Control method of heat storage type enclosure and heat storage type enclosure

Abstract

This invention provides a control method for a thermal storage enclosure structure and the thermal storage enclosure structure itself. The control method first obtains initial control weight curves for multiple control objectives of the thermal storage enclosure structure. Then, according to a preset adjustment step size, the initial control weight curves are gradually corrected based on the operational performance of the thermal storage enclosure structure, resulting in corrected weight curves for the multiple control objectives. Next, based on the real-time operating state parameters of the thermal storage enclosure structure and a predictive model, the operational optimization function of the thermal storage enclosure structure is solved to obtain the control quantity of the thermal storage enclosure structure. Finally, the thermal storage enclosure structure is controlled to execute control actions corresponding to the control quantity. This control method for the thermal storage enclosure structure, through multi-objective weight adaptive correction and model predictive optimization, can closely meet the actual user needs, accurately and stably maintain indoor comfort, minimize room temperature fluctuations, provide more timely responses, and consistently remain within the comfortable range.

Description

Technical Field

[0001] This invention relates to the field of thermal storage enclosure technology, and in particular to a control method for a thermal storage enclosure structure and a thermal storage enclosure structure. Background Technology

[0002] With the increasing demands for building energy conservation and thermal comfort, thermal storage building envelopes have become an important development direction in the field of low-energy buildings. Especially in extreme climates such as hot and dry, and cold regions, the use of phase change materials, heat pipes, and other components in conjunction with the building envelope to store and transfer solar energy and waste heat can effectively reduce building heating and cooling energy consumption. This approach aligns with the energy conservation requirements of buildings under the dual-carbon development goals. Currently, thermal storage building envelopes have evolved from a single phase change thermal storage layer design to an integrated approach encompassing "thermal storage, thermal conduction, and temperature control." The integrated application of adjustable thermally conductive components and intelligent temperature control systems has become a core research and development direction for improving the thermal storage utilization efficiency of building envelopes.

[0003] Existing control methods for thermal storage building envelopes mainly rely on simple on / off control and constant temperature control. Some studies have introduced predictive control and weighted regulation, adjusting the thermal conductivity of the building envelope by collecting meteorological and indoor temperature data, attempting to balance thermal storage, energy saving, and thermal comfort goals. However, these technologies still have several limitations.

[0004] On the one hand, existing control methods for thermal storage envelopes generate control commands based on a single temperature threshold or fixed weights. Some schemes adjust temperature control strategies in conjunction with short-term weather forecasts, attempting to achieve dynamic regulation of heat transfer within the envelope. However, these control methods lack hierarchical design, and the generated strategies are easily detached from the actual user needs.

[0005] On the other hand, existing control methods for thermal storage enclosure structures mostly involve fixed values ​​or simple linear adjustments in weight regulation, which cannot achieve dynamic adaptive correction of weights based on the operating performance of the enclosure structure, making it difficult to balance energy-saving and thermal comfort requirements at different times. Summary of the Invention

[0006] One object of the present invention is to overcome at least one defect in the prior art and to provide a control method for a thermal storage enclosure structure and a thermal storage enclosure structure.

[0007] A further object of the present invention is to adjust the operation of the thermal storage enclosure structure in layers to meet the actual needs of users.

[0008] Another further objective of the present invention is to modify the initial control weight curve to take into account both the energy-saving needs and thermal comfort needs of users at different times.

[0009] In particular, the present invention provides a control method for a thermal storage enclosure structure, characterized by comprising: The initial control weight curves of multiple control objectives for the thermal storage building envelope are obtained. The control objectives include: indoor comfort objective, energy saving objective, and energy utilization rate objective. The initial control weight curves are used to define the changing trend of the weight of each control objective over time. According to the preset adjustment step size, the initial control weight curve is gradually corrected based on the operation effect of the thermal storage enclosure structure to obtain the corrected weight curves of multiple control targets. Based on the real-time operating state parameters and prediction model of the thermal storage enclosure structure, the operation optimization function of the thermal storage enclosure structure is solved to obtain the control quantity of the thermal storage enclosure structure. Control the thermal storage enclosure structure to perform control actions corresponding to the control quantities.

[0010] Optionally, the step of gradually correcting the initial control weight curve according to the operating effect of the thermal storage enclosure structure based on a preset adjustment step size includes: Obtain the correction parameters corresponding to the initial control weight curves of multiple control objectives; The corrected weight curve is calculated based on the corrected parameters; where, The correction parameters corresponding to the initial control weight curve of the indoor comfort target include: the learning coefficient of the comfort weight, the actual comfort default ratio, and the target comfort default ratio; The correction parameters corresponding to the initial control weight curve of the energy-saving target include: the energy-saving weight learning coefficient, the dimensionless value corresponding to the expected energy-saving level, the normalized energy dimension, and the average energy-saving level of the previous period. The correction parameters corresponding to the initial control weight curve of the energy utilization rate target include: the unmanned heat release penalty coefficient and the actual heat release coefficient during the unmanned period of the previous window.

[0011] Optionally, the step of calculating the corrected weight curve based on the corrected parameters includes: The corrected weight curve for the indoor comfort target is calculated based on the corrected parameters; the calculation formula is as follows: ; in, The corrected weighting curve for indoor comfort targets. The initial control weight curve for the indoor comfort target. The learning coefficient for comfort weights. The actual comfort default ratio, The default ratio for target comfort.

[0012] Optionally, the step of calculating the corrected weight curve based on the corrected parameters includes: The corrected weight curve for the energy-saving target is calculated based on the corrected parameters; the calculation formula is as follows: ; in, The corrected weighting curve for energy-saving targets. The initial control weight curve for the energy-saving target. For energy-saving weight learning coefficients, E0 represents the dimensionless value corresponding to the desired energy saving level, and E0 represents the normalized energy dimension. This represents the average energy-saving level for the previous period.

[0013] Optionally, the step of calculating the corrected weight curve based on the corrected parameters includes: The corrected weight curve for the energy utilization rate target is calculated based on the corrected parameters; the calculation formula is as follows: ; in, The corrected weighting curve for the energy utilization efficiency target. The initial control weight curve for the energy utilization rate target. The penalty coefficient for no heat release. This represents the actual heat release coefficient during the previous window's unoccupied period.

[0014] Optionally, the steps for solving the operational optimization function of the thermal storage enclosure structure based on the real-time operational state parameters and prediction model include: Establish a thermal prediction model to predict room temperature. The control parameters for the thermal storage building envelope are calculated using an optimization function based on room temperature; among them... Thermal prediction models include: heat pipe heat conduction model, wall thermal inertia recursive model, and indoor air temperature recursive model; The optimized function is: ; Where J is the optimization objective. The corrected weighting curve for indoor comfort targets. The corrected weighting curve for the energy utilization efficiency target. The corrected weighting curve for energy-saving targets. The indoor thermal comfort temperature deviation is calculated by subtracting the room temperature from the set indoor temperature. The energy consumed in the i-th prediction step to adjust the heat conduction of the heat pipes in the thermal storage building envelope. Let k be the net energy saving level of the i-th prediction step, k be the current control cycle number, and i be the prediction cycle number.

[0015] Optionally, the calculation formula for the heat pipe heat conduction model is: ; in, The effective condensation length for the i-th prediction step. This is the total length of the heat pipe condenser section. This represents the maximum equivalent thermal conductivity of the heat pipe when it participates in condensation along its entire length in the condensing section. Let be the equivalent thermal conductivity of the heat pipe in the i-th prediction step. The temperature of the phase change material near the evaporation section of the heat pipe. Let the temperature of the wall thermal inertia node be the temperature at the i-th prediction step. To control the cycle duration, Let be the amount of heat that the heat pipe can release to the wall in the i-th prediction step. To control the quantity.

[0016] Optionally, the calculation formula for the wall thermal inertia recursive model is as follows: ; in, The equivalent heat capacity of the main body of the building envelope. , These are the thermal inertia nodes of the main body of the enclosure structure for the i-th and i+1-th prediction steps, respectively. Let be the amount of heat that the heat pipe can release to the wall in the i-th prediction step. Let i be the indoor plaster layer temperature in the i-th prediction step. To maintain the equivalent thermal resistance from the structural thermal inertia nodes to the interior surface.

[0017] Optionally, the calculation formula for the indoor air temperature recursive model is as follows: ; in, , These represent the room temperature at the i-th and (i+1)-th prediction steps, respectively. The indoor convective heat transfer coefficient is... The indoor heat exchange area, The temperature of the indoor plaster layer. For indoor heat gain, The mass flow rate of the air exchange. The specific heat of air at constant pressure. This refers to the outdoor air temperature.

[0018] According to another aspect of the present invention, a heat-storing enclosure structure is also provided, comprising: Main body of the enclosure structure; Thermal insulation layer, installed on the outside of the main building envelope; The phase change heat storage layer is set on the outside of the thermal insulation layer. The phase change heat storage layer stores heat through phase change during the day and supplies heat to the indoor side at night. The interior plaster layer is installed on the inside of the main building envelope; The heat pipe extends upwards from the bottom of the phase change heat storage layer to the middle of the phase change heat storage layer. From the middle of the phase change heat storage layer, the heat pipe extends obliquely towards the indoor side to the middle of the main body of the building envelope, near the indoor plaster layer. From the middle of the main body of the building envelope, near the indoor plaster layer, the heat pipe extends upwards to the top of the main body of the building envelope, near the indoor plaster layer. The heat pipe is a gravity heat pipe, which includes: The evaporation section is vertically installed within the phase change heat storage layer; The condensation section is vertically installed within the main enclosure structure; The adiabatic section is inclined and positioned between the evaporation section and the condensation section; A gas storage chamber, located above the condensation section, is used to adjust the condensation effect of the gravity heat pipe; A control device, including a memory, a processor, and a computer program stored in the memory, characterized in that the processor executes the computer program to implement the steps of the control method for the thermal storage enclosure structure described above.

[0019] The control method for a thermal storage enclosure structure provided by this invention obtains initial control weight curves for multiple control objectives of the thermal storage enclosure structure. Then, according to a preset adjustment step size, the initial control weight curves are gradually corrected based on the operational performance of the thermal storage enclosure structure. Finally, based on the real-time operating state parameters and a prediction model of the thermal storage enclosure structure, the operational optimization function of the thermal storage enclosure structure is solved to obtain the control quantity of the thermal storage enclosure structure and control the thermal storage enclosure structure to execute the control action corresponding to the control quantity. The hierarchical design in the control method for the thermal storage enclosure structure provided by this invention allows the system to prioritize indoor comfort while automatically adjusting according to actual operating conditions, meeting user needs for indoor comfort, energy saving, and energy utilization efficiency targets.

[0020] Furthermore, the control method for the thermal storage building envelope provided by this invention calculates a corrected weight curve based on the correction parameters corresponding to the initial control weight curves of multiple control objectives. By utilizing various correction parameters corresponding to the initial weight curves of indoor comfort objectives, energy-saving objectives, and energy utilization efficiency objectives, the control method for the thermal storage building envelope provided by this invention can precisely adjust the initial weight curves to balance the energy-saving and thermal comfort needs of users at different times.

[0021] The above and other objects, advantages and features of the present invention will become more apparent to those skilled in the art from the following detailed description of specific embodiments of the invention in conjunction with the accompanying drawings. Attached Figure Description

[0022] The following sections will describe some specific embodiments of the invention in detail by way of example and not limitation, with reference to the accompanying drawings. The same reference numerals in the drawings denote the same or similar parts or portions. Those skilled in the art should understand that these drawings are not necessarily drawn to scale. In the drawings: Figure 1 This is a schematic diagram of a heat-storing enclosure structure according to an embodiment of the present invention; Figure 2 This is a schematic diagram of a control device according to an embodiment of the present invention; Figure 3 This is a schematic flowchart of a control method for a thermal storage enclosure structure according to an embodiment of the present invention; Figure 4 This is a flowchart illustrating the steps of gradually correcting the initial control weight curve according to the operating effect of the thermal storage enclosure structure based on a preset adjustment step size, according to an embodiment of the present invention. Figure 5 This is a flowchart illustrating the steps of solving the operational optimization function of a thermal storage enclosure structure based on real-time operational state parameters and a prediction model according to an embodiment of the present invention. Detailed Implementation

[0023] This invention provides a heat-storing enclosure structure 10, such as... Figure 1 , Figure 2 As shown, the thermal storage enclosure structure 10 includes: a main enclosure structure 100, a thermal insulation layer 200, a phase change thermal storage layer 300, and an interior plaster layer 400. The thermal insulation layer 200 can be made of rigid polyurethane foam, extruded polystyrene board, or other materials with a thermal conductivity of less than or equal to 0.045 W / (m·K). The thermal insulation layer 200 is located on the outside of the main enclosure structure 100, and the phase change thermal storage layer 300 is located on the outside of the thermal insulation layer 200. The phase change thermal storage layer 300 stores heat during the day through phase change and supplies heat to the interior at night. The phase change heat storage layer 300 of the heat storage type building envelope 10 efficiently absorbs and stores solar energy through phase change, while the thermal insulation layer 200 reduces the meaningless transfer of heat. This not only ensures the heat storage, insulation and load-bearing performance of the building envelope foundation, but also meets the building's needs for daytime energy storage and nighttime heating through the working mode of the phase change heat storage layer 300 storing heat during the day and releasing heat at night. This achieves the combination of building energy conservation and natural energy utilization from the structural level.

[0024] The heat storage type enclosure structure 10 also includes a heat pipe 500. The heat pipe 500 extends upward from the bottom of the phase change heat storage layer 300 to the middle of the phase change heat storage layer 300. The heat pipe 500 extends obliquely from the middle of the phase change heat storage layer 300 towards the indoor side to the middle of the main body of the enclosure structure 100 near the indoor plaster layer 400. The heat pipe 500 extends upward from the middle of the main body of the enclosure structure 100 near the indoor plaster layer 400 to the top of the main body of the enclosure structure 100 near the indoor plaster layer 400.

[0025] The phase change heat storage layer 300 uses a phase change material with a phase change temperature 2-7°C higher than the indoor set temperature in winter. This allows it to undergo phase change heat storage near the room temperature range during the day in winter and supply heat to the indoor side at night or in the evening. The outer surface of the phase change heat storage layer 300 is coated with a selective absorption coating with high absorptivity and low emissivity. Its solar absorptivity is greater than or equal to 0.85, and its far-infrared emissivity is less than or equal to 0.15, in order to improve the absorption of short-wave solar radiation during the day and suppress long-wave radiation heat loss to the sky at night.

[0026] The heat pipe 500 is a gravity heat pipe, comprising an evaporation section 510, a condensation section 520, and an insulation section 530. The evaporation section 510 is vertically installed within the phase change heat storage layer 300, the condensation section 520 is vertically installed within the main enclosure structure 100, and the insulation section 530 is inclinedly installed between the evaporation section 510 and the condensation section 520. The insulation section 530 uses materials with a thermal conductivity of less than 10 W / m². -1 ·K -1 It is made of metallic material and has a double-layer annular vacuum jacket. The inner surface of the jacket is coated with a low emissivity coating and the annular gap is 0.3 to 1.0 mm, which is used to reduce radial heat dissipation and axial parasitic heat conduction.

[0027] In some optional embodiments, a gas storage cavity 540 is further provided at the upper end of the condensation section 520 for storing non-condensable gases within the gravity heat pipe 500. Pressure / temperature changes in the gas storage cavity 540 cause its volume to change; after expansion, the non-condensable gases entering the condensation section 520 occupy the upper space of the condensation section 520, reducing the effective condensation length and thus lowering the equivalent thermal conductivity of the heat pipe. Pressure / temperature changes in the gas storage cavity 540 also cause its volume to change, allowing the non-condensable gases to be recycled back into the gas storage cavity 540, thereby increasing the effective condensation length, improving thermal conductivity, and thus regulating the condensation effect of the gravity heat pipe 500.

[0028] The arrangement of the heat pipe 500, which extends from the bottom of the phase change heat storage layer 300 upwards to the middle, then slopes to the middle of the plaster layer inside the main body of the enclosure structure 100 and extends upwards to the top, allows the evaporation section 510 of the heat pipe 500 to fully cover the core area of ​​the phase change heat storage layer 300, maximizing the absorption of the heat stored in the heat storage layer. At the same time, it allows the condensation section 520 to extend longitudinally along the plaster layer inside the main body of the enclosure structure 100, so that the heat can be evenly transferred to the wall and released into the room, avoiding local overheating.

[0029] The thermal storage enclosure structure 10 also includes a heat-conducting component 700, which is inserted into the phase change thermal storage layer 300 along the height direction of the thermal storage enclosure structure 10. The heat-conducting component 700 can be a high thermal conductivity graphite component or a graphite / metal composite component, and the vertical equivalent thermal conductivity of the heat-conducting component 700 is greater than the radial equivalent thermal conductivity. The vertical / radial thermal conductivity ratio is greater than or equal to 5. Since the evaporation section 510 is arranged in the lower region of the enclosure structure, the upper part of the phase change thermal storage layer 300 is prone to storing more heat due to strong solar radiation and its own low thermal conductivity. In order to avoid the problem of large temperature difference between the upper and lower parts of the phase change thermal storage layer 300 and difficulty in heat transfer in the upper part of the phase change thermal storage layer 300 after the heat pipe is started, the heat-conducting component 700 is set to conduct the heat stored in the upper part to the lower part near the evaporation section 510, thereby improving the overall usability of the phase change thermal storage layer 300.

[0030] In some optional embodiments, the thermal storage enclosure 10 further includes a control device 600, which includes a memory 610, a processor 620, and a computer program 630 stored in the memory 610. The processor 620 executes the computer program 630 to implement a control method for the thermal storage enclosure 10.

[0031] This invention implements a control method for the thermal storage building envelope 10 by executing a computer program 630 through the processor 620 of the control device 600. This allows the thermal storage and heat transfer processes of the building envelope to be dynamically adjusted according to real-time operating status, meteorological conditions, and building usage needs. It precisely controls the heat pipe 500, ensuring a high degree of match between the thermal storage of the phase change thermal storage layer 300, the heat transfer of the heat pipe 500, and the indoor heating demand. This ensures that the control output from the control device guarantees that the effective condensation length within the heat pipe 500 meets the target value. Simultaneously, by combining hardware structure with software control, this invention solves the problems of lag, fixed strategies, and difficulty in simultaneously addressing multiple objectives in traditional thermal storage building envelopes. Ultimately, it achieves synergistic optimization of the building envelope's thermal storage utilization efficiency, building energy efficiency, and indoor thermal comfort.

[0032] In some alternative embodiments, the control device 600 can regulate the temperature within the gas storage chamber 540 by adjusting the heat released from the heater, cooler, or circulating fluid. The control device 600 can also regulate the pressure within the gas storage chamber 540 through valve-controlled connections / bypasses, variable-volume chambers, or other equivalent methods.

[0033] The above-described methods for adjusting the temperature and pressure within the gas storage chamber 540 are merely examples. Those skilled in the art can select appropriate temperature or pressure adjustment methods based on actual usage requirements to meet the control needs of the thermal storage enclosure structure 10.

[0034] This invention also provides a control method for a thermal storage enclosure structure, used to control the thermal storage enclosure structure. For example... Figure 3 As shown, the control method for the thermal storage enclosure structure includes at least the following steps S101 to S104.

[0035] Step S101: Obtain the initial control weight curves for multiple control objectives of the thermal storage building envelope. The initial control weight curves for multiple control objectives, including indoor comfort, energy saving, and energy utilization rate, are obtained, and the curves define the trend of weight changes over time, breaking through the limitations of fixed weights or single-objective priority in traditional control methods. This provides a standardized and adjustable blueprint for subsequent dynamic correction of weights, avoiding the blindness of control strategies without clear initial basis and ensuring the orderly implementation of subsequent control steps.

[0036] In some optional embodiments, the step of obtaining the initial control weight curves of multiple control objectives of the thermal storage enclosure structure can be as follows: first, determine the operating mode of the thermal storage enclosure structure, and then generate weight curves based on the selected operating mode. The operating modes of the thermal storage enclosure structure can include at least a daytime thermal storage-evening thermal release mode, a full-day thermal suppression mode, and an early thermal release-thermal inertia maintenance mode.

[0037] The above-mentioned working modes of thermal storage enclosure structures are just examples. Those skilled in the art can flexibly configure various working modes of thermal storage enclosure structures according to the application scenarios and specific needs of the thermal storage enclosure structures.

[0038] The daytime heat storage-evening heat release mode stores heat through the phase change heat storage layer during the day when solar radiation is sufficient, and releases the accumulated heat at night to regulate the indoor temperature. The all-day heat suppression mode keeps the outdoor high temperatures out throughout the day, keeping the indoor environment cool and reducing the energy consumption of indoor air conditioning. The pre-heat release-thermal inertia maintenance mode releases heat from the heat storage layer before people enter the room, ensuring a stable indoor temperature when people are present.

[0039] In some optional embodiments, the calculation formula for determining the operating mode of the thermal storage enclosure structure can be: ; in, The optimal operating mode selected for the d-th daytime segment. These are the weather characteristics of the day, including solar irradiance, daily maximum / minimum temperature, and relative humidity. This refers to the characteristics of the time of day when the property is occupied, such as people being there in the evening or at noon. This represents the average net energy saving level of the previous period. The ratio of comfort level breach time in the previous period. This is an evaluation function used to comprehensively compare the above factors. This is a set of preset operating modes. This is a function that takes the maximum value among the variables. The evaluation function can be weighted by four factors; for example, the evaluation function could be: ; in, , , , These are the weighting coefficients for the weather characteristics of the day, the occupancy period characteristics of the day, the average net energy saving level of the previous period, and the comfort default time ratio of the previous period, respectively. , , , The sum is 1. Let's take daytime heat storage-evening heat release mode, all-day heat suppression mode, and early heat release-thermal inertia maintenance mode as examples (modes 1, 2, and 3 respectively), assuming... It is 0.35. It is 0.3. It is 0.2. It is 0.15.

[0040] The weather characteristic values ​​for the day are scored based on their compatibility with the design and adaptation scenarios of each model; the closer the match, the higher the score. For example, taking a sunny winter day with solar irradiance ≥800W / ㎡, a daily minimum temperature of -15℃, and a daily maximum temperature of 5℃ as an example, the weather characteristic values ​​for that day score 0.95 in Model 1, 0.1 in Model 2, and 0.7 in Model 3.

[0041] The daily occupancy period characteristics are scored based on the matching degree between the building occupancy characteristics of the day and the heating / storage periods of each mode. The higher the overlap between the heating period and the occupied period, the higher the score. Taking the period from 18:00 to 23:00 as an example, and the rest of the time as unoccupied, the daily occupancy period characteristics score is 0.9 in Mode 1, 0.05 in Mode 2, and 0.85 in Mode 3.

[0042] The average net energy saving level of the previous period can be calculated by normalization based on the energy saving level of the previous stage. The minimum NES range for the building's historical energy saving is -5 kWh / day, and the maximum is 12 kWh / day. The NES(d) of the previous stage is 9.5 kWh / day. The calculation result is (9.5+5) / (12+5) = 14.5 / 17 ≈ 0.85, and this value is shared by all models.

[0043] The comfort default time ratio of the previous period is also a common value for all modes. Taking the comfort default time ratio of the previous period as an example, which is 0.96.

[0044] Substitute the above values ​​into the evaluation function. Mode 1: 1 = 0.35 × 0.95 + 0.3 × 0.9 + 0.2 × 0.85 + 0.15 × 0.96 = 0.9165; Mode 2: 2 = 0.35 × 0.1 + 0.3 × 0.05 + 0.2 × 0.85 + 0.15 × 0.96 = 0.364; Mode 3: 3 = 0.35 × 0.7 + 0.3 × 0.85 + 0.2 × 0.85 + 0.15 × 0.96 = 0.814 Therefore, the maximum value is taken, and the final operating mode is Mode 1, namely, the daytime heat storage and evening heat release mode. The above calculation formula for determining the operating mode and evaluation function of the thermal storage enclosure structure is only an example. Those skilled in the art can choose an appropriate method to determine the operating mode of the thermal storage enclosure structure according to actual needs.

[0045] Step S102 involves progressively correcting the initial control weight curve based on the operational performance of the thermal storage building envelope according to a preset adjustment step size, resulting in corrected weight curves for multiple control targets. By using a preset adjustment step size combined with actual operational performance to progressively correct the initial weight curve, the weight curve is made to closely align with the actual operating conditions of the building, effectively adapting to real-time changes in meteorological conditions, resident usage habits, and the thermal characteristics of the building envelope. This progressive correction of the initial control weight curve resolves the problem of the initial weights being disconnected from actual operation.

[0046] Step S103 involves solving the operational optimization function of the thermal storage building envelope based on real-time operating state parameters and a prediction model, yielding the control quantity for the thermal storage building envelope. Combining real-time operating state parameters ensures the control quantity is based on the actual thermal state of the building envelope, guaranteeing its real-world relevance. Introducing a prediction model overcomes the limitations of traditional passive feedback control, enabling early prediction of subsequent thermal changes in the building envelope and achieving predictive control. This effectively avoids problems such as delayed heat transfer, insufficient thermal storage utilization, and delayed indoor temperature achievement. By solving the operational optimization function, the correction weights of multiple control objectives, real-time status, and prediction results are integrated into the quantitative calculation. This allows the generation of the control quantity to consider the synergistic optimization of comfort, energy saving, and energy utilization efficiency, rather than being driven by a single objective. The final control quantity is the optimal solution under multi-objective balance, ensuring the accuracy of the control.

[0047] In some alternative embodiments, the control quantity can be the temperature and / or pressure within the gas storage chamber where the non-condensable gas is stored. That is, by adjusting the temperature or pressure within the gas storage chamber, the length of the condensation section occupied by the non-condensable gas is changed, thereby altering the effective condensation length and equivalent thermal conductivity of the heat pipe to adjust the condensation effect of the gravity heat pipe.

[0048] Step S104 involves controlling the thermal storage envelope to execute control actions corresponding to the control quantities. Precise matching of these control actions with the optimal control quantities ensures that the heat conduction through the heat pipes and the heat storage and release through the phase change thermal storage layer of the envelope always align with the building's heating needs and meet multi-objective optimization requirements. This maximizes the energy-saving potential of the thermal storage envelope, ensuring indoor thermal comfort while effectively suppressing ineffective heat release and reducing heat pipe regulation energy consumption. Ultimately, this achieves a synergistic improvement in thermal storage utilization efficiency, building energy efficiency, and indoor thermal comfort.

[0049] The control method for thermal storage building envelopes provided by this invention divides the control system into three layers from top to bottom. The upper layer is a long-term strategy learning layer, the middle layer is a weight adaptive layer, and the lower layer is an optimization control layer. The upper layer corresponds to the initial control weight curves of multiple control objectives obtained in step S101, and uses the initial control weight curves to control the basic regulation trend of the thermal storage building envelope. The long-term strategy learning layer can determine the optimal operating mode of the building envelope by combining external factors such as building weather characteristics and occupancy period characteristics, which is the basis for subsequent weight correction and optimization control.

[0050] In step S102 of the middle layer, the initial control weight curve is gradually corrected according to the preset adjustment step size based on the operating effect of the thermal storage envelope. The weight adaptive layer is based on the initial control weight curve output by the long-term strategy learning layer, and combines various correction parameters fed back during the actual operation of the envelope to dynamically and smoothly adaptively correct the weight curves of the three objectives of indoor comfort, energy saving, and energy utilization rate, so that the weight settings fit the actual operating conditions of the building from the theoretical preset.

[0051] The lower layer corresponds to step S103, where the operation optimization function of the thermal storage envelope is solved based on the real-time operating status parameters and prediction model. The optimization control layer relies on a thermal prediction model composed of heat pipe heat conduction, wall thermal inertia recursion, and indoor air temperature recursion to predict the room temperature change trend. At the same time, it integrates the corrected weight curve output from the middle layer and incorporates key indicators such as indoor thermal comfort temperature deviation, heat pipe regulation energy consumption, and net energy saving level into the operation optimization function for quantitative solution, and finally obtains the optimal control quantity under multi-objective collaborative balance.

[0052] The three-layer hierarchical design enables the control system to possess both long-term operating strategies and the flexibility to adapt in real time. This design effectively solves the problems of fixed strategies and difficulty in simultaneously addressing multiple objectives inherent in traditional control methods, achieving synergistic optimization of indoor comfort, energy conservation, and energy utilization efficiency.

[0053] In some optional embodiments, the step of gradually correcting the initial control weight curve according to the operating effect of the thermal storage enclosure structure according to a preset adjustment step size includes at least the following steps S201 to S202.

[0054] Step S201: Obtain the correction parameters corresponding to the initial control weight curves of multiple control targets. Obtaining the corresponding correction parameters provides accurate and quantitative operational feedback for the calibration of the initial control weight curves. Weight adjustments no longer rely on experience-based settings, but are closely combined with actual comfort violation situations and target control requirements.

[0055] Step S202: Calculate the correction weight curve based on the correction parameters. The calculated correction weight curve allows for adaptive and smooth correction of comfort weights based on actual indoor thermal comfort performance. This ensures that the control system automatically increases comfort weights when comfort is insufficient and rationally balances energy-saving needs when comfort is adequate. This effectively guarantees indoor thermal comfort stability while avoiding indoor temperature fluctuations caused by sudden weight changes, forming a closed-loop control from operational performance to weight optimization, significantly improving the accuracy and adaptability of comfort control.

[0056] In some optional embodiments, the correction parameters corresponding to the initial control weight curve of the indoor comfort target include: the learning coefficient of the comfort weight, the actual comfort default ratio, and the target comfort default ratio. The correction parameters corresponding to the initial control weight curve of the energy-saving target include: the energy-saving weight learning coefficient, the dimensionless value corresponding to the desired energy-saving level, the normalized energy dimension, and the average energy-saving level of the previous period. The correction parameters corresponding to the initial control weight curve of the energy utilization rate target include: the unattended heat release penalty coefficient and the actual heat release coefficient of the unattended period in the previous window.

[0057] The learning coefficient of comfort weight can be an adaptive adjustment coefficient set for the indoor comfort target. It is used to adjust the correction range and adjustment rate of the comfort weight curve according to the actual comfort violation situation, so that the comfort weight can achieve a smooth and reasonable adaptive update based on the actual operation effect of indoor thermal comfort. This ensures the timeliness of control response and avoids excessive adjustment range causing drastic fluctuations in indoor temperature, thereby improving the stability and accuracy of the control system.

[0058] The actual comfort default ratio represents the percentage of time or degree that the indoor temperature deviates from the set comfort temperature or exceeds the allowable range within the previous statistical window, directly reflecting the actual achievement of indoor comfort standards. A higher value indicates a greater failure to meet comfort requirements and a more severe comfort default; a lower value indicates a better indoor thermal comfort state. The actual comfort default ratio serves as the actual feedback basis for weight correction, comparing it with the target comfort default ratio to achieve adaptive correction of the comfort weight curve, allowing the control system to automatically adjust its control strategy based on actual comfort performance. Correspondingly, the target comfort default ratio is a pre-set upper limit reference value for the degree of indoor thermal comfort non-compliance, serving as a benchmark indicator for measuring whether indoor comfort requirements are met.

[0059] The energy-saving weight learning coefficient can be an adaptive adjustment coefficient set for the energy-saving target. It is used to control the correction range and adjustment speed of the energy-saving weight curve according to the deviation between the actual energy-saving operation effect and the expected energy-saving level, so that the energy-saving weight can be updated smoothly and reasonably. While ensuring the energy-saving effect of the building, it avoids the fluctuation of the control system caused by excessive weight adjustment range, and improves the stability and rationality of the overall control.

[0060] The dimensionless value corresponding to the expected energy saving level can be the energy saving target benchmark value preset by the system. After dimensionless processing, it is used to compare with the actual energy saving level to determine whether the current energy saving effect has met expectations. It serves as the target reference for energy saving weight correction.

[0061] Normalized energy dimensions can be standardized conversion factors set up to enable unified calculation of energy consumption data of different magnitudes and units. They convert actual energy consumption and energy-saving levels to the same numerical range, ensuring the accuracy and comparability of weight correction and optimization calculations.

[0062] The average energy saving level of the previous period can be the average energy saving effect actually achieved in the previous control cycle, which directly reflects the real energy saving operation of the building envelope in the previous stage. It is used as feedback data to correct the energy saving weight and make the control strategy fit the actual operation effect.

[0063] The unattended heat release penalty coefficient can be an adjustment coefficient set for periods when no one is in the room. It is used to suppress unnecessary heat release from the heat pipe and reduce heat waste. When there is excess heat release during unattended periods, the energy utilization rate weight will be reduced through this coefficient to strengthen energy-saving constraints.

[0064] The actual heat release coefficient during the previous unattended period can be a quantitative indicator of the actual heat release of the building envelope during the previous unattended period. It reflects whether the heat is excessively released when no one is present. As actual operational feedback, it is used to determine whether there is ineffective heat release and thus correct the target weight of energy utilization rate.

[0065] In some optional embodiments, the step of calculating the corrected weight curve based on the corrected parameters includes: calculating the corrected weight curve of the indoor comfort target based on the corrected parameters; the calculation formula is as follows: ; in, The corrected weighting curve for indoor comfort targets. The initial control weight curve for the indoor comfort target. The learning coefficient for comfort weights. The actual comfort default ratio, The target comfort default ratio is used. This formula is employed to calculate the corrected weight curve for the indoor comfort target. Based on the deviation between the actual comfort default ratio and the target comfort default ratio, and combined with the learning coefficient of the comfort weights, the initial control weights are adaptively corrected, allowing the comfort weights to dynamically change according to the actual indoor thermal comfort level. When the actual comfort level deviates from the target, the weights are automatically adjusted, enabling the control system to respond to indoor comfort needs in real time. Simultaneously, the correction magnitude is smoothly adjusted through the learning coefficient, avoiding sudden weight changes that could cause indoor temperature fluctuations. This ensures stable achievement of indoor thermal comfort targets and achieves a reasonable balance between the comfort target and other control objectives, improving the overall accuracy and stability of the control.

[0066] In some optional embodiments, the step of calculating the corrected weight curve based on the corrected parameters includes: calculating the corrected weight curve of the energy-saving target based on the corrected parameters; the calculation formula is as follows: ; in, The corrected weighting curve for energy-saving targets. The initial control weight curve for the energy-saving target. For energy-saving weight learning coefficients, E0 represents the dimensionless value corresponding to the desired energy saving level, and E0 represents the normalized energy dimension. This represents the average energy saving level of the previous period. Using this formula to calculate the corrected weight curve for the energy saving target allows for adaptive correction of the initial control weights of the energy saving target based on the deviation between the average energy saving level of the previous period and the expected energy saving level, combined with the energy saving weight learning coefficient. This enables the energy saving weights to dynamically adjust according to the actual energy-saving performance of the building envelope. When the actual energy saving level is lower than the expected value, the energy saving weight is automatically increased; when the energy saving effect is good, the weight is reasonably decreased. Simultaneously, normalized energy dimensions are used to achieve unified quantitative calculation of parameters, and the correction amplitude is smoothly controlled by the energy saving weight learning coefficient, avoiding fluctuations in the control system caused by sudden weight changes. This ensures the effective achievement of the building's energy saving target while maintaining a reasonable balance between the energy saving target and other control targets such as indoor comfort, improving the overall stability, adaptability, and optimization effect of the control.

[0067] In some optional embodiments, the step of calculating the corrected weight curve based on the corrected parameters includes: calculating the corrected weight curve of the energy utilization rate target based on the corrected parameters; the calculation formula is as follows: ; in, The corrected weighting curve for the energy utilization efficiency target. The initial control weight curve for the energy utilization rate target. The penalty coefficient for no heat release. This represents the actual heat release coefficient during the previous unoccupied period. Using this formula to calculate the corrected weight curve for the energy utilization rate target allows for adaptive correction of the initial control weights based on the actual heat release coefficient and the unoccupied heat release penalty coefficient during the previous unoccupied period. This enables the energy utilization rate weights to dynamically adjust according to the actual heat release of the building envelope during unoccupied periods. When ineffective heat release occurs, the weights are automatically constrained, effectively suppressing unnecessary heat loss and improving energy efficiency. Simultaneously, coefficient adjustment ensures smooth weight correction, preventing sudden weight changes that could cause control system fluctuations. This achieves both on-demand heat release and reduced energy waste control, while maintaining a reasonable balance between the energy utilization rate target and the indoor comfort target, further enhancing the overall control accuracy, stability, and energy-saving benefits.

[0068] In some optional embodiments, solving the operation optimization function of the thermal storage enclosure based on the real-time operating state parameters and prediction model of the thermal storage enclosure includes at least the following steps S301 to S302.

[0069] Step S301: Establish a thermal prediction model to predict room temperature. The thermal prediction model may include: a heat pipe conduction model, a wall thermal inertia recursive model, and an indoor air temperature recursive model. Establishing a thermal prediction model to predict room temperature allows for early prediction of indoor temperature trends, providing a reliable predictive basis for indoor comfort targets. This enables the control system to respond before the room temperature deviates from the comfort range, avoiding the problem of delayed comfort adjustments and ensuring the stability and continuity of indoor thermal comfort from a predictive perspective.

[0070] Step S302: The control quantity of the heat storage building envelope is calculated using an optimization function based on the room temperature. By substituting the predicted room temperature into the optimization function to calculate the control quantity, the indoor comfort target can be closely integrated with the corrected weights. The control command most conducive to maintaining the comfort level can be solved quantitatively, allowing the adjustment action of the building envelope to accurately match the indoor comfort needs. This achieves proactive, precise, and optimal control of the comfort target, further improving the achievement rate and stability of indoor thermal comfort.

[0071] In some optional embodiments, the optimization function is: ; Where J is the optimization objective. The optimal optimization objective is obtained by solving for it, and this optimization objective can be used as the control variable. The corrected weighting curve for indoor comfort targets. The corrected weighting curve for the energy utilization efficiency target. The corrected weighting curve for energy-saving targets. The indoor thermal comfort temperature deviation is calculated by subtracting the room temperature from the set indoor temperature. The energy consumed in the i-th prediction step to adjust the heat conduction of the heat pipes in the thermal storage building envelope. Let k represent the net energy saving level of the i-th prediction step, k be the current control cycle number, and i be the prediction cycle number. The optimization function uses indoor thermal comfort temperature deviation as the core evaluation index and weights it using a corrected weight curve of the indoor comfort target. This allows the control system to prioritize precise constraints on the indoor temperature deviation based on the real-time corrected comfort weights when solving for control variables, ensuring the room temperature is always close to the set comfort temperature. Simultaneously, the optimization function weights and balances comfort targets with energy utilization and energy saving targets within the same optimization framework. This ensures that indoor comfort has a corresponding weight in control decisions, achieving stable and reliable thermal comfort protection, while avoiding excessive pursuit of comfort and energy waste through multi-objective collaborative optimization. This makes indoor comfort control more reasonable, smooth, and adaptive, significantly improving the accuracy and stability of comfort control.

[0072] In some optional embodiments, the calculation formula for the heat pipe heat conduction model is as follows: ; in, The effective condensation length for the i-th prediction step. This is the total length of the heat pipe condenser section. This represents the maximum equivalent thermal conductivity of the heat pipe when it participates in condensation along its entire length in the condensing section. Let be the equivalent thermal conductivity of the heat pipe in the i-th prediction step. The temperature of the phase change material near the evaporation section of the heat pipe; Let the temperature of the wall thermal inertia node be the temperature at the i-th prediction step. To control the cycle duration, Let be the amount of heat that the heat pipe can release to the wall in the i-th prediction step. To control the amount of heat released, the heat pipe thermal conductivity model calculates the effective condensation length, equivalent thermal conductivity, and wall thermal inertia node temperature. This allows for precise quantification of the heat released by the heat pipe into the wall during each control cycle, ensuring that the heat transfer capacity of the heat pipe matches the required heat for indoor comfort and preventing temperature fluctuations caused by excessive or insufficient heating. Furthermore, by directly driving the adjustment of the effective condensation length with this control quantity, continuous and smooth adjustments to the heating intensity can be achieved. Combined with the predictive model's advance heat output, this keeps the room temperature stable within the comfort range, significantly improving the response speed and stability of comfort control. This provides reliable and precise thermal support for indoor thermal comfort from the source of heat transfer.

[0073] In some optional embodiments, the calculation formula for the wall thermal inertia recursive model is as follows: ; in, This refers to the equivalent heat capacity of the main body of the enclosure structure. , These are the thermal inertia nodes of the main body of the enclosure structure for the i-th and i+1-th prediction steps, respectively. Let be the amount of heat that the heat pipe can release to the wall in the i-th prediction step. Let i be the indoor plaster layer temperature in the i-th prediction step. This refers to the equivalent thermal resistance from the thermal inertia nodes of the building envelope to the interior surface. The wall thermal inertia recursive model can reflect the dynamic process of heat storage and release in the building envelope. By using key parameters such as equivalent heat capacity, thermal resistance, and heat transfer through heat pipes, it can predict the temperature change inside the wall at the next moment, avoiding large fluctuations in indoor temperature caused by sudden changes in wall temperature, and making the indoor heat distribution more uniform and the temperature change more gentle.

[0074] In some optional embodiments, the calculation formula for the indoor air temperature recursive model is as follows: ; in, , These represent the room temperature at the i-th and (i+1)-th prediction steps, respectively. The indoor convective heat transfer coefficient is... The indoor heat exchange area, The temperature of the indoor plaster layer. For indoor heat gain, The mass flow rate of the air exchange. The specific heat of air at constant pressure. The outdoor air temperature is used as the reference point. The indoor air temperature recursive model reflects the dynamic changes in room temperature due to factors such as indoor plaster layer temperature, indoor heat gain, ventilation, and outdoor meteorological parameters. By accurately predicting the room temperature at the next moment, the indoor air temperature recursive model provides quantifiable and predictable temperature data for indoor comfort targets. This allows the control system to adjust before the room temperature deviates from the comfortable range, greatly improving the timeliness, stability, and accuracy of indoor comfort control.

[0075] Therefore, those skilled in the art should recognize that although numerous exemplary embodiments of the present invention have been shown and described in detail herein, many other variations or modifications conforming to the principles of the present invention can be directly determined or derived from the disclosure of the present invention without departing from the spirit and scope of the invention. Thus, the scope of the present invention should be understood and construed as covering all such other variations or modifications.

[0076] Unless otherwise expressly specified and limited, the terms "installation," "connection," "linking," "fixing," and "setting," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components, unless otherwise expressly limited. Those skilled in the art should be able to understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0077] Unless otherwise specified, all terms used in the description of this disclosure (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains.

[0078] In the description of this disclosure, references to terms such as "one embodiment," "some embodiments," "illustrative embodiment," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0079] Those skilled in the art should understand that the embodiments described below are merely a part of the embodiments of the present invention, and not all of the embodiments of the present invention. These partial embodiments are intended to explain the technical principles of the present invention and are not intended to limit the scope of protection of the present invention. Based on the embodiments provided by the present invention, all other embodiments obtained by those skilled in the art without creative effort should still fall within the scope of protection of the present invention.

Claims

1. A control method for a thermal storage type enclosure structure, characterized in that... include: The initial control weight curves of multiple control objectives of the thermal storage enclosure structure are obtained. The control objectives include: indoor comfort objective, energy saving objective, and energy utilization rate objective. The initial control weight curves are used to define the changing trend of the weight of each of the control objectives over time. According to the preset adjustment step size, the initial control weight curve is gradually corrected based on the operating effect of the heat storage enclosure structure to obtain the corrected weight curve of the multiple control targets. Based on the real-time operating state parameters and prediction model of the thermal storage enclosure structure, the operation optimization function of the thermal storage enclosure structure is solved to obtain the control quantity of the thermal storage enclosure structure. The thermal storage enclosure structure is controlled to perform control actions corresponding to the control quantity.

2. The control method for the thermal storage enclosure structure according to claim 1, characterized in that, The step of gradually correcting the initial control weight curve according to the operating effect of the thermal storage enclosure structure by a preset adjustment step size includes: Obtain the correction parameters corresponding to the initial control weight curves of the multiple control targets; The corrected weight curve is calculated based on the corrected parameters; wherein... The correction parameters corresponding to the initial control weight curve of the indoor comfort target include: the learning coefficient of the comfort weight, the actual comfort default ratio, and the target comfort default ratio; The correction parameters corresponding to the initial control weight curve of the energy-saving target include: energy-saving weight learning coefficient, dimensionless value corresponding to the expected energy-saving level, normalized energy dimension, and average energy-saving level of the previous period. The correction parameters corresponding to the initial control weight curve of the energy utilization rate target include: the unmanned heat release penalty coefficient and the actual heat release coefficient during the unmanned period of the previous window.

3. The control method for the thermal storage type enclosure structure according to claim 2, characterized in that, The step of calculating the corrected weight curve based on the corrected parameters includes: The corrected weight curve for the indoor comfort target is calculated based on the corrected parameters; the calculation formula is as follows: ； in, The corrected weighting curve for the indoor comfort target. The initial control weight curve for the indoor comfort target. The learning coefficients for the comfort weights are... The actual comfort default ratio is... The target comfort default ratio is given.

4. The control method for the thermal storage enclosure structure according to claim 2, characterized in that, The step of calculating the corrected weight curve based on the corrected parameters includes: The corrected weight curve for the energy-saving target is calculated based on the corrected parameters; the calculation formula is as follows: ； in, The corrected weighting curve for the energy-saving target. The initial control weight curve for the energy-saving target. The energy-saving weight learning coefficients are... Let E0 be the dimensionless value corresponding to the desired energy saving level, and E0 be the normalized energy dimension. This represents the average energy-saving level of the previous time period.

5. The control method for the thermal storage type enclosure structure according to claim 2, characterized in that, The step of calculating the corrected weight curve based on the corrected parameters includes: The corrected weight curve for the energy utilization rate target is calculated based on the corrected parameters; the calculation formula is as follows: ； in, The corrected weighting curve for the energy utilization efficiency target. The initial control weight curve for the energy utilization rate target. The unmanned heat release penalty coefficient is... This is the actual heat release coefficient during the unoccupied period of the previous window.

6. The control method for the thermal storage enclosure structure according to claim 1, characterized in that, The steps for solving the operational optimization function of the thermal storage enclosure structure based on the real-time operating state parameters and prediction model of the thermal storage enclosure structure include: A thermal prediction model is established to predict room temperature using the thermal prediction model; The control parameters of the thermal storage enclosure structure are calculated using an optimization function based on the stated room temperature; wherein... The thermal prediction model includes: a heat pipe heat conduction model, a wall thermal inertia recursive model, and an indoor air temperature recursive model. The optimization function is: ； Where J is the optimization objective. The corrected weighting curve for the indoor comfort target. The corrected weighting curve for the energy utilization rate target. The corrected weighting curve for the energy-saving target. The indoor thermal comfort temperature deviation is obtained by subtracting the room temperature from the set indoor temperature. This refers to the energy consumed in the i-th prediction step to adjust the heat conduction of the heat pipes in the thermal storage enclosure. Let k be the net energy saving level of the i-th prediction step, k be the current control cycle number, and i be the prediction cycle number.

7. The control method for the thermal storage enclosure structure according to claim 6, characterized in that, The calculation formula for the heat pipe heat conduction model is as follows: ； in, The effective condensation length for the i-th prediction step. This is the total length of the heat pipe condenser section. This represents the maximum equivalent thermal conductivity of the heat pipe when it participates in condensation along its entire length in the condensing section. Let be the equivalent thermal conductivity of the heat pipe in the i-th prediction step. The temperature of the phase change material near the evaporation section of the heat pipe. Let the temperature of the wall thermal inertia node be the temperature at the i-th prediction step. To control the cycle duration, Let be the amount of heat that the heat pipe can release to the wall in the i-th prediction step. The control quantity is denoted as .

8. The control method for the thermal storage enclosure structure according to claim 6, characterized in that, The calculation formula for the wall thermal inertia recursive model is as follows: ； in, The equivalent heat capacity of the main body of the enclosure structure. , These are the main thermal inertia nodes of the maintenance structure in the i-th and i+1-th prediction steps, respectively. Let be the amount of heat that the heat pipe can release to the wall in the i-th prediction step. Let i be the indoor plaster layer temperature in the i-th prediction step. To maintain the equivalent thermal resistance from the thermal inertia nodes of the main structure to the indoor surface.

9. The control method for the thermal storage enclosure structure according to claim 6, characterized in that, The calculation formula for the indoor air temperature recursive model is as follows: ； in, , These refer to the room temperature mentioned in the i-th and (i+1)-th prediction steps, respectively. The indoor convective heat transfer coefficient is... The indoor heat exchange area, The temperature of the indoor plaster layer. For indoor heat gain, The mass flow rate of the air exchange. The specific heat of air at constant pressure. This refers to the outdoor air temperature.

10. A heat-storing enclosure structure, characterized in that, include: Main body of the enclosure structure; A thermal insulation layer is provided on the outside of the main body of the enclosure structure; A phase change heat storage layer is disposed on the outside of the thermal insulation layer. The phase change heat storage layer stores heat through phase change during the day and supplies heat to the indoor side at night. An interior plaster layer is provided on the inner side of the main body of the enclosure structure; A heat pipe extends upward from the bottom of the phase change heat storage layer to the middle of the phase change heat storage layer; the heat pipe extends obliquely from the middle of the phase change heat storage layer towards the indoor side to the middle of the main body of the enclosure structure near the indoor plaster layer; the heat pipe extends upward from the middle of the main body of the enclosure structure near the indoor plaster layer to the top of the main body of the enclosure structure near the indoor plaster layer. The heat pipe is a gravity heat pipe, which includes: The evaporation section is vertically arranged within the phase change heat storage layer; The condensation section is vertically installed within the main body of the enclosure structure; An insulating section is inclinedly disposed between the evaporation section and the condensation section; A gas storage chamber is located above the condensation section and is used to adjust the condensation effect of the gravity heat pipe. A control device, comprising a memory, a processor, and a computer program stored in the memory, characterized in that the processor executes the computer program to implement the steps of the control method for the thermal storage enclosure structure according to any one of claims 1 to 9.

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