Collaborative control system of distributed cooling units in liquid cooling room

Abstract

The present invention discloses a distributed heat dissipation unit collaborative control system for a liquid cooling room, and relates to the field of liquid cooling heat dissipation technology. The system includes: a real-time monitoring module deploys multiple sensors based on the spatial structure of a target liquid cooling room, generates a sensor network, and obtains multiple sets of real-time operating parameters through real-time monitoring. A heat dissipation demand assessment module constructs an environmental control unit according to multiple real-time operating parameters, performs heat dissipation assessment on the target liquid cooling room, determines heat dissipation demand, and constructs multiple heat dissipation units. An initial collaborative strategy module combines multiple heat dissipation units with the environmental control unit for collaborative control, and formulates an initial collaborative control strategy. A strategy simulation optimization module executes an initial collaborative control strategy for collaborative simulation, optimizes the initial collaborative control strategy according to the simulated heat dissipation results, and generates a collaborative control optimization strategy. The collaborative control module executes the collaborative control optimization strategy to collaboratively control the target liquid cooling room. A technical effect of improving heat dissipation efficiency and reducing system energy consumption is achieved.

Description

Technical Field

[0001] The present invention relates to the field of liquid cooling and heat dissipation technology, and in particular to a coordinated control system for distributed heat dissipation units in a liquid cooling machine room. Background Art

[0002] With the development of information technology and the surge in data volume, the heat dissipation problem of data centers has become increasingly prominent. Traditional air cooling systems are difficult to meet the needs of high-density computing environments due to their low energy efficiency and are gradually being replaced by efficient liquid cooling systems. Liquid cooling technology directly removes heat through liquid media, significantly improving heat dissipation efficiency and reducing energy consumption in data centers. When existing heat dissipation control systems are applied to large-scale data centers, it is difficult to perform efficient heat dissipation management in the face of a large number of distributed heat dissipation units. There are technical problems such as low heat dissipation efficiency and high energy consumption. Summary of the invention

[0003] The present invention provides a distributed heat dissipation unit collaborative control system for a liquid cooling room to solve the technical problems of low heat dissipation efficiency and high energy consumption in the prior art, and achieves the technical effect of improving heat dissipation efficiency and reducing system energy consumption.

[0004] The present invention provides a liquid cooling room distributed heat dissipation unit collaborative control system, wherein the system comprises:

[0005] A real-time monitoring module, which is used to deploy multiple sensors based on the spatial structure of the target liquid cooling room to generate a sensor network, and to monitor the target liquid cooling room in real time through the sensor network to obtain multiple sets of real-time operating parameters;

[0006] a heat dissipation demand assessment module, the heat dissipation demand assessment module being used to construct an environmental control unit based on the multiple real-time operating parameters, perform heat dissipation assessment on a target liquid cooling room according to the multiple real-time operating parameters, determine a heat dissipation demand assessment result, and construct a plurality of heat dissipation units according to the heat dissipation assessment result;

[0007] An initial collaborative strategy module, the initial collaborative strategy module is used to coordinate the multiple heat dissipation units with the environmental control unit to formulate an initial collaborative control strategy;

[0008] A strategy simulation optimization module, wherein the strategy simulation optimization module is used to execute the initial collaborative control strategy to perform collaborative simulation, optimize the initial collaborative control strategy according to the collaborative simulation heat dissipation result, and generate a collaborative control optimization strategy;

[0009] A collaborative control module is used to execute the collaborative control optimization strategy to collaboratively control the target liquid cooling room.

[0010] The present invention discloses a coordinated control system for distributed heat dissipation units in a liquid cooling room, including: a real-time monitoring module for arranging multiple sensors based on the spatial structure of a target liquid cooling room, generating a sensor network, monitoring the target liquid cooling room in real time through the sensor network, and obtaining multiple sets of real-time operating parameters; a heat dissipation demand evaluation module for constructing an environmental control unit based on the multiple real-time operating parameters, performing heat dissipation evaluation on the target liquid cooling room according to the multiple real-time operating parameters, determining heat dissipation demand evaluation results, and constructing multiple heat dissipation units according to the heat dissipation evaluation results; an initial coordinated strategy module for combining the multiple heat dissipation units with the environmental control unit for coordinated control and formulating an initial coordinated control strategy; a strategy simulation optimization module for executing the initial coordinated control strategy for coordinated simulation, optimizing the initial coordinated control strategy according to the coordinated simulation heat dissipation results, and generating a coordinated control optimization strategy; a coordinated control module for executing the coordinated control optimization strategy to coordinately control the target liquid cooling room. The coordinated control system for distributed heat dissipation units in a liquid cooling room disclosed by the present invention solves the technical problems of low heat dissipation efficiency and high energy consumption, and achieves the technical effects of improving heat dissipation efficiency and reducing system energy consumption. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] Figure 1 It is a structural schematic diagram of the coordinated control system of the distributed heat dissipation unit in the liquid cooling room of the present invention;

[0012] Figure 2 It is a schematic diagram of the execution steps of the coordinated control system of the distributed heat dissipation unit in the liquid cooling room of the present invention.

[0013] Explanation of the reference numerals: real-time monitoring module 11 , heat dissipation demand assessment module 12 , initial collaborative strategy module 13 , strategy simulation optimization module 14 , collaborative control module 15 . DETAILED DESCRIPTION

[0014] The technical solution provided in the embodiments of the present invention is to solve the technical problems of low heat dissipation efficiency and high energy consumption in the prior art. The overall idea adopted is as follows:

[0015] First, the real-time monitoring module deploys multiple sensors based on the spatial structure of the target liquid cooling room to form a sensor network, through which the target liquid cooling room is monitored in real time to obtain multiple sets of real-time operating parameters. Secondly, the heat dissipation demand assessment module constructs an environmental control unit based on multiple real-time operating parameters, uses these parameters to evaluate the heat dissipation demand of the target liquid cooling room, determines the heat dissipation demand assessment results, and constructs multiple heat dissipation units accordingly. Next, the initial collaborative strategy module combines the environmental control unit and multiple heat dissipation units for collaborative control and formulates an initial collaborative control strategy. Then, the strategy simulation optimization module executes the initial collaborative control strategy for collaborative simulation, optimizes the initial collaborative control strategy according to the simulated heat dissipation results, and generates a collaborative control optimization strategy. Finally, the collaborative control module executes the collaborative control optimization strategy to collaboratively control the target liquid cooling room to meet the heat dissipation demand and optimize energy utilization.

[0016] The above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods of the specification to better understand the above technical solution. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments of the present invention. It should be understood that the present invention is not limited to the example embodiments used only to explain the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention. In addition, it should be noted that, for the convenience of description, only the parts related to the present invention are shown in the drawings, rather than all of them.

[0017] Figure 1 The structure diagram of the distributed heat dissipation unit collaborative control system of the liquid cooling room of the present invention is shown in FIG. 1 ; wherein the system includes:

[0018] The real-time monitoring module 11 is used to deploy multiple sensors based on the spatial structure of the target liquid cooling room to generate a sensor network, and to monitor the target liquid cooling room in real time through the sensor network to obtain multiple sets of real-time operating parameters.

[0019] Optionally, the target liquid cooling computer room refers to a single server room or a collection of multiple server rooms including multiple liquid cooling servers, and the target liquid cooling computer room improves the cooling efficiency and energy utilization of the data center by using liquid as a heat transfer medium.

[0020] Optionally, a detailed analysis is performed on the spatial structure of the target liquid cooling room to determine the key areas and equipment locations. The spatial structure of the target liquid cooling room includes the layout of the room, the arrangement and grouping of cooling equipment, the direction of the coolant pipes, and the air circulation path. By obtaining the above spatial structure, it is helpful to determine the best location for the sensor to be deployed to ensure that all key areas are covered.

[0021] For example, multiple sensors are deployed around key equipment, on the surface of coolant pipes, coolant inlets and outlets, coolant distributors, and air circulation channels. At the same time, the sensors are deployed in a grid or ring structure to ensure data redundancy and reliability.

[0022] Optionally, based on different monitoring requirements, appropriate sensor types are selected, including temperature sensors, humidity sensors, pressure sensors, flow sensors, etc. Specifically, the selection of each sensor is evaluated based on its accuracy, response speed, and durability.

[0023] In some embodiments, the multiple sensors are arranged based on the spatial structure of the target liquid cooling room to generate a sensor network, and the execution steps of the system include:

[0024] Based on the spatial structure of the target liquid cooling room, a heat scan is performed to obtain a heat distribution map; based on the heat distribution map, a heat analysis is performed to obtain heat accumulation concentration information and heat accumulation range information; according to the heat accumulation concentration information, the heat accumulation range is graded to obtain a heat accumulation grade, and according to the heat accumulation grade, the heat accumulation points on the heat distribution map are marked to generate a plurality of heat accumulation points; based on the plurality of heat accumulation points, the plurality of sensors are deployed to generate the sensor network.

[0025] Optionally, an infrared thermal imager, a thermocouple array or other heat scanning equipment is used, combined with the spatial structure of the target liquid cooling room, to perform an all-round scan of the room to obtain heat data at different locations, thereby generating a heat distribution map, which is a three-dimensional chart showing the distribution of heat in the target liquid cooling room space.

[0026] Specifically, the heat distribution map is analyzed to extract heat accumulation concentration information and heat accumulation range information. Among them, the heat accumulation concentration information refers to the degree of heat accumulation in a specific area, reflecting the heat accumulation. The heat accumulation range information is the area range where heat accumulates in space, reflecting the distribution range of heat. Through the above heat analysis, the degree and distribution range of heat accumulation in a specific area are obtained.

[0027] Exemplarily, it includes qualitatively analyzing the heat in the heat distribution map based on the mapping relationship between the chromaticity information or grayscale information and the temperature value, combined with the preset temperature control threshold, obtaining the heat accumulation area, and then calculating the average value, maximum value, minimum value and other parameters of each heat accumulation area by counting the color or grayscale value of each heat accumulation area, and obtaining the concentration information of the heat accumulation; measuring the area of ​​each heat accumulation area in the image to determine its range information. It involves image processing technology (such as edge detection, morphological processing, etc.) to accurately identify the boundaries of the heat accumulation area.

[0028] Optionally, based on a preset heat level-heat accumulation concentration mapping matrix, the heat levels of multiple heat accumulation ranges are determined, and then corresponding points are identified according to different heat accumulation levels. Among them, sensors are densely deployed in high heat level areas to ensure accurate monitoring, and sensors are deployed less in low heat level areas to ensure coverage of all key areas while reducing monitoring costs.

[0029] Optionally, multiple sensors are connected to the central monitoring component of the real-time monitoring module 11 to generate a sensor network. Specifically, the sensor network uses a wireless sensor network (WSN) or a wired sensor network (such as Ethernet) to form a network topology, including a star network topology, a mesh network topology, a tree network topology, or a composite network topology. The sensor network is used for real-time data collection and transmission through multiple connected sensors.

[0030] In some embodiments, the target liquid cooling room is monitored in real time through the sensor network to obtain multiple sets of real-time operating parameters. The execution steps of the system include:

[0031] The sensor network is used to monitor the multiple heat accumulation points in real time based on the heat accumulation level to generate a heat accumulation monitoring data set; a cloud monitoring platform is built to transmit the heat accumulation monitoring data set to the cloud monitoring platform, and the cloud monitoring platform is used to determine whether the heat accumulation monitoring data set is in a preset cooling range; if not, the sensor network is started to collect real-time environmental data of the target liquid cooling room to generate the multiple real-time operating parameter sets.

[0032] Optionally, the sensor network performs real-time monitoring of multiple heat accumulation points based on the heat accumulation level, wherein the heat accumulation points with higher heat accumulation levels are configured with higher monitoring levels, corresponding to higher monitoring sampling frequencies, and correspondingly, the heat accumulation points with lower heat accumulation levels correspond to lower monitoring sampling frequencies.

[0033] Furthermore, cloud computing technology is used to build a monitoring platform, and a communication connection is established between the monitoring platform and the distributed liquid cooling unit to ensure efficient storage and processing of data, and obtain a cloud monitoring platform, wherein the heat accumulation monitoring data set is transmitted to the cloud monitoring platform via the network, and the transmission process adopts a secure transmission protocol, such as HTTPS or MQTT.

[0034] Specifically, the cloud monitoring platform uses the heat accumulation monitoring data set to analyze whether the target computer room is in the preset coolable range, thereby determining the cause of the heat accumulation, that is, judging whether the current temperature is caused by the distributed liquid cooling unit or by environmental overheating. For example, different ambient temperatures correspond to different preset coolable ranges. If the heat accumulation monitoring data set shows that the operating temperature of the liquid-cooled server in the computer room exceeds the preset coolable range under the current ambient temperature, it means that the current heat accumulation is caused by environmental overheating, and the ambient temperature needs to be adjusted and controlled.

[0035] Optionally, if the judgment result is no, the sensor network is started to collect real-time environmental information of the target liquid cooling room to generate multiple real-time operating parameter sets, wherein the real-time operating parameter sets include temperature, flow, pressure, etc., to provide comprehensive environmental status information.

[0036] The heat dissipation demand evaluation module 12 is used to construct an environmental control unit based on the multiple actual operating parameters, perform heat dissipation evaluation on the target liquid cooling room according to the multiple actual operating parameters, determine the heat dissipation demand evaluation results, and construct multiple heat dissipation units according to the heat dissipation evaluation results.

[0037] In some embodiments, the environmental control unit is constructed based on the multiple real-time operating parameters, and the execution steps of the system include:

[0038] Feature extraction is performed on the multiple actual operating parameters to generate key operating features; the key operating features are used as input variables of a decision tree, and the multiple actual operating parameters are recursively divided according to the input variables using a decision tree algorithm until a preset number of recursions is met, thereby constructing an environmental control decision tree model; and the environmental control decision tree model is added to the environmental control unit.

[0039] Optionally, use signal processing, statistical methods or machine learning technology to extract representative features from real-time collected parameters such as temperature, humidity, flow, pressure, etc. For example, based on the principal component analysis method, extract features from multiple real-time operating parameters to obtain key operating features. Preferably, select the first K components with cumulative contribution rates of 85% to 95% as key operating features. By extracting key operating features from real-time operating parameters, a basis is provided for subsequent environmental control decisions.

[0040] Furthermore, a decision tree algorithm is used to recursively divide multiple actual operation parameters according to the key operation characteristics to construct an environmental control decision tree model. Specifically, the key operation characteristics are used as the input variables of the decision tree, and decision tree algorithms such as ID3, C4.5, and CART are used for recursive division until the preset number of recursions or other termination conditions are met. The environmental control decision tree model is used to make environmental control decisions based on the actual operation parameters, such as turning on or off the environmental control equipment (such as air conditioning) of the target computer room, adjusting the operating parameters of the environmental control equipment (such as air conditioning), etc.

[0041] Optionally, the environmental control decision tree model is added to the environmental control unit. The environmental control unit is an automated control system, such as a PLC, an industrial computer, etc., or an intelligent controller, such as a temperature controller, a humidity controller, etc. The environmental control unit uses the above-mentioned environmental control decision tree model as a control strategy to make environmental control decisions for the target liquid cooling room and automatically perform environmental control operations. Through the above-mentioned integrated method, precise control and management of the liquid cooling room environment is achieved, operating efficiency and energy utilization are improved, and automation and intelligence of environmental control are achieved.

[0042] In some embodiments, heat dissipation evaluation is performed on the target liquid cooling room according to the multiple real-time operating parameters to determine a heat dissipation demand evaluation result, and the execution steps of the system include:

[0043] Based on the multiple actual operating parameters, the target liquid cooling room is calculated to obtain multiple heat dissipation parameters of the target liquid cooling room, wherein the multiple heat dissipation parameters include heat load data, heat dissipation efficiency, and heat dissipation; based on the heat load data, the heat dissipation efficiency, and the heat dissipation, in combination with the multiple actual operating parameters, an environmental factor correction factor is generated; based on the environmental factor correction factor, a heat dissipation evaluation function is constructed; and heat dissipation evaluation calculation is performed through the heat dissipation evaluation function to generate the heat dissipation evaluation result.

[0044] Optionally, the target liquid cooling room is calculated based on multiple real-time operating parameters to obtain multiple heat dissipation parameters. The heat load data represents the total heat generation of all devices in the room. The heat dissipation efficiency represents the efficiency of the liquid cooling system in removing heat from the room, that is, the heat value removed per unit energy consumed. The heat dissipation represents the total heat removed by the liquid cooling system in a specific time period.

[0045] Furthermore, based on the heat load data, heat dissipation efficiency, heat dissipation, and multiple actual operating parameters, an environmental factor correction factor is generated. The environmental factor correction factor is used to correct the heat dissipation parameters to reflect the impact of the actual operating environment on the heat dissipation effect. Exemplarily, the environmental factor correction factor includes a weighted combination of multiple actual operating parameters. Characterized by: ;in, T, H, F Respectively represent the temperature parameters, humidity parameters, and flow parameters in the actual operation parameters. , , They are the temperature experience correction coefficient, humidity experience correction coefficient, and flow experience correction coefficient corresponding to the temperature parameter, humidity parameter, and flow parameter respectively.

[0046] Specifically, the above-mentioned temperature empirical correction coefficient, humidity empirical correction coefficient, and flow empirical correction coefficient are obtained based on statistical analysis, and characterize the influence characteristics of actual operating parameters on heat dissipation. Specifically, if the ambient temperature rises, the heat transfer gradient of the liquid cooling system to the environment decreases, resulting in a decrease in heat dissipation capacity.

[0047] In some implementations, the heat dissipation evaluation function is: ;in, For the heat dissipation evaluation results, is the number of heat dissipation areas, is the heat dissipation importance weight of the i-th heat dissipation area, is the heat dissipation of the ith heat dissipation area, is the heat dissipation efficiency of the i-th heat dissipation area, is the environmental factor correction factor of the i-th heat dissipation area. Optionally, a heat dissipation evaluation function is used to perform heat dissipation evaluation calculation to generate a heat dissipation evaluation result. The heat dissipation evaluation result represents the evaluation value of the current overall heat dissipation performance of the computer room, which is used to determine whether the liquid cooling system needs to be adjusted or optimized. Among them, the heat dissipation area with higher heat dissipation importance corresponds to a higher evaluation weight.

[0048] Optionally, generating the heat dissipation evaluation result further includes performing a partition heat dissipation evaluation calculation on multiple heat dissipation areas based on the heat dissipation evaluation function. In this case, the number of heat dissipation areas is determined based on the partition range of the heat dissipation areas. For example, if a partition heat dissipation evaluation calculation is performed on a subspace in the computer room space that includes M heat dissipation spaces, then n=M. In particular, if an independent heat dissipation evaluation calculation is performed on a single heat dissipation area, then n=1. =1.

[0049] In some embodiments, a plurality of heat dissipation units are constructed according to the heat dissipation evaluation result, and the execution steps of the system include:

[0050] Based on the heat dissipation assessment result, a heat dissipation analysis is performed on the target liquid cooling room to generate multiple heat dissipation demand information; based on the multiple actual operating parameters and according to the multiple heat dissipation demand information, a heat dissipation optimization direction is determined; according to the heat dissipation optimization direction, the multiple heat dissipation areas are traversed for matching, and multiple heat dissipation instructions are executed according to the matching results; and the multiple heat dissipation instructions are added to multiple heat dissipation units according to the multiple heat dissipation areas.

[0051] Specifically, first, according to the heat dissipation assessment results, combined with the actual operation of the heat dissipation unit, a heat dissipation analysis is performed on the target liquid cooling room to generate multiple heat dissipation demand information, wherein the heat dissipation demand information includes specific heat dissipation parameters of each heat dissipation area, such as the heat dissipation amount that needs to be increased or decreased, the heat dissipation efficiency that needs to be adjusted, etc. Multiple heat dissipation demand information corresponds to multiple heat dissipation areas.

[0052] Optionally, based on multiple real-time operating parameters and heat dissipation demand information, the heat dissipation optimization direction is determined, so as to formulate an effective heat dissipation strategy to improve the overall heat dissipation performance of the liquid-cooled computer room. For example, if a certain heat dissipation area needs to increase the heat dissipation, and multiple real-time operating parameters show that the coolant temperature of the distributed heat dissipation unit corresponding to the heat dissipation area is normal, then the heat dissipation optimization direction is to change the fan speed. Correspondingly, if a certain heat dissipation area needs to increase the heat dissipation, and multiple real-time operating parameters show that the liquid temperature of the distributed heat dissipation unit corresponding to the heat dissipation area is high, then the heat dissipation optimization direction is to prioritize increasing the coolant flow rate. Through the above steps, the optimization direction of the heat dissipation system can be clarified, providing guidance and support for improving the heat dissipation efficiency of the liquid-cooled computer room.

[0053] Optionally, based on the determined heat dissipation optimization direction, multiple heat dissipation areas are traversed for matching. That is, based on the preset heat dissipation optimization direction and based on multiple heat dissipation requirement information of multiple heat dissipation areas, corresponding multiple heat dissipation instructions are configured for the multiple heat dissipation areas, thereby ensuring that multiple heat dissipation areas can perform efficient heat dissipation adjustments.

[0054] The initial collaborative strategy module 13 is used to coordinate the multiple heat dissipation units with the environmental control unit to perform collaborative control and formulate an initial collaborative control strategy.

[0055] In some embodiments, the multiple heat dissipation units are combined with the environment control unit for collaborative control to formulate an initial collaborative control strategy, and the execution steps of the system include:

[0056] The multiple heat dissipation units and the environmental control unit are monitored and recorded through the cloud monitoring platform to generate multiple heat dissipation parameters and environmental control parameters; collaborative control targets are formulated based on the multiple heat dissipation parameters and the environmental control parameters; based on multiple heat accumulation points, it is determined whether the operating control parameters of the target liquid cooling room meet the collaborative control targets; if not, the multiple heat accumulation points are traversed, the multiple heat dissipation units and / or the environmental control unit are activated for collaborative control, and collaborative control instructions are generated; and the collaborative control instructions are added to the initial collaborative control strategy.

[0057] Optionally, multiple heat accumulation points are traversed, and multiple heat dissipation parameters and environmental control parameters obtained by the cloud monitoring platform are analyzed to obtain collaborative control targets to ensure the optimization of the overall heat dissipation effect and the operating efficiency of a single heat dissipation area. The collaborative control targets include point control targets and overall control targets.

[0058] Furthermore, it is determined whether the corresponding heat dissipation demand information and collaborative control targets are achieved in multiple heat dissipation areas, and the cause of overheating is determined based on the distribution of the areas that have not been achieved. For example, if a discrete individual heat accumulation point is overheated, the corresponding distributed heat dissipation unit is activated for single-point control. If multiple adjacent heat accumulation points are overheated, it means that the cause of overheating is environmental overheating, and environmental control is started accordingly. In addition, if the above two overheating conditions exist at the same time, synchronous collaborative control is performed. While performing environmental control, single-point control is performed on discrete heat accumulation points with higher temperature levels among multiple adjacent heat accumulation points.

[0059] The strategy simulation optimization module 14 is used to execute the initial collaborative control strategy to perform collaborative simulation, optimize the initial collaborative control strategy according to the collaborative simulation heat dissipation result, and generate a collaborative control optimization strategy.

[0060] Optionally, based on the twin simulation method, the initial collaborative control strategy is collaboratively simulated. First, based on the spatial structure, real-time environmental information and equipment parameter characteristics of the target liquid cooling room, a digital twin model is created to accurately simulate the physical characteristics and operating status of the actual system. Then, the initial collaborative control strategy is run in the digital twin model. Through virtual simulation, the temperature distribution of the target liquid cooling room after the initial collaborative control strategy is applied is obtained, and the collaborative simulation heat dissipation results are obtained. Then, the collaborative simulation results are analyzed to identify the shortcomings of the initial control strategy, such as local overheating, excessive energy consumption, etc.; then, the control strategy is adjusted according to the analysis results, and the parameters and rules are optimized to generate a new collaborative control optimization strategy. Among them, the optimization measures include adjusting the fan speed, optimizing the coolant flow, improving the heat exchanger settings, adjusting the environmental parameters, etc.

[0061] Optionally, the collaborative control optimization strategy is simulated and verified again in the digital twin model. If the collaborative control optimization strategy performs better than the initial collaborative control strategy in the simulation, it is used as the new collaborative control scheme.

[0062] The collaborative control module 15 is used to execute the collaborative control optimization strategy to collaboratively control the target liquid cooling room.

[0063] Optionally, update the transmission collaborative control optimization strategy to the corresponding distributed cooling unit to perform collaborative control of the target liquid cooling room.

[0064] In summary, the liquid cooling room distributed heat dissipation unit collaborative control system provided by the present invention has the following technical effects:

[0065] The real-time monitoring module deploys multiple sensors based on the spatial structure of the target liquid cooling room to generate a sensor network, and the target liquid cooling room is monitored in real time through the sensor network to obtain multiple sets of real-time operating parameters; the heat dissipation demand evaluation module constructs an environmental control unit based on the multiple real-time operating parameters, performs heat dissipation evaluation on the target liquid cooling room according to the multiple real-time operating parameters, determines the heat dissipation demand evaluation results, and constructs multiple heat dissipation units according to the heat dissipation evaluation results; the initial collaborative strategy module combines the multiple heat dissipation units with the environmental control unit for collaborative control and formulates an initial collaborative control strategy; the strategy simulation optimization module executes the initial collaborative control strategy for collaborative simulation, optimizes the initial collaborative control strategy according to the collaborative simulation heat dissipation results, and generates a collaborative control optimization strategy; the collaborative control module executes the collaborative control optimization strategy to perform collaborative control on the target liquid cooling room. This has the technical effect of improving heat dissipation efficiency and reducing system energy consumption.

[0066] It should be understood that the embodiments disclosed in the present invention and the above description can enable those skilled in the art to use the present invention to implement the present invention. At the same time, the present invention is not limited to the above-mentioned embodiments. It should be understood that those skilled in the art can still modify the technical solutions recorded in the above-mentioned embodiments, or replace some of the technical features therein by equivalents; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the protection scope of the present invention.

Claims

1. Liquid cooling room distributed heat dissipation unit collaborative control system, characterized in that: The system comprises: A real-time monitoring module, which is used to deploy multiple sensors based on the spatial structure of the target liquid cooling room to generate a sensor network, and to monitor the target liquid cooling room in real time through the sensor network to obtain multiple real-time operating parameters; a heat dissipation demand assessment module, the heat dissipation demand assessment module being used to construct an environmental control unit based on the multiple real-time operating parameters, perform heat dissipation assessment on a target liquid cooling room according to the multiple real-time operating parameters, determine a heat dissipation demand assessment result, and construct a plurality of heat dissipation units according to the heat dissipation demand assessment result; An initial collaborative strategy module, the initial collaborative strategy module is used to coordinate the multiple heat dissipation units with the environmental control unit to formulate an initial collaborative control strategy; A strategy simulation optimization module, wherein the strategy simulation optimization module is used to execute the initial collaborative control strategy to perform collaborative simulation, optimize the initial collaborative control strategy according to the collaborative simulation heat dissipation result, and generate a collaborative control optimization strategy; A collaborative control module, the collaborative control module is used to execute the collaborative control optimization strategy to collaboratively control the target liquid cooling room; The environmental control unit is constructed based on the multiple real-time operating parameters, and the execution steps of the system include: Extracting features from the multiple real-time operating parameters to generate key operating features; The key operation characteristics are used as input variables of a decision tree, and a decision tree algorithm is used to recursively divide the multiple actual operation parameters according to the input variables until a preset number of recursions is met, thereby constructing an environmental control decision tree model; Adding the environmental control decision tree model to the environmental control unit; According to the heat dissipation demand evaluation result, a plurality of heat dissipation units are constructed, and the execution steps of the system include: Based on the heat dissipation demand assessment result, a heat dissipation analysis is performed on the target liquid cooling room to generate multiple heat dissipation demand information; Determine a heat dissipation optimization direction based on the multiple real-time operating parameters and the multiple heat dissipation demand information, wherein the heat dissipation optimization direction includes changing a fan speed and increasing a coolant flow rate; Traversing multiple heat dissipation areas for matching according to the heat dissipation optimization direction, and executing multiple heat dissipation instructions according to the matching results; The plurality of heat dissipation instructions are added to a plurality of heat dissipation units according to the plurality of heat dissipation areas.

2. The liquid cooling room distributed heat dissipation unit collaborative control system according to claim 1, characterized in that: The system deploys multiple sensors based on the spatial structure of the target liquid cooling room to generate a sensor network, and the execution steps of the system include: Performing a heat scan based on the spatial structure of the target liquid cooling room to obtain a heat distribution map; Perform heat analysis according to the heat distribution diagram to obtain heat accumulation concentration information and heat accumulation range information; According to the heat accumulation concentration information, the heat accumulation range is graded to obtain a heat accumulation grade, and heat accumulation points are marked on the heat distribution map according to the heat accumulation grade to generate a plurality of heat accumulation points; The multiple sensors are arranged based on the multiple heat accumulation points to generate the sensor network.

3. The liquid cooling room distributed heat dissipation unit collaborative control system according to claim 2, characterized in that: The target liquid cooling room is monitored in real time by the sensor network to obtain multiple real-time operating parameters. The execution steps of the system include: The plurality of heat accumulation points are monitored in real time based on the heat accumulation level by the sensor network to generate a heat accumulation monitoring data set; Building a cloud monitoring platform, transmitting the heat accumulation monitoring data set to the cloud monitoring platform, and determining whether the heat accumulation monitoring data set is in a preset cooling range through the cloud monitoring platform; If not, the sensor network is started to collect the real-time environment information of the target liquid cooling room to generate the multiple real-time operation parameters.

4. The liquid cooling room distributed heat dissipation unit collaborative control system according to claim 1, characterized in that: Performing heat dissipation evaluation on the target liquid cooling room according to the multiple real-time operating parameters to determine a heat dissipation demand evaluation result, the execution steps of the system include: Calculate the target liquid cooling room based on the multiple actual operation parameters to obtain multiple heat dissipation parameters of the target liquid cooling room, wherein the multiple heat dissipation parameters include heat load data, heat dissipation efficiency, and heat dissipation amount; Generate an environmental factor correction factor based on the heat load data, the heat dissipation efficiency, the heat dissipation amount, and the plurality of actual operating parameters; Based on the environmental factor correction factor, construct a heat dissipation evaluation function; The heat dissipation evaluation function is used to perform heat dissipation evaluation calculation to generate the heat dissipation demand evaluation result.

5. The liquid cooling room distributed heat dissipation unit collaborative control system according to claim 4, characterized in that: The heat dissipation evaluation function is: ;in, The results of the heat dissipation demand assessment are as follows: is the number of heat dissipation areas, For the The heat dissipation importance weight of each heat dissipation area, For the The heat dissipation of each heat dissipation area, For the The heat dissipation efficiency of each heat dissipation area is For the Environmental correction factors for each cooling area.

6. The liquid cooling room distributed heat dissipation unit collaborative control system according to claim 3, characterized in that: The multiple heat dissipation units are combined with the environmental control unit for collaborative control to formulate an initial collaborative control strategy, and the execution steps of the system include: The plurality of heat dissipation units and the environmental control unit are monitored and recorded by the cloud monitoring platform to generate a plurality of heat dissipation parameters and environmental control parameters; Formulate a collaborative control target according to the multiple heat dissipation parameters and the environmental control parameters; Based on multiple heat accumulation points, determining whether the operation control parameters of the target liquid cooling room meet the collaborative control target; If not, traverse the multiple heat accumulation points, activate the multiple heat dissipation units and / or the environmental control unit for coordinated control, and generate a coordinated control instruction; The cooperative control instruction is added to the initial cooperative control strategy.

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