Micro-grid load increment and liquid cooling system synchronous operation method and system

Abstract

The invention provides a micro-grid load increment and liquid cooling system synchronous operation method and system. According to the implementation scheme, boosting simulation is carried out on liquid cooling boosting branches corresponding to all load abrupt change nodes in the micro-grid, voltage reduction simulation is carried out on liquid cooling voltage reduction branches corresponding to all load stable nodes, and target rising hydraulic pressure of all the liquid cooling boosting branches and target falling hydraulic pressure of all the liquid cooling voltage reduction branches are obtained; on the basis of the predicted load sudden change probability of each load stabilization node in the first time and the target drop hydraulic pressure of the corresponding liquid cooling voltage reduction branch, the cooling insufficiency risk of each liquid cooling voltage reduction branch for heat dissipation of the corresponding load stabilization node is predicted; and adjusting the target drop hydraulic pressure of each liquid cooling step-down branch so as to operate the liquid cooling system in the first time to dissipate heat of the micro-grid. According to the invention, the heat dissipation efficiency of the micro-grid can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of mechatronic control, and particularly to a method and system for synchronous operation of the load increment of a microgrid and a liquid cooling system. Background Art

[0002] A microgrid refers to a small power generation and distribution system composed of distributed power sources, energy storage devices, energy conversion devices, monitoring and protection devices, etc. When these devices in the microgrid generate, transfer or bear load electric energy, certain heat energy will be generated. In some technologies, the microgrid is configured with a liquid cooling system as a heat dissipation device, which can not only reduce the temperature of the microgrid devices, but also recycle the heat energy.

[0003] Generally, multiple parallel U-shaped pipes are arranged in the liquid cooling system, and the liquid flow rate and flow velocity between each other can be controlled by some liquid flow valves. During the operation of the microgrid, how to control the flow distribution of each parallel branch in the liquid cooling system to improve the overall heat dissipation effect of the microgrid is a technical problem to be solved in this field. Summary of the Invention

[0004] The present invention provides a method and system for synchronous operation of the load increment of a microgrid and a liquid cooling system, which can solve at least one of the above technical problems.

[0005] According to one aspect of the present invention, there is provided a method for synchronous operation of the load increment of a microgrid and a liquid cooling system, including: Based on the current load change rate of each load node in the microgrid, determining the load mutation nodes and the load stable nodes; Performing a boost simulation on the liquid cooling boost branches corresponding to each of the load mutation nodes and performing a step-down simulation on the liquid cooling step-down branches corresponding to each of the load stable nodes to obtain the target rising hydraulic pressure of each of the liquid cooling boost branches and the target falling hydraulic pressure of each of the liquid cooling step-down branches; Based on the predicted load mutation probability of each of the load stable nodes within a first time period and the target falling hydraulic pressure of the corresponding liquid cooling step-down branch, predicting the cooling deficiency risk of each of the liquid cooling step-down branches for dissipating heat from the corresponding load stable node; Based on the cooling deficiency risk of each of the liquid cooling step-down branches, adjusting the target falling hydraulic pressure of each of the liquid cooling step-down branches; Based on the target rising hydraulic pressure of each of the liquid cooling boost branches and the adjusted target falling hydraulic pressure of each of the liquid cooling step-down branches, operating the liquid cooling system within the first time period to dissipate heat from the microgrid.

[0006] According to another aspect of the present invention, there is provided a device for synchronous operation of a microgrid load increment and a liquid cooling system, including: A load node determination module, configured to determine a load mutation node and a load stable node based on the current load change rate of each load node in the microgrid; A step-up / step-down simulation module, configured to perform step-up simulation on the liquid cooling step-up branches corresponding to each of the load mutation nodes and perform step-down simulation on the liquid cooling step-down branches corresponding to each of the load stable nodes, to obtain the target rising hydraulic pressure of each of the liquid cooling step-up branches and the target falling hydraulic pressure of each of the liquid cooling step-down branches; A risk prediction module, configured to predict the cooling insufficiency risk of each of the liquid cooling step-down branches for heat dissipation for the corresponding load stable nodes based on the predicted load mutation probability of each of the load stable nodes within a first time period and the target falling hydraulic pressure of the corresponding liquid cooling step-down branch; A hydraulic pressure adjustment module, configured to adjust the target falling hydraulic pressure of each of the liquid cooling step-down branches based on the cooling insufficiency risk of each of the liquid cooling step-down branches; A liquid cooling system operation module, configured to operate the liquid cooling system within the first time period based on the target rising hydraulic pressure of each of the liquid cooling step-up branches and the adjusted target falling hydraulic pressure of each of the liquid cooling step-down branches, to dissipate heat from the microgrid.

[0007] According to another aspect of the present invention, there is provided a system for synchronous operation of a microgrid load increment and a liquid cooling system, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein, the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the method for synchronous operation of a microgrid load increment and a liquid cooling system according to any one of the embodiments of the present invention.

[0008] According to another aspect of the present invention, there is provided a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to cause a computer to execute the method for synchronous operation of a microgrid load increment and a liquid cooling system according to any one of the embodiments of the present invention.

[0009] Adopting the technical solution of the present invention, based on the current load change rate of each load node in the microgrid, load mutation nodes and load stable nodes are determined; boost simulation is performed on the liquid-cooled boost branches corresponding to each load mutation node and step-down simulation is performed on the liquid-cooled step-down branches corresponding to each load stable node to obtain the target rising hydraulic pressure of each liquid-cooled boost branch and the target falling hydraulic pressure of each liquid-cooled step-down branch. In this way, accurate target rising hydraulic pressure of the liquid-cooled boost branches and target falling hydraulic pressure of the liquid-cooled step-down branches are obtained through boost and step-down simulations. Based on the predicted load mutation probability of each load stable node within the first time period and the target falling hydraulic pressure of its corresponding liquid-cooled step-down branch, the cooling deficiency risk of each liquid-cooled step-down branch for heat dissipation to its corresponding load stable node is predicted; based on the cooling deficiency risk of each liquid-cooled step-down branch, the target falling hydraulic pressure of each liquid-cooled step-down branch is adjusted; in this way, the situation where the liquid-cooled boost branch drops too much and causes insufficient heat dissipation can be avoided. Thus, based on the target rising hydraulic pressure of each liquid-cooled boost branch and the adjusted target falling hydraulic pressure of each liquid-cooled step-down branch, the liquid-cooling system is operated within the first time period to achieve balanced heat dissipation for the microgrid, which can not only improve the heat dissipation efficiency for load mutation nodes, but also avoid the situation of insufficient heat dissipation for load stable nodes.

[0010] It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present invention, nor is it used to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. Brief Description of the Drawings

[0011] The drawings are used to better understand the present solution and do not constitute a limitation to the present invention. Among them: Figure 1 is a flowchart of a method for synchronous operation of a microgrid load increment and a liquid-cooling system according to an embodiment of the present invention; Figure 2 is a schematic diagram of the structural distribution of a microgrid according to an embodiment of the present invention; Figure 3 is a block diagram of the structure of a device for synchronous operation of a microgrid load increment and a liquid-cooling system according to an embodiment of the present invention; Figure 4 is a block diagram of an electronic device for implementing the method according to an embodiment of the present invention. Detailed Embodiments

[0012] The following describes exemplary embodiments of the present invention in conjunction with the accompanying drawings. Various details of the embodiments of the present invention are included to facilitate understanding, and they should be considered merely exemplary. Therefore, those of ordinary skill in the art should recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope of the present invention. Similarly, descriptions of well-known functions and structures are omitted in the following description for clarity and conciseness.

[0013] Figure 1 is a flowchart of a method for synchronous operation of the load increment of a microgrid and a liquid cooling system according to an embodiment of the present invention.

[0014] As Figure 1 shown, the method for synchronous operation of the load increment of a microgrid and a liquid cooling system may include: S110, determining load mutation nodes and load stable nodes based on the current load change rates of each load node in the microgrid; S120, performing boost simulation on the liquid cooling boost branches corresponding to each load mutation node and performing step-down simulation on the liquid cooling step-down branches corresponding to each load stable node to obtain the target rising hydraulic pressure of each liquid cooling boost branch and the target falling hydraulic pressure of each liquid cooling step-down branch; S130, predicting the cooling deficiency risk of each liquid cooling step-down branch for heat dissipation of its corresponding load stable node based on the predicted load mutation probability of each load stable node within a first time period and the target falling hydraulic pressure of its corresponding liquid cooling step-down branch; S140, adjusting the target falling hydraulic pressure of each liquid cooling step-down branch based on the cooling deficiency risk of each liquid cooling step-down branch; S150, operating the liquid cooling system within the first time period based on the target rising hydraulic pressure of each liquid cooling boost branch and the adjusted target falling hydraulic pressure of each liquid cooling step-down branch to dissipate heat from the microgrid.

[0015] Exemplarily, the microgrid may include a plurality of distributed load nodes and power generation nodes. Among them, the distribution of the load nodes may be as Figure 2 shown. The distances between these load nodes are not far, generally 1 meter or 2 meters, and of course, they can also be within 10 meters.

[0016] Exemplarily, the liquid cooling system may include a plurality of liquid cooling branches. One liquid cooling branch is respectively arranged in one load node to dissipate heat from the equipment of the load node. Each liquid cooling branch may include connected liquid cooling elbows or U-shaped tubes. A switch valve may be arranged at the inlet of each liquid cooling branch to control the inlet opening and the hydraulic pressure of the branch. By controlling the hydraulic pressure of each branch, the liquid flow velocity in each liquid cooling branch can be adjusted, and the heat exchange efficiency can be adjusted.

[0017] Exemplarily, if the current load change rate of a load node in the microgrid is greater than a preset load change rate threshold, then determine that the load node is a load mutation node; if the current load change rate of a load node in the microgrid is less than the preset load change rate threshold, then determine that the load node is a load stable node.

[0018] Exemplarily, the load change rate threshold can be the average or median of the current load change rates of each load node in the microgrid.

[0019] It can be understood that a load mutation node can be a node where the load suddenly increases or suddenly decreases. A load stable node can be a node with a relatively small load change rate, which means that the load remains unchanged or changes slightly.

[0020] Exemplarily, for the first time period from the current moment to the next moment, boost simulation can be performed on the liquid-cooled boost branches corresponding to each load mutation node and step-down simulation can be performed on the liquid-cooled step-down branches corresponding to each load stable node to obtain the target rising hydraulic pressure of each liquid-cooled boost branch and the target falling hydraulic pressure of each liquid-cooled step-down branch. The boost simulation and the step-down simulation can be performed simultaneously, or the boost simulation can be performed first and then the step-down simulation.

[0021] Exemplarily, first, using the current load change rate and the current load value of each load mutation node, predict the predicted load change amplitude of the liquid-cooled boost branch corresponding to each load mutation node within the first time period. Based on the predicted load change amplitude, perform boost simulation on the liquid-cooled boost branches corresponding to each load mutation node and perform step-down simulation on the liquid-cooled step-down branches corresponding to each load stable node to obtain the target rising hydraulic pressure of each liquid-cooled boost branch and the target falling hydraulic pressure of each liquid-cooled step-down branch.

[0022] It can be understood that the target rising hydraulic pressure is used to control the hydraulic pressure of the liquid-cooled boost branch to rise and reach the value of the target rising hydraulic pressure, and the target falling hydraulic pressure is used to control the hydraulic pressure of the liquid-cooled step-down branch to fall and reach the value of the target falling hydraulic pressure.

[0023] Exemplarily, based on the historical hydraulic pressure drop amplitude and the corresponding historical cooling deficiency impact degree, construct a mapping relationship between the hydraulic pressure drop amplitude and the historical cooling deficiency impact degree. Based on the difference between the current hydraulic pressure and the target falling hydraulic pressure of the load stable node, determine the estimated hydraulic pressure drop amplitude. Based on the estimated hydraulic pressure drop amplitude, find the corresponding cooling deficiency impact degree in the above mapping relationship. Based on the product of the found cooling deficiency impact degree and the predicted load mutation probability of the load stable node within the first time period, determine the cooling deficiency risk of the corresponding liquid-cooled step-down branch within the first time period.

[0024] Exemplarily, if the risk of insufficient cooling of the liquid-cooled step-down branch is too high, the value of the target hydraulic pressure drop of the liquid-cooled step-down branch is increased to reduce the amplitude of the hydraulic pressure drop. If the risk of insufficient cooling of the liquid-cooled step-down branch is small, the value of the target hydraulic pressure drop of the liquid-cooled step-down branch remains unchanged.

[0025] Exemplarily, based on the target rising hydraulic pressure of each liquid-cooled boost branch and the adjusted target falling hydraulic pressure of each liquid-cooled step-down branch, the hydraulic pressure of the hydraulic valve at the inlet of the corresponding branch is adjusted to operate the liquid-cooled system in the first time to achieve balanced heat dissipation for the power equipment at each load node in the microgrid.

[0026] According to the above embodiments, based on the current load change rate of each load node in the microgrid, load mutation nodes and load stable nodes are determined; boost simulation is performed on the liquid-cooled boost branches corresponding to each load mutation node and step-down simulation is performed on the liquid-cooled step-down branches corresponding to each load stable node to obtain the target rising hydraulic pressure of each liquid-cooled boost branch and the target falling hydraulic pressure of each liquid-cooled step-down branch. In this way, accurate target rising hydraulic pressure of the liquid-cooled boost branch and target falling hydraulic pressure of the liquid-cooled step-down branch are obtained through boost and step-down simulations. Based on the predicted load mutation probability of each load stable node in the first time and the target falling hydraulic pressure of the corresponding liquid-cooled step-down branch, the risk of insufficient cooling for each liquid-cooled step-down branch to dissipate heat for the corresponding load stable node is predicted; based on the risk of insufficient cooling of each liquid-cooled step-down branch, the target falling hydraulic pressure of each liquid-cooled step-down branch is adjusted; in this way, the situation where the liquid-cooled boost branch drops too much and causes insufficient heat dissipation can be avoided. Thus, based on the target rising hydraulic pressure of each liquid-cooled boost branch and the adjusted target falling hydraulic pressure of each liquid-cooled step-down branch, the liquid-cooled system is operated in the first time to achieve balanced heat dissipation for the microgrid, which can not only improve the heat dissipation efficiency for load mutation nodes, but also avoid the situation of insufficient heat dissipation for load stable nodes.

[0027] In one embodiment, a boost simulation is performed on the liquid-cooled boost branches corresponding to each load mutation node, and a step-down simulation is performed on the liquid-cooled step-down branches corresponding to each load stable node, to obtain the target rising hydraulic pressure of each liquid-cooled boost branch and the target falling hydraulic pressure of each liquid-cooled step-down branch, including: determining the liquid flow resistance coefficients respectively from the liquid-cooled step-down branches corresponding to each load stable node to the liquid-cooled boost branches corresponding to the load mutation nodes based on the distances between the load mutation nodes and each load stable node; performing a boost simulation on the liquid-cooled boost branches based on the liquid flow resistance coefficients from the liquid-cooled step-down branches corresponding to each load stable node to the liquid-cooled boost branches corresponding to the load mutation nodes, and the predicted load change amplitude of the load mutation node within the first time period, to obtain the target rising hydraulic pressure of the liquid-cooled boost branches; and determining the target falling hydraulic pressure of each liquid-cooled step-down branch based on the target rising hydraulic pressure of each liquid-cooled boost branch.

[0028] Exemplarily, a preset liquid flow resistance coefficient calculation function can be adopted, and the distance between the load mutation node and the load stable node is input into the liquid flow resistance coefficient calculation function to obtain the output liquid flow resistance coefficient. Among them, the function can be a linear function. The greater the distance between the load mutation node and the load stable node, the greater the liquid flow resistance coefficient between the corresponding branches of the two.

[0029] Exemplarily, with the liquid-cooled step-down branches remaining unchanged, a boost simulation is performed on the liquid-cooled boost branches to obtain the corresponding target rising hydraulic pressure.

[0030] Exemplarily, after obtaining the target rising hydraulic pressure of each liquid-cooled boost branch, the target falling hydraulic pressure of each liquid-cooled step-down branch is determined based on the target rising hydraulic pressure of each liquid-cooled boost branch. For example, the amplitudes of the target rising hydraulic pressure of each liquid-cooled boost branch relative to its current hydraulic pressure are summed to obtain the total hydraulic pressure rising amplitude. Then, a genetic algorithm is used to solve for minimizing the standard deviation between the amplitudes of the target falling hydraulic pressure of each liquid-cooled step-down branch relative to its current hydraulic pressure, and the sum of the amplitudes of the target falling hydraulic pressure of each liquid-cooled step-down branch relative to its current hydraulic pressure is equal to the total hydraulic pressure rising amplitude. In this way, the target falling hydraulic pressure of each liquid-cooled step-down branch can be obtained.

[0031] According to the above embodiments, based on the distances between the load mutation nodes and each load stable node, the liquid flow resistance coefficients from the liquid cooling step-down branches corresponding to each load stable node to the liquid cooling step-up branch corresponding to the load mutation node are determined. Thus, using these liquid flow resistance coefficients, the predicted load change amplitudes of each load mutation node within the first time can be used to perform step-up simulation on the corresponding liquid cooling step-up branches, improving the simulation accuracy. Thus, the accurate target rising hydraulic pressure of the liquid cooling step-up branch can be obtained. Furthermore, based on the target rising hydraulic pressures of each liquid cooling step-up branch, the target falling hydraulic pressures of each liquid cooling step-down branch can also be accurately determined.

[0032] In one embodiment, based on the liquid flow resistance coefficients from the liquid cooling step-down branches corresponding to each load stable node to the liquid cooling step-up branch corresponding to the load mutation node, and the predicted load change amplitude of the load mutation node within the first time, a step-up simulation is performed on the liquid cooling step-up branch to obtain the target rising hydraulic pressure of the liquid cooling step-up branch, including: based on the current hydraulic pressure of the liquid cooling step-up branch corresponding to the load mutation node and the predicted load change amplitude of the load mutation node within the first time, determining the first predicted temperature change curve of the load mutation node within the first time; for each candidate rising hydraulic pressure, controlling the liquid cooling step-up branch to work under the candidate rising hydraulic pressure, and at the same time controlling the load mutation node to perform load change within the time length corresponding to the first time according to the predicted load change amplitude, so as to simulate the flow change of the liquid flow of each liquid cooling step-down branch to the liquid cooling step-up branch corresponding to the load mutation node under their respective corresponding liquid flow resistance coefficients, and obtaining the simulated temperature change curve of the load mutation node within the time length corresponding to the first time; based on the difference between the first predicted temperature change curve and the simulated temperature change curves corresponding to each candidate rising hydraulic pressure, determining the target rising hydraulic pressure of the liquid cooling step-up branch among each candidate rising hydraulic pressure.

[0033] It can be understood that for the determination process of the target rising hydraulic pressure of each liquid cooling step-up branch, it can be determined according to the above example.

[0034] It can be understood that the first predicted temperature change curve is used to describe the temperature change of the load mutation node within the first time when the current hydraulic pressure remains unchanged.

[0035] Exemplarily, based on the deviation values of each time point between the first predicted temperature change curve and the simulated temperature change curves corresponding to the candidate rising hydraulic pressures, the deviation degree between the first predicted temperature change curve and the simulated temperature change curves corresponding to the candidate rising hydraulic pressures is determined. Thus, using the deviation degrees between the first predicted temperature change curve and the simulated temperature change curves corresponding to each candidate rising hydraulic pressure, the candidate rising hydraulic pressure with the smallest deviation degree is selected among each candidate rising hydraulic pressure as the target rising hydraulic pressure of the liquid cooling step-up branch.

[0036] According to the above embodiments, based on the liquid flow resistance coefficients between the liquid cooling step-down branches corresponding to each load stable node and the liquid cooling step-up branches corresponding to the load mutation nodes, and the predicted load change amplitude of the load mutation nodes within the first time period, a step-up simulation is performed on the liquid cooling step-up branches, and the target rising hydraulic pressure of the liquid cooling step-up branches can be accurately obtained.

[0037] In one embodiment, determining the target descending hydraulic pressure of each liquid cooling step-down branch based on the target rising hydraulic pressure of each liquid cooling step-up branch includes: determining the total rising hydraulic pressure based on the target rising hydraulic pressure of each liquid cooling step-up branch; and determining the target descending hydraulic pressure of each liquid cooling step-down branch based on the total rising hydraulic pressure.

[0038] It can be understood that the total rising hydraulic pressure is the total hydraulic pressure rising amplitude. The total hydraulic pressure rising amplitude of each liquid cooling step-up branch should be equal to or greater than the total descending hydraulic pressure of each liquid cooling step-down branch. For example, in addition to providing liquid cooling branches for each load node, a standby liquid cooling storage tank can be provided in the system so that the pressurization effect can still be achieved when pressurizing a certain or some liquid cooling branches while other branches remain unpressurized.

[0039] Exemplarily, after obtaining the target rising hydraulic pressure of each liquid cooling step-up branch, the target descending hydraulic pressure of each liquid cooling step-down branch is determined based on the target rising hydraulic pressure of each liquid cooling step-up branch. For example, the amplitudes of the target rising hydraulic pressure of each liquid cooling step-up branch relative to its current hydraulic pressure are summed to obtain the total hydraulic pressure rising amplitude.

[0040] Exemplarily, a genetic algorithm is used to solve for minimizing the standard deviation of the amplitudes between the target descending hydraulic pressure of each liquid cooling step-down branch and its current hydraulic pressure, and the sum of the amplitudes between the target descending hydraulic pressure of each liquid cooling step-down branch and its current hydraulic pressure is equal to the total hydraulic pressure rising amplitude. In this way, the target descending hydraulic pressure of each liquid cooling step-down branch can be obtained.

[0041] According to the above embodiments, based on the target rising hydraulic pressure of each liquid cooling step-up branch, the total rising hydraulic pressure amplitude is obtained. In this way, the total descending hydraulic pressure amplitude can be determined, and the total descending hydraulic pressure amplitude is used to determine the target descending hydraulic pressure of each liquid cooling step-down branch, thereby accurately obtaining the target descending hydraulic pressure of each liquid cooling step-down branch.

[0042] In one embodiment, based on the predicted load mutation probability of each load stable node within the first time period and the target decreased hydraulic pressure of the corresponding liquid cooling pressure reduction branch, the cooling deficiency risk of each liquid cooling pressure reduction branch for heat dissipation of its corresponding load stable node is predicted, including: predicting the second predicted temperature change curve of the liquid cooling pressure reduction branch within the first time period based on the predicted load mutation probability of the load stable node within the first time period and the current hydraulic pressure of the liquid cooling pressure reduction branch corresponding to the load stable node; predicting the third predicted temperature change curve of the liquid cooling pressure reduction branch within the first time period based on the predicted load mutation probability of the load stable node within the first time period and the target decreased hydraulic pressure of the liquid cooling pressure reduction branch corresponding to the load stable node; determining the cooling deficiency risk of the liquid cooling pressure reduction branch for heat dissipation of the load stable node based on the difference between the second predicted temperature change curve and the third predicted temperature change curve.

[0043] Exemplarily, based on the predicted load mutation probability of the load stable node within the first time period, the predicted load mutation probability of the load stable node at each moment within the first time period is determined. Thus, in combination with the current hydraulic pressure of the liquid cooling pressure reduction branch corresponding to the load stable node, the second predicted temperature change curve of the liquid cooling pressure reduction branch within the first time period can be predicted. For example, by inputting the current hydraulic pressure of the liquid cooling pressure reduction branch corresponding to the load stable node and the predicted load mutation probability of the load stable node at each moment within the first time period into the simulation platform, the second predicted temperature change curve of the liquid cooling pressure reduction branch within the first time period output by the simulation platform can be obtained.

[0044] Exemplarily, based on the predicted load mutation probability of the load stable node within the first time period, the predicted load mutation probability of the load stable node at each moment within the first time period is determined. Thus, in combination with the target decreased hydraulic pressure of the liquid cooling pressure reduction branch corresponding to the load stable node, the third predicted temperature change curve of the liquid cooling pressure reduction branch within the first time period can be predicted. For example, by inputting the target decreased hydraulic pressure of the liquid cooling pressure reduction branch corresponding to the load stable node and the predicted load mutation probability of the load stable node at each moment within the first time period into the simulation platform, the third predicted temperature change curve of the liquid cooling pressure reduction branch within the first time period output by the simulation platform can be obtained.

[0045] Exemplarily, based on the temperature at each time point of the second predicted temperature change curve and the temperature at the corresponding time point of the third predicted temperature change curve, the temperature deviation degree between the two curves is determined. Using the temperature deviation degree of the two curves, the cooling deficiency risk is determined. If the temperature deviation degree is higher, the cooling deficiency risk is greater.

[0046] According to the above embodiment, the cooling deficiency risk of the liquid cooling pressure reduction branch for heat dissipation of its corresponding load stable node can be accurately predicted.

[0047] In one embodiment, based on the cooling deficiency risks of each liquid cooling pressure reduction branch, adjusting the target reduced hydraulic pressure of each liquid cooling pressure reduction branch includes: when the cooling deficiency risk of a liquid cooling pressure reduction branch is greater than a preset first risk threshold, multiplying the difference between the cooling deficiency risk of the liquid cooling pressure reduction branch and the first risk threshold by a preset standard hydraulic amplitude to obtain a first value; based on the first value, increasing the target reduced hydraulic pressure of the liquid cooling pressure reduction branch to obtain the adjusted target reduced hydraulic pressure of the liquid cooling pressure reduction branch.

[0048] Exemplarily, adding the first value to the target reduced hydraulic pressure of the liquid cooling pressure reduction branch to obtain the adjusted target reduced hydraulic pressure of the liquid cooling pressure reduction branch.

[0049] According to the above embodiment, based on the cooling deficiency risks of each liquid cooling pressure reduction branch, adjusting the target reduced hydraulic pressure of each liquid cooling pressure reduction branch can avoid the situation of insufficient heat dissipation at the corresponding load stable nodes of the subsequent liquid cooling pressure reduction branches.

[0050] Figure 3 It is a structural block diagram of a device for synchronous operation of a microgrid load increment and a liquid cooling system according to an embodiment of the present invention.

[0051] As Figure 3 shown, the device for synchronous operation of a microgrid load increment and a liquid cooling system may include: A load node determination module 310, configured to determine a load mutation node and a load stable node based on the current load change rate of each load node in the microgrid; A boost and reduction simulation module 320, configured to perform a boost simulation on the liquid cooling boost branch corresponding to each load mutation node and a reduction simulation on the liquid cooling pressure reduction branch corresponding to each load stable node to obtain the target increased hydraulic pressure of each liquid cooling boost branch and the target reduced hydraulic pressure of each liquid cooling pressure reduction branch; A risk prediction module 330, configured to predict the cooling deficiency risk of each liquid cooling pressure reduction branch for heat dissipation to its corresponding load stable node based on the predicted load mutation probability of each load stable node within a first time period and the target reduced hydraulic pressure of its corresponding liquid cooling pressure reduction branch; A hydraulic pressure adjustment module 340, configured to adjust the target reduced hydraulic pressure of each liquid cooling pressure reduction branch based on the cooling deficiency risk of each liquid cooling pressure reduction branch; A liquid cooling system operation module 350, configured to operate the liquid cooling system within the first time period based on the target increased hydraulic pressure of each liquid cooling boost branch and the adjusted target reduced hydraulic pressure of each liquid cooling pressure reduction branch to dissipate heat from the microgrid.

[0052] In one embodiment, the buck-boost simulation module 320 includes: A resistance coefficient determination unit configured to respectively determine the liquid flow resistance coefficients from the liquid-cooled buck branches corresponding to each load stable node to the liquid-cooled boost branch corresponding to the load mutation node based on the distances between the load mutation node and each load stable node; A boost simulation unit configured to perform a boost simulation on the liquid-cooled boost branch based on the liquid flow resistance coefficients from the liquid-cooled buck branches corresponding to each load stable node to the liquid-cooled boost branch corresponding to the load mutation node, and the predicted load change amplitude of the load mutation node within the first time period, to obtain the target rising hydraulic pressure of the liquid-cooled boost branch; A descending hydraulic pressure determination unit configured to determine the target descending hydraulic pressures of the respective liquid-cooled buck branches based on the target rising hydraulic pressures of the respective liquid-cooled boost branches.

[0053] In one embodiment, the boost simulation unit is specifically configured to: Determine a first predicted temperature change curve of the load mutation node within the first time period based on the current hydraulic pressure of the liquid-cooled boost branch corresponding to the load mutation node and the predicted load change amplitude of the load mutation node within the first time period; For each candidate rising hydraulic pressure, control the liquid-cooled boost branch to operate at the candidate rising hydraulic pressure, and at the same time control the load mutation node to change its load within the time length corresponding to the first time period according to the predicted load change amplitude, so as to simulate the flow change of the liquid flows of the respective liquid-cooled buck branches to the liquid-cooled boost branch corresponding to the load mutation node under their respective corresponding liquid flow resistance coefficients, and obtain a simulated temperature change curve of the load mutation node within the time length corresponding to the first time period; Based on the difference between the first predicted temperature change curve and the simulated temperature change curves corresponding to each candidate rising hydraulic pressure, determine the target rising hydraulic pressure of the liquid-cooled boost branch among each candidate rising hydraulic pressure.

[0054] In one embodiment, the descending hydraulic pressure determination unit is specifically configured to: Determine a total rising hydraulic pressure based on the target rising hydraulic pressures of the respective liquid-cooled boost branches; Determine the target descending hydraulic pressures of the respective liquid-cooled buck branches based on the total rising hydraulic pressure.

[0055] In one embodiment, the risk prediction module 330 includes: The first curve determination unit is configured to predict a second predicted temperature change curve of the liquid-cooled pressure-reducing branch in the first time based on the predicted load mutation probability of the load stable node in the first time and the current hydraulic pressure of the liquid-cooled pressure-reducing branch corresponding to the load stable node; The second curve determination unit is configured to predict a third predicted temperature change curve of the liquid-cooled pressure-reducing branch in the first time based on the predicted load mutation probability of the load stable node in the first time and the target reduced hydraulic pressure of the liquid-cooled pressure-reducing branch corresponding to the load stable node; The risk prediction unit is configured to determine a cooling deficiency risk of the liquid-cooled pressure-reducing branch for heat dissipation of the load stable node based on the difference between the second predicted temperature change curve and the third predicted temperature change curve.

[0056] In one embodiment, the hydraulic pressure adjustment module 340 includes: The first value determination unit is configured to multiply the difference between the cooling deficiency risk of the liquid-cooled pressure-reducing branch and the first risk threshold by a preset hydraulic pressure standard amplitude to obtain a first value when the cooling deficiency risk of the liquid-cooled pressure-reducing branch is greater than a preset first risk threshold; The hydraulic pressure value adjustment unit is configured to increase the target reduced hydraulic pressure of the liquid-cooled pressure-reducing branch based on the first value to obtain the adjusted liquid-cooled pressure-reducing branch.

[0057] For the specific functions and examples of the modules and sub-modules of the system according to the embodiments of the present invention, reference may be made to the relevant descriptions of the corresponding steps in the above method embodiments, which will not be repeated here.

[0058] In the technical solution of the present invention, the acquisition, storage, and application of the user's personal information involved all comply with the provisions of relevant laws and regulations and do not violate public order and good customs.

[0059] According to the embodiments of the present invention, the present invention also provides a system and a readable storage medium.

[0060] Figure 4 FIG. shows a schematic block diagram of an exemplary electronic device 800 that can be used to implement the embodiments of the present invention. The electronic device is intended to represent various forms of digital computers, such as, laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as, personal digital assistants, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are only examples and are not intended to limit the implementation of the present invention described herein and / or claimed.

[0061] As shown Figure 4 in FIG. 1, the electronic device 800 includes a computing unit 801, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 802 or a computer program loaded from a storage unit 808 into a random access memory (RAM) 803. In the RAM 803, various programs and data required for the operation of the device 800 can also be stored. The computing unit 801, the ROM 802, and the RAM 803 are connected to each other via a bus 804. An input / output (I / O) interface 805 is also connected to the bus 804.

[0062] A plurality of components in the electronic device 800 are connected to the I / O interface 805, including: an input unit 806, such as a keyboard, a mouse, etc.; an output unit 807, such as various types of displays, speakers, etc.; a storage unit 808, such as a magnetic disk, an optical disc, etc.; and a communication unit 809, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 809 allows the device 800 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0063] The computing unit 801 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 801 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 801 executes the various methods and processes described above, such as the method for synchronous operation of the microgrid load increment and the liquid cooling system. For example, in some embodiments, the method for synchronous operation of the microgrid load increment and the liquid cooling system can be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as the storage unit 808. In some embodiments, part or all of the computer program can be loaded and / or installed onto the device 800 via the ROM 802 and / or the communication unit 809. When the computer program is loaded into the RAM 803 and executed by the computing unit 801, one or more steps of the method for synchronous operation of the microgrid load increment and the liquid cooling system described above can be executed. Alternatively, in other embodiments, the computing unit 801 can be configured to execute the method for synchronous operation of the microgrid load increment and the liquid cooling system by any other suitable means (e.g., by means of firmware).

[0064] The various embodiments of the systems and techniques described above in this specification can be implemented in digital electronic circuitry, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on a chip (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include: being implemented in one or more computer programs that are executable and / or interpretable on a programmable system including at least one programmable processor, which can be a special-purpose or general-purpose programmable processor that receives data and instructions from, and transmits data and instructions to, a storage system, at least one input device, and at least one output device.

[0065] The program code for implementing the methods of the present invention can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the program codes, when executed by the processor or controller, cause the functions / operations specified in the flowchart and / or block diagram to be implemented. The program code can be executed entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine, or entirely on the remote machine or server.

[0066] In the context of the present invention, a machine-readable medium can be a tangible medium that can contain or store a program for use by or in connection with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0067] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the computer. Other kinds of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0068] The systems and techniques described herein can be implemented in a computing system including backend components (e.g., as a data server), or a computing system including middleware components (e.g., an application server), or a computing system including frontend components (e.g., a user computer having a graphical user interface or a web browser through which the user can interact with an implementation of the systems and techniques described herein), or a computing system including any combination of such backend components, middleware components, or frontend components. The components of the system can be interconnected by digital data communication in any form or medium (e.g., a communication network). Examples of communication networks include: local area network (LAN), wide area network (WAN), and the Internet.

[0069] A computer system can include a client and a server. The client and the server are generally far from each other and typically interact through a communication network. The relationship between the client and the server is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, a server of a distributed system, or a server incorporating a blockchain.

[0070] It should be understood that various forms of the processes shown above can be used, with steps reordered, added, or deleted. For example, the steps recited in the present invention can be executed in parallel, sequentially, or in a different order, as long as the desired results of the technical solutions disclosed in the present invention can be achieved, and no limitation is made herein.

[0071] The above specific embodiments do not constitute a limitation on the protection scope of the present invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the principles of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for synchronous operation of microgrid load increment and liquid cooling system, characterized in that: include: Based on the current load change rate of each load node in the microgrid, determine the load mutation node and the load stability node; Performing a pressure-increasing simulation on the liquid-cooled pressure-increasing branch corresponding to each of the load mutation nodes and performing a pressure-reducing simulation on the liquid-cooled pressure-reducing branch corresponding to each of the load stability nodes, to obtain a target rising hydraulic pressure of each of the liquid-cooled pressure-increasing branches and a target falling hydraulic pressure of each of the liquid-cooled pressure-reducing branches; Based on the predicted load mutation probability of each load stabilizing node within the first time and the target drop hydraulic pressure of each corresponding liquid-cooled pressure-reducing branch, the risk of insufficient cooling of each liquid-cooled pressure-reducing branch for heat dissipation of the corresponding load stabilizing node is predicted; Based on the risk of insufficient cooling of each of the liquid-cooled pressure-reducing branches, adjusting the target hydraulic pressure reduction of each of the liquid-cooled pressure-reducing branches; Based on the target rising hydraulic pressure of each of the liquid-cooled boost branches and the adjusted target falling hydraulic pressure of each of the liquid-cooled buck branches, the liquid cooling system is operated within the first time to dissipate heat from the microgrid.

2. The method according to claim 1, characterized in that: The step of performing a pressure-increasing simulation on the liquid-cooled pressure-increasing branch corresponding to each of the load mutation nodes and performing a pressure-increasing simulation on the liquid-cooled pressure-increasing branch corresponding to each of the load stability nodes to obtain a target rising hydraulic pressure of each of the liquid-cooled pressure-increasing branches and a target falling hydraulic pressure of each of the liquid-cooled pressure-increasing branches includes: Based on the distance between the load mutation node and each of the load stabilization nodes, respectively determine the liquid flow resistance coefficient between the liquid cooling pressure reduction branch corresponding to each of the load stabilization nodes and the liquid cooling pressure boost branch corresponding to the load mutation node; Based on the liquid flow resistance coefficient between the liquid cooling pressure reduction branch corresponding to each load stabilization node and the liquid cooling pressure boost branch corresponding to the load mutation node, and the predicted load change amplitude of the load mutation node within the first time, the liquid cooling pressure boost branch is simulated to obtain the target rising hydraulic pressure of the liquid cooling pressure boost branch; The target lowering hydraulic pressure of each of the liquid-cooling pressure-increasing branches is determined based on the target rising hydraulic pressure of each of the liquid-cooling pressure-increasing branches.

3. The method according to claim 2, characterized in that The step of performing a pressure boost simulation on the liquid-cooled pressure boost branch based on the liquid flow resistance coefficient between the liquid-cooled pressure reduction branch corresponding to each load stabilization node and the liquid-cooled pressure boost branch corresponding to the load mutation node, and the predicted load change amplitude of the load mutation node within the first time, to obtain a target rising hydraulic pressure of the liquid-cooled pressure boost branch, includes: Determine a first predicted temperature change curve of the load mutation node within the first time based on the current hydraulic pressure of the liquid-cooled boost branch corresponding to the load mutation node and the predicted load change amplitude of the load mutation node within the first time; For each candidate rising hydraulic pressure, the liquid-cooled boost branch is controlled to operate under the candidate rising hydraulic pressure, and at the same time, the load mutation node is controlled to perform load change within the time length corresponding to the first time according to the predicted load change amplitude, so as to simulate the flow change of the liquid flow of each of the liquid-cooled pressure-reducing branches to the liquid-cooled boost branch corresponding to the load mutation node under the respective corresponding liquid flow resistance coefficients, and obtain a simulated temperature change curve of the load mutation node within the time length corresponding to the first time; Based on the difference between the first predicted temperature variation curve and the simulated temperature variation curve corresponding to each of the candidate rising hydraulic pressures, the target rising hydraulic pressure of the liquid-cooling boost branch is determined from among the candidate rising hydraulic pressures.

4. The method according to claim 2, characterized in that: The step of determining the target lowering hydraulic pressure of each of the liquid-cooled pressure-reducing branches based on the target rising hydraulic pressure of each of the liquid-cooled pressure-reducing branches comprises: determining a total rising hydraulic pressure based on target rising hydraulic pressures of the respective liquid-cooling boost branches; Based on the total rising hydraulic pressure, the target falling hydraulic pressure of each of the liquid-cooling pressure-reducing branches is determined.

5. The method according to claim 1, characterized in that: The predicting of insufficient cooling risk of each of the liquid-cooled pressure-reducing branches for heat dissipation of the corresponding load stabilizing nodes based on the predicted load mutation probability of each of the load stabilizing nodes within the first time and the target drop hydraulic pressure of each of the corresponding liquid-cooled pressure-reducing branches includes: Based on the predicted load mutation probability of the load stabilization node within the first time and the current hydraulic pressure of the liquid-cooled pressure-reducing branch corresponding to the load stabilization node, predict a second predicted temperature change curve of the liquid-cooled pressure-reducing branch within the first time; Based on the predicted load mutation probability of the load stabilization node within the first time and the target drop hydraulic pressure of the liquid-cooled pressure-reducing branch corresponding to the load stabilization node, predict a third predicted temperature change curve of the liquid-cooled pressure-reducing branch within the first time; Based on the difference between the second predicted temperature change curve and the third predicted temperature change curve, the risk of insufficient cooling of the liquid-cooled pressure-reducing branch for heat dissipation of the load stabilizing node is determined.

6. The method according to claim 1, characterized in that The step of adjusting the target hydraulic pressure drop of each of the liquid-cooled pressure-reducing branches based on the risk of insufficient cooling of each of the liquid-cooled pressure-reducing branches comprises: When the risk of insufficient cooling of the liquid-cooled pressure-reducing branch is greater than a preset first risk threshold, multiplying the difference between the risk of insufficient cooling of the liquid-cooled pressure-reducing branch and the first risk threshold and a preset hydraulic standard amplitude to obtain a first value; Based on the first value, the target lowering hydraulic pressure of the liquid-cooled pressure-reducing branch is increased to obtain the adjusted liquid-cooled pressure-reducing branch.

7. A device for synchronous operation of microgrid load increment and liquid cooling system, characterized in that: include: A load node determination module is used to determine a load mutation node and a load stability node based on the current load change rate of each load node in the microgrid; A boost and depressurization simulation module, used to perform boost simulation on the liquid-cooled boost branch corresponding to each of the load mutation nodes and to perform depressurization simulation on the liquid-cooled depressurization branch corresponding to each of the load stability nodes, to obtain a target rising hydraulic pressure of each of the liquid-cooled boost branches and a target falling hydraulic pressure of each of the liquid-cooled depressurization branches; a risk prediction module, for predicting the risk of insufficient cooling of each of the liquid-cooled pressure-reducing branches for heat dissipation of the corresponding load stabilizing nodes based on the predicted load mutation probability of each of the load stabilizing nodes within the first time and the target drop hydraulic pressure of the corresponding liquid-cooled pressure-reducing branches; A hydraulic adjustment module, configured to adjust a target hydraulic pressure drop of each of the liquid-cooled pressure-reducing branches based on a risk of insufficient cooling of each of the liquid-cooled pressure-reducing branches; The liquid cooling system operation module is used to operate the liquid cooling system within the first time based on the target rising hydraulic pressure of each of the liquid cooling boost branches and the adjusted target falling hydraulic pressure of each of the liquid cooling step-down branches to dissipate heat for the microgrid.

8. The device according to claim 7, characterized in that The voltage step-up and voltage step-down simulation module comprises: a resistance coefficient determining unit, for determining, based on the distance between the load mutation node and each of the load stabilization nodes, respectively the liquid flow resistance coefficient between the liquid cooling pressure reduction branch corresponding to each of the load stabilization nodes and the liquid cooling pressure boost branch corresponding to the load mutation node; a boost simulation unit, configured to perform a boost simulation on the liquid-cooled boost branch based on a liquid flow resistance coefficient between the liquid-cooled pressure reduction branch corresponding to each of the load stabilization nodes and the liquid-cooled pressure boost branch corresponding to the load mutation node, and a predicted load change amplitude of the load mutation node within the first time, to obtain a target boost hydraulic pressure of the liquid-cooled boost branch; The descending hydraulic pressure determination unit is used to determine the target descending hydraulic pressure of each of the liquid-cooled pressure-reducing branches based on the target ascending hydraulic pressure of each of the liquid-cooled pressure-reducing branches.

9. A microgrid load increment and liquid cooling system synchronous operation system, comprising: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 6.

10. A non-transitory computer-readable storage medium storing computer instructions, wherein: The computer instructions are used to make a computer execute the method according to any one of claims 1-6.

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