A parameter setting method and system for a speed control system in a grid-connected thermal power unit

Abstract

The present application discloses a method and system for parameter setting of a speed control system in a grid-connected thermal power unit, and relates to the technical field of parameter setting of thermal power units. The method comprises the following steps: obtaining parameter information of a grid-connected thermal power unit and creating a simulation mathematical model of a speed control system; determining a first value range of a target parameter in the speed control system based on the simulation mathematical model, and determining a plurality of operating condition data based on historical operating data of the thermal power unit, wherein each group of operating condition data comprises an operating condition, a load level and a frequency fluctuation; verifying, based on the plurality of operating condition data, whether the frequency fluctuation overshoot of the speed control system of the simulated target parameter output by the simulation mathematical model within the first value range is less than a preset overshoot threshold; determining a second value range according to the actual parameters of the unit and the first value range, and determining an optimized parameter value of the target parameter in the speed control system according to the second value range. The method optimizes and sets the parameters of the control system of the thermal power unit, and improves the frequency regulation performance and power stability of the unit.

Description

Technical Field

[0001] The present application relates to the technical field of parameter setting of thermal power units, and in particular to a parameter setting method and system for a speed control system in a grid-connected thermal power unit. Background Art

[0002] Under the development model of the power system with "large units, ultra-high voltage, and large power grids", the operating environment of the power system has become increasingly complex, and the requirements for its safety and stability have also increased accordingly.

[0003] As the key control system of steam turbine generator sets, the speed control system has gradually attracted attention as the scale of grid interconnection expands. In order to ensure that the unit has good primary frequency regulation performance and prevent abnormal conditions such as overspeed in the event of a fault, the speed control system must have extremely high dynamic response capabilities. Under no-load and grid-connected operation, the speed control system maintains the stability of the system frequency by adjusting the generator speed and output power. In particular, when a power system fault occurs, it is crucial to quickly start the backup unit to ensure the stable operation of the power grid.

[0004] At present, there are still obvious deficiencies in the stability optimization and parameter setting of the speed control system of thermal power units. For example, when the load changes frequently, the response speed is slow, resulting in a delayed frequency response, which affects the frequency regulation performance and power stability of the unit. In addition, due to the failure to fully consider the impact of grid fluctuations, the existing methods cannot provide sufficient frequency regulation support when the grid frequency fluctuates greatly, affecting the grid-connected stability of the system. Therefore, a method for accurately setting the control parameters of the speed control system is proposed, which has important engineering application value and practical significance for improving system stability and ensuring the grid-related performance of the unit. Summary of the invention

[0005] The present application aims to solve the problems of insufficient dynamic response speed and insufficient grid-related performance optimization in the speed control system of thermal power units in the prior art in terms of stability optimization and parameter setting. Therefore, a parameter setting method and system for the speed control system in a grid-related thermal power unit are proposed.

[0006] In order to achieve the above-mentioned purpose, in a first aspect, the present application provides a method for parameter setting of a speed control system in a grid-related thermal power unit, comprising:

[0007] Acquiring parameter information of thermal power units involved in grid operation, and creating a simulation mathematical model of the speed regulation system based on the parameter information;

[0008] Based on the simulation test of the simulation mathematical model, determining a first value range of the target parameter in the speed regulation system, wherein the first value range is used to indicate that the thermal power unit can meet the primary frequency regulation performance constraint and low-frequency oscillation suppression requirement during the frequency regulation process;

[0009] Based on the historical operating data of the thermal power unit, a plurality of groups of operating condition data are determined, each group of the operating condition data includes corresponding operating conditions, load levels and frequency fluctuations;

[0010] Based on the plurality of groups of the operating condition data, verify whether the frequency fluctuation overshoot of the speed regulation system within the first value range of the simulated target parameter output by the simulation mathematical model is less than a preset overshoot threshold;

[0011] If yes, actual parameters of the prime mover and the speed control system in the thermal power unit are obtained based on the measured data and the modeling results, and a second value range is determined according to the actual parameters and the first value range, and the second value range is within the first value range;

[0012] According to the second value range, an optimized parameter value of the target parameter in the speed regulation system is determined, and the optimized parameter value is used to characterize the parameter value of the speed regulation system that meets the frequency regulation performance requirements and effectively suppresses low-frequency oscillations.

[0013] In some possible embodiments, the step of obtaining parameter information of the thermal power generating units involved in grid operation and creating a simulation mathematical model of the speed regulation system based on the parameter information includes:

[0014] Obtain parameter information of thermal power units including control systems, actuators, steam pipelines and prime movers.

[0015] Based on the parameter information, a controller differential equation and a corresponding transfer function, an actuator electro-hydraulic servo transfer function and a prime mover power model transfer function in the control system are created.

[0016] In some possible embodiments, the step of creating a controller differential equation and a corresponding transfer function, an actuator electro-hydraulic servo transfer function, and a prime mover power model transfer function in a control system based on the parameter information includes:

[0017] The transfer function expression of the actuator electro-hydraulic servo is:

[0018] Where s is a complex frequency variable, is the proportional gain, is the integral gain, is the differential gain, is the inertia time constant of the system, It is the time of the oil motor stroke feedback link;

[0019] The transfer function of the prime mover power model is:

[0020] Where s is a complex frequency variable, is the time constant of the high pressure cylinder, is the reheater time constant, is the crossover tube time constant, is the power ratio of the high pressure cylinder, Medium pressure cylinder power ratio, Low pressure cylinder power ratio, It is the natural over-regulation coefficient of high-pressure cylinder power.

[0021] In some possible embodiments, the simulation test based on the simulation mathematical model determines the first value range of the target parameter in the speed regulation system, including:

[0022] According to the evaluation index requirements of the speed control system, the output consideration parameters of the simulation mathematical model are determined, wherein the output consideration parameters include the proportional gain and the integral gain of the controller;

[0023] Based on the simulation test of the simulation mathematical model, the preliminary proportional gain and integral gain parameter range of the speed control system that meets the requirements is determined.

[0024] In some possible embodiments, if so, actual parameters of the prime mover and the speed control system in the thermal power unit are obtained based on measured data and modeling results, and a second value range is determined according to the actual parameters and the first value range, and the second value range is within the first value range, including:

[0025] Designing a control strategy of model predictive control, and predicting future state information of the speed regulation system in real time based on the control strategy;

[0026] The second value range is dynamically adjusted in real time based on the future state information to improve the response speed and stability of the speed regulation system.

[0027] In some possible embodiments, the control strategy of the design model predictive control, based on which the future state information of the speed regulation system is predicted in real time, includes:

[0028] The control strategy of model predictive control is designed based on the following expression:

[0029]

[0030]

[0031] In the formula, is the state vector of the system, is the control input vector, is the output vector, is the system error, is the state matrix, is the input matrix, is the output matrix, is the proportional gain, is the integral gain, From time To the current time The cumulative error of

[0032] The real-time prediction of the future state and output expression of the unit system is:

[0033]

[0034]

[0035] In the formula, For the moment The predicted system state at time The known state at the time; For the moment The predicted system output at time To predict the status information of To predict the number of steps, for Matrix The power indicates that the state changes over time. The evolution of For control input The impact on the state gradually changes with the time step. is the proportional gain The impact of future errors.

[0036] In some possible embodiments, the real-time dynamic adjustment of the second value range based on the future state information to improve the response speed and stability of the speed control system also includes:

[0037] Create an optimization objective function for the control input:

[0038] In the formula, is the reference signal, To control the increment, and is the weight matrix, For the moment The predicted system output at time To predict the status information of

[0039] The second value range is adjusted according to the optimized control input, wherein the adjustment process expression is:

[0040]

[0041] In the formula, is the control input of the proportional-integral controller, is the deviation between the set value and the output, is the cumulative sum of errors.

[0042] The above technical solution provided by this application, compared with the prior art, includes at least the following technical effects or advantages:

[0043] 1) The method of this application establishes the open-loop transfer function and closed-loop transfer function of the whole system according to the thermal power unit speed control system, the turbine and steam pipeline, and the load transfer function model. First, the thermal power unit that may be involved in the grid operation is simulated and modeled, and the mathematical simulation model of the speed control system is constructed. Based on the simulation test, combined with the unit's primary frequency regulation performance constraints and low-frequency oscillation suppression requirements, the preliminary speed control system parameter range is determined. Secondly, under various operating conditions such as different load levels and frequency fluctuations, the preliminary parameter range is fully verified to ensure the reliability and stability of the system in the actual operating environment. The actual parameters of the unit's prime mover and speed control system are obtained through actual measurement modeling. Based on the intersection of the control parameter value range and combined with model predictive control, the speed control system parameters are adjusted in real time and dynamically, and applied in the simulation analysis and verification of the setting method. Taking into account the primary frequency regulation parameter setting domain and low-frequency oscillation suppression requirements, the parameter value range that meets the frequency regulation performance requirements and can effectively suppress low-frequency oscillations is determined, and the parameters of the thermal power unit control system model are optimized and set accordingly.

[0044] 2) The method of the present application optimizes and determines the parameter range of the controller in the speed regulation system of the thermal power unit, which makes the response speed faster, avoids the frequency regulation response lag, and improves the frequency regulation performance and power stability of the unit. At the same time, under complex working conditions, such as frequent load fluctuations or power grid failures, the parameter setting of the system can adapt to the changing operating conditions, avoid the decline of system stability, and realize real-time dynamic adjustment, automatically adjust the control parameters according to the changes in the actual working conditions, further improve the stability of the system, thereby effectively ensuring the stability of the power grid.

[0045] In a second aspect, the present application provides a parameter setting system for a speed control system in a grid-related thermal power unit, comprising:

[0046] A model creation module is configured to obtain parameter information of a thermal power unit involved in grid operation, and create a simulation mathematical model of the speed regulation system based on the parameter information;

[0047] A first simulation module is configured to determine a first value range of a target parameter in the speed regulation system based on a simulation test of the simulation mathematical model, wherein the first value range is used to indicate that the thermal power unit can meet a primary frequency regulation performance constraint and a low-frequency oscillation suppression requirement during a frequency regulation process;

[0048] A first determination module is configured to determine a plurality of groups of operating condition data based on the historical operating data of the thermal power unit, each group of the operating condition data including corresponding operating conditions, load levels and frequency fluctuations;

[0049] A parameter verification module is configured to verify, based on the plurality of groups of operating condition data, whether the simulated target parameter output by the simulation mathematical model has an overshoot of the frequency fluctuation of the speed regulation system within the first value range and is less than a preset overshoot threshold;

[0050] A second determination module is configured to obtain actual parameters of the prime mover and the speed control system in the thermal power unit based on measured data and modeling results, and determine a second value range according to the actual parameters and the first value range, wherein the second value range is within the first value range;

[0051] The third determination module is configured to determine the optimized parameter value of the target parameter in the speed regulation system according to the second value range, and the optimized parameter value is used to characterize the parameter value of the speed regulation system that meets the frequency regulation performance requirements and effectively suppresses low-frequency oscillation.

[0052] In a third aspect, the present application further provides an electronic device, including:

[0053] at least one processor; and

[0054] a memory communicatively connected to the at least one processor; wherein,

[0055] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the steps of the parameter setting method of the speed control system in the grid-related thermal power unit provided in any one of the first aspects above.

[0056] In a fourth aspect, the present application further provides a computer-readable storage medium having computer program instructions stored thereon, which, when executed by a processor, implement the steps of the method for parameter setting of a speed control system in a grid-related thermal power unit as described in any one of the items provided in the first aspect above.

[0057] It can be understood that the beneficial effects of the technical solutions provided in the second, third and fourth aspects can be found in the relevant description of the first aspect, and will not be repeated here.

[0058] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0060] Figure 1 is a flow chart of a method for parameter setting of a speed control system in a grid-related thermal power unit according to an embodiment of the present application;

[0061] Figure 2 It is a control flow chart of a control system model in a grid-related thermal power unit according to an embodiment of the present application;

[0062] Figure 3 is a control flow chart of an actuator in a speed control system model according to an embodiment of the present application;

[0063] Figure 4 It is a control flow chart of a steam pipeline and a prime mover model in a grid-related thermal power unit according to an embodiment of the present application;

[0064] Figure 5 It is a comparison diagram of an actual curve and a simulation curve of a frequency modulation upper step in the method application according to an embodiment of the present application;

[0065] Figure 6 It is a comparison diagram of the actual step curve and the simulation curve under the primary frequency modulation in the method application according to the embodiment of the present application;

[0066] Figure 7 It is a block diagram of a parameter setting system of a speed control system in a grid-related thermal power unit according to an embodiment of the present application;

[0067] Figure 8 It is a structural block diagram of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0068] The embodiments of the present application are described in detail below. The embodiments described with reference to the accompanying drawings are exemplary. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0069] It should be noted that, unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein in the specification of this application are only for the purpose of describing specific implementations and are not intended to limit this application. The term "and / or" used herein includes any and all combinations of one or more of the related listed items.

[0070] See also Figures 1 to 4 This embodiment provides a method for setting parameters of a speed control system in a grid-related thermal power unit, including:

[0071] Step S100: acquiring parameter information of a thermal power unit involved in grid operation, and creating a simulation mathematical model of the speed regulation system based on the parameter information;

[0072] In this step, it should be noted that the method provided in this embodiment is mainly applied to thermal power units involved in grid operation. The parameter information of the thermal power units mainly includes the parameter information of the control system, the actuator, the steam pipeline and the prime mover, such as Figures 2 to 4 As shown, Figure 2 The control flow chart of the control system model in the grid-connected thermal power generation unit provided by this embodiment is shown. Figure 3 The control flow chart of the actuator in the speed regulation system model provided in this embodiment is shown. Figure 4 The control flow chart of the steam pipeline and prime mover model in the grid-related thermal power unit provided in this embodiment is shown. The parameter information may include information such as the size, properties, rated power, load characteristics and response time of each sub-component device. For example, the parameter information of the control system may include gain parameters (proportional gain, integral gain and differential gain), time constant, dead zone and sampling frequency, etc., which can be selectively obtained according to actual needs and are not limited here.

[0073] The creation of the simulation mathematical model of the speed control system can be based on MATLAB / Simulink, and of course it can also be built based on other simulation modeling software, without any restriction here. Figures 2 to 4 The control flow of each part is given, and the controller differential equation and corresponding transfer function, actuator electro-hydraulic servo transfer function and prime mover power model transfer function in the control part of the speed control system are established based on the parameter information of the thermal power unit.

[0074] In one example, for the controller differential equation and the corresponding transfer function, the actuator electro-hydraulic servo transfer function and the prime mover power model transfer function in the control part, the control subsystem of the speed control system specifically includes a proportional differential integral regulator (PID), and its differential equation expression is:

[0075]

[0076] In the formula, For output, For input, is the proportional gain, is the integral gain, is the differential gain, is the integration time constant, is the differential time constant.

[0077] The corresponding transfer function is:

[0078]

[0079] The transfer function of the electro-hydraulic servo actuator is:

[0080]

[0081] In the formula, is the inertia time constant of the system, The time for the oil motor stroke feedback link

[0082] The transfer function expression for the prime mover power model is:

[0083]

[0084] Where s is a complex frequency variable, is the time constant of the high pressure cylinder, is the reheater time constant, is the crossover tube time constant, is the power ratio of the high pressure cylinder, Medium pressure cylinder power ratio, Low pressure cylinder power ratio, It is the natural over-regulation coefficient of high-pressure cylinder power.

[0085] It can be understood that, in addition to the mathematical models of the various parts given above, the speed control system model includes the prime mover, speed governor, load regulation system, and related components such as the power grid. The model can model the dynamic response characteristics of the thermal power unit in detail, and specially consider the inertia, damping characteristics and load fluctuations of the system.

[0086] Step S200: determining a first value range of a target parameter in the speed regulation system based on a simulation test of the simulation mathematical model, wherein the first value range is used to indicate that the thermal power unit can meet a primary frequency regulation performance constraint and a low-frequency oscillation suppression requirement during the frequency regulation process;

[0087] In this step, the simulation mathematical model established in step S100 is simulated and tested, and the first value range of the target parameter in the preliminary speed control system is determined by taking into account the primary frequency regulation performance constraints and low-frequency oscillation suppression requirements of the unit. It can be understood that the first value range represents the value range of the thermal power unit that can meet the primary frequency regulation performance constraints and low-frequency oscillation suppression requirements during the frequency regulation process set to the target parameters. According to the main evaluation index requirements of the speed control system, the output consideration parameters of the simulation mathematical model are determined, wherein the consideration parameters include the proportional gain and integral gain of the controller. Based on the simulation test of the simulation mathematical model, the preliminary proportional gain and integral gain parameter range of the speed control system that meets the requirements is determined.

[0088] It should be noted that in the simulation test, the main evaluation indicators of the speed regulation system include frequency regulation response time, frequency regulation error and stability during the frequency regulation process. In order to meet the performance requirements of the power grid dispatching center for primary frequency regulation, the system needs to reach a steady state within a specified time and keep the steady state error within a specified range. Based on these requirements, the and to ensure that the system can respond quickly and maintain stability during the frequency modulation process.

[0089] Through comprehensive analysis of the simulation test results, the preliminary speed regulation system parameter range that meets the primary frequency regulation performance requirements and low-frequency oscillation suppression requirements is finally determined. Specifically, in this step, the proportional gain is given and integral gain This parameter range will be further verified and optimized in subsequent steps.

[0090] Step S300: determining a plurality of groups of operating condition data based on the historical operating data of the thermal power unit, each group of the operating condition data including corresponding operating conditions, load levels and frequency fluctuations;

[0091] In this step, in order to comprehensively verify the stability of the first value range of the speed control system parameters preliminarily determined, multiple typical operating conditions are set in the simulation. Multiple typical operating conditions determine multiple groups of operating condition data based on the historical operating data of the thermal power unit. Each group of the operating condition data includes corresponding operating conditions, load levels and frequency fluctuations. For example, the load level can include four different operating states of 50%, 60%, 75%, and 90%, and the frequency fluctuation range can be set to ±0.5Hz, ±1Hz.

[0092] Step S400: based on the plurality of groups of the operating condition data, verifying whether the frequency fluctuation overshoot of the speed regulation system within the first value range of the simulated target parameter output by the simulation mathematical model is less than a preset overshoot threshold;

[0093] In this step, it can be understood that the multiple groups of operating condition data obtained in step S300 are input into the simulation mathematical model to determine whether the frequency fluctuation overshoot of the speed control system within the first value range of the simulated target parameter output is less than the preset overshoot threshold. Through these settings, various load and frequency fluctuation conditions that the speed control system may encounter in actual operation can be simulated. Through verification, it can be preliminarily confirmed that the selected speed control system parameter range is reliable and stable in the actual operating environment.

[0094] Step S500: If yes, obtain actual parameters of the prime mover and the speed control system in the thermal power unit based on the measured data and the modeling results, and determine a second value range according to the actual parameters and the first value range, wherein the second value range is within the first value range;

[0095] In this step, the actual parameters of the unit prime mover and the speed control system are obtained based on the measured data and the modeling results. On this basis, the intersection operation is performed with the first value range to obtain the control parameter value range, and the model predictive control (MPC) method is applied to perform real-time dynamic adjustment of the speed control system parameters. During the real-time dynamic adjustment process, the control strategy of the model predictive control is designed to predict the future state information of the speed control system in real time, and the second value range is adjusted in real time and dynamically based on the future state information to improve the response speed and stability of the speed control system. In the simulation analysis and actual verification, the control parameters are timely corrected according to different operating conditions to ensure the optimal setting effect of the speed control system parameters.

[0096] In one example, in real-time dynamic adjustment of speed control system parameters in combination with model predictive control (MPC), for the controller, The differential phase usually defaults to 0, focusing on and The MPC control strategy is designed based on the following state space model:

[0097]

[0098]

[0099] in, is the state vector of the system, is the control input vector, is the output vector, is the system error, that is, the deviation between the set value and the output, is the state matrix, is the input matrix, is the output matrix.

[0100] Through recursive prediction, MPC is able to predict future states and outputs:

[0101]

[0102]

[0103] in, For the moment The predicted system state at time The known state at the time; For the moment The predicted system output at time To predict the status information of To predict the number of steps; for Matrix The power is the state over time The evolution of For control input The impact on the state changes gradually with the time step; is the proportional gain Impact on future errors; This is from time To the current time The cumulative error of

[0104] The optimization of the control input is achieved by minimizing the following objective function:

[0105]

[0106] in, is the reference signal, To control the increment, and is the weight matrix.

[0107] MPC optimizes control input Adjust the parameters of the PID controller and set the proportional gain of the PID controller and integral gain :

[0108]

[0109] in, is the control input of the proportional-integral controller, the error is the deviation between the set value and the output. is the cumulative sum of errors;

[0110] In this step, MPC mainly adjusts and To optimize the control effect, in each control cycle, MPC predicts the future system state through the state space model and determines the optimal control input by optimizing the objective function. The PID controller adjusts the proportional and integral quantities according to the parameters given by MPC to achieve precise control of the system.

[0111] The second value range is adjusted according to the optimized control input, wherein the adjustment process expression is:

[0112]

[0113] In the formula, is the total control input, is the control input of the model predictive controller;

[0114] It should be noted that, due to the slow response speed of the existing speed regulation system when the load changes frequently, the frequency regulation response lags, affecting the frequency regulation performance and power stability of the unit. That is, the dynamic response speed of the existing system in terms of stability optimization and parameter setting is insufficient. Under some complex working conditions, such as frequent load fluctuations or power grid failures, the system parameter setting is difficult to adapt to the changing operating conditions, resulting in decreased system stability and poor adaptability. Through the control strategy in this step, the speed regulation system can be dynamically adjusted under complex working conditions to ensure stability and response speed under a variety of operating conditions.

[0115] Step S600: determining an optimized parameter value of a target parameter in the speed regulation system according to the second value range, wherein the optimized parameter value is used to characterize a parameter value of the speed regulation system that meets frequency regulation performance requirements and effectively suppresses low-frequency oscillations.

[0116] In this step, based on the comprehensive consideration of the primary frequency modulation parameter setting requirements and the low-frequency oscillation suppression requirements, an optimized parameter value that can meet the frequency modulation performance requirements and effectively suppress low-frequency oscillations is finally determined based on the second value range, and the unit control system model is optimized and adjusted accordingly to ensure the stability and efficiency of the system in actual operation. For example, the final parameter range is applied to the control system model of the unit, and the system simulation is re-performed. The simulation results show that the system exhibits excellent dynamic response and steady-state performance under the test conditions, especially in terms of frequency modulation response and low-frequency oscillation suppression. The system has achieved the expected design goals. The optimized model further verifies the effectiveness and applicability of this method.

[0117] It should be noted that the method steps provided in the above embodiments include at least the following technical effects or advantages:

[0118] Methods According to the thermal power unit speed control system, turbine, steam pipeline and load transfer function model, the open-loop transfer function and closed-loop transfer function of the whole system are established respectively. Firstly, the thermal power unit that may be involved in the grid operation is simulated and modeled, and the mathematical simulation model of the speed control system is constructed. Based on the simulation test, combined with the unit primary frequency regulation performance constraints and low-frequency oscillation suppression requirements, the preliminary speed control system parameter range is determined. Secondly, under various operating conditions such as different load levels and frequency fluctuations, the preliminary parameter range is fully verified to ensure the reliability and stability of the system in the actual operating environment. The actual parameters of the unit prime mover and speed control system are obtained through measured modeling. Based on the intersection of the control parameter value range and combined with model predictive control, the speed control system parameters are adjusted in real time and dynamically, and applied in the simulation analysis and verification of the setting method. Considering the primary frequency regulation parameter setting domain and low-frequency oscillation suppression requirements, the parameter value range that not only meets the frequency regulation performance requirements but also can effectively suppress low-frequency oscillation is determined, and the parameters of the thermal power unit control system model are optimized and set accordingly.

[0119] By optimizing and determining the controller parameter range in the thermal power unit speed regulation system through the above method steps, the response speed is faster, the frequency regulation response lag is avoided, and the frequency regulation performance and power stability of the unit are improved. At the same time, under complex working conditions, such as frequent load fluctuations or power grid failures, the system parameter setting can adapt to the changing operating conditions and avoid the decline of system stability. It can also realize real-time dynamic adjustment and automatically adjust the control parameters according to the changes in the actual working conditions, further improving the stability of the system, thereby effectively ensuring the stability of the power grid.

[0120] Combination Figure 5 and Figure 6 In some embodiments, a practical application example of the parameter setting method of the speed control system in the grid-related thermal power unit in the above embodiment is provided. After the method of the above embodiment is engineered, it is applied to a 660MW supercritical thermal power unit. Based on the actual parameters and operating conditions of the 660MW unit, a simulation model of the speed control system is first established in MATLAB / Simulink. By comparing and verifying with the actual measured data of the unit, it is ensured that the simulation model can accurately reflect the actual dynamic behavior of the unit.

[0121] According to the method of the above embodiment, a frequency regulation performance test is first carried out in a simulation environment, and the preliminary PID parameter range of the speed regulation system is determined in combination with the actual frequency regulation requirements of the unit and the low-frequency oscillation suppression requirements of the power grid. The range of is initially determined to be [0.1,3], and the integral gain The range is [0.1,0.5].

[0122] In the simulation model, the unit was simulated and tested multiple times at load levels of 50%, 60%, 75% and 90%. At the same time, different frequency fluctuation ranges were set to simulate various operating conditions that may be encountered in actual operation. The test results show that the preliminarily determined PID parameter range can maintain the stability of the system under these operating conditions, and the system's frequency modulation response and low-frequency oscillation suppression effects have met expectations.

[0123] As shown in Table 1 and Table 2, the simulation results show that under the different load levels and frequency fluctuation conditions tested, the actual values ​​of the upper and lower step active power of the speed control system are within the allowable deviation, and the speed control system shows good stability. The overshoot is controlled within 10%, the stabilization time is within 30 seconds, and the steady-state error is close to zero. At the same time, the system shows good oscillation suppression ability under low-frequency oscillation conditions, and no instability occurs. Based on these results, it can be preliminarily confirmed that the selected speed control system parameter range is reliable and stable in the actual operating environment.

[0124] Table 1: Comparison of actual and simulated active power curves for primary frequency modulation

[0125]

[0126] Table 2: Comparison of actual and simulated step active power curves under primary frequency modulation

[0127]

[0128] Based on multiple simulation test results, the PID parameters were further fine-tuned to achieve the best performance. The final proportional gain , integral gain These optimized parameters were applied to the control system of the actual unit and then field tested. The test results are as follows: Figure 5 and Figure 6 As shown, the frequency regulation response speed and stability of the unit are significantly improved, and the low-frequency oscillation phenomenon is effectively suppressed.

[0129] See also Figure 7 , Figure 7 The block diagram of the parameter setting system 200 of the speed control system in the grid-connected thermal power generation unit provided in this embodiment is shown, wherein the parameter setting system 200 of the speed control system in the grid-connected thermal power generation unit includes:

[0130] The model creation module 210 is configured to obtain parameter information of the thermal power units involved in grid operation, and create a simulation mathematical model of the speed regulation system based on the parameter information;

[0131] The first simulation module 220 is configured to determine a first value range of the target parameter in the speed regulation system based on a simulation test of the simulation mathematical model, wherein the first value range is used to indicate that the thermal power unit can meet a primary frequency regulation performance constraint and a low-frequency oscillation suppression requirement during the frequency regulation process;

[0132] A first determination module 230 is configured to determine a plurality of groups of operating condition data based on the historical operating data of the thermal power unit, each group of the operating condition data including corresponding operating conditions, load levels and frequency fluctuations;

[0133] The parameter verification module 240 is configured to verify whether the frequency fluctuation overshoot of the speed regulation system is less than a preset overshoot threshold value within the first value range of the simulated target parameter output by the simulation mathematical model based on the multiple groups of the operating condition data;

[0134] The second determination module 250 is configured to obtain actual parameters of the prime mover and the speed control system in the thermal power unit based on the measured data and the modeling results, and determine a second value range according to the actual parameters and the first value range, wherein the second value range is within the first value range;

[0135] The third determination module 260 is configured to determine the optimized parameter value of the target parameter in the speed regulation system according to the second value range, and the optimized parameter value is used to characterize the parameter value of the speed regulation system that meets the frequency regulation performance requirements and effectively suppresses low-frequency oscillation.

[0136] It can be understood that when the parameter setting system 200 of the speed control system in the grid-connected thermal power unit in this embodiment is implemented, each module runs the above Figures 1 to 6 The steps of the parameter setting method of the speed control system in the grid-related thermal power unit in the corresponding embodiment, and the technical effects achieved can be referred to the above Figures 1 to 6 The technical effects achieved by the parameter setting method of the speed control system in the grid-related thermal power unit in the corresponding embodiment will not be elaborated here.

[0137] See also Figure 8 , Figure 8 5 is a block diagram of a structure of an electronic device provided in an embodiment of the present application. The server 500 of the electronic device includes: a processor 501, a memory 502, and a computer program 503 stored in the memory 502 and executable on the processor 501, such as a program of a parameter setting method for a speed control system in a grid-connected thermal power generation unit. When the processor 501 executes the computer program 503, the steps of the parameter setting method for a speed control system in a grid-connected thermal power generation unit in the above-mentioned embodiments are implemented, such as Figure 1 Alternatively, the processor 501 executes the computer program 503 to implement the above Figure 7The functions of each module in the corresponding embodiment are, for example, Figure 7 For details on the functions of each module (such as the model creation module 210), please refer to Figure 7 The relevant descriptions in the corresponding embodiments are not repeated here.

[0138] Exemplarily, the computer program 503 may be divided into one or more units, one or more units are stored in the memory 502, and are executed by the processor 501 to complete the technical solution provided in the above embodiment. One or more units may be a series of computer program instruction segments that can complete specific functions, and the instruction segments are used to describe the execution process of the computer program 503 in the server 500.

[0139] The electronic device may include, but is not limited to, a processor 501 and a memory 502. Those skilled in the art will appreciate that Figure 8 It is only an example of the server 500 of an electronic device and does not constitute a limitation of the server 500. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the turntable terminal device may also include an input and output terminal device, a network access terminal device, a bus, etc.

[0140] The processor 501 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0141] The memory 502 may be an internal storage unit of the server 500, such as a hard disk or memory of the server 500. The memory 502 may also be an external storage terminal device of the server 500, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the server 500. Further, the memory 502 may also include both an internal storage unit of the server 500 and an external storage terminal device. The memory 502 is used to store computer programs and other programs and data required by the turntable terminal device. The memory 502 may also be used to temporarily store data that has been output or is to be output.

[0142] In some embodiments, a computer-readable storage medium is also provided, which stores a computer program. When the computer program is executed by a processor, it implements the steps of the parameter setting method of the speed control system in the grid-related thermal power unit as described in any of the above embodiments.

[0143] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0144] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Among them, the computer-readable storage medium can be non-volatile or volatile. Based on this understanding, the present application implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable storage medium may include: any entity or device capable of carrying computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electrical carrier signal, telecommunication signal and software distribution medium, etc.

[0145] The terms "first", "second", "third", etc. in the specification and claims of the present application and the drawings are used to distinguish different objects rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a series of steps or units are included, or optionally, steps or units not listed are included, or optionally, other steps or units inherent to these processes, methods, products or devices are included.

[0146] Only the part relevant to the present application is shown in the accompanying drawings, but not all of the content. Before discussing the exemplary embodiments in more detail, it should be mentioned that some exemplary embodiments are described as processing or methods depicted as flow charts. Although the flow chart describes each operation (or step) as a sequential process, many of the operations therein can be implemented in parallel, concurrently or simultaneously. In addition, the order of each operation can be rearranged. When its operation is completed, the process can be terminated, but it can also have additional steps not included in the accompanying drawings. The process can correspond to a method, function, procedure, subroutine, subprogram, etc.

[0147] The terms "component", "module", "system", "unit", etc. used in this specification are used to represent computer-related entities, hardware, firmware, a combination of hardware and software, software, or software in execution. For example, a unit can be, but is not limited to, a process running on a processor, a processor, an object, an executable file, an execution thread, a program, and / or distributed between two or more computers. In addition, these units can be executed from various computer-readable media having various data structures stored thereon. Units can communicate through local and / or remote processes, for example, based on signals having one or more data packets (e.g., data from a second unit interacting with another unit in a local system, a distributed system, and / or a network. For example, the Internet interacts with other systems via signals).

[0148] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "illustrative embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials, or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example.

[0149] Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Mentioning "embodiment" in this article means that the specific features, structures or characteristics described in conjunction with the embodiment may be included in at least one embodiment of the present embodiment application. The appearance of this phrase in various positions in the specification is not necessarily the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It can be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0150] Although the embodiments of the present application have been shown and described, those skilled in the art will appreciate that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present application, and that the scope of the present application is defined by the claims and their equivalents.

[0151] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the disclosure disclosed herein. The present application is intended to cover any modification, use or adaptation of the present application, which follows the general principles of the present application and includes common knowledge or customary techniques in the art that are not disclosed in the present application. The specification and examples are intended to be exemplary only, and the true scope and spirit of the present application are indicated by the following claims.

Claims

1. A method for setting parameters of a speed control system in a grid-connected thermal power unit, characterized in that: include: Acquiring parameter information of thermal power units involved in grid operation, and creating a simulation mathematical model of the speed regulation system based on the parameter information; Based on the simulation test of the simulation mathematical model, determining a first value range of the target parameter in the speed regulation system, wherein the first value range is used to indicate that the thermal power unit can meet the primary frequency regulation performance constraint and low-frequency oscillation suppression requirement during the frequency regulation process; Based on the historical operating data of the thermal power unit, a plurality of groups of operating condition data are determined, each group of the operating condition data includes corresponding operating conditions, load levels and frequency fluctuations; Based on the plurality of groups of the operating condition data, verify whether the frequency fluctuation overshoot of the speed regulation system within the first value range of the simulated target parameter output by the simulation mathematical model is less than a preset overshoot threshold; If so, actual parameters of the prime mover and the speed control system in the thermal power unit are obtained based on the measured data and the modeling results, and a second value range is determined according to the actual parameters and the first value range, and the second value range is within the first value range, including: Design a control strategy of model predictive control, based on which the future state information of the speed regulation system is predicted in real time. The control strategy of model predictive control is designed based on the following expression: In the formula, is the state vector of the system, is the control input vector, is the output vector, is the system error, is the state matrix, is the input matrix, is the output matrix, is the proportional gain, is the integral gain, From time To the current time The cumulative error of The real-time prediction of the future state and output expression of the unit system is: In the formula, For the moment The predicted system state at time The known state at the time; For the moment The predicted system output at time To predict the status information of To predict the number of steps, for Matrix The power indicates that the state changes over time. The evolution of For control input The impact on the state gradually changes with the time step. is the proportional gain The impact on future errors, The second value range is dynamically adjusted in real time based on the future state information to improve the response speed and stability of the speed regulation system, including creating an optimization objective function of the control input: In the formula, is the reference signal, To control the increment, and is the weight matrix, For the moment The predicted system output at time To predict the status information of The second value range is adjusted according to the optimized control input, wherein the adjustment process expression is: In the formula, is the control input of the proportional-integral controller, is the deviation between the set value and the output, is the cumulative sum of errors; According to the second value range, an optimized parameter value of the target parameter in the speed regulation system is determined, and the optimized parameter value is used to characterize the parameter value of the speed regulation system that meets the frequency regulation performance requirements and effectively suppresses low-frequency oscillations.

2. The method for parameter setting of the speed control system in a grid-connected thermal power unit according to claim 1 is characterized in that: The step of obtaining parameter information of the thermal power generating units involved in grid operation and creating a simulation mathematical model of the speed regulation system based on the parameter information includes: Obtain parameter information of thermal power units including control systems, actuators, steam pipelines and prime movers. Based on the parameter information, a controller differential equation and a corresponding transfer function, an actuator electro-hydraulic servo transfer function and a prime mover power model transfer function in the control system are created.

3. The method for parameter setting of the speed control system in a grid-connected thermal power unit according to claim 2 is characterized in that: The step of creating a controller differential equation and a corresponding transfer function, an actuator electro-hydraulic servo transfer function, and a prime mover power model transfer function in a control system based on the parameter information includes: The transfer function expression of the actuator electro-hydraulic servo is: Where s is a complex frequency variable, is the proportional gain, is the integral gain, is the differential gain, is the inertia time constant of the system, It is the time of the oil motor stroke feedback link; The transfer function of the prime mover power model is: Where s is a complex frequency variable, is the time constant of the high pressure cylinder, is the reheater time constant, is the crossover tube time constant, is the power ratio of the high pressure cylinder, Medium pressure cylinder power ratio, Low pressure cylinder power ratio, It is the natural over-regulation coefficient of high-pressure cylinder power.

4. The method for parameter setting of the speed control system in a grid-connected thermal power unit according to claim 1 is characterized in that: The simulation test based on the simulation mathematical model determines a first value range of the target parameter in the speed regulation system, including: According to the evaluation index requirements of the speed control system, the output consideration parameters of the simulation mathematical model are determined, wherein the output consideration parameters include the proportional gain and the integral gain of the controller; Based on the simulation test of the simulation mathematical model, the preliminary proportional gain and integral gain parameter range of the speed control system that meets the requirements is determined.

5. A parameter setting system for a speed control system in a grid-connected thermal power unit, characterized in that: include: A model creation module is configured to obtain parameter information of a thermal power unit involved in grid operation, and create a simulation mathematical model of the speed regulation system based on the parameter information; A first simulation module is configured to determine a first value range of a target parameter in the speed regulation system based on a simulation test of the simulation mathematical model, wherein the first value range is used to indicate that the thermal power unit can meet a primary frequency regulation performance constraint and a low-frequency oscillation suppression requirement during a frequency regulation process; A first determination module is configured to determine a plurality of groups of operating condition data based on the historical operating data of the thermal power unit, each group of the operating condition data including corresponding operating conditions, load levels and frequency fluctuations; A parameter verification module is configured to verify, based on the plurality of groups of operating condition data, whether the simulated target parameter output by the simulation mathematical model has an overshoot of the frequency fluctuation of the speed regulation system within the first value range and is less than a preset overshoot threshold; The second determination module is configured to obtain actual parameters of the prime mover and the speed control system in the thermal power unit based on the measured data and the modeling results, and determine a second value range according to the actual parameters and the first value range, wherein the second value range is within the first value range, including: Design a control strategy of model predictive control, based on which the future state information of the speed regulation system is predicted in real time. The control strategy of model predictive control is designed based on the following expression: In the formula, is the state vector of the system, is the control input vector, is the output vector, is the system error, is the state matrix, is the input matrix, is the output matrix, is the proportional gain, is the integral gain, From time To the current time The cumulative error of The real-time prediction of the future state and output expression of the unit system is: In the formula, For the moment The predicted system state at time The known state at the time; For the moment The predicted system output at time To predict the status information of To predict the number of steps, for Matrix The power indicates that the state changes over time. The evolution of For control input The impact on the state gradually changes with the time step. is the proportional gain The impact on future errors, The second value range is dynamically adjusted in real time based on the future state information to improve the response speed and stability of the speed regulation system, including creating an optimization objective function of the control input: In the formula, is the reference signal, To control the increment, and is the weight matrix, For the moment The predicted system output at time To predict the status information of The second value range is adjusted according to the optimized control input, wherein the adjustment process expression is: In the formula, is the control input of the proportional-integral controller, is the deviation between the set value and the output, is the cumulative sum of errors; The third determination module is configured to determine the optimized parameter value of the target parameter in the speed regulation system according to the second value range, and the optimized parameter value is used to characterize the parameter value of the speed regulation system that meets the frequency regulation performance requirements and effectively suppresses low-frequency oscillation.

6. An electronic device, characterized in that: include: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the steps of a parameter setting method for a speed control system in a grid-related thermal power unit as described in any one of claims 1-5.

7. A computer-readable storage medium having computer program instructions stored thereon, characterized in that: When the computer program instructions are executed by the processor, the steps of a method for parameter setting of a speed control system in a grid-related thermal power unit described in any one of claims 1-5 are implemented.

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