A method and system for grading and recycling waste heat of kiln flue gas

Abstract

The application discloses a kind of kiln flue gas waste heat grading circulation power generation method and system, adopt multi-stage purification and temperature utilization combination, first, kiln flue gas is carried out component analysis and desulfurization purification treatment, establish layered purification chain and identify acid dew point area, form safe purification flue gas area by material adaptability evaluation and corrosion control measure;Then, temperature gradient analysis and temperature field reconstruction are carried out to purified flue gas, establish heat grade distribution mechanism and form cascade thermal energy flow, realize the complementary use of different temperature section heat source;Further, build the cascade power generation system of water vapor main cycle and organic working medium auxiliary cycle, integrate magnetic suspension bearing technology to improve auxiliary cycle power generation efficiency;Through heat matching degree monitoring and mismatch detection, establish heat balance parameter and optimize circulation network;Finally, build energy transfer matrix, through generator coupling analysis and speed coordination control, form distributed power generation configuration and complete stable electric energy output, realize the efficient use of waste heat.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of energy-saving management, in particular to a method and system for grading and circulating power generation of kiln flue gas waste heat. BACKGROUND

[0002] As an important equipment for industrial production, kiln is widely used in steel, cement, glass, ceramics and other industries. A large amount of high-temperature flue gas is generated during its operation. These flue gases contain rich waste heat resources and have great energy recovery potential. However, the composition of kiln flue gas is complex, containing sulfur dioxide, nitrogen oxides, particulate matter and other pollutants, and the temperature distribution is uneven, which brings technical challenges to the efficient utilization of waste heat.

[0003] The existing flue gas waste heat power generation technology mainly adopts a single cycle system, which can usually only utilize high-temperature section flue gas for power generation, and the utilization efficiency of medium and low-temperature section waste heat is low. The traditional method has shortcomings in dealing with the coordination between flue gas purification and waste heat recovery, and often has the problem that the purification effect and power generation efficiency are difficult to balance. At the same time, the operation mode of single generator set lacks flexibility and cannot adapt to the dynamic changes of flue gas parameters. Therefore, a method is needed to solve at least one of the above problems. SUMMARY

[0004] The present application discloses a method and system for grading and circulating power generation of kiln flue gas waste heat, which obtains kiln flue gas composition data and process parameter information, generates purified flue gas through desulfurization reaction and builds a layered purification chain, identifies the acid dew point area and reduces the corrosion intensity to form a purified flue gas area, analyzes the temperature gradient of the purified flue gas area to form a gradient thermal energy flow, establishes a complex power generation configuration and performs heat matching degree monitoring, finally builds an energy transfer matrix and forms a distributed power generation configuration, and realizes grading and circulating efficient power generation of kiln flue gas waste heat.

[0005] The present application discloses a method and system for grading and circulating power generation of kiln flue gas waste heat, which obtains kiln flue gas composition data and process parameter information, generates purified flue gas through desulfurization reaction and builds a layered purification chain, identifies the acid dew point area and reduces the corrosion intensity to form a purified flue gas area, analyzes the temperature gradient of the purified flue gas area to form a gradient thermal energy flow, establishes a complex power generation configuration and performs heat matching degree monitoring, finally builds an energy transfer matrix and forms a distributed power generation configuration, and realizes grading and circulating efficient power generation of kiln flue gas waste heat.

[0006] Obtain kiln flue gas composition data and process parameter information, generate purified flue gas through desulfurization reaction based on the kiln flue gas composition data, and build a layered purification chain based on the purified flue gas and the process parameter information;

[0007] Determine the pollutant-temperature mapping relationship through the layered purification chain and the purified flue gas, identify the acid dew point area through the pollutant-temperature mapping relationship, and reduce the corrosion intensity of the acid dew point area to form a purified flue gas area;

[0008] A temperature fluctuation curve is formed by performing temperature gradient analysis on the purified flue gas region, a temperature distribution field is generated by reconstructing a temperature field based on the temperature fluctuation curve, and a hierarchical thermal energy configuration is generated by allocating thermal grades based on the temperature distribution field, and a hierarchical thermal energy flow is formed by using the hierarchical thermal energy configuration to form complementary heat sources at different temperature segments to generate a cascade thermal energy flow.

[0009] A main water vapor cycle and an auxiliary organic working medium cycle are generated by performing cycle distribution on the hierarchical thermal energy flow, auxiliary cycle power is extracted by integrating magnetic suspension bearings into the auxiliary organic working medium cycle, and a cascade power generation configuration is formed by superimposing the auxiliary cycle power on the power generation output of the main water vapor cycle.

[0010] An operation state parameter is obtained by performing thermal matching degree monitoring on the cascade power generation configuration, a mismatch region is identified by performing thermal mismatch detection according to the operation state parameter, a thermal balance parameter is generated by performing compensation adjustment based on the mismatch region, and an optimized cycle network is generated by coupling the thermal balance parameter with the cascade power generation configuration.

[0011] An energy transfer matrix is constructed based on the optimized cycle network, a distributed power generation configuration is generated by performing generator coupling analysis on the energy transfer matrix, and stable power output is completed.

[0012] The second aspect of the present application proposes a furnace flue gas waste heat hierarchical cycle power generation system, comprising:

[0013] A desulfurization purification module is used to obtain furnace flue gas composition data and process parameter information, generate purified flue gas by performing desulfurization reaction based on the furnace flue gas composition data, and construct a layered purification chain based on the purified flue gas and the process parameter information.

[0014] A region generation module is used to determine a pollutant-temperature mapping relationship through the layered purification chain and the purified flue gas, identify an acid dew point region through the pollutant-temperature mapping relationship, and reduce the corrosion intensity of the acid dew point region to form a purified flue gas region.

[0015] A thermal energy configuration module is used to perform temperature gradient analysis on the purified flue gas region to form a temperature fluctuation curve, reconstruct a temperature field based on the temperature fluctuation curve to generate a temperature distribution field, allocate thermal grades based on the temperature distribution field to generate a hierarchical thermal energy configuration, and use the hierarchical thermal energy configuration to form complementary heat sources at different temperature segments to generate a hierarchical thermal energy flow.

[0016] A cascade power generation module is used to generate a main water vapor cycle and an auxiliary organic working medium cycle by performing cycle distribution on the hierarchical thermal energy flow, extract auxiliary cycle power by integrating magnetic suspension bearings into the auxiliary organic working medium cycle, and form a cascade power generation configuration by superimposing the auxiliary cycle power on the power generation output of the main water vapor cycle.

[0017] a balance optimization module, configured to acquire operation state parameters for heat matching degree monitoring of the cascade power generation configuration, to perform heat mismatch detection to identify a mismatch region according to the operation state parameters, to perform compensation adjustment to generate a heat balance parameter based on the mismatch region, and to perform coupling with the cascade power generation configuration based on the heat balance parameter to generate an optimized circulating network;

[0018] an electric energy output module, configured to construct an energy transfer matrix based on the optimized circulating network, to perform generator coupling analysis on the energy transfer matrix to generate a distributed power generation configuration, and to complete stable electric energy output.

[0019] The beneficial effects of the present application are embodied in the following aspects: first, by establishing a hierarchical purification chain and acid dew point control technology, deep purification of kiln flue gas and equipment corrosion protection are achieved. The acid dew point region is identified by using the pollutant-temperature mapping relationship, combined with corrosion-heat transfer collaborative analysis and material adaptability evaluation technology, the corrosion and heat transfer balance point is determined and the material configuration parameter is generated, which effectively reduces the corrosion risk of flue gas treatment equipment, converts the high-risk area of acid dew point into a safe operation area, prolongs the service life of the equipment, and creates a safe and reliable operation environment for waste heat recovery. Second, the cascade heat energy utilization and cascade power generation system is innovatively established, and through temperature gradient analysis and temperature field reconstruction technology, hierarchical heat energy configuration from high temperature to low temperature is realized. The construction of cascade heat energy flow makes different temperature segments of heat source form a complementary relationship, combined with the cascade power generation configuration of water vapor main cycle and organic working medium auxiliary cycle, and integrated with magnetic suspension bearing technology to improve the auxiliary cycle power generation efficiency, realizing the maximum utilization of waste heat resources and efficient collaborative operation of the power generation system. Finally, based on the system optimization control concept, a distributed coordinated power generation technology is constructed, which identifies the thermodynamic mismatch problem in system operation through heat matching degree monitoring and mismatch detection and performs compensation adjustment to generate an optimized circulating network. Generator coupling analysis is performed using the energy transfer matrix to realize speed differentiation coordination and frequency synchronization processing, forming a stable distributed power generation configuration, which improves the reliability and adaptability of the power generation system.

[0020] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit the present application. BRIEF DESCRIPTION OF DRAWINGS

[0021] The drawings herein show specific examples of the technical solutions described in the present application, and constitute part of the specification together with the specific embodiments, for explaining the technical solutions, principles and effects of the present application.

[0022] Figure 1 Figure 1 is a flowchart of a kiln flue gas waste heat hierarchical circulating power generation method according to the present application.

[0023] Figure 2This is a schematic diagram of the structure of the furnace flue gas purification system of the present invention.

[0024] Among them: 1-furnace, 2-gas analyzer, 3-temperature sensor, 4-pressure sensor, 5-flow sensor, 6-distributed control system, 7-desulfurization tower, 8-limestone slurry storage tank, 9-circulating pump, 10-oxidation fan, 11-low temperature economizer, 12-wet electrostatic precipitator, 13-SCR reactor, 14-ammonia water storage tank.

[0025] Figure 3 This is a structural block diagram of a waste heat generation system for furnace flue gas according to the present invention. Detailed Implementation

[0026] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0027] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0028] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0029] The technical solutions of the embodiments of this application will be described below.

[0030] like Figure 1 As shown, this embodiment of the invention provides a method for staged recycling of waste heat from furnace flue gas for power generation, including the following steps S110-S160:

[0031] Step S110, obtain kiln flue gas composition data and process parameter information, based on kiln flue gas composition data for desulfurization reaction to generate purified flue gas, based on purified flue gas and process parameter information to build a hierarchical purification chain.

[0032] Specifically, as Figure 2 The gas analyzer 2 arranged at the flue outlet of the kiln 1 is used to collect the concentration data of sulfur dioxide, nitrogen oxides, particulate matter, carbon monoxide, carbon dioxide and water vapor in the flue gas in real time. The gas analyzer 2 uses ultraviolet differential absorption spectroscopy to measure gaseous pollutants, uses laser scattering principle to detect particulate matter concentration, and uses infrared absorption method to determine carbon dioxide content. The flue gas composition data includes real-time concentration value, molar fraction and mass fraction information under temperature conditions of each component. For example, in the application of cement kiln, the concentration of sulfur dioxide in flue gas is usually in the range of 200-800mg / m³, the concentration of nitrogen oxides is between 300-1200mg / m³, and the concentration of particulate matter is in the range of 30-150mg / m³. The process parameter information of the kiln 1 is collected synchronously, including the key parameters such as combustion temperature, flue gas flow, flue gas pressure, oxygen content in the furnace and fuel consumption. The process parameters are recorded in real time by the distributed control system 6, the combustion temperature is measured by the temperature sensor 3, the flue gas flow is detected by the flow sensor 5, and the flue gas pressure is monitored by the pressure sensor 4. The desulfurization treatment is carried out by the desulfurization tower 7, the limestone slurry is provided by the limestone slurry tank 8, the circulating pump 9 is responsible for the slurry circulation, and the oxidation air blower 10 provides oxidation air. The hierarchical purification chain includes low-temperature economizer 11 for waste heat recovery, wet-type electric dust collector 12 for removing particulate matter, and SCR reactor 13 cooperating with ammonia water tank 14 for denitration treatment. The data acquisition system is equipped with data buffer and communication interface, and the flue gas composition data and process parameter information are recorded and transmitted synchronously according to the unified time stamp. The data acquisition frequency is set to once per minute, which ensures the capture of the dynamic change characteristics of flue gas composition and process parameters.

[0033] The desulfurization reaction is based on the composition data of the kiln flue gas to generate purified flue gas. According to the sulfur dioxide concentration information in the collected flue gas composition data, the dosage of desulfurizer and reaction conditions are calculated. The desulfurization reaction adopts a wet desulfurization process, using limestone slurry as the absorbent, and performing gas-liquid contact reaction with the flue gas in the desulfurization tower. The dosage of desulfurizer is calculated according to the stoichiometric relationship, and the Ca / S molar ratio is controlled within 1.02-1.05 to ensure sufficient desulfurization efficiency. The pH value in the desulfurization tower is adjusted according to the acid gas concentration in the flue gas composition data, and maintained in the optimal reaction interval of 5.0-6.0. For example, when the sulfur dioxide concentration in the flue gas is 500 mg / m³, the corresponding limestone slurry consumption is about 2.3 tons per hour, and the desulfurization efficiency can reach more than 95%. During the desulfurization reaction process, the solid content of the slurry and the circulation ratio are monitored, the solid content is controlled within 15%-20%, and the circulation ratio is maintained between 8-12, to ensure the sufficiency and economy of the reaction. Through real-time feedback of the flue gas composition data, the desulfurization process parameters are dynamically adjusted, including slurry spraying amount, circulating pump speed and oxidation air volume, etc. The main chemical process of the desulfurization reaction is CaCO3+SO2+H2O→CaSO3·½H2O+CO2, where CaCO3 is limestone, SO2 is sulfur dioxide in the flue gas, and the generated calcium sulfite is further oxidized to calcium sulfate. After desulfurization treatment, the sulfur dioxide concentration in the purified flue gas is reduced to below 50 mg / m³, and most of the particulate matter and part of the nitrogen oxides are removed, the purified flue gas temperature is about 50-60℃, and the moisture content increases but the pollutant concentration is greatly reduced.

[0034] Based on the purified flue gas and process parameter information, a hierarchical purification chain is constructed. The purified flue gas after desulfurization is treated in layers according to temperature and pollutant concentration, and a multi-stage purification process is designed combining process parameter information. The first layer of purification is aimed at recovering the waste heat in the purified flue gas, using the heat energy of the flue gas at 50-60℃, and recovering sensible heat through a low-temperature coal economizer. According to the flue gas flow data in the process parameter information, the waste heat recovery potential is calculated, and for every increase of 1000 m³ / h in flue gas flow, about 150-200 kW of heat can be recovered. The second layer of purification treats the residual particulate matter in the purified flue gas, using a wet-type electric precipitator to further reduce the particulate matter concentration to below 10 mg / m³. The third layer of purification is aimed at the nitrogen oxides in the purified flue gas, and through selective catalytic reduction technology, ammonia water or urea solution is injected for denitration treatment under process parameter control. According to the oxygen content data in the process parameter information, the denitration reaction is adjusted to ensure the removal of nitrogen oxides to below 50 mg / m³. The fourth layer of purification is aimed at the remaining trace pollutants in the purified flue gas, and through a wet scrubber, the flue gas is further treated to meet the emission standards. The purified flue gas after the fourth layer of purification is discharged to the atmosphere, and the flue gas temperature is about 40-50℃, and the moisture content is increased but the pollutant concentration is greatly reduced. The molar ratio is generally controlled in the range of 0.8-1.0. For example, in a glass kiln application, the first layer of the layered purification chain recovers flue gas sensible heat to generate 0.8 MPa steam, the second layer removes fine particulate matter, and the third layer reduces the concentration of nitrogen oxides from 200 mg / m³ to below 50 mg / m³. The construction of the layered purification chain also takes into account the temperature change and composition evolution of the purified flue gas between layers, with the purified flue gas from each layer becoming the input to the next layer, forming a series of purification processes. Through real-time monitoring of process parameter information, the operating parameters of each layer of purification equipment are adjusted to maintain coordinated operation of the layered purification chain and optimal purification effect.

[0035] In step S120, the pollutant-temperature mapping relationship is determined by the layered purification chain and the purified flue gas, the acid dew point region is identified by the pollutant-temperature mapping relationship, and the corrosion intensity of the acid dew point region is reduced to form the purified flue gas region.

[0036] Specifically, the pollutant-temperature mapping relationship is determined by the layered purification chain and the purified flue gas. The layered purification chain and the purified flue gas information output by step S110 are received, and the correlation characteristics of pollutant concentration and temperature in each purification level are analyzed. In the first layer of the layered purification chain, the temperature of the purified flue gas is gradually reduced from the initial 50-60°C, and the changes in the concentrations of residual SO2 and NO X are monitored. Through temperature stepwise reduction experiments, the pollutant concentration distribution at different temperature points is measured, and the pollutant concentration value is recorded every 5°C decrease in temperature. In the second layer of particulate matter removal process, the particulate matter in the purified flue gas carries part of the acidic substances, and as the particulate matter is removed, the concentration of acidic pollutants changes accordingly. In the third layer of denitration treatment, the working temperature of the catalyst affects the conversion efficiency of NO x , and also affects the distribution of acidic gases in the flue gas. For example, the SO2 concentration in the purified flue gas is 35 mg / m³ at 45°C, rises to 38 mg / m³ at 40°C, and reaches 42 mg / m³ at 35°C, showing the characteristic of pollutant concentration caused by temperature reduction. A mathematical relationship between pollutant concentration and temperature C=C0×exp(α / T) is established, where C is the pollutant concentration, C0 is the reference concentration, α is the temperature influence coefficient, and T is the absolute temperature. Comprehensive analysis of the data from each layer generates a complete pollutant-temperature mapping relationship graph, which shows the concentration distribution and change trend of various pollutants under different temperature conditions.

[0037] In some embodiments, the identifying the acid dew point region through the pollutant-temperature mapping relationship comprises: performing corrosion-heat transfer synergistic analysis based on the pollutant-temperature mapping relationship to obtain synergistic evaluation data; performing material adaptability evaluation on the synergistic evaluation data to determine a corrosion-heat transfer balance point; performing equipment material selection optimization according to the corrosion-heat transfer balance point to generate material configuration parameters; and determining an acid dew point safety region through the material configuration parameters.

[0038] The corrosion-heat transfer synergistic analysis based on the pollutant-temperature mapping relationship obtains synergistic evaluation data. The concentration-temperature data in the established pollutant-temperature mapping relationship is utilized, and the mutual influence of the corrosion process and the heat transfer process is considered, to perform comprehensive synergistic analysis. The corrosion process analysis adopts electrochemical corrosion theory, and according to the acid gas concentration at different temperature points in the pollutant-temperature mapping relationship, the corrosion potential and the corrosion current density of the metal material are calculated. The heat transfer process analysis considers the convective heat transfer between the flue gas and the heat transfer surface, and the influence of the corrosion product on the heat transfer performance. The corrosion-heat transfer synergistic effect mainly reflects that the formation of the corrosion product layer increases the heat transfer thermal resistance, and the heat transfer strengthening accelerates the corrosion reaction. Through the data of the pollutant-temperature mapping relationship, a correlation model of the corrosion rate and the heat transfer coefficient is established. For example, in the low-temperature heat exchanger of the furnace system, when the flue gas temperature is 120°C and the SO3 concentration is 10 mg / m³, the corrosion rate of the carbon steel material is 1.2 mm / year, and the corresponding heat transfer coefficient is 45 W / (m²·K); when the temperature drops to 100°C, the corrosion rate rises to 3.8 mm / year, and the heat transfer coefficient decreases to 38 W / (m²·K). Based on the operation data under different operating conditions, the corrosion rate-heat transfer coefficient data combination under different operating conditions is obtained, to form a synergistic evaluation database. The synergistic evaluation data contains multi-dimensional information such as corrosion intensity level, heat transfer performance parameters, material life prediction and economic indicators.

[0039] The material adaptability evaluation of the synergistic evaluation data determines the corrosion and heat transfer balance point. The material adaptability evaluation adopts a multi-objective decision-making method, considering two key indicators of corrosion resistance and heat transfer performance. A material performance evaluation matrix is established, with rows corresponding to different candidate materials (such as carbon steel, stainless steel, titanium alloy, nickel-based alloy, etc.), and columns corresponding to performance indicators (such as corrosion resistance, thermal conductivity, mechanical strength, cost, etc.). According to the corrosion environment parameters in the synergistic evaluation data, the corrosion resistance score of various materials is calculated, with a score range of 1-10 points, and the higher the score, the better the corrosion resistance. According to the heat transfer performance parameters, the heat transfer performance score of various materials is calculated, considering factors such as thermal conductivity, surface heat transfer coefficient, and fouling resistance. The determination of the corrosion and heat transfer balance point adopts a weighted scoring method, and the corrosion resistance weight and the heat transfer performance weight are adjusted according to specific application requirements. For example, in the acid dew point area, the corrosion resistance weight is set to 0.7, and the heat transfer performance weight is 0.3; in the non-acid dew point area, the weight ratio can be adjusted to 0.4 and 0.6. Through comprehensive analysis of the synergistic evaluation data, the comprehensive score of 316L stainless steel in a medium corrosion environment at 120°C is determined to be 8.2 points, becoming the corrosion and heat transfer balance point material under this working condition.

[0040] According to the corrosion and heat transfer balance point, the material configuration parameters are generated for equipment material selection optimization. Based on the material score results determined by the corrosion and heat transfer balance point, targeted equipment material selection optimization decisions are made. For 316L stainless steel with a comprehensive score of 8.2, it is selected as the preferred material in a medium corrosion environment, suitable for areas with flue gas temperature of 110-130°C and SO3 concentration of 10-20 mg / m³. According to the score differences of different materials in the corrosion and heat transfer balance point analysis, a grading standard for material selection is established: materials with a score of 8.0 or above are used for key heating surfaces, materials with a score of 6.0-8.0 are used for general corrosion areas, and materials with a score of 6.0 or below are only used in light corrosion environments. Based on the optimal material combination determined by the corrosion and heat transfer balance point, a specific material configuration scheme is developed. In the high-temperature low-corrosion area, according to the balance point analysis, 310S stainless steel is selected, with a corrosion score of 7.8 and a heat transfer score of 8.5, meeting the requirements of this area. In the low-temperature high-corrosion area, the balance point analysis recommends the use of Inconel625 nickel-based alloy, with a comprehensive score of 9.1. The quantitative score of the corrosion and heat transfer balance point is converted into specific material configuration parameters: the wall thickness design determines the safety factor according to the score, the lower the score, the higher the safety factor; the welding material selection needs to match the score of the base material; the surface treatment method is determined according to the corrosion score level. The generated material configuration parameters include material grade selection, geometric size determination, surface treatment specifications, and quality control requirements based on balance point analysis, ensuring the consistency of material selection decisions and balance point evaluation results.

[0041] Determine the acid dew point safety zone by material configuration parameters. The acid dew point safety zone refers to the area where the selected materials can safely operate without serious corrosion under the expected operating conditions. The determination of the safety zone needs to consider the corrosion resistance of the materials, the design corrosion allowance and the actual operating environment. According to the material grade information in the material configuration parameters, the expected corrosion rate and service life of various materials in the specific corrosion environment are calculated. For the area using 316L stainless steel, in the environment of SO3 concentration 15 mg / m³ and temperature 110 ℃, the expected corrosion rate is 0.05 mm / year, the design life is 20 years, and the corrosion allowance is set to 2 mm, which can ensure safe operation. For the high corrosion area using Inconel 625, the corrosion rate is lower and the safety margin is higher. The boundary of the acid dew point safety zone is determined by the double constraints of temperature and material performance, and the flue gas temperature in the zone should be higher than the lower limit of the safe operating temperature of the material. For example, in the flue gas waste heat recovery device of the furnace system, through reasonable material configuration, the original high-risk area of acid dew point of 105-125 ℃ is converted into a safety zone, and the heat exchange operation in the safety zone can be carried out normally without worrying about serious corrosion problems.

[0042] Reduce the corrosion intensity of the acid dew point area to form a purified flue gas area. For the identified acid dew point area, reduce the corrosion intensity through temperature control and material protection measures to convert the high corrosion risk area into a safe and operable purified flue gas area. Use flue gas heating technology to add heating devices in the equipment section prone to acid dew point, and maintain the flue gas temperature at 5-10 ℃ above the acid dew point temperature to prevent acid condensation. The heating method is selected as steam heating or electric heating, and is controlled in different zones according to the temperature requirements of different positions. Use corrosion-resistant coating or corrosion-resistant materials on the surface of the equipment in the acid dew point area to reduce the damage of acid corrosion to the equipment. The corrosion-resistant coating is selected as epoxy glass flake paint or fluorocarbon paint, with a thickness of 0.3-0.5 mm, which has good acid resistance and adhesion. For areas where acid condensation cannot be avoided, set up an acid liquid collection and discharge system to remove the condensed acid liquid in time and reduce the residence time of the acid liquid on the equipment surface. For example, in the furnace system, by installing a steam heater at the inlet section of the economizer, the flue gas temperature is raised from 110 ℃ to 125 ℃, effectively avoiding acid condensation, and the corrosion rate is reduced from 2.5 mm / year to less than 0.3 mm / year. After corrosion intensity control, the original high-risk area of acid dew point is converted into a purified flue gas area, and the flue gas temperature in the area is stable above the acid dew point, and the equipment material is effectively protected.

[0043] In step S130, temperature gradient analysis is performed on the purified flue gas area to form a temperature fluctuation curve, the temperature field is reconstructed based on the temperature fluctuation curve to generate a temperature distribution field, and the heat grade is allocated based on the temperature distribution field to generate a hierarchical heat energy configuration. The hierarchical heat energy configuration is used to form a complementary heat source in different temperature sections to generate a hierarchical heat energy flow.

[0044] Specifically, temperature gradient analysis is performed on the flue gas purification area to form a temperature fluctuation curve. A network of temperature measurement points is arranged in the flue gas purification area, with longitudinal measurement points arranged according to the flow direction of the flue gas and transverse measurement points arranged according to the radial direction of the cross section, forming a three-dimensional temperature monitoring grid. The longitudinal measurement point spacing is set to 2-3 meters, and the transverse measurement points are evenly distributed according to the flue cross section, with 9 measurement points arranged in a 3x3 matrix in each cross section. The temperature gradient analysis uses the finite difference method to calculate the temperature difference and gradient change rate between each measurement point. The longitudinal temperature gradient reflects the temperature attenuation characteristics of the flue gas along the flow direction, where T i is the temperature of the ith measurement point, and Δx is the measurement point spacing. The transverse temperature gradient reflects the unevenness of the flue gas cross section temperature distribution, where Tmax and Tmin are the highest and lowest temperatures of the cross section respectively, and D is the flue diameter. For example, in the flue gas waste heat recovery section of the furnace system, the inlet temperature of the flue gas purification area is 180°C, the outlet temperature is 120°C, the length is 30 meters, and the calculated longitudinal temperature gradient is 2°C / m. By continuously monitoring the temperature gradient data at different times, the fluctuation characteristics and variation rules of the flue gas temperature are captured. The temperature gradient data is processed according to the time sequence, and the temperature fluctuation curve is drawn, with the horizontal axis representing time and the vertical axis representing temperature gradient value, reflecting the dynamic change process of the temperature field in the flue gas purification area.

[0045] Based on the temperature fluctuation curve, the temperature distribution field is reconstructed. The temperature fluctuation curve provides time-varying temperature information of discrete measurement points, which needs to be extended to the entire spatial region through mathematical methods. The Kriging interpolation method is used for spatial temperature field reconstruction, which can consider the spatial correlation and variation characteristics of temperature. The reconstruction process first analyzes the spatial variation function in the temperature fluctuation curve to determine the correlation distance and variation degree of the temperature field. The mathematical model of the temperature field is established as T(x, y, z) = T0 + f(x, y, z) + ε(x, y, z), where T0 is the average temperature, f(x, y, z) is the deterministic trend function, and ε(x, y, z) is the random error term. Through statistical analysis of the temperature fluctuation curve, the parameters of the trend function and the distribution characteristics of the random error are determined. The reconstructed temperature distribution field divides the flue gas purification area into several temperature grade intervals, including high temperature zone (160-180°C), medium-high temperature zone (140-160°C), medium temperature zone (120-140°C), and low temperature zone (100-120°C). For example, in the flue gas purification area of the furnace system, the reconstructed temperature distribution field shows that the high temperature zone accounts for 25% of the total volume, the medium-high temperature zone accounts for 35%, the medium temperature zone accounts for 30%, and the low temperature zone accounts for 10%. The reconstruction of the temperature distribution field also considers the influence of flue gas flow on temperature distribution, with relatively high temperature in the center of the flue and lower temperature near the wall. The generated temperature distribution field is represented in the form of a three-dimensional grid, with each grid node corresponding to a specific temperature value and spatial coordinates.

[0046] In some embodiments, the generating a hierarchical thermal energy configuration based on the temperature distribution field and the thermal grade allocation comprises: identifying and extracting energy conversion nodes in the temperature distribution field; performing chain transfer analysis on the energy conversion nodes to form an energy propagation chain; performing grade attenuation compensation processing based on the energy propagation chain to generate compensated energy; and reconstructing the compensated energy to generate a hierarchical thermal energy configuration.

[0047] Identify and extract energy conversion nodes in the temperature distribution field. Identify special locations with large temperature gradients and high heat flux density from the three-dimensional grid data of the temperature distribution field as energy conversion nodes. Energy conversion nodes are key locations where thermal energy changes significantly or energy forms are converted, usually located at the interface between different temperature intervals or the inlet and outlet of heat exchange equipment. By analyzing the temperature gradient distribution in the temperature distribution field, grid points with temperature gradient values exceeding the set threshold are identified as candidate nodes. Set the temperature gradient threshold to 5°C / m, and when the temperature gradient of a certain grid point exceeds this value, mark it as an energy conversion node. The identification of energy conversion nodes also considers the direction of heat flow and the change of heat flux density, and judges the position of energy collection or divergence by calculating the divergence and curl of the heat flow vector. For example, in the temperature distribution field of the furnace system, 12 main energy conversion nodes are identified, including 4 high-temperature zone outlet nodes, 4 medium-temperature zone inlet nodes, 2 heat exchanger nodes and 2 split nodes. Each energy conversion node records its spatial coordinates, temperature value, heat flux density and conversion type, etc. attribute information.

[0048] Perform chain transfer analysis on the energy conversion nodes to form an energy propagation chain. Chain transfer analysis uses network topology method, taking energy conversion nodes as network nodes and heat energy transfer path as network edge to form directed graph structure of energy propagation. According to the direction of heat flow in the temperature distribution field and the spatial position relationship between nodes, determine the connection relationship and transmission direction between nodes. Energy propagation follows the second law of thermodynamics, heat energy transfers from high-temperature nodes to low-temperature nodes, and the transfer strength is proportional to the temperature difference. The heat transfer equation between nodes is established as q=hA(T1-T2), where q is the transferred heat, h is the heat transfer coefficient, A is the heat transfer area, and T1 and T2 are the temperatures of high-temperature and low-temperature nodes respectively. By analyzing the transfer relationship between all nodes, a complete energy propagation chain network is formed. For example, in the furnace system, the energy propagation chain shows that heat energy starts from the 4 source nodes of the high-temperature zone, passes through 8 intermediate conversion nodes, and finally converges to the 2 sink nodes of the low-temperature zone, forming a tree-like energy propagation structure. The energy propagation chain also contains transfer efficiency and loss information, and there is a certain heat loss and irreversibility at each transfer link.

[0049] Compensation energy is generated based on exergy attenuation compensation processing of energy propagation chain. Exergy attenuation is an inevitable phenomenon of heat energy in the process of transmission, which will cause the decrease of available energy and the increase of entropy. Through the analysis of energy propagation chain, the most serious transmission link and node position of exergy attenuation are identified. The quantification of exergy attenuation adopts the exergy analysis method to calculate the exergy value Ex = H-T0S of each node, where Ex is the exergy, H is the enthalpy, T0 is the environmental temperature, and S is the entropy. Exergy attenuation compensation processing adopts various technical means, including heat exchange enhancement, heat pump lifting, heat recovery and heat storage methods. For heat loss caused by long transmission distance, heat preservation enhancement and heat pipe technology are used to reduce heat loss. For irreversible loss caused by large temperature difference, multi-stage heat exchange and counter-flow arrangement are used to reduce the heat transfer temperature difference. The generated compensation energy is classified according to temperature level, high-temperature compensation energy is used for high-grade applications, and low-temperature compensation energy is used for low-grade applications.

[0050] The hierarchical thermal energy configuration is generated by reconstructing the compensation energy. The reconstruction of compensation energy needs to consider its temperature level, quantity size and utilization method, and coordinate with the original thermal energy configuration. The reconstruction process first allocates the compensation energy to the corresponding temperature interval according to the temperature level, the high-temperature compensation energy enhances the thermal energy configuration of the high-temperature zone, and the low-temperature compensation energy supplements the thermal energy deficiency of the low-temperature zone. The original hierarchical thermal energy configuration is 30% for high-temperature zone, 35% for medium-high temperature zone, 25% for medium temperature zone and 10% for low temperature zone, and after adding the compensation energy, it is adjusted to 32% for high-temperature zone, 36% for medium-high temperature zone, 24% for medium temperature zone and 8% for low temperature zone. The reconstruction also considers the quality characteristics and utilization efficiency of the compensation energy, and the high-quality compensation energy is preferentially configured to high-value applications. For example, in the furnace system, the high-temperature compensation energy obtained by heat pump lifting is preferentially used for power generation, and the medium-temperature compensation energy obtained by heat recovery is used for process heating. The generated hierarchical thermal energy configuration contains complete parameter information such as the total amount of thermal energy and temperature level of each temperature section after compensation.

[0051] In some embodiments, the utilization of the hierarchical thermal energy configuration to form a gradient thermal energy flow with complementary heat sources in different temperature sections includes: obtaining thermal energy distribution data of each temperature section in the hierarchical thermal energy configuration; performing thermal energy complementary relationship matching on the thermal energy distribution data to form a complementary configuration table; generating a coordinated heat source according to the complementary configuration table; and forming a gradient thermal energy flow through gradient transmission path construction by the coordinated heat source.

[0052] The thermal energy distribution data of each temperature section in the hierarchical thermal energy configuration is obtained. After the compensated energy reconstruction of the hierarchical thermal energy configuration, the specific distribution of each temperature section is as follows: the high-temperature zone (160-180°C) accounts for 32% of the total thermal energy, with a total thermal energy of about 15.2 MW; the medium-high-temperature zone (140-160°C) accounts for 36%, with a total thermal energy of about 17.1 MW; the medium-temperature zone (120-140°C) accounts for 24%, with a total thermal energy of about 11.4 MW; and the low-temperature zone (100-120°C) accounts for 8%, with a total thermal energy of about 3.8 MW. The thermal energy distribution data also includes spatial location information of each temperature section, with the high-temperature zone mainly distributed in the front section of the flue, the medium-temperature zone distributed in the middle section of the flue, and the low-temperature zone distributed in the rear section of the flue. The thermal energy density and flow parameters of each temperature section are also recorded in detail, with the highest thermal energy density in the high-temperature zone, about 0.8 MW / m³, and the lowest thermal energy density in the low-temperature zone, about 0.2 MW / m³. For example, in the furnace system, the thermal energy distribution data of each temperature section shows that the total thermal energy is 47.5 MW, of which 15.2 MW is high-grade thermal energy that can be directly used for power generation, 17.1 MW is medium-grade thermal energy that can be used for process heating, and 15.2 MW is low-grade thermal energy that can be used for low-temperature applications.

[0053] The thermal energy distribution data is matched with the thermal energy complementary relationship to form a complementary configuration table. Based on the obtained thermal energy distribution data, the temperature level of the waste heat generated in the utilization process of the high-temperature zone thermal energy matches the demand temperature range of the medium-high-temperature zone, forming the main complementary relationship between the high-temperature zone and the medium-high-temperature zone. Capacity matching analysis is performed on the waste heat generated in the high-temperature zone and the total demand of the medium-high-temperature zone, and the waste heat supply capacity accounts for 71% of the demand of the medium-high-temperature zone, and about 29% of the heat source needs to be supplemented externally. The waste heat generated after the utilization of the medium-high-temperature zone thermal energy is matched with the thermal energy demand of the medium-temperature zone, and the waste heat supply capacity exceeds the demand, with a matching degree of 120%, and there is surplus thermal energy that can be redistributed. The waste heat generated after the utilization of the medium-temperature zone thermal energy is matched with the demand of the low-temperature zone, and the waste heat supply is sufficient, forming the complementary relationship between the medium-temperature zone and the low-temperature zone. Through the step-by-step matching analysis of the thermal energy distribution data of each temperature section, the three-stage serial complementary relationship is identified: the high-temperature zone supplies waste heat to the medium-high-temperature zone, the medium-high-temperature zone supplies waste heat to the medium-temperature zone, and the medium-temperature zone supplies waste heat to the low-temperature zone. Based on the matching analysis results of the thermal energy distribution data, a complementary configuration table is established, which records the supply capacity, demand capacity, matching relationship, and surplus amount of each temperature section, providing a data basis for the subsequent heat source coordination.

[0054] The coordinated heat sources are generated according to the heat source coordination matching based on the complementary configuration table. The goal of the coordination matching is to maximize the complementary utilization efficiency of heat energy, reduce heat source waste and improve overall energy utilization. According to the 71% high-medium high temperature matching degree in the complementary configuration table, additional heat sources need to be supplemented in the medium high temperature zone to meet the total demand of 17.1 MW. The supplementary heat sources can come from auxiliary heating outside the system or internal heat energy redistribution. For the 120% matching degree of the medium high-medium temperature section, the 2.3 MW surplus heat energy generated can be redistributed to other temperature sections or used for system preheating. The coordination matching adopts a linear programming method, with the maximum heat energy utilization rate as the objective function and the capacity constraints of each temperature section as the limiting conditions. A mathematical model of coordinated heat sources is established to determine the optimal heat source allocation scheme. For example, in the furnace system, the coordinated heat source configuration is: 12.5 MW of independent heat source in the high temperature zone, 15.2 MW of self-supply heat source; 4.8 MW of external supplement, 12.1 MW of internal supply, and 17.1 MW of self-supply heat source in the medium high temperature zone; 13.7 MW of external supply and 11.4 MW of self-supply heat source in the medium temperature zone. The generated coordinated heat sources have clear parameters such as capacity configuration, supply source and adjustment capacity.

[0055] The gradient heat energy flow is formed by constructing the gradient transmission path through the coordinated heat sources. The gradient transmission path follows the natural transmission direction from high to low temperature, while considering the grade retention and utilization efficiency of heat energy. The first level transmission path starts from the high temperature zone, and 15.2 MW of high temperature heat energy is first used for efficient power generation, with a power generation efficiency of 25%, generating 3.8 MW of electric energy, and the remaining 11.4 MW of waste heat entering the second level. In the second level transmission, 11.4 MW of waste heat is combined with 4.8 MW of external supplementary heat source in the medium high temperature zone to form 16.2 MW of medium high temperature heat source for process heating, with a utilization efficiency of 80%, generating 12.96 MW of effective heat energy, and the remaining 3.24 MW of waste heat entering the third level. In the third level transmission, 3.24 MW of waste heat is combined with other waste heat to form 11.4 MW of medium temperature heat source for domestic hot water and air conditioning heating, with a utilization efficiency of 90%, generating 10.26 MW of effective heat energy. The gradient transmission path also includes heat energy storage and adjustment links, and heat energy buffer tanks are set between each level to balance supply and demand fluctuations and improve system stability. For example, in the furnace system, the gradient heat energy flow realizes the whole process heat energy utilization from 180°C to 90°C, with a total heat energy utilization rate of 68%, which is 170% higher than the traditional single level utilization. The formed gradient heat energy flow has clear transmission sequence, flow distribution and temperature degradation characteristics, providing a complete heat energy flow scheme for the design and operation of the waste heat power generation system.

[0056] In step S140, the step of cyclically distributing the cascade thermal energy flow to generate a water vapor main cycle and an organic working medium auxiliary cycle, the step of integrating a magnetic suspension bearing to extract auxiliary cycle power from the organic working medium auxiliary cycle, and the step of superimposing the auxiliary cycle power and the water vapor main cycle power to form a cascade power generation configuration.

[0057] Specifically, the cascade thermal energy flow is cyclically distributed to generate a water vapor main cycle and an organic working medium auxiliary cycle. According to the thermal energy characteristics of different temperature sections in the cascade thermal energy flow, the working medium is reasonably distributed and matched. The high-temperature section (160-180℃) and the medium-high temperature section (140-160℃) have high thermal energy grade, and are suitable for using water vapor as the working medium to establish a main cycle power generation system. The water vapor main cycle uses high-grade heat sources to generate high-pressure steam, which is discharged after doing work in the turbine. The medium temperature section (120-140℃) and the low temperature section (100-120℃) have relatively low thermal energy grade, and it is more economical and reasonable to use organic working medium to establish an auxiliary cycle system. The organic working medium auxiliary cycle selects R245fa as the circulating medium, which has good evaporation characteristics and thermodynamic properties at low temperature. For example, in the furnace system, the cascade thermal energy flow is distributed according to temperature, and the high-temperature section and the medium-high temperature section are allocated to the water vapor main cycle, and the medium temperature section and the low temperature section are allocated to the organic working medium auxiliary cycle. The cycle distribution also considers the thermodynamic matching and economy of the working medium. The water vapor main cycle is suitable for high-temperature and high-efficiency power generation, and the organic working medium auxiliary cycle is suitable for low-temperature waste heat utilization. The distributed water vapor main cycle and organic working medium auxiliary cycle form a complementary power generation configuration. The main cycle is responsible for efficient power generation, the auxiliary cycle is responsible for low-temperature waste heat utilization, and the two cycle systems are independent of each other in heat source utilization and complementary to each other in power generation output.

[0058] In some embodiments, the step of integrating a magnetic suspension bearing to extract auxiliary cycle power from the organic working medium auxiliary cycle includes the steps of: generating a magnetic field intensity distribution based on the magnetic field coupling effect of the organic working medium auxiliary cycle; capturing a suspension stable control center from the magnetic field intensity distribution; performing energy focusing analysis on the suspension stable control center to form a conversion energy density map; and deriving auxiliary cycle power according to the conversion energy density map.

[0059] The magnetic field strength distribution is generated based on the coupling effect of the magnetic field and the auxiliary organic working medium cycle. The high-speed rotation of the turbine rotor in the auxiliary organic working medium cycle generates mechanical vibration and dynamic load. These dynamic characteristics are coupled with the magnetic bearing system. The rotation of the rotor driven by the organic working medium changes the magnetic field environment around the magnetic bearing. The magnetic permeability of the rotor material changes slightly at high speed, affecting the spatial distribution of the magnetic field. The load change of the auxiliary organic working medium cycle directly affects the operating state of the rotor. Load fluctuations cause changes in rotor position and vibration characteristics, which in turn affect the magnetic field distribution of the magnetic bearing. The analysis of the magnetic field coupling effect considers the dynamic characteristics of the organic working medium cycle and the electromagnetic characteristics of the magnetic bearing. The three-dimensional magnetic field strength distribution around the magnetic bearing system is obtained. The magnetic field strength is higher near the pole surface of the electromagnet, and the magnetic field strength is moderate in the rotor suspension gap. The magnetic field strength distribution shows dynamic characteristics with changes in the working conditions of the auxiliary organic working medium cycle.

[0060] The suspension stability control center is captured from the magnetic field strength distribution. Based on the magnetic field strength distribution data generated in the previous section, a gradient analysis method is used to identify the key position of the magnetic field force balance. By calculating the spatial gradient of the magnetic field strength distribution, the region with a gradient value close to zero is found as the candidate position of the suspension stability control center. In the magnetic field strength distribution map, the control center corresponds to the region with the most gentle change in magnetic field strength. The magnetic field force in this region achieves stable balance. A numerical calculation method is used to perform second-order derivative analysis on the magnetic field strength distribution to determine the spatial position with the smallest magnetic field curvature. Combined with the operating characteristics of the auxiliary organic working medium cycle, the stable region suitable for rotor suspension is selected from the magnetic field strength distribution. The capture of the control center considers the dynamic change characteristics of the magnetic field distribution. With the change of the cycle working condition, the control center position is adjusted accordingly. Through spatial geometric analysis and magnetic field characteristic evaluation, the optimal control center position is identified. The captured suspension stability control center has a clear three-dimensional coordinate position and stability index, which becomes the control reference point of the magnetic bearing system.

[0061] For example, the energy focusing analysis of the suspension stability control center forms a converted energy density map, including: performing full-condition energy backtracking analysis on the suspension stability control center to obtain energy accumulation data; based on the energy accumulation data, analyzing the energy action mechanism of each magnetic field factor to generate an energy focusing intensity distribution, the magnetic field factors include magnetic field strength fluctuation, rotational speed gradient change, and bearing position offset; and performing density conversion processing on the energy focusing intensity distribution to generate a converted energy density map.

[0062] The energy accumulation data is obtained by full-condition energy backtracking analysis of the suspension stability control center. For the captured suspension stability control center coordinate position, an energy monitoring point array is set up, and 32 measurement points are arranged in the radial and axial directions for energy data collection. Four standard working conditions are set for full-condition analysis: start-up condition (0-600 seconds), rated condition (steady-state operation), variable load condition (load range 50%-120%), and shutdown condition (600-0 speed attenuation). The changes in the characteristics of the three magnetic field factors, magnetic field intensity fluctuation, rotational speed gradient change, and bearing position offset, are monitored simultaneously under each working condition. The magnetic field intensity fluctuation is measured by a Hall sensor, and the time-domain fluctuation amplitude and frequency characteristics of the magnetic induction intensity are recorded. The rotational speed gradient change is monitored by an encoder, and the gradient values of the acceleration and deceleration processes are recorded. The bearing position offset is measured by an eddy current sensor, and the radial and axial offset amplitudes are recorded. The trapezoidal integration method is used for energy backtracking analysis, with a sampling interval of 0.1 seconds to calculate the energy accumulation E(t) = Σ[P(ti) + P(ti+1)] x Δt / 2 of each measurement point, where E(t) is the cumulative energy at time t, P(ti) is the instantaneous power at time ti, P(ti+1) is the instantaneous power at time ti+1, and Δt is the sampling time interval 0.1 seconds. For example, in a furnace system, the magnetic field intensity fluctuation amplitude under rated condition is ±0.08T, the rotational speed gradient change range is ±150rpm / s, and the bearing position offset amplitude is ±0.12mm. Through data statistics of the four working conditions, the mean, standard deviation, and change range of the three magnetic field factors are obtained. The obtained energy accumulation data includes the time series data, statistical characteristic parameters, and correlation coefficients between factors of each magnetic field factor, forming a complete magnetic field factor energy database.

[0063] Based on the energy accumulation data analysis of each magnetic field factor, the energy focusing intensity distribution is generated. The time series data and statistical parameters of magnetic field strength fluctuation, rotational speed gradient change and bearing position offset are extracted from the magnetic field factor energy database. The magnetic field strength fluctuation factor analysis adopts the mean and standard deviation of the fluctuation amplitude to calculate the influence coefficient of the fluctuation on the energy focusing intensity. The fluctuation amplitude increases by 0.01T, which corresponds to an 8% change in focusing intensity. The rotational speed gradient change factor analysis adopts the time series data of the gradient change to establish a correlation model between the gradient change rate and energy redistribution. A gradient change of 50rpm / s corresponds to a 0.05mm shift in the focusing area. The bearing position offset factor analysis adopts the statistical data of the radial and axial offset to calculate the influence of the offset on the focusing mode. A position offset of 0.1mm results in a 12% decrease in focusing intensity. Using the correlation coefficient data of the three magnetic field factors, a multi-factor coupled energy focusing model F(x,y,z)=F0×[1+α×ΔB+β×Δω+γ×Δr] is established, where F is the focusing intensity, F0 is the reference focusing intensity, α, β, γ are the influence coefficients of the magnetic field strength, rotational speed gradient and position offset respectively, and ΔB, Δω, Δr are the change amounts of the three factors. For example, in the furnace system, the main frequencies of the three factors are identified through frequency domain analysis of the time series data. The main frequency of the magnetic field strength fluctuation is 50Hz, the main frequency of the rotational speed gradient change is 8Hz, and the main frequency of the position offset is 3Hz. The multi-factor coupled model is applied to the three-dimensional space of the suspension control center to calculate the focusing intensity values at each spatial position and generate a complete energy focusing intensity distribution.

[0064] The energy focusing intensity distribution is subjected to density conversion processing to generate a converted energy density map. The energy focusing intensity distribution data is used to unify the physical dimensions and convert the values. The conversion relationship between focusing intensity and energy density is established: ρ=k×I×η, where ρ represents energy density, k represents conversion coefficient, I represents focusing intensity, and η represents conversion efficiency. Through normalization processing, the relative focusing intensity values are converted into absolute energy density values to ensure that the conversion results have clear physical meaning. During the density conversion process, the spatial integration effect is considered, and the focusing intensity of different regions is weighted and converted according to the volume weight. The converted energy density data is subjected to spatial reconstruction to eliminate the numerical discontinuity caused by discretization processing. The conversion results are subjected to smoothing filter processing to generate a continuous energy density spatial distribution. Through three-dimensional visualization processing of the density data, a complete spatial energy distribution image is constructed. The converted energy density map contains the energy density values and distribution characteristics of each point in space, and the high density area in the map corresponds to the spatial position with the highest energy conversion efficiency.

[0065] The auxiliary cycle power is derived from the conversion energy density map. The distribution data of high energy density regions, including region location, effective volume and average density value, are extracted from the conversion energy density map. The conversion relationship between energy density and power generation is established: P = η × ρ × V × ω, where P is the power generation, η is the energy conversion efficiency, ρ is the average energy density, V is the effective conversion volume, and ω is the rotor angular velocity. According to the spatial distribution characteristics shown in the conversion energy density map, the contribution of each high-density region to the total power generation is calculated. Combined with the operating parameters of the organic working medium auxiliary cycle, the rotor speed and conversion efficiency and other key parameters are determined. Through the integral calculation of the energy distribution in the density map, the total energy conversion capacity of the magnetic bearing system is obtained. Considering the periodic characteristics of the rotor rotation, the spatial energy density is converted into time-averaged power output. Finally, the extractable power generation value of the organic working medium auxiliary cycle integrated through the magnetic bearing is derived.

[0066] The auxiliary cycle power is derived from the conversion energy density map. The distribution data of high energy density regions, including region location, effective volume and average density value, are extracted from the conversion energy density map. The conversion relationship between energy density and power generation is established: P = η × ρ × V × ω, where P is the power generation, η is the energy conversion efficiency, ρ is the average energy density, V is the effective conversion volume, and ω is the rotor angular velocity. According to the spatial distribution characteristics shown in the conversion energy density map, the contribution of each high-density region to the total power generation is calculated. Combined with the operating parameters of the organic working medium auxiliary cycle, the rotor speed and conversion efficiency and other key parameters are determined. Through the integral calculation of the energy distribution in the density map, the total energy conversion capacity of the magnetic bearing system is obtained. Considering the periodic characteristics of the rotor rotation, the spatial energy density is converted into time-averaged power output. Finally, the extractable power generation value of the organic working medium auxiliary cycle integrated through the magnetic bearing is derived.

[0067] In step S150, the heat matching degree monitoring is performed for the combined power generation configuration to obtain operating state parameters, heat mismatch detection is performed according to the operating state parameters to identify mismatch regions, compensation adjustment is performed based on the mismatch regions to generate heat balance parameters, and the combined power generation configuration is coupled based on the heat balance parameters to generate an optimized cycle network.

[0068] Specifically, the heat matching degree monitoring obtains operating state parameters for the cascade power generation configuration. Temperature, pressure, and flow sensors are installed at key heat exchange nodes in the cascade power generation configuration to establish a real-time monitoring system. Monitoring points are set at key positions such as the inlet and outlet of the evaporator, the inlet and outlet of the superheater, the steam inlet and outlet of the turbine, and the like in the main steam cycle. Monitoring points are set at key positions such as the evaporator, the condenser, and the turbine inlet and outlet of the organic working medium auxiliary cycle. The heat matching degree monitoring evaluates the thermodynamic matching state of the system by calculating three core indicators: the heat supply-demand ratio, the temperature matching degree, and the heat resistance matching coefficient. The temperature gradient dT / dx at each monitoring point is calculated based on the monitoring data to analyze the heat flow conduction direction and determine the heat transfer resistance R=ΔT / Q of each heat exchanger. The temperature matching degree is calculated by analyzing the matching relationship between the heat source temperature and the working medium evaporation temperature to evaluate the influence of temperature difference on heat transfer effect. The heat resistance matching coefficient is calculated by measuring the heat resistance ratio of both sides of the heat exchanger to evaluate the coordination of the heat transfer process. The temperature, pressure, and flow time series data of each monitoring point, as well as the temperature gradient, heat flow direction, and heat transfer resistance information calculated, form a complete operating state parameter data set.

[0069] In some embodiments, the heat mismatch detection according to the operating state parameters identifies a mismatch region, including: performing heat flow distribution analysis on the operating state parameters to generate heat flow distribution data; quantitatively analyzing the temperature difference in the heat flow distribution data to construct a temperature difference parameter; performing matching analysis on the heat flow distribution data and the temperature difference parameter to obtain a mismatch threshold; and performing detection processing based on the mismatch threshold to identify a mismatch region.

[0070] For example, the heat flow distribution analysis on the operating state parameters to generate heat flow distribution data includes: obtaining heat conduction path distribution data based on the operating state parameters to determine conduction efficiency distribution; reconstructing the path based on the conduction efficiency distribution to form an optimal conduction channel; performing impedance matching analysis based on the optimal conduction channel to generate conduction optimization parameters; and constructing heat flow distribution data based on the conduction optimization parameters.

[0071] Heat flow conduction path distribution data is obtained based on operating state parameters to determine conduction efficiency distribution. The temperature gradient, heat flow direction, and heat transfer resistance information of each monitoring point are extracted from the operating state parameter data set to establish a heat flow conduction path network in the cascade power generation configuration. Conduction path analysis divides the heat flow conduction process into multiple series and parallel conduction links such as heat source-heat exchanger, heat exchanger-pipe, pipe-turbine, and turbine-condenser. The path data of each conduction link includes starting temperature, ending temperature, conduction distance, conduction medium, and conduction area, etc. The identification of heat flow conduction path uses temperature field gradient analysis method to calculate the gradient vector of temperature field The main conduction direction of the heat flow is determined, wherein is the temperature gradient vector, respectively. The conduction efficiency is calculated by the definition of heat transfer efficiency η = Q_actual / Q_ideal, where η is the conduction efficiency, Q_actual is the actual conduction heat, and Q_ideal is the ideal conduction heat. The spatial distribution of conduction efficiency is established by the efficiency calculation of each conduction link. The conduction efficiency distribution data of the furnace system shows the difference in conduction performance of different equipment. The conduction efficiency of the evaporator area is relatively high, there is a conduction bottleneck in the superheater area, and the conduction efficiency of the pipeline system performs well.

[0072] The optimal conduction channel is formed by path reconstruction based on the conduction efficiency distribution. The identified low-efficiency links and areas are used to redesign and optimize the conduction path. The principle of path reconstruction is to maximize the overall conduction efficiency, preferentially select high-efficiency conduction links, and avoid low-efficiency conduction areas. The reconstruction process first analyzes the bottleneck links in the existing conduction path and identifies the weak links of the conduction efficiency in the system. Path reconstruction uses parallel shunting, series optimization, and detour obstacle avoidance strategies to divert part of the heat flow from low-efficiency areas to high-efficiency areas. A mathematical model of path reconstruction is established, with the maximum total conduction efficiency as the objective function max∑(ηi×Qi), and the conduction capacity and geometric constraints as the restriction conditions, where ηi is the conduction efficiency of the ith path, and Qi is the conduction heat of the ith path. The optimal conduction path configuration is solved by numerical optimization method. The reconstructed conduction channel adopts a multi-path parallel conduction mode, with the main channel bearing most of the heat flow conduction and the auxiliary channel bearing the remaining heat flow conduction, avoiding the efficiency bottleneck of a single path. For the conduction bottleneck area, the optimal conduction channel design uses a shunting strategy to divide the heat flow into a main channel and a bypass channel. The main channel passes through the improved original equipment, and the bypass channel bypasses the low-efficiency area, thereby improving the overall conduction efficiency through double-channel parallel conduction.

[0073] The conduction optimization parameters are generated according to the impedance matching analysis of the optimal conduction channel. The conduction impedance is defined as R = ΔT / Q, where R is the conduction impedance, ΔT is the temperature difference, and Q is the conduction heat. The goal of the impedance matching analysis is to match the impedance of each conduction link to avoid the loss of conduction efficiency caused by impedance mismatch. By calculating the impedance of each link in the optimal conduction channel, the links with excessive or insufficient impedance are identified. The impedance matching adjustment is achieved by changing the conduction area, conduction distance, and conduction medium, etc. For the links with excessive impedance, the conduction area is increased or the conduction medium is improved to reduce the impedance; for the links with insufficient impedance, the conduction distance is appropriately increased or the conduction conditions are adjusted to increase the impedance. The generation of the conduction optimization parameters includes the impedance adjustment value of each link, the conduction area adjustment ratio, and the conduction condition improvement measures. The impedance matching adjustment achieves the coordinated balance of the impedance of each link by increasing the conduction area, improving the heat preservation conditions, etc. The impedance of the superheater link is reduced by expanding the conduction area, and the impedance of the pipeline link is adjusted by optimizing the heat preservation, thereby achieving the matching and balance of the overall impedance.

[0074] The heat flow distribution data is constructed by the conduction optimization parameters. The heat flow conduction amount of each link is recalculated using the impedance adjustment value in the conduction optimization parameters. The optimized heat flow distribution calculation formula is qi = (T i-1 -T i ) / Ri_opt, where qi is the heat flow of the i-th link, T i-1 and T i are the temperatures at both ends of the link, and Ri_opt is the optimized conduction impedance. The optimized heat flow distribution field is established by calculating the heat flow of each link. The temperature data Ti and the heat flow data qi of each link are associated to construct the distribution data containing both temperature and heat flow information. The calculated heat flow distribution data is subjected to spatial interpolation processing to generate a continuous three-dimensional heat flow distribution field. The heat flow distribution data contains complete information such as heat flow density, temperature value, and flow direction at each spatial position, and the heat flow density distribution in each region is more uniform. The heat flow conduction capacity of the main circulation and auxiliary circulation regions is improved, and the overall heat flow conduction performance is improved.

[0075] The temperature difference parameter is constructed by quantitative analysis of temperature difference in heat flow distribution data. The temperature values of each spatial position are extracted from the temperature information contained in the heat flow distribution data, and the temperature difference between different regions and different positions is calculated. The quantitative analysis of temperature difference includes three dimensions of analysis of spatial temperature gradient, temporal temperature fluctuation and design temperature deviation. The spatial temperature gradient analysis calculates the temperature difference and gradient change rate between adjacent regions, and identifies regions with rapid temperature change and regions with gentle temperature change. The temporal temperature fluctuation analysis calculates the amplitude and frequency characteristics of temperature change with time at each position, and identifies stable temperature regions and fluctuation regions. The design temperature deviation analysis compares the difference between the actual running temperature and the design working condition temperature, and identifies abnormal regions that exceed the design range. The temperature difference parameter ΔT is constructed by the temperature difference calculation method between adjacent regions, ΔT = |T1-T2|, where T1 and T2 are the temperature values of adjacent regions. The representative temperature difference values of each region are determined by statistical analysis method, and the spatial distribution of temperature difference parameter ΔT is formed. The constructed temperature difference parameter ΔT fully reflects the change characteristics and matching relationship of temperature field in heat flow distribution data.

[0076] The mismatch threshold is obtained by matching analysis according to heat flow distribution data and temperature difference parameter. The matching analysis adopts correlation analysis method to calculate the correlation coefficient of heat flux and temperature difference, and to evaluate the matching degree of the two. In the ideal matching state, the high heat flux region should correspond to appropriate temperature difference, and too large or too small temperature difference indicates heat transfer mismatch phenomenon. The heat-temperature matching relationship model R = f(q, ΔT) is established, where R is the matching coefficient, q is the heat flux, and ΔT is the temperature difference parameter. The determination of mismatch threshold adopts statistical method to calculate the mean and standard deviation of matching coefficient, and sets the mismatch threshold as the range of mean ± 2 times standard deviation. When the matching coefficient exceeds this range, it is determined as heat transfer mismatch phenomenon. According to the different degrees of mismatch, three levels of threshold values of light, medium and heavy mismatch are set. The furnace system determines the threshold standards of different mismatch levels through matching analysis, which provides quantitative judgment basis for system mismatch detection.

[0077] The detection processing is performed by the mismatch threshold to identify the mismatch region. With the acquired mismatch threshold criteria, including the normal range and threshold intervals of different levels of mismatch, systematic mismatch detection is performed on each region in the cascade power generation configuration. The detection processing uses a point-by-point scanning method to calculate the matching coefficient of each spatial position and compare it with the mismatch threshold to determine the mismatch level. The calculated matching coefficient value is compared with the threshold range, and the positions exceeding the normal range are marked as mismatch points. The mismatch level is determined according to the extent of the exceedance. Cluster analysis is performed on the identified mismatch points to merge adjacent mismatch points into mismatch regions, and the area, mismatch degree, and impact range of each mismatch region are calculated. The identification of the mismatch region also considers the persistence of the mismatch phenomenon. Only the mismatch phenomenon with a duration exceeding the set threshold is confirmed as a real mismatch region to avoid false positives due to transient fluctuations. A mismatch region database is established to record detailed information such as the position coordinates, mismatch level, duration, and impact degree of each mismatch region. The detection processing of the furnace system identifies the main mismatch regions in the main and auxiliary cycles and prioritizes them according to the impact degree.

[0078] The compensation adjustment based on the mismatch region generates the heat balance parameter. For the identified mismatch regions, including different types of thermal mismatch problems in the main and auxiliary cycles, corresponding compensation adjustment schemes are designed. For thermal supply-demand ratio mismatch, the heat source diversion adjustment method is used to divert part of the high-temperature heat source to other heat-using loads to adjust the heat supply intensity of each region. The diversion adjustment controls the heat source distribution ratio by installing adjustment valves, and calculates the required diversion flow and adjustment parameters. For thermal resistance mismatch, strengthening heat transfer measures are used, including increasing heat exchange area, improving fluid flow, and adjusting heat transfer medium flow. The heat transfer adjustment determines the heat exchanger improvement parameters by calculating the required heat transfer coefficient improvement. Compensation adjustment also includes dynamic adjustment of operating parameters, which adjusts the operating conditions of the cycle system in real time according to the mismatch degree. The generation of the heat balance parameter uses the energy balance equation Q_in = Q_out + Q_loss + Q_store, where Q_in is the input heat, Q_out is the output heat, Q_loss is the heat loss, and Q_store is the heat storage change. Through energy balance calculation after compensation adjustment, the heat balance parameter values of each part are determined. The generated heat balance parameter includes the heat balance coefficient, adjustment parameter, and control strategy of each region, providing parameter support for system optimization.

[0079] The heat balance parameter is used as the control basis for the overall optimization of the cascade power generation configuration, coordinating the joint operation of the main water vapor cycle and the auxiliary organic working fluid cycle. The heat balance parameter guides the heat distribution ratio of the main cycle and the auxiliary cycle in the cascade power generation configuration, and determines the load distribution of the two cycle systems according to the heat balance coefficient. The coupling optimization of the cascade power generation configuration realizes the coordinated control of the two cycle systems by establishing the heat transfer relationship between the main cycle and the auxiliary cycle. The steam pressure and temperature of the main cycle are adjusted according to the heat balance parameter, and the flow rate and condensation temperature of the organic working fluid of the auxiliary cycle are adjusted at the same time, maintaining the overall heat balance state. The construction of the optimized cycle network integrates the main cycle, the auxiliary cycle and the heat balance control system, forming a unified control architecture of the cascade power generation configuration. Through the guidance of the heat balance parameter, the control logic and adjustment strategy of the cycle network are designed, and the linkage relationship and complementary mechanism of the main cycle and the auxiliary cycle are established. The generated optimized cycle network realizes the overall coordinated operation of the cascade power generation configuration, with complete system architecture, control strategy and operating parameters.

[0080] In step S160, an energy transfer matrix is constructed based on the optimized cycle network, and a distributed power generation configuration is generated by generator coupling analysis of the energy transfer matrix to complete stable power output.

[0081] Specifically, the energy transfer matrix is constructed based on the optimized cycle network. The optimized cycle network includes the power generation path of the water vapor main cycle, the power generation path of the organic working fluid auxiliary cycle, and the thermodynamic coupling relationship between them. The construction of the energy transfer matrix mathematically expresses the energy flow relationship in the optimized cycle network, and establishes the energy transfer law between different cycle links. The matrix construction first identifies the energy nodes in the optimized cycle network, including the heat source input node, the heat exchanger node, the turbine node, the generator node and the heat dissipation output node. Each energy node corresponds to a row and a column in the matrix, and the energy transfer relationship between nodes corresponds to the element value in the matrix. The energy transfer matrix adopts a square matrix form E=[eij], where eij represents the energy transfer amount from the ith node to the jth node. The calculation of the matrix elements is based on the energy conservation relationship in the optimized cycle network, considering the energy conversion efficiency and transfer loss of each link. The energy transfer path of the main cycle forms the main transfer chain in the matrix, from the heat source node through the heat exchanger node, the turbine node to the generator node. The energy transfer path of the auxiliary cycle forms a parallel transfer chain in the matrix, which shares part of the heat source node with the main cycle but has an independent conversion path. The energy transfer matrix of the furnace system reflects the complex energy flow mode in the optimized cycle network, and the energy transfer of the main cycle and the auxiliary cycle is independent and has thermodynamic coupling.

[0082] In some embodiments, the generator coupling analysis on the energy transfer matrix generates a distributed power generation configuration, including: performing a speed differentiation analysis on the energy transfer matrix to obtain optimal speed distribution data; performing asynchronous coordination analysis on the optimal speed distribution data to form a speed configuration scheme; performing frequency synchronization processing based on the speed configuration scheme to determine power synthesis parameters; and forming a distributed power generation configuration through the power synthesis parameters.

[0083] The speed differentiation analysis on the energy transfer matrix obtains optimal speed distribution data. The energy input data of each generator node is extracted from the constructed energy transfer matrix, and the optimal operating speed of the generator under different energy input conditions is analyzed. The speed differentiation analysis considers the different working characteristics and energy input modes of the water vapor main cycle generator and the organic working medium auxiliary cycle generator. The main cycle generator is driven by high-temperature and high-pressure steam and has a high rated speed and power output capacity. Its optimal speed is mainly determined by the steam parameters and load conditions. The auxiliary cycle generator is driven by medium and low temperature organic working medium steam, and has a relatively low rated speed but good flexibility. Its optimal speed is closely related to the evaporation temperature and flow of the organic working medium. The speed differentiation analysis calculates the output power and operating efficiency of the generator under different speed conditions by establishing a three-dimensional relationship model of speed-power-efficiency. The energy flow data in the energy transfer matrix is used as the input condition in the analysis process to calculate the theoretical optimal speed n_opt=√(2πηP_in / T_rated) of each generator under the current energy input, where n_opt is the optimal speed, η is the generator efficiency, P_in is the energy input power, and T_rated is the rated torque. The principle of determining the optimal speed is to achieve the highest power generation efficiency and power output under the condition of meeting the safe operation of the generator. The speed differentiation analysis of the furnace system shows that the optimal speeds of the main cycle and auxiliary cycle generators are different, and the coordinated operation of the two needs to be realized through coordinated control. The obtained optimal speed distribution data includes the speed setting value and efficiency expectation of each generator under different working conditions.

[0084] The optimal speed distribution data is executed for asynchronous coordination analysis to form a speed configuration scheme. The optimal speed distribution data is obtained, and asynchronous coordination analysis is performed to handle the coordination problem of the speed difference between the two generators. The core of the asynchronous coordination analysis is to solve the speed difference between the main circulating generator and the auxiliary circulating generator due to different working characteristics, and to realize the coordinated operation of the two in the electrical connection. The analysis process first identifies the speed difference range and variation law of the two generators in the optimal speed distribution data, and establishes a correlation model between the speed difference and the system performance. The speed variation of the main circulating generator is relatively stable, mainly affected by the change of steam parameters; the speed variation of the auxiliary circulating generator is relatively flexible, greatly affected by the change of organic working medium conditions. The asynchronous coordination analysis adopts a speed decoupling control strategy, allowing the two generators to run independently at their respective optimal speeds, and realizing the coordination of electrical output through power electronic devices. The design of the coordinated control system includes three main functional modules: speed monitoring, speed regulation and speed synchronization. The speed monitoring module monitors the actual speed of the two generators in real time and compares it with the optimal speed set value. The speed regulation module automatically adjusts the steam flow or steam parameters of the turbine according to the speed deviation, realizing accurate control of the speed. The speed synchronization module realizes the frequency synchronization of the output power of the two generators through frequency converters and other power electronic equipment. The asynchronous coordination analysis of the furnace system establishes an independent speed control strategy for the main circulating generator and the auxiliary circulating generator, and realizes the coordinated power generation of the two while maintaining their respective optimal speeds. The speed configuration scheme formed determines the independent speed control and coordinated operation requirements of the two generators.

[0085] The frequency synchronization processing is performed based on the rotational speed configuration scheme to determine the power synthesis parameters. According to the formed rotational speed configuration scheme, the frequency synchronization processing is performed to realize the frequency unification of the output power of the two generators. The target of the frequency synchronization processing is to convert the different frequency power generated by the two generators at different rotational speeds into power output with unified frequency. The processing process adopts frequency synchronization technology, and the frequency unification is realized through the AC-DC-AC power conversion mode. The output power of the main cycle generator is first converted into DC power through the rectifier, and then converted into AC power with standard frequency through the inverter. The output power of the auxiliary cycle generator adopts the same conversion flow, ensuring that the frequencies of the two power outputs are completely consistent. The frequency synchronization processing also includes phase synchronization control, which ensures that the phase relationship of the output power of the two generators meets the requirements of parallel operation. The synchronization control system adopts phase-locked loop technology to realize accurate phase tracking and synchronization. The determination of the power synthesis parameters needs to consider the power distribution ratio of the two generators, the voltage matching relationship and the protection configuration requirements. The power distribution ratio is determined according to the rated power and actual operating capacity of each generator, and usually the main cycle generator undertakes the main power output and the auxiliary cycle generator provides supplementary power. The voltage matching realizes the unification of the voltage level through the transformer, and the protection configuration includes overcurrent, overvoltage, undervoltage and other protection functions. The frequency synchronization processing of the furnace system realizes the frequency and phase unification of the output power of the main cycle and auxiliary cycle generators, and creates conditions for the synthesis output of power.

[0086] The distributed power generation configuration is formed through the power synthesis parameters. The power distribution ratio in the power synthesis parameters guides the load sharing of the two generators, and the dynamic power distribution adjustment is realized through the load distribution controller. The voltage level parameter determines the transformer ratio setting and insulation configuration requirements of each stage transformer, ensuring the voltage quality of the power output. The frequency standard parameter sets the output frequency of the frequency converter and the synchronization control accuracy, ensuring that the output power meets the grid standard. The protection setting value parameter configures the action threshold and time setting of various protection devices, ensuring the safe operation of the power generation system. The construction of the distributed power generation configuration includes three main aspects of electrical equipment selection, connection mode design and control system configuration. The electrical equipment selection selects appropriate transformers, switch devices, protection devices and control devices according to the requirements of the power synthesis parameters. The connection mode design determines the electrical connection relationship and installation arrangement of the generators, transformers, switches and protection devices. The control system configuration establishes a comprehensive control platform for generator control, load distribution, synchronization control and protection control. The distributed power generation configuration of the furnace system realizes the coordinated power generation of the main cycle and auxiliary cycle generators, forming a reliable distributed power output capability. Through the dynamic adjustment of the load distribution controller and the accurate coordination of the synchronization control system, it ensures that the two generators can provide stable power output under various working conditions, and completes the stable power output function of the cascade power generation system.

[0087] To implement a kind of kiln flue gas waste heat fractional circulation power generation method corresponding to the above-mentioned method embodiment, to realize corresponding function and technical effect. Figure 3 , Figure 3 The structure block diagram of a kind of kiln flue gas waste heat fractional circulation power generation system 300 provided by the embodiment of the application is shown.For ease of illustration, only the part related to the present embodiment is shown, and the kiln flue gas waste heat fractional circulation power generation system 300 provided by the embodiment of the application includes:

[0088] Desulfurization purification module 301 is used to obtain kiln flue gas composition data and process parameter information, to generate purified flue gas based on the kiln flue gas composition data Desulfurization reaction, and to construct a layered purification chain based on the purified flue gas and the process parameter information.

[0089] Regional generation module 302 is used to determine the pollutant-temperature mapping relationship through the layered purification chain and the purified flue gas, to identify the acid dew point region through the pollutant-temperature mapping relationship, and to reduce the corrosion intensity of the acid dew point region to form a purified flue gas region.

[0090] Thermal energy configuration module 303 is used to analyze the temperature gradient of the purified flue gas region to form a temperature fluctuation curve, to generate a temperature distribution field based on the temperature fluctuation curve Temperature field reconstruction, based on the temperature distribution field, grade thermal energy configuration is generated by thermal grade allocation, and complementary heat source is generated by using the fractional thermal energy configuration in different temperature segments to form a cascade heat flow.

[0091] Cascade power generation module 304 is used to generate a water vapor main cycle and an organic working medium auxiliary cycle by circulating distribution of the cascade heat flow, to extract auxiliary cycle power by integrating magnetic suspension bearing for the organic working medium auxiliary cycle, and to form a cascade power generation configuration by power superposition of the auxiliary cycle power and the power output of the water vapor main cycle.

[0092] Balancing optimization module 305 is used to monitor the running state parameters by heat matching degree for the cascade power generation configuration, to identify the mismatch region by heat mismatch detection according to the running state parameters, to generate heat balance parameters by compensation adjustment based on the mismatch region, and to generate an optimized circulation network by coupling based on the heat balance parameters and the cascade power generation configuration.

[0093] Electric energy output module 306 is used to construct an energy transfer matrix based on the optimized circulation network, to generate a distributed power generation configuration by generator coupling analysis of the energy transfer matrix, and to complete stable electric energy output.

[0094] The above-mentioned kiln flue gas waste heat staged circulating power generation system 300 can implement a kiln flue gas waste heat staged circulating power generation method of the above-mentioned method embodiment. The optional items in the above-mentioned method embodiment are also applicable to the present embodiment, which will not be described in detail herein. The remaining content of the present embodiment can be referred to the content of the above-mentioned method embodiment, which will not be described in detail herein.

[0095] The purpose of the above embodiments is to exemplarily reproduce and deduce the technical solutions of the present application, and to completely describe the technical solutions, purposes and effects of the present application. The purpose is to make the public understand the disclosure of the present application more thoroughly and comprehensively, and not to limit the protection scope of the present application.

[0096] The above embodiments are also not an exhaustive enumeration based on the present application, and there can be many other unlisted embodiments. Any replacement and improvement made without violating the concept of the present application is within the protection scope of the present application.

Claims

1. A method for generating electricity by staged circulation of waste heat from furnace flue gas, characterized in that, The method comprises the following steps: Acquiring kiln flue gas composition data and process parameter information, generating purified flue gas through desulfurization reaction based on the kiln flue gas composition data, and constructing a layered purification chain based on the purified flue gas and the process parameter information, including: layering the purified flue gas after desulfurization treatment according to temperature and pollutant concentration, designing a multi-stage purification process in combination with process parameter information, the first layer of purification is aimed at waste heat recovery in the purified flue gas, the second layer of purification treats residual particulate matter in the purified flue gas, and the third layer of purification is aimed at nitrogen oxides in the purified flue gas; Determine the pollutant-temperature mapping relationship through the layered purification chain and the purified flue gas, identify the acid dew point zone through the pollutant-temperature mapping relationship, reduce the corrosion intensity of the acid dew point zone through temperature control and material protection measures to form a purified flue gas area; Perform temperature gradient analysis on the purified flue gas area to form a temperature fluctuation curve, reconstruct the temperature field based on the temperature fluctuation curve to generate a temperature distribution field, and allocate the heat grade based on the temperature distribution field to generate a hierarchical heat energy configuration, including: identifying and extracting energy conversion nodes in the temperature distribution field; Perform chain transmission analysis on the energy conversion nodes to form an energy propagation chain; perform grade attenuation compensation processing based on the energy propagation chain to generate compensation energy; reconstruct the compensation energy to generate a hierarchical heat energy configuration, use the hierarchical heat energy configuration to form a complementary heat source in different temperature segments to generate a gradient heat flow, including: acquiring heat energy distribution data of each temperature segment in the hierarchical heat energy configuration; match the heat energy distribution data to form a complementary configuration table; according to the complementary configuration table, coordinate and match the heat source to generate a coordinated heat source; and build a gradient transmission path through the coordinated heat source to form a gradient heat flow; Perform cyclic distribution on the gradient heat flow to generate a main cycle of water vapor and an auxiliary cycle of organic working medium, integrate the auxiliary cycle of organic working medium into a magnetic suspension bearing to extract auxiliary cycle power, and superimpose the auxiliary cycle power on the power output of the main cycle of water vapor to form a cascade power generation configuration; Perform heat matching degree monitoring on the cascade power generation configuration to obtain operating state parameters, perform heat mismatch detection according to the operating state parameters to identify mismatch areas, generate heat balance parameters based on the mismatch areas, and couple the heat balance parameters with the cascade power generation configuration to generate an optimized circulation network; Based on the optimized circulation network, construct an energy transmission matrix, perform generator coupling analysis on the energy transmission matrix to generate a distributed power generation configuration, and complete stable power output.

2. The method of claim 1, wherein, The acid dew point zone is identified through the pollutant-temperature mapping relationship, including: Perform corrosion-heat transfer coordination analysis based on the pollutant-temperature mapping relationship to obtain coordination evaluation data; Determine the corrosion and heat transfer balance point through material adaptability evaluation of the coordination evaluation data; Optimize equipment selection according to the corrosion and heat transfer balance point to generate material configuration parameters; Determine the acid dew point safety zone through the material configuration parameters.

3. The method of claim 1, wherein, The auxiliary cycle of organic working medium is integrated into a magnetic suspension bearing to extract auxiliary cycle power, including: Generating a magnetic field intensity distribution based on the organic working medium auxiliary cycle excitation magnetic field coupling effect; Capturing a suspension stability control center from the magnetic field intensity distribution; Forming a conversion energy density map by performing energy focusing analysis on the suspension stability control center; Deriving auxiliary cycle power generation power according to the conversion energy density map.

4. The method of claim 1, wherein, The heat mismatch detection according to the operating state parameter includes: Performing heat flow distribution analysis on the operating state parameter to generate heat flow distribution data; Quantitative analysis based on temperature differences in the heat flow distribution data to construct temperature difference parameters; Matching analysis according to the heat flow distribution data and the temperature difference parameter to obtain a mismatch threshold; Identify the mismatch region through the mismatch threshold detection processing.

5. The method of claim 1, wherein, The generator coupling analysis of the energy transfer matrix includes: Optimal speed distribution data is obtained by analyzing the speed difference of the energy transfer matrix; Forming a speed configuration scheme by performing asynchronous coordination analysis on the optimal speed distribution data; Determine the power synthesis parameter by performing frequency synchronization processing based on the speed configuration scheme; Forming a distributed power generation configuration through the power synthesis parameter.

6. The method of claim 3, wherein, The energy focusing strength distribution is generated by analyzing the energy accumulation data of each magnetic field factor, including magnetic field intensity fluctuation, speed gradient change and bearing position offset. The heat flow distribution data is generated by performing heat flow distribution analysis on the operating state parameter, including: Determine the conduction efficiency distribution based on the operating state parameter to obtain the heat conduction path distribution data; Form the optimal conduction channel by reconstructing the path through the conduction efficiency distribution; 7. The method of claim 4, wherein, Generate conduction optimization parameters by performing impedance matching analysis according to the optimal conduction channel; Construct the heat flow distribution data through the conduction optimization parameters. It includes: Desulfurization purification module, for obtaining kiln flue gas composition data and process parameter information, generating purified flue gas based on the desulfurization reaction of the kiln flue gas composition data, and constructing a hierarchical purification chain based on the purified flue gas and the process parameter information, including: The purified flue gas treated by desulfurization is layered according to temperature and pollutant concentration, and a multi-stage purification process is designed in combination with process parameter information, the first layer purification is aimed at waste heat recovery in purified flue gas, the second layer purification treats residual particulate matter in purified flue gas, and the third layer purification is aimed at nitrogen oxides in purified flue gas; The region generation module is used to determine the pollutant-temperature mapping relationship through the hierarchical purification chain and the purified flue gas, identify the acid dew point area through the pollutant-temperature mapping relationship, and reduce the corrosion intensity of the acid dew point area through temperature control and material protection measures to form a purified flue gas region; 8. A furnace flue gas waste heat cascade cycle power generation system, characterized in that, ​ ​ ​ The thermal energy configuration module is configured to analyze the temperature gradient of the purified flue gas region to form a temperature fluctuation curve, reconstruct a temperature field based on the temperature fluctuation curve to generate a temperature distribution field, and distribute thermal grades based on the temperature distribution field to generate a hierarchical thermal energy configuration, including: identifying and extracting energy conversion nodes in the temperature distribution field; performing chain transmission analysis on the energy conversion nodes to form an energy propagation chain; performing grade attenuation compensation processing based on the energy propagation chain to generate compensated energy; reconstructing the compensated energy to generate a hierarchical thermal energy configuration, using the hierarchical thermal energy configuration to form complementary heat sources in different temperature segments to generate a hierarchical thermal energy flow, including: obtaining thermal energy distribution data for each temperature segment in the hierarchical thermal energy configuration; matching the thermal energy distribution data to form a complementary configuration table; coordinating and matching heat sources according to the complementary configuration table to generate coordinated heat sources; and constructing a hierarchical transmission path through the coordinated heat sources to form a hierarchical thermal energy flow; The cascade power generation module is configured to circulate and distribute the hierarchical thermal energy flow to generate a water vapor main cycle and an organic working medium auxiliary cycle, integrate magnetic suspension bearings into the organic working medium auxiliary cycle to extract auxiliary cycle power, and superimpose the auxiliary cycle power on the power output of the water vapor main cycle to form a cascade power generation configuration; The balance optimization module is configured to monitor the thermal matching degree of the cascade power generation configuration to obtain operating state parameters, perform thermal mismatch detection based on the operating state parameters to identify mismatched regions, generate thermal balance parameters based on the mismatched regions, and couple the thermal balance parameters with the cascade power generation configuration to generate an optimized cycle network; The electrical energy output module is configured to construct an energy transmission matrix based on the optimized cycle network, perform generator coupling analysis on the energy transmission matrix to generate a distributed power generation configuration, and complete stable electrical energy output.

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