A desulfurization system operation optimization method and system based on Lasso algorithm

Abstract

The present invention discloses a desulfurization system operation optimization method and system based on a Lasso algorithm. The desulfurization system includes several slurry circulation pumps. The method comprises: constructing a desulfurization efficiency model based on the Lasso algorithm, the desulfurization efficiency model is used to obtain the operating number of the slurry circulation pumps by obtaining the SO2 concentration and pH value of the desulfurization outlet; collecting the SO2 concentration and pH value of the desulfurization outlet, and obtaining the optimal operating number of the slurry circulation pumps through the Lasso algorithm; obtaining the minimum power consumption by adjusting the pH value and / or the operating number of the slurry circulation pumps based on the limit value of the SO2 concentration; and controlling the desulfurization system to operate based on the minimum power consumption. The present invention adopts the Lasso algorithm to model the desulfurization system, provides a guarantee for the accuracy of the desulfurization system operation optimization, and provides adjustable parameter setting values with low material consumption and energy consumption according to different working conditions, thereby realizing low-cost and high-efficiency control of flue gas pollutant removal.

Description

Technical Field

[0001] The present invention relates to the technical field of power plant operation optimization, and in particular to a desulfurization system operation optimization method and system based on a Lasso algorithm. Background Art

[0002] Against the backdrop of the development goals of "carbon peak and carbon neutrality," my country's energy structure has begun to shift toward green and low-carbon development. However, at present, my country's power structure is still dominated by coal-fired thermal power units. With the decrease in the output of high-quality coal and the increase in its price, coal-fired power plants will use some low-quality coal to ensure economic benefits. Low-quality coal not only has a low calorific value but also has a high sulfur content. Therefore, controlling SO2 emissions from coal-fired units is particularly important. The purpose of flue gas desulfurization equipment is to remove pollutants from flue gas within the desulfurization tower through certain chemical methods. Desulfurization efficiency is usually used in desulfurization systems to evaluate the desulfurization capacity of the desulfurization system. In actual operation, in order to ensure that the outlet concentration of the desulfurization system meets the standards, operators often increase the number of slurry circulation pumps in operation, resulting in increased power consumption. Therefore, it is particularly important to ensure that the desulfurization system operates economically and stably while ensuring that the outlet concentration of the desulfurization system meets the standards. If a certain modeling method can be used to obtain a correlation model between desulfurization efficiency, pH value, and the number of slurry circulation pumps in operation, and based on the model, the optimal number of slurry circulation pumps in operation under the current operating conditions and the optimal pH value corresponding to the current number of slurry circulation pumps are determined, then while greatly improving the control quality of the desulfurization system, it also plays a role in energy conservation and consumption reduction, which can further improve the efficiency of the power plant. Therefore, there is an urgent need for a desulfurization system operation optimization method and system based on the Lasso algorithm to meet existing technical needs. Summary of the Invention

[0003] In view of the problems of unscientific operation and significant waste of material and energy consumption in the desulfurization system, the purpose of the present invention is to propose a desulfurization system operation optimization method and system based on the Lasso algorithm. By establishing a desulfurization efficiency model, the operation of the desulfurization system can be accurately and effectively optimized, thereby saving electricity and material consumption and improving the efficiency of the power plant.

[0004] In order to achieve the above technical objectives, the present application provides a desulfurization system operation optimization method based on the Lasso algorithm, wherein the desulfurization system includes several slurry circulation pumps; the method includes the following steps:

[0005] A desulfurization efficiency model is constructed based on the Lasso algorithm. The desulfurization efficiency model is used to obtain the number of slurry circulation pumps in operation by obtaining the SO2 concentration and pH value at the desulfurization outlet.

[0006] Collect the SO2 concentration and pH value at the desulfurization outlet and use the Lasso algorithm to obtain the optimal operating number of the slurry circulation pump;

[0007] Based on the limit of SO2 concentration, the lowest power consumption is obtained by adjusting the pH value and / or the number of slurry circulation pumps running;

[0008] Based on the minimum power consumption, the desulfurization system is controlled to operate.

[0009] Preferably, in the process of constructing the desulfurization efficiency model, based on the Lasso algorithm, the operating number of the slurry circulation pump is generated by obtaining the SO2 concentration and pH value at the desulfurization outlet, the unit load, the inlet flue gas flow, the circulating slurry amount, and the inlet SO2 concentration.

[0010] Preferably, in the process of constructing the desulfurization efficiency model, the desulfurization efficiency model is expressed as:

[0011]

[0012] Among them, Y is the SO2 concentration at the desulfurization outlet, x1 is the unit load; x2 is the inlet flue gas flow; x3 is the circulating slurry volume; x4 is the inlet SO2 concentration; and x5 is the pH value.

[0013] Preferably, in the process of adjusting the pH value, the pH value is adjusted in the range of 5.2-5.7.

[0014] Preferably, in the process of obtaining the power consumption, the power consumption is generated by collecting the unit load, inlet flue gas flow rate, and inlet SO2 concentration based on the desulfurization efficiency model.

[0015] Preferably, in the process of obtaining the minimum power consumption, the pH value is increased, and it is determined whether the desulfurization efficiency is met after stopping one slurry circulation pump. If so, one slurry circulation pump is stopped to save power consumption. If not, the current state is maintained, indicating that the operating conditions are now the optimal conditions.

[0016] Preferably, when the desulfurization efficiency is not met after shutting down one slurry circulation pump, the number of circulating pumps in operation is maintained, and it is determined whether the desulfurization efficiency is met after appropriately lowering the pH value. If so, the pH value is lowered to save limestone costs; if not, the current state is maintained, indicating that the operating conditions are now the optimal conditions.

[0017] The present invention provides a desulfurization system operation optimization system based on the Lasso algorithm, comprising:

[0018] Data acquisition module, used to collect SO2 concentration and pH value at the desulfurization outlet;

[0019] The data processing module is used to build a desulfurization efficiency model based on the Lasso algorithm, and to generate the operating number of the slurry circulation pump by obtaining the SO2 concentration and pH value at the desulfurization outlet. The optimal operating number of the slurry circulation pump is obtained through the Lasso algorithm;

[0020] The optimization control module is used to obtain the minimum power consumption by adjusting the pH value and / or the number of slurry circulation pump operations based on the limit value of SO2 concentration, and control the desulfurization system to operate based on the minimum power consumption.

[0021] Preferably, the data processing module includes:

[0022] The power consumption calculation unit is used to generate power consumption based on the desulfurization efficiency model by collecting unit load, inlet flue gas flow, and inlet SO2 concentration;

[0023] The operation quantity calculation unit is used to generate the operation quantity of the slurry circulation pump based on the Lasso algorithm by obtaining the SO2 concentration and pH value at the desulfurization outlet, the unit load, the inlet flue gas flow, the circulating slurry volume, and the inlet SO2 concentration.

[0024] Preferably, the optimization control module includes:

[0025] The first optimization unit is used to increase the pH value and determine whether the desulfurization efficiency is met after stopping one slurry circulation pump. If so, the slurry circulation pump is stopped to save power consumption. If not, the current state is maintained, indicating that the current working condition is the optimal working condition.

[0026] The second optimization unit is used to determine whether the desulfurization efficiency can be met after the pH value is appropriately lowered while maintaining the number of circulating pumps in operation. If so, the pH value is lowered to save limestone costs; if not, the current state is maintained, indicating that the operating conditions are now the optimal conditions.

[0027] The present invention discloses the following technical effects:

[0028] 1. Use the Lasso algorithm to model the desulfurization system to ensure the accuracy of desulfurization system operation optimization;

[0029] 2. The optimization strategy proposed by the method of the present invention based on economic analysis is combined with the experience of actual operation, is applicable to the actual site, and is easy for operators to operate;

[0030] 3. The optimal target value operation rule base established by the method of the present invention provides adjustable parameter setting values with low material and energy consumption according to different working conditions, thereby achieving low-cost and high-efficiency control of flue gas pollutant removal. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0032] Figure 1 is the proportion of various costs of the desulfurization system described in the present invention;

[0033] Figure 2 It is a flow chart of the method described in the present invention. DETAILED DESCRIPTION

[0034] In order to make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments. The components of the embodiments of the present application generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application for which protection is claimed, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work are within the scope of protection of this application.

[0035] like Figure 1-2 As shown, the present invention provides a desulfurization system operation optimization method based on the Lasso algorithm, wherein the desulfurization system includes several slurry circulation pumps; the method includes the following steps:

[0036] A desulfurization efficiency model is constructed based on the Lasso algorithm. The desulfurization efficiency model is used to obtain the optimal operating number of the slurry circulation pump by obtaining the SO2 concentration and pH value at the desulfurization outlet;

[0037] Collect the SO2 concentration and pH value at the desulfurization outlet and use the Lasso algorithm to obtain the optimal operating number of the slurry circulation pump;

[0038] Based on the limit of SO2 concentration, the lowest power consumption is obtained by adjusting the pH value and / or the number of slurry circulation pumps running;

[0039] Based on the minimum power consumption, the desulfurization system is controlled to operate.

[0040] Further preferably, in the process of constructing the desulfurization efficiency model, based on the Lasso algorithm, the present invention generates the operating number of the slurry circulation pump by obtaining the SO2 concentration and pH value of the desulfurization outlet, the unit load, the inlet flue gas flow, the circulating slurry amount, and the inlet SO2 concentration.

[0041] Further preferably, in the process of constructing the desulfurization efficiency model of the present invention, the desulfurization efficiency model mentioned in the present invention is expressed as:

[0042]

[0043] Among them, Y is the SO2 concentration at the desulfurization outlet, x1 is the unit load; x2 is the inlet flue gas flow; x3 is the circulating slurry volume; x4 is the inlet SO2 concentration; and x5 is the pH value.

[0044] Further preferably, in the process of adjusting the pH value of the present invention, the adjustment range of the pH value mentioned in the present invention is 5.2-5.7.

[0045] Further preferably, in the process of obtaining power consumption, the present invention generates power consumption by collecting unit load, inlet flue gas flow, and inlet SO2 concentration based on the desulfurization efficiency model.

[0046] Further preferably, in the process of obtaining the minimum power consumption, the present invention determines whether the desulfurization efficiency is met after stopping a slurry circulation pump by increasing the pH value. If so, the slurry circulation pump is stopped to save power consumption. If not, the current state is maintained, indicating that the operating conditions at this time are the optimal conditions.

[0047] Further preferably, when the desulfurization efficiency is not met after shutting down a slurry circulation pump, the present invention determines whether the desulfurization efficiency is met after appropriately lowering the pH value while maintaining the number of circulating pumps in operation. If so, the pH value is lowered to save limestone costs; if not, the current state is maintained, indicating that the operating conditions are now the optimal conditions.

[0048] The present invention provides a desulfurization system operation optimization system based on the Lasso algorithm, comprising:

[0049] Data acquisition module, used to collect SO2 concentration and pH value at the desulfurization outlet;

[0050] The data processing module is used to build a desulfurization efficiency model based on the Lasso algorithm. By obtaining the SO2 concentration and pH value at the desulfurization outlet, the operating number of the slurry circulation pump is generated. The optimal operating number of the slurry circulation pump and the power consumption of the desulfurization system are obtained through the Lasso algorithm.

[0051] The optimization control module is used to obtain the minimum power consumption by adjusting the pH value and / or the number of slurry circulation pump operations based on the limit value of SO2 concentration, and control the desulfurization system to operate based on the minimum power consumption.

[0052] Further preferably, the data processing module mentioned in the present invention includes:

[0053] The power consumption calculation unit is used to generate power consumption based on the desulfurization efficiency model by collecting unit load, inlet flue gas flow, and inlet SO2 concentration;

[0054] The operation quantity calculation unit is used to generate the operation quantity of the slurry circulation pump based on the Lasso algorithm by obtaining the SO2 concentration and pH value at the desulfurization outlet, the unit load, the inlet flue gas flow, the circulating slurry volume, and the inlet SO2 concentration.

[0055] Further preferably, the optimization control module mentioned in the present invention includes:

[0056] The first optimization unit is used to increase the pH value and determine whether the desulfurization efficiency is met after stopping one slurry circulation pump. If so, the slurry circulation pump is stopped to save power consumption. If not, the current state is maintained, indicating that the current working condition is the optimal working condition.

[0057] The second optimization unit is used to determine whether the desulfurization efficiency can be met after the pH value is appropriately lowered while maintaining the number of circulating pumps in operation. If so, the pH value is lowered to save limestone costs; if not, the current state is maintained, indicating that the operating conditions are now the optimal conditions.

[0058] The present invention establishes a desulfurization efficiency model through the Lasso algorithm. Based on the desulfurization efficiency model, the power consumption of the slurry circulation pump is used as the optimization target, and the SO2 concentration and pH value at the desulfurization outlet are used as constraints. An economic operation rule library of the desulfurization system is established to realize online operation optimization guidance of the desulfurization system.

[0059] The present invention provides a desulfurization system operation optimization method based on the Lasso algorithm, comprising the following steps:

[0060] 1. Lasso regression algorithm:

[0061] The Lasso regression algorithm (Least absolute shrinkage and selection operator) is a compression estimation algorithm. The basic idea is to minimize the residual under the constraint that the sum of the absolute values of the regression coefficients is less than a constant, thereby obtaining an interpretable model. The specific calculation formula is as follows

[0062]

[0063] Where X=(x1,x2,…,x n ) T It is the data matrix, that is, the input of the model after variable screening, Y = (y1, y2, ..., y n ) T It is a column vector consisting of labels, i.e., the output of the prediction model, and w is the coefficient matrix.

[0064] To solve w, we use the coordinate descent method to iterate and solve the minimum value of the function in a heuristic way. First, we set the initial value w (0), the number in the brackets indicates the number of iterations. In the kth iteration, the iteration formula of the n dimensions of w is as follows:

[0065]

[0066]

[0067] …

[0068]

[0069] If w (k) and w (k-1) The changes in each dimension are small enough, then w (k) If yes, it is what we want, otherwise we continue to the next iteration.

[0070] Assuming the desulfurization efficiency model of the desulfurization system is a linear model, its specific expression can be written as

[0071] Y=λ1*x1+λ2*x2+...+λ n *x n +β (5)

[0072] Where Y is the outlet SO2 concentration, X=(x1,x2,…,x n ) is the selected parameter, λ is the regression coefficient, and β is the overall error. In the regression model, in order to ensure the fitting effect, the loss function RRS is generally required to be minimized. Let the loss function be

[0073]

[0074] Since the Lasso algorithm also belongs to the category of linear algorithms, fitting with a simple linear term will result in insufficient model complexity and insufficient prediction accuracy. In order to further improve the prediction accuracy, the present invention selects the optimal function form of each parameter instead. The final prediction model is:

[0075] Y=λ1*h(x1)+λ2*h(x2)+...+λ n *h(x n )+β (7)

[0076] Where h(x) is the optimal function expression of each parameter, including the linear function h(x) = k*x + c, the quadratic polynomial function h(x) = a*x 2 +b*x+c, power function h(x)=a*x b wait.

[0077] 2. Establishment of desulfurization efficiency model:

[0078] Modeling study of desulfurization efficiency based on the theory of Lasso algorithm

[0079] 2.1 Selection of function form:

[0080] Assuming that each parameter is independent of each other, each parameter is fitted in a different function form. After comparison, the present invention adopts four structures of linear, quadratic polynomial, cubic polynomial, and power function for fitting. The optimal function form of each parameter is shown in Table 1.

[0081] Table 1

[0082]

[0083] 2.2. Establishment of desulfurization efficiency model:

[0084] The Lasso algorithm is used to train the filtered training samples to obtain the optimal coefficient combination λ of each parameter. The final prediction formula is obtained by combining the optimal function form of each parameter:

[0085]

[0086] In the formula, Y is the SO2 concentration at the desulfurization outlet, x1 is the unit load; x2 is the inlet flue gas flow rate; x3 is the circulating slurry volume; x4 is the inlet SO2 concentration; and x5 is the pH value.

[0087] 3. Desulfurization system operation optimization:

[0088] The operating parameters of the desulfurization system are optimized based on the desulfurization efficiency model and historical data.

[0089] 3.1 Establishment of optimization goals:

[0090] Desulfurization cost mainly consists of desulfurization electricity consumption cost, limestone cost and desulfurization water consumption cost. We use the actual operation data of the site for a whole year to calculate the desulfurization electricity consumption cost, limestone cost and desulfurization water consumption cost for each month. The results are as follows: Figure 1 As shown:

[0091] The range of changes and proportions of relevant costs are shown in Table 2:

[0092] Table 2

[0093]

[0094] As can be seen from the chart, among the various costs of the desulfurization system, the desulfurization electricity consumption cost accounts for the highest proportion and has the largest range of variation, so it has the largest room for optimization. The limestone cost is second, and the desulfurization water consumption cost accounts for the smallest proportion. The present invention optimizes according to the following principles:

[0095] (1) Ensure the safe operation of the desulfurization system;

[0096] (2) Ensure that pollutant emissions meet standards;

[0097] (3) Maintain pH within the range of 5.2-5.7;

[0098] (4) On the basis of satisfying the first three items, the principle is to minimize the overall cost of the desulfurization system.

[0099] 3.2 Operation condition optimization based on desulfurization efficiency model:

[0100] The present invention is based on the established desulfurization efficiency model and simulates actual operating conditions to meet the desulfurization efficiency and ensure that the pH value is within a safe range. According to the optimization principle with the circulation pump power consumption as the main optimization target, the specific optimization strategy of the present invention is as follows:

[0101] Establish a desulfurization efficiency model based on historical data;

[0102] Enter the current operating conditions (unit load, inlet flue gas flow, inlet SO2 concentration);

[0103] Appropriately increase the pH value and determine whether the desulfurization efficiency is met after stopping one slurry circulation pump;

[0104] If the requirement is met, one slurry circulation pump will be shut down to save electricity;

[0105] If not, maintain the number of circulating pumps in operation and determine whether the desulfurization efficiency can be met after appropriately lowering the pH value;

[0106] If it meets the requirement, the pH value is adjusted lower to save limestone cost;

[0107] If not satisfied, maintain the current state, indicating that the current working condition is the optimal working condition;

[0108] To better guide actual operation, we used unit load, flue gas flow, and inlet SO₂ concentration as the basis for operating condition classification. Based on historical data, we identified 500 target operating conditions. We then optimized these conditions using the optimization strategy presented in this paper to obtain the optimal set values for the controllable variables, which were then summarized and collated. Table 3 shows the optimal target value operating rule base for all operating conditions.

[0109] Table 3

[0110]

[0111]

[0112] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0113] In the description of the present invention, it should be understood that the terms "first" and "second" are used for descriptive purposes only and should not be understood to indicate or imply relative importance or implicitly specify the number of the technical features indicated. Therefore, a feature specified as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, "plurality" means two or more, unless otherwise specifically defined.

[0114] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

Claims

1. A desulfurization system operation optimization method based on Lasso algorithm, wherein the desulfurization system includes several slurry circulation pumps; characterized in that: The following steps are involved: Constructing a desulfurization efficiency model based on the Lasso algorithm, wherein the desulfurization efficiency model is used to obtain the optimal operating number of the slurry circulation pump by obtaining the SO2 concentration and pH value at the desulfurization outlet; Collecting the SO2 concentration and pH value of the desulfurization outlet, and obtaining the optimal operating number of the slurry circulation pump through the Lasso algorithm; Based on the limit of the SO2 concentration, the minimum power consumption is obtained by adjusting the pH value and / or the number of operations of the slurry circulation pump; Based on the minimum power consumption, controlling the desulfurization system to operate; In the process of constructing the desulfurization efficiency model, based on the Lasso algorithm, the operating number of the slurry circulation pump is generated by obtaining the SO2 concentration and pH value at the desulfurization outlet, the unit load, the inlet flue gas flow rate, the circulating slurry amount, and the inlet SO2 concentration; In the process of constructing the desulfurization efficiency model, the desulfurization efficiency model is expressed as: Among them, Y is the SO2 concentration at the desulfurization outlet, x1 is the unit load; x2 is the inlet flue gas flow; x3 is the circulating slurry volume; x4 is the inlet SO2 concentration; and x5 is the pH value.

2. The desulfurization system operation optimization method based on the Lasso algorithm according to claim 1, characterized in that: During the process of adjusting the pH value, the pH value is adjusted in a range of 5.2-5.

7.

3. The desulfurization system operation optimization method based on the Lasso algorithm according to claim 2, characterized in that: In the process of obtaining the power consumption, the power consumption is generated based on the desulfurization efficiency model by collecting the unit load, the inlet flue gas flow rate, and the inlet SO2 concentration.

4. The desulfurization system operation optimization method based on the Lasso algorithm according to claim 3 is characterized in that: In the process of obtaining the minimum power consumption, the pH value is increased, and it is determined whether the desulfurization efficiency is met after stopping one slurry circulation pump. If so, one slurry circulation pump is stopped to save power consumption. If not, the current state is maintained, indicating that the operating conditions are now the optimal conditions.

5. The desulfurization system operation optimization method based on the Lasso algorithm according to claim 4 is characterized in that: When the desulfurization efficiency is not met after shutting down one slurry circulation pump, the number of circulating pumps in operation is maintained to determine whether the desulfurization efficiency is met after appropriately lowering the pH value. If so, the pH value is lowered to save limestone costs; if not, the current state is maintained, indicating that the operating conditions are now optimal.

6. A desulfurization system operation optimization system based on Lasso algorithm, characterized in that: include: Data acquisition module, used to collect SO2 concentration and pH value at the desulfurization outlet; A data processing module is used to construct a desulfurization efficiency model based on the Lasso algorithm, and to generate the operating number of the slurry circulation pump by obtaining the SO2 concentration and pH value at the desulfurization outlet, wherein the optimal operating number of the slurry circulation pump and the power consumption of the desulfurization system are obtained by the Lasso algorithm; an optimization control module, configured to obtain a minimum power consumption by adjusting the pH value and / or the number of operations of the slurry circulation pump based on the SO2 concentration, and control the desulfurization system to operate based on the minimum power consumption; The data processing module includes: A power consumption calculation unit, configured to generate the power consumption based on the desulfurization efficiency model by collecting the unit load, inlet flue gas flow rate, and inlet SO2 concentration; An operation quantity calculation unit is used to generate the operation quantity of the slurry circulation pump based on the Lasso algorithm by obtaining the SO2 concentration and pH value at the desulfurization outlet, the unit load, the inlet flue gas flow rate, the circulating slurry amount, and the inlet SO2 concentration; In the process of constructing the desulfurization efficiency model, the desulfurization efficiency model is expressed as: Among them, Y is the SO2 concentration at the desulfurization outlet, x1 is the unit load; x2 is the inlet flue gas flow; x3 is the circulating slurry volume; x4 is the inlet SO2 concentration; and x5 is the pH value.

7. The desulfurization system operation optimization method based on the Lasso algorithm according to claim 6, characterized in that: The optimization control module includes: The first optimization unit is configured to increase the pH value and determine whether the desulfurization efficiency is met after stopping one slurry circulation pump. If so, the desulfurization efficiency is stopped to save power. If not, the current state is maintained, indicating that the operating condition is now the optimal operating condition. The second optimization unit is used to determine whether the desulfurization efficiency can be met after the pH value is appropriately lowered while maintaining the number of circulating pumps in operation. If so, the pH value is lowered to save limestone costs; if not, the current state is maintained, indicating that the operating conditions are now the optimal conditions.

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