Supercritical unit variable condition frequency modulation equivalent modeling method and system and medium

Abstract

The power system operation control relates to the technical field, and particularly relates to a supercritical unit variable condition frequency modulation equivalent modeling method, system and medium, the method comprises the following steps: obtaining the operation data of the supercritical unit at the starting moment of the primary frequency modulation under the variable condition, and determining the initial boundary condition; establishing a distributed parameter mechanism model based on the conservation of mass, energy and momentum; performing approximate equivalent transformation on the distributed parameter mechanism model to obtain a lumped parameter equivalent model; identifying the model parameters using the primary frequency modulation response data to obtain a frequency modulation dynamic model; solving the primary frequency modulation dynamic response based on the frequency modulation dynamic model, and determining the primary frequency modulation capacity. Through the present application, the problem that the existing supercritical unit primary frequency modulation model is difficult to consider both the accurate representation of the thermal mechanism and the efficient application of the power grid dynamic simulation under the variable condition is effectively solved.

Description

Technical Field

[0001] This invention relates to the field of power system operation and control technology, and in particular to an equivalent modeling method, system and medium for frequency regulation under varying operating conditions of supercritical units. Background Technology

[0002] With the high proportion of new energy integration and the increasing complexity of grid operation, thermal power units need to undertake more frequent primary frequency regulation tasks in scenarios such as deep peak shaving, rapid load changes, and frequency disturbance support. When supercritical units operate under varying conditions, their main steam pressure, main steam flow, steam energy storage, heat absorption state of the heating surface, and valve margin will change significantly with load levels and control strategies. This means that the unit's primary frequency regulation response is no longer determined solely by simple valve opening or rated operating parameters, but is jointly influenced by the boiler-side thermal processes, the pressure propagation of the main steam system, and the turbine power conversion process.

[0003] In existing technologies, thermal power unit models used for power grid dynamic simulation typically employ lumped parameter or empirical equivalent models. While these models are simple in structure and computationally efficient, their parameters largely depend on typical operating conditions, resulting in unclear physical meanings and difficulty in accurately characterizing the frequency regulation dynamics of supercritical units under varying operating conditions, which are jointly determined by steam inventory, steam quality, heat input from heating surfaces, and valve position margins. Other distributed parameter models based on thermodynamic mechanisms, while capable of describing the working fluid flow, heat transfer, and pressure changes in greater detail, require complex spatiotemporal discretization solutions, making it difficult to directly establish input-output mapping relationships suitable for online power grid simulation, operation adjustment, and safety and stability verification. Consequently, existing technologies struggle to simultaneously achieve accurate thermodynamic mechanism representation and efficient engineering simulation in primary frequency regulation analysis under varying operating conditions, thus affecting the accuracy and applicability of supercritical unit frequency regulation capability assessment, control parameter tuning, and operational safety boundary judgment.

[0004] The information disclosed in this background section is intended only to enhance the understanding of the general background of this disclosure and should not be construed as an admission or in any way implying that the information constitutes prior art known to those skilled in the art. Summary of the Invention

[0005] This invention provides an equivalent modeling method, system, and medium for frequency regulation under varying operating conditions in supercritical units, which can effectively solve the problems in the background art.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows: A method for equivalent modeling of frequency regulation under varying operating conditions in supercritical units, the method comprising: The operating data of the supercritical unit at the start of primary frequency regulation under variable operating conditions is obtained, and the initial boundary conditions of the supercritical unit are determined based on the operating data. Based on the operating data and the initial boundary conditions, a distributed parameter mechanism model characterizing the primary frequency regulation thermodynamic dynamics of the supercritical unit is established based on the conservation of mass, energy, and momentum. An approximate equivalent transformation is performed on the distributed parameter mechanism model to obtain a lumped parameter equivalent model characterizing the coupled dynamic relationship between main steam pressure, main steam flow rate and unit power; The model parameters of the lumped parameter equivalent model are identified using the primary frequency regulation response data of the supercritical unit to obtain a frequency regulation dynamic model suitable for the variable operating conditions. The primary frequency regulation dynamic response of the supercritical unit is solved based on the frequency regulation dynamic model, and the primary frequency regulation capability of the supercritical unit is determined based on the primary frequency regulation dynamic response.

[0007] Furthermore, the operating data at the start of the primary frequency regulation under varying operating conditions is acquired, and the initial boundary conditions are determined, including: The steam state data, valve state data, heating state data, and load frequency state data of the supercritical unit at the start of the primary frequency regulation under the variable operating condition are obtained, and the steam state data, valve state data, heating state data, and load frequency state data are used as the operating data. Based on the operating data, the feedwater side boundary, main steam side boundary, valve side boundary, heating surface side boundary, and load frequency side boundary of the supercritical unit are determined, and the feedwater side boundary, main steam side boundary, valve side boundary, heating surface side boundary, and load frequency side boundary are used as the initial boundary conditions. The operating data is obtained from at least one of the following data sources: the distributed control system of the supercritical unit, the turbine electro-hydraulic control system, historical test data, and real-time operating data, and the initial boundary conditions are updated using the operating data.

[0008] Furthermore, a distributed parameter mechanism model characterizing the primary frequency regulation thermodynamic dynamics of the supercritical unit is established, including: Based on the operating data and the initial boundary conditions, the boiler heating surface, main steam passage, high-pressure regulating valve and turbine main steam inlet participating in the variable operating condition primary frequency regulation in the supercritical unit are determined, and the boiler heating surface, the main steam passage, the high-pressure regulating valve and the turbine main steam inlet are used as modeling objects; Based on the working fluid density, working fluid velocity, working fluid pressure, working fluid temperature, working fluid enthalpy and heat input of the heated surface in the modeling object, the mass conservation relationship, energy conservation relationship and momentum conservation relationship of the modeling object are established. By coupling the mass conservation relationship, the energy conservation relationship, and the momentum conservation relationship, a distribution parameter mechanism model characterizing the changes in thermodynamic parameters with time and space during the primary frequency regulation of the supercritical unit under varying operating conditions is obtained.

[0009] Furthermore, the distributed parameter mechanism model is approximated by an equivalent transformation to obtain a lumped parameter equivalent model characterizing the coupled dynamic relationship between main steam pressure, main steam flow rate, and unit power, including: Under the condition that the supercritical unit enters the variable operating condition primary frequency regulation from steady state, the time variation term in the distributed parameter mechanism model is set to zero to obtain a steady-state model for solving the initial thermodynamic distribution. Based on the feedwater pressure, main steam pressure, inlet enthalpy, and outlet enthalpy in the operating data, the working fluid flow region in the steady-state model is divided into thermodynamic states, and the boundary temperature and boundary enthalpy of each segment are determined. Based on the boundary temperature of each segment, the boundary enthalpy of each segment, and the heat input of the heated surface in the initial boundary conditions, calculate the heat distribution, segment length, and heat transfer parameters of each segment. The pressure drop distribution of each segment is calculated based on the segment length, working fluid viscosity parameters, and flow resistance parameters. The boundary temperature, boundary enthalpy, segment length, and heat transfer parameters of each segment are updated according to the pressure drop distribution of each segment, and the initial equilibrium parameters corresponding to each segment are obtained when the results of two adjacent calculations meet the preset convergence conditions.

[0010] Furthermore, the thermodynamic state is segmented, including: Based on the working fluid phase state and thermodynamic state in the working fluid flow region, the working fluid flow region is divided into a subcooled section and a supercritical section, and lumped parameter modules corresponding to the subcooled section and the supercritical section are established. When a vapor-liquid coexistence process or an equivalent phase change process exists in the working fluid flow region, a two-phase section is set between the subcooled section and the supercritical state section, and a lumped parameter module corresponding to the two-phase section is established. Based on the initial equilibrium parameters corresponding to at least two of the subcooled section, the two-phase section, and the supercritical state section, a two-segment or three-segment lumped parameter structure is formed for performing the approximate equivalent transformation.

[0011] Furthermore, the lumped parameter equivalent model is established, including: Based on the initial equilibrium parameters, the difference between the module inlet mass flow rate and the module outlet mass flow rate in the distributed parameter mechanism model is converted into the module average density change, and the module average density change is converted into the module pressure change based on the gas-water working fluid property function, so as to obtain the mass conservation equivalent relationship between flow rate, density and pressure. Based on the initial equilibrium parameters, the module net heat flux, module inlet enthalpy, module outlet enthalpy, and module equivalent mass in the distributed parameter mechanism model are converted into the change in module average enthalpy or module average temperature to obtain the energy conservation equivalent relationship between heat flux, enthalpy, and temperature. Based on the initial equilibrium parameters, the module inlet pressure, module outlet pressure, friction resistance, and local resistance in the distributed parameter mechanism model are converted into changes in module mass flow rate or module velocity to obtain the momentum conservation equivalent relationship between pressure, resistance, and flow rate. By coupling the mass conservation equivalent relation, the energy conservation equivalent relation, and the momentum conservation equivalent relation, a lumped parameter equivalent model is constructed that characterizes the dynamic coupling relationship between the main steam pressure, the main steam flow rate, the main steam enthalpy, and the unit power.

[0012] Furthermore, a frequency regulation dynamic model applicable to the aforementioned variable operating conditions is established, including: The measured data of main steam pressure, main steam flow, unit power, main steam temperature, and valve position change of the supercritical unit during the primary frequency regulation process under the variable operating conditions are obtained, and the measured data of main steam pressure, main steam flow, unit power, main steam temperature, and valve position change are used as the primary frequency regulation response data. Based on the deviation between the primary frequency modulation response data and the model output of the lumped parameter equivalent model, a parameter identification objective function is established to identify the model parameters. Based on the parameter identification objective function, at least one of the model parameters in the lumped parameter equivalent model, including the equivalent inertia constant, proportional coefficient, pressure-density transformation coefficient, enthalpy-pressure coupling coefficient, and valve position margin correlation coefficient, is identified and corrected. The model parameters are corrected online or offline using at least one parameter identification algorithm among recursive least squares, Kalman filtering, neural network regression, and support vector regression to obtain the frequency modulation dynamic model suitable for the variable operating conditions.

[0013] Furthermore, the dynamic response of the primary frequency regulation of the supercritical unit is solved, and the primary frequency regulation capability is determined, including: The initial boundary conditions and the identified and corrected model parameters are input into the frequency regulation dynamic model to solve the primary frequency regulation dynamic response of the main steam pressure, the main steam flow rate, the main steam enthalpy, and the unit power as a function of time. Based on the primary frequency regulation dynamic response, the maximum adjustable power, equivalent inertia constant, and proportional coefficient of the supercritical unit under the variable operating conditions are determined. Based on the first frequency regulation dynamic response, the lower limit constraint of main steam pressure, the main steam temperature deviation constraint and the valve position margin limit of the supercritical unit under the variable operating conditions are determined. Based on the maximum adjustable power, the equivalent inertia constant, the proportional coefficient, the main steam pressure lower limit constraint, the main steam temperature deviation constraint, and the valve position margin limit, the primary frequency regulation capability is obtained for power grid online operation adjustment, unit control parameter setting, or power system safety and stability verification.

[0014] A supercritical unit frequency regulation equivalent modeling system under varying operating conditions, the system comprising: The operation data acquisition module acquires the operation data of the supercritical unit at the start of primary frequency regulation under variable operating conditions, and determines the initial boundary conditions of the supercritical unit based on the operation data. The mechanism model construction module establishes a distributed parameter mechanism model characterizing the primary frequency regulation thermodynamic dynamics of a supercritical unit based on operating data and initial boundary conditions, and on the principles of mass conservation, energy conservation, and momentum conservation. The equivalent model generation module performs an approximate equivalent transformation on the distributed parameter mechanism model to obtain a lumped parameter equivalent model that characterizes the coupled dynamic relationship between main steam pressure, main steam flow rate and unit power. The model parameter identification module uses the primary frequency regulation response data of the supercritical unit to identify the model parameters of the lumped parameter equivalent model, thereby obtaining a frequency regulation dynamic model suitable for variable operating conditions. The frequency regulation capability assessment module solves the primary frequency regulation dynamic response of the supercritical unit based on the frequency regulation dynamic model, and determines the primary frequency regulation capability of the supercritical unit based on the primary frequency regulation dynamic response.

[0015] A computer-readable storage medium stores a computer program, the computer program including program instructions, which, when executed by a processor, can implement the aforementioned equivalent modeling method for frequency regulation under varying operating conditions of a supercritical unit.

[0016] The technical solution of this invention can achieve the following technical effects: By acquiring primary frequency regulation operation data of supercritical units under varying operating conditions, a distributed parameter mechanism model is established based on the three conservation laws. Through approximate equivalent transformation, parameter identification, and dynamic response solution, the primary frequency regulation capability is evaluated. This effectively solves the problem that existing primary frequency regulation models for supercritical units are difficult to accurately represent the thermodynamic mechanism and efficiently apply dynamic simulation of the power grid under varying operating conditions.

[0017] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 A flowchart illustrating an equivalent modeling method for frequency regulation under varying operating conditions in a supercritical unit; Figure 2 This is a schematic diagram of the structure of the first approximate equivalent transformation mechanism model for supercritical units; Figure 3 This is a schematic diagram of the structure of the second approximate equivalent transformation mechanism model for supercritical units; Figure 4 This is a schematic diagram of the structure of the mass conservation equivalent model; Figure 5 A schematic diagram of the energy conservation equivalent model; Figure 6 This is a schematic diagram of the equivalent model of momentum conservation; Figure 7 This is a schematic diagram of the complete equivalent model; Figure 8 A schematic diagram of the dynamic response curve of the main steam pressure during primary frequency regulation under the acceptance condition of 95% steam turbine heat consumption. Detailed Implementation

[0020] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0021] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0022] Example 1; like Figure 1 As shown, this application provides an equivalent modeling method for frequency regulation under varying operating conditions in supercritical units. The method includes: S10: Obtain the operating data of the supercritical unit at the start of primary frequency regulation under variable operating conditions, and determine the initial boundary conditions of the supercritical unit based on the operating data; S20: Based on the operating data and initial boundary conditions, establish a distributed parameter mechanism model characterizing the primary frequency regulation thermodynamic dynamics of the supercritical unit based on the conservation of mass, energy and momentum; S30: Approximate equivalent transformation is performed on the distributed parameter mechanism model to obtain a lumped parameter equivalent model characterizing the coupled dynamic relationship between main steam pressure, main steam flow and unit power; S40: Using the primary frequency regulation response data of the supercritical unit, the model parameters of the lumped parameter equivalent model are identified to obtain a frequency regulation dynamic model suitable for variable operating conditions. S50: Solve the primary frequency regulation dynamic response of the supercritical unit based on the frequency regulation dynamic model, and determine the primary frequency regulation capability of the supercritical unit based on the primary frequency regulation dynamic response.

[0023] Specifically, in one implementation method, the approximate equivalent modeling method for primary frequency regulation of supercritical units under varying operating conditions includes the following process: First, before the supercritical unit enters primary frequency regulation or at the start of primary frequency regulation, the operating data of the supercritical unit is obtained from the unit's distributed control system, the turbine electro-hydraulic control system, historical test data, or real-time operating data. The operating data includes feedwater pressure, main steam pressure, main steam temperature, main steam flow rate, steam volume, valve position margin, unit load, frequency deviation, feedwater flow rate, valve opening command, and heat input of the heating surface. Based on the operating data, the feedwater side boundary, main steam side boundary, valve side boundary, heating surface side boundary, and load frequency side boundary of the supercritical unit are determined to form initial boundary conditions. Then, based on the operating data and initial boundary conditions, the boiler heating surface, main steam passage, high-pressure regulating valve, and turbine main steam inlet are taken as modeling objects. The working fluid density, flow velocity, pressure, temperature, enthalpy, and heat input are taken as state variables. The mass conservation equation, energy conservation equation, and momentum conservation equation of the modeling objects are established respectively. Then, the mass conservation equation, energy conservation equation, and momentum conservation equation are coupled to obtain a distribution parameter mechanism model that can characterize the changes of thermodynamic parameters with time and space in the primary frequency regulation process of the supercritical unit. Subsequently, under the condition that the supercritical unit enters primary frequency regulation from steady state, the distributed parameter mechanism model is stabilized, and the modeling object is divided into at least two segments among the subcooled segment, two-phase segment and supercritical state segment according to the thermodynamic state of the working fluid. The initial equilibrium parameters of the distributed parameter mechanism model are obtained by iteratively calculating the boundary temperature, boundary enthalpy, heat distribution, segment length, heat transfer parameters and pressure drop distribution of each segment. Next, based on the initial equilibrium parameters, the distributed parameter mechanism model is subjected to an approximate equivalent transformation. Specifically, the difference between the module inlet mass flow rate and the module outlet mass flow rate is converted into the module average density change, and further converted into the module pressure change, to form a mass conservation equivalent relationship. The module net heat flow, module inlet enthalpy, module outlet enthalpy, and module equivalent mass are converted into the module average enthalpy or module average temperature change, to form an energy conservation equivalent relationship. The module inlet pressure, module outlet pressure, friction loss, and local resistance are converted into the module mass flow rate or velocity change, to form a momentum conservation equivalent relationship. Finally, the mass conservation equivalent relationship, energy conservation equivalent relationship, and momentum conservation equivalent relationship are coupled to obtain a lumped parameter equivalent model characterizing the coupled dynamic relationship between main steam pressure, main steam flow rate, and unit power. Subsequently, using the primary frequency regulation response data collected during the primary frequency regulation test or actual operation of the supercritical unit, the model parameters in the lumped parameter equivalent model are identified. The model parameters include at least one of the following: equivalent inertia constant, proportional coefficient, pressure-density transformation coefficient, enthalpy-pressure coupling coefficient, and valve position margin correlation coefficient. During the identification process, the deviation between the measured response and the model output of the main steam pressure, main steam flow, main steam temperature, unit power, and valve position changes is used as the objective function. The model parameters are corrected online or offline using at least one of the following methods: recursive least squares, Kalman filtering, neural network regression, or support vector regression, thereby obtaining a frequency regulation dynamic model suitable for variable operating conditions. Finally, the initial boundary conditions and the identified model parameters are input into the frequency regulation dynamic model to solve the dynamic response of the supercritical unit to the changes in main steam pressure, main steam flow, main steam enthalpy, and unit power over time during the primary frequency regulation process. Based on the dynamic response, the maximum adjustable power, equivalent inertia constant, proportional coefficient, lower limit constraint of main steam pressure, main steam temperature deviation constraint, and valve position margin limit of the supercritical unit under varying operating conditions are determined. Thus, the primary frequency regulation capability of the supercritical unit is obtained. The primary frequency regulation capability can be used for online operation adjustment of the power grid, unit control parameter tuning, and power system safety and stability verification.

[0024] The technical solution of this invention obtains primary frequency regulation operation data of supercritical units under varying operating conditions, establishes a distributed parameter mechanism model based on the three conservation laws, and achieves primary frequency regulation capability assessment through approximate equivalent transformation, parameter identification, and dynamic response solution. This effectively solves the problem that existing primary frequency regulation models for supercritical units are difficult to accurately represent the thermodynamic mechanism and efficiently apply dynamic simulation of the power grid under varying operating conditions.

[0025] Furthermore, acquiring the operating data at the start of primary frequency regulation under varying operating conditions and determining the initial boundary conditions includes: Acquire steam and water state data, valve state data, heating state data, and load frequency state data of the supercritical unit at the start of primary frequency regulation under variable operating conditions, and use the steam and water state data, valve state data, heating state data, and load frequency state data as operating data; The feedwater side boundary, main steam side boundary, valve side boundary, heating surface side boundary, and load frequency side boundary of the supercritical unit are determined based on the operating data, and the feedwater side boundary, main steam side boundary, valve side boundary, heating surface side boundary, and load frequency side boundary are used as the initial boundary conditions. Operational data is obtained from at least one of the following data sources: the distributed control system of the supercritical unit, the turbine electro-hydraulic control system, historical test data, and real-time operation data, and the initial boundary conditions are updated using the operational data.

[0026] Furthermore, a distributed parameter mechanism model characterizing the primary frequency regulation thermodynamic dynamics of a supercritical unit is established, including: Based on the operating data and initial boundary conditions, the boiler heating surface, main steam passage, high-pressure regulating valve and turbine main steam inlet that participate in the primary frequency regulation under variable operating conditions in the supercritical unit are determined, and the boiler heating surface, main steam passage, high-pressure regulating valve and turbine main steam inlet are taken as modeling objects. Based on the working fluid density, working fluid velocity, working fluid pressure, working fluid temperature, working fluid enthalpy and heat input of the heated surface in the modeling object, the mass conservation relationship, energy conservation relationship and momentum conservation relationship of the modeling object are established. By coupling the mass conservation relationship, energy conservation relationship, and momentum conservation relationship, a distribution parameter mechanism model characterizing the changes of thermodynamic parameters with time and space during the primary frequency regulation process of a supercritical unit under varying operating conditions is obtained.

[0027] As a preferred embodiment of the above, firstly, a distributed parameter model that can reflect the spatiotemporal evolution of thermodynamic parameters is established; secondly, the initial equilibrium point is solved under steady-state start-up conditions; then, drawing on the Norton equivalent concept of circuits, the distributed parameter processes reflecting mass transfer, energy transfer, and momentum transfer are respectively converted into equivalent transfer relationships between several lumped nodes, forming an ordinary differential model that can directly participate in the dynamic simulation of the power grid; finally, the mechanism coefficients are identified using primary frequency regulation test data, forming a hybrid modeling scheme that combines mechanism and data-driven approaches. To address the flow, heat transfer, and pressure propagation of compressible fluids in boilers and main steam systems, this invention employs mass conservation equations, momentum conservation equations, and energy conservation equations to construct a distributed parameter model, the basic form of which can be expressed as: mass conservation equation: ; Momentum conservation equation: ; Energy conservation and heat transfer equations: ; Where ρ is the density of the working fluid, and c p Here, λ is the specific heat capacity at constant pressure, t is the thermal conductivity, T is the working fluid temperature, U is the working fluid velocity vector, P is the working fluid pressure, t is time, f is the volume force term, τ is the viscous stress tensor, ρUU represents the dextral product of velocity vectors U and U, x, y, z are the spatial coordinate directions, and u, v, w are the components of the velocity vector in the x, y, z directions; the frequency modulation dynamic process is determined by the initial thermodynamic state and the three conservation equations. Furthermore, by performing an approximate equivalent transformation on the distributed parameter mechanism model, a lumped parameter equivalent model characterizing the coupled dynamic relationship between main steam pressure, main steam flow rate, and unit power is obtained, including: Under the condition that the supercritical unit enters the variable operating condition primary frequency regulation from steady state, the time variation term in the distributed parameter mechanism model is set to zero to obtain a steady-state model for solving the initial thermodynamic distribution. Based on the feedwater pressure, main steam pressure, inlet enthalpy, and outlet enthalpy in the operating data, the working fluid flow region in the steady-state model is divided into thermodynamic states, and the boundary temperature and boundary enthalpy of each segment are determined. Based on the boundary temperature, boundary enthalpy, and heat input of the heated surface in the initial boundary conditions of each segment, calculate the heat distribution, segment length, and heat transfer parameters of each segment. The pressure drop distribution of each segment is calculated based on the segment length, working fluid viscosity parameters, and flow resistance parameters. The boundary temperature, boundary enthalpy, segment length, and heat transfer parameters of each segment are updated based on the pressure drop distribution of each segment, and the initial equilibrium parameters corresponding to each segment are obtained when the results of two consecutive calculations meet the preset convergence conditions.

[0028] As a preferred embodiment of the above embodiments, in one preferred implementation, assuming that the primary frequency modulation starts from a steady state, the time term in the distributed parameter model is set to zero, and only the spatial term is retained to solve for the distribution of thermodynamic parameters along the path. The solution process can be carried out using a piecewise iterative method: (1) Based on the constant pressure heat absorption characteristics of the boiler, we first approximate the assumption that the segmented pressure remains constant in the current iteration round in order to determine the phase change boundary temperature and enthalpy value; (2) Based on the inlet and outlet enthalpy values ​​and the total heat conservation relationship, solve for the temperature distribution, heat transfer coefficient and segment length of the subcooled section, the two-phase section and the superheated or supercritical state respectively; (3) Based on the obtained segment length and flow resistance, distribute the pressure drop of each segment according to the ratio of the viscosity coefficients of the liquid phase and the gas phase; (4) After considering the small changes in pressure along the friction, update the phase change boundary, segment length and heat transfer coefficient; (5) Repeat steps (2) to (4) until the pressure, temperature and segment length converge; Under normal operating conditions of a supercritical unit, the two-phase section can be degenerated into an equivalent phase transition section or incorporated into the supercritical state section. However, to maintain the model's compatibility with different operating states, the three-phase unified expression method is still retained.

[0029] Furthermore, the thermal state segmentation includes: Based on the phase state and thermodynamic state of the working fluid in the flow region, the flow region is divided into a subcooled section and a supercritical section, and lumped parameter modules corresponding to the subcooled section and the supercritical section are established. When a vapor-liquid coexistence process or an equivalent phase change process exists in the working fluid flow region, a two-phase section is set between the subcooled section and the supercritical state section, and a lumped parameter module corresponding to the two-phase section is established. Based on the initial equilibrium parameters corresponding to at least two segments of the subcooled section, two-phase section, and supercritical state section, a two- or three-segment lumped parameter structure is formed for approximate equivalent transformation.

[0030] As a preferred embodiment of the above, the numerical solution method based on the partial differential equation system needs to be discretized and iterated simultaneously at multiple time steps and spatial steps. The main steam pressure and main steam flow rate at each time step need to be input as thermodynamic parameters of all spatial points of the previous time step. Therefore, although a more refined spatiotemporal distribution result can be obtained, it is difficult to form an input-output direct mapping relationship suitable for online operation and adjustment of the power system, and it is also difficult to explicitly incorporate the safety threshold of intermediate variables into a unified analytical expression of frequency regulation capability. While theoretically a high fidelity can be achieved by directly combining such partial differential solution models with ordinary differential dynamic models of power systems, significant engineering challenges exist in parameter tuning, initial state setting, mechanism coefficient identification, and fault tracing. Therefore, it is necessary to construct an approximate equivalent model that can preserve key thermodynamic mechanisms and has an ordinary differential expression.

[0031] Furthermore, establishing a lumped parameter equivalent model includes: Based on the initial equilibrium parameters, the difference between the module inlet mass flow rate and the module outlet mass flow rate in the distributed parameter mechanism model is converted into the module average density change. Then, based on the gas-water working fluid property function, the module average density change is converted into the module pressure change to obtain the mass conservation equivalent relationship between flow rate, density, and pressure. Based on the initial equilibrium parameters, the module net heat flux, module inlet enthalpy, module outlet enthalpy, and module equivalent mass in the distributed parameter mechanism model are converted into the change in module average enthalpy or module average temperature, so as to obtain the energy conservation equivalent relationship between heat flux, enthalpy, and temperature. Based on the initial equilibrium parameters, the module inlet pressure, module outlet pressure, friction resistance, and local resistance in the distributed parameter mechanism model are converted into changes in module mass flow rate or module velocity to obtain the momentum conservation equivalent relationship between pressure, resistance, and flow rate. By coupling the equivalent relations of mass conservation, energy conservation, and momentum conservation, a lumped parameter equivalent model is constructed to characterize the dynamic coupling relationship between main steam pressure, main steam flow rate, main steam enthalpy, and unit power.

[0032] As a preferred embodiment of the above, drawing on the Norton equivalent concept, the continuous spatial distribution of the boiler and main steam system is concentrated into several nodes with clear physical meanings, and lumped parameter dynamic equations are established for mass conservation, energy conservation and momentum conservation respectively. For the i-th lumped parameter module, its mass conservation can be expressed in equivalent form as: ; ; Wherein, ρᵢ is the average density of the working fluid within the i-th lumped parameter module, and G...i ,in and G i ,out represent the module's inlet and outlet mass flow rates, respectively, V i For the equivalent volume of the module, K p ρ, i The pressure-density transformation coefficient is determined by the working fluid property function; the above relationship corresponds to Figure 4 The mass conservation equivalent model shown; For the i-th lumped parameter module, its energy conservation can be expressed in equivalent form as: ; Among them, Q i h is the net heat flux of the module. i h is the average enthalpy of the module. i ,in is the enthalpy of the inlet working fluid, h i ,out represents the specific enthalpy of the working fluid at the outlet, M i For the equivalent mass of the module; the energy conservation equivalent model is as follows: Figure 5 As shown; For the i-th lumped parameter module, its momentum conservation can be expressed in equivalent form as: ; Among them, G i Let K_G be the equivalent mass flow rate within or through the i-th lumped parameter module. i P is the momentum transfer equivalence coefficient. i ,in represents the inlet-side pressure of the i-th lumped parameter module, P i ,out represents the outlet pressure of the i-th lumped parameter module, ΔPloss, i The equivalent loss term consists of frictional resistance and local resistance; the momentum conservation equivalent model is as follows: Figure 6 As shown; Furthermore, the main steam flow rate, main steam pressure, and main steam enthalpy all affect the turbine power response, and their equivalent output relationship can be expressed as: ΔP e = K1·ΔGms + K2·ΔPms + K3·Δhms; Wherein, ΔP e Let ΔGms be the change in active power of the unit, ΔPms be the change in main steam flow rate, Δhms be the change in main steam pressure, and K1, K2, and K3 be the coupling coefficients to be identified. Through the above equivalent transformation, the original partial differential model can be compressed into a lumped parameter model suitable for control and simulation. Figure 2 and Figure 3 Two optional model topologies are shown. Figure 7 The complete equivalent model used for simulation is shown.

[0033] Furthermore, establishing a frequency regulation dynamic model applicable to varying operating conditions includes: Acquire measured data of main steam pressure, main steam flow, unit power, main steam temperature, and valve position change of the supercritical unit during the primary frequency regulation process under varying operating conditions, and use these data as primary frequency regulation response data. Based on the deviation between the primary frequency regulation response data and the model output of the lumped parameter equivalent model, a parameter identification objective function is established to identify the model parameters. Based on the objective function of parameter identification, at least one of the model parameters in the lumped parameter equivalent model, namely the equivalent inertia constant, proportional coefficient, pressure-density transformation coefficient, enthalpy-pressure coupling coefficient, and valve position margin correlation coefficient, is identified and corrected. By employing at least one parameter identification algorithm among recursive least squares, Kalman filtering, neural network regression, and support vector regression, the model parameters are calibrated online or offline to obtain a frequency modulation dynamic model suitable for varying operating conditions.

[0034] Furthermore, solving for the primary frequency regulation dynamic response of a supercritical unit and determining its primary frequency regulation capability includes: The initial boundary conditions and the identified and corrected model parameters are input into the frequency regulation dynamic model to solve the primary frequency regulation dynamic response of the main steam pressure, main steam flow, main steam enthalpy and unit power as a function of time. Based on the dynamic response of a single frequency regulation, the maximum adjustable power, equivalent inertia constant, and proportional coefficient of the supercritical unit under varying operating conditions are determined. Based on the dynamic response of a single frequency regulation, the lower limit constraint of main steam pressure, the main steam temperature deviation constraint, and the valve position margin limit of the supercritical unit under variable operating conditions are determined. Based on the maximum adjustable power, equivalent inertia constant, proportional coefficient, main steam pressure lower limit constraint, main steam temperature deviation constraint, and valve position margin limit, the primary frequency regulation capability is obtained for power grid online operation adjustment, unit control parameter setting, or power system safety and stability verification.

[0035] As a preferred embodiment of the above embodiments, to improve the adaptability of the model under different loads and control logics, this invention employs an identification method combining mechanistic models and experimental data to determine key coefficients. Parameter identification can be based on the following objective function: min ( θ ) Σ t ‖ymeas(t) - ymodel(t; θ)‖ 2 ; Wherein, θ includes the equivalent inertia constant, proportionality coefficient, pressure-density transformation coefficient, enthalpy-pressure coupling coefficient, and valve position margin correlation coefficient; ymeas(t) is the experimentally measured output, and ymodel(t; θ) is the model output; the identification algorithm can adopt at least one of the following methods: recursive least squares, extended Kalman filtering, neural network regression, support vector regression, etc.; for residual terms that are difficult to fully represent by the mechanism model, a lightweight data-driven correction term can be further introduced to form a mechanism-data fusion model; After obtaining the identified lumped parameter model, the primary frequency regulation capability under different loads, different valve position margins, and different initial steam stock can be analytically evaluated. Preferably, the lower limit of main steam pressure, the limit of main steam temperature deviation, and the lower limit of valve position margin are used as safety constraints to determine the unit's maximum sustainable frequency regulation power, equivalent inertia constant, and proportional coefficient. The evaluation results can be directly used for grid online operation adjustment, unit control parameter optimization, and multi-unit system fault disturbance support capability analysis. In a preferred embodiment, primary frequency regulation test data under the 95% turbine heat consumption acceptance THA condition of a supercritical unit is selected as the verification object. Measurement data such as feedwater pressure, main steam pressure, main steam temperature, main steam flow rate, power output, and valve position changes are collected, and a complete equivalent model is constructed according to the aforementioned steps, such as... Figure 7 As shown.

[0036] The measured curves were compared with the model outputs. The dynamic response of the main steam pressure under 95% THA conditions is as follows: Figure 8 As shown, the model simulation values ​​can track the changing trend of the measured values ​​well. They can reflect the rapid decrease in main steam pressure caused by the release of main steam stock in the early stage of frequency regulation, as well as the gradual change caused by the subsequent heat input compensation of the heating surface and flow redistribution. This verifies the effectiveness of the model of the present invention in primary frequency regulation analysis under high load and variable operating conditions. Under 80% THA conditions, the initial equilibrium point is re-solved using the same procedure as in the aforementioned embodiments. The equivalent inertial constant, proportional coefficient, and enthalpy coupling coefficient are identified by combining the corresponding primary frequency regulation test data. Since the steam inventory, subcooling section length, and valve position margin change under this condition compared to the 95% THA condition, the mechanism coefficients are adjusted accordingly. The identified lumped parameter model can still maintain consistent tracking of the dynamic trends of main steam pressure, main steam flow, and active power. Under the 65% THA deep peak-shaving condition, the initial main steam pressure and available valve position margin of the unit are further reduced, and the ratio of the subcooled section to the supercritical section changes significantly. When modeling this condition using this scheme, the analytical evaluation of the primary frequency regulation capability at low load can be achieved by updating the segment length, heat flow distribution, and equivalent coefficients. The results show that this scheme can maintain the consistency of the model structure under deep variable load conditions and identify the key intermediate parameters that limit the frequency regulation capability, providing a basis for judging the unit's safety boundary.

[0037] Example 2; Based on the same inventive concept as the equivalent modeling method for frequency regulation under varying operating conditions of a supercritical unit in the foregoing embodiments, the present invention also provides an equivalent modeling system for frequency regulation under varying operating conditions of a supercritical unit, the system comprising: The operation data acquisition module acquires the operation data of the supercritical unit at the start of primary frequency regulation under variable operating conditions, and determines the initial boundary conditions of the supercritical unit based on the operation data. The mechanism model construction module establishes a distributed parameter mechanism model characterizing the primary frequency regulation thermodynamic dynamics of a supercritical unit based on operating data and initial boundary conditions, and on the principles of mass conservation, energy conservation, and momentum conservation. The equivalent model generation module performs an approximate equivalent transformation on the distributed parameter mechanism model to obtain a lumped parameter equivalent model that characterizes the coupled dynamic relationship between main steam pressure, main steam flow rate and unit power. The model parameter identification module uses the primary frequency regulation response data of the supercritical unit to identify the model parameters of the lumped parameter equivalent model, thereby obtaining a frequency regulation dynamic model suitable for variable operating conditions. The frequency regulation capability assessment module solves the primary frequency regulation dynamic response of the supercritical unit based on the frequency regulation dynamic model, and determines the primary frequency regulation capability of the supercritical unit based on the primary frequency regulation dynamic response.

[0038] The system described above in this invention can effectively implement an equivalent modeling method for frequency regulation under varying operating conditions of a supercritical unit, and the technical effects it can achieve are as described in the above embodiments, and will not be repeated here.

[0039] Example 3; Based on the same inventive concept as the equivalent modeling method for frequency regulation under varying operating conditions of a supercritical unit in the foregoing embodiments, the present invention also provides a computer-readable storage medium storing a computer program, the computer program including program instructions, which, when executed by a processor, can realize the equivalent modeling method for frequency regulation under varying operating conditions of a supercritical unit.

[0040] Although this application has been described in conjunction with specific features and embodiments, it is obvious that various modifications and combinations can be made thereto without departing from the spirit and scope of this application. Accordingly, this specification and drawings are merely exemplary illustrations of the application as defined herein, and are to be considered as covering any and all modifications, variations, combinations, or equivalents within the scope of this application. Clearly, those skilled in the art can make various alterations and modifications to this application without departing from its scope. Thus, if such modifications and modifications fall within the scope of this application and its equivalents, this application intends to include such modifications and modifications.

Claims

1. A method for equivalent modeling of frequency regulation under varying operating conditions in supercritical units, characterized in that, The method includes: The operating data of the supercritical unit at the start of primary frequency regulation under variable operating conditions is obtained, and the initial boundary conditions of the supercritical unit are determined based on the operating data. Based on the operating data and the initial boundary conditions, a distributed parameter mechanism model characterizing the primary frequency regulation thermodynamic dynamics of the supercritical unit is established based on the conservation of mass, energy, and momentum. An approximate equivalent transformation is performed on the distributed parameter mechanism model to obtain a lumped parameter equivalent model characterizing the coupled dynamic relationship between main steam pressure, main steam flow rate and unit power; The model parameters of the lumped parameter equivalent model are identified using the primary frequency regulation response data of the supercritical unit to obtain a frequency regulation dynamic model suitable for the variable operating conditions. The primary frequency regulation dynamic response of the supercritical unit is solved based on the frequency regulation dynamic model, and the primary frequency regulation capability of the supercritical unit is determined based on the primary frequency regulation dynamic response.

2. The equivalent modeling method for frequency regulation under varying operating conditions of supercritical units according to claim 1, characterized in that, Acquire the operating data at the start of primary frequency regulation under varying operating conditions and determine the initial boundary conditions, including: The steam state data, valve state data, heating state data, and load frequency state data of the supercritical unit at the start of the primary frequency regulation under the variable operating condition are obtained, and the steam state data, valve state data, heating state data, and load frequency state data are used as the operating data. Based on the operating data, the feedwater side boundary, main steam side boundary, valve side boundary, heating surface side boundary, and load frequency side boundary of the supercritical unit are determined, and the feedwater side boundary, main steam side boundary, valve side boundary, heating surface side boundary, and load frequency side boundary are used as the initial boundary conditions. The operating data is obtained from at least one of the following data sources: the distributed control system of the supercritical unit, the turbine electro-hydraulic control system, historical test data, and real-time operating data, and the initial boundary conditions are updated using the operating data.

3. The equivalent modeling method for frequency regulation under varying operating conditions of supercritical units according to claim 1, characterized in that, A distributed parameter mechanism model characterizing the primary frequency regulation thermodynamic dynamics of the supercritical unit is established, including: Based on the operating data and the initial boundary conditions, the boiler heating surface, main steam passage, high-pressure regulating valve and turbine main steam inlet participating in the variable operating condition primary frequency regulation in the supercritical unit are determined, and the boiler heating surface, the main steam passage, the high-pressure regulating valve and the turbine main steam inlet are used as modeling objects; Based on the working fluid density, working fluid velocity, working fluid pressure, working fluid temperature, working fluid enthalpy and heat input of the heated surface in the modeling object, the mass conservation relationship, energy conservation relationship and momentum conservation relationship of the modeling object are established. By coupling the mass conservation relationship, the energy conservation relationship, and the momentum conservation relationship, a distribution parameter mechanism model characterizing the changes in thermodynamic parameters with time and space during the primary frequency regulation of the supercritical unit under varying operating conditions is obtained.

4. The equivalent modeling method for frequency regulation under varying operating conditions of supercritical units according to claim 1, characterized in that, An approximate equivalent transformation is performed on the distributed parameter mechanism model to obtain a lumped parameter equivalent model characterizing the coupled dynamic relationship between main steam pressure, main steam flow rate, and unit power, including: Under the condition that the supercritical unit enters the variable operating condition primary frequency regulation from steady state, the time variation term in the distributed parameter mechanism model is set to zero to obtain a steady-state model for solving the initial thermodynamic distribution. Based on the feedwater pressure, main steam pressure, inlet enthalpy, and outlet enthalpy in the operating data, the working fluid flow region in the steady-state model is divided into thermodynamic states, and the boundary temperature and boundary enthalpy of each segment are determined. Based on the boundary temperature of each segment, the boundary enthalpy of each segment, and the heat input of the heated surface in the initial boundary conditions, calculate the heat distribution, segment length, and heat transfer parameters of each segment. The pressure drop distribution of each segment is calculated based on the segment length, working fluid viscosity parameters, and flow resistance parameters. The boundary temperature, boundary enthalpy, segment length, and heat transfer parameters of each segment are updated according to the pressure drop distribution of each segment, and the initial equilibrium parameters corresponding to each segment are obtained when the results of two adjacent calculations meet the preset convergence conditions.

5. The equivalent modeling method for frequency regulation under varying operating conditions of a supercritical unit according to claim 4, characterized in that, Thermodynamic state segmentation includes: Based on the working fluid phase state and thermodynamic state in the working fluid flow region, the working fluid flow region is divided into a subcooled section and a supercritical section, and lumped parameter modules corresponding to the subcooled section and the supercritical section are established. When a vapor-liquid coexistence process or an equivalent phase change process exists in the working fluid flow region, a two-phase section is set between the subcooled section and the supercritical state section, and a lumped parameter module corresponding to the two-phase section is established. Based on the initial equilibrium parameters corresponding to at least two of the subcooled section, the two-phase section, and the supercritical state section, a two-segment or three-segment lumped parameter structure is formed for performing the approximate equivalent transformation.

6. The equivalent modeling method for frequency regulation under varying operating conditions of a supercritical unit according to claim 4, characterized in that, Establishing the lumped parameter equivalent model includes: Based on the initial equilibrium parameters, the difference between the module inlet mass flow rate and the module outlet mass flow rate in the distributed parameter mechanism model is converted into the module average density change, and the module average density change is converted into the module pressure change based on the gas-water working fluid property function, so as to obtain the mass conservation equivalent relationship between flow rate, density and pressure. Based on the initial equilibrium parameters, the module net heat flux, module inlet enthalpy, module outlet enthalpy, and module equivalent mass in the distributed parameter mechanism model are converted into the change in module average enthalpy or module average temperature to obtain the energy conservation equivalent relationship between heat flux, enthalpy, and temperature. Based on the initial equilibrium parameters, the module inlet pressure, module outlet pressure, friction resistance, and local resistance in the distributed parameter mechanism model are converted into changes in module mass flow rate or module velocity to obtain the momentum conservation equivalent relationship between pressure, resistance, and flow rate. By coupling the mass conservation equivalent relation, the energy conservation equivalent relation, and the momentum conservation equivalent relation, a lumped parameter equivalent model is constructed that characterizes the dynamic coupling relationship between the main steam pressure, the main steam flow rate, the main steam enthalpy, and the unit power.

7. The equivalent modeling method for frequency regulation under varying operating conditions of supercritical units according to claim 1, characterized in that, Establishing a frequency regulation dynamic model applicable to the aforementioned variable operating conditions includes: The measured data of main steam pressure, main steam flow, unit power, main steam temperature, and valve position change of the supercritical unit during the primary frequency regulation process under the variable operating conditions are obtained, and the measured data of main steam pressure, main steam flow, unit power, main steam temperature, and valve position change are used as the primary frequency regulation response data. Based on the deviation between the primary frequency modulation response data and the model output of the lumped parameter equivalent model, a parameter identification objective function is established to identify the model parameters. Based on the parameter identification objective function, at least one of the model parameters in the lumped parameter equivalent model, including the equivalent inertia constant, proportional coefficient, pressure-density transformation coefficient, enthalpy-pressure coupling coefficient, and valve position margin correlation coefficient, is identified and corrected. The model parameters are corrected online or offline using at least one parameter identification algorithm among recursive least squares, Kalman filtering, neural network regression, and support vector regression to obtain the frequency modulation dynamic model suitable for the variable operating conditions.

8. The equivalent modeling method for frequency regulation under varying operating conditions of a supercritical unit according to claim 1, characterized in that, Solving for the primary frequency regulation dynamic response of a supercritical unit and determining its primary frequency regulation capability includes: The initial boundary conditions and the identified and corrected model parameters are input into the frequency regulation dynamic model to solve the primary frequency regulation dynamic response of the main steam pressure, the main steam flow rate, the main steam enthalpy, and the unit power as a function of time. Based on the first frequency regulation dynamic response, the maximum adjustable power, equivalent inertia constant, and proportional coefficient of the supercritical unit under the variable operating conditions are determined. Based on the first frequency regulation dynamic response, the lower limit constraint of main steam pressure, the main steam temperature deviation constraint and the valve position margin limit of the supercritical unit under the variable operating conditions are determined. Based on the maximum adjustable power, the equivalent inertia constant, the proportional coefficient, the main steam pressure lower limit constraint, the main steam temperature deviation constraint, and the valve position margin limit, the primary frequency regulation capability is obtained for power grid online operation adjustment, unit control parameter setting, or power system safety and stability verification.

9. A supercritical unit variable operating condition frequency regulation equivalent modeling system, characterized in that, The system includes: The operation data acquisition module acquires the operation data of the supercritical unit at the start of primary frequency regulation under variable operating conditions, and determines the initial boundary conditions of the supercritical unit based on the operation data. The mechanism model construction module establishes a distributed parameter mechanism model characterizing the primary frequency regulation thermodynamic dynamics of a supercritical unit based on operating data and initial boundary conditions, and on the principles of mass conservation, energy conservation, and momentum conservation. The equivalent model generation module performs an approximate equivalent transformation on the distributed parameter mechanism model to obtain a lumped parameter equivalent model that characterizes the coupled dynamic relationship between main steam pressure, main steam flow rate and unit power. The model parameter identification module uses the primary frequency regulation response data of the supercritical unit to identify the model parameters of the lumped parameter equivalent model, thereby obtaining a frequency regulation dynamic model suitable for variable operating conditions. The frequency regulation capability assessment module solves the primary frequency regulation dynamic response of the supercritical unit based on the frequency regulation dynamic model, and determines the primary frequency regulation capability of the supercritical unit based on the primary frequency regulation dynamic response.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, which includes program instructions that, when executed by a processor, can implement the equivalent modeling method for frequency regulation under varying operating conditions of a supercritical unit as described in any one of claims 1-8.

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