Ultra-supercritical boiler deep peak shaving dry-wet state conversion dynamic characteristic prediction control method and related equipment

Abstract

The application discloses a supercritical boiler deep peak shaving dry-wet state conversion dynamic characteristic prediction control method and related equipment, and belongs to the technical field of thermal energy engineering. The method is applied to a coal-fired power generation unit control system, and comprises the following steps: obtaining dry state stable operation parameters of a boiler heating surface loop before dry-wet state conversion and changes of boundary conditions such as heating surface heat load, working medium inlet enthalpy, inlet mass flow and outlet pressure of the heating surface loop with time during the conversion process; taking the dry state parameters as initial conditions and the dynamic boundary conditions as inputs, iteratively calculating a transient hydrodynamic calculation model based on a one-dimensional homogeneous flow assumption and coupled with transient control equations of a fluid domain and transient heat conduction equations of a metal pipe wall to obtain predicted values of key parameters; and generating a load reduction rate optimization suggestion and / or an enthalpy-water level control strategy switching time suggestion according to the predicted values. The method can accurately predict dynamic changes of parameters in the dry-wet state conversion process, and provides a forward-looking adjustment signal for an automatic control system.

Description

Technical Field

[0001] This invention belongs to the field of thermal energy engineering technology, specifically relating to a method and related equipment for predicting and controlling the dynamic characteristics of dry-wet state conversion during deep peak shaving in ultra-supercritical boilers. Background Technology

[0002] With the increasing proportion of new energy power generation such as wind power and photovoltaic power in the power grid, the power system is placing higher demands on the load response capability of automatic generation control (AGC) of coal-fired power generating units. Ultra-supercritical coal-fired boilers, due to their high efficiency and good economic performance, have become the main type of unit undertaking deep peak shaving tasks. When the target load for deep peak shaving of the unit is lower than the minimum DC load, the working fluid in the boiler's steam-water separator will change from a dry state of pure gas to a wet state of coexisting steam and liquid phases, i.e., a dry-wet state transition occurs. During this transition, the hydrodynamic characteristics are complex, and parameters such as temperature, pressure, and flow rate within the heating surface fluctuate significantly, directly affecting the safe operation of the unit.

[0003] Currently, the dry-wet transition process in ultra-supercritical boilers mainly relies on manual operation by operators. Operators adjust parameters such as feedwater flow, coal feed, and steam-water separator water level based on experience, attempting to maintain a smooth transition. However, manual operation makes it difficult to accurately grasp the timing and magnitude of control. Simultaneously, existing automatic control systems lack accurate predictive methods for dynamic parameter changes during the transition, failing to anticipate parameter trends and thus hindering effective implementation of the dry-wet transition process. Specifically, during the dry-wet transition, improper control of the water-coal ratio and main steam pressure can easily lead to drastic fluctuations in key parameters such as separator outlet steam temperature, main steam temperature, and reheat steam temperature, causing frequent switching between dry and wet states, which in turn causes fluctuations in metal wall temperature, resulting in fatigue damage to the water-cooled walls. The root cause of these problems lies in the fact that the dry-wet transition is a highly transient process involving phase change, and current technology lacks methods to accurately predict the dynamic changes of key parameters in the water-cooling system during this process. This results in the automatic control system lacking forward-looking adjustment signals, making it unable to achieve a smooth and safe automatic transition. Summary of the Invention

[0004] To address the problems existing in the prior art, this invention provides a method and related equipment for predicting and controlling the dynamic characteristics of dry-wet state transition in ultra-supercritical boilers for deep peak shaving. The purpose is to solve the problem that the lack of accurate prediction methods for the dynamic changes of parameters during the dry-wet state transition process in the prior art makes it difficult to effectively implement automatic control systems and manual operation can easily cause drastic parameter fluctuations.

[0005] To solve the above-mentioned technical problems, the present invention is achieved through the following technical solution: According to a first aspect of the present invention, a predictive control method for the dynamic characteristics of deep peak shaving dry-wet state transition in an ultra-supercritical boiler is provided, applied to the control system of a coal-fired power generation unit, comprising: Obtain the dry-state stable operating parameters of the boiler heating surface circuit before the dry-wet state transition, as well as the preset boundary condition change data during the transition process. The boundary condition change data includes at least the changes in heating surface heat load, working fluid inlet enthalpy, inlet mass flow rate, and outlet pressure over time. Using the dry-state stable operating parameters as initial conditions and the boundary condition change data as input, the pre-constructed transient hydrodynamic calculation model is used for iterative calculation to obtain the predicted values ​​of key parameters characterizing the dynamic characteristics within the heated surface during the conversion process. The transient hydrodynamic calculation model is established based on the one-dimensional homogeneous flow assumption and coupled solution of the transient control equation of the fluid domain and the transient heat conduction equation of the metal tube wall. Based on the predicted values ​​of the key parameters, control strategy recommendations for the dry-wet transition process are generated and output. The control strategy recommendations include at least the load reduction rate optimization recommendation and / or the timing recommendation for switching the enthalpy-water level control strategy.

[0006] In one possible implementation of the first aspect, the dry-state stable operating parameters include: The inlet pressure, outlet pressure, inlet temperature, outlet temperature, and inlet mass flow rate of the water-cooled wall during dry stable operation.

[0007] In one possible implementation of the first aspect, using the dry-state stable operating parameters as initial conditions includes: Based on the inlet pressure, outlet pressure, inlet temperature, outlet temperature, and inlet mass flow rate of the water-cooled wall during dry stable operation, the initial distribution of working fluid pressure, flow rate, enthalpy, and density along the length of the heated surface tube is determined as the initial conditions for the transient hydrodynamic calculation model.

[0008] In one possible implementation of the first aspect, obtaining the preset boundary condition change data during the conversion process includes: The changes in the heat load of the heating surface, the inlet enthalpy of the working fluid, the inlet mass flow rate, and the outlet pressure over time can be directly obtained or calculated from the variable operating conditions preset by the automatic power generation control system based on the grid dispatch instructions.

[0009] In one possible implementation of the first aspect, the transient control equations of the fluid domain, coupled and solved by the transient hydrodynamic calculation model, include: mass conservation equation:

[0010] Momentum conservation equation:

[0011] Energy conservation equation:

[0012] And the equation of state, used to determine fluid density in single-phase and two-phase regions based on fluid pressure and enthalpy; The transient heat conduction equation of the metal tube wall is:

[0013] In the formula, The area of ​​circulation within the pipe, For fluid density, For time, For the working fluid mass flow rate, Position along the longitudinal axis of the pipe. For fluid pressure, The angle between the flow direction and the horizontal direction. The coefficient of frictional resistance. The inner diameter of the pipe. , , These are the resistance coefficients for the inlet, outlet, and elbow, respectively. This is the total length of the pipeline. This refers to the enthalpy of the fluid. The heat released per unit length of the inner wall, The metal outer wall absorbs heat. Specific heat capacity of the metal The mass of metal per unit length of tube This refers to the temperature of the inner wall.

[0014] In one possible implementation of the first aspect, during the iterative calculation process, the heat release per unit length of the inner wall is updated using the following simplified convective heat transfer equation. :

[0015] In the formula, superscript and Representing the previous time layer and the current computation time layer respectively, the subscripts... Represents spatial nodes. The fluid convective heat transfer coefficient, For heat exchange area, The inner wall temperature The temperature of the working fluid.

[0016] In one possible implementation of the first aspect, the iterative calculation using a pre-built transient hydrodynamic calculation model specifically includes: In the current calculation layer, assuming the inlet pressure of the heated surface, spatial propagation calculation is performed from the inlet to the outlet, one control volume at a time. Within each control volume, the mass conservation equation, momentum conservation equation, energy conservation equation, and state equation are solved simultaneously through multiple iterations until the calculated outlet density meets the preset accuracy requirements. When the space advances to the outlet of the heated surface and the calculated outlet pressure is obtained, the calculated outlet pressure is compared with the outlet pressure used as a boundary condition. If the relative error does not meet the preset accuracy requirements, the assumed inlet pressure of the heated surface is corrected and the space advance calculation is performed again until the outlet pressure meets the convergence condition.

[0017] In one possible implementation of the first aspect, the predicted values ​​of the key parameters include the trend of change in superheat at the midpoint, and the trend of change in the water level of the water tank or parameters related to the water level of the water tank. The generation and output of control strategy recommendations for the dry-wet transition process include: Based on the trend of superheat change at the midpoint, the proposed optimization of the load reduction rate is generated; and, Based on the changing trend of the water level in the storage tank or parameters related to the water level in the storage tank, a suggestion for switching the enthalpy-water level control strategy is generated.

[0018] According to a second aspect of the present invention, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the aforementioned method for predictive control of dynamic characteristics of deep peak shaving and dry-wet state transition in an ultra-supercritical boiler.

[0019] According to a third aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing a computer program, which, when executed by a processor, implements the aforementioned method for predictive control of dynamic characteristics of deep peak shaving and dry-wet state transition in ultra-supercritical boilers.

[0020] According to a fourth aspect of the present invention, a computer program product is provided, which, when executed by a processor, implements the aforementioned method for predictive control of dynamic characteristics of deep peak shaving and wet-dry state transition in an ultra-supercritical boiler.

[0021] Compared with the prior art, the present invention has at least the following beneficial effects: This invention provides a predictive control method for the dynamic characteristics of dry-wet state transition in ultra-supercritical boilers during deep peak shaving. By acquiring the dry-state stable operating parameters before the transition and the dynamic boundary conditions during the transition, and using a transient hydrodynamic calculation model based on the one-dimensional homogeneous flow assumption and coupled solution of the transient control equations of the fluid domain and the transient heat conduction equations of the metal tube wall for iterative calculation, the method can accurately predict the dynamic change trends of key parameters such as temperature, pressure, flow rate, and enthalpy of the water cooling system during the dry-wet state transition of the ultra-supercritical boiler. Using the predicted results of parameter changes within the heating surface during the transition from the transient hydrodynamic calculation model, the method generates optimized suggestions for load reduction rate and suggestions for switching the enthalpy-water level control strategy. This allows the control system to obtain forward-looking adjustment signals in advance, avoiding drastic parameter fluctuations caused by improper timing of control in traditional manual operation modes, ensuring a smooth and safe dry-wet state transition process. By using dry-state stable operating parameters as initial conditions and time-varying boundary conditions during the conversion process as dynamic inputs for iterative calculation, this method can adapt to the structural characteristics and operating conditions of different ultra-supercritical boilers and can adapt to the dry-wet conversion control of various models under deep peak shaving conditions. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the specific embodiments of the present invention, the drawings used in the description of the specific embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0023] Figure 1 This is a flowchart of a method for predictive control of dynamic characteristics of deep peak shaving dry-wet state transition in an ultra-supercritical boiler according to the present invention; Figure 2 This is a schematic diagram of the calculation method for the dynamic characteristics of the dry-wet state conversion process during deep peak shaving in a supercritical boiler according to the present invention. Figure 3 The division of tube sections in a supercritical boiler; Figure 4 This refers to changes in boundary conditions; Figure 5 The changes in the working fluid temperature and wall temperature at the water-cooled wall outlet when the load reduction rate is 2% are shown. Figure 6 The changes in the working fluid temperature and wall temperature at the water-cooled wall outlet when the load reduction rate is 3% are shown. Figure 7 This shows the change of enthalpy at the outlet of the water-cooled wall over time. Figure 8 This shows the change in water-cooled wall outlet flow rate over time. Detailed Implementation

[0024] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0025] This invention provides a predictive control method for the dynamic characteristics of dry-wet state transition in ultra-supercritical boilers with deep peak shaving capabilities, applicable to the control system of coal-fired power generating units. This method obtains the steady-state parameters before the dry-wet state transition and the dynamic boundary conditions during the transition process, performs predictive calculations using a transient hydrodynamic calculation model, and generates control strategy suggestions based on the prediction results, thereby providing a forward-looking adjustment signal for the automatic control of the dry-wet state transition process.

[0026] like Figure 1 As shown, the method specifically includes the following steps: S1: Obtain the dry-state stable operating parameters of the boiler heating surface circuit before the dry-wet state transition, as well as the preset boundary condition change data during the transition process.

[0027] Among them, the dry-state stable operating parameters are the operating data of the boiler in direct-flow operation before the dry-wet state transition. The boundary condition change data are the operating parameters that change over time during the transition, including at least the changes in heat load of the heating surface, enthalpy of the working fluid at the inlet, mass flow rate at the inlet, and pressure at the outlet over time.

[0028] The above parameters can be obtained from historical data or real-time monitoring data of the distributed control system (DCS) of the unit. The boundary condition change data can also be calculated based on the variable operating conditions preset by the automatic generation control system under the grid dispatch command.

[0029] S2: Using dry-state stable operating parameters as initial conditions and boundary condition change data as input, the pre-built transient hydrodynamic calculation model is used for iterative calculation to obtain the predicted values ​​of key parameters characterizing the dynamic characteristics of the heated surface during the conversion process.

[0030] The transient hydrodynamic calculation model is a mathematical model established under a set of basic assumptions. These basic assumptions include: the use of a one-dimensional axial approximation, considering fluid compressibility and thermal expansion; the vapor-liquid two-phase system is in thermodynamic equilibrium, i.e., underheated boiling and interphase thermal relaxation are not considered, and the two-phase region is described by a homogeneous model; only radial heat transfer between the working fluid and the pipe wall is considered, while axial heat transfer is ignored; and the energy equation ignores the effects of viscous dissipation, kinetic energy, and potential energy.

[0031] Based on the above assumptions, the transient hydrodynamic calculation model coupled the solutions to the transient governing equations of the fluid domain and the transient heat conduction equations of the metal tube wall. The transient governing equations of the fluid domain include the mass conservation equation, momentum conservation equation, energy conservation equation, and state equation. The transient heat conduction equation of the metal tube wall is used to describe the influence of heat storage in the tube wall on the transient process.

[0032] S3: Based on the obtained predicted values ​​of key parameters, generate and output control strategy recommendations for the dry-wet transition process. The control strategy recommendations should include at least suggestions for optimizing the load reduction rate and / or suggestions for the timing of switching the enthalpy-water level control strategy.

[0033] Specifically, the recommended load reduction rate is used to guide operators or automatic control systems to reduce unit load at an appropriate rate, avoiding drastic parameter fluctuations caused by excessively rapid load reduction. The recommended enthalpy-water level control strategy switching timing is used to indicate the timing of energy balance feedback regulation based on intermediate point superheat under dry operation, and the switching point to control based on water tank level under wet operation.

[0034] This embodiment establishes a complete process from data acquisition and model prediction to control strategy generation through the above steps. Based on the one-dimensional homogeneous flow assumption and coupled with transient heat conduction through the metal pipe wall, this method constructs a transient hydrodynamic calculation model that accurately describes the physical essence of the dry-wet transition process. The transient hydrodynamic calculation model is used to predict the dynamic changes of key parameters within the heated surface during the transition, and based on the prediction results, forward-looking control strategy suggestions are generated to ensure safe, stable, and automatic control of the dry-wet transition process.

[0035] In one feasible approach, the dry-state steady-state operating parameters include the inlet pressure, outlet pressure, inlet temperature, outlet temperature, and inlet mass flow rate of the water-cooled wall during dry-state steady-state operation. These parameters comprehensively describe the thermal state of the water-cooled wall during dry-state operation, encompassing both the thermodynamic parameters at the inlet and outlet boundaries and the fundamental parameters of the working fluid flow.

[0036] The dry-state stable operating parameters are used as initial conditions. Specifically, based on the inlet pressure, outlet pressure, inlet temperature, outlet temperature, and inlet mass flow rate of the water-cooled wall during dry-state stable operation, the initial distribution of the working fluid pressure, flow rate, enthalpy, and density along the length of the heated surface tube is determined and used as the initial conditions for the transient hydrodynamic calculation model.

[0037] The initial distribution of the working fluid along the pipe length can be determined as follows: using inlet pressure, inlet temperature, and inlet mass flow rate as the inlet boundary, and outlet pressure as the outlet boundary, solve the one-dimensional flow control equations under steady-state assumptions to obtain the pressure, flow rate, enthalpy, and density distribution at each node. The density in the single-phase region is determined by the physical property functions of water and steam based on the pressure and enthalpy.

[0038] This embodiment determines the complete initial distribution along the pipe length using dry-state stable operating parameters, providing accurate initial conditions for transient calculations. Compared to methods that only provide inlet and outlet parameters as initial conditions, the distribution along the pipe length more realistically reflects the working fluid state within the heated surface at the start of the conversion, reducing numerical disturbances in the initial stage of transient calculations and resulting in more stable and accurate predictions.

[0039] In one possible approach, acquiring the preset boundary condition change data during the conversion process includes: directly acquiring or calculating the changes in the heat load of the heating surface, the inlet enthalpy of the working fluid, the inlet mass flow rate, and the outlet pressure over time from the preset variable operating conditions of the automatic power generation control system based on the grid dispatch instructions.

[0040] Specifically, after receiving grid dispatch instructions, the automatic generation control system determines the unit load change curve according to the preset load change logic. The heat load of the heating surfaces can be estimated by querying the inlet and outlet enthalpy values ​​of the working fluid based on the inlet and outlet pressures and temperatures of the heating surfaces, and by predicting the change in the average heat load of each heating surface over time from the changes in thermodynamic parameters. The formula for calculating the heat load is:

[0041] In the formula, Heat load, in kW / m² 2 ; This is the flow rate per pipe, expressed in kg / s. and These are the inlet and outlet enthalpy values, respectively, in kJ / kg; The heated area of ​​the pipe, in meters (m²). 2 .

[0042] The inlet enthalpy of the working fluid can be determined from the physical property functions of water and steam based on the inlet pressure and temperature. The inlet mass flow rate is provided by the feedwater regulation system. The outlet pressure is determined from the sliding pressure curve corresponding to the steam-water separator pressure or the unit load. During the dry-wet transition process, the above boundary conditions can be considered to change linearly with time.

[0043] This embodiment obtains or calculates boundary conditions from the preset variable operating conditions of the automatic generation control system, realizing the direct correlation between predictive calculation and grid dispatch instructions. This enables the model to respond to the actual needs of the grid for changes in unit load, providing boundary inputs that match the actual operating conditions for the generation of control strategies.

[0044] In one feasible approach, the transient control equations of the fluid domain, which are solved by the coupled transient hydrodynamic computational model, include the mass conservation equation, momentum conservation equation, energy conservation equation, and state equation.

[0045] The mass conservation equation is:

[0046] In the formula, The flow area within the pipe is expressed in meters (m²). 2 ; Fluid density, in kg / m³ 3 ; Time, in seconds; The mass flow rate of the working fluid is expressed in kg / s. The position is along the longitudinal axis of the pipe, in meters (m).

[0047] The momentum conservation equation is:

[0048] In the formula, This refers to fluid pressure, expressed in MPa. The angle between the flow direction and the horizontal direction is expressed in rad. The coefficient of frictional resistance; This refers to the inner diameter of the pipe, in meters (m). , , These are the resistance coefficients for the inlet, outlet, and elbow, respectively. This refers to the total length of the pipeline, in meters (m). This is the function of the local resistance term, a distribution function that only acts at the location of the local resistance element.

[0049] The energy conservation equation is:

[0050] In the formula, This is the enthalpy of the fluid, expressed in J / kg. The heat released per unit length of the inner wall is expressed in W / m.

[0051] The equation of state is used to determine fluid density in both single-phase and two-phase regions based on fluid pressure and enthalpy. In the single-phase region, density is determined by pressure and enthalpy through the physical property functions of water and steam. In the two-phase region, a homogeneous model is used, and density is calculated using the following formula:

[0052] Right now,

[0053] In the formula, The density of saturated water, For saturated vapor density, This represents the mass vapor content. The mass vapor content is calculated from the fluid enthalpy, saturated water enthalpy, and saturated steam enthalpy.

[0054] The transient heat conduction equation for the metal tube wall is:

[0055] In the formula, Heat absorbed by the outer metal wall refers to the heat transferred by radiation and convection from the furnace side to the tube wall, expressed in W / m. Specific heat capacity of the metal, expressed in J / (kg·℃); The mass of metal per unit length of pipe, expressed in kg / m; This represents the inner wall temperature, expressed in °C.

[0056] Heat transfer on the working fluid side is described by the following convective heat transfer equation:

[0057] In the formula, The fluid convective heat transfer coefficient is expressed in W / (m³). 2 ·℃); The heat exchange area is the inner wall area per unit length of the tube, measured in meters (m²). 2 ; The fluid temperature is expressed in °C.

[0058] In one implementation, during the iterative calculation process, the heat release per unit length of the inner wall is updated using the following simplified convective heat transfer equation. :

[0059] In the formula, superscript and Representing the previous time layer and the current computation time layer respectively; subscript Represents spatial nodes; The fluid convective heat transfer coefficient is expressed in W / (m²·℃). This refers to the heat exchange area, expressed in m². This refers to the inner wall temperature, in °C. The temperature of the working fluid is expressed in °C.

[0060] In the numerical solution process, the convective heat transfer coefficient It can be determined by the corresponding empirical correlation of convective heat transfer based on the current working fluid temperature and pressure of the stratum.

[0061] It should be noted that the unsimplified heat transfer equation is:

[0062] This embodiment updates the heat release from the pipe wall by updating the convective heat transfer equation at the current time layer, achieving time-layer coupled solution of the heat transfer process between the fluid side and the pipe wall side. This approach can accurately reflect the dynamic balance between heat storage in the pipe wall and heat absorption in the working fluid during the dry-wet transition, improving the accuracy of wall temperature prediction.

[0063] In one possible implementation, such as Figure 2 As shown, the specific process of iterative calculation using the transient hydrodynamic calculation model in step S2 is as follows: S201: Based on the operating parameters of the ultra-supercritical boiler before the dry-wet state transition, determine the distribution of the working fluid parameters along the tube length at each node during the dry-state stable operation of the water-cooled wall working fluid. This distribution serves as the initial field for transient calculations.

[0064] S202: After initiating the dry-wet state conversion process, the heat load of the heating surface, the inlet enthalpy of the working fluid, the inlet mass flow rate, and the outlet pressure boundary conditions are known. Considering the influence of metal heat storage, the current inner wall temperature of the pipe section is... The calculations need to be performed based on the metal heat storage equation of the previous time layer, and then the heat release per unit length of the inner wall of the current pipe section needs to be calculated using the convection heat transfer equation. Repeat steps S203 to S205 to perform the calculation for the next time layer until the calculation time meets the requirements.

[0065] S203: In the current calculation layer, assume the inlet pressure of the heated surface. .

[0066] S204: Spatial propulsion calculations are performed volume by volume from the entrance to the exit. The control volumes are numbered as follows: Within each control body, the following iterative calculations are performed: S204a: Assuming the outlet density of control volume i ; S204b: Calculate the outlet mass flow rate using the discrete form of the mass conservation equation. ; S204c: Determine the outlet pressure using the discrete form of the momentum conservation equation. ; S204d: Calculate the outlet enthalpy using the discrete form of the energy conservation equation. ; S204e: Calculate the new density based on the equation of state. .like As assumed in step S204a If the relative error between them meets the preset accuracy requirement, then take... As the inlet density of the next control body, continue to the next control body; otherwise, return to step S204a. Iterate again using the new assumptions.

[0067] S205: After the space advances to the outlet of the heated surface and all control volume calculations are completed, the outlet pressure of the heated surface is obtained. The calculated outlet pressure is compared with the outlet pressure used as a boundary condition. If the relative error meets the preset accuracy requirement, the calculation for the current time layer is complete, and the calculation proceeds to the next time layer; otherwise, the assumed inlet pressure is adjusted. Perform iterative corrections, return to step S203 to recalculate, until the outlet pressure meets the convergence condition.

[0068] In the discretization process, the internal node method is used to mesh the control volume. Based on the furnace heat load distribution, the pipes are divided into multiple pipe groups along the flow direction, and each pipe group is further divided into several pipe segments. The interface physical properties are determined using a first-order upwind difference scheme, and the time term is discretized using a fully implicit scheme to ensure computational stability. The discretized forms of each governing equation are as follows.

[0069] The discrete form of the mass conservation equation is:

[0070] In the formula, The time step is expressed in seconds (s). This represents the spatial step size, measured in meters (m).

[0071] The discrete form of the momentum conservation equation is:

[0072] The discrete form of the energy conservation equation is:

[0073] The discrete form of the state equation is:

[0074] The discrete form of the metal heat storage equation is:

[0075] The discrete form of the convective heat transfer equation is:

[0076] Based on the established calculation model, a program for calculating the dynamic characteristics of water-cooled walls during the dry-wet transition process of a supercritical boiler was developed using the Fortran language, realizing the above iterative solution process.

[0077] This embodiment, through the aforementioned dual-iterative solution process, sequentially completes the spatial propagation along the pipe length and the outlet pressure verification at each time layer, enabling stable and accurate solutions for the working fluid parameters at each node during the transient process of dry-wet transition. The fully implicit time discretization scheme eliminates the limitation of time step on computational stability, allowing for the use of larger time steps for long-period transient simulations, thus improving computational efficiency. The first-order upwind difference scheme conforms to the direction of physical information transmission in the flow, further enhancing the stability of the numerical solution.

[0078] In one feasible approach, the predicted key parameters include the trend of midpoint superheat and the trend of the water level in the storage tank or parameters related to the water level. Midpoint superheat is the difference between the working fluid temperature and the saturation temperature at the corresponding pressure. The water level in the storage tank, or parameters related to it, such as the dryness fraction or enthalpy at the outlet of the steam-water separator, are key parameters reflecting the mass balance of the working fluid under wet operation. Transient hydrodynamic calculation models can predict the dynamic changes of these parameters during the dry-wet transition process.

[0079] Generate and output control strategy recommendations for the dry-wet transition process, specifically including the following two aspects: On the one hand, based on the trend of superheat at the midpoint, optimization suggestions for the load reduction rate are generated. When the prediction results show that the superheat at the midpoint decreases too quickly or approaches the saturation boundary, it indicates that the current load reduction rate may be too fast, posing a risk of premature entry into the wet state or drastic parameter fluctuations. In this case, it is recommended to reduce the load reduction rate or temporarily maintain the current load to delay the conversion process. When the prediction results show that the superheat at the midpoint changes gradually and the conversion process is controllable, the load reduction rate can be maintained or appropriately increased.

[0080] On the other hand, based on the changing trends of the water level in the storage tank or parameters related to the water level, a recommendation for switching the enthalpy-water level control strategy is generated. During the dry operation phase, the control system uses the intermediate-point superheat as the feedback adjustment variable for energy balance, maintaining the stability of the intermediate-point superheat by adjusting the water and coal feed rates. When the prediction results show that the intermediate-point superheat has dropped to near zero and the water level in the storage tank begins to build up, or related parameters reach the characteristic values ​​of wet operation, it indicates that the dry-wet transition has been completed. It is recommended to switch the control strategy from intermediate-point superheat control to storage tank water level control to meet the requirements of mass balance control during wet operation.

[0081] By specifying the predicted values ​​of key parameters as the trends of superheat change at the intermediate point and the changes of water level-related parameters in the water storage tank, the most critical control indicators under both dry and wet operating modes are directly linked. Based on their respective predicted trends, corresponding control strategy suggestions are generated, enabling accurate control of the timing of the entire dry-wet transition process. This effectively avoids drastic parameter fluctuations caused by untimely control mode switching or inappropriate load reduction rates, thus improving the stability and safety of the transition process.

[0082] Taking the dry-wet state switching operation of an ultra-supercritical boiler unit in a power plant as an example, the specific application of this invention is illustrated. The lower furnace of this boiler's water-cooled wall is a spiral tube coil, while the upper furnace is a vertical tube wall. The structural parameters and tube segment division of the boiler's heating surface circuit are as follows: Figure 3 As shown.

[0083] When applying the method of this invention, the inlet and outlet pressures, inlet and outlet temperatures, and inlet mass flow rate of the water-cooled wall during dry-state stable operation are first obtained from the unit's distributed control system to determine the initial parameter distribution along the pipe length. Simultaneously, the curves of the heat load of the heating surface, inlet enthalpy, inlet mass flow rate, and outlet pressure changing with time during load variation are obtained from the automatic power generation control system. The changes in each parameter during the conversion process can be considered linear with time, and the boundary conditions are as follows: Figure 4 As shown. The dryness of the working fluid in the separator after stable wet operation can be pre-input. The enthalpy of the working fluid can be retrieved by comparing the outlet pressure and dryness to calculate the furnace heat load under wet operation. The heat load is calculated according to the formula... Calculations also suggest that it changes linearly during the transition between dry and wet states.

[0084] The above parameters were input into the transient hydrodynamic calculation model to obtain the variation trends of the working fluid temperature, wall temperature, enthalpy and flow rate at the water-cooled wall outlet under different load reduction rates.

[0085] Figure 5 The changes in the working fluid temperature and wall temperature at the water-cooled wall outlet are shown when the load reduction rate is 2%. Figure 6 The changes in the working fluid temperature and wall temperature at the water-cooled wall outlet are shown when the load reduction rate is 3%. Figure 7 This shows the change in enthalpy at the outlet of the water-cooled wall over time. Figure 8 This shows the change in water-cooled wall outlet flow rate over time.

[0086] The calculation results show that a faster load reduction rate results in a shorter time to complete the dry-wet transition, but also more drastic changes in the enthalpy and mass flow rate at the water-cooled wall outlet, leading to a greater impact on the unit's operational stability. At a load reduction rate of 2%, the parameter changes are relatively gradual, and the transition process is well-controllable. At a load reduction rate of 3%, the transition time is shortened, but the amplitude of enthalpy and flow rate changes increases significantly, posing a risk of drastic parameter fluctuations.

[0087] Based on the predicted trends of superheat at the midpoint and water level-related parameters, corresponding suggestions for optimizing the load reduction rate and switching the enthalpy-water level control strategy can be generated. For example, if the prediction results indicate that the rate of decrease in superheat at the midpoint is too rapid, a suggestion to reduce the load reduction rate will be output; if the prediction results show that the water level in the storage tank begins to build up and tends to stabilize, a suggestion to switch the control strategy from superheat control at the midpoint to water level control will be output.

[0088] The above method can be embedded in a predictive controller, which takes the current system state and future control operations provided by the controlled platform as input, simulates the future parameter change trend in real time, and generates feedback information in advance to accelerate the unit's adjustment rate, thus realizing the application of automatic control methods in the dry-wet state conversion control of ultra-supercritical units.

[0089] In another embodiment of the present invention, a computer device is provided, comprising a processor and a memory. The memory stores a computer program, which includes program instructions. The processor executes the program instructions stored in the computer storage medium. The processor may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing and control core of the terminal, suitable for implementing one or more instructions, specifically suitable for loading and executing one or more instructions in the computer storage medium to achieve a corresponding method flow or corresponding function. The processor described in this embodiment of the present invention can be used in the operation of a dynamic characteristic prediction control method for deep peak shaving and dry-wet state conversion in ultra-supercritical boilers.

[0090] In another embodiment of the present invention, a storage medium is provided, specifically a computer-readable storage medium (Memory), which is a memory device in a computer device used to store programs and data. It is understood that the computer-readable storage medium here can include both the built-in storage medium in the computer device and extended storage media supported by the computer device. The computer-readable storage medium provides storage space that stores the terminal's operating system. Furthermore, the storage space also stores one or more instructions suitable for loading and execution by a processor. These instructions can be one or more computer programs (including program code). It should be noted that the computer-readable storage medium here can be Random Access Memory (RAM) or non-volatile memory, such as at least one disk storage device. The processor can load and execute one or more instructions stored in the computer-readable storage medium to implement the corresponding steps of the above embodiment regarding a method for predictive control of the dynamic characteristics of deep peak shaving dry-wet state transition in an ultra-supercritical boiler.

[0091] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, optical storage, etc.) containing computer-usable program code.

[0092] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0093] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0094] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0095] This invention also provides a computer program product for executing any of the above-described methods for predictive control of dynamic characteristics during dry-wet state transition in ultra-supercritical boilers with deep peak shaving. Since the computer program product provided by this invention belongs to the same inventive concept as the above-described method for predictive control of dynamic characteristics during dry-wet state transition in ultra-supercritical boilers with deep peak shaving, the computer program product provided by this invention possesses all the advantages of the above-described method for predictive control of dynamic characteristics during dry-wet state transition in ultra-supercritical boilers with deep peak shaving. Therefore, the beneficial effects of the computer program product provided by this invention will not be elaborated upon here.

[0096] In this invention, the terms "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to a specific feature, structure, material, or characteristic described in connection with that embodiment or example, which is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0097] Finally, it should be noted that the above-described embodiments are merely specific implementations of the present invention, used to illustrate the technical solutions of the present invention, and not to limit them. The scope of protection of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments within the scope of the technology disclosed in the present invention, or make equivalent substitutions for some of the technical features; and these modifications, changes, 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 the present invention, and should all be covered within the scope of protection of the present invention.

Claims

1. A predictive control method for the dynamic characteristics of dry-wet state transition during deep peak shaving in an ultra-supercritical boiler, characterized in that, Applications in coal-fired power generation unit control systems include: Obtain the dry-state stable operating parameters of the boiler heating surface circuit before the dry-wet state transition, as well as the preset boundary condition change data during the transition process. The boundary condition change data includes at least the changes in heating surface heat load, working fluid inlet enthalpy, inlet mass flow rate, and outlet pressure over time. Using the dry-state stable operating parameters as initial conditions and the boundary condition change data as input, the pre-constructed transient hydrodynamic calculation model is used for iterative calculation to obtain the predicted values ​​of key parameters characterizing the dynamic characteristics within the heated surface during the conversion process. The transient hydrodynamic calculation model is established based on the one-dimensional homogeneous flow assumption and coupled solution of the transient control equation of the fluid domain and the transient heat conduction equation of the metal tube wall. Based on the predicted values ​​of the key parameters, control strategy recommendations for the dry-wet transition process are generated and output. The control strategy recommendations include at least the load reduction rate optimization recommendation and / or the timing recommendation for switching the enthalpy-water level control strategy.

2. The method for predictive control of dynamic characteristics of deep peak shaving dry-wet state transition in an ultra-supercritical boiler according to claim 1, characterized in that, The dry-state stable operating parameters include: The inlet pressure, outlet pressure, inlet temperature, outlet temperature, and inlet mass flow rate of the water-cooled wall during dry stable operation.

3. The method for predictive control of dynamic characteristics of deep peak shaving dry-wet state transition in an ultra-supercritical boiler according to claim 2, characterized in that, The step of using the dry-state stable operating parameters as initial conditions includes: Based on the inlet pressure, outlet pressure, inlet temperature, outlet temperature, and inlet mass flow rate of the water-cooled wall during dry stable operation, the initial distribution of working fluid pressure, flow rate, enthalpy, and density along the length of the heated surface tube is determined as the initial conditions for the transient hydrodynamic calculation model.

4. The method for predictive control of dynamic characteristics of deep peak shaving dry-wet state transition in an ultra-supercritical boiler according to claim 1, characterized in that, The acquisition of preset boundary condition change data during the conversion process includes: The changes in the heat load of the heating surface, the inlet enthalpy of the working fluid, the inlet mass flow rate, and the outlet pressure over time can be directly obtained or calculated from the variable operating conditions preset by the automatic power generation control system based on the grid dispatch instructions.

5. The method for predictive control of dynamic characteristics of deep peak shaving dry-wet state transition in an ultra-supercritical boiler according to claim 1, characterized in that, The transient control equations of the fluid domain obtained by the coupled solution of the transient hydrodynamic calculation model include: mass conservation equation: Momentum conservation equation: Energy conservation equation: And the equation of state, used to determine fluid density in single-phase and two-phase regions based on fluid pressure and enthalpy; The transient heat conduction equation of the metal tube wall is: In the formula, The area of ​​circulation within the pipe, For fluid density, For time, For the working fluid mass flow rate, Position along the longitudinal axis of the pipe. For fluid pressure, The angle between the flow direction and the horizontal direction. The coefficient of frictional resistance. The inner diameter of the pipe. , , These are the resistance coefficients for the inlet, outlet, and elbow, respectively. This is the total length of the pipeline. This refers to the enthalpy of the fluid. The heat released per unit length of the inner wall, The metal outer wall absorbs heat. Specific heat capacity of the metal The mass of metal per unit length of tube This refers to the temperature of the inner wall.

6. The method for predictive control of dynamic characteristics of deep peak shaving dry-wet state transition in ultra-supercritical boilers according to claim 5, characterized in that, During the iterative calculation, the heat release per unit length of the inner wall is updated using the following simplified convective heat transfer equation. : In the formula, superscript and Representing the previous time layer and the current computation time layer respectively, the subscripts... Represents spatial nodes. The fluid convective heat transfer coefficient, For heat exchange area, The inner wall temperature The temperature of the working fluid.

7. The method for predictive control of dynamic characteristics of deep peak shaving dry-wet state transition in ultra-supercritical boilers according to claim 5, characterized in that, The iterative calculation using a pre-built transient hydrodynamic calculation model specifically includes: In the current calculation layer, assuming the inlet pressure of the heated surface, spatial propagation calculation is performed from the inlet to the outlet, one control volume at a time. Within each control volume, the mass conservation equation, momentum conservation equation, energy conservation equation, and state equation are solved simultaneously through multiple iterations until the calculated outlet density meets the preset accuracy requirements. When the space advances to the outlet of the heated surface and the calculated outlet pressure is obtained, the calculated outlet pressure is compared with the outlet pressure used as a boundary condition. If the relative error does not meet the preset accuracy requirements, the assumed inlet pressure of the heated surface is corrected and the space advance calculation is performed again until the outlet pressure meets the convergence condition.

8. The method for predictive control of dynamic characteristics of deep peak shaving dry-wet state transition in ultra-supercritical boilers according to claim 1, characterized in that, The predicted values ​​of the key parameters include the trend of superheat at the midpoint, and the trend of the water level in the water tank or parameters related to the water level in the water tank. The generation and output of control strategy recommendations for the dry-wet transition process include: Based on the trend of superheat change at the midpoint, the proposed optimization of the load reduction rate is generated. as well as, Based on the changing trend of the water level in the storage tank or parameters related to the water level in the storage tank, a suggestion for switching the enthalpy-water level control strategy is generated.

9. A computer 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 a predictive control method for the dynamic characteristics of deep peak shaving and wet-dry state conversion in an ultra-supercritical boiler as described in any one of claims 1 to 8.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the dynamic characteristic prediction and control method for deep peak shaving and wet-dry state conversion of an ultra-supercritical boiler as described in any one of claims 1 to 8.

Images