Multi-objective optimization method for a wet flue gas desulfurization system

Abstract

The present invention discloses a multi-objective optimization method for a wet flue gas desulfurization system. The present invention includes steps of obtaining operation data of a target wet flue gas desulfurization system during the desulfurization process and evaluating whether the operation data is complete; in the case where the operation data of the target wet flue gas desulfurization system is incomplete, performing CFD simulation on the desulfurization process of the target wet flue gas desulfurization system to obtain complete operation data; extracting a physical model of the target wet flue gas desulfurization system; constructing a transfer function for the whole of the target wet flue gas desulfurization system or a slurry pump flow control system; solving the transfer function using the operation data to obtain an optimal transfer function; performing time-frequency domain analysis on the optimal transfer function to obtain a Bode plot, and analyzing stability according to the time-frequency domain analysis and the Bode plot, and taking the value range during stable desulfurization as the optimization result. The present invention is used for comprehensively optimizing a wet flue gas desulfurization system.

Description

Technical Field

[0001] The invention belongs to the technical field of process control of desulfurization equipment, and particularly relates to a multi-objective optimization method for a wet desulfurization system. Background Art

[0002] Flue gas desulfurization is currently the main method for controlling sulfur dioxide emissions. For the desulfurization of power plant tail gas, there are dry method, semi-dry method and wet method. Among them, the wet flue gas desulfurization has the widest application range, stable operation, mature technology and obvious desulfurization effect. Therefore, in-depth understanding and recognition of the internal desulfurization mechanism and mechanism of the wet flue gas desulfurization system used for controlling pollutant emissions in coal-fired power plants can provide a basis or support for the good operation of desulfurization equipment and the upgrading of process transformation. A typical wet flue gas desulfurization system is a wet desulfurization tower. One type of wet desulfurization tower is a spray tower, which mainly relies on the contact reaction between the slurry spray and the flue gas for desulfurization. Another type of wet desulfurization tower is a bubble column, which mainly desulfurizes by the contact reaction between the bubbles and the slurry in the slurry pool. However, whether it is a spray tower or a bubble column, the final desulfurization performance analysis still needs to be evaluated by comparing whether the changes in the pH value of the absorption slurry, the sulfur dioxide concentration of the flue gas, and the temperature of the flue gas during the whole desulfurization process meet the expectations.

[0003] In the prior art, for the optimization method of the operation process equipment setting of wet desulfurization equipment, the experimental test is used to study and optimize the desulfurization performance, which belongs to a semi-empirical development process. The related experiments or actual measurements of the wet desulfurization system in the prior art adopt the single-factor control variable method. In order to obtain the influencing factors of the desulfurization equipment for analysis, either the existing wet desulfurization system in operation needs to interrupt the production plan for a long time to make resources available for actual measurement, or other influencing factors need to be repeatedly controlled during production, which will also make the production plan disordered. In addition, industrial application-level desulfurization equipment usually has a complex structure, many internal equipment, and fast-changing operation data. When using the single-factor control variable method, many factors affecting the desulfurization of the wet desulfurization tower need to be considered, and the obtained conclusions are relatively single, which can only provide a general reference and optimization direction, and it is difficult to accurately, comprehensively and systematically reflect the desulfurization performance of the desulfurization system, and the relationship between desulfurization performance and operation economic cost is also ignored. Summary of the Invention

[0004] In order to overcome one or more defects and deficiencies existing in the prior art, the purpose of the present invention is to provide a multi-objective optimization method for a wet desulfurization system, which is used to analyze how to optimize the setting of the wet desulfurization system.

[0005] In order to achieve the above purpose, the present invention adopts the following technical solutions.

[0006] A multi-objective optimization method for a wet desulfurization system includes the following steps:

[0007] Obtain the three operating data of the flue gas sulfur dioxide concentration, flue gas temperature, and absorption slurry pH value during the desulfurization process of the target wet desulfurization system to be optimized, and evaluate whether these three operating data are complete;

[0008] In the case where the operating data of the target wet desulfurization system is incomplete, conduct a CFD simulation of the desulfurization process of the target wet desulfurization system to obtain complete operating data of the flue gas sulfur dioxide concentration, flue gas temperature, and absorption slurry pH value;

[0009] When the operating data of the target wet desulfurization system is complete or complete operating data is obtained through CFD simulation, extract the physical model of the target wet desulfurization system. The target wet desulfurization system is simplified to be composed of a wet desulfurization tower and a slurry pump flow control system;

[0010] Construct the transfer function of the slurry pump flow control system; use the operating data to solve the transfer function in Matlab software to obtain the optimal transfer function;

[0011] Conduct time-frequency domain analysis on the optimal transfer function, then obtain the Bode plot from it, and analyze the stability of the target wet desulfurization system during the desulfurization process based on the time-frequency domain analysis and the Bode plot, obtain the value range of the operating data during stable desulfurization, and use the value range during stable desulfurization as the optimization result.

[0012] Preferably, the specific process of obtaining the operating data includes:

[0013] For the target wet desulfurization system to be optimized, through the set sensor components, obtain the data of its operating data when inputting and outputting the target wet desulfurization system without controlling a certain variable, and evaluate whether the obtained operating data is complete.

[0014] Further, whether the operating data is complete depends on whether all the data of the changes in the three parameters of the flue gas sulfur dioxide concentration, flue gas temperature, and absorption slurry pH value within the set monitoring duration can be obtained. If all can be obtained, it is complete; otherwise, it is incomplete.

[0015] Further, the specific process of conducting a CFD simulation of the desulfurization process of the target wet desulfurization system includes:

[0016] Conduct a CFD simulation of the desulfurization process of the target wet desulfurization system in Ansys fluent 16 software;

[0017] According to the CFD simulation of the gas-liquid flow, heat transfer, and mass transfer processes in the target wet flue gas desulfurization system, record the hydrodynamic characteristics of the gas-liquid flow of the flue gas and absorption slurry, as well as the changes in the sulfur dioxide concentration and temperature of the flue gas during the period from the initial state to the stable state;

[0018] Based on the process of hydrodynamic characteristics, sulfur dioxide concentration, and temperature change, preliminarily obtain the respective simulation fluctuation signals of the sulfur dioxide concentration of the flue gas, the temperature of the flue gas, and the pH value of the absorption slurry during the desulfurization process within the set time length in the simulated desulfurization process of the target wet flue gas desulfurization system, and use the simulation fluctuation signals as the complete operation data of the sulfur dioxide concentration of the flue gas, the temperature of the flue gas, and the pH value of the absorption slurry.

[0019] Furthermore, extract the physical model of the target wet flue gas desulfurization system. The specific process includes:

[0020] Simplify the equipment for accommodating the flue gas and absorption slurry during the desulfurization process into the form of a wet flue gas desulfurization tower, and simplify the equipment for transporting the materials required for the desulfurization process to the wet flue gas desulfurization tower into the form of a slurry pump flow control system;

[0021] Connect the slurry pump flow control system and the wet flue gas desulfurization tower to each other.

[0022] Furthermore, the slurry pump flow control system is composed of an inverter, a motor, and a circulation pump;

[0023] The inverter is connected to the motor and is used to provide working power to the motor;

[0024] The motor is connected to the circulation pump, and the motor is used to drive the circulation pump to pump materials into or out of the wet flue gas desulfurization tower;

[0025] The circulation pump is connected to the wet flue gas desulfurization tower, and the circulation pump is used to pump materials into or out of the interior of the wet flue gas desulfurization tower.

[0026] Furthermore, construct the transfer function of the slurry pump flow control system. The specific process includes:

[0027] Construct the mathematical model of the inverter The formula is as follows:

[0028]

[0029] Among them, K int represents the voltage-frequency coefficient of the input port of the inverter, K f represents the voltage-frequency coefficient of the motor phase port of the inverter, and s represents the complex frequency of the Laplace transform;

[0030] Construct the mathematical model of the motor The formula is as follows:

[0031]

[0032] Among them, K M represents the motor gain coefficient, and T L represents the mechanical time constant, and T S represents the electrical time constant;

[0033] Construct the mathematical model of the circulation pump as follows:

[0034]

[0035] Among them, Q1(S) represents the rated flow rate of the circulation pump, n1(s) represents the rated flow velocity of the circulation pump, and k a represents the ratio of the rated flow rate to the rated flow velocity;

[0036] Combining the mathematical models of the frequency converter, the motor, and the circulation pump respectively, the transfer function G(s) formula of the slurry pump flow control system is as follows:

[0037]

[0038] Furthermore, use the operation data to solve the transfer function to obtain the optimal transfer function. The specific process includes:

[0039] Take the data of the operation data when input into the target wet flue gas desulfurization system as the input data of the transfer function G(s), obtain different orders of the transfer function G(s) from it, then use Matlab software to program and simulate the transfer function G(s), solve the function tfest for different orders, and then perform error fitting on the solution results and the data of the operation data when output from the target wet flue gas desulfurization system to determine the order with the highest fitting degree. At this time, the transfer function is optimal.

[0040] Furthermore, analyze the stability of the separation process to obtain the preferred value range of the operation data. The specific process includes:

[0041] Perform time-frequency domain analysis on the optimal transfer function, then obtain the Bode diagram corresponding to the current transfer function, and judge the stability of the target wet flue gas desulfurization system through the stability condition that whether the amplitude margin and phase angle margin corresponding to the amplitude-frequency characteristic and phase-frequency characteristic of the transfer function are both greater than zero; if the stability condition is satisfied, it indicates that the desulfurization process of the target wet flue gas desulfurization system is stable at this time; if the stability condition is not satisfied, it indicates that the desulfurization process of the target wet flue gas desulfurization system is unstable at this time;

[0042] Set the operation data when the stability condition is satisfied as the preferred value range.

[0043] Furthermore, the steps of the multi-objective optimization method for the wet flue gas desulfurization system further include performing an economic cost analysis on the desulfurization process. The specific process is as follows:

[0044] Obtain the economic cost of the equipment construction of the target wet flue gas desulfurization system;

[0045] When obtaining the preferred value range of the operating data in the target wet flue gas desulfurization system, obtain the economic cost per unit of energy consumed and the economic cost of the absorption slurry corresponding to the consumption of per unit of energy;

[0046] Integrate the economic cost of the equipment construction of the target wet flue gas desulfurization system, the economic cost per unit of energy consumed, and the economic cost of the absorption slurry corresponding to the consumption of per unit of energy, and use the subset of the value range of the operating data with a lower integrated economic cost as the final optimization result.

[0047] Compared with the prior art, the technical solution of the present invention has the following beneficial effects:

[0048] Compared with the prior art where there are significant differences in the completeness of the measured operating data of the wet flue gas desulfurization of flue gas, by using comprehensive analysis to analyze the removal performance, stability, and economy of the wet flue gas desulfurization of flue gas, a more comprehensive and accurate optimization strategy for the wet flue gas desulfurization system can be given; compared with the prior art where the stability can only be effectively judged by measuring the operating data of the wet flue gas desulfurization system through the single-factor control variable method, the present invention does not need to consider the limitations of the single-factor control variable method measurement. By constructing a transfer function for time-frequency domain analysis, the stability of the desulfurization process of the wet flue gas desulfurization system can be comprehensively analyzed and judged even when the operating data is incomplete; compared with the prior art which only uses on-site measured values for analysis or separate CFD simulations, the present invention combines CFD simulations with the constructed transfer function and then combines with Bode diagram analysis to be able to perform stability analysis in the time-frequency domain for the desulfurization process, which helps to optimize according to the analyzed operating performance before the process transformation of the wet flue gas desulfurization system, avoiding a large number of ineffective process transformations; the prior art only considered the influence of the desulfurization process itself on equipment optimization alone, lacking the consideration of the optimization of the wet flue gas desulfurization system from multiple perspectives and ignoring the relationship between the process transformation of the wet flue gas desulfurization system or the process transformation and the operating economic cost and the stability of the desulfurization process. The present invention further performs an operating economic cost analysis after the stability analysis to realize the optimization of the process transformation plan of the wet flue gas desulfurization system from multiple perspectives. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 It is a schematic diagram of the general process flow of a multi-objective optimization method for a wet flue gas desulfurization system of the present invention;

[0050] Figure 2 It is a schematic diagram of the internal structure of a simplified geometric model of a wet flue gas desulfurization tower using a square bubbler;

[0051] Figure 3 Schematic diagram of the internal structure of a simplified geometric model of a wet flue gas desulfurization tower with a circular bubbler

[0052] Figure 4 Curve graph for comparing the effects of on-site measurement and CFD simulation of the same wet flue gas desulfurization system

[0053] Figure 5 Gas holdup curve graph of the slurry pool of a desulfurization tower with a square bubbler at a height of 0.15 m

[0054] Figure 6 Bin3 bubble number density distribution curve graph of the slurry pool of a desulfurization tower with a square bubbler at a height of 3.8 m

[0055] Figure 7 Sulfur dioxide mass fraction distribution curve graph of the slurry pool of a desulfurization tower with a square bubbler at a height of 0.1 m

[0056] Figure 8 Sulfur dioxide mass fraction distribution curve graph of the slurry pool of a desulfurization tower with a square bubbler at a height of 4 m

[0057] Figure 9 Gas holdup curve graph of the slurry pool of a desulfurization tower with a circular bubbler at a height of 0.15 m

[0058] Figure 10 Bin3 bubble number density distribution curve graph of the slurry pool of a desulfurization tower with a circular bubbler at a height of 3.8 m

[0059] Figure 11 Sulfur dioxide mass fraction distribution curve graph of the slurry pool of a desulfurization tower with a circular bubbler at a height of 0.1 m

[0060] Figure 12 Sulfur dioxide mass fraction distribution curve graph of the slurry pool of a desulfurization tower with a circular bubbler at a height of 4 m

[0061] Figure 13 Curve graph of the change in the pH value of the absorption slurry in the wet flue gas desulfurization system

[0062] Figure 14 Bode diagram of the amplitude margin corresponding to the pH value of the absorption slurry in the wet flue gas desulfurization system

[0063] Figure 15 Bode diagram of the phase margin corresponding to the pH value of the absorption slurry in the wet flue gas desulfurization system

[0064] Figure 16It is a curve graph of the change in the outlet flue gas temperature of the wet flue gas desulfurization system;

[0065] Figure 17 It is a Bode diagram of the amplitude margin corresponding to the change in the outlet flue gas temperature of the wet flue gas desulfurization system;

[0066] Figure 18 It is a Bode diagram of the phase margin corresponding to the change in the outlet flue gas temperature of the wet flue gas desulfurization system;

[0067] In Figure 2 and Figure 3 : 1 - slurry pool, 2 - scattering tube, 3 - square bubbler, 4 - circular bubbler. Specific implementation manner

[0068] In order to make the objectives, technical solutions and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below in conjunction with the accompanying drawings and their embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0069] Embodiment

[0070] As Figure 1 shown, a multi-objective optimization method for a wet flue gas desulfurization system in this embodiment includes the following steps:

[0071] S1. For the target wet flue gas desulfurization system to be optimized, through the set sensor assembly, without controlling a certain variable, simultaneously obtain the input data at the inlet of the target wet flue gas desulfurization system and the output data at the outlet of the target wet flue gas desulfurization system for its operating data, and evaluate whether the obtained operating data is complete; if the operating data is complete, then directly execute step S3; if the operating data is incomplete, then first execute step S2;

[0072] In this embodiment, the preferred operating data includes three parameters: the flue gas sulfur dioxide concentration, the flue gas temperature, and the pH value of the absorption slurry during the desulfurization process of the wet flue gas desulfurization system; the preferably set sensor assembly is used to monitor the data of the changes in the flue gas sulfur dioxide concentration, the flue gas temperature, and the pH value of the absorption slurry; whether the preferred operating data is complete refers to whether all the data of the changes in the three parameters of the flue gas sulfur dioxide concentration, the flue gas temperature, and the pH value of the absorption slurry within the set monitoring duration can be obtained. If all can be obtained, it is complete, otherwise it is incomplete;

[0073] S2. For the case where the operating data of the target wet flue gas desulfurization system is incomplete, perform CFD simulation on the desulfurization process of the target wet flue gas desulfurization system, simulate the desulfurization process through the simulation, and obtain the complete simulation situation of the three operating data of the flue gas sulfur dioxide concentration, the flue gas temperature, and the pH value of the absorption slurry within the set monitoring duration; the specific process is as follows:

[0074] S21. Conduct a CFD simulation on the desulfurization process of the target wet desulfurization system in Ansys Fluent 16 software. The specific process includes:

[0075] S211. Determine the simulation area and perform geometric model modeling. In this embodiment, it is preferably that the simulation area is the slurry pool and the dispersion tube of the wet desulfurization tower in the target wet desulfurization system.

[0076] S212. Determine the boundary conditions according to the geometric model and set the physical model algorithms corresponding to different operating data objects in the desulfurization process.

[0077] S213. Establish a simulation equation according to the physical model algorithm and give the initial conditions and control parameters to the simulation equation.

[0078] S214. Input the initial conditions to start calculating and solving the simulation equation, obtain the simulation results of the output equation and perform visualization.

[0079] S22. According to the visualization results of the CFD simulation, for the gas-liquid flow, heat transfer, and mass transfer processes in the target wet desulfurization system, obtain the hydrodynamic characteristics of the corresponding flue gas and absorption slurry gas-liquid flow, the change of flue gas sulfur dioxide concentration, and the change of flue gas temperature during the period from the initial state to the stable state. And according to the processes of hydrodynamic characteristics, sulfur dioxide concentration, and temperature change, obtain the simulation fluctuation signals of the flue gas sulfur dioxide concentration, flue gas temperature, and absorption slurry pH value in the desulfurization process of the target wet desulfurization system within the set time length, and use the simulation fluctuation signals as the complete operating data of the flue gas sulfur dioxide concentration, flue gas temperature, and absorption slurry pH value.

[0080] In this embodiment, it is preferably to conduct a CFD simulation on the wet desulfurization system of the bubbling tower type; for most wet desulfurization systems of the bubbling tower type, the desulfurization process is carried out in a slurry pool, and the flue gas enters the slurry pool through multiple parallel dispersion tubes. The absorption slurry is placed in the slurry pool to contact with the flue gas, and the flue gas directly contacts with the absorption slurry through the parallel dispersion tubes. Therefore, the geometric model modeling can be carried out according to such a structure during the CFD simulation.

[0081] To further illustrate the stability of the desulfurization process analyzed by the CFD simulation, this embodiment sets a wet desulfurization system of the bubbling tower type, and its specifications are set as The input flue gas volume is 10,000 - 60,000 m 3 / h, and the input flue gas sulfur dioxide concentration is 200 - 2000 mg / m 3。We examine within the same slurry pool 1. Specifically, for the same set of multiple parallel scattering tubes 2, different bubbling methods at the flue gas outlet are respectively set as a square bubbler 3 and a circular bubbler 4. Both the square bubbler 3 and the circular bubbler 4 are located at one end of the scattering tube 2 close to the bottom of the slurry pool 1. The results obtained from geometric model modeling are as follows Figure 2 and Figure 3 shown. The slurry pool 1 is a cylinder, and the specific numerical settings are as follows: the middle height of the slurry pool 1 is set to 4 meters, the diameter is 2.5 meters, the height at which multiple parallel scattering tubes 2 are immersed in the absorption slurry from the bottom of the slurry pool is not lower than the liquid level height of the absorption slurry, and the cross-sectional areas and the number of pipes of the square bubbler 3 and the circular bubbler 4 are the same;

[0082] According to the above modeling settings, simulation calculations are carried out, and the results of various parameters obtained through analysis are as shown in Figures 5 to 12 . Among them, Figures 5 to 8 corresponds to the results of the square bubbler 2, Figures 9 to 12 corresponds to the results of the circular bubbler 3. Comparing these two parts can be used to analyze the stability effect of the desulfurization process. The relevant situations of the stability of the desulfurization process obtained through simulation are as follows:

[0083] 1. In the initial stage, especially when it is less than 22 seconds, the gas holdup distribution at the cross-section 0.15 meters above the slurry pool of the square bubbler is uneven; after a period of gas-liquid reaction, starting from 65 seconds, for both the square bubbler and the circular bubbler, the average gas holdup fluctuation at the cross-section 0.15 meters above the slurry pool drops significantly. Especially after 110 seconds, the gas holdup of the square bubbler basically oscillates slightly back and forth at about 0.7 ± 0.2, while the gas holdup of the circular bubbler basically oscillates slightly back and forth at about 0.78 ± 0.1; the gas holdup fluctuation of the circular bubbler is relatively weak. Since the inlet wide angle of the circular bubbler is wider and the radiation surface is wider, and the flow rate of the absorption slurry near the circular bubbler at the cross-section 0.15 meters above the slurry pool is relatively low, the content of the absorption slurry carried away is relatively small, so the gas holdup is relatively high, and the gas holdup at the cross-section 0.15 meters above the slurry pool of the circular bubbler also reaches the state of uniform fluctuation earlier than that of the square bubbler;

[0084] 2. The fluctuation of the Bin3 bubble number density distribution at the cross-section 3.8 meters above the slurry pool with time is very large. The Bin3 bubble number density of the circular bubbler is of the high-frequency oscillation type, while that of the square bubbler is of the type of wide-amplitude oscillation with time. The square bubbler completes one cycle of oscillation every about 140 seconds, while the cycle of the circular bubbler is 40 seconds. The reason is that the circular bubbling caused by the circular bubbler is more conducive to the gas phase entering the liquid phase for shuttle penetration, which is thus conducive to the process of turbulent kinetic energy triggering, breaking of large bubbles, and small bubbles colliding to form large bubbles. Therefore, the oscillation cycle of the Bin-3 bubble number density of the circular bubbler is compressed;

[0085] 3. The sulfur dioxide mass fraction at the cross-section of the circular bubbler at a height of 4 meters in the slurry pool (i.e., the outlet of the slurry pool) reaches a state of uniform and slightly fluctuating more quickly than that of the square bubbler. At the same time, whether at the cross-section at a height of 0.1 meters in the slurry pool or at the cross-section at the outlet of the slurry pool, the sulfur dioxide mass fraction of the circular bubbler is lower than that of the square bubbler. This is because when the circular bubbler bubbles, it increases the gas holdup distribution near the cross-section at a height of 0.1 meters in the slurry pool, reduces the flow velocity distribution of the absorption slurry, and is more conducive to the backmixing of the absorption slurry. Therefore, more sulfur dioxide enters the absorption slurry for mass transfer reaction, which is conducive to the absorption of sulfur dioxide. In addition, since the gas holdup and Bin-3 bubble number density distribution of the circular bubbler reach a uniform and stable state more quickly, it is also more conducive to the sulfur dioxide mass fraction reaching a uniform and stable state in a shorter period, significantly reducing the sulfur dioxide mass fraction in a short time, which is beneficial to reducing the start-up time of the newly built or renovated wet flue gas desulfurization system in engineering applications and improving safety and stability. The sulfur dioxide signal of the circular bubbler at the outlet of the slurry pool fluctuates less after 180 seconds, while the square bubbler gradually reaches a relatively stable state after 240 seconds. The sulfur dioxide absorption rate corresponding to the circular bubbler is higher than that corresponding to the square bubbler.

[0086] As Figure 4 shown, this embodiment also preferably uses CFD simulation to simulate the performance of an actual operating flue gas desulfurization system to illustrate the effectiveness of CFD simulation. By comparing the simulated values with the measured values, it can be seen that when the inlet depth of the absorption slurry in the scattering tube is sufficient, the sulfur dioxide concentration at the outlet during the desulfurization process of the actual wet flue gas desulfurization system oscillates slightly around the sulfur dioxide concentration at the outlet of the wet flue gas desulfurization system reflected by the CFD simulation. From this derivation, it can be seen that the CFD simulation method is sufficient to meet the accurate reproduction requirements of the desulfurization process of the wet flue gas desulfurization system under the determined boundary conditions, and thus can be used for the stability analysis of the desulfurization process of the target wet flue gas desulfurization system.

[0087] S3. After obtaining the complete operation data of the target wet flue gas desulfurization system through step S2 or step S1, extract the physical model of the target wet flue gas desulfurization system. Simplify the equipment that accommodates the flue gas and the absorption slurry for the desulfurization process into the form of a wet flue gas desulfurization tower, and simplify the equipment that transports the materials required for the desulfurization process to the wet flue gas desulfurization tower into the form of a slurry pump flow control system. Connect the slurry pump flow control system and the wet flue gas desulfurization tower. The slurry pump flow control system is used to pump sufficient absorption slurry or flue gas for the desulfurization process into the wet flue gas desulfurization tower, and at the same time pump out part of the absorption slurry or flue gas that has undergone the desulfurization process from the wet flue gas desulfurization tower. The wet flue gas desulfurization tower is used to accommodate the absorption slurry to desulfurize the flue gas. After the flue gas enters the interior of the wet flue gas desulfurization tower, it contacts the absorption slurry for desulfurization and then is discharged from the wet flue gas desulfurization tower.

[0088] In a wet desulfurization system composed of a slurry pump flow control system and a wet desulfurization tower, based on the obtained complete operation data, it can be known that the changes in flue gas sulfur dioxide concentration, flue gas temperature, and pH value of the absorption slurry are affected by the slurry pump flow control system. Therefore, the desulfurization process of the wet desulfurization tower can be regulated through the slurry pump flow control system;

[0089] The slurry pump flow control system is specifically composed of a frequency converter, a motor, and a circulating pump. The input port of the frequency converter is connected to the external alternating current. Then, the alternating current is filtered, inverted, and rectified in the frequency converter to form a direct current with adjustable voltage and frequency. Then, the direct current is loaded onto the motor at the motor phase port of the frequency converter as the working power supply of the motor. The frequency converter is used to control and adjust the working power supply of the motor operation. In this embodiment, it is preferably that the frequency converter adopts a variable frequency speed regulation PID control algorithm when controlling the motor. The motor is connected to the circulating pump, and the motor is used to drive the circulating pump to perform mechanical movement of pumping materials into or out of the wet desulfurization tower. The circulating pump is connected to the wet desulfurization tower, and the circulating pump is used to pump materials into or out of the wet desulfurization tower, so as to control the desulfurization effect of the flue gas by adjusting the amount of flue gas and absorption slurry in the wet desulfurization tower;

[0090] The wet desulfurization tower is specifically composed of a bubble reactor and a scattering plate. The scattering plate is arranged at the bottom of the bubble reactor. Among them, the scattering plate is used to introduce the flue gas into the bubble reactor, and the bubble reactor is used to accommodate the absorption slurry for the desulfurization process. The bubble reactor is connected to the circulating pump. The settings of the scattering plate and the bubble reactor have an impact on the stability of the desulfurization process;

[0091] In addition, in most cases, the gas-liquid flow and sulfur dioxide mass transfer reaction during the desulfurization process of the wet desulfurization tower change significantly more violently in the bubble column type than in the spray column type. Due to the more complex structure inside the bubble column, many disordered eddies are generated in the gas-liquid two-phase in the bubble column, and the time taken for the gas-liquid flow and sulfur dioxide mass transfer reaction in the bubble column to reach a stable state is longer than that of the spray column. In addition, when the desulfurized flue gas is discharged in the bubble column, the mass fraction of sulfur dioxide fluctuates violently during the whole process, presenting a discrete random signal. Therefore, it is suitable to further analyze various parameters of the wet desulfurization system in the time-frequency domain. The time-frequency domain analysis of the wet desulfurization system includes two types: using time series for stability analysis and using frequency signals for frequency structure analysis. The stability analysis is to judge the stability of the desulfurization process by whether parameters such as the mean, variance, or covariance of the time series are prone to significant changes. The frequency structure analysis is to convert the time domain data through Fourier transform into harmonic components to obtain important parameters such as amplitude, phase, power, and energy;

[0092] S4. On the basis of the physical model extraction of the wet flue gas desulfurization system completed in step S3, construct the transfer function of the slurry pump flow control system. The specific process is as follows:

[0093] S41. Taking the voltage at the input port of the frequency converter as the input and the voltage at the motor phase port of the frequency converter as the output, construct the mathematical model of the frequency converter The formula is as follows:

[0094]

[0095] Among them, K int represents the voltage frequency coefficient at the input port of the frequency converter, K f represents the voltage frequency coefficient at the motor phase port of the frequency converter, and s represents the complex frequency of the Laplace transform;

[0096] S42. Regarding the motor as consisting of two simplified links, mechanical and electrical, construct the mathematical model of the motor The formula is as follows:

[0097]

[0098] Among them, K M represents the motor gain coefficient, T L represents the mechanical time constant, T S represents the electrical time constant. In this embodiment, it is preferably that the value of K M is 1. In other embodiments, the value of K M can be adjusted according to the actual situation of the wet flue gas desulfurization system;

[0099] S43. According to the principle that the output of the circulation pump is proportional to the actual rotational speed of the motor, construct the mathematical model of the circulation pump as follows:

[0100]

[0101] Among them, Q1(S) represents the rated flow of the circulation pump, n1(s) represents the rated flow velocity of the circulation pump, and k a represents the ratio of the rated flow to the rated flow velocity;

[0102] S44. Combining the mathematical models of the frequency converter, the motor, and the circulation pump respectively, according to the constant pressure ratio method, the transfer function G(s) formula of the entire slurry pump flow control system is obtained as follows:

[0103]

[0104] S5. On the basis of constructing the transfer function G(s) of the slurry pump flow control system in step S4, the three complete operation data of the obtained target wet flue gas desulfurization system within the set time duration are respectively used in the transfer function G(s), and the time-frequency domain analysis is carried out on the transfer functions G(s) corresponding to the flue gas sulfur dioxide concentration, flue gas temperature, and absorption slurry pH value respectively. The stability of the wet flue gas desulfurization process is analyzed by using the Bode diagram corresponding to the transfer function, and according to the trend of the change of its stability, the value ranges of the three parameters of the flue gas sulfur dioxide concentration, flue gas temperature, and absorption slurry pH value under the condition of meeting the stability condition are determined. The specific process is as follows:

[0105] S51. The data when the corresponding operation data are input into the target wet flue gas desulfurization system are respectively used as the input data of the transfer function G(s), different orders of the transfer function G(s) are obtained therefrom, and then the Matlab2016 software is used to program and simulate the calculation of the transfer function G(s). The function tfest is solved for different orders, and then the solution results are subjected to error fitting with the data when the corresponding operation data are output from the target wet flue gas desulfurization system, and the order with the highest fitting degree is determined. At this time, the transfer function is optimal;

[0106] S52. After obtaining the optimal transfer function, time-frequency domain analysis is carried out on the optimal transfer function, and then the Bode diagram corresponding to the current transfer function is obtained. Whether the gain margin and phase margin corresponding to the amplitude-frequency characteristic and phase-frequency characteristic of the transfer function are both greater than zero is used as the stability condition to judge the stability of the target wet flue gas desulfurization system. If the stability condition is met, it indicates that the desulfurization process of the target wet flue gas desulfurization system is stable at this time. If the stability condition is not met, it indicates that the desulfurization process of the target wet flue gas desulfurization system is unstable at this time. The gain margin and phase margin can also be obtained from the Bode diagram. The phase margin being greater than zero means that the phase angle is at a position above 180 degrees;

[0107] S53. The three operation data when the stability condition is met are set as the preferred value range;

[0108] In this embodiment, it is preferably analyzed that the absorption slurry pH value, flue gas sulfur dioxide concentration, and flue gas temperature are respectively used as inputs to examine the changes of the corresponding three transfer functions in the time-frequency domain, and then the corresponding gain margin and phase margin are obtained from the Bode diagram obtained from the optimal transfer function, and the influence of different operation data settings on the stability of the desulfurization process is examined, so as to determine in which value range the operation data setting of the target wet flue gas desulfurization system is more optimal, and this more optimal value range is used as the preliminary optimization result;

[0109] This embodiment analyzes the stability of the desulfurization process of the desulfurization system of the bubbling tower type in the foregoing CFD simulation. The specification is set as The input flue gas volume is 10,000 - 60,000 m3 / h, the input flue gas sulfur dioxide concentration is 200 - 2000 mg / m 3 , after obtaining the complete operation data, the pH value of the absorption slurry and the flue gas temperature are calculated for stability analysis as follows:

[0110] (1) During the desulfurization process of the target wet flue gas desulfurization system, the variation of the pH value of the absorption slurry with time is as Figure 13 shown; according to Figure 13 the variation of the pH value of the absorption slurry shown, through programming simulation calculation, the optimal transfer function form representing the pH value of the absorption slurry is finally determined as shown in the following formula:

[0111]

[0112] The transfer function is analyzed in the time - frequency domain and the corresponding Bode plot is obtained. The above formula is transformed to get the following formula:

[0113]

[0114] Let S = jw, then the transfer function of the pH value of the absorption slurry can be regarded as consisting of the following one proportional link, one first - order differential link, and five inertia links;

[0115] Proportional link:

[0116]

[0117] Its logarithmic amplitude - frequency characteristic is:

[0118]

[0119] Its logarithmic phase - frequency characteristic is:

[0120]

[0121] First - order differential link:

[0122]

[0123] Its logarithmic amplitude - frequency characteristic is:

[0124]

[0125] Its logarithmic phase - frequency characteristic is:

[0126]

[0127] The first inertia link:

[0128]

[0129] Its logarithmic amplitude - frequency characteristic is:

[0130]

[0131] Its logarithmic phase-frequency characteristic is:

[0132]

[0133] The second inertia link:

[0134]

[0135] Its logarithmic amplitude-frequency characteristic is:

[0136]

[0137] Its logarithmic phase-frequency characteristic is:

[0138]

[0139] The third inertia link:

[0140]

[0141] Its logarithmic amplitude-frequency characteristic is:

[0142]

[0143] Its logarithmic phase-frequency characteristic is:

[0144]

[0145] The fourth inertia link:

[0146]

[0147] Its logarithmic amplitude-frequency characteristic is:

[0148]

[0149] Its logarithmic phase-frequency characteristic is:

[0150]

[0151] The fifth inertia link:

[0152]

[0153] Its logarithmic amplitude-frequency characteristic is:

[0154]

[0155] Its logarithmic phase-frequency characteristic is:

[0156]

[0157] At this time, the overall logarithmic amplitude-frequency characteristic of the transfer function of the absorption slurry pH value is as follows:

[0158]

[0159] The overall logarithmic phase-frequency characteristic of the transfer function of the absorption slurry pH value is as follows:

[0160]

[0161] Let Solve for where ω c is the shear frequency, ω g is the phase crossover frequency, is the threshold value of the overall logarithmic amplitude-frequency characteristic and the overall logarithmic phase-frequency characteristic of the transfer function of the absorption slurry pH value when the corresponding amplitude margin and phase margin meet the stability conditions;

[0162] Through the shear frequency ω c The amplitude margin γ can be obtained as follows:

[0163]

[0164] Through the phase crossover frequency ω g The phase margin K g (dB) can be obtained as follows:

[0165]

[0166] Combined with Figure 14 and Figure 15 As can be seen, when the phase margin and the amplitude margin are both greater than zero, the desulfurization process of the target wet flue gas desulfurization system has the best stability. At this time, the frequency characteristic G(jω) of the optimal transfer function of the absorption slurry pH value is as shown in the following formula:

[0167]

[0168] Obtain the operating data that meet the condition that the phase margin and the amplitude margin are both greater than zero;

[0169] (2) Set that during the desulfurization process of the target wet flue gas desulfurization system, the change of its flue gas temperature with time is as Figure 16 shown. Through the same idea as in the previous (1), the Bode diagram corresponding to the transfer function of the flue gas temperature can be obtained as Figure 17 and Figure 18 shown, so as to obtain the situation when the flue gas temperature meets the stability conditions according to the Bode diagram;

[0170] S6. After obtaining the preferred value range representing stability, conduct an economic cost analysis of the entire desulfurization process of the target wet desulfurization system. The specific process is as follows:

[0171] First, obtain the economic cost of the equipment construction of the target wet desulfurization system;

[0172] Then, obtain the economic cost of consuming unit energy and the economic cost of the absorption slurry corresponding to consuming unit energy when the operating data of the target wet desulfurization system is within the preferred value range;

[0173] Next, integrate the economic cost of the equipment construction of the target wet desulfurization system, the economic cost of consuming unit energy, and the economic cost of the absorption slurry corresponding to consuming unit energy;

[0174] Finally, examine which subset of the operating data value range in the preferred operating data value range of the target wet desulfurization system has a lower integrated economic cost, and use this subset of the operating data value range with a lower economic cost as the final optimization result, and deduce the specific operating settings of the target wet desulfurization system from the optimization result.

[0175] In this embodiment, through the analysis of the stability and economic cost of the wet desulfurization system, the main adjustment directions for the actual wet desulfurization system are obtained as follows:

[0176] To avoid frequent manual adjustment, and considering the probability of maintenance, replacement cost, corrosion and wear cost, the immersion depth of the pipe material of the scattering plate in the absorption slurry; when the inlet gas volume flow fluctuates within a certain range, the mass fraction of calcium compounds in the absorption slurry can be controlled to exceed a certain threshold to maintain theoretically stable and efficient desulfurization; the height level of the absorption slurry must be set below a certain height to keep the system pressure change lower than the ideal situation; the larger the liquid-gas ratio in the bubble reactor, the larger the liquid film side surface area, the larger the mass transfer area between the flue gas and the slurry, and the higher the sulfur dioxide absorption rate. Too low a liquid-gas ratio is not conducive to sulfur dioxide absorption, and too large a liquid-gas ratio will lead to an increase in economic cost.

[0177] Compared with the prior art, the beneficial effects of this embodiment are as follows:

[0178] Compared with the situation where there are significant differences in the completeness of the measured operation data of wet flue gas desulfurization in the prior art, the use of comprehensive analysis to analyze the removal performance, stability, and economy of wet flue gas desulfurization can more comprehensively and accurately give the optimization strategy for the wet flue gas desulfurization system; compared with the problem that the stability judgment can be effectively carried out only by measuring the operation data of the wet flue gas desulfurization system through the single-factor control variable method in the prior art, this embodiment does not need to consider the limitation of the single-factor control variable method measurement. By constructing a transfer function for time-frequency domain analysis, the stability of the desulfurization process of the wet flue gas desulfurization system can still be comprehensively analyzed and judged when the operation data is incomplete; compared with the prior art that only uses on-site measured values for analysis or separate CFD simulation, this embodiment combines CFD simulation with on-site measurement and uses the transfer function in combination with the Bode diagram analysis method to be able to perform stability analysis in the time-frequency domain for the desulfurization process, which helps to optimize according to the analyzed operation performance before the wet flue gas desulfurization system is technically modified, avoiding a large number of ineffective technical modifications; the prior art only considered the influence of the desulfurization process itself on equipment optimization alone, lacked the consideration of the optimization problem of the wet flue gas desulfurization system from multiple perspectives, and ignored the relationship between the technical modification of the wet flue gas desulfurization system or the technical modification needs to consider the operation economic cost and the stability of the desulfurization process. This embodiment further conducts an operation economic cost analysis after the stability analysis to achieve the optimization of the technical modification plan for the wet flue gas desulfurization system from multiple perspectives.

[0179] The above embodiments are preferred embodiments of the present invention, but the embodiments of the present invention are not limited to the above embodiments. Any other changes, modifications, substitutions, combinations, and simplifications made without departing from the spirit and principle of the present invention shall be equivalent replacement methods and are all included in the protection scope of the present invention.

Claims

1. An optimization method for a wet desulfurization system, characterized in that, The steps are as follows: Obtain the three operating parameters of the flue gas sulfur dioxide concentration, flue gas temperature, and absorption slurry pH value during the desulfurization process of the target wet flue gas desulfurization system to be optimized, and evaluate whether these three operating parameters are complete; The specific process of obtaining the operating parameters includes: For the target wet flue gas desulfurization system to be optimized, through the set sensor assembly, obtain the data of its operating parameters when entering and leaving the target wet flue gas desulfurization system without controlling a certain variable, and evaluate whether the obtained operating parameters are complete; Whether the operating parameters are complete means whether all the data of the changes in the three parameters of flue gas sulfur dioxide concentration, flue gas temperature, and absorption slurry pH value within the set monitoring duration can be obtained. If all can be obtained, it is complete; otherwise, it is incomplete; In the case where the operating parameters of the target wet flue gas desulfurization system are incomplete, perform CFD simulation on the desulfurization process of the target wet flue gas desulfurization system to obtain complete operating parameters of flue gas sulfur dioxide concentration, flue gas temperature, and absorption slurry pH value; The specific process of performing CFD simulation on the desulfurization process of the target wet flue gas desulfurization system includes: Perform CFD simulation on the desulfurization process of the target wet flue gas desulfurization system in Ansys fluent 16 software; According to the CFD simulation of the gas-liquid flow, heat transfer, and mass transfer processes in the target wet flue gas desulfurization system, record the changes in the hydrodynamic characteristics of the gas-liquid flow of the corresponding flue gas and absorption slurry, flue gas sulfur dioxide concentration, and flue gas temperature during the period from the initial state to the stable state; According to the process of hydrodynamic characteristics, sulfur dioxide concentration, and temperature change, preliminarily obtain the simulation fluctuation signals of the flue gas sulfur dioxide concentration, flue gas temperature, and absorption slurry pH value during the desulfurization process within the set duration of the simulated desulfurization process of the target wet flue gas desulfurization system, and use the simulation fluctuation signals as the complete operating parameters of the flue gas sulfur dioxide concentration, flue gas temperature, and absorption slurry pH value; When the operating parameters of the target wet flue gas desulfurization system are complete, or complete operating parameters are obtained through CFD simulation, extract the physical model of the target wet flue gas desulfurization system, and the target wet flue gas desulfurization system is simplified to be composed of a wet desulfurization tower and a slurry pump flow control system; The specific process of extracting the physical model of the target wet flue gas desulfurization system includes: Simplify the equipment for accommodating flue gas and absorption slurry for desulfurization process into the form of a wet desulfurization tower, and simplify the equipment for transporting the materials required for the desulfurization process to the wet desulfurization tower into the form of a slurry pump flow control system; Connect the slurry pump flow control system and the wet desulfurization tower to each other; The slurry pump flow control system is composed of an inverter, a motor, and a circulation pump; The inverter is connected to the motor and is used to provide working power to the motor; The motor is connected to the circulation pump, and the motor is used to drive the circulation pump to pump materials into or out of the wet desulfurization tower; The circulation pump is connected to the wet desulfurization tower, and the circulation pump is used to pump materials into or out of the interior of the wet desulfurization tower; Construct the transfer function of the slurry pump flow control system; use the operating parameters to solve the transfer function in Matlab software to obtain the optimal transfer function; Conduct time-frequency domain analysis on the optimal transfer function, then obtain the Bode plot from it, and analyze the stability of the target wet flue gas desulfurization system during the desulfurization process based on the time-frequency domain analysis and the Bode plot, obtain the value range of the operating parameters during stable desulfurization, and take the value range during stable desulfurization as the result of optimization.

2. The optimization method of the wet desulfurization system according to claim 1, characterized in that, The specific process of constructing the transfer function of the slurry pump flow control system includes: Build the mathematical model of the frequency converter The formula is as follows: Among them, K int represents the voltage-frequency coefficient of the input port of the frequency converter, and K f represents the voltage-frequency coefficient of the motor phase port of the frequency converter, and s represents the complex frequency of the Laplace transform; Build the mathematical model of the motor The formula is as follows: Among them, K M represents the motor gain coefficient, T L represents the mechanical time constant, T S represents the electrical time constant; Build a mathematical model of the circulation pump As follows: Among them, Q1(S) represents the rated flow rate of the circulation pump, n1(s) represents the rated flow velocity of the circulation pump, and k a represents the ratio of the rated flow rate to the rated flow velocity; Integrate the respective mathematical models of the frequency converter, motor, and circulation pump to obtain the formula for the transfer function G(s) of the slurry pump flow control system as follows:

3. The optimization method of the wet desulfurization system according to claim 2, characterized in that, The specific process of using the operating parameters to solve the transfer function to obtain the optimal transfer function includes: Take the data of the operating parameters when input into the target wet flue gas desulfurization system as the input data of the transfer function G(s), obtain different orders of the transfer function G(s) from it, then use Matlab software to program and simulate the calculation of the transfer function G(s), solve the function tfest for different orders, and then perform error fitting on the solution results and the data of the operating parameters when output from the target wet flue gas desulfurization system to determine the order with the highest fitting degree. At this time, the transfer function is optimal.

4. The optimization method of the wet desulfurization system according to claim 3, characterized in that, The specific process of analyzing the stability of the desulfurization process to obtain the preferred value range of the operating parameters includes: Conduct time-frequency domain analysis on the optimal transfer function, then obtain the Bode plot corresponding to the current transfer function, and judge the stability of the target wet flue gas desulfurization system through the stability condition of whether the amplitude margin and phase angle margin corresponding to the amplitude-frequency characteristic and phase-frequency characteristic of the transfer function are both greater than zero; if the stability condition is met, it indicates that the desulfurization process of the target wet flue gas desulfurization system is stable at this time; if the stability condition is not met, it indicates that the desulfurization process of the target wet flue gas desulfurization system is unstable at this time; Set the operating data when the stability condition is met as the preferred value range.

5. The optimization method of the wet desulfurization system according to claim 4, characterized in that, The steps of the optimization method for the wet flue gas desulfurization system also include conducting an economic cost analysis of the desulfurization process. The specific process includes: Obtain the economic cost of the equipment construction of the target wet flue gas desulfurization system; Obtain the economic cost per unit energy consumption and the economic cost of the absorption slurry corresponding to per unit energy consumption in the preferred value range of the operating parameters in the target wet flue gas desulfurization system; Integrate the economic cost of the equipment construction of the target wet flue gas desulfurization system, the economic cost per unit energy consumption, and the economic cost of the absorption slurry corresponding to per unit energy consumption, and take the subset of the value range of the operating parameters with lower integrated economic cost as the final optimization result.

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