Control methods and devices for coal-fired power units

Abstract

This application discloses a control method and apparatus for a coal-fired power unit, belonging to the field of thermal control technology for thermal power plants. The control method for the coal-fired power unit includes: controlling the operation of the coal-fired power unit based on a first control variable; when a transient condition is detected in the coal-fired power unit at the current sampling time, processing the state information of the coal-fired power unit at the current sampling time based on a model predictive controller to obtain the predicted behavior of the coal-fired power unit within at least one prediction period corresponding to the current sampling time; using the model predictive controller, determining the compensation control variable corresponding to the coal-fired power unit at the target sampling time based on the predicted behavior of the coal-fired power unit within each prediction period; compensating the first control variable based on the compensation control variable; and controlling the operation of the coal-fired power unit based on the compensated first control variable. The control method for the coal-fired power unit in this application improves the dynamic response speed, anti-interference capability, operating economy, and control accuracy of the coal-fired power unit under wide operating conditions.

Description

Technical Field

[0001] This application belongs to the field of thermal control technology for thermal power plants, and particularly relates to a control method and device for coal-fired units. Background Technology

[0002] Coal-fired power generating units are a key component of the power system, and the performance of their control systems directly affects the stability, economy, and environmental friendliness of unit operation. With the increasing proportion of renewable energy, the power grid places higher demands on the rapid load-changing capabilities of coal-fired units. The boiler-turbine system of coal-fired units exhibits strong nonlinearity, large inertia, and time-varying characteristics. While methods based on PID (proportion integration differentiation) controllers exist for controlling coal-fired unit operation, these methods struggle to balance response speed and control accuracy under dynamic operating conditions, easily leading to overshoot and oscillations, which in turn affect unit efficiency and equipment safety. Summary of the Invention

[0003] This application aims to address at least one of the technical problems existing in the related art. To this end, this application proposes a control method and device for a coal-fired power unit, which can optimize the control input of the coal-fired power unit, improve the transient response performance of the coal-fired power unit system, and enhance the dynamic response speed, anti-interference ability, operating economy and control accuracy of the coal-fired power unit under a wide range of operating conditions. This avoids problems such as overshoot and oscillation under dynamic operating conditions, and ensures the efficiency and equipment safety of the coal-fired power unit.

[0004] In a first aspect, this application provides a control method for a coal-fired power unit, the method comprising:

[0005] When the operation of the coal-fired power unit is controlled based on a first control quantity, and a transient situation is detected in the coal-fired power unit at the current sampling time, the model prediction controller processes the state information of the coal-fired power unit at the current sampling time to obtain the predicted behavior of the coal-fired power unit within at least one prediction period corresponding to the current sampling time; the first control quantity is obtained by using an active disturbance rejection controller based on the state information of the coal-fired power unit at the current sampling time.

[0006] Using the model prediction controller, based on the prediction behavior of the coal-fired unit within each prediction period, the compensation control quantity corresponding to the coal-fired unit at the target sampling time is determined; the target sampling time is the next sampling time after the current sampling time.

[0007] The first control quantity is compensated based on the compensated control quantity, and the operation of the coal-fired unit is controlled based on the compensated first control quantity.

[0008] According to the control method for coal-fired power units provided in the embodiments of this application, by using an active disturbance rejection controller to generate a first control quantity, and controlling the operation of the coal-fired power unit based on the first control quantity, the stability of the system under steady-state operation and normal disturbance conditions can be effectively guaranteed. By actively using a model predictive controller to incorporate control under transient conditions such as load changes and strong disturbances, the control input of the coal-fired power unit can be optimized, improving the transient response performance of the coal-fired power unit system. This enhances the dynamic response speed, anti-interference capability, operating economy, and control accuracy of the coal-fired power unit under a wide range of operating conditions, thereby avoiding problems such as overshoot and oscillation under dynamic conditions, and ensuring the efficiency and equipment safety of the coal-fired power unit.

[0009] A control method for a coal-fired power unit according to an embodiment of this application, wherein compensating the first control quantity based on the compensation control quantity includes:

[0010] The first control quantity and the compensated control quantity are processed based on the mixing coefficient to obtain the compensated first control quantity of the coal-fired unit at the target sampling time.

[0011] A control method for a coal-fired power unit according to an embodiment of this application, wherein processing the first control quantity and the compensated control quantity based on a mixing coefficient to obtain the compensated first control quantity of the coal-fired power unit at the target sampling time includes:

[0012] Based on the following formula:

[0013] u=αu ADRC +(1-α)u MPC

[0014] Obtain the first control quantity after compensation, where u is the first control quantity after compensation. ADRC Let u be the first control variable. MPC Let α be the compensation control quantity, and α be the mixing coefficient.

[0015] One embodiment of the control method for a coal-fired power unit according to this application includes determining the compensation control quantity of the coal-fired power unit at the target sampling time based on the predicted behavior of the coal-fired power unit within each predicted time period using the model predictive controller.

[0016] Based on the prediction behavior of the coal-fired power units in each prediction period, the reference behavior of the coal-fired power units in each prediction period, and the energy efficiency index information of the coal-fired power units, the target cost function is determined.

[0017] Based on the objective cost function, the compensation control quantity corresponding to the coal-fired unit in each of the predicted time periods is obtained;

[0018] The compensation control quantity within the prediction period in which the target sampling time is located is determined as the compensation control quantity of the coal-fired unit corresponding to the target sampling time.

[0019] One embodiment of the control method for a coal-fired power unit in this application utilizes the active disturbance rejection controller to obtain the first control quantity based on the state information of the coal-fired power unit at the current sampling time, including:

[0020] Based on the following formula:

[0021]

[0022] Obtain the first control quantity, where u is the first control quantity, u0 is the basic control quantity that is adjusted based on the deviation between the output value and the reference value corresponding to the coal-fired unit, z2 is the disturbance estimate value corresponding to the coal-fired unit, and b0 is the nominal control gain.

[0023] A control method for a coal-fired power unit according to an embodiment of this application, wherein detecting a transient in the coal-fired power unit at the current sampling time includes:

[0024] At the current sampling time, at least one of the following is detected: the tracking error corresponding to the coal-fired unit is greater than or equal to a first threshold; the estimated value of the disturbance state corresponding to the coal-fired unit is greater than or equal to a second threshold; and the output change rate corresponding to the coal-fired unit is greater than or equal to a third threshold. The tracking error is used to characterize the error between the output value and the reference value corresponding to the control target corresponding to the first control quantity.

[0025] Secondly, this application provides a control device for a coal-fired power unit, comprising:

[0026] The first processing module is used to control the operation of the coal-fired power unit based on a first control quantity. When a transient situation is detected in the coal-fired power unit at the current sampling time, the module processes the state information of the coal-fired power unit at the current sampling time based on a model prediction controller to obtain the predicted behavior of the coal-fired power unit within at least one prediction period corresponding to the current sampling time. The first control quantity is obtained by using an active disturbance rejection controller based on the state information of the coal-fired power unit at the current sampling time.

[0027] The second processing module is used to determine the compensation control quantity of the coal-fired unit at the target sampling time based on the prediction behavior of the coal-fired unit in each prediction period using the model prediction controller; the target sampling time is the next sampling time after the current sampling time.

[0028] The third processing module is used to compensate the first control quantity based on the compensation control quantity, and to control the operation of the coal-fired unit based on the compensated first control quantity.

[0029] According to the control device for a coal-fired power unit provided in the embodiments of this application, by using an active disturbance rejection controller to generate a first control quantity, and controlling the operation of the coal-fired power unit based on the first control quantity, the stability of the system under steady-state operation and normal disturbance conditions can be effectively guaranteed. By actively using a model predictive controller to incorporate control under transient conditions such as load changes and strong disturbances, the control input of the coal-fired power unit can be optimized, improving the transient response performance of the coal-fired power unit system. This enhances the dynamic response speed, anti-interference capability, operating economy, and control accuracy of the coal-fired power unit under a wide range of operating conditions, thereby avoiding problems such as overshoot and oscillation under dynamic conditions, and ensuring the efficiency and equipment safety of the coal-fired power unit.

[0030] Thirdly, this application provides an electronic device including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the control method for a coal-fired power unit as described in the first aspect above.

[0031] Fourthly, this application provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the control method for a coal-fired power unit as described in the first aspect above.

[0032] Fifthly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the control method for a coal-fired power unit as described in the first aspect above.

[0033] The above-described one or more technical solutions in the embodiments of this application have at least one of the following technical effects:

[0034] By employing an active disturbance rejection controller to generate a first control quantity, and then controlling the operation of the coal-fired power unit based on this first control quantity, the stability of the system under steady-state operation and normal disturbance conditions can be effectively guaranteed. By actively using a model predictive controller to incorporate control under transient conditions such as load changes and strong disturbances, the control input of the coal-fired power unit can be optimized, improving the transient response performance of the coal-fired power unit system. This enhances the dynamic response speed, anti-interference capability, operating economy, and control accuracy of the coal-fired power unit under a wide range of operating conditions, thereby avoiding problems such as overshoot and oscillation under dynamic conditions and ensuring the efficiency and equipment safety of the coal-fired power unit.

[0035] Furthermore, by using active disturbance rejection controllers and model predictive controllers for joint control, uncertainties and external disturbances in the system can be effectively estimated and compensated, thereby improving the robustness of the system. By predicting the future behavior of the system and optimizing the control input, the system performance can be improved. By setting the mixing coefficient, a smooth transition can be achieved between different control strategies, avoiding abrupt changes in control quantities, thereby improving the stability of the system.

[0036] Furthermore, by incorporating energy efficiency indicators such as thermal efficiency and coal consumption rate into the objective cost function, the advantages of model predictive controllers in energy consumption optimization can be fully utilized while ensuring the dynamic response performance of the system, thereby improving the overall economic efficiency and environmental friendliness of coal-fired power units.

[0037] Furthermore, by combining feedforward control and feedback control to construct a composite control law, and obtaining the first control quantity based on the composite control law, effective control can be performed before and after the disturbance occurs, thereby achieving active disturbance rejection and ensuring the stability of the system under steady-state operation and normal disturbance conditions.

[0038] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0039] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the description of the embodiments taken in conjunction with the following drawings, in which:

[0040] Figure 1 This is a schematic flowchart of the control method for a coal-fired power unit provided in the embodiments of this application;

[0041] Figure 2 This is a schematic diagram illustrating the principle of the control method for a coal-fired power unit provided in the embodiments of this application;

[0042] Figure 3 This is one of the schematic diagrams showing the results of the control method for a coal-fired power unit provided in the embodiments of this application;

[0043] Figure 4 This is the second schematic diagram showing the result of the control method for a coal-fired power unit provided in the embodiments of this application;

[0044] Figure 5 This is a schematic diagram of the structure of the control device for a coal-fired power unit provided in the embodiments of this application;

[0045] Figure 6 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0046] The technical solutions of the embodiments of this application will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application are within the scope of protection of this application.

[0047] The terms "first," "second," etc., used in the specification and claims of this application are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such use of data can be interchanged where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first," "second," etc., are generally of the same class and the number of objects is not limited; for example, a first object can be one or more. Furthermore, in the specification and claims, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0048] The control method, control device, electronic equipment, and readable storage medium for coal-fired power units provided in this application will be described in detail below with reference to the accompanying drawings and through specific embodiments and application scenarios.

[0049] The control method for coal-fired power units can be applied to the terminal, which can be executed by the hardware or software in the terminal.

[0050] The terminal includes, but is not limited to, portable communication devices such as mobile phones or tablets with touch-sensitive surfaces (e.g., touchscreen displays and / or touchpads). It should also be understood that, in some embodiments, the terminal may not be a portable communication device, but rather a desktop computer with touch-sensitive surfaces (e.g., touchscreen displays and / or touchpads).

[0051] The following embodiments describe a terminal including a display and a touch-sensitive surface. However, it should be understood that the terminal may include one or more other physical user interface devices such as a physical keyboard, mouse, and joystick.

[0052] The control method for a coal-fired power unit provided in this application embodiment can be executed by an electronic device or a functional module or entity in an electronic device that can implement the control method for the coal-fired power unit. The electronic devices mentioned in this application embodiment include, but are not limited to, mobile phones, tablets, computers, cameras, and wearable devices. The control method for a coal-fired power unit provided in this application embodiment is described below using an electronic device as the execution subject.

[0053] like Figure 1As shown, the control method for the coal-fired unit includes steps 110, 120, and 130.

[0054] It should be noted that the control method for coal-fired power units provided in this application is not only applicable to coal-fired power units, but also to other industrial units with similar dynamic characteristics and control requirements. This application does not limit the application.

[0055] Step 110: When the coal-fired unit is controlled based on the first control quantity and a transient situation is detected in the coal-fired unit at the current sampling time, the state information of the coal-fired unit at the current sampling time is processed based on the model prediction controller to obtain the predicted behavior of the coal-fired unit in at least one prediction period corresponding to the current sampling time.

[0056] In this step, the coal-fired unit is a mechanical device that can convert the chemical energy of fossil fuels such as coal into electrical energy.

[0057] The boiler-turbine system of a coal-fired power unit has characteristics such as strong nonlinearity, large inertia, time-varying characteristics, and multivariable coupling.

[0058] The first control variable is calculated at the current sampling time using the Active Disturbance Rejection Control (ADRC) based on the current state information.

[0059] In discrete-time control systems, the system can collect system state information and output signals within a specific time interval (sampling period). The time point of these collected data is the sampling time, and the current sampling time is the time point at which data acquisition and control calculation are currently being performed.

[0060] Active disturbance rejection controllers can include tracking differentiators, extended state observers, and nonlinear error feedback control laws.

[0061] The active disturbance rejection controller can estimate in real time the state information of the coal-fired unit and obtain the disturbance in the compensation system to provide a basic control quantity to the coal-fired unit, namely, the first control quantity.

[0062] The status information of a coal-fired power unit can include the unit's output values ​​and input controls at the current sampling time.

[0063] Transient events in coal-fired power units can be detected by monitoring key indicators such as output change rate and tracking error.

[0064] Transient states are used to characterize load changes or strong disturbances in coal-fired power units.

[0065] In the event of a transient condition, the Model Predictive Control (MPC) can intervene to process the state information of the coal-fired unit at the current sampling time.

[0066] Model predictive controllers can use the system's dynamic model to predict the behavior of coal-fired power units over multiple future time steps (prediction periods). The predicted behavior can include the system output and state at future moments.

[0067] In actual implementation, it can be based on the nonlinear dynamic model of coal-fired power units. (in, y is the system output, g(·) is a nonlinear function containing the system's higher-order dynamics and unmodeled characteristics, d is the external disturbance, b is the system control gain, and u is the control input. In the coal-fired unit coordination system, the input variable u can include coal feed rate and main steam valve opening, etc., and the output variable y can include load and main steam pressure, etc. (The range of variable values ​​can be determined based on the design and operating conditions of the coal-fired unit). A model predictive controller is constructed.

[0068] The coordination system corresponding to the coal-fired unit can be linearized near the operating point to obtain a discrete state-space model:

[0069] Δx(k+1)=A m Δx(k)+B m Δu(k)

[0070] Δy(k)=C m Δx(k)

[0071] Where Δx(k) is the state variable increment vector, including parameters such as drum pressure and main steam pressure; Δu(k) is the control input increment vector, including adjustment commands such as coal feed rate and valve opening; A m B m and C m These are the linearized system state matrix, input matrix, and output matrix, respectively.

[0072] Then, multi-step prediction equations can be constructed based on the discrete state-space model:

[0073] Y(k)=ΨΔx(k)+ΘΔU(k)

[0074] Where Y(k) is the predicted output sequence, including time from k+1 to k+N. p The output prediction value (i.e., prediction behavior) at time k is the current sampling time, and ΔU(k) ​​is the control increment sequence to be optimized, including time k to k+N. c Changes in control quantity at time -1.

[0075] Where, N p To predict the time domain length, which characterizes the time from the current sampling moment, the model prediction controller will predict the system output in the future N... p Changes within a step.

[0076] N c To control the time domain length, which characterizes the time starting from the current sampling moment, the model predictive controller will calculate and apply the control inputs over the next N time intervals. c Changes within a step.

[0077] The prediction time domain length and control time domain length can be determined based on the system's dynamic characteristics, control objectives, and computational resources. For example, for rapidly changing systems, a longer prediction time domain can be set to capture the system's dynamic behavior; for systems with limited computational resources, a shorter control time domain can be set to reduce computational requirements; thus, a better balance can be achieved between control accuracy and computational burden.

[0078] In this application, by constructing a multi-step prediction equation, the model predictive controller is able to predict the behavior of the system in multiple future time steps. This enables the model predictive controller not only to respond to the current system state, but also to anticipate and compensate for future disturbances and uncertainties, thereby improving the control performance of the system.

[0079] Step 120: Using the model predictive controller, based on the predictive behavior of the coal-fired unit in each prediction period, determine the compensation control quantity corresponding to the coal-fired unit at the target sampling time.

[0080] In this step, the model predictive controller can solve an optimization problem based on the predicted behavior to determine the compensation control quantity corresponding to the target sampling time.

[0081] The target sampling time is the next sampling time after the current sampling time.

[0082] For example, a cost function can be set, and the objective of the optimization problem can be set to minimize the cost function. Then, the optimization problem can be solved by numerical optimization methods (such as quadratic programming) to obtain the optimal control increment sequence, so as to obtain the compensation control quantity corresponding to the coal-fired unit at the target sampling time.

[0083] Step 130: Compensate the first control quantity based on the compensated control quantity, and control the operation of the coal-fired unit based on the compensated first control quantity.

[0084] In this step, the compensation control quantity obtained from the model predictive controller can be combined with the first control quantity obtained from the active disturbance rejection controller to obtain the final control input.

[0085] The compensated control quantity can be applied to the coal-fired unit, and the controller will operate.

[0086] At the next sampling time, the above process can be repeated to re-detect the system state and calculate the new control quantity.

[0087] In actual implementation, such as Figure 2 As shown, active disturbance rejection controllers (ADRC1 and ADRC2) can be used as the main controllers, and model predictive controllers (MPC) can be used as auxiliary controllers. Under normal operating conditions, the active disturbance rejection controllers are responsible for maintaining the stable operation of the system. The active disturbance rejection controllers can control the operation of the coal-fired unit based on the first control variables (u′1 and u′2). In the event of a transient in the system, the model predictive controllers intervene to provide a compensating control variable Δu, so that the operation of the coal-fired unit can be controlled based on the compensated first control variables (u1 and u2).

[0088] According to the control method for coal-fired power units provided in the embodiments of this application, by using an active disturbance rejection controller to generate a first control quantity, and controlling the operation of the coal-fired power unit based on the first control quantity, the stability of the system under steady-state operation and normal disturbance conditions can be effectively guaranteed. By actively using a model predictive controller to incorporate control under transient conditions such as load changes and strong disturbances, the control input of the coal-fired power unit can be optimized, improving the transient response performance of the coal-fired power unit system. This enhances the dynamic response speed, anti-interference capability, operating economy, and control accuracy of the coal-fired power unit under a wide range of operating conditions, thereby avoiding problems such as overshoot and oscillation under dynamic conditions, and ensuring the efficiency and equipment safety of the coal-fired power unit.

[0089] In some embodiments, compensating the first control quantity based on the compensation control quantity may include:

[0090] The first control quantity and the compensated control quantity are processed based on the mixing coefficient to obtain the compensated first control quantity of the coal-fired unit at the target sampling time.

[0091] In this embodiment, the mixing coefficient is used to determine the contribution ratio of the active disturbance rejection controller and the model predictive controller to the final control quantity at the target sampling time.

[0092] The final control quantity can be adjusted by setting the mixing coefficient.

[0093] By setting a mixing coefficient, the first control quantity can be compensated based on the compensation control quantity, thereby obtaining the compensated first control quantity.

[0094] In some embodiments, processing the first control quantity and the compensated control quantity based on the mixing coefficient to obtain the compensated first control quantity of the coal-fired unit at the target sampling time may include:

[0095] Based on the following formula:

[0096] u=αu ADRC+(1-α)u MPC

[0097] Obtain the first control quantity after compensation.

[0098] In this embodiment, u is the compensated first control variable, u ADRC As the first control variable, u MPC The control quantity is α, which is the mixing coefficient.

[0099] The mixing coefficients can be smoothly transitioned using the hyperbolic tangent function:

[0100]

[0101] Where, ‖e‖ is the norm of the tracking error, used to characterize the deviation between the system's output value and the reference value (expected value).

[0102] ∈ represents the threshold corresponding to the tracking error, used to adjust the degree of influence of the error on the mixing coefficient.

[0103] is the norm of the disturbance estimate, used to characterize the magnitude of the disturbance within the system.

[0104] δ is the threshold for the perturbation estimate, used to adjust the degree of influence of the perturbation on the mixing coefficient.

[0105] In this application, by using a hyperbolic tangent function to smoothly transition the design of the mixing coefficients, it is possible to ensure that there is no impact during the switching of control modes. At the same time, when the model predictive controller optimizes the control quantity, it can inherit the disturbance compensation term from the disturbance rejection controller, thus forming a complementary advantage.

[0106] The value of α is usually between 0 and 1. For example, when α is close to 1, the control quantity u depends more on the first control quantity, that is, the coal-fired unit system tends to use the active disturbance rejection controller to maintain stable operation; when α is close to 0, the control quantity u depends more on the compensation control quantity, that is, the coal-fired unit system tends to use the model predictive controller to optimize the control effect, such as when dealing with transient changes.

[0107] By adjusting the value of α, a balance can be achieved between system stability and optimized performance.

[0108] In this application, by real-time monitoring of parameters such as error change rate and disturbance estimate, the mixing coefficient is automatically adjusted to automatically adjust the weight allocation of the active disturbance rejection controller and the model predictive controller, thereby achieving seamless switching and synergistic optimization of the two control strategies and ensuring a smooth transition of the control process.

[0109] According to the control method for coal-fired power units provided in the embodiments of this application, by using an active disturbance rejection controller and a model predictive controller for joint control, it is possible to effectively estimate and compensate for uncertainties and external disturbances in the system, thereby improving the robustness of the system. It can predict the future behavior of the system and optimize the control input, thereby improving the system performance. By setting a mixing coefficient, a smooth transition can be achieved between different control strategies, avoiding abrupt changes in control quantities, thereby improving the stability of the system.

[0110] In some embodiments, step 120 may include:

[0111] Based on the prediction behavior of coal-fired units in each prediction period, the reference behavior of coal-fired units in each prediction period, and the energy efficiency index information of coal-fired units, the target cost function is determined.

[0112] Based on the objective cost function, the corresponding compensation control quantities of the coal-fired power unit in each prediction period are obtained;

[0113] The compensation control quantity within the prediction period in which the target sampling time is located is determined as the compensation control quantity corresponding to the coal-fired unit at the target sampling time.

[0114] In this embodiment, the reference behavior is the output trajectory that the system expects to achieve within each prediction period. The reference trajectory can be set based on the system's control objectives, such as the expected load output or main steam pressure.

[0115] Energy efficiency indicators for coal-fired power units can include information such as thermal efficiency or coal consumption rate.

[0116] The objective cost function is an optimization objective used to evaluate the deviation between the predicted behavior and the reference behavior, taking into account changes in control inputs and energy efficiency indicators.

[0117] By minimizing the objective cost function, an optimization problem is solved, which allows us to determine the corresponding compensation control quantity for each prediction period.

[0118] Numerical optimization methods can be used to solve the optimization problem, obtain the optimal control increment sequence, and determine the first control increment in the control increment sequence as the compensation control quantity corresponding to the coal-fired unit at the target sampling time.

[0119] In actual implementation, the target cost function can be constructed as follows:

[0120]

[0121] Where J is the objective cost function, y(k+i|k) is the system output prediction (prediction behavior) given the current sampling time k in the prediction period k+i, r(k+i) is the reference behavior (reference trajectory or setpoint) in the prediction period k+i, Δu(k+i|k) is the control increment, η(k+i) is the energy efficiency index or other performance index, and Q, R and S are weight matrices used to balance the priorities of different control objectives.

[0122] The first term on the right side of the equation ensures that the output variables (such as main steam pressure and power generation) can accurately track the reference value r(k+i). The second term on the right side of the equation can constrain the abrupt change in the control input and ensure the smooth operation of the actuator. The third term on the right side of the equation introduces the direct optimization of energy efficiency indicators such as thermal efficiency η.

[0123] In solving the above objective cost function and obtaining the optimal control increment, practical engineering constraints can also be considered:

[0124] U min (k)≤U(k)≤U max (k)

[0125] ΔU min (k)≤ΔU(k)≤ΔU max (k)

[0126] Among them, U min U is the minimum constraint matrix of the input. max Let ΔU be the maximum value constraint matrix of the input. min Let ΔU be the minimum constraint matrix for the input increment. max This is the maximum value constraint matrix for the input increment, where the input may include coal feed rate and water feed rate, etc.

[0127] In this application, by taking into account practical engineering constraints, the control input sequence that satisfies the constraints can be obtained within the feasible solution space of the optimization problem in the objective cost function.

[0128] According to the control method for coal-fired power units provided in the embodiments of this application, energy efficiency indicators such as thermal efficiency and coal consumption rate are incorporated into the objective cost function. While ensuring the dynamic response performance of the system, the advantages of the model predictive controller in energy consumption optimization can be fully utilized, thereby improving the overall economic efficiency and environmental friendliness of the coal-fired power unit.

[0129] In some embodiments, using an active disturbance rejection controller to obtain a first control quantity based on the state information of the coal-fired unit at the current sampling time may include:

[0130] Based on the following formula:

[0131]

[0132] Obtain the first control variable.

[0133] In this embodiment, u is the first control variable, and u0 is the basic control variable that is adjusted based on the deviation between the output value and the reference value of the coal-fired unit. For example, the basic control variable can be calculated by proportional control.

[0134] z2 is the disturbance estimate corresponding to the coal-fired unit. The disturbance state corresponding to the coal-fired unit can be estimated by the extended state observer, i.e., the disturbance estimate.

[0135] The disturbance estimate is used to characterize the uncertainty and external disturbance in the coal-fired unit system.

[0136] By subtracting the disturbance estimate from the basic control quantity, disturbances in the system can be offset, thereby improving the system's disturbance immunity.

[0137] b0 is the nominal control gain, used to adjust the control quantity to an appropriate scale.

[0138] In actual implementation, a dynamic mathematical model of the controlled object of the coal-fired unit can be established. This model can describe the input-output relationship of the system in the form of first-order differential equations, and unmodeled dynamics and external disturbances of the system can be uniformly represented as lumped disturbance terms. This model can accurately describe the dynamic characteristics of the unit under different operating conditions.

[0139] The dynamic equations of the coordinated controlled system of a coal-fired power unit can be expressed as:

[0140]

[0141] Where y is the system output, g(·) is a nonlinear function that includes the system's higher-order dynamics and unmodeled characteristics, d is the external disturbance, b is the system control gain, and u is the control input.

[0142] The nominal control gain b0 can be used as an approximation of the system control gain b, satisfying the engineering accuracy requirement of b0≈b.

[0143] The system dynamic equations can be reformulated as including the nominal model and lumped disturbance terms:

[0144]

[0145] Where f is the lumped disturbance term, which includes model uncertainty and external disturbances, b0 is the nominal control gain, and u is the control input.

[0146] Then, using the state extension method, the lumped disturbance term f can be treated as a new system state variable x2 to construct an augmented state-space model. The state extension method handles uncertainties and external disturbances in the system, treating them as additional state variables and thus incorporating them into the system's dynamic model for unified processing. By extending the lumped disturbance f as part of the system state, the dynamic behavior of the system can be described more accurately.

[0147] The resulting augmented state-space model is shown below:

[0148]

[0149] Where x1 is the system state, x2 is the lumped disturbance of the system, b0 is the nominal control gain, u is the control input, y is the system output, and f is the lumped disturbance term.

[0150] In this application, by designing an extended state observer, the unmodeled dynamics inside the system and external disturbances are estimated in real time as extended states. This enables active suppression of various disturbances and real-time estimation and compensation of unmodeled dynamics and external disturbances in the system, thereby improving the robustness and control accuracy of the system. This avoids problems such as overshoot and oscillation under dynamic operating conditions, ensuring the efficiency and equipment safety of the coal-fired unit.

[0151] Based on the augmented state-space model, an extended state observer can be designed to achieve real-time estimation of the system state and lumped disturbances.

[0152] By using the extended state observer equation, the system state x1 and disturbance state x2 are estimated in real time. The extended state observer can use the current control input u and system output y to update the state estimate z1 and disturbance estimate z2. The estimated disturbance state z2 can be used to compensate for uncertainties and external disturbances in the system.

[0153] The extended state observer can employ the following dynamic equations:

[0154]

[0155] Where z1 is the state estimate, z2 is the disturbance estimate, b0 is the nominal control gain, u is the control input, y is the system output, and β1 and β2 are the parameters of the extended state observer.

[0156] Among them, β1 and β2 can be tuned based on the bandwidth w0 of the extended state observer:

[0157] β1=2w0

[0158]

[0159] Where β1 and β2 are the parameters of the extended state observer, and w0 is the bandwidth of the extended state observer.

[0160] Then, a composite control law with active disturbance rejection function (i.e., the control law of an active disturbance rejection controller) can be designed.

[0161] Composite control laws can achieve active disturbance rejection by combining feedforward control and feedback control.

[0162] Feedforward control can adjust the system in advance to counteract the effects of disturbances based on prior knowledge of the system's dynamic characteristics; feedback control can adjust the system based on the deviation between the system's real-time output and the desired value (reference value) to ensure the accuracy of the system output.

[0163] The final closed-loop system has definite first-order inertial characteristics:

[0164]

[0165] Where G(s) is the transfer function of the closed-loop system, k p Let be the proportional gain, and s be the complex frequency variable in the Laplace transform.

[0166] According to the control method for coal-fired power units provided in the embodiments of this application, a composite control law is constructed by combining feedforward control and feedback control. The first control quantity is obtained based on the composite control law, which enables effective control before and after disturbances occur, thereby achieving active disturbance rejection and ensuring the stability of the system under steady-state operation and normal disturbance conditions.

[0167] In some embodiments, detecting a transient in a coal-fired power unit at the current sampling time may include:

[0168] At the current sampling time, at least one of the following is detected: the tracking error corresponding to the coal-fired unit is greater than or equal to a first threshold; the estimated value of the disturbance state corresponding to the coal-fired unit is greater than or equal to a second threshold; and the output change rate corresponding to the coal-fired unit is greater than or equal to a third threshold.

[0169] In this embodiment, the tracking error is used to characterize the error between the output value and the reference value corresponding to the control target corresponding to the first control quantity.

[0170] The first threshold can be user-defined. If the tracking error is detected to be greater than or equal to the first threshold, it can be determined that a transient has occurred in the coal-fired unit.

[0171] The estimated value of the perturbation state can be obtained based on the extended state observer.

[0172] The second threshold can be user-defined. If the estimated value of the detected disturbance state is greater than or equal to the second threshold, it can be determined that a transient has occurred in the coal-fired unit.

[0173] The rate of change of output is the rate of change of the output of the coal-fired power unit system.

[0174] The third threshold can be user-defined. If the output change rate is detected to be greater than or equal to the third threshold, it can be determined that a transient has occurred in the coal-fired unit.

[0175] In actual execution, when the tracking error e = ||ry|| exceeds the first threshold ε, or the perturbation estimate is detected... Exceeding the second threshold δ, or the rate of change of output If the value exceeds the third threshold γ, it can be determined that a transient has occurred in the coal-fired unit, and the model predictive controller can intervene in the control process, where e is the tracking error, r is the reference value, and y is the output value. z2 and z2 are estimates of the perturbation state. This is the output rate of change.

[0176] According to the inventor's tests, such as Figure 3 As shown, under ramping conditions, coal-fired power units need to respond quickly to changes in grid load. This requires the control system to adjust the main steam valve opening and coal supply rate quickly and accurately. The control method (ADRC-MPC) for coal-fired power units provided in this application embodiment can achieve faster system response speed and smaller overshoot compared with the traditional active disturbance rejection controller (ADRC).

[0177] The control method (ADRC-MPC) for coal-fired power units provided in this application embodiment can reduce the integral absolute error by approximately 24.3% in the output power control loop and by approximately 14.5% in the main steam pressure control loop.

[0178] The control method for coal-fired power units provided in this application not only improves the tracking accuracy of the system but also enhances the stability of the system, and the adjustment of the control input is smoother, thereby improving energy utilization efficiency. During the ramp-up process, it can better handle multivariate coupling problems, achieve more precise and faster control, and can be better applied to scenarios with frequent changes in grid load.

[0179] like Figure 4 As shown, under disturbance conditions, coal-fired power units may encounter sudden situations such as coal supply disturbances or valve opening disturbances, requiring the control system to have strong robustness.

[0180] When the system encounters coal supply disturbances, the control method (ADRC-MPC) for coal-fired power units provided in this application embodiment can reduce the integral absolute error by about 21%; when the valve opening disturbances occur, the control method (ADRC-MPC) for coal-fired power units provided in this application embodiment can reduce the integral absolute error by about 10.4%.

[0181] The control method for coal-fired power units provided in this application can not only respond quickly to system disturbances, but also effectively restore the system to a stable state, reducing the impact of disturbances on system performance.

[0182] The control method for coal-fired power units provided in the embodiments of this application can effectively improve the system's response speed, control accuracy, and stability, while reducing the control complexity caused by multivariable coupling.

[0183] The control device for the coal-fired power unit provided in this application is described below. The control device for the coal-fired power unit described below can be referred to in correspondence with the control method for the coal-fired power unit described above.

[0184] The control method for a coal-fired power unit provided in this application can be executed by a control device for the coal-fired power unit. This application uses the example of a control device for a coal-fired power unit executing the control method to illustrate the control device for the coal-fired power unit provided in this application.

[0185] This application also provides a control device for a coal-fired power unit.

[0186] like Figure 5 As shown, the control device of the coal-fired unit includes: a first processing module 510, a second processing module 520 and a third processing module 530.

[0187] The first processing module 510 is used to process the state information of the coal-fired unit at the current sampling time based on the model prediction controller when the coal-fired unit is controlled to operate based on the first control quantity and a transient state of the coal-fired unit is detected at the current sampling time, and to obtain the predicted behavior of the coal-fired unit within at least one prediction period corresponding to the current sampling time; the first control quantity is obtained by using the active disturbance rejection controller based on the state information of the coal-fired unit at the current sampling time.

[0188] The second processing module 520 is used to determine the compensation control quantity of the coal-fired unit at the target sampling time based on the prediction behavior of the coal-fired unit in each prediction period using the model prediction controller; the target sampling time is the next sampling time after the current sampling time.

[0189] The third processing module 530 is used to compensate the first control quantity based on the compensation control quantity, and to control the operation of the coal-fired unit based on the compensated first control quantity.

[0190] According to the control device for a coal-fired power unit provided in the embodiments of this application, by using an active disturbance rejection controller to generate a first control quantity, and controlling the operation of the coal-fired power unit based on the first control quantity, the stability of the system under steady-state operation and normal disturbance conditions can be effectively guaranteed. By actively using a model predictive controller to incorporate control under transient conditions such as load changes and strong disturbances, the control input of the coal-fired power unit can be optimized, improving the transient response performance of the coal-fired power unit system. This enhances the dynamic response speed, anti-interference capability, operating economy, and control accuracy of the coal-fired power unit under a wide range of operating conditions, thereby avoiding problems such as overshoot and oscillation under dynamic conditions, and ensuring the efficiency and equipment safety of the coal-fired power unit.

[0191] In some embodiments, the third processing module 530 can also be used for:

[0192] The first control quantity and the compensated control quantity are processed based on the mixing coefficient to obtain the compensated first control quantity of the coal-fired unit at the target sampling time.

[0193] In some embodiments, the third processing module 530 can also be used for:

[0194] Based on the following formula:

[0195] u=αu ADRC +(1-α)u MPC

[0196] Obtain the first control variable after compensation, where u is the first control variable after compensation. ADRC As the first control variable, u MPC The control quantity is α, which is the mixing coefficient.

[0197] In some embodiments, the second processing module 520 may also be used for:

[0198] Based on the prediction behavior of coal-fired units in each prediction period, the reference behavior of coal-fired units in each prediction period, and the energy efficiency index information of coal-fired units, the target cost function is determined.

[0199] Based on the objective cost function, the corresponding compensation control quantities of the coal-fired power unit in each prediction period are obtained;

[0200] The compensation control quantity within the prediction period in which the target sampling time is located is determined as the compensation control quantity corresponding to the coal-fired unit at the target sampling time.

[0201] In some embodiments, the first processing module 510 may also be used for:

[0202] Based on the following formula:

[0203]

[0204] Obtain the first control variable, where u is the first control variable, u0 is the basic control variable that is adjusted based on the deviation between the output value and the reference value of the coal-fired unit, z2 is the disturbance estimate value of the coal-fired unit, and b0 is the nominal control gain.

[0205] In some embodiments, the first processing module 510 may also be used for:

[0206] At the current sampling time, at least one of the following is detected: the tracking error corresponding to the coal-fired unit is greater than or equal to the first threshold; the estimated value of the disturbance state corresponding to the coal-fired unit is greater than or equal to the second threshold; and the output change rate corresponding to the coal-fired unit is greater than or equal to the third threshold. The tracking error is used to characterize the error between the output value and the reference value corresponding to the control target corresponding to the first control quantity.

[0207] The control device for the coal-fired power unit in this application embodiment can be an electronic device or a component of an electronic device, such as an integrated circuit or a chip. The electronic device can be a terminal or other devices besides a terminal. For example, the electronic device can be a mobile phone, tablet computer, laptop computer, PDA, in-vehicle electronic device, mobile internet device (MID), augmented reality (AR) / virtual reality (VR) device, robot, wearable device, ultra-mobile personal computer (UMPC), netbook, or personal digital assistant (PDA), etc. It can also be a server, network attached storage (NAS), personal computer (PC), television (TV), ATM, or self-service machine, etc. This application embodiment does not specifically limit the scope of the device.

[0208] The control device for the coal-fired power unit in this application embodiment can be a device with an operating system. This operating system can be Android, iOS, or other possible operating systems; this application embodiment does not specifically limit the specific operating system used.

[0209] The control device for the coal-fired power unit provided in this application embodiment can achieve... Figures 1 to 4 The various processes implemented in the method implementation examples will not be described again here to avoid repetition.

[0210] In some embodiments, such as Figure 6 As shown, this application embodiment also provides an electronic device 600, including a processor 601, a memory 602, and a computer program stored in the memory 602 and executable on the processor 601. When the program is executed by the processor 601, it implements the various processes of the control method embodiment of the coal-fired unit described above and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0211] It should be noted that the electronic devices in the embodiments of this application include the mobile electronic devices and non-mobile electronic devices described above.

[0212] On the other hand, this application also provides a computer program product, which includes a computer program stored on a non-transitory computer-readable storage medium. The computer program includes program instructions. When the program instructions are executed by a computer, the computer can execute the various processes of the above-described control method embodiments for coal-fired power units and achieve the same technical effect. To avoid repetition, it will not be described again here.

[0213] In another aspect, this application also provides a non-transitory computer-readable storage medium storing a computer program thereon. When the computer program is executed by a processor, it implements various processes of the control method embodiments of the coal-fired power unit described above, and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0214] On another note, this application also provides a chip, which includes a processor and a communication interface. The communication interface is coupled to the processor, and the processor is used to run programs or instructions to implement the various processes of the control method embodiments of the coal-fired power unit described above, and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0215] It should be understood that the chip mentioned in the embodiments of this application may also be referred to as a system-on-a-chip, system chip, chip system, or system-on-a-chip, etc.

[0216] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0217] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the parts that contribute to the related technology, can be embodied in the form of software products. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0218] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A control method for a coal-fired power unit, characterized in that, include: When the operation of the coal-fired power unit is controlled based on the first control variable, and a transient situation is detected in the coal-fired power unit at the current sampling time, the state information of the coal-fired power unit at the current sampling time is processed by the model prediction controller to obtain the predicted behavior of the coal-fired power unit in at least one prediction period corresponding to the current sampling time. The first control quantity is obtained using an active disturbance rejection controller based on the state information of the coal-fired unit at the current sampling time; Using the model prediction controller, based on the prediction behavior of the coal-fired unit within each prediction period, the compensation control quantity corresponding to the coal-fired unit at the target sampling time is determined; the target sampling time is the next sampling time after the current sampling time. The first control quantity is compensated based on the compensation control quantity, and the coal-fired unit is controlled to operate based on the compensated first control quantity. The compensation of the first control quantity based on the compensation control quantity includes: The first control quantity and the compensated control quantity are processed based on the mixing coefficient to obtain the compensated first control quantity of the coal-fired unit at the target sampling time. The step of processing the first control quantity and the compensated control quantity based on the mixing coefficient to obtain the compensated first control quantity of the coal-fired unit at the target sampling time includes: Based on the following formula: Obtain the first control quantity after compensation, wherein, This refers to the first control quantity after compensation. This is the first control variable. The compensation control quantity is... The mixing coefficient is mentioned above; The step of using the model prediction controller to determine the compensation control quantity of the coal-fired power unit at the target sampling time based on the prediction behavior of the coal-fired power unit in each prediction period includes: Based on the prediction behavior of the coal-fired power units in each prediction period, the reference behavior of the coal-fired power units in each prediction period, and the energy efficiency index information of the coal-fired power units, the target cost function is determined. Based on the objective cost function, the compensation control quantity corresponding to the coal-fired unit in each of the predicted time periods is obtained; The compensation control quantity within the prediction period in which the target sampling time is located is determined as the compensation control quantity of the coal-fired unit corresponding to the target sampling time.

2. The control method for a coal-fired power unit according to claim 1, characterized in that, The first control variable is obtained using the active disturbance rejection controller based on the state information of the coal-fired power unit at the current sampling time, including: Based on the following formula: Obtain the first control quantity, wherein, This is the first control variable. This is the basic control variable used for adjustment based on the deviation between the output value and the reference value of the coal-fired power unit. This is the disturbance estimate corresponding to the coal-fired unit. This is the nominal control gain.

3. The control method for a coal-fired power unit according to claim 1, characterized in that, The detection of a transient in the coal-fired power unit at the current sampling time includes: At the current sampling time, at least one of the following is detected: the tracking error corresponding to the coal-fired unit is greater than or equal to a first threshold; the estimated value of the disturbance state corresponding to the coal-fired unit is greater than or equal to a second threshold; and the output change rate corresponding to the coal-fired unit is greater than or equal to a third threshold. The tracking error is used to characterize the error between the output value and the reference value corresponding to the control target corresponding to the first control quantity.

4. A control device for a coal-fired power unit, characterized in that, include: The first processing module is used to control the operation of the coal-fired unit based on the first control quantity, and when a transient situation is detected in the coal-fired unit at the current sampling time, it processes the state information of the coal-fired unit at the current sampling time based on the model prediction controller to obtain the predicted behavior of the coal-fired unit within at least one prediction period corresponding to the current sampling time. The first control quantity is obtained using an active disturbance rejection controller based on the state information of the coal-fired unit at the current sampling time; The second processing module is used to determine the compensation control quantity of the coal-fired unit at the target sampling time based on the prediction behavior of the coal-fired unit in each prediction period using the model prediction controller; the target sampling time is the next sampling time after the current sampling time. The third processing module is used to compensate the first control quantity based on the compensation control quantity, and to control the operation of the coal-fired unit based on the compensated first control quantity. The compensation of the first control quantity based on the compensation control quantity includes: The first control quantity and the compensated control quantity are processed based on the mixing coefficient to obtain the compensated first control quantity of the coal-fired unit at the target sampling time. The step of processing the first control quantity and the compensated control quantity based on the mixing coefficient to obtain the compensated first control quantity of the coal-fired unit at the target sampling time includes: Based on the following formula: Obtain the first control quantity after compensation, wherein, This refers to the first control quantity after compensation. This is the first control variable. The compensation control quantity is... The mixing coefficient is mentioned above; The step of using the model prediction controller to determine the compensation control quantity of the coal-fired power unit at the target sampling time based on the prediction behavior of the coal-fired power unit in each prediction period includes: Based on the prediction behavior of the coal-fired power units in each prediction period, the reference behavior of the coal-fired power units in each prediction period, and the energy efficiency index information of the coal-fired power units, the target cost function is determined. Based on the objective cost function, the compensation control quantity corresponding to the coal-fired unit in each of the predicted time periods is obtained; The compensation control quantity within the prediction period in which the target sampling time is located is determined as the compensation control quantity of the coal-fired unit corresponding to the target sampling time.

5. An electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the control method for a coal-fired power unit as described in any one of claims 1-3.

6. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the control method for a coal-fired power unit as described in any one of claims 1-3.

7. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the control method for a coal-fired power unit as described in any one of claims 1-3.

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