CN-121995751-A - Starting-up optimization control method of large-sized water motor unit based on full-view simulation and dynamic verification

CN121995751ACN 121995751 ACN121995751 ACN 121995751ACN-121995751-A

Abstract

The invention belongs to the field of hydroelectric power generation control engineering and fluid mechanical dynamics, and particularly discloses a startup optimization control method of a large-sized hydroelectric generating set based on full-view simulation and dynamic verification, which comprises the following steps: the method comprises the steps of constructing a multidimensional true machine test database, evaluating a reference, defining a one-dimensional system simulation and a macroscopic boundary, simulating a three-dimensional high-fidelity transient flow field, observing a microscopic mechanism, dynamically optimizing a startup rule based on simulation insight, and performing closed loop and iterative refining by a simulation-test technology. Compared with the prior art, the invention organically combines one-dimensional system simulation with three-dimensional high-fidelity flow field simulation for the first time, solves the comprehensive analysis problem from the macroscopic hydraulic transition process to the microscopic complex flow mechanism, realizes the 'full-transparency' insight of the starting process, can simultaneously consider a plurality of performance indexes such as vibration, swing, stress, temperature and the like, and realizes the cooperative promotion of the whole stability of the unit.

Inventors

AN XUELI
LU YINGYU
LIU QIYUAN
XUE QIYAO
WU TINGWEI

Assignees

中国水利水电科学研究院

Dates

Publication Date: 20260508
Application Date: 20260119

Claims (10)

1. The startup optimization control method of the large-sized water motor unit based on full visual angle simulation and dynamic verification is characterized by comprising the following steps of: S1, systematically executing a plurality of preset startup control modes aiming at a target unit, synchronously acquiring structural dynamics data, vibration data, stability data, thermodynamic data and hydraulic data, establishing a reference database, and quantitatively evaluating the advantages and disadvantages of each startup mode; S2, establishing a hydraulic-mechanical-electric one-dimensional system simulation model of the unit based on a characteristic line method, calculating macroscopic dynamic responses of the power generation system under different startup rules, defining a safe operation boundary and providing time-varying boundary conditions; S3, based on the time-varying boundary conditions of the step S2, establishing a three-dimensional full-flow-channel high-fidelity CFD model containing all the overcurrent components, carrying out transient unsteady flow field simulation, and revealing internal complex flow phenomena and excitation sources; s4, synthesizing simulation results of the steps S2 and S3, adjusting a startup curve aiming at a strong vibration flow state interval, and generating a multi-section variable parameter startup optimization curve by optimizing acceleration, an open loop holding section and an open loop/closed loop switching point; S5, applying the optimized starting-up rule in the step S4 to a true machine test, comparing a test result with a simulation prediction result, solidifying the rule when the coincidence degree reaches the standard, and otherwise, correcting the model parameter for iterative optimization; s6, constructing a multi-index comprehensive scoring system based on the Riemann manifold, calculating the comprehensive score of each starting mode, and screening the optimal starting mode.
2. The method according to claim 1, characterized in that step S1 comprises in particular the sub-steps of: s11, selecting a starting mode, wherein the starting mode comprises guide vane large starting, guide vane small starting, variable acceleration control, open loop and closed loop combined starting; S12, arranging starting-up test measuring points, including a unit vibration measuring point, a swing degree measuring point, a water pressure pulsation measuring point, a strain measuring point, a stress measuring point and a rotating speed measuring point; S13, performing a startup test at a selected water head, and recording the opening degree of the guide vane and the change condition of data of each measuring point along with time; s14, processing the acquired data, and calculating the peak amplitude and the stress value of the mixing peak; s15, comparing and analyzing the same data under different starting modes, and quantitatively evaluating the advantages and disadvantages of all the starting modes.
3. The method according to claim 2, wherein in step S14, the peak amplitude of the mixing peak is a 97% confidence value, that is, a statistical point probability is calculated for the time waveform map partition, and the 3% untrusted region data is removed, and the stress is calculated according to the following equation according to the strain value collected in the test process: ; Wherein, the E is the elastic modulus of the tested structural material and is the strain value, Is stress.
4. The method according to claim 1, characterized in that step S2 comprises in particular the sub-steps of: s21, constructing a mathematical model of a hydraulic system based on a characteristic line method, wherein the hydraulic system comprises a pressure pipeline, a water turbine and a speed regulator; s22, carrying out simulation calculation under different starting modes, analyzing time domain change conditions of the rotating speed of the unit, the volute pressure and the draft tube pressure, and providing an initial optimized starting mode.
5. The method according to claim 4, wherein in step S21, the mathematical model of the pressure pipe is established using the following formula: ; ; Wherein, the subscript i is any grid intersection point in the x direction; A head of point P; The flow is the flow of the point P; 、、、 Is the moment of time Is obtained using the following formula: ; Wherein, the constants B and R are obtained by adopting the following formula: ; ; Wherein A is the area of the pipeline section, m 2 , g is the gravity acceleration, m/s 2 , f is the hydraulic loss coefficient along the course of Darcy-Weisbach, D is the pipeline diameter, m; the length of each section after being divided into n sections is equal to the length of a pipeline with the length L, m is the water hammer wave speed, m/s, and the water hammer wave speed is obtained by adopting the following formula: ; Wherein K is the volume elastic modulus of water; The density of water, E is the elastic modulus of the pipe, N/m 2 , D is the inner diameter of the pipe, m, and E is the thickness of the pipe wall, m.
6. The method according to claim 4, wherein in step S21, the mathematical model of the hydraulic turbine is established using the following formula: ; ; ; ; ; in the formula, Is a flow function; Is a moment function; Is the relative value of the opening degree of the guide vane; Is the opening degree of the guide vane; Is the relative value of the water head; Is the relative flow value; Is the relative value of the rotating speed; Is the relative value of moment; is the relative angular velocity deviation; The moment relative value of the instantaneous shaft of the water turbine; is the relative value of electromagnetic resistance; Is rated torque; Is the inertial time constant of the unit, s; Is flywheel moment, t.m 2 ; Rated power, kW; ; In the above formula, subscript r represents rated parameter value.
7. The method of claim 4, wherein in step 21, the mathematical model of the governor is constructed using the formula: ; ; ; in the formula, The relative value of the deviation of the output signal of the speed regulator; The subscript 0 represents an initial value for the relative value of the rotational speed deviation of the unit; is a permanent slip coefficient, and the value of the permanent slip coefficient is selected in the range of 0-0.1; The reaction time of the guide vane servomotor; the relative value of the deviation of the guide vane servomotor represents the deviation of the servomotor stroke y and the maximum stroke Is a ratio of (2); The relative value of the stroke deviation of the main distributing valve represents the ratio of the stroke of the main distributing valve deviating from the central position to the maximum stroke, and the maximum stroke refers to the stroke of the main distributing valve when the deviation of an input rotating speed signal is 100%; The proportional gain of the speed regulator; Integrating the gain for the speed regulator; differential gain for the governor; The method is obtained by adopting the following formula: ; ; ; in the formula, The transient slip coefficient of the speed regulator; buffer time constant for the governor; is the differential time constant or the acceleration time constant of the speed regulator.
8. The method according to claim 1, characterized in that step S3 comprises in particular the sub-steps of: S31, establishing a full-river basin geometric model of a unit volute, a fixed guide vane, a movable guide vane, a rotating wheel and a draft tube; s32, carrying out grid division on the geometric model; S33, setting boundary conditions, adopting an SST k-omega turbulence model to seal an N-S equation set, setting total pressure at the inlet of a volute, setting static pressure at the outlet of a draft tube, adopting a rotating coordinate system method for rotating wheel steady-state calculation, and adopting a sliding grid method for transient calculation; S34, arranging pressure pulsation measuring points on the rotating wheel, the volute, the vicinity of the fixed guide vane, the vicinity of the movable guide vane, the vaneless region and the draft tube; S35, carrying out flow field evolution analysis on typical calculation working conditions with different startup rules; S36, comparing and analyzing the pressure pulsation evolution of each overcurrent component under different startup rules; S37, primarily screening an optimal starting mode.
9. The method according to claim 1, characterized in that step S31 comprises the following sub-steps: S311, arranging component structure data of a unit volute, a fixed guide vane, a movable guide vane and a draft tube, and establishing a three-dimensional geometric model by adopting solidworks modeling software; S312, acquiring a rotating wheel three-dimensional geometric model through reverse modeling after acquiring a point cloud through site three-dimensional scanning; S313, directly establishing a three-dimensional geometrical structure of the drainage basin for the volute and the draft tube, acquiring corresponding drainage basins of the runner and the guide vane through Boolean operation, and assembling all the components to form a full-drainage-basin geometrical model.
10. The method according to claim 1, wherein in step S5, if the matching degree of the test result and the simulation prediction result is greater than or equal to the preset threshold and the optimization goal is reached, the startup rule is cured, otherwise, the test data is fed back to the one-dimensional and three-dimensional simulation models, and steps S2 to S5 are repeated after the parameters are corrected until the optimal startup rule meeting the safety and stability requirements is obtained.

Description

Starting-up optimization control method of large-sized water motor unit based on full-view simulation and dynamic verification Technical Field The invention belongs to the field of hydroelectric power generation control engineering and fluid mechanical dynamics, and particularly relates to a startup optimization control method of a large-sized hydroelectric generating set based on full-view simulation and dynamic verification. Background Along with the rapid development of hydropower technology, huge hydropower units with single-machine capacity reaching the level of millions of kilowatts (such as a crane beach hydropower station) are becoming large-country heavy machines. The machine set has the characteristics of complex structure, large rotational inertia, complex hydraulic conditions and the like. The starting-up process of the machine set is a complex transient transition process involving multiple physical field coupling of machinery, water power, electromagnetism and the like. In the process, an unreasonable startup rule (such as a guide vane opening speed, acceleration control, open-loop/closed-loop switching time and the like) can induce strong pressure pulsation, mechanical vibration and swing degree, impact on key components (such as a top cover, bolts, bearings, a stator base and the like) of the unit, accelerate fatigue damage of the unit and threaten safe and stable operation of a power station. In the existing startup law optimization technology, the following main defects mainly exist: The simulation means is single, macroscopic and microscopic can not be considered, the complex vortex, cavitation and pressure pulsation behind the guide vane and inside the rotating wheel in the starting process can not be captured in the traditional one-dimensional hydraulic transition process calculation, the simulation calculation amount of a pure three-dimensional CFD flow field is extremely large, the whole process dynamic response from static to rated rotation speed is difficult to simulate, and the deviation exists between the simulation result and the actual dynamic characteristic of a real machine. The consideration of structural fatigue is lacking, the conventional startup rule optimization mostly aims at the overshoot of the rotating speed and the adjustment time, and transient dynamic stress and accumulated fatigue damage to key connectors such as a top cover and a bolt caused by severe pressure pulsation in the startup process are ignored. For millions of kilowatt units, huge water thrust can cause micro-deformation of structural members, and vibration is caused, so that the traditional method is lack of evaluation. The test is separated from the theory, the prior art often depends on a field trial-and-error method to adjust PID parameters or guide vane opening modes, and lacks a closed loop mechanism of 'simulation prediction-true machine verification-model correction-strategy optimization', so that the debugging risk is large and the period is long. Therefore, the prior art lacks a large hydroelectric generating set startup control method which can penetrate through the characteristics and micro-flow mechanism of a macro system and can be accurately optimized in multiple targets and multiple dimensions under the condition of low risk. Disclosure of Invention Aiming at the defects of the technology, the invention provides a startup optimization control method of a large-sized water motor unit based on full-view simulation and dynamic verification. In order to achieve the above purpose, the present invention provides the following technical solutions: The invention provides a startup optimization control method of a large-sized water motor unit based on full-view simulation and dynamic verification, which comprises the following steps: S1, systematically executing a plurality of preset startup control modes aiming at a target unit, synchronously acquiring structural dynamics data, vibration data, stability data, thermodynamic data and hydraulic data, establishing a reference database, and quantitatively evaluating the advantages and disadvantages of each startup mode; S2, establishing a hydraulic-mechanical-electric one-dimensional system simulation model of the unit based on a characteristic line method, calculating macroscopic dynamic responses of the power generation system under different startup rules, defining a safe operation boundary and providing time-varying boundary conditions; S3, based on the time-varying boundary conditions of the step S2, establishing a three-dimensional full-flow-channel high-fidelity CFD model containing all the overcurrent components, carrying out transient unsteady flow field simulation, and revealing internal complex flow phenomena and excitation sources; s4, synthesizing simulation results of the steps S2 and S3, adjusting a startup curve aiming at a strong vibration flow state interval, and generating a multi-section variable parameter startup optimization c