ③ to calculate the fin tube heat exchanger, that is, directly use the ambient air parameters to enter the fin tube heat exchanger calculation.

[0301] ③ Preset the refrigerant enthalpy value at the outlet of the fin-tube heat exchanger, and take the corresponding t c The saturated liquid enthalpy is at or slightly below this value.

[0302] The heat exchange components of the evaporative cooling condenser include a fin-tube heat exchanger and fillers, and the refrigerant condensation heat exchange process occurs in the fin-tube heat exchanger.

[0303] ④ Determine whether the outlet refrigerant is too cold:

[0304] The outlet refrigerant temperature is determined based on the refrigerant pressure at the outlet of the two-phase zone of the condenser and the refrigerant enthalpy at the outlet of the fin-tube heat exchanger.

[0305] Determine whether the refrigerant at the outlet of the fin-tube heat exchanger is too cold. If it is too cold, execute ⑤, otherwise execute ⑥.

[0306] ⑤Calculate the length of the heat exchange tube in the subcooling zone of the condenser:

[0307] According to the refrigerant state parameters at the inlet and outlet of the supercooling zone, each micro-section of the supercooling zone is solved in turn to obtain the length of the heat exchange tube of each micro-section, thereby calculating the length of the heat exchange tube in the supercooling zone.

[0308] ⑥Calculate the length of the two-phase region:

[0309] According to the refrigerant state parameters at the inlet and outlet of the two-phase region, the length of each microelement segment of the two-phase region is solved in turn, so as to obtain the length of the heat exchange tube corresponding to the two-phase region.

[0310] ⑦ Determine whether the inlet refrigerant of the fin-tube heat exchanger is overheated:

[0311] In the heat pipe mode, the refrigerant at the inlet of the fin-tube heat exchanger can be in a two-phase state. If it is overheated, execute ⑧, otherwise execute ⑨;

[0312] ⑧Calculate the length of the heat exchange tube in the superheated area of ​​the condenser:

[0313] According to the refrigerant state parameters at the inlet and outlet of the superheat zone, each micro-element section of the superheat zone is solved in turn to obtain the length of the heat exchange tube of each micro-element section, thereby calculating the length of the heat exchange tube in the superheat zone.

[0314] ⑨ Determine whether the total length of the fin heat exchanger is equal to the actual length:

[0315] The calculated values ​​of the length of the heat exchange tubes in the superheated zone, two-phase zone and supercooled zone are obtained by adding the calculated values.

[0316] Compare the calculated value with the actual length of the flap tube. If the absolute value of the difference between the two is less than the preset value, continue to output the calculation result. The output parameters include the refrigerant outlet state parameters and the refrigerant heat exchange capacity.

[0317] Otherwise, when the calculated value is greater than the actual value, the iterative lower limit of the refrigerant enthalpy value at the outlet of the fin-tube heat exchanger is increased; when the calculated value is less than the actual value, the iterative upper limit of the refrigerant enthalpy value at the outlet of the fin-tube heat exchanger is reduced, and the preset outlet enthalpy value is adjusted before returning to execution ④.

[0318] S4, calculating the electronic expansion valve module;

[0319] S41. Determine the refrigerant enthalpy value at the outlet of the electronic expansion valve

[0320] S42, determine whether the refrigerant enthalpy value at the outlet of the electronic expansion valve is consistent with the preset H ri whether they are equal;

[0321] If the two are equal, execute S43;

[0322] Otherwise, the refrigerant enthalpy value at the outlet of the electronic expansion valve is assigned as the new H ri After that, return to execute S1;

[0323] S43, judging whether the calculated value of the refrigerant charge amount is equal to the input actual value,

[0324] Among them, the calculated value of the refrigerant charge is calculated based on the internal volume of each component (evaporator, condenser, compressor, pipeline, etc.) and the density of the refrigerant in different states;

[0325] If the two are equal, the calculation result is output and the iteration ends;

[0326] If the calculated value is greater than the actual value, K is increased, i.e., K is adjusted, and the process returns to execute S1.

[0327] Step 7: Determine control parameters of the air-conditioning equipment using the composite air-conditioning system model, and control the air-conditioning equipment with higher priority based on the control parameters.

[0328] Based on the optimal operating parameters corresponding to the air conditioning equipment, the control parameters of the air conditioning are determined using the composite air conditioning system model;

[0329] Determine the control priority of air conditioning equipment according to dynamic coding;

[0330] Based on the control parameters, the air conditioning equipment with high priority is controlled.

[0331] In this embodiment, 1. the problem of abnormal energy consumption of individual variable frequency refrigeration air conditioners causing energy consumption burden on the overall cooling unit and increasing additional expenses is solved. 2. the problem of frequent changes in the operating state of the whole machine due to indiscriminate control of air conditioners, which reduces the service life of air conditioners, is solved.

[0332] Embodiment 2:

[0333] like Figure 2 As shown, this embodiment provides a control device for an air conditioning system, which is applied to a data center computer room. The data center computer room includes a plurality of air conditioning devices, and is used to perform the steps of the above-mentioned air conditioning control method, including:

[0334] The acquisition module 201 is used to acquire the operating environment data and equipment parameters of each air-conditioning device, wherein the operating environment data is various environment and equipment status information collected in real time during the operation of the air-conditioning system;

[0335] A first determination module 202, connected to the acquisition module, is used to determine a current energy consumption reference value of each of the air-conditioning devices according to the operating environment data and device parameters, wherein the current energy consumption reference value is used to characterize the energy consumption level of the air-conditioning device in the current operating state;

[0336] A second determination module 203, connected to the first determination module, is used to determine an abnormal energy consumption value of each air-conditioning device according to a current energy consumption reference value and a rated energy consumption reference value of each air-conditioning device, wherein the abnormal energy consumption value is used to characterize the energy consumption degree of the air-conditioning device;

[0337] A third determination module 204, connected to the second determination module, is used to determine the control priority of each air-conditioning device according to the abnormal energy consumption value of each air-conditioning device;

[0338] The control module 205 is connected to the third determination module, and is used to control each air-conditioning device according to the control priority of each air-conditioning device.

[0339] Optionally, the operating environment data includes the air volume of the air conditioner fan, and the equipment parameters include the wind resistance of the air supply pipe network and the efficiency of the air conditioner fan.

[0340] The first determining module 202 is specifically configured to:

[0341] The current energy consumption reference value is calculated by the following formula (1):

[0342]

[0343] Among them, P fg Indicates the power of the air conditioner fan, Q fg Indicates the air volume of the air conditioner fan, H fg Indicates the wind pressure on both sides of the air conditioner fan, ηfg represents the air conditioning fan efficiency, and R represents the wind resistance of the air supply pipe network of the air conditioning.

[0344] Optionally, the control module 205 includes:

[0345] A determination unit, used to determine a target air-conditioning device according to the control priority and control target of each air-conditioning device;

[0346] An acquisition unit, used to acquire the current operating environment parameters of the target air conditioner;

[0347] A prediction unit, configured to predict the optimal operating parameters of the target air-conditioning equipment based on the current operating environment parameters and using a preset optimal operating parameter prediction model;

[0348] A conversion unit, used to convert the optimal operating parameters into control parameters using a preset composite air conditioning system model;

[0349] A control unit is used to control the target air-conditioning equipment according to the control parameters.

[0350] In the embodiment of the present application, the operating environment data and equipment parameters of the air-conditioning equipment are collected in real time, the current energy consumption reference value is accurately calculated, and compared with the rated energy consumption to determine the energy consumption abnormal value. The control priority is determined based on the energy consumption abnormal value, so that the manager can regulate the high-energy consumption equipment in a targeted manner, improve the operating efficiency of the air-conditioning system, and reduce unnecessary energy consumption.

[0351] Embodiment 3:

[0352] Figure 3 A schematic diagram of the hardware structure of an electronic device provided in an embodiment of the present application is shown.

[0353] The electronic device may include a processor 301 and a memory 302 storing computer program instructions.

[0354] Specifically, the processor 301 may include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiments of the present application.

[0355] The memory 302 may include a large capacity memory for data or instructions. By way of example and not limitation, the memory 302 may include a hard disk drive (HDD), a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus (USB) drive or a combination of two or more of these. In appropriate cases, the memory 302 may include a removable or non-removable (or fixed) medium. In appropriate cases, the memory 302 may be inside or outside the integrated gateway disaster recovery device. In a specific embodiment, the memory 302 is a non-volatile solid-state memory.

[0356] The memory may include read-only memory (ROM), random access memory (RAM), magnetic disk storage media devices, optical storage media devices, flash memory devices, electrical, optical or other physical / tangible memory storage devices. Thus, typically, the memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the method according to an aspect of the present disclosure.

[0357] The processor 301 implements any one of the air conditioning control methods in the above embodiments by reading and executing computer program instructions stored in the memory 302 .

[0358] In one example, the electronic device may further include a communication interface 303 and a bus 304. Figure 3 As shown, the processor 301, the memory 302, and the communication interface 303 are connected via a bus 304 and communicate with each other.

[0359] The communication interface 303 is mainly used to implement communication between various modules, devices, units and / or equipment in the embodiments of the present application.

[0360] Bus 304 includes hardware, software or both, and the parts of online data flow billing equipment are coupled to each other. For example, but not limitation, bus may include accelerated graphics port (AGP) or other graphics bus, enhanced industrial standard architecture (EISA) bus, front-end bus (FSB), hypertransport (HT) interconnection, industrial standard architecture (ISA) bus, infinite bandwidth interconnection, low pin count (LPC) bus, memory bus, micro channel architecture (MCA) bus, peripheral component interconnection (PCI) bus, PCI-Express (PCI-X) bus, serial advanced technology attachment (SATA) bus, video electronics standard association local (VLB) bus or other suitable bus or two or more of these combinations. In appropriate cases, bus 304 may include one or more buses. Although the present application embodiment describes and shows a specific bus, the present application considers any suitable bus or interconnection.

[0361] In addition, in combination with the air conditioning control method in the above embodiment, the embodiment of the present application can provide a computer storage medium for implementation. The computer storage medium stores computer program instructions; when the computer program instructions are executed by the processor, any barcode recognition method in the above embodiment is implemented.

[0362] It should be clear that the present application is not limited to the specific configuration and processing described above and shown in the figures. For the sake of simplicity, a detailed description of the known method is omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of the present application is not limited to the specific steps described and shown, and those skilled in the art can make various changes, modifications and additions, or change the order between the steps after understanding the spirit of the present application.

[0363] The functional blocks shown in the above block diagram can be implemented as hardware, software, firmware or a combination thereof. When implemented in hardware, it can be, for example, an electronic circuit, an application specific integrated circuit (ASIC), appropriate firmware, a plug-in, a function card, etc. When implemented in software, the elements of the present application are programs or code segments that are used to perform the required tasks. The program or code segment can be stored in a machine-readable medium, or transmitted on a transmission medium or a communication link by a data signal carried in a carrier wave. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, optical fiber media, radio frequency (RF) links, etc. The code segment can be downloaded via a computer network such as the Internet, an intranet, etc.

[0364] It should also be noted that the exemplary embodiments mentioned in this application describe some methods or systems based on a series of steps or devices. However, this application is not limited to the order of the above steps, that is, the steps can be performed in the order mentioned in the embodiment, or in a different order from the embodiment, or several steps can be performed simultaneously.

[0365] Aspects of the present disclosure are described above with reference to the flowchart and / or block diagram of the method, device (system) and computer program product according to the embodiment of the present disclosure. It should be understood that each box in the flowchart and / or block diagram and the combination of each box in the flowchart and / or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device to produce a machine so that these instructions executed by the processor of the computer or other programmable data processing device enable the implementation of the function / action specified in one or more boxes of the flowchart and / or block diagram. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field programmable logic circuit. It can also be understood that each box in the block diagram and / or flowchart and the combination of boxes in the block diagram and / or flowchart can also be implemented by dedicated hardware that performs a specified function or action, or can be implemented by a combination of dedicated hardware and computer instructions.

[0366] The above are only specific implementation methods of the present application. Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working processes of the systems, modules and units described above can refer to the corresponding processes in the aforementioned method embodiments, and will not be repeated here. It should be understood that the protection scope of the present application is not limited to this. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed in this application, and these modifications or replacements should be included in the protection scope of this application.

Claims

1. An air conditioning control method, characterized in that: Applied to a data center computer room, the data center computer room includes a plurality of air conditioning devices, the method includes: Acquire the operating environment data and equipment parameters of each air-conditioning device, wherein the operating environment data is various environment and equipment status information collected in real time during the operation of the air-conditioning system; Determine a current energy consumption reference value of each of the air-conditioning devices according to the operating environment data and the device parameters, wherein the current energy consumption reference value is used to characterize the energy consumption level of the air-conditioning device in the current operating state; Determine an abnormal energy consumption value of each air-conditioning device according to a current energy consumption reference value and a rated energy consumption reference value of each air-conditioning device, wherein the abnormal energy consumption value is used to characterize the energy consumption degree of the air-conditioning device; Determine the control priority of each air-conditioning equipment according to the abnormal energy consumption value of each air-conditioning equipment; Each air-conditioning device is regulated according to its regulation priority.

2. The method according to claim 1, characterized in that The operating environment data includes the air volume of the air conditioner fan, and the equipment parameters include the wind resistance of the air supply pipe network and the efficiency of the air conditioner fan. Determining the current energy consumption reference value of each of the air-conditioning devices according to the operating environment data and the device parameters specifically includes: The current energy consumption reference value is calculated by the following formula (1): Among them, P fg Indicates the power of the air conditioner fan, Q fg Indicates the air volume of the air conditioner fan, H fg Indicates the wind pressure on both sides of the air conditioner fan, η fg represents the air conditioning fan efficiency, and R represents the wind resistance of the air supply pipe network of the air conditioning.

3. The method according to claim 1, characterized in that: The regulating and controlling of each air-conditioning device according to the regulating and controlling priority of each air-conditioning device specifically includes: Determine the target air-conditioning equipment according to the control priority and control target of each air-conditioning equipment; Obtaining current operating environment parameters of the target air conditioner; Based on the current operating environment parameters, using a preset optimal operating parameter prediction model, predicting the optimal operating parameters of the target air-conditioning equipment; Using a preset composite air conditioning system model, the optimal operating parameters are converted into control parameters; The target air-conditioning equipment is controlled according to the control parameters.

4. The method according to claim 3, characterized in that: The method further comprises: Constructing the optimal operating parameter prediction model; The constructing of the optimal operating parameter prediction model specifically includes: Acquiring historical operating environment data and historical operating parameters of each of the air-conditioning devices; Based on the historical operating environment data and historical operating parameters, a neural network model is trained to obtain the optimal operating parameter prediction model.

5. The method according to claim 3, characterized in that: The method further comprises: Construct a composite air conditioning system model; The optimal operating parameters include the evaporation temperature of the evaporator, the condensation temperature of the condenser, and the compressor frequency of the compressor. The method of converting the optimal operating parameters into control parameters by using the preset composite air conditioning system model specifically includes the following steps: Step 1: Calculate the target parameters of the evaporator according to the evaporation temperature of the evaporator, the refrigerant superheat at the evaporator outlet, the refrigerant enthalpy at the evaporator inlet, the evaporator inlet pressure and the cooling capacity of each branch evaporator; Step 2: determining the target parameters of the compressor according to the compressor frequency of the compressor, the refrigerant flow rate of the compressor, the condensing temperature of the condenser and the target parameters of the evaporator, wherein the target parameters of the compressor include the refrigerant flow rate in the compressor; Step 3: when the refrigerant flow rate of the throttle valve of the condenser is greater than the refrigerant flow rate in the compressor, the condensing temperature is increased by a preset unit, the condensing temperature is updated, and the step 1 is returned to be executed; When the refrigerant flow rate of the throttle valve of the condenser is equal to the refrigerant flow rate in the compressor, executing step 4; Step 4: Determine the target parameters of the condenser according to the condensation temperature of the condenser, the condenser mechanism parameters, and the heat exchange medium inlet parameters; Step 5: When the refrigerant enthalpy value at the outlet of the electronic expansion valve is not equal to the refrigerant enthalpy value at the inlet of the evaporator, the refrigerant enthalpy value at the inlet of the evaporator is updated according to the refrigerant enthalpy value at the outlet of the electronic expansion valve, and the process returns to execute step 1; When the refrigerant enthalpy at the outlet of the electronic expansion valve is equal to the refrigerant enthalpy at the inlet of the evaporator, executing step six; Step 6: When the calculated value of the refrigerant charge amount of the electronic expansion valve is greater than the actual value, the opening of the electronic expansion valve is increased by a preset unit, the opening of the electronic expansion valve is updated, and the process returns to step 1; When the calculated value of the refrigerant charge amount of the electronic expansion valve is equal to the actual value, a target parameter of the evaporator, a target parameter of the compressor, a target parameter of the condenser, and a target parameter of the electronic expansion valve are output.

6. The method according to claim 5, characterized in that The evaporator is a parallel evaporator. The step 1: calculating the target parameters of the evaporator according to the evaporation temperature of the evaporator, the refrigerant superheat at the evaporator outlet, the refrigerant enthalpy at the evaporator inlet, the evaporator inlet pressure and the cooling capacity of each branch evaporator, specifically includes: S11, obtaining the refrigerant superheat at the outlet of the parallel evaporator by thermodynamic calculation; S12, when the superheat of the refrigerant at the outlet of the parallel evaporator is greater than a preset superheat, increasing the evaporation temperature by a preset unit and updating the evaporation temperature; S13, obtaining reference branch input parameters and non-reference branch input parameters of the parallel evaporators; S14, calculating output parameters of the reference branch according to the reference branch input parameters; S15, calculating output parameters of the non-reference branches according to input parameters of each non-reference branch, wherein the input parameters of the non-reference branches include the opening of the regulating valve of the non-reference branch; S16, when the refrigerant pressure at the reference branch outlet is greater than the refrigerant pressure at the non-reference branch outlet, adjusting the opening of the regulating valve of the non-reference branch to decrease by a preset unit, and returning to execute S15; When the refrigerant pressure at the reference branch outlet is equal to the refrigerant pressure at the non-reference branch outlet, executing S17; S17. Calculate the target parameters of the evaporator according to the output parameters of the reference branch and the output parameters of each non-reference branch.

7. A control device for an air conditioning system, characterized in that: Applied to a data center room, the data center room includes multiple air conditioning equipment, and the device includes: An acquisition module is used to acquire operating environment data and equipment parameters of each air-conditioning device, wherein the operating environment data is various environment and equipment status information collected in real time during the operation of the air-conditioning system; A first determination module, connected to the acquisition module, for determining a current energy consumption reference value of each of the air-conditioning devices according to the operating environment data and device parameters, wherein the current energy consumption reference value is used to characterize the energy consumption level of the air-conditioning device in the current operating state; A second determination module, connected to the first determination module, is used to determine an abnormal energy consumption value of each air-conditioning device according to a current energy consumption reference value and a rated energy consumption reference value of each air-conditioning device, wherein the abnormal energy consumption value is used to characterize the energy consumption degree of the air-conditioning device; A third determination module, connected to the second determination module, for determining the control priority of each air-conditioning device according to the abnormal energy consumption value of each air-conditioning device; The control module is connected to the third determination module and is used to regulate each air-conditioning device according to the regulation priority of each air-conditioning device.

8. The device according to claim 7, characterized in that The operating environment data includes the air volume of the air conditioner fan, and the equipment parameters include the wind resistance of the air supply pipe network and the efficiency of the air conditioner fan. The first determining module is specifically configured to: The current energy consumption reference value is calculated by the following formula (1): Among them, P fg Indicates the power of the air conditioner fan, Q fg Indicates the air volume of the air conditioner fan, H fg Indicates the wind pressure on both sides of the air conditioner fan, η fg represents the air conditioning fan efficiency, and R represents the wind resistance of the air supply pipe network of the air conditioning.

9. The device according to claim 8, characterized in that The control module comprises: A determination unit, used to determine a target air-conditioning device according to the control priority and control target of each air-conditioning device; An acquisition unit, used to acquire the current operating environment parameters of the target air conditioner; A prediction unit, configured to predict the optimal operating parameters of the target air-conditioning equipment based on the current operating environment parameters and using a preset optimal operating parameter prediction model; A conversion unit, used to convert the optimal operating parameters into control parameters using a preset composite air conditioning system model; A control unit is used to control the target air-conditioning equipment according to the control parameters.

10. An electronic device, characterized in that: It includes a processor, a memory, and a program or instruction stored in the memory and executable on the processor, wherein the program or instruction, when executed by the processor, implements the air conditioning control method as described in any one of claims 1 to 6.

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