A boiler combustion optimization method and device based on oxygen feedback and a system thereof

Abstract

The application provides a boiler combustion optimization method and device based on oxygen feedback and a system thereof, and belongs to the technical field of energy management. The boiler combustion optimization method based on oxygen feedback comprises the following steps: determining a corresponding target combustion heat power according to a received target load instruction; determining a target air supply amount and a target fuel supply amount required for maintaining complete combustion in a reference operation state according to the target combustion heat power and in combination with a preset combustion model, wherein the reference operation state corresponds to a first combustion environment parameter set; acquiring a second combustion environment parameter set in a current operation condition, the second combustion environment parameter set comprising an actual oxygen concentration, a furnace negative pressure, a flue gas temperature and a fuel low calorific value; and dynamically correcting the target air supply amount and the target fuel supply amount according to a difference between the first combustion environment parameter set and the second combustion environment parameter set in the case that the difference exists.

Description

Technical Field

[0001] This invention belongs to the field of energy management and relates to a boiler combustion optimization method, device and system based on oxygen feedback. Background Technology

[0002] Currently, boiler combustion control technology is a crucial element in ensuring the efficient and stable operation of thermal energy systems. Traditional combustion control methods typically rely on a fixed air-fuel ratio or empirically set oxygen levels. While these methods offer a degree of reliability under normal operating conditions, their ability to dynamically adjust the combustion process is limited when load fluctuates, fuel characteristics change, or environmental conditions alter, making it difficult to consistently maintain the optimal excess air coefficient. Therefore, combustion optimization strategies based on real-time oxygen feedback are gradually being introduced. By dynamically adjusting the air supply volume through online monitoring of flue gas oxygen content, combustion efficiency can be improved and pollutant emissions reduced.

[0003] However, in actual operation, due to factors such as boiler heating surface contamination, sensor response lag, or combustion disturbance, there may be a deviation between the oxygen feedback signal and the actual combustion state in the furnace, resulting in an incomplete match between air volume regulation and combustion demand, which in turn affects the accuracy and stability of combustion control. Summary of the Invention

[0004] The purpose of this invention is to address the aforementioned problems in existing technologies by proposing a boiler combustion optimization method, apparatus, and system based on oxygen feedback.

[0005] The objective of this invention can be achieved through the following technical solutions:

[0006] According to a first aspect of the embodiments of this application, a boiler combustion optimization method based on oxygen feedback is provided, applied to a combustion regulation component in a boiler combustion control system, the combustion regulation component including an air supply actuator and a fuel supply actuator, the method comprising:

[0007] Based on the received target load instruction, the corresponding target combustion heat power is determined, wherein the target load instruction is generated by the central controller based on the power grid dispatch signal or user-defined parameters;

[0008] Based on the target combustion heat power and combined with the preset combustion model, the target air volume and target fuel supply required to maintain complete combustion under the baseline operating conditions are determined, wherein the baseline operating conditions correspond to a first set of combustion environment parameters.

[0009] Obtain the second set of combustion environment parameters under the current operating conditions. The second set of combustion environment parameters includes the actual oxygen concentration, furnace negative pressure, flue gas temperature and fuel lower heating value.

[0010] When there is a difference between the first combustion environment parameter set and the second combustion environment parameter set, the target air supply volume and the target fuel supply volume are dynamically corrected according to the difference, and the corrected air supply control command and fuel control command are generated. The air supply control command is sent to the air supply actuator, and the fuel control command is sent to the fuel supply actuator, so that the actual combustion state in the furnace approaches the theoretical optimal combustion state.

[0011] In some embodiments, the combustion environment parameter set includes an oxygen concentration reference value, fuel characteristic parameters, and a heat transfer surface cleanliness index. The first combustion environment parameter set includes a preset oxygen concentration range, a standard fuel lower heating value range, and a reference heat transfer surface thermal resistance value.

[0012] When there is a difference between the first combustion environment parameter set and the second combustion environment parameter set, the target air volume and target fuel supply are dynamically corrected according to the difference, including:

[0013] The actual oxygen concentration is compared with the preset oxygen concentration range, the current fuel lower heating value is compared with the standard fuel lower heating value range, and the thermal resistance deviation of the heated surface calculated based on the exhaust temperature and the theoretical exhaust temperature is compared with the reference thermal resistance value of the heated surface to identify combustion environment parameters with deviations.

[0014] Based on the combustion environment parameters that have deviations, calculate the corresponding air volume correction factor and fuel correction factor respectively;

[0015] The air volume correction coefficient is applied to the target air supply volume to generate a corrected air supply control command; the fuel correction coefficient is applied to the target fuel supply amount to generate a corrected fuel control command.

[0016] In some embodiments, based on the combustion environment parameters that have deviations, the corresponding air volume correction factor and fuel correction factor are calculated respectively, including:

[0017] For each combustion environment parameter that has a deviation, calculate its corresponding first correction factor;

[0018] For combustion environment parameters that do not deviate, the corresponding second correction factor is assigned to 1;

[0019] The weighted product of all the first and second correction coefficients is performed to obtain the comprehensive air volume correction coefficient and the comprehensive fuel correction coefficient.

[0020] For each combustion environment parameter with deviation, the corresponding first correction coefficient is calculated, including:

[0021] If the actual oxygen concentration is lower than the lower limit of the preset oxygen concentration range, then the lower limit extreme point that is closest to the actual oxygen concentration is selected in the preset oxygen concentration range; the absolute difference between the actual oxygen concentration and the lower limit extreme point is calculated, and the ratio of the absolute difference to the width of the preset oxygen concentration range is used as the oxygen deviation factor; then the oxygen correction coefficient is determined according to the oxygen deviation factor through a preset nonlinear mapping function.

[0022] If the current lower heating value of the fuel exceeds the range of the standard lower heating value of the fuel, then select the boundary extreme point in the range of the standard lower heating value of the fuel that is closest to the current lower heating value of the fuel; calculate the relative deviation rate between the current lower heating value of the fuel and the boundary extreme point, and determine the fuel calorific value correction coefficient based on the relative deviation rate by using a lookup table method.

[0023] If the dust level of the heated surface calculated based on the flue gas temperature exceeds a preset threshold, the contamination correction coefficient of the heated surface is determined by the heat transfer efficiency inversion model based on the thermal resistance difference between the dust level of the heated surface and the baseline cleanliness.

[0024] In some embodiments, the method further includes:

[0025] Based on the revised air supply control command and fuel control command, predict the furnace combustion stability index within the future preset time window;

[0026] When the combustion stability index is lower than the preset stability threshold, the combustion disturbance compensation mechanism is activated;

[0027] The combustion disturbance compensation mechanism includes: identifying the current disturbance mode based on historical combustion oscillation data, retrieving matching feedforward compensation parameters from the disturbance suppression strategy library, and superimposing them on the air supply control command and fuel control command.

[0028] In some embodiments, activating the combustion disturbance compensation mechanism includes:

[0029] Real-time monitoring of furnace pressure fluctuation spectrum;

[0030] The furnace pressure fluctuation spectrum is pattern matched with a pre-stored typical disturbance feature template.

[0031] If the match is successful, the phase delay compensation and amplitude gain coefficient corresponding to the disturbance template are extracted.

[0032] The phase delay compensation is used to adjust the timing of the air supply actuator in advance, and the amplitude gain coefficient is used to amplify the response intensity of the fuel supply actuator.

[0033] In some embodiments, the method further includes:

[0034] When acquiring the second set of combustion environment parameters under the current operating conditions, if the output signal of the oxygen sensor is abnormal or data is missing, the redundant oxygen estimation module is activated.

[0035] The redundant oxygen estimation module reconstructs the oxygen concentration estimate based on the carbon monoxide concentration sensor, flue gas temperature gradient, and fuel flow signal through a multivariate soft measurement model, and incorporates the oxygen concentration estimate as a substitute parameter into the second combustion environment parameter set.

[0036] In some embodiments, if enabling the redundant oxygen estimation module fails, the historical operating database is invoked, and based on the current load level, fuel type, and ambient temperature, historical oxygen concentration records under similar operating conditions are retrieved from the historical operating database, and the weighted average of the historical oxygen concentration records is used as a temporary oxygen concentration parameter.

[0037] According to a second aspect of the embodiments of this application, a boiler combustion optimization device based on oxygen feedback is provided, applied to a combustion regulation component in a boiler combustion control system. The combustion regulation component includes an air supply actuator and a fuel supply actuator. The device includes:

[0038] The instruction parsing module is used to determine the corresponding target combustion heat power based on the received target load instruction, wherein the target load instruction is generated by the central controller based on the power grid dispatch signal or user-defined parameters;

[0039] The baseline parameter calculation module is used to determine the target air volume and target fuel supply required to maintain complete combustion under the baseline operating state based on the target combustion heat power and a preset combustion model. The baseline operating state corresponds to a first set of combustion environment parameters.

[0040] The environmental parameter acquisition module is used to acquire a second set of combustion environment parameters under the current operating conditions. The second set of combustion environment parameters includes the actual oxygen concentration, furnace negative pressure, flue gas temperature and fuel lower heating value.

[0041] The dynamic correction module is used to dynamically correct the target air supply volume and target fuel supply volume according to the difference between the first combustion environment parameter set and the second combustion environment parameter set, generate the corrected air supply control command and fuel control command, and send the air supply control command to the air supply actuator and the fuel control command to the fuel supply actuator, so as to make the actual combustion state in the furnace approach the theoretical optimal combustion state.

[0042] According to a third aspect of the embodiments of this application, a boiler combustion optimization system is provided, including a central controller and a combustion regulating device. The combustion regulating device includes an air supply actuator, a fuel supply actuator, and a distributed sensor network. The distributed sensor network includes an oxygen sensor, a furnace pressure transmitter, a flue gas temperature thermocouple, and a fuel composition analyzer. The distributed sensor network is communicatively connected to the central controller. The central controller is configured to execute the method described in the first aspect, for generating a target load command based on a power grid dispatch signal or user-defined parameters, and calculating and issuing air supply control commands and fuel control commands to the air supply actuator and the fuel supply actuator based on real-time data fed back from the distributed sensor network.

[0043] According to a fourth aspect of the embodiments of this application, a computer storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the boiler combustion optimization method based on oxygen feedback as described in the first aspect.

[0044] Compared with existing technologies, this invention has the following advantages: By constructing a multi-dimensional combustion environment parameter set including oxygen concentration, fuel characteristics, and heating surface condition, and establishing a dynamic mapping relationship between the benchmark parameter set and the real-time parameter set, this invention achieves coordinated correction of air supply and fuel supply. This method not only overcomes the problem of inaccurate regulation caused by sensor lag or heating surface contamination in single oxygen feedback, but also significantly improves the robustness and adaptability of the combustion control system under complex conditions such as variable load, variable coal quality, and equipment aging by introducing disturbance feedforward compensation and data redundancy mechanisms. Simultaneously, by calculating independent sub-coefficients for various deviation parameters and synthesizing a comprehensive correction coefficient, the tuning difficulties caused by parameter coupling in traditional PID control are avoided. This effectively maintains the combustion process within a high-efficiency, low-emission range close to the theoretically optimal excess air coefficient, thereby effectively improving thermal efficiency and reducing the concentration of nitrogen oxides and carbon monoxide while ensuring the safe and stable operation of the boiler. Attached Figure Description

[0045] Figure 1 The flowchart below illustrates the steps of the boiler combustion optimization method based on oxygen feedback in this application.

[0046] Figure 2 This is a functional module structure diagram of the boiler combustion optimization device according to this application. Detailed Implementation

[0047] 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 a part of the embodiments of the present invention, and not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0048] To enable those skilled in the art to better understand the technical solutions in the embodiments of this application, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art should fall within the protection scope of the embodiments of this application.

[0049] The specific implementation of the embodiments of this application will be further described below with reference to the accompanying drawings.

[0050] like Figure 1 As shown, this invention provides a boiler combustion optimization method based on oxygen feedback. This method is applied to a combustion regulation component in a boiler combustion control system. The combustion regulation component includes an air supply actuator and a fuel supply actuator. The air supply actuator is configured to adjust the frequency converter of the blower or the opening of the damper, and the fuel supply actuator is configured to control the speed of the coal feeder or the opening of the gas regulating valve. Specifically, as... Figure 1 As shown, the method may include:

[0051] S101, determine the corresponding target combustion heat power according to the received target load instruction, wherein the target load instruction is generated by the central controller according to the power grid dispatch signal or user-set parameters.

[0052] In this invention, the boiler combustion control system includes a central controller and multiple combustion adjustment components. The central controller is connected to the local controllers in each combustion adjustment component via an industrial communication bus. In steady-state operation mode, the central controller generates a target load command based on the grid dispatch signal or operator-set parameters and sends the command to the local controller. After receiving the target load command, the local controller parses the corresponding target combustion heat power based on the built-in heat power-load mapping table.

[0053] In one example, the steady-state operation mode of the present invention refers to the condition where the boiler load change rate is less than 5% of the rated load / minute.

[0054] In one example, the central controller has a pre-stored heat power-load mapping table, which can be obtained through boiler thermal performance test calibration or theoretically calculated based on boiler design parameters.

[0055] S102, based on the target combustion heat power and combined with the preset combustion model, determine the target air volume and target fuel supply required to maintain complete combustion under the reference operating state, wherein the reference operating state corresponds to a first combustion environment parameter set.

[0056] In this invention, after determining the target combustion heat power, the local controller calls a preset combustion model to calculate the required air-fuel ratio under the baseline operating conditions. The preset combustion model is constructed based on the principle of stoichiometry and takes into account the boiler structural characteristics and typical fuel composition. The calculation results are the target air supply volume (unit: Nm³ / h) and the target fuel supply volume (unit: kg / h or Nm³ / h).

[0057] In one example, the baseline operating state corresponds to a first set of combustion environment parameters, which includes a preset oxygen concentration range, a standard fuel lower heating value range, and a baseline heating surface thermal resistance value. The baseline operating state can be understood as the state in which the boiler operates under clean heating surfaces, standard coal quality, and ideal combustion conditions, at which point the excess air coefficient is in the theoretically optimal range.

[0058] S103, obtain the second set of combustion environment parameters under the current operating conditions. The second set of combustion environment parameters includes the actual oxygen concentration, furnace negative pressure, flue gas temperature and fuel lower heating value.

[0059] In this invention, the distributed sensor network includes an oxygen sensor, a furnace pressure transmitter, a flue gas temperature thermocouple, and a fuel composition analyzer. Each sensor is connected to the local controller via an industrial bus. After determining the target air supply and target fuel supply, the local controller synchronously reads the output signals of the above sensors to form a second set of combustion environment parameters. This set of parameters includes the actual oxygen concentration (vol%), furnace negative pressure (Pa), flue gas temperature (°C), and fuel lower heating value (kJ / kg).

[0060] S104, when there is a difference between the first combustion environment parameter set and the second combustion environment parameter set, the target air supply volume and the target fuel supply volume are dynamically corrected according to the difference, and the corrected air supply control command and fuel control command are generated. The air supply control command is sent to the air supply actuator, and the fuel control command is sent to the fuel supply actuator, so that the actual combustion state in the furnace approaches the theoretical optimal combustion state.

[0061] In this invention, the local controller compares each parameter in the second combustion environment parameter set with the corresponding reference value in the first combustion environment parameter set. If any parameter exceeds its preset tolerance range, a difference is determined. Subsequently, based on the type and magnitude of the difference, the air volume correction coefficient and the fuel correction coefficient are calculated and applied to the target air volume and the target fuel supply, respectively, to generate the final control command.

[0062] The boiler combustion optimization method provided by this invention involves a combustion regulation component that, upon receiving a target load command, determines the target combustion thermal power based on the command, and then determines the target air supply and target fuel supply required under a baseline operating environment based on the target combustion thermal power. Furthermore, it acquires a second set of combustion environment parameters under the current operating conditions. In the event of a difference between the first and second sets of combustion environment parameters, the target air supply and target fuel supply are dynamically corrected based on the difference, thereby bringing the actual combustion state in the furnace closer to the theoretical optimal combustion state. This overcomes the problem of inaccurate single oxygen feedback caused by heating surface contamination, fuel fluctuations, or sensor lag, and improves the accuracy and robustness of combustion control.

[0063] Furthermore, the preferred combustion environment parameters of the present invention include oxygen concentration, lower heating value of fuel and thermal resistance of heated surface. The combustion environment parameter set includes a first combustion environment parameter set and a second combustion environment parameter set. The first combustion environment parameter set includes a preset oxygen concentration range, a standard lower heating value range of fuel and a reference thermal resistance value of heated surface.

[0064] When there are differences between the first set of combustion environment parameters and the second set of combustion environment parameters, dynamically adjusting the target air supply and target fuel supply based on the differences may include the following steps:

[0065] The actual oxygen concentration is compared with the preset oxygen concentration range, the current lower heating value of the fuel is compared with the standard lower heating value range of the fuel, and the thermal resistance deviation of the heated surface calculated based on the exhaust temperature and the theoretical exhaust temperature is compared with the reference thermal resistance value of the heated surface to identify combustion environment parameters with deviations.

[0066] In this invention, the local controller performs three independent comparison operations: First, it determines whether the actual oxygen concentration is within a preset oxygen concentration range (e.g., 3.0%-4.5%); second, it determines whether the current lower heating value of the fuel is within the standard lower heating value range (e.g., 20000-25000 kJ / kg); finally, based on the difference between the measured flue gas temperature and the theoretical flue gas temperature (calculated from the load and fuel quantity), it estimates the additional thermal resistance caused by ash on the heated surface and determines whether this additional thermal resistance exceeds the reference heated surface thermal resistance value (e.g., 0.002 m). 2 The preset threshold for K / W.

[0067] In one example, the preset oxygen concentration range is 3.0%-4.5%, the standard fuel lower heating value range is 20000-25000 kJ / kg, and the reference heating surface thermal resistance is 0.002 m. 2 • K / W; The above values ​​can be adjusted according to the boiler model and operating experience.

[0068] Based on the combustion environment parameters with deviations, calculate the corresponding air volume correction factor and fuel correction factor respectively.

[0069] In this invention, after the comparison is completed, the local controller independently calculates the impact factor on air volume and fuel for each parameter with deviation; if only the oxygen concentration is low, the air volume is mainly corrected; if the fuel calorific value decreases, the fuel supply and air volume need to be corrected simultaneously; if the heated surface is severely contaminated, the air supply needs to be increased to compensate for the loss of heat transfer efficiency.

[0070] The air volume correction coefficient is applied to the target air supply volume to generate a corrected air supply control command; the fuel correction coefficient is applied to the target fuel supply amount to generate a corrected fuel control command.

[0071] In this invention, the modified air supply control command is sent to the drive unit of the air supply actuator via the Modbus TCP protocol, and the modified fuel control command is sent to the control unit of the fuel supply actuator via a 4-20mA analog signal or the Profibus DP protocol, thereby realizing closed-loop regulation of the combustion process.

[0072] This invention compares a first set of combustion environment parameters with a second set of combustion environment parameters to accurately identify key sources of deviation affecting combustion efficiency and calculates correction coefficients independently accordingly. This avoids the tuning difficulties caused by multi-variable coupling in traditional control strategies, thereby achieving coordinated and precise control of air supply and fuel.

[0073] Furthermore, based on the combustion environment parameters with deviations, the corresponding airflow correction factor and fuel correction factor are calculated, including:

[0074] For each combustion environment parameter that has a deviation, calculate its corresponding first correction factor.

[0075] If the actual oxygen concentration is lower than the lower limit of the preset oxygen concentration range, then the lower limit extreme point that is closest to the actual oxygen concentration is selected in the preset oxygen concentration range; the absolute difference between the actual oxygen concentration and the lower limit extreme point is calculated, and the ratio of the absolute difference to the width of the preset oxygen concentration range is used as the oxygen deviation factor; then the oxygen correction coefficient is determined according to the oxygen deviation factor through a preset nonlinear mapping function.

[0076] If the current lower heating value of the fuel exceeds the range of the standard lower heating value of the fuel, then select the boundary extreme point in the range of the standard lower heating value of the fuel that is closest to the current lower heating value of the fuel; calculate the relative deviation rate between the current lower heating value of the fuel and the boundary extreme point, and determine the fuel calorific value correction coefficient based on the relative deviation rate by using a lookup table method.

[0077] If the dust level of the heated surface calculated based on the flue gas temperature exceeds a preset threshold, the contamination correction coefficient of the heated surface is determined by the heat transfer efficiency inversion model based on the thermal resistance difference between the dust level of the heated surface and the baseline cleanliness.

[0078] In this invention, if the actual oxygen concentration is lower than the lower limit of a preset oxygen concentration range (e.g., 3.0%), then the lower limit extreme point (3.0%) is selected as a reference within the preset oxygen concentration range; the absolute difference between the actual oxygen concentration and this lower limit extreme point is calculated. The ratio of this difference to the preset oxygen concentration range width (1.5%) is defined as the oxygen deviation factor. Subsequently, a pre-defined nonlinear mapping function (such as a piecewise linear function or a lookup table method) is used to... Convert to oxygen content correction factor .

[0079] If the current lower heating value of the fuel exceeds the standard lower heating value range (e.g., below 20,000 kJ / kg), then select the closest boundary extreme point (20,000 kJ / kg) within the standard range; calculate the relative deviation rate. The fuel calorific value correction factor is determined by a pre-stored lookup table method. .

[0080] If the dust level on the heated surface calculated based on the exhaust gas temperature exceeds a preset threshold, then the actual measured exhaust gas temperature will be used as the basis for determining the dust level. With theoretical flue gas temperature The difference Using the heat transfer efficiency inversion model Calculate the thermal efficiency loss and determine the contamination correction factor for the heated surface accordingly. V

[0081] In one implementation, the oxygen content nonlinear correction coefficient The calculation formula is as follows:

[0082]

[0083] Oxygen content correction factor; : Nonlinear correction function for oxygen content; Actual oxygen concentration; Oxygen content reference value.

[0084] In one implementation, the fuel calorific value correction factor The calculation formula is as follows:

[0085]

[0086] : Fuel calorific value correction coefficient; LookupTable(·): Lookup table function, which directly outputs the corresponding fuel calorific value correction coefficient based on the input ratio through a pre-established mapping relationship; Lower heating value of fuel; : Reference operating parameters.

[0087] In one implementation, the contamination correction coefficient of the heated surface The calculation formula is as follows:

[0088]

[0089] in: : Contamination correction coefficient for heated surface; g(·): Over-temperature triggering correction function, used to output the corresponding correction coefficient based on the difference between fluid temperature and theoretical temperature; : Actual temperature of the working fluid on the heated surface; Theoretical temperature of the working fluid on the heated surface.

[0090] The above calculation process can be summarized as the parameter mapping relationship shown in the table below:

[0091]

[0092] Triggering condition: When the thermal resistance of the heated surface... ≤0.002m 2 • At K / W, over-temperature correction is not triggered; when >0.002m 2 At K / W, over-temperature correction is triggered. Calculated using the function described above.

[0093] The weighted product of all the first and second correction coefficients is performed to obtain the comprehensive air volume correction coefficient and the comprehensive fuel correction coefficient.

[0094] In this invention, for combustion environment parameters that do not deviate, the corresponding second correction factor is assigned to be 1; the comprehensive air volume correction factor... It is the product of all relevant modifier coefficients, i.e. Comprehensive fuel correction factor Mainly composed of Decision, and introduction if necessary The weakly coupled terms.

[0095] In one example, if only the oxygen concentration is low while the fuel calorific value and the condition of the heating surface are normal, then , .

[0096] In one example, if the fuel has a low calorific value and the heating surface is contaminated, then , .

[0097] This invention achieves decoupling of multiple disturbance sources by independently calculating the correction coefficients of each deviation parameter and synthesizing the comprehensive correction coefficient, thus significantly improving the adaptive capability of the control system.

[0098] Furthermore, the method of the present invention may further include the following steps:

[0099] Based on the revised air supply control command and fuel control command, the furnace combustion stability index is predicted within a future preset time window.

[0100] In this invention, the local controller has a built-in combustion stability prediction model. This model calculates the combustion stability index (CSI) for the next 10-30 seconds based on the dynamic response characteristics of air supply and fuel, furnace volume and historical oscillation data. The lower the CSI value, the more unstable the combustion.

[0101] When the combustion stability index is lower than the preset stability threshold, the combustion disturbance compensation mechanism is activated.

[0102] In this invention, the preset stability threshold can be set to 0.7 (dimensionless); when CSI < 0.7, the local controller activates the feedforward compensation module in the disturbance suppression strategy library.

[0103] The combustion disturbance compensation mechanism includes: identifying the current disturbance mode based on historical combustion oscillation data, retrieving matching feedforward compensation parameters from the disturbance suppression strategy library, and superimposing them on the air supply control command and fuel control command.

[0104] Activate the combustion disturbance compensation mechanism, including:

[0105] Real-time monitoring of furnace pressure fluctuation spectrum;

[0106] The furnace pressure fluctuation spectrum is pattern matched with a pre-stored typical disturbance feature template.

[0107] If the match is successful, the phase delay compensation and amplitude gain coefficient corresponding to the disturbance template are extracted.

[0108] The phase delay compensation is used to adjust the timing of the air supply actuator in advance, and the amplitude gain coefficient is used to amplify the response intensity of the fuel supply actuator.

[0109] The local controller monitors the furnace pressure fluctuation spectrum in real time and performs pattern matching with pre-stored typical disturbance feature templates. If the matching is successful, the phase delay compensation amount and amplitude gain coefficient are extracted and used to adjust the action sequence of the air supply actuator and amplify the response intensity of the fuel supply actuator, respectively.

[0110] In this invention, typical disturbance feature templates include coal feeding fluctuation type, air supply sudden change type, coking and shedding type, etc. Each template is associated with specific spectral features (such as main frequency 2-5Hz) and corresponding compensation parameters; the phase delay compensation amount is used to trigger air supply adjustment 0.5-2 seconds in advance, and the amplitude gain coefficient is used to amplify the fuel adjustment amplitude by 1.1-1.3 times.

[0111] Furthermore, the method of the present invention further includes the following steps:

[0112] When acquiring the second set of combustion environment parameters under the current operating conditions, if the output signal of the oxygen sensor is abnormal or data is missing, the redundant oxygen estimation module is activated.

[0113] The redundant oxygen estimation module reconstructs the oxygen concentration estimate based on the carbon monoxide concentration sensor, flue gas temperature gradient, and fuel flow signal through a multivariate soft measurement model, and incorporates the oxygen concentration estimate as a substitute parameter into the second combustion environment parameter set.

[0114] In this invention, the redundant oxygen estimation module is configured to receive carbon monoxide concentration sensor, flue gas temperature gradient (calculated by multi-point thermocouples) and fuel flow signal; the module reconstructs the oxygen concentration estimate through a multivariate soft measurement model (such as a model based on neural network or partial least squares regression) and incorporates it as a substitute parameter into the second combustion environment parameter set.

[0115] If enabling the redundant oxygen estimation module fails, the historical operating database is invoked. Based on the current load level, fuel type, and ambient temperature, the historical oxygen concentration records under similar operating conditions are retrieved from the historical operating database, and the weighted average of the historical oxygen concentration records is used as a temporary oxygen concentration parameter.

[0116] In this invention, the determination of similar working conditions adopts Euclidean distance metric, and the weight allocation prioritizes load matching degree; if there are multiple matching records, the data within the most recent 7 days is selected first.

[0117] In the event of sensor failure or signal anomaly, this invention ensures the continuity and safety of combustion control logic through redundant estimation and historical data backtracking mechanisms.

[0118] Furthermore, such as Figure 2As shown, this invention provides a boiler combustion optimization device based on oxygen feedback, applied to the combustion regulation component in a boiler combustion control system. The device includes:

[0119] The instruction parsing module 301 is used to determine the corresponding target combustion heat power based on the received target load instruction;

[0120] The baseline parameter calculation module 302 is used to determine the target air volume and target fuel supply required to maintain complete combustion under baseline operating conditions based on the target combustion heat power and a preset combustion model.

[0121] The environmental parameter acquisition module 303 is used to acquire the second combustion environment parameter set under the current operating conditions;

[0122] The dynamic correction module 304 is used to dynamically correct the target air supply volume and the target fuel supply volume according to the difference between the first combustion environment parameter set and the second combustion environment parameter set, and generate the corrected air supply control command and fuel control command.

[0123] The combustion optimization device in this embodiment is used to implement the aforementioned method embodiment and has corresponding beneficial effects, which will not be repeated here. The functional implementation of each module can be referred to the corresponding parts described in the aforementioned method embodiment.

[0124] Furthermore, the present invention provides a boiler combustion optimization system, including a central controller and a combustion regulation device. The combustion regulation device includes an air supply actuator, a fuel supply actuator, and a distributed sensor network. The distributed sensor network includes an oxygen sensor, a furnace pressure transmitter, a flue gas temperature thermocouple, and a fuel composition analyzer. The distributed sensor network is communicatively connected to the central controller. The central controller is configured to execute the method described above, for generating target load commands based on grid dispatch signals or user-defined parameters, and calculating and issuing air supply control commands and fuel control commands to the air supply actuator and the fuel supply actuator based on real-time data fed back from the distributed sensor network.

[0125] It should be noted that, depending on the implementation needs, the various steps described in this invention can be broken down into more sub-steps, or multiple steps can be combined into new steps to achieve the purpose of this invention.

[0126] The above method can be implemented in a dedicated controller, PLC, or embedded system, or it can be implemented as program code stored on a computer-readable medium, which, when executed by a processor, implements the method described in this invention.

[0127] Those skilled in the art will recognize that the functions of the present invention can be implemented by hardware, firmware or software, and the specific implementation method depends on the application scenario and design constraints, but none of them depart from the protection scope of the present invention.

[0128] The above embodiments are for illustrative purposes only and are not intended to limit the scope of the invention. Various modifications and variations can be made by those skilled in the art without departing from the spirit and scope of the invention. All equivalent technical solutions fall within the protection scope of the invention, and the scope of patent protection should be defined by the claims.

[0129] To enable those skilled in the art to fully understand and implement this invention, the specific implementation principles of this invention are further supplemented below with a specific application scenario.

[0130] It should be noted that all directional indications in the embodiments of the present invention, such as up, down, left, right, front, back, etc., are only used to explain the relative positional relationship and movement of the components in a specific posture, as shown in the attached figure. If the specific posture changes, the directional indication will also change accordingly.

[0131] Furthermore, the use of terms such as "first" and "second" in this invention is for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined with "first" or "second" may explicitly or implicitly include at least one of those features. Meanwhile, the word "and / or" throughout the text means including three solutions; for example, "A and / or B" includes solution A, solution B, or a solution that simultaneously satisfies A and B. Additionally, the technical solutions of the various embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. When the combination of technical solutions is contradictory or impossible to implement, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed by this invention.

[0132] All of the above components are general standard parts or components known to those skilled in the art. Their structure and principles can be learned by those skilled in the art through technical manuals or conventional experimental methods.

[0133] For example, the computer program may be divided into one or more modules / units, which are stored in the memory and executed by the processor to complete the present invention. The one or more modules / units may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program in the electronic device.

[0134] The electronic device may be a desktop computer, laptop, handheld computer, or smart tablet, etc. The electronic device may include, but is not limited to, a processor and memory. Those skilled in the art will understand that the above components are merely examples of electronic devices and do not constitute a limitation on the electronic device. It may include more or fewer components than described above, or combine certain components, or different components. For example, the electronic device may also include input / output devices, network access devices, buses, etc.

[0135] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor. The processor is the control center of the electronic device, connecting various parts of the electronic device through various interfaces and lines.

[0136] The memory can be used to store the computer programs and / or modules. The processor implements various functions of the electronic device by running or executing the computer programs and / or modules stored in the memory and by calling data stored in the memory. The memory may mainly include a program storage area and a data storage area. The program storage area may store the operating system, at least one application program required for a function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created according to the use of the mobile phone (such as audio data, phonebook, etc.). In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as hard disk, memory, plug-in hard disk, smart media card (SMC), secure digital card (SD card), flash card, at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0137] If the modules / units integrated in the electronic device are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content included in the computer-readable medium can be appropriately added or removed according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electrical carrier signals and telecommunication signals.

[0138] It should be noted that the device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Furthermore, in the accompanying drawings of the device embodiments provided by this invention, the connection relationships between modules indicate that they have communication connections, which can be specifically implemented as one or more communication buses or signal lines. Those skilled in the art can understand and implement this without any creative effort.

[0139] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. In particular, it should be noted that any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention for those skilled in the art.

Claims

1. A boiler combustion optimization method based on oxygen feedback, applied to a combustion regulation component in a boiler combustion control system, the combustion regulation component comprising an air supply actuator and a fuel supply actuator, characterized in that, The method includes: Based on the received target load command, determine the corresponding target combustion heat power; Based on the target combustion heat power and combined with the preset combustion model, the target air volume and target fuel supply required to maintain complete combustion under the baseline operating conditions are determined, wherein the baseline operating conditions correspond to a first set of combustion environment parameters. Obtain the second set of combustion environment parameters under the current operating conditions. The second set of combustion environment parameters includes the actual oxygen concentration, furnace negative pressure, flue gas temperature and fuel lower heating value. When there is a difference between the first combustion environment parameter set and the second combustion environment parameter set, the target air supply volume and the target fuel supply volume are dynamically corrected according to the difference, and the corrected air supply control command and fuel control command are generated. The air supply control command is sent to the air supply actuator, and the fuel control command is sent to the fuel supply actuator, so that the actual combustion state in the furnace approaches the theoretical optimal combustion state.

2. The boiler combustion optimization method based on oxygen feedback according to claim 1, characterized in that, The combustion environment parameter set includes oxygen concentration reference value, fuel characteristic parameters and heat transfer surface cleanliness index. The first combustion environment parameter set includes preset oxygen concentration range, standard fuel low heating value range and reference heat transfer surface thermal resistance value. When there is a difference between the first combustion environment parameter set and the second combustion environment parameter set, the target air volume and target fuel supply are dynamically adjusted according to the difference, including: The actual oxygen concentration is compared with the preset oxygen concentration range, the current fuel lower heating value is compared with the standard fuel lower heating value range, and the thermal resistance deviation of the heated surface calculated based on the exhaust temperature and the theoretical exhaust temperature is compared with the reference thermal resistance value of the heated surface to identify combustion environment parameters with deviations. Based on the combustion environment parameters that have deviations, calculate the corresponding air volume correction factor and fuel correction factor respectively; The air volume correction coefficient is applied to the target air supply volume to generate a corrected air supply control command; the fuel correction coefficient is applied to the target fuel supply amount to generate a corrected fuel control command.

3. The boiler combustion optimization method based on oxygen feedback according to claim 2, characterized in that, Based on the combustion environment parameters with deviations, calculate the corresponding airflow correction factor and fuel correction factor, including: For each combustion environment parameter that has a deviation, calculate its corresponding first correction factor; For combustion environment parameters that do not deviate, the corresponding second correction factor is assigned to 1; The weighted product of all the first and second correction coefficients is performed to obtain the comprehensive air volume correction coefficient and the comprehensive fuel correction coefficient. Specifically, for each combustion environment parameter exhibiting deviation, its corresponding first correction factor is calculated, including: If the actual oxygen concentration is lower than the lower limit of the preset oxygen concentration range, then the lower limit extreme point that is closest to the actual oxygen concentration is selected in the preset oxygen concentration range; the absolute difference between the actual oxygen concentration and the lower limit extreme point is calculated, and the ratio of the absolute difference to the width of the preset oxygen concentration range is used as the oxygen deviation factor; then the oxygen correction coefficient is determined according to the oxygen deviation factor through a preset nonlinear mapping function. If the current lower heating value of the fuel exceeds the range of the standard lower heating value of the fuel, then select the boundary extreme point in the range of the standard lower heating value of the fuel that is closest to the current lower heating value of the fuel; calculate the relative deviation rate between the current lower heating value of the fuel and the boundary extreme point, and determine the fuel calorific value correction coefficient based on the relative deviation rate by using a lookup table method. If the dust level of the heated surface calculated based on the flue gas temperature exceeds a preset threshold, the contamination correction coefficient of the heated surface is determined by the heat transfer efficiency inversion model based on the thermal resistance difference between the dust level of the heated surface and the baseline cleanliness.

4. The boiler combustion optimization method based on oxygen feedback according to claim 1, characterized in that, The method further includes: Based on the revised air supply control command and fuel control command, predict the furnace combustion stability index within the future preset time window; When the combustion stability index is lower than the preset stability threshold, the combustion disturbance compensation mechanism is activated; The combustion disturbance compensation mechanism includes: identifying the current disturbance mode based on historical combustion oscillation data, retrieving matching feedforward compensation parameters from the disturbance suppression strategy library, and superimposing them on the air supply control command and fuel control command.

5. The boiler combustion optimization method based on oxygen feedback according to claim 4, characterized in that, The activation of the combustion disturbance compensation mechanism includes: Real-time monitoring of furnace pressure fluctuation spectrum; The furnace pressure fluctuation spectrum is pattern matched with a pre-stored typical disturbance feature template. If the match is successful, the phase delay compensation and amplitude gain coefficient corresponding to the disturbance template are extracted. The phase delay compensation is used to adjust the timing of the air supply actuator in advance, and the amplitude gain coefficient is used to amplify the response intensity of the fuel supply actuator.

6. The boiler combustion optimization method based on oxygen feedback according to claim 1, characterized in that, The method further includes: When acquiring the second set of combustion environment parameters under the current operating conditions, if the output signal of the oxygen sensor is abnormal or data is missing, the redundant oxygen estimation module is activated. The redundant oxygen estimation module reconstructs the oxygen concentration estimate based on the carbon monoxide concentration sensor, flue gas temperature gradient, and fuel flow signal through a multivariate soft measurement model, and incorporates the oxygen concentration estimate as a substitute parameter into the second combustion environment parameter set.

7. The boiler combustion optimization method based on oxygen feedback according to claim 1, characterized in that, If enabling the redundant oxygen estimation module fails, the historical operating database is invoked. Based on the current load level, fuel type, and ambient temperature, the historical oxygen concentration records under similar operating conditions are retrieved from the historical operating database, and the weighted average of the historical oxygen concentration records is used as a temporary oxygen concentration parameter.

8. A boiler combustion optimization device based on oxygen feedback, applied to a combustion regulation component in a boiler combustion control system, the combustion regulation component comprising an air supply actuator and a fuel supply actuator, characterized in that, The device includes: The instruction parsing module is used to determine the corresponding target combustion heat power based on the received target load instruction, wherein the target load instruction is generated by the central controller based on the power grid dispatch signal or user-defined parameters; The baseline parameter calculation module is used to determine the target air volume and target fuel supply required to maintain complete combustion under the baseline operating state based on the target combustion heat power and a preset combustion model. The baseline operating state corresponds to a first set of combustion environment parameters. The environmental parameter acquisition module is used to acquire a second set of combustion environment parameters under the current operating conditions. The second set of combustion environment parameters includes the actual oxygen concentration, furnace negative pressure, flue gas temperature and fuel lower heating value. The dynamic correction module is used to dynamically correct the target air supply volume and target fuel supply volume according to the difference between the first combustion environment parameter set and the second combustion environment parameter set, generate the corrected air supply control command and fuel control command, and send the air supply control command to the air supply actuator and the fuel control command to the fuel supply actuator, so as to make the actual combustion state in the furnace approach the theoretical optimal combustion state.

9. A boiler combustion optimization system, comprising a central controller and a combustion regulating device, wherein the combustion regulating device includes an air supply actuator, a fuel supply actuator, and a distributed sensor network, wherein the distributed sensor network includes an oxygen sensor, a furnace pressure transmitter, a flue gas temperature thermocouple, and a fuel composition analyzer, and the distributed sensor network is communicatively connected to the central controller; the central controller is configured to execute the method described in any one of claims 1-7, for generating a target load command based on a power grid dispatch signal or user-defined parameters, and calculating and issuing air supply control commands and fuel control commands to the air supply actuator and the fuel supply actuator based on real-time data fed back from the distributed sensor network.

Images