A high-temperature flue gas waste heat recovery power generation system and method based on molten salt heat storage

Abstract

This invention discloses a high-temperature flue gas waste heat recovery power generation system and method based on molten salt thermal storage, belonging to the field of waste heat power generation technology. This invention collects the operating status parameters of each thermal storage module and analyzes the thermal equilibrium state and flow channel freezing risk state among the modules based on these parameters. Based on the thermal equilibrium state and freezing risk state, it determines the heat coordination and allocation relationship between modules. Based on the heat coordination and allocation relationship, it performs supplementary heating control on high-freezing-risk areas and generates an anti-freezing control strategy. The anti-freezing control strategy is executed, and dynamic compensation and adjustment are performed according to real-time temperature changes. This effectively reduces the risk of molten salt flow channel freezing, reduces pipe blockage, equipment downtime, and maintenance costs caused by molten salt solidification, and improves the safety, stability, and power generation efficiency of the high-temperature flue gas waste heat recovery power generation system.

Description

Technical Field

[0001] This invention relates to the field of waste heat power generation technology, specifically a high-temperature flue gas waste heat recovery power generation system and method based on molten salt thermal storage. Background Technology

[0002] Existing industrial waste heat molten salt thermal storage systems mostly use fixed thermal storage units in conjunction with external circulating heat exchange structures to achieve heat storage and release. Under high-temperature waste heat recovery and intermittent operation conditions, due to the low-temperature solidification characteristics of the molten salt medium, when the system is in a state of start-stop switching, local low load or ambient temperature fluctuation, problems such as local temperature drop, molten salt crystallization blockage and uneven heat exchange are likely to occur, which in turn affect the heat storage and release efficiency and the system operation stability. While some existing modular thermal storage systems can improve the flexibility of equipment layout, most of them lack effective heat coordination and dynamic adjustment mechanisms between the thermal storage modules, making it difficult to achieve a balanced distribution of thermal energy within the system. At the same time, traditional antifreeze measures usually rely on active heating or high-flow circulation to maintain the temperature, resulting in high system operating energy consumption and difficulty in balancing temperature maintenance effect and operational stability under complex operating conditions. Therefore, how to achieve coordinated heat regulation and waste heat recycling among modules in a modular molten salt thermal storage system, reduce the risk of molten salt freezing, and improve the thermal stability and operational reliability of the system under start-up, shutdown, and complex operating conditions has become a technical problem that needs to be solved in the field of industrial waste heat storage. Summary of the Invention

[0003] The purpose of this invention is to provide a high-temperature flue gas waste heat recovery power generation system and method based on molten salt thermal storage, so as to solve the problems raised in the prior art.

[0004] To solve the above-mentioned technical problems, the present invention provides the following technical solution: a method for high-temperature flue gas waste heat recovery and power generation based on molten salt thermal storage, the method comprising: Step S100: Collect the operating status parameters of each thermal storage module, and analyze the thermal equilibrium status and flow channel freezing risk status among the thermal storage modules based on the operating status parameters. Step S200: Based on the thermal equilibrium state and freezing risk state, determine the heat coordination and allocation relationship between modules; Step S300: Based on the heat coordination and allocation relationship, perform heat replenishment control on high-freezing-risk areas and generate anti-freezing control strategies; Step S400: Execute the anti-freeze control strategy and make dynamic compensation adjustments based on real-time temperature changes.

[0005] Furthermore, step S100 includes: The operating status parameters include the average temperature of the high-temperature molten salt chamber, the average temperature of the low-temperature molten salt chamber, the inlet temperature of the flow channel, the outlet temperature of the flow channel, and the module operating power; Based on the difference between the average temperature of the high-temperature molten salt chamber and the average temperature of the low-temperature molten salt chamber of each thermal storage module, the effective temperature difference between the two chambers of the corresponding thermal storage module is calculated. Based on the ratio of the change in the effective temperature difference between the two chambers within a preset time interval to the corresponding time interval, the rate of change of the effective temperature difference between the two chambers of the corresponding thermal storage module is calculated. The average effective temperature difference change rate of the dual chambers of each thermal storage module is calculated to obtain the average effective temperature difference change rate of the dual chambers of the system. Based on the difference between the effective temperature difference change rate of the dual chambers of each thermal storage module and the average effective temperature difference change rate of the dual chambers of the system, the thermal deviation coefficient of the corresponding thermal storage module is calculated. Based on the statistical dispersion of each thermal deviation coefficient, the thermal uniformity of the system is calculated. The statistical dispersion is the standard deviation of each thermal deviation coefficient and the average value of the thermal deviation coefficient. Based on the temperature difference between the lowest temperature and the safe temperature threshold of each flow channel within a preset time window, and the duration of the temperature being below the safe temperature threshold, the difference is multiplied by the duration to calculate the low temperature accumulation index of the corresponding flow channel. The low temperature accumulation index is then divided by the preset maximum low temperature accumulation index to calculate the freezing sensitivity coefficient of the corresponding flow channel. The cooling rate of the corresponding flow channel is calculated based on the ratio of the change in flow channel outlet temperature within a preset time interval to the corresponding time interval. The preset system characteristic cooling rate is used as a reference value. The cooling rate is divided by the reference value to obtain the normalized cooling rate. The freezing sensitivity coefficient of each flow channel is weighted and summed with the normalized cooling rate of the corresponding flow channel to obtain the freezing risk value of the corresponding flow channel. Flow channels with freezing risk values ​​greater than a preset risk threshold are identified as target high-risk flow channels. Based on the physical connectivity between flow channels, the freezing propagation correlation between the target high-risk flow channels and adjacent flow channels is established, and a flow channel freezing risk topology map is generated based on the freezing propagation correlation. Based on the freezing risk value of the flow channel in each thermal storage module and the risk propagation path length and adjacent flow channel risk influence weight in the flow channel freezing risk topology map, the freezing risk value of each flow channel in the corresponding thermal storage module is calculated by propagation attenuation weighting to obtain the module freezing risk index of the corresponding thermal storage module. The system thermal equilibrium degree and the module freezing risk index are normalized respectively. The normalized system thermal equilibrium degree and the module freezing risk index are weighted and summed to obtain the comprehensive freezing risk evaluation value. Summarize the comprehensive freezing risk assessment value corresponding to the historical operation records, calculate the standard deviation 'a' of the comprehensive freezing risk assessment value, and presuppose that there are 'b' freezing risk levels. The range of each freezing risk level is {[A1, A1+1×a), [A1+1×a, A1+2×a), ..., [A1+b×a, A2]}, where A1 and A2 represent the minimum and maximum values ​​of the comprehensive freezing risk assessment value, respectively. Divide the freezing risk level of each thermal storage module and output the corresponding freezing risk level identifier. By establishing the effective temperature difference and its rate of change between the average temperature of the high-temperature molten salt chamber and the average temperature of the low-temperature molten salt chamber, dynamic characterization parameters of the thermal state of the thermal storage module are established. Furthermore, the thermal deviation coefficient and the system thermal equilibrium degree are introduced to achieve quantitative analysis of the uniformity of heat distribution inside the system. This enables accurate identification of local thermal imbalance phenomena and improves the ability to perceive abnormal thermal states of the thermal storage system. By using the difference between the lowest temperature in the flow channel and the safe temperature threshold, as well as the duration of low temperature, a low temperature accumulation index is constructed, and a freezing sensitivity coefficient is further formed. This not only considers whether the temperature is below the threshold, but also comprehensively reflects the intensity and duration of the low temperature effect, which can effectively avoid misjudgment caused by instantaneous temperature fluctuations and improve the accuracy of freezing risk identification. By combining the characteristics of temperature change at the flow channel outlet to calculate the cooling rate, and by establishing a freezing risk value in conjunction with the freezing sensitivity coefficient, a comprehensive analysis of the flow channel temperature evolution trend and freezing development speed can be achieved. This can identify potential freezing risks in advance and enhance the timeliness of risk warning. Based on the risk propagation path length and the influence weight of adjacent channels, the propagation attenuation weighted calculation of channel risk is performed to form a module freezing risk index, realizing the aggregated analysis from channel-level risk to module-level risk. This can more comprehensively reflect the overall freezing status of the thermal storage module and improve the reliability of risk assessment results.

[0006] Furthermore, step S200 includes: Obtain the freezing risk level identifier, module freezing risk index, system thermal balance and remaining thermal storage capacity for each thermal storage module, and select target high-risk thermal storage modules whose freezing risk level is higher than the preset level threshold based on the freezing risk level identifier. Information on adjacent thermal storage modules corresponding to each target high-risk thermal storage module is obtained. The system thermal balance, remaining thermal storage capacity, and module freezing risk index corresponding to each adjacent thermal storage module are extracted. The system thermal balance, remaining thermal storage capacity, and module freezing risk index are normalized respectively. Based on the normalized system thermal balance, remaining thermal storage capacity, and module freezing risk index, the module thermal allocation priority coefficient P=H×c1+R×c2-F×c3 of the corresponding adjacent thermal storage module is calculated, where H represents the normalized system thermal balance, R represents the normalized remaining thermal storage capacity, F represents the normalized module freezing risk index, and c1, c2, and c3 represent the weight coefficients of system thermal balance, remaining thermal storage capacity, and module freezing risk index, respectively. According to the priority coefficient of module heat allocation from high to low, each adjacent thermal storage module is sorted, and the adjacent thermal storage module ranked in the top Z position is selected as the target heating module. The target heating module is then controlled to allocate heat to the corresponding target high-risk thermal storage module. The heat allocation process includes obtaining the freezing risk value, channel length, and channel inlet temperature of each target high-risk channel within the target high-risk thermal storage module. Based on the freezing risk value, channel length, and the temperature difference between the channel inlet temperature and the safe temperature threshold, the required anti-freezing heat replenishment demand G = (v × e × h × T) × M × (1 + d1 × L + d2 × T) for the corresponding target high-risk channel is calculated, where v represents the volume of molten salt in the channel, e represents the density of molten salt, h represents the specific heat capacity of molten salt, M represents the freezing risk value, L represents the channel length, T represents the temperature difference, and d1 and d2 represent the channel length influence coefficient and the temperature difference influence coefficient, respectively. Based on the molten salt transport path length between the target heating module and the target high-risk thermal storage module, the pipeline heat dissipation coefficient, and the molten salt transport time, the heat loss compensation value Q = u × L1 × t during the heat transport process is calculated, where u represents the pipeline heat dissipation coefficient, L1 represents the molten salt transport path length between the target heating module and the target high-risk thermal storage module, and t represents the molten salt transport time. Based on the anti-freezing heat replenishment demand and heat loss compensation value corresponding to each target high-risk flow channel, the cumulative calculation is performed to obtain the target output heat corresponding to the target heating module. Based on the target output heat, the corresponding molten salt flow direction, single allocation flow rate, and allocation duration are determined. Based on the determined molten salt flow direction, single allocation flow rate, and allocation duration, the inter-module heat coordination allocation relationship between each thermal storage module is generated. High-risk screening of thermal storage modules based on freezing risk level identification can quickly locate target high-risk thermal storage modules with potential freezing hazards, enabling targeted heat intervention in key risk areas, improving the accuracy and real-time performance of system anti-freezing control. By comprehensively considering the system thermal balance, remaining thermal storage capacity, and module freezing risk index of adjacent thermal storage modules, a module heat allocation priority coefficient is constructed. Through normalization processing, the influence of different parameter dimensions is eliminated, achieving unified evaluation and ranking under multi-dimensional operating conditions. This can effectively select thermal storage modules with stable thermal state, sufficient thermal storage capacity, and low freezing risk as heat sources, improving the rationality of heat allocation. By prioritizing the selection of target heating modules, the problem of local overload caused by traditional random or fixed-path heat allocation can be avoided, the overall heat resource utilization efficiency of the system can be enhanced, and the internal thermal balance of the thermal storage system can be maintained. By combining the freezing risk value of the target high-risk flow channel, the flow channel length, and the temperature difference between the inlet temperature and the safe temperature threshold, a model of anti-freezing heat replenishment demand can be established. This model not only considers the severity of freezing risk, but also comprehensively reflects the flow channel structural characteristics and actual temperature status, which can more accurately determine the actual heat replenishment demand of each high-risk flow channel and improve the precision of heat allocation. By incorporating the molten salt transport path length, pipeline heat dissipation coefficient, and transport time into the heat loss compensation calculation process, dynamic correction of heat loss during heat transport can be achieved. This avoids insufficient heat replenishment due to transport heat loss and improves the accuracy and effectiveness of the actual heat obtained by the target thermal storage module.

[0007] Furthermore, step S300 includes: Obtain the low temperature accumulation index, cooling rate, freezing risk value, and target input heat corresponding to the target high-risk flow channel in each target high-risk thermal storage module, and calculate the required heating power per unit length of the corresponding target high-risk flow channel W=G / (L×t1), based on the flow channel length, molten salt volume, and temperature difference between the flow channel inlet temperature and the safe temperature threshold of each target high-risk flow channel. Electric heat tracing auxiliary units are set at intervals along the flow path of each target high-risk flow path. Based on the required supplementary heating power per unit length of the corresponding target high-risk flow path, the required number of corresponding electric heat tracing auxiliary units is calculated as N=(W×L) / Y, where Y represents the rated output power of a single electric heat tracing auxiliary unit. The required number is rounded up. Based on the flow path length and the required number of electric heat tracing auxiliary units, the deployment interval distance x=L / (N-1) of the electric heat tracing auxiliary units is calculated, and they are deployed at intervals according to the deployment interval distance. Obtain the curved flow channel area, pipe connection interface area and valve connection area in each target high-risk flow channel, and extract the freezing sensitivity coefficient of the corresponding area. For local areas where the freezing sensitivity coefficient is greater than the preset sensitivity threshold, add additional heat tracing compensation power based on the heat compensation power required per unit length of the corresponding target high-risk flow channel. Calculate the additional heat tracing compensation power W1=r×W×L', where r represents the freezing sensitivity coefficient and L' represents the length of the local area. Based on the target input heat, molten salt flow direction, single allocation flow rate and allocation duration in the heat coordination and allocation relationship between modules, and combined with the output power, running time and additional heat tracing compensation power of each electric heat tracing auxiliary unit, an anti-freezing control strategy for the corresponding high-risk thermal storage module is generated. By acquiring the low-temperature accumulation index, cooling rate, and freezing risk value of the target high-risk flow channel, and combining it with the target input heat in the heat coordination and allocation relationship between modules, a comprehensive analysis of the actual heat gap in the flow channel can be conducted. This can more accurately identify potential freezing areas inside the flow channel and improve the pertinence and reliability of anti-freezing control. Based on the flow channel length, molten salt volume, and the temperature difference between the inlet temperature and the safe temperature threshold, the required heating power per unit length is calculated, enabling a quantitative analysis of the flow channel heat demand. This makes the configuration of the electric heat tracing auxiliary unit more in line with actual operating conditions, avoiding the problems of insufficient heating or energy waste caused by traditional experience-based configuration. The number of electric heat tracing auxiliary units deployed is determined based on the required heat supplementation power per unit length, and the deployment interval is automatically calculated in combination with the flow channel length to achieve uniform distribution of electric heat tracing auxiliary units along the flow channel. This can effectively improve the overall temperature field uniformity of the flow channel and reduce the probability of local low temperature areas. By identifying easily frozen areas such as curved flow channel areas, pipe connection interface areas, and valve connection areas, and introducing a freezing sensitivity coefficient for local risk assessment, highly sensitive areas that are difficult to cover by traditional uniform heat supplementation methods can be accurately identified, thereby improving the anti-freezing capability of key areas. Additional heat tracing compensation power is added to local areas where the freezing sensitivity coefficient is greater than the preset sensitivity threshold, so that the local high-risk areas can receive additional heat compensation, which can effectively reduce the local freezing problem caused by rapid heat loss at elbows, interfaces and valves, and improve the safety of system operation. By combining the output power and operating time of the electric heat tracing auxiliary unit with the additional heat tracing compensation power in local areas to generate an anti-freezing control strategy, the heat tracing operating parameters can be dynamically adjusted according to the risk status of different flow channels, improving the flexibility and intelligence of anti-freezing control. It realizes the integrated management of the entire process of risk identification, heat tracing demand analysis, optimized deployment of heat tracing units, and local key heat supplementation control for high-risk flow channels, which can improve the automation level of anti-freezing control of thermal storage systems and reduce the cost of manual inspection and maintenance.

[0008] Furthermore, step S400 includes: The generated anti-freezing control strategy is executed in real time, and the inlet temperature, outlet temperature, real-time freezing risk value, and remaining heat storage capacity of the target heating module are collected according to the preset detection cycle for each target high-risk flow channel. When the outlet temperature of the target high-risk flow channel is detected to be higher than the safe temperature threshold, and the real-time freezing risk value is lower than the preset risk threshold within a preset number of consecutive detection cycles, the single-time flow rate and the output power of the electric heat tracing auxiliary unit are gradually reduced according to the preset attenuation ratio. During the execution of the anti-freezing control strategy, the remaining heat storage capacity of the target heating module is monitored in real time. When the remaining heat storage capacity of the target heating module is lower than the preset lower limit threshold, the adjacent heat storage module with the highest priority coefficient for heat allocation is reselected from the corresponding adjacent heat storage modules as the new target heating module, and the corresponding heat coordination and allocation relationship between modules is updated. By collecting the inlet temperature, outlet temperature, real-time freezing risk value, and remaining heat storage capacity of the target high-risk flow channel in real time according to the preset detection cycle, the operating status of the heat storage system can be continuously obtained, realizing dynamic monitoring of the flow channel thermal status and freezing risk, and improving the real-time performance and accuracy of anti-freezing control. By jointly judging the flow channel outlet temperature and the real-time freezing risk value, when the flow channel outlet temperature is higher than the safe temperature threshold and the freezing risk is lower than the preset risk threshold for multiple consecutive detection cycles, the single-time flow rate and the output power of the electric heat tracing auxiliary unit are gradually reduced. This can prevent the system from operating at high power for a long time, thereby reducing energy consumption and improving thermal energy utilization efficiency. By gradually reducing the heat distribution flow rate and electric heat tracing output power according to a preset attenuation ratio, compared with the traditional method of directly stopping the heat tracing or suddenly reducing the power, the risk of secondary freezing caused by the rapid drop in flow channel temperature can be effectively avoided, thus improving the stability of system operation. By monitoring the remaining heat storage capacity of the target heating module in real time, the insufficient heat status of the target heating module can be identified in a timely manner, avoiding the rapid decay of heat storage capacity due to the continuous output of a single heating module. This improves the overall heating continuity of the heat storage system, realizes dynamic switching of the heating path, effectively avoids the problem of anti-freezing failure caused by the depletion of heat in a local heat storage module, realizes the adaptive redistribution of heat resources within the heat storage system, and forms a linkage heat compensation mechanism between multiple heat storage modules, which can improve the overall heat allocation capability and anti-freezing capability of the system. By combining real-time freezing risk assessment, dynamic adjustment of heat tracing power, and switching control of heating modules, the anti-freezing control strategy can be automatically adjusted according to different operating stages, improving the intelligence level and environmental adaptability of the anti-freezing control process. It can dynamically reduce unnecessary heat output and electric heat tracing operation load, thereby reducing system operating energy consumption, reducing aging problems caused by long-term full-load operation of electric heat tracing equipment, and extending equipment service life.

[0009] To better implement the above method, a high-temperature flue gas waste heat recovery power generation system based on molten salt thermal storage is also proposed. The system includes a high-temperature flue gas waste heat recovery power generation method based on molten salt thermal storage. The system is characterized by including a flow channel freezing risk status module, a module for coordinated heat allocation between modules, an anti-freezing control strategy module, and a dynamic compensation and adjustment module. Flow channel freezing risk status module: Collects the operating status parameters of each thermal storage module, and analyzes the thermal equilibrium status and flow channel freezing risk status between each thermal storage module based on the operating status parameters. Inter-module heat coordination and allocation relationship module: Based on the aforementioned thermal equilibrium state and freezing risk state, determine the inter-module heat coordination and allocation relationship; Anti-freezing control strategy module: Based on the heat coordination and allocation relationship, it performs heat replenishment control on high-freezing-risk areas and generates anti-freezing control strategies; Dynamic compensation adjustment module: Executes the anti-freeze control strategy and performs dynamic compensation adjustment based on real-time temperature changes.

[0010] Furthermore, the flow channel freezing risk status module includes a unit for generating a flow channel freezing risk topology map and a unit for determining the freezing risk level: The unit generating the flow channel freezing risk topology map: The operating status parameters include the average temperature of the high-temperature molten salt chamber, the average temperature of the low-temperature molten salt chamber, the flow channel inlet temperature, the flow channel outlet temperature, and the module operating power. Based on the difference between the average temperatures of the high-temperature and low-temperature molten salt chambers of each heat storage module, the effective temperature difference between the two chambers of the corresponding heat storage module is calculated. Based on the ratio of the change in the effective temperature difference between the two chambers within a preset time interval to the corresponding time interval, the rate of change of the effective temperature difference between the two chambers of the corresponding heat storage module is calculated. The rate of change of the effective temperature difference between the two chambers of each heat storage module is averaged to obtain the system average rate of change of the effective temperature difference between the two chambers. Based on the difference between the rate of change of the effective temperature difference between the two chambers of each heat storage module and the system average rate of change of the effective temperature difference between the two chambers, the thermal deviation coefficient of the corresponding heat storage module is calculated. Based on the statistical dispersion of each thermal deviation coefficient, the system thermal balance is calculated. The statistical dispersion is the standard deviation of each thermal deviation coefficient from the average thermal deviation coefficient. This is based on the flow channels within a preset time window. The temperature difference between the minimum temperature and the safe temperature threshold, and the duration of the temperature being below the safe temperature threshold, are multiplied by the difference and the duration to calculate the low temperature accumulation index of the corresponding flow channel. The low temperature accumulation index is divided by the preset maximum low temperature accumulation index to calculate the freezing sensitivity coefficient of the corresponding flow channel. The cooling rate of the corresponding flow channel is calculated based on the ratio of the change in the flow channel outlet temperature within a preset time interval to the corresponding time interval. The preset system characteristic cooling rate is used as a benchmark value. The cooling rate is divided by the benchmark value to calculate the normalized cooling rate. The freezing sensitivity coefficient of each flow channel is weighted and summed with the normalized cooling rate of the corresponding flow channel to calculate the freezing risk value of the corresponding flow channel. Flow channels with freezing risk values ​​greater than the preset risk threshold are identified as target high-risk flow channels. Based on the physical connectivity between flow channels, a freezing propagation correlation relationship is established between the target high-risk flow channels and adjacent flow channels. A flow channel freezing risk topology map is generated based on the freezing propagation correlation relationship. Determine the freezing risk level unit: Based on the freezing risk value corresponding to the flow channel within each thermal storage module, the risk propagation path length in the flow channel freezing risk topology map, and the risk impact weight of adjacent flow channels, perform propagation attenuation weighted calculation on the freezing risk value of each flow channel within the corresponding thermal storage module to obtain the module freezing risk index of the corresponding thermal storage module. Normalize the system thermal equilibrium degree and the module freezing risk index respectively. Weight the normalized system thermal equilibrium degree and the module freezing risk index to calculate the comprehensive freezing risk evaluation value. Summarize the comprehensive freezing risk evaluation values ​​corresponding to historical operation records to calculate the range of each freezing risk level. Divide each thermal storage module into freezing risk levels and output the corresponding freezing risk level identifier.

[0011] Furthermore, the module for inter-module heat coordination and allocation includes a unit for calculating the priority coefficient of inter-module heat allocation and a unit for generating inter-module heat coordination and allocation relationships: The module thermal allocation priority coefficient calculation unit: obtains the freezing risk level identifier, module freezing risk index, system thermal balance and remaining thermal storage capacity corresponding to each thermal storage module; filters out target high-risk thermal storage modules whose freezing risk level is higher than the preset level threshold based on the freezing risk level identifier; obtains the information of adjacent thermal storage modules corresponding to each target high-risk thermal storage module; extracts the system thermal balance, remaining thermal storage capacity and module freezing risk index corresponding to each adjacent thermal storage module; and normalizes the system thermal balance, remaining thermal storage capacity and module freezing risk index respectively; and calculates the module thermal allocation priority coefficient of the corresponding adjacent thermal storage module based on the normalized system thermal balance, remaining thermal storage capacity and module freezing risk index. The inter-module heat coordination and allocation unit: Adjacent thermal storage modules are sorted according to their heat allocation priority coefficients from high to low. The adjacent thermal storage module ranked in the top Z position is selected as the target heating module, and the target heating module is controlled to allocate heat to the corresponding high-risk thermal storage module. The heat allocation process includes obtaining the freezing risk value, channel length, and channel inlet temperature of each high-risk channel within the target high-risk thermal storage module. Based on the freezing risk value, channel length, and the temperature difference between the channel inlet temperature and the safe temperature threshold, the required anti-freezing heat replenishment demand for the corresponding high-risk channel is calculated. Based on the length of the molten salt transport path between the target heating module and the target high-risk thermal storage module, the pipeline heat dissipation coefficient, and the molten salt transport time, the heat loss compensation value during the heat transport process is calculated. Based on the anti-freezing heat replenishment demand and heat loss compensation value corresponding to each target high-risk flow channel, the target output heat corresponding to the target heating module is calculated by summing them up. Based on the target output heat, the corresponding molten salt flow direction, single allocation flow rate, and allocation duration are determined. Based on the determined molten salt flow direction, single allocation flow rate, and allocation duration, the inter-module heat coordination allocation relationship between each thermal storage module is generated.

[0012] Furthermore, the anti-freezing control strategy module includes a unit for calculating the required heat compensation power per unit length and a unit for calculating the additional heat tracing compensation power. Unit for calculating the required supplementary heating power per unit length: Obtain the low temperature accumulation index, cooling rate, freezing risk value, and target input heat corresponding to the target high-risk flow channel in each target high-risk thermal storage module, and calculate the required supplementary heating power per unit length of the corresponding target high-risk flow channel based on the flow channel length, molten salt volume, and temperature difference between the flow channel inlet temperature and the safe temperature threshold. Calculate the additional heat tracing compensation power unit: Obtain the curved flow channel area, pipe connection interface area and valve connection area in each target high-risk flow channel, and extract the freezing sensitivity coefficient of the corresponding area. For local areas where the freezing sensitivity coefficient is greater than the preset sensitivity threshold, add additional heat tracing compensation power based on the heat compensation power required per unit length of the corresponding target high-risk flow channel, and calculate the additional heat tracing compensation power.

[0013] Furthermore, the dynamic compensation adjustment module includes an adjustment output unit and a redistribution unit: Adjustment output unit: Executes the generated anti-freezing control strategy in real time, and collects the inlet temperature, outlet temperature, real-time freezing risk value, and remaining heat storage capacity of the target heating module for each target high-risk flow channel according to the preset detection cycle. When the outlet temperature of the target high-risk flow channel is detected to be higher than the safe temperature threshold, and the real-time freezing risk value is lower than the preset risk threshold for a continuous preset number of detection cycles, the single adjustment flow rate and the output power of the electric heat tracing auxiliary unit are gradually reduced according to the preset attenuation ratio. Reallocation Unit: During the execution of the anti-freeze control strategy, the remaining heat storage capacity of the target heating module is monitored in real time. When the remaining heat storage capacity of the target heating module is lower than the preset lower limit threshold, the adjacent heat storage module with the highest priority coefficient for heat allocation is selected from the corresponding adjacent heat storage modules as the new target heating module, and the corresponding heat coordination and allocation relationship between modules is updated.

[0014] Compared with the prior art, the beneficial effects of the present invention are: by collecting operating status parameters such as the average temperature of the high-temperature molten salt chamber, the average temperature of the low-temperature molten salt chamber, the inlet temperature of the flow channel, the outlet temperature of the flow channel, and the operating power of the module, the thermal equilibrium status and the flow channel freezing risk status of each thermal storage module are jointly analyzed. This not only reflects the overall thermal distribution of the thermal storage system, but also identifies local low-temperature abnormal areas in advance, thereby improving the accuracy and real-time performance of the operating status judgment of the high-temperature flue gas waste heat recovery system. By introducing the effective temperature difference change rate of the dual chamber, the thermal deviation coefficient, and the system thermal balance, the thermal imbalance state between the thermal storage modules is quantitatively analyzed. In addition, a flow channel freezing risk topology map is established by combining the freezing sensitivity coefficient, cooling rate, and freezing propagation correlation. This enables dynamic prediction and propagation analysis of freezing risks. Compared with the single-point temperature threshold judgment method in the existing technology, it can identify potential freezing risks earlier and improve the system's early warning capability. Based on the freezing risk level, system thermal balance, remaining heat storage capacity, and module freezing risk index, a module heat allocation priority coefficient is constructed, and target heating modules are selected accordingly. This enables coordinated heat allocation among heat storage modules, which can accurately supplement heat to high-risk areas while ensuring the overall thermal stability of the system, avoiding local freezing, reducing unnecessary heat consumption, improving waste heat utilization efficiency, and more accurately determining the target output heat and molten salt allocation parameters. This improves heat delivery matching, reduces heat waste, and enhances the economic efficiency of system operation. It can effectively reduce the risk of molten salt channel freezing, reduce pipe blockage, equipment downtime and maintenance costs caused by molten salt solidification, and improve the safety, stability and power generation efficiency of high-temperature flue gas waste heat recovery power generation system. Attached Figure Description

[0015] Figure 1 This is a schematic diagram of a high-temperature flue gas waste heat recovery power generation system based on molten salt thermal storage according to the present invention. Detailed Implementation

[0016] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0017] Please see Figure 1 This invention provides a technical solution: a method for high-temperature flue gas waste heat recovery and power generation based on molten salt thermal storage, the method comprising: Step S100: Collect the operating status parameters of each thermal storage module, and analyze the thermal equilibrium status and flow channel freezing risk status among the thermal storage modules based on the operating status parameters. Step S100 includes: The operating status parameters include the average temperature of the high-temperature molten salt chamber, the average temperature of the low-temperature molten salt chamber, the inlet temperature of the flow channel, the outlet temperature of the flow channel, and the module operating power; Based on the difference between the average temperature of the high-temperature molten salt chamber and the average temperature of the low-temperature molten salt chamber of each thermal storage module, the effective temperature difference between the two chambers of the corresponding thermal storage module is calculated. Based on the ratio of the change in the effective temperature difference between the two chambers within a preset time interval to the corresponding time interval, the rate of change of the effective temperature difference between the two chambers of the corresponding thermal storage module is calculated. The average effective temperature difference change rate of the dual chambers of each thermal storage module is calculated to obtain the average effective temperature difference change rate of the dual chambers of the system. Based on the difference between the effective temperature difference change rate of the dual chambers of each thermal storage module and the average effective temperature difference change rate of the dual chambers of the system, the thermal deviation coefficient of the corresponding thermal storage module is calculated. Based on the statistical dispersion of each thermal deviation coefficient, the thermal uniformity of the system is calculated. The statistical dispersion is the standard deviation of each thermal deviation coefficient and the average value of the thermal deviation coefficient. Based on the temperature difference between the lowest temperature and the safe temperature threshold of each flow channel within a preset time window, and the duration of the temperature being below the safe temperature threshold, the difference is multiplied by the duration to calculate the low temperature accumulation index of the corresponding flow channel. The low temperature accumulation index is then divided by the preset maximum low temperature accumulation index to calculate the freezing sensitivity coefficient of the corresponding flow channel. The cooling rate of the corresponding flow channel is calculated based on the ratio of the change in flow channel outlet temperature within a preset time interval to the corresponding time interval. The preset system characteristic cooling rate is used as a reference value. The cooling rate is divided by the reference value to obtain the normalized cooling rate. The freezing sensitivity coefficient of each flow channel is weighted and summed with the normalized cooling rate of the corresponding flow channel to obtain the freezing risk value of the corresponding flow channel. Flow channels with freezing risk values ​​greater than a preset risk threshold are identified as target high-risk flow channels. Based on the physical connectivity between flow channels, the freezing propagation correlation between the target high-risk flow channels and adjacent flow channels is established, and a flow channel freezing risk topology map is generated based on the freezing propagation correlation. Based on the freezing risk value of the flow channel in each thermal storage module and the risk propagation path length and adjacent flow channel risk influence weight in the flow channel freezing risk topology map, the freezing risk value of each flow channel in the corresponding thermal storage module is calculated by propagation attenuation weighting to obtain the module freezing risk index of the corresponding thermal storage module. The system thermal equilibrium degree and the module freezing risk index are normalized respectively. The normalized system thermal equilibrium degree and the module freezing risk index are weighted and summed to obtain the comprehensive freezing risk evaluation value. Summarize the comprehensive freezing risk assessment value corresponding to the historical operation records, calculate the standard deviation 'a' of the comprehensive freezing risk assessment value, and presuppose that there are 'b' freezing risk levels. The range of each freezing risk level is {[A1, A1+1×a), [A1+1×a, A1+2×a), ..., [A1+b×a, A2]}, where A1 and A2 represent the minimum and maximum values ​​of the comprehensive freezing risk assessment value, respectively. Divide the freezing risk level of each thermal storage module and output the corresponding freezing risk level identifier. For example, in a sintering waste heat recovery power generation system of a steel plant, three parallel molten salt thermal storage modules are set up, denoted as thermal storage module M1, thermal storage module M2 and thermal storage module M3 respectively. Each thermal storage module has four heat exchange channels. The system uses binary molten salt as the thermal storage medium. The normal operating temperature range is 280℃-565℃, the safe temperature threshold is set at 285℃, the system sampling cycle is set at 5min, the freezing risk analysis time window is set at 30min, and the preset maximum low temperature cumulative index is set at 600. During a certain operating cycle, the average temperature of the high-temperature molten salt chamber of thermal storage module M1 was 548℃, the average temperature of the low-temperature molten salt chamber was 326℃, the inlet temperature of the flow channel was 534℃, the outlet temperature of the flow channel was 318℃, and the module's operating power was 4.8MW; the average temperature of the high-temperature molten salt chamber of thermal storage module M2 was 541℃, the average temperature of the low-temperature molten salt chamber was 331℃, the inlet temperature of the flow channel was 528℃, the outlet temperature of the flow channel was 315℃, and the module's operating power was 4.6MW; the average temperature of the high-temperature molten salt chamber of thermal storage module M3 was 556℃, the average temperature of the low-temperature molten salt chamber was 302℃, the inlet temperature of the flow channel was 540℃, the outlet temperature of the flow channel was 291℃, and the module's operating power was 5.1MW. The effective temperature difference between the two chambers is calculated based on the difference between the average temperature of the high-temperature molten salt chamber and the average temperature of the low-temperature molten salt chamber of each thermal storage module. The effective temperature difference between the two chambers of thermal storage module M1 is 548-326=222℃, the effective temperature difference between the two chambers of thermal storage module M2 is 541-331=210℃, and the effective temperature difference between the two chambers of thermal storage module M3 is 556-302=254℃. Combining the data from the previous sampling period, the effective temperature difference between the two chambers in the previous period is 226℃ for M1, 214℃ for M2, and 261℃ for M3. Therefore, the rate of change of the effective temperature difference between the two chambers is calculated to be -0.8℃ / min for M1, -0.8℃ / min for M2, and -1.4℃ / min for M3. The average effective temperature difference change rate of each thermal storage module's dual chambers was calculated, yielding an average effective temperature difference change rate of -1.0℃ / min. Thermal deviation coefficients were calculated based on the difference between the effective temperature difference change rate of each module's dual chambers and the system average. Specifically, the thermal deviation coefficients for M1, M2, and M3 were 0.2 and 0.4, respectively, with an average thermal deviation coefficient of 0.267. The standard deviation of each thermal deviation coefficient relative to the average was 0.094. Based on this, the system's thermal equilibrium was calculated to be 0.906. Taking the four channels in the thermal storage module M3 as an example, within a 30-minute time window, the lowest temperature detected in channel C1 was 282℃, which was 3℃ below the safe temperature threshold, and lasted for 10 minutes; the lowest temperature in channel C2 was 279℃, which was 6℃ below the safe temperature threshold, and lasted for 18 minutes; the lowest temperature in channel C3 was 287℃, which was not below the safe temperature threshold; and the lowest temperature in channel C4 was 276℃, which was 9℃ below the safe temperature threshold, and lasted for 22 minutes. Based on this, the calculated low-temperature cumulative indices were 30, 108, 0, and 198, respectively. Further dividing these indices by the preset maximum low-temperature cumulative index of 600℃·min yielded freezing sensitivity coefficients of 0.050, 0.180, 0, and 0.330, respectively. The measured outlet temperature of flow channel C1 decreased from 288℃ to 282℃ at a rate of 1.2℃ / min; flow channel C2 decreased from 288℃ to 279℃ at a rate of 1.8℃ / min; flow channel C3 decreased from 291℃ to 287℃ at a rate of 0.8℃ / min; and flow channel C4 decreased from 287℃ to 276℃ at a rate of 2.2℃ / min. A system characteristic cooling rate of 1℃ / min was set as the baseline value, and the cooling rates were normalized during calculation. Freezing temperature was also considered. With the freezing sensitivity coefficient weighted at 0.7 and the cooling rate weighted at 0.3, the freezing risk values ​​are calculated as follows: C1 = freezing sensitivity coefficient × freezing sensitivity coefficient weight + normalized cooling rate × cooling rate weight = 0.050 × 0.7 + 1.2 × 0.3 = 0.395, C2 = 0.180 × 0.7 + 1.8 × 0.3 = 0.666, C3 = 0 × 0.7 + 0.8 × 0.3 = 0.240, C4 = 0.330 × 0.7 + 2.2 × 0.3 = 0.891; With a freezing risk threshold set at 0.65, channels C2 and C4 are identified as high-risk channels. Based on the physical connectivity of the channels within the thermal storage module M3, the freezing propagation relationship is established as C4→C2→C1→C3, and a channel freezing risk topology map is generated. Assuming the influence weight of adjacent channels is 0.8 and the risk propagation path length attenuation factor is 0.85, after propagation attenuation, the propagation influence value of C4 on C2 is freezing risk value × adjacent channel influence weight × risk propagation path length attenuation factor = 0.891 × 0.8 × 0.85 = 0.606, and the propagation influence value of C2 on C1 is 0.666 × 0.8 × 0.85 = 0.453. Based on the combined freezing risk values ​​of each flow channel and the propagation attenuation effect, the freezing risk index of thermal storage module M3 was calculated, yielding a freezing risk index of 0.742. Similarly, the freezing risk index of module M1 was calculated to be 0.281, and the freezing risk index of module M2 was calculated to be 0.337. The system thermal equilibrium degree of 0.906 was normalized to 0.906, and the normalized freezing risk indices were kept at their original values. Assuming the thermal equilibrium weight is 0.4 and the freezing risk weight is 0.6, the comprehensive freezing risk evaluation values ​​are as follows: M1 = Thermal equilibrium weight × Normalized system thermal equilibrium degree + × Freezing risk weight × Freezing risk index = 0.4 × 0.906 + 0.6 × 0.281 = 0.531, M2 = 0.4 × 0.906 + 0.6 × 0.337 = 0.565, M3 = 0.4 × 0.906 + 0.6 × 0.742 = 0.808. The system retrieved historical operation records for the past 180 days, obtaining a total of 2160 sets of comprehensive freezing risk assessment values. The standard deviation was calculated to be a = 0.097. The number of freezing risk levels was set to b = 4. The historical minimum comprehensive freezing risk assessment value A1 = 0.320, and the maximum value A2 = 0.920. Therefore, the freezing risk level intervals are divided as follows: Level I [0.320, 0.417), Level II [0.417, 0.514), Level III [0.514, 0.611), and Level IV [0.611, 0.920]. Based on this, the comprehensive freezing risk assessment value for thermal storage module M1 is determined to be 0.531, corresponding to Level III freezing risk; the comprehensive freezing risk assessment value for thermal storage module M2 is 0.565, corresponding to Level III freezing risk; and the comprehensive freezing risk assessment value for thermal storage module M3 is 0.808, corresponding to Level IV freezing risk.

[0018] Step S200: Based on the thermal equilibrium state and freezing risk state, determine the heat coordination and allocation relationship between modules; Step S200 includes: Obtain the freezing risk level identifier, module freezing risk index, system thermal balance and remaining thermal storage capacity for each thermal storage module, and select target high-risk thermal storage modules whose freezing risk level is higher than the preset level threshold based on the freezing risk level identifier. Information on adjacent thermal storage modules corresponding to each target high-risk thermal storage module is obtained. The system thermal balance, remaining thermal storage capacity, and module freezing risk index corresponding to each adjacent thermal storage module are extracted. The system thermal balance, remaining thermal storage capacity, and module freezing risk index are normalized respectively. Based on the normalized system thermal balance, remaining thermal storage capacity, and module freezing risk index, the module thermal allocation priority coefficient P=H×c1+R×c2-F×c3 of the corresponding adjacent thermal storage module is calculated, where H represents the normalized system thermal balance, R represents the normalized remaining thermal storage capacity, F represents the normalized module freezing risk index, and c1, c2, and c3 represent the weight coefficients of system thermal balance, remaining thermal storage capacity, and module freezing risk index, respectively. According to the priority coefficient of module heat allocation from high to low, each adjacent thermal storage module is sorted, and the adjacent thermal storage module ranked in the top Z position is selected as the target heating module. The target heating module is then controlled to allocate heat to the corresponding target high-risk thermal storage module. The heat allocation process includes obtaining the freezing risk value, channel length, and channel inlet temperature of each target high-risk channel within the target high-risk thermal storage module. Based on the freezing risk value, channel length, and the temperature difference between the channel inlet temperature and the safe temperature threshold, the required anti-freezing heat replenishment demand G = (v × e × h × T) × M × (1 + d1 × L + d2 × T) for the corresponding target high-risk channel is calculated, where v represents the volume of molten salt in the channel, e represents the density of molten salt, h represents the specific heat capacity of molten salt, M represents the freezing risk value, L represents the channel length, T represents the temperature difference, and d1 and d2 represent the channel length influence coefficient and the temperature difference influence coefficient, respectively. Based on the molten salt transport path length between the target heating module and the target high-risk thermal storage module, the pipeline heat dissipation coefficient, and the molten salt transport time, the heat loss compensation value Q = u × L1 × t during the heat transport process is calculated, where u represents the pipeline heat dissipation coefficient, L1 represents the molten salt transport path length between the target heating module and the target high-risk thermal storage module, and t represents the molten salt transport time. Based on the anti-freezing heat replenishment demand and heat loss compensation value corresponding to each target high-risk flow channel, the cumulative calculation is performed to obtain the target output heat corresponding to the target heating module. Based on the target output heat, the corresponding molten salt flow direction, single allocation flow rate, and allocation duration are determined. Based on the determined molten salt flow direction, single allocation flow rate, and allocation duration, the inter-module heat coordination allocation relationship between each thermal storage module is generated. For example, based on the calculation results of step S100, the freezing risk level threshold is set to level III. That is, thermal storage modules with a freezing risk level higher than level III are identified as target high-risk thermal storage modules. Therefore, thermal storage module M3 is selected as the target high-risk thermal storage module. The current remaining thermal storage capacity of each thermal storage module is 72% for M1, 65% for M2, and 41% for M3. The system thermal balance is maintained at 0.906 as calculated in step S100. The system acquires information on adjacent thermal storage modules corresponding to the high-risk thermal storage module M3. Since the system adopts a parallel molten salt thermal storage structure, both M1 and M2 are considered adjacent thermal storage modules of M3. The system thermal equilibrium degree, remaining thermal storage capacity, and module freezing risk index corresponding to the adjacent thermal storage modules are extracted and normalized. Because the system thermal equilibrium degree is a global parameter, the normalized thermal equilibrium degree for both M1 and M2 is set to 0.906. Using the maximum remaining thermal storage capacity of 72% and the minimum of 41% as the normalization benchmark, the normalized value R of the remaining thermal storage capacity of M1 is then calculated. =(72-41) / (72-41)=1.000, the normalized value of the remaining thermal storage capacity of M2 is R=(65-41) / (72-41)=0.774. Taking the maximum value of the module freezing risk index of 0.742 and the minimum value of 0.281 as the normalization benchmark, the normalized value of the freezing risk index of module M1 is F=(0.281-0.281) / (0.742-0.281)=0, and the normalized value of the freezing risk index of module M2 is F=(0.337-0.281) / (0.742-0.281)=0.121. The system thermal balance weighting coefficient is set as c1=0.35, the remaining thermal storage margin weighting coefficient is set as c2=0.40, and the module freezing risk index weighting coefficient is set as c3=0.25. The module thermal allocation priority coefficients for M1 are calculated as P=0.906×0.35+1.000×0.40-0×0.25=0.717; and for M2 as P=0.906×0.35+0.774×0.40-0.121×0.25=0.596. After sorting the modules according to their thermal allocation priority coefficients from high to low, the result is M1>M2. The number of target heating modules is set as N=2. Therefore, M1 and M2 are selected as target heating modules and will be used together to allocate heat to the target high-risk thermal storage module M3. In M3, the high-risk flow channels include flow channels C2 and C4. Flow channel C2 has a freezing risk value of 0.666, a length of 14m, and an inlet temperature of 281℃. Flow channel C4 has a freezing risk value of 0.891, a length of 18m, and an inlet temperature of 278℃. The safe temperature threshold is still set at 285℃. Therefore, the temperature difference T for C2 is 285-281=4℃, and the temperature difference T for C4 is 285-278=7℃. Further testing revealed that the molten salt volume v in channel C2 was 0.82 m³, the molten salt density e was 1820 kg / m³, and the molten salt specific heat capacity h was 1.52 kJ / (kg·℃); the molten salt volume v in channel C4 was 0.95 m³, with other molten salt parameters remaining consistent. Assuming the influence coefficient of channel length d1 = 0.015 and the influence coefficient of temperature difference d2 = 0.020, the calculated antifreeze heat replenishment requirement for channel C2 was G = (0.82 × 1820 × 1.52 × 4) × 0.666 × (1 + 0.015 × 14 + 0.020 × 4) = 7654 kJ; the antifreeze heat replenishment requirement for channel C4 was G = (0.95 × 1820 × 1.52 × 7) × 0.891 × (1 + 0.015 × 18 + 0.020 × 7) = 19238 kJ. The measured molten salt transport path length L1 between M1 and M3 is 42m, and the molten salt transport path length L1 between M2 and M3 is 36m. The pipeline heat dissipation coefficient u is set to 0.45kJ / (m·min), and the molten salt transport time t is 8min. The calculated heat loss compensation values ​​Q between M1 and M3 are 0.45×42×8=151.2kJ and Q between M2 and M3 are 0.45×36×8=129.6kJ. Based on the antifreeze heat replenishment demand corresponding to the target high-risk flow channels C2 and C4 and the heat loss compensation values, the total output heat demand of the target M3 is obtained as 7654+19238+151.2+129.6=27172.8kJ. Of these, M1 accounts for 54.6% of the heating supply (0.717 / (0.717+0.596) = 45.4%), and M2 accounts for 45.4%. Based on this, the target heat output of M1 is approximately 14837 kJ, and the target heat output of M2 is approximately 12336 kJ. Assuming an average molten salt temperature of 540℃, a specific heat capacity of 1.52 kJ / (kg·℃), and a single allowable flow rate limit of 22 kg / s, the flow direction of the molten salt is determined to be M1→M3 and M2→M3 after conversion. The flow rate of M1 is set to 19 kg / s and the duration of M2 is set to 11 min. The flow rate of M2 is set to 16 kg / s and the duration of M2 is set to 10 min. Based on the molten salt flow direction, the flow rate of M2, and the duration of M2, the system generates a heat coordination relationship between modules and sends a control command to the execution control unit to prioritize the heating of the high-risk channels C2 and C4 to reduce the risk of freezing of the heat storage module M3.

[0019] Step S300: Based on the heat coordination and allocation relationship, perform heat replenishment control on high-freezing-risk areas and generate anti-freezing control strategies; Step S300 includes: Obtain the low temperature accumulation index, cooling rate, freezing risk value, and target input heat corresponding to the target high-risk flow channel in each target high-risk thermal storage module, and calculate the required heating power per unit length of the corresponding target high-risk flow channel W=G / (L×t1), based on the flow channel length, molten salt volume, and temperature difference between the flow channel inlet temperature and the safe temperature threshold of each target high-risk flow channel. Electric heat tracing auxiliary units are set at intervals along the flow path of each target high-risk flow path. Based on the required supplementary heating power per unit length of the corresponding target high-risk flow path, the required number of corresponding electric heat tracing auxiliary units is calculated as N=(W×L) / Y, where Y represents the rated output power of a single electric heat tracing auxiliary unit. The required number is rounded up. Based on the flow path length and the required number of electric heat tracing auxiliary units, the deployment interval distance x=L / (N-1) of the electric heat tracing auxiliary units is calculated, and they are deployed at intervals according to the deployment interval distance. Obtain the curved flow channel area, pipe connection interface area and valve connection area in each target high-risk flow channel, and extract the freezing sensitivity coefficient of the corresponding area. For local areas where the freezing sensitivity coefficient is greater than the preset sensitivity threshold, add additional heat tracing compensation power based on the heat compensation power required per unit length of the corresponding target high-risk flow channel. Calculate the additional heat tracing compensation power W1=r×W×L', where r represents the freezing sensitivity coefficient and L' represents the length of the local area. Based on the target input heat, molten salt flow direction, single allocation flow rate and allocation duration in the heat coordination and allocation relationship between modules, and combined with the output power, running time and additional heat tracing compensation power of each electric heat tracing auxiliary unit, an anti-freezing control strategy for the corresponding high-risk thermal storage module is generated. For example, if the preset heating time t1 is set to 12 min, the anti-freezing heating requirement G for channel C2 is 7654 kJ, and the channel length L is 14 m, then the heating power required per unit length of channel C2 is calculated as 7654 / (14 × 12) = 45.56 kJ / (m·min); the anti-freezing heating requirement G for channel C4 is 19238 kJ, and the channel length L is 18 m, then the heating power required per unit length of channel C4 is calculated as 19238 / (18 × 12) = 89.06 kJ / (m·min). Combining the freezing risk values ​​obtained in step S100, where the freezing risk value of C2 is 0.666 and the freezing risk value of C4 is 0.891, the system determines that channel C4 belongs to the highest priority heating channel and prioritizes the allocation of electric heat tracing resources. The system installs electric heat tracing auxiliary units at intervals along the flow path of the target high-risk flow channel. The rated output power Y of a single electric heat tracing auxiliary unit is set to 680 kJ / min. The required number of electric heat tracing auxiliary units is calculated based on the required supplementary heating power per unit length. The required number for flow channel C2 is (45.56 × 14) / 680 = 0.938, which, after rounding up, is determined to be one set of electric heat tracing auxiliary units. However, to ensure at least one effective deployment interval is formed, the number of electric heat tracing auxiliary units should not be less than two sets. Therefore, it is ultimately determined that two sets of electric heat tracing auxiliary units will be installed in flow channel C2. The required number of flow channels C4 is (89.06×18) / 680=2.357, which is rounded up to determine as 3 sets of electric heat tracing auxiliary units. The deployment interval is further calculated based on the flow channel length and the required number of electric heat tracing auxiliary units. The deployment interval of flow channel C2 is 14 / (2-1)=14m, that is, 1 set of electric heat tracing auxiliary units is deployed at the inlet and outlet ends of the flow channel respectively; the deployment interval of flow channel C4 is 18 / (3-1)=9m, that is, 3 sets of electric heat tracing auxiliary units are deployed in the inlet area, middle area and outlet area of ​​the flow channel respectively. Highly sensitive local areas were identified within the high-risk flow channels. Flow channel C2 was found to have a curved section, L', 2.5m long, 5m from the inlet, with a freezing sensitivity coefficient of 0.42. Flow channel C4 had a valve connection area, L', 1.8m long, 7m from the inlet, with a freezing sensitivity coefficient of 0.58, and a pipe connection interface area, L', 2.2m long, 3m from the outlet, with a freezing sensitivity coefficient of 0.63. With a freezing sensitivity threshold set at 0.40, these local areas were identified as key areas requiring additional heat tracing. For the aforementioned localized areas, the system adds additional heat tracing compensation power based on the required heat replenishment power per unit length of the corresponding high-risk flow channel. The additional heat tracing compensation power for the bend area of ​​flow channel C2 is calculated to be 0.42 × 45.56 × 2.5 = 47.84 kJ / min; the additional heat tracing compensation power for the valve connection area of ​​flow channel C4 is calculated to be 0.58 × 89.06 × 1.8 = 92.95 kJ / min; and the additional heat tracing compensation power for the pipe interface area of ​​flow channel C4 is calculated to be 0.63 × 89.06 × 2.2 = 123.45 kJ / min. Based on the results of the additional heat tracing compensation power, the system adds extra high-density electric heat tracing tape to the corresponding localized areas and increases the electric heat tracing output level of the corresponding areas to reduce the probability of localized freezing. Based on the inter-module heat coordination and allocation relationship generated in step S200, the system further generates an anti-freezing control strategy for the corresponding high-risk thermal storage module M3. M1 continuously supplies high-temperature molten salt to M3 for 11 minutes, maintaining a flow rate of 19 kg / s; M2 continuously supplies high-temperature molten salt to M3 for 10 minutes, maintaining a flow rate of 16 kg / s; the two sets of electric heat tracing auxiliary units corresponding to flow channel C2 are started simultaneously, with the single-unit operating power set at 650 kJ / min, and running continuously for 12 minutes; the three sets of electric heat tracing auxiliary units corresponding to flow channel C4 are started simultaneously, with the operating power of the electric heat tracing units corresponding to the inlet area and valve connection area increased to 760 kJ / min, and the middle area maintained at 680 kJ / min, running continuously for 15 minutes; for the C4 outlet interface area, the system additionally activates a local enhanced heat tracing mode, so that the corresponding additional heat tracing compensation power is maintained at 123.45 kJ / min.

[0020] Step S400: Execute the anti-freeze control strategy and make dynamic compensation adjustments based on real-time temperature changes; Step S400 includes: The generated anti-freezing control strategy is executed in real time, and the inlet temperature, outlet temperature, real-time freezing risk value, and remaining heat storage capacity of the target heating module are collected according to the preset detection cycle for each target high-risk flow channel. When the outlet temperature of the target high-risk flow channel is detected to be higher than the safe temperature threshold, and the real-time freezing risk value is lower than the preset risk threshold within a preset number of consecutive detection cycles, the single-time flow rate and the output power of the electric heat tracing auxiliary unit are gradually reduced according to the preset attenuation ratio. During the execution of the anti-freezing control strategy, the remaining heat storage capacity of the target heating module is monitored in real time. When the remaining heat storage capacity of the target heating module is lower than the preset lower limit threshold, the adjacent heat storage module with the highest priority coefficient for heat allocation is reselected from the corresponding adjacent heat storage modules as the new target heating module, and the corresponding heat coordination and allocation relationship between modules is updated. For example, when the system enters the dynamic compensation and adjustment phase, the real-time detection cycle is set to 2 minutes, the preset risk threshold is still 0.65, the number of continuous stable detection cycles is set to 3 times, the single allocation flow attenuation ratio is set to 10%, the output power attenuation ratio of the electric heat tracing auxiliary unit is set to 8%, and the remaining heat storage lower limit threshold of the target heating module is set to 35%. The system first executes the anti-freezing control strategy generated in step S300. Two minutes after the anti-freezing control strategy was implemented, the system collected data showing that the inlet temperature of flow channel C2 increased from 281℃ to 286℃, the outlet temperature increased from 279℃ to 283℃, and the real-time freezing risk value decreased from 0.666 to 0.592; the inlet temperature of flow channel C4 increased from 278℃ to 284℃, the outlet temperature increased from 276℃ to 281℃, and the real-time freezing risk value decreased from 0.891 to 0.742. Since the outlet temperature of flow channel C2 is still below the safe temperature threshold of 285℃, and the real-time freezing risk value of flow channel C4 is still higher than the preset risk threshold of 0.65, the system maintains the current inter-module heat coordination and the electric heat tracing output status unchanged. When the anti-freeze control strategy was in effect for 4 minutes, the system collected operating parameters again. It was found that the inlet temperature of flow channel C2 had further increased to 291℃ and the outlet temperature to 287℃, with the real-time freezing risk value decreasing to 0.468; the inlet temperature of flow channel C4 had increased to 289℃ and the outlet temperature to 285℃, with the real-time freezing risk value decreasing to 0.638. At this point, the outlet temperature of flow channel C2 was higher than the safe temperature threshold of 285℃, and the real-time freezing risk value was lower than 0.65; the outlet temperature of flow channel C4 had reached the safe temperature threshold, but the real-time freezing risk value was still close to the risk threshold. Therefore, the system only put the electric heat tracing auxiliary unit corresponding to flow channel C2 into observation mode and temporarily did not execute power attenuation control. When the anti-freeze control strategy was executed for 6 minutes, the system continued to perform real-time detection according to the 2-minute detection cycle. The detection showed that the outlet temperature of flow channel C2 remained at 288℃, and the real-time freezing risk value further decreased to 0.352; the outlet temperature of flow channel C4 increased to 289℃, and the real-time freezing risk value decreased to 0.521. Since the outlet temperatures of flow channels C2 and C4 were both higher than the safe temperature threshold of 285℃, and the real-time freezing risk value had been lower than the preset risk threshold of 0.65 for two consecutive detection cycles, the system recorded a stable operating state and continued to maintain the current adjustment parameters. When the anti-freezing control strategy was executed for 8 minutes, the system detected that the inlet temperature of flow channel C2 was 295℃ and the outlet temperature was 291℃, and the real-time freezing risk value decreased to 0.244; the inlet temperature of flow channel C4 was 297℃ and the outlet temperature was 292℃, and the real-time freezing risk value decreased to 0.418. Since the above two target high-risk flow channels have met the condition of "outlet temperature higher than the safe temperature threshold and real-time freezing risk value lower than the preset risk threshold" for three consecutive detection cycles, the system activated the dynamic attenuation adjustment mechanism. The system gradually reduces the single-time flow rate and the output power of the electric heat tracing auxiliary unit according to the preset attenuation ratio. Specifically, the flow rate from M1 to M3 is reduced from 19 kg / s to 17.1 kg / s, and the flow rate from M2 to M3 is reduced from 16 kg / s to 14.4 kg / s. The output power of the electric heat tracing auxiliary unit corresponding to flow channel C2 is reduced from 650 kJ / min to 598 kJ / min. The electric heat tracing output power in the inlet and outlet areas of flow channel C4 is reduced from 760 kJ / min to 699 kJ / min, and in the middle area from 680 kJ / min to 626 kJ / min. During the subsequent 10-minute operating cycle, the system continued to monitor the changes in the remaining heat storage capacity of the target heating modules. It was detected that the remaining heat storage capacity of heat storage module M1 decreased from 72% to 37%, and the remaining heat storage capacity of heat storage module M2 decreased from 65% to 52%. Since the remaining heat storage capacity of heat storage module M1 was close to the preset lower limit threshold of 35%, the system entered the heating module switching warning state in advance and recalculated the module heat allocation priority coefficient of adjacent heat storage modules. At this time, the system detected the addition of a backup heat storage module M4, whose current remaining heat storage capacity is 78%, and the module freeze risk index is 0.215. After normalization, the corresponding heat allocation priority coefficient calculation result is 0.906×0.35+1.000×0.40-0.000×0.25=0.717, which is higher than the 0.596 corresponding to the current heat storage module M2. Therefore, the system identified heat storage module M4 as the new backup target heating module. When the system reached the 12th minute, the remaining heat storage capacity of the heat storage module M1 further decreased to 34%, which is lower than the preset lower limit threshold of 35%. The system immediately implemented the dynamic switching mechanism for the heating modules, stopped the molten salt transport control between M1 and M3, and regenerated the heat coordination and allocation relationship between the modules. The new molten salt flow direction was adjusted to M4→M3 and M2→M3. The single allocation flow rate of M4 was set to 18 kg / s, and the continuous allocation time was set to 6 minutes. The single allocation flow rate of M2 remained unchanged at 14.4 kg / s. At the same time, the system synchronously adjusted the operating power of the electric heat tracing auxiliary units corresponding to the flow channels C2 and C4 to avoid the local temperature from dropping again due to the heating switching.

[0021] To better implement the above method, a high-temperature flue gas waste heat recovery power generation system based on molten salt thermal storage is also proposed. The system includes a flow channel freezing risk status module, a module for coordinated heat allocation between modules, an anti-freezing control strategy module, and a dynamic compensation and adjustment module. Flow channel freezing risk status module: Collects the operating status parameters of each thermal storage module, and analyzes the thermal equilibrium status and flow channel freezing risk status between each thermal storage module based on the operating status parameters. The flow channel freezing risk status module includes a unit for generating a flow channel freezing risk topology map and a unit for determining the freezing risk level. The unit generating the flow channel freezing risk topology map: The operating status parameters include the average temperature of the high-temperature molten salt chamber, the average temperature of the low-temperature molten salt chamber, the flow channel inlet temperature, the flow channel outlet temperature, and the module operating power. Based on the difference between the average temperatures of the high-temperature and low-temperature molten salt chambers of each heat storage module, the effective temperature difference between the two chambers of the corresponding heat storage module is calculated. Based on the ratio of the change in the effective temperature difference between the two chambers within a preset time interval to the corresponding time interval, the rate of change of the effective temperature difference between the two chambers of the corresponding heat storage module is calculated. The rate of change of the effective temperature difference between the two chambers of each heat storage module is averaged to obtain the system average rate of change of the effective temperature difference between the two chambers. Based on the difference between the rate of change of the effective temperature difference between the two chambers of each heat storage module and the system average rate of change of the effective temperature difference between the two chambers, the thermal deviation coefficient of the corresponding heat storage module is calculated. Based on the statistical dispersion of each thermal deviation coefficient, the system thermal balance is calculated. The statistical dispersion is the standard deviation of each thermal deviation coefficient from the average thermal deviation coefficient. This is based on the flow channels within a preset time window. The temperature difference between the minimum temperature and the safe temperature threshold, and the duration of the temperature being below the safe temperature threshold, are multiplied by the difference and the duration to calculate the low temperature accumulation index of the corresponding flow channel. The low temperature accumulation index is divided by the preset maximum low temperature accumulation index to calculate the freezing sensitivity coefficient of the corresponding flow channel. The cooling rate of the corresponding flow channel is calculated based on the ratio of the change in the flow channel outlet temperature within a preset time interval to the corresponding time interval. The preset system characteristic cooling rate is used as a benchmark value. The cooling rate is divided by the benchmark value to calculate the normalized cooling rate. The freezing sensitivity coefficient of each flow channel is weighted and summed with the normalized cooling rate of the corresponding flow channel to calculate the freezing risk value of the corresponding flow channel. Flow channels with freezing risk values ​​greater than the preset risk threshold are identified as target high-risk flow channels. Based on the physical connectivity between flow channels, a freezing propagation correlation relationship is established between the target high-risk flow channels and adjacent flow channels. A flow channel freezing risk topology map is generated based on the freezing propagation correlation relationship. Determine the freezing risk level unit: Based on the freezing risk value corresponding to the flow channel within each thermal storage module, the risk propagation path length in the flow channel freezing risk topology map, and the risk impact weight of adjacent flow channels, perform propagation attenuation weighted calculation on the freezing risk value of each flow channel within the corresponding thermal storage module to obtain the module freezing risk index of the corresponding thermal storage module. Normalize the system thermal equilibrium degree and the module freezing risk index respectively. Weight the normalized system thermal equilibrium degree and the module freezing risk index to calculate the comprehensive freezing risk evaluation value. Summarize the comprehensive freezing risk evaluation values ​​corresponding to historical operation records to calculate the range of each freezing risk level. Divide each thermal storage module into freezing risk levels and output the corresponding freezing risk level identifier.

[0022] Inter-module heat coordination and allocation relationship module: Based on the aforementioned thermal equilibrium state and freezing risk state, determine the inter-module heat coordination and allocation relationship; The module for inter-module heat coordination and allocation includes a unit for calculating the priority coefficient of heat allocation between modules and a unit for generating the inter-module heat coordination and allocation relationship. The module thermal allocation priority coefficient calculation unit: obtains the freezing risk level identifier, module freezing risk index, system thermal balance and remaining thermal storage capacity corresponding to each thermal storage module; filters out target high-risk thermal storage modules whose freezing risk level is higher than the preset level threshold based on the freezing risk level identifier; obtains the information of adjacent thermal storage modules corresponding to each target high-risk thermal storage module; extracts the system thermal balance, remaining thermal storage capacity and module freezing risk index corresponding to each adjacent thermal storage module; and normalizes the system thermal balance, remaining thermal storage capacity and module freezing risk index respectively; and calculates the module thermal allocation priority coefficient of the corresponding adjacent thermal storage module based on the normalized system thermal balance, remaining thermal storage capacity and module freezing risk index. The inter-module heat coordination and allocation unit: Adjacent thermal storage modules are sorted according to their heat allocation priority coefficients from high to low. The adjacent thermal storage module ranked in the top Z position is selected as the target heating module, and the target heating module is controlled to allocate heat to the corresponding high-risk thermal storage module. The heat allocation process includes obtaining the freezing risk value, channel length, and channel inlet temperature of each high-risk channel within the target high-risk thermal storage module. Based on the freezing risk value, channel length, and the temperature difference between the channel inlet temperature and the safe temperature threshold, the required anti-freezing heat replenishment demand for the corresponding high-risk channel is calculated. Based on the length of the molten salt transport path between the target heating module and the target high-risk thermal storage module, the pipeline heat dissipation coefficient, and the molten salt transport time, the heat loss compensation value during the heat transport process is calculated. Based on the anti-freezing heat replenishment demand and heat loss compensation value corresponding to each target high-risk flow channel, the target output heat corresponding to the target heating module is calculated by summing them up. Based on the target output heat, the corresponding molten salt flow direction, single allocation flow rate, and allocation duration are determined. Based on the determined molten salt flow direction, single allocation flow rate, and allocation duration, the inter-module heat coordination allocation relationship between each thermal storage module is generated.

[0023] Anti-freezing control strategy module: Based on the heat coordination and allocation relationship, it performs heat replenishment control on high-freezing-risk areas and generates anti-freezing control strategies; The anti-freezing control strategy module includes a unit for calculating the required heat compensation power per unit length and a unit for calculating the additional heat tracing compensation power. Unit for calculating the required supplementary heating power per unit length: Obtain the low temperature accumulation index, cooling rate, freezing risk value, and target input heat corresponding to the target high-risk flow channel in each target high-risk thermal storage module, and calculate the required supplementary heating power per unit length of the corresponding target high-risk flow channel based on the flow channel length, molten salt volume, and temperature difference between the flow channel inlet temperature and the safe temperature threshold. Calculate the additional heat tracing compensation power unit: Obtain the curved flow channel area, pipe connection interface area and valve connection area in each target high-risk flow channel, and extract the freezing sensitivity coefficient of the corresponding area. For local areas where the freezing sensitivity coefficient is greater than the preset sensitivity threshold, add additional heat tracing compensation power based on the heat compensation power required per unit length of the corresponding target high-risk flow channel, and calculate the additional heat tracing compensation power.

[0024] Dynamic compensation adjustment module: Executes the anti-freeze control strategy and performs dynamic compensation adjustment based on real-time temperature changes; The dynamic compensation adjustment module includes an adjustment output unit and a redistribution unit. Adjustment output unit: Executes the generated anti-freezing control strategy in real time, and collects the inlet temperature, outlet temperature, real-time freezing risk value, and remaining heat storage capacity of the target heating module for each target high-risk flow channel according to the preset detection cycle. When the outlet temperature of the target high-risk flow channel is detected to be higher than the safe temperature threshold, and the real-time freezing risk value is lower than the preset risk threshold for a continuous preset number of detection cycles, the single adjustment flow rate and the output power of the electric heat tracing auxiliary unit are gradually reduced according to the preset attenuation ratio. Reallocation Unit: During the execution of the anti-freeze control strategy, the remaining heat storage capacity of the target heating module is monitored in real time. When the remaining heat storage capacity of the target heating module is lower than the preset lower limit threshold, the adjacent heat storage module with the highest priority coefficient for heat allocation is selected from the corresponding adjacent heat storage modules as the new target heating module, and the corresponding heat coordination and allocation relationship between modules is updated.

[0025] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

Claims

1. A method for high-temperature flue gas waste heat recovery and power generation based on molten salt thermal storage, characterized in that, The methods include: Step S100: Collect the operating status parameters of each thermal storage module, and analyze the thermal equilibrium status and flow channel freezing risk status among the thermal storage modules based on the operating status parameters. Step S200: Based on the thermal equilibrium state and freezing risk state, determine the heat coordination and allocation relationship between modules; Step S300: Based on the heat coordination and allocation relationship, perform heat replenishment control on high-freezing-risk areas and generate anti-freezing control strategies; Step S400: Execute the anti-freeze control strategy and make dynamic compensation adjustments based on real-time temperature changes.

2. The method for high-temperature flue gas waste heat recovery and power generation based on molten salt thermal storage according to claim 1, characterized in that, Step S100 includes the following steps: The operating status parameters include the average temperature of the high-temperature molten salt chamber, the average temperature of the low-temperature molten salt chamber, the inlet temperature of the flow channel, the outlet temperature of the flow channel, and the module operating power; Based on the difference between the average temperature of the high-temperature molten salt chamber and the average temperature of the low-temperature molten salt chamber of each thermal storage module, the effective temperature difference between the two chambers of the corresponding thermal storage module is calculated. Based on the ratio of the change in the effective temperature difference between the two chambers within a preset time interval to the corresponding time interval, the rate of change of the effective temperature difference between the two chambers of the corresponding thermal storage module is calculated. The average effective temperature difference change rate of the dual chambers of each thermal storage module is calculated to obtain the average effective temperature difference change rate of the dual chambers of the system. Based on the difference between the effective temperature difference change rate of the dual chambers of each thermal storage module and the average effective temperature difference change rate of the dual chambers of the system, the thermal deviation coefficient of the corresponding thermal storage module is calculated. Based on the statistical dispersion of each thermal deviation coefficient, the thermal uniformity of the system is calculated. The statistical dispersion is the standard deviation of each thermal deviation coefficient and the average value of the thermal deviation coefficient. Based on the temperature difference between the lowest temperature and the safe temperature threshold of each flow channel within a preset time window, and the duration of the temperature being below the safe temperature threshold, the difference is multiplied by the duration to calculate the low temperature accumulation index of the corresponding flow channel. The low temperature accumulation index is then divided by the preset maximum low temperature accumulation index to calculate the freezing sensitivity coefficient of the corresponding flow channel. The cooling rate of the corresponding flow channel is calculated based on the ratio of the change in flow channel outlet temperature within a preset time interval to the corresponding time interval. The preset system characteristic cooling rate is used as a reference value. The cooling rate is divided by the reference value to obtain the normalized cooling rate. The freezing sensitivity coefficient of each flow channel is weighted and summed with the normalized cooling rate of the corresponding flow channel to obtain the freezing risk value of the corresponding flow channel. Flow channels with freezing risk values ​​greater than a preset risk threshold are identified as target high-risk flow channels. Based on the physical connectivity between flow channels, the freezing propagation correlation between the target high-risk flow channels and adjacent flow channels is established, and a flow channel freezing risk topology map is generated based on the freezing propagation correlation. Based on the freezing risk value of the flow channel in each thermal storage module and the risk propagation path length and adjacent flow channel risk influence weight in the flow channel freezing risk topology map, the freezing risk value of each flow channel in the corresponding thermal storage module is calculated by propagation attenuation weighting to obtain the module freezing risk index of the corresponding thermal storage module. The system thermal equilibrium degree and the module freezing risk index are normalized respectively. The normalized system thermal equilibrium degree and the module freezing risk index are weighted and summed to obtain the comprehensive freezing risk evaluation value. Summarize the comprehensive freezing risk assessment values ​​corresponding to historical operation records, calculate the standard deviation 'a' of the comprehensive freezing risk assessment values, and presuppose that there are 'b' freezing risk levels, each of which has a range of {[A1, A1+1×a), [A1+1×a, A1+2×a), ..., [A1+b×a, A2]}, where A1 and A2 represent the minimum and maximum values ​​of the comprehensive freezing risk assessment values, respectively. Divide each thermal storage module into freezing risk levels and output the corresponding freezing risk level identifier.

3. The method for high-temperature flue gas waste heat recovery and power generation based on molten salt thermal storage according to claim 1, characterized in that, Step S200 includes the following steps: Obtain the freezing risk level identifier, module freezing risk index, system thermal balance and remaining thermal storage capacity for each thermal storage module, and select target high-risk thermal storage modules whose freezing risk level is higher than the preset level threshold based on the freezing risk level identifier. Information on adjacent thermal storage modules corresponding to each target high-risk thermal storage module is obtained. The system thermal balance, remaining thermal storage capacity, and module freezing risk index corresponding to each adjacent thermal storage module are extracted. The system thermal balance, remaining thermal storage capacity, and module freezing risk index are normalized respectively. Based on the normalized system thermal balance, remaining thermal storage capacity, and module freezing risk index, the module thermal allocation priority coefficient P=H×c1+R×c2-F×c3 of the corresponding adjacent thermal storage module is calculated, where H represents the normalized system thermal balance, R represents the normalized remaining thermal storage capacity, F represents the normalized module freezing risk index, and c1, c2, and c3 represent the weight coefficients of system thermal balance, remaining thermal storage capacity, and module freezing risk index, respectively. According to the priority coefficient of module heat allocation from high to low, each adjacent thermal storage module is sorted, and the adjacent thermal storage module ranked in the top Z position is selected as the target heating module. The target heating module is then controlled to allocate heat to the corresponding target high-risk thermal storage module. The heat allocation process includes obtaining the freezing risk value, channel length, and channel inlet temperature of each target high-risk channel within the target high-risk thermal storage module. Based on the freezing risk value, channel length, and the temperature difference between the channel inlet temperature and the safe temperature threshold, the required anti-freezing heat replenishment demand G = (v × e × h × T) × M × (1 + d1 × L + d2 × T) for the corresponding target high-risk channel is calculated, where v represents the volume of molten salt in the channel, e represents the density of molten salt, h represents the specific heat capacity of molten salt, M represents the freezing risk value, L represents the channel length, T represents the temperature difference, and d1 and d2 represent the channel length influence coefficient and the temperature difference influence coefficient, respectively. Based on the molten salt transport path length between the target heating module and the target high-risk thermal storage module, the pipeline heat dissipation coefficient, and the molten salt transport time, the heat loss compensation value during the heat transport process is calculated as Q = u × L1 × t, where u represents the pipeline heat dissipation coefficient, L1 represents the molten salt transport path length between the target heating module and the target high-risk thermal storage module, and t represents the molten salt transport time. Based on the anti-freezing heat replenishment demand and heat loss compensation value corresponding to each target high-risk flow channel, the target output heat corresponding to the target heating module is calculated by summing the values. Based on the target output heat, the corresponding molten salt flow direction, single allocation flow rate, and allocation duration are determined. Based on the determined molten salt flow direction, single allocation flow rate, and allocation duration, the inter-module heat coordination allocation relationship between each thermal storage module is generated.

4. The method for high-temperature flue gas waste heat recovery and power generation based on molten salt thermal storage according to claim 1, characterized in that, Step S300 includes the following steps: Obtain the low temperature accumulation index, cooling rate, freezing risk value, and target input heat corresponding to the target high-risk flow channel in each target high-risk thermal storage module, and calculate the required heating power per unit length of the corresponding target high-risk flow channel W=G / (L×t1), based on the flow channel length, molten salt volume, and temperature difference between the flow channel inlet temperature and the safe temperature threshold of each target high-risk flow channel. Electric heat tracing auxiliary units are set at intervals along the flow path of each target high-risk flow path. Based on the required supplementary heating power per unit length of the corresponding target high-risk flow path, the required number of corresponding electric heat tracing auxiliary units is calculated as N=(W×L) / Y, where Y represents the rated output power of a single electric heat tracing auxiliary unit. The required number is rounded up. Based on the flow path length and the required number of electric heat tracing auxiliary units, the deployment interval distance x=L / (N-1) of the electric heat tracing auxiliary units is calculated, and they are deployed at intervals according to the deployment interval distance. Obtain the curved flow channel area, pipe connection interface area and valve connection area in each target high-risk flow channel, and extract the freezing sensitivity coefficient of the corresponding area. For local areas where the freezing sensitivity coefficient is greater than the preset sensitivity threshold, add additional heat tracing compensation power based on the heat compensation power required per unit length of the corresponding target high-risk flow channel. Calculate the additional heat tracing compensation power W1=r×W×L', where r represents the freezing sensitivity coefficient and L' represents the length of the local area. Based on the target input heat, molten salt flow direction, single allocation flow rate and allocation duration in the heat coordination and allocation relationship between modules, and combined with the output power, running time and additional heat tracing compensation power of each electric heat tracing auxiliary unit, an anti-freezing control strategy for the corresponding high-risk thermal storage module is generated.

5. A method for high-temperature flue gas waste heat recovery and power generation based on molten salt thermal storage according to claim 1, characterized in that, Step S400 includes the following steps: The generated anti-freezing control strategy is executed in real time, and the inlet temperature, outlet temperature, real-time freezing risk value, and remaining heat storage capacity of the target heating module are collected according to the preset detection cycle for each target high-risk flow channel. When the outlet temperature of the target high-risk flow channel is detected to be higher than the safe temperature threshold, and the real-time freezing risk value is lower than the preset risk threshold within a preset number of consecutive detection cycles, the single-time flow rate and the output power of the electric heat tracing auxiliary unit are gradually reduced according to the preset attenuation ratio. During the execution of the anti-freezing control strategy, the remaining heat storage capacity of the target heating module is monitored in real time. When the remaining heat storage capacity of the target heating module is lower than the preset lower limit threshold, the adjacent heat storage module with the highest priority coefficient for heat allocation is reselected from the corresponding adjacent heat storage modules as the new target heating module, and the corresponding heat coordination and allocation relationship between modules is updated.

6. A high-temperature flue gas waste heat recovery power generation system based on molten salt thermal storage, used to implement the high-temperature flue gas waste heat recovery power generation method based on molten salt thermal storage as described in any one of claims 1-5, characterized in that, The system includes a flow channel freezing risk status module, a module for coordinated heat distribution between modules, a freeze prevention control strategy module, and a dynamic compensation and adjustment module. The flow channel freezing risk status module collects the operating status parameters of each thermal storage module and analyzes the thermal equilibrium status and flow channel freezing risk status between each thermal storage module based on the operating status parameters. The module for inter-module heat coordination and allocation relationship: determines the inter-module heat coordination and allocation relationship based on the heat balance state and freezing risk state; The anti-freezing control strategy module: based on the heat coordination and allocation relationship, performs heat replenishment control on high-freezing-risk areas and generates an anti-freezing control strategy; The dynamic compensation adjustment module executes the anti-freeze control strategy and performs dynamic compensation adjustment based on real-time temperature changes.

7. A high-temperature flue gas waste heat recovery power generation system based on molten salt thermal storage according to claim 6, characterized in that, The flow channel freezing risk status module includes a unit for generating a flow channel freezing risk topology map and a unit for determining the freezing risk level: The generation of the flow channel freezing risk topology map unit: The operating status parameters include the average temperature of the high-temperature molten salt chamber, the average temperature of the low-temperature molten salt chamber, the flow channel inlet temperature, the flow channel outlet temperature, and the module operating power. Based on the difference between the average temperature of the high-temperature molten salt chamber and the average temperature of the low-temperature molten salt chamber of each heat storage module, the effective temperature difference between the two chambers of the corresponding heat storage module is calculated. Based on the ratio of the change in the effective temperature difference between the two chambers within a preset time interval to the corresponding time interval, the rate of change of the effective temperature difference between the two chambers of the corresponding heat storage module is calculated. The rate of change of the effective temperature difference between the two chambers of each heat storage module is averaged to obtain the system average rate of change of the effective temperature difference between the two chambers. Based on the difference between the rate of change of the effective temperature difference between the two chambers of each heat storage module and the system average rate of change of the effective temperature difference between the two chambers, the thermal deviation coefficient of the corresponding heat storage module is calculated. Based on the statistical dispersion of each thermal deviation coefficient, the system thermal balance is calculated. The statistical dispersion is the standard deviation of each thermal deviation coefficient from the average thermal deviation coefficient. Based on the flow channels within a preset time window... The temperature difference between the lowest temperature and the safe temperature threshold, and the duration of the temperature being below the safe temperature threshold, are multiplied by the difference and the duration to calculate the low temperature accumulation index of the corresponding flow channel. The low temperature accumulation index is divided by the preset maximum low temperature accumulation index to calculate the freezing sensitivity coefficient of the corresponding flow channel. The cooling rate of the corresponding flow channel is calculated based on the ratio of the change in the flow channel outlet temperature within a preset time interval to the corresponding time interval. The preset system characteristic cooling rate is used as a benchmark value. The cooling rate is divided by the benchmark value to calculate the normalized cooling rate. The freezing sensitivity coefficient of each flow channel is weighted and summed with the normalized cooling rate of the corresponding flow channel to calculate the freezing risk value of the corresponding flow channel. Flow channels with freezing risk values ​​greater than the preset risk threshold are identified as target high-risk flow channels. Based on the physical connectivity between flow channels, a freezing propagation correlation relationship is established between the target high-risk flow channel and adjacent flow channels. A flow channel freezing risk topology map is generated based on the freezing propagation correlation relationship. The step of determining the freezing risk level unit involves: based on the freezing risk value corresponding to the flow channel within each thermal storage module, the risk propagation path length in the flow channel freezing risk topology map, and the risk impact weight of adjacent flow channels, performing propagation attenuation weighted calculation on the freezing risk value of each flow channel within the corresponding thermal storage module to obtain the module freezing risk index of the corresponding thermal storage module; normalizing the system thermal equilibrium degree and the module freezing risk index respectively; weighted summing the normalized system thermal equilibrium degree and the module freezing risk index to calculate the comprehensive freezing risk evaluation value; summing the comprehensive freezing risk evaluation values ​​corresponding to historical operation records to calculate the range of each freezing risk level; classifying the freezing risk level of each thermal storage module; and outputting the corresponding freezing risk level identifier.

8. A high-temperature flue gas waste heat recovery power generation system based on molten salt thermal storage according to claim 6, characterized in that, The module for inter-module heat coordination and allocation includes a unit for calculating the priority coefficient of heat allocation between modules and a unit for generating the inter-module heat coordination and allocation relationship. The calculation module's thermal allocation priority coefficient unit: obtains the freezing risk level identifier, module freezing risk index, system thermal balance, and remaining thermal storage capacity corresponding to each thermal storage module; filters out target high-risk thermal storage modules whose freezing risk level is higher than a preset threshold based on the freezing risk level identifier; obtains information on adjacent thermal storage modules corresponding to each target high-risk thermal storage module; extracts the system thermal balance, remaining thermal storage capacity, and module freezing risk index corresponding to each adjacent thermal storage module; normalizes the system thermal balance, remaining thermal storage capacity, and module freezing risk index respectively; and calculates the module thermal allocation priority coefficient of the corresponding adjacent thermal storage module based on the normalized system thermal balance, remaining thermal storage capacity, and module freezing risk index. The heat coordination and allocation unit between the generation modules sorts adjacent thermal storage modules from high to low according to their heat allocation priority coefficients, selects the top Z-ranked adjacent thermal storage module as the target heating module, and controls the target heating module to allocate heat to the corresponding high-risk thermal storage module. The heat allocation process includes obtaining the freezing risk value, channel length, and channel inlet temperature of each target high-risk channel within the target high-risk thermal storage module, and calculating the required anti-freezing heat replenishment for the corresponding target high-risk channel based on the freezing risk value, channel length, and the temperature difference between the channel inlet temperature and the safe temperature threshold. The heat loss compensation value during heat transfer is calculated based on the molten salt transport path length, pipeline heat dissipation coefficient, and molten salt transport time between the target heating module and the target high-risk thermal storage module. Based on the anti-freezing heat replenishment demand and heat loss compensation value corresponding to each target high-risk flow channel, the target output heat corresponding to the target heating module is obtained by summing the values. Based on the target output heat, the corresponding molten salt flow direction, single allocation flow rate, and allocation duration are determined. Based on the determined molten salt flow direction, single allocation flow rate, and allocation duration, the inter-module heat coordination allocation relationship between each thermal storage module is generated.

9. A high-temperature flue gas waste heat recovery power generation system based on molten salt thermal storage according to claim 6, characterized in that, The anti-freezing control strategy module includes a unit for calculating the required heat replenishment power per unit length and a unit for calculating additional heat tracing compensation power. The unit for calculating the required supplementary heating power per unit length: obtains the low temperature accumulation index, cooling rate, freezing risk value, and target input heat corresponding to the target high-risk flow channel in each target high-risk thermal storage module, and calculates the required supplementary heating power per unit length of the corresponding target high-risk flow channel based on the flow channel length, molten salt volume, and temperature difference between the flow channel inlet temperature and the safe temperature threshold. The calculation of additional heat tracing compensation power unit: obtains the curved flow channel area, pipe connection interface area and valve connection area in each target high-risk flow channel, and extracts the freezing sensitivity coefficient of the corresponding area. For local areas where the freezing sensitivity coefficient is greater than the preset sensitivity threshold, the additional heat tracing compensation power is increased based on the heat compensation power required per unit length of the corresponding target high-risk flow channel, and the additional heat tracing compensation power is calculated.

10. A high-temperature flue gas waste heat recovery power generation system based on molten salt thermal storage according to claim 6, characterized in that, The dynamic compensation adjustment module includes an adjustment output unit and a redistribution unit: The regulating output unit executes the generated anti-freezing control strategy in real time and collects the inlet temperature, outlet temperature, real-time freezing risk value, and remaining heat storage capacity of the target heating module for each target high-risk flow channel according to a preset detection cycle. When the outlet temperature of the target high-risk flow channel is detected to be higher than the safe temperature threshold, and the real-time freezing risk value is lower than the preset risk threshold for a consecutive preset number of detection cycles, the single-time flow rate and the output power of the electric heat tracing auxiliary unit are gradually reduced according to a preset attenuation ratio. The reallocation unit: During the execution of the anti-freezing control strategy, it monitors the remaining heat storage capacity of the target heating module in real time. When the remaining heat storage capacity of the target heating module is lower than the preset lower limit threshold, it re-selects the adjacent heat storage module with the highest priority coefficient from the corresponding adjacent heat storage modules as the new target heating module, and updates the corresponding heat coordination and allocation relationship between modules.

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