Intelligent control system of efficient refrigerating machine room

Abstract

The invention relates to a high-efficiency intelligent control system for a refrigerating machine room, and relates to the technical field of refrigerating machine rooms. The detection device is used for collecting the operation state of the machine room operation equipment to form equipment operation data; the optimization analysis module is used for receiving the equipment operation data, processing the equipment operation data by adopting an energy efficiency optimization algorithm model so as to form equipment control information, and outputting the equipment control information to the machine room operation equipment so as to adjust the operation state; the energy efficiency optimization algorithm model comprises a load prediction sub-model and a host optimization sub-model, the load prediction sub-model calls meteorological data and analyzes the meteorological data and the equipment operation data to form load prediction information, and the host optimization sub-model calls preset host performance data and analyzes the preset host performance data and the load prediction information to form host control information; and the host control information is used as equipment control information. The method has the effect of reducing the operation energy consumption of the refrigerating machine room.

Description

Technical Field

[0001] The invention relates to the technical field of refrigeration rooms, in particular to a high-efficiency intelligent control system for refrigeration rooms. Background Art

[0002] A refrigeration room is a special room where refrigeration equipment is placed, mainly used to provide refrigeration services for buildings or industrial production.

[0003] The refrigeration room is equipped with a refrigeration unit for refrigeration, a cooling tower for dissipating the heat discharged by the refrigeration unit, and a water pump for delivering cooling water to the refrigeration unit. The cooling water is delivered to the refrigeration unit by the water pump to absorb the heat and discharge it, and then the cooling water that has absorbed the heat is dissipated and cooled by the cooling tower, thereby maintaining continuous refrigeration.

[0004] At present, when controlling the operation of refrigeration rooms, simple start-stop control and variable frequency control for water pumps are generally adopted. When the actual load changes, the operating status of the equipment remains unchanged, resulting in high operating energy consumption. Summary of the invention

[0005] In order to reduce the operating energy consumption of a refrigeration room, the present invention provides a high-efficiency intelligent control system for a refrigeration room.

[0006] In a first aspect, the present invention provides a high-efficiency intelligent control system for a refrigeration room, which adopts the following technical solutions: An efficient intelligent control system for a refrigeration room, comprising: Equipment in the computer room for cooling; A detection device, used for collecting the operating status of the operating equipment in the computer room to form equipment operating data; An optimization analysis module, used to receive equipment operation data and process it using an energy efficiency optimization algorithm model to form equipment control information, and output the equipment control information to the operating equipment in the computer room to adjust the operating status; The energy efficiency optimization algorithm model includes a load prediction sub-model and a host optimization sub-model. The load prediction sub-model retrieves meteorological data and analyzes it with equipment operation data to form load prediction information. The host optimization sub-model retrieves preset host performance data and analyzes it with load prediction information to form host control information, and uses the host control information as equipment control information.

[0007] Optionally, the analysis and processing steps of the host optimization sub-model include: Get the air conditioning demand temperature value; Retrieve the load-generated temperature value based on the load forecast information; Calculate the difference between the load generated temperature value and the air conditioning demand temperature value and use it as the temperature deviation value; Retrieve host parameter values ​​and host individual values ​​based on host performance data; According to the corresponding relationship between the host parameter value and the preset single adjustment temperature difference value, the single adjustment temperature difference value corresponding to the host parameter value is determined; Calculate the quotient between the temperature deviation value and the single adjusted temperature difference value and use it as the temperature difference adjustment value; According to the comparison result between the temperature difference adjustment value and the host value, the number of host start-up and stop units, the unit load rate and the outlet water temperature value are determined, and the number of host start-up and stop units, the unit load rate and the outlet water temperature value are used as the host control information.

[0008] Optionally, the energy efficiency optimization algorithm model also includes a cooling tower optimization sub-model, which retrieves preset cooling tower performance data and analyzes it with load forecast information to form cooling tower control information, and adds the cooling tower control information to the equipment control information for updating.

[0009] Optionally, the analysis and processing steps of the cooling tower optimization sub-model include: According to the corresponding relationship between the load-generated temperature value and the preset heat dissipation required temperature value, the heat dissipation required temperature value corresponding to the load-generated temperature value is determined; Retrieve cooling tower parameter values ​​and cooling tower individual values ​​based on cooling tower performance data; According to the corresponding relationship between the cooling tower parameter value and the preset single cooling water capacity value, the single cooling water capacity value corresponding to the cooling tower parameter value is determined; Determining a single cooling temperature value based on a single cooling water capacity value; Calculate the quotient between the heat dissipation requirement temperature value and the single cooling temperature value and use it as the heat dissipation requirement value; According to the comparison result between the heat dissipation demand value and the cooling tower value, the number of cooling towers started and stopped and the operating frequency of the cooling towers are determined, and the number of cooling towers started and stopped and the operating frequency of the cooling towers are used as cooling tower control information.

[0010] Optionally, the energy efficiency optimization algorithm model also includes a hydraulic prediction sub-model, which retrieves meteorological data and analyzes it with equipment operation data to form hydraulic prediction information.

[0011] Optionally, the energy efficiency optimization algorithm model also includes a distribution pump group optimization sub-model, which retrieves preset water pump performance data and analyzes it with load forecast information and hydraulic forecast information to form pump group control information, and adds the pump group control information to the equipment control information for updating.

[0012] Optionally, the analysis and processing steps of the distribution pump group optimization sub-model include: Retrieve the cooling tower location point based on the cooling tower performance data; Retrieve host location points based on host performance data; Calculate the distance between the cooling tower location point and the host location point and use it as the flow demand distance value; According to the corresponding relationship between the flow demand distance value and the preset hydraulic distance influence value, the hydraulic distance influence value corresponding to the flow demand distance value is determined; Retrieving hydraulic forecast demand value based on hydraulic forecast information; Calculate the product of the hydraulic distance impact value and the hydraulic forecast demand value and use it as the hydraulic demand adjustment value; Based on the water pump performance data, retrieve the single pump hydraulic output value and single pump flow output value; The quotient between the hydraulic demand adjustment value and the hydraulic output value of a single pump is used as the number of hydraulic starts and stops; According to the correspondence between the heat dissipation demand temperature value and the preset heat dissipation demand water volume value, the heat dissipation demand water volume value corresponding to the heat dissipation demand temperature value is determined; Calculate the quotient between the required water volume for heat dissipation and the output value of a single pump and use it as the number of water volume starts and stops; The number of water pump starts and stops and the water pump operating frequency are determined based on the comparison results between the number of hydraulic starts and stops and the number of water volume starts and stops, and the number of water pump starts and stops and the water pump operating frequency are used as the pump group control information.

[0013] Optionally, the method for determining the number of water pump starts and stops and the water pump operation frequency includes: According to the corresponding relationship between the number of hydraulic start-stop units, the hydraulic demand adjustment value and the preset hydraulic operation frequency, the hydraulic operation frequency corresponding to the number of hydraulic start-stop units and the hydraulic demand adjustment value is determined; Determine whether the number of hydraulic start and stop units is greater than the number of water volume start and stop units; If yes, the hydraulic operation frequency is used as the water pump operation frequency, and the number of hydraulic starts and stops is used as the number of water pump starts and stops; If not, the hydraulic water quantity value corresponding to the number of hydraulic start and stop units is determined according to the corresponding relationship between the number of hydraulic start and stop units and the preset hydraulic water quantity value; Calculate the difference between the hydraulic water volume value and the heat dissipation demand water volume value and use it as the water volume deviation value; According to the correspondence between the water volume deviation value, the number of hydraulic start-stop units and the preset frequency water volume deviation adjustment value, the frequency water volume deviation adjustment value corresponding to the water volume deviation value and the number of hydraulic start-stop units is determined; The hydraulic operation frequency is adjusted based on the frequency water volume deviation adjustment value to form a hydraulic operation adjustment frequency, and the hydraulic operation adjustment frequency is used as the water pump operation frequency, and the number of hydraulic starts and stops is used as the number of water pump starts and stops.

[0014] Optionally, the method further includes a step after taking the hydraulic operation adjustment frequency as the water pump operation frequency and taking the hydraulic start and stop number as the water pump start and stop number, which is specifically as follows: According to the correspondence between the hydraulic operation adjustment frequency and the preset adjustment frequency single pump energy consumption value, the adjustment frequency single pump energy consumption value corresponding to the hydraulic operation adjustment frequency is determined; According to the corresponding relationship between the hydraulic operation frequency and the preset hydraulic frequency single pump energy consumption value, the hydraulic frequency single pump energy consumption value corresponding to the hydraulic operation frequency is determined; Calculate the difference between the energy consumption value of a single pump with an adjustment frequency and the energy consumption value of a single pump with a hydraulic frequency and use it as the energy consumption deviation value; Calculate the quotient between the energy consumption value of a single hydraulic frequency pump and the energy consumption deviation value and use it as the number of units required for energy consumption deviation; Calculate the difference between the number of hydraulic start-stop units and the number of water volume start-stop units and use it as the unit deviation value; Determine whether the number of units required for energy consumption deviation is greater than the number deviation value; If yes, continue to output the water pump operating frequency and the number of water pump starts and stops; If not, the hydraulic operation frequency will be used as the water pump operation frequency, and the number of water volume starts and stops will be used as the number of water pump starts and stops.

[0015] Optionally, the energy efficiency optimization algorithm model also includes an air-conditioning terminal optimization sub-model, which retrieves preset air-conditioning terminal performance data and analyzes it with load prediction information and hydraulic prediction information to form air-conditioning terminal control information, and adds the air-conditioning terminal control information to the equipment control information for updating.

[0016] In summary, the present invention includes at least one of the following beneficial technical effects: 1. The equipment operation data is collected through the detection device and analyzed by the optimization analysis module using the energy efficiency optimization algorithm model, so as to obtain the equipment control information and output it to the operating equipment in the computer room to adjust the operating status, thereby reducing the operating energy consumption of the refrigeration room; 2. The temperature deviation value is calculated by obtaining the required air conditioning temperature value and calling the load-generated temperature value through the load forecast information. The host parameter value and the host individual value are called through the host performance data. The single adjustment temperature difference value is determined through the host parameter value query to calculate the temperature difference adjustment individual value. Then, the comparison result between the temperature difference adjustment individual value and the host individual value is analyzed to determine the number of host start-up and stop units, the unit load rate and the outlet water temperature value and use them as the host control information. Thus, the host control information is analyzed to improve the accuracy of the acquired host control information; 3. The cooling tower control information is formed through the cooling tower optimization sub-model analysis, the distribution pump group optimization sub-model analysis is formed by the pump group control information, and the air-conditioning terminal optimization sub-model analysis is formed by the air-conditioning terminal control information. The cooling tower control information, pump group control information and air-conditioning terminal control information are used to update the equipment control information, thereby improving the accuracy of the acquired equipment control information. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 is a system flow chart of efficient refrigeration room intelligent control according to an embodiment of the present invention; Figure 2 is a method flow chart of the analysis and processing steps of the host optimization sub-model according to an embodiment of the present invention; Figure 3 is a method flow chart of the analysis and processing steps of the cooling tower optimization sub-model according to an embodiment of the present invention; Figure 4 is a method flow chart of the analysis and processing steps of the distribution pump group optimization sub-model according to an embodiment of the present invention; Figure 5 is a flow chart of a method for determining the number of water pump starts and stops and the water pump operation frequency according to an embodiment of the present invention; Figure 6 It is a method flow chart of an embodiment of the present invention, which is located after the hydraulic operation adjustment frequency is used as the water pump operation frequency, and the hydraulic start and stop number is used as the water pump start and stop number.

[0018] The names of the parts indicated by the numerical labels in the above figures are as follows: 1. Computer room operating equipment; 2. Detection device; 3. Optimization analysis module; 4. Energy efficiency optimization algorithm model; 5. Load prediction sub-model; 6. Host optimization sub-model; 7. Cooling tower optimization sub-model; 8. Hydraulic prediction sub-model; 9. Distribution pump group optimization sub-model; 10. Air conditioning terminal optimization sub-model. DETAILED DESCRIPTION

[0019] The present invention is further described in detail below in conjunction with the accompanying drawings and embodiments.

[0020] Reference Figure 1 The embodiment of the present invention discloses an efficient intelligent control system for a refrigeration room, which includes a room operation device 1, a detection device 2 and an optimization analysis module 3. The room operation device 1 refers to equipment used for refrigeration, and the room operation device 1 includes a refrigeration unit, a cooling tower unit, a distribution pump unit and other equipment. The detection device 2 refers to a device preset on the room operation device 1 and used to detect the operating status of the room operation device 1 to form equipment operation data. The equipment operation data refers to the parameter data of the operating status of the room operation device 1.

[0021] Reference Figure 1, the optimization analysis module 3 refers to a module that analyzes the operating status of the computer room operating equipment 1 and adjusts the computer room operating equipment 1 in real time. The optimization analysis module 3 stores a preset energy efficiency optimization algorithm model 4, which refers to a model for optimizing the energy efficiency of the equipment. The energy efficiency optimization algorithm model 4 is obtained after pre-input. The energy efficiency optimization algorithm model 4 includes a load prediction sub-model 5, a host optimization sub-model 6, a cooling tower optimization sub-model 7, a hydraulic prediction sub-model 8, a distribution pump group optimization sub-model 9, and an air conditioning terminal optimization sub-model 10.

[0022] Reference Figure 1 The load prediction sub-model 5 refers to a sub-model for analyzing load prediction information. The load prediction sub-model 5 is obtained by training a neural network by inputting meteorological data and equipment operation data of historical time to form load prediction information. Among them, meteorological data refers to the weather condition data of the location of the computer room operation equipment 1 at the current time. The meteorological data is obtained by querying and retrieving the weather data of the location of the computer room operation equipment 1 at the current time and serving as meteorological data. Load prediction information refers to prediction information for predicting the temperature and other parameters corresponding to the load generated by the computer room operation equipment 1. The load prediction sub-model 5 retrieves the meteorological data and analyzes it with the equipment operation data to form the load prediction information.

[0023] Reference Figure 1 The hydraulic prediction sub-model 8 refers to a sub-model for analyzing hydraulic prediction information. The hydraulic prediction sub-model 8 is obtained by training a neural network that inputs historical meteorological data and equipment operation data to form hydraulic prediction information. The hydraulic prediction information refers to the prediction information for predicting the hydraulic power corresponding to the operation of the equipment room operation equipment 1. The hydraulic prediction sub-model 8 retrieves meteorological data and equipment operation data for analysis to form hydraulic prediction information.

[0024] Reference Figure 1 The air conditioning terminal optimization sub-model 10 refers to a sub-model for analyzing the air conditioning terminal control information. The air conditioning terminal optimization sub-model 10 is obtained by training a neural network by inputting the load prediction information and hydraulic prediction information of the historical time and the preset air conditioning terminal performance data to form the air conditioning terminal control information. The air conditioning terminal control information refers to the control information for adjusting the operating state of the air conditioning terminal. The preset air conditioning terminal performance data is retrieved by the air conditioning terminal optimization sub-model 10 and analyzed with the load prediction information and hydraulic prediction information to form the air conditioning terminal control information. Among them, the air conditioning terminal performance data refers to the performance, number and other data corresponding to the air conditioning terminal under different operating states. The air conditioning terminal performance data is obtained after pre-input.

[0025] Reference Figure 1, the host optimization sub-model 6 refers to a sub-model for analyzing the host control information, and the host optimization sub-model 6 is obtained after pre-input. The host control information refers to the control information used to adjust the operating state of the refrigeration unit. The host optimization sub-model 6 retrieves the preset host performance data and analyzes it with the load forecast information to form the host control information. The host performance data refers to the performance, number, location and other data corresponding to the refrigeration unit under different operating conditions, and the host performance data is obtained after pre-input.

[0026] Reference Figure 1 , the cooling tower optimization submodel 7 refers to a submodel for analyzing the cooling tower control information, and the cooling tower optimization submodel 7 is obtained after pre-input. The cooling tower control information refers to the control information used to adjust the operating state of the cooling tower group. The cooling tower optimization submodel 7 retrieves the preset cooling tower performance data and analyzes it with the load forecast information to form the cooling tower control information. The cooling tower performance data refers to the performance, number, location and other data corresponding to the cooling tower group under different operating conditions, and the cooling tower performance data is obtained after pre-input.

[0027] Reference Figure 1 , the distribution pump group optimization sub-model 9 refers to a sub-model for analyzing the pump group control information, and the distribution pump group optimization sub-model 9 is obtained after pre-input. Pump group control information refers to control information used to adjust the operating status of the distribution pump group. The distribution pump group optimization sub-model 9 retrieves the preset water pump performance data and analyzes it with the load forecast information and hydraulic forecast information to form the pump group control information. Water pump performance data refers to the performance, hydraulics, water volume and other data corresponding to the distribution pump group under different operating conditions. The water pump performance data is obtained after pre-input. By combining the host control information, air-conditioning terminal control information, cooling tower control information, and pump group control information as equipment control information. Equipment control information refers to control information used to adjust the operating status of the computer room operating equipment 1.

[0028] In order to further ensure the rationality of the host optimization sub-model 6, it is necessary to further analyze and calculate the host optimization sub-model 6 separately. Figure 2 The steps shown are explained in detail.

[0029] Reference Figure 2 , the analysis and processing steps of the host optimization sub-model 6 include: Step S100: obtaining the air conditioning demand temperature value.

[0030] The air conditioning demand temperature value refers to the temperature value that the air conditioning terminal needs to reach, and the air conditioning demand temperature value is obtained after being pre-input by the operator.

[0031] Step S101: Retrieve the load-generated temperature value based on the load forecast information.

[0032] The load-generated temperature value refers to the temperature value corresponding to the load generated when the computer room operating equipment 1 is running. The load-generated temperature value is retrieved through the load prediction information to facilitate subsequent use.

[0033] Step S102: Calculate the difference between the load generation temperature value and the air conditioning demand temperature value and use it as the temperature deviation value.

[0034] The temperature deviation value refers to the deviation value when the temperature has a deviation. The difference between the load-generated temperature value and the air-conditioning demand temperature value is calculated and used as the temperature deviation value for subsequent use.

[0035] Step S103: Retrieve host parameter values ​​and host individual values ​​based on the host performance data.

[0036] Among them, the host parameter value refers to the performance parameter value corresponding to the refrigeration unit under different operating conditions, and the host individual value refers to the individual value that the refrigeration unit can use in the computer room. The host parameter value and the host individual value are retrieved through the host performance data to facilitate subsequent use.

[0037] Step S104: determining a single adjustment temperature difference value corresponding to the host parameter value according to the corresponding relationship between the host parameter value and the preset single adjustment temperature difference value.

[0038] The single adjustment temperature difference value refers to the temperature difference value that can be adjusted when a single host in the refrigeration unit adjusts the temperature. The single adjustment temperature difference value is obtained by querying a database storing different host parameter values ​​and corresponding single adjustment temperature difference values. The database is obtained after pre-input. The single adjustment temperature difference value is determined by querying the host parameter value, which is convenient for subsequent use.

[0039] Step S105: Calculate the quotient between the temperature deviation value and the single adjusted temperature difference value and use it as the temperature difference adjustment value.

[0040] Among them, the temperature difference adjustment value refers to the value of the single host in the refrigeration group that needs to run when adjusting the temperature deviation. The quotient between the temperature deviation value and the single adjustment temperature difference value is calculated, and the number of single hosts in the refrigeration group that need to run is determined based on the quotient and the residual value and used as the temperature difference adjustment value for subsequent use.

[0041] Step S106: According to the comparison result between the temperature difference adjustment value and the host value, the number of host start-up and stop units, the unit load factor and the outlet water temperature value are determined, and the number of host start-up and stop units, the unit load factor and the outlet water temperature value are used as the host control information.

[0042] Among them, the number of host start-stops refers to the number of single hosts in the refrigeration unit that need to be controlled to start, the unit load rate refers to the load rate corresponding to the operation of a single host in the refrigeration unit, and the outlet water temperature value refers to the temperature value corresponding to the outlet water when a single host in the refrigeration unit is in operation. By analyzing the comparison results between the temperature difference adjustment value and the host value, when the temperature difference adjustment value is less than the host value, the temperature difference adjustment value is used as the number of host start-stops, and the preset unit base load rate is output as the unit load rate, and the preset outlet water base temperature value is output as the outlet water temperature value. The unit base load rate refers to the base load rate corresponding to the operation of a single host, and the unit base load rate is obtained after pre-input. The outlet water base temperature value refers to the base temperature value corresponding to the outlet water when a single host is in operation, and the outlet water base temperature value is obtained after pre-input.

[0043] When the value of the temperature difference adjustment is not less than the value of the host, the host value is used as the number of host starts and stops, and the difference between the temperature difference adjustment value and the host value is calculated and used as the host number deviation value. Based on the host number deviation value, the corresponding load number deviation impact value and the outlet water temperature number deviation impact value are retrieved, and then based on the load number deviation impact value, the preset unit benchmark load rate is updated, and based on the outlet water temperature number deviation impact value, the preset outlet water benchmark temperature value is updated. The load number deviation impact value and the outlet water temperature number deviation impact value are obtained by querying a database that stores different host number deviation values ​​and the corresponding load number deviation impact values ​​and outlet water temperature number deviation impact values, and the database is obtained after pre-input. Then, the number of host starts and stops, the unit load rate and the outlet water temperature value are used as host control information to improve the accuracy of the acquired host control information.

[0044] In order to further ensure the rationality of the cooling tower optimization sub-model 7, it is necessary to further analyze and calculate the cooling tower optimization sub-model 7 separately. Figure 3 The steps shown are explained in detail.

[0045] Reference Figure 3 , the analysis and processing steps of the cooling tower optimization sub-model 7 include: Step S200: determining the heat dissipation requirement temperature value corresponding to the load-generated temperature value according to the corresponding relationship between the load-generated temperature value and the preset heat dissipation requirement temperature value.

[0046] The heat dissipation requirement temperature value refers to the temperature value that needs to be dissipated, and the heat dissipation requirement temperature value is obtained by querying from a database storing different load-generated temperature values ​​and corresponding heat dissipation requirement temperature values, and the database is obtained after pre-input. The heat dissipation requirement temperature value is determined by querying the load-generated temperature value, which is convenient for subsequent use.

[0047] Step S201: Retrieve cooling tower parameter values ​​and cooling tower individual values ​​based on cooling tower performance data.

[0048] Among them, the cooling tower parameter value refers to the performance parameter value corresponding to the cooling tower under different operating conditions, and the cooling tower individual value refers to the individual value of the cooling tower that can be used in the machine room. The cooling tower parameter value and the cooling tower individual value are retrieved through the cooling tower performance data to facilitate subsequent use.

[0049] Step S202: determining a single cooling water capacity value corresponding to the cooling tower parameter value according to a correspondence between the cooling tower parameter value and the preset single cooling water capacity value.

[0050] Among them, the single cooling water capacity value refers to the capacity value corresponding to the cooling water stored in a single cooling tower. The single cooling water capacity value is obtained by querying from a database storing different cooling tower parameter values ​​and corresponding single cooling water capacity values. The database is obtained after pre-input. The single cooling water capacity value is determined by querying the cooling tower parameter value, which is convenient for subsequent use.

[0051] Step S203: determining a single cooling temperature value based on the single cooling water capacity value.

[0052] Among them, the single cooling temperature value refers to the temperature value corresponding to the cooling of a single cooling tower, and the single cooling temperature value is obtained by querying from a database storing different single cooling water capacity values ​​and corresponding single cooling temperature values, and the database is obtained after pre-input. The single cooling temperature value is determined by querying the single cooling water capacity value, which is convenient for subsequent use.

[0053] Step S204: Calculate the quotient between the heat dissipation requirement temperature value and the single cooling temperature value and use it as the heat dissipation requirement value.

[0054] Among them, the heat dissipation demand value refers to the value at which the cooling tower needs to operate when heat dissipation is performed. The quotient between the heat dissipation demand temperature value and the single cooling temperature value is calculated, and the number of cooling towers required to operate is determined based on the quotient and the residual value and used as the heat dissipation demand value for subsequent use.

[0055] Step S205: Determine the number of cooling towers started and stopped and the operating frequency of the cooling towers according to the comparison result between the heat dissipation demand value and the cooling tower value, and use the number of cooling towers started and stopped and the operating frequency of the cooling towers as cooling tower control information.

[0056] Among them, the number of cooling towers started and stopped refers to the number of cooling towers that need to be controlled to start, and the cooling tower operating frequency refers to the frequency corresponding to the need to control the cooling tower to operate. By analyzing the comparison results between the heat dissipation demand value and the cooling tower value, when the heat dissipation demand value is less than the cooling tower value, the heat dissipation demand value is used as the number of cooling towers started and stopped, and the preset cooling tower reference operating frequency is output as the cooling tower operating frequency. The cooling tower reference operating frequency refers to the reference frequency corresponding to the operation of a single cooling tower, and the cooling tower reference operating frequency is obtained after pre-input.

[0057] When the heat dissipation demand value is not less than the cooling tower value, the cooling tower value is used as the number of cooling towers to be started and stopped, and the difference between the heat dissipation demand value and the cooling tower value is calculated and used as the cooling tower number deviation value. The corresponding frequency number deviation impact value is retrieved based on the cooling tower number deviation value, and then the preset cooling tower reference operating frequency is updated based on the frequency number deviation impact value. The frequency number deviation impact value is obtained by querying from a database storing different cooling tower number deviation values ​​and the corresponding frequency number deviation impact values, and the database is obtained after pre-input. Then the number of cooling towers started and stopped and the cooling tower operating frequency are used as cooling tower control information to improve the accuracy of the obtained cooling tower control information.

[0058] In order to further ensure the rationality of the transmission and distribution pump group optimization sub-model 9, it is necessary to further analyze and calculate the transmission and distribution pump group optimization sub-model 9 separately. Figure 4 The steps shown are explained in detail.

[0059] Reference Figure 4 , the analysis and processing steps of the distribution pump group optimization sub-model 9 include: Step S300: Retrieve the cooling tower location point based on the cooling tower performance data.

[0060] Among them, the cooling tower location point refers to the location point of the cooling tower. The cooling tower location point is retrieved through the cooling tower performance data to facilitate subsequent use.

[0061] Step S301: Retrieve the host location point based on the host performance data.

[0062] The host location point refers to the location point of the refrigeration unit. The host location point is retrieved through the host performance data to facilitate subsequent use.

[0063] Step S302: Calculate the distance between the cooling tower location point and the host location point and use it as the flow demand distance value.

[0064] The required flow distance value refers to the distance that the cooling water needs to flow. The distance between the cooling tower location point and the host location point is calculated and used as the required flow distance value for subsequent use.

[0065] Step S303: determining the hydraulic distance influence value corresponding to the flow demand distance value according to the corresponding relationship between the flow demand distance value and the preset hydraulic distance influence value.

[0066] The hydraulic distance impact value refers to the impact degree of flow distance on hydraulics, and is obtained by querying a database storing different flow demand distance values ​​and corresponding hydraulic distance impact values, and the database is obtained by pre-input.

[0067] Step S304: Retrieve the hydraulic forecast demand value based on the hydraulic forecast information.

[0068] The hydraulic prediction demand value refers to the hydraulic demand value predicted during the operation of the computer room operating equipment 1. The hydraulic prediction demand value is retrieved through the hydraulic prediction information to facilitate subsequent use.

[0069] Step S305: Calculate the product of the hydraulic distance impact value and the hydraulic forecast demand value and use it as the hydraulic demand adjustment value.

[0070] The hydraulic demand adjustment value refers to the adjustment value for adjusting the required hydraulic power, which is calculated by multiplying the hydraulic distance impact value and the hydraulic forecast demand value and used as the hydraulic demand adjustment value for subsequent use.

[0071] Step S306: Retrieve the single pump hydraulic output value and the single pump flow output value based on the water pump performance data.

[0072] Among them, the single pump hydraulic output value refers to the hydraulic value corresponding to the output of a single water pump in the distribution pump group, and the single pump flow output value refers to the water volume value corresponding to the output of a single water pump in the distribution pump group. The single pump hydraulic output value and the single pump flow output value are retrieved through the water pump performance data to facilitate subsequent use.

[0073] Step S307: The quotient between the hydraulic demand adjustment value and the single pump hydraulic output value is used as the number of hydraulic starts and stops.

[0074] Among them, the number of hydraulic start and stop units refers to the number corresponding to the operation of the hydraulically controlled water pump. The quotient between the hydraulic demand adjustment value and the hydraulic output value of a single pump is calculated, and the number of water pumps required to operate is determined based on the quotient and the residual value and used as the number of hydraulic start and stop units for subsequent use.

[0075] Step S308: determining the heat dissipation required water volume value corresponding to the heat dissipation required temperature value according to the correspondence between the heat dissipation required temperature value and the preset heat dissipation required water volume value.

[0076] The heat dissipation water demand value refers to the water demand value required to dissipate heat at the heat dissipation temperature demand value, and the heat dissipation water demand value is obtained by querying from a database storing different heat dissipation temperature demand values ​​and corresponding heat dissipation water demand values, and the database is obtained after pre-input. The heat dissipation water demand value is determined by querying the heat dissipation temperature demand value, which is convenient for subsequent use.

[0077] Step S309: Calculate the quotient between the required water volume for heat dissipation and the output value of the single pump flow rate and use it as the number of water volume starts and stops.

[0078] Among them, the number of water start-stop units refers to the number of units corresponding to the operation of the water pump controlled by the water volume. The quotient between the heat dissipation demand water volume value and the single pump flow output value is calculated, and the number of water pumps required to run is determined based on the quotient and the residual value and used as the number of water start-stop units for subsequent use.

[0079] Step S310: Determine the number of water pump starts and stops and the water pump operating frequency based on the comparison result between the number of hydraulic starts and stops and the number of water volume starts and stops, and use the number of water pump starts and stops and the water pump operating frequency as the pump group control information.

[0080] Among them, the number of water pump starts and stops refers to the number of water pumps that need to run, and the water pump operating frequency refers to the frequency that the water pump needs to reach when running. By analyzing the comparison results between the hydraulic start-stop number and the water volume start-stop number, the number of water pump starts and stops and the water pump operating frequency are determined, and the number of water pump starts and stops and the water pump operating frequency are used as pump group control information, thereby improving the accuracy of the obtained pump group control information.

[0081] exist Figure 4 In step S310, in order to further ensure the rationality of the number of water pump starts and stops and the water pump operation frequency, it is necessary to further analyze and calculate the number of water pump starts and stops and the water pump operation frequency. Figure 5 The steps shown are explained in detail.

[0082] Reference Figure 5 The method for determining the number of water pump starts and stops and the water pump operation frequency includes the following steps: Step S400: According to the correspondence between the number of hydraulic start-stop units, the hydraulic demand adjustment value and the preset hydraulic operation frequency, the hydraulic operation frequency corresponding to the number of hydraulic start-stop units and the hydraulic demand adjustment value is determined.

[0083] The hydraulic operation frequency refers to the operating frequency corresponding to the operation of a single water pump according to the hydraulic power. The hydraulic operation frequency is obtained by querying from a database storing different hydraulic start and stop numbers, hydraulic demand adjustment values ​​and corresponding hydraulic operation frequencies. The database is obtained after pre-input. The hydraulic operation frequency is determined by querying the hydraulic start and stop numbers and hydraulic demand adjustment values ​​to facilitate subsequent use.

[0084] Step S401: Determine whether the number of hydraulic start-stop units is greater than the number of water volume start-stop units. If yes, execute step S402; if no, execute step S403.

[0085] Among them, by judging whether the number of hydraulic start-stop units is greater than the number of water volume start-stop units, it is judged whether the hydraulic operation frequency needs to be adjusted.

[0086] Step S402: The hydraulic operation frequency is used as the water pump operation frequency, and the hydraulic start and stop number is used as the water pump start and stop number.

[0087] Among them, when the number of hydraulic starts and stops is greater than the number of water volume starts and stops, it means that the hydraulic operation frequency does not need to be adjusted at this time. Therefore, the hydraulic operation frequency is used as the water pump operation frequency, and the number of hydraulic starts and stops is used as the number of water pump starts and stops, so as to improve the accuracy of the obtained water pump start and stop numbers and water pump operation frequencies.

[0088] Step S403: According to the correspondence between the number of hydraulic start-stop units and the preset hydraulic water volume value, the hydraulic water volume value corresponding to the number of hydraulic start-stop units is determined.

[0089] The hydraulic water volume value refers to the water volume value generated according to the number of hydraulic start and stop units. The hydraulic water volume value is obtained by querying from a database storing different hydraulic water volume values ​​and corresponding hydraulic water volume values. The database is obtained after pre-input. The hydraulic water volume value is determined by querying the number of hydraulic start and stop units, which is convenient for subsequent use.

[0090] Step S404: Calculate the difference between the hydraulic water volume value and the heat dissipation demand water volume value and use it as the water volume deviation value.

[0091] The water volume deviation value refers to the deviation value corresponding to the water volume deviation. The difference between the hydraulic water volume value and the heat dissipation demand water volume value is calculated and used as the water volume deviation value for subsequent use.

[0092] Step S405: According to the correspondence between the water volume deviation value, the number of hydraulic start-stop units and the preset frequency water volume deviation adjustment value, the frequency water volume deviation adjustment value corresponding to the water volume deviation value and the number of hydraulic start-stop units is determined.

[0093] Among them, the frequency water volume deviation adjustment value refers to the adjustment value adjusted according to the influence of water volume deviation on frequency. The frequency water volume deviation adjustment value is obtained by querying from a database storing different water volume deviation values, hydraulic start and stop numbers and corresponding frequency water volume deviation adjustment values. The database is obtained after pre-input. The frequency water volume deviation adjustment value is determined by querying the water volume deviation value and the hydraulic start and stop number, which is convenient for subsequent use.

[0094] Step S406: Based on the frequency water volume deviation adjustment value, the hydraulic operation frequency is adjusted to form a hydraulic operation adjustment frequency, and the hydraulic operation adjustment frequency is used as the water pump operation frequency, and the number of hydraulic starts and stops is used as the number of water pump starts and stops.

[0095] Among them, the hydraulic operation adjustment frequency refers to the frequency after adjusting the operating frequency corresponding to the operation of a single water pump according to the hydraulic power. The sum of the frequency water volume deviation adjustment value and the hydraulic operation frequency is calculated, and the sum is used as the hydraulic operation adjustment frequency. The hydraulic operation adjustment frequency is used as the water pump operating frequency, and the number of hydraulic starts and stops is used as the number of water pump starts and stops, thereby improving the accuracy of the obtained number of water pump starts and stops and the water pump operation frequency.

[0096] exist Figure 5 After step S406, in order to further ensure the rationality of the number of water pump starts and stops and the water pump operation frequency, it is necessary to further analyze and calculate the number of water pump starts and stops and the water pump operation frequency. Figure 6 The steps shown are explained in detail.

[0097] Reference Figure 6 The steps after taking the hydraulic operation adjustment frequency as the water pump operation frequency and taking the hydraulic start and stop number as the water pump start and stop number include the following steps: Step S500: determining the single pump energy consumption value of the adjustment frequency corresponding to the hydraulic operation adjustment frequency according to the correspondence between the hydraulic operation adjustment frequency and the preset single pump energy consumption value of the adjustment frequency.

[0098] Among them, the energy consumption value of a single pump with an adjustment frequency refers to the energy consumption value corresponding to the operation of a single water pump according to the hydraulic operation adjustment frequency. The energy consumption value of a single pump with an adjustment frequency is obtained by querying from a database storing different hydraulic operation adjustment frequencies and corresponding energy consumption values ​​of single pumps with adjustment frequencies. The database is obtained after pre-input. The energy consumption value of a single pump with an adjustment frequency is determined by querying the hydraulic operation adjustment frequency, which is convenient for subsequent use.

[0099] Step S501: Determine the hydraulic frequency single pump energy consumption value corresponding to the hydraulic operation frequency according to the correspondence between the hydraulic operation frequency and the preset hydraulic frequency single pump energy consumption value.

[0100] Among them, the hydraulic frequency single pump energy consumption value refers to the energy consumption value corresponding to a single water pump when it operates according to the hydraulic operation frequency. The hydraulic frequency single pump energy consumption value is obtained by querying from a database storing different hydraulic operation frequencies and corresponding hydraulic frequency single pump energy consumption values. The database is obtained after pre-input. The hydraulic frequency single pump energy consumption value is determined by querying the hydraulic operation frequency, which is convenient for subsequent use.

[0101] Step S502: Calculate the difference between the energy consumption value of the single pump at the adjustment frequency and the energy consumption value of the single pump at the hydraulic frequency and use it as the energy consumption deviation value.

[0102] Among them, the energy consumption deviation value refers to the deviation value when there is a deviation in energy consumption. The difference between the energy consumption value of a single pump with an adjustment frequency and the energy consumption value of a single pump with a hydraulic frequency is calculated and used as the energy consumption deviation value to facilitate subsequent use.

[0103] Step S503: Calculate the quotient between the energy consumption value of a single hydraulic frequency pump and the energy consumption deviation value and use it as the energy consumption deviation required number of units.

[0104] Among them, the number of energy consumption deviation requirements refers to the number of water pumps required to process the energy consumption deviation value. The quotient between the energy consumption value of a single pump with hydraulic frequency and the energy consumption deviation value is calculated and used as the number of energy consumption deviation requirements for subsequent use.

[0105] Step S504: Calculate the difference between the number of hydraulic start-stop units and the number of water volume start-stop units and use it as the unit number deviation value.

[0106] Among them, the number deviation value refers to the deviation value when there is a deviation between the number of pumps corresponding to hydraulic power and the number of pumps corresponding to water volume. The difference between the number of hydraulic start-stop units and the number of water volume start-stop units is calculated and used as the number deviation value for convenience in subsequent use.

[0107] Step S505: Determine whether the energy consumption deviation required number of units is greater than the number deviation value. If yes, execute step S506; if no, execute step S507.

[0108] Among them, by judging whether the number of energy consumption deviation requirements is greater than the number deviation value, it is judged whether the water pump operation frequency and the number of water pump starts and stops need to be adjusted.

[0109] Step S506: Continue to output the water pump operating frequency and the number of water pumps started and stopped.

[0110] Among them, when the energy consumption deviation required number is greater than the number deviation value, it means that there is no need to adjust the water pump operating frequency and the number of water pump starts and stops at this time, so the water pump operating frequency and the number of water pump starts and stops continue to be output, thereby improving the accuracy of the obtained water pump operating frequency and the number of water pump starts and stops.

[0111] Step S507: The hydraulic operation frequency is used as the water pump operation frequency, and the number of water volume starts and stops is used as the number of water pump starts and stops.

[0112] Among them, when the energy consumption deviation required number is not greater than the number deviation value, it means that the water pump operating frequency and the number of water pump starts and stops need to be adjusted at this time. Therefore, the hydraulic operating frequency is used as the water pump operating frequency, and the water volume start and stop number is used as the water pump start and stop number, thereby improving the accuracy of the obtained water pump operating frequency and water pump start and stop number.

[0113] Furthermore, in order to improve the accuracy of the acquired number of water pump starts and stops and the water pump operation frequency, after step S507, the following steps are also included: Step S600: Calculate the product of the number deviation value and the energy consumption deviation value and use it as the comprehensive energy consumption value of the number deviation.

[0114] Among them, the comprehensive energy consumption value of the number of units deviation refers to the energy consumption value increased according to the number of deviation units. The product value between the number of units deviation value and the energy consumption deviation value is calculated and used as the comprehensive energy consumption value of the number of units deviation for subsequent use.

[0115] Step S601: Calculate the quotient between the comprehensive energy consumption value of the number of pumps deviation and the energy consumption value of a single hydraulic frequency pump and use it as the number of pumps adjustment value.

[0116] Among them, the number adjustment value refers to the number of units corresponding to the increase in energy consumption that can meet the operation of a single water pump. The quotient between the comprehensive energy consumption value of the number deviation and the energy consumption value of a single pump with hydraulic frequency is calculated and used as the number adjustment value for subsequent use.

[0117] Step S602: determining an adjustment reference value corresponding to the unit number deviation value according to a correspondence relationship between the unit number deviation value and a preset adjustment reference value.

[0118] The adjustment reference value refers to the reference value corresponding to the allowable reduction of a single water pump in operation. The adjustment reference value is obtained by querying from a database storing different number deviation values ​​and corresponding adjustment reference values. The database is obtained after pre-input. The adjustment reference value is determined by querying the number deviation value to facilitate subsequent use.

[0119] Step S603: Determine whether the number of units adjusted value is less than the adjustment reference value. If yes, execute step S604; if no, execute step S606.

[0120] Here, it is determined whether the number of units can be adjusted by determining whether the number of units adjustment value is smaller than the adjustment reference value.

[0121] Step S604: Calculate the difference between the number of units deviation value and the number of units adjustment value and use it as the number of units idle value.

[0122] Among them, the idle value of the number of units refers to the number of units corresponding to the stop of the water pump. When the number adjustment value is less than the adjustment reference value, it means that the number of units can be adjusted at this time. Therefore, the difference between the number deviation value and the number adjustment value is calculated and used as the idle value of the number of units for subsequent use.

[0123] Step S605: based on the idle value of the number of pumps, the number of pumps started and stopped is updated to form a new number of pumps started and stopped.

[0124] Among them, the idle value of the number of pumps is used to update the number of pump starts and stops, so that the number of running pumps corresponding to the idle value of the number of pumps started and stopped is reduced by the number of pumps started and stopped, and a new number of pumps started and stopped is formed, thereby improving the accuracy of the obtained number of pumps started and stopped.

[0125] Step S606: Continue to output the number of water pump starts and stops and the water pump operation frequency.

[0126] Among them, when the number adjustment value is not less than the adjustment reference value, it means that the number cannot be adjusted at this time, so the number of pumps started and stopped and the water pump operation frequency continue to be output.

[0127] The above is only a preferred embodiment of the present invention, and the protection scope of the present invention is not limited to the above embodiments. All technical solutions under the concept of the present invention belong to the protection scope of the present invention. It should be pointed out that for ordinary technicians in this technical field, some improvements and modifications without departing from the principle of the present invention should also be regarded as the protection scope of the present invention.

Claims

1. An efficient intelligent control system for refrigeration room, characterized in that: include: Computer room operating equipment (1), used for cooling; A detection device (2) for collecting the operating status of the operating equipment (1) in the machine room to form equipment operating data; An optimization analysis module (3) is used to receive equipment operation data and process it using an energy efficiency optimization algorithm model (4) to form equipment control information, and output the equipment control information to the equipment room operation equipment (1) to adjust the operation status; The energy efficiency optimization algorithm model (4) includes a load prediction sub-model (5) and a host optimization sub-model (6), wherein the load prediction sub-model (5) retrieves meteorological data and analyzes it with equipment operation data to form load prediction information, and the host optimization sub-model (6) retrieves preset host performance data and analyzes it with the load prediction information to form host control information, and uses the host control information as the equipment control information; The energy efficiency optimization algorithm model (4) also includes a hydraulic prediction sub-model (8), wherein the hydraulic prediction sub-model (8) retrieves meteorological data and analyzes it with equipment operation data to form hydraulic prediction information; The energy efficiency optimization algorithm model (4) also includes a distribution pump group optimization sub-model (9), wherein the distribution pump group optimization sub-model (9) retrieves preset water pump performance data and analyzes the load prediction information and hydraulic prediction information to form pump group control information, and adds the pump group control information to the equipment control information for updating; The analysis and processing steps of the distribution pump group optimization sub-model (9) include: Retrieve the cooling tower location point based on the cooling tower performance data; Retrieve host location points based on host performance data; Calculate the distance between the cooling tower location point and the host location point and use it as the flow demand distance value; According to the corresponding relationship between the flow demand distance value and the preset hydraulic distance influence value, the hydraulic distance influence value corresponding to the flow demand distance value is determined; Retrieving hydraulic forecast demand value based on hydraulic forecast information; Calculate the product of the hydraulic distance impact value and the hydraulic forecast demand value and use it as the hydraulic demand adjustment value; Based on the water pump performance data, retrieve the single pump hydraulic output value and single pump flow output value; The quotient between the hydraulic demand adjustment value and the hydraulic output value of a single pump is used as the number of hydraulic starts and stops; According to the correspondence between the heat dissipation demand temperature value and the preset heat dissipation demand water volume value, the heat dissipation demand water volume value corresponding to the heat dissipation demand temperature value is determined; Calculate the quotient between the required water volume for heat dissipation and the output value of a single pump and use it as the number of water volume starts and stops; The number of water pump starts and stops and the water pump operating frequency are determined based on the comparison results between the number of hydraulic starts and stops and the number of water volume starts and stops, and the number of water pump starts and stops and the water pump operating frequency are used as the pump group control information.

2. The high-efficiency refrigeration room intelligent control system according to claim 1 is characterized in that: The analysis and processing steps of the host optimization sub-model (6) include: Get the air conditioning demand temperature value; Retrieve the load-generated temperature value based on the load forecast information; Calculate the difference between the load generated temperature value and the air conditioning demand temperature value and use it as the temperature deviation value; Retrieve host parameter values ​​and host individual values ​​based on host performance data; According to the corresponding relationship between the host parameter value and the preset single adjustment temperature difference value, the single adjustment temperature difference value corresponding to the host parameter value is determined; Calculate the quotient between the temperature deviation value and the single adjusted temperature difference value and use it as the temperature difference adjustment value; According to the comparison result between the temperature difference adjustment value and the host value, the number of host start-up and stop units, the unit load rate and the outlet water temperature value are determined, and the number of host start-up and stop units, the unit load rate and the outlet water temperature value are used as the host control information.

3. The high-efficiency refrigeration room intelligent control system according to claim 2 is characterized in that: The energy efficiency optimization algorithm model (4) also includes a cooling tower optimization sub-model (7), which retrieves preset cooling tower performance data and analyzes it with load forecast information to form cooling tower control information, and adds the cooling tower control information to the equipment control information for updating.

4. The high-efficiency refrigeration room intelligent control system according to claim 3 is characterized in that: The analysis and processing steps of the cooling tower optimization sub-model (7) include: According to the corresponding relationship between the load-generated temperature value and the preset heat dissipation required temperature value, the heat dissipation required temperature value corresponding to the load-generated temperature value is determined; Retrieve cooling tower parameter values ​​and cooling tower individual values ​​based on cooling tower performance data; According to the corresponding relationship between the cooling tower parameter value and the preset single cooling water capacity value, the single cooling water capacity value corresponding to the cooling tower parameter value is determined; Determining a single cooling temperature value based on a single cooling water capacity value; Calculate the quotient between the heat dissipation requirement temperature value and the single cooling temperature value and use it as the heat dissipation requirement value; According to the comparison result between the heat dissipation demand value and the cooling tower value, the number of cooling towers started and stopped and the operating frequency of the cooling towers are determined, and the number of cooling towers started and stopped and the operating frequency of the cooling towers are used as cooling tower control information.

5. The high-efficiency refrigeration room intelligent control system according to claim 1 is characterized in that: Methods for determining the number of pump starts and stops and the pump operation frequency include: According to the corresponding relationship between the number of hydraulic start-stop units, the hydraulic demand adjustment value and the preset hydraulic operation frequency, the hydraulic operation frequency corresponding to the number of hydraulic start-stop units and the hydraulic demand adjustment value is determined; Determine whether the number of hydraulic start and stop units is greater than the number of water volume start and stop units; If yes, the hydraulic operation frequency is used as the water pump operation frequency, and the number of hydraulic starts and stops is used as the number of water pump starts and stops; If not, the hydraulic water quantity value corresponding to the number of hydraulic start and stop units is determined according to the corresponding relationship between the number of hydraulic start and stop units and the preset hydraulic water quantity value; Calculate the difference between the hydraulic water volume value and the heat dissipation demand water volume value and use it as the water volume deviation value; According to the correspondence between the water volume deviation value, the number of hydraulic start-stop units and the preset frequency water volume deviation adjustment value, the frequency water volume deviation adjustment value corresponding to the water volume deviation value and the number of hydraulic start-stop units is determined; The hydraulic operation frequency is adjusted based on the frequency water volume deviation adjustment value to form a hydraulic operation adjustment frequency, and the hydraulic operation adjustment frequency is used as the water pump operation frequency, and the number of hydraulic starts and stops is used as the number of water pump starts and stops.

6. The high-efficiency intelligent control system for refrigeration room according to claim 5 is characterized in that: The method also includes the following steps after the hydraulic operation adjustment frequency is used as the water pump operation frequency and the hydraulic start and stop number is used as the water pump start and stop number, which are as follows: According to the correspondence between the hydraulic operation adjustment frequency and the preset adjustment frequency single pump energy consumption value, the adjustment frequency single pump energy consumption value corresponding to the hydraulic operation adjustment frequency is determined; According to the corresponding relationship between the hydraulic operation frequency and the preset hydraulic frequency single pump energy consumption value, the hydraulic frequency single pump energy consumption value corresponding to the hydraulic operation frequency is determined; Calculate the difference between the energy consumption value of a single pump with an adjustment frequency and the energy consumption value of a single pump with a hydraulic frequency and use it as the energy consumption deviation value; Calculate the quotient between the energy consumption value of a single hydraulic frequency pump and the energy consumption deviation value and use it as the number of units required for energy consumption deviation; Calculate the difference between the number of hydraulic start-stop units and the number of water volume start-stop units and use it as the unit deviation value; Determine whether the number of units required for energy consumption deviation is greater than the number deviation value; If yes, continue to output the water pump operating frequency and the number of water pump starts and stops; If not, the hydraulic operation frequency will be used as the water pump operation frequency, and the number of water volume starts and stops will be used as the number of water pump starts and stops.

7. The high-efficiency refrigeration room intelligent control system according to claim 1 is characterized in that: The energy efficiency optimization algorithm model (4) also includes an air conditioning terminal optimization sub-model (10), which retrieves preset air conditioning terminal performance data and analyzes it with load prediction information and hydraulic prediction information to form air conditioning terminal control information, and adds the air conditioning terminal control information to the equipment control information for updating.

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