Energy efficiency control optimization method for wet flue gas desulfurization systems

Abstract

The present application relates to the technical field of wet desulfurization, and particularly relates to an energy efficiency control optimization method for a wet desulfurization system. The method comprises the following steps: obtaining operation data of wet desulfurization, calculating the adiabatic saturation temperature of flue gas under the current working condition by using a wet air enthalpy-humidity diagram model; defining the difference between the outlet flue gas temperature and the adiabatic saturation temperature as a temperature difference approaching degree; monitoring the sulfur dioxide concentration at the outlet of the absorption tower, and generating a strengthening demand signal when the sulfur dioxide concentration exceeds an alarm value; executing a differentiated control strategy according to the temperature difference approaching degree: if the temperature difference approaching degree is greater than a preset threshold, generating an instruction to increase the number of operating slurry circulating pumps; if the temperature difference approaching degree is less than or equal to the preset threshold, generating an instruction to reduce the number of operating slurry circulating pumps and simultaneously increase the slurry pH set value. The present application intelligently selects energy-saving means by identifying the saturation state of flue gas, thereby significantly reducing the energy consumption of the system while ensuring the desulfurization efficiency.

Description

Energy efficiency control optimization method for wet desulfurization systems Technical Field

[0001] This invention relates to the field of wet desulfurization technology. More specifically, this invention relates to an energy efficiency control optimization method for wet desulfurization systems. Background Technology

[0002] Wet flue gas desulfurization (FGD) is a core environmental protection technology for controlling sulfur dioxide emissions in coal-fired power plants and heavy chemical industries. Its operational stability and economic efficiency directly affect the environmental compliance and production costs of enterprises. However, wet FGD systems are typically complex processes with large time lags, nonlinearity, and multivariate coupling, and are inherently characterized by large load fluctuations and complex reaction mechanisms.

[0003] To ensure emission compliance, the industry has adopted various methods, ranging from traditional PID control to model predictive control, but all have significant limitations. Traditional methods typically rely on simple feedback regulation between the outlet sulfur dioxide concentration and the number of operating slurry circulation pumps. This reactive control mode often maintains excessive slurry circulation for extended periods to cope with fluctuations in peak values, leading to an imbalance where the pump is over-powered and resulting in significant energy waste. Furthermore, existing technologies generally neglect the influence of flue gas thermodynamics on desulfurization efficiency, i.e., they do not consider whether the flue gas has reached adiabatic saturation. When the flue gas is close to saturation, simply increasing the slurry circulation rate exhibits a highly diminishing marginal return on desulfurization efficiency. At this point, further increasing the number of operating pumps not only fails to effectively reduce emissions but also unnecessarily increases energy consumption.

[0004] In summary, existing wet desulfurization control technologies still face severe challenges in practical applications, including low energy efficiency and poor adaptability to operating conditions. On the one hand, traditional methods lack the ability to intelligently select the optimal efficiency-enhancing measures due to a lack of perception of flue gas saturation. On the other hand, the lack of a precise mass transfer compensation mechanism in the pursuit of energy conservation and emission reduction easily leads to excessive emissions. Therefore, developing an optimized control method that can significantly reduce system energy consumption while ensuring desulfurization efficiency based on thermodynamic state identification has become a key technical problem urgently needing to be solved in this field. Summary of the Invention

[0005] The purpose of this invention is to propose an energy efficiency control optimization method for wet desulfurization systems, in order to solve the problem that energy consumption and efficiency are difficult to optimize in a coordinated manner in the prior art.

[0006] The present invention provides an energy efficiency control optimization method for a wet desulfurization system, comprising: acquiring operating data of the wet desulfurization system, the operating data including inlet flue gas temperature, inlet flue gas humidity, inlet flue gas pressure, outlet flue gas temperature, sulfur dioxide concentration at the absorber outlet, number of currently operating slurry circulation pumps, and slurry pH value; calculating the adiabatic saturation temperature of the flue gas under the current operating conditions using a wet air enthalpy-humidity diagram model based on the inlet flue gas temperature, inlet flue gas humidity, and inlet flue gas pressure; and comparing the outlet flue gas temperature with the adiabatic saturation temperature. The difference is defined as the temperature difference convergence; a desulfurization enhancement demand signal is generated by monitoring the sulfur dioxide concentration at the outlet of the absorption tower; in response to the desulfurization enhancement demand signal, a differentiated control strategy is executed according to the temperature difference convergence: if the temperature difference convergence is greater than a preset threshold, an instruction to increase the number of slurry circulation pumps in operation is generated; if the temperature difference convergence is less than or equal to the preset threshold, an instruction to decrease the number of slurry circulation pumps in operation is generated, and an instruction to increase the slurry pH setting value is also generated; according to the control strategy, the slurry circulation pumps or slurry supply regulating valves are driven to perform actions respectively.

[0007] This invention quantifies the mass transfer potential between flue gas and slurry by introducing a temperature difference convergence index, and executes a differentiated control strategy in conjunction with the desulfurization enhancement demand signal. This can dynamically optimize the number of slurry circulation pumps in operation and the pH setpoint while ensuring desulfurization efficiency, thus significantly reducing system energy consumption.

[0008] Optionally, the process of acquiring the operating data includes: collecting signals of inlet flue gas temperature, inlet flue gas humidity, inlet flue gas pressure, outlet flue gas temperature, and slurry pH value through sensors arranged on the flue and absorption tower; transmitting the collected signals to the control system; and performing noise reduction processing on the signals to obtain the operating data.

[0009] Optionally, at least two slurry circulation pumps are connected in parallel; the slurry supply regulating valve is a regulating valve for adjusting the flow rate of limestone slurry.

[0010] Optionally, the calculation process of the adiabatic saturation temperature includes: establishing an isenthalpic process equation based on the law of conservation of energy; substituting the inlet flue gas temperature, inlet flue gas humidity, and inlet flue gas pressure into the isenthalpic process equation to calculate the total specific enthalpy of the inlet state; and solving the isenthalpic process equation using an iterative numerical solution method until the temperature variable in the equation makes the difference between the calculated total specific enthalpy of the saturated state and the total specific enthalpy of the inlet state less than a preset convergence accuracy, and this temperature variable is the adiabatic saturation temperature.

[0011] This invention establishes an isenthalpic process equation based on the law of conservation of energy and employs an iterative numerical method to solve for the adiabatic saturation temperature. This calculation method integrates multi-dimensional parameters such as the temperature, humidity, and pressure of the inlet flue gas, enabling a high-precision reconstruction of the final temperature of the flue gas during an ideal adiabatic humidification process. Compared to empirical formulas, this method calculates the adiabatic saturation temperature with minimal error, providing a precise benchmark for subsequent calculations of temperature difference convergence and ensuring the accuracy of control strategy switching.

[0012] Optionally, generating the desulfurization enhancement demand signal includes: comparing the sulfur dioxide concentration at the outlet of the absorption tower with a preset value; and generating the desulfurization enhancement demand signal when the sulfur dioxide concentration at the outlet of the absorption tower is higher than the preset value.

[0013] Optionally, the instruction for generating the number of running slurry circulation pumps includes: querying the current number of running slurry circulation pumps; if the current number of running pumps is greater than two, generating an instruction to stop one circulation pump; if the current number of running pumps is less than or equal to two, not performing the pump reduction operation, but only performing the action of increasing the pH setting value of the slurry.

[0014] Optionally, the instruction to reduce the number of operating slurry circulation pumps includes energy efficiency compensation logic: while issuing the instruction to reduce one slurry circulation pump, the loss of mass transfer coefficient caused by reducing the pump is calculated; according to the two-film theory formula, the pH increment required to compensate for the loss of mass transfer coefficient is calculated; the pH increment is added to the current pH setting value to form the instruction to increase the pH setting value of the slurry.

[0015] This invention introduces an energy efficiency compensation logic based on the dual-film theory. When performing energy-saving operations such as reducing the number of slurry circulation pumps, the system can calculate in real time the loss of mass transfer coefficient due to the decrease in the liquid-to-gas ratio and quantitatively calculate the pH increment required to compensate for this loss. This precise compensation mechanism eliminates the risk of instantaneous emission exceedances that may be caused by energy-saving operations, achieving the dual goals of energy conservation and environmental protection, and greatly improving the robustness of the control system.

[0016] Optionally, the control method further includes safety logic: real-time monitoring of the sulfur dioxide concentration at the outlet of the absorption tower and its changing trend; when the rate of increase of the sulfur dioxide concentration at the outlet exceeds a preset first threshold, or the absolute value of the sulfur dioxide concentration at the outlet exceeds a preset second threshold, the differentiated control strategy is disabled, and actions such as increasing the number of slurry circulation pumps in operation and increasing the pH setting of the slurry are executed.

[0017] When a sharp increase in sulfur dioxide concentration at the outlet is detected or exceeds the upper limit threshold, the energy-saving strategy will be immediately disabled, and the system will be forced to enter maximum operating mode. This design ensures that environmental protection indicators are prioritized in the event of drastic fluctuations or sudden anomalies, thus improving industrial applicability.

[0018] Optionally, the action execution steps of the slurry supply regulating valve include: using the slurry pH setpoint generated by the control strategy as the target value, and using the real-time collected slurry pH value as the feedback value; calculating the target opening degree of the slurry supply regulating valve based on the target value and the feedback value; and driving the slurry supply regulating valve to adjust to the target opening degree.

[0019] Optionally, the step of acquiring the operating data further includes sensor validity verification: calculating the specific enthalpy difference between the inlet flue gas and the outlet flue gas; calculating the theoretical amount of water evaporation according to the law of conservation of energy; comparing the theoretical amount of water evaporation with the measured value of the absorber water flow meter; if the deviation exceeds the verification threshold, triggering a temperature sensor fault alarm.

[0020] This invention establishes a sensor validity verification mechanism based on the law of conservation of energy. By comparing the theoretical water evaporation rate with the actual water replenishment flow rate, drift faults in temperature sensors or flow meters can be diagnosed in real time online. This mechanism ensures that optimized control strategies are based on reliable data.

[0021] The beneficial effects of this invention are as follows: By constructing the key thermodynamic index of temperature difference convergence and combining it with a differentiated control strategy, this invention provides a novel energy efficiency control optimization method. This method accurately identifies the hygroscopic potential and physical mass transfer bottlenecks of flue gas by calculating the adiabatic saturation temperature under current operating conditions. When the temperature difference convergence is small, it indicates that physical spraying has approached its limit, and the system intelligently switches to a chemical efficiency enhancement mode of reducing pumps and increasing pH, avoiding ineffective slurry circulation. This thermodynamic state-based decision-making mechanism fundamentally solves the energy waste problem caused by blindly increasing the circulation pump in traditional methods, achieving a significant reduction in system energy consumption while ensuring desulfurization efficiency. Attached Figure Description

[0022] Figure 1 is a flowchart of an energy efficiency control optimization method for a wet desulfurization system according to an embodiment of the present invention. Detailed Implementation

[0023] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. As shown in Figure 1, it is a flowchart of an energy efficiency control optimization method for a wet desulfurization system according to an embodiment of the present invention.

[0024] S1: Obtain the operating data of the wet desulfurization system and calculate the adiabatic saturation temperature and temperature difference convergence.

[0025] First, the operational data of the wet desulfurization system is acquired. This operational data refers to a set of key parameters that reflect the real-time operating status and flue gas characteristics of the desulfurization system. Specifically, it includes inlet flue gas temperature, inlet flue gas humidity, inlet flue gas pressure, outlet flue gas temperature, sulfur dioxide concentration at the absorber outlet, the number of currently operating slurry circulation pumps, and slurry pH value. This operational data is acquired through sensors deployed on the flue and absorber. The collected sensor signals are transmitted to the distributed control system via a fieldbus. To improve data quality, the signals are denoised. The denoising process employs a moving average filtering algorithm, with a window length set to five sampling periods. The moving average filtering algorithm replaces the current value with the arithmetic mean of the data within the window, effectively suppressing random noise while maintaining the dynamic response characteristics of the data.

[0026] Furthermore, the data acquisition steps also include sensor validity verification to ensure that control decisions are based on accurate and reliable data. The specific steps of sensor validity verification are as follows: calculate the enthalpy difference between the inlet and outlet flue gas; calculate the theoretical water evaporation rate according to the law of conservation of energy; compare the theoretical water evaporation rate with the measured value of the absorber water flow meter; if the deviation exceeds the verification threshold, a temperature sensor fault alarm is triggered. The enthalpy difference between the inlet and outlet flue gas reflects the heat released by the flue gas in the absorber, which is mainly used for water evaporation. According to the law of conservation of energy, the theoretical water evaporation rate is equal to the enthalpy difference divided by the latent heat of vaporization of water. Comparing the theoretical calculation value with the measured value of the water flow meter, if the deviation exceeds 20%, it is determined that the temperature sensor may be faulty, triggering an alarm signal to prompt operators to check and calibrate. Through sensor validity verification, online diagnosis of key temperature sensors is achieved using physical constraint relationships, effectively avoiding control failures caused by sensor malfunctions and improving the reliability and safety of the system.

[0027] Next, based on the inlet flue gas temperature, inlet flue gas humidity, and inlet flue gas pressure, the adiabatic saturation temperature of the flue gas under the current operating conditions is calculated using a humid air enthalpy-humidity diagram model. The adiabatic saturation temperature refers to the temperature at which unsaturated humid air and water reach saturation under adiabatic conditions, and is a key parameter characterizing the thermodynamic state of the flue gas. The calculation of the adiabatic saturation temperature is based on an isenthalpic process equation established by the law of conservation of energy, assuming that the total specific enthalpy of the flue gas remains constant during the adiabatic humidification process. During the adiabatic humidification process, the total specific enthalpy of the flue gas remains constant, that is, the total specific enthalpy at the inlet state is equal to the total specific enthalpy at saturation. The total specific enthalpy consists of two parts: the specific enthalpy of dry air and the specific enthalpy of water vapor. Its calculation involves the isobaric specific heat capacity, temperature, moisture content, latent heat of vaporization of water at zero degrees Celsius, and the isobaric specific heat capacity of water vapor. The inlet flue gas temperature, inlet flue gas humidity, and inlet flue gas pressure are substituted into the isenthalpic process equation to calculate the total specific enthalpy at the inlet state. The inlet state moisture content is calculated based on the inlet flue gas humidity and temperature, where the saturated water vapor pressure can be calculated using the Antoine equation. An iterative numerical method is used to solve the isenthalpic process equation until the temperature variable in the equation causes the difference between the calculated total specific enthalpy of the saturated state and the total specific enthalpy of the inlet state to be less than a preset convergence accuracy. This temperature variable is the adiabatic saturation temperature. The specific iterative process is as follows: First, the initial guess value is set to the inlet flue gas temperature minus ten degrees Celsius; then, the saturated water vapor pressure and moisture content at this temperature are calculated; next, the total specific enthalpy of the saturated state is calculated; the residual, i.e., the difference between the total specific enthalpy of the inlet state and the total specific enthalpy of the saturated state, is calculated; if the absolute value of the residual is less than the convergence accuracy, the current temperature is the desired adiabatic saturation temperature; otherwise, the temperature is updated using the Newton-Raphson iteration method, and the iteration continues. Through the above iterative calculations, the adiabatic saturation temperature of the flue gas under the current operating conditions is obtained.

[0028] Specifically, the calculation of the adiabatic saturation temperature is based on the law of conservation of energy, establishing the following isenthalpic process equation:

[0029] ;

[0030] In the formula, the left side of the equal sign represents the total specific enthalpy under inlet conditions, and the right side represents the total specific enthalpy under saturation conditions; variables and These represent the inlet flue gas temperature and the adiabatic saturation temperature, respectively, in °C. and These represent the isobaric specific heat capacities of dry air and water vapor, respectively, in units of... ; The latent heat of vaporization of water at 0℃, in units of ; and These represent the moisture content at the inlet and saturated states, respectively, in units of... It is worth noting that saturated moisture content It is about The function requires the partial pressure of saturated water vapor to be calculated using the Antoine equation. Correlation calculations are performed, and the nonlinear equation is finally solved using an iterative numerical method to obtain the accurate adiabatic saturation temperature under the current operating conditions. .

[0031] The difference between the outlet flue gas temperature and the adiabatic saturation temperature is defined as the temperature difference convergence. This temperature difference convergence is a key indicator characterizing the degree to which the flue gas approaches saturation within the absorption tower. A smaller temperature difference convergence indicates that the outlet flue gas is closer to saturation, and the effect of further enhancing mass transfer by increasing the circulation pump is more limited. The introduction of the temperature difference convergence provides a scientific basis for subsequent differentiated control strategies, enabling the control system to intelligently select the optimal efficiency-enhancing measures based on the actual saturation state of the flue gas.

[0032] S2: Monitor the sulfur dioxide concentration at the outlet of the absorption tower and generate a signal indicating the need for enhanced desulfurization.

[0033] The sulfur dioxide concentration at the absorber outlet is monitored in real time. This concentration is compared to a preset value, set at 35 mg / m³ in this embodiment. When the sulfur dioxide concentration at the absorber outlet exceeds the preset value, a desulfurization enhancement demand signal is generated. This signal is a Boolean variable; it is true when the sulfur dioxide concentration at the absorber outlet exceeds the preset value, and false otherwise. To avoid frequent triggering due to measurement noise, a delayed confirmation mechanism is implemented. The signal is confirmed as true only when the sulfur dioxide concentration at the absorber outlet continuously exceeds the preset value for a preset time. In this embodiment, the preset time is set to two minutes. By establishing the desulfurization enhancement demand signal as the trigger condition for the differentiated control strategy, it is ensured that control actions are executed only when necessary, avoiding the impact of frequent adjustments on system stability and improving the reliability and economy of the control system.

[0034] S3: Responding to the demand signal for enhanced desulfurization, it implements differentiated control strategies based on the degree of temperature difference convergence.

[0035] When a desulfurization enhancement demand signal is detected as true, a differentiated control strategy is initiated. The core of this strategy lies in judging the flue gas saturation state based on the temperature difference proximity and intelligently selecting the optimal efficiency enhancement method. First, the temperature difference proximity is compared with a preset threshold. The preset threshold is determined based on the absorber tower design parameters and operating experience; in this embodiment, it is set to eight degrees Celsius. The physical meaning of this threshold is: when the temperature difference proximity is greater than eight degrees Celsius, the flue gas still has considerable room to reach saturation, and increasing the circulation pump can effectively improve the gas-liquid contact area and mass transfer coefficient; when the temperature difference proximity is less than or equal to eight degrees Celsius, the flue gas is close to saturation, and further increasing the circulation pump has limited efficiency enhancement; therefore, increasing the pH value is more economical.

[0036] If the temperature difference approaches a preset threshold, an instruction to increase the number of operating slurry circulation pumps is triggered. In this embodiment, the absorber is configured with four slurry circulation pumps operating in parallel, each with a flow rate of 6,000 cubic meters per hour and a power of 500 kilowatts. At least two slurry circulation pumps are connected in parallel. The execution logic of the instruction to increase the number of circulation pumps is as follows: First, the current number of operating slurry circulation pumps is queried; if the current number is less than four, an instruction to start one standby circulation pump is generated, with the target number being the current number plus one; if the current number is equal to four (i.e., all circulation pumps are running), the current state is maintained, and an alarm signal is triggered to prompt operators to check for other abnormalities in the system. The circulation pump start instruction is sent to the motor control center through the distributed control system to execute the pump start operation. To avoid water hammer, the circulation pump adopts a soft start method, with a start time set to 30 seconds. By increasing the number of operating circulation pumps, the slurry circulation volume and gas-liquid contact area are increased, enhancing the mass transfer effect and thus improving desulfurization efficiency.

[0037] If the temperature difference convergence is less than or equal to a preset threshold, a command to reduce the number of operating slurry circulation pumps and simultaneously increase the slurry pH setting is triggered. This control strategy includes energy efficiency compensation logic to ensure that desulfurization efficiency remains unchanged while reducing energy consumption. First, a command to reduce the number of operating slurry circulation pumps is generated. The current number of operating slurry circulation pumps is queried; if the current number of operating pumps is greater than two, a command to stop one circulation pump is generated, with the target number of operating pumps being the current number minus one. This ensures that at least two pumps are operating to maintain basic mass transfer requirements. If the current number of operating pumps is less than or equal to two, the pump reduction operation is not performed, only the pH increase operation is performed. Next, while issuing the command to reduce one slurry circulation pump, the loss of mass transfer coefficient due to the reduction of this pump is calculated. According to the two-film theory, the overall gas-liquid mass transfer coefficient mainly depends on the liquid film mass transfer coefficient. The liquid film mass transfer coefficient has a power function relationship with the slurry flow rate. After reducing one circulation pump, the total slurry flow rate decreases, resulting in a reduction in the gas-liquid contact area and a decrease in the overall mass transfer capacity. The ratio of the liquid film mass transfer coefficient before and after pump reduction is calculated to obtain the mass transfer coefficient loss rate. Based on the two-film theory formula, the pH increment required to compensate for the mass transfer coefficient loss is calculated. The absorption rate of sulfur dioxide in the liquid phase is directly proportional to the hydroxide ion concentration, while pH value has a logarithmic relationship with hydroxide ion concentration. To compensate for the mass transfer coefficient loss, the slurry pH value needs to be increased to enhance the chemical absorption rate. By establishing a balance between the mass transfer coefficient and hydroxide ion concentration, the required pH increment is calculated. This pH increment is then added to the current pH setpoint to form the instruction to increase the slurry pH setpoint. Through energy efficiency compensation logic, while reducing energy consumption by decreasing the circulating pump, the loss of the mass transfer coefficient is compensated by increasing the pH value, ensuring that the desulfurization efficiency remains unchanged, thus achieving true energy efficiency optimization.

[0038] Specifically, the calculation of the energy efficiency compensation logic is based on the equilibrium equation established by the two-film theory:

[0039] ;

[0040] In the formula, Represents the total resistance in the gas-liquid mass transfer process of sulfur dioxide, where The gas-phase overall mass transfer coefficient is expressed in kmol / (m³). 2 ·s·kPa); Represents the resistance to gas film diffusion, where This is the gas film mass transfer coefficient, with units of kmol / (m²). 2 ·s·kPa); This represents the combined mass transfer resistance in the liquid phase; H is the Henry's constant for sulfur dioxide in the liquid phase, with units of kPa·m. 3 / kmol; The liquid film mass transfer coefficient, expressed in m / s, is the mass transfer coefficient during the physical absorption process. This coefficient exhibits a power-law relationship with the slurry flow rate, determined by the number of slurry circulation units. E is the chemical enhancement factor, a dimensionless constant used to characterize the promoting effect of chemical reactions on the mass transfer rate. The control logic of this invention lies in: when changes in flue gas conditions lead to changes in the liquid film mass transfer coefficient... When the mass transfer coefficient decreases, by increasing E, we ensure that the product remains relatively stable, thereby maintaining the overall mass transfer coefficient. The process remains unchanged, achieving energy-saving compensation.

[0041] S4: Drive the slurry circulation pump or slurry supply regulating valve to perform actions according to the control strategy.

[0042] For circulating pump control, commands are sent to the motor control center via the distributed control system based on start or stop instructions to execute the corresponding pump start / stop operations. The start / stop operations of the circulating pumps strictly adhere to electrical safety regulations to ensure safe and reliable equipment operation. For pH control, this is achieved by adjusting the opening of the slurry supply regulating valve. The slurry supply regulating valve is a pneumatic regulating valve that adjusts the flow rate of limestone slurry. The execution steps of the slurry supply regulating valve include: using the slurry pH setpoint generated by the control strategy as the target value, and using the real-time collected slurry pH value as the feedback value; calculating the target opening of the slurry supply regulating valve based on the target value and the feedback value; and driving the slurry supply regulating valve to adjust to the target opening. Specifically, first, the pH deviation, i.e., the difference between the target value and the feedback value, is calculated; then, a proportional-integral-derivative control algorithm is used to calculate the target opening of the slurry supply regulating valve; the calculated control quantity is converted into a valve opening command; finally, the distributed control system sends an opening command to the slurry supply regulating valve, driving the valve to adjust to the target opening. By precisely controlling the opening of the slurry supply regulating valve, accurate adjustment of the slurry pH value is achieved, ensuring stable desulfurization efficiency.

[0043] To ensure system safety, the control method also includes safety logic. The concentration of sulfur dioxide at the outlet of the absorption tower and its changing trend are monitored in real time. When the rate of increase of the outlet sulfur dioxide concentration exceeds a preset first threshold, or the absolute value of the outlet sulfur dioxide concentration exceeds a preset second threshold, the differentiated control strategy is disabled, and the actions of increasing the number of operating slurry circulation pumps and raising the slurry pH setting are forcibly executed. The first threshold is a safe limit for the rate of increase of sulfur dioxide concentration, set at 5 mg / m³ / min in this embodiment. The second threshold is a safe limit for the absolute value of sulfur dioxide concentration, set at 45 mg / m³ in this embodiment. When a sharp deterioration in desulfurization efficiency or approaching the emission limit is detected, the system immediately switches to the most conservative control strategy, simultaneously starting all available circulation pumps and raising the pH setting to the upper limit to ensure that environmental emission requirements are met under any operating conditions. The safety logic provides a final safety barrier for the system, effectively preventing the risk of exceeding emission standards due to control strategy optimization, and improving the safety and reliability of the control system.

[0044] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be within the scope of protection of the present invention.

Claims

1. An energy efficiency control optimization method for wet desulfurization systems, characterized in that, The control method includes: acquiring operating data of the wet desulfurization system, including inlet flue gas temperature, inlet flue gas humidity, inlet flue gas pressure, outlet flue gas temperature, sulfur dioxide concentration at the absorber outlet, the current number of operating slurry circulation pumps, and slurry pH value; calculating the adiabatic saturation temperature of the flue gas under the current operating conditions using a wet air enthalpy-humidity diagram model based on the inlet flue gas temperature, inlet flue gas humidity, and inlet flue gas pressure; defining the difference between the outlet flue gas temperature and the adiabatic saturation temperature as the temperature difference convergence; generating a desulfurization enhancement demand signal by monitoring the sulfur dioxide concentration at the absorber outlet; and executing a differentiated control strategy based on the temperature difference convergence: if the temperature difference convergence is greater than a preset threshold, generating an instruction to increase the number of operating slurry circulation pumps; if the temperature difference convergence is less than or equal to the preset threshold, generating an instruction to decrease the number of operating slurry circulation pumps and simultaneously generating an instruction to increase the slurry pH setpoint; and driving the slurry circulation pumps or slurry supply regulating valves to perform actions according to the control strategy.

2. The energy efficiency control optimization method for wet desulfurization systems according to claim 1, characterized in that, The process of acquiring the operational data includes: collecting signals of inlet flue gas temperature, inlet flue gas humidity, inlet flue gas pressure, outlet flue gas temperature, and slurry pH value through sensors arranged on the flue and absorption tower; transmitting the collected signals to the control system; and performing noise reduction processing on the signals to obtain the operational data.

3. The energy efficiency control optimization method for wet desulfurization systems according to claim 1, characterized in that, The slurry circulation pump is configured with at least two units connected in parallel; the slurry supply regulating valve is a regulating valve for adjusting the flow rate of limestone slurry.

4. The energy efficiency control optimization method for wet desulfurization systems according to claim 1, characterized in that, The calculation process of the adiabatic saturation temperature includes: establishing an isenthalpic process equation based on the law of conservation of energy; substituting the inlet flue gas temperature, inlet flue gas humidity, and inlet flue gas pressure into the isenthalpic process equation to calculate the total specific enthalpy of the inlet state; and solving the isenthalpic process equation using an iterative numerical solution method until the temperature variable in the equation makes the difference between the calculated total specific enthalpy of the saturation state and the total specific enthalpy of the inlet state less than the preset convergence accuracy. This temperature variable is the adiabatic saturation temperature.

5. The energy efficiency control optimization method for a wet desulfurization system according to claim 4, characterized in that, The process of generating a desulfurization enhancement demand signal includes: comparing the sulfur dioxide concentration at the outlet of the absorption tower with a preset value; and generating the desulfurization enhancement demand signal when the sulfur dioxide concentration at the outlet of the absorption tower is higher than the preset value.

6. The energy efficiency control optimization method for a wet desulfurization system according to claim 1, characterized in that, The instruction to reduce the number of operating slurry circulation pumps includes: querying the current number of operating slurry circulation pumps; if the current number of operating pumps is greater than two, generating an instruction to stop one circulation pump; if the current number of operating pumps is less than or equal to two, not performing the pump reduction operation, but only performing the action of increasing the pH setting value of the slurry.

7. The energy efficiency control optimization method for wet desulfurization systems according to claim 1, characterized in that, The instruction to reduce the number of operating slurry circulation pumps includes energy efficiency compensation logic: while issuing the instruction to reduce one slurry circulation pump, the loss of mass transfer coefficient caused by reducing the pump is calculated; according to the two-film theory formula, the pH increment required to compensate for the loss of mass transfer coefficient is calculated. The pH increment is added to the current pH setting to form the instruction to increase the pH setting of the slurry.

8. The energy efficiency control optimization method for a wet desulfurization system according to claim 1, characterized in that, The control method also includes safety logic: real-time monitoring of the sulfur dioxide concentration at the outlet of the absorption tower and its changing trend; when the rate of increase of the sulfur dioxide concentration at the outlet exceeds a preset first threshold, or the absolute value of the sulfur dioxide concentration at the outlet exceeds a preset second threshold, the differentiated control strategy is disabled, and actions such as increasing the number of slurry circulation pumps in operation and increasing the pH setting of the slurry are executed.

9. The energy efficiency control optimization method for a wet desulfurization system according to claim 1, characterized in that, The action execution steps of the slurry supply regulating valve include: taking the slurry pH set value generated by the control strategy as the target value and taking the real-time collected slurry pH value as the feedback value; calculating the target opening degree of the slurry supply regulating valve according to the target value and the feedback value; and driving the slurry supply regulating valve to adjust to the target opening degree.

10. The energy efficiency control optimization method for a wet desulfurization system according to claim 1, characterized in that, The steps for acquiring the operating data also include sensor validity verification: calculating the enthalpy difference between the inlet flue gas and the outlet flue gas; calculating the theoretical amount of water evaporation based on the law of conservation of energy; comparing the theoretical amount of water evaporation with the measured value of the absorber water flow meter; if the deviation exceeds the verification threshold, triggering a temperature sensor fault alarm.

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