Waste heat recovery method and system for prefabricated building wall panels

Abstract

The present invention discloses a method and system for waste heat recovery of prefabricated building wall panels, belonging to the technical field of energy-saving heat exchange devices. The method includes obtaining the embedded structure parameters of the prefabricated building wall panels, generating the partition structure parameters of the wall panels based on the embedded structure parameters; generating the thermosiphon gradient parameters by using a preset thermosiphon effect gradient model, and configuring the diversion path of the wall panel cavity based on the thermosiphon gradient parameters; dynamically controlling the flow rate of the waste heat gas flow through the pressure difference and obtaining the real-time temperature data and flow rate data of each wall panel partition based on the partition structure parameters, generating a dynamic heat regulation instruction, dividing the waste heat into a primary heat network and a secondary heat network according to a preset gradient, and distributing them to the corresponding terminal devices. The present invention dynamically configures the diversion path by using the thermosiphon effect gradient model, and combines the micro-turbine fan with the cross-system collaborative distribution mechanism, which can improve the waste heat recovery efficiency, reduce the operation energy consumption, and realize the optimal integration of building energy conservation and the energy system.

Description

Technical Field

[0001] The present invention relates to the technical field of energy-saving heat exchange devices, and more particularly to a method and system for recovering waste heat from prefabricated building wall panels. Background Art

[0002] As a core component of the industrialized building system, prefabricated building wall panels usually integrate heating pipelines and insulation structures. Existing technologies achieve heat conduction by setting cavities inside the wall panels, and some solutions use metal fins to enhance the heat diffusion efficiency.

[0003] Current technologies mostly achieve waste heat recovery by embedding single-direction heat pipes or forced ventilation devices inside the wall panels. For example, serpentine metal heat pipes are used to accelerate heat conduction, and heat exchangers are connected to the ends to transfer heat. Additionally, axial fans are installed outside the wall panels to accelerate the air flow circulation in the cavities.

[0004] However, the fixed cavity diversion path in the existing technologies cannot adapt to dynamic temperature differences, resulting in heat energy retention; the energy consumption of the forced convection device accounts for more than 15% of the total system energy consumption, offsetting the energy-saving benefits; at the same time, there is a lack of a grading utilization mechanism for waste heat quality, and the mixed recovery of high-temperature waste heat and low-temperature waste heat leads to a waste of energy quality. In addition, the single heat pipe solution has heat conduction blind spots in the special-shaped structures of the wall panels, significantly reducing the heat recovery efficiency. Summary of the Invention

[0005] To solve the above problems, the present invention provides a method and system for recovering waste heat from prefabricated building wall panels. By using a thermosiphon effect gradient model to dynamically configure the diversion path, combined with a micro-turbine fan and a cross-system collaborative distribution mechanism, it can improve the waste heat recovery efficiency, reduce the operating energy consumption, and achieve the optimal integration of building energy conservation and the energy system.

[0006] The above objectives can be achieved through the following solutions:

[0007] A method for recovering waste heat from prefabricated building wall panels, including obtaining the embedded structure parameters of the prefabricated building wall panels, generating partition structure parameters of the wall panels based on the embedded structure parameters, where the partition structure parameters include the sizes and positions of the core heat generation area, the edge conduction area, and the energy storage interface area; according to the partition structure parameters, using a preset thermosiphon effect gradient model to generate thermosiphon gradient parameters, and configuring the diversion path of the wall panel cavity based on the thermosiphon gradient parameters; deploying a micro-turbine fan device according to the diversion path, dynamically controlling the flow rate of the waste heat air flow through the pressure difference; and obtaining the real-time temperature data and flow rate data of each wall panel partition based on the partition structure parameters, generating a dynamic heat regulation instruction; based on the dynamic heat regulation instruction, dividing the waste heat into a primary heat network and a secondary heat network according to a preset gradient, and distributing it to the corresponding terminal devices.

[0008] Optionally, obtaining the real-time temperature data and flow rate data of each wall panel partition based on the partition structure parameters includes: identifying an abnormal heat surge area in the real-time temperature data that exceeds a preset threshold; in response to the abnormal heat surge area, generating a water cooling compensation instruction and starting the capillary network and external spray cooling device built in the wall panel.

[0009] Optionally, after generating the water cooling compensation instruction, it includes: extracting the historical temperature fluctuation data of the abnormal heat surge area, predicting the subsequent heat surge cycle; and adjusting the spray trigger frequency according to the prediction result.

[0010] Optionally, the allocation to the corresponding terminal device includes: allocating the waste heat of the primary heat network to the domestic hot water system; and allocating the waste heat of the secondary heat network to the heating system or the energy storage interface according to a preset priority.

[0011] Optionally, the allocation to the heating system or the energy storage interface according to a preset priority includes: extracting the real-time status data of external energy devices, where the external energy devices include solar water heaters and ground source heat pumps; matching the extraction path of the remaining heat energy based on the real-time status data and generating a cross-system collaborative allocation instruction.

[0012] Optionally, generating the cross-system collaborative allocation instruction includes: obtaining the time-of-use electricity price data of the power grid, preprocessing to generate peak period and valley period marks; calculating the electricity price peak-valley difference within a continuous preset period based on the peak period and valley period marks; generating an electric auxiliary heating trigger threshold according to the electricity price peak-valley difference and the user load demand; when the electricity price peak-valley difference is greater than or equal to the electric auxiliary heating trigger threshold and the valley period mark is detected, dynamically adjusting the heating power based on the real-time power grid load signal; storing the heat energy output by the electric auxiliary heating device in the phase change energy storage wall panel and feeding back the heat storage status through a temperature sensor.

[0013] Optionally, generating the thermosiphon gradient parameter using a preset thermosiphon effect gradient model includes: establishing a temperature difference gradient mapping table between the wall panel cavity and the external environment; selecting aluminum honeycomb core or phase change gypsum board as the filling material for the core heating area based on the gradient mapping table; performing feature extraction on the temperature gradient mapping table and the filling material to obtain the thermosiphon gradient parameter.

[0014] Optionally, after configuring the flow path of the wall panel cavity based on the thermosiphon gradient parameter, it further includes: simulating the dynamic relationship between the core heating area and the ambient temperature in different seasons, generating a season adaptation coefficient; and correcting the heat transfer efficiency of the flow path according to the season adaptation coefficient.

[0015] Optionally, after dynamically controlling the flow rate of the waste heat air flow through the pressure difference, the following steps are further included: collecting the flow rate of the waste heat air flow and the pressure difference threshold; dynamically adjusting the rotation speed of the micro turbine fan based on the pressure difference threshold to generate a flow rate equalization feedback signal.

[0016] Based on the same inventive concept, the present invention also provides a waste heat recovery system for prefabricated building wall panels. The system includes: a zoning module for obtaining the embedded structure parameters of the prefabricated building wall panels and generating the zoning structure parameters of the wall panels based on the embedded structure parameters, where the zoning structure parameters include the sizes and positions of the core heat generation area, the edge conduction area, and the energy storage interface area; a diversion path planning module for generating a thermosiphon gradient parameter using a preset thermosiphon effect gradient model according to the zoning structure parameters and configuring the diversion path of the wall panel cavity based on the thermosiphon gradient parameter; a control module for dynamically controlling the flow rate of the waste heat air flow through the pressure difference according to the micro turbine fan device deployed along the diversion path, and obtaining the real-time temperature data and flow rate data of each wall panel zone based on the zoning structure parameters to generate a dynamic heat regulation instruction; an execution module for dividing the waste heat into a primary heat network and a secondary heat network according to a preset gradient based on the dynamic heat regulation instruction and distributing it to the corresponding terminal devices.

[0017] Compared with the prior art, the present invention has the following advantages:

[0018] 1. Through the precise matching of the zoning structure parameters and the thermosiphon gradient parameters, the present invention optimizes the diversion path of the wall panel cavity, enhances the self-driving ability of the hot air flow, reduces the dependence on external mechanical forced convection, and improves the waste heat recovery efficiency; the collaborative design of the core heat generation area and the edge conduction area effectively inhibits heat dissipation, and at the same time, the dynamic control of the pressure difference of the micro turbine fan ensures the equalization of the flow rate of the waste heat air flow, reducing the ineffective loss during the heat energy transmission process;

[0019] 2. Based on the dynamic heat regulation instruction of the real-time temperature and flow rate data, the present invention can quickly identify the abnormal heat surge area and trigger the water cooling compensation mechanism, predict the heat surge cycle in combination with historical data, and adaptively adjust the spraying frequency to ensure the stable operation of the system under complex working conditions; the multi-level heat network distribution strategy matches the terminal device requirements according to the energy grade, improving the waste heat utilization rate;

[0020] 3. Through the cross-system collaborative distribution instruction, the system integrates the solar water heater, the ground source heat pump, and the time-of-use electricity price information of the power grid, dynamically distributes the waste heat resources, and preferentially meets the high-economic and high-energy-efficiency demand scenarios; the intelligent linkage of the electric auxiliary heating and the phase change energy storage wall panel stores low-price electric energy as heat energy during the low-load period of the power grid, reducing the comprehensive energy consumption cost;

[0021] 4. The present invention adopts a partitioned modular design and a complementary mechanism of natural convection and forced convection, reducing the investment in redundant equipment; the self-adaptive optimization characteristics of the thermosiphon effect gradient model extend the service life of key components, and combined with the abnormal warning and automatic repair functions, significantly reduce the need for manual intervention and the maintenance complexity.

[0022] Other features and advantages of the present invention will be described in the following specification, and, in part, will be obvious from the specification, or will be understood by implementing the present invention. The objectives and other advantages of the present invention can be realized and obtained by the structure pointed out in the specification, claims, and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0024] Figure 1 It is a schematic flow chart of the waste heat recovery method for prefabricated building wall panels in an embodiment of the present invention.

[0025] Figure 2 It is a schematic diagram of energy economy regulation in an embodiment of the present invention.

[0026] Figure 3 It is a schematic structural diagram of the waste heat recovery system for prefabricated building wall panels in an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0027] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0028] Refer to Figure 1 , an embodiment of the present invention proposes a waste heat recovery method for prefabricated building wall panels, which dynamically configures the diversion path by using the thermosiphon effect gradient model, and combines a micro-turbine fan and a cross-system collaborative distribution mechanism, which can improve the waste heat recovery efficiency, reduce the operating energy consumption, and realize the optimal integration of building energy conservation and the energy system.

[0029] The method of this embodiment specifically includes:

[0030] Obtaining pre-embedded structural parameters of the prefabricated building wall panel, and generating partition structural parameters of the wall panel based on the pre-embedded structural parameters, wherein the partition structural parameters include the size and position of the core heating area, the edge conduction area, and the energy storage interface area;

[0031] Specifically, the embedded structural parameters are the cavity distribution, material density, and connection interface layout information preset within the prefabricated building wall panels. The three-dimensional structural data of the wall panels is extracted through laser scanning or Building Information Modeling (BIM). Based on the physical distance between the cavity position and the building's heating pipes, the core heating zone is automatically divided into a high-thermal conductivity area adjacent to the heating pipes, the edge conduction zone is a buffer zone close to the exterior wall, and the energy storage interface zone is the area surrounding the interface for pre-set connection to the ground-source heat pump or water tank. The size of the core heating zone is calculated based on the coverage of the heating pipes, and the thickness of the edge conduction zone is no less than 15% of the total wall panel thickness.

[0032] Among them, the embedded structure parameters are the physical property data of the non-detachable structure preset in the prefabricated building wall panels, including cavity volume, material type and interface coordinates. The partition structure parameters are the functional area definitions based on the dynamic division of the embedded structure, which are used to distinguish the priorities and transmission paths of different waste heat recovery. The core heating area is the heat-conducting tape in the wall panel that is in direct contact with the heating pipe, with concentrated heat and high temperature gradient. The edge conduction area is the area adjacent to the outer layer of the wall panel and the exterior wall of the building, which is responsible for buffering the temperature difference between the inside and outside and storing medium and low temperature heat. The energy storage interface area is the area around the standard port reserved for connecting external energy storage equipment on the wall panel, which is used to export excess heat.

[0033] According to the partition structure parameters, a thermosiphon effect gradient model is used to generate thermosiphon gradient parameters, and a diversion path of the wall panel cavity is configured based on the thermosiphon gradient parameters;

[0034] The micro-turbofan device deployed along the flow guide path dynamically controls the flow rate of the waste heat airflow through pressure difference; and obtains real-time temperature and flow data of each wall panel partition based on the partition structure parameters to generate dynamic thermal control instructions;

[0035] Based on the dynamic heat control instruction, the waste heat is divided into a primary heat network and a secondary heat network according to a preset gradient, and distributed to corresponding terminal devices.

[0036] This method converts the passive heat dissipation of prefabricated building wall panels into controllable energy through the coordination of structural zoning, optimization of the thermosiphon effect, dynamic regulation, and hierarchical utilization of waste heat. The high-efficiency heat-conducting material in the core heating area is combined with the phase-change heat storage in the edge conduction area to solve the contradiction between heat dissipation and delayed heat recovery in traditional methods; the dynamic complementarity of the thermosiphon effect and the micro-turbine fan enhances the diversion stability; the hierarchical distribution strategy driven by real-time data matches the energy requirements of multiple scenarios. Ultimately, it realizes the overall improvement of waste heat recovery efficiency, system response speed, and cross-system coordination ability, while reducing the equipment transformation cost and maintenance complexity.

[0037] Optionally, obtaining the real-time temperature data and flow data of each wall panel partition based on the partition structure parameters includes:

[0038] Identifying the abnormal heat surge areas in the real-time temperature data that exceed the preset threshold;

[0039] Specifically, the preset threshold is the temperature critical value set according to different seasons and building functions, and is determined through the historical building energy consumption data and thermal simulation. The judgment of the abnormal heat surge area needs to meet two conditions at the same time. Condition 1 is that the temperature of a single partition exceeds the threshold for 3 consecutive acquisition cycles (15 seconds), and Condition 2 is that the temperature difference between adjacent partitions exceeds 10 and shows a spreading trend. The real-time temperature data is collected through a temperature sensor network, and the sliding window algorithm is used to compare the historical mean value and mark the coordinates of the abnormal area. The abnormal heat surge area is an unexpected temperature rise area caused by external heat sources (such as direct sunlight, equipment failure), and its temperature fluctuation amplitude and rate exceed the normal waste heat recovery range. The sliding window algorithm is a dynamic data segmentation processing method based on time series, which identifies abnormal peaks through local mean and standard deviation.

[0040] In response to the abnormal heat surge area, a water-cooling compensation instruction is generated to start the capillary network and the external spray cooling device built in the wall panel.

[0041] Specifically, the capillary network is a distributed micro water pipe embedded in the wall panel sandwich, made of polyethylene material and arranged along the coordinates of the abnormal area. The water-cooling compensation instruction includes parameters such as water flow rate, cooling duration, and coverage range, and calculates the required heat dissipation according to the temperature overrun value. At the same time, the external spray device sprays an atomized water curtain on the outer surface of the wall panel to reduce the surface temperature of the wall panel through evaporation heat absorption. The spray trigger frequency is dynamically adjusted according to the temperature drop rate of the abnormal area, and the spray stops when the detected temperature drop slope is greater than 5°C / min. For the minimum spray volume , there is:

[0042] ;

[0043] In the formula, is the measured value of the abnormal temperature, is the preset threshold, is the area of the abnormal region, is the heat dissipation coefficient of the material, which is used to unify the dimension of the calculation result.

[0044] Among them, the capillary network is a micron-level water flow channel network embedded in the wall panel, which absorbs abnormal heat through circulating cold water. The external spray cooling device is an array of atomizing nozzles installed on the outside of the wall panel, which accelerates the heat dissipation of the wall surface through the evaporation of water mist. The water-cooling compensation instruction is a set of cooling control parameters calculated according to the abnormal heat, including the water flow rate, the spraying range and the duration.

[0045] Exemplarily, for the abnormal region on the west side (area 2m², =48℃), it is calculated that the spraying volume is 240L / h, the capillary network is started to circulate and cool at a water flow rate of 0.5m / s, and at the same time the external spray operates in a mode of spraying for 3 seconds every 10 seconds. After 20 minutes, the temperature of this area drops to 43℃. The active cooling mechanism can quickly suppress the unexpected temperature rise and avoid heat accumulation from damaging the wall panel structure. Increase the dynamic abnormal processing ability on the basis of real-time monitoring. Accurately identify the abnormal region through the preset threshold and the sliding window algorithm, avoiding misjudgment caused by a single threshold in the traditional method; the combination of the two-way heat absorption (internal conduction plus external evaporation) of the capillary network realizes efficient temperature control in a limited space. Cooperate with the dynamic heat regulation instruction to make the waste heat recovery system have self-healing ability, reduce manual intervention and improve the overall stability.

[0046] Optionally, after generating the water-cooling compensation instruction, it includes:

[0047] Extract the historical temperature fluctuation data of the abnormal heat surge region and predict the subsequent heat surge cycle;

[0048] Specifically, the historical temperature fluctuation data is the temperature time series data recorded in the past 30 days in the same abnormal region, including the temperature peak value, the duration and the interval period. An exponential smoothing method is used to establish a prediction model, and by assigning higher weights to the recent values of the weighted historical data, predict the possible occurrence time and duration of the heat surge in the next 24 hours. If the interval time between two consecutive heat surges in the prediction result is shortened by more than 20, it is determined that the high-frequency abnormal period has entered. The historical temperature fluctuation data is a record set of periodic or sporadic temperature abnormal events under the same geographical coordinates, which is used to analyze the heat surge pattern. The exponential smoothing method is an algorithm based on the decreasing weighted average of historical data in time series prediction and is suitable for short-term trend prediction. The subsequent heat surge cycle is the possible time window of the next abnormal temperature rise output by the model and the predicted value of its duration.

[0049] Adjust the spray trigger frequency according to the prediction result.

[0050] Specifically, layout density adjustment involves reducing the spacing of the capillary network within the abnormal area by 30 to 50° during the predicted abnormal period to improve heat dissipation efficiency per unit area. The sprinkler trigger frequency is dynamically set based on the predicted temperature rise rate: if the predicted peak temperature increase exceeds 5°C / min, the sprinkler interval is shortened to 50°C of the original standard; if a slow rise is predicted (increase rate ≤ 2°C / min), an interval trigger mode is used to save water. Adjustment parameters are transmitted to the actuator via the control unit. The sprinkler trigger frequency is the number of times the external sprinkler system is activated per unit time and is positively correlated with the intensity of the thermal surge.

[0051] Optionally, the allocating to a corresponding terminal device includes:

[0052] distributing the waste heat of the primary heating network to the domestic hot water system;

[0053] Specifically, the primary heat network is defined as a collection of waste heat above 45°C, which is delivered to the preheating end of the domestic hot water system via independent, high-temperature-resistant pipes. During distribution, priority is given to meeting the real-time needs of the hot water storage tanks. When the hot water tank water level falls below 50% or the temperature falls below a set value (e.g., 50°C), the primary heat network valve opens. When the tank is full or the temperature meets the specified value, the system switches to a backup distribution path. This backup path may include industrial heating equipment or temporary energy storage buffer tanks to prevent excess heat from stagnating and overheating the wall panels.

[0054] The primary heat network is a transmission network for high-temperature waste heat recovered from wall panels, providing thermal quality that meets immediate domestic hot water needs. Independent high-temperature-resistant pipes are enclosed, stainless steel or ceramic-lined pipes with a temperature tolerance of 100°C or higher, minimizing heat loss. A backup distribution path serves as an emergency outlet for the primary heat network when primary target equipment is at full capacity, maintaining a dynamic balance of waste heat.

[0055] The waste heat of the secondary heat network is distributed to the heating system or energy storage interface according to preset priorities.

[0056] Specifically, the secondary heating network covers waste heat ranging from 30-45°C. It prioritizes waste heat utilization by grade, maximizing its energy value through pre-set priorities. The primary network ensures immediate, rigid demand for high-quality thermal energy, while the secondary network flexibly adapts to flexible demands in multiple scenarios. In conjunction with dynamic control instructions, this network simultaneously ensures stable domestic hot water supply and adaptability to combined heating and cooling in buildings, resolving the supply-demand mismatch caused by traditional single-source allocation methods.

[0057] Optionally, the allocating to the heating system or energy storage interface according to preset priority includes:

[0058] Extracting real-time status data of external energy devices, including solar water heaters and ground-source heat pumps;

[0059] Specifically, the real-time status data of the external energy equipment includes the collector temperature of the solar water heater, the water tank level, the remaining capacity of the heat storage layer of the ground source heat pump, and the underground soil temperature. It communicates with the external device controller through the Modbus or CAN bus protocol, collects data every 2 seconds, and stores it in the central database. After the data preprocessing module filters out the noise, it marks the current available heat capacity and the maximum load threshold of the equipment. When the remaining capacity of the heat storage layer of the ground source heat pump is less than 20%, it is determined as the "low storage state"; when the temperature difference between the solar collector and the water tank is less than 5, it is determined as the "low-efficiency heat collection state".

[0060] Among them, the external energy equipment is an independent energy device linked with the waste heat recovery system, which is used to supplement or store waste heat. The real-time status data is a set of dynamic parameters during the operation of the external device, reflecting its current energy supply or energy storage capacity. The low storage state is the operation stage when the remaining space for heat reception in the heat storage layer of the ground source heat pump is less than the critical value. The low-efficiency heat collection state is the working condition where the heating efficiency of the solar water heater decreases due to insufficient sunlight or collector pollution. Through multi-dimensional status marking, the supply-demand gap of the external device can be accurately identified, providing a decision-making basis for waste heat redistribution.

[0061] Based on the real-time status data, match the extraction path of the remaining heat energy and generate a cross-system collaborative distribution instruction.

[0062] Specifically, the extraction path matching adopts a two-level decision-making logic, namely priority sorting and path dynamic binding. Priority sorting generates a heating gap level according to the status mark of the external device. For example, the low storage state of the ground source heat pump is a first-level gap, and the low-efficiency heat collection of the solar energy is a second-level gap. Path dynamic binding preferentially imports the waste heat into the gap device with the highest priority and reserves 10% of the heat as an emergency buffer. The cross-system collaborative distribution instruction includes the target device address, valve opening, and transmission rate upper limit, and is sent to the actuator through the OPC UA protocol.

[0063] Among them, the cross-system collaborative distribution instruction is a set of linkage control parameters for the waste heat recovery system and the external energy equipment, which is used to realize the dynamic allocation of heat energy among multiple devices. The extraction path is the physical channel for the waste heat to transfer from the wall panel diversion network to the external device, including pipeline connection, valve control, and flow regulation.

[0064] Exemplarily, for the low-efficiency heat collection and low-reservoir state, an instruction is generated to allocate 60% of the waste heat from the secondary heat network to the supplementary heating of the solar water heater tank, 30% to the expansion of the heat storage layer of the ground-source heat pump, and the remaining 10% as an emergency buffer. When the weather clears up and the solar energy resumes efficient heat collection, the instruction is dynamically switched to deliver 70% of the waste heat to the ground-source heat pump. By integrating the real-time data of external devices and the waste heat distribution strategy, the isolated operation mode of the traditional waste heat system and external energy is broken. The complementary combination of priority allocation and collaborative allocation makes the waste heat recovery system an intelligent scheduling node of the multi-energy network. By real-time binding the transfer path and the equipment gap, the flexibility to cope with complex energy scenarios is improved, and a closed loop of "waste heat flowing across the network on demand - dynamic consumption by external devices" is achieved, effectively solving the problem of low collaborative efficiency of multiple devices in the traditional method. Through dynamic collaborative allocation, the short-term supply shortage of external energy is made up, and at the same time, the waste of heat energy caused by the overload of a single device is avoided.

[0065] Optionally, the generation of the cross-system collaborative allocation instruction includes:

[0066] Obtain the time-of-use electricity price data of the power grid, and preprocess it to generate peak period and valley period marks;

[0067] Specifically, collect the time-of-use electricity price data of a specified area through the communication interface of the power market trading platform or the smart meter. According to a preset time window, for example, 8:00 - 20:00 every day is the peak period, 20:00 - 8:00 the next day is the valley period, or the peak and valley stages are dynamically divided according to the real-time power grid load prediction. Perform normalization and filtering processing on the electricity price data to eliminate instantaneous fluctuation noise and output a periodic peak and valley mark sequence.

[0068] Among them, the time-of-use electricity price data is the unit electricity price information released by the power grid company divided by different periods (peak, flat, valley), which is used to guide users to optimize their electricity consumption costs. The peak period and valley period marks are time period identifiers set based on the electricity price level or the power grid load. For example, the valley period corresponds to the time period with the lowest electricity price and the lightest power grid load. The filtering process is to smooth and correct the short-term abnormal fluctuations (such as instantaneous electricity price jumps caused by power grid faults) in the electricity price data, and is usually implemented by a moving average algorithm.

[0069] Based on the peak period and valley period marks, calculate the electricity price peak-valley difference within a continuous preset period;

[0070] Specifically, taking the valley period electricity price as the reference value (for example, 0.3 yuan / kWh) and the peak period electricity price as the comparison value (for example, 0.9 yuan / kWh), generate the peak-valley difference. For the electricity price peak-valley difference , there is:

[0071] ;

[0072] In the formula, is the average electricity price during peak hours, The difference calculation result is a dynamic variable. When the price difference exceeds a preset economic threshold, the electric auxiliary heating instruction is triggered. The economic threshold is the minimum trigger condition calculated based on historical data or cost models. When the difference exceeds this threshold, the economic benefits of electric auxiliary heating exceed the energy storage cost.

[0073] generating an electric auxiliary heating trigger threshold according to the peak-valley difference in electricity prices and user load demand;

[0074] Specifically, the trigger threshold is determined based on the user's preset building heat load demand (for example, the winter heating load demand is 50kWh per day) and the peak-valley difference in electricity prices. ,have:

[0075] ;

[0076] Where, is the predicted value of daily average heat load, The heat storage capacity of a single phase change energy storage wall panel (e.g. 30kWh / time). When , the electric energy conversion instruction is triggered. For example, if Yuan / kWh, and currently Yuan / kWh, electric auxiliary heating is allowed to start.

[0077] When the peak-valley difference of the electricity price is greater than or equal to the electric auxiliary heating trigger threshold and the valley period mark is detected, the heating power is dynamically adjusted based on the real-time grid load signal;

[0078] Specifically, when it is detected that the valley period mark is effective and the trigger threshold is met, a start-up instruction is sent to the electric auxiliary heating device (such as a resistive heater). The heating power is dynamically adjusted by the grid load signal, and a power segmentation control strategy is adopted: if the total load of the grid is lower than the safety threshold (for example, the load rate ≤ 70%), full-power heating is allowed; if the grid load is close to the upper limit (for example, the load rate > 85%), the heating power is proportionally limited to avoid overload. The grid load signal is the real-time load rate data (0-100%) released by the grid operator, and the power segmentation control strategy is a response mechanism that adjusts the power of the equipment in a hierarchical manner according to the grid status.

[0079] The heat energy output by the electric auxiliary heating device is stored in the phase change energy storage wall panel, and the heat storage status is fed back through the temperature sensor.

[0080] Specifically, the phase change energy storage wall panel receives the heat energy generated by the electric auxiliary heating device through the heat conduction pipeline. After absorbing the heat, the phase change material changes from solid state to liquid state, completing the heat energy storage. During the heat storage process, the distributed temperature sensors (such as PT100 thermal resistors) built in the wall panel monitor the temperature distribution gradient, and feedback the real-time heat storage efficiency and capacity status (for example, when the temperature reaches the phase change point, it is regarded as being saturated with heat storage). The temperature distribution gradient is the temperature difference at different positions of the phase change material during the heat storage process, reflecting the uniformity of heat transfer. The heat storage saturation is the maximum capacity of heat energy storage when the phase change material reaches the critical value of the phase change temperature.

[0081] Exemplarily, the electricity price during the valley period (22:00 - 6:00) in a certain area is 0.3 yuan per degree, and the electricity price during the peak period (7:00 - 21:00) is 0.8 yuan per degree. yuan per degree. The user's heat load , , yuan per degree. Due to , it is determined that the current period does not meet the trigger condition. When the user temporarily increases the next-day heat load to 80 kWh, is updated to (0.5 × 80) / 20 = 2.0 yuan per degree, and it is still determined not to trigger. If the grid operator temporarily increases the electricity price subsidy during the valley period, becomes 0.7 yuan per degree. At this time, the condition is still not met, and the model parameters need to be optimized again. This verification example shows that, as Figure 2 shown, through the dynamic matching of the electricity price difference trigger threshold and the user's heat load, heat storage is only started when both the grid economic conditions and the user's needs are met, avoiding ineffective power consumption. The thermal inertia characteristic of the phase change energy storage wall panel further smooths the grid load fluctuation and improves the energy supply stability of the local energy system.

[0082] Optionally, the generation of the thermosiphon gradient parameter by using the preset thermosiphon effect gradient model includes:

[0083] Establishing a temperature difference gradient mapping table between the wall panel cavity and the external environment;

[0084] Specifically, the thermosiphon effect gradient model is a natural convection mathematical model based on temperature difference driving, which calculates the thermal pressure difference distribution in the vertical direction of each partition cavity. By setting the temperature difference between the reference temperature of the core heating area and the external temperature of the edge conduction area, a gradient mapping table of the thermal pressure difference driving the air flow rising rate is generated for subsequent diversion path optimization.

[0085] Selecting the aluminum honeycomb core or the phase change gypsum board as the filling material for the core heating area based on the gradient mapping table;

[0086] Specifically, the aluminum honeycomb core is suitable for rapid heat conduction scenarios with large temperature differences, and its honeycomb grid accelerates the lateral diffusion of heat; the phase change gypsum board is suitable for heat storage and buffering scenarios with medium and low temperature differences, and delays the dissipation of heat through the latent heat absorption of the phase change material. If the thermal pressure difference in the cavity of the gradient mapping table is greater than or equal to 100 Pa, it is determined as a high diversion demand, and the aluminum honeycomb core is selected; if the thermal pressure difference in the cavity is less than 100 Pa and the external temperature fluctuation is greater than 8 °C, the phase change gypsum board is selected.

[0087] Feature extraction is performed on the temperature gradient mapping table and the filling material to obtain the thermosiphon gradient parameter.

[0088] Specifically, the thermosiphon gradient parameter is the optimal parameter combination of the air flow rate and direction output according to the model, including the cavity inclination angle, the filling material density, and the curvature of the diversion path space, which is obtained by performing feature extraction on the temperature gradient mapping table and the filling material.

[0089] Optionally, after configuring the diversion path of the wallboard cavity based on the thermosiphon gradient parameter, the following steps are further included:

[0090] Simulate the dynamic relationship between the core heating area and the ambient temperature in different seasons to generate a seasonal adaptation coefficient;

[0091] Specifically, the seasonal adaptation coefficient is a thermal engineering adjustment parameter generated by integrating historical meteorological data and building heat load requirements. By simulating the correlation curves of the core heating area temperature and the external temperature in winter, summer, and transitional seasons within the annual cycle, the temperature difference change characteristics in different seasons are quantified. In the winter model, when the external temperature is below 10 °C, the core heating area is mainly for heating, and the temperature difference gradient is stable. In the summer model, when the external temperature is above 30 °C, the core heating area is affected by the cooling demand, and the temperature difference shows diurnal fluctuations. In the transitional season model, when the external temperature is between 10 - 30 °C, the temperature difference between the core area and the outside fluctuates randomly, and dynamic adaptation is required. Based on the above models, the adaptation coefficient for each season is generated. For the seasonal adaptation coefficient , there is:

[0092] ;

[0093] In the formula, is the seasonal average temperature difference, is the annual average temperature difference. The seasonal adaptation coefficient is a parameter that quantifies the influence of temperature difference changes in different seasons on the diversion path and is used to dynamically adjust the heat transfer efficiency. The dynamic relationship simulation is a numerical modeling method based on historical data, which reflects the heat transfer interaction law between the core area and the outside during the seasonal cycle.

[0094] Correct the heat energy transfer efficiency of the diversion path according to the seasonal adaptation coefficient.

[0095] Specifically, for the corrected diversion efficiency , there are:

[0096] ;

[0097] In the formula, is the basic transmission efficiency, is the filling material density adjustment coefficient. When in winter is greater than 1, output a prompt to increase the filling density of the aluminum honeycomb core, such as increasing it by 20%, and synchronously increasing the turbine fan speed by 10%; when in summer is less than 1, output a prompt to replace part of the aluminum honeycomb core with phase change gypsum board and slow down the natural convection speed; when in the transitional season is approximately equal to 1, maintain the reference parameters and only fine-tune according to short-term temperature difference fluctuations. The correction instruction is sent to the actuator through the central controller.

[0098] Exemplarily, the summer adaptation coefficient , replace 30% of the aluminum honeycomb core in the core area with phase change gypsum board, and reduce the turbine fan speed to 85% of the reference value. After adjustment, the diversion efficiency , realizing the dynamic balance between the heat transfer rate and the cooling demand. Combining seasonal characteristics to multi-maintain and correct the diversion efficiency can not only suppress the overheating risk in summer but also ensure efficient recovery in winter, extending the system application cycle. Achieving intelligent optimization of the diversion path through seasonal adaptation. Combining the temperature difference gradient mapping table with seasonal correction enables the system to autonomously respond to periodic climate changes. After collaborating and complementing with cross-systems, the adjustment of the diversion efficiency further optimizes the energy supply-storage matching of external energy equipment, forming a full-link energy-saving closed-loop of "seasonal adaptation-efficiency correction-collaborative distribution".

[0099] Optionally, after dynamically controlling the flow rate of the waste heat air flow through the pressure difference, it further includes:

[0100] Collect the flow rate and pressure difference threshold of the waste heat air flow;

[0101] Specifically, the flow rate is the volume flow rate of the air flow in the diversion path measured in real time by an ultrasonic flowmeter or a differential pressure sensor, and the unit is m³ / s. The pressure difference threshold is the preset minimum effective pressure difference value in the thermosiphon effect gradient model. When the measured pressure difference is lower than this threshold, it is determined that the natural convection is insufficient. The data collection frequency is synchronized with the data collection sensor network of each wall panel partition, and the flow rate and pressure difference data are updated every 5 seconds and stored in the buffer of the edge computing module.

[0102] Among them, the flow rate of the waste heat air flow is the transfer speed of the recovered heat energy in the diversion path, reflecting the real-time efficiency of heat energy recovery. The pressure difference threshold is the critical pressure difference value for maintaining the stability of natural convection. When it is lower than this value, forced convection compensation needs to be started.

[0103] Dynamically adjust the rotational speed of the micro turbine fan based on the pressure difference threshold to generate a flow rate equilibrium feedback signal.

[0104] Specifically, the dynamic adjustment uses a fuzzy control algorithm. The percentage of the pressure difference deviating from the threshold is input into the controller, and the corresponding increment or decrement of the rotational speed of the turbine fan is output. For the rotational speed adjustment amount , there is:

[0105] ;

[0106] In the formula, is the proportionality coefficient, is the integral coefficient, is the pressure difference threshold, is the measured pressure difference, represents the cumulative amount of the deviation at all time points from the initial moment to the current moment. The flow rate equilibrium feedback signal is a report on the flow rate stability after the system self-checks after the rotational speed adjustment. When the flow rate volatility ≤ 3%, it is regarded as equilibrium.

[0107] Among them, the fuzzy control algorithm is an imprecise control method that combines empirical rules and continuous variable processing, and is suitable for the pressure difference dynamic fluctuation scenario. The flow rate equilibrium feedback signal is the self-check result of the system after the turbine fan is adjusted, and is used to evaluate the compensation effect of forced convection.

[0108] Exemplarily, assume that the proportionality coefficient is 2, the integral coefficient is 0.5, the target pressure difference, that is, the pressure difference threshold, is 100 Pa, and the measured pressure difference is 80 Pa. The calculated rotational speed adjustment amount is 50. The system increases the rotational speed of the turbine fan by 50 RPM. After 10 seconds, the pressure difference returns to 95 Pa, and the flow rate volatility drops to 2.5%. The feedback signal is marked as "equilibrium". Through the closed-loop adjustment mechanism, the diversion stability is quickly restored, avoiding the response lag caused by manual intervention. Through the real-time closed-loop control of the flow rate and pressure difference, the dynamic stability of the waste heat diversion is enhanced. After the diversion path design and the turbine fan compensation are coordinated, a complementary mechanism of "natural convection as the main - forced convection as the auxiliary" is formed. Combined with the electric energy compensation strategy, it is ensured that high-efficiency waste heat recovery can still be maintained during the low pressure difference period. This combined effect enables the system to have adaptive robustness under complex working conditions, avoiding the efficiency conflict between mechanical compensation and natural convection in traditional methods.

[0109] Based on the same inventive concept, as Figure 3 shown, the present invention also provides a waste heat recovery system for prefabricated building wall panels. The system includes:

[0110] A zoning module, configured to obtain the embedded structure parameters of the prefabricated building wall panel, and generate the zoning structure parameters of the wall panel based on the embedded structure parameters, where the zoning structure parameters include the sizes and positions of the core heat generation area, the edge conduction area, and the energy storage interface area;

[0111] A diversion path planning module, configured to generate thermosiphon gradient parameters by using a preset thermosiphon effect gradient model according to the partition structure parameters, and configure a diversion path for the wall panel cavity based on the thermosiphon gradient parameters;

[0112] A control module, configured to dynamically control the flow rate of the waste heat air flow according to the pressure difference by means of a micro-turbine fan device deployed according to the diversion path, and obtain real-time temperature data and flow rate data of each wall panel partition based on the partition structure parameters, and generate a dynamic thermal regulation instruction;

[0113] An execution module, configured to divide the waste heat into a primary heat network and a secondary heat network according to a preset gradient based on the dynamic thermal regulation instruction, and allocate them to corresponding terminal devices.

[0114] It should be noted that the electrical connections between the above-mentioned various units do not necessarily mean direct connections of the circuits. Indirect connection methods, as long as they can achieve the purpose of the present invention, are applicable to the embodiments of the present invention. The above are only exemplary embodiments of the present invention, and the scope of the present invention cannot be limited thereby.

[0115] That is, any equivalent changes and modifications made in accordance with the teachings of the present invention still fall within the scope covered by the present invention. After considering the specification and the disclosure of the practical truth, those skilled in the art will easily think of other implementation schemes of the present invention. This application aims to cover any variations, uses or adaptive changes of the present invention, and these variations, uses or adaptive changes follow the general principles of the present invention and include common general knowledge or conventional technical means in the technical field not recorded in the present invention.

Claims

1. Method for recovering waste heat of prefabricated building wall panels, characterized in that, The method includes: Obtaining the embedded structure parameters of the prefabricated building wall panel, and generating the partition structure parameters of the wall panel based on the embedded structure parameters, where the partition structure parameters include the sizes and positions of the core heating area, the edge conduction area, and the energy storage interface area; According to the partition structure parameters, using a preset thermosyphon effect gradient model to generate thermosyphon gradient parameters, and configuring the flow path of the wall panel cavity based on the thermosyphon gradient parameters; where generating the thermosyphon gradient parameters includes: establishing a temperature difference gradient mapping table between the wall panel cavity and the external environment; selecting aluminum honeycomb core or phase change gypsum board as the filling material for the core heating area based on the temperature difference gradient mapping table; extracting features from the temperature difference gradient mapping table and the filling material to obtain the thermosyphon gradient parameters; Deploying a micro turbine fan device according to the flow path, dynamically controlling the flow rate of the waste heat air flow through the pressure difference; and obtaining the real-time temperature data and flow rate data of each wall panel partition based on the partition structure parameters, and generating a dynamic thermal regulation instruction; where obtaining the real-time temperature data and flow rate data of each wall panel partition based on the partition structure parameters includes: identifying the abnormal heat surge area in the real-time temperature data that exceeds a preset threshold; in response to the abnormal heat surge area, generating a water cooling compensation instruction and starting the capillary network and external spray cooling device built in the wall panel; Based on the dynamic thermal regulation instruction, dividing the waste heat into a primary heat network and a secondary heat network according to a preset gradient, and distributing them to the corresponding terminal devices; where distributing to the corresponding terminal devices includes distributing the waste heat of the primary heat network to the domestic hot water system; distributing the waste heat of the secondary heat network to the heating system or the energy storage interface according to a preset priority; where, distributing to the heating system or the energy storage interface according to a preset priority includes: extracting the real-time status data of the external energy equipment, and the external energy equipment includes a solar water heater and a ground source heat pump; matching the extraction path of the remaining heat energy based on the real-time status data, and generating a cross-system collaborative distribution instruction; Wherein, after configuring the flow path of the wall panel cavity based on the thermosyphon gradient parameters, it further includes: Simulating the dynamic relationship between the core heating area and the ambient temperature in different seasons, and generating a season adaptation coefficient; Correcting the heat energy transmission efficiency of the flow path according to the season adaptation coefficient; Wherein, after generating the water cooling compensation instruction, it includes: Extracting the historical temperature fluctuation data of the abnormal heat surge area, and predicting the subsequent heat surge cycle; Adjusting the spray trigger frequency according to the prediction result.

2. The waste heat recovery method for the prefabricated building wall panel according to claim 1, characterized in that, The generating of the cross-system collaborative distribution instruction includes: Obtaining the time-of-use electricity price data of the power grid, and preprocessing to generate peak period and valley period marks; Based on the peak period and valley period marks, calculating the electricity price peak-valley difference within a continuous preset period; Generating an electric auxiliary heating trigger threshold according to the electricity price peak-valley difference and the user load demand; When the electricity price peak-valley difference is greater than or equal to the electric auxiliary heating trigger threshold and the valley period mark is detected, dynamically adjusting the heating power based on the real-time power grid load signal; Storing the heat energy output by the electric auxiliary heating device into the phase change energy storage wall panel, and feeding back the heat storage status through a temperature sensor.

3. The waste heat recovery method for the prefabricated building wall panel according to claim 1, wherein After dynamically controlling the flow rate of the waste heat gas flow through the pressure difference, the following steps are further included: Collect the flow rate of the waste heat gas flow and the pressure difference threshold value; Based on the pressure difference threshold value, dynamically adjust the rotation speed of the micro-turbine fan to generate a flow rate equalization feedback signal.

4. Prefabricated building wall panel waste heat recovery system, applied to the prefabricated building wall panel waste heat recovery method described in any one of claims 1-3, characterized in that, The system includes: A zoning module, configured to obtain the embedded structure parameters of the prefabricated building wall panel, and generate the zoning structure parameters of the wall panel based on the embedded structure parameters, where the zoning structure parameters include the sizes and positions of the core heat generation area, the edge conduction area, and the energy storage interface area; A diversion path planning module, configured to generate thermosiphon gradient parameters by using a preset thermosiphon effect gradient model according to the zoning structure parameters, and configure the diversion path of the wall panel cavity based on the thermosiphon gradient parameters; where generating the thermosiphon gradient parameters includes: establishing a temperature difference gradient mapping table between the wall panel cavity and the external environment; selecting aluminum honeycomb core or phase change gypsum board as the filling material for the core heat generation area based on the gradient mapping table; performing feature extraction on the temperature difference gradient mapping table and the filling material to obtain the thermosiphon gradient parameters; A control module, configured to dynamically control the flow rate of the waste heat gas flow through the pressure difference according to the micro-turbine fan device deployed in the diversion path, and obtain the real-time temperature data and flow rate data of each wall panel zone based on the zoning structure parameters to generate a dynamic heat regulation instruction; where obtaining the real-time temperature data and flow rate data of each wall panel zone based on the zoning structure parameters includes: identifying the abnormal heat surge area in the real-time temperature data that exceeds the preset threshold; in response to the abnormal heat surge area, generating a water cooling compensation instruction and starting the capillary network and the external spray cooling device built in the wall panel; An execution module, configured to divide the waste heat into a primary heat network and a secondary heat network according to a preset gradient based on the dynamic heat regulation instruction, and distribute them to the corresponding terminal devices; where distributing to the corresponding terminal devices includes distributing the waste heat of the primary heat network to the domestic hot water system; distributing the waste heat of the secondary heat network to the heating system or the energy storage interface according to a preset priority; where, distributing to the heating system or the energy storage interface according to a preset priority includes: extracting the real-time status data of the external energy equipment, and the external energy equipment includes a solar water heater and a ground source heat pump; matching the extraction path of the remaining heat energy based on the real-time status data to generate a cross-system collaborative distribution instruction; Where, after configuring the diversion path of the wall panel cavity based on the thermosiphon gradient parameters, the following steps are further included: Simulate the dynamic relationship between the core heat generation area and the ambient temperature in different seasons to generate a season adaptation coefficient; Correct the heat energy transmission efficiency of the diversion path according to the season adaptation coefficient; Where, after generating the water cooling compensation instruction, the following steps are included: Extract the historical temperature fluctuation data of the abnormal heat surge area and predict the subsequent heat surge cycle; Adjust the spray trigger frequency according to the prediction result.

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