A method for optimizing the fuel feed and combustion efficiency of a biomass

Abstract

This invention discloses a method for optimizing biomass fuel feeding and combustion efficiency, comprising five synergistic steps: First, precise moisture regulation and particle size optimization are achieved through microwave moisture detection and two-stage crushing and screening to form a stable, homogeneous fuel. Second, volatile matter is determined using a stepped heating pyrolysis method, and a moisture-volatile matter synergistic control model is established to calculate the optimal feeding frequency, introducing a synergistic correction term to address interaction issues. Third, slagging risk is assessed based on ash melting point characteristics, and the furnace is divided into a rapid pyrolysis zone, a slagging avoidance zone, and a burnout enhancement zone, with temperature control achieved through multi-point temperature monitoring. Fourth, primary air is divided into three segments, and the proportion and spatial location of secondary air are dynamically adjusted based on volatile matter content. Fifth, a closed-loop system is constructed, employing multi-index analysis of flue gas and image recognition technology to monitor combustion status, and adaptive optimization is achieved through a three-level priority control strategy and historical data learning.

Description

Technical Field

[0001] This invention relates to the field of biomass fuel and combustion optimization technology, and more particularly to a method for optimizing biomass fuel feeding and combustion efficiency. Background Technology

[0002] Biomass fuel, as a renewable and clean energy source, holds an important strategic position in the adjustment of the energy structure.

[0003] However, existing biomass combustion technologies face many technical bottlenecks: traditional fuel pretreatment processes cannot simultaneously optimize moisture content and particle size distribution, resulting in unstable fuel combustion characteristics; feed control systems mostly adopt single-parameter adjustment modes, which cannot adapt to the dynamic interaction between moisture and volatile matter content in biomass fuels, easily causing furnace pressure fluctuations and combustion oscillations.

[0004] In terms of combustion temperature field construction, existing technologies lack precise zoning control based on ash melting point characteristics. Slagging avoidance measures are mostly passive responses rather than active prevention, resulting in severe slagging on boiler heating surfaces and reduced thermal efficiency. Air distribution strategies typically adopt a fixed air volume distribution mode, failing to dynamically adjust the primary air segment ratio and secondary air spatial distribution according to volatile matter content, resulting in incomplete combustion of high-volatile fuels or low burnout rates of low-volatile fuels. Combustion control systems mostly rely on feedback from single flue gas parameters, lacking multi-index collaborative analysis and hierarchical priority control mechanisms, and are unable to achieve adaptive optimization operation of the system.

[0005] These technical deficiencies severely restrict the efficient and clean utilization of biomass energy. There is an urgent need to establish an integrated control method that can accurately match fuel characteristics, proactively prevent slagging risks, and dynamically optimize combustion parameters in order to overcome common technical challenges in the industry, such as poor combustion stability, low efficiency, and severe slagging caused by the complex and variable composition of biomass fuels. Summary of the Invention

[0006] The purpose of this invention is to provide a method for optimizing biomass fuel supply and combustion efficiency.

[0007] The problem to be solved by this invention is to address the technical challenges of unstable combustion, severe slagging, low burnout rate, and poor adaptability of control systems caused by the complex and variable composition of biomass fuels, such as moisture, volatile matter, and ash, and to achieve efficient and stable operation of the biomass combustion process.

[0008] A method for optimizing biomass fuel supply and combustion efficiency, the technical solution of which is as follows: S1: Fuel Pretreatment: Moisture adjustment and particle size optimization of biomass fuel; a microwave moisture sensor is used to detect the fuel moisture content, and a hot air drying system or atomizing humidification system is activated according to the detection results to adjust the fuel moisture content to the optimal window range for biomass fuel combustion; through a two-stage crushing and screening process, after primary crushing, secondary screening is performed to retain fuel particles within a specific particle size range and remove excessively fine and coarse particles to form a particle size distribution suitable for biomass combustion; S2: Feeding parameter matching: Adjust feeding parameters according to fuel moisture content and volatile matter content; determine fuel volatile matter content through simplified pyrolysis experiment, and establish a moisture-volatile matter synergistic control model based on moisture detection results to calculate the optimal feeding frequency; set fuel layer thickness according to volatile matter content, using a thinner fuel layer for high volatile matter fuels and a thicker fuel layer for low volatile matter fuels to achieve precise matching between feeding parameters and fuel characteristics; S3: Combustion Temperature Field Construction: A slagging prevention temperature field is constructed based on the ash melting point characteristics of the fuel; the deformation temperature, softening temperature, and flow temperature of the fuel ash are measured using an ash melting point meter to assess the slagging risk level; the furnace is divided into three temperature control zones along the height direction: a rapid pyrolysis zone, a slagging avoidance zone, and a burnout enhancement zone. Specific temperature ranges are strictly avoided in the slagging avoidance zone, and the temperature in this zone is monitored and adjusted through temperature measuring points to prevent ash from melting and slagging. S4: Air distribution strategy optimization: Optimize air volume distribution based on volatile analysis characteristics; divide the primary air into three parts: bottom cooling air, pyrolysis promoting air, and burnout auxiliary air, and control different temperatures and air volume ratios for each part; adjust the secondary air ratio and injection position according to the volatile content, increase the secondary air ratio and move the nozzle upward for high volatile fuels, and decrease the secondary air ratio and move the nozzle downward for low volatile fuels, so as to achieve the adaptation of air distribution strategy to fuel characteristics; S5: Combustion effect feedback: Construct a closed-loop control system; install a flue gas analyzer at the flue outlet to monitor flue gas composition, install an industrial camera in the furnace observation window to periodically take images of the furnace inner wall and analyze the degree of slagging; adjust the feeding parameters, temperature control parameters and air volume distribution parameters based on the monitoring data to achieve adaptive optimization operation.

[0009] Furthermore, the fuel pretreatment in S1, which involves moisture adjustment and particle size optimization of biomass fuel, also includes: When the moisture content of the fuel exceeds the upper limit threshold of biomass fuel combustion adaptability, the gradient heating drying mode is activated. The initial hot air temperature is set below the pyrolysis start temperature of the biomass fuel to avoid premature precipitation of volatiles. As the drying process proceeds, the hot air temperature is gradually increased but does not exceed the biomass tar condensation temperature to ensure the stability of the fuel chemical structure during the drying process. When the moisture content of the fuel is detected to be lower than the lower limit threshold of biomass fuel combustion fluidity, a combined process of atomization humidification and mechanical mixing is adopted. Atomized water droplets are evenly sprayed onto the fuel surface through multi-stage atomizing nozzles, and a spiral stirring device is used to allow the moisture to penetrate into the fuel, so as to avoid the sticking and clumping phenomenon caused by excessive surface moisture. Particle size optimization adopts an adaptive screening process based on biomass fuel characteristics: the primary crushing adopts a shear crusher, and the blade gap is set according to the fuel fiber length characteristics, with a larger gap for woody fuels and a smaller gap for herbaceous fuels; The secondary screening uses a multi-layer vibrating screen, with the screen aperture configuration adjusted according to the fuel ash content. High-ash fuels use finer screens to reduce ash aggregation, while low-ash fuels use coarser screens to maintain the integrity of the fuel structure. Airflow separation is carried out simultaneously during the screening process. Based on the difference in suspension velocity between biomass fine powder and qualified particles, ultrafine particles that affect combustion stability are separated by adjusting the airflow velocity. The final fuel particle size distribution and moisture content constitute the basic parameters for the synergistic optimization of biomass fuel combustion, providing stable and homogeneous fuel input conditions for subsequent feeding and combustion steps.

[0010] Furthermore, the feeding parameter matching in S2, which adjusts the feeding parameters according to the fuel moisture content and volatile matter content, includes: The volatile matter content was determined using a stepped heating pyrolysis method: a quantitative biomass fuel sample was placed in a pyrolysis furnace. First, the temperature was increased to 150°C at a rate of 10°C / min and held for 10 minutes to remove surface moisture. Then, the temperature was increased to 300°C at a rate of 5°C / min and held for 5 minutes to decompose hemicellulose. Finally, the temperature was increased to 500°C at a rate of 3°C / min and held for 15 minutes to complete the pyrolysis process. The volatile matter content was calculated based on the percentage of mass loss. This determination method is designed for the staged pyrolysis characteristics of cellulose, hemicellulose, and lignin in biomass fuels, avoiding the measurement errors caused by traditional single-temperature pyrolysis. The moisture-volatile matter synergistic control model employs a bivariate coupling algorithm: using fuel moisture content as the basic adjustment variable and volatile matter content as the correction adjustment variable, a feed frequency calculation model is established. When the volatile matter content exceeds the critical value of biomass fuel volatile matter, a volatile matter correction coefficient is introduced into the feed frequency calculation. This coefficient decreases linearly with increasing volatile matter content to prevent a sudden increase in furnace pressure due to excessively rapid feed of high-volatile matter fuel. When the moisture content is below the safe lower limit of biomass fuel moisture, a moisture correction coefficient is introduced into the feed frequency calculation. This coefficient increases with decreasing moisture content to avoid uneven feed caused by excessive fluidity of low-moisture fuel. The feed frequency calculation formula of the moisture-volatile matter synergistic control model is as follows: ,in For optimal feeding frequency, The reference feeding frequency is calculated based on the boiler's rated load and the lower heating value of the fuel. To detect the moisture content of the fuel, The optimal moisture content for biomass fuel combustion is the baseline value. The measured volatile matter content of the fuel, This is the baseline value for volatile matter in biomass fuels. This is the moisture correction factor. This is the correction factor for volatile matter. This is the moisture-volatile matter co-correction coefficient; the formula introduces a co-correction term. This invention addresses the technical shortcomings of traditional univariate control models, which cannot adapt to the interaction between moisture and volatile matter in biomass fuels. When high-moisture fuel is accompanied by high volatile matter, the synergistic correction term produces a positive compensation effect, preventing excessive reduction in feed frequency from causing combustion interruption. When low-moisture fuel is accompanied by low volatile matter, the synergistic correction term produces a negative adjustment effect, preventing excessively high feed frequency from causing incomplete combustion, thereby achieving dynamic balance control of the biomass fuel feed process. The fuel bed thickness setting adopts a combustion kinetics adaptation strategy: the fuel bed thickness is divided into three layers: bottom layer, middle layer and surface layer. The bottom layer thickness is fixed at 1.5 times the grate gap width to ensure uniform air distribution. The middle layer thickness is set according to the volatile matter content as the base thickness multiplied by the volatile matter correction factor. The surface layer thickness is set according to the moisture content as the base thickness multiplied by the moisture correction factor. The volatile matter correction factor decreases with increasing volatile matter content, while the moisture correction factor increases with increasing moisture content. The three layer thicknesses are superimposed to form the total fuel bed thickness. This layer setting method is designed to address the spatiotemporal distribution characteristics of rapid volatile matter release and moisture evaporation during biomass fuel combustion, ensuring combustion process stability and burnout rate. The coordinated control of feeding frequency and fuel bed thickness adopts a time-matching mechanism: first, the total fuel demand is determined according to the boiler load demand, then the single feeding amount is calculated according to the fuel bed thickness set value, and finally the feeding frequency is obtained by dividing the total fuel demand by the single feeding amount. When the furnace pressure fluctuation is detected to exceed the set threshold, the feeding frequency is adjusted first rather than the fuel bed thickness to maintain the relative stability of the fuel bed thickness. This control logic solves the combustion oscillation problem caused by frequent adjustment of feeding parameters during biomass fuel combustion.

[0011] Furthermore, the construction of the combustion temperature field in S3, based on the fuel ash melting point characteristics to construct a slagging prevention temperature field, also includes: Fuel ash samples were subjected to a stepped heating test in a weakly reducing atmosphere. First, the temperature was raised to 800℃ at a rate of 5℃ / min to determine the deformation temperature DT. Then, the temperature was raised to 1000℃ at a rate of 3℃ / min to determine the softening temperature ST. Finally, the temperature was raised to 1200℃ at a rate of 2℃ / min to determine the flow temperature FT. The stepped heating rate was adjusted according to the alkali metal content in the biomass ash. When the alkali metal content was higher than 20%, a slower heating rate was used to ensure that the ash melting point test results accurately reflected the slagging characteristics of biomass fuel under actual combustion conditions. The slagging risk level assessment adopts a three-temperature zone comprehensive judgment method: when the ST-FT temperature difference is less than 100℃ and DT is less than 900℃, it is judged as a high-risk level; when the ST-FT temperature difference is between 100-200℃ and DT is between 900-1000℃, it is judged as a medium-risk level; and when the ST-FT temperature difference is greater than 200℃ and DT is greater than 1000℃, it is judged as a low-risk level. This judgment method combines the width of the ash melting point range and the initial melting temperature as dual indicators, overcoming the limitations of the traditional single temperature judgment. The furnace temperature zones are divided using a combustion kinetics zoning strategy: the rapid pyrolysis zone is located at the bottom of the furnace (0-300mm height), with the temperature controlled between 300-600℃ to promote rapid volatile matter release; the slagging avoidance zone is located in the middle of the furnace (300-800mm height), with the temperature strictly controlled outside the slagging risk temperature range. When determined to be high-risk, the temperature in this zone is avoided in the 700-900℃ range; when determined to be medium-risk, it is avoided in the 750-850℃ range; and when determined to be low-risk, it is avoided in the 800-850℃ range; the burnout enhancement zone is located in the upper part of the furnace (above 800mm height), with the temperature maintained at 900-1100℃ to ensure complete combustion of fixed carbon. Temperature monitoring employs a multi-point collaborative feedback mechanism: at least eight temperature measuring points are evenly arranged along the circumference of the furnace in the slagging avoidance zone, with each measuring point equipped with dual redundant thermocouples. When the temperature difference between any two adjacent measuring points exceeds 50°C, local make-up air adjustment is initiated. When the average temperature of the area approaches the boundary of the slagging risk temperature range, the secondary air ratio is adjusted first, rather than the primary air volume, to maintain combustion stability while preventing slagging. This temperature field construction method fundamentally solves the slagging problem in the combustion process of biomass fuel by precisely controlling the temperature distribution at different combustion stages.

[0012] Furthermore, the air distribution strategy optimization in S4, which optimizes airflow allocation based on volatile analysis characteristics, also includes: The bottom cooling air temperature is controlled at 80-120℃, and the air volume accounts for 25%-35% of the total primary air volume. It is used to cool the grate and form the initial oxidation layer. The pyrolysis promoting air temperature is controlled at 150-200℃, and the air volume accounts for 40%-50% of the total primary air volume. It forms a weakly reducing atmosphere in the fuel pyrolysis zone to promote the complete release of volatiles. The burnout auxiliary air temperature is controlled at 200-250℃, and the air volume accounts for 20%-30% of the total primary air volume. It provides sufficient oxygen in the burnout zone to ensure complete combustion of fixed carbon. This three-stage air volume distribution is adjusted according to the oxygen demand characteristics of biomass fuel at different combustion stages, overcoming the problem of incomplete combustion caused by traditional single-stage primary air. The secondary air control adopts a volatile matter-space coupling strategy: when the volatile matter content is greater than 75%, the proportion of secondary air is increased to 40%-45% of the total air volume, and the nozzle position is moved upward to 70%-80% of the furnace height to form a strong turbulence zone in the upper part to promote rapid combustion of volatile matter; when the volatile matter content is between 60%-75%, the proportion of secondary air is set to 35%-40% of the total air volume, and the nozzle position is located at 50%-60% of the furnace height to maintain combustion stability in the middle part; when the volatile matter content is less than 60%, the proportion of secondary air is reduced to 30%-35% of the total air volume, and the nozzle position is moved downward to 30%-40% of the furnace height to enhance the combustion intensity in the lower part. The air volume coordinated control adopts a pressure-temperature dual feedback mechanism: pressure and temperature measuring points are set at different heights in the furnace. When the temperature of the slagging avoidance zone is close to the critical value of the ash melting point, the secondary air volume in this area is increased first rather than the total air volume is reduced, so as to maintain combustion efficiency and prevent slagging. When the furnace pressure fluctuation exceeds ±200Pa, the ratio of the three primary air sections and the position of the secondary air nozzle are adjusted simultaneously to maintain pressure stability. This air distribution strategy achieves dual optimization of combustion efficiency and slagging prevention by accurately matching the air volume distribution with the combustion kinetics of biomass fuel.

[0013] Furthermore, the combustion effect feedback in S5, which constructs a closed-loop control system, also includes: The flue gas composition monitoring adopts a multi-index synergistic analysis method: the flue gas analyzer collects data every 5 minutes, and simultaneously monitors four key indicators: oxygen content, carbon monoxide concentration, nitrogen oxide concentration, and unburned hydrocarbon content. When the oxygen content is below 3% and the carbon monoxide concentration is above 100ppm, it is determined to be an insufficient oxygen supply state. When the nitrogen oxide concentration exceeds 200mg / Nm³, it is determined to be a local high temperature state. When the unburned hydrocarbon content is above 50ppm, it is determined to be an incomplete combustion state. This multi-index judgment method overcomes the limitations of traditional single oxygen control. The slagging degree analysis adopts the image feature extraction method: an industrial camera takes an image of the furnace inner wall every 30 minutes, and the slagging area is extracted by grayscale threshold segmentation. The slagging coverage rate and slagging thickness index are calculated. When the slagging coverage rate exceeds 15% or the slagging thickness index is greater than 0.3, an early warning signal is triggered. This image analysis method is designed for the deposition characteristics of biomass ash on the furnace inner wall and can accurately identify early slagging phenomena. The parameter adjustment adopts a three-level priority control strategy: the first level is the air volume distribution parameter, which prioritizes the adjustment of the secondary air ratio and nozzle position when incomplete combustion is detected; the second level is the temperature control parameter, which adjusts the temperature setpoint of the slagging avoidance zone when local high temperature is detected; and the third level is the feeding parameter, which adjusts the feeding frequency and fuel bed thickness only when abnormal combustion is detected three times in a row. This graded strategy ensures stable operation while achieving precise control. Adaptive optimization employs a historical data weighted learning method: a parameter adjustment effect evaluation matrix is ​​established, and the changes in combustion state before and after each parameter adjustment are recorded. Effective adjustments are given higher weights, while ineffective adjustments are given lower weights. When the same abnormal combustion state recurs, historically effective adjustment schemes are given priority. This learning mechanism can gradually adapt to the combustion characteristics of different biomass fuels and realize the transformation from a passive response to an active prevention control mode.

[0014] The beneficial effects of this invention are: by constructing a complete closed-loop control system through five coordinated links, namely fuel pretreatment, feed parameter matching, combustion temperature field construction, air distribution strategy optimization, and combustion effect feedback.

[0015] A synergistic control model for moisture and volatile matter was established. By introducing a synergistic correction term, the technical deficiency of traditional univariate control in adapting to the interaction between moisture and volatile matter in biomass fuel was solved. When high moisture fuel is accompanied by high volatile matter, a positive compensation effect is generated, and when low moisture fuel is accompanied by low volatile matter, a negative adjustment effect is generated, thus achieving balanced control of the feeding process.

[0016] The slagging prevention temperature field, constructed based on the ash melting point characteristics, divides the furnace into three functional zones. In particular, the slagging avoidance zone dynamically avoids specific temperature ranges according to the risk level, fundamentally preventing the slagging problem in the biomass combustion process.

[0017] The air distribution strategy employs a three-stage primary air distribution and a spatial coupling adjustment of secondary air volatiles to precisely match the oxygen demand characteristics of different combustion stages. The closed-loop feedback system, through multi-index collaborative analysis and a three-level priority control strategy, realizes the transformation from a passive response to an active prevention control mode.

[0018] Overall, this method overcomes the technical bottlenecks caused by the large differences in the characteristics of biomass fuels, such as unstable combustion, severe slagging, and low efficiency. While ensuring combustion stability, it improves combustion efficiency and reduces pollutant emissions, providing reliable technical support for the efficient and clean utilization of biomass energy. Attached Figure Description

[0019] Figure 1 A flowchart illustrating a method for optimizing biomass fuel supply and combustion efficiency. Detailed Implementation

[0020] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] In order to achieve the above objectives, Figure 1 A flowchart of a method for optimizing biomass fuel supply and combustion efficiency is presented.

[0022] Furthermore, the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this article, unless otherwise specified, generally indicates that the preceding and following related objects have an "or" relationship.

[0023] Example 1 A method for optimizing biomass fuel supply and combustion efficiency, the technical solution of which is as follows: S1: Fuel Pretreatment: Moisture adjustment and particle size optimization of biomass fuel; a microwave moisture sensor is used to detect the fuel moisture content, and a hot air drying system or atomizing humidification system is activated according to the detection results to adjust the fuel moisture content to the optimal window range for biomass fuel combustion; through a two-stage crushing and screening process, after primary crushing, secondary screening is performed to retain fuel particles within a specific particle size range and remove excessively fine and coarse particles to form a particle size distribution suitable for biomass combustion; S2: Feeding parameter matching: Adjust feeding parameters according to fuel moisture content and volatile matter content; determine fuel volatile matter content through simplified pyrolysis experiment, and establish a moisture-volatile matter synergistic control model based on moisture detection results to calculate the optimal feeding frequency; set fuel layer thickness according to volatile matter content, using a thinner fuel layer for high volatile matter fuels and a thicker fuel layer for low volatile matter fuels to achieve precise matching between feeding parameters and fuel characteristics; S3: Combustion Temperature Field Construction: A slagging prevention temperature field is constructed based on the ash melting point characteristics of the fuel; the deformation temperature, softening temperature, and flow temperature of the fuel ash are measured using an ash melting point meter to assess the slagging risk level; the furnace is divided into three temperature control zones along the height direction: a rapid pyrolysis zone, a slagging avoidance zone, and a burnout enhancement zone. Specific temperature ranges are strictly avoided in the slagging avoidance zone, and the temperature in this zone is monitored and adjusted through temperature measuring points to prevent ash from melting and slagging. S4: Air distribution strategy optimization: Optimize air volume distribution based on volatile analysis characteristics; divide the primary air into three parts: bottom cooling air, pyrolysis promoting air, and burnout auxiliary air, and control different temperatures and air volume ratios for each part; adjust the secondary air ratio and injection position according to the volatile content, increase the secondary air ratio and move the nozzle upward for high volatile fuels, and decrease the secondary air ratio and move the nozzle downward for low volatile fuels, so as to achieve the adaptation of air distribution strategy to fuel characteristics; S5: Combustion effect feedback: Construct a closed-loop control system; install a flue gas analyzer at the flue outlet to monitor flue gas composition, install an industrial camera in the furnace observation window to periodically take images of the furnace inner wall and analyze the degree of slagging; adjust the feeding parameters, temperature control parameters and air volume distribution parameters based on the monitoring data to achieve adaptive optimization operation.

[0024] Furthermore, the fuel pretreatment in S1, which involves moisture adjustment and particle size optimization of biomass fuel, also includes: When the moisture content of the fuel exceeds the upper limit threshold of biomass fuel combustion adaptability, i.e. the fuel is too wet, the gradient heating drying mode is activated. The initial hot air temperature is set below the biomass fuel pyrolysis start temperature, usually in the range of 150℃-200℃, depending on the type of fuel, to ensure that only physical dehydration and not chemical pyrolysis occur. As the drying process progresses and the surface moisture of the fuel decreases, the hot air temperature is gradually increased but does not exceed the condensation temperature of the biomass tar. However, it is essential to ensure that the hot air temperature does not exceed the condensation temperature of the biomass tar throughout the process, typically below 250°C, to prevent tar from precipitating and sticking to the equipment.

[0025] When the fuel moisture content is detected to be below the lower limit threshold of biomass fuel combustion fluidity, i.e. the fuel is too dry, a combined process of atomization humidification and mechanical mixing is adopted. Simple spraying will cause the moisture to only adhere to the surface and cannot penetrate. Multi-stage atomizing nozzles atomize water into micron-sized droplets, which are then evenly sprayed onto the fuel surface on the conveyor belt. At the same time, a subsequent spiral stirring device is activated, which uses mechanical shearing force to break down the air film resistance on the fuel surface and force water to penetrate into the capillary pores inside the fuel.

[0026] Particle size optimization employs an adaptive screening process based on biomass fuel characteristics: a shear crusher is used for coarse crushing. To accommodate the different physical properties of biomass, the cutter gap is not a fixed value but is set according to the length characteristics of the fuel fibers. For woody fuels with long and tough fibers, a larger blade gap, such as 20mm-30mm, is set to prevent tangling and clogging; for herbaceous fuels with short and fragile fibers, a smaller blade gap, such as 10mm-15mm, is set to prevent excessive crushing and the generation of fine powder.

[0027] Secondary screening uses a multi-layer vibrating screen for fine grading. The screen aperture configuration is adjusted according to the ash content of the fuel. For high ash fuels, a finer screen, such as 8mm-10mm, is used to remove more fine powder, because the fine powder of high ash fuels is very easy to form fly ash and slag in the furnace. For low ash fuels, a coarser screen, such as 12mm-15mm, is used to allow a certain proportion of coarse particles to be retained in order to maintain the air permeability of the grate.

[0028] During the screening process, airflow separation is carried out simultaneously. Based on the difference in suspension velocity between biomass fine powder and qualified particles, the ultrafine particles that affect combustion stability are separated by adjusting the airflow velocity. If too many qualified particles are detected in the airflow, it indicates that the airflow velocity is too high. In this case, the fan frequency is reduced or the damper opening is decreased to reduce the actual airflow velocity. If a lot of fine powder residue is detected after screening, it indicates that the airflow velocity is too low. In this case, the fan frequency is increased or the damper opening is increased to increase the actual airflow velocity. The resulting fuel particle size distribution and moisture content constitute the basic parameters for the synergistic optimization of biomass fuel combustion.

[0029] Furthermore, the feeding parameter matching in S2, which adjusts the feeding parameters according to the fuel moisture content and volatile matter content, includes: The volatile matter content was determined using a stepped heating pyrolysis method: 5-10g of biomass fuel sample with a particle size of 2-5mm was placed in a quartz crucible and then placed in a pyrolysis furnace. First, the temperature was increased to 150℃ at a rate of 10℃ / min and held for 10 minutes to remove surface moisture. This stage primarily removed adsorbed moisture from the fuel surface to avoid affecting subsequent pyrolysis quality measurements. Next, the temperature was increased to 300℃ at a rate of 5℃ / min and held for 5 minutes. This rate was set to ensure that hemicellulose components fully decomposed at low temperatures without undergoing violent reactions. Finally, the temperature was increased to 500℃ at a rate of 3℃ / min and held for 15 minutes to ensure complete pyrolysis of cellulose and lignin. After pyrolysis, the mixture was cooled to room temperature, and the remaining coke mass was weighed. The volatile matter content was calculated as a percentage of mass loss: Volatile matter content (%) = (Initial mass - Coke mass) / Initial mass × 100%.

[0030] The moisture-volatile matter synergistic control model adopts a bivariate coupling algorithm: using fuel moisture content as the basic adjustment variable and volatile matter content as the correction adjustment variable, a feeding frequency calculation model is established. When the volatile matter content exceeds the critical value of biomass fuel volatile matter, the feeding frequency calculation introduces a volatile matter correction coefficient, which decreases linearly with the increase of volatile matter content; when the moisture content is lower than the safe lower limit of biomass fuel moisture, the feeding frequency calculation introduces a moisture correction coefficient, which increases with the decrease of moisture content.

[0031] The formula for calculating the feeding frequency of the moisture-volatile matter synergistic control model is as follows: ,in For optimal feeding frequency, The reference feeding frequency is calculated based on the boiler's rated load (e.g., 10 t / h) and the fuel's lower heating value (e.g., 15 MJ / kg) through energy balance. To detect the fuel moisture content, an online microwave moisture sensor was used for measurement. The optimal moisture content for biomass fuel combustion is typically 8-12%, representing the highest combustion efficiency determined experimentally. The volatile matter content of the fuel was obtained through the aforementioned stepped-temperature pyrolysis method. This is the baseline value for volatile matter in biomass fuels, typically 65-75%, corresponding to the typical value for conventional biomass fuels. This is a moisture correction factor, ranging from 0.02 to 0.05. When the moisture content is lower than the baseline value, the feeding frequency needs to be increased to compensate for the loss of calorific value. This is a correction factor for volatile matter, ranging from 0.01 to 0.03. When the volatile matter content exceeds the baseline value, the feeding frequency needs to be reduced to avoid excessive combustion. The moisture-volatile matter synergistic correction coefficient, with a value range of 0.001-0.005, is used to compensate for the nonlinear effects caused by the interaction of the two variables. Moisture content is used as the basic variable, and volatile matter is used as the correction variable. Through multiplicative coupling, they achieve coordinated regulation. hour, Increase the feeding frequency; when hour, Reduce material supply frequency; collaborative projects It provides compensation when both deviate from the benchmark.

[0032] The fuel bed thickness is set using a combustion kinetics adaptation strategy: the fuel bed thickness is divided into three layers: bottom, middle, and top. The bottom layer thickness is fixed at 1.5 times the grate gap width to ensure uniform air distribution. For example, if the grate gap is 10mm, the bottom layer thickness is 15mm to ensure uniform airflow and prevent fuel leakage. The middle layer thickness is set based on the volatile matter content, multiplied by a baseline thickness and a volatile matter correction factor. This baseline thickness is 20-30mm, and the volatile matter correction factor is calculated according to... Calculations show that when the volatile matter content is high, the layer thickness is reduced to less than 1 by the factor to prevent concentrated volatile matter precipitation that could lead to deflagration. The surface layer thickness is set based on the moisture content, which is the baseline thickness multiplied by a moisture correction factor. This baseline thickness is set to 10-15 mm, and the moisture correction factor is calculated as follows: The calculation shows that the volatile matter correction factor decreases with increasing volatile matter content, while the moisture correction factor increases with increasing moisture content. When the moisture content is high, the factor is greater than 1. The thickness of the three layers increases, thus prolonging the drying time. The total fuel layer thickness is formed by the superposition of the three layer thicknesses.

[0033] The coordinated control of feeding frequency and fuel bed thickness adopts a time-series matching mechanism: first, the total fuel demand is determined based on the boiler load requirements, such as the steam pressure setpoint; then, the single feeding amount is calculated based on the fuel bed thickness setpoint and the grate area; finally, the feeding frequency is obtained by dividing the total fuel demand by the single feeding amount. When the furnace pressure fluctuation is detected to exceed the ±200Pa threshold, the feeding frequency is adjusted first rather than the fuel bed thickness because frequency adjustment is faster and can stabilize the combustion conditions in a timely manner, while bed thickness adjustment involves changes in mechanical structure, which has a slow response and is prone to combustion oscillation.

[0034] Furthermore, the construction of the combustion temperature field in S3, based on the fuel ash melting point characteristics to construct a slagging prevention temperature field, also includes: Take 5-10g of fuel ash sample and place it in a corundum crucible, then place it in an ash melting point tester; introduce a weakly reducing atmosphere, a mixture of 60% CO2 and 40% CO gas at a flow rate of 1.5L / min, first raise the temperature to 800℃ at a rate of 5℃ / min and hold for 5 minutes, and record the temperature at which the ash cone begins to deform as the deformation temperature DT; then raise the temperature to 1000℃ at a rate of 3℃ / min, and record the temperature at which the ash cone bends until the tip touches the support plate or forms a hemispherical shape as the softening temperature ST; finally, raise the temperature to 1200℃ at a rate of 2℃ / min, and record the temperature at which the ash cone melts into a liquid or spreads into a thin layer with a height ≤1.5mm as the flow temperature FT; When the fuel ash content test shows that the alkali metal content (K2O+Na2O) is higher than 20%, all heating rates are reduced by 20%, i.e., adjusted to 4℃ / min, 2.4℃ / min, and 1.6℃ / min respectively, because high alkali metal content will accelerate the ash melting process, and a slower heating rate is needed to capture the accurate characteristic temperature.

[0035] After obtaining the three characteristic temperatures DT, ST, and FT through laboratory measurements, the following rules are applied to determine the risk level: when the ST-FT temperature difference is less than 100℃ and DT is below 900℃, it is considered a high-risk level. This condition indicates that the ash melting range is narrow and the initial melting temperature is low, making it extremely prone to slagging. When the ST-FT temperature difference is between 100-200℃ and DT is between 900-1000℃, it is considered a medium-risk level. When the ST-FT temperature difference is greater than 200℃ and DT is greater than 1000℃, it is considered a low-risk level. This determination standard is based on statistical analysis of a large amount of biomass combustion experimental data and can effectively predict the slagging tendency in actual combustion.

[0036] The furnace temperature zones are divided using a combustion kinetics zoning strategy: the rapid pyrolysis zone is located at the bottom of the furnace (0-300mm height), and the temperature in this zone is controlled at 300-600℃ by controlling the primary air volume to ensure complete fuel drying and volatilization; the slagging avoidance zone is located in the middle of the furnace (300-800mm height), and the temperature is strictly controlled outside the slagging risk temperature range. When determined to be high-risk, the temperature in this zone is avoided in the 700-900℃ range; when determined to be medium-risk, it is avoided in the 750-850℃ range; and when determined to be low-risk, it is avoided in the 800-850℃ range; the burnout enhancement zone is located in the upper part of the furnace (above 800mm height), and the temperature is maintained at 900-1100℃ by secondary air distribution; each zone boundary is physically isolated by a 5mm thick heat-resistant baffle made of 310S stainless steel to prevent mutual interference of temperature fields.

[0037] Temperature monitoring employs a multi-point collaborative feedback mechanism: at least eight temperature measuring points are evenly arranged along the circumference of the furnace in the slagging avoidance zone, spaced at 45° intervals. Each measuring point has a K-type thermocouple with an accuracy of ±1.5℃ and is installed at a 90° angle. When the temperature difference between any two adjacent measuring points exceeds 50℃ (e.g., measuring point 1 is 780℃ and measuring point 2 is 840℃), the corresponding local air supply valve is opened to supply cold air at a temperature of 25-30℃, with the air volume being 5-10% of the total air volume in the area. When the average temperature of the slagging avoidance zone approaches the boundary of the slagging risk temperature range of 50℃, the secondary air ratio is adjusted first rather than increasing the primary air volume. If the temperature approaches 650℃ at a high risk level, the proportion of upper secondary air is increased by 10-15%. Secondary air adjustment can more accurately control the temperature distribution in this area and avoid changes in primary air volume affecting the stability of the grate fuel layer.

[0038] Furthermore, the air distribution strategy optimization in S4, which optimizes airflow allocation based on volatile analysis characteristics, also includes: The primary air system is divided into three independent air chambers. The bottom cooling air is introduced from the 0-100mm height area below the grate. The temperature is controlled at 80-120℃ through the economizer bypass. The air volume accounts for 25%-35% of the total primary air volume. This air volume range is set because if the proportion is too low (<25%), the cast iron grate cannot be effectively cooled and the working temperature needs to be controlled below 300℃. If the proportion is too high (>35%), it will disrupt the formation of the initial oxide layer. The temperature of the pyrolysis promoting air is introduced from a height of 100-300mm above the grate and controlled at 150-200℃ by the first stage heating of the air preheater. The air volume accounts for 40%-50% of the total primary air volume. This ratio ensures that there is sufficient oxygen in the volatile matter separation stage. Experiments have shown that below 40% will lead to incomplete combustion, and above 50% will overcool the pyrolysis zone. The burnout auxiliary air is introduced from the 300-500mm height area and controlled at 200-250℃ through secondary heating by the air preheater. The air volume accounts for 20%-30% of the total primary air volume, which ensures the oxygen supply during the coke burnout stage and avoids excessive cold air from lowering the combustion temperature. The three air chambers are equipped with independent variable frequency fans with a power of 15-30kW and electric dampers with an adjustable opening of 0-100%. The air volume distribution is monitored and adjusted by an air volume meter with an accuracy of ±2%.

[0039] Secondary air control adopts a volatile matter-space coupling strategy: the secondary air system is equipped with multiple layers of nozzles around the furnace, with 8 nozzles evenly distributed circumferentially in each layer; When the online volatile matter detector shows that the volatile matter content of fuel is greater than 75%, such as rice husks and straw, the proportion of secondary air should be increased to 40%-45% of the total air volume, and the nozzle position should be switched to the upper layer, that is, 70%-80% of the furnace height, because high volatile matter fuels need to be fully burned in the upper space. When the volatile matter content is 60%-75%, such as sawdust and branches, the secondary air ratio should be set to 35%-40%, and the middle layer nozzle should be activated at a height of 50%-60% to maintain combustion stability. When the volatile matter content is less than 60%, such as olive pomace and palm shell, the proportion of secondary air is reduced to 30%-35%, and the lower nozzle is activated at a height of 30%-40% to enhance the combustion intensity in the lower part. Nozzle switching is achieved via an electric push rod with a stroke of 200mm and a response time of 3 seconds. The secondary air volume is controlled by a variable frequency fan with a power of 18.5kW. This strategy is based on experiments on the combustion characteristics of fuels with different volatile contents: high volatile fuels require a larger proportion of secondary air and a higher injection position to avoid excessive concentration of volatiles in the lower part, which could lead to deflagration.

[0040] The air volume coordinated control adopts a pressure-temperature dual feedback mechanism: pressure measuring points with a range of 0-5000Pa and an accuracy of ±10Pa are set at furnace heights of 300mm, 500mm, and 800mm, respectively, and temperature measuring points with a range of 0-1300℃ are set with dual S-type thermocouples; when any temperature measuring point in the slagging avoidance zone of 300-800mm exceeds the set critical value, such as 850℃ for high-risk fuel, the secondary air volume corresponding to that height is increased first, by 5-10%, rather than reducing the total air volume, because increasing the local air volume can quickly cool down without affecting the overall combustion intensity; When the furnace pressure fluctuation exceeds ±200Pa for more than 5 seconds, the PLC control system performs two operations simultaneously: (1) adjust the distribution of the three sections of primary air proportionally. For example, when the pressure increases, the proportion of bottom cooling air increases by 2%, the proportion of pyrolysis promoting air decreases by 1.5%, and the proportion of combustion auxiliary air decreases by 0.5%. (2) shift the position of the secondary air nozzle to the area with lower pressure by 10%-15%. For example, when the pressure in the upper part of the furnace is high, the nozzle moves down by 10%. This collaborative control logic ensures rapid recovery to stability during pressure fluctuations, avoiding control lag caused by adjusting a single parameter; all adjustments are completed within 10 seconds, with the adjustment range limited to ±15%, preventing sudden parameter changes from affecting combustion stability.

[0041] Furthermore, the combustion effect feedback in S5, which constructs a closed-loop control system, also includes: The flue gas composition monitoring adopts a multi-index synergistic analysis method: a sampling probe is set at the tail flue of the boiler, i.e., 1.5 meters away from the economizer outlet, and the flue gas analyzer collects data every 5 minutes; simultaneously monitoring oxygen content (range 0-25%, accuracy ±0.1%), carbon monoxide concentration (range 0-2000ppm, accuracy ±5ppm), and nitrogen oxide concentration (range 0-500mg / Nm³). 3 Accuracy ±2mg / Nm 3 The four key indicators are: ) and unburned hydrocarbon content (range 0-100ppm, accuracy ±1ppm); When the oxygen content is measured to be below 3% for two consecutive tests and the carbon monoxide concentration is above 100 ppm, it is considered an oxygen-deficient state. This is based on combustion stoichiometric ratio experimental data, at which point the theoretical air coefficient is below 1.15; when the nitrogen oxide concentration exceeds 200 mg / Nm³, it is considered an oxygen-deficient state. 3 The condition was determined to be a localized high-temperature state because experiments showed that when the furnace temperature exceeded 1100℃, thermal NO... x The generation rate increased dramatically; When the unburned hydrocarbon content is higher than 50 ppm, it is considered an incomplete combustion state; this corresponds to a critical point where the combustion efficiency decreases by about 5%; all determinations must be confirmed by two consecutive tests to avoid misjudgment due to instantaneous fluctuations.

[0042] The slagging degree analysis adopts the image feature extraction method: one industrial camera is installed on each of the four walls of the furnace, at the front, back, left, and right, with a resolution of 1280×1024 and a frame rate of 30fps. The industrial cameras take images of the furnace inner wall every 30 minutes; the slagging area is extracted by grayscale threshold segmentation, and the slagging coverage rate and slagging thickness index are calculated. When the slagging coverage rate exceeds 15% or the slagging thickness index is greater than 0.3, an early warning signal is triggered. Image processing employs a grayscale threshold segmentation method: after converting the RGB image to a grayscale image, a grayscale threshold of 120 is set, and pixels below this value are identified as slagging areas; the slagging coverage rate is calculated as: number of pixels in slagging areas / total number of pixels × 100%; the slagging thickness index is obtained through edge gradient analysis, and the calculation formula is: standard deviation of grayscale values ​​of pixels at the edge of the slagging area / 255; when the slagging coverage rate of any furnace wall exceeds 15% or the slagging thickness index is greater than 0.3, an audible and visual warning signal is triggered, with an 85dB buzzer, a red warning light, and the coordinates of the warning location are recorded.

[0043] The parameter adjustment adopts a three-level priority control strategy: Level 1 adjustment response time <10 seconds: When incomplete combustion is detected, the secondary air ratio and nozzle position are adjusted first. The ratio is adjusted by 2-3% each time, and the position is adjusted by 5% each time. If CO exceeds the standard, if the volatile matter is >75%, the secondary air ratio is increased from 42% to 45%, and the nozzle is moved up to 75% height. Secondary adjustment response time 30-60 seconds: When a local high temperature is detected, adjust the temperature setting of the slagging avoidance zone, lowering it by 20-30℃ each time, such as from 850℃ to 820℃, but it must not be lower than the fuel ignition point, usually >600℃; Level 3 adjustment response time > 2 minutes: Only when the same combustion anomaly is detected three times consecutively with an interval of 5 minutes, will the feed frequency (adjustment range of 5-10% each time) and fuel bed thickness (adjustment range of 1-2mm each time) be adjusted. The frequency will be adjusted by 5-10% each time, and the bed thickness will be adjusted by 1-2mm each time. If there is insufficient oxygen supply for three consecutive times, the feed frequency will be reduced from 15 times / minute to 13 times / minute, and the fuel bed thickness will be reduced from 40mm to 38mm. This priority design ensures that rapid disturbances are regulated by rapid response parameters first, avoiding frequent adjustments of feed parameters from affecting system stability.

[0044] Adaptive optimization employs a historical data weighted learning method: a parameter adjustment effect evaluation matrix is ​​established, recording the following data for each adjustment: combustion state before adjustment (i.e., the values ​​of four flue gas indicators), type and magnitude of adjustment parameters, changes in combustion state within 10 minutes after adjustment, and adjustment effect score, ranging from 1 to 5 points, with 5 points being the best; effective adjustment scores ≥ 4 points are assigned a weight of 0.8, and ineffective adjustment scores ≤ 2 points are assigned a weight of 0.2. When the same abnormal combustion condition occurs repeatedly, such as when NO is detected twice consecutively...x >200mg / Nm 3 Prioritize the use of historically effective adjustment schemes, such as those historically used when rice husk fuel NO x If the temperature in the slagging avoidance zone is reduced from 850℃ to 820℃ and the secondary air in the zone is increased by 5%, the solution will score 4.5 points and will be given priority. Historical data storage adopts a circular buffer design, retaining the most recent 100 adjustment records to ensure data timeliness; all adjustment schemes must undergo security verification before execution to ensure that parameters are within the allowable range of the equipment, such as the temperature not being lower than 600℃ or higher than 1200℃.

[0045] Example 2 This embodiment describes the application of rice husk fuel in a 6-ton / hour chain grate biomass boiler. The rice husk fuel has a moisture content of 12.5%, a volatile matter content of 78.3%, an ash content of 15.2%, a rated boiler load of 4.2MW, a furnace length × width × height of 2.5m × 1.8m × 6m, and a grate gap width of 8mm.

[0046] During the initial operation phase, the system recorded an abnormal combustion state: the flue gas analyzer showed a nitrogen oxide concentration of 215 mg / Nm³ in two consecutive measurements. 3 and 228mg / Nm 3 Exceeding 200 mg / Nm 3 The threshold was reached, and the temperature measurement point of the slagging avoidance zone at a height of 500mm reached 875℃, which was judged as a local high temperature state. According to the three-level priority control strategy, the second-level adjustment was initiated: the temperature setpoint of the slagging avoidance zone was lowered from 850℃ to 820℃, and the secondary air volume in this area was increased by 8%.

[0047] Within 10 minutes of adjustment, the nitrogen oxide concentration was monitored to have decreased to 185 mg / Nm³. 3 The temperature in the slagging avoidance zone dropped to 815℃, and the combustion state returned to normal. The adjustment effect score was 4.2 points. This adjustment plan was recorded in the parameter adjustment effect evaluation matrix, including the parameters before adjustment (temperature setting of 850℃, secondary air ratio of 42%), the adjustment parameters (temperature reduction of 30℃, secondary air increase of 8%), and NO. x 185mg / Nm 3 The adjusted state at 815℃ and the score of 4.2 points are assigned a weight of 0.75.

[0048] After running for 3 days, the same abnormal state was detected again, NO. x 218mg / Nm 3Temperature 872℃; historical data was checked, and an effective adjustment plan for the same operating conditions 3 days ago was found; this historical plan was prioritized: the temperature setpoint of the slagging avoidance zone was lowered from 850℃ to 820℃, and the secondary air volume in this area was increased by 8%; 8 minutes after the adjustment, NO x The concentration dropped to 178 mg / Nm 3 The temperature dropped to 810℃, the adjustment effect score was 4.5 points, and the weight of the updated scheme was 0.78.

[0049] On the 7th day of operation, due to a change in fuel batches, specifically a new batch of rice husks with a volatile matter content of 81.5%, unburned hydrocarbon content reached 58 ppm, exceeding the 50 ppm threshold. A first-level adjustment was initiated: the secondary air ratio was increased from 43% to 46%, and the nozzle position was moved from 75% to 78% height. However, the adjustment had little effect; after 10 minutes, the unburned hydrocarbon content remained at 55 ppm, resulting in a score of only 2.8. Analysis indicated that the change in volatile matter content required a more significant adjustment. A second adjustment increased the secondary air ratio to 48% and moved the nozzle position to 80% height. After this adjustment, the unburned hydrocarbon content decreased to 42 ppm, resulting in a score of 4.3. The data from both adjustments were recorded, with the first ineffective adjustment assigned a weight of 0.25 and the second effective adjustment assigned a weight of 0.76.

[0050] After 30 days of continuous operation, a total of 86 parameter adjustments were recorded, of which 68 were effective adjustments (scoring ≥4 points). Statistics show that after adopting adaptive optimization, compared with the initial operation phase, the boiler's average combustion efficiency increased from 83.5% to 87.2%, and the average nitrogen oxide emissions decreased from 235 mg / Nm³. 3 Reduced to 178 mg / Nm 3 The number of slagging warnings decreased from 5.2 times per week to 1.3 times per week; the historical data ring buffer always maintains the records of the most recent 100 adjustments, and a safety check is performed before each new adjustment plan is implemented: check whether the temperature setpoint is within the range of 600-1200℃, whether the air volume adjustment range is within ±15%, and whether the feeding frequency is within the range of 5-25 times / minute, to ensure that all parameters are within the safe operating boundaries of the equipment.

[0051] This embodiment demonstrates that the adaptive optimization module can dynamically learn the optimal control strategy based on historical adjustment effects, effectively improving combustion efficiency and reducing pollutant emissions. Moreover, all adjustment processes are implemented within the scope described in the patented technical solution without introducing any new technical features.

[0052] All formulas in this invention are dimensionless and calculated by taking their numerical values. Dimensionlessness can be achieved through various methods such as standardization, which will not be elaborated here. The formulas are derived from software simulations using a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas can be set by those skilled in the art according to the actual situation.

[0053] In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for optimizing biomass fuel supply and combustion efficiency, characterized in that, include: S1: Fuel pretreatment: Detect the physicochemical parameters of the fuel and adjust the moisture content and particle size of the fuel in a closed loop according to the test results; The closed-loop regulation includes: based on the moisture content detection results, controlling the operation of the hot air system or the atomizing humidification system to maintain the fuel moisture content within a preset range; Based on the particle size analysis results, multi-stage crushing and grading screening were performed to separate particles that did not meet the requirements of combustion kinetics and to construct the target particle size distribution. S2: Feeding parameter matching: Establish a feeding model based on fuel characteristics; determine the volatile content of the fuel, construct a multivariate coupled model in combination with the physicochemical parameters, and calculate the optimal feeding frequency; calculate and set the thickness distribution of the fuel layer according to the volatile content and the preset reference layer thickness to achieve matching between feeding parameters and fuel characteristics; S3: Combustion temperature field construction: Based on the slagging risk assessment of fuel ash characteristics, construct an anti-slagging furnace temperature field; divide the control area in the height direction of the furnace according to the ash characteristics, including the bottom pyrolysis zone, the middle slagging avoidance zone and the top burnout zone; in the slagging avoidance zone, set the temperature threshold according to the slagging risk level, and adjust the temperature of the area through multi-point temperature feedback to avoid the ash melting zone. S4: Air distribution strategy optimization: Establish a layered air distribution model based on the combustion stage; divide the primary air into bottom cooling air, middle pyrolysis air and upper burnout air, and control the temperature and flow rate of each air layer respectively; adjust the proportion coefficient of the secondary air and the nozzle position according to the volatile content to form a graded air distribution strategy that is adapted to the fuel layer thickness and volatile characteristics. S5: Combustion effect feedback: Construct a closed-loop control system based on multi-source sensing; monitor flue gas composition and furnace inner wall images, and construct combustion state evaluation indicators based on the monitoring data; according to the evaluation indicators, perform graded priority adjustment of feeding model parameters, temperature field thresholds and air distribution strategy parameters to achieve adaptive optimization of the combustion process.

2. The method for optimizing biomass fuel supply and combustion efficiency as described in claim 1, characterized in that, The process S1, which involves detecting the physicochemical parameters of the fuel and adjusting the moisture content and particle size of the fuel in a closed loop based on the detection results, further includes: The gradient heating drying process is adopted: when the fuel moisture content is detected to exceed the preset upper limit, the gradient heating mode is activated. The initial hot air temperature is set below the fuel pyrolysis start temperature, and the hot air temperature is gradually increased during the drying process, but does not exceed the tar condensation temperature. The process employs atomization humidification and mechanical mixing: when the fuel moisture content is detected to be lower than the preset lower limit, water mist is evenly sprayed onto the fuel surface through multi-stage atomizing nozzles, and a mechanical stirring device is used to promote moisture penetration. The process employs a fuel characteristic adaptive screening process: the primary crushing sets the cutter gap according to the fuel fiber characteristics; the secondary screening adjusts the screen aperture according to the ash content and simultaneously performs airflow separation to separate ultrafine particles based on the difference in particle suspension velocity.

3. The method for optimizing biomass fuel supply and combustion efficiency as described in claim 1, characterized in that, The material feeding parameter matching in S2 also includes: The determination of volatile matter content adopts the stepped heating pyrolysis method: the fuel sample is subjected to staged heating and heat preservation treatment, and the volatile matter content is calculated by the percentage of mass loss. The multivariate coupled model is constructed using a bivariate correction algorithm: moisture content is used as the basic adjustment variable, volatile matter content is used as the correction adjustment variable, and a feeding frequency calculation model is established to calculate the feeding frequency. When the volatile matter content exceeds the critical value, a correction coefficient that decreases with the increase of volatile matter is introduced; when the moisture content is below the safety lower limit, a correction coefficient that increases with the decrease of moisture content is introduced. The formula for calculating the feeding frequency of the moisture-volatile matter synergistic control model is as follows: ,in For optimal feeding frequency, The reference feeding frequency is calculated based on the boiler's rated load and the lower heating value of the fuel. To detect the moisture content of the fuel, The optimal moisture content for biomass fuel combustion is the baseline value. The measured volatile matter content of the fuel, This is the baseline value for volatile matter in biomass fuels. This is the moisture correction factor. This is the correction factor for volatile matter. The moisture-volatile matter synergistic correction coefficient; The set fuel layer thickness distribution adopts a combustion kinetics stratification strategy: the fuel layer is divided into a bottom layer, a middle layer and a surface layer; the bottom layer thickness is fixed to ensure uniform air distribution; the middle layer thickness is set according to the volatile matter content multiplied by a correction factor; the surface layer thickness is set according to the moisture content multiplied by a correction factor; the thicknesses of the three layers are superimposed to form the total fuel layer thickness. The coordinated control of feeding frequency and fuel bed thickness adopts a time-series matching mechanism: the total fuel demand is determined based on the boiler load, the amount of fuel fed at one time is determined based on the fuel bed thickness, and the feeding frequency is calculated; when the furnace pressure fluctuation exceeds the threshold, the feeding frequency is adjusted first.

4. The method for optimizing biomass fuel supply and combustion efficiency as described in claim 1, characterized in that, The construction of the combustion temperature field in S3 also includes: The ash properties were determined using a stepped heating test method: in a weakly reducing atmosphere, the deformation temperature, softening temperature, and flow temperature of the ash were measured at different heating rates. The slagging risk assessment adopts a three-temperature zone comprehensive judgment method: based on the temperature difference between softening temperature and flow temperature and the value of deformation temperature, the slagging risk is divided into three levels: high, medium and low. The control zone for dividing the furnace height adopts a combustion dynamics zoning strategy: the rapid pyrolysis zone is set at the bottom of the furnace, and the temperature is controlled in the first preset range; the slagging avoidance zone is set in the middle of the furnace, and the temperature is strictly controlled outside the slagging risk temperature range, avoiding specific temperature ranges according to the risk level; the burnout enhancement zone is set in the upper part of the furnace, and the temperature is maintained in the second preset range. The temperature of the area is adjusted by multi-point temperature feedback: redundant temperature measuring points are arranged circumferentially in the slagging avoidance zone. When the temperature difference between adjacent measuring points exceeds the set value, local air supply adjustment is initiated. When the average temperature of the area approaches the slagging risk boundary, the secondary air ratio is adjusted first.

5. The method for optimizing biomass fuel supply and combustion efficiency as described in claim 1, characterized in that, The air distribution strategy optimization in S4 also includes: The primary air is divided into three sections using a three-stage allocation strategy: bottom cooling air is used to cool the grate and form an oxide layer; pyrolysis promoting air is used to provide the heat required for pyrolysis; and burnout auxiliary air is used to enhance combustion. The air volume ratio of each section is adjusted according to the oxygen demand characteristics of the combustion stage. The adjustment of secondary air adopts a volatile matter-space coupling strategy: the proportion of secondary air and the nozzle height are adjusted according to the volatile matter content; for fuels with high volatile matter content, the proportion of secondary air is increased and the nozzle is moved upward; for fuels with low volatile matter content, the proportion of secondary air is decreased and the nozzle is moved downward. Pressure and temperature measuring points are set at different heights in the furnace. When the temperature in the slag avoidance zone approaches the critical value, the secondary air volume is increased first. When the furnace pressure fluctuation exceeds the set range, the primary air ratio and the position of the secondary air nozzle are adjusted simultaneously.

6. The method for optimizing biomass fuel supply and combustion efficiency as described in claim 1, characterized in that, The combustion effect feedback in S5 also includes: The monitoring of flue gas components employs a multi-index synergistic analysis method: simultaneously monitoring oxygen content, carbon monoxide concentration, nitrogen oxide concentration, and unburned hydrocarbon content; and determining insufficient oxygen supply, localized high temperature, or incomplete combustion based on the combination of indicators. The monitoring of the furnace inner wall image adopts the image feature extraction method: the furnace inner wall image is taken regularly, the slag area is extracted by grayscale threshold segmentation, and the slag coverage rate and slag thickness index are calculated; when the warning threshold is exceeded, a signal is triggered. The adjustment is prioritized in three levels: Level 1 adjustment is to the air volume distribution parameters; Level 2 adjustment is to the temperature control parameters; and Level 3 adjustment is to the material supply parameters. The adaptive optimization adopts a historical data weighted learning method: a parameter adjustment effect evaluation matrix is ​​established, with higher weights assigned to effective adjustments and lower weights assigned to ineffective adjustments; when the same abnormal state occurs repeatedly, historical effective solutions are called first.

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