Method for manufacturing and operating miniaturized model of rear door cooling device

Abstract

Provided is a method for manufacturing and operating a miniaturized model of a rear door cooling device. According to an embodiment of the present invention, the system for testing a miniaturized model of a rear door cooling device comprises: a case for simulating a containment in a data center; a rack-type support for simulating a rack in the data center; a water cooler for serving as a rear door cooling device of the rack; a cooling module cooling a refrigerant; and a heat exchange device for cooling the cooling water in the water cooler with the refrigerant in the cooling module. Accordingly, various air conditioning schemes can be tested at low costs and in small spaces through multiple rear door cooling device miniaturized models, and IT equipment loads and the fan speed of section-specific rear door cooling device miniaturized models can be remotely controlled by software, thereby enabling development of various energy optimization algorithms using artificial intelligence.

Description

Manufacturing and operating method of a scale model of a rear door cooling device

[0001] The present invention relates to an experiment on a rear door cooling device, and more particularly, to a method for developing various optimal operation software algorithms for energy saving using a scaled-down model of a rear door cooling device that operates in the same manner as the principle of a rear door cooling device but is significantly reduced in size.

[0002] Rear-door cooling units are devices attached to data center racks to help manage heat at the rack level. Experiments with various air conditioning methods, including rear-door cooling, require actual equipment operation.

[0003] However, rear-door cooling devices are not only difficult to obtain domestically, but are also large in size, take up a lot of space, and are expensive, making it difficult to build an experimental environment consisting of multiple rear-door cooling devices for the development of optimal operating software algorithms for energy conservation.

[0004] Additionally, the loads used instead of IT equipment in data center air conditioning experiments are large in size and take up a lot of space, and there is a problem in that the loads cannot be controlled remotely to generate the desired load.

[0005] The present invention has been devised to solve the above problems, and the purpose of the present invention is to provide a method for constructing an experimental environment similar to that constructed with a number of rear-door cooling devices at low cost and in a small space, and utilizing this to develop various optimal operation software algorithms for reducing data center air conditioning energy.

[0006] A scale model experimental system of a rear door cooling device according to one embodiment of the present invention for achieving the above object includes: a case simulating a containment in a data center; a rack-shaped support simulating a rack in a data center; a water-cooling cooler that functions as a rear door cooling device of the rack; a cooling module that cools a refrigerant; and a heat exchange device that cools the cooling water of the water-cooling cooler with the refrigerant of the cooling module.

[0007] The case can be made from the actual refrigerator case.

[0008] The cooling module and heat exchanger can be manufactured using components from an actual refrigerator.

[0009] The pedestal may include fan heaters that simulate the heat generation of IT equipment; and thermometers that measure the temperature of air heated by the heat emitted from the fan heaters to determine the temperature of each section of the pedestal.

[0010] A water cooling cooler may include fans that expel air heated by the heat emitted from the fan heaters.

[0011] The heat exchange device may include a refrigerant evaporator that exchanges heat with a liquid refrigerant from a cooling module by contacting it with a cooling water tank; a cooling water tank that exchanges heat with cooling water from a water-cooled cooler by contacting it with the refrigerant evaporator; a cooling water pump that circulates the cooling water from the water-cooled cooler; and a thermometer that measures the temperature of the cooling water from the cooling water pump.

[0012] A scale model experimental system of a rear door cooling device according to the present invention may include an operating system that controls a water cooler, a cooling module, and a heat exchange device while monitoring the status of the pedestal and the heat exchange device.

[0013] The operating system may include a temperature collection device that collects temperatures from thermometers of a pedestal and a thermometer (440) of a heat exchanger; a power consumption collection device that collects power consumption data from a water-cooling cooler, a heat exchanger, and a cooling module; a first variable control device that remotely controls the load of fan heaters of the pedestal; a second variable control device that remotely controls the rotation speed of fans of the water-cooling cooler; a third variable control device that controls the rotation speed of a cooling water pump of the heat exchanger; a fourth variable control device that remotely controls the refrigerant temperature of the cooling module; and an energy-saving optimal operation management device that calculates control values ​​of the second variable control device, the third variable control device, and the fourth variable control device based on the temperatures collected by the temperature collection device, and transmits control commands to the second variable control device, the third variable control device, and the fourth variable control device according to the calculated control values.

[0014] The energy saving optimal operation management equipment can control the second variable control equipment, the third variable control equipment, and the fourth variable control equipment using an artificial intelligence model that calculates control values ​​for controlling the second variable control equipment, the third variable control equipment, and the fourth variable control equipment according to the temperature collected by the temperature collection equipment, and can train the artificial intelligence model by monitoring the temperature collected by the temperature collection equipment while controlling the second variable control equipment, the third variable control equipment, and the fourth variable control equipment.

[0015] According to another aspect of the present invention, a method for testing a scaled-down model of a rear-door cooling device is provided, characterized in that it comprises the steps of: cooling a refrigerant; and cooling the coolant of a water-cooling cooler that functions as a rear-door cooling device with the coolant of a cooling module on a rack-shaped support that simulates a rack in a data center, which is provided in a case that simulates a containment in a data center.

[0016] According to another aspect of the present invention, a scale model experimental system of a rear door cooling device is provided, characterized by including a case simulating a containment in a data center; a rack-shaped support simulating a rack in a data center; and a water cooler that functions as a rear door cooling device of the rack.

[0017] According to another aspect of the present invention, a scaled-down model experimental system of a rear-door cooling device is provided, characterized in that it includes a water-cooling cooler that functions as a rear-door cooling device for a rack-shaped support that simulates a rack in a data center, which is provided in a case that simulates a containment in a data center; a cooling module that cools a refrigerant; and a heat exchange device that cools the cooling water of the water-cooling cooler with the refrigerant of the cooling module.

[0018] As described above, according to embodiments of the present invention, experiments on various air conditioning methods can be performed at low cost and in a small space through a number of scale models of rear door cooling devices.

[0019] In addition, according to embodiments of the present invention, the IT equipment load and the fan speed of the section-by-section rear door cooling device scale model can be remotely controlled through software, thereby enabling the development of various energy optimization algorithms utilizing artificial intelligence.

[0020] Figure 1 is a configuration of a scaled-down model experimental system of a rear door cooling device according to one embodiment of the present invention;

[0021] Fig. 2 is a detailed configuration of the stainless steel support shown in Fig. 1;

[0022] Figure 3 is a detailed configuration of the water cooling cooler shown in Figure 1.

[0023] Fig. 4 is a detailed configuration of the cooling water refrigerant heat exchange device shown in Fig. 1.

[0024] Figure 5 is a detailed configuration of the optimal operation system of the air conditioning equipment shown in Figure 1.

[0025] Figure 6 is an energy-saving optimal operation method of a scaled-down model experimental system of a rear door cooling device.

[0026] Hereinafter, the present invention will be described in more detail with reference to the drawings.

[0027] In an embodiment of the present invention, a method for fabricating and operating a scaled-down model of a rear door cooling device is presented. Specifically, the scaled-down model of the rear door cooling device is a technology that implements an experimental device with a significantly reduced size while operating on the same principles as the rear door cooling device, and utilizes this to develop various optimal operating software algorithms for energy savings.

[0028] FIG. 1 is a drawing showing the configuration of a scaled-down model experimental system of a rear door cooling device according to one embodiment of the present invention.

[0029] As shown in the drawing, a scale model experimental system of a rear door cooling device according to an embodiment of the present invention is configured to include a refrigerator case (100), a stainless steel stand (200), a water-cooled cooler (300), a cooling water refrigerant heat exchanger (400), a refrigerant-type cooling module (500), and an air conditioning equipment optimal operation system (600).

[0030] The refrigerator case (100) is a configuration that performs a containment role within a data center, and can be implemented by disassembling an actual refrigerator and using only the external case excluding the internal parts.

[0031] The stainless steel pedestal (200) is implemented in the form of a small rack to simulate / perform the role of a data center rack. The water cooling cooler (300) is implemented as a PC water cooling cooler that simulates / performs the role of a rear door cooling device.

[0032] The cooling water refrigerant heat exchanger (400) is configured to perform heat exchange between the cooling water of the water-cooled cooler (300) and the refrigerant of the cooling module (500), and the refrigerant-type cooling module (500) is configured to cool the refrigerant. The cooling water refrigerant heat exchanger (400) and the cooling module (500) can be implemented as internal components of an actual refrigerator.

[0033] The optimal operation system (600) for air conditioning equipment is configured to control a water-cooled cooler (300), a cooling water refrigerant heat exchanger (400), and a cooling module (500) using a refrigerant method while monitoring the temperature of a stainless steel support (200) and a cooling water refrigerant heat exchanger (400) so as to save data center energy.

[0034] Fig. 2 is a drawing showing a detailed configuration of a stainless steel support (200) illustrated in Fig. 1. The rack-shaped stainless steel support (200) that functions as a rack is configured to include, as illustrated, a plurality of thermometers (210, 211, ..., 21n) and a plurality of PTC fan heaters (220, 221, ..., 22n).

[0035] PTC fan heaters (220, 221, ..., 22n) are configured to simulate the heat generation of IT equipment such as servers. The heat emitted from the PTC fan heaters (220, 221, ..., 22n) simulates the heat emitted from the rear door rack.

[0036] Thermometers (210, 211, ..., 21n) measure the temperature of air heated by heat emitted from PTC fan heaters (220, 221, ..., 22n) to measure the temperature of each section of the stainless steel stand (200).

[0037] Fig. 3 is a drawing showing a detailed configuration of a water cooling cooler (300) illustrated in Fig. 1. As illustrated, the water cooling cooler (300) is configured to include a plurality of EC fans (310, 311, ..., 31n).

[0038] EC fans (310, 311, ..., 31n) exhaust air heated by heat emitted from PTC fan heaters (220, 221, ..., 22n) of a stainless steel base (200).

[0039] Fig. 4 is a drawing showing a detailed configuration of a cooling water refrigerant heat exchange device (400) illustrated in Fig. 1. As illustrated, the cooling water refrigerant heat exchange device (400) is configured to include a refrigerant evaporator (410), a cooling water tank (420), a cooling water pump (430), and a thermometer (440).

[0040] The refrigerant evaporator (410) exchanges heat with the liquid refrigerant from the refrigerant-type cooling module (500) by contacting it with the cooling water tank (420), and the cooling water tank (420) exchanges heat with the cooling water from the water-cooling cooler (300) by contacting it with the refrigerant evaporator (410). As a result, the cooling water moved from the water-cooling cooler (300) to the cooling water tank (420) is cooled by the liquid refrigerant moved from the refrigerant-type cooling module (500) to the refrigerant evaporator (410).

[0041] The cooling water pump (430) is configured to circulate cooling water from the water-cooling cooler (300), and the thermometer (440) is configured to measure the temperature of the cooling water from the cooling water pump (430).

[0042] FIG. 5 is a drawing showing a detailed configuration of an air conditioning equipment optimal operation system (600) illustrated in FIG. 1. As illustrated, the air conditioning equipment optimal operation system (600) for energy saving is configured to include a temperature collection device (610), a power usage collection device (620), an energy saving optimal operation management device (630), a PTC fan heater remote variable control device (640), an EC fan remote variable control device (650), a cooling water pump remote variable control device (660), and a cooling module remote variable control device (670).

[0043] The temperature collection device (610) is configured to collect temperature from the thermometers (210, 211, ..., 21n) of the stainless steel stand (200) and the thermometer (440) of the cooling water refrigerant heat exchange device (400).

[0044] The power usage collection device (620) is configured to collect power usage data from a water-cooled cooler (300), a cooling water refrigerant heat exchanger (400), and a refrigerant-type cooling module (500).

[0045] The energy-saving optimal operation management equipment (630) calculates appropriate control values ​​of the control equipment (650, 660, 670) described later according to the energy-saving optimal operation method based on the temperature collected by the temperature collection equipment (610), and transmits control commands to the control equipment (650, 660, 670) according to the calculated control values.

[0046] The PTC fan heater remote variable control device (640) controls the load of the PTC fan heaters (220, 221, ..., 22n) of the stainless steel stand (200) to change arbitrarily as the load of the IT equipment changes, or to change the load periodically according to the usage pattern.

[0047] The EC fan remote variable control equipment (650) receives control values ​​for the EC fans (310, 311, ..., 31n) of the water-cooling cooler (300) from the energy-saving optimal operation management equipment (630), and remotely controls the rotation speed of the EC fans (310, 311, ..., 31n).

[0048] The cooling water pump remote variable control equipment (660) receives a control value for the cooling water pump (430) of the cooling water refrigerant heat exchange device (400) from the energy saving optimal operation management equipment (630) and controls the rotation speed of the cooling water pump (430).

[0049] The cooling module remote variable control equipment (670) receives control values ​​for the refrigerant-type cooling module (500) from the energy-saving optimal operation management equipment (630) and remotely controls the refrigerant temperature of the refrigerant-type cooling module (500).

[0050] The energy-saving optimal operation method of the scaled-down model experimental system of the rear door cooling device by the optimal operation system of the air conditioning equipment (600) is illustrated in Fig. 6.

[0051] As shown, first, the energy saving optimal operation management equipment (630) checks the temperature of the thermometer (440) collected by the temperature collection equipment (610), i.e., the temperature of the outlet of the cooling water tank (420) (S710).

[0052] If the confirmed temperature is higher than the critical temperature, the energy-saving optimal operation management equipment (630) calculates control values ​​for the EC fans (310, 311, ..., 31n), the cooling water pump (430), and the refrigerant-type cooling module (500) (S720). The control values ​​are calculated using an artificial intelligence model that calculates the above control values ​​from the temperature of the outlet of the cooling water tank (420).

[0053] And the energy saving optimal operation management equipment (630) controls the EC fans (310, 311, ..., 31n), cooling water pump (430), and refrigerant type cooling module (500) through variable control equipment (650, 660, 670) with the control values ​​calculated in step S720 (S730).

[0054] The next energy saving optimal operation management equipment (630) checks the power usage collected through the power usage collection equipment (620) (S740).

[0055] If it is confirmed that power usage has decreased in step S740, the energy saving optimal operation management equipment (630) provides a reward to the artificial intelligence model that calculates control values ​​to enable learning (S750).

[0056] Afterwards, steps S710 to S750 are repeated to optimize the artificial intelligence model that calculates control values ​​for energy saving.

[0057] So far, a method for manufacturing and operating a scale model of a rear door cooling device has been described in detail with a preferred embodiment.

[0058] In the above example, an experimental environment was constructed with a number of rear-door cooling devices at low cost and in a small space, and these were utilized to develop various types of optimal operation software algorithms, thereby reducing data center air conditioning energy.

[0059] This allows for experiments on various air conditioning methods to be conducted at low cost and in a small space through a number of scale models of rear-door cooling devices, and allows for the remote control of IT equipment load and the fan speed of each scale model of rear-door cooling devices by software, enabling the development of various energy optimization algorithms using artificial intelligence.

[0060] Meanwhile, it goes without saying that the technical idea of ​​the present invention can also be applied to a computer-readable recording medium containing a computer program that performs the functions of the device and method according to the present embodiment. In addition, the technical idea according to various embodiments of the present invention can be implemented in the form of computer-readable code recorded on a computer-readable recording medium. The computer-readable recording medium can be any data storage device that can be read by a computer and store data. For example, the computer-readable recording medium can be a ROM, a RAM, a CD-ROM, a magnetic tape, a floppy disk, an optical disk, a hard disk drive, etc. In addition, the computer-readable code or program stored on the computer-readable recording medium can be transmitted through a network connected between computers.

[0061] In addition, although the preferred embodiments of the present invention have been illustrated and described above, the present invention is not limited to the specific embodiments described above, and various modifications can be made by a person having ordinary skill in the art to which the present invention pertains without departing from the gist of the present invention as claimed in the claims, and such modifications should not be understood individually from the technical idea or prospect of the present invention.

Claims

1. A case simulating containment within a data center; A rack-shaped pedestal that mimics the racks inside a data center; A water cooler that acts as a rear door cooling device for the rack; A cooling module that cools the refrigerant; A scale model experimental system of a rear door cooling device, characterized by including a heat exchange device that cools the cooling water of a water-cooled cooler with the refrigerant of a cooling module.

2. In claim 1, The case is, A scale model experimental system for a rear-door refrigeration unit characterized by being constructed using the case of an actual refrigerator.

3. In claim 2, The cooling module and heat exchanger device, A scale model experimental system for a rear-door refrigeration unit featuring components manufactured from actual refrigerator parts.

4. In claim 1, The pedestal is, Fan heaters that simulate the heat generation of IT equipment; A scale model experimental system of a rear door cooling device, characterized by including thermometers for measuring the temperature of air heated by heat emitted from fan heaters and thereby measuring the temperature of each section of the pedestal.

5. In claim 4, Water cooling cooler, A scale model experimental system of a rear door cooling device, characterized by including fans for exhausting air heated by heat emitted from fan heaters.

6. In claim 1, The heat exchanger is, A refrigerant evaporator that exchanges heat by bringing liquid refrigerant from a cooling module into contact with a cooling water tank; A cooling water tank that exchanges heat by bringing cooling water from a water-cooled cooler into contact with a refrigerant evaporator; A coolant pump that circulates coolant from a water-cooling cooler; A scale model experimental system for a rear door cooling device, characterized by including a thermometer for measuring the temperature of coolant coming from a coolant pump.

7. In claim 1, A scale model experimental system of a rear door cooling device, characterized by including an operating system for controlling a water cooling cooler, a cooling module and a heat exchanger while monitoring the status of the pedestal and the heat exchanger.

8. In claim 7, The operating system is, Temperature collection equipment for collecting temperatures from the thermometers on the pedestal and the thermometers (440) of the heat exchanger; Power usage collection equipment that collects power usage data from water cooling coolers, heat exchangers, and cooling modules; A first variable control device for remotely controlling the load of the fan heaters on the pedestal; A second variable control device that remotely controls the rotation speed of the fans of the water cooling cooler; A third variable control device that controls the rotation speed of the cooling water pump of the heat exchanger; A fourth variable control device for remotely controlling the refrigerant temperature of the cooling module; A scale model experimental system of a rear door cooling device, characterized by including an energy-saving optimal operation management device that calculates control values ​​of a second variable control device, a third variable control device, and a fourth variable control device based on temperatures collected by a temperature collection device, and transmits control commands to the second variable control device, the third variable control device, and the fourth variable control device according to the calculated control values.

9. In claim 8, The optimal energy saving operation management equipment is, Using an artificial intelligence model that calculates control values ​​for controlling the second variable control equipment, the third variable control equipment, and the fourth variable control equipment according to the temperature collected by the temperature collection equipment, while controlling the second variable control equipment, the third variable control equipment, and the fourth variable control equipment, A scale model experimental system of a rear door cooling device characterized by training an artificial intelligence model by monitoring the temperature collected by a temperature collection device.

10. Step of cooling the refrigerant; and A method for testing a scale model of a rear-door cooling device, characterized in that it includes a step of cooling the cooling water of a water-cooling cooler that functions as a rear-door cooling device with the refrigerant of a cooling module on a rack-shaped pedestal that simulates a rack in a data center, which is installed in a case that simulates a containment in a data center.

11. A case simulating containment within a data center; A rack-shaped pedestal that mimics a rack in a data center; and A scale model experimental system of a rear door cooling device, characterized by including a water cooling cooler that performs the role of a rear door cooling device of a rack.

12. A water cooling cooler that acts as a rear door cooling device for a rack-shaped pedestal replicating a data center rack, housed in a case replicating a data center containment; A cooling module for cooling the refrigerant; and A scale model experimental system of a rear door cooling device, characterized by including a heat exchange device that cools the cooling water of a water-cooled cooler with the refrigerant of a cooling module.

Images