A control method of cold and heat source high-efficiency machine room integrated system based on system synergy theory

Abstract

The application relates to the air conditioning technical field and discloses a cold and heat source efficient machine room integrated system control method based on a system coordination theory, which comprises the following steps: synchronously collecting the total active power of a water chilling unit, the total active power of a water supply and distribution pump, the total active power of a cooling tower fan, a chilled water supply temperature setting value and the total return water temperature of chilled water of an air conditioning water system at a preset sampling period; directly calculating a water supply and distribution power loss factor by using a mapping relationship between real-time power and a supply and return water temperature difference without relying on physical temperature disturbance; combining a host heat gain factor calculation system total energy consumption gradient covering a cold source heat dissipation cost, and dynamically adjusting the chilled water supply temperature setting value until the gradient converges to a balance dead zone, so that the engineering problem that real-time sensitivity of a large inertia water system cannot be measured is solved.

Description

Technical Field

[0001] This invention relates to a control method for a high-efficiency integrated system of cold and heat sources in a computer room based on system synergy theory, belonging to the field of air conditioning technology. Background Technology

[0002] In current centralized cooling systems for large public buildings and industrial facilities, the chiller / heater room serves as the core hub for energy consumption, making system efficiency a focus of industry attention. Existing mainstream technologies typically employ variable flow distribution systems, adjusting the chilled water supply temperature or flow rate setpoints to find the optimal balance between chiller unit operating efficiency and distribution pump power consumption. Industry-recognized control logic suggests that while increasing the chilled water supply temperature improves the chiller unit's coefficient of performance (COP), maintaining constant terminal cooling demand leads to a significant increase in the required circulation flow rate of the distribution network, according to the thermodynamic energy conservation principle. This causes the pump power consumption to increase exponentially. Under dynamically changing load conditions, capturing the critical point where thermal gains on the main unit side and hydraulic losses on the distribution side are offset, i.e., obtaining the real-time sensitivity gradient of the system's total energy consumption relative to the control variables, is a core technical challenge for achieving optimal overall energy efficiency in the chiller room.

[0003] Existing technologies addressing these challenges largely rely on the stacking of system hardware, lacking deep decoupling capabilities for complex fluid networks in the control dimension. For example, Chinese invention patent CN108366516B discloses a passive heat pipe natural cooling room air conditioning system and its control method. This solution reduces energy consumption by utilizing outdoor natural cooling sources through hardware coupling of a passive heat pipe circulation system and an auxiliary cooling source system. However, the control logic is inherently limited by static physical parameter boundaries. The solution mainly relies on whether the outdoor temperature and return air temperature meet preset switching temperature difference conditions to mechanically switch modes or start / stop fans. This discrete control strategy based on fixed thresholds, while utilizing natural cooling sources, cannot perceive the resistance characteristics of the pipeline network due to the dynamic drift caused by random valve movements in real time, and lacks continuous quantitative analysis of energy consumption sensitivity on the transmission and distribution side. In practical engineering applications, obtaining energy consumption sensitivity faces challenges related to physical mechanisms and... The air conditioning water system faces a dual challenge in terms of time dimension. It has huge thermal inertia and transmission lag. Traditional extreme value search methods based on trial disturbances often require several minutes or even longer to observe the steady-state power response of the system to temperature adjustment. Long-term adjustment lag can easily lead to oscillations and energy waste under non-optimal operating conditions. Although the prediction method based on theoretical models has a fast response, it is limited by the high uncertainty of the pipe network resistance characteristics. The random action of many terminal regulating valves causes the pipe network resistance curve to drift in real time. This causes the predicted value based on the static hydraulic model to deviate significantly from the actual operating conditions. As a result, the control system issues incorrect adjustment commands, the equipment operation cycle is extended, and the thermal resistance of the condenser and evaporator surfaces gradually increases. This causes the actual thermal response characteristics of the equipment to deviate from the factory standard curve. If the control algorithm cannot perceive the physical attenuation and still schedules according to the ideal model, the auxiliary equipment will do excessive work while the main unit's energy efficiency does not improve as expected, resulting in a negative optimization phenomenon.

[0004] Therefore, how to construct a control mechanism that can real-time analyze the hydraulic sensitivity of the pipe network and self-adaptively correct the thermal decay characteristics of the equipment, so as to realize real-time closed-loop optimization of the system global energy efficiency under the premise of guaranteeing the service quality at the end, becomes a technical problem to be solved by the present application. SUMMARY

[0005] To solve the problems in the background art, the technical scheme of the present application is as follows: a cold and heat source high-efficiency machine room integrated system control method based on system coordination theory, the method being applied to an air conditioning water system comprising a water chiller, a variable frequency water supply and distribution pump, a cooling tower fan and an end load, and comprising:

[0006] synchronously collecting the total active power of the water chiller, the total active power of the water supply and distribution pump, the total active power of the cooling tower fan, the chilled water supply temperature set value and the total chilled water return water temperature of the air conditioning water system at a preset sampling period;

[0007] calculating a water supply and distribution hydraulic loss factor by using a calculation rule preset by the controller, the calculation rule being defined as dividing the total active power of the water supply and distribution pump by the difference between the total chilled water return water temperature and the chilled water supply temperature set value, and multiplying the obtained quotient by a preset hydraulic characteristic index, so as to directly calculate the energy consumption sensitivity of the water supply and distribution side under the current working condition by using the mapping relationship between the real-time power and the supply and return water temperature difference, and the calculation process does not include performing a temperature exploratory adjustment on the air conditioning water system;

[0008] synchronously obtaining a main machine thermal gain factor of the water chiller, and calculating the algebraic sum of the main machine thermal gain factor and the water supply and distribution hydraulic loss factor to obtain a system total energy consumption gradient;

[0009] adjusting the chilled water supply temperature set value according to the sign direction of the system total energy consumption gradient, increasing the chilled water supply temperature set value when the absolute value of the main machine thermal gain factor is greater than the absolute value of the water supply and distribution hydraulic loss factor, and decreasing the chilled water supply temperature set value when the absolute value of the main machine thermal gain factor is less than the absolute value of the water supply and distribution hydraulic loss factor, until the system total energy consumption gradient is within a preset balance dead zone range.

[0010] Preferably, in the step of calculating the water supply and distribution hydraulic loss factor, the following formula is specifically used: wherein, is the water supply and distribution hydraulic loss factor, is the total active power of the water supply and distribution pump, is the total chilled water return water temperature, is the chilled water supply temperature set value, is the hydraulic characteristic index, and the formula represents the derivative relationship of the water supply and distribution pump power relative to the supply water temperature change under the quasi-steady state of the end load.

[0011] Preferably, the hydraulic characteristic index is a dimensionless coefficient representing the power change index of the water supply and distribution pump under the current pipe network resistance characteristics, and the value range is 2.0 to 3.0; the hydraulic characteristic index stored in the controller register is called, and a one-time algebraic operation is performed combined with the real-time collected operating parameters to obtain the water supply and distribution hydraulic loss factor.

[0012] Preferably, the step of obtaining the host heat gain factor further comprises a correction step based on the condenser heat exchange performance attenuation: collecting the saturated temperature corresponding to the condensing pressure of the water chiller and the cooling water outlet temperature, calculating the difference between the two to obtain the real-time approach temperature difference; calculate the ratio of the real-time approach temperature difference to the preset reference approach temperature difference to obtain the performance attenuation coefficient; use the performance attenuation coefficient to reduce the weight of the initial host heat gain factor determined based on the water chiller performance curve, and obtain the host heat gain factor, to compensate for the deviation of the host energy efficiency response caused by the increase of the condenser surface dirt thermal resistance.

[0013] Preferably, the correction step specifically includes: when the real-time approach temperature difference is greater than the reference approach temperature difference, the performance attenuation coefficient takes a value less than 1, and the absolute value of the host heat gain factor is reduced by using the performance attenuation coefficient, so as to reduce the energy saving benefit weight of the water chiller side in the calculation of the system total energy consumption gradient.

[0014] Preferably, the step of adjusting the chilled water supply temperature set value comprises a constraint judgment based on the terminal hydraulic working condition: real-time monitoring of the opening value of all two-way regulating valves in the terminal load, and identifying the maximum opening value; judge whether the maximum opening value is greater than the preset hydraulic limit threshold; if the maximum opening value is greater than the hydraulic limit threshold, generate an adjustment lock instruction, which prohibits any action that will cause the chilled water supply temperature set value to rise, until the maximum opening value falls below the recovery threshold.

[0015] Preferably, the recovery threshold is less than the hydraulic limit threshold, so as to form a hysteresis return difference in the control logic to prevent adjustment oscillation.

[0016] Preferably, the host heat gain factor is negative, indicating that the power of the water chiller decreases with the increase of the supply water temperature; the water supply and distribution hydraulic loss factor is positive, indicating that the power of the water supply and distribution pump increases with the increase of the supply water temperature; the sign of the system total energy consumption gradient indicates the change trend of the system total power with respect to the supply water temperature.

[0017] Preferably, the step of adjusting the chilled water supply temperature set value adopts a variable step adjustment strategy: calculating the absolute value of the system total energy consumption gradient; according to the absolute value, searching for the corresponding temperature adjustment step in the preset step table, the step table is configured to output a larger step when the gradient absolute value is larger, and output a smaller step when the gradient absolute value is smaller; use the temperature adjustment step to correct the chilled water supply temperature set value.

[0018] Preferably, the method is run in an industrial programmable logic controller in communication with the chiller unit and the water distribution pump, and the collecting, calculating and adjusting steps are completed within a single scan cycle of the industrial programmable logic controller.

[0019] Compared with the prior art, the present application has the following beneficial effects:

[0020] 1. In the high-efficiency chiller plant integration, a mechanism based on the transient fluid affinity law and the algebraic mapping of thermodynamic energy equations is constructed to realize real-time analysis of the hydraulic energy consumption sensitivity of the distribution system. The ratio of the real-time active power of the chilled water pump to the supply and return water temperature difference is used to directly map the dynamic and complex resistance characteristics of the pipe network due to valve action into a single observable physical quantity. Without the need to establish a pipe network hydraulic model and without the need to rely on system temperature disturbance, the gradient of the influence of the supply water temperature change on the power consumption of the pump is captured in real time, the response lag and oscillation risk of trial and error adjustment in a large inertia water system are eliminated, the control logic is ensured to always make decisions based on the real hydraulic transportation cost under variable flow conditions, and zero-time delay response and physical state self-adaptation of the chiller system in terms of energy consumption evaluation on the distribution side are realized.

[0021] 2. The present application uses the condenser approach temperature difference to represent the physical efficiency of the heat exchanger, establishes dynamic correction logic for the host thermodynamic gain factor, quantifies the effect of increased thermal resistance due to heat exchanger pipe wall dirt deposition or biological slime adhesion by monitoring the real-time approach temperature difference deviation from the reference state, automatically reduces the weight of the cooling water temperature reduction expected benefit in the control algorithm accordingly, automatically suppresses the tendency to excessively increase the cooling tower fan power consumption in pursuit of theoretical energy efficiency during the natural decay process of the equipment heat transfer performance over time, avoids negative optimization phenomena caused by mismatch between model parameters and actual equipment state from the perspective of thermodynamics, and ensures the stability of the energy saving strategy throughout the life cycle of the equipment.

[0022] 3. A physical veto mechanism based on the endmost unfavorable loop valve opening is introduced in the gradient optimization control closed loop to construct a rigid boundary between energy efficiency optimization and service quality guarantee, directly map the pipe network endmost cold energy transportation demand into a one-way cut-off signal of the adjustment logic, and lock or reverse adjust the supply water temperature set value when the endmost regulating valve opening reaches the hydraulic transportation limit, thereby shielding the energy consumption gradient energy saving direction indication, solving the problem of excessive pursuit of host energy efficiency breakthrough pipe network transportation capacity bottom line under partial load conditions by pure mathematical optimization logic, realizing energy consumption extremum search based on guaranteeing the cold energy acquisition ability of end users, and decoupling the physical conflict between energy saving target and comfort guarantee target under critical conditions.

[0023] 4. The present application realizes real-time closed-loop optimization of the COP of the chiller system (host + cooling tower) through double-factor gradient optimization. Unlike the traditional logic of controlling the cooling tower only according to the fixed condensing pressure or cooling water temperature, the present scheme maps the cooling source heat dissipation benefit (represented by the condensing pressure) and the distribution cost (represented by the cooling water temperature) into a single observable physical quantity, and realizes real-time closed-loop optimization of the COP of the chiller system (host + cooling tower) through double-factor gradient optimization. The system performs real-time decoupling and hedging to ensure that the cooling source system always operates at the extreme point where the power increment is zero, that is, the COP of the cooling source system reaches the physical limit under the current load conditions. This effectively avoids the negative optimization phenomenon where the energy-saving benefits on the main unit side are offset by the power consumption of auxiliary equipment (cooling tower fans, water pumps). Attached Figure Description

[0024] Fig. 1 This is a flowchart of the system collaborative optimization control logic for the dual-factor energy consumption gradient of the present invention;

[0025] Fig. 2 This is a curve comparing the dynamic response of the total power of the system and the improvement in energy efficiency of the present invention.

[0026] Fig. 3 This is a schematic diagram of the hardware topology and signal interaction principle of the integrated hydraulic constraint control system of this invention. Detailed Implementation

[0027] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with specific implementation methods. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0028] This embodiment discloses a control method for a high-efficiency integrated cold and heat source computer room system based on system coordination theory. The system includes chillers, variable frequency water pumps, cooling tower fans, and terminal air handling equipment. The method is executed by an industrial programmable logic controller (PLC) or direct digital controller (DDC). The controller communicates with each device via an industrial fieldbus such as Modbus or BACnet. The controller synchronously collects the operating parameters of the air conditioning water system at a preset sampling period, set to 30 to 60 seconds. The operating parameters include the total active power of all operating chillers at the current moment. Total active power of all operating water distribution pumps Total active power of cooling tower fans in operation Current chilled water supply temperature setpoint and total return water temperature of chilled water The controller uses operating parameters to implement the hydraulic loss factor for transmission and distribution. Calculation procedure; hydraulic loss factor for transmission and distribution The controller directly determines the power of the water distribution pumps based on preset algebraic calculation rules, characterizing the pumps' sensitivity to changes in supply water temperature. The value is calculated according to the following rule: the total active power of the water distribution pumps. Divide by the total return temperature of chilled water With chilled water supply temperature setpoint The difference is calculated, and the resulting quotient is multiplied by a preset hydraulic characteristic index. The calculation formula is as follows: ,in, The unit is kilowatts per degree Celsius; The unit is kilowatt; and The unit is Celsius, and the difference between the two is the real-time supply and return water temperature difference. The dimensionless hydraulic characteristic index ranges from 2.0 to 3.0. The calculation rule is based on the chain derivative relationship between the fluid similarity law and the thermodynamic energy equation. It directly analyzes the hydraulic sensitivity of the pipeline network under the current operating conditions using real-time power and temperature difference data, without the need to perform exploratory temperature adjustments on the system.

[0029] Hydraulic characteristic index The determination of the required parameters requires the execution of a standardized calibration procedure during the system commissioning phase. This procedure includes: maintaining a constant valve opening at the end of the pipeline network; controlling the frequency of the distribution pumps to stabilize at three different operating points, such as 40Hz, 45Hz, and 50Hz; recording the pump power and flow rate data corresponding to each operating point; performing logarithmic linear regression fitting on the power and flow rate data to obtain the exponential relationship between power and flow rate; and using its power exponent as the hydraulic characteristic index. Write to the controller's register; the controller synchronously acquires the chiller unit's main thermal gain factor. The controller, based on the current load rate of the chiller unit and the chilled water outlet temperature, retrieves the equipment standard partial load performance curve stored in the controller, and looks up the table to obtain the theoretical derivative of power relative to supply water temperature at that operating point, i.e., the initial host thermal gain factor. This factor is usually negative, representing the decrease in main unit power caused by an increase in supply water temperature, and is the main unit thermal gain factor. In essence, this relates to the sensitivity of the overall coefficient of performance (COP) of a generalized cold source system (including chillers and cooling towers) to changes in supply water temperature. Its core logic lies in quantifying the algebraic offsetting relationship between the power derating of the main compressor caused by an increase in supply water temperature and the potential increase in cooling tower fan power consumption to maintain heat exchange efficiency, thereby locking in the globally optimal energy efficiency operating point on the cold source side. Secondly, the controller executes a correction step based on the degradation of condenser heat exchange performance, and the controller collects the saturation temperature corresponding to the current condensing pressure of the chiller unit. and cooling water outlet temperature The difference between the two is calculated to obtain the real-time approximate temperature difference. The controller calls the preset reference approximation temperature difference. This benchmark value is the approximate temperature difference measured by the equipment under clean conditions and at the same load rate. The controller calculates the performance degradation coefficient k, and its calculation formula is: Due to the increase of fouling thermal resistance The value of performance attenuation coefficient k is less than 1 as the equipment running time increases, and the controller corrects the initial factor using the coefficient to obtain the corrected host thermal gain factor The calculation formula is This step reduces the energy saving benefit weight of the chiller unit side in the control logic by real-time physical parameter feedback to match the actual thermal response characteristics of the equipment; through real-time monitoring of the approach temperature difference The system can immediately analyze the real boundary of the contribution of cooling tower heat dissipation performance to the host energy efficiency; if the approach temperature difference increases due to environmental wet-bulb temperature limitation or cooling tower heat exchange efficiency decline, the correction step will automatically inhibit the tendency of the system to excessively increase the cooling tower fan power consumption for the purpose of blindly pursuing the improvement of the host individual COP, and ensure that the overall energy efficiency of the cooling source system does not be optimized.

[0030] The controller calculates the total energy consumption gradient of the system The gradient is the algebraic sum of the corrected host thermal gain factor And the water supply and distribution hydraulic loss factor That is The controller adjusts the chilled water supply temperature set value according to the sign direction of The controller generates a command to increase ; The controller generates a command to decrease ; when is within the preset balance dead zone range, for example, the absolute value is less than 0.5 kilowatts per degree Celsius, the controller keeps the current set value unchanged; before executing the above adjustment, the controller performs constraint judgment based on the end hydraulic working condition, and the controller collects the opening feedback value of all two-way regulating valves at the end of the water supply and distribution system through real-time traversal collection through the communication network, and identifies the maximum opening value The controller judges whether is greater than the preset hydraulic limit threshold, which is set to 90%; if is greater than 90%, the controller generates a regulation lock command, which prohibits any action that causes the chilled water supply temperature set value to rise, until falls below the recovery threshold, which is set to 85%; this step uses the end valve opening as a physical boundary constraint to prevent flow shortage in the most unfavorable loop due to excessive energy saving.

[0031] ​Example 1: In a renovation project of an existing commercial building's air conditioning water system, which is operating under partial load and where the chiller's heat exchange performance is degraded, the air conditioning system is in transitional season operation mode, with the total cooling load rate fluctuating between 30% and 45%. Furthermore, fouling deposits on the chiller's condenser side cause the actual heat exchange efficiency to deviate from the factory standard curve. Simultaneously, there is a most unfavorable loop area with high hydraulic resistance at the end of the pipe network. The controller synchronously collects system operating parameters every 30 seconds, measuring the total active power of all operating water pumps. 45kW, total chilled water return temperature for Current chilled water supply temperature setpoint It is 7.0. Corresponding real-time supply and return water temperature difference The controller calls the calibrated hydraulic characteristic index according to the preset calculation rules. The value is 2.8, using the formula. The current hydraulic loss factor for transmission and distribution is calculated. for This value quantifies the situation where, under the current pipeline resistance characteristics, the water supply temperature setpoint is increased by 1. The increase in pump power consumption caused by the increased flow rate required to maintain terminal cooling balance.

[0032] The controller synchronously obtains the theoretical initial host thermal gain factor by referring to the standard performance curve based on the current unit load rate. The current condensing pressure of the chiller unit corresponds to the saturation temperature. With cooling water outlet temperature Real-time approximate temperature difference between Based on the benchmark approach temperature difference under this operating condition The calculated performance degradation coefficient k is 0.6. The controller uses the formula... The actual host thermal gain factor is obtained by correcting the initial factor. The issue reflects that the energy savings from increasing the water supply temperature due to condenser fouling and thermal resistance are lower than theoretically expected. The controller utilizes a formula... Total energy consumption gradient of the synthesis system This positive gradient indicates that the energy penalty on the pump side due to increased flow exceeds the actual energy-saving benefits of the main unit. Based on this, the controller generates a lower setpoint for the chilled water supply temperature. The controller, by lowering the supply water temperature to increase the supply and return water temperature difference and reducing the distribution flow rate, resolves the dynamic contradiction between the thermal gains of the main unit and the hydraulic losses of the distribution system within a single architecture. Before executing temperature regulation, the controller performs a real-time scan of the opening of the two-way regulating valves of the terminal air handling units, identifying the opening of the two-way valve of an air handling unit in a conference room located at the farthest end of the pipeline network. reaches 92%, which exceeds the preset hydraulic limit threshold 90% and indicates that the most unfavorable loop approaches the physical limit of the delivery capacity. The system identifies that the state is consistent with the direction of reducing the supply water temperature indicated by the aforementioned energy consumption gradient calculation, and accordingly performs the temperature reduction adjustment action to simultaneously meet the dual needs of reducing the total energy consumption of the system and relieving the end hydraulic imbalance, ensuring that the global energy efficiency optimization of the system always operates within the boundary of the physical delivery capacity of the pipe network.

[0033] Example 2: In this embodiment, the control method of the cold and heat source high-efficiency machine room integrated system based on the system synergy theory in Example 1 is systematically verified on a simulation test platform with variable working conditions. The actual regulation effect and engineering feasibility of the control method under dynamic load changes, equipment performance degradation, and hydraulic working conditions are evaluated. The test platform includes a chiller model with programmable load simulation capability, a variable frequency water pump group, and a pipe network resistance simulation device. The platform is configured with a power analyzer, a flow meter, and a temperature sensor for real-time acquisition of key physical quantities of system operation. The data acquisition frequency of all sensors is set to 1 Hz. The test process simulates the daily load variation curve of a typical office building in the summer cooling season. The load rate range is set to 20% to 90%. The test sets the baseline working condition parameters: the rated supply and return water temperature difference of the chiller is 5 , and the pipe network design resistance characteristic curve meets the conventional engineering standard. At the beginning of the test, the system operates at 50% partial load. The controller calculates the water supply and distribution hydraulic loss factor and the main machine thermodynamic gain factor corrected for dirt . At the initial moment, the simulated condenser is in a clean state. The baseline approach temperature difference is consistent with the real-time approach temperature difference. The performance degradation coefficient k is 1.0. At this time, the energy consumption gradient indicates the optimization direction. The controller adjusts the chilled water supply temperature set value accordingly.

[0034] The test introduces an interference working condition with gradually increasing dirt thermal resistance. By adjusting the simulation parameters, the real-time approach temperature difference is gradually increased from 1.5 to 3.0 . The controller captures this change in real time. The calculated performance degradation coefficient k decreases from 1.0 to 0.5. This change causes the absolute value of the corrected main machine thermodynamic gain factor to decrease, indicating that the energy saving benefit obtained by increasing the supply water temperature on the main machine side is weakened. Accordingly, the controller automatically adjusts the optimization strategy to suppress the excessive increase of the supply water temperature, avoiding the increase of the cooling tower fan energy consumption due to the pursuit of the main machine COP when the heat exchange performance decreases. In the third stage of the test, the hydraulic imbalance at the end of the pipe network is simulated. By adjusting the resistance valve in the simulation device, the end valve opening degree representing the most unfavorable loop is gradually increased from 0.5 to 1.0. Forced to 95%, at this time, although the energy consumption gradient calculation results may still suggest to increase the supply water temperature to reduce the host energy consumption, but the controller identifies More than 90% of the hydraulic limit threshold, triggering the hydraulic lockout logic, the system is forced to stop the supply water temperature rising action, and according to the logic reverse to reduce the supply water temperature set value, priority to guarantee the flow and cold supply at the end.

[0035] Table 1: Key operating data record table of different test stages in this embodiment

[0036]

[0037] Referring to Table 1, in the initial stable stage, the negative gradient drives the supply water temperature to rise to save energy; in the dirt interference stage, due to the decrease of k value Correction, the gradient turns to positive, the system performs reverse adjustment; in the hydraulic limit stage, although the gradient is positive indicating to lower the temperature (consistent with the direction of hydraulic constraint), but the system responds to The lockout protection triggered by exceeding the threshold value, to ensure that the physical boundary is not broken.

[0038] Embodiment 3: This embodiment combines Figs. 1 to 3 , a kind of cold and heat source high-efficiency machine room integrated system control method based on system synergy theory is described, as shown in Fig. 1 , control logic executes data synchronization acquisition, covering unit power, water pump power, supply water set value and return water temperature, two calculation branches are executed in parallel, one of which calculates the water delivery and distribution hydraulic loss factor using real-time power and supply and return water temperature difference mapping relationship, this process directly calculates without physical temperature disturbance, the second obtains and corrects the host thermal response characteristic to obtain the host thermal gain factor, which represents the trend of host power change with temperature, after the synthesis of the two factors, the system total energy consumption gradient is calculated and the system energy consumption trend is judged, enter the gradient sign direction judgment link, compare the absolute value of the factor, when the absolute value of the host thermal gain is less than the absolute value of the water delivery and distribution hydraulic loss and the gradient indicates the energy saving direction is negative, execute lower chilled water supply temperature set value, otherwise when the absolute value of the host thermal gain is greater than the absolute value of the water delivery and distribution hydraulic loss and the gradient indicates the energy saving direction is positive, execute higher chilled water supply temperature set value, until the system total energy consumption gradient is in the preset balance dead zone range, trigger the balance dead zone convergence determination to maintain the current set value.

[0039] As shown in Fig. 2 , the horizontal axis unit is minute, the left vertical axis unit is , the right vertical axis unit is The total power curve of the control method system of the application shown by the solid line coincides with the total power curve of the conventional control method system shown by the dotted line at the starting point, the former presents a faster descending rate over time and stabilizes at a lower power level, while the latter descends gently and finally stabilizes at a higher power level, the difference between the two forms an energy efficiency improvement amplitude curve shown by the dotted line, which gradually rises and maintains in the positive value interval after the system stabilizes; as shown in Fig. 3 The overall architecture is centered on a programmable logic controller (PLC), which internally integrates a collaborative optimization algorithm resident core, specifically covering the functions of mainframe attenuation correction, energy consumption gradient optimization, and loss analysis of the distribution system. The controller interacts with the upper cold source mainframe system in both directions, receives the reported unit power and approach temperature difference, and issues the water supply temperature set value instruction. At the same time, it receives the water pump power and supply-return water temperature difference reported by the variable frequency distribution system on the lower left, and collects the maximum valve opening of the two-way regulating valve feedback from the end load facility on the lower right. When the opening signal reaches the threshold, it triggers the hydraulic limit locking mechanism, which acts as a veto signal directly on the core algorithm, thus forming a closed-loop control topology containing energy efficiency optimization and boundary constraints at the physical hardware level.

[0040] Example 4: This example is aimed at the adaptive parameter calibration scenario of the air conditioning water system during the initial commissioning stage and the seasonal transition period. It details the standardized engineering construction procedures for determining the hydraulic characteristic index and the reference approach temperature difference involved in the specific embodiments mentioned above, and further discloses a variable step size adjustment logic based on real-time gradient. During the commissioning period after the completion of physical installation and the first operation of the cold and heat source machine room, the controller enters the hydraulic property self-learning mode. At this time, the controller sends instructions to the end system to lock all two-way regulating valves at a pre-set typical opening position, such as 50% opening, and keeps the system in a closed-loop hydraulic stable state. The controller drives the variable frequency distribution water pump to perform stepwise variable frequency action, with the frequency set value increasing by 5 Hz as a step from 35 Hz to 50 Hz. After maintaining stable operation for 5 minutes at each frequency step, the controller records the current total active power of the distribution water pump and the corresponding total flow of the circuit The controller obtains at least four sets of valid data points and performs a logarithmic linear regression operation on them. The controller uses the least squares method to fit the equation where the slope term is the hydraulic characteristic index of the current working condition of the pipe network, and C is the fitting intercept constant. This calculation process is directly completed in the bottom register of the controller. The calculated value is solidified as the reference parameter for subsequent real-time operation, ensuring that the calculation of the distribution hydraulic loss factor is anchored to the true pipe network resistance characteristics.

[0041] After the hydraulic calibration, the system enters the thermal benchmarking phase, and establishes the baseline approach temperature difference model of the water chiller in the clean state Under the condition that the cooling water quality meets the standard and the condenser is in the initial state without fouling deposition, the controller monitors and records the operating data of the water chiller under different load rate intervals. The system covers the load rate interval of 30% to 90% by adjusting the terminal load or using a dummy load, and records the condensing pressure corresponding to the saturation temperature at each load rate point with an interval of 10% The cooling water outlet temperature The controller calculates the measured approach temperature difference at each point, and establishes the functional relationship between the load rate and the baseline approach temperature difference using a quadratic polynomial fitting algorithm, that is The coefficients obtained by fitting are stored in the control logic library as the only basis for calculating the performance degradation coefficient in subsequent operation. This procedure upgrades the acquisition of baseline values from a static single value to a dynamic curve covering the full load condition, eliminating the risk of false judgment caused by deviation from the design point.

[0042] Based on the above calibrated physical parameters, when the controller performs dynamic adjustment of the chilled water supply temperature set value , the controller further adopts a variable step size adjustment strategy based on the gradient. The controller calculates the absolute value of the system total energy consumption gradient , and generates a temperature adjustment step size in real time according to a pre-set mapping function . The mapping logic is configured as follows: when is greater than a set threshold such as 2.0kW / , it indicates that the system is far from the optimal operating point, and the controller outputs a larger adjustment step size such as 0.5 to achieve rapid approximation of the energy efficiency extreme; when is in the convergence interval such as , the adjustment step size decreases linearly with the decrease of the gradient absolute value; when is less than the balance dead zone threshold such as , the step size is zero, and the system maintains the current set value.

[0043] Example 5: This embodiment describes a pre-deployment calibration procedure for ensuring the stable operation of the cold and heat source high-efficiency machine room integrated system control method under different hardware environments and seasonal operating conditions. Before the system is formally put into closed-loop automatic control, after the physical wiring and communication debugging of the machine room control system are completed, the engineering personnel start the sensor consistency verification program. The system controls all the parallel running chilled water pumps to run at the same frequency, such as 45 Hz, and maintains the total valve opening of the pipe network unchanged. The system runs continuously for 30 minutes to reach hydraulic steady state. At this time, the controller synchronously reads the real-time readings of the supply water main temperature sensor and each cold water chiller outlet branch temperature sensor. If the absolute value of the deviation between the total pipe reading and the weighted average of the branch pipe readings exceeds 0.2 , the controller automatically generates a calibration bias and writes it into the underlying register to eliminate the temperature gradient calculation error caused by individual differences in sensors. The flowmeter zero drift correction is performed. When the pump is completely stopped and it is confirmed that there is no flow in the pipe network, the controller reads the instantaneous flow feedback value of the electromagnetic flowmeter. If the value is not zero, it is stored as the zero point noise in the system configuration parameters and is deducted in all subsequent flow calculations.

[0044] After completing the sensor calibration, the system performs an adaptive setting procedure for the seasonal operating condition boundary. Based on the difference in cooling water inlet temperature between the transition season and the summer season, the controller sets the minimum cooling water temperature protection threshold in the current season according to the local meteorological data or historical operation records . For example, in the transition season, to prevent the condensing pressure from being too low and causing the unit to have difficulty returning oil, the controller sets 20 ; while in the summer high temperature and high humidity operating condition, to ensure the heat exchange efficiency, the threshold is automatically raised to 25 . At the same time, according to the technical manual provided by the chiller manufacturer, the controller records the unit surge boundary curve at different cooling water inlet temperatures. In subsequent real-time control, if the calculated optimal chilled water supply temperature set value causes the unit operating point to approach the surge boundary, such as a safety margin of less than 10%, the system will limit the further adjustment of the supply water temperature, and preferentially maintain the safe and stable operation of the unit. This pre-calibration procedure standardizes the initialization of the physical perception layer and the safety logic layer, and builds a reliable and safe execution environment for the gradient-based energy efficiency optimization algorithm.

[0045] Example 6: In the scene of on-site tuning of control parameters for specific cold and heat source machine room physical characteristics, to eliminate the subjective and experiential deviation of the preset balance dead zone threshold and the variable step adjustment interval boundary, the controller performs a closed-loop identification procedure based on the system inherent noise and step response characteristics. When the system load rate remains relatively stable and there is no external large disturbance input, the controller locks the chilled water supply temperature set value and maintain constant for 30 minutes, during which the total system energy consumption gradient calculated in real time is continuously collected at a frequency of 1 Hz Data sequence, the controller calculates the standard deviation of the data sequence , the controller will physically anchor the upper and lower limit boundaries of the balance dead zone range as , ensuring that subsequent control actions are only triggered by physical changes in energy efficiency, rather than random noise triggered by sensor fluctuations or fluid turbulence; second, the controller performs a step test for gradient response sensitivity to build a quantized mapping function for variable step adjustment, and the controller sets the cold water supply temperature setpoint to 1.0 , a step signal with an amplitude of 1.0 , the absolute change in the total system energy consumption gradient , which is defined as the response gain G of the system per unit temperature gradient, the controller sets the maximum step intervention threshold in the variable step adjustment strategy as , and sets the lower limit of the linear adjustment interval as the noise boundary calculated above , thus constructing a linear interpolation function connecting the dead zone and the maximum step zone determined by the measured physical response characteristics, ensuring that the generation logic of the adjustment step fully adapts to the thermal inertia and hydraulic transmission lag characteristics of the specific computer room water system.

[0046] To eliminate the interference of sensor high-frequency noise and fluid turbulence on energy consumption gradient calculation, the controller performs algebraic operations on the hydraulic loss factor and the main machine thermal gain factor Before the sliding time window preprocessing is performed on the collected real-time power and temperature data sequences, the sliding window length is set to 3 to 5 times the sampling period, and the arithmetic mean and standard deviation of the data sequence in the real-time calculation window are calculated. When the window data standard deviation is less than the preset sensor accuracy threshold, such as temperature 0.1 and power 0.5 kW, the arithmetic mean is used as the input parameter for formula calculation, otherwise the last period calculation result is maintained to prevent adjustment oscillation; during the gradient response sensitivity step test and variable step adjustment strategy parameter setting process, the system stability determination does not depend on time, and the controller real-time monitors the total return water temperature of the chilled water relative to the time first derivative , when the absolute value of the derivative is less than 0.1 per minute thermal inertia convergence threshold for 3 consecutive sampling periods, it is determined that the system has completed the physical response of the chilled water supply temperature step signal, triggering the system total energy consumption gradient change record and response gain G calculation, ensuring that the control parameter setting is based on the thermal equilibrium physical working condition; and for the reference approach temperature difference model Verification, the system establishes thermal benchmark after performing consistency check, the controller will cold water unit 100% full load condition measured approach temperature difference and unit design approach temperature difference of factory technical manual comparison, if the absolute value of both deviation exceeds 0.5 , determine the current cleaning state does not reach clean benchmark requirements or sensor exists zero drift, generate the lock signal of prohibition into adaptive control mode, until the completion of physical cleaning or sensor calibration and reset signal.

[0047] For those skilled in the art, it is obvious that the present application is not limited to the details of the above exemplary embodiments, and the present application can be implemented in other specific forms without departing from the spirit or essential characteristics of the present application.

[0048] Finally, it should be noted that the above examples are only used to illustrate the technical solutions of the present application and are not limiting. Although the present application is described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present application can be modified or replaced equivalently without departing from the spirit and scope of the technical solutions of the present application.

Claims

1. A control method of a high-efficiency machine room integrated system of a cold and heat source based on a system synergy theory, characterized in that, The method is applied to an air conditioning water system comprising a chiller, a variable frequency water supply and distribution pump, a cooling tower fan and an end load, and comprises: synchronously collecting the total active power of the chiller, the total active power of the water supply and distribution pump, the total active power of the cooling tower fan, the chilled water supply temperature set value and the total chilled water return temperature of the air conditioning water system at a preset sampling period; calculating the water supply and distribution hydraulic loss factor using a calculation rule preset by the controller, the calculation rule being defined as the total active power of the water supply and distribution pump divided by the difference between the total chilled water return temperature and the chilled water supply temperature set value, and the resulting quotient multiplied by a preset hydraulic characteristic index, to directly calculate the water supply and distribution side energy consumption sensitivity under the current working condition using the mapping relationship between real-time power and the supply and return water temperature difference, and the calculation process not including performing temperature trial regulation on the air conditioning water system; Synchronously acquire the main engine thermal gain factor of the water chilling unit, and the controller calls the equipment standard part load performance curve stored in the controller according to the current load rate and the chilled water outlet temperature of the water chilling unit, acquires the theoretical derivative of the power relative to the water supply temperature at the working condition point, that is, the initial main engine thermal gain factor And calculate the algebraic sum of the main engine thermal gain factor and the water supply and distribution loss factor to obtain the system total energy consumption gradient. adjusting the chilled water supply temperature set value according to the sign direction of the system total energy consumption gradient, increasing the chilled water supply temperature set value when the absolute value of the chiller thermal gain factor is greater than the absolute value of the water supply and distribution hydraulic loss factor, and decreasing the chilled water supply temperature set value when the absolute value of the chiller thermal gain factor is less than the absolute value of the water supply and distribution hydraulic loss factor, until the system total energy consumption gradient is within a preset balance deadband range; and, the step of obtaining the chiller thermal gain factor further comprises a correction step based on condenser heat exchange performance attenuation: collecting the saturated temperature corresponding to the condenser pressure of the chiller and the cooling water outlet temperature, calculating the difference between the two to obtain a real-time approach temperature difference; calculating the ratio of the real-time approach temperature difference to a preset reference approach temperature difference to obtain a performance attenuation coefficient; and using the performance attenuation coefficient to reduce the weight of the initial chiller thermal gain factor determined based on the chiller performance curve to obtain the chiller thermal gain factor, to compensate for the deviation in chiller energy efficiency response caused by the increase in condenser surface fouling thermal resistance.

2. The control method of the cold and heat source high-efficiency machine room integrated system based on the system synergy theory according to claim 1, characterized in that, In the step of calculating the water distribution and supply hydraulic loss factor, the following formula is used: wherein, is the water distribution and supply hydraulic loss factor, is the total active power of the water distribution and supply pump, is the total return water temperature of the chilled water, is the set value of the chilled water supply temperature, is the hydraulic characteristic index, and the formula represents the derivative relationship between the water distribution and supply pump power and the supply temperature change under the quasi-steady state of the terminal load.

3. The control method of the cold and heat source high-efficiency machine room integrated system based on the system synergy theory according to claim 2, characterized in that, The hydraulic characteristic index is a dimensionless coefficient representing the exponential relationship between the power of the water supply and distribution pump and the flow rate under the current pipe network resistance characteristics, and its value range is 2.0 to 3.0; the calculation rule calls the hydraulic characteristic index stored in the controller register, and performs one algebraic operation combined with the real-time collected operating parameters to obtain the water supply and distribution hydraulic loss factor.

4. The control method of the cold and heat source high-efficiency machine room integrated system based on the system synergy theory according to claim 1, characterized in that, The correction step specifically includes: when the real-time approach temperature difference is greater than the reference approach temperature difference, the performance attenuation coefficient takes a value less than 1, and the absolute value of the chiller thermal gain factor is reduced using the performance attenuation coefficient, thereby reducing the energy saving benefit weight of the chiller side in the calculation of the system total energy consumption gradient.

5. The control method of the cold and heat source high-efficiency machine room integrated system based on the system synergy theory according to claim 1, characterized in that, The step of adjusting the chilled water supply temperature set value includes a constraint judgment based on the end hydraulic working condition: real-time monitoring the opening value of all two-way regulating valves in the end load and identifying the maximum opening value; judging whether the maximum opening value is greater than a preset hydraulic limit threshold; if the maximum opening value is greater than the hydraulic limit threshold, generating a regulation lock instruction, the regulation lock instruction prohibiting any action that would cause the chilled water supply temperature set value to rise, until the maximum opening value falls below a recovery threshold.

6. The control method of the cold and heat source high-efficiency machine room integrated system based on the system synergy theory according to claim 5, characterized in that, The recovery threshold is less than the hydraulic limit threshold, to form a hysteresis back difference in the control logic to prevent regulation oscillation.

7. The system synergy theory-based control method for a high-efficiency data center integrated system of cold and heat sources according to claim 1, characterized in that, The host thermal gain factor is negative, representing that the power of the water chilling unit decreases with the increase of the supply water temperature; the water distribution loss factor is positive, representing that the power of the water distribution pump increases with the increase of the supply water temperature; the sign of the total system energy consumption gradient indicates the change trend of the total system power relative to the supply water temperature.

8. The control method of the cold and heat source high efficiency machine room integrated system based on system synergy theory according to claim 1, characterized in that, The step of adjusting the chilled water supply temperature set value adopts a variable step adjustment strategy: calculating the absolute value of the total system energy consumption gradient; searching for the corresponding temperature adjustment step in a preset step table according to the absolute value, the step table being configured to output a larger step when the gradient absolute value is larger and output a smaller step when the gradient absolute value is smaller; The temperature adjustment step is used to correct the chilled water supply temperature set value.

9. The control method of the cold and heat source high-efficiency machine room integrated system based on the system synergy theory according to claim 1, characterized in that, The method is run in an industrial programmable logic controller in communication connection with the water chilling unit and the water distribution pump, and the steps of acquisition, calculation and adjustment are completed in a single scanning cycle of the industrial programmable logic controller.

Images