Simulation modeling method for minimum unit of hydraulic turbine unit speed regulator based on hydrodynamics

Abstract

The invention discloses a hydraulic turbine unit speed regulator minimum unit simulation modeling method based on hydrodynamics, and belongs to the field of industrial simulation. According to the method, a modeling method is provided, multi-domain minimum unit decomposition is carried out, and a speed regulation system is decoupled into six functional subsystems. State-space equations are established for electric, hydraulic and mechanical equipment of speed regulators such as a proportional valve, a main distributing valve and a main servomotor, and a'control-hydraulic-mechanical 'interface coupling link is constructed. And verifying the model through unit-level and system-level tests. Key physical parameters of the verified unit model are set to be externally adjustable, a centralized parameter database is established, and flexible configuration, efficient multiplexing and dynamic updating of the model are achieved. According to the technical framework, the transparency of a physical mechanism serves as a foundation stone, unification of theoretical preciseness and engineering practicability is formed through a dynamic reconstruction and collaborative verification mechanism, and an autonomous and controllable technical base is constructed for digital design, intelligent regulation and control and service life prediction of major equipment such as hydropower equipment and nuclear power equipment.

Description

Technical Field

[0001] This invention relates to the field of industrial simulation, specifically to a simulation modeling method for the smallest unit of a hydro turbine governor based on fluid dynamics. Background Technology

[0002] The turbine speed control system is one of the core control devices in a hydropower station. Its core function is to achieve precise matching between the unit speed and the grid load by dynamically adjusting the opening of the guide vanes. This system directly affects the power generation efficiency of the hydropower station, the stability of the grid frequency, and the safe operation of the equipment, especially under complex operating conditions, which places higher demands on dynamic response speed and control accuracy.

[0003] Current modeling methods for turbine speed control systems mainly include using simplified first-order inertial models to describe electro-hydraulic conversion units, hydraulic amplification units, and execution units, simulating the hydraulic link from the governor's electrical output to the guide vane opening; or constructing high-precision nonlinear dynamic relationship fitting models through data-driven methods (such as neural networks); in addition, there are hydraulic component libraries based on the Modelica platform and professional simulation software such as AMESim, establishing physical mechanism simulation models including key components such as hydraulic cylinders and servo valves, and realizing system-level dynamic characteristic analysis.

[0004] The aforementioned methods, by neglecting the key physical and geometric characteristics of the governor equipment, result in large modeling errors, poor adaptability, and difficulty in accurately describing the nonlinear characteristics of the turbine hydraulic system. Furthermore, their poor adaptive capabilities lead to deviations between the control strategy and the actual operating state, potentially causing unit vibration, power oscillations, and even safety hazards. Therefore, a novel speed control system modeling scheme is urgently needed, capable of integrating equipment geometric and physical parameters, high-precision nonlinear modeling, and adaptive optimization capabilities to overcome the bottlenecks of traditional technologies. Summary of the Invention

[0005] For the speed control system of hydropower units, this invention proposes a simulation modeling method for the smallest unit of the hydropower unit speed governor based on fluid dynamics. It adopts a self-programmed numerical calculation method to establish a high-precision, dynamically adjustable, and highly reusable speed governor simulation model.

[0006] This invention provides a simulation modeling method for the smallest unit of a hydro turbine governor based on fluid dynamics, the method comprising the following steps: S1. Multi-domain minimum unit decomposition The turbine control system is a multi-domain (mechanical-electrical-hydraulic-control) coupled, multi-level (component-assembly unit-system) model constructed based on the coupling relationships and spatial positions of equipment domains within the control system. It employs a multi-domain, multi-level, parameterized physical entity-consistent planning, modular implementation, and distributed management approach. The speed control system is decoupled into six major functional subsystems: (1) Electrical control subsystem: electrical PID controller; (2) Main pressure regulating valve subsystem: proportional servo valve, servo motor-guided valve, manual / automatic switching valve, emergency stop valve, main pressure regulating valve; (3) Segmented shut-off valve subsystem: cam stroke valve, segmented shut-off valve; (4) Emergency pressure regulating valve subsystem: emergency pilot solenoid valve, emergency pilot hydraulic control valve, emergency pressure regulating valve; (5) Oil pressurization tank subsystem: oil pressurization tank, oil collection tank, oil pressurization pump, combination valve (safety valve, check valve, etc.); (6) Actuator: guide vane servo (axial propeller type and impeller servo).

[0007] By identifying the physical devices under each of the above subsystems and creating a modeling list, a foundation is laid for overall planning and research.

[0008] S2. State-space modeling and interface coupling Speed ​​control systems involve complex physical processes such as flow and potential-to-kinetic energy conversion, requiring nonlinear dynamic modeling and solving. At the same time, it is necessary to consider the optimization and correction of data-driven models and the interface with real-time sensors.

[0009] First, the key equipment is modeled as unit modules. Based on the characteristics of the equipment, its input and output physical variables are defined. Additionally, the necessary geometric and physical parameters of the physical equipment are measured, and the state-space equations of the key equipment are derived based on the input-output relationships. The following is the mathematical modeling process for several key pieces of equipment: (1) Proportional valve modeling The dynamic response of the proportional valve spool position is dominated by the rate of change of the input current signal, which ranges from 4 to 20 mA. At 12 mA, the spool is in the neutral position; at 20 mA, it is in position 1; and at 4 mA, it is in position -1. An enhanced second-order differential equation is established with the current signal as the input:

[0010] Where: m: valve core mass; x: valve core displacement; c: viscous resistance coefficient; k: spring stiffness coefficient; K e Electromagnetic force coefficient; In terms of dynamics, since the internal geometric and physical parameters of a proportional valve are difficult to obtain, traditional dynamic modeling is difficult to implement. Therefore, its motion can be represented by a classical second-order system. This model can effectively characterize the inertia, damping, and elastic effects of the valve core under the action of a control signal. Its dynamic performance is jointly determined by two key parameters: the system's natural frequency and damping ratio. Regarding flow characteristics, this model assumes that the proportional valve has ideal linear flow regulation characteristics. This means that under the condition that the pressure difference across the valve remains constant, the flow rate through the proportional valve is strictly linearly proportional to the displacement of the valve core. Combining valve core dynamics and linear flow characteristics, a complete mathematical model of the proportional valve can be established as follows:

[0011]

[0012]

[0013] In the formula: ω n : Resonant frequency; ζ: Damping ratio; x: Valve core position (-1, 1); I: Current (4-20mA); Q: Flow rate; Qv: Rated flow rate (maximum opening flow rate under a differential pressure of 35 bar).

[0014] (2) Modeling of the main pressure regulating valve The piston position of the main pressure regulating valve is controlled by the flow rate into the control chamber from the pilot valve. The opening area between the piston displacement and the bushing serves as the flow domain of the main pressure circuit. The state-space equations for the piston displacement and the pressure in the control chamber of the main pressure regulating valve are constructed as follows:

[0015]

[0016] Where: x: displacement of the main piston; m: mass of the main piston; A K : Cross-sectional area of ​​the control cavity; P K : Control chamber pressure; B: Viscous friction coefficient; f: Load force on the other side of the piston; k: Piston end resistance coefficient; V: Control chamber volume; β: Oil elastic modulus; Q: Flow rate into the control chamber.

[0017] The flow rate in the main pressure circuit of the main pressure regulating valve satisfies the flow equation, where positive and negative signs indicate the direction of the oil path: "+" indicates the direction of the open-chamber oil path, and "-" indicates the direction of the closed-chamber oil path.

[0018] Where: Q: Flow rate of the main pressure regulating valve channel; C d : Flow coefficient (typically 0.6-0.8 for thin-walled orifices); ΔP: Pressure difference between the inlet and outlet of the channel; ρ: Oil density.

[0019] (3) Modeling of the main relay device The two chambers of the main servo actuator are connected to the two orifices of the main pressure regulating valve, respectively. The flow entering or leaving the start-up chamber is accompanied by the back-and-forth movement of the piston of the main servo actuator. The state-space equations for the displacement and velocity of the piston rod and the pressure in the two chambers are as follows:

[0020]

[0021]

[0022] Where: x: displacement of the main servo piston; m: mass of the main servo piston; A A Cross-sectional area of ​​the opening cavity; A B : Cross-sectional area of ​​the shutdown chamber; P A : Start-up chamber pressure; P B B: Pressure in the shut-off chamber; F: Coefficient of viscous friction; f: Load force (resistance) on the other side of the piston; end Piston cylinder end limiting resistance; V A : Volume of the opening chamber; V B : Volume of the shutdown chamber; β: Elastic modulus of the oil; Q A : Start-up chamber flow rate; Q B : Shutdown chamber flow rate.

[0023] by Figure 3 Taking the integrated system of the main pressure regulating valve and the main servo as an example: when the main pressure regulating valve is in a certain open state, its port A and port B are connected to the opening chamber and closing chamber of the servo, respectively. The system uses the servo's opening chamber pressure P. A and the pressure P of the closed cavity B As input, the flow rate Q entering the two chambers is calculated using the flow equation. A and Q B These two flow rates are then used as inputs to the relay model to iteratively calculate the chamber pressure P at the next moment. A and P B At the same time, the displacement x of the relay is output.

[0024] Based on the above interface coupling mechanism, all speed controller units can be connected in series to form a complete system model, realizing the seamless flow and dynamic iteration of various physical quantities in the system, and finally outputting the overall response of the system.

[0025] S3. Modular Testing and Verification This phase employs a "bottom-up, step-by-step" strategy to thoroughly test the model and ensure its reliability and accuracy.

[0026] (1) The unit-level verification process adopts a progressive testing strategy to ensure that the dynamic characteristics of each smallest unit conform to engineering practice. Step response test: For example, apply a step current signal (10%, 50%, 100% of rated command) with progressively increasing amplitude to a proportional servo valve, and monitor the valve spool position feedback in real time. The response time and phase difference must fully meet industry standards. Apply a step current signal (10%, 50%, 100% of rated command) with progressively increasing amplitude to a relay, and monitor the relay displacement curve. The response time, opening or closing speed, and overshoot must all meet industry standards.

[0027] Fault injection test: For example, reduce the maximum valve window to simulate valve jamming, increase the internal leakage coefficient of the relay to simulate oil leakage, and verify that the displacement speed of the actuator meets the expectations.

[0028] (2) System-level integration testing: Co-simulation: Control, hydraulic and mechanical equipment are connected through physical quantity coupling and are calculated and simulated according to the same step size.

[0029] Comparison with actual machine data: Import actual machine data of a power plant during startup, load increase / decrease, load shedding, primary frequency regulation, and shutdown, and verify that the displacement error of the model actuator is within 1%.

[0030] S4. Parameterized encapsulation and reuse This phase is a crucial step in transforming the validated, high-precision unit models from the first three phases into standardized digital assets that are flexibly configurable, easy to maintain, and capable of collaborative operation. Its core objective is to build a parameter-driven model ecosystem, enabling efficient model reuse and dynamic updates.

[0031] (1) Set the key geometric parameters (piston height of main pressure regulating valve, cross-sectional area of ​​piston of main servo, stroke of servo, etc.) and physical parameters (such as piston mass of main pressure regulating valve, rated flow of proportional valve, etc.) in the digital models of each device as external adjustable parameters, and establish a centralized parameter database; use industry standards such as FMI (Functional Mock-up Interface) to encapsulate the model, store the encapsulated model in a unified component library, and the encapsulated model can be connected to the external parameter database through the configuration interface; by calling this interface, the parameter values ​​are automatically read from the parameter database and loaded into the model for simulation.

[0032] (2) For different power plants or different types of units, new system models can be quickly assembled by calling different models of similar equipment in the component library, which greatly improves the efficiency of new product development. At the same time, when equipment is upgraded or worn out, the model can also be updated in a timely manner by actually measuring the physical parameters required by the model and updating them to the constructed parameter database, thus forming a self-adaptive system.

[0033] Compared with the prior art, the beneficial effects of the present invention include: (1) Deep transparency of physical mechanisms: The equipment-level model built based on state-space equations has parameters that are directly traceable to the measured geometric properties and physical characteristics of the equipment, completely avoiding the problem of the parameters of traditional black-box models being disconnected from the physical entity. This "direct coupling of physical quantities" mechanism enables the model to have clear engineering traceability - when the equipment is worn or replaced, only the parameter library needs to be updated to trigger the automatic reconstruction of the model, and the historical operation data chain is retained at the same time, which significantly improves the accuracy of fault attribution analysis.

[0034] (2) Dynamic adaptive modeling capability solves the adaptation bottleneck of non-standard equipment. Through the graphical process calculation framework, users can customize the fluid boundary conditions of complex topological structures, breaking through the limitations of commercial software standard templates in representing irregular flow channels. At the same time, the open algorithm integration environment supports agile iteration of control strategies. Combined with the modular testing system, it realizes dynamic optimization of the entire link from design parameters to control logic, which greatly shortens the technical adaptation cycle of non-standard equipment.

[0035] (3) The multi-domain collaborative verification system ensures the engineering credibility of the simulation. It adopts a progressive verification strategy of "unit-system". At the unit level, the dynamic characteristics compliance is verified through step response testing. At the system level, the simulation results of mechanical-hydraulic-electrical multi-domain coupling are verified through closed-loop verification of real machine data to ensure consistency with the industrial field. This system not only covers routine performance verification, but also exposes hidden risks in advance through fault simulation, providing a highly robust decision-making basis for intelligent operation and maintenance.

[0036] In summary, this technical framework, based on the transparency of physical mechanisms, achieves a unity of theoretical rigor and engineering practicality through dynamic reconstruction and collaborative verification mechanisms, thus building an independent and controllable technical foundation for the digital design, intelligent control, and life prediction of major equipment such as hydropower and nuclear power. Attached Figure Description

[0037] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0038] Figure 1 This is a schematic diagram of the overall process of the present invention.

[0039] Figure 2 This is a schematic diagram of the speed regulation subsystem of the present invention.

[0040] Figure 3 This is a schematic diagram of the input-output physical quantity coupling structure of the main pressure regulating valve-main relay of the present invention. Detailed Implementation

[0041] The present invention discloses a simulation modeling method for the smallest unit of a hydro-turbine governor based on fluid dynamics. For the simulation modeling of governors in small and medium-sized mixed-flow hydro-turbine units, the overall flowchart is as follows: Figure 1 As shown, the specific implementation is as follows: S1. Multi-domain minimum unit decomposition The speed control system is decoupled into six functional subsystems, such as Figure 2 As shown, considering the characteristics of the mixed-flow turbine units (10MW per unit) of this hydropower station, the specific equipment list for each subsystem is defined as follows: (1) Electrical control subsystem: The electrical PID controller adopts Siemens S7-1200PLC type PID controller, and the input signal is unit speed 450-550r / min and output 0-10MW; (2) Main pressure regulating valve subsystem: including 4WRAE6 type proportional servo valve (rated current 4-20mA), DSG-01 type pilot valve, manual / automatic switching knob, JT-1 type emergency stop valve, DP-80 type main pressure regulating valve; (3) Segmented shut-off valve subsystem: CT-20 type cam stroke valve and GF-50 type segmented shut-off valve are selected; (4) Emergency pressure regulating valve subsystem: including 2W-25 type emergency pilot solenoid valve, YF-32 type emergency pilot hydraulic control valve, and SP-63 type emergency pressure regulating valve; (5) Pressurized oil tank subsystem: 2m³ volume 3 Pressure oil tank, 1m 3 Oil collection tank, two CB-40 type oil pressure pumps, and a combination valve including an A22H type safety valve and an H41H type check valve; (6) Actuator: Only includes guide vane servo, no wheel blade servo.

[0042] The final modeling list of 21 devices was formed, clarifying the model, installation location, and coupling relationship of each device with other subsystems.

[0043] S2. State-space modeling and interface coupling Mathematical models were established for the core equipment, with a focus on completing the following modeling: (1) Proportional valve modeling: Input: 4-20mA current signal (12mA in the middle position, corresponding to 0 displacement of the valve core).

[0044] Mathematical model: The enhanced second-order differential equation described in the invention is used, and the measured parameters are substituted in: resonant frequency ω n =50Hz, damping ratio ζ=0.6, rated flow rate Qv=40L / min; Flow characteristics: Follows the L-curve, with a flow rate of -40L / min at valve position -1 (4mA) and +40L / min at valve position 1 (20mA).

[0045] (2) Modeling of the main pressure regulating valve: The piston position of the main pressure regulating valve is controlled by the flow rate into the control chamber from the pilot valve. The opening area between the piston displacement and the bushing serves as the flow domain of the main pressure circuit. The state-space equations for the piston displacement and the pressure in the control chamber of the main pressure regulating valve are constructed as follows:

[0046]

[0047] Substituting the measured parameters, the mass of the main piston is m = 5 kg, and the cross-sectional area of ​​the control chamber is A. K =0.01m 2 The coefficient of viscous friction is B = 10 N·s / m, and the volume of the control cavity is V = 0.002 m³. 3 The elastic modulus of the oil is β = 2.1 × 10⁻⁶. 9 Pa.

[0048] The flow rate in the main pressure circuit of the main pressure regulating valve satisfies the flow equation, where positive and negative signs indicate the direction of the oil path: "+" indicates the direction of the open-chamber oil path, and "-" indicates the direction of the closed-chamber oil path.

[0049] Flow coefficient C d =0.7, oil density ρ=850kg / m³, and the pressure difference ΔP between the inlet and outlet of the channel is taken as 16MPa.

[0050] (3) Modeling of the main relay device: The two chambers of the main servo actuator are connected to the two orifices of the main pressure regulating valve, respectively. The flow entering or leaving the start-up chamber is accompanied by the back-and-forth movement of the piston of the main servo actuator. The state-space equations for the displacement and velocity of the piston rod and the pressure in the two chambers are as follows:

[0051]

[0052]

[0053] Substituting the measured parameters, piston mass m = 12 kg, viscous friction coefficient B = 18 N·s / m, constant load force f = 800 N, and end-capacitance resistance f end =600N, cross-sectional area of ​​the machine cavity A A =0.0707m², Cross-sectional area A of the shutdown chamber B =0.0628m².

[0054] (4) Interface coupling: The 4-20mA current signal output by the PID controller is connected to the proportional servo valve. The output flow rate Q of the proportional servo valve is connected to the control chamber of the main pressure regulating valve. Port A (open chamber) and Port B (closed chamber) of the main pressure regulating valve are connected to the start-up chamber and stop-down chamber of the main servo motor, respectively. The flow rate Q... A Q B The drive relay displacement x forms a complete signal chain of "control-hydraulic-mechanical", enabling seamless iteration of physical quantities.

[0055] S3. Modular Testing and Verification This phase employs a "bottom-up, step-by-step" strategy to thoroughly test the model and ensure its reliability and accuracy.

[0056] (1) Unit-level verification, step response test: Apply 10% (12-12.8mA), 50% (12-16mA), and 100% (12-20mA) rated current step signals to the proportional servo valve and monitor the valve core position feedback: response time ≤ 0.2s, phase difference ≤ 5°; apply the corresponding flow step signal to the guide vane relay and monitor the displacement curve: opening speed 50mm / s, closing speed 40mm / s, overshoot ≤ 3%, which meets the requirements.

[0057] Fault injection test: The maximum window of the main pressure regulating valve was reduced by 20% to simulate jamming, and the displacement speed of the guide vane servo decreased to 35 mm / s (expected value 32-38 mm / s). The internal leakage coefficient of the servo was increased to 0.05 L / min to simulate oil leakage, and the displacement speed decreased to 38 mm / s, both of which met expectations.

[0058] (2) System-level integration testing: Collaborative simulation: Control, hydraulic and mechanical equipment are connected through physical coupling and calculated synchronously in 0.01s steps, with no disconnection or delay in the simulation curve.

[0059] Comparison with actual machine data: Import data on the hydropower station's start-up, no-load, increase / decrease operations, primary frequency regulation, and shutdown, and verify that the displacement error of the model's actuator is within 1%. S4. Parameterized encapsulation and reuse (1) Intelligent module packaging: The proportional valve ω n Twenty-eight key parameters, including ζ, main pressure regulating valve m, and servo diameter, are set to be externally adjustable. A centralized parameter database in Excel format is established. All unit models are encapsulated using the FMI2.0 standard and stored in the "Small and Medium Mixed Flow Unit Model Component Library". The encapsulated model is connected to the parameter database through an API interface and can automatically read parameter values.

[0060] (2) Dynamic Reconstruction and Reuse: When a model of a similar 5MW hydropower station needs to be built, similar equipment models such as the 4WRAE6 proportional valve and the DP-80 main pressure distribution valve are called from the component library. Only the diameter of the guide vane servo in the parameter database is modified from 300mm to 250mm, and the volume of the pressure tank is changed from 2m³ to 250mm. 3 Change to 1.5m 3 The new model can be assembled within 2 hours without the need for remodeling.

Claims

1. A simulation modeling method for the smallest unit of a hydro-turbine governor based on fluid dynamics, characterized in that... Includes the following steps: S1. Multi-domain minimum unit decomposition: Based on the multi-domain coupling and multi-level characteristics of the turbine control system, combined with the equipment domain coupling relationship and spatial position relationship, a multi-domain, multi-level, parameterized corresponding physical entity consistent planning, modular implementation, and distributed management approach is adopted to decouple the speed control system into 6 major functional subsystems, sort out the physical equipment under each subsystem and form a modeling list; S2. State-space modeling and interface coupling: For complex flow and potential energy to kinetic energy conversion physical processes in speed regulation systems, unit module modeling is performed on important equipment, the physical variables of equipment input and output are divided, the geometric and physical parameters of physical equipment are measured, the state-space equations of important equipment are listed, and an interface coupling mechanism between equipment is established to realize seamless flow and dynamic iteration of system physical quantities. S3. Modular Testing and Verification: A bottom-up, progressive strategy is adopted, first conducting unit-level verification, including step response testing and fault injection testing, and then performing system-level integration testing, including co-simulation and comparison with real machine data, to ensure the reliability and accuracy of the model; S4. Parametric Encapsulation and Reuse: The key geometric and physical parameters of the verified unit model are set to be externally adjustable. A centralized parameter database is established, and the model is encapsulated using industry standards and stored in a unified component library to achieve flexible configuration, efficient reuse and dynamic updates of the model.

2. The simulation modeling method for the smallest unit of a hydro-turbine governor based on fluid dynamics according to claim 1, characterized in that: The six functional subsystems in step S1 include the electrical control subsystem, the main pressure regulating valve subsystem, the segmented shut-off valve subsystem, the emergency pressure regulating valve subsystem, the pressure oil tank system, and the actuator. The electrical control subsystem includes an electrical PID controller; The main pressure regulating valve subsystem includes a proportional servo valve, a servo motor-guided valve, a manual / automatic switching valve, an emergency stop valve, and a main pressure regulating valve. The segmented shut-off valve subsystem includes a cam stroke valve and a segmented shut-off valve; The emergency pressure regulating valve subsystem includes an emergency pilot solenoid valve, an emergency pilot hydraulic control valve, and an emergency pressure regulating valve. The oil pressure tank subsystem includes an oil pressure tank, an oil collection tank, an oil pressure pump, and a combination valve; The actuator includes a guide vane servo, and if it is an axial-flow propeller turbine unit, it also includes a rotor blade servo.

3. The simulation modeling method for the smallest unit of a hydro-turbine governor based on fluid dynamics according to claim 1, characterized in that: The specific requirements for forming the modeling list in step S1 are as follows: the list must clearly define the model specifications, installation space location, and coupling relationship of each physical device with devices in other subsystems, and the coupling relationship must correspond to the actual physical connection logic between devices, so as to provide a basis for subsequent global modeling and overall research.

4. The simulation modeling method for the smallest unit of a hydro-turbine governor based on fluid dynamics according to claim 1, characterized in that: The unit module modeling of important equipment in step S2 includes proportional valve modeling. The specific process of proportional valve modeling is as follows: the dynamic response of the valve core position of the proportional valve is dominated by the rate of change of the input current signal, where the current signal range is 4-20mA. At 12mA, the valve core is in the middle position, at 20mA it is in the first position, and at 4mA it is in the -1 position. An enhanced second-order differential equation with the current signal as input is established: ； Where: m: valve core mass; x: valve core displacement; c: Viscous resistance coefficient; k: Spring stiffness coefficient; K e Electromagnetic force coefficient; In terms of dynamics, since the internal geometric and physical parameters of a proportional valve are difficult to obtain, traditional dynamic modeling is difficult to implement. Therefore, its motion can be represented by a classical second-order system. This model can effectively characterize the inertia, damping, and elastic effects of the valve core under the action of a control signal. Its dynamic performance is jointly determined by two key parameters: the system's natural frequency and damping ratio. Regarding flow characteristics, this model assumes that the proportional valve has ideal linear flow regulation characteristics. This means that under the condition that the pressure difference across the valve remains constant, the flow rate through the proportional valve is strictly linearly proportional to the displacement of the valve core. Combining valve core dynamics and linear flow characteristics, a complete mathematical model of the proportional valve can be established as follows: ； ； ； In the formula: ω n : Resonant frequency; ζ: Damping ratio; x: Valve spool position; I: Current; Q: Flow rate; Qv: Rated flow rate; ΔP: Pressure difference between inlet and outlet of the channel.

5. The simulation modeling method for the smallest unit of a hydro-turbine governor based on fluid dynamics according to claim 1, characterized in that: The unit module modeling of important equipment in step S2 includes the modeling of the main pressure regulating valve, and the construction of the state-space equations for the displacement of the main pressure regulating valve piston and the pressure of the control chamber: ； ； In the formula: x: displacement of the main piston; m: Mass of the main piston; A K : Cross-sectional area of ​​the control cavity; P K : Control chamber pressure; B: Coefficient of viscous friction; f: Load force on the other side of the piston; k: piston end resistance coefficient; V: control chamber volume; β: oil elastic modulus; Q: Flow rate into the control chamber; The flow rate in the main pressure circuit of the main pressure regulating valve satisfies the flow equation, where positive and negative signs indicate the direction of the oil path: "+" indicates the direction of the open-chamber oil path, and "-" indicates the direction of the closed-chamber oil path. ； Where: Q: Flow rate of the main pressure regulating valve channel; C d Flow coefficient (typically 0.6-0.8 for thin-walled orifices); ΔP: Pressure difference between the inlet and outlet of the channel; ρ: oil density.

6. The simulation modeling method for the smallest unit of a hydro-turbine governor based on fluid dynamics according to claim 1, characterized in that: The unit module modeling of the important equipment in step S2 includes the modeling of the main servo motor. The two chambers of the main servo motor are respectively connected to the two holes of the main pressure regulating valve. The flow entering or leaving the start-up chamber is accompanied by the back-and-forth movement of the piston of the main servo motor. The state-space equations of the piston rod displacement, velocity, and pressure in the two chambers are as follows: ； ； ； Where: x: displacement of the main relay piston; m: Mass of the main relay piston; A A Cross-sectional area of ​​the opening cavity; A B : Cross-sectional area of ​​the shutdown chamber; P A : Start-up chamber pressure; P B B: Pressure in the shutdown chamber; C: Coefficient of viscous friction; f: Load force (resistance) on the other side of the piston; f end Piston cylinder end limiting resistance; V A : Volume of the opening chamber; V B : Volume of the shutdown chamber; β: Elastic modulus of the oil; Q A : Start-up chamber flow rate; Q B : Shutdown chamber flow rate.

7. The simulation modeling method for the smallest unit of a hydro-turbine governor based on fluid dynamics according to claim 1, characterized in that: The specific implementation of the interface coupling mechanism in step S2 is as follows: the 4-20mA current signal output by the PID controller in the electrical control subsystem is connected to the proportional servo valve of the main pressure regulating valve subsystem. The output flow of the proportional servo valve is connected to the control chamber of the main pressure regulating valve. The opening and closing chambers of the main pressure regulating valve are respectively connected to the starting and closing chambers of the main servo valve. Through the flow Q A Q B The drive relay displacement x forms a complete coupled link of control signal - hydraulic signal - mechanical action, realizing seamless transmission and dynamic iteration of physical quantities between various devices.

8. The simulation modeling method for the smallest unit of a hydro-turbine governor based on fluid dynamics according to claim 1, characterized in that: The unit-level verification in step S3 includes step response testing and fault injection testing; The step response test includes applying a step current signal with an amplitude increment of 10%, 50%, and 100% of the rated command to the proportional servo valve, monitoring the valve core position feedback, and requiring the response time and phase difference to meet industry standards; applying a flow step signal with a corresponding amplitude increment to the guide vane relay, monitoring the displacement curve, and requiring the response time, opening / closing speed, and overshoot to meet industry standards. The fault injection test simulates valve jamming by reducing the maximum valve window and simulates oil leakage by increasing the internal leakage coefficient of the relay, thus verifying that the displacement speed of the actuator meets the expected design value.

9. The simulation modeling method for the smallest unit of a hydro-turbine governor based on fluid dynamics according to claim 1, characterized in that: The system-level integration test in step S3 includes co-simulation and comparison of real machine data; The collaborative simulation involves coupling control, hydraulic, and mechanical equipment through physical quantities and performing synchronous calculations and simulations according to the same time step to ensure that the simulation curves are uninterrupted and without delay. The comparison of actual machine data involves importing actual machine data under the operating conditions of the target power plant during startup, load increase / decrease, load shedding, and shutdown, and verifying the error between the simulated value and the actual value of the actuator displacement in the model. The error is required to be within 1%.

10. The simulation modeling method for the smallest unit of a hydro-turbine governor based on fluid dynamics according to claim 1, characterized in that: The parameterization encapsulation and reuse in step S4 includes parameter database construction, model encapsulation, and model reuse. The parameter database is constructed by setting key geometric and physical parameters in the digital models of each device, including but not limited to the piston height of the main pressure regulating valve, the cross-sectional area of ​​the piston of the main servo motor, the stroke of the servo motor, the mass of the piston of the main pressure regulating valve, and the rated flow of the proportional valve, as external adjustable parameters, and establishing a centralized parameter database. The database format supports compatibility with the model encapsulation interface. The model encapsulation method uses the FMI function mock-up interface industry standard to encapsulate the verified unit model. The encapsulated model is stored in a unified component library, which supports model classification retrieval and calling. The model reuse method involves calling similar equipment models from the component library for different power plants or different types of units, modifying the key physical parameters of the corresponding equipment through the parameter database, and realizing the rapid assembly of new system models. When the equipment is upgraded, modified, or worn out, the corresponding parameter values ​​in the parameter database are updated, and the model is automatically adapted and updated.

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