Intelligent control method and system for coal slurry concentration of coal water slurry gasification furnace

Abstract

The invention belongs to the technical field of intelligent control, and particularly discloses an intelligent control method and system for the coal slurry concentration of a coal water slurry gasification furnace. According to the intelligent control method for the coal slurry concentration of the coal water slurry gasification furnace, online automatic monitoring and adjustment of the coal slurry concentration of the coal water slurry gasification furnace and automatic control of a coal slurry configuration system of the coal water slurry gasification furnace can be achieved, and the stability of coal slurry concentration control of the coal water slurry gasification furnace is improved; further, the reaction efficiency of a subsequent section, namely the coal water slurry gasifier, is improved, and the production energy consumption is reduced.

Description

Technical Field

[0001] The present invention relates to the field of intelligent control technology, and in particular to an intelligent control method and system for coal slurry concentration in a water-coal slurry gasifier. Background Art

[0002] A water-coal slurry gasifier is a core process equipment that converts coal into a water-coal slurry and then partially oxidizes it with oxygen or air under high-temperature and high-pressure conditions to produce syngas (CO + H2). This technology is widely used in the coal chemical industry (such as coal-to-methanol, coal-to-liquids, and IGCC power generation) and is a key link in achieving clean and efficient coal utilization. Coal slurry concentration, as the most basic parameter in coal gasification, plays a crucial role in the gasification process. Therefore, determining coal slurry concentration is crucial. Different coal slurry concentrations have varying degrees of impact on coal gasification. According to relevant experiments, the effective gas content increases with increasing coal slurry concentration. Therefore, the coal slurry concentration should be increased as much as possible to increase the effective gas content while ensuring that the gasifier does not overheat. According to relevant calculation results, the carbon conversion rate tends to decrease with the increase of coal slurry concentration, but the decrease is basically small. Although the decrease in carbon conversion rate will affect the economic operation of the gasifier, the gas production efficiency per unit volume of the gasifier will be greatly improved. At the same time, due to the significant reduction in the content of non-effective gases such as H20, CO2, and CH4, the capacity of the removal equipment will also be reduced accordingly. Therefore, the stable control of the coal slurry concentration of the water-coal slurry gasifier is of great significance to the production of the water-coal slurry gasifier. At present, the following main problems exist in the production process: 1) The dynamics of the calorific value and hydrophilicity of the raw coal, as well as the stability of the coal powder particle size distribution, make it difficult for traditional manual adjustment methods relying on human experience to meet the high standards of modern production for rapid response, precise control, stable operation, and consistency; 2) The coal slurry concentration used in water-coal slurry gasifiers is primarily determined by manual analysis. Operators rely on experience and manual analysis results to control the slurry concentration, resulting in unstable control and large fluctuations in slurry concentration. Too low a slurry concentration, i.e., high water content, significantly increases gasification energy consumption and reduces the effective components of syngas. Too high a slurry concentration can lead to poor fluidity and difficulty pumping.

[0003] In view of this, the present invention is proposed. Summary of the Invention

[0004] The present invention aims to solve at least one of the above technical problems and provides an intelligent control method and system for coal slurry concentration in a water-coal slurry gasifier.

[0005] In order to achieve the above object, the first technical solution adopted by the present invention is: The intelligent control method for coal slurry concentration of a water-coal slurry gasifier comprises the following steps: Obtain historical data on the coal feeder belt flow rate, coal slurry concentration, coal slurry water flow rate, additive flow rate, and agitator current in the water-coal slurry gasifier, as well as the initial values of the coal feeder belt flow rate, coal slurry water flow rate, and additive flow rate; A first relationship model is established based on historical data of coal slurry concentration and agitator current, and a second relationship model is established based on historical data of coal feeder belt flow, coal slurry concentration, coal slurry water flow, and additive flow; The first relationship model is used to monitor and obtain the real-time value of the coal slurry concentration; The theoretical values of the coal feeder belt flow, coal slurry water flow, and additive flow are calculated using the second relationship model at the target coal slurry concentration. Calculate the deviation between the initial value and theoretical value of coal feeder belt flow, coal slurry water flow and additive flow; The coal feeder belt flow, coal slurry water flow and additive flow are updated according to the deviation to obtain updated values; Through the deviation between the real-time value of coal slurry concentration and the target value at each moment, the deviation between the updated value of coal feeder belt flow, coal slurry water flow and additive flow and the theoretical value, the coal feeder belt flow, coal slurry water flow and additive flow are continuously adjusted to maintain the coal slurry concentration at the target value.

[0006] Preferably, the method for updating the coal feeder belt flow, the coal slurry water flow, and the additive flow according to the deviation to obtain updated values includes: Calculate the adjustment steps of the coal feeder belt flow, coal slurry water flow, and additive flow according to the preset adjustment time interval and steady-state time; The deviation between the real-time value and the target value of the coal slurry concentration is used as an adjustment coefficient; Obtaining an adjustment value according to the adjustment step and the adjustment coefficient; The updated value is obtained by adding the adjustment value to the initial values of the coal machine belt flow, the coal slurry water distribution flow and the additive flow.

[0007] Preferably, the adjustment step and the adjustment coefficient are multiplied to obtain the adjustment value.

[0008] Preferably, the calculation formula of the first relationship model is: ； in I is the historical data of agitator current, k and m are constants related to agitator power and slurry rheological properties, I0 is the agitator idling current; Ci is the historical data of coal slurry concentration.

[0009] Preferably, the calculation formula of the second relationship model is: ; Where Ci is the historical data of coal slurry concentration value, Mcoal is the historical data of coal feeder belt flow, Mwater is the historical data of coal slurry water distribution flow, Madditive is the historical data of additive flow, and a is the dry basis coefficient of coal.

[0010] Preferably, historical data of coal slurry concentration is updated regularly.

[0011] The second technical solution adopted in the present invention is: The intelligent control system for coal slurry concentration in a water-coal slurry gasifier includes: The data acquisition module is used to obtain the historical data of the coal feeder belt flow, coal slurry concentration, coal slurry water flow, additive flow and agitator current in the water-coal slurry gasifier, as well as the initial values of the coal feeder belt flow, coal slurry water flow and additive flow; a model building module for building a first relationship model based on historical data of coal slurry concentration and agitator current, and building a second relationship model based on historical data of coal feeder belt flow, coal slurry concentration, coal slurry water flow, and additive flow; A monitoring module, configured to monitor and obtain a real-time value of coal slurry concentration using the first relationship model; The first calculation module is used to calculate the theoretical values of the coal feeder belt flow rate, the coal slurry water flow rate, and the additive flow rate under the target value of the coal slurry concentration by using the second relationship model; The second calculation module is used to calculate the deviation between the initial value and the theoretical value of the coal feeder belt flow rate, the coal slurry water flow rate and the additive flow rate; An updating module, configured to update the coal feeder belt flow, the coal slurry water flow, and the additive flow according to the deviation to obtain updated values; The regulation module is used to continuously adjust the coal feeder belt flow, coal slurry water flow and additive flow according to the deviation between the real-time value of the coal slurry concentration and the target value at each moment, and the deviation between the updated value of the coal feeder belt flow, coal slurry water flow and additive flow and the theoretical value, so as to maintain the coal slurry concentration at the target value.

[0012] Compared with the prior art, the present invention has the following beneficial effects: The present invention can realize online automatic monitoring and adjustment of the coal slurry concentration of the water-coal slurry gasifier, as well as automatic control of the coal slurry configuration system of the water-coal slurry gasifier, thereby improving the stability of the coal slurry concentration control of the water-coal slurry gasifier, thereby improving the reaction efficiency of the subsequent process section, namely the water-coal slurry gasifier, and reducing production energy consumption. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 A schematic flow chart of an intelligent control method for coal slurry concentration in a water-coal slurry gasifier provided in an embodiment of the present invention; Figure 2This is a schematic structural diagram of an intelligent control system for coal slurry concentration in a water-coal slurry gasifier provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0014] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0015] Coal slurry concentration directly affects gasification efficiency and energy consumption. The main parameters influencing coal slurry concentration are the feeder belt flow rate, slurry water flow rate, additive flow rate, and agitator current. The feeder belt flow rate refers to the amount of coal delivered from the feeder to the pulverizer. The slurry water flow rate refers to the flow of process water added to the pulverizer during the preparation of water-coal slurry, which is directly used to adjust the coal slurry concentration. The additive flow rate refers to the amount of additives added. Additives address the inherent contradictions of coal-water mixing by dispersing coal particles, stabilizing the slurry, optimizing flow, and assisting reactions. Their dosage directly affects coal slurry concentration. Changes in coal feed require simultaneous adjustments to the water flow rate and additive flow rate to maintain a constant coal slurry concentration. The agitator current refers to the operating current of the agitator motor in the coal slurry container, which reflects the agitator load status. Abnormal current can indirectly reflect the coal slurry status (such as a sudden change in viscosity), requiring a reverse verification of the coal feed / water ratio to determine if there is an imbalance.

[0016] refer to Figure 1 The first embodiment of the present invention provides an intelligent control method for coal slurry concentration in a water-coal slurry gasifier, comprising the following steps: S1, obtain the historical data of the coal feeder belt flow, coal slurry concentration, coal slurry water flow, additive flow and agitator current in the water-coal slurry gasifier, as well as the initial values of the coal feeder belt flow, coal slurry water flow and additive flow.

[0017] Historical data can be obtained through laboratory testing, industrial process control system records, online monitoring, and other methods. Data from these sources can also be integrated to systematically build a historical database for each parameter. Initial values refer to the data read when the system is put into use.

[0018] Based on the historical data obtained, the multi-input and multi-output coal slurry concentration analysis results and the corresponding relationships between the coal machine belt flow rate, coal slurry water flow rate, additive flow rate and agitator current can be obtained, as shown in Table 1.

[0019] Table 1 Correspondence between various historical data .

[0020] S2, establishing a first relationship model based on historical data of coal slurry concentration and agitator current, and establishing a second relationship model based on historical data of coal feeder belt flow, coal slurry concentration, coal slurry water flow and additive flow.

[0021] The first relationship model is the relationship model between coal slurry concentration and agitator current I, and the calculation formula is: ； in I is the historical data of the agitator current, k and m are constants related to the agitator power and slurry rheological properties, I0 is the agitator idling current, and Ci is the historical data of the coal slurry concentration. The values of k and m in the formula are determined by fitting the coal slurry concentration with the historical data of the agitator current at the corresponding time points.

[0022] The second relationship model is the relationship model between the coal feeder belt flow, coal slurry concentration, coal slurry water flow, and additive flow. The calculation formula is: Where Ci is the historical data on coal slurry concentration, Mcoal is the historical data on the feeder belt flow rate, Mwater is the historical data on the slurry water flow rate, Madditive is the historical data on the additive flow rate, and a is the dry basis coefficient of coal. The value of a is determined by fitting the coal slurry concentration with the historical data on the feeder belt flow rate, slurry water flow rate, and additive flow rate at the corresponding time point.

[0023] S3, using the first relationship model to monitor and obtain the real-time value of the coal slurry concentration.

[0024] After obtaining the first relationship model, the real-time value of the coal slurry concentration can be monitored through the current signal.

[0025] S4, using the second relationship model to calculate the theoretical values of the coal feeder belt flow rate, the coal slurry water flow rate, and the additive flow rate at the target coal slurry concentration.

[0026] S5, calculate the deviation between the initial value and the theoretical value of the coal feeder belt flow, coal slurry water flow and additive flow.

[0027] S6, updating the coal feeder belt flow, coal slurry water flow, and additive flow according to the deviation to obtain updated values.

[0028] This step specifically includes: calculating the adjustment step of the coal feeder belt flow, coal slurry water flow, and additive flow according to the preset adjustment time interval and steady-state time; using the deviation value between the real-time value and the target value of the coal slurry concentration as the adjustment coefficient; obtaining the adjustment value according to the adjustment step and the adjustment coefficient; and adding the adjustment value to the initial value of the coal feeder belt flow, coal slurry water flow, and additive flow to obtain the updated value.

[0029] The adjustment value is obtained by multiplying the adjustment step and the adjustment coefficient.

[0030] S7, through the deviation between the real-time value of the coal slurry concentration and the target value at each moment, the deviation between the updated value of the coal feeder belt flow, coal slurry water flow and additive flow and the theoretical value, continuously adjust the coal feeder belt flow, coal slurry water flow and additive flow to achieve the goal of maintaining the coal slurry concentration at the target value.

[0031] Conduct manual laboratory analysis of coal slurry concentration regularly (once a day or multiple times a day), and use the analysis results to update historical data for parameter correction of control methods, optimize the deviation of calculation parameters, and improve the accuracy of model calculation results.

[0032] refer to Figure 2 The second embodiment of the present invention provides an intelligent control system 200 for coal slurry concentration in a water-coal slurry gasifier, including a data acquisition module 201, a model building module 202, a monitoring module 203, a first calculation module 204, a second calculation module 205, an update module 206, and an adjustment module 207.

[0033] The data acquisition module is used to obtain the historical data of the coal feeder belt flow, coal slurry concentration, coal slurry water flow, additive flow and agitator current in the water-coal slurry gasifier, as well as the initial values of the coal feeder belt flow, coal slurry water flow and additive flow; a model building module for building a first relationship model based on historical data of coal slurry concentration and agitator current, and building a second relationship model based on historical data of coal feeder belt flow, coal slurry concentration, coal slurry water flow, and additive flow; A monitoring module, configured to monitor and obtain a real-time value of coal slurry concentration using the first relationship model; The first calculation module is used to calculate the theoretical values of the coal feeder belt flow rate, the coal slurry water flow rate, and the additive flow rate under the target value of the coal slurry concentration by using the second relationship model; The second calculation module is used to calculate the deviation between the initial value and the theoretical value of the coal feeder belt flow rate, the coal slurry water flow rate and the additive flow rate; An updating module, configured to update the coal feeder belt flow, the coal slurry water flow, and the additive flow according to the deviation to obtain updated values; The regulation module is used to continuously adjust the coal feeder belt flow, coal slurry water flow and additive flow according to the deviation between the real-time value of the coal slurry concentration and the target value at each moment, and the deviation between the updated value of the coal feeder belt flow, coal slurry water flow and additive flow and the theoretical value, so as to maintain the coal slurry concentration at the target value.

[0034] The above description is only a preferred embodiment of the present invention and is not intended to limit the scope of the substantive technical content of the present invention. The amount of modeling data is much higher than the example data to improve the accuracy of the model. The substantive technical content of the present invention is broadly defined in the scope of the claims of the application. Any technical entity or method completed by others, if it is exactly the same as that defined in the scope of the claims of the application or is an equivalent variation, will be deemed to be included in the scope of the claims.

Claims

1. An intelligent control method for coal slurry concentration in a water-coal slurry gasifier, characterized in that: The following steps are involved: Obtain historical data on the coal feeder belt flow rate, coal slurry concentration, coal slurry water flow rate, additive flow rate, and agitator current in the water-coal slurry gasifier, as well as the initial values of the coal feeder belt flow rate, coal slurry water flow rate, and additive flow rate; A first relationship model is established based on historical data of coal slurry concentration and agitator current, and a second relationship model is established based on historical data of coal feeder belt flow, coal slurry concentration, coal slurry water flow, and additive flow; The first relationship model is used to monitor and obtain the real-time value of the coal slurry concentration; The theoretical values of the coal feeder belt flow, coal slurry water flow, and additive flow are calculated using the second relationship model at the target coal slurry concentration. Calculate the deviation between the initial value and theoretical value of coal feeder belt flow, coal slurry water flow and additive flow; The coal feeder belt flow, coal slurry water flow and additive flow are updated according to the deviation to obtain updated values; Through the deviation between the real-time value of coal slurry concentration and the target value at each moment, the deviation between the updated value of coal feeder belt flow, coal slurry water flow and additive flow and the theoretical value, the coal feeder belt flow, coal slurry water flow and additive flow are continuously adjusted to maintain the coal slurry concentration at the target value.

2. The intelligent control method for coal slurry concentration in a water-coal slurry gasifier according to claim 1, characterized in that: The method for updating the coal feeder belt flow, coal slurry water flow, and additive flow according to the deviation to obtain updated values includes: Calculate the adjustment steps of the coal feeder belt flow, coal slurry water flow, and additive flow according to the preset adjustment time interval and steady-state time; The deviation between the real-time value and the target value of the coal slurry concentration is used as an adjustment coefficient; Obtaining an adjustment value according to the adjustment step and the adjustment coefficient; The updated value is obtained by adding the adjustment value to the initial values of the coal machine belt flow, the coal slurry water distribution flow and the additive flow.

3. The intelligent control method for coal slurry concentration in a water-coal slurry gasifier according to claim 2, characterized in that: The adjustment step and the adjustment coefficient are multiplied to obtain an adjustment value.

4. The intelligent control method for coal slurry concentration in a water-coal slurry gasifier according to claim 1, characterized in that: The calculation formula of the first relational model is: ； in I is the historical data of agitator current, k and m are constants related to agitator power and slurry rheological properties, I0 is the agitator idling current; Ci is the historical data of coal slurry concentration.

5. The intelligent control method for coal slurry concentration in a water-coal slurry gasifier according to claim 1, characterized in that: The calculation formula of the second relational model is: ; Where Ci is the historical data of coal slurry concentration value, Mcoal is the historical data of coal feeder belt flow, Mwater is the historical data of coal slurry water distribution flow, Madditive is the historical data of additive flow, and a is the dry basis coefficient of coal.

6. The intelligent control method for coal slurry concentration in a water-coal slurry gasifier according to claim 1, characterized in that: Update historical data of coal slurry concentration regularly.

7. An intelligent control system for coal slurry concentration in a water-coal slurry gasifier, characterized in that: include: The data acquisition module is used to obtain the historical data of the coal feeder belt flow, coal slurry concentration, coal slurry water flow, additive flow and agitator current in the water-coal slurry gasifier, as well as the initial values of the coal feeder belt flow, coal slurry water flow and additive flow; a model building module for building a first relationship model based on historical data of coal slurry concentration and agitator current, and building a second relationship model based on historical data of coal feeder belt flow, coal slurry concentration, coal slurry water flow, and additive flow; A monitoring module, configured to monitor and obtain a real-time value of coal slurry concentration using the first relationship model; The first calculation module is used to calculate the theoretical values of the coal feeder belt flow rate, the coal slurry water flow rate, and the additive flow rate under the target value of the coal slurry concentration by using the second relationship model; The second calculation module is used to calculate the deviation between the initial value and the theoretical value of the coal feeder belt flow rate, the coal slurry water flow rate and the additive flow rate; An updating module, configured to update the coal feeder belt flow, the coal slurry water flow, and the additive flow according to the deviation to obtain updated values; The regulation module is used to continuously adjust the coal feeder belt flow, coal slurry water flow and additive flow according to the deviation between the real-time value of the coal slurry concentration and the target value at each moment, and the deviation between the updated value of the coal feeder belt flow, coal slurry water flow and additive flow and the theoretical value, so as to maintain the coal slurry concentration at the target value.

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