A quantitative evaluation method and system for desulfurization slurry quality in wet desulfurization process

Abstract

The present invention provides a method and system for quantitatively evaluating the quality of desulfurization slurry in a wet desulfurization process. The method comprises: obtaining a desulfurization slurry quality evaluation index determination model; wherein the desulfurization slurry quality evaluation index determination model can determine the desulfurization slurry quality evaluation index through the desulfurization efficiency of the desulfurization equipment and the desulfurization operation state parameters that can be obtained in real time; in the wet desulfurization process, the desulfurization efficiency of the desulfurization equipment and the desulfurization operation state parameters that can be obtained in real time are obtained; based on the obtained desulfurization efficiency of the desulfurization equipment and the desulfurization operation state parameters that can be obtained in real time, the desulfurization slurry quality evaluation index determination model is used to determine the desulfurization slurry quality evaluation index in the wet desulfurization process. The method can realize real-time monitoring of the desulfurization slurry quality in the wet desulfurization process.

Description

Technical Field

[0001] The invention belongs to the technical field of coal desulfurization, and in particular relates to a method and system for quantitatively evaluating the quality of desulfurization slurry in a wet desulfurization process. Background Art

[0002] Most of the existing coal-fired power plant desulfurization systems use the limestone wet flue gas desulfurization (FGD) process, which uses the CaO in the desulfurization slurry and the SO in the flue gas to react in the desulfurization tower. 2 The reaction produces gypsum, which removes SO from the flue gas. 2 Therefore, the quality of the desulfurization slurry seriously restricts the desulfurization efficiency of the desulfurization process. When the quality of the desulfurization slurry decreases or slurry poisoning occurs, the desulfurization efficiency will be reduced, and the SO 2 If the concentration exceeds the standard, it may even limit the operating load of the power plant in serious cases.

[0003] There are many chemical reactions in the desulfurization tower, and it is impossible to evaluate the actual reactions and the content of each component in the desulfurization tower through conventional testing and detection methods. At present, the evaluation of the quality of the desulfurization tower slurry is only to regularly evaluate several core components in the desulfurization slurry (including CaCO 3 , CaSO 4 ·2H 2 O, CaSO 3 1 / 2H 2 O, acid insoluble matter, etc.) is tested. At present, there is no current standard to judge whether the various indicators of desulfurization tower slurry meet the standards. It is more based on operating experience or general industry requirements to judge whether the content of each component meets the requirements. Therefore, at this stage, there is no comprehensive indicator for quantifiable evaluation of the quality of desulfurization slurry.

[0004] In addition, the current evaluation of desulfurization slurry also has the problem of being unable to be evaluated in real time: the physical and chemical properties and material composition of various raw materials used for desulfurization, such as limestone and process water, cannot be tested in real time; the flue gas components entering the desulfurization tower are only NOx and SO 2 , and online detection instruments for solid particles, other flue gas components cannot be detected in real time; the quality of the desulfurization slurry in the desulfurization tower is a slowly changing process, and it is impossible to perform real-time content detection of its core components.

[0005] Based on the above practical problems, real-time quantitative evaluation of desulfurization slurry quality is one of the main problems currently existing. Establishing a method for real-time evaluation of desulfurization slurry quality is of great practical significance for evaluating the operating status of the desulfurization tower and guiding the corresponding desulfurization process adjustment. Summary of the invention

[0006] The object of the present invention is to provide a method and system for quantitatively evaluating the quality of desulfurization slurry in a wet desulfurization process, which is helpful for better real-time monitoring of the quality of desulfurization slurry in a wet desulfurization process.

[0007] In order to achieve the above-mentioned object, in a first aspect, the present invention provides a method for quantitatively evaluating the quality of desulfurization slurry in a wet desulfurization process, wherein the method comprises:

[0008] Obtaining a desulfurization slurry quality evaluation index determination model; wherein the desulfurization slurry quality evaluation index determination model can determine the desulfurization slurry quality evaluation index through the desulfurization efficiency of the desulfurization equipment and the desulfurization operation state parameters that can be obtained in real time;

[0009] In the wet desulfurization process, obtaining the desulfurization efficiency of the desulfurization equipment and the desulfurization operation status parameters that can be obtained in real time;

[0010] Based on the desulfurization efficiency of the desulfurization equipment and the desulfurization operation state parameters that can be obtained in real time, the desulfurization slurry quality evaluation index determination model is used to determine the desulfurization slurry quality evaluation index in the wet desulfurization process;

[0011] This enables quantitative evaluation of the quality of desulfurization slurry in the wet desulfurization process.

[0012] According to a preferred embodiment of the first aspect, the desulfurization operation status parameters that can be obtained in real time include but are not limited to the desulfurization efficiency of the desulfurization equipment, the load of the desulfurization equipment unit, the flue gas volume at the inlet of the desulfurization equipment, the flue gas temperature at the inlet of the desulfurization equipment, the oxygen content of the flue gas at the inlet of the desulfurization equipment, the liquid-gas ratio of the desulfurization equipment, the flue gas SO at the inlet of the desulfurization equipment, and the desulfurization equipment. 2 concentration;

[0013] For example, the desulfurization slurry quality evaluation index determination model can be realized by the desulfurization efficiency of the desulfurization equipment, the unit load of the desulfurization equipment, the flue gas volume at the inlet of the desulfurization equipment, the flue gas temperature at the inlet of the desulfurization equipment, the oxygen content of the flue gas at the inlet of the desulfurization equipment, the liquid-gas ratio of the desulfurization equipment, the flue gas SO 2 Concentration determines the quality evaluation index of desulfurization slurry.

[0014] According to a preferred embodiment of the first aspect, the obtaining of the desulfurization slurry quality evaluation index determination model comprises:

[0015] Obtaining a desulfurization efficiency determination model; wherein the desulfurization efficiency determination model can determine the desulfurization efficiency through desulfurization operation state parameters that can be obtained in real time and parameters related to the quality of the desulfurization slurry;

[0016] Based on the desulfurization efficiency determination model, the desulfurization slurry quality evaluation index determination model is determined; wherein the desulfurization slurry quality evaluation index is a comprehensive representation of the parameters related to the desulfurization slurry quality.

[0017] According to a preferred embodiment of the first aspect, the parameters related to the quality of the desulfurization slurry include but are not limited to the dust concentration of the flue gas at the inlet of the desulfurization equipment, the density of the desulfurization slurry, the pH value of the desulfurization slurry, the liquid level of the desulfurization slurry, and the oxidation air volume of the desulfurization equipment.

[0018] According to a preferred embodiment of the first aspect, the obtaining of the desulfurization efficiency determination model includes:

[0019] Obtain historical operation data of desulfurization operation status parameters that affect desulfurization efficiency;

[0020] Obtain historical operating data of parameters related to desulfurization slurry quality that affect desulfurization efficiency;

[0021] Obtain historical operating data of desulfurization efficiency;

[0022] Determining the desulfurization efficiency determination model based on the acquired historical operation data of the desulfurization operation state parameters, the historical operation data of the parameters related to the desulfurization slurry quality, and the historical operation data of the desulfurization efficiency;

[0023] Preferably, the determining of the desulfurization efficiency determination model based on the acquired historical operation data of the desulfurization operation state parameters, the historical operation data of the parameters related to the desulfurization slurry quality, and the historical operation data of the desulfurization efficiency comprises:

[0024] Preprocessing the historical operation data to divide the historical operation data into a training data set and a verification data set;

[0025] Determining the desulfurization efficiency determination model based on the training data set and the validation data set;

[0026] More preferably, the desulfurization efficiency determination model is evaluated at least in terms of fit, robustness and predictability and all of them meet the standards;

[0027] Preferably, the fitting coefficient is between 0 and 1, and the larger the value, the higher the fitting, and is generally required to be greater than 0.85; wherein the fitting coefficient is determined by the following method:

[0028]

[0029] In the formula, R 2 is the fitting coefficient; η i is the measured value of desulfurization efficiency in the training data set; The desulfurization efficiency prediction value is obtained by using the desulfurization efficiency determination model; is the average value of the measured desulfurization efficiency of the training data set;

[0030] Preferably, the robustness coefficient is between 0 and 1. The larger the value, the higher the robustness. It is generally required to be greater than 0.5. The robustness coefficient is determined by the following method:

[0031]

[0032] In the formula, q 2 is the robustness coefficient; η i is the measured value of desulfurization efficiency in the training data set; The desulfurization efficiency prediction value is obtained by using the desulfurization efficiency determination model; is the average value of the measured desulfurization efficiency of the training data set;

[0033] More preferably, the predictability coefficient is between 0 and 1. The larger the value, the higher the robustness. It is generally required to be greater than 0.8. The predictability coefficient is determined by the following method:

[0034]

[0035] In the formula, is the predictive coefficient; η′ i To verify the measured values ​​of desulfurization efficiency of the data set; The desulfurization efficiency prediction value is obtained by using the desulfurization efficiency determination model; It is the average value of the measured value of desulfurization efficiency in the validation data set.

[0036] According to a preferred embodiment of the first aspect, the desulfurization slurry quality evaluation index determination model is determined based on the desulfurization efficiency determination model by the following method:

[0037] In the desulfurization efficiency determination model, all items involving parameters related to the desulfurization slurry quality are integrated into one parameter, namely, the desulfurization slurry quality evaluation index, and then a model for determining the desulfurization slurry quality evaluation index using desulfurization efficiency and desulfurization operation status parameters is obtained, which is the desulfurization slurry quality evaluation index determination model.

[0038] According to a preferred embodiment of the first aspect, the desulfurization efficiency determination model is a linear equation with desulfurization efficiency as the dependent variable and the desulfurization operation state parameter and the parameter related to the desulfurization slurry quality as the independent variables;

[0039] Preferably, the desulfurization efficiency determination model is:

[0040] η=a+(b 1 ·x 1 +b 2 ·x 2 +...b m ·x m )+(c 1 ·y1 +c 2 ·y 2 +……c m ·y n )

[0041] Where, η is the desulfurization efficiency; x i is the desulfurization operation state parameter; i are parameters related to the quality of desulfurized slurry; a, b i 、c i All are coefficients;

[0042] According to a preferred embodiment of the first aspect, the desulfurization slurry quality evaluation index determination model is:

[0043]

[0044] In the formula, Q ture is the quality evaluation index of desulfurization slurry; η is the desulfurization efficiency; x i are desulfurization operation state parameters; a, b i , c are coefficients.

[0045] According to a preferred embodiment of the first aspect, the method further comprises:

[0046] Normalizing the desulfurization slurry quality evaluation index to obtain a normalized desulfurization slurry quality evaluation index;

[0047] Preferably, the normalization process of the desulfurization slurry quality evaluation index is performed using the highest and lowest values ​​of the historical data of the desulfurization slurry quality evaluation index; more preferably, when the desulfurization slurry quality evaluation index calculated by real-time operation is less than the lowest value of the historical data of the desulfurization slurry quality evaluation index, the desulfurization slurry quality evaluation index at this time replaces the lowest value of the historical data of the desulfurization slurry quality evaluation index; when the desulfurization slurry quality evaluation index calculated by real-time operation is greater than the highest value of the historical data of the desulfurization slurry quality evaluation index, the desulfurization slurry quality evaluation index at this time replaces the highest value of the historical data of the desulfurization slurry quality evaluation index;

[0048] Preferably, the normalization of the desulfurization slurry quality evaluation index can achieve normalization of the desulfurization slurry quality evaluation index to 0-100;

[0049] For example, the normalization process of the desulfurization slurry quality evaluation index is performed by the following formula:

[0050]

[0051] Wherein, Q is the normalized desulfurization slurry quality evaluation index, which is between 0 and 100; Qmin is the lowest value of the desulfurization slurry quality evaluation index historical data; Qmax is the highest value of the desulfurization slurry quality evaluation index historical data; Q true It is an evaluation index for the quality of desulfurization slurry.

[0052] In a second aspect, the present invention further provides a system for quantitatively evaluating the quality of desulfurization slurry in a wet desulfurization process, wherein the system comprises:

[0053] Model acquisition module: used to obtain a model for determining the quality evaluation index of desulfurization slurry; wherein the model for determining the quality evaluation index of desulfurization slurry can determine the quality evaluation index of desulfurization slurry through the desulfurization efficiency of the desulfurization equipment and the desulfurization operation status parameters that can be obtained in real time;

[0054] Parameter acquisition module: used to obtain the desulfurization efficiency of the desulfurization equipment and the desulfurization operation status parameters that can be obtained in real time in the wet desulfurization process;

[0055] Evaluation index determination module: used to determine the desulfurization slurry quality evaluation index in the wet desulfurization process based on the desulfurization efficiency of the desulfurization equipment and the desulfurization operation status parameters that can be obtained in real time, using the desulfurization slurry quality evaluation index determination model.

[0056] According to a preferred embodiment of the first aspect, the desulfurization operation status parameters that can be obtained in real time include but are not limited to the desulfurization efficiency of the desulfurization equipment, the load of the desulfurization equipment unit, the flue gas volume at the inlet of the desulfurization equipment, the flue gas temperature at the inlet of the desulfurization equipment, the oxygen content of the flue gas at the inlet of the desulfurization equipment, the liquid-gas ratio of the desulfurization equipment, the flue gas SO at the inlet of the desulfurization equipment, and the desulfurization equipment. 2 concentration;

[0057] For example, the desulfurization slurry quality evaluation index determination model can be realized by the desulfurization efficiency of the desulfurization equipment, the unit load of the desulfurization equipment, the flue gas volume at the inlet of the desulfurization equipment, the flue gas temperature at the inlet of the desulfurization equipment, the oxygen content of the flue gas at the inlet of the desulfurization equipment, the liquid-gas ratio of the desulfurization equipment, the flue gas SO 2 Concentration determines the quality evaluation index of desulfurization slurry.

[0058] According to a preferred embodiment of the second aspect, the parameters related to the quality of the desulfurization slurry include but are not limited to the dust concentration of the flue gas at the inlet of the desulfurization equipment, the density of the desulfurization slurry, the pH value of the desulfurization slurry, the liquid level of the desulfurization slurry, and the oxidation air volume of the desulfurization equipment.

[0059] According to a preferred implementation of the second aspect, the model acquisition module includes:

[0060] The first model acquisition submodule is used to acquire a desulfurization efficiency determination model; wherein the desulfurization efficiency determination model can determine the desulfurization efficiency through desulfurization operation state parameters that can be acquired in real time and parameters related to the quality of the desulfurization slurry;

[0061] The second model acquisition submodule is used to determine the desulfurization slurry quality evaluation index determination model based on the desulfurization efficiency determination model; wherein the desulfurization slurry quality evaluation index is a comprehensive representation of the parameters related to the desulfurization slurry quality.

[0062] According to a preferred implementation of the second aspect, the first model acquisition submodule includes:

[0063] A first data acquisition unit: used to acquire historical operation data of desulfurization operation state parameters affecting desulfurization efficiency;

[0064] The second data acquisition unit is used to acquire historical operation data of parameters related to the quality of desulfurization slurry that affect the desulfurization efficiency;

[0065] The third data acquisition unit is used to acquire the historical operation data of desulfurization efficiency;

[0066] A desulfurization efficiency determination model acquisition unit is used to determine the desulfurization efficiency determination model based on the acquired historical operation data of the desulfurization operation state parameters, the historical operation data of the parameters related to the desulfurization slurry quality, and the historical operation data of the desulfurization efficiency;

[0067] Preferably, the desulfurization efficiency determination model acquisition unit includes:

[0068] Data processing subunit: used for preprocessing the historical operation data and dividing the historical operation data into a training data set and a verification data set;

[0069] Desulfurization efficiency determination model acquisition subunit: used to determine the desulfurization efficiency determination model based on the training data set and the verification data set;

[0070] More preferably, the desulfurization efficiency determination model is evaluated at least in terms of fit, robustness and predictability and all of them meet the standards;

[0071] Preferably, the fitting coefficient is between 0 and 1, and the larger the value, the higher the fitting, and is generally required to be greater than 0.85; wherein the fitting coefficient is determined by the following method:

[0072]

[0073] In the formula, R 2 is the fitting coefficient; η i is the measured value of desulfurization efficiency in the training data set; The desulfurization efficiency prediction value is obtained by using the desulfurization efficiency determination model; is the average value of the measured desulfurization efficiency of the training data set;

[0074] Preferably, the robustness coefficient is between 0 and 1. The larger the value, the higher the robustness. It is generally required to be greater than 0.5. The robustness coefficient is determined by the following method:

[0075]

[0076] In the formula, q 2 is the robustness coefficient; η i is the measured value of desulfurization efficiency in the training data set; The desulfurization efficiency prediction value is obtained by using the desulfurization efficiency determination model; is the average value of the measured desulfurization efficiency of the training data set;

[0077] More preferably, the predictability coefficient is between 0 and 1. The larger the value, the higher the robustness. It is generally required to be greater than 0.8. The predictability coefficient is determined by the following method:

[0078]

[0079] In the formula, is the predictive coefficient; η′ i To verify the measured values ​​of desulfurization efficiency of the data set; The desulfurization efficiency prediction value is obtained by using the desulfurization efficiency determination model; It is the average value of the measured value of desulfurization efficiency in the validation data set.

[0080] According to a preferred embodiment of the second aspect, the desulfurization slurry quality evaluation index determination model is determined based on the desulfurization efficiency determination model by the following method:

[0081] In the desulfurization efficiency determination model, all items involving parameters related to the desulfurization slurry quality are integrated into one parameter, namely, the desulfurization slurry quality evaluation index, and then a model for determining the desulfurization slurry quality evaluation index using desulfurization efficiency and desulfurization operation status parameters is obtained, which is the desulfurization slurry quality evaluation index determination model.

[0082] According to a preferred embodiment of the second aspect, the desulfurization efficiency determination model is a linear equation with desulfurization efficiency as the dependent variable and the desulfurization operation state parameter and the parameter related to the desulfurization slurry quality as the independent variables;

[0083] Preferably, the desulfurization efficiency determination model is:

[0084] η=a+(b 1 ·x 1 +b2 ·x 2 +...b m ·x m )+(c 1 ·y 1 +c 2 ·y 2 +……c m ·y n )

[0085] Where, η is the desulfurization efficiency; x i is the desulfurization operation state parameter; i are parameters related to the quality of desulfurized slurry; a, b i 、c i All are coefficients;

[0086] According to a preferred embodiment of the second aspect, the desulfurization slurry quality evaluation index determination model is:

[0087]

[0088] In the formula, Q ture is the quality evaluation index of desulfurization slurry; η is the desulfurization efficiency; x i are desulfurization operation state parameters; a, b i , c are coefficients.

[0089] According to a preferred embodiment of the second aspect, the system further comprises:

[0090] Normalization processing module: used to normalize the desulfurization slurry quality evaluation index to obtain the normalized desulfurization slurry quality evaluation index;

[0091] Preferably, the normalization process of the desulfurization slurry quality evaluation index is performed using the highest and lowest values ​​of the historical data of the desulfurization slurry quality evaluation index; more preferably, when the desulfurization slurry quality evaluation index calculated by real-time operation is less than the lowest value of the historical data of the desulfurization slurry quality evaluation index, the desulfurization slurry quality evaluation index at this time replaces the lowest value of the historical data of the desulfurization slurry quality evaluation index; when the desulfurization slurry quality evaluation index calculated by real-time operation is greater than the highest value of the historical data of the desulfurization slurry quality evaluation index, the desulfurization slurry quality evaluation index at this time replaces the highest value of the historical data of the desulfurization slurry quality evaluation index;

[0092] Preferably, the normalization of the desulfurization slurry quality evaluation index can achieve normalization of the desulfurization slurry quality evaluation index to 0-100;

[0093] For example, the normalization process of the desulfurization slurry quality evaluation index is performed by the following formula:

[0094]

[0095] Wherein, Q is the normalized desulfurization slurry quality evaluation index, which is between 0 and 100; Qmin is the lowest value of the desulfurization slurry quality evaluation index historical data; Qmax is the highest value of the desulfurization slurry quality evaluation index historical data; Q ture It is an evaluation index for the quality of desulfurization slurry.

[0096] The technical solution provided by the present invention solves the problem in the existing wet desulfurization process that the quality of the desulfurization slurry cannot be effectively and real-time evaluated due to the complexity of the desulfurization slurry, the inability to measure it online in real time, the lack of quantitative indicators and other characteristics. It can realize real-time quantitative evaluation of the quality of the desulfurization slurry and guide the safe and effective operation of the wet desulfurization. BRIEF DESCRIPTION OF THE DRAWINGS

[0097] Figure 1 A schematic flow chart of a method for quantitatively evaluating the quality of desulfurization slurry in a wet desulfurization process provided in one embodiment of the present invention.

[0098] Figure 2 A schematic diagram of the structure of a system for quantitatively evaluating the quality of desulfurization slurry in a wet desulfurization process provided by one embodiment of the present invention.

[0099] Figure 3 This is a diagram of partial data calculation results involved in Example 1 of the present invention. DETAILED DESCRIPTION

[0100] In order to make the purpose, technical solution and advantages of the embodiment of the present invention clearer, the technical solution in the embodiment of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiment of the present invention. Obviously, the described embodiment is a part of the embodiment of the present invention, not all of the embodiments. Based on the embodiment of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work belong to the protection scope of the present invention.

[0101] The principle and spirit of the present invention are described in detail below with reference to several representative embodiments of the present invention.

[0102] The quality of desulfurization slurry in the wet flue gas desulfurization process is the most critical factor affecting the desulfurization efficiency. However, due to the complexity of the desulfurization slurry, the inability to measure it online in real time, and the lack of quantitative indicators, it is currently impossible to effectively and real-time evaluate the quality of the desulfurization slurry.

[0103] The inventor proposed the technical solution of the present invention based on the process characteristics and principles of wet desulfurization.

[0104] See also Figure 1In order to achieve the purpose of real-time quantitative monitoring of the quality of desulfurization slurry in a wet desulfurization process, the present invention provides a method for quantitatively evaluating the quality of desulfurization slurry in a wet desulfurization process, wherein the method comprises:

[0105] Step S1: obtaining a desulfurization slurry quality evaluation index determination model; wherein the desulfurization slurry quality evaluation index determination model can determine the desulfurization slurry quality evaluation index through the desulfurization efficiency of the desulfurization equipment and the desulfurization operation state parameters that can be obtained in real time;

[0106] Step S2: in the wet desulfurization process, obtaining the desulfurization efficiency of the desulfurization equipment and the desulfurization operation status parameters that can be obtained in real time;

[0107] Step S3: Based on the desulfurization efficiency of the desulfurization equipment and the desulfurization operation state parameters that can be obtained in real time, the desulfurization slurry quality evaluation index determination model is used to determine the desulfurization slurry quality evaluation index in the wet desulfurization process;

[0108] This enables quantitative evaluation of the quality of desulfurization slurry in the wet desulfurization process.

[0109] In one embodiment, the desulfurization operation status parameters that can be obtained in real time include but are not limited to the desulfurization efficiency of the desulfurization equipment, the load of the desulfurization equipment unit, the flue gas volume at the inlet of the desulfurization equipment, the flue gas temperature at the inlet of the desulfurization equipment, the oxygen content of the flue gas at the inlet of the desulfurization equipment, the liquid-to-gas ratio of the desulfurization equipment, the flue gas SO at the inlet of the desulfurization equipment, and the desulfurization equipment. 2 concentration;

[0110] For example, the desulfurization slurry quality evaluation index determination model can be realized by the desulfurization efficiency of the desulfurization equipment, the unit load of the desulfurization equipment, the flue gas volume at the inlet of the desulfurization equipment, the flue gas temperature at the inlet of the desulfurization equipment, the oxygen content of the flue gas at the inlet of the desulfurization equipment, the liquid-gas ratio of the desulfurization equipment, the flue gas SO 2 Concentration determines the quality evaluation index of desulfurization slurry.

[0111] In one embodiment, step S1 includes:

[0112] Step S11: obtaining a desulfurization efficiency determination model; wherein the desulfurization efficiency determination model can determine the desulfurization efficiency through desulfurization operation state parameters that can be obtained in real time and parameters related to the quality of the desulfurization slurry;

[0113] Step S12: Based on the desulfurization efficiency determination model, determine the desulfurization slurry quality evaluation index determination model; wherein the desulfurization slurry quality evaluation index is a comprehensive representation of the parameters related to the desulfurization slurry quality.

[0114] This preferred technical solution constructs a determination model for desulfurization efficiency to reversely infer the quantitative indicators of desulfurization slurry quality, thereby realizing the establishment of a determination model for desulfurization slurry quality evaluation indicators.

[0115] In one embodiment, step S11 includes:

[0116] Step S111: acquiring historical operation data of desulfurization operation state parameters affecting desulfurization efficiency;

[0117] Step S112: acquiring historical operation data of parameters related to the quality of desulfurization slurry that affect desulfurization efficiency;

[0118] Step S113: obtaining historical operation data of desulfurization efficiency;

[0119] Step S114: determining the desulfurization efficiency determination model based on the acquired historical operation data of the desulfurization operation state parameters, the historical operation data of the parameters related to the desulfurization slurry quality, and the historical operation data of the desulfurization efficiency;

[0120] Further, step S114 includes:

[0121] Step S1141: pre-processing the historical operation data, dividing the historical operation data into a training data set and a verification data set;

[0122] Step S1142: determining the desulfurization efficiency determination model based on the training data set and the verification data set;

[0123] Furthermore, the desulfurization efficiency determination model obtained is evaluated at least in terms of fit, robustness, and predictability and all of them meet the standards;

[0124] Furthermore, the fitting coefficient is between 0 and 1. The larger the value, the better the fit. It is generally required to be greater than 0.85. The fitting coefficient is determined by the following method:

[0125]

[0126] In the formula, R 2 is the fitting coefficient; η i is the measured value of desulfurization efficiency in the training data set; The desulfurization efficiency prediction value is obtained by using the desulfurization efficiency determination model; is the average value of the measured desulfurization efficiency of the training data set;

[0127] Furthermore, the robustness coefficient is between 0 and 1. The larger the value, the higher the robustness. It is generally required to be greater than 0.5. The robustness coefficient is determined by the following method:

[0128]

[0129] In the formula, a 2 is the robustness coefficient; η i is the measured value of desulfurization efficiency in the training data set; The desulfurization efficiency prediction value is obtained by using the desulfurization efficiency determination model; is the average value of the measured desulfurization efficiency of the training data set;

[0130] Furthermore, the predictability coefficient is between 0 and 1. The larger the value, the higher the robustness. It is generally required to be greater than 0.8. The predictability coefficient is determined by the following method:

[0131]

[0132] In the formula, is the predictive coefficient; η′ i To verify the measured values ​​of desulfurization efficiency of the data set; The desulfurization efficiency prediction value is obtained by using the desulfurization efficiency determination model; It is the average value of the measured value of desulfurization efficiency in the validation data set.

[0133] In one embodiment, the parameters related to the quality of the desulfurization slurry include but are not limited to the dust concentration of the flue gas at the inlet of the desulfurization equipment, the density of the desulfurization slurry, the pH value of the desulfurization slurry, the liquid level of the desulfurization slurry, and the oxidation air volume of the desulfurization equipment.

[0134] In one embodiment, in step S12, the desulfurization slurry quality evaluation index determination model is determined based on the desulfurization efficiency determination model by the following method:

[0135] In the desulfurization efficiency determination model, all items involving parameters related to the desulfurization slurry quality are integrated into one parameter, namely, the desulfurization slurry quality evaluation index, and then a model for determining the desulfurization slurry quality evaluation index using desulfurization efficiency and desulfurization operation status parameters is obtained, which is the desulfurization slurry quality evaluation index determination model.

[0136] In one embodiment, the desulfurization efficiency determination model is a linear equation with desulfurization efficiency as the dependent variable and the desulfurization operation state parameter and the parameter related to the desulfurization slurry quality as the independent variables;

[0137] Furthermore, the desulfurization efficiency determination model is:

[0138] η=a+(b 1 ·x 1 +b 2 ·x 2 +...b m ·x m )+(c 1 ·y1 +c 2 ·y 2 +……c m ·y n )

[0139] Where, η is the desulfurization efficiency; x i is the desulfurization operation state parameter; i are parameters related to the quality of desulfurized slurry; a, b i 、c i All are coefficients;

[0140] In one embodiment, the desulfurization slurry quality evaluation index determination model is:

[0141]

[0142] In the formula, Q true is the quality evaluation index of desulfurization slurry; η is the desulfurization efficiency; x i are desulfurization operation state parameters; a, b i , c are coefficients.

[0143] In one embodiment, the method further comprises:

[0144] Step S4: normalizing the desulfurization slurry quality evaluation index to obtain a normalized desulfurization slurry quality evaluation index;

[0145] The normalized desulfurization slurry quality evaluation index can well guide the safe and effective operation of wet desulfurization.

[0146] Furthermore, the normalization processing of the desulfurization slurry quality evaluation index is performed using the highest and lowest values ​​of the historical data of the desulfurization slurry quality evaluation index; further, when the desulfurization slurry quality evaluation index calculated by real-time operation is less than the lowest value of the historical data of the desulfurization slurry quality evaluation index, the desulfurization slurry quality evaluation index at this time replaces the lowest value of the historical data of the desulfurization slurry quality evaluation index; when the desulfurization slurry quality evaluation index calculated by real-time operation is greater than the highest value of the historical data of the desulfurization slurry quality evaluation index, the desulfurization slurry quality evaluation index at this time replaces the highest value of the historical data of the desulfurization slurry quality evaluation index;

[0147] Furthermore, the normalization of the desulfurization slurry quality evaluation index can achieve normalization of the desulfurization slurry quality evaluation index to 0-100;

[0148] For example, the normalization process of the desulfurization slurry quality evaluation index is performed by the following formula:

[0149]

[0150] Wherein, Q is the normalized desulfurization slurry quality evaluation index, which is between 0 and 100; Qmin is the lowest value of the desulfurization slurry quality evaluation index historical data; Qmax is the highest value of the desulfurization slurry quality evaluation index historical data; Q ture It is an evaluation index for the quality of desulfurization slurry.

[0151] The normalized desulfurization slurry quality evaluation index is more convenient for guiding the safe and effective operation of wet desulfurization. In a specific embodiment, the safety control threshold of the normalized desulfurization slurry quality evaluation index can be determined according to the actual operating conditions of the power plant desulfurization equipment (for example, it can be determined according to the actual operating conditions when the desulfurization slurry has bubbling and overflow, gypsum is difficult to dehydrate, etc.). When the normalized desulfurization slurry quality evaluation index is not within the safety control threshold range, a warning to replace the desulfurization slurry is issued to guide the safe and effective operation of wet desulfurization.

[0152] Figure 2 is a structural block diagram of a system for quantitatively evaluating the quality of desulfurization slurry in a wet desulfurization process provided by an embodiment of the present invention, such as Figure 2 As shown, the system includes:

[0153] Model acquisition module 21: used to obtain a desulfurization slurry quality evaluation index determination model; wherein the desulfurization slurry quality evaluation index determination model can determine the desulfurization slurry quality evaluation index through the desulfurization efficiency of the desulfurization equipment and the desulfurization operation state parameters that can be obtained in real time;

[0154] Parameter acquisition module 22: used to obtain the desulfurization efficiency of the desulfurization equipment and the desulfurization operation status parameters that can be obtained in real time in the wet desulfurization process;

[0155] Evaluation index determination module 23: used to determine the desulfurization slurry quality evaluation index in the wet desulfurization process based on the desulfurization efficiency of the desulfurization equipment and the desulfurization operation status parameters that can be obtained in real time, using the desulfurization slurry quality evaluation index determination model.

[0156] In one embodiment, the desulfurization operation status parameters that can be obtained in real time include but are not limited to the desulfurization efficiency of the desulfurization equipment, the load of the desulfurization equipment unit, the flue gas volume at the inlet of the desulfurization equipment, the flue gas temperature at the inlet of the desulfurization equipment, the oxygen content of the flue gas at the inlet of the desulfurization equipment, the liquid-to-gas ratio of the desulfurization equipment, the flue gas SO at the inlet of the desulfurization equipment, and the desulfurization equipment. 2 concentration;

[0157] For example, the desulfurization slurry quality evaluation index determination model can be realized by the desulfurization efficiency of the desulfurization equipment, the unit load of the desulfurization equipment, the flue gas volume at the inlet of the desulfurization equipment, the flue gas temperature at the inlet of the desulfurization equipment, the oxygen content of the flue gas at the inlet of the desulfurization equipment, the liquid-gas ratio of the desulfurization equipment, the flue gas SO 2Concentration determines the quality evaluation index of desulfurization slurry.

[0158] In one embodiment, the model acquisition module 21 includes:

[0159] The first model acquisition submodule 211 is used to acquire a desulfurization efficiency determination model; wherein the desulfurization efficiency determination model can determine the desulfurization efficiency through desulfurization operation state parameters that can be acquired in real time and parameters related to the quality of the desulfurization slurry;

[0160] The second model acquisition submodule 212 is used to determine the desulfurization slurry quality evaluation index determination model based on the desulfurization efficiency determination model; wherein the desulfurization slurry quality evaluation index is a comprehensive representation of the parameters related to the desulfurization slurry quality.

[0161] This preferred technical solution reversely infers the quantitative index of desulfurization slurry quality by constructing a determination model of desulfurization efficiency, thereby realizing the establishment of a determination model for desulfurization slurry quality evaluation indexes.

[0162] In one embodiment, the parameters related to the quality of the desulfurization slurry include but are not limited to the dust concentration of the flue gas at the inlet of the desulfurization equipment, the density of the desulfurization slurry, the pH value of the desulfurization slurry, the liquid level of the desulfurization slurry, and the oxidation air volume of the desulfurization equipment.

[0163] In one embodiment, the first model acquisition submodule 211 includes:

[0164] The first data acquisition unit 2111 is used to acquire historical operation data of desulfurization operation state parameters that affect desulfurization efficiency;

[0165] The second data acquisition unit 2112 is used to acquire historical operation data of parameters related to the quality of desulfurization slurry that affect the desulfurization efficiency;

[0166] The third data acquisition unit 2113 is used to acquire historical operation data of desulfurization efficiency;

[0167] A desulfurization efficiency determination model acquisition unit 2114 is used to determine the desulfurization efficiency determination model based on the acquired historical operation data of the desulfurization operation state parameters, the historical operation data of the parameters related to the desulfurization slurry quality, and the historical operation data of the desulfurization efficiency;

[0168] Furthermore, the desulfurization efficiency determination model acquisition unit 2114 includes:

[0169] Data processing subunit 21141: used for preprocessing the historical operation data, dividing the historical operation data into a training data set and a verification data set;

[0170] Desulfurization efficiency determination model acquisition subunit 21142: used to determine the desulfurization efficiency determination model based on the training data set and the verification data set;

[0171] Furthermore, the desulfurization efficiency determination model obtained is evaluated at least in terms of fit, robustness, and predictability and all of them meet the standards;

[0172] Furthermore, the fitting coefficient is between 0 and 1. The larger the value, the better the fit. It is generally required to be greater than 0.85. The fitting coefficient is determined by the following method:

[0173]

[0174] In the formula, R 2 is the fitting coefficient; η i is the measured value of desulfurization efficiency in the training data set; The desulfurization efficiency prediction value is obtained by using the desulfurization efficiency determination model; is the average value of the measured desulfurization efficiency of the training data set;

[0175] Furthermore, the robustness coefficient is between 0 and 1. The larger the value, the higher the robustness. It is generally required to be greater than 0.5. The robustness coefficient is determined by the following method:

[0176]

[0177] In the formula, q 2 is the robustness coefficient; η i is the measured value of desulfurization efficiency in the training data set; The desulfurization efficiency prediction value is obtained by using the desulfurization efficiency determination model; is the average value of the measured desulfurization efficiency of the training data set;

[0178] Furthermore, the predictability coefficient is between 0 and 1. The larger the value, the higher the robustness. It is generally required to be greater than 0.8. The predictability coefficient is determined by the following method:

[0179]

[0180] In the formula, is the predictive coefficient; η′ i To verify the measured values ​​of desulfurization efficiency of the data set; The desulfurization efficiency prediction value is obtained by using the desulfurization efficiency determination model; It is the average value of the measured value of desulfurization efficiency in the validation data set.

[0181] In one embodiment, the desulfurization slurry quality evaluation index determination model is determined based on the desulfurization efficiency determination model by the following method:

[0182] In the desulfurization efficiency determination model, all items involving parameters related to the desulfurization slurry quality are integrated into one parameter, namely, the desulfurization slurry quality evaluation index, and then a model for determining the desulfurization slurry quality evaluation index using desulfurization efficiency and desulfurization operation status parameters is obtained, which is the desulfurization slurry quality evaluation index determination model.

[0183] In one embodiment, the desulfurization efficiency determination model is a linear equation with desulfurization efficiency as the dependent variable and the desulfurization operation state parameter and the parameter related to the desulfurization slurry quality as the independent variables;

[0184] Furthermore, the desulfurization efficiency determination model is:

[0185] η=a+(b 1 ·x 1 +b 2 ·x 2 +...b m ·x m )+(c 1 ·y 1 +c 2 ·y 2 +……c m ·y n )

[0186] Where, η is the desulfurization efficiency; x i is the desulfurization operation state parameter; i are parameters related to the quality of desulfurized slurry; a, b i 、c i All are coefficients;

[0187] In one embodiment, the desulfurization slurry quality evaluation index determination model is:

[0188]

[0189] In the formula, Q ture is the quality evaluation index of desulfurization slurry; η is the desulfurization efficiency; x i are desulfurization operation state parameters; a, b i , c are coefficients.

[0190] In one embodiment, the system further comprises:

[0191] Normalization processing module 24: used to normalize the desulfurization slurry quality evaluation index to obtain a normalized desulfurization slurry quality evaluation index;

[0192] The normalized desulfurization slurry quality evaluation index can well guide the safe and effective operation of wet desulfurization.

[0193] Furthermore, the normalization processing of the desulfurization slurry quality evaluation index is performed using the highest and lowest values ​​of the historical data of the desulfurization slurry quality evaluation index; further, when the desulfurization slurry quality evaluation index calculated by real-time operation is less than the lowest value of the historical data of the desulfurization slurry quality evaluation index, the desulfurization slurry quality evaluation index at this time replaces the lowest value of the historical data of the desulfurization slurry quality evaluation index; when the desulfurization slurry quality evaluation index calculated by real-time operation is greater than the highest value of the historical data of the desulfurization slurry quality evaluation index, the desulfurization slurry quality evaluation index at this time replaces the highest value of the historical data of the desulfurization slurry quality evaluation index;

[0194] Furthermore, the normalization of the desulfurization slurry quality evaluation index can achieve normalization of the desulfurization slurry quality evaluation index to 0-100;

[0195] For example, the normalization process of the desulfurization slurry quality evaluation index is performed by the following formula:

[0196]

[0197] Wherein, Q is the normalized desulfurization slurry quality evaluation index, which is between 0 and 100; Qmin is the lowest value of the desulfurization slurry quality evaluation index historical data; Qmax is the highest value of the desulfurization slurry quality evaluation index historical data; Q true It is an evaluation index for the quality of desulfurization slurry.

[0198] The normalized desulfurization slurry quality evaluation index is more convenient for guiding the safe and effective operation of wet desulfurization. In a specific embodiment, the safety control threshold of the normalized desulfurization slurry quality evaluation index can be determined according to the actual operating conditions of the power plant desulfurization equipment (for example, it can be determined according to the actual operating conditions when the desulfurization slurry has bubbling and overflow, gypsum is difficult to dehydrate, etc.). When the normalized desulfurization slurry quality evaluation index is not within the safety control threshold range, a warning to replace the desulfurization slurry is issued to guide the safe and effective operation of wet desulfurization.

[0199] Example 1

[0200] This embodiment provides a method for quantitatively evaluating the quality of desulfurization slurry in a wet desulfurization process, wherein the method comprises:

[0201] Step 1: Acquire historical operation data of desulfurization operation state parameters affecting desulfurization efficiency, historical operation data of parameters related to desulfurization slurry quality affecting desulfurization efficiency, and historical operation data of desulfurization efficiency;

[0202] Among them, the historical operation data of the desulfurization operation status parameters that affect the desulfurization efficiency, including the historical operation data of the desulfurization equipment unit load x1 , Historical operation data of flue gas volume at the inlet of desulfurization equipment x 2 , Historical operating data of flue gas temperature at the inlet of desulfurization equipment x 3 , Historical operating data of flue gas oxygen content at the inlet of desulfurization equipment x 3 , historical operation data of liquid-gas ratio of desulfurization equipment x 4 , SO2 in the flue gas at the inlet of desulfurization equipment 2 Concentration historical operation data x 4 ;

[0203] Historical operating data of parameters related to the quality of desulfurization slurry that affect desulfurization efficiency, including historical operating data of flue gas dust concentration at the inlet of desulfurization equipment 1 , Historical operation data of desulfurization slurry density of the first desulfurization tower 2 , Historical operation data of desulfurization slurry density of the second desulfurization tower 3 , Historical operation data of pH value of desulfurization slurry in the first desulfurization tower 4 , Historical operation data of pH value of desulfurization slurry in the second desulfurization tower 5 , Historical operation data of desulfurization slurry level in the first desulfurization tower 6 , Historical operation data of desulfurization slurry level in the second desulfurization tower 7 , Historical operation data of oxidation air volume of the first desulfurization tower 8 , Historical operation data of oxidation air volume of the second desulfurization tower 9 ;

[0204] Specifically, the historical operating data of a 1000MW coal-fired unit for three months was selected, and one data was extracted every 10 seconds, totaling 777,600 sets of historical operating data; the desulfurization of this unit adopts a double-tower double-cycle desulfurization process.

[0205] Step 2: preprocessing the historical operation data, dividing the historical operation data into a training data set and a verification data set;

[0206] Specifically: 80% of the samples in 777,600 sets of historical operation data are selected as the training data set, and the remaining 20% ​​of the samples are selected as the validation data set.

[0207] Step 3: Determine the desulfurization efficiency determination model based on the training data set and the validation data set;

[0208] Specifically: taking desulfurization efficiency as the dependent variable, and taking the desulfurization operation state parameters and the parameters related to the quality of the desulfurization slurry as independent variables, constructing the best linear equation for determining the desulfurization efficiency, namely, the desulfurization efficiency determination model; determining that the desulfurization efficiency determination model obtained is evaluated from at least three aspects of fitting, robustness, and predictability, and all of them meet the standards;

[0209] The fitting coefficient is between 0 and 1. The larger the value, the better the fit. It is required to be greater than 0.85. The fitting coefficient is determined by the following method:

[0210]

[0211] In the formula, R 2 is the fitting coefficient; η i is the measured value of desulfurization efficiency in the training data set; The desulfurization efficiency prediction value is obtained by using the desulfurization efficiency determination model; is the average value of the measured desulfurization efficiency of the training data set;

[0212] The robustness coefficient is between 0 and 1. The larger the value, the higher the robustness. It is required to be greater than 0.5. The robustness coefficient is determined by the following method:

[0213]

[0214] In the formula, q 2 is the robustness coefficient; η i is the measured value of desulfurization efficiency in the training data set; The desulfurization efficiency prediction value is obtained by using the desulfurization efficiency determination model; is the average value of the measured desulfurization efficiency of the training data set;

[0215] The predictability coefficient is between 0 and 1. The larger the value, the higher the robustness. It is required to be greater than 0.8. The predictability coefficient is determined by the following method:

[0216]

[0217] In the formula, is the predictive coefficient; η′ i To verify the measured values ​​of desulfurization efficiency of the data set; The desulfurization efficiency prediction value is obtained by using the desulfurization efficiency determination model; is the average value of the measured value of desulfurization efficiency of the validation data set;

[0218] Finally, the established desulfurization efficiency determination model is:

[0219] η=-233.3228+0.0015·x 2 +0.0776 x 3 -0.1044 x 4 +0.1875 x 5 -0.0006 x 6 -0.1448·y 1 -0.0069·y 2 -0.0037·y 3+2.4929·y 4 -0.7089·y 5 -16.1518·y 6 +1.4092·y 7 +0.0489·y 8 +0.0258·y 9

[0220] The model's fitting coefficient R 2 =0.992, robustness coefficient q 2 =0.618, predictive coefficient All of them meet the model evaluation index requirements.

[0221] Step 4: Integrate all items related to the parameters related to the quality of the desulfurized slurry in the desulfurization efficiency determination model into one parameter, namely, the desulfurized slurry quality evaluation index, and then obtain a model for determining the desulfurized slurry quality evaluation index using the desulfurization efficiency and the desulfurization operation state parameters, namely, the desulfurized slurry quality evaluation index determination model;

[0222] Finally, the model for determining the quality evaluation index of desulfurization slurry is determined as follows:

[0223] Q ture =-0.1448·y 1 -0.0069·y 2 -0.0037·y 3 +2.4929·y 4 -0.7089·y 5 -16.1518·y 6 +1.4092·y 7 +0.0489·y 8 +0.0258·y 9 =η+233.3228-0.0015·x 2 -0.0776 x 3 +0.1044 x 4 -0.1875 x 5 +0.0006 x 6

[0224] Step 5: In the wet desulfurization process, obtaining the desulfurization efficiency of the desulfurization equipment and the desulfurization operation status parameters that can be obtained in real time;

[0225] Step 6: Based on the desulfurization efficiency of the desulfurization equipment obtained in step 5 and the desulfurization operation status parameters that can be obtained in real time, the desulfurization slurry quality evaluation index determination model is determined by using step 4 to determine the desulfurization slurry quality evaluation index in the wet desulfurization process;

[0226] Step 7: normalize the desulfurization slurry quality evaluation index to obtain a normalized desulfurization slurry quality evaluation index; wherein the normalization is performed by the following formula:

[0227]

[0228] Where, Q is the normalized desulfurization slurry quality evaluation index, which is between 0 and 100; Qmin is the lowest value of the desulfurization slurry quality evaluation index historical data; Qmax is the highest value of the desulfurization slurry quality evaluation index historical data; Q ture It is an evaluation index for the quality of desulfurization slurry;

[0229] When the desulfurization slurry quality parameter Q is calculated in real time ture When it is less than Qmin, it indicates that the current desulfurization slurry quality is worse than the worst slurry quality in history, and the Q at this time should be ture Replace the historical data Qmin and re-enter Q ture The normalized formula of ;

[0230] When the desulfurization slurry quality parameter Q is calculated in real time ture When it is less than Qmax, it indicates that the current desulfurization slurry is of better quality than the best slurry in history, and the Q at this time should be ture Replace the Qmax of the historical data and re-enter Q ture The normalized formula of ;

[0231] In the historical data, Qmax is 320.1 and Qmin is 315.4, so the calculation formula for the normalized slurry quality is:

[0232]

[0233] Filter out the operation data when slurry bubbles overflow in the historical operation ( Figure 3 Fault condition data in), calculate Q 故障 =50, set 10% desulfurization slurry quality margin, that is, in actual operation, Q 阈值 Set to 60.

[0234] The preferred embodiments of the present invention are described above with reference to the accompanying drawings. Many features and advantages of these embodiments are clear from this detailed description, and therefore the claims are intended to cover all such features and advantages of these embodiments that fall within their true spirit and scope. In addition, since many modifications and changes are easily conceivable to those skilled in the art, it is not intended to limit the embodiments of the present invention to the precise structure and operation illustrated and described, but all suitable modifications and equivalents falling within its scope may be covered.

[0235] The present invention uses specific embodiments to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims

1. A method for quantitatively evaluating the quality of desulfurization slurry in a wet desulfurization process, wherein: The method includes: Obtaining a desulfurization slurry quality evaluation index determination model; wherein the desulfurization slurry quality evaluation index determination model can determine the desulfurization slurry quality evaluation index through the desulfurization efficiency of the desulfurization equipment and the desulfurization operation state parameters that can be obtained in real time; In the wet desulfurization process, obtaining the desulfurization efficiency of the desulfurization equipment and the desulfurization operation status parameters that can be obtained in real time; Based on the desulfurization efficiency of the desulfurization equipment and the desulfurization operation state parameters that can be obtained in real time, the desulfurization slurry quality evaluation index determination model is used to determine the desulfurization slurry quality evaluation index in the wet desulfurization process; Wherein, the model for determining the quality evaluation index of desulfurization slurry includes: Obtaining a desulfurization efficiency determination model; wherein the desulfurization efficiency determination model can determine the desulfurization efficiency through the desulfurization operation state parameters that can be obtained in real time and the parameters related to the desulfurization slurry quality; the desulfurization efficiency determination model is a linear equation with the desulfurization efficiency as the dependent variable and the desulfurization operation state parameters and the parameters related to the desulfurization slurry quality as the independent variables; Based on the desulfurization efficiency determination model, the desulfurization slurry quality evaluation index determination model is determined; wherein the desulfurization slurry quality evaluation index is a comprehensive representation of the parameters related to the desulfurization slurry quality; Wherein, based on the desulfurization efficiency determination model, the desulfurization slurry quality evaluation index determination model is determined in the following manner: In the desulfurization efficiency determination model, all items involving parameters related to the desulfurization slurry quality are integrated into one parameter, namely, the desulfurization slurry quality evaluation index, and then a model for determining the desulfurization slurry quality evaluation index using desulfurization efficiency and desulfurization operation status parameters is obtained, which is the desulfurization slurry quality evaluation index determination model.

2. The evaluation method according to claim 1, wherein: The desulfurization operation status parameters that can be obtained in real time include the desulfurization equipment unit load, the flue gas volume at the desulfurization equipment inlet, the flue gas temperature at the desulfurization equipment inlet, the oxygen content of the flue gas at the desulfurization equipment inlet, the liquid-gas ratio of the desulfurization equipment, and the SO2 concentration of the flue gas at the desulfurization equipment inlet; The desulfurization slurry quality evaluation index determination model can determine the desulfurization slurry quality evaluation index through the desulfurization efficiency of the desulfurization equipment, the unit load of the desulfurization equipment, the flue gas volume at the inlet of the desulfurization equipment, the flue gas temperature at the inlet of the desulfurization equipment, the oxygen content of the flue gas at the inlet of the desulfurization equipment, the liquid-gas ratio of the desulfurization equipment, and the SO2 concentration of the flue gas at the inlet of the desulfurization equipment.

3. The evaluation method according to claim 1, wherein: The parameters related to the quality of the desulfurization slurry include the dust concentration of the flue gas at the inlet of the desulfurization equipment, the density of the desulfurization slurry, the pH value of the desulfurization slurry, the liquid level of the desulfurization slurry, and the oxidation air volume of the desulfurization equipment.

4. The evaluation method according to claim 1, wherein: The desulfurization efficiency determination model includes: Obtain historical operation data of desulfurization operation status parameters that affect desulfurization efficiency; Obtain historical operating data of parameters related to desulfurization slurry quality that affect desulfurization efficiency; Obtain historical operating data of desulfurization efficiency; The desulfurization efficiency determination model is determined based on the acquired historical operation data of the desulfurization operation state parameters, the historical operation data of the parameters related to the desulfurization slurry quality, and the historical operation data of the desulfurization efficiency.

5. The evaluation method according to claim 4, wherein: Determining the desulfurization efficiency determination model based on the acquired historical operation data of the desulfurization operation state parameters, the historical operation data of the parameters related to the desulfurization slurry quality, and the historical operation data of the desulfurization efficiency includes: Preprocessing the historical operation data to divide the historical operation data into a training data set and a verification data set; The desulfurization efficiency determination model is determined based on the training data set and the validation data set.

6. The evaluation method according to claim 5, wherein: Determine that the desulfurization efficiency determination model obtained is evaluated from at least three aspects of fit, robustness, and predictability and all meet the standards; The fitting coefficient is greater than 0.85; the fitting coefficient is determined by: In the formula, R 2 is the fitting coefficient; η i is the measured value of desulfurization efficiency in the training data set; The desulfurization efficiency prediction value is obtained by using the desulfurization efficiency determination model; is the average value of the measured desulfurization efficiency of the training data set; Wherein, the robustness coefficient is greater than 0.5; Wherein, the robustness coefficient is determined by the following method: In the formula, q 2 is the robustness coefficient; η i is the measured value of desulfurization efficiency in the training data set; The desulfurization efficiency prediction value is obtained by using the desulfurization efficiency determination model; is the average value of the measured desulfurization efficiency of the training data set; Wherein, the predictability coefficient is greater than 0.8; Wherein, the predictability coefficient is determined by the following method: In the formula, is the predictive coefficient; η′ i To verify the measured values ​​of desulfurization efficiency of the data set; The desulfurization efficiency prediction value is obtained by using the desulfurization efficiency determination model; It is the average value of the measured value of desulfurization efficiency in the validation data set.

7. The evaluation method according to any one of claims 1 to 6, wherein: The desulfurization efficiency determination model is: η=a+(b1·x1+b2·x2+……b m ·x m )+(c1·y1+c2·y2+……c m ·y n ) Where, η is the desulfurization efficiency; x i is the desulfurization operation state parameter; i are parameters related to the quality of desulfurized slurry; a, b i 、c i All are coefficients.

8. The evaluation method according to claim 7, wherein: The desulfurization slurry quality evaluation index determination model is: In the formula, Q ture is the quality evaluation index of desulfurization slurry; η is the desulfurization efficiency; x i are desulfurization operation state parameters; a, b i , c are coefficients.

9. The evaluation method according to claim 1, wherein: The method further comprises: The desulfurization slurry quality evaluation index is normalized to obtain a normalized desulfurization slurry quality evaluation index.

10. The evaluation method according to claim 9, wherein: The normalization process of the desulfurization slurry quality evaluation index is performed using the highest value and the lowest value of the historical data of the desulfurization slurry quality evaluation index.

11. The evaluation method according to claim 10, wherein: When the desulfurization slurry quality evaluation index calculated by real-time operation is less than the lowest value of the historical data of the desulfurization slurry quality evaluation index, the desulfurization slurry quality evaluation index at this time replaces the lowest value of the historical data of the desulfurization slurry quality evaluation index; When the desulfurization slurry quality evaluation index calculated in real-time operation is greater than the highest value of the historical data of the desulfurization slurry quality evaluation index, the desulfurization slurry quality evaluation index at this time replaces the highest value of the historical data of the desulfurization slurry quality evaluation index.

12. The evaluation method according to claim 10 or 11, wherein: The normalization process of the desulfurization slurry quality evaluation index can realize normalization of the desulfurization slurry quality evaluation index to 0-100; The normalization of the desulfurization slurry quality evaluation index is performed by the following formula: Wherein, Q is the normalized desulfurization slurry quality evaluation index; Qmin is the lowest value of the desulfurization slurry quality evaluation index historical data; Qmax is the highest value of the desulfurization slurry quality evaluation index historical data; Q ture It is an evaluation index for the quality of desulfurization slurry.

13. A quantitative evaluation system for the quality of desulfurization slurry in a wet desulfurization process, wherein: The system includes: Model acquisition module: used to obtain a model for determining the quality evaluation index of desulfurization slurry; wherein the model for determining the quality evaluation index of desulfurization slurry can determine the quality evaluation index of desulfurization slurry through the desulfurization efficiency of the desulfurization equipment and the desulfurization operation status parameters that can be obtained in real time; Parameter acquisition module: used to obtain the desulfurization efficiency of the desulfurization equipment and the desulfurization operation status parameters that can be obtained in real time in the wet desulfurization process; Evaluation index determination module: used to determine the desulfurization slurry quality evaluation index in the wet desulfurization process based on the desulfurization efficiency of the desulfurization equipment and the desulfurization operation state parameters that can be obtained in real time, and using the desulfurization slurry quality evaluation index determination model; Among them, the model acquisition module includes: The first model acquisition submodule is used to acquire a desulfurization efficiency determination model; wherein the desulfurization efficiency determination model can determine the desulfurization efficiency through the desulfurization operation state parameters and the parameters related to the desulfurization slurry quality that can be acquired in real time; the desulfurization efficiency determination model is a linear equation with the desulfurization efficiency as the dependent variable and the desulfurization operation state parameters and the parameters related to the desulfurization slurry quality as the independent variables; The second model acquisition submodule is used to determine the desulfurization slurry quality evaluation index determination model based on the desulfurization efficiency determination model; wherein the desulfurization slurry quality evaluation index is a comprehensive representation of the parameters related to the desulfurization slurry quality; Wherein, the desulfurization slurry quality evaluation index determination model is determined based on the desulfurization efficiency determination model by the following method: In the desulfurization efficiency determination model, all items involving parameters related to the desulfurization slurry quality are integrated into one parameter, namely, the desulfurization slurry quality evaluation index, and then a model for determining the desulfurization slurry quality evaluation index using desulfurization efficiency and desulfurization operation status parameters is obtained, which is the desulfurization slurry quality evaluation index determination model.

14. The system according to claim 13, wherein: The desulfurization operation status parameters that can be obtained in real time include the desulfurization equipment unit load, the flue gas volume at the desulfurization equipment inlet, the flue gas temperature at the desulfurization equipment inlet, the oxygen content of the flue gas at the desulfurization equipment inlet, the liquid-gas ratio of the desulfurization equipment, and the SO2 concentration of the flue gas at the desulfurization equipment inlet; The desulfurization slurry quality evaluation index determination model can determine the desulfurization slurry quality evaluation index through the desulfurization efficiency of the desulfurization equipment, the unit load of the desulfurization equipment, the flue gas volume at the inlet of the desulfurization equipment, the flue gas temperature at the inlet of the desulfurization equipment, the oxygen content of the flue gas at the inlet of the desulfurization equipment, the liquid-gas ratio of the desulfurization equipment, and the SO2 concentration of the flue gas at the inlet of the desulfurization equipment.

15. The system of claim 13, wherein: The first model acquisition submodule includes: A first data acquisition unit: used to acquire historical operation data of desulfurization operation state parameters affecting desulfurization efficiency; The second data acquisition unit is used to acquire historical operation data of parameters related to the quality of desulfurization slurry that affect the desulfurization efficiency; The third data acquisition unit is used to acquire the historical operation data of desulfurization efficiency; Desulfurization efficiency determination model acquisition unit: used to determine the desulfurization efficiency determination model based on the acquired historical operation data of the desulfurization operation state parameters, the historical operation data of the parameters related to the desulfurization slurry quality, and the historical operation data of the desulfurization efficiency.

16. The system of claim 15, wherein: The desulfurization efficiency determination model acquisition unit includes: Data processing subunit: used for preprocessing the historical operation data and dividing the historical operation data into a training data set and a verification data set; Desulfurization efficiency determination model acquisition subunit: used to determine the desulfurization efficiency determination model based on the training data set and the verification data set.

17. The system according to any one of claims 13 to 16, wherein: The desulfurization efficiency determination model is: η=a+(b1·x1+b2·x2+……b m ·x m )+(c1·y1+c2·y2+……c m ·y n ) Where, η is the desulfurization efficiency; x i is the desulfurization operation state parameter; i are parameters related to the quality of desulfurized slurry; a, b i 、c i All are coefficients.

18. The system of claim 17, wherein: The desulfurization slurry quality evaluation index determination model is: In the formula, Q ture is the quality evaluation index of desulfurization slurry; η is the desulfurization efficiency; x i are desulfurization operation state parameters; a, b i , c are coefficients.

19. The system of claim 13, wherein: The system further comprises: Normalization processing module: used to normalize the desulfurization slurry quality evaluation index to obtain the normalized desulfurization slurry quality evaluation index.

20. The system of claim 19, wherein: The normalization process of the desulfurization slurry quality evaluation index is performed using the highest value and the lowest value of the historical data of the desulfurization slurry quality evaluation index.

21. The system of claim 20, wherein: When the desulfurization slurry quality evaluation index calculated by real-time operation is less than the lowest value of the historical data of the desulfurization slurry quality evaluation index, the desulfurization slurry quality evaluation index at this time replaces the lowest value of the historical data of the desulfurization slurry quality evaluation index; When the desulfurization slurry quality evaluation index calculated in real-time operation is greater than the highest value of the historical data of the desulfurization slurry quality evaluation index, the desulfurization slurry quality evaluation index at this time replaces the highest value of the historical data of the desulfurization slurry quality evaluation index.

22. The system according to claim 20 or 21, wherein: The normalization process of the desulfurization slurry quality evaluation index can realize normalization of the desulfurization slurry quality evaluation index to 0-100; The normalization of the desulfurization slurry quality evaluation index is performed by the following formula: Wherein, Q is the normalized desulfurization slurry quality evaluation index, which is between 0 and 100; Qmin is the lowest value of the desulfurization slurry quality evaluation index historical data; Qmax is the highest value of the desulfurization slurry quality evaluation index historical data; Q ture It is an evaluation index for the quality of desulfurization slurry.

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