Dynamic thermal storage and heating regulation system and method based on energy efficiency optimization

Abstract

This invention relates to the field of thermal energy storage technology, and more particularly to a dynamic thermal energy storage and heating regulation system and method based on energy efficiency optimization. This invention collaboratively models multiple parameters such as server load rate, cooling water return temperature, and heating-side supply and return water temperatures to convert instantaneous surplus heat into dispatchable thermal storage. By releasing the stored heat and adjusting the proportion of auxiliary heat sources, the temperature difference between the heating-side supply and return water is stabilized within the target range, avoiding room temperature deviations and energy efficiency deterioration caused by heat source fluctuations. Simultaneously, closed-loop corrections of the charging and releasing heat power, heating demand range, and index weights allow the system to gradually approach the balance point of minimum energy consumption and optimal thermal comfort during long-term operation. This significantly improves waste heat utilization and reduces unit heating energy consumption while ensuring the thermal comfort of the building complex, effectively solving the problems of insufficient heating stability and low waste heat utilization efficiency caused by asynchronous heating regulation and waste heat recovery responses.

Description

Technical Field

[0001] This invention relates to the field of thermal energy storage technology, and in particular to a dynamic thermal energy storage and heating regulation system and method based on energy efficiency optimization. Background Technology

[0002] With the rapid advancement of the digital economy and smart city construction, the scale of data centers and urban centralized heating systems continues to expand, leading to a continuous increase in energy consumption intensity. The transformation of energy systems from a single supply model to a multi-energy collaborative utilization model has become a development trend. However, under complex operating environments, the supply and demand relationships of various energy sources exhibit significant dynamism and uncertainty. Significant differences exist in the operating rhythms, load changes, and response capabilities of different systems, resulting in increasing difficulty in energy matching. In actual operation, problems such as supply-demand imbalance, lagging regulation, and insufficient energy utilization efficiency are gradually emerging. These issues not only constrain the overall operational stability of the energy system but also place higher demands on energy conservation, emission reduction, and refined management. There is an urgent need to construct a more flexible, efficient, and adaptive energy collaborative control mechanism to address the complex operational challenges under multi-source coupling conditions.

[0003] Chinese Patent Publication No. CN116428632A discloses a data center temperature control and waste heat recovery system. The system includes: a data center, a building complex, an energy supply system, and a temperature control system. The temperature control system is connected to both the building complex and the data center. The temperature control system is suitable for cooling the data center and for heating the building complex. The temperature control system includes a heat storage element, which is connected to both the building complex and the data center. The heat storage element is suitable for absorbing and storing the heat energy generated by the data center and for using the heat energy generated by the data center to heat the building complex. The energy supply system is connected to the temperature control system and is suitable for providing energy to the temperature control system.

[0004] Therefore, the existing technology has the following problems: its operation and regulation mainly rely on fixed control strategies, lacking the ability to dynamically adapt to load changes and supply and demand fluctuations, and is prone to heat regulation lag and energy configuration imbalance under complex operating conditions; there is a lack of coordinated feedback mechanism between waste heat recovery and heat output, and the system regulation is based on a single operating condition parameter, which can easily lead to low waste heat utilization efficiency and insufficient heat supply stability; its thermal storage unit operation control does not fully consider the overall energy efficiency evolution characteristics of the system, and the regulation process lacks closed-loop optimization logic, which can easily lead to frequent start-up and shutdown of thermal storage devices and an increase in unit heat supply energy consumption. Summary of the Invention

[0005] To address this, the present invention provides a dynamic thermal storage and heating regulation system and method based on energy efficiency optimization. This system overcomes the problems of insufficient heating stability and low waste heat utilization efficiency caused by the asynchronous response of heating regulation and waste heat recovery in the prior art by constructing a coordinated regulation mechanism for data center load fluctuations and changes in building group heating demand.

[0006] To achieve the above objectives, on the one hand, the present invention provides a dynamic thermal storage and heating control system based on energy efficiency optimization, comprising:

[0007] The data acquisition module is used to collect data in real time on the server load rate, cooling return water temperature, heating side supply water temperature, heating side return water temperature, heat storage capacity of the heat storage device operating based on preset charging and discharging power, and average room temperature of the building complex during the operation of the data center's cooling and heating systems.

[0008] The status determination module is used to determine the waste heat recovery capacity index based on the server load rate, the cooling return water temperature and the preset index weight, and to determine the waste heat status range based on the comparison result between the waste heat recovery capacity index and the preset heating demand range.

[0009] The operation module is used to perform a heat charging operation or a heat compensation operation based on the state switching characteristics of the waste heat state interval within a preset operation judgment time. The heat charging operation includes waste heat charging or combined heating, and the heat compensation includes heat release compensation and / or limiting the intervention ratio of auxiliary heat sources.

[0010] The adjustment module is used to adjust the preset heat charging and discharging power based on the temperature difference between the supply water temperature and the return water temperature on the heating side within a preset observation period after the heat charging operation or heat compensation operation.

[0011] The correction module is used to statistically analyze the waste heat utilization rate, unit heating energy consumption, and heat storage turnover rate within a preset operating cycle after adjusting the heat charging and discharging power. Based on the trend of the statistical results and the average room temperature of the building complex, the module corrects the preset heating demand range and the preset index weights.

[0012] Furthermore, the state determination module includes:

[0013] The indicator calculation unit is used to perform a fusion calculation based on the server load rate, the cooling water return temperature and the preset indicator weights to determine the waste heat recovery capacity indicator.

[0014] The state interval determination unit is used to determine that the waste heat state interval is an ample interval when the waste heat recovery capacity index is greater than the upper limit of the preset heating demand range, or to determine that the waste heat state interval is an insufficient interval when the waste heat recovery capacity index is less than the lower limit of the preset heating demand range, or to determine that the waste heat state interval is a balanced interval when the waste heat recovery capacity index is within the preset heating demand range.

[0015] Furthermore, the operation module includes:

[0016] The switching statistics unit is used to count the frequency of switching from the ample interval to the balanced interval or the insufficient interval based on the preset operation determination duration, denoted as the first switching frequency, and to count the frequency of switching from the insufficient interval to the balanced interval or the ample interval, denoted as the second switching frequency.

[0017] An operation unit is used to perform the heating operation or the heat compensation operation based on the threshold comparison results of the first switching frequency and the second switching frequency and the residual heat state range.

[0018] Furthermore, the operating unit includes:

[0019] The first heat charging subunit is used to perform the waste heat charging when the first switching frequency is less than the preset first switching threshold and the current waste heat state interval is the ample interval.

[0020] The second heat charging subunit is used to perform the combined heat charging when the first switching frequency is greater than or equal to a preset first switching threshold and the current residual heat state interval is the ample interval.

[0021] Furthermore, the operating unit also includes:

[0022] The first compensation subunit is used to perform the heat release compensation operation when the second switching frequency is less than the preset second switching threshold and the current waste heat state interval is the insufficient interval.

[0023] The second compensation subunit is used to perform the heat release compensation operation when the second switching frequency is greater than or equal to the preset second switching threshold and the current waste heat state interval is the insufficient interval, and simultaneously start the auxiliary heat source and limit the intervention ratio to not exceed the preset auxiliary ratio.

[0024] Furthermore, the adjustment module includes:

[0025] The trend analysis unit is used to calculate the standard deviation of the temperature difference between the supply water temperature and the return water temperature on the heating side and the integral of the temperature difference relative to the preset temperature difference threshold within the preset observation period.

[0026] An adjustment unit is used to adjust the preset charge / discharge heat power based on the threshold comparison results of the deviation integral and the standard deviation.

[0027] Furthermore, the adjustment unit includes:

[0028] The first down-adjustment subunit is used to determine that there is a continuous thermal imbalance when the integral amount of the deviation is greater than the preset integral stability threshold, and to reduce the preset charge and discharge heat power by a preset first down-adjustment magnitude.

[0029] The second down-adjustment subunit is used to determine the presence of high-frequency disturbance when the integral of the deviation is less than or equal to a preset integral stability threshold and the standard deviation is greater than a preset fluctuation threshold, and to down-adjust the preset charge / discharge heat power by a preset second down-adjustment magnitude.

[0030] Furthermore, the adjustment unit also includes:

[0031] An adjustment unit is used to increase the preset charge / discharge heat power by a preset adjustment amount when the integral of the deviation is less than or equal to the preset integral stability threshold and the standard deviation is less than or equal to the preset fluctuation threshold.

[0032] Furthermore, the correction module includes:

[0033] The correction statistics unit is used to calculate the waste heat utilization rate, unit heating energy consumption, and heat storage turnover times within the preset operating cycle.

[0034] The range correction unit is used to calculate the change rate of waste heat utilization rate and unit heating energy consumption in the current preset operating cycle and the previous preset operating cycle, and to determine whether there is a decrease in energy efficiency based on the calculation results. Based on the energy efficiency decrease determination result, the upper limit of the heating demand range is reduced by a preset first correction step size. It also calculates the average value of the heat storage turnover times in the current preset operating cycle, and counts the total number of times the average room temperature of the building complex is continuously less than a preset room temperature threshold. When the average value is greater than a preset mean threshold and the total number of times is greater than a preset total number threshold, the lower limit of the heating demand range is increased by a preset second correction step size.

[0035] The weight correction unit is used to adjust the weight of the preset index according to the preset weight adjustment coefficient when the total duration during which the average room temperature of the building complex is greater than the preset room temperature threshold is greater than the preset operating cycle, and the absolute value of the change rate of unit heating energy consumption in the energy efficiency decline determination result is less than the preset improvement expectation threshold.

[0036] On the other hand, the present invention also provides a dynamic thermal storage and heating regulation method based on energy efficiency optimization, comprising:

[0037] Real-time data collection of server load rate, cooling return water temperature, heating side supply water temperature, heating side return water temperature, heat storage capacity of heat storage devices operating based on preset charging and discharging power, and average room temperature of the building complex during the operation of the data center's cooling and heating systems.

[0038] The waste heat recovery capacity index is determined based on the server load rate, the cooling water return temperature, and the preset index weights. The waste heat status range is determined based on the comparison between the waste heat recovery capacity index and the preset heating demand range.

[0039] Based on the state switching characteristics of the waste heat state interval within the preset operation judgment time, a heat charging operation or a heat compensation operation is performed. The heat charging operation includes waste heat charging or combined heating, and the heat compensation includes heat release compensation and / or limiting the intervention ratio of auxiliary heat sources.

[0040] The preset heat charging and discharging power is adjusted based on the changing trend of the temperature difference between the supply water temperature and the return water temperature on the heating side within a preset observation period after the heat charging or heat compensation operation.

[0041] After statistically adjusting the heat charge and discharge power, the waste heat utilization rate, unit heating energy consumption, and heat storage turnover times within the preset operating cycle are calculated. Based on the changing trend of the statistical results and the average room temperature of the building complex, the preset heating demand range and the preset index weights are adjusted.

[0042] Compared with existing technologies, the beneficial effects of this invention are as follows: by collaboratively modeling multiple source parameters such as server load rate, cooling return water temperature, and heating supply and return water temperatures, when the server load increases and the cooling return water temperature rises, indicating an increase in recoverable heat, the system prioritizes guiding the heat storage device to charge waste heat or conduct combined charging, thereby converting instantaneous surplus heat into dispatchable heat storage. When the load decreases or the return water temperature drops, resulting in insufficient recoverable heat, the system releases the stored heat and adjusts the auxiliary heat source intervention ratio to stabilize the temperature difference between the heating supply and return water within the target range, avoiding room temperature deviation and energy efficiency deterioration caused by heat source fluctuations. Simultaneously, the closed-loop correction of charging and releasing power, heating demand range, and index weights allows the system to gradually approach the balance point of minimum energy consumption and optimal thermal comfort during long-term operation. This significantly improves waste heat utilization and reduces unit heating energy consumption while ensuring the thermal comfort of the building complex, effectively solving the problems of insufficient heating stability and low waste heat utilization efficiency caused by asynchronous heating regulation and waste heat recovery response.

[0043] Furthermore, by weighted fusion calculation of server load rate and cooling return water temperature, a waste heat recovery capacity index is constructed. This allows the calculation results to simultaneously reflect the comprehensive changes in the heat generation intensity on the heat source side and the heat absorption capacity on the heat exchange side. The server load rate directly represents the heat generation level per unit time, while the cooling return water temperature reflects the energy level state of the system after absorbing and carrying heat. The joint calculation of the two can dynamically characterize the availability of waste heat resources. Furthermore, by comparing the waste heat status with the preset heating demand range, a continuous hierarchical judgment from insufficient to balanced to abundant is achieved. This transforms the heating control logic from a single threshold trigger to interval-based and hierarchical decision-making, thereby achieving a more stable, precise, and predictable adjustment effect under different operating conditions and avoiding frequent switching and adjustment lag problems.

[0044] Furthermore, by statistically analyzing the switching frequency of the waste heat state interval within the preset operation judgment time, and using the first switching frequency from the abundant interval to the balanced or insufficient interval as a characterizing parameter for measuring the stability of waste heat supply, the impact of data center server load fluctuations and changes in the cooling system's heat recovery capacity on the sustainability of waste heat can be reflected: when the first switching frequency is low, it indicates that the waste heat supply level has good continuity and stability in the time dimension, and it is suitable to directly use waste heat for charging to improve the overall energy efficiency of the system; when the first switching frequency is high, it indicates that there are significant fluctuations in waste heat supply, and a single waste heat source is difficult to continuously meet the stable charging demand of the heat storage device. At this time, by introducing a combined charging method, the fluctuations on the heat source side can be smoothed out while ensuring the heat storage rate, which is beneficial to avoid the adverse effects of frequent start-stop and power oscillation on system operation.

[0045] Furthermore, by introducing a second switching frequency, the dynamic characteristics of the transition from insufficient to balanced or sufficient waste heat are characterized, enabling the system to distinguish between two typical operating conditions: short-term load disturbances and continuous insufficient heating. When the second switching frequency is low, it indicates that the heating gap has transient characteristics, and the heat released by the thermal storage device can achieve load balance under the action of system thermal inertia. Therefore, only heat release compensation is needed to stabilize the temperature field on the heating side. When the second switching frequency is high, it indicates that the heat load of the building complex is continuously higher than the waste heat supply capacity. Relying solely on the thermal storage device is prone to fluctuations in thermal storage depth and continuous deviations in heating temperature. In this case, while performing heat release compensation, a limited proportion of auxiliary heat sources is introduced. This can make up for the long-term heat gap while suppressing the rapid decay of thermal storage, thereby establishing a dynamic balance between heating stability, thermal storage utilization efficiency, and system energy efficiency.

[0046] Furthermore, by jointly analyzing the standard deviation and integral of the temperature difference between the supply and return water on the heating side within a preset observation period, the transient fluctuation characteristics and cumulative thermal deviation level of the system's heating status can be simultaneously characterized. The integral of the deviation reflects the degree of long-term energy supply and demand imbalance in the heating system, while the standard deviation characterizes the intensity of short-term disturbances. When the integral of the deviation is large, the corresponding building complex is continuously in a state of insufficient or excessive heating. Reducing the charging and releasing power can effectively suppress energy overshoot and promote the system's return to thermal balance. When the standard deviation is large and the integral of the deviation is within a stable range, it indicates that the system is significantly affected by transient disturbances. Slightly reducing the power can weaken high-frequency oscillations and improve operational stability. When both are at low levels, it indicates that the system's heat exchange process is stable and the supply and demand matching degree is high. At this time, appropriately increasing the charging and releasing power can improve the level of waste heat utilization and accelerate the turnover of the thermal storage device, thereby achieving continuous improvement in energy efficiency while ensuring heating stability.

[0047] Furthermore, by conducting coordinated statistics and dynamic comparisons of waste heat utilization rate, unit heating energy consumption, and heat storage turnover within a preset operating cycle, when energy efficiency declines, the upper limit of the heating demand range is lowered to suppress energy waste caused by excessive heating; when the heat storage device operates frequently but does not significantly improve room temperature stability, the lower limit of the heating demand range is raised to reduce system disturbances caused by frequent heat charging and discharging, thereby forming an adaptive balance between heating intensity and heat buffering capacity; at the same time, when the heating quality continues to meet the standards but energy efficiency improvement is insufficient, the weight allocation of server load rate and cooling return water temperature is dynamically adjusted to guide the system to prioritize the use of high-grade waste heat and weaken the impact of inefficient heat exchange links, so that the heating control strategy evolves synchronously with the system heat source structure and load status, achieving optimal synergy between heating stability, heat storage efficiency, and overall energy efficiency, and ultimately achieving the goal of adaptive regulation of the heating process and comprehensive energy efficiency improvement.

[0048] Furthermore, by dynamically coupling and modeling the waste heat characteristics of data center cooling with the heating demand of the building complex, and constructing a waste heat recovery capacity index using server load rate and cooling return water temperature, a real-time mapping of waste heat supply levels is achieved. Combined with the heating demand range, the waste heat state interval is determined. Based on this, a state-switching frequency-driven heat release decision mechanism is introduced, enabling the intervention process of the heat storage device and auxiliary heat source to adaptively adjust according to the system's operating status. Simultaneously, the heat release power is adjusted through closed-loop feedback of the supply and return water temperature difference trend, and the waste heat utilization rate, unit heating energy consumption, and heat storage turnover are collaboratively corrected on an operational cycle scale. This allows the heating strategy to continuously evolve with the heat source structure and load fluctuations, thereby effectively improving waste heat utilization efficiency and reducing overall heating energy consumption while ensuring heating stability and indoor thermal comfort, achieving dynamic optimization and control of the heating system. Attached Figure Description

[0049] Figure 1 This is a schematic diagram of the dynamic thermal storage and heating control system based on energy efficiency optimization in this embodiment;

[0050] Figure 2 This is a schematic diagram of the state determination module in this embodiment;

[0051] Figure 3 This is a logic diagram of the operation module in this embodiment;

[0052] Figure 4 This is a flowchart of the dynamic thermal storage and heating regulation method based on energy efficiency optimization in this embodiment. Detailed Implementation

[0053] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0054] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0055] Please see Figure 1 As shown, this is a schematic diagram of the dynamic thermal storage and heating control system based on energy efficiency optimization in this embodiment. On one hand, this embodiment provides a dynamic thermal storage and heating control system based on energy efficiency optimization, including:

[0056] The data acquisition module is used to collect data in real time on the server load rate, cooling return water temperature, heating side supply water temperature, heating side return water temperature, heat storage capacity of the heat storage device operating based on preset charging and discharging power, and average room temperature of the building complex during the operation of the data center's cooling and heating systems.

[0057] The status determination module is connected to the acquisition module and is used to determine the waste heat recovery capacity index based on the server load rate, the cooling return water temperature and the preset index weight, and to determine the waste heat status range based on the comparison result between the waste heat recovery capacity index and the preset heating demand range.

[0058] An operation module, which is connected to a state determination module, is used to perform a heat charging operation or a heat compensation operation based on the state switching characteristics of the waste heat state interval within a preset operation determination time. The heat charging operation includes waste heat charging or combined charging, and the heat compensation includes heat release compensation and / or limiting the intervention ratio of auxiliary heat sources.

[0059] An adjustment module, which is connected to the operation module and the acquisition module respectively, is used to adjust the preset heat charging and discharging power based on the temperature difference between the supply water temperature and the return water temperature on the heating side within a preset observation period after performing a heat charging operation or a heat compensation operation.

[0060] The correction module, which is connected to the adjustment module and the acquisition module respectively, is used to statistically analyze the waste heat utilization rate, unit heating energy consumption and heat storage turnover times within the preset operating cycle after adjusting the charging and discharging heat power. Based on the changing trend of the statistical results and the average room temperature of the building complex, the preset heating demand range and the preset index weights are corrected.

[0061] In this embodiment, any operating state that does not meet any of the above adjustment trigger conditions is considered to be in normal and stable operating condition, and no parameter adjustment operation is performed, maintaining the current operating state unchanged.

[0062] In this embodiment, the data acquisition module is installed in the combined cooling and heating system of the data center and its supporting buildings. It is used for waste heat recovery and heating in the data center. Through unified perception of the operating status of the cooling system, heating system, and heat-consuming end, it realizes real-time mapping of waste heat recovery potential and heating demand. Among them, the server load rate is obtained by the existing server management system or data center infrastructure management system of the data center by statistically analyzing operating parameters such as CPU utilization and power consumption. The cooling return water temperature is collected in real time by temperature sensors arranged on the cooling return water main or the return water side of the heat exchanger. The heating side supply water temperature and heating side return water temperature are obtained by temperature transmitters installed at the supply and return ends of the heating network, respectively. The heat storage capacity of the heat storage device is calculated online based on the temperature, flow rate, and specific heat capacity parameters of the heat storage medium by temperature sensors and flow meters installed at the inlet and outlet of the heat storage device. The average room temperature of the building complex is collected by room temperature sensors distributed in representative rooms of each building and calculated by weighted average. All the above-mentioned sensors, transmitters, and management systems are conventional configurations in this field and can be connected to the controller via wired or wireless communication to complete data collection.

[0063] In this embodiment, the heat charging operation includes waste heat charging and combined charging. Waste heat charging refers to adjusting the opening of the bypass valve of the waste heat recovery heat exchanger and the speed of the circulating pump when there is surplus recoverable waste heat in the data center cooling system and the heating demand of the building complex is low or the heat storage device is in a charging state. This allows the waste heat in the cooling return water to be preferentially transferred to the heat storage device through the heat exchanger, storing the heat in the heat storage medium and thus improving the heat storage level of the heat storage device. Combined charging refers to simultaneously starting an auxiliary heat source to supplement the heating of the heat storage device when the waste heat supply capacity is insufficient to meet the rapid heating demand of the heat storage device, or when the building complex is about to enter a high-load heating period. This is done on the basis of waste heat charging. By coordinating the flow distribution ratio between the waste heat recovery loop and the auxiliary heat source loop, the heat storage device can be rapidly and efficiently charged. Heat compensation includes heat release compensation and limiting the involvement ratio of auxiliary heat sources. Heat release compensation refers to releasing stored heat to the heating side when the waste heat recovery capacity decreases or the instantaneous heating demand of the building complex increases, by opening the heat release circuit of the heat storage device, adjusting the heat exchange capacity of the heat release heat exchanger and the speed of the circulating pump, so as to make up for the insufficient real-time heating capacity. Limiting the involvement ratio of auxiliary heat sources refers to setting an upper limit on the output power or heating flow rate of auxiliary heat sources during the process of starting auxiliary heat sources to participate in heat compensation, so that their maximum heating ratio does not exceed the preset auxiliary ratio. In this way, while ensuring the stability of heating, waste heat and stored heat energy are used first, reducing the dependence on high-energy-consuming auxiliary heat sources.

[0064] In this embodiment, the correction module performs statistical analysis on system operation data within a preset operating cycle to obtain three evaluation indicators: waste heat utilization rate, unit heating energy consumption, and heat storage turnover rate. The waste heat utilization rate characterizes the actual utilization level of recoverable waste heat in the data center. Its statistical method is as follows: within the preset operating cycle, the waste heat power Qrec(t) transferred to the heating system and heat storage device via the waste heat recovery heat exchanger is collected in real time, and the cumulative recovered waste heat Erec is obtained by time integration. Simultaneously, the theoretical maximum recoverable waste heat power Qmax(t) provided by the cooling system is collected, and the theoretical total recoverable waste heat Emax is obtained by time integration. The waste heat utilization rate Rrec is then defined as Rrec = Erec / Emax, reflecting the comprehensive utilization efficiency of the waste heat recovery system. The unit heating energy consumption characterizes the energy utilization level of the system's heating process. Its statistical method is as follows: within the preset operating cycle, the auxiliary heat source and electric drive circulation pump... The input energy Ein of energy-consuming equipment such as the control system is accumulated and statistically analyzed. At the same time, the effective heat output Eheat to the building complex is integrally calculated, and the unit heat supply energy consumption V is defined as V=Ein / Eheat to measure the input energy level consumed per unit of heat supply. The heat storage turnover rate is used to characterize the heat storage device's charging and discharging activity level within the statistical period. The statistical method is as follows: within the preset operating period, the cumulative total heat charge Ech and the cumulative total heat release Edis of the heat storage device are recorded. Using the rated effective heat storage capacity Esto of the heat storage device as a benchmark, the heat storage turnover rate N is defined as N=min(Ech, Edis) / Esto to reflect the equivalent complete heat charge and discharge cycle number of the heat storage device, thereby comprehensively evaluating the dynamic participation level of the heat storage system.

[0065] The preset heat transfer power is determined based on the rated heat exchange power of the thermal storage device, the system design flow rate, and the allowable temperature rise of the pipeline network. Specifically, this includes: first, obtaining the rated heat exchange power Prated of the thermal storage device, and calculating the theoretical maximum heat exchange capacity of the system under stable operating conditions based on the design flow rates of the primary and secondary sides; second, determining the adjustable power limit under safe operating conditions based on the maximum allowable temperature difference between the supply and return water ΔTmax, the system design flow rate G, and the heat exchange efficiency coefficient η; finally, setting the preset heat transfer power Pset as: Pset = min(k × Prated, ρ × c × G × ΔTmax × η), where ρ is the water density, c is the specific heat capacity of water, and the coefficient k is taken from 0.3 to 1.0, selected according to the system's operational stability requirements. A larger value is used when the system has high thermal inertia and slow load fluctuations, and a smaller value is used when the system load fluctuates frequently or the thermal storage device capacity is small. In this embodiment, k = 0.6 is selected based on the rated power of the thermal storage device and the thermal response characteristics of the pipeline network to balance heat transfer efficiency and system operational safety.

[0066] The preset index weights are used to characterize the relative impact of server load rate and cooling return water temperature on waste heat recovery capability. The determination process includes: collecting server load rate, cooling return water temperature and actual recoverable waste heat power data within a preset operating cycle; fitting a waste heat recovery model through multiple linear regression: Q=a×L+b×Tr+e, where L is the server load rate, Tr is the cooling return water temperature, a (kW / load rate) and b (kW / ℃) are regression coefficients, and e is the regression residual term, used to characterize the unmodeled waste heat deviation caused by factors such as cooling system control strategy fluctuations, environmental disturbances and measurement errors, with a mean of 0; then normalizing each regression coefficient to obtain the index weights wL=|a| / (|a|+|b|) and wT=|b| / (|a|+|b|), thereby determining the server load rate weight wL and the cooling return water temperature weight wT. In this embodiment, regression analysis was performed on historical operating data to obtain corresponding weights of 0.6 and 0.4, so that the waste heat recovery capacity index can truly reflect the actual operating status of the system.

[0067] The preset heating demand range is used to characterize the target heating capacity demand level of a building complex under different environmental conditions. Its determination process includes: First, establishing a heat load calculation model for the building complex based on the heat transfer coefficient of the building envelope, total building area, floor height, orientation, and occupancy density. Then, calculating the theoretical heating load Qd required by the building complex under steady-state conditions based on the outdoor ambient temperature Tout and the target indoor set temperature Tin. The calculation formula is as follows: Where Ki is the comprehensive heat transfer coefficient of the i-th type of building envelope, Ai is the corresponding heat transfer area, and Qint is the internal heat gain generated by personnel, equipment, and lighting, etc.; secondly, the theoretical heating load Qd is normalized according to the rated heating capacity Qmax of the system to obtain the heating demand index D: D=Qd / Qmax, and the range of D values ​​corresponding to the condition that the average room temperature of the building complex is stably in the preset comfortable temperature range [20℃, 22℃] is taken as the preset heating demand range; in this embodiment, according to the thermal parameters of the building complex and the typical winter outdoor temperature conditions in the local area, the corresponding heating demand index D is calculated to be stably distributed between [0.45, 0.70], so the range is set as the preset heating demand range, so that the waste heat recovery capacity index and the actual heating demand are in the same index space, ensuring that the state range determination results are comparable and the project is feasible.

[0068] The preset operation judgment duration is determined based on the system's thermal inertia time constant and load change cycle. Specifically, it includes: calculating the time ts required for the system to reach steady state by step changing the heating power and collecting the supply and return water temperature response curves, and statistically analyzing the main cycle tl of the server load change. Finally, the operation judgment duration Top is set to: Top = max(0.5ts, 0.5tl), and limited to the range of 5 min to 60 min. In this embodiment, the tested system thermal response time is approximately 20 min, and the main cycle of load change is approximately 30 min. Therefore, the preset operation judgment duration is set to 15 min to ensure that the state switching frequency statistics reflect the true trend of the system while avoiding instantaneous disturbances.

[0069] The preset observation duration is determined based on the dynamic response time of the heating system and the heat exchange delay of the heat storage device. Specifically, it includes: continuously collecting the supply and return water temperature change curves after performing the charging or releasing operation, and statistically analyzing the time 'to' required for the temperature difference change rate to stabilize. The observation duration 'Tobs' is set as: 'Tobs = (1.0~1.5) × 'to', and limited to the range of 10 min to 90 min. In this embodiment, the system temperature difference stabilization time is approximately 20 min, so the preset observation duration is set to 30 min to ensure that the evaluation of the control effect is sufficiently representative.

[0070] The preset operating cycle is determined based on the diurnal variation pattern of the building complex's heating load and statistical stability requirements. Specifically, this includes: statistically analyzing the heating load variation curves over multiple consecutive days to determine its main cycle as 24 hours, and using at least one complete main cycle as the operating cycle. Simultaneously, considering data stability requirements, the operating cycle is limited to between 12 hours and 72 hours. In this embodiment, 24 hours is selected as the preset operating cycle to ensure that the statistically obtained waste heat utilization rate, unit heating energy consumption, and heat storage turnover rate can fully reflect the characteristics of typical daily operating conditions.

[0071] By collaboratively modeling multiple parameters such as server load rate, cooling water return temperature, and heating supply and return water temperatures, the system can convert instantaneous surplus heat into manageable heat storage when server load increases and cooling water return temperature rises, indicating an increase in recoverable heat. When load decreases or return water temperature drops, resulting in insufficient recoverable heat, the system releases stored heat and adjusts the proportion of auxiliary heat sources to stabilize the temperature difference between heating supply and return water within the target range. This avoids room temperature deviations and energy efficiency deterioration caused by heat source fluctuations. Simultaneously, closed-loop corrections to the heat release and charge power, heating demand range, and indicator weights allow the system to gradually approach the balance point of minimum energy consumption and optimal thermal comfort during long-term operation. This significantly improves waste heat utilization and reduces unit heating energy consumption while ensuring the thermal comfort of the building complex, effectively solving the problems of insufficient heating stability and low waste heat utilization efficiency caused by asynchronous heating regulation and waste heat recovery responses.

[0072] Please see Figure 2 As shown, this is a schematic diagram of the state determination module in this embodiment. In this embodiment, the state determination module includes:

[0073] The indicator calculation unit is used to perform a fusion calculation based on the server load rate, the cooling water return temperature and the preset indicator weights to determine the waste heat recovery capacity indicator.

[0074] A state interval determination unit, connected to an index calculation unit, is used to determine that the waste heat state interval is an ample interval when the waste heat recovery capacity index is greater than the upper limit of the preset heating demand range, or to determine that the waste heat state interval is an insufficient interval when the waste heat recovery capacity index is less than the lower limit of the preset heating demand range, or to determine that the waste heat state interval is a balanced interval when the waste heat recovery capacity index is within the preset heating demand range.

[0075] In this embodiment, during the fusion calculation based on the server load rate, the cooling water return temperature, and preset index weights, the server load rate and cooling water return temperature are first normalized to their maximum and minimum values: Ln = (L - Lmin) / (Lmax - Lmin), Trn = (Tr - Trmin) / (Trmax - Trmin), where Lmax and Lmin are the maximum and minimum values ​​of the server load rate within a preset operating period, and Trmax and Trmin are the maximum and minimum values ​​of the cooling water return temperature, respectively. Subsequently, a weighted summation calculation is performed based on the preset index weights to obtain the waste heat recovery capacity index.

[0076] By weighted and fused calculations of server load rate and cooling return water temperature, a waste heat recovery capacity index is constructed. This allows the calculation results to simultaneously reflect the comprehensive changes in the heat generation intensity on the heat source side and the heat absorption capacity on the heat exchange side. The server load rate directly represents the heat generation level per unit time, while the cooling return water temperature reflects the energy level state of the system after absorbing and carrying heat. The joint calculation of the two can dynamically characterize the availability of waste heat resources. Furthermore, by comparing the waste heat status with the preset heating demand range, a continuous hierarchical judgment from insufficient to balanced to abundant is achieved. This transforms the heating regulation logic from a single threshold trigger to interval-based and hierarchical decision-making, thereby achieving a more stable, precise, and predictable adjustment effect under different operating conditions and avoiding frequent switching and adjustment lag issues.

[0077] Please see Figure 3 As shown, this is a decision logic diagram of the operation module in this embodiment. In this embodiment, the operation module includes:

[0078] The switching statistics unit is used to count the frequency of switching from the ample interval to the balanced interval or the insufficient interval based on the preset operation determination duration, denoted as the first switching frequency, and to count the frequency of switching from the insufficient interval to the balanced interval or the ample interval, denoted as the second switching frequency.

[0079] An operation unit, connected to a switching statistics unit, is used to perform the heating operation or the heat compensation operation based on the threshold comparison results of the first switching frequency and the second switching frequency and the residual heat state range.

[0080] Specifically, the operation unit includes:

[0081] The first heat charging subunit is used to perform the waste heat charging when the first switching frequency is less than the preset first switching threshold and the current waste heat state interval is the ample interval.

[0082] The second heat charging subunit is used to perform the combined heat charging when the first switching frequency is greater than or equal to a preset first switching threshold and the current residual heat state interval is the ample interval.

[0083] A preset first switching threshold is used to characterize the critical frequency at which the waste heat state transitions from stable to fluctuating. Its value is determined jointly based on the system's thermal inertia characteristics, the server load change rate, and the dynamic response of the thermal storage device. Specifically, during the commissioning phase, under different server load conditions, the state sequence of the waste heat state interval over time is continuously collected. The number of times the system switches from the sufficient interval to the balanced or insufficient interval within a unit operation judgment time is counted, and the stability index of the thermal storage device's charging power under the corresponding conditions is recorded simultaneously. The maximum switching frequency value is selected based on the relative fluctuation amplitude of the charging power not exceeding a preset stability threshold (±5% in this embodiment), and this maximum switching frequency value is set as the preset first switching threshold. Furthermore, considering the adaptability to systems of different scales, the first switching threshold is limited to the range of 0.05 to 0.30 times / min. A smaller value is used when the system's thermal inertia is large and the load change is slow, while a larger value is used when the server load fluctuates frequently or the thermal storage device capacity is small. In this embodiment, based on the actual operation statistics, the preset first switching threshold is set to 0.12 times / min, so as to suppress power oscillation during the charging process while ensuring efficient utilization of waste heat.

[0084] By statistically analyzing the switching frequency of the waste heat status interval within a preset operation judgment time, and using the first switching frequency from the abundant interval to the balanced or insufficient interval as a characterizing parameter for measuring the stability of waste heat supply, the impact of data center server load fluctuations and changes in the cooling system's heat recovery capacity on the sustainability of waste heat can be reflected: when the first switching frequency is low, it indicates that the waste heat supply level has good continuity and stability in the time dimension, and it is suitable to directly use waste heat for charging to improve the overall energy efficiency of the system; when the first switching frequency is high, it indicates that there are significant fluctuations in waste heat supply, and a single waste heat source is difficult to continuously meet the stable charging requirements of the heat storage device. At this time, by introducing a combined charging method, the fluctuations on the heat source side can be smoothed out while ensuring the heat storage rate, which is conducive to avoiding the adverse effects of frequent start-stop and power oscillation on system operation.

[0085] Specifically, the operation unit further includes:

[0086] The first compensation subunit is used to perform the heat release compensation operation when the second switching frequency is less than the preset second switching threshold and the current waste heat state interval is the insufficient interval.

[0087] The second compensation subunit is used to perform the heat release compensation operation when the second switching frequency is greater than or equal to the preset second switching threshold and the current waste heat state interval is the insufficient interval, and simultaneously start the auxiliary heat source and limit the intervention ratio to not exceed the preset auxiliary ratio.

[0088] The preset second switching threshold is used to characterize the stability criterion during the transition of the waste heat state interval from the insufficient interval to the balanced interval or the sufficient interval. The determination process includes: during the system commissioning phase, under different typical heating load conditions, the change sequence of the waste heat state interval is continuously collected, and the actual frequency of switching from the insufficient interval to the balanced interval or the sufficient interval within the unit operation judgment time is statistically recorded. At the same time, the fluctuation range of the average room temperature of the building group and the stability index of the supply and return water temperature difference on the heating side are recorded simultaneously. The average room temperature of the building group can be stably maintained within the preset comfortable temperature range, and the fluctuation range of the supply and return water temperature difference does not exceed the preset stability threshold is used as the heating stability criterion. The maximum stable switching frequency under the corresponding operating condition is selected as the benchmark value of the preset second switching threshold. Furthermore, in order to take into account the adaptability of data centers and building groups of different sizes, the second switching threshold is limited to the range of 0.05 times / minute to 0.5 times / minute. Among them, when the heat load of the building group changes slowly and the heat storage capacity is large, a larger value is taken, and when the heat load of the building group fluctuates frequently or the heat storage capacity is limited, a smaller value is taken. In this embodiment, through statistical analysis of data under typical winter operating conditions, the second switching threshold is determined to be 0.2 times / minute, so that the system can achieve a good balance between heating stability and thermal storage utilization efficiency.

[0089] The preset auxiliary ratio is used to limit the maximum degree of involvement of auxiliary heat sources in the heating compensation process, so as to avoid weakening the waste heat utilization rate and causing a decrease in system energy efficiency due to excessive involvement of auxiliary heat sources. The determination process includes: during the system commissioning phase, under different building group heating load levels and different waste heat recovery capacity conditions, the heating ratio of auxiliary heat sources is gradually increased, and the changes in the average room temperature of the building group, the temperature difference between the supply and return water on the heating side, the unit heating energy consumption, and the waste heat utilization rate are collected simultaneously. The average room temperature of the building group is stably within the preset comfortable temperature range, the fluctuation range of the supply and return water temperature difference does not exceed the preset stability threshold, and the unit heating energy consumption does not increase significantly as a comprehensive evaluation criterion. The maximum auxiliary heat source involvement ratio that meets the optimal trade-off between heating stability and energy efficiency is determined as the benchmark value of the preset auxiliary ratio. Furthermore, to adapt to different system scales and heat load characteristics, the preset auxiliary ratio is limited to a range of 10% to 40%. A larger value is used when waste heat recovery capacity fluctuates significantly and the heat load of the building complex changes drastically, to enhance heating security; a smaller value is used when waste heat recovery capacity is stable and heat storage capacity is sufficient, to improve the overall waste heat utilization efficiency of the system. In this embodiment, after testing and statistical analysis of typical winter operating conditions, 20% was selected as the preset auxiliary ratio, enabling the system to minimize auxiliary energy consumption while ensuring the thermal comfort of the building complex.

[0090] By introducing a second switching frequency, the dynamic characteristics of the waste heat state transitioning from insufficient to balanced or sufficient are characterized, enabling the system to distinguish between two typical operating conditions: short-term load disturbances and continuous insufficient heating. When the second switching frequency is low, it indicates that the heating gap has transient characteristics, and the heat released by the thermal storage device can achieve load balance under the action of system thermal inertia. Therefore, only heat release compensation is needed to stabilize the temperature field on the heating side. When the second switching frequency is high, it indicates that the heat load of the building complex is continuously higher than the waste heat supply capacity. Relying solely on the thermal storage device is prone to fluctuations in thermal storage depth and continuous deviations in heating temperature. In this case, while performing heat release compensation, a limited proportion of auxiliary heat sources is introduced. This can make up for the long-term heat gap while suppressing the rapid decay of thermal storage, thereby establishing a dynamic balance between heating stability, thermal storage utilization efficiency, and system energy efficiency.

[0091] Specifically, the adjustment module includes:

[0092] The trend analysis unit is used to calculate the standard deviation of the temperature difference between the supply water temperature and the return water temperature on the heating side and the integral of the temperature difference relative to the preset temperature difference threshold within the preset observation period.

[0093] An adjustment unit, connected to a trend analysis unit, is used to adjust the preset charge / discharge heat power based on the threshold comparison results of the deviation integral and the standard deviation.

[0094] Specifically, the adjustment unit includes:

[0095] The first down-adjustment subunit is used to determine that there is a continuous thermal imbalance when the integral amount of the deviation is greater than the preset integral stability threshold, and to reduce the preset charge and discharge heat power by a preset first down-adjustment magnitude.

[0096] The second down-adjustment subunit is used to determine the presence of high-frequency disturbance when the integral of the deviation is less than or equal to a preset integral stability threshold and the standard deviation is greater than a preset fluctuation threshold, and to down-adjust the preset charge / discharge heat power by a preset second down-adjustment magnitude.

[0097] A preset integral stability threshold is used to determine whether the heating system is in a state of continuous thermal imbalance. It depends on the thermal inertia characteristics of the building complex, the heating system's adjustment response capability, and the allowable deviation range of room temperature, and is typically set between 10 and 60 °C·min. In this embodiment, based on the dynamic response characteristics of the building complex's heating system and the requirements for indoor thermal comfort control, the preset integral stability threshold is set to 30 °C·min to ensure heating stability while avoiding excessive sensitivity to instantaneous fluctuations.

[0098] The preset first reduction range is used to adjust the reduction intensity of the charging and discharging heat power when a persistent thermal imbalance is determined. It depends on the rated power of the thermal storage device, the thermal response speed of the pipeline network, and the system's safety margin, and is typically set between 5% and 20% of the rated charging and discharging heat power. In this embodiment, based on the capacity of the thermal storage device and the stability requirements of the heating system, the first reduction range is set to 10% to balance adjustment efficiency and system operational safety.

[0099] A preset fluctuation threshold is used to determine whether there are significant high-frequency disturbances in the supply and return water temperature difference. It depends on the control accuracy of the heating system, the dynamic characteristics of the heat exchange equipment, and the hydraulic stability of the pipeline network, and is typically set between 0.5 and 2.0 ℃. In this embodiment, based on statistical analysis of the heat exchange station's operating data, the preset fluctuation threshold is set to 1.0 ℃ to accurately identify short-period disturbances affecting heating stability.

[0100] The preset second reduction range is used to adjust the reduction intensity of the charging and discharging heat power when high-frequency disturbances are detected. It depends on the system's transient adjustment capability and the sensitivity requirements for suppressing power fluctuations, and is typically set between 2% and 10% of the rated charging and discharging heat power, and is less than the first reduction range. In this embodiment, the second reduction range is set to 5% to effectively suppress power oscillations while avoiding a significant impact on the overall heating capacity of the system.

[0101] Specifically, the adjustment unit further includes:

[0102] An adjustment unit is used to increase the preset charge / discharge heat power by a preset adjustment amount when the integral of the deviation is less than or equal to the preset integral stability threshold and the standard deviation is less than or equal to the preset fluctuation threshold.

[0103] The preset upward adjustment range is used to characterize the incremental adjustment intensity of the preset charging and discharging heat power under the condition that the system is operating stably and the temperature difference fluctuation on the heating side is small. Its value is determined jointly based on the system's thermal inertia characteristics, the rated power of the heat storage device, and the network regulation sensitivity. Specifically, it includes: under the steady-state operation of the system, by increasing the charging and discharging heat power in a step-like manner and collecting the supply and return water temperature difference response curves, calculating the time required for the temperature difference to reach a new steady state and the overshoot range, and using the maximum power increment whose temperature difference overshoot does not exceed the preset temperature difference threshold as the safe adjustment upper limit; normalizing this safe upper limit with the rated power Prated of the heat storage device to obtain the upward adjustment ratio α, whose value ranges from 2% to 10%; in this embodiment, based on the system thermal inertia test results and the network regulation stability requirements, α=5% is selected, that is, the preset upward adjustment range is set to 0.05×Prated, thereby improving the waste heat utilization efficiency and accelerating the energy turnover of the heat storage device while ensuring the stable operation of the heating system.

[0104] By jointly analyzing the standard deviation and integral of the temperature difference between the supply and return water on the heating side within a preset observation period, the transient fluctuation characteristics and cumulative thermal deviation level of the system's heating status can be simultaneously characterized. The integral of the deviation reflects the degree of long-term energy supply and demand imbalance in the heating system, while the standard deviation characterizes the intensity of short-term disturbances. When the integral of the deviation is large, the corresponding building complex is continuously in a state of insufficient or excessive heating. Reducing the charging and releasing power can effectively suppress energy overshoot and promote the system's return to thermal balance. When the standard deviation is large and the integral of the deviation is within a stable range, it indicates that the system is significantly affected by transient disturbances. Slightly reducing the power can weaken high-frequency oscillations and improve operational stability. When both are at low levels, it indicates that the system's heat exchange process is stable and the supply and demand matching degree is high. At this time, appropriately increasing the charging and releasing power can improve the level of waste heat utilization and accelerate the turnover of the thermal storage device, thereby achieving continuous improvement in energy efficiency while ensuring heating stability.

[0105] Specifically, the correction module includes:

[0106] The correction statistics unit is used to calculate the waste heat utilization rate, unit heating energy consumption, and heat storage turnover times within the preset operating cycle.

[0107] The range correction unit, connected to the correction statistics unit, is used to calculate the change rate of waste heat utilization rate and unit heating energy consumption in the current preset operating cycle and the previous preset operating cycle, and to determine whether there is a decrease in energy efficiency based on the calculation results. Based on the energy efficiency decrease determination result, the upper limit of the heating demand range is reduced by a preset first correction step size. The unit also calculates the average value of the number of times the heat storage turnover is in the current preset operating cycle, and counts the total number of times the average room temperature of the building complex is continuously less than a preset room temperature threshold. When the average value is greater than a preset mean threshold and the total number of times is greater than a preset total number threshold, it is determined that the frequent operation of the heat storage device has not improved the heating stability, and the lower limit of the heating demand range is increased by a preset second correction step size.

[0108] A weight correction unit, connected to the range correction unit, is used to determine that energy efficiency has not met expectations while ensuring heating quality when the total duration during which the average room temperature of the building complex is greater than the preset room temperature threshold is greater than the preset operating cycle, and the absolute value of the rate of change of unit heating energy consumption in the energy efficiency decline determination result is less than the preset improvement expectation threshold. The unit then adjusts the weights of the preset indicators according to a preset weight adjustment coefficient. Specifically, it increases the weight value corresponding to the server load rate based on the preset weight adjustment coefficient and decreases the weight value corresponding to the cooling water return temperature by an equal amount.

[0109] In this embodiment, the range correction unit is used to calculate the rate of change of waste heat utilization rate and unit heating energy consumption in the current preset operating cycle and the previous preset operating cycle, so as to obtain the waste heat utilization change degree and energy consumption change degree. When the sign of the waste heat utilization change degree is negative and its absolute value is greater than the preset first sensitive threshold, and the sign of the energy consumption change degree is negative and its absolute value is greater than the preset second sensitive threshold, it is determined that energy efficiency has decreased.

[0110] The preset first correction step size characterizes the magnitude of a single adjustment to lower the upper limit of the heating demand range when an energy efficiency decline is detected. Its value comprehensively considers system thermal inertia, pipeline network response time, and the heat release capacity of the thermal storage device. This ensures that the heating power adjustment process can quickly suppress the growth of ineffective energy consumption while avoiding drastic temperature fluctuations on the heating side due to excessively rapid adjustments. Thus, it gradually compresses the excessively high heating demand range while ensuring heating stability. If the correction step size is too large, it can easily lead to drastic fluctuations in the supply and return water temperatures, resulting in hydraulic instability in the pipeline network and a decrease in end-point heating comfort. If the step size is too small, it is difficult to suppress the continuously increasing ineffective heating power in a timely manner, leading to a cumulative increase in energy consumption. Therefore, the first correction step size is limited to the range of 2% to 8%, with a typical value of 5% in this embodiment, enabling the system to achieve rapid convergence of excessively high heating power while ensuring adjustment stability.

[0111] The preset correction judgment count is used to characterize the minimum number of judgments required for continuous observation and statistical analysis of the average room temperature of the building complex before implementing heating demand range correction. Its value comprehensively considers the thermal inertia of the building envelope, the response delay of the indoor thermal environment, and the impact of short-term environmental disturbances on the room temperature measurement results. This ensures that the correction triggering logic can accurately reflect the heating deviation trend at the system level, rather than transient random fluctuations. If the judgment count is too small, it is easily affected by short-term disturbances such as window opening, personnel activity, and local ventilation, leading to misjudgments of the heating status and frequent corrections of heating power, reducing system stability. If the judgment count is too large, it will delay the identification of insufficient or excessive heating, resulting in control lag and causing the room temperature to deviate from the target range for too long. Therefore, the correction judgment count is limited to the range of 3 to 10 times. In this embodiment, a typical value of 5 times is used, enabling the system to quickly identify continuous heating deviations while suppressing short-term disturbances.

[0112] A preset room temperature threshold serves as a lower limit reference standard for characterizing the heating comfort of a building complex. Its value is determined by comprehensively considering human thermal comfort models, heating design specifications, and energy-saving operation requirements. This ensures that room temperature evaluation guarantees basic thermal comfort needs while avoiding energy waste due to excessive heating. If the room temperature threshold is set too low, although heating energy consumption can be reduced, it can easily lead to a decrease in user thermal comfort and even the risk of complaints. If it is set too high, it will significantly increase the heating load, causing the system to operate in a high-energy-consumption state for a long time, reducing the overall energy efficiency level. Therefore, the room temperature threshold is limited to the range of 18℃ to 22℃. In this embodiment, a typical value of 20℃ is used, enabling the heating system to achieve a coordinated balance between heating quality and energy-saving operation while meeting human thermal comfort requirements.

[0113] A preset average threshold is used to characterize the abnormal judgment standard of the number of times the thermal storage device turns over within a unit operating cycle. Its value comprehensively considers the thermal capacity characteristics, heat exchange efficiency, and system heat load change rate of the thermal storage device, so that the frequency of thermal storage operation can objectively reflect the system's heating regulation pressure level. If the average threshold is set too low, the regulation behavior under normal operating conditions may be misjudged as abnormal, leading to frequent increases in the lower limit of the heating demand range and increased energy consumption. If it is set too high, it will delay the identification of the high-frequency operating state of the thermal storage device, causing the system to operate under long-term high load conditions and shortening the life of the thermal storage equipment. Therefore, the average threshold is limited to the range of 2 times / cycle to 6 times / cycle. In this embodiment, the typical value is 4 times / cycle, so that the system can accurately distinguish between normal regulation and abnormal high-frequency compensation states, thereby providing a reliable basis for heating capacity correction.

[0114] The preset total number of times threshold is used to characterize the lower limit of the cumulative number of times the average room temperature of the building complex is continuously lower than the preset room temperature threshold. Its value takes into account the thermal inertia of the building complex, the cycle of outdoor temperature change, and the adjustment lag characteristics of the heating system, so that the determination of insufficient heating capacity is based on a continuous low temperature trend, rather than occasional short-term fluctuations. If the total number of times threshold is set too low, it is easy to trigger the expansion of heating capacity due to a sudden drop in temperature or local load fluctuations, resulting in over-adjustment of the system; if it is set too high, it will delay the correction of the insufficient heating state, leaving the building complex in the low comfort range for a long time. Therefore, the total number of times threshold is limited to the range of 3 to 8 times. In this embodiment, a typical value of 5 times is used, so that the system can achieve timely correction of the continuous insufficient heating state while ensuring room temperature stability.

[0115] The preset second correction step size characterizes the magnitude of a single upward adjustment of the lower limit of the heating demand range when the thermal storage device is determined to operate frequently without improving heating stability. Its value comprehensively considers the maximum output capacity of the heat source, the pipeline transmission capacity, and the overall heat load elasticity of the building complex, ensuring that the heating capacity improvement process has sufficient compensation strength while avoiding system overshoot. If the second correction step size is too small, it will be difficult to compensate for systemic heating insufficiency in a timely manner, resulting in persistently low room temperature; if the step size is too large, it will easily cause a rapid increase in the supply water temperature, leading to an enhanced thermal shock effect and increased instantaneous energy consumption. Therefore, the second correction step size is limited to the range of 3% to 10%, with a typical value of 6% in this embodiment, enabling the system to quickly repair insufficient heating capacity while ensuring adjustment stability.

[0116] The preset improvement expectation threshold is used to characterize the minimum expected level of reduction in unit heating energy consumption under the premise of meeting heating quality standards. Its value comprehensively considers system control accuracy, building group heat load fluctuation range, and energy-saving operation targets, making energy efficiency optimization evaluation practically operable. If the improvement expectation threshold is set too high, the system will struggle to meet the judgment conditions, causing the weight correction logic to fail to trigger for extended periods, leading to a rigid energy efficiency optimization strategy. If it is set too low, frequent weight adjustments will be triggered, causing the indicator weight structure to fluctuate too rapidly, reducing the overall stability of the system. Therefore, the improvement expectation threshold is limited to the range of 2% to 6%, with a typical value of 4% in this embodiment, enabling the system to effectively identify insufficient energy efficiency optimization while ensuring heating quality.

[0117] By statistically analyzing and dynamically comparing waste heat utilization rate, unit heating energy consumption, and thermal storage turnover rate within a preset operating cycle, the system achieves an adaptive balance between heating intensity and heat buffering capacity. Specifically, when energy efficiency declines, the upper limit of heating demand range is lowered to suppress energy waste caused by excessive heating. When the thermal storage device operates frequently but fails to significantly improve room temperature stability, the lower limit of heating demand range is raised to reduce system disturbances caused by frequent heat charging and discharging. Simultaneously, when heating quality consistently meets standards but energy efficiency improvement is insufficient, the weighting of server load rate and cooling return water temperature is dynamically adjusted to guide the system to prioritize the use of high-grade waste heat and reduce the impact of inefficient heat exchange links. This allows the heating control strategy to evolve synchronously with the system's heat source structure and load status, achieving optimal synergy between heating stability, thermal storage efficiency, and overall energy efficiency. Ultimately, this achieves the goal of adaptive regulation of the heating process and comprehensive energy efficiency improvement.

[0118] Please see Figure 4 As shown, this is a flowchart of the dynamic thermal storage and heating regulation method based on energy efficiency optimization in this embodiment. Furthermore, this embodiment also provides a dynamic thermal storage and heating regulation method based on energy efficiency optimization, including:

[0119] Real-time data collection of server load rate, cooling return water temperature, heating side supply water temperature, heating side return water temperature, heat storage capacity of heat storage devices operating based on preset charging and discharging power, and average room temperature of the building complex during the operation of the data center's cooling and heating systems.

[0120] The waste heat recovery capacity index is determined based on the server load rate, the cooling water return temperature, and the preset index weights. The waste heat status range is determined based on the comparison between the waste heat recovery capacity index and the preset heating demand range.

[0121] Based on the state switching characteristics of the waste heat state interval within the preset operation judgment time, a heat charging operation or a heat compensation operation is performed. The heat charging operation includes waste heat charging or combined heating, and the heat compensation includes heat release compensation and / or limiting the intervention ratio of auxiliary heat sources.

[0122] The preset heat charging and discharging power is adjusted based on the changing trend of the temperature difference between the supply water temperature and the return water temperature on the heating side within a preset observation period after the heat charging or heat compensation operation.

[0123] After statistically adjusting the heat charge and discharge power, the waste heat utilization rate, unit heating energy consumption, and heat storage turnover times within the preset operating cycle are calculated. Based on the changing trend of the statistical results and the average room temperature of the building complex, the preset heating demand range and the preset index weights are adjusted.

[0124] By dynamically coupling and modeling the waste heat characteristics of data center cooling with the heating demand of building complexes, and constructing a waste heat recovery capacity index using server load rate and cooling return water temperature, a real-time mapping of waste heat supply levels is achieved. Combined with the heating demand range, the waste heat state interval is determined. Based on this, a state-switching frequency-driven heat release decision mechanism is introduced, enabling the intervention process of the thermal storage device and auxiliary heat source to adaptively adjust according to the system's operating status. Simultaneously, the heat release power is adjusted through closed-loop feedback of the supply and return water temperature difference trend, and the waste heat utilization rate, unit heating energy consumption, and thermal storage turnover are collaboratively corrected on an operational cycle scale. This allows the heating strategy to continuously evolve with the heat source structure and load fluctuations, thereby effectively improving waste heat utilization efficiency and reducing overall heating energy consumption while ensuring heating stability and indoor thermal comfort, achieving dynamic optimization and control of the heating system.

[0125] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A dynamic heat storage and supply system based on energy efficiency optimization, characterized in that, include: The data acquisition module is used to collect data in real time on the server load rate, cooling return water temperature, heating side supply water temperature, heating side return water temperature, heat storage capacity of the heat storage device operating based on preset charging and discharging power, and average room temperature of the building complex during the operation of the data center's cooling and heating systems. The status determination module is used to determine the waste heat recovery capacity index based on the server load rate, the cooling return water temperature and the preset index weight, and to determine the waste heat status range based on the comparison result between the waste heat recovery capacity index and the preset heating demand range. The operation module is used to perform a heat charging operation or a heat compensation operation based on the state switching characteristics of the waste heat state interval within a preset operation judgment time. The heat charging operation includes waste heat charging or combined heating, and the heat compensation includes heat release compensation and / or limiting the intervention ratio of auxiliary heat sources. The adjustment module is used to adjust the preset heat charging and discharging power based on the temperature difference between the supply water temperature and the return water temperature on the heating side within a preset observation period after the heat charging operation or heat compensation operation. The correction module is used to statistically analyze the waste heat utilization rate, unit heating energy consumption, and heat storage turnover rate within a preset operating cycle after adjusting the heat charging and discharging power. Based on the trend of the statistical results and the average room temperature of the building complex, the module corrects the preset heating demand range and the preset index weights.

2. The dynamic thermal storage and heating control system based on energy efficiency optimization according to claim 1, characterized in that, The status determination module includes: The indicator calculation unit is used to perform a fusion calculation based on the server load rate, the cooling water return temperature and the preset indicator weights to determine the waste heat recovery capacity indicator. The state interval determination unit is used to determine that the waste heat state interval is an ample interval when the waste heat recovery capacity index is greater than the upper limit of the preset heating demand range, or to determine that the waste heat state interval is an insufficient interval when the waste heat recovery capacity index is less than the lower limit of the preset heating demand range, or to determine that the waste heat state interval is a balanced interval when the waste heat recovery capacity index is within the preset heating demand range.

3. The dynamic thermal storage and heating control system based on energy efficiency optimization according to claim 2, characterized in that, The operation module includes: The switching statistics unit is used to count the frequency of switching from the ample interval to the balanced interval or the insufficient interval based on the preset operation determination duration, denoted as the first switching frequency, and to count the frequency of switching from the insufficient interval to the balanced interval or the ample interval, denoted as the second switching frequency. An operation unit is used to perform the heating operation or the heat compensation operation based on the threshold comparison results of the first switching frequency and the second switching frequency and the residual heat state range.

4. The dynamic thermal storage and heating control system based on energy efficiency optimization according to claim 3, characterized in that, The operation unit includes: The first heat charging subunit is used to perform the waste heat charging when the first switching frequency is less than the preset first switching threshold and the current waste heat state interval is the ample interval. The second heat charging subunit is used to perform the combined heat charging when the first switching frequency is greater than or equal to a preset first switching threshold and the current residual heat state interval is the ample interval.

5. The dynamic thermal storage and heating control system based on energy efficiency optimization according to claim 4, characterized in that, The operation unit further includes: The first compensation subunit is used to perform the heat release compensation operation when the second switching frequency is less than the preset second switching threshold and the current waste heat state interval is the insufficient interval. The second compensation subunit is used to perform the heat release compensation operation when the second switching frequency is greater than or equal to the preset second switching threshold and the current waste heat state interval is the insufficient interval, and simultaneously start the auxiliary heat source and limit the intervention ratio to not exceed the preset auxiliary ratio.

6. The dynamic thermal storage and heating control system based on energy efficiency optimization according to claim 5, characterized in that, The adjustment module includes: The trend analysis unit is used to calculate the standard deviation of the temperature difference between the supply water temperature and the return water temperature on the heating side and the integral of the temperature difference relative to the preset temperature difference threshold within the preset observation period. An adjustment unit is used to adjust the preset charge / discharge heat power based on the threshold comparison results of the deviation integral and the standard deviation.

7. The dynamic thermal storage and heating control system based on energy efficiency optimization according to claim 6, characterized in that, The adjustment unit includes: The first down-adjustment subunit is used to determine that there is a continuous thermal imbalance when the integral amount of the deviation is greater than the preset integral stability threshold, and to reduce the preset charge and discharge heat power by a preset first down-adjustment magnitude. The second down-adjustment subunit is used to determine the presence of high-frequency disturbance when the integral of the deviation is less than or equal to a preset integral stability threshold and the standard deviation is greater than a preset fluctuation threshold, and to down-adjust the preset charge / discharge heat power by a preset second down-adjustment magnitude.

8. The dynamic thermal storage and heating control system based on energy efficiency optimization according to claim 7, characterized in that, The adjustment unit further includes: An adjustment unit is used to increase the preset charge / discharge heat power by a preset adjustment amount when the integral of the deviation is less than or equal to the preset integral stability threshold and the standard deviation is less than or equal to the preset fluctuation threshold.

9. The dynamic thermal storage and heating control system based on energy efficiency optimization according to claim 8, characterized in that, The correction module includes: The correction statistics unit is used to calculate the waste heat utilization rate, unit heating energy consumption, and heat storage turnover times within the preset operating cycle. The range correction unit is used to calculate the change rate of waste heat utilization rate and unit heating energy consumption in the current preset operating cycle and the previous preset operating cycle, and to determine whether there is a decrease in energy efficiency based on the calculation results. Based on the energy efficiency decrease determination result, the upper limit of the heating demand range is reduced by a preset first correction step size. It also calculates the average value of the number of times the heat storage turnover is in the current preset operating cycle, and counts the total number of times the average room temperature of the building complex is continuously less than a preset room temperature threshold. When the average value is greater than a preset mean threshold and the total number is greater than a preset total number threshold, the lower limit of the heating demand range is increased by a preset second correction step size. The weight correction unit is used to adjust the weight of the preset index according to the preset weight adjustment coefficient when the total duration during which the average room temperature of the building complex is greater than the preset room temperature threshold is greater than the preset operating cycle, and the absolute value of the change rate of unit heating energy consumption in the energy efficiency decline determination result is less than the preset improvement expectation threshold.

10. A dynamic thermal energy storage and heating control method based on energy efficiency optimization, applied to the dynamic thermal energy storage and heating control system based on energy efficiency optimization as described in any one of claims 1-9, characterized in that, include: Real-time data collection of server load rate, cooling return water temperature, heating side supply water temperature, heating side return water temperature, heat storage capacity of heat storage devices operating based on preset charging and discharging power, and average room temperature of the building complex during the operation of the data center's cooling and heating systems. The waste heat recovery capacity index is determined based on the server load rate, the cooling water return temperature, and the preset index weights. The waste heat status range is determined based on the comparison between the waste heat recovery capacity index and the preset heating demand range. Based on the state switching characteristics of the waste heat state interval within the preset operation judgment time, a heat charging operation or a heat compensation operation is performed. The heat charging operation includes waste heat charging or combined heating, and the heat compensation includes heat release compensation and / or limiting the intervention ratio of auxiliary heat sources. The preset heat charging and discharging power is adjusted based on the changing trend of the temperature difference between the supply water temperature and the return water temperature on the heating side within a preset observation period after the heat charging or heat compensation operation. After statistically adjusting the heat charge and discharge power, the waste heat utilization rate, unit heating energy consumption, and heat storage turnover times within the preset operating cycle are calculated. Based on the changing trend of the statistical results and the average room temperature of the building complex, the preset heating demand range and the preset index weights are adjusted.

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