CN114025575A - Refrigeration method using natural cold source, energy-saving system and storage medium - Google Patents
Refrigeration method using natural cold source, energy-saving system and storage medium Download PDFInfo
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Abstract
The embodiment of the application provides a refrigeration method, an energy-saving system and a storage medium by using a natural cold source, the current critical wet bulb temperature is calculated according to the obtained current IT equipment load of a data center and basic parameters of a refrigeration system, when the current outdoor wet bulb temperature is less than the current critical wet bulb temperature, then the predicted outdoor wet bulb temperature after the first preset time is obtained through the prediction of an environment parameter model obtained through pre-training, when the predicted outdoor wet bulb temperature after the first preset time is also less than the current critical wet bulb temperature, which indicates that the starting condition of refrigeration by using the natural cold source is reached, the energy-saving system sends a message for starting the natural refrigeration mode to the refrigeration system to instruct the refrigeration system to start the natural refrigeration mode, so that the critical wet bulb temperature of the starting condition of the natural refrigeration mode is dynamically adjusted according to the actual IT equipment load of the data center, the actual condition of the data center is considered, the utilization of the natural cold source is realized to the maximum extent, and the usable time of the natural cold source is also increased.
Description
Technical Field
The present disclosure relates to refrigeration technologies, and in particular, to a refrigeration method using a natural cold source, an energy saving system, and a storage medium.
Background
With the rapid development of technologies such as big data and industrial internet, the quantity and the scale of the data center are gradually increased, the machine room of the data center needs to be refrigerated all year round, the machine room can be refrigerated through different heating and ventilation systems, and the temperature of the machine room is reduced, so that equipment is protected better.
At present, a common heating and ventilation system comprises an air-cooled air conditioner, a freezing water system and a water side natural cooling system, wherein in the water side natural cooling system, a water chilling unit is normally started to refrigerate in summer, and in other seasons, cooling water of a cooling tower and freezing water in the tail end of the air conditioner exchange heat through a plate heat exchanger, so that natural cooling is realized, and compared with the air-cooled air conditioner and the freezing water system, the energy consumption is greatly reduced.
However, in the water side indirect natural cooling technology, the natural cooling starting condition is greatly restricted, and the outdoor wet bulb temperature is continuously less than the critical wet bulb temperature for 1 hour and 6 ℃ for starting, so that the natural cold source is not utilized to the maximum extent under the condition, and the energy waste is caused.
Disclosure of Invention
The application provides a refrigeration method, an energy-saving system and a storage medium by utilizing a natural cold source, which are used for solving the problem of energy waste caused by large restriction on the starting condition of natural cooling of a water side indirect natural cooling technology.
In a first aspect, the present application provides a refrigeration method using a natural cold source, comprising:
acquiring the load of the current information technology IT equipment of the data center and basic parameters of a refrigeration system;
calculating the current critical wet bulb temperature according to the current IT equipment load and the basic parameters;
when the current outdoor wet bulb temperature is lower than the current critical wet bulb temperature, inputting the environmental parameters after the first preset time into an environmental parameter model obtained by pre-training to predict and obtain the predicted outdoor wet bulb temperature after the first preset time;
and when the predicted outdoor wet bulb temperature after the first preset time is less than the current critical wet bulb temperature, sending a natural refrigeration mode starting message to the refrigeration system, wherein the natural refrigeration mode starting message is used for indicating the refrigeration system to start a natural refrigeration mode.
Optionally, the calculating a current critical wet bulb temperature according to the current IT equipment load and the basic parameter includes:
calculating the current critical wet bulb temperature according to the following critical wet bulb temperature formula:
wherein, TmaxIs the current critical wet bulb temperature, Q1For the current IT equipment load, the basic parameters are: t is1For air-conditioning the ambient temperature of the cold channel, Q2For distributing loads, Q3Is the building load, L is the sum of the flow of the chilled water main, T2For heat exchange temperature difference, T, of plate heat exchangers3The cooling tower approach and K is the mass flow coefficient.
Optionally, before sending a message to start a natural cooling mode to the cooling system when the predicted outdoor wet bulb temperature after the first preset time is less than the current critical wet bulb temperature, the method further includes:
inputting the power-on and power-off data of the equipment after the second preset time into an IT equipment load prediction model obtained by pre-training to predict the IT equipment load of the data center after the second preset time, wherein the second preset time is longer than the first preset time;
calculating the critical wet bulb temperature after the second preset time according to the IT equipment load after the second preset time and the basic parameters;
inputting the environmental parameters after the second preset time into the environmental parameter model to predict the outdoor wet bulb temperature after the second preset time;
the sending a message to the refrigeration system to turn on a natural cooling mode includes:
and when the predicted outdoor wet bulb temperature after the second preset time is less than the critical wet bulb temperature after the second preset time, sending the message of starting the natural refrigeration mode to the refrigeration system.
Optionally, the method further includes:
acquiring first training data, wherein the first training data comprise historical environmental parameters and temperature labels, and the temperature labels are used for describing outdoor wet bulb temperatures under corresponding environmental parameters;
and training a first preset model according to the first training data to obtain the environment parameter model. Optionally, the method further includes:
acquiring second training data, wherein the second training data comprises historical equipment power-on and power-off data and a load label, and the load label is used for describing IT equipment loads corresponding to the equipment power-on and power-off data;
and training a second preset model according to the second training data to obtain the IT equipment load prediction model.
In a second aspect, the present application provides an energy saving system comprising:
the system comprises an acquisition module, a data center and a control module, wherein the acquisition module is used for acquiring the load of the current information technology IT equipment of the data center and the basic parameters of a refrigeration system;
the calculation module is used for calculating the current critical wet bulb temperature according to the current IT equipment load and the basic parameters;
the prediction module is used for inputting the environmental parameters after the first preset time into an environmental parameter model obtained by pre-training to predict and obtain the predicted outdoor wet bulb temperature after the first preset time when the current outdoor wet bulb temperature is less than the current critical wet bulb temperature;
and the sending module is used for sending a natural refrigeration mode starting message to the refrigeration system when the predicted outdoor wet bulb temperature after the first preset time is less than the current critical wet bulb temperature, wherein the natural refrigeration mode starting message is used for indicating the refrigeration system to start a natural refrigeration mode.
Optionally, the calculation module is specifically configured to:
calculating the current critical wet bulb temperature according to the following critical wet bulb temperature formula:
wherein, TmaxIs the current critical wet bulb temperature, Q1For the current IT equipment load, the basic parameters are: t is1For air-conditioning the ambient temperature of the cold channel, Q2For distributing loads, Q3Is the building load, L is the sum of the flow of the chilled water main, T2For heat exchange temperature difference, T, of plate heat exchangers3The cooling tower approach and K is the mass flow coefficient.
Optionally, the sending module is specifically configured to:
inputting the power-on and power-off data of the equipment after the second preset time into an IT equipment load prediction model obtained by pre-training to predict the IT equipment load of the data center after the second preset time, wherein the second preset time is longer than the first preset time;
calculating the critical wet bulb temperature after the second preset time according to the IT equipment load after the second preset time and the basic parameters;
inputting the environmental parameters after the second preset time into the environmental parameter model to predict the outdoor wet bulb temperature after the second preset time;
the sending a message to the refrigeration system to turn on a natural cooling mode includes:
and when the predicted outdoor wet bulb temperature after the second preset time is less than the critical wet bulb temperature after the second preset time, sending the message of starting the natural refrigeration mode to the refrigeration system.
The application provides a refrigeration method, an energy-saving system and a storage medium using a natural cold source, wherein the current critical wet bulb temperature is calculated according to the obtained current IT equipment load of a data center and basic parameters of a refrigeration system, when the current outdoor wet bulb temperature is less than the current critical wet bulb temperature, then the predicted outdoor wet bulb temperature after the first preset time is obtained through the prediction of an environment parameter model obtained through pre-training, namely the outdoor wet bulb temperature after the first preset time is obtained in advance, when the predicted outdoor wet bulb temperature after the first preset time is also less than the current critical wet bulb temperature, which indicates that the starting condition of refrigeration by using the natural cold source is reached, the energy-saving system sends a message for starting the natural refrigeration mode to the refrigeration system to instruct the refrigeration system to start the natural refrigeration mode, so that the critical wet bulb temperature of the starting condition of the natural refrigeration mode is dynamically adjusted according to the actual IT equipment load of the data center, the actual condition of the data center is considered, the utilization of the natural cold source is realized to the maximum extent, the outdoor wet bulb temperature after the first preset time is predicted in advance, and the available time of the natural cold source is prolonged.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and together with the description, serve to explain the principles of the application.
Fig. 1 is a schematic diagram of an application scenario in which the present application is applicable;
fig. 2 is a schematic flow chart illustrating a refrigeration method using a natural cold source according to an embodiment of the present application;
fig. 3 is a schematic flow chart illustrating a refrigeration method using a natural cold source according to a second embodiment of the present application;
fig. 4 is a signaling flowchart of a refrigeration method using a natural cold source according to a third embodiment of the present application;
fig. 5 is a schematic structural diagram of an energy saving system according to a fourth embodiment of the present application;
fig. 6 is a schematic structural diagram of an energy saving system according to a fifth embodiment of the present invention.
With the above figures, there are shown specific embodiments of the present application, which will be described in more detail below. These drawings and written description are not intended to limit the scope of the inventive concepts in any manner, but rather to illustrate the inventive concepts to those skilled in the art by reference to specific embodiments.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.
At present, a common heating and ventilation system is provided with an air-cooled air conditioner, a freezing water system and a water side natural cooling system, the water side natural cooling system at least comprises an air conditioner tail end, a cooling tower, a water chilling unit and a plate heat exchanger, and the system has two realization modes: the water side direct natural cooling technology and the water side indirect natural cooling technology are characterized in that in the water side indirect natural cooling technology, a water chilling unit is normally started to refrigerate in summer, and cooling water of a cooling tower and chilled water in the tail end of an air conditioner are used for heat exchange through a plate heat exchanger in other seasons, so that natural cooling is achieved, and compared with an air-cooled air conditioner and a chilled water system, energy consumption is greatly reduced. However, in the water side indirect natural cooling technology, the natural cooling start condition is greatly restricted, and the outdoor wet bulb temperature needs to be continuously less than the critical wet bulb temperature for 1 hour and 6 ℃ for starting, and the start condition is also limited by a plurality of factors of the whole refrigeration system, and the geographic positions and the load conditions of all data centers are different, so that the natural cold source cannot be utilized to the maximum extent by the fixed start condition, and the energy waste is caused.
In order to solve the above problems in the prior art, the refrigeration method energy-saving system and the storage medium using the natural cold source provided by the application determine the opening condition of the natural refrigeration mode by combining the actual IT equipment load of the data center, and predict the outdoor wet bulb temperature after the first preset time in advance to judge whether the opening condition is met, so that the utilization of the natural cold source is realized to the maximum extent, and the available time of the natural cold source is also increased.
Fig. 1 is a schematic diagram of an application scenario to which the present application is applied. As shown in fig. 1, the refrigeration system 101 and the economizer system 102 communicate information via the internet. The energy-saving system 102 determines a starting condition for refrigeration by using a natural cold source according to the received actual IT equipment load sent by the data center moving loop monitoring system and the basic parameters of the refrigeration system sent by the refrigeration system, judges whether the natural refrigeration mode can be started or not, and when the condition is met, the energy-saving system 102 sends a message corresponding to the judgment result to the refrigeration system 101 so that the refrigeration system 101 starts the natural refrigeration mode according to the message. It is understood that the number of the refrigeration systems 101 and the economizer system 102 can be plural, and are not shown in the figure.
The following describes the technical solutions of the present application and how to solve the above technical problems with specific embodiments. The following embodiments may exist independently or in combination, and the same or similar concepts or processes may not be described in detail in some embodiments. Embodiments of the present application will be described below with reference to the accompanying drawings.
Referring to fig. 2, fig. 2 is a schematic flow chart of a refrigeration method using a natural cold source according to an embodiment of the present application, where the method may be performed by an economizer system, and the method includes the following steps.
S201, acquiring the current IT equipment load of the data center and basic parameters of a refrigeration system.
In seasons with low air temperature, a refrigeration system of a data center generally utilizes a natural cold source to cool a machine room of the data center, and a refrigeration method utilizing the natural cold source can be understood as a process of discharging heat from an object to an environment medium through heat transfer modes such as heat exchange and convection, reducing the temperature of the object, and finally achieving the spontaneity same as the environment temperature.
The current IT equipment load can be acquired by a data center dynamic loop monitoring system and sent to an energy-saving system, and the basic parameters of the refrigeration system are sent to the energy-saving system by the refrigeration system. The IT equipment load refers to the sum of electric power consumed by various types of equipment of a data center at a certain moment, the unit can be KW (kilowatt), and basic parameters of a refrigeration system comprise: the method comprises the following steps of air conditioner cold channel environment temperature, power distribution load, building load, sum of flow of a chilled water main pipe, plate heat exchanger heat exchange temperature difference and cooling tower approximation degree.
The environment temperature of the cold channel of the air conditioner can be set to be a proper temperature of a machine room, for example, 25 ℃, the power distribution load is the power loss of a power distribution link of the data center, and the unit can be KW.
The building load is the heat loss of a data center building, the unit can be KW, and the heat exchange temperature difference of the plate heat exchanger is generally the difference between the hot end outlet water temperature and the cold end outlet water temperature.
The temperature difference between heat exchanges of the plate heat exchanger is generally a constant value, for example 1 ℃.
The cooling tower approach is the difference between the temperature of the water cooled by the cooling tower and the ambient wet bulb temperature, and is typically a fixed value, such as 5 ℃.
The building load can be calculated by the following formula: q10.07 × S, wherein Q1And S is the sum of the area of the machine room input by the data center.
The sum of the flow rates of the chilled water main pipes can be calculated by the following formula:
wherein, XijOpening of a certain air conditioner water valve of a certain type of air conditioner in data center, AiThe water flow of the air conditioner of the model is n, the number of the air conditioner models of the machine room of the data center is n, and the number of the air conditioners of a certain model of the machine room of the data center is m.
For example, the air conditioner models of the machine rooms of the data center are P2080 and P2110, and the sum of the flow rates of the chilled water main of the refrigeration system of the data center is the sum of the water valve opening degrees of the air conditioners of the P2080 model multiplied by the water flow rate of the air conditioners of the P2080 model, and the sum of the water valve opening degrees of the air conditioners of the P2110 model multiplied by the water flow rate of the air conditioners of the P2110 modelThe water flow of the air conditioner is that when the sum of the water valve opening degrees of the air conditioners in the P2080 models is 2, the sum of the water valve opening degrees of the air conditioners in the P2110 models is 1.5, and the water flow of the air conditioners in the P2080 models is 13.68m3Water flow rate of 18 m/h (cubic meter/hour) for air conditioner model P21103And h, the sum of the flow rates of the chilled water main of the refrigerating system of the data center is 2 multiplied by 13.68 and 1.5 multiplied by 18 which is 54.36m3/h。
S202, calculating the current critical wet bulb temperature according to the current IT equipment load and the basic parameters.
In order to utilize a natural cold source to the maximum extent, that is, to set a condition for starting a natural cooling mode at present by combining with an actual situation of a data center, a current critical wet bulb temperature is calculated according to an acquired current IT equipment load and a basic parameter, and the following formula is used:
wherein, TmaxIs the current critical wet bulb temperature, Q1For the current IT equipment load, T1For air-conditioning the ambient temperature of the cold channel, Q2For distributing loads, Q3Is the building load, L is the sum of the flow of the chilled water main, T2For heat exchange temperature difference, T, of plate heat exchangers3For the cooling tower approximation degree, K is a mass flow coefficient and can be a fixed value of 1.163.
Exemplary, Q when data center1Is 260KW, T1At 25 ℃ Q2Is 6KW, Q3134.6KW, L54.36 m3/h，T2At 1 ℃ and T3At 5 deg.C, K is 1.163, and the calculated current critical wet bulb temperature is 11.3 deg.C.
S203, when the current outdoor wet bulb temperature is smaller than the current critical wet bulb temperature, inputting the environmental parameters after the first preset time into an environmental parameter model obtained by pre-training to predict the predicted outdoor wet bulb temperature after the first preset time.
After the current critical wet bulb temperature is obtained, whether the current outdoor wet bulb temperature is smaller than the current critical wet bulb temperature or not is judged, the current outdoor wet bulb temperature is measured by a building equipment automatic control system, when the current outdoor wet bulb temperature is smaller than the current critical wet bulb temperature, one of conditions for starting a natural refrigeration mode of a refrigeration system of a data center is met, in order to increase the available time of a natural cold source, namely, the outdoor wet bulb temperature does not need to be measured after waiting for the first preset time, environmental parameters after the first preset time, namely weather, temperature, humidity, wind power, wind direction, air pressure, air pollution and altitude, can be input into an environmental parameter model obtained through pre-training, and the predicted outdoor wet bulb temperature after the first preset time is obtained through prediction.
The environment parameter model is obtained by training a first preset model according to first training data, the first training data comprise historical environment parameters and temperature tags, the historical environment parameters comprise weather, temperature, humidity, wind power, wind direction, air pressure, air pollution and altitude, the temperature tags are used for describing outdoor wet bulb temperature under the corresponding environment parameters, and exemplarily, the energy-saving system obtains the historical environment parameters of nearly 1 year through a historical data interface provided by a local meteorological station server of a data center: weather, temperature, humidity, wind power, wind direction, atmospheric pressure, air pollution and height above sea level still include the timestamp among the environmental parameter, and economizer system receives the outdoor wet bulb temperature of history that the timestamp corresponds among the historical environmental parameter that building equipment autonomous system sent, then generates first training data according to historical environmental parameter and the outdoor wet bulb temperature of history.
For example, the energy saving system obtains the environmental parameters after 1 hour, namely weather, temperature, humidity, wind power, wind direction, air pressure, air pollution and altitude, by calling a prediction data interface provided by a local weather station server of the data center, and inputs the parameters into an environmental parameter model, namely the obtained value of the outdoor wet bulb temperature after 1 hour.
And S204, when the predicted outdoor wet bulb temperature after the first preset time is less than the current critical wet bulb temperature, sending a message of starting a natural refrigeration mode to the refrigeration system.
When the predicted outdoor wet bulb temperature after the first preset time is less than the current critical wet bulb temperature, for example, when the predicted outdoor wet bulb temperature after 1 hour is less than the current critical wet bulb temperature, it indicates that the outdoor wet bulb temperature will be less than the current critical wet bulb temperature for 1 hour continuously, and the start condition of the natural cooling mode is met, the energy saving system sends a message of starting the natural cooling model to the cooling system, and instructs the cooling system to start the natural cooling mode.
In the embodiment, the current critical wet bulb temperature is calculated according to the obtained current IT equipment load of the data center and basic parameters of the refrigeration system, when the current outdoor wet bulb temperature is lower than the current critical wet bulb temperature, then the environment parameters after the first preset time are input into an environment parameter model obtained by pre-training to predict the predicted outdoor wet bulb temperature after the first preset time, namely the outdoor wet bulb temperature after the first preset time is obtained in advance, when the predicted outdoor wet bulb temperature after the first preset time is also lower than the current critical wet bulb temperature, which indicates that the starting condition of refrigeration by using a natural cold source is reached, the energy-saving system sends a message for starting the natural refrigeration mode to the refrigeration system to instruct the refrigeration system to start the natural refrigeration mode, so that the critical wet bulb temperature of the starting condition of the natural refrigeration mode is dynamically adjusted according to the actual IT equipment load of the data center, the practical situation of the data center is considered, the utilization of the natural cold source is realized to the maximum extent, and the available time of the natural cold source is also increased.
In the above embodiment, when both the current outdoor wet bulb temperature and the outdoor wet bulb temperature after the first preset time are less than the current critical wet bulb temperature, the natural refrigeration mode may be started, and considering that the critical wet bulb temperature of the present application is determined according to the real-time IT equipment load of the data center, the outdoor wet bulb temperature after the first preset time is also obtained through the prediction model, in order to make the setting of the starting condition of the present application more accurate and better meet the actual situation of the data center, the natural refrigeration mode may be further determined whether to be started by judging the magnitudes of the predicted outdoor wet bulb temperature after the second preset time and the critical wet bulb temperature after the second preset time. The following describes the setting of the condition for turning on the natural cooling mode in the embodiment.
Referring to fig. 3, fig. 3 is a schematic flow chart of a refrigeration method using a natural cold source according to a second embodiment of the present application, where the present embodiment further illustrates a condition for starting a natural refrigeration mode on the basis of the first embodiment, and the method may be executed by an energy saving system, and includes the following steps.
S301, inputting the power-on and power-off data of the equipment after the second preset time into an IT equipment load prediction model obtained through pre-training to predict the IT equipment load of the data center after the second preset time.
The equipment power-on and power-off data after the second preset time comprises the number of racks, the number of equipment, the type of equipment, rated power consumption of the equipment and floor area of the equipment.
In the above embodiment, when the predicted outdoor wet bulb temperature after the first preset time is less than the current critical wet bulb temperature, before the economizer system sends the message of turning on the natural cooling mode to the refrigeration system, the IT equipment load after the second preset time may also be predicted by the IT equipment load prediction model, and is used to calculate the critical wet bulb temperature after the second preset time, where the second preset time is greater than the first preset time, that is, the second preset time is after the first preset time.
The IT equipment load prediction model is obtained by training a second preset model according to second training data, the second training data include historical equipment power-on and power-off data and load labels, the historical equipment power-on and power-off data include rack number, equipment type, equipment rated power consumption and equipment floor area, the load labels are used for describing IT equipment loads corresponding to the equipment power-on and power-off data, and exemplarily, the energy-saving system receives the IT equipment loads and the corresponding historical equipment power-on and power-off data of nearly 1 year sent by the moving-loop monitoring system: the number of the racks, the number of the devices, the types of the devices, the rated power consumption of the devices and the occupied area of the devices, and second training data are generated according to historical device power-on and power-off data and IT device loads.
For example, the energy saving system may obtain the power on/off data of the equipment after 24 hours, that is, the number of racks, the number of equipment, the type of equipment, the rated power consumption of the equipment, and the floor area of the equipment, through an interface provided by the moving loop monitoring system, and input the data into an IT equipment load prediction model, that is, an available predicted value of the IT equipment load after 24 hours.
And S302, calculating the critical wet bulb temperature after the second preset time according to the IT equipment load and the basic parameters after the second preset time.
The critical wet bulb temperature after the second preset time can be calculated through the formula (1) in the first embodiment, that is, the sum of the ambient temperature of the cold channel of the air conditioner, the distribution load, the building load, the flow of the chilled water main pipe, the heat exchange temperature difference of the plate heat exchanger and the approximation degree of the cooling tower are obtained, K is the mass flow coefficient, and the IT equipment load after the second preset time is substituted into the formula (1), so that the critical wet bulb temperature after the second preset time is obtained.
And S303, inputting the environmental parameters after the second preset time into the environmental parameter model to predict the outdoor wet bulb temperature after the second preset time.
The energy-saving system obtains the environmental parameters after the second preset time, namely weather, temperature, humidity, wind power, wind direction, air pressure, air pollution and altitude, by calling a prediction data interface provided by a local meteorological station server of the data center, and inputs the data into an environmental parameter model, namely the value of the outdoor wet bulb temperature after the second preset time can be obtained.
S304, when the predicted outdoor wet bulb temperature after the second preset time is less than the critical wet bulb temperature after the second preset time, sending a message of starting a natural refrigeration mode to the refrigeration system.
Illustratively, when the predicted outdoor wet bulb temperature after 24 hours is less than the critical wet bulb temperature after 24 hours, the natural cooling mode is determined to be started, so that the starting condition of the natural cooling mode is more accurate for the actual situation of the data center.
In this embodiment, on the basis of the first embodiment, the power-on and power-off data of the device after the second preset time is input into the IT device load prediction model obtained through pre-training to predict the IT device load of the data center after the second preset time, the critical wet bulb temperature after the second preset time is obtained through calculation according to the IT device load and the basic parameters of the data center, and when the predicted outdoor wet bulb temperature after the second preset time is less than the critical wet bulb temperature after the second preset time, the energy saving system sends a message for starting the natural cooling mode to the cooling system of the data center to instruct the cooling system to start the natural cooling mode, so that the setting of the starting condition of the application is more accurate, and the actual situation of the data center is more met.
Referring to fig. 4, fig. 4 is a signaling flowchart of a cooling method using a natural cold source according to a third embodiment of the present application, and this embodiment describes in detail an interaction process between devices based on the first embodiment and the second embodiment, as shown in fig. 4, the method of this embodiment includes the following steps.
S401, the weather station server sends historical environment parameters to the energy-saving system.
The energy saving system sends a historical environmental parameter request message to the weather station server, which may include a time, such as 1 year, and the weather station server sends the historical environmental parameters for 1 year to the energy saving system based on the time.
For example, the energy saving system may send the historical environmental parameter request message to the weather station server by calling a historical data interface of the weather station server.
The historical environmental parameters include: weather, temperature, humidity, wind direction, air pressure, air pollution and altitude.
S402, the building equipment automatic control system sends the historical outdoor wet bulb temperature to the energy-saving system.
The historical environmental parameters also comprise timestamps, optionally, the energy-saving system can send historical outdoor wet bulb temperature request messages to the building equipment automatic control system, the request messages comprise timestamps corresponding to the historical environmental parameters, and the refrigerating system sends the historical outdoor wet bulb temperatures corresponding to the timestamps to the energy-saving system according to the timestamps.
The refrigeration system can also actively send the historical outdoor wet bulb temperature and the corresponding timestamp to the energy-saving system, and the energy-saving system selects the historical outdoor wet bulb temperature corresponding to the timestamp in the historical environment parameters according to the received historical outdoor wet bulb temperature.
And S403, generating first training data by the energy-saving system according to the historical environmental parameters and the outdoor wet bulb temperature, and training a first preset model by using the first training data to obtain an environmental parameter model.
The first training data includes historical environmental parameters and a temperature label describing outdoor wet bulb temperature at the corresponding environmental parameters.
S404, the dynamic loop monitoring system sends historical equipment power-on and power-off data and corresponding IT equipment loads to the energy-saving system.
Optionally, the energy saving system may send a historical device power-on and power-off data request message to the dynamic loop monitoring system, where the request message may include time, for example, 1 year, and the dynamic loop monitoring system sends historical device power-on and power-off data within 1 year to the energy saving system according to the time, or the dynamic loop monitoring system may actively send historical device power-on and power-off data within 1 year to the energy saving system.
The historical device power-on and power-off data comprises: the number of racks, the number of devices, the type of devices, the rated power consumption of the devices, and the floor space of the devices.
S405, the energy-saving system generates second training data according to the historical equipment power-on and power-off data and the IT equipment load, and trains a second preset model by using the second training data to obtain an IT equipment load prediction model.
The second training data includes historical device power-up and power-down data and a load label describing a load of the IT device.
And S406, the refrigerating system sends basic parameters of the refrigerating system to the energy-saving system.
Optionally, the energy saving system may send a basic parameter request message of the refrigeration system to the refrigeration system, and the refrigeration system sends the basic parameter of the refrigeration system to the energy saving system according to the request message, or the refrigeration system may actively send the basic parameter of the refrigeration system to the energy saving system.
The basic parameters comprise the ambient temperature of an air conditioner cold channel, the distribution load, the building load, the sum of the flow of a chilled water main pipe, the heat exchange temperature difference of the plate heat exchanger and the approximation degree of the cooling tower, and the basic parameters are used for calculating the critical wet bulb temperature.
S407, the dynamic loop monitoring system sends the current IT equipment load to the energy-saving system.
Optionally, the energy saving system may send a current IT device load request message to the dynamic loop monitoring system, and the dynamic loop monitoring system sends the current IT device load to the energy saving system according to the request message, or the dynamic loop monitoring system may actively send the current IT device load to the energy saving system.
It is understood that step S406 and step S407 are not performed sequentially.
And S408, the energy-saving system calculates the current critical wet bulb temperature according to the current IT equipment load and the basic parameters.
The current critical wet bulb temperature can be calculated by equation (1) in example one.
And S409, the building equipment automatic control system sends the current outdoor wet bulb temperature to the energy-saving system.
Optionally, the energy saving system may send a current outdoor wet bulb temperature request message to the building equipment automatic control system, and the building equipment automatic control system sends the current outdoor wet bulb temperature to the energy saving system according to the request message, or the building equipment automatic control system may actively send the current IT equipment load to the energy saving system.
S410, the energy-saving system judges whether the current outdoor wet bulb temperature is less than the current critical wet bulb temperature.
When the current outdoor wet bulb temperature is less than the current critical wet bulb temperature, step S411 is executed.
And when the current outdoor wet bulb temperature is not less than the current critical wet bulb temperature, not executing any step.
S411, the weather station server sends the environmental parameters after the first preset time to the energy-saving system
The energy-saving system sends an environmental parameter request message after the first preset time to the weather station server, and the weather station server sends the environmental parameter after the first preset time to the energy-saving system according to the time.
For example, the energy saving system may send the environmental parameter request message after the first preset time to the weather station server by calling a forecast data interface of the weather station server.
The environmental parameters include: weather, temperature, humidity, wind direction, air pressure, air pollution and altitude.
S412, inputting the environmental parameters after the first preset time into an environmental parameter model to obtain the predicted outdoor wet bulb temperature after the first preset time.
And S413, judging whether the outdoor wet bulb temperature after the first preset time is less than the current critical wet bulb temperature by the energy-saving system.
When the outdoor wet bulb temperature after the first preset time is less than the current critical wet bulb temperature, step S414 is executed.
And when the outdoor wet bulb temperature after the first preset time is not less than the current critical wet bulb temperature, not executing any step.
And S414, the dynamic loop monitoring system sends the equipment power-on and power-off data after the second preset time to the energy-saving system.
Optionally, the energy saving system may send a device power-on and power-off data request message after the second preset time to the moving loop monitoring system, and the moving loop monitoring system sends the device power-on and power-off data after the second preset time to the energy saving system according to the request message, or the moving loop monitoring system actively sends the device power-on and power-off data after the second preset time to the energy saving system.
The device power-on and power-off data comprises the number of racks, the number of devices, the type of devices, the rated power consumption of the devices and the occupied area of the devices.
And S415, inputting the power-on and power-off data of the equipment after the second preset time into the IT equipment load prediction model by the energy-saving system to obtain the IT equipment load after the second preset time.
And S416, the weather station server sends the environmental parameters after the second preset time to the energy-saving system.
And the energy-saving system sends the environmental parameter request message after the second preset time to the weather station server, and the weather station server sends the environmental parameter after the first preset time to the energy-saving system according to the time.
For example, the energy saving system may send the environmental parameter request message after the second preset time to the weather station server by calling a forecast data interface of the weather station server.
The energy-saving system acquires the environmental parameters after the second preset time by calling an interface of the weather station server, wherein the environmental parameters comprise: weather, temperature, humidity, wind direction, air pressure, air pollution and altitude.
And S417, inputting the environmental parameters after the second preset time into an environmental parameter model to obtain the predicted outdoor wet bulb temperature after the second preset time.
S418, the energy-saving system judges whether the outdoor wet bulb temperature after the second preset time is less than the critical wet bulb temperature after the second preset time.
When the outdoor wet bulb temperature after the second preset time is less than the critical wet bulb temperature after the second preset time, step S419 is performed.
And when the outdoor wet bulb temperature after the first preset time is not less than the current critical wet bulb temperature, not executing any step.
S419, the energy-saving system sends a message of starting a natural cooling mode to the cooling system.
The natural cooling mode on message is used to instruct the refrigeration system to turn on the natural cooling mode.
In the embodiment, the current critical wet bulb temperature is calculated according to the obtained current IT equipment load of the data center and basic parameters of the refrigeration system, when the current outdoor wet bulb temperature is lower than the current critical wet bulb temperature, then the environmental parameters after the first preset time are input into an environmental parameter model obtained by pre-training to predict and obtain the predicted outdoor wet bulb temperature after the first preset time, when the predicted outdoor wet bulb temperature after the first preset time is also lower than the current critical wet bulb temperature, then the critical wet bulb temperature after the second preset time is calculated according to the predicted IT equipment load after the second preset time and the basic parameters of the data center, when the predicted outdoor wet bulb temperature after the second preset time is lower than the critical wet bulb temperature after the second preset time, which indicates that the starting condition of refrigeration by using a natural cold source is achieved, the energy-saving system sends a message for starting a natural refrigeration mode to the refrigeration system of the data center, the refrigeration system is instructed to start the natural refrigeration mode, so that the critical wet bulb temperature of the starting condition of the natural refrigeration mode is dynamically adjusted according to the actual IT equipment load of the data center, the actual condition of the data center is considered, the utilization of a natural cold source is realized to the greatest extent, and the available time of the natural cold source is prolonged.
Referring to fig. 5, fig. 5 is a schematic structural diagram of an energy saving system according to a fourth embodiment of the present application. As shown in fig. 5, the economizer system 50 includes: an acquisition module 501, a calculation module 502, a prediction module 503, and a sending module 504.
The obtaining module 501 is configured to obtain a load of a current information technology IT device of the data center and basic parameters of the refrigeration system.
The calculating module 502 is configured to calculate the current critical wet bulb temperature according to the current IT equipment load and the basic parameters.
The predicting module 503 is configured to, when the current outdoor wet bulb temperature is lower than the current critical wet bulb temperature, input the environmental parameter after the first preset time into an environmental parameter model obtained through pre-training to predict the predicted outdoor wet bulb temperature after the first preset time.
The sending module 504 is configured to send a natural cooling mode starting message to the refrigeration system when the predicted outdoor wet bulb temperature after the first preset time is less than the current critical wet bulb temperature, where the natural cooling mode starting message is used to instruct the refrigeration system to start a natural cooling mode.
Optionally, the calculating module 502 is specifically configured to:
calculating the current critical wet bulb temperature according to the following critical wet bulb temperature formula:
wherein, TmaxIs the current critical wet bulb temperature, Q1For the current IT equipment load, the basic parameters are: t is1For air-conditioning the ambient temperature of the cold channel, Q2For distributing loads, Q3For building load, L is the flow rate of the main chilled water pipeAnd, T2For heat exchange temperature difference, T, of plate heat exchangers3The cooling tower approach and K is the mass flow coefficient.
Optionally, the sending module 504 is specifically configured to:
and inputting the power-on and power-off data of the equipment after the second preset time into an IT equipment load prediction model obtained by pre-training to predict the IT equipment load of the data center after the second preset time, wherein the second preset time is longer than the first preset time.
And calculating the critical wet bulb temperature after the second preset time according to the IT equipment load and the basic parameters after the second preset time.
And inputting the environmental parameters after the second preset time into the environmental parameter model to predict the outdoor wet bulb temperature after the second preset time.
Sending a natural cooling mode on message to a refrigeration system, comprising:
and when the predicted outdoor wet bulb temperature after the second preset time is less than the critical wet bulb temperature after the second preset time, sending a message for starting the natural refrigeration mode to the refrigeration system.
Optionally, the method further includes: acquiring first training data, wherein the first training data comprise historical environmental parameters and temperature labels, and the temperature labels are used for describing outdoor wet bulb temperatures under the corresponding environmental parameters.
And training the first preset model according to the first training data to obtain an environment parameter model.
Optionally, the method further includes: and acquiring second training data, wherein the second training data comprises historical equipment power-on and power-off data and a load label, and the load label is used for describing IT equipment loads corresponding to the equipment power-on and power-off data.
And training the second preset model according to the second training data to obtain an IT equipment load prediction model.
The energy saving system of this embodiment may be configured to perform the steps of the refrigeration method using a natural cold source in any one of the first to third embodiments, and the specific implementation manner and the technical effect are similar, and are not described herein again.
Fig. 6 is a schematic structural diagram of an energy saving system according to a fifth embodiment of the present invention, and as shown in fig. 6, the system 60 includes: the processor 601, the memory 602, the transceiver 603, and the memory 602 are configured to store instructions, the transceiver 603 is configured to communicate with other devices, and the processor 601 is configured to execute the instructions stored in the memory, so that the energy saving system 60 executes the steps of the refrigeration method using a natural cold source as in any one of the first to third embodiments.
A sixth embodiment of the present invention provides a computer-readable storage medium, where computer-executable instructions are stored in the computer-readable storage medium, and when the computer-executable instructions are executed by a processor, the steps of the refrigeration method using a natural cold source as described in any one of the first to third embodiments are implemented, and the specific implementation manner and the technical effects are similar, and are not described herein again.
A seventh embodiment of the present invention provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, the steps of the refrigeration method using a natural cold source as described in any one of the first to third embodiments are implemented, and the specific implementation manner and the technical effect are similar, and are not described herein again.
Other embodiments of the present application will be apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the application and including such departures from the present disclosure as come within known or customary practice within the art to which the invention pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the application being indicated by the following claims.
It will be understood that the present application is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the application is limited only by the appended claims.
Claims (10)
1. A refrigeration method using a natural cold source is characterized by being applied to an energy-saving system and comprising the following steps:
acquiring the load of the current information technology IT equipment of the data center and basic parameters of a refrigeration system;
calculating the current critical wet bulb temperature according to the current IT equipment load and the basic parameters;
when the current outdoor wet bulb temperature is lower than the current critical wet bulb temperature, inputting the environmental parameters after the first preset time into an environmental parameter model obtained by pre-training to predict to obtain the predicted outdoor wet bulb temperature after the first preset time;
and when the predicted outdoor wet bulb temperature after the first preset time is less than the current critical wet bulb temperature, sending a natural refrigeration mode starting message to the refrigeration system, wherein the natural refrigeration mode starting message is used for indicating the refrigeration system to start a natural refrigeration mode.
2. The method of claim 1, wherein said calculating a current critical wet bulb temperature based on said current IT equipment load and said base parameter comprises:
calculating the current critical wet bulb temperature according to the following critical wet bulb temperature formula:
wherein, TmaxIs the current critical wet bulb temperature, Q1For the current IT equipment load, the basic parameters are: t is1For air-conditioning the ambient temperature of the cold channel, Q2For distributing loads, Q3Is the building load, L is the sum of the flow of the chilled water main, T2For heat exchange temperature difference, T, of plate heat exchangers3The cooling tower approach and K is the mass flow coefficient.
3. The method as claimed in claim 1, wherein before sending the message to the refrigeration system to turn on natural cooling mode when the predicted outdoor wet bulb temperature after the first preset time is less than the current critical wet bulb temperature, further comprising:
inputting the power-on and power-off data of the equipment after the second preset time into an IT equipment load prediction model obtained by pre-training to predict the IT equipment load of the data center after the second preset time, wherein the second preset time is longer than the first preset time;
calculating the critical wet bulb temperature after the second preset time according to the IT equipment load after the second preset time and the basic parameters;
inputting the environmental parameters after the second preset time into the environmental parameter model to predict the outdoor wet bulb temperature after the second preset time;
the sending a message to the refrigeration system to turn on a natural cooling mode includes:
and when the predicted outdoor wet bulb temperature after the second preset time is less than the critical wet bulb temperature after the second preset time, sending the message of starting the natural refrigeration mode to the refrigeration system.
4. The method according to any one of claims 1-3, further comprising:
acquiring first training data, wherein the first training data comprise historical environmental parameters and temperature labels, and the temperature labels are used for describing outdoor wet bulb temperatures under corresponding environmental parameters;
and training a first preset model according to the first training data to obtain the environment parameter model.
5. The method of claim 3, further comprising:
acquiring second training data, wherein the second training data comprises historical equipment power-on and power-off data and a load label, and the load label is used for describing IT equipment loads corresponding to the equipment power-on and power-off data;
and training a second preset model according to the second training data to obtain the IT equipment load prediction model.
6. An energy saving system, comprising:
the system comprises an acquisition module, a data center and a control module, wherein the acquisition module is used for acquiring the load of the current information technology IT equipment of the data center and the basic parameters of a refrigeration system;
the calculation module is used for calculating the current critical wet bulb temperature according to the current IT equipment load and the basic parameters;
the prediction module is used for inputting the environmental parameters after the first preset time into an environmental parameter model obtained by pre-training to predict and obtain the predicted outdoor wet bulb temperature after the first preset time when the current outdoor wet bulb temperature is less than the current critical wet bulb temperature;
and the sending module is used for sending a natural refrigeration mode starting message to the refrigeration system when the predicted outdoor wet bulb temperature after the first preset time is less than the current critical wet bulb temperature, wherein the natural refrigeration mode starting message is used for indicating the refrigeration system to start a natural refrigeration mode.
7. The energy saving system of claim 6, wherein the computing module is specifically configured to:
calculating the current critical wet bulb temperature according to the following critical wet bulb temperature formula:
wherein, TmaxIs the current critical wet bulb temperature, Q1For the current IT equipment load, the basic parameters are: t is1For air-conditioning the ambient temperature of the cold channel, Q2For distributing loads, Q3Is the building load, L is the sum of the flow of the chilled water main, T2For heat exchange temperature difference, T, of plate heat exchangers3The cooling tower approach and K is the mass flow coefficient.
8. The energy saving system of claim 6, wherein the sending module is specifically configured to:
inputting the power-on and power-off data of the equipment after the second preset time into an IT equipment load prediction model obtained by pre-training to predict the IT equipment load of the data center after the second preset time, wherein the second preset time is longer than the first preset time;
calculating the critical wet bulb temperature after the second preset time according to the IT equipment load after the second preset time and the basic parameters;
inputting the environmental parameters after the second preset time into the environmental parameter model to predict the outdoor wet bulb temperature after the second preset time;
the sending a message to the refrigeration system to turn on a natural cooling mode includes:
and when the predicted outdoor wet bulb temperature after the second preset time is less than the critical wet bulb temperature after the second preset time, sending the message of starting the natural refrigeration mode to the refrigeration system.
9. An energy saving system, comprising: a processor, and a memory communicatively coupled to the processor;
the memory stores computer-executable instructions;
the processor executes computer-executable instructions stored by the memory to implement the method of any of claims 1-5.
10. A computer-readable storage medium, comprising: a processor, and a memory communicatively coupled to the processor;
the memory stores computer-executable instructions;
the processor executes computer-executable instructions stored by the memory to implement the method of any of claims 1-5.
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