Real-time control method for phase change energy storage of heating radiator

Abstract

The invention provides a heating radiator phase change energy storage real-time control method, which comprises the following steps: according to an obtained energy storage state distribution condition, analyzing a thermal load distribution deviation between each group of heating radiators, calculating a deviation ratio between the actual power and the average power of each group of heating radiators, comparing the deviation ratio value by adopting a preset threshold range, and determining the phase change energy storage of each group of heating radiators. Determining the thermal load distribution deviation ratio of each group of heating radiators; according to the optimized power distribution scheme, an adjustment instruction is sent to a control unit of each group of heating radiators, first-time energy storage state detection is carried out, real-time power execution feedback data and temperature response data of a phase change material are obtained, and whether the adjusted heat supply power reaches a balance state or not is determined; and according to the judged synchronous control deviation degree, the energy storage progress is dynamically corrected, and synchronous operation parameters of each group of heating radiators are obtained by optimizing the latent heat release rate of the phase change material in real time.

Description

Technical Field

[0001] The present invention relates to the field of information technology, and in particular to a real-time control method for phase-change energy storage of a radiator. Background Art

[0002] In the field of building heating, research on multi-connected radiator control systems is of vital importance, directly impacting the energy efficiency and user comfort of heating systems. With the increasing demand for energy conservation and environmental protection, optimizing the coordinated operation of multiple radiator groups has become a key issue in improving heating efficiency and system stability. Research in this area not only impacts energy utilization but also has a profound impact on indoor temperature uniformity and user experience. However, current multi-connected control systems have significant shortcomings in practical applications. Many methods struggle to cope with the dynamic changes in the operating status of multiple radiator groups. This is particularly true in terms of heat distribution and coordinated control, often leading to resource waste and uneven heating. These limitations prevent optimal overall system efficiency and hinder the achievement of energy conservation goals. A deeper analysis reveals that the core challenge lies in achieving a dynamic balance between heat load distribution and energy storage coordination among multiple radiator groups. When the energy storage status of one radiator group differs from that of other groups, this leads to an imbalance in heating power distribution, which in turn causes asynchronous energy storage progress among the groups. This asynchrony not only weakens the overall operating efficiency of the system, but may also exacerbate the uneven heating phenomenon, causing some areas to overheat or overcool, affecting the user experience. To complicate matters further, this imbalance is difficult to predict and adjust during dynamic operation. Traditional control strategies are often unable to respond to these changes in a timely manner, leading to a further decline in system coordination. Therefore, how to dynamically adjust the heat load distribution strategy in the case of differences in the energy storage status of multiple groups of radiators to achieve rebalancing of heating power and synchronous control of energy storage progress has become a key issue in improving the overall efficiency of the system and the uniformity of heating. Summary of the Invention

[0003] The present invention provides a real-time control method for phase change energy storage of a radiator, which mainly includes:

[0004] Obtain the energy storage state difference data within the phase change temperature range of the phase change energy storage material of each group of radiators. Based on the real-time heat load demand of each group of radiators, calculate the solid-liquid phase ratio and residual latent heat capacity of the phase change material in each group of radiators. Combined with the deviation between the current room temperature and the set temperature, the current energy storage state distribution of each group is obtained;

[0005] Based on the obtained energy storage state distribution, the heat load distribution deviation between each group of radiators is analyzed, the deviation rate between the actual power and the average power of each group of radiators is calculated, and the deviation rate values are compared using a preset threshold range to determine the heat load distribution deviation rate of each group of radiators;

[0006] If the determined heat load distribution deviation rate exceeds the preset threshold, the power demand data of the radiator group with the exceeded deviation rate is extracted to obtain the difference between the demand data and the ideal power distribution. The power distribution direction that needs to be adjusted is determined. The heating power of each radiator group is recalculated based on the current phase change progress and remaining latent heat capacity of the phase change material. The adjusted power value is calibrated to obtain the optimized power distribution plan.

[0007] According to the optimized power distribution plan, adjustment instructions are sent to the control units of each group of radiators to conduct the first energy storage status detection, obtain real-time power execution feedback data and phase change material temperature response data, and determine whether the adjusted heating power has reached a balanced state;

[0008] If the adjusted heating power does not reach a balanced state, a secondary test will be conducted on the energy storage progress synchronization of each group of radiators to obtain the latest phase change material phase change completion and energy storage status difference data to determine the degree of deviation in synchronization control. If the adjusted heating power reaches a balanced state, the current power allocation plan will be maintained and the stable operation mode will be entered. The operating parameters of each group of radiators will be regularly collected and stored as historical data.

[0009] Based on the determined degree of synchronization control deviation, the energy storage progress is dynamically corrected, and the synchronization operation parameters of each group of radiators are obtained through real-time optimization of the latent heat release rate of the phase change material;

[0010] Based on the obtained synchronous operation parameters, the heating uniformity of each group of radiators is evaluated, and real-time temperature distribution data of each indoor monitoring point is obtained. The heating power of areas with local overheating or overcooling is fine-tuned, and feedback on the adjusted temperature distribution is obtained to obtain the coordinated control results of the heating system.

[0011] The technical solution provided by the embodiment of the present invention may have the following beneficial effects:

[0012] The present invention discloses a real-time control method for phase-change energy storage of radiators. The method obtains the energy storage state difference data of the phase-change material by monitoring the operating status of multiple groups of radiators, and calculates the heat load distribution deviation rate in combination with the room temperature deviation. When the deviation rate exceeds the threshold, the heating power is redistributed according to the phase change progress and the remaining latent heat capacity of the phase-change material. Through multiple detections and dynamic corrections, the synchronous operation and uniform heating of each group of radiators are achieved. The present invention can also make fine adjustments to local temperature distribution problems, and ultimately achieve a stable and efficient heating effect. The method makes full use of the latent heat characteristics of the phase-change material, realizes the intelligent coordinated control of the heating system, and improves the heating efficiency and indoor temperature uniformity. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1This is a flow chart of a real-time control method for phase-change energy storage of a radiator according to the present invention. DETAILED DESCRIPTION

[0014] To further understand the content of the present invention, the present invention is described in detail with reference to the accompanying drawings and examples. The present application is further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are intended only to illustrate the relevant invention and are not intended to limit the invention. It should also be noted that, for ease of description, only portions relevant to the invention are shown in the accompanying drawings.

[0015] like Figure 1 In this embodiment, a real-time control method for phase change energy storage of a radiator may specifically include:

[0016] S101. Obtain energy storage state difference data within the phase change temperature range of the phase change energy storage material of each group of radiators. Calculate the solid-liquid phase ratio and residual latent heat capacity of the phase change material in each group of radiators based on the real-time heat load demand of each group of radiators. Combined with the deviation between the current room temperature and the set temperature, obtain the current energy storage state distribution of each group.

[0017] Real-time temperature data for the phase change energy storage material within each radiator group is obtained. The current phase change stage is determined based on the material's phase change temperature range. The mass ratio of the solid and liquid phases in the phase change material is calculated based on the corresponding relationship between temperature and the phase change characteristic curve. Combined with the material's phase change latent heat value, the current residual latent heat capacity of each radiator group is determined. The room temperature sensor reading for each radiator group is subtracted from the preset target temperature to obtain a temperature deviation. Based on the sign and magnitude of the deviation, the immediate heat load demand for each space is calculated using the heat conduction equation. A negative deviation indicates the need to release stored heat, while a positive deviation indicates the conditions for continued heat storage. Based on the residual latent heat capacity of each radiator group and the heat load demand of the corresponding space, the heat storage and release priority of each group is determined by comparing the ratio of residual latent heat capacity to heat load demand. Combined with the solid-liquid phase ratio data for each phase change material group, an energy storage state distribution is generated, which includes the solid-liquid phase ratio, residual latent heat capacity, and heat storage and release status of each group.

[0018] For example, the application of phase change energy storage materials in radiators is based on their unique phase change properties. When the temperature of the material reaches the phase change point, it will convert between solid and liquid states. In this process, a large amount of latent heat is absorbed or released while the temperature remains relatively constant.

[0019] Specifically, the phase change temperature of paraffin-based phase change materials is usually between 18 and 28 degrees Celsius, and the phase change latent heat per kilogram of material can reach more than 200 kilojoules, which means that the same mass of phase change material stores several times more heat than water.

[0020] In one possible implementation, a temperature sensor monitors the temperature change of the phase change material in real time. When it is detected that the temperature is within the phase change range, the solid-liquid phase ratio is determined by a pre-established temperature and phase change degree correspondence curve.

[0021] For example, a certain phase-change material has a phase-change temperature range of 22-26 degrees Celsius. At a measured temperature of 24 degrees Celsius, the material's phase-change characteristic curve indicates that approximately 60% of the material has converted to a liquid phase, while 40% remains solid. This percentage directly determines the material's remaining heat storage capacity. A higher percentage of liquid phase indicates more stored heat and a lower ability to absorb further heat.

[0022] It's important to note that the calculation of heat load demand is based on the indoor-outdoor temperature difference and the heat loss characteristics of the space. When the room temperature sensor detects that the actual temperature is lower than the set point, the temperature deviation value is negative, indicating that the radiator needs to release heat. Conversely, a negative temperature deviation indicates that the current room temperature is too high and the radiator can continue to store heat. The heat conduction equation takes into account multiple factors, such as room volume, insulation performance, and external temperature. These parameters can accurately calculate the heat supply rate required to maintain the set point temperature.

[0023] For example, in a residence equipped with three phase change energy storage radiators, the living room radiator's phase change material liquid phase accounts for 80%, leaving only 20% of the total capacity. In contrast, the bedroom radiator's liquid phase accounts for only 30%, leaving 70% of the total heat storage capacity. Meanwhile, the living room's current temperature is 2 degrees Celsius below the set point, requiring 2,000 kilojoules of heat per hour; the bedroom's temperature is 1 degree Celsius above the set point, temporarily eliminating the need for heating. By comparing the ratio of each group's remaining latent heat capacity to the heat load demand, the living room radiator receives the highest heating priority and should immediately activate heat release mode; the bedroom radiator can continue storing heat or remain in standby mode. This intelligent control method, based on the phase change material's state, not only improves energy efficiency but also enables precise temperature control in each room. Through real-time monitoring and dynamic adjustment, heat can be stored during periods of low electricity prices and released when needed, reducing electricity costs while ensuring a stable and comfortable indoor temperature.

[0024] S102. Analyze the heat load distribution deviation between the radiators in each group based on the obtained energy storage state distribution, calculate the deviation rate between the actual power and the average power of each radiator group, compare the deviation rate values using a preset threshold range, and determine the heat load distribution deviation rate of each radiator group.

[0025] Based on the remaining latent heat capacity and solid-liquid phase ratio data for each radiator group in the energy storage state distribution, the actual operating power value of each radiator group is obtained. The average power is obtained by summing the power values of all groups and dividing it by the number of groups. For each radiator group, the initial deviation rate of the group is calculated by subtracting the average power from the actual power and dividing it by the average power. The initial deviation rate of each group is compared using a preset deviation rate threshold range. If the initial deviation rate exceeds the upper threshold, it is assigned a positive deviation rate. If it is below the lower threshold, it is assigned a negative deviation rate. If it is within the threshold range, it is assigned a zero deviation rate. The heat load distribution deviation rate of each radiator group is determined based on the ratio of the assigned value to the actual heat load demand of each group.

[0026] For example, the energy storage state distribution reflects the heat storage capacity and actual operating state of each group of radiators at a specific moment.

[0027] Specifically, the heat release capacity of phase-change materials varies significantly when they are in different solid-liquid phase ratios. Radiators with a high liquid phase ratio already store a large amount of thermal energy, resulting in a relatively high actual operating power. Radiators with a high solid phase ratio, on the other hand, store less heat and have a relatively low actual operating power. This power difference directly impacts the balance of heat load distribution across the entire heating system.

[0028] In one possible implementation, the actual operating power is obtained based on the relationship between the heat release rate of the phase change material and the temperature gradient. When the liquid phase of the phase change material in a group of radiators reaches 70%, its heat release power per unit time is 2 kilowatts; while the heat release power of another group of radiators with a liquid phase ratio of only 30% may be only 1 kilowatt. By summing the power values of all radiator groups and dividing by the number of groups, the average power is 1.5 kilowatts. At this time, the initial deviation rate of the first group is 33.3%, and the initial deviation rate of the second group is -33.3%. This deviation directly reflects the degree of unbalanced load distribution between the groups.

[0029] It should be noted that the preset deviation rate threshold range is usually determined based on the building's thermal insulation performance and user comfort requirements.

[0030] For example, the upper threshold is set to 20% and the lower threshold is set to -20%. When the initial deviation rate of a group of radiators exceeds this range, it indicates that the heat load borne by this group is significantly different from the average level. Groups exceeding the upper limit are overworking, which may cause excessive temperatures in the area and increased energy consumption. Groups below the lower limit are not fully utilizing their heating function, which may cause insufficient temperatures in the corresponding area. The conversion between the initial deviation rate and the heat load distribution deviation rate takes into account the actual heat demand factor.

[0031] For example, although the power deviation rate of a group of radiators is positive 30%, if the actual heat load demand in the area where the group is located is also 40% higher than the average, then its heat load distribution deviation rate is actually -10%, indicating that the heating capacity of the group is still insufficient. This conversion mechanism ensures that the calculation of the deviation rate is more in line with the actual heating demand, rather than simply pursuing power balance. Through the calculation and analysis of this deviation rate, the system can identify which radiator groups are in unreasonable working conditions. For groups with excessive deviation rates, the heat load distribution can be optimized by adjusting the heating parameters; for groups with deviation rates within a reasonable range, the current operating status is maintained. This deviation rate-based control method not only improves the overall heating efficiency, but also extends the service life of the phase change material and achieves balanced temperature control in each area.

[0032] S103. If the determined heat load distribution deviation rate exceeds the preset threshold, the power demand data is extracted from the radiator group with the exceeded deviation rate, and the difference between the data and the ideal power distribution is obtained. The power distribution direction that needs to be adjusted is determined. Combined with the current phase change progress and the remaining latent heat capacity of the phase change material, the heating power of each group of radiators is recalculated, and the adjusted power value is calibrated to obtain an optimized power distribution plan.

[0033] If the heat load distribution deviation rate exceeds a preset threshold, the current power demand data and the ideal power distribution value calculated based on the area and insulation coefficient of each zone are extracted from the radiator group with the exceeded deviation rate. The power gap value is then subtracted from the current power demand data. The sign of the gap value determines whether the group's power distribution needs to be increased or decreased. The upper limit of power adjustment for that group is determined based on the mass percentage of the phase change material in that group that has completed phase change and the remaining latent heat capacity. Based on the ratio of the upper limit to the power gap value, a linear interpolation method is used to calculate the adjusted power value for each radiator group. The interpolation coefficient is the ratio of the power gap value to the upper limit. The adjusted power values of all groups are accumulated and compared with the preset total power limit. If the limit is exceeded, the power distribution is proportionally reduced according to the power share of each group. Based on this preliminary adjusted power distribution data, the supply and demand balance is determined by calculating the difference between the heat supply generated by each group's adjusted power and the heat load demand of the corresponding zone. The power value is then adjusted based on the difference. The correction amount is the product of the difference and the heat transfer coefficient. After correction, the optimized power distribution plan is obtained.

[0034] For example, if the heat load distribution deviation rate exceeds a preset threshold, it indicates that there is a heat supply imbalance in the system, which may cause some areas to be overheated while other areas are underheated.

[0035] Specifically, the ideal power allocation is determined based on the actual heating needs of each area, taking into account factors such as room area, wall insulation coefficient, and window heat loss. For a 20-square-meter bedroom and a 40-square-meter living room, under the same insulation conditions, the ideal power allocation for the latter is approximately twice that of the former.

[0036] In one possible implementation, if the current power of a group of radiators is 3 kW, while the ideal power calculated based on regional characteristics is 2 kW, the power gap is 1 kW, indicating that the group has excess power. This requires consideration of the state constraints of the phase change material. The percentage of mass that has completed the phase change reflects the progress of the material's phase change. If 80% of the material has transitioned from solid to liquid, the heat storage capacity is near saturation, and the ability to continue heating is limited. The remaining latent heat capacity directly determines the physical limit of power adjustment.

[0037] It should be noted that the application of linear interpolation in power adjustment ensures smooth adjustment. The interpolation coefficient is determined by the ratio of the power gap value to the upper limit of power adjustment, and this coefficient is usually between 0 and 1.

[0038] For example, if the power gap is 1 kW and the power adjustment limit is 1.5 kW, the interpolation coefficient is 0.67, meaning the actual adjustment is 67% of the target adjustment. This gradual adjustment avoids drastic system fluctuations. The total power limit is a hard constraint on the power supply system, typically determined by the building's power capacity. When the total adjusted power of each group exceeds this limit, a proportional reduction is required.

[0039] For example, if the adjusted power of four radiators is 3, 2.5, 2.8, and 3.2 kilowatts, respectively, the total of 11.5 kilowatts exceeds the 10 kilowatt limit. Therefore, each radiator's power must be multiplied by a reduction factor of 0.87, resulting in allocations of 2.61, 2.17, 2.44, and 2.78 kilowatts, respectively. The matching of heat supply and heat load demand is assessed based on the principle of energy conservation. The actual heat supply of each radiator group is calculated by multiplying power by time, while the heat load demand takes into account factors such as indoor and outdoor temperature differences and ventilation losses. When the heat supply is less than the demand, a negative difference is generated, requiring an increase in power; otherwise, a decrease is required. The heat transfer coefficient plays a key role in this correction process, reflecting the efficiency of the radiator in transferring heat to the indoor space. Through this multi-level power optimization and adjustment, the system achieves a dynamic balance of heating supply across zones while meeting the total power constraint. Compared to traditional fixed power allocation, this adjustment method based on real-time deviations and material conditions significantly improves energy efficiency, reduces temperature fluctuations, and enhances living comfort.

[0040] S104. According to the optimized power distribution plan, an adjustment instruction is sent to the control unit of each group of radiators to perform the first energy storage state detection, obtain real-time power execution feedback data and temperature response data of the phase change material, and determine whether the adjusted heating power reaches a balanced state.

[0041] According to the target power value of each group of radiators in the optimized power distribution scheme, a control instruction containing the target power value and the adjustment rate is generated, and the control instruction is sent to the control unit of each group of radiators. After receiving the instruction, the control unit adjusts the power supply voltage and current parameters, and records the time when the instruction is sent as the adjustment starting time point. Starting from the adjustment starting time point, the first energy storage state detection is performed after a preset time interval, and the real-time power execution value of each group of radiators and the current temperature data of the phase change material are obtained. The real-time power execution value is used as the power execution feedback data, and the current temperature data is used as the temperature response data. The power execution deviation is obtained according to the difference between the power execution feedback data and the target power value, and the temperature change rate is obtained by dividing the difference between the temperature response data and the temperature at the previous moment by the time interval. If the power execution deviation is less than the preset deviation threshold and the absolute value of the temperature change rate is less than the preset rate threshold, it is determined that the adjusted heating power has reached a balanced state.

[0042] Illustratively, the generation and sending of control instructions are key steps in the execution of power adjustment.

[0043] Specifically, once the target power value is determined, the control unit converts it into specific electrical parameters. For example, if the target power of a group of radiators is adjusted from 2 kW to 2.5 kW, the control instruction contains the target power value of 2.5 kW, and the adjustment rate is set at 0.1 kW per second. This allows for a smooth power increase within 5 seconds, avoiding grid shock and thermal stress concentration in the phase change material.

[0044] In one possible implementation, the adjustment of supply voltage and current parameters follows the basic principle that power equals voltage multiplied by current. For a radiator with a rated voltage of 220 volts, when adjusting from 2 kilowatts to 2.5 kilowatts, the current needs to increase from 9.1 amps to 11.4 amps. The control unit achieves this precise adjustment through a thyristor voltage regulator circuit and records the exact time the command is sent, such as 2:35:20 PM, as a time reference for subsequent testing.

[0045] It should be noted that the selection of the preset time interval is closely related to the thermal response characteristics of the phase change material. Paraffin-based phase change materials have slow thermal conductivity and a lag in temperature changes, typically requiring 3-5 minutes to reach a new thermal equilibrium. Detecting too early will yield unstable transition state data, while detecting too late will affect the system's response speed. Therefore, the first energy storage state detection is typically performed 4 minutes after power adjustment. The acquisition of power execution feedback data relies on real-time monitoring of the current transformer and voltage sampling circuit.

[0046] For example, when a control command requests 2.5 kilowatts of power, the actual detected power may be 2.48 kilowatts. This 0.02-kilowatt deviation is primarily due to factors such as grid voltage fluctuations and component aging. Simultaneously, the temperature of the phase-change material detected by the temperature sensor rises from 24.5 degrees Celsius before adjustment to 25.2 degrees Celsius. This temperature change directly reflects the accumulation of thermal energy. Calculating the rate of temperature change provides an important basis for determining system equilibrium. If the temperature rises by 0.7 degrees Celsius within 4 minutes, the rate of temperature change is 0.175 degrees Celsius per minute. When this rate gradually decreases and stabilizes below 0.02 degrees Celsius per minute, the heat absorption process of the phase-change material has stabilized and the system is approaching thermal equilibrium. The dual criteria of power execution deviation and temperature change rate ensure accurate determination of equilibrium.

[0047] For example, the power execution deviation threshold is set at 2% of the target power, or 0.05 kilowatts; the temperature change rate threshold is set at 0.03 degrees Celsius per minute. Only when the difference between the measured power and the target power is less than 0.05 kilowatts, and the temperature change rate is less than 0.03 degrees Celsius per minute, can the system be considered to have reached a stable equilibrium state. This dual verification mechanism effectively avoids misjudgments that could arise from single-parameter analysis, improving the reliability and stability of system operation.

[0048] S105. If the adjusted heating power does not reach a balanced state, a secondary inspection is performed on the energy storage progress synchronization of each group of radiators to obtain the latest phase change completion degree of the phase change material and the energy storage state difference data, and the degree of deviation of the synchronous control is judged. If the adjusted heating power reaches a balanced state, the current power distribution plan is maintained and the stable operation mode is entered. The operating parameters of each group of radiators are regularly collected and stored as historical data.

[0049] If the heating power has not reached a balanced state, the temperature sensor data and power execution data of each group of radiators are read, and based on the comparative relationship between the temperature of the phase change material and the phase change temperature range, the mass percentage of each group of phase change materials that has completed the phase change is calculated as the phase change completion degree, and the latest energy storage state difference data is obtained by the difference between the phase change completion degrees of each group. Based on the energy storage state difference data, the standard deviation of the phase change completion degree of each group is calculated, and the standard deviation is compared with the preset synchronization deviation threshold to determine the degree of synchronization control deviation of the energy storage progress of each group of radiators. If the standard deviation exceeds the threshold, it is necessary to return to power adjustment. If the heating power reaches a balanced state, the current power distribution value of each group of radiators remains unchanged, and the stable operation mode is entered. The temperature value, power value, and phase change completion value of each group are obtained as operating parameters at preset time intervals, and the acquisition time and corresponding operating parameter values are stored in the data storage unit.

[0050] For example, the fact that the heating power has not reached a balanced state means that the system is still in the process of dynamic adjustment, and at this time, it is necessary to deeply analyze the operating differences of each group of radiators.

[0051] Specifically, the calculation of phase change completion is based on the physical properties of the phase change material. When the material temperature is in the phase change temperature range, the proportion of completed phase change can be inferred from the temperature value.

[0052] For example, the solid-liquid phase transition temperature range of a certain phase change material is 22-26 degrees Celsius. When the detection temperature is 25 degrees Celsius, according to linear interpolation, it can be seen that about 75% of the material has completed the transition from solid to liquid.

[0053] In one possible implementation, the phase change completion rates for the four groups of radiators are 75%, 82%, 68%, and 71%, respectively. These values directly reflect the energy storage progress of each group. By calculating the difference between adjacent groups, such as a 7 percentage point difference between the first and second groups and a 14 percentage point difference between the second and third groups, we can obtain energy storage status differences. Such differences indicate inconsistencies in the heat load distribution or phase change material properties of the radiators in each group.

[0054] It should be noted that standard deviation, as a statistical indicator measuring data dispersion, is crucial for assessing synchronization control deviation. For the four data sets mentioned above, the average value is 74%, and the squared deviations of each group from the average are 1, 64, 36, and 9, respectively, resulting in a calculated standard deviation of approximately 5.24%. When the preset synchronization deviation threshold is 5%, the actual standard deviation exceeds the threshold, indicating poor synchronization between groups and requiring a return to the power adjustment process for optimization. If the standard deviation exceeds the threshold, the system needs to reassess the power allocation for each group. Groups with higher phase change completion rates indicate faster heat storage or higher initial heat storage capacity, and their power should be appropriately reduced. Conversely, groups with lower completion rates should have their power increased to accelerate heat storage. This dynamic adjustment mechanism, based on real-time status, ensures that each radiator group reaches the target energy storage state synchronously. When the heating power reaches equilibrium, the system enters stable operation mode, indicating that power allocation has been optimized. During stable operation, data collection intervals are typically set to 10-15 minutes to capture system operational changes while minimizing redundant data. Each data collection includes three key parameters: temperature reflects the thermal state of the phase change material, power reflects energy consumption, and phase change completion indicates the degree of energy storage. Data is stored using a timestamp plus parameter value structure, for example, "2024-12-2014:30:00, Group 1: Temperature 25.3°C, Power 2.45kW, Completion 76%." This structured storage facilitates subsequent data analysis and trend prediction. By accumulating historical data, the system can learn optimal operating parameters under different environmental conditions, continuously improving heating efficiency and comfort. Long-term data accumulation also helps identify equipment aging trends and prevent failures.

[0055] S106. Based on the determined degree of synchronization control deviation, the energy storage progress is dynamically corrected, and the synchronization operation parameters of each group of radiators are obtained by real-time optimization of the latent heat release rate of the phase change material.

[0056] Based on the determined degree of synchronous control deviation, a pre-established set of thermal balance equations is invoked. This set of equations relates the latent heat release of the phase change material to temperature, expressed as Q = m × L × φ, where Q represents the released heat, m is the mass of the phase change material, L is the latent heat of phase change, and φ is the liquid phase ratio. Solving this set of equations yields the required energy storage schedule adjustment for each radiator group. Based on the obtained energy storage schedule adjustment, the heat conduction law q = k × A × ΔT / d, where q is the heat flux, k is the thermal conductivity, A is the heat transfer area, ΔT is the temperature difference, and d is the heat transfer distance, is used to adjust the heat transfer area A by adjusting the immersion depth of the replacement heat pipe within the phase change material container. This allows for real-time optimization of the latent heat release rate, resulting in the thermal power output curves for each radiator group over different time periods. Based on the obtained thermal power output curve, the total heat required for each group of radiators to reach the target temperature is determined through integral calculation. Combined with the heat storage capacity of the phase change material, the synchronous operation parameters of each group of radiators are determined, including the initial heating temperature of the phase change material, the immersion depth adjustment sequence of the heat exchange tubes, and the start and stop time nodes of each group of radiators, to obtain the synchronous operation parameters of each group of radiators.

[0057] Exemplarily, the acquisition of temperature sensor data and phase change material state data is the basis for achieving precise control.

[0058] Specifically, the temperature sensor usually adopts PT100 platinum resistance thermometer, which is installed at the water inlet and outlet of each radiator to monitor the water temperature change in real time. The phase change state data of the phase change material is obtained through an ultrasonic detector, and the difference in the propagation speed of ultrasonic waves in the solid phase and liquid phase is used to determine the liquid phase proportion of the material. When the phase change material gradually changes from solid to liquid, its internal lattice structure changes, and the propagation path and reflection characteristics of the ultrasonic wave also change accordingly. By analyzing the time difference and intensity change of the echo signal, the volume proportion occupied by the liquid phase can be accurately calculated. The calculation of the deviation degree value involves comparative analysis in multiple dimensions.

[0059] In one possible implementation, the system sets an ideal temperature rise curve as a baseline. This curve takes into account the room's heat load, external temperature fluctuations, and user comfort requirements. In actual operation, the temperature data of each radiator group is compared with this baseline curve in real time, while also considering the temperature consistency between groups.

[0060] For example, if the temperature of the first set of radiators is 65°C and the second set is only 58°C, the temperature difference reaches 7°C. At the same time, if the liquid phase ratio of the phase change material in the first set is 80% and the second set is only 60%, it indicates that there is a significant asynchrony in energy release between the two groups. The establishment of the thermal balance equations is based on the principle of conservation of energy and the basic laws of heat transfer.

[0061] It's important to note that phase change materials absorb or release large amounts of latent heat during phase changes, while maintaining a relatively constant temperature. This property enables the system to store and release large amounts of energy within a relatively small temperature fluctuation range. The amount of latent heat released, Q, in the equations is not only related to the mass and latent heat value of the phase change material, but also closely related to the liquid phase ratio, φ. If the system detects that the temperature of a particular group of radiators is too low, it can compensate for the heat shortage by increasing the liquid phase conversion rate of that group's phase change material. Adjusting the immersion depth of the heat exchanger tubes is a key means of optimizing the latent heat release rate.

[0062] Preferably, the heat exchange tubes adopt a spiral structure with fins on the outer surface to increase the heat exchange area. A servo motor-driven lifting mechanism allows for precise control of the immersion depth of the heat exchange tubes in the phase change material container. To accelerate heat release, the immersion depth of the heat exchange tubes is increased, allowing more heat exchange area to come into contact with the liquid phase change material. Conversely, to slow heat release, the heat exchange tubes are raised, reducing the effective heat exchange area. This adjustment method responds quickly, capable of changing thermal power output within seconds, achieving precise control of the temperature of each radiator group.

[0063] S107. Based on the obtained synchronous operation parameters, the heating uniformity of each group of radiators is evaluated, and real-time temperature distribution data of each indoor monitoring point is obtained. The heating power of the area with local overheating or overcooling is fine-tuned, and feedback of the adjusted temperature distribution is obtained to obtain the coordinated control result of the heating system.

[0064] Based on the obtained synchronous operation parameters, including the initial heating temperature of each radiator group, the immersion depth of the heat exchange tubes, and the start and stop time nodes, the actual operating data of each radiator group is read and the heat dissipation of each radiator group is calculated as Q = c × m × ΔT, where c is the specific heat capacity of water, m is the circulating water flow rate, and ΔT is the supply and return water temperature difference. The degree of heating uniformity is evaluated by calculating the standard deviation of the heat dissipation of all groups. At the same time, real-time temperature data is obtained from the temperature monitoring points arranged in a grid pattern indoors to generate an indoor temperature distribution map. For the generated indoor temperature distribution map, the deviation value of each monitoring point temperature is compared with the set temperature. If the temperature deviation of a monitoring point exceeds the preset threshold, the area and coordinate position of the monitoring point are marked. The boundary of the local overheating or undercooling area is determined based on the temperature data of adjacent monitoring points. By querying the corresponding relationship table between monitoring points and radiators, the radiator group corresponding to the problematic area is determined. For the determined radiator group, read the current water supply flow value of the group, and change the circulating water flow through the radiator group by adjusting the opening percentage of the electric regulating valve on the water inlet pipe of the group. The flow change directly affects the heating power of the group. The valve opening value and flow change data before and after the adjustment are recorded, and the temperature feedback data of each monitoring point after the adjustment are continuously collected. Based on the collected temperature feedback data, calculate the temperature deviation improvement rate R = (T1-T2) / T1×100%, where T1 is the absolute value of the temperature deviation before adjustment, and T2 is the absolute value of the temperature deviation after adjustment. If R is greater than the preset threshold and the temperature deviations of all monitoring points are within the allowable range, it is judged that the expected stable state has been reached, and the coordinated control results of the heating system are output, including the optimized operating parameter configuration of each group of radiators and the evaluation value of the indoor temperature distribution uniformity.

[0065] For example, the acquisition and application of synchronous operation parameters are key links in achieving precise control of the heating system.

[0066] Specifically, these parameters include the initial heating temperature setpoint for each radiator group, the immersion depth of the heat exchange tubes in the phase change material container, and the start and stop times for each group. The initial heating temperature is typically determined based on the outdoor temperature and the building's heat load characteristics. When the outdoor temperature is -5°C, the water supply temperature might be set to 70°C. The immersion depth of the heat exchange tubes directly determines the contact area with the phase change material, which in turn affects heat exchange efficiency. The start and stop times are set to take into account user routines and peak and off-peak electricity prices to achieve economical operation. Heat dissipation calculations are based on fundamental thermodynamic principles.

[0067] In one possible implementation, the heat dissipation of each radiator group is determined by measuring the supply water temperature, return water temperature and circulating water flow rate. The specific heat capacity of water is 4.2kJ / kg·℃. When the circulating water flow rate is 0.5m 3 / h, and a 20°C supply / return water temperature difference, the heat dissipation power of this group of radiators is approximately 11.6kW. By calculating the standard deviation of the heat dissipation of multiple radiator groups, we can quantitatively assess the uniformity of heating across groups. The smaller the standard deviation, the closer the heat dissipation of each radiator group, and the more uniform the heating. The placement of indoor temperature monitoring points follows specific principles.

[0068] It's important to note that monitoring points are typically distributed in a grid pattern. A 100-square-meter room might have nine monitoring points, forming a 3x3 monitoring grid. Each monitoring point is equipped with a high-precision temperature sensor and installed at a height of 1.5 meters, away from the direct influence of doors, windows, and radiators. This arrangement comprehensively reflects the distribution characteristics of the indoor temperature field and promptly identifies areas of overheating or undercooling. The mapping between monitoring points and radiators is established using a pre-established mapping table.

[0069] For example, the three monitoring points on the east side of the room are primarily affected by the first set of radiators. When the temperatures at these monitoring points are low, the system can quickly locate the first set of radiators that require adjustment. This correspondence takes into account heat conduction paths and air convection patterns, making it possible to trace abnormal temperature areas back to specific equipment. The electric control valve enables precise regulation of heating power.

[0070] Preferably, the regulating valve adopts proportional integral control mode, and the valve opening is continuously adjustable from 0% to 100%. When the heating power of a group of radiators needs to be increased, the control system sends a command to increase the opening of the regulating valve on the water inlet pipe of the group, so that more high-temperature water flows through the radiator; otherwise, the opening is reduced. Every 10% change in valve opening changes the flow rate through the group by approximately 0.05m 3 / h, corresponding to a heating power change of approximately 1.2 kW. Calculating the temperature deviation improvement rate provides a quantitative evaluation indicator of regulation effectiveness. By comparing the temperature deviation values before and after adjustment, the effectiveness of control measures can be intuitively reflected. For example, if the initial temperature at a monitoring point is 18°C, the set temperature is 22°C, and the deviation is 4°C; after flow adjustment, the temperature rises to 21°C and the deviation decreases to 1°C, the improvement rate is 75%. This evaluation method enables the system to determine whether further adjustment is needed, avoiding energy waste caused by over-adjustment.

[0071] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A real-time control method for phase change energy storage of a radiator, characterized in that: The method comprises: By monitoring the operating status of multiple groups of radiators, the energy storage state difference data within the phase change temperature range of each group of phase change energy storage materials is obtained, the solid-liquid phase ratio and the residual latent heat capacity of the phase change materials in each group of radiators are calculated, and the energy storage state distribution of each group of radiators is determined in combination with the deviation value between the current room temperature and the set temperature; based on the energy storage state distribution, the deviation rate between the actual power and the average power of each group of radiators is calculated, and compared with the preset threshold range to determine the heat load distribution deviation rate of each group of radiators; if the heat load distribution deviation rate exceeds the preset threshold, the power demand data is extracted from the radiator group with the exceeded deviation rate, and the gap value with the ideal power distribution is calculated, and the heating power of each group of radiators is recalculated in combination with the solid-liquid phase ratio and the residual latent heat capacity of the phase change material. , generate an optimized power distribution plan after calibration; according to the optimized power distribution plan, send adjustment instructions to the control unit of each group of radiators, detect the real-time power execution feedback data and the temperature response data of the phase change material, and determine whether the heating power has reached a balanced state; if the heating power has not reached a balanced state, detect the phase change completion degree and energy storage state difference data of each group of radiators to determine the degree of synchronous control deviation; according to the degree of synchronous control deviation, adjust the latent heat release rate of the phase change material, and generate the synchronous operation parameters of each group of radiators; according to the synchronous operation parameters, obtain the temperature distribution data of each monitoring point in the room, determine the temperature deviation of the local area, fine-tune the heating power of the local area, and generate the optimized operation parameter configuration of each group of radiators.

2. The radiator phase change energy storage real-time control method according to claim 1, characterized in that: The method monitors the operating status of multiple groups of radiators, obtains energy storage state difference data within the phase change temperature range of each group of phase change energy storage materials, calculates the solid-liquid phase ratio and residual latent heat capacity of the phase change materials in each group of radiators, and determines the energy storage state distribution of each group of radiators based on the deviation between the current room temperature and the set temperature, including: Real-time temperature data of the phase change energy storage material in each group of radiators is obtained, and the current phase change stage is determined based on the phase change temperature range of the phase change energy storage material. The mass ratio of the solid phase and the liquid phase in the phase change energy storage material is calculated through the correspondence between the temperature and the phase change characteristic curve. In combination with the phase change latent heat value, the residual latent heat capacity of each group of radiators is determined; room temperature sensor data of the space where each group of radiators is located is obtained, and a deviation value is calculated from the preset target temperature. Based on the deviation value, the heat load demand of each space is calculated through the heat conduction equation; based on the ratio of the residual latent heat capacity to the heat load demand, the heat storage and release priority of each group of radiators is determined, and in combination with the solid-liquid phase ratio, an energy storage state distribution including the solid-liquid phase ratio, the residual latent heat capacity and the heat storage and release state is generated.

3. The radiator phase change energy storage real-time control method according to claim 1, characterized in that: The step of calculating the deviation rate between the actual power and the average power of each group of radiators based on the energy storage state distribution and comparing the deviation rate with a preset threshold range to determine the heat load distribution deviation rate of each group of radiators includes: According to the residual latent heat capacity and the solid-liquid phase ratio in the energy storage state distribution, the actual operating power value of each group of radiators is obtained, and the average value of the power values of all groups is calculated. For each group of radiators, the difference between its actual power and the average value is calculated and divided by the average value to generate an initial deviation rate; the initial deviation rate is compared with the preset threshold range, and a positive deviation rate, a negative deviation rate or zero is assigned. According to the ratio of the assigned result to the heat load demand of each group, the heat load distribution deviation rate of each group of radiators is determined.

4. The radiator phase change energy storage real-time control method according to claim 1, characterized in that: If the heat load distribution deviation rate exceeds a preset threshold, power demand data is extracted from the radiator group with the exceeded deviation rate, the difference from the ideal power distribution is calculated, and the heating power of each radiator group is recalculated based on the solid-liquid phase ratio and the residual latent heat capacity of the phase change material. After calibration, an optimized power distribution plan is generated, including: The current power demand data and the ideal power distribution value calculated based on the regional area and the insulation coefficient are extracted from the radiator group with an excessive deviation rate, and the difference between the two is calculated to generate a power gap value. The power adjustment direction is determined based on the positive or negative sign of the power gap value, and the power adjustment upper limit is determined based on the solid-liquid phase ratio and the residual latent heat capacity of the phase change material. The adjusted power value is calculated based on the ratio of the power adjustment upper limit to the power gap value, and the optimized power distribution plan is generated after calibration.

5. The radiator phase change energy storage real-time control method according to claim 1, characterized in that: The method includes sending adjustment instructions to the control units of each group of radiators according to the optimized power distribution plan, detecting real-time power execution feedback data and temperature response data of the phase change material, and determining whether the heating power reaches a balanced state, including: According to the target power value in the optimized power distribution scheme, a control instruction is generated and sent to the control unit of each group of radiators, and the time when the instruction is sent is recorded; after a preset time interval, the real-time power execution value of each group of radiators and the temperature data of the phase change material are detected, and the difference between the real-time power execution value and the target power value is calculated to determine whether the heating power has reached a balanced state.

6. The radiator phase change energy storage real-time control method according to claim 1, characterized in that: If the heating power does not reach a balanced state, detecting the phase change completion degree and energy storage state difference data of each group of radiators to determine the degree of synchronous control deviation includes: If the heating power has not reached a balanced state, the temperature sensor data and power execution data of each group of radiators are read, and the phase change completion degree of each group of phase change materials is calculated based on the comparison between the temperature of the phase change material and the phase change temperature range. The difference in the phase change completion degree of each group is calculated, and the energy storage state difference data is generated to determine the degree of synchronous control deviation.

7. The radiator phase change energy storage real-time control method according to claim 1, characterized in that: The method of adjusting the latent heat release rate of the phase change material according to the degree of synchronization control deviation to generate synchronization operation parameters of each group of radiators includes: The temperature data of each group of radiators and the phase change state of the phase change material are obtained, the difference between the current temperature and the target temperature of each group of radiators and the liquid phase ratio are calculated, and the deviation degree of the difference and the liquid phase ratio are calculated; according to the deviation degree, the heat balance equation group is called to calculate the energy storage progress adjustment amount of each group of radiators; according to the energy storage progress adjustment amount, the immersion depth of the heat exchange tube is adjusted to generate a thermal power output curve; according to the thermal power output curve, the total heat to reach the target temperature is calculated, and combined with the heat storage capacity of the phase change material, the synchronous operation parameters including the initial heating temperature, the heat exchange tube immersion depth sequence and the start and stop time nodes are generated.

8. The radiator phase change energy storage real-time control method according to claim 1, characterized in that: The method of obtaining temperature distribution data of each indoor monitoring point according to the synchronous operation parameters, determining the temperature deviation of the local area, fine-tuning the heating power of the local area, and generating the optimized operation parameter configuration of each group of radiators includes: According to the synchronous operation parameters, the actual operation data of each group of radiators is read, the heat dissipation of each group is calculated, and an indoor temperature distribution map is generated; according to the temperature distribution map, the deviation value between the temperature of each monitoring point and the set temperature is calculated, and the temperature deviation of the local area is determined; for the radiator group with deviation, the opening of the electric regulating valve is adjusted, the circulating water flow rate is changed, the adjusted temperature data is collected, and a coordinated control result including the optimized operation parameter configuration of each group of radiators is generated.

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