Power plant operation simulation method and system

Abstract

The invention relates to the technical field of intelligent simulation, and particularly provides a power plant operation simulation method and system, and the method comprises the steps: building a mathematical model of an element based on the principles of thermodynamics and fluid mechanics; constructing a simulation conservation model through mass flow energy conservation; a back-end optimization solution structure is constructed through an iterative computation optimization method, and a matrix solution of the simulation conservation model is obtained; and calculating operation parameters of each node based on the matrix solution, and calculating performance parameters and global performance parameters of the element based on the operation parameters of each node and the mathematical model of the element. Based on efficient matrix operation, the simulation precision and calculation efficiency of the large-scale complex industrial process are remarkably improved, meanwhile, the limitation of traditional commercial software is overcome, and higher flexibility and customizability are provided.

Description

Technical Field

[0001] The present invention belongs to the technical field of intelligent simulation, and in particular relates to a power plant operation simulation method and system. Background Art

[0002] In the field of industrial simulation, traditional commercial software has long dominated, but with the advancement of technology and the evolution of user needs, the limitations of these traditional tools have become increasingly prominent. First, they have obvious deficiencies in their ability to handle large-scale complex systems and are difficult to meet the needs of modern industrial processes. Second, these software are relatively closed in terms of integrating advanced matrix solving algorithms, making it difficult for users to optimize the solution process according to the characteristics of specific problems. Third, although a graphical user interface is provided, its customizability and flexibility are often limited, making it difficult for users to add new components or modify existing models according to specific needs. In addition, the ability to process large-scale historical data and real-time data is limited, making it difficult to effectively use accumulated operating data to optimize simulation accuracy. Summary of the invention

[0003] In view of the above-mentioned deficiencies in the prior art, the present invention provides a power plant operation simulation method and system to solve the above-mentioned technical problems.

[0004] In a first aspect, the present invention provides a power plant operation simulation method, comprising: Based on the principles of thermodynamics and fluid mechanics, mathematical models of components are established; Construct a simulation conservation model through mass flow energy conservation; The back-end optimization solution structure is constructed through iterative calculation optimization method to obtain the matrix solution of the simulation conservation model; The operating parameters of each node are calculated based on the matrix solution, and the performance parameters and global performance parameters of the component are calculated based on the operating parameters of each node and the mathematical model of the component.

[0005] In an optional embodiment, a mathematical model of the element is established based on the principles of thermodynamics and fluid mechanics, including: Construct a mathematical model of the heat exchanger, including: Temperature characteristic equation: Upper end difference : , in, is the temperature at the hot end inlet, is the temperature of the cold end outlet; Lower end difference ΔT IID : , in, is the temperature at the hot end outlet, is the temperature of the cold end inlet; Logarithmic Mean Temperature Difference (LMTD): ; The enthalpy balance equation is: , , , , ; in, is the enthalpy calculation formula, is the mass of the hot side fluid, is the mass of the cold side fluid, and are the hot side and cold side inlet pressures, respectively; and are the hot side and cold side outlet pressures respectively; and are the hot side and cold side inlet temperatures, respectively; and are the hot side and cold side outlet temperatures, respectively; The entropy balance equation is: , is the outlet enthalpy, is the inlet enthalpy, is the specific volume, For pressure, is the temperature, The specific entropy-pressure ratio equation is:

[0006] is the outlet pressure, is the inlet pressure, is the inlet and outlet pressure ratio; Heat transfer coefficient dependence: Heat transfer coefficient kA independent of area: ; is the hot side outlet enthalpy, is the hot side inlet enthalpy, is the hot side outlet temperature, is the cold side inlet temperature, is the hot side inlet temperature, is the cold side outlet temperature; Cold side heat exchanger efficiency equation: ; is the ideal specific enthalpy at the cold side outlet pressure and hot side inlet temperature, is the cold side outlet enthalpy, is the cold side inlet enthalpy.

[0007] Hot side heat exchanger efficiency equation: ; is the ideal specific enthalpy at the hot side outlet pressure and cold side inlet temperature, is the hot side outlet enthalpy, is the hot side inlet enthalpy; Independent friction coefficient equation: ; ; in, and are the inlet and outlet pressures, respectively; is the mass flow rate; It is the flow judgment threshold; is the local resistance coefficient; is the characteristic diameter; and are the inlet and outlet specific volumes, respectively.

[0008] In an optional embodiment, a simulation conservation model is constructed by mass flow energy conservation, including: Pressure equality constraint formula: , in and Represent the input and output pressures of the closed-loop component, respectively; Enthalpy equality constraint formula: , in and represent the enthalpy at the input and output of the closed loop component respectively; Quality deviation calculation formula: , in and represent the input and output mass flow rates respectively; Flow composition deviation calculation formula: , in and Represents the first and second The mole fraction of a component.

[0009] In an optional implementation, a back-end optimization solution structure is constructed by an iterative calculation optimization method to obtain a matrix solution of a simulation conservation model, including: Acquire initial parameters of the mathematical model of the element, the initial parameters including pressure, temperature, mass flow rate and element performance parameters in boundary parameters, and convert the initial parameters into a parameter matrix; Use matrix analysis to transform the system's mass conservation equation, energy conservation equation, and momentum conservation equation into a set of nonlinear equations; Calculating the Jacobian matrix of the nonlinear system of equations; Solving the Jacobian matrix of the nonlinear equations by an iterative algorithm and setting convergence conditions; The matrix solution obtained by the iterative algorithm is compared with the boundary conditions of the mathematical model of the component. If the matrix solution does not exceed the boundary conditions, the matrix solution is adopted; if the matrix solution exceeds the boundary conditions, the boundary conditions or performance parameters of the corresponding mathematical model are adjusted.

[0010] In an optional embodiment, the operating parameters of each node are calculated based on the matrix solution, and the performance parameters and global performance parameters of the component are calculated based on the operating parameters of each node and the mathematical model of the component, including: Calculating operating parameters of each node based on the matrix solution, the operating parameters including temperature, pressure, mass flow, enthalpy and entropy, the node being the inlet and outlet of the element; Calculate the heat transfer efficiency, compression work and expansion work of the components according to the operating parameters of each node and the mathematical model of the components; An energy balance calculation is performed for each element to determine the input work and output work, and the global total output power and overall efficiency are calculated based on the input work and output work of each element.

[0011] In an optional embodiment, the method further comprises: Generate graphs for element heat transfer efficiency, compression and expansion work, input and output work, and global total output power and overall efficiency; The global total output power and overall efficiency are compared with the target values, and the comparison results are output.

[0012] In a second aspect, the present invention provides a power plant operation simulation system, comprising: Basic building blocks for building mathematical models of components based on the principles of thermodynamics and fluid mechanics; Conservation building module, used to build simulation conservation models through mass flow energy conservation; Iterative calculation module, used to construct the back-end optimization solution structure through iterative calculation optimization method to obtain the matrix solution of the simulation conservation model; The parameter calculation module is used to calculate the operating parameters of each node based on the matrix solution, and calculate the performance parameters and global performance parameters of the element based on the operating parameters of each node and the mathematical model of the element.

[0013] In a third aspect, a device is provided, comprising: A memory, used for storing a power plant operation simulation program; A processor is used to implement the steps of the power plant operation simulation method provided in the first aspect when executing the power plant operation simulation program.

[0014] In a fourth aspect, a computer-readable storage medium is provided, on which a power plant operation simulation program is stored. When the power plant operation simulation program is executed by a processor, the steps of the power plant operation simulation method provided in the first aspect are implemented.

[0015] The beneficial effect of the present invention is that the power plant operation simulation method and system provided by the present invention, based on efficient matrix operations, significantly improve the simulation accuracy and computational efficiency of large-scale complex industrial processes, while overcoming the limitations of traditional commercial software and providing higher flexibility and customizability.

[0016] In addition, the invention has a reliable design principle, a simple structure and a very broad application prospect. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0018] Figure 1 is a schematic flow chart of a method according to an embodiment of the present invention.

[0019] Figure 2 is a schematic block diagram of a system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0020] In order to enable those skilled in the art to better understand the technical solutions in the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0021] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used in the specification of the present invention herein are only for the purpose of describing specific embodiments and are not intended to limit the present invention.

[0022] The power plant operation simulation method provided in the embodiment of the present invention is executed by a computer device, and accordingly, the power plant operation simulation system runs in the computer device.

[0023] Figure 1 is a schematic flow chart of a method according to an embodiment of the present invention. Figure 1 The execution subject may be a power plant operation simulation system. According to different requirements, the order of the steps in the flow chart may be changed, and some may be omitted.

[0024] like Figure 1 As shown, the method includes: S1. Establish mathematical models of components based on the principles of thermodynamics and fluid mechanics; S2. Construct a simulation conservation model through mass flow energy conservation; S3. construct a back-end optimization solution structure through an iterative calculation optimization method to obtain a matrix solution of the simulation conservation model; S4. Calculate the operating parameters of each node based on the matrix solution, and calculate the performance parameters and global performance parameters of the component based on the operating parameters of each node and the mathematical model of the component.

[0025] In an embodiment of the present invention, based on step S1, a possible embodiment is given below to illustrate its specific implementation scheme in a non-limiting manner.

[0026] Construct a mathematical model of the heat exchanger, including: Temperature characteristic equation: Upper end difference : , in, is the temperature at the hot end inlet, is the temperature of the cold end outlet; Lower end difference ΔT IID : , in, is the temperature at the hot end outlet, is the temperature of the cold end inlet; Logarithmic Mean Temperature Difference (LMTD): ; The enthalpy balance equation is: , , , , ; in, is the enthalpy calculation formula, is the mass of the hot side fluid, is the mass of the cold side fluid, and are the hot side and cold side inlet pressures, respectively; and are the hot side and cold side outlet pressures respectively; and are the hot side and cold side inlet temperatures, respectively; and are the hot side and cold side outlet temperatures, respectively; The entropy balance equation is: , is the outlet enthalpy, is the inlet enthalpy, is the specific volume, For pressure, is the temperature, The specific entropy-pressure ratio equation is:

[0027] is the outlet pressure, is the inlet pressure, is the inlet and outlet pressure ratio; Heat transfer coefficient dependence: Heat transfer coefficient kA independent of area: ; is the hot side outlet enthalpy, is the hot side inlet enthalpy, is the hot side outlet temperature, is the cold side inlet temperature, is the hot side inlet temperature, is the cold side outlet temperature; Cold side heat exchanger efficiency equation: ; is the ideal specific enthalpy at the cold side outlet pressure and hot side inlet temperature, is the cold side outlet enthalpy, is the cold side inlet enthalpy.

[0028] Hot side heat exchanger efficiency equation: ; is the ideal specific enthalpy at the hot side outlet pressure and cold side inlet temperature, is the hot side outlet enthalpy, is the hot side inlet enthalpy; Independent friction coefficient equation: ; ; in, and are the inlet and outlet pressures, respectively; is the mass flow rate; It is the flow judgment threshold; is the local resistance coefficient; is the characteristic diameter; and are the inlet and outlet specific volumes, respectively.

[0029] in, and are the inlet and outlet pressures, respectively; is the mass flow rate; It is the flow judgment threshold; is the local resistance coefficient; is the characteristic diameter; and are the inlet and outlet specific volumes, respectively.

[0030] The mathematical model of the gas turbine is as follows: Air compression process: Compression work W comp It can be calculated by the following formula: ; Where, p is the pressure, V 1 and V 2 are the volumes before and after compression respectively.

[0031] The increase in enthalpy of air, Δh, can be calculated using the following formula: ; Among them, c p is the specific heat at constant pressure, T 1 and T 2 are the temperatures before and after compression, respectively.

[0032] Heat energy released by combustion Q burn It can be calculated by the following formula: ; in, is the mass flow rate of fuel, It is the lower heating value of the fuel.

[0033] The power output of the turbine is W turb It can be calculated by the following formula: ; in, is the mass flow rate of gas, h 3 and h 4 are the enthalpy values ​​at the turbine inlet and outlet, respectively.

[0034] The pressure ratio π can be calculated by the following formula: π=p 1 / p 2 ; Among them, p 1 and p 2 are the gas turbine inlet and outlet pressures respectively.

[0035] Thermal efficiency η th It can be calculated by the following formula: ; Among them, Q rec is the heat of the waste heat recovery system.

[0036] Mechanical efficiency η mech It is usually estimated through experimental determination or empirical formula.

[0037] Total efficiency η total It can be calculated by the following formula: .

[0038] The mathematical model of the compressor is as follows: This model is designed to describe the aerodynamic performance of the compressor, especially the relationship between pressure, temperature, flow rate and other parameters during the compression process. Through this model, we can predict the compressor's compression ratio, efficiency and other performance indicators. The model is based on the one-dimensional flow assumption, that is, it is assumed that the flow in the compressor is a one-dimensional flow along the axial direction.

[0039] Import parameters: P 1 : Inlet pressure (Pa); T 1 : inlet temperature (K); : mass flow rate (kg / s); Export parameters: P 2 : outlet pressure (Pa); T 2 : outlet temperature (K); Compressor characteristic parameters: π: Compression ratio (P 2 / P 1 ) η: Isentropic efficiency (dimensionless) N: speed (rpm) Geometric parameters (such as blade angle, throat area, etc., which are usually determined through experiments or design and used as input to the model).

[0040] Compression ratio function: The compression ratio π is the ratio of the compressor outlet pressure to the inlet pressure, which is usually related to the compressor speed N and geometric parameters. In practical applications, the compression ratio can be determined by experimental data or empirical formulas. In order to simplify the model, we can assume that the compression ratio has a power law relationship with the speed, that is: ; Among them, k 1 and k 2 is a constant obtained by fitting the experimental data.

[0041] Isentropic efficiency η is the ratio of useful work in the actual compression process of the compressor to the theoretical compression work. It is usually related to the compressor speed N, inlet flow rate and geometric parameters. Similarly, to simplify the model, it is assumed that the isentropic efficiency has a certain functional relationship with these parameters, such as: ; Among them, k 3 , k 4 and k 5 is a constant obtained by fitting the experimental data.

[0042] According to the principle of energy conservation, the compressor outlet temperature T 2 It can be calculated by the following formula: ; where γ is the specific heat ratio of the gas (usually 1.4 for air).

[0043] The flow function is usually used to describe the flow characteristics of the compressor under different operating conditions. In practical applications, the flow can be determined by experimental data or empirical formulas. In order to simplify the model, it is assumed that the flow is related to the speed and inlet pressure of the compressor, and a flow coefficient C is introduced. f To express this relationship: ; Among them, C f is a constant obtained by fitting experimental data, f 3 is a function related to the geometric shape parameters.

[0044] In an embodiment of the present invention, based on step S2, a possible embodiment is given below to illustrate its specific implementation scheme in a non-limiting manner.

[0045] Pressure equality constraint formula: , in and Represent the input and output pressures of the closed-loop component, respectively; Enthalpy equality constraint formula: , in and represent the enthalpy at the input and output of the closed loop component respectively; Quality deviation calculation formula: , in and represent the input and output mass flow rates respectively; Flow composition deviation calculation formula: , in and Represents the first and second The mole fraction of a component.

[0046] In an embodiment of the present invention, based on step S3, a possible embodiment is given below to illustrate its specific implementation scheme in a non-limiting manner.

[0047] S301. Obtaining initial parameters of the mathematical model of the component When constructing a mathematical model of a complex system, it is first necessary to determine the initial parameters of each component (such as pipes, valves, compressors, heat exchangers, etc.). These initial parameters usually include boundary parameters and component performance parameters.

[0048] Boundary parameters: Pressure: The pressure value at the inlet and outlet of the component is an important parameter to describe the fluid flow state.

[0049] Temperature: The temperature value at the inlet and outlet of the component affects the thermodynamic properties and energy conversion of the fluid.

[0050] Mass flow rate: The mass flow rate of fluid passing through the element, reflecting the transmission rate of the fluid.

[0051] Component performance parameters: These parameters are usually related to the physical characteristics and working conditions of the components, such as the efficiency of the compressor, the heat transfer coefficient of the heat exchanger, etc.

[0052] After obtaining these parameters, they need to be organized into a parameter matrix for subsequent mathematical analysis and calculation.

[0053] S302. Transforming conservation equations using matrix analysis After determining the initial parameters of the system, it is necessary to establish a mathematical model of the system using basic physical laws such as conservation of mass, conservation of energy, and conservation of momentum. These conservation equations are usually nonlinear and involve multiple variables and parameters.

[0054] In order to simplify the calculation, these conservation equations can be transformed into a system of nonlinear equations using matrix analysis. The specific steps include: Represent the variables and parameters in the conservation equation in matrix form.

[0055] Using matrix operations and algebraic methods, the conservation equations are transformed into standard nonlinear equations.

[0056] S303. Compute the Jacobian matrix of a nonlinear system of equations The Jacobian matrix is ​​an important tool when solving nonlinear equations. It describes the degree of influence of each variable in the equations on each other, that is, the derivative matrix of the equations.

[0057] The steps to calculate the Jacobian matrix include: Take the partial derivative of each equation in the nonlinear system of equations to get the derivative of the system with respect to each variable.

[0058] Arranging these derivatives into a matrix form gives us the Jacobian matrix.

[0059] S304. Using iterative algorithms to solve the Jacobian matrix After obtaining the Jacobian matrix, we can use iterative algorithms (such as Newton-Raphson method, quasi-Newton method, etc.) to solve the nonlinear equations. The basic idea of ​​the iterative algorithm is to gradually reduce the error range by continuously approaching the true solution.

[0060] During the iteration process, it is necessary to set a convergence condition to determine whether the iteration is complete. The convergence condition is usually based on the size of the iteration error or the limit on the number of iterations.

[0061] S305. Comparison of matrix solutions and boundary conditions After obtaining the solution of the iterative algorithm, it is necessary to compare it with the boundary conditions of the mathematical model of the component to ensure the validity and accuracy of the solution.

[0062] If the matrix solution does not exceed the boundary conditions, the solution can be used as the mathematical model solution of the system.

[0063] If the matrix solution exceeds the boundary conditions, it is necessary to adjust the boundary conditions or performance parameters of the corresponding mathematical model and re-perform iterative calculations.

[0064] S306. Adjustment and Optimization During the comparison process, if it is found that the matrix solution does not meet the boundary conditions, the following adjustments need to be made: Adjust boundary conditions: Modify boundary conditions such as inlet or outlet pressure, temperature and mass flow rate according to actual conditions.

[0065] Optimize performance parameters: Improve system performance by adjusting component performance parameters (such as compressor efficiency, heat transfer coefficient of heat exchanger, etc.).

[0066] The adjusted parameters need to be substituted into the mathematical model again for calculation until a solution that meets the boundary conditions is obtained.

[0067] Through the above steps, a mathematical model of a complex system can be constructed and solved. This model can describe the flow state and performance characteristics of each component in the system, providing an important basis for the design and optimization of the system.

[0068] In an embodiment of the present invention, based on step S4, a possible embodiment is given below to illustrate its specific implementation scheme in a non-limiting manner.

[0069] S401. Calculate the operating parameters of each node based on the matrix solution After obtaining the matrix solution of the simulation conservation model, the operating parameters of each node in the system can be further calculated. These parameters are crucial for understanding and analyzing the performance of the system.

[0070] Node operating parameters: including temperature, pressure, mass flow, enthalpy and entropy, etc. These parameters can fully describe the state of the fluid in the element.

[0071] Temperature: Indicates the thermal state of the fluid and is particularly important for performance analysis of components such as heat exchangers.

[0072] Pressure: affects the flow characteristics of fluids and the operating conditions of components, such as the performance of compressors and turbines.

[0073] Mass flow rate: describes the mass transfer rate of a fluid through a component and is the basis for calculating power and efficiency.

[0074] Enthalpy: It represents the total energy of the fluid (including internal energy and kinetic energy) and is crucial for energy conservation analysis.

[0075] Entropy value: reflects the degree of disorder of the system and helps analyze the efficiency loss in the energy conversion process.

[0076] Node: In this article, nodes refer specifically to the inlet and outlet of a component. By calculating the operating parameters of these nodes, we can understand the changes of the fluid in the component.

[0077] S402. Calculate the heat transfer efficiency, compression work and expansion work of the element according to the operating parameters of each node and the mathematical model of the element After obtaining the operating parameters of the node, the performance parameters of the component can be further calculated.

[0078] Heat transfer efficiency: For a heat exchanger, its heat transfer efficiency can be calculated by comparing the enthalpy changes of the inlet and outlet fluids. This helps to evaluate the performance of the heat exchanger.

[0079] Compression work: For a compressor, its compression work can be calculated by calculating the pressure difference between the inlet and outlet fluids and the mass flow rate. This reflects the energy required by the compressor to compress the fluid to the required pressure.

[0080] Expansion work: For expansion elements such as turbines, the expansion work can be calculated by calculating the pressure difference and mass flow rate of the inlet and outlet fluids. This represents the energy released by the fluid during the expansion process.

[0081] S403. Perform energy balance calculation for each component to determine input work and output work In order to evaluate the overall performance of the system, an energy balance calculation is required for each component.

[0082] Input work: refers to the energy obtained by a component from the outside during its operation, such as the electrical energy obtained by a compressor from a power supply.

[0083] Output work: refers to the energy released by a component to the outside during operation, such as the heat energy released by a heat exchanger to the environment or the mechanical energy provided by a turbine to a generator.

[0084] By calculating the input work and output work of each component, we can understand the efficiency loss and energy distribution of the system during the energy conversion process.

[0085] S404. Calculate the global total output power and overall efficiency based on the input work and output work of each element After obtaining the input work and output work of each component, the global performance parameters of the system can be further calculated.

[0086] Total output power: refers to the sum of all output work of the system, reflecting the system's ability to provide energy to the outside.

[0087] Overall efficiency: refers to the ratio of the total output power of the system to the sum of all input work, which is used to evaluate the energy conversion efficiency of the system. The higher the overall efficiency, the smaller the loss of the system in the energy conversion process and the better the performance.

[0088] On the basis of the above embodiments, in order to further improve the visualization level, a feasible way is to convert the key parameters into a chart.

[0089] Generate graphs for the heat transfer efficiency, compression and expansion work, input and output work of the element, and the global total output power and overall efficiency; compare the global total output power and overall efficiency with the target values ​​and output the comparison results.

[0090] All parameters and results calculated in S4 are systematically organized to create a comprehensive table containing key parameters. Use flow charts, Ts diagrams, or Ph diagrams to intuitively display the thermodynamic cycle process and the trend of each parameter. Highlight the key performance indicators of the system, such as total power output and system efficiency, and compare them with the design goals.

[0091] In a specific application example, the user uses the component library provided on the simulation platform to build a gas turbine system and defines the units of various parameters in the system: pressure unit is MPa, temperature unit is °C, specific enthalpy unit is kJ / kg, and mass flow unit is kg / s. The main components include: air inlet component, fuel inlet component, flue gas outlet component, gas turbine component, compressor component, and combustion chamber component.

[0092] These components are connected on the canvas to build a complete system, forming the basic structure of the gas turbine. The topology of the system is as follows: 1. The air inlet is connected to the compressor; 2. The compressor outlet is connected to the combustion chamber; 3. The fuel inlet is connected to the combustion chamber; 4. The combustion chamber outlet is connected to the gas turbine; 5. The gas turbine outlet is connected to the flue gas outlet.

[0093] The system boundary parameters and component performance parameters are set on the canvas based on given operating data.

[0094] These include: 1. Air inlet conditions: Composition: {"Ar": 0.0129, "N2": 0.7553, "CO2": 0.0004, "O2": 0.2314}; Pressure: 0.1003 MPa; Mass flow rate: 569.1 kg / s; Temperature: 29.9°C.

[0095] 2. Compressor outlet conditions: Pressure: 1.649 MPa; Temperature: 445.4°C.

[0096] 3. Fuel inlet conditions: Components: {'methane': 91.04%, 'ethane': 6.42%, 'Propane': 1.72%, 'nButane': 0.58%, 'N2': 0.24%}; Mass flow rate: 12.87 kg / s; Pressure: 3.611 MPa; Temperature: 205.4°C; Combustion chamber pressure drop: outlet pressure is 96% of inlet pressure.

[0097] 4. Gas turbine export conditions: Pressure: 0.1043 MPa; Temperature: 605.1°C.

[0098] 5. Component performance conditions and boundary conditions Gas turbine efficiency: 96%; Compressor efficiency: 96%.

[0099] The total output power of the system is 227.0 MW.

[0100] After setting the parameters, you can click on the simulation to run. The backend will automatically build equilibrium equations and nonlinear thermodynamic equations based on the mechanism models of each component and convert them into matrices.

[0101] The solution is handled by the improved Newton-Raphson method. The solution process will automatically consider constraints such as mass conservation, energy conservation, component balance, and boundary conditions of components and fluids. The system will automatically construct the Jacobian matrix and obtain the equilibrium state of the system through iterative solution.

[0102] After the solution is completed, the system automatically extracts and records the key performance parameters. And summarizes them into a table, and completes the simulation. The output parameters are as follows: Air inlet to compressor inlet: mass flow rate: 569.1 kg / s, pressure: 0.1003 MPa, specific enthalpy: 303.6 kJ / kg, temperature: 29.99°C.

[0103] From compressor outlet to combustion chamber inlet: mass flow rate: 569.1 kg / s, pressure: 1.649 MPa, specific enthalpy: 734.1 kJ / kg, temperature: 445.4°C.

[0104] Fuel inlet to combustion chamber: mass flow rate: 12.87 kg / s, pressure: 3.611 MPa, specific enthalpy: 1320 kJ / kg, temperature: 205.4°C.

[0105] From combustion chamber outlet to gas turbine inlet: mass flow rate: 582.0 kg / s, pressure: 1.583 MPa, specific enthalpy: 1927 kJ / kg, temperature: 1296°C.

[0106] From gas turbine outlet to flue gas outlet: mass flow rate: 582.0 kg / s, pressure: 0.1043 MPa, specific enthalpy: 1064 kJ / kg, temperature: 605.1°C.

[0107] Compressor power: 245MW, isentropic efficiency: 0.864, pressure ratio 16.4.

[0108] Combustion chamber excess air coefficient: 2.59, heat input: 639 MW, pressure ratio: 0.96, efficiency: 0.973, heat loss (Q_loss): -17.3 MW.

[0109] Gas turbine output power (P): 502 MW, isentropic efficiency: 0.933, pressure ratio: 0.0659.

[0110] System net output power: 257.3 MW.

[0111] In some embodiments, the power plant operation simulation system may include a plurality of functional modules composed of computer program segments. The computer programs of the various program segments in the power plant operation simulation system may be stored in a memory of a computer device and executed by at least one processor to perform (see Figure 1 Description) Functions of power plant operation simulation.

[0112] In this embodiment, the power plant operation simulation system can be divided into multiple functional modules according to the functions it performs, such as Figure 2 As shown. The functional modules of the system 200 may include: a basic construction module 210, a conservation construction module 220, an iterative calculation module 230 and a parameter calculation module 240. The module referred to in the present invention refers to a series of computer program segments that can be executed by at least one processor and can complete fixed functions, which are stored in a memory. In this embodiment, the functions of each module will be described in detail in subsequent embodiments.

[0113] Basic building blocks for building mathematical models of components based on the principles of thermodynamics and fluid mechanics; Conservation building module, used to build simulation conservation models through mass flow energy conservation; Iterative calculation module, used to construct the back-end optimization solution structure through iterative calculation optimization method to obtain the matrix solution of the simulation conservation model; The parameter calculation module is used to calculate the operating parameters of each node based on the matrix solution, and calculate the performance parameters and global performance parameters of the element based on the operating parameters of each node and the mathematical model of the element.

[0114] Optionally, as an embodiment of the present invention, a mathematical model of the element is established based on the principles of thermodynamics and fluid mechanics, including: Temperature characteristic equation: Upper end difference : , in, is the temperature at the hot end inlet, is the temperature of the cold end outlet; Lower end difference ΔT IID : , in, is the temperature at the hot end outlet, is the temperature of the cold end inlet; Logarithmic Mean Temperature Difference (LMTD): ; The enthalpy balance equation is: , , , , ; in, is the enthalpy calculation formula, is the mass of the hot side fluid, is the mass of the cold side fluid, and are the hot side and cold side inlet pressures, respectively; and are the hot side and cold side outlet pressures respectively; and are the hot side and cold side inlet temperatures, respectively; and are the hot side and cold side outlet temperatures, respectively; The entropy balance equation is: , is the outlet enthalpy, is the inlet enthalpy, is the specific volume, For pressure, is the temperature, The specific entropy-pressure ratio equation is:

[0115] is the outlet pressure, is the inlet pressure, is the inlet and outlet pressure ratio; Heat transfer coefficient dependence: Heat transfer coefficient kA independent of area: ; is the hot side outlet enthalpy, is the hot side inlet enthalpy, is the hot side outlet temperature, is the cold side inlet temperature, is the hot side inlet temperature, is the cold side outlet temperature; Cold side heat exchanger efficiency equation: ; is the ideal specific enthalpy at the cold side outlet pressure and hot side inlet temperature, is the cold side outlet enthalpy, is the cold side inlet enthalpy.

[0116] Hot side heat exchanger efficiency equation: ; is the ideal specific enthalpy at the hot side outlet pressure and cold side inlet temperature, is the hot side outlet enthalpy, is the hot side inlet enthalpy; Independent friction coefficient equation: ; ; in, and are the inlet and outlet pressures, respectively; is the mass flow rate; It is the flow judgment threshold; is the local resistance coefficient; is the characteristic diameter; and are the inlet and outlet specific volumes, respectively.

[0117] Optionally, as an embodiment of the present invention, a simulation conservation model is constructed by mass flow energy conservation, including: Pressure equality constraint formula: , in and Represent the input and output pressures of the closed-loop component, respectively; Enthalpy equality constraint formula: , in and represent the enthalpy at the input and output of the closed loop component respectively; Quality deviation calculation formula: , in and represent the input and output mass flow rates respectively; Flow composition deviation calculation formula: , in and Represents the first and second The mole fraction of a component.

[0118] Optionally, as an embodiment of the present invention, a back-end optimization solution structure is constructed by an iterative calculation optimization method to obtain a matrix solution of a simulation conservation model, including: Acquire initial parameters of the mathematical model of the element, the initial parameters including pressure, temperature, mass flow rate and element performance parameters in boundary parameters, and convert the initial parameters into a parameter matrix; Use matrix analysis to transform the system's mass conservation equation, energy conservation equation, and momentum conservation equation into a set of nonlinear equations; Calculating the Jacobian matrix of the nonlinear system of equations; Solving the Jacobian matrix of the nonlinear equations by an iterative algorithm and setting convergence conditions; The matrix solution obtained by the iterative algorithm is compared with the boundary conditions of the mathematical model of the component. If the matrix solution does not exceed the boundary conditions, the matrix solution is adopted; if the matrix solution exceeds the boundary conditions, the boundary conditions or performance parameters of the corresponding mathematical model are adjusted.

[0119] Optionally, as an embodiment of the present invention, the operating parameters of each node are calculated based on the matrix solution, and the performance parameters and global performance parameters of the component are calculated based on the operating parameters of each node and the mathematical model of the component, including: Calculating operating parameters of each node based on the matrix solution, the operating parameters including temperature, pressure, mass flow, enthalpy and entropy, the node being the inlet and outlet of the element; Calculate the heat transfer efficiency, compression work and expansion work of the components according to the operating parameters of each node and the mathematical model of the components; An energy balance calculation is performed for each element to determine the input work and output work, and the global total output power and overall efficiency are calculated based on the input work and output work of each element.

[0120] Optionally, as an embodiment of the present invention, it further includes: Generate graphs for element heat transfer efficiency, compression and expansion work, input and output work, and global total output power and overall efficiency; The global total output power and overall efficiency are compared with the target values, and the comparison results are output.

[0121] Although the present invention has been described in detail with reference to the accompanying drawings and in combination with the preferred embodiments, the present invention is not limited thereto. Without departing from the spirit and essence of the present invention, a person of ordinary skill in the art may make various equivalent modifications or substitutions to the embodiments of the present invention, and these modifications or substitutions shall be within the scope of the present invention. Any person of ordinary skill in the art may easily think of changes or substitutions within the technical scope disclosed by the present invention, and these shall be within the scope of protection of the present invention.

Claims

1. A power plant operation simulation method, characterized in that: include: Based on the principles of thermodynamics and fluid mechanics, mathematical models of components are established; Construct a simulation conservation model through mass flow energy conservation; The back-end optimization solution structure is constructed through iterative calculation optimization method to obtain the matrix solution of the simulation conservation model; The operating parameters of each node are calculated based on the matrix solution, and the performance parameters and global performance parameters of the component are calculated based on the operating parameters of each node and the mathematical model of the component.

2. The method according to claim 1, characterized in that Based on the principles of thermodynamics and fluid mechanics, a mathematical model of the components is established, including: Construct a mathematical model of the heat exchanger, including: Temperature characteristic equation: Upper end difference : ， in, is the temperature at the hot end inlet, is the temperature of the cold end outlet; Lower end difference ΔT IID : ， in, is the temperature at the hot end outlet, is the temperature of the cold end inlet; Logarithmic mean temperature difference LMTD: ； The enthalpy balance equation is: ， , , , ； in, is the enthalpy calculation formula, is the mass of the hot side fluid, is the mass of the cold side fluid, and are the hot side and cold side inlet pressures, respectively; and are the hot side and cold side outlet pressures respectively; and are the hot side and cold side inlet temperatures, respectively; and are the hot side and cold side outlet temperatures, respectively; The entropy balance equation is: ， is the outlet enthalpy, is the inlet enthalpy, is the specific volume, For pressure, is the temperature, The specific entropy-pressure ratio equation is: is the outlet pressure, is the inlet pressure, is the inlet and outlet pressure ratio; Heat transfer coefficient dependence: Heat transfer coefficient kA independent of area: ； is the hot side outlet enthalpy, is the hot side inlet enthalpy, is the hot side outlet temperature, is the cold side inlet temperature, is the hot side inlet temperature, is the cold side outlet temperature; Cold side heat exchanger efficiency equation: ； is the ideal specific enthalpy at the cold side outlet pressure and hot side inlet temperature, is the cold side outlet enthalpy, is the cold side inlet enthalpy. Hot side heat exchanger efficiency equation: ； is the ideal specific enthalpy at the hot side outlet pressure and cold side inlet temperature, is the hot side outlet enthalpy, is the hot side inlet enthalpy; Independent friction coefficient equation: ； ； in, and are the inlet and outlet pressures, respectively; is the mass flow rate; It is the flow judgment threshold; is the local resistance coefficient; is the characteristic diameter; and are the inlet and outlet specific volumes, respectively.

3. The method according to claim 1, characterized in that Construct a simulation conservation model through mass flow energy conservation, including: Pressure equality constraint formula: ， in and Represent the input and output pressures of the closed-loop component, respectively; Enthalpy equality constraint formula: ， in and represent the enthalpy at the input and output of the closed loop component respectively; Quality deviation calculation formula: ， in and Represent the input and output mass flow rates respectively; Flow composition deviation calculation formula: ， in and Represents the first and second The mole fraction of a component.

4. The method according to claim 1, characterized in that: The back-end optimization solution structure is constructed through iterative calculation optimization method to obtain the matrix solution of the simulation conservation model, including: Acquire initial parameters of the mathematical model of the element, the initial parameters including pressure, temperature, mass flow rate and element performance parameters in boundary parameters, and convert the initial parameters into a parameter matrix; Use matrix analysis to transform the system's mass conservation equation, energy conservation equation, and momentum conservation equation into a set of nonlinear equations; Calculating the Jacobian matrix of the nonlinear system of equations; Solving the Jacobian matrix of the nonlinear equations by an iterative algorithm and setting convergence conditions; The matrix solution obtained by the iterative algorithm is compared with the boundary conditions of the mathematical model of the component. If the matrix solution does not exceed the boundary conditions, the matrix solution is adopted; if the matrix solution exceeds the boundary conditions, the boundary conditions or performance parameters of the corresponding mathematical model are adjusted.

5. The method according to claim 1, characterized in that The operating parameters of each node are calculated based on the matrix solution, and the performance parameters and global performance parameters of the component are calculated based on the operating parameters of each node and the mathematical model of the component, including: Calculating operating parameters of each node based on the matrix solution, the operating parameters including temperature, pressure, mass flow, enthalpy and entropy, the node being the inlet and outlet of the element; Calculate the heat transfer efficiency, compression work and expansion work of the components according to the operating parameters of each node and the mathematical model of the components; An energy balance calculation is performed for each element to determine the input work and output work, and the global total output power and overall efficiency are calculated based on the input work and output work of each element.

6. The method according to claim 5, characterized in that The method further comprises: Generate graphs for element heat transfer efficiency, compression and expansion work, input and output work, and global total output power and overall efficiency; The global total output power and overall efficiency are compared with the target values, and the comparison results are output.

7. A power plant operation simulation system, characterized in that: include: Basic building blocks for building mathematical models of components based on the principles of thermodynamics and fluid mechanics; Conservation building module, used to build simulation conservation models through mass flow energy conservation; Iterative calculation module, used to construct the back-end optimization solution structure through iterative calculation optimization method to obtain the matrix solution of the simulation conservation model; The parameter calculation module is used to calculate the operating parameters of each node based on the matrix solution, and calculate the performance parameters and global performance parameters of the element based on the operating parameters of each node and the mathematical model of the element.

8. The system according to claim 7, characterized in that The basic building blocks include: Construct a mathematical model of the heat exchanger, including: Temperature characteristic equation: Upper end difference : ， in, is the temperature at the hot end inlet, is the temperature of the cold end outlet; Lower end difference ΔT IID : ， in, is the temperature at the hot end outlet, is the temperature of the cold end inlet; Logarithmic Mean Temperature Difference (LMTD): ； The enthalpy balance equation is: ， , , , ； in, is the enthalpy calculation formula, is the mass of the hot side fluid, is the mass of the cold side fluid, and are the hot side and cold side inlet pressures, respectively; and are the hot side and cold side outlet pressures respectively; and are the hot side and cold side inlet temperatures, respectively; and are the hot side and cold side outlet temperatures, respectively; The entropy balance equation is: ， is the outlet enthalpy, is the inlet enthalpy, is the specific volume, For pressure, is the temperature, The specific entropy-pressure ratio equation is: is the outlet pressure, is the inlet pressure, is the inlet and outlet pressure ratio; Heat transfer coefficient dependence: Heat transfer coefficient kA independent of area: ； is the hot side outlet enthalpy, is the hot side inlet enthalpy, is the hot side outlet temperature, is the cold side inlet temperature, is the hot side inlet temperature, is the cold side outlet temperature; Cold side heat exchanger efficiency equation: ； is the ideal specific enthalpy at the cold side outlet pressure and hot side inlet temperature, is the cold side outlet enthalpy, is the cold side inlet enthalpy. Hot side heat exchanger efficiency equation: ； is the ideal specific enthalpy at the hot side outlet pressure and cold side inlet temperature, is the hot side outlet enthalpy, is the hot side inlet enthalpy; Independent friction coefficient equation: ； ； in, and are the inlet and outlet pressures, respectively; is the mass flow rate; It is the flow judgment threshold; is the local resistance coefficient; is the characteristic diameter; and are the inlet and outlet specific volumes, respectively.

9. The system according to claim 7, characterized in that The conservation building blocks include: Pressure equality constraint formula: ， in and Represent the input and output pressures of the closed-loop component, respectively; Enthalpy equality constraint formula: ， in and represent the enthalpy at the input and output of the closed loop component respectively; Quality deviation calculation formula: ， in and Represent the input and output mass flow rates respectively; Flow composition deviation calculation formula: ， in and Represents the first and second The mole fraction of a component.

10. The system according to claim 7, characterized in that The iterative calculation module comprises: An initialization unit, used to obtain initial parameters of the mathematical model of the element, the initial parameters including pressure, temperature, mass flow rate and element performance parameters in the boundary parameters, and convert the initial parameters into a parameter matrix; An equation conversion unit is used to convert the mass conservation equation, energy conservation equation and momentum conservation equation of the system into a nonlinear equation group by using a matrix analysis method; A matrix generation unit, used for calculating the Jacobian matrix of the nonlinear equation system; A matrix solving unit, used for solving the Jacobian matrix of the nonlinear equations by using an iterative algorithm and setting a convergence condition; The boundary checking unit is used to compare the matrix solution obtained by the iterative algorithm with the boundary conditions of the mathematical model of the component. If the matrix solution does not exceed the boundary conditions, the matrix solution is adopted; if the matrix solution exceeds the boundary conditions, the boundary conditions or performance parameters of the corresponding mathematical model are adjusted.

Images