Cold storage temperature optimization control system and method of chilled water storage air conditioning system

Abstract

The invention discloses a cold storage temperature optimization control system and method for a chilled water storage air conditioning system, and relates to the technical field of chilled water storage air conditioning management.The method comprises the steps that 1, a plurality of operation parameters in the system operation process are collected; performing time synchronization and abnormal value elimination on the operation parameters to form a dynamic operation data set; and 2, judging the current hydraulic circulation state based on the dynamic operation data set, and outputting a circulation deviation signal when any index of the total flow of the system, the flow distribution of each branch or the temperature difference change rate of the supplied water and the returned water exceeds a set corresponding threshold value. By constructing the dynamic operation data set and monitoring key parameters such as the system temperature, the flow and the water pump operation state in real time, a unified multi-dimensional data basis is established, support is provided for follow-up operation state recognition and control strategy execution, and the real-time performance and accuracy of control are remarkably improved.

Description

Technical Field

[0001] This invention relates to the field of water-cooled air conditioning management technology, specifically to a water-cooled air conditioning system with optimized cooling temperature control system and method. Background Technology

[0002] In the context of centralized energy consumption in urban buildings, water-based cooling systems are widely used in large public buildings, commercial complexes, and data centers due to their high energy storage capacity and good operating economy. Water-based cooling air conditioning systems achieve the goal of peak shaving and valley filling by storing cooling capacity during off-peak hours and releasing it during peak hours, effectively alleviating grid load pressure and improving the operating efficiency of cooling equipment. The key to this type of system lies in the reasonable control of the cooling storage process and the effective release of cooling capacity.

[0003] Existing water-based cooling control strategies are mostly based on preset cooling temperature targets and time windows, controlling the operating parameters of the cooling source and circulation system under a fixed operating mode. This approach can meet the basic operating requirements of the system in most operating scenarios and improve energy utilization efficiency by rationally planning the cooling storage time and capacity. However, in application environments with drastic dynamic load changes and complex operating conditions, fixed strategies may not be able to adapt to the rapid changes in the actual operating status of the system, thus affecting the overall performance of the system. To further enhance the adaptive capability and hierarchical structure stability of the system, some research and engineering practices have begun to explore data-driven and feedback-optimized cold storage control methods in recent years. These methods attempt to introduce more real-time monitoring parameters, such as water tank temperature profile, flow distribution, and system load prediction, to achieve more flexible control strategies. However, there is still room for further optimization in terms of accurately identifying hydraulic anomalies, maintaining the stability of the water tank's thermal stratification structure, and achieving coordinated control between temperature and flow. Therefore, this invention proposes a cold storage temperature optimization control system and method for a water-based cold air conditioning system. Summary of the Invention

[0004] The purpose of this invention is to provide a system and method for optimizing the storage temperature of a water-cooled air conditioning system, in order to solve the problems mentioned in the background art.

[0005] This invention can be achieved through the following technical solution: a method for optimizing and controlling the cold storage temperature of a water-based cold air conditioning system, comprising the following steps: Step 1: Collect multiple operating parameters during system operation; Operating parameters should include at least the supply and return water temperatures, the operating status of the circulating water pump, the inlet and outlet flow rates of the cold water storage tank, the flow velocity at key nodes, and the valve opening. The runtime parameters are synchronized with time and outliers are removed to form a dynamic runtime dataset; Step 2: Determine the current hydraulic circulation status based on the dynamic operation dataset. When any of the following indicators exceeds the set threshold: total system flow, flow distribution of each branch, or rate of change of supply and return water temperature difference, output the circulation deviation signal. Step 3: After receiving the cycle deviation signal, identify whether there is a low flow velocity stagnation zone and abnormal temperature profile of the cold water tank in the system, identify the flow velocity distribution and temperature profile characteristics based on the dynamic operation data set, and generate a cycle abnormal state signal. Step 4: Based on the building load forecast results, time-of-use electricity price information, and cold storage capacity, calculate the target value of cold storage temperature and the cold storage time window; Step 5: Combine the cyclic abnormal state signal output in Step 3 with the target value of cold storage temperature and the cold storage time window in Step 4, and perform coupled optimization control of temperature and flow rate. Step 6: During the cold storage process, temperature profile data is collected based on multiple temperature sensors installed at different heights in the water tank, and the trend of temperature gradient change is monitored. When the rate of change of temperature gradient or the magnitude of temperature rise exceeds the preset limit, amplitude limiting control is executed.

[0006] A further technical improvement of the present invention lies in: the method for stratifying the water tank in step 6, comprising: A1. Disturbance injection operation: In the initial stage of cold storage operation, by adjusting the operating parameters of the refrigeration unit, a cold disturbance of a limited duration is injected into the cold water tank to stimulate the thermal stratification response process inside the water body. A2. Temperature Response Acquisition and Delay Determination: Based on an array of temperature sensors deployed at different heights in the water tank, the temperature change information of each temperature sensor after the disturbance is injected is collected, and the response delay time of each measuring point from the start of the disturbance to the occurrence of the temperature change is determined. A3. Interface Recognition: The response delay time of adjacent height measuring points is compared. When the difference in response delay between adjacent measuring points exceeds the preset abrupt change threshold, the location is determined as the thermal stratification interface of the water tank to divide the upper and lower water areas. A4. Calculation of Stratified Stability Index: After identifying the thermal stratification interface, the average response delay time of each measuring point in the area above the interface and the area below the interface is calculated respectively. The difference in stratification response delay between the two areas is used as the stability index of the current thermal stratification state, which is used to characterize the stability of the thermal stratification structure inside the water tank. A5. Status Feedback Output: The location of the thermal stratification interface and the stratification stability index are introduced as dynamic stratification state signals into the cold storage temperature optimization control logic. When the stratification stability index is lower than the preset stratification stability threshold, stratification protection control is executed, including adjusting the rate of decrease of cold storage temperature, reducing the intensity of circulating water flow, or correcting the opening of key valves, in order to reduce fluid disturbance and maintain the stability of the stratification structure.

[0007] A further technical improvement of the present invention is that, when calculating the initial target value of cold storage temperature and the cold storage control time window, the system first extracts the cold load operation data of the building in the past preset time window and constructs a cold load time series; The cooling load operation data is based on the actual operating load or cooling output power of the refrigeration equipment, and is compiled hourly in combination with the building space usage schedule and set temperature control parameters. Furthermore, the system combines meteorological forecast information for the future operating cycle to determine the trend of external temperature changes and identifies the peak range of cooling load based on the cooling load sequence; The peak range is compared with the off-peak period in the time-of-use electricity price data, and the overlapping time period is determined as the initial cold storage time window. The system acquires data from multiple temperature sensors deployed at different heights in the cold water tank, calculates the temperature rise rate of the upper layer and the temperature drop rate of the lower layer, and uses the difference between the two as an index of temperature disturbance intensity. When in multiple consecutive sampling periods: The rate of temperature rise in the upper layer exceeds the system's preset temperature rise response threshold; Furthermore, the average temperature of the lower layer is higher than the preset deviation range of the current cold storage target temperature; Therefore, it is determined that the current thermal stratification structure is at risk of disturbance. At this point, the system performs a dynamic correction operation: Limit the upper limit of the rate of decrease of the target value of cold storage temperature; Alternatively, shorten the duration of the current cold storage control window; This is to prevent cold energy from penetrating the interface of the layers and causing mixing, and to maintain the stability of the layered structure and the efficiency of cold storage.

[0008] A further technical improvement of the present invention is that: the system performs time series analysis on the temperature profile data of the cold water tank in multiple operating cycles, calculates the temperature change rate of each temperature sensor during the cold storage operation, and calculates the standard deviation of the temperature change rate at each vertical height position. When the standard deviation of the temperature change rate in a certain height section is greater than the preset multiple difference threshold of the adjacent sections for multiple consecutive operating cycles, the system determines that height section as a disturbance sensitive area. During subsequent cold storage operation, the system monitors the temperature change rate of the temperature sensor in the disturbance sensitive area in real time. If the temperature rise rate in this area exceeds the disturbance judgment threshold for multiple consecutive sampling periods, and its average growth slope meets the preset temperature rise trend threshold, it is judged to be a disturbance approaching state. Based on this, the system performs temperature drop limiting control in advance. The trigger point for advance control is the first complete sampling cycle after the temperature rise trend continues to reach the set slope threshold, and there is a buffer interval of no less than the preset time between the system's normal limiting response and the temperature drop limiting response.

[0009] A further technical improvement of the present invention is that water quality parameters and temperature parameters are collected in the upper and lower regions of the cold water storage tank, respectively, and the water density value of each layer is calculated. Within multiple consecutive sampling periods, the rate of change of water density difference between the upper and lower regions is calculated, and this rate of change of density difference is compared with a preset threshold for stratification stability. When the rate of change of density difference between the upper and lower regions exceeds the stratification stability change threshold for multiple consecutive sampling cycles, and the rate of change of temperature gradient decreases synchronously to below the set temperature stability threshold within the corresponding time period, it is determined that the thermal stratification stability inside the cold water tank is in a decaying trend. Based on the time delay relationship between the rate of change of density difference and the rate of change of temperature gradient, the time advance of the thermal stratification structure disturbance is predicted. When the expected arrival time is reached, feedforward control is actively triggered.

[0010] A further technical improvement of the present invention is: a method for obtaining the advance amount of the disturbance occurrence time, comprising: Within each historical operating cycle, the point in time when the rate of change of density difference first continuously exceeds the threshold of change of stratification stability is identified as the precursor trigger moment of the disturbance signal. Meanwhile, in the subsequent time series of the same operating cycle, the time point at which the rate of change of the temperature gradient first continuously falls below the set temperature stability threshold is determined as the starting moment of the hierarchical structure response. The time interval between the trigger moment of the density difference change rate and the response moment of the temperature gradient change rate in each running cycle is used as the delay time sample for that running cycle. The delay time samples obtained from multiple running cycles are aggregated to construct a delay time sample set; For each sample in the delayed time sample set, calculate the average rate of decrease of the temperature gradient change rate within that period, and use it as the disturbance response intensity parameter corresponding to that delayed sample. Based on the delay time sample set and the corresponding disturbance response intensity parameters, a weighted statistical analysis is performed with the disturbance response intensity as the weight to obtain the weighted average of the delay time or the lower boundary value of the delay time distribution, which can be used as the time advance for predicting the occurrence of thermal stratification disturbances.

[0011] This invention also discloses a cooling temperature optimization control system for a water-based cooling air conditioning system, comprising: The parameter acquisition module is used to collect multiple operating parameters during system operation. The operating parameters include at least the supply and return water temperatures, the operating status of the circulating water pump, the inlet and outlet flow rates of the cold water storage tank, the flow velocity at key nodes, and the valve opening. The collected data is synchronized with the execution time and outliers are removed to form a dynamic operating dataset. The status judgment module determines the current hydraulic circulation status based on the dynamic operation dataset, and outputs a circulation deviation signal when any of the following indicators exceeds the set corresponding threshold: total system flow, flow distribution of each branch, or rate of change of supply and return water temperature difference. The anomaly identification module receives the cyclic deviation signal and, based on the flow velocity distribution and temperature profile characteristics in the dynamic running dataset, identifies whether there is a low flow velocity stagnation zone and an abnormal temperature profile in the cold water tank in the system, and outputs a cyclic anomaly status signal. The control module calculates the target value of the cold storage temperature and the cold storage time window based on the building load forecast results, electricity price time-of-use information and cold storage capacity. The coupled control execution module combines the abnormal state signal of the cycle with the cold storage control parameters to generate control commands and execute coupled optimization regulation of temperature and flow rate. During the cold storage process, the temperature profile monitoring module collects temperature profile data inside the cold water tank and monitors the changing trend of the temperature gradient based on multiple temperature sensors installed at different heights in the cold water tank. The limiting control module is used to perform limiting control when the rate of change of temperature gradient or the magnitude of temperature rise exceeds a preset limit, including but not limited to: limiting the rate of change of the set value of the chiller outlet water temperature, reducing the frequency of the circulating water pump, or limiting the rate of change of the opening degree of key valves.

[0012] Compared with the prior art, the present invention has the following beneficial effects: This invention constructs a dynamic operation dataset to monitor key parameters such as system temperature, flow rate, and pump operating status in real time, establishing a unified multidimensional data foundation. This provides support for subsequent operation status identification and control strategy execution, significantly improving the real-time performance and accuracy of control. Compared with existing technologies, this invention can effectively identify abnormal states such as hydraulic circulation mismatch, uneven cold distribution, or damage to the water tank stratification structure during operation. By constructing an anomaly judgment logic based on flow rate, temperature difference, and temperature gradient, the control system can autonomously identify stagnation zones and stratification instability phenomena, and adjust the target value of cold storage temperature, water pump frequency, and valve opening based on the anomaly signal, thereby achieving dynamic optimization of the cold energy transportation process. On the other hand, by introducing disturbance injection, response delay identification and prediction mechanism based on density difference change trend, this invention establishes a feedforward control model in the cold storage process, which can predict the change trend of stratification stability in advance, actively adjust the temperature drop rate and hydraulic disturbance intensity, effectively protect the thermal stratification structure, and improve cold storage efficiency and system stability. Therefore, the overall system has a high degree of self-adaptation and collaborative control capability, and can adapt to complex building load fluctuations and different operating environment requirements. Attached Figure Description

[0013] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings.

[0014] Figure 1 This is a schematic diagram of the method logic of the present invention. Detailed Implementation

[0015] To further illustrate the technical means and effects of the present invention in achieving its intended purpose, the following detailed description of the specific implementation methods, structures, features, and effects of the present invention, in conjunction with the accompanying drawings and preferred embodiments, is provided.

[0016] Example 1

[0017] Please see Figure 1 As shown, the present invention provides a method for optimizing and controlling the cold storage temperature of a water-based cold air conditioning system, comprising the following steps: Step 1: Collect system operating parameters and build a dynamic operating dataset: During the operation of the water-cooled air conditioning system, the following parameters are collected through distributed sensors: Inlet and outlet flow rates of the cold water storage tank; Supply water temperature and return water temperature; Circulating water pump speed; Flow velocity at key nodes in the pipeline network; Opening degree of each main valve; After time synchronization and outlier removal, the collected parameters constitute the system dynamic operation dataset, which includes the system's temperature, flow rate and hydraulic operation characteristics at different time points. Specifically, during the operation of the water-cooled air conditioning system, multiple parameters of key operating components are collected through distributed monitoring nodes; The sensors include flow meters installed at the inlet and outlet of the cold water storage tank, temperature sensors in the supply and return water pipelines, speed and power detection units on the circulating water pump, flow velocity sensors at key nodes of the pipeline network, and opening feedback devices for each major valve. The sensor continuously collects data at a preset sampling frequency and aggregates the signals to the central data acquisition module via the field controller. The system performs time synchronization processing on the acquired raw data to eliminate data offset caused by sensor clock errors; at the same time, it removes or interpolates outliers and missing points to ensure data continuity and validity. After the above processing, a dynamic system operation dataset is generated, which includes supply and return water temperatures, flow distribution, pump speed, and valve status.

[0018] This dynamic operating dataset reflects the temperature field and hydraulic operating characteristics of the system at various times, providing a unified data foundation for subsequent cycle state identification and control optimization.

[0019] Step 2: Perform hydraulic circulation validity identification on the dynamically running dataset: The following calculations are performed on the system dynamic operation dataset obtained in step 1: a1. Deviation rate between total system flow and design flow; a2. The ratio of actual flow rate to design flow rate for each branch; a3. The rate of change of the supply and return water temperature difference ΔT within the set time window; When any one of the indicators a1, a2 or a3 exceeds the preset corresponding threshold, it is determined to be a hydraulic circulation mismatch state, and a corresponding circulation deviation signal is generated. Specifically, the dynamic operation dataset formed in step 1 is used to quantitatively calculate the hydraulic state of the system as a whole and its branches; First, the rated flow rate of the system and the design flow rate of each branch are obtained according to the design operating parameters. The measured flow rate in the current sampling period is compared with the design value, and the total flow deviation rate of the system and the flow ratio of each branch are calculated. Secondly, the time change rate of temperature difference ΔT is calculated using the supply and return water temperature data to reflect the dynamic trend of cold energy transfer efficiency. When any of the above indicators deviates from the design value by more than the preset corresponding threshold, the control system determines that there is a hydraulic circulation mismatch. The judgment result is then synthesized logically to generate a cyclic deviation signal; The cyclic deviation signal carries the flow deviation type and location label, providing triggering conditions for subsequent stagnation zone location and stratified damage identification, realizing the conversion from measurement data to hydraulic diagnostic information.

[0020] Step 3: Identify the stagnation zone and delamination failure state based on the cyclic deviation signal from Step 2: When the system detects a cyclic deviation signal, it extracts the flow velocity distribution and cold water tank temperature distribution data of each pipeline node from the system dynamic operation dataset in step 1, and performs the following identification: If the local flow velocity is lower than the design lower limit and the corresponding return water temperature rises in advance, the area is determined to be a low flow velocity stagnation zone. If the temperature gradient between the upper, middle, and lower layers of the water tank decreases or reverses, it is determined to be a state of stratification failure. The identification results are output as a cyclic abnormal state signal for subsequent control use; Specifically, when the system receives the cyclic deviation signal output in step 2, it extracts the flow velocity distribution and cold water tank temperature profile information for the corresponding time period from the dynamic operation dataset. The control algorithm first analyzes the flow velocity change trend of each node in the pipeline network. If it is detected that the flow velocity in a certain area is lower than the design lower limit for a long time and the corresponding return water temperature rises earlier than other branches, it is determined that there is a low flow velocity stagnation phenomenon in that area. The system then calculates the rate of change of temperature gradient in the upper, middle and lower layers of the cold water tank. If the temperature distribution shows a weakening or reverse change in gradient, i.e. the upper layer temperature decreases while the lower layer temperature increases, it is determined that the stratified structure of the water tank is destroyed, i.e. there is an abnormal temperature profile of the cold water tank. The above analysis process is executed in real time in the controller and generates a cyclical abnormal state signal containing the abnormality type, location, and severity. This abnormal state signal serves as the input for subsequent temperature-flow coupling control, ensuring that the control strategy can specifically address issues such as uneven flow or stratification instability.

[0021] Step 4: Calculate the initial target cold storage temperature and time window based on the load forecast results: Based on the building's cooling load forecast, time-of-use electricity price data, and system cold storage capacity parameters, the initial target value for cold storage temperature and the cold storage control time window are calculated. The initial target value of cold storage temperature and the time window are used as input parameters for temperature-flow coupling optimization; When calculating the initial target value of cold storage temperature and the cold storage control time window, the system first extracts the cold load operation data of the building in the past preset time window and constructs a cold load time series. The cooling load operation data is based on the actual operating load or cooling output power of the refrigeration equipment, and is compiled hourly in combination with the building space usage schedule and set temperature control parameters. Furthermore, the system combines meteorological forecast information for the future operating cycle to determine the trend of external temperature changes and identifies the peak range of cooling load based on the cooling load sequence; The peak range is compared with the off-peak period in the time-of-use electricity price data, and the overlapping time period is determined as the initial cold storage time window. At the same time, the system calculates the available cold storage energy margin based on the rated cold storage capacity parameters of the cold water tank and the current average temperature of the tank. Under energy balance constraints, determine the target outlet water temperature to be achieved within the initial cold storage time window; Specifically, the energy balance constraint refers to the process of determining the target value of the cold storage temperature and the cold storage time window. The system analyzes the energy matching relationship between the storable cold capacity and the expected cooling load demand to ensure that the calculation results do not exceed the system's cold storage capacity or fall below the building's cooling load demand, thereby achieving coordinated control of cold storage efficiency and operational economy.

[0022] If the calculated target outlet water temperature is lower than the minimum operating temperature limit allowed by the system, the upper limit of the cold storage control time window is adjusted to prevent overcharging of cold storage capacity from causing energy waste or stratification damage. The system acquires data from multiple temperature sensors deployed at different heights in the cold water tank, calculates the temperature rise rate of the upper layer and the temperature drop rate of the lower layer, and uses the difference between the two as an index of temperature disturbance intensity. When in multiple consecutive sampling periods: The rate of temperature rise in the upper layer exceeds the system's preset temperature rise response threshold; Furthermore, the average temperature of the lower layer is higher than the preset deviation range of the current cold storage target temperature; Therefore, it is determined that the current thermal stratification structure is at risk of disturbance. At this point, the system performs a dynamic correction operation: Limit the upper limit of the rate of decrease of the target value of cold storage temperature; Alternatively, shorten the duration of the current cold storage control window; This is to prevent cold energy from penetrating the interface of the layers and causing mixing, and to maintain the stability of the layered structure and the efficiency of cold storage.

[0023] Specifically, the system first extracts the cooling load operation data recorded in the building within a preset time window (such as seven days). The cooling load operation data is based on the hourly cooling output power curve generated from the operation records of the refrigeration unit, terminal equipment, etc. Combined with the building space usage plan and the set indoor temperature control target, the hourly cooling load is sorted and collected to form cooling load time series data. Subsequently, the system acquires hourly meteorological forecast data for the future operating cycle, especially the trend of changes in outside air temperature; by statistically analyzing the hourly rate of change of outside air temperature and superimposing and analyzing the time series change curve of cooling load, the system identifies the location and duration of future high load increase segments and relatively stable segments. The system further calls the time-of-use electricity price data that has been set in the electricity billing system to obtain the start and end time periods of the off-peak electricity price, and compares the off-peak electricity price period with the identified peak cooling load period in time, and selects the overlapping time range of the two as the initial cold storage control time window. The principle for setting the initial cooling storage time window is to complete the main cooling storage operation within the overlapping period when the electricity price is the lowest and the cooling load is about to rise rapidly, so as to achieve a balance between economy and security. After obtaining the initial cold storage time window, the system calls the detection data of multiple temperature sensors at different heights in the cold water tank in real time to calculate the temperature change rate of the upper and lower layers of water in the tank respectively. Specifically, it continuously acquires the rate of temperature rise of the upper layer of water and the rate of temperature fall of the lower layer of water, and further calculates the rate difference to reflect the stability trend of the thermal stratification structure inside the tank. When the system detects that the rate of temperature rise of the upper water exceeds the preset disturbance threshold and the temperature of the lower water has not yet reached the set target temperature for cold storage, it determines that there is a risk of disturbance penetrating the stratification interface, which may damage the thermal stratification structure of the water tank. Based on this judgment, the system dynamically adjusts the original target value of cold storage temperature and the cold storage control time window, including: appropriately reducing the upper limit of the target temperature drop to delay the upward penetration of cold energy driven by temperature difference, or shortening the current cold storage time window to reduce the total disturbance time of the system. This adjustment mechanism implements a closed-loop control strategy for temperature target based on the stratification state of the water tank, effectively preventing the collapse of the stratification structure and the decrease in cold storage efficiency caused by excessive cold storage or excessive disturbance. Conversely, when the system monitors that the temperature gradient between the upper and lower layers of the water tank remains stable over multiple consecutive sampling periods, and the rate of change of the upper water temperature is lower than the disturbance threshold, it indicates that the stratified structure is stable. The system then maintains the original temperature drop plan and the length of the cold storage time window unchanged. Through this dynamic strategy based on the combined correction of the external heat load change trend and the internal thermal stratification state of the water tank, the system can achieve adaptive and coordinated control of temperature, flow rate, and structure, thereby improving the overall cold storage efficiency and energy utilization rate.

[0024] Step 5: Perform temperature-flow coupling optimization control based on the cyclic abnormal state signal from Step 3. Based on the initial target value of cold storage temperature in step 4 and the abnormal state signal in step 3, the following optimization logic is executed: When the change in b1 is continuously lower than the set decrease threshold, and at the same time, a region in the circulation system with a flow rate lower than the design flow rate lower limit is detected, it is determined to be a circulation stagnation state; at this time: Increase the target value of the cold storage temperature so that the outlet water temperature of the chiller unit can be maintained within the range required for stable circulation; Extend the current cold storage time window to compensate for localized delays in cold transfer; b2. When the system determines that the actual flow rate of each main branch or main pipeline deviates from the design flow rate by more than the set allowable deviation threshold, it is judged as a state of uneven hydraulic distribution; at this time: Adjust the operating frequency of the circulating water pump to bring the total system flow rate back to the design matching range; The opening degree of key valves is adjusted in a coordinated manner to restore the balance of flow distribution among the main branches; b3. When the rate of change of the temperature gradient between the upper and lower layers in the temperature profile of the cold water tank is continuously lower than the set stability threshold, or when a reverse temperature rise trend occurs, it is determined to be a state of reduced stratification stability; at this time: Limit the cold storage rate by adjusting the outlet water temperature or heat exchange power of the chiller unit to control the temperature drop. Simultaneously reduce the operating frequency of the circulating water pump to weaken internal fluid disturbance and maintain the stability of the stratified structure; Specifically, after receiving the cyclic abnormal state signal from step 3 and the initial cold storage parameters calculated in step 4, the control system executes the coupled optimization logic of temperature and flow rate. If the temperature difference between the supply and return water is detected to be consistently lower than the threshold and there is a region where the flow rate is lower than the design limit, it is determined to be a stagnant state. At this time, the target value of the cold storage temperature is increased and the cold storage time window is extended to match the cooling load with the fluid renewal rate. If the flow rate of the main branch or main pipe of the system deviates from the design range, indicating uneven hydraulic distribution, the operating frequency of the circulating water pump and the opening of key valves should be adjusted to restore the total flow rate and distribution ratio to the design balance. If the temperature gradient of the water tank decreases or a reverse temperature rise trend occurs, it indicates that the stratification stability has decreased. The system suppresses disturbances by limiting the cold storage rate, adjusting the outlet water temperature of the chiller unit, and reducing the operating frequency of the water pump. The optimized parameters form a temperature-flow coupled control instruction set, which is sent to the actuator in real time to achieve dynamic adaptive control.

[0025] Step 6: Control of cold storage amplitude based on dynamic correction of water tank temperature profile: During the cold storage process, the system uses multiple temperature sensors deployed at different heights in the cold water tank to collect the temperature of the upper, middle and lower layers of the tank in real time and generate temperature profile data of the tank. The system performs time series analysis on the temperature profile data of the cold water tank in multiple operating cycles, calculates the temperature change rate of each temperature sensor during cold storage operation, and calculates the standard deviation of the temperature change rate at each vertical height position. When the standard deviation of the temperature change rate in a certain height section is greater than the preset multiple difference threshold of the adjacent sections for multiple consecutive operating cycles, the system determines that height section as a disturbance sensitive area. During subsequent cold storage operation, the system monitors the temperature change rate of the temperature sensor in the disturbance sensitive area in real time. If the temperature rise rate in this area exceeds the disturbance judgment threshold for multiple consecutive sampling periods, and its average growth slope meets the preset temperature rise trend threshold, it is judged to be a disturbance approaching state. Based on this, the system performs temperature drop limiting control in advance. The trigger point for advance control is the first complete sampling cycle after the temperature rise trend continues to reach the set slope threshold, and there is a buffer interval of no less than the preset time between the system's normal limiting response and the temperature drop limiting response.

[0026] In this embodiment, the system first calls the historical temperature profile data of the cold water tank in multiple operating cycles, extracts the cycle-by-cycle temperature change rate of each temperature sensor during the cold storage period, and performs standard deviation calculation on the multiple cycle temperature change rates at the same vertical height position to obtain the temperature fluctuation intensity index of that height segment. The system then uses the sensor deployment height as a benchmark to compare the standard deviation of the temperature change rate of any height segment with the standard deviation of its adjacent segments above and below. When it is detected that the standard deviation of the temperature change rate of that height segment continuously exceeds the preset multiple threshold of the average standard deviation of the upper and lower segments in multiple independent operating cycles (this multiple threshold is set by the system and is used to measure the relative fluctuation amplitude), the system identifies that height segment as a disturbance sensitive area and records its vertical position interval and the corresponding sensor number. In actual operation, the system collects temperature change data in the disturbance-sensitive area in real time and calculates the average temperature rise rate and slope in continuous sampling period. When the temperature rise rate of the region exceeds the preset disturbance judgment threshold in multiple consecutive sampling periods, and the average slope meets the temperature rise trend threshold condition, the system determines that there is a trend state approaching disturbance. The system sets the advance triggering logic for temperature drop limiting control: if the above trend judgment conditions are met, the system triggers the feedforward limiting control operation at the end of the first complete sampling period, and there is a buffer interval of no less than one control sampling period between the triggering time and the response time point based on the traditional gradient change judgment. Temperature drop limiting control includes, but is not limited to: limiting the maximum rate of drop in the chiller unit outlet water temperature setpoint to prevent cold energy from penetrating the stratification interface too quickly; reducing the operating frequency of the circulating water pump to slow down the cold water injection rate; or adjusting the opening rate of key valves to limit the intensity of local flow field disturbance. The above control actions can be executed individually or in combination, and the specific execution strategy is dynamically adjusted according to the system operating status and control priority.

[0027] The control system calculates the rate of change of the temperature profile gradient, and when it detects: If the rate of temperature rise at the top exceeds a preset threshold, or if the temperature rise in the middle or lower layers exceeds a set limit, the risk of water tank stratification failure is determined to be increased, and the following control operations will be executed immediately: To limit the rate of temperature drop during the cold storage process, the cooling rate is kept below the set limit by adjusting the outlet water temperature setpoint of the chiller unit. Reduce the frequency of the circulating water pump, weaken fluid disturbance, and stabilize the stratified interface; Once the temperature profile is detected to have returned to a normal gradient, the system automatically removes the limiting and resumes the original cold storage control mode.

[0028] Example 2

[0029] A method for optimizing and controlling the cold storage temperature of a water-based cold air conditioning system includes the following steps: Step 1: Collect system operating parameters and build a dynamic operating dataset: During the operation of the water-cooled air conditioning system, the following parameters are collected through distributed sensors: Inlet and outlet flow rates of the cold water storage tank; Supply water temperature and return water temperature; Circulating water pump speed; Flow velocity at key nodes in the pipeline network; Opening degree of each main valve; After time synchronization and outlier removal, the collected parameters constitute the system dynamic operation dataset, which includes the system's temperature, flow rate and hydraulic operation characteristics at different time points. Step 2: Perform hydraulic circulation validity identification on the dynamically running dataset: The following calculations are performed on the system dynamic operation dataset obtained in step 1: a1. Deviation rate between total system flow and design flow; a2. The ratio of actual flow rate to design flow rate for each branch; a3. The rate of change of the supply and return water temperature difference ΔT within the set time window; When any one of the indicators a1, a2 or a3 exceeds the preset corresponding threshold, it is determined to be a hydraulic circulation mismatch state, and a corresponding circulation deviation signal is generated. Step 3: Identify the stagnation zone and delamination failure state based on the cyclic deviation signal from Step 2: When the system detects a cyclic deviation signal, it extracts the flow velocity distribution and cold water tank temperature distribution data of each pipeline node from the system dynamic operation dataset in step 1, and performs the following identification: If the local flow velocity is lower than the design lower limit and the corresponding return water temperature rises in advance, the area is determined to be a low flow velocity stagnation zone. If the temperature gradient between the upper, middle, and lower layers of the water tank decreases or reverses, it is determined to be a state of stratification failure. The identification results are output as a cyclic abnormal state signal for subsequent control use; Step 4: Calculate the initial target cold storage temperature and time window based on the load forecast results: Based on the building's cooling load forecast, time-of-use electricity price data, and system cold storage capacity parameters, the initial target value for cold storage temperature and the cold storage control time window are calculated. The initial target value of cold storage temperature and the time window are used as input parameters for temperature-flow coupling optimization; Step 5: Perform temperature-flow coupling optimization control based on the cyclic abnormal state signal from Step 3. Based on the initial target value of cold storage temperature in step 4 and the abnormal state signal in step 3, the following optimization logic is executed: When the change in b1 is continuously lower than the set decrease threshold, and at the same time, a region in the circulation system with a flow rate lower than the design flow rate lower limit is detected, it is determined to be a circulation stagnation state; at this time: Increase the target value of the cold storage temperature so that the outlet water temperature of the chiller unit can be maintained within the range required for stable circulation; Extend the current cold storage time window to compensate for localized delays in cold transfer; b2. When the system determines that the actual flow rate of each main branch or main pipeline deviates from the design flow rate by more than the set allowable deviation threshold, it is judged as a state of uneven hydraulic distribution; at this time: Adjust the operating frequency of the circulating water pump to bring the total system flow rate back to the design matching range; The opening degree of key valves is adjusted in a coordinated manner to restore the balance of flow distribution among the main branches; b3. When the rate of change of the temperature gradient between the upper and lower layers in the temperature profile of the cold water tank is continuously lower than the set stability threshold, or when a reverse temperature rise trend occurs, it is determined to be a state of reduced stratification stability; at this time: Limit the cold storage rate by adjusting the outlet water temperature or heat exchange power of the chiller unit to control the temperature drop. Simultaneously reduce the operating frequency of the circulating water pump to weaken internal fluid disturbance and maintain the stability of the stratified structure; Step 6: Control of cold storage amplitude based on dynamic correction of water tank temperature profile: During the cold storage process, the system uses multiple temperature sensors deployed at different heights in the cold water tank to collect the temperature of the upper, middle and lower layers of the tank in real time and generate temperature profile data of the tank. Compared to Example 1, the method for stratifying the water tank in step 6 of Example 2 includes: A1. Disturbance injection operation: In the initial stage of starting the cold storage mode of the water-cooled air conditioning system, a short-cycle cold disturbance is injected into the bottom of the cold water tank within a set time range by adjusting the set value of the outlet water temperature of the chiller unit, in order to stimulate the thermal stratification response of the water body. Specifically, in the initial stage of cold storage operation of the water-cooled air conditioning system, the system adjusts the set value of the outlet water temperature of the chiller unit to make it drop briefly within a set disturbance period (e.g., 0.5 to 2 minutes), thereby injecting a distinctive cold disturbance into the bottom of the water tank. The disturbance process is achieved by controlling the opening of the outlet valve and the cooling power of the chilled water side heat exchanger or the chiller unit itself, ensuring that the disturbance can effectively act on the lower water body in a short time, while not significantly interfering with the original operating state of the system. The goal of this perturbation operation is to stimulate the temperature response behavior at different height levels inside the water tank, thereby providing input conditions for subsequent stratification.

[0030] A2. Temperature Response Acquisition and Delay Determination: The system is based on multiple temperature sensors deployed at different vertical heights in the water tank, and continuously collects the moment when the temperature of each sensor first changes after the disturbance is injected; The time elapsed from the start of the disturbance to the detection of the temperature change at each measuring point is defined as the disturbance response delay time of that measuring point. Specifically, after the cold energy disturbance injection is completed, the system uses multiple temperature sensors that have been deployed at different vertical heights in the cold water tank to continuously collect the time when each measuring point first shows a significant temperature change after the disturbance occurs. The system records the time interval between the start of the disturbance and the detection of the cold disturbance effect (i.e., a significant temperature change) at each measuring point, and defines this time interval as the "disturbance response delay time" of that measuring point. To improve the accuracy of data acquisition, the system sets a minimum identification threshold for the rate of temperature change to avoid misjudging small fluctuations or changes in the system background as disturbance responses. The response delay time data of all measuring points are uniformly stored in the central controller for subsequent hierarchical structure analysis.

[0031] A3. Interface Recognition: The system calculates the time difference of disturbance response delay between adjacent temperature sensors one by one; When the response time difference between any group of adjacent sensors is greater than the system's preset abrupt change judgment threshold, the system will take the abrupt change location as the stratification boundary point inside the water tank and identify it as the boundary between the upper and lower thermal strata. Specifically, after obtaining the disturbance response delay time of each temperature sensor, the system compares the delay time differences between all adjacent sensors one by one and calculates the difference. If the difference in response delay time between any pair of adjacent measuring points exceeds the system's set abrupt change identification threshold (this threshold is determined based on the system's historical operating conditions or actual test debugging), then the location is determined to be a sudden change area in the conduction of cold energy inside the water tank. Based on this, the system uses the mutation point as the thermal stratification interface of the water tank, and labels its upper and lower parts as the "upper water layer" and the "lower water layer," respectively.

[0032] A4. Calculation of Stratified Stability Index: After identifying the layer boundary location, the system calculates the disturbance response delay time of all temperature sensors in the area above and below the interface, and calculates the average response time of the upper and lower layers. Subtracting the average response time of the upper layer from the average response time of the lower layer yields the "layer response delay difference," which serves as a stability indicator for the current thermal stratification state. The larger the difference in response delay between the layers, the stronger the obstruction of the conduction of cold energy in the lower layer, and the more stable the layered structure. If the difference in the layer response delay gradually approaches zero, it indicates that the disturbance rapidly penetrates the layer boundary, and the thermal layer structure tends to be destroyed. Specifically, after the interface recognition is completed, the system calculates the disturbance response delay time of all temperature sensors in each area based on the identified upper and lower partitions, and calculates the average response time of each area. Subsequently, the average response time of the upper layer is subtracted from the average response time of the lower layer to obtain the "layered response delay difference" index. The difference reflects the degree of conduction restriction during the upward propagation of cold energy disturbance, and thus indirectly characterizes the integrity of the thermal stratification structure in the water tank; When the delay difference is large, it indicates that the cooling capacity is concentrated in the lower layer, the upper layer responds slowly, and the layered structure is clear and stable. When the difference approaches zero, it indicates that the disturbance is rapidly penetrating the layer boundary, thermal convection is enhanced, the original stratification tends to become disordered, and corresponding operational intervention is required.

[0033] A5. Status Feedback Output: The location of the thermal stratification interface and the stratification stability index are introduced as dynamic stratification state signals into the cold storage temperature optimization control logic. When the stratification stability index is lower than the preset stratification stability threshold, stratification protection control is executed, including adjusting the rate of decrease of cold storage temperature, reducing the intensity of circulating water flow, or correcting the opening of key valves, in order to reduce fluid disturbance and maintain the stability of the stratification structure.

[0034] The identified location of the water tank thermal layer boundary and the corresponding "layer response delay difference" are used as dynamic layer status signals and output to the cold storage temperature optimization control logic. If the difference in response delay between the layers is greater than the set stability threshold, it indicates that the propagation of cold energy disturbance between the upper and lower layers is limited, and the layered structure is still in a stable state. At this time, the system can maintain the currently set rate of decrease in cold storage temperature and the intensity of circulating water flow. When the difference in the stratified response delay decreases and reaches the preset disturbance penetration threshold (i.e., the criterion for a significant decrease in the stratified structure response capability), the system immediately triggers the stratified protection control strategy, including: reducing the rate of decrease in the outlet water temperature of the chiller unit, reducing the operating frequency of the circulating water pump, or adjusting the opening settings of key valves in conjunction with the system, in order to reduce the disturbance intensity and delay heat mixing, thereby maintaining the thermal stratification structure inside the water tank and improving the cold storage efficiency and energy storage effect.

[0035] Example 3 A method for optimizing and controlling the cold storage temperature of a water-based cold air conditioning system includes the following steps: Step 1: Collect system operating parameters and build a dynamic operating dataset: During the operation of the water-cooled air conditioning system, the following parameters are collected through distributed sensors: Inlet and outlet flow rates of the cold water storage tank; Supply water temperature and return water temperature; Circulating water pump speed; Flow velocity at key nodes in the pipeline network; Opening degree of each main valve; After time synchronization and outlier removal, the collected parameters constitute the system dynamic operation dataset, which includes the system's temperature, flow rate and hydraulic operation characteristics at different time points. Step 2: Perform hydraulic circulation validity identification on the dynamically running dataset: The following calculations are performed on the system dynamic operation dataset obtained in step 1: a1. Deviation rate between total system flow and design flow; a2. The ratio of actual flow rate to design flow rate for each branch; a3. The rate of change of the supply and return water temperature difference ΔT within the set time window; When any one of the indicators a1, a2 or a3 exceeds the preset corresponding threshold, it is determined to be a hydraulic circulation mismatch state, and a corresponding circulation deviation signal is generated. Step 3: Identify the stagnation zone and delamination failure state based on the cyclic deviation signal from Step 2: When the system detects a cyclic deviation signal, it extracts the flow velocity distribution and cold water tank temperature distribution data of each pipeline node from the system dynamic operation dataset in step 1, and performs the following identification: If the local flow velocity is lower than the design lower limit and the corresponding return water temperature rises in advance, the area is determined to be a low flow velocity stagnation zone. If the temperature gradient between the upper, middle, and lower layers of the water tank decreases or reverses, it is determined to be a state of stratification failure. The identification results are output as a cyclic abnormal state signal for subsequent control use; Step 4: Calculate the initial target cold storage temperature and time window based on the load forecast results: Based on the building's cooling load forecast, time-of-use electricity price data, and system cold storage capacity parameters, the initial target value for cold storage temperature and the cold storage control time window are calculated. The initial target value of cold storage temperature and the time window are used as input parameters for temperature-flow coupling optimization; Step 5: Perform temperature-flow coupling optimization control based on the cyclic abnormal state signal from Step 3. Based on the initial target value of cold storage temperature in step 4 and the abnormal state signal in step 3, the following optimization logic is executed: When the change in b1 is continuously lower than the set decrease threshold, and at the same time, a region in the circulation system with a flow rate lower than the design flow rate lower limit is detected, it is determined to be a circulation stagnation state; at this time: Increase the target value of the cold storage temperature so that the outlet water temperature of the chiller unit can be maintained within the range required for stable circulation; Extend the current cold storage time window to compensate for localized delays in cold transfer; b2. When the system determines that the actual flow rate of each main branch or main pipeline deviates from the design flow rate by more than the set allowable deviation threshold, it is judged as a state of uneven hydraulic distribution; at this time: Adjust the operating frequency of the circulating water pump to bring the total system flow rate back to the design matching range; The opening degree of key valves is adjusted in a coordinated manner to restore the balance of flow distribution among the main branches; b3. When the rate of change of the temperature gradient between the upper and lower layers in the temperature profile of the cold water tank is continuously lower than the set stability threshold, or when a reverse temperature rise trend occurs, it is determined to be a state of reduced stratification stability; at this time: Limit the cold storage rate by adjusting the outlet water temperature or heat exchange power of the chiller unit to control the temperature drop. Simultaneously reduce the operating frequency of the circulating water pump to weaken internal fluid disturbance and maintain the stability of the stratified structure; Step 6: Control of cold storage amplitude based on dynamic correction of water tank temperature profile: During the cold storage process, the system uses multiple temperature sensors deployed at different heights in the cold water tank to collect the temperature of the upper, middle and lower layers of the tank in real time and generate temperature profile data of the tank. Compared to Embodiment 1 and Embodiment 2, Embodiment 3 defines the water storage space area on the side where the chilled water outlet pipe interface is located as the upper area of ​​the cold water storage tank, and defines the water storage space area on the side where the chilled water return pipe interface is located as the lower area of ​​the cold water storage tank. In the two spatial areas with different fluid inlet / outlet functions, water quality and temperature acquisition devices are deployed to obtain water quality and temperature parameters for each area. Water quality and temperature parameters were collected in the upper and lower areas of the cold water tank, and the water density values ​​of each layer were calculated. Within multiple consecutive sampling periods, the rate of change of water density difference between the upper and lower regions is calculated, and this rate of change of density difference is compared with a preset threshold for stratification stability. When the rate of change of density difference between the upper and lower regions exceeds the stratification stability change threshold for multiple consecutive sampling cycles, and the rate of change of temperature gradient decreases synchronously to below the set temperature stability threshold within the corresponding time period, it is determined that the thermal stratification stability inside the cold water tank is in a decaying trend. Based on the time delay relationship between the rate of change of density difference and the rate of change of temperature gradient, the time advance of the thermal stratification structure disturbance is predicted. When the expected arrival time is reached, feedforward control is actively triggered.

[0036] Specifically, the system collects water quality parameters and temperature parameters in the upper and lower areas of the cold water storage tank, respectively. The water quality parameters include at least conductivity or total dissolved solids concentration. The system obtains water quality values ​​of each layer of water by using multiple water quality sensors set at different heights, and records temperature parameters simultaneously, and calculates the water density value at the corresponding sampling time. The system calculates the rate of change of the density difference between the upper and lower layers in a continuous sampling period and compares the rate of change of the density difference with a preset layer stability change threshold. When the rate of decrease of the density difference exceeds the stability change threshold for multiple consecutive periods and the rate of change of the temperature gradient decreases synchronously to below the set stability threshold in the corresponding time period, it is determined that the layer stability inside the water tank is in a decaying trend. Furthermore, based on the historical correspondence between the rate of change of density difference and the rate of change of temperature gradient, the system statistically analyzes the average time interval between the advance of density difference change and the decay of temperature gradient in historical operating data to determine the predicted lead amount of hierarchical structure disturbance. Lead time is the time window during which the system uses feedforward control response.

[0037] When the predicted lead time arrives, the system actively triggers feedforward control. Feedforward control includes limiting the rate of decrease of the chiller outlet water temperature setpoint, reducing the operating frequency of the circulating water pump, or limiting the rate of change of the opening of key valves, in order to reduce the intensity of water density disturbance caused by rapid penetration of local cold energy, suppress the risk of damage to the thermal stratification interface, and maintain the stability of cold storage efficiency and stratification structure.

[0038] Methods for obtaining the advance of disturbance occurrence include: Within each historical operating cycle, the point in time when the rate of change of density difference first continuously exceeds the threshold of change of stratification stability is identified as the precursor trigger moment of the disturbance signal. Meanwhile, in the subsequent time series of the same operating cycle, the time point at which the rate of change of the temperature gradient first continuously falls below the set temperature stability threshold is determined as the starting moment of the hierarchical structure response. The time interval between the trigger moment of the density difference change rate and the response moment of the temperature gradient change rate in each running cycle is used as the delay time sample for that running cycle. The delay time samples obtained from multiple running cycles are aggregated to construct a delay time sample set; For each sample in the delayed time sample set, calculate the average rate of decrease of the temperature gradient change rate within that period, and use it as the disturbance response intensity parameter corresponding to that delayed sample. Based on the delay time sample set and the corresponding disturbance response intensity parameters, a weighted statistical analysis is performed with the disturbance response intensity as the weight to obtain the weighted average of the delay time, which is used as the time advance for predicting the occurrence of thermal stratification disturbance.

[0039] Specifically, the system first extracts the continuous decreasing segment of the temperature gradient change rate in the disturbance response phase of the operating cycle corresponding to each delay time sample. Based on the temperature change data of this segment, the system calculates the average decreasing rate of the temperature gradient, which reflects the response strength of the hierarchical structure to the disturbance in this cycle. The system uses this as the weight value corresponding to the delay time sample.

[0040] Subsequently, the system iterates through all delay time samples and their corresponding weight values, and calculates the thermal stratification disturbance time advance using the following weighted average method: Each delayed time sample is assigned a weight, the weight value of which is equal to its corresponding temperature gradient descent rate; Multiply each delay time sample by its corresponding weight value to obtain the weighted time value; Sum all the weighted time values ​​to get the weighted time sum; Add all the weight values ​​together to get the total weight. Divide the weighted sum of times by the weighted sum of weights to obtain the final weighted average delay time.

[0041] The weighted average delay time is the time advance by which the system predicts the occurrence of thermal stratification disturbance. It is used to set the response time point for temperature drop limiting control after the density difference change rate is detected to meet the disturbance triggering condition.

[0042] On the other hand, a cold storage temperature optimization control system for a water-based cold storage air conditioning system in Examples 1, 2, and 3 includes: The parameter acquisition module is used to collect multiple operating parameters during system operation. The operating parameters include at least the supply and return water temperatures, the operating status of the circulating water pump, the inlet and outlet flow rates of the cold water storage tank, the flow velocity at key nodes, and the valve opening. The collected data is synchronized with the execution time and outliers are removed to form a dynamic operating dataset. The status judgment module determines the current hydraulic circulation status based on the dynamic operation dataset, and outputs a circulation deviation signal when any of the following indicators exceeds the set corresponding threshold: total system flow, flow distribution of each branch, or rate of change of supply and return water temperature difference. The anomaly identification module receives the cyclic deviation signal and, based on the flow velocity distribution and temperature profile characteristics in the dynamic running dataset, identifies whether there is a low flow velocity stagnation zone and an abnormal temperature profile in the cold water tank in the system, and outputs a cyclic anomaly status signal. The control module calculates the target value of the cold storage temperature and the cold storage time window based on the building load forecast results, electricity price time-of-use information and cold storage capacity. The coupled control execution module combines the abnormal state signal of the cycle with the cold storage control parameters to generate control commands and execute coupled optimization regulation of temperature and flow rate. During the cold storage process, the temperature profile monitoring module collects temperature profile data inside the cold water tank and monitors the changing trend of the temperature gradient based on multiple temperature sensors installed at different heights in the cold water tank. The limiting control module is used to perform limiting control when the rate of change of temperature gradient or the magnitude of temperature rise exceeds a preset limit, including but not limited to: limiting the rate of change of the set value of the chiller outlet water temperature, reducing the frequency of the circulating water pump, or limiting the rate of change of the opening degree of key valves.

[0043] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters and thresholds in the formulas are set by those skilled in the art according to the actual situation.

[0044] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A method for optimizing and controlling the cold storage temperature of a water-based cold storage air conditioning system, characterized in that, include: Step 1: Collect multiple operating parameters during system operation; Operating parameters should include at least the supply and return water temperatures, the operating status of the circulating water pump, the inlet and outlet flow rates of the cold water storage tank, the flow velocity at key nodes, and the valve opening. The runtime parameters are synchronized with time and outliers are removed to form a dynamic runtime dataset; Step 2: Determine the current hydraulic circulation status based on the dynamic operation dataset. When any of the following indicators exceeds the set threshold: total system flow, flow distribution of each branch, or rate of change of supply and return water temperature difference, output the circulation deviation signal. Step 3: After receiving the cycle deviation signal, identify whether there is a low flow velocity stagnation zone and abnormal temperature profile of the cold water tank in the system, identify the flow velocity distribution and temperature profile characteristics based on the dynamic operation data set, and generate a cycle abnormal state signal. Step 4: Based on the building load forecast results, time-of-use electricity price information, and cold storage capacity, calculate the target value of cold storage temperature and the cold storage time window; Step 5: Combine the cyclic abnormal state signal output in Step 3 with the target value of cold storage temperature and the cold storage time window in Step 4, and perform coupled optimization control of temperature and flow rate. Step 6: During the cold storage process, temperature profile data is collected based on multiple temperature sensors installed at different heights in the water tank, and the trend of temperature gradient change is monitored. When the rate of change of temperature gradient or the magnitude of temperature rise exceeds the preset limit, amplitude limiting control is executed.

2. The method for optimizing and controlling the cold storage temperature of a water-based cold storage air conditioning system according to claim 1, characterized in that, In step 5, the coupling optimization control includes: When insufficient hydraulic circulation and limited cold energy transfer are detected, adjust the target value of cold storage temperature and extend the cold storage control time window. When a deviation from the design state in hydraulic distribution is detected, the operating frequency of the circulating water pump and the opening of key valves are adjusted to restore flow balance. When a decrease in the stratification stability of the water tank temperature profile is identified, the cold storage rate is limited and the water pump operating frequency is reduced to mitigate system disturbances.

3. A method for optimizing and controlling the cold storage temperature of a water-based cold storage air conditioning system according to claim 2, characterized in that, Step 6 includes the following limiting control: Limit the rate of decrease in the outlet water temperature of the chiller unit and reduce the operating frequency of the circulating water pump to control the cooling rate to not exceed the preset limit. Once the water tank temperature profile returns to the set stable gradient range, the system automatically releases the limiting control and resumes the normal cold storage mode.

4. A method for optimizing and controlling the cold storage temperature of a water-based cold storage air conditioning system according to claim 3, characterized in that, Step 6, the method for stratifying the water tank, includes: A1. In the initial stage of cold storage operation, by adjusting the operating parameters of the refrigeration unit, a cold disturbance of a limited duration is injected into the cold water tank to stimulate the thermal stratification response process inside the water body. A2. Based on an array of temperature sensors deployed at different heights in the water tank, collect temperature change information of each temperature sensor after disturbance injection, and determine the response delay time of each measuring point from the start of disturbance to the occurrence of temperature change. A3. Compare the response delay times of adjacent height measuring points. When the difference in response delay between adjacent measuring points exceeds the preset abrupt change threshold, the location is determined as the thermal stratification interface of the water tank to divide the upper and lower water areas. A4. After identifying the thermal stratification interface, calculate the average response delay time of each measuring point in the area above the interface and the area below the interface respectively, and use the difference in stratification response delay between the two areas as the stability index of the current thermal stratification state. A5. The location of the thermal stratification interface and the stratification stability index are introduced as dynamic stratification status signals into the cold storage temperature optimization control logic. When the stratification stability index is lower than the preset stratification stability threshold, stratification protection control is executed.

5. A method for optimizing and controlling the cold storage temperature of a water-based cold storage air conditioning system according to claim 1, characterized in that, When calculating the initial target value of cold storage temperature and the cold storage control time window, the system first extracts the cold load operation data of the building in the past preset time window and constructs a cold load time series. Furthermore, the system combines meteorological forecast information for the future operating cycle to determine the trend of external temperature changes and identifies the peak range of cooling load based on the cooling load sequence; The peak range is compared with the off-peak period in the time-of-use electricity price data, and the overlapping time period is determined as the initial cold storage time window. At the same time, the system calculates the available cold storage energy margin based on the rated cold storage capacity parameters of the cold water tank and the current average temperature of the tank. Under energy balance constraints, determine the target outlet water temperature to be achieved within the initial cold storage time window; If the calculated target outlet water temperature is lower than the minimum allowable operating temperature limit of the system, then the upper limit of the cold storage control time window is adjusted. The system acquires data from multiple temperature sensors deployed at different heights in the cold water tank, calculates the temperature rise rate of the upper layer and the temperature drop rate of the lower layer, and uses the difference between the two as an index of temperature disturbance intensity. When in multiple consecutive sampling periods: The rate of temperature rise in the upper layer exceeds the system's preset temperature rise response threshold; Furthermore, the average temperature of the lower layer is higher than the preset deviation range of the current cold storage target temperature; If the current thermal stratification structure is deemed to be at risk of disturbance, a preset dynamic correction operation will be performed.

6. A method for optimizing and controlling the cold storage temperature of a water-based cold storage air conditioning system according to claim 1, characterized in that, The system performs time series analysis on the temperature profile data of the cold water tank in multiple operating cycles, calculates the temperature change rate of each temperature sensor during cold storage operation, and calculates the standard deviation of the temperature change rate at each vertical height position. When the standard deviation of the temperature change rate in a certain height section is greater than the preset multiple difference threshold of the adjacent sections for multiple consecutive operating cycles, the system determines that height section as a disturbance sensitive area. During subsequent cold storage operation, the system monitors the temperature change rate of the temperature sensor in the disturbance sensitive area in real time. If the temperature rise rate in this area exceeds the disturbance judgment threshold for multiple consecutive sampling periods, and its average growth slope meets the preset temperature rise trend threshold, it is judged to be a disturbance approaching state. Based on this, the system will perform temperature drop limiting control in advance; The trigger point for advance control is the first complete sampling cycle after the temperature rise trend continues to reach the set slope threshold, and there is a buffer interval of no less than the preset time between it and the normal amplitude limiting response of the system.

7. A method for optimizing and controlling the cold storage temperature of a water-based cold storage air conditioning system according to claim 1, characterized in that, Water quality and temperature parameters were collected in the upper and lower areas of the cold water tank, and the water density values ​​of each layer were calculated. Within multiple consecutive sampling periods, the rate of change of water density difference between the upper and lower regions is calculated, and this rate of change of density difference is compared with a preset threshold for stratification stability. When the rate of change of density difference between the upper and lower regions exceeds the stratification stability change threshold for multiple consecutive sampling cycles, and the rate of change of temperature gradient decreases synchronously to below the set temperature stability threshold within the corresponding time period, it is determined that the thermal stratification stability inside the cold water tank is in a decaying trend. Based on the time delay relationship between the rate of change of density difference and the rate of change of temperature gradient, the time advance of the thermal stratification structure disturbance is predicted. When the expected arrival time is reached, feedforward control is actively triggered.

8. A method for optimizing and controlling the cold storage temperature of a water-based cold storage air conditioning system according to claim 7, characterized in that, Methods for obtaining the time lead of disturbance occurrence include: Within each historical operating cycle, the point in time when the rate of change of density difference first continuously exceeds the threshold of change of stratification stability is identified as the precursor trigger moment of the disturbance signal. Meanwhile, in the subsequent time series of the same operating cycle, the time point at which the rate of change of the temperature gradient first continuously falls below the set temperature stability threshold is determined as the starting moment of the hierarchical structure response. The time interval between the trigger moment of the density difference change rate and the response moment of the temperature gradient change rate in each running cycle is used as the delay time sample for that running cycle. The delay time samples obtained from multiple running cycles are aggregated to construct a delay time sample set; For each sample in the delayed time sample set, calculate the average rate of decrease of the temperature gradient change rate within that period, and use it as the disturbance response intensity parameter corresponding to that delayed sample. Based on the delay time sample set and the corresponding disturbance response intensity parameters, a weighted statistical analysis is performed with the disturbance response intensity as the weight to obtain the weighted average of the delay time, which is used as the time advance for predicting the occurrence of thermal stratification disturbance.

9. A cooling temperature optimization control system for a water-based cooling air conditioning system, characterized in that, The system employs the cold storage temperature optimization control method according to any one of claims 1-8.

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