A method and system for multiple cooling delta thermal load balancing and flow optimization

Abstract

The application provides a multi-cooling triangle heat load balancing and flow optimization method and system, and relates to the field of indirect air cooling systems. The method comprises the following steps: obtaining pipe network topology, step response data, wind field data, flow and temperature measured values, establishing a hydraulic and thermal coupling model, calculating the resistance coefficient and cooling coefficient of each branch, and obtaining a heat load balancing index in combination with the measured temperature; when the heat load balancing index exceeds a threshold value, a comprehensive optimization function is constructed with the minimum heat load deviation square, flow change rate square sum and valve throttling loss square sum as the target, and the target flow of each branch is solved; the target flow of each branch is fed forward and compensated through a hydraulic coupling matrix to obtain the compensated flow, and the target opening degree instruction of each valve is obtained based on the valve percentage characteristic; the deviation of the outlet water temperature of each branch and the target temperature is obtained, the target opening degree instruction of each valve is adjusted according to the deviation size, three priority levels and the same level sequence of decreasing first and then increasing, and the final execution instruction is generated.

Description

Technical Field

[0001] This invention relates to the field of indirect air-cooling system technology, specifically to a method and system for balancing heat load and optimizing flow in a multi-cooling triangle. Background Technology

[0002] In recent years, with the increasing demands for energy conservation and emission reduction in thermal power generation, indirect air-cooling systems have become increasingly widely used in large-scale generator units in coal-rich and water-scarce regions due to their superior water-saving performance. Indirect air-cooling systems typically consist of multiple parallel cooling triangular sectors, undertaking the heat exchange task at the cold end of the unit. This multi-sector parallel radiator array, with its large heat exchange area and adaptability to complex operating conditions, can dissipate large-scale heat loads and occupies a central position in various power plant cold-end condensation scenarios. In actual operation, the system is affected by environmental wind disturbances, varying distances from the center of the duct to each sector, and differences in the angle of attack. For operators relying solely on monitoring the main duct parameters, there are blind spots in local operating conditions. Therefore, practical use urgently requires understanding the true heat exchange status of each branch to intuitively assess overall cooling efficiency and prevent localized freezing.

[0003] Existing technologies for regulating the cooling of indirect air-cooled systems mainly include the louvered unified control method and manual intervention based on experience. The louvered unified control method is an extension of traditional control logic in the air-cooling field, requiring a pre-set fixed adjustment curve, but it often struggles to adapt to rapidly changing environmental wind field disturbances. Manual intervention based on experience involves operators manually adjusting the system by observing macroscopic back pressure and total return water temperature; its low operational threshold has led to its widespread use. However, due to the inherent uneven resistance of parallel pipelines and the specific characteristics of meteorological conditions, relying solely on manual experience or unified commands can result in significant hydraulic distribution deviations. The target cooling triangle often operates in a highly coupled and continuously disturbed environment, making it difficult for traditional single-loop control to effectively address the issues of uneven flow distribution and large differences in outlet water temperature among parallel branches. Therefore, there is an urgent need to introduce a synergistic mechanism between water-side flow and air-side cooling capacity to correct heat load deviations; however, research similar to this invention is limited. The existing indirect air-cooling system adjustment methods are mostly coarse adjustments based on the total inlet and outlet water parameters to adjust the fan speed or the overall movement of the louvers. These methods cannot address the challenges of eliminating water temperature deviations in each heat dissipation branch and achieving balanced heat load and precise flow distribution across multiple cooling triangles under complex operating conditions. Summary of the Invention

[0004] This invention addresses the problems existing in the prior art by providing a method and system for balancing heat load and optimizing flow in multiple cooling triangles. It overcomes the defects of hydraulic imbalance and uneven heat load distribution in existing indirect air-cooled systems operating with multiple sectors in parallel. It solves the technical problem that uneven heat load distribution is caused by factors such as uneven air field, strong hydraulic-thermal coupling, and valve nonlinearity in indirect air-cooled systems operating with multiple cooling triangles in parallel, and that traditional optimization methods cannot effectively decouple and achieve synergistic optimization of balance and flow.

[0005] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0006] Obtain pipeline topology, step response data, wind field data, and measured flow and temperature values; establish a hydraulic-thermal coupling model; calculate the resistance coefficient and cooling coefficient of each branch; and obtain the heat load balance index by combining the measured temperature. When the heat load balance index exceeds the threshold, a comprehensive optimization function is constructed with the objectives of minimizing the square of the heat load deviation, the sum of the squares of the flow rate change rate, and the sum of the squares of the valve throttling loss, and the target flow rate of each branch is solved. The target flow rate of each branch is compensated by the hydraulic coupling matrix feedforward compensation to obtain the compensated flow rate, and then the target opening command of each valve is obtained by back-calculation based on the valve equal percentage characteristics. The deviation between the outlet water temperature of each branch and the target temperature is obtained. The valves are adjusted according to the deviation in three priority levels, with the same level decreasing first and then increasing, to generate the final execution command.

[0007] In some embodiments, the process of acquiring pipeline topology, step response data, wind field data, measured flow and temperature values, establishing a hydraulic-thermal coupling model, and calculating the resistance coefficient and cooling coefficient of each branch includes: The topology of the parallel pipe network of the indirect air-cooled system, the step response data of each branch, and the wind field data are obtained. The pipe network is abstracted into a directed graph, in which the node set includes the circulating water pump outlet node, the distribution manifold node, the inlet node of each cooling triangle, the outlet node of each cooling triangle, the collection manifold node, and the return water header node. The edge set includes the main pipe section, each branch pipe section, and the cooling triangle heat exchanger section. Based on the principles of mass and energy conservation in fluid mechanics, a hydraulic-thermal coupling model is obtained by establishing the nodal continuity equation and the loop pressure drop balance equation. The hydraulic resistance coefficient and heat exchanger pressure drop characteristic coefficient of each branch were calibrated by the step response method, and the cooling coefficient of each branch was calculated by calibrating the wind field influence correction function parameters by the orthogonal test method.

[0008] In some embodiments, the process of obtaining the heat load balance index by combining measured temperature includes: Obtain the measured flow rate of each branch, the inlet water temperature of the main pipe and the outlet water temperature of each branch, and calculate the real-time heat load and ideal heat load of each branch based on the hydraulic resistance coefficient of each branch, the pressure drop characteristic coefficient of the heat exchanger and the cooling coefficient of each cooling triangle. The heat load balance index is calculated based on the real-time heat load and ideal heat load of each branch.

[0009] In some embodiments, the process of constructing a comprehensive optimization function with the objective of minimizing the square of the heat load imbalance index, the sum of the squares of the flow rate change rate, and the sum of the squares of the valve throttling loss when the heat load balance index exceeds a threshold, and solving for the target flow rate of each branch, includes: When the heat load balance index is greater than the threshold, a comprehensive optimization objective function is constructed. The objective function is the square of the heat load balance index multiplied by the first weight coefficient, plus the sum of the squares of the deviations between the flow rate of each branch and the flow rate of the previous cycle multiplied by the second weight coefficient, plus the sum of the squares of the ratio of the valve throttling loss of each branch to the power of the circulating water pump multiplied by the third weight coefficient. Under the constraints of maintaining the total flow rate, limiting the upper and lower limits of the flow rates of each branch, and ensuring that the outlet temperature of each branch is not lower than the freezing temperature plus a safety margin, the target flow rate of each branch is obtained by using a sequential quadratic programming algorithm.

[0010] In some embodiments, the process of obtaining the compensated flow rate by feedforward compensation of the target flow rate of each branch through a hydraulic coupling matrix includes: The feedforward compensation amount is calculated by multiplying the target flow of each branch by the hydraulic coupling coefficient through the hydraulic coupling matrix and then summing the results. The feedforward compensation is applied to the target flow of each branch to obtain the compensated flow. The hydraulic coupling coefficient is initially calibrated through an offline step response test, and is corrected online when the residual of the flow prediction of a certain branch exceeds the range within several consecutive control cycles.

[0011] In some embodiments, the formula for deriving the target opening command of each valve based on the valve's equal percentage characteristics is as follows: ; This is the target opening command for the i-th branch valve. For maximum opening, The flow rate after compensation for the i-th branch is... Let i be the flow coefficient of the valve in the i-th branch. For the density of circulating water, R represents the throttling loss of the valve in the i-th branch, and R is the adjustable ratio.

[0012] In some embodiments, the process of obtaining the deviation between the outlet water temperature of each branch and the target temperature, adjusting the target opening command of each valve according to the deviation magnitude in three priority levels and in the order of decreasing and increasing for the same level, and generating the final execution command includes: Obtain the deviation between the outlet water temperature of each branch and the target temperature; Each branch is divided into three priorities based on temperature deviation: branches with deviation exceeding the first degree Celsius are of first priority, branches with deviation between the first and second degrees Celsius are of second priority, and branches with deviation less than the second degree Celsius are of third priority. The valves are operated in the order of first priority, second priority, and third priority. Within the same priority, the valves are adjusted in the order of decreasing first and then increasing. The final execution command of each valve is obtained, and the heat load balancing and circulating water flow optimization of the multi-cooling triangle in the indirect air-cooled system are carried out.

[0013] This invention proposes a multi-cooling triangle heat load balancing and flow optimization system, comprising: The modeling unit is configured to acquire pipeline topology, step response data, wind field data, measured flow and temperature values, establish a hydraulic-thermal coupling model, calculate the resistance coefficient and cooling coefficient of each branch, and obtain the heat load balance index by combining the measured temperature. The solution unit is configured to construct a comprehensive optimization function with the objective of minimizing the square of the heat load deviation, the sum of the squares of the flow rate change rate, and the sum of the squares of the valve throttling loss when the heat load balance index exceeds the threshold, and solve for the target flow rate of each branch. The compensation unit is configured to obtain the compensated flow rate by feedforward compensation of the target flow rate of each branch through the hydraulic coupling matrix, and then back-calculate the target opening command of each valve based on the valve's equal percentage characteristics. The adjustment unit is configured to obtain the deviation between the outlet water temperature of each branch and the target temperature, and adjust the target opening command of each valve according to the deviation size in three priority levels, with the same level decreasing first and then increasing, to generate the final execution command.

[0014] This invention proposes a computer device, comprising: At least one processor; and a memory storing a computer program executable on the processor, wherein the processor executes the steps of the multi-cooling triangle heat load balancing and flow optimization method when executing the program.

[0015] The present invention proposes a computer-readable storage medium storing a computer program, which, when executed by a processor, performs the steps of the multi-cooling triangle heat load balancing and flow optimization method.

[0016] Compared with the prior art, the present invention has the following beneficial effects: This invention proposes a multi-cooling triangle heat load balancing and flow optimization method and system. The method includes: acquiring pipe network topology, step response data, wind field data, and measured flow and temperature values; establishing a hydraulic-thermal coupling model; calculating the resistance coefficient and cooling coefficient of each branch; and obtaining a heat load balancing index based on the measured temperature. When the heat load balancing index exceeds a threshold, a comprehensive optimization function is constructed with the objectives of minimizing the square of the heat load deviation, the sum of the squares of the flow rate change rate, and the sum of the squares of the valve throttling losses to solve for the target flow of each branch. The target flow of each branch is then compensated by feedforward compensation using a hydraulic coupling matrix, and the target opening command of each valve is then derived based on the valve's equal percentage characteristics. The deviation between the outlet water temperature and the target temperature of each branch is acquired, and the target opening command of each valve is adjusted according to the deviation magnitude in three priority levels, with the same level decreasing first and then increasing, to generate the final execution command.

[0017] This invention achieves quantitative evaluation and real-time monitoring of the heat load distribution state of multiple cooling triangles by establishing a hydraulic-thermal coupling model and introducing a heat load balance index. A comprehensive optimization function is constructed, incorporating heat load deviation, flow rate change rate, and valve throttling losses, balancing heat load while considering system dynamic stability and energy efficiency. By utilizing feedforward compensation of the hydraulic coupling matrix and back-calculation based on the valve's percentage characteristics, execution deviations caused by inter-branch hydraulic coupling interference and valve nonlinearity are effectively eliminated. A three-level priority hierarchical correction strategy ensures accurate execution of optimization commands and rapid system convergence.

[0018] This invention establishes a hydraulic-thermal coupling mathematical model, which enables accurate characterization of the parallel operation of multiple branches in an indirect air-cooled system. This avoids the problem of reduced control accuracy caused by the traditional method of forcibly simplifying a multi-input multi-output coupled system into a single-loop control.

[0019] This invention quantifies the degree to which the heat load of each branch deviates from the ideal distribution by introducing a heat load balance index λ, thereby achieving a quantitative diagnosis of uneven heat load distribution and solving the problem that traditional methods rely solely on human experience and lack objective standards.

[0020] This invention eliminates the negative coupling effect between branches by introducing a hydraulic coupling matrix for feedforward compensation, avoids interference of flow regulation of a single branch on other branches, and improves the stability and response speed of the system.

[0021] By employing a sequential quadratic programming algorithm to solve for the optimal flow distribution scheme, precise allocation of circulating water flow in each cooling triangle was achieved, controlling the temperature deviation of water at the outlet of each branch and reducing the risk of local freezing in winter.

[0022] By adopting a time-sharing action strategy to coordinate the actions of multiple valves, the instantaneous and drastic fluctuations in the main pipe flow are avoided, the over-adjustment oscillation amplitude is suppressed to a certain extent, and the system response time is shortened. Attached Figure Description

[0023] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other embodiments can be obtained based on these drawings without creative effort.

[0024] Figure 1 The flowchart of a multi-cooling triangle heat load balancing and flow optimization method provided by the present invention is shown.

[0025] Figure 2 This invention provides a multi-cooling triangle heat load balancing and flow optimization system module diagram.

[0026] Figure 3 A schematic diagram of the structure of an embodiment of the computer device provided by the present invention.

[0027] Figure 4 This is a schematic diagram of an embodiment of the computer-readable storage medium provided by the present invention.

[0028] Figure 5 This invention provides a schematic diagram of the parallel pipe network structure of an indirect air-cooled system with multiple cooling triangles for heat load balancing and flow optimization.

[0029] Figure 6 This is a flowchart of an embodiment of a multi-cooling triangle heat load balancing and flow optimization method provided by the present invention.

[0030] Figure 7 The flowchart illustrates the flow optimization allocation process of a multi-cooling triangle heat load balancing and flow optimization method provided by this invention.

[0031] Figure 8 The flowchart of the hydraulic-thermal coupling model calculation for a multi-cooling triangle heat load balancing and flow optimization method provided by the present invention is shown. Detailed Implementation

[0032] The present invention will be further described below with reference to the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solutions of the present invention and should not be construed as limiting the scope of protection of the present invention. It should be noted that the following detailed descriptions are exemplary and intended to provide further explanation of this application.

[0033] It should be noted that all uses of "first" and "second" in the embodiments of the present invention are for the purpose of distinguishing two entities or parameters with the same name but different names. It is clear that "first" and "second" are only for the convenience of expression and should not be construed as limiting the embodiments of the present invention. Subsequent embodiments will not explain this in detail.

[0034] This invention proposes a method for balancing heat load and optimizing flow rate in a multi-cooling triangle configuration. Please refer to [link / reference]. Figure 1 and Figure 6 ,include: Obtain pipeline topology, step response data, wind field data, and measured flow and temperature values; establish a hydraulic-thermal coupling model; calculate the resistance coefficient and cooling coefficient of each branch; and obtain the heat load balance index by combining the measured temperature. When the heat load balance index exceeds the threshold, a comprehensive optimization function is constructed with the objectives of minimizing the square of the heat load deviation, the sum of the squares of the flow rate change rate, and the sum of the squares of the valve throttling loss, and the target flow rate of each branch is solved. The target flow rate of each branch is compensated by the hydraulic coupling matrix feedforward compensation to obtain the compensated flow rate, and then the target opening command of each valve is obtained by back-calculation based on the valve equal percentage characteristics. The deviation between the outlet water temperature of each branch and the target temperature is obtained. The valves are adjusted according to the deviation in three priority levels, with the same level decreasing first and then increasing, to generate the final execution command.

[0035] This invention is applied to indirect air-cooled systems. A hydraulic-thermal coupling mathematical model of the parallel pipe network of the indirect air-cooled system is established to calculate the hydraulic resistance coefficient and cooling coefficient of each branch. Based on the measured outlet water temperature of each branch, the degree of imbalance in heat load distribution is diagnosed, and the heat load balance index is calculated. When the balance index exceeds the threshold, the optimal flow distribution scheme is solved, and the flow rate is precisely controlled by adjusting the opening of the electric regulating valve. A hydraulic coupling matrix is ​​introduced for feedforward compensation.

[0036] This invention establishes a hydraulic-thermal coupling model by acquiring pipeline topology, step response data, wind field data, and measured flow and temperature values. This model accurately characterizes the resistance characteristics and cooling capacity of each branch and quantifies the heat load balance index based on measured temperature, providing a measurable evaluation index for the system's heat load distribution. When the heat load balance index exceeds a set threshold, a comprehensive optimization function is constructed, incorporating three indices: the square of the heat load deviation, the sum of the squares of the flow rate change rate, and the sum of the squares of the valve throttling loss. This approach balances heat load balance with system stability and economy, avoiding the problems of drastic flow fluctuations and excessive throttling energy consumption caused by single-objective optimization. The target flow rate of each branch is solved using a sequential quadratic programming algorithm under constraints such as flow conservation, flow upper and lower limits, and antifreeze temperature, ensuring the engineering feasibility of the optimization results. Feedforward compensation of the target flow rate using a hydraulic coupling matrix effectively eliminates the interference of hydraulic coupling between branches on flow distribution, making the actual flow rate of each branch closer to the target value. By using the valve's percentage-based characteristics to inversely deduce the target opening command, the nonlinear flow characteristics of the valve were matched, significantly reducing the deviation between the opening command and the actual flow rate. Finally, by acquiring the deviation between the outlet water temperature of each branch and the target temperature, the opening commands were adjusted according to three priority levels based on the magnitude of the deviation, with the opening command adjusted in the order of decreasing first and then increasing within the same priority level. This ensured that branches with large temperature deviations were corrected first, and avoided drastic fluctuations in pipeline pressure caused by multiple valves increasing or decreasing simultaneously within the same priority level. This achieved rapid and stable heat load balancing and optimized flow distribution.

[0037] In some embodiments, please refer to Figure 1 , Figure 7 and Figure 8 The process of acquiring pipeline topology, step response data, wind field data, measured flow and temperature values, establishing a hydraulic-thermal coupling model, and calculating the resistance coefficient and cooling coefficient of each branch includes: The topology of the parallel pipe network of the indirect air-cooled system, the step response data of each branch, and the wind field data are obtained. The pipe network is abstracted into a directed graph, in which the node set includes the circulating water pump outlet node, the distribution manifold node, the inlet node of each cooling triangle, the outlet node of each cooling triangle, the collection manifold node, and the return water header node. The edge set includes the main pipe section, each branch pipe section, and the cooling triangle heat exchanger section. Based on the principles of mass and energy conservation in fluid mechanics, a hydraulic-thermal coupling model is obtained by establishing the nodal continuity equation and the loop pressure drop balance equation. The hydraulic resistance coefficient and heat exchanger pressure drop characteristic coefficient of each branch were calibrated by the step response method, and the cooling coefficient of each branch was calculated by calibrating the wind field influence correction function parameters by the orthogonal test method.

[0038] Establish a hydraulic-thermal coupling mathematical model for the parallel pipe network of the indirect air-cooled system, including: The physical piping network of the indirect air-cooled system is abstracted as a directed graph G=(V,E), where the node set V includes: circulating water pump outlet node, distribution manifold node, each cooling triangle inlet node, each cooling triangle outlet node, collection manifold node, and return water header node; the edge set E includes: main pipe section, each branch pipe section, and cooling triangle heat exchanger section.

[0039] Based on the principles of mass and energy conservation in fluid mechanics, nodal continuity equations and loop pressure drop balance equations are established.

[0040] The nodal continuity equation is:

[0041] In the formula, Q is the total circulating water flow rate in the main pipe, and the unit is... ; The flow rate of the i-th branch is expressed in units of 1 / 2 Ω. n represents the number of cooling triangles.

[0042] The circuit voltage drop balance equation is:

[0043] In the formula, For common section pressure reduction, the unit is ; The hydraulic resistance coefficient of the i-th branch is given by [value]. ; The pressure drop of the i-th cooling triangle heat exchanger is expressed in Pa.

[0044] The pressure drop versus flow rate relationship for cooling a triangular heat exchanger is as follows:

[0045] In the formula, , The pressure drop characteristic coefficient of the i-th cooling triangle is obtained through field step response test calibration.

[0046] The cooling coefficients of each cooling triangle change dynamically due to the influence of the environmental wind field. An online estimation model for the cooling coefficients is established:

[0047] In the formula, This is the baseline cooling coefficient for the i-th cooling triangle under standard operating conditions, in units of... ; Ambient wind speed, unit: ; This is the wind direction angle, in degrees. The distance from the i-th cooling triangle to the center of the air duct is in meters. The airflow angle of the i-th cooling triangle is expressed in degrees. This is the correction function for the wind field influence.

[0048] The wind field influence correction function adopts an engineering approximation form:

[0049] In the formula, ∈[0.02,0.08] represents the wind speed sensitivity coefficient; ∈[0.5,0.8] represents the wind speed index; ∈[-0.15,0.15] represents the wind direction sensitivity coefficient; ∈[0.1,0.3] represents the distance decay exponent; This is a reference distance, in meters.

[0050] The parallel pipe network of the indirect air-cooled system is abstracted into a directed graph structure. The node set includes six types of nodes: circulating water pump outlet node, distribution manifold node, each cooling triangle inlet node, each cooling triangle outlet node, collection manifold node, and return water header node. The edge set includes three types of pipe sections: main pipe section, each branch pipe section, and cooling triangle heat exchanger section.

[0051] Based on this topology, a nodal continuity equation is established based on the principle of mass conservation in fluid mechanics, that is, the sum of the flow rates flowing into any node is equal to the sum of the flow rates flowing out of that node; a loop pressure drop balance equation is established based on the principle of energy conservation, that is, the algebraic sum of the pressure drops of each pipe segment in any closed loop is zero. The two sets of equations are combined to form a hydraulic-thermal coupling model.

[0052] The hydraulic resistance coefficient and heat exchanger pressure drop characteristic coefficient of each branch in the model are calibrated by the step response method. Specifically, a step opening change of known amplitude is applied to the valve of a certain branch, and the dynamic response curves of the flow of the branch and other branches are recorded. The resistance coefficient and pressure drop characteristic coefficient are obtained by back-calculating the steady-state gain and time constant of the fitted response curve.

[0053] The cooling coefficient of each branch is calculated by calibrating the wind field influence correction function parameters through orthogonal experimental design. Specifically, the orthogonal experimental design is based on factors such as wind speed, wind direction, and ambient temperature, with the heat exchange of each branch as the index. The order of importance of each factor and the optimal parameter combination are determined through range analysis and variance analysis, thereby establishing a quantitative correction function between the cooling coefficient and the wind field parameters.

[0054] In some embodiments, please refer to Figure 1 , Figure 7 and Figure 8 The process of obtaining the heat load balance index by combining the measured temperature includes: Obtain the measured flow rate of each branch, the inlet water temperature of the main pipe and the outlet water temperature of each branch, and calculate the real-time heat load and ideal heat load of each branch based on the hydraulic resistance coefficient of each branch, the pressure drop characteristic coefficient of the heat exchanger and the cooling coefficient of each cooling triangle. The heat load balance index is calculated based on the real-time heat load and ideal heat load of each branch.

[0055] Furthermore, based on the measured outlet water temperature of each branch, the degree of imbalance in heat load distribution is diagnosed, including: Calculate the real-time heat load borne by the i-th cooling triangle:

[0056] In the formula, The heat load of the i-th branch is expressed in W. This refers to the specific heat capacity of circulating water, in units of... ; This refers to the inlet water temperature of the main pipe, in °C. The water temperature at the outlet of the i-th branch is expressed in °C.

[0057] Calculate the ideal heat load for the i-th cooling triangle:

[0058] In the formula, The total system heat load is expressed in W. Let be the heat exchange area of ​​the i-th cooling triangle, in m².

[0059] The heat load balance index λ is defined to quantify the degree to which the heat load of each branch deviates from the ideal distribution:

[0060] In the formula, λ is the heat load balance index, which is dimensionless. When λ=0, it indicates perfect balance; when λ>0.15, it is considered that the heat load distribution is severely unbalanced, and flow redistribution needs to be triggered.

[0061] First, the measured flow rate of each branch, the inlet water temperature of the main pipe, and the outlet water temperature of each branch are obtained. Based on this, using the calibrated hydraulic resistance coefficient of each branch, the pressure drop characteristic coefficient of the heat exchanger, and the cooling coefficient of each cooling triangle, the real-time heat load and ideal heat load of each branch are calculated respectively. The heat load balance index is defined as the normalized root mean square value of the deviation between the real-time heat load and the ideal heat load of each branch. The closer the heat load balance index is to zero, the more balanced the heat load distribution; the larger the heat load balance index, the more unbalanced the distribution.

[0062] In some embodiments, please refer to Figure 1 , Figure 7 and Figure 8When the heat load balance index exceeds the threshold, the process of constructing a comprehensive optimization function with the objectives of minimizing the square of the heat load deviation, the sum of the squares of the flow rate change rate, and the sum of the squares of the valve throttling loss, and solving for the target flow rate of each branch includes: When the heat load balance index is greater than the threshold, a comprehensive optimization objective function is constructed. The objective function is the square of the heat load balance index multiplied by the first weight coefficient, plus the sum of the squares of the deviations between the flow rate of each branch and the flow rate of the previous cycle multiplied by the second weight coefficient, plus the sum of the squares of the ratio of the valve throttling loss of each branch to the power of the circulating water pump multiplied by the third weight coefficient. Under the constraints of maintaining the total flow rate, limiting the upper and lower limits of the flow rates of each branch, and ensuring that the outlet temperature of each branch is not lower than the freezing temperature plus a safety margin, the target flow rate of each branch is obtained by using a sequential quadratic programming algorithm.

[0063] When the equilibrium index exceeds the threshold, an objective function for optimizing traffic allocation is constructed to solve for the optimal traffic allocation scheme:

[0064] In the formula, J is the comprehensive optimization objective function, which is dimensionless; These are weighting coefficients, dimensionless. The flow rate of the i-th branch in the previous control cycle, in units of Δt is the control period, in seconds. The throttling loss of the i-th branch regulating valve is expressed in Pa. The power of the circulating water pump is expressed in watts (W).

[0065] The constraints include: (1) Equality constraint (conservation of total flow):

[0066] (2) Inequality constraints (equipment safety boundaries):

[0067]

[0068] In the formula, , The upper and lower limits of the flow rate of the i-th branch are given in units of 1. ; This refers to the ambient dew point temperature, expressed in °C. For safety margin, the unit is ℃.

[0069] The Sequential Quadratic Programming (SQP) algorithm is used to solve the above nonlinear programming problem to obtain the target flow rate of each branch. .

[0070] When the heat load balance index exceeds a threshold, the constructed comprehensive optimization objective function consists of a weighted sum of squares of three terms. The first term is the square of the heat load balance index multiplied by a first weighting coefficient of 10, representing the pursuit of a balanced heat load. The second term is the sum of squares of the deviations between the flow rates of each branch and the previous cycle's flow rate multiplied by a second weighting coefficient of 1, representing the constraint on the smoothness of flow rate changes and preventing drastic flow rate jumps. The third term is the sum of squares of the ratios of valve throttling losses to circulating pump power in each branch multiplied by a third weighting coefficient of 0.5, representing the suppression of throttling energy consumption; the greater the valve throttling loss, the heavier the penalty for this term. The optimization solution is performed under three sets of constraints: the first set is the main pipe flow conservation constraint; the second set is the upper and lower limit constraints on the flow rates of each branch; and the third set is the anti-freezing safety constraint, i.e., the outlet temperature of each branch should not be lower than the freezing temperature plus a safety margin, typically taken as 3°C. The solution algorithm uses a sequential quadratic programming algorithm (SQP), which approximates the nonlinear optimization problem as a quadratic programming subproblem in each iteration, offering advantages such as fast convergence and insensitivity to initial values.

[0071] In some embodiments, please refer to Figure 1 , Figure 7 and Figure 8 The process of obtaining the compensated flow rate by feedforward compensation of the target flow rate of each branch through the hydraulic coupling matrix includes: The feedforward compensation amount is calculated by multiplying the target flow of each branch by the hydraulic coupling coefficient through the hydraulic coupling matrix and then summing the results. The feedforward compensation is applied to the target flow of each branch to obtain the compensated flow. The hydraulic coupling coefficient is initially calibrated through an offline step response test, and is corrected online when the residual of the flow prediction of a certain branch exceeds the range within several consecutive control cycles.

[0072] Since the branches are coupled through a common header, the flow regulation of a single branch will affect other branches. Therefore, a hydraulic coupling matrix H is introduced for feedforward compensation.

[0073] In the formula, The change in target flow rate of the i-th branch is expressed in units of... ; The required feedforward compensation for the j-th branch is expressed in units of... ; The hydraulic coupling coefficient, representing the influence of flow changes in the i-th branch on the j-th branch, is determined through a combination of offline calibration and online correction. Offline benchmark calibration obtains the initial coupling matrix H0 through field step response tests, using the same calibration method as for the branch resistance coefficient. Online drift correction is based on the residuals between the measured values ​​and model predictions of the flow sensors in each branch. A recursive least squares method is used to periodically correct the coupling matrix. The correction trigger condition is that the residual of the flow prediction for a certain branch exceeds ±5% of the full scale within three consecutive control cycles. The correction period is no less than 10 minutes to avoid coupling oscillations with the main control loop.

[0074] The flow characteristic of the electric control valve adopts an equal percentage characteristic, and the relationship between valve opening and flow rate is as follows:

[0075] In the formula, Let be the flow coefficient of the i-th valve, in units of . ρ is the density of circulating water, in kg / m³; R is the adjustable ratio, dimensionless. The current valve opening is expressed as % (%). This represents the maximum valve opening.

[0076] Because of the hydraulic coupling between branches in a parallel pipe network, when the target flow rate of one branch changes, it will cause passive changes in the flow rates of other branches through changes in the pressure drop of the common pipe section. The purpose of feedforward compensation is to predict and offset this coupling effect before the target flow rate is issued. Specifically, the feedforward compensation amount is calculated using a hydraulic coupling matrix. The initial value of the matrix is ​​calibrated through an offline step response test: a step opening change is applied to each branch sequentially, the flow response of all branches is recorded, and the initial matrix is ​​obtained through system identification. During online operation, when the flow prediction residual of a branch (i.e., the difference between the actual flow rate and the compensated predicted flow rate) exceeds 5% of the flow range of that branch within five consecutive control cycles, the corresponding row in the matrix is ​​corrected online.

[0077] In some embodiments, the formula for deriving the target opening command of each valve based on the valve's equal percentage characteristics is as follows: ; This is the target opening command for the i-th branch valve. For maximum opening, The flow rate after compensation for the i-th branch is... Let i be the flow coefficient of the valve in the i-th branch. For the density of circulating water, R represents the throttling loss of the valve in the i-th branch, and R is the adjustable ratio.

[0078] Compared to the linear back-calculation method, the above formula fully considers the nonlinear logarithmic relationship between valve opening and flow rate, and can maintain high back-calculation accuracy in both small and large opening regions.

[0079] In some embodiments, the process of obtaining the deviation between the outlet water temperature of each branch and the target temperature, adjusting the target opening command of each valve according to the deviation magnitude in three priority levels and in the order of decreasing and increasing for the same level, and generating the final execution command includes: Obtain the deviation between the outlet water temperature of each branch and the target temperature; Each branch is divided into three priorities based on temperature deviation: branches with deviation exceeding the first degree Celsius are of first priority, branches with deviation between the first and second degrees Celsius are of second priority, and branches with deviation less than the second degree Celsius are of third priority. The valves are operated in the order of first priority, second priority, and third priority. Within the same priority, the valves are adjusted in the order of decreasing first and then increasing. The final execution command of each valve is obtained, and the heat load balancing and circulating water flow optimization of the multi-cooling triangle in the indirect air-cooled system are carried out.

[0080] To avoid system oscillation caused by simultaneous operation of multiple valves, a time-sharing action strategy is adopted: branches with deviations exceeding ±5°C of the first temperature range are adjusted first; branches with deviations within the range of ±2°C of the second temperature range to ±5°C of the first temperature range are adjusted second; and branches with deviations less than ±2°C of the second temperature range are fine-tuned last. Branches within the same priority range operate in a decrement-then-increment order.

[0081] First, the deviation between the outlet water temperature of each branch and the target temperature is obtained, which is equal to the target temperature minus the measured temperature. Then, all branches are divided into three priorities according to the magnitude of the deviation: branches with an absolute deviation value exceeding the first degree Celsius are classified as first priority, and these branches have the largest temperature deviation and need to be processed with the highest priority; branches with an absolute deviation value in the range of first to second degree Celsius are classified as second priority; and branches with an absolute deviation value less than the second degree Celsius are classified as third priority.

[0082] Adjustments are strictly executed in the order of first priority, second priority, and third priority. Within the same priority level, adjustments are made in the order of decreasing flow first, then increasing flow. That is, if there are branches with high outlet water temperature requiring increased flow and branches with low outlet water temperature requiring decreased flow, the flow reduction action is executed first, followed by the flow increase action. This avoids a sudden increase in the total flow rate due to multiple valves increasing their openings simultaneously, or a sudden decrease in the total flow rate due to multiple valves decreasing their openings simultaneously. The adjustment amount is calculated based on the magnitude of the deviation and allocated proportionally; the larger the deviation, the larger the adjustment.

[0083] This invention proposes a multi-cooling triangle heat load balancing and flow optimization system. Please refer to [link / reference].Figure 2 , Figure 5 ,include: The modeling unit is configured to acquire pipeline topology, step response data, wind field data, measured flow and temperature values, establish a hydraulic-thermal coupling model, calculate the resistance coefficient and cooling coefficient of each branch, and obtain the heat load balance index by combining the measured temperature. The solution unit is configured to construct a comprehensive optimization function with the objective of minimizing the square of the heat load deviation, the sum of the squares of the flow rate change rate, and the sum of the squares of the valve throttling loss when the heat load balance index exceeds the threshold, and solve for the target flow rate of each branch. The compensation unit is configured to obtain the compensated flow rate by feedforward compensation of the target flow rate of each branch through the hydraulic coupling matrix, and then back-calculate the target opening command of each valve based on the valve's equal percentage characteristics. The adjustment unit is configured to obtain the deviation between the outlet water temperature of each branch and the target temperature, and adjust the target opening command of each valve according to the deviation size in three priority levels, with the same level decreasing first and then increasing, to generate the final execution command.

[0084] First, a hydraulic-thermal coupling mathematical model of the parallel pipe network of the indirect air-cooled system is established to calculate the hydraulic resistance coefficient and cooling coefficient of each branch. Then, based on the measured outlet water temperature of each branch, the degree of imbalance in heat load distribution is diagnosed, and the heat load balance index is calculated. Finally, when the balance index exceeds the threshold, the optimal flow distribution scheme is solved, and the flow rate is precisely controlled by adjusting the opening of the electric regulating valve. A hydraulic coupling matrix is ​​also introduced for feedforward compensation.

[0085] The indirect air-cooling system in this embodiment includes eight cooling triangle sectors operating in parallel. The spatial distribution of each cooling triangle is shown in the table below: Table 1 Spatial distribution of each cooling triangle

[0086] The hardware system of this embodiment includes: one main inlet water temperature sensor (PT100 RTD, accuracy ±0.1℃), eight branch outlet water temperature sensors (PT100 RTD, accuracy ±0.1℃), one environmental weather station (including an anemometer and wind direction indicator), eight branch flow sensors (electromagnetic flowmeter, accuracy ±0.5%FS), eight electric regulating valves (equal percentage characteristic, adjustable ratio R=50), and one to two circulating water pumps (frequency conversion speed control).

[0087] S1: Establish a hydraulic-thermal coupling mathematical model The hydraulic resistance coefficients of each branch were calibrated using the step response method. : Keeping the valve openings of other branches constant, the valve in the i-th branch is stepped from 50% to 60%, and the flow rate changes before and after the step are recorded. and pressure difference change ,calculate:

[0088] Repeat the process three times and take the average value to obtain the hydraulic resistance coefficient of each branch. =2.5×10 -5 Pa·s² / m 6 .

[0089] The parameters of the wind field influence correction function were calibrated using the orthogonal experimental method. : Design an orthogonal test table to cover combinations of wind speed (0, 4, 8, 12 m / s) and wind direction (0°, 90°, 180°, 270°). Run the test table stably for 30 minutes at each operating point and record the temperature drop of each branch. ,according to Back-calculation of actual cooling coefficient The least squares method was used to fit the result. =0.05, =0.6, =0.1, =0.2.

[0090] Calculate the cooling coefficient of each branch based on the wind field correction function:

[0091] In this embodiment, the reference cooling coefficient of the cooling triangular heat exchanger under "standard operating conditions (no environmental wind field interference)" is... =45W / (m²·℃), the actual physical distance of cooling triangles 1 to 4 from the center of the air duct. =25m.

[0092] S2: Heat load deviation diagnosis Calculate the real-time heat load borne by the i-th cooling triangle:

[0093] In the formula, the specific heat capacity of circulating water is defined as the pressure at standard atmospheres and the operating temperature at normal operating temperature. =4186J / (kg·℃).

[0094] Assuming each cooling triangle bears the heat load proportionally according to its cooling capacity, calculate the ideal heat load of the i-th cooling triangle:

[0095] Calculate the heat load balance index:

[0096] In this embodiment, the reasonable engineering threshold for triggering the control loop is typically 5%. To effectively avoid the impact of minute sensor measurement noise, the equalization threshold is used. =0.05. When λ> At that time, traffic redistribution is triggered.

[0097] S3: Traffic Optimization Allocation Calculation Construct the objective function for optimized traffic allocation:

[0098] In this embodiment, after testing, a weighting coefficient was determined to eliminate local temperature differences and prevent local icing and cracking of the radiator in extremely cold weather. =0.7; a weighting coefficient to suppress hydraulic overshoot oscillations in the system. =0.2; Under the premise of absolutely ensuring equipment safety and stable operation, while taking into account the energy saving of the system, the weighting coefficient is 0.2. =0.1, control period Δt=30s.

[0099] Constraints: Main flow conservation:

[0100] In this embodiment, the total circulating water flow rate Q = 8000 m³ / h.

[0101] Equipment safety boundaries:

[0102]

[0103] The Sequential Quadratic Programming (SQP) algorithm is used to solve the above nonlinear programming problem to obtain the target flow rate of each branch. .

[0104] S4: Hydraulic Coupling Compensation and Valve Control Introducing a hydraulic coupling matrix H for feedforward compensation:

[0105] In this embodiment, the hydraulic coupling coefficient It is determined by combining offline calibration with online correction.

[0106] The opening command of the electric regulating valve is derived from the target flow rate:

[0107] In this embodiment, the adjustable ratio R=50, and the circulating water density ρ=1000kg / m³ at standard atmospheric pressure and normal operating temperature.

[0108] A time-sharing action strategy is adopted to coordinate the operation of multiple valves: branches with deviations exceeding ±5℃ are adjusted first, branches with deviations within the range of ±2℃ to ±5℃ are adjusted second, and branches with deviations less than ±2℃ are fine-tuned last. Branches within the same priority are operated in the order of "decrease first, then increase".

[0109] Example of heat load balancing control prioritizing winter freeze protection: This embodiment provides a method for balancing the heat load and optimizing the circulating water flow in a multi-cooling triangle in an indirect air-cooled system suitable for low-temperature winter environments. This embodiment still uses the indirect air-cooled system structure described in the previous embodiment, i.e., multiple cooling triangles operate in parallel. Each cooling triangle is equipped with a branch outlet water temperature sensor, a branch flow sensor, and an electric regulating valve. The main pipe is equipped with an inlet water temperature measuring point and a main pipe circulating water flow measuring point. Simultaneously, environmental wind speed and direction information are obtained from an environmental meteorological station.

[0110] During winter operation, due to low ambient temperatures and varying air-side heat transfer intensities caused by wind patterns, some cooling triangles on the windward side or with stronger local cooling capacity are prone to significantly lower outlet water temperatures. If overall control is based solely on the main pipe return water temperature or unit back pressure, operators may struggle to detect overcooling in individual cooling triangles or local branches in a timely manner. Therefore, this embodiment prioritizes freeze protection. While ensuring the main pipe flow rate remains constant and equipment safety boundaries are met, the circulating water flow rate of each branch is redistributed to bring the outlet water temperature of branches at low-temperature risk back to a safe range, while simultaneously maintaining a balanced heat load distribution across the cooling triangles.

[0111] The specific control process in this embodiment is as follows: First, the control system collects data such as the main pipe inlet water temperature, the outlet water temperature of each branch, the flow rate of each branch, the opening degree of each electric regulating valve, the ambient wind speed, and the ambient wind direction according to a predetermined control cycle. After the data collection is completed, the control system uses the aforementioned hydraulic-thermal coupling mathematical model to calculate the hydraulic state and cooling capacity of each branch, and calculates the real-time heat load borne by each cooling triangle based on the measured outlet water temperature of each branch.

[0112] Secondly, the control system calculates the corresponding ideal heat load based on the heat exchange area and cooling capacity of each cooling triangle, and further calculates the heat load balance index. If the heat load balance index does not exceed the existing threshold, and the outlet water temperature of each branch is within the equipment safety boundary, the control system maintains the current valve opening and only performs routine monitoring. If the heat load balance index exceeds the existing threshold, or the outlet water temperature of a certain branch approaches the equipment safety boundary, the control system enters the winter anti-freeze priority control state.

[0113] Under the winter anti-freeze priority control mode, the control system first identifies low-temperature risk branches. Low-temperature risk branches refer to cooling triangle branches where the water temperature is significantly lower than other branches, or where, based on existing equipment safety boundaries, there is a risk of localized overcooling. For such branches, the control system no longer simply pursues maximizing overall cooling capacity, but instead prioritizes reducing the degree of localized overcooling in these branches through flow redistribution. Specifically, the control system inputs the current outlet water temperature, current branch flow rate, valve opening, and the corresponding cooling triangle's wind field correction cooling coefficient into the flow optimization allocation process. The SQP algorithm then solves for the target flow rate of each branch under the constraints of main pipe flow conservation, branch flow upper and lower limits, and equipment safety boundaries.

[0114] After obtaining the target flow rate for each branch, the control system calculates the target opening degree of each electric regulating valve based on the existing valve flow characteristics. Since the branches are coupled to each other through a common header, the action of a valve in a low-temperature risk branch may cause synchronous changes in the flow rate of other branches. Therefore, the control system further calls on the existing hydraulic coupling matrix for feedforward compensation to obtain the actual execution command of each valve.

[0115] During the valve execution phase, the control system employs an existing time-sharing action strategy. Branches with outlet water temperature deviations exceeding ±5℃ are prioritized for regulation; branches with outlet water temperature deviations between ±2℃ and ±5℃ are treated as secondary regulation targets; and branches with outlet water temperature deviations less than ±2℃ undergo only final-stage fine-tuning. Within the same priority level, actions are executed in the existing order of decreasing followed by increasing to avoid simultaneous large-scale valve movements causing instantaneous fluctuations in the main pipe flow.

[0116] Under winter operating conditions, the control system detected that the outlet water temperatures of the second and third cooling triangles were significantly lower than those of other branches, and that these two cooling triangles were affected by ambient wind, resulting in relatively strong cooling capacity. Based on this, the control system identified the second and third branches as low-temperature risk branches and added them to the priority adjustment queue. Subsequently, the control system calculated the target flow rate for each branch based on the heat load balance index and flow optimization target, ensuring a more reasonable water distribution for the low-temperature risk branches while meeting equipment safety boundaries. Simultaneously, the system maintained a constant flow rate in the main pipe through compensation adjustments to other branches. After execution, the control system re-collected the outlet water temperatures of each branch in the next control cycle and determined whether the low-temperature branches had escaped the subcooling state. If, after one or more control cycles, the outlet water temperature of the low-temperature risk branches gradually recovered, and the temperature deviation between branches decreased, the control system continued to fine-tune according to the heat load balance target. If a branch continued to approach the equipment safety boundary, the control system maintained anti-freeze priority control and continuously limited the branch from developing higher cooling intensities until its temperature returned to a safe range.

[0117] Example of degradation control under sensor malfunction: This embodiment provides a degraded control method for an indirect air-cooled system under conditions of partial field sensor anomalies. This embodiment is applicable to control scenarios where any type of data from the main pipe inlet water temperature sensor, branch outlet water temperature sensor, branch flow sensor, ambient wind speed and direction measuring points, or valve feedback signals is abnormal.

[0118] In actual engineering operations, sensor data may become unusable due to loose wiring, measurement point drift, communication interruption, sudden changes in measurement values, or long-term deviation from actual operating conditions. If the control system still directly uses abnormal data to calculate the heat load balance index or solve the optimal flow distribution scheme, it may cause erroneous valve actions, leading to imbalances in branch flow distribution. Therefore, this embodiment adds a degraded execution mode after abnormal data identification without changing the original main control logic, enabling the system to maintain basic heat load balance capability even when some measurement points are unavailable.

[0119] The specific control process in this embodiment is as follows: First, the control system reads data from various field measurement points in each control cycle and assesses the validity of the data. The assessment includes: whether there is a communication interruption at the measurement point; whether the measured value significantly exceeds the physically reasonable range; whether the measured value has undergone unreasonable abrupt changes relative to the previous control cycle; and whether the measured value is inconsistent with the prediction results of the hydraulic-thermal coupling model over a long period. These assessments are based solely on existing measurement points, existing models, and existing control cycles, without introducing new calculation formulas or independent control parameters.

[0120] When all key measuring points are normal, the control system calculates the real-time heat load, ideal heat load, and heat load balance index in a conventional manner, and solves for the optimal flow distribution scheme when the heat load balance index exceeds an existing threshold. When an abnormality occurs at a measuring point in a branch, the control system first marks the abnormal measuring point and switches the branch to a degraded control state.

[0121] If the abnormal measurement point is a branch outlet water temperature sensor, the control system will not directly use the abnormal temperature value in the calculation of the heat load balance index. For the thermal state of this branch, the control system can make alternative judgments based on the branch's most recent effective outlet water temperature, the outlet water temperature change trend of adjacent or similar cooling triangles, the branch's current flow rate, the current valve opening, and the estimation results of the existing hydraulic-thermal coupling model. In this case, this branch will not be actively amplified for regulation; only limited follow-up regulation or maintaining the current valve opening is allowed to avoid accidental valve opening or closing due to erroneous temperature signals.

[0122] If the abnormal measurement point is a flow sensor in a specific branch, the control system will not directly use the abnormal flow value for online correction of the hydraulic coupling matrix. For the flow rate of this branch, the control system can estimate it based on valve opening, valve flow characteristics, main pipe flow, and the branch hydraulic resistance model. Until the flow sensor returns to normal, the control system will not use the residual flow rate of this branch to correct the hydraulic coupling matrix; it will only retain the original offline calibration matrix and feedback information from other normal branches to avoid abnormal flow data contaminating the hydraulic coupling relationship.

[0123] If the abnormal measurement point is an ambient wind speed or wind direction measurement point, the control system will suspend drastic corrections to the cooling coefficient and instead use the most recent valid wind field information or the cooling coefficient under standard operating conditions as the calculation basis. In this state, the system can still rely on the feedback of the outlet water temperature of each branch to complete the heat load balance control, but will no longer make significant changes to the cooling capacity of each cooling triangle based on abnormal wind field data.

[0124] If the abnormal signal is feedback on the opening of an electrically operated control valve, the control system sets the branch containing that valve as a restricted control branch. For this branch, the control system no longer sends frequently changing target opening commands, but instead maintains or slightly corrects the valve action based on the current verifiable state, and performs overall flow and heat load balancing compensation through other normal branches. If the valve feedback returns to normal, the branch re-enters the normal flow optimization allocation process.

[0125] Under degraded control, the control system still maintains the main flow conservation constraint and equipment safety boundary constraints. For abnormal branches, the control system reduces its active participation in flow redistribution; for normal branches, the control system continues to regulate valves according to existing SQP optimization results and time-sharing action strategies. This avoids malfunctions in abnormal branches while maintaining overall system heat load balance through normal branches.

[0126] During a certain operating cycle, the outlet water temperature sensor of branch 4 malfunctioned, with its measured value showing a significant inconsistency with the temperature trends of adjacent branches. The control system marked the temperature measuring point of branch 4 as abnormal and suspended its use for calculating the heat load balance index. Subsequently, the system estimated the thermal state of branch 4 based on the previous effective outlet water temperature, current valve opening, current branch flow rate, and the hydraulic-thermal coupling model, while simultaneously setting the valve of branch 4 to a restricted regulation state. During this period, the system primarily used the normal measuring points of branches 1, 2, 3, and 5 through 8 to complete the heat load balance calculation and flow optimization allocation. If the temperature measuring point of branch 4 returns to normal and its value matches the model prediction and the trend of adjacent branches in subsequent control cycles, the control system removes the abnormality mark, allowing branch 4 to rejoin the regular heat load balance control.

[0127] Based on the same inventive concept, according to another aspect of the present invention, such asFigure 3 As shown, an embodiment of the present invention also provides a computer device 30, which includes a processor 310 and a memory 320. The memory 320 stores a computer program 321 that can be run on the processor. When the processor 310 executes the program, it performs the steps of the method described above.

[0128] Based on the same inventive concept, according to another aspect of the present invention, such as Figure 4 As shown, embodiments of the present invention also provide a computer-readable storage medium 40, which stores a computer program 410 that, when executed by a processor, performs the methods described above.

[0129] Embodiments of the present invention may also include a corresponding computer device. The computer device includes a memory, at least one processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes any of the methods described above when executing the program.

[0130] The memory, as a non-volatile computer-readable storage medium, can be used to store non-volatile software programs, non-volatile computer-executable programs, and modules, such as program instructions / modules in the embodiments of this application. The processor executes various functional applications and data processing of the device by running the non-volatile software programs, instructions, and modules stored in the memory, thereby implementing the above-described method.

[0131] The memory may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on the use of the device. Furthermore, the memory may include high-speed random access memory and non-volatile memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state storage device. In embodiments, the memory may optionally include memory remotely located relative to the processor, which can be connected to the local module via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0132] Finally, it should be noted that those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. The storage medium for the program can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc. The above computer program embodiments can achieve the same or similar effects as any of the corresponding foregoing method embodiments.

[0133] Those skilled in the art will also understand that the various exemplary logic blocks, modules, circuits, and algorithm steps described in conjunction with the disclosure herein can be implemented as electronic hardware, computer software, or a combination of both. To clearly illustrate this interchangeability between hardware and software, the functionality of various illustrative components, blocks, modules, circuits, and steps has been generally described. Whether this functionality is implemented as software or as hardware depends on the specific application and the design constraints imposed on the system as a whole. Those skilled in the art can implement the functionality in various ways for each specific application, but such implementation decisions should not be construed as departing from the scope of the embodiments disclosed herein.

[0134] The above are exemplary embodiments disclosed in this invention. However, it should be noted that various changes and modifications can be made without departing from the scope of the embodiments of this invention as defined by the claims. The functions, steps, and / or actions of the methods according to the disclosed embodiments described herein do not need to be performed in any particular order. The sequence numbers of the disclosed embodiments of this invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments. Furthermore, although the elements disclosed in the embodiments of this invention may be described or claimed individually, they may be understood as multiple unless explicitly limited to a singular number.

[0135] It should be understood that, as used herein, the singular form “a” is intended to include the plural form as well, unless the context clearly supports an exception. It should also be understood that, as used herein, “and / or” refers to any and all possible combinations of one or more of the associated listed items.

[0136] Those skilled in the art should understand that the discussion of any of the above embodiments is merely exemplary and is not intended to imply that the scope of the invention (including the claims) is limited to these examples. Within the framework of the invention, technical features of the above embodiments or different embodiments can be combined, and many other variations of different aspects of the invention exist, which are not provided in the details for the sake of brevity. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the invention should be included within the protection scope of the invention.

Claims

1. A method for balancing heat load and optimizing flow rate in a multi-cooling triangle, characterized in that, include: Obtain pipeline topology, step response data, wind field data, and measured flow and temperature values; establish a hydraulic-thermal coupling model; calculate the resistance coefficient and cooling coefficient of each branch; and obtain the heat load balance index by combining the measured temperature. When the heat load balance index exceeds the threshold, a comprehensive optimization function is constructed with the objectives of minimizing the square of the heat load deviation, the sum of the squares of the flow rate change rate, and the sum of the squares of the valve throttling loss, and the target flow rate of each branch is solved. The target flow rate of each branch is compensated by the hydraulic coupling matrix feedforward compensation to obtain the compensated flow rate, and then the target opening command of each valve is obtained by back-calculation based on the valve equal percentage characteristics. The deviation between the outlet water temperature of each branch and the target temperature is obtained. The valves are adjusted according to the deviation in three priority levels, with the same level decreasing first and then increasing, to generate the final execution command.

2. The method for balancing heat load and optimizing flow rate in a multi-cooling triangle according to claim 1, characterized in that, The process of acquiring pipeline topology, step response data, wind field data, measured flow and temperature values, establishing a hydraulic-thermal coupling model, and calculating the resistance coefficient and cooling coefficient of each branch includes: The topology of the parallel pipe network of the indirect air-cooled system, the step response data of each branch, and the wind field data are obtained. The pipe network is abstracted into a directed graph, in which the node set includes the circulating water pump outlet node, the distribution manifold node, the inlet node of each cooling triangle, the outlet node of each cooling triangle, the collection manifold node, and the return water header node. The edge set includes the main pipe section, each branch pipe section, and the cooling triangle heat exchanger section. Based on the principles of mass and energy conservation in fluid mechanics, a hydraulic-thermal coupling model is obtained by establishing the nodal continuity equation and the loop pressure drop balance equation. The hydraulic resistance coefficient and heat exchanger pressure drop characteristic coefficient of each branch were calibrated by the step response method, and the cooling coefficient of each branch was calculated by calibrating the wind field influence correction function parameters by the orthogonal test method.

3. The method for balancing heat load and optimizing flow rate in a multi-cooling triangle according to claim 2, characterized in that, The process of obtaining the heat load balance index by combining measured temperature includes: Obtain the measured flow rate of each branch, the inlet water temperature of the main pipe and the outlet water temperature of each branch, and calculate the real-time heat load and ideal heat load of each branch based on the hydraulic resistance coefficient of each branch, the pressure drop characteristic coefficient of the heat exchanger and the cooling coefficient of each cooling triangle. The heat load balance index is calculated based on the real-time heat load and ideal heat load of each branch.

4. The method for balancing heat load and optimizing flow rate in a multi-cooling triangle according to claim 1, characterized in that, When the heat load balance index exceeds the threshold, the process of constructing a comprehensive optimization function with the objectives of minimizing the square of the heat load deviation, the sum of the squares of the flow rate change rate, and the sum of the squares of the valve throttling loss, and solving for the target flow rate of each branch includes: When the heat load balance index is greater than the threshold, a comprehensive optimization objective function is constructed. The objective function is the square of the heat load balance index multiplied by the first weight coefficient, plus the sum of the squares of the deviations between the flow rate of each branch and the flow rate of the previous cycle multiplied by the second weight coefficient, plus the sum of the squares of the ratio of the valve throttling loss of each branch to the power of the circulating water pump multiplied by the third weight coefficient. Under the constraints of maintaining the total flow rate, limiting the upper and lower limits of the flow rates of each branch, and ensuring that the outlet temperature of each branch is not lower than the freezing temperature plus a safety margin, the target flow rate of each branch is obtained by using a sequential quadratic programming algorithm.

5. The method for balancing heat load and optimizing flow rate in a multi-cooling triangle according to claim 1, characterized in that, The process of obtaining the compensated flow rate by feedforward compensation of the target flow rate of each branch through the hydraulic coupling matrix includes: The feedforward compensation amount is calculated by multiplying the target flow of each branch by the hydraulic coupling coefficient through the hydraulic coupling matrix and then summing the results. The feedforward compensation is applied to the target flow of each branch to obtain the compensated flow. The hydraulic coupling coefficient is initially calibrated through an offline step response test, and is corrected online when the residual of the flow prediction of a certain branch exceeds the range within several consecutive control cycles.

6. The method for balancing heat load and optimizing flow rate in a multi-cooling triangle according to claim 1, characterized in that, The formula for deriving the target opening command of each valve based on the valve's equal percentage characteristics is as follows: ； This is the target opening command for the i-th branch valve. For maximum opening, The flow rate after compensation for the i-th branch is... Let i be the flow coefficient of the valve in the i-th branch. For the density of circulating water, R represents the throttling loss of the valve in the i-th branch, and R is the adjustable ratio.

7. The method for balancing heat load and optimizing flow rate in a multi-cooling triangle according to claim 1, characterized in that, The process of obtaining the deviation between the outlet water temperature of each branch and the target temperature, adjusting the target opening command of each valve according to the deviation magnitude in three priority levels, and adjusting the valves in the same priority level in a decrement-then-increase order, and generating the final execution command includes: Obtain the deviation between the outlet water temperature of each branch and the target temperature; Each branch is divided into three priorities based on temperature deviation: branches with deviation exceeding the first degree Celsius are of first priority, branches with deviation between the first and second degrees Celsius are of second priority, and branches with deviation less than the second degree Celsius are of third priority. The valves are operated in the order of first priority, second priority, and third priority. Within the same priority, the valves are adjusted in the order of decreasing first and then increasing. The final execution command of each valve is obtained, and the heat load balancing and circulating water flow optimization of the multi-cooling triangle in the indirect air-cooled system are carried out.

8. A multi-cooling triangle heat load balancing and flow optimization system, characterized in that, include: The modeling unit is configured to acquire pipeline topology, step response data, wind field data, measured flow and temperature values, establish a hydraulic-thermal coupling model, calculate the resistance coefficient and cooling coefficient of each branch, and obtain the heat load balance index by combining the measured temperature. The solution unit is configured to construct a comprehensive optimization function with the objective of minimizing the square of the heat load deviation, the sum of the squares of the flow rate change rate, and the sum of the squares of the valve throttling loss when the heat load balance index exceeds the threshold, and solve for the target flow rate of each branch. The compensation unit is configured to obtain the compensated flow rate by feedforward compensation of the target flow rate of each branch through the hydraulic coupling matrix, and then back-calculate the target opening command of each valve based on the valve's equal percentage characteristics. The adjustment unit is configured to obtain the deviation between the outlet water temperature of each branch and the target temperature, and adjust the target opening command of each valve according to the deviation size in three priority levels, with the same level decreasing first and then increasing, to generate the final execution command.

9. A computer device, comprising: At least one processor; The processor also includes a memory storing a computer program that can run on the processor, characterized in that the processor executes the program to perform the steps of a multi-cooling triangle heat load balancing and flow optimization method as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it performs the steps of the multi-cooling triangle heat load balancing and flow optimization method as described in any one of claims 1 to 7.

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