An Identification Method for Parameters of Integral Time-delay Zero-point Model and a Water Level Rolling Simulation Method

Abstract

The present invention discloses a method for identifying the parameters of an integral time-delay zero-point model and rolling simulation of water levels, which relates to the technical field of power station optimal dispatching. The method includes: constructing a one-dimensional river hydrodynamic model based on the Saint-Venant equations; wherein, the one-dimensional river hydrodynamic model is used for calibrating the Manning coefficient of the model, designing working conditions, and obtaining the stable operation state of the working conditions; when the one-dimensional river hydrodynamic model is in a stable operation state, a flow step is applied to the stable operation hydrodynamic model for parameter identification to obtain the key parameters under different working conditions; using a multivariable fitting method to fit each key parameter to determine the parameter function relationship; based on the parameter function relationship, introducing the time-domain expression of the integral time-delay zero-point model to calculate the water level difference between adjacent moments; and performing rolling simulation of the river water level according to the set upstream and downstream flows, the initial river water level, and the water level difference between adjacent moments. The present invention can improve the efficiency and accuracy of real-time dispatching of power stations.

Description

Technical Field

[0001] The present invention relates to the technical field of power station optimal scheduling, and particularly to a method for identifying parameters of an integral time-delay zero model and rolling simulation of water level. Background Art

[0002] In the water resource scheduling of power stations, accurate prediction of water level is a key link to ensure the safe operation of water conservancy projects and improve the utilization efficiency of water resources. With the frequent occurrence of climate change and extreme hydrological events, the water level changes of power stations have become more complex and difficult to predict, posing a huge challenge to real-time scheduling. To address these issues, various water level prediction methods have been proposed, such as hydrodynamic models based on numerical simulation, machine learning models driven by data, etc.

[0003] However, these methods still have certain limitations in practical applications. Although the hydrodynamic model can more accurately reflect the water level changes in the river channel, its high computational complexity and cumbersome parameter debugging process make it difficult to meet the rapid response needs of front-line schedulers. On the other hand, although the machine learning model has good prediction ability under certain conditions, it depends on a large amount of historical data, and the black-box characteristics of the model are difficult to explain, which also limits its wide application in actual water level scheduling. Summary of the Invention

[0004] The purpose of the present invention is to provide a method for identifying parameters of an integral time-delay zero model and rolling simulation of water level, which can improve the efficiency and accuracy of real-time scheduling of power stations.

[0005] To achieve the above object, the present invention provides the following solution:

[0006] A method for identifying parameters of an integral time-delay zero model and rolling simulation of water level, comprising:

[0007] Constructing a one-dimensional hydrodynamic model of the river channel based on the Saint-Venant equations; the one-dimensional hydrodynamic model of the river channel is used for Manning coefficient calibration, working condition design, and obtaining the stable operation state of the working condition;

[0008] When the one-dimensional hydrodynamic model of the river channel is in a stable operation state, applying a flow step to the stable hydrodynamic model for parameter identification to obtain key parameters under different working conditions;

[0009] Using a multivariable fitting method to fit each of the key parameters to determine the parameter function relationship;

[0010] Based on the parameter function relationship, introducing the time-domain expression of the integral time-delay zero model to calculate the water level difference between adjacent moments;

[0011] Perform a rolling simulation of the river water level based on the set upstream and downstream flows, the initial water level of the river channel, and the water level difference at adjacent times.

[0012] Optionally, the expression of the one-dimensional hydrodynamic model of the river channel is:

[0013] ,

[0014] where, B is the surface width of the cross-section, in m; Z is the water level, in m; t is the time, in s; Q is the flow rate, in m³ / s; x is the longitudinal distance of the channel along the main flow direction, in m; α is the momentum correction coefficient; A is the cross-sectional area, in m²; g is the acceleration due to gravity, in m / s²; S f is the friction slope; q is the lateral water volume per unit length of the river channel, with a positive value indicating inflow, a negative value indicating outflow, and a zero value indicating no lateral exchange, in m 2 / s.

[0015] Optionally, the process of calibrating the Manning coefficient of the model includes: automatically calibrating the Manning coefficient of the model using the particle swarm optimization algorithm and performing iteration with the minimum error between the model simulation results and the observed data as the objective function; the specific objective function is:

[0016] ,

[0017] where: is the objective function with the minimum error as the goal; N represents the number of observed data; is the model simulation result; is the observed data; i represents the i th data.

[0018] Optionally, the process of designing the working conditions includes: performing parameter analysis based on historical flow and water level data, determining the range of historical operation intervals, and sequentially setting different working conditions from low to high according to the range of historical operation intervals.

[0019] Optionally, the process of obtaining the stable operation state of the working conditions includes: based on the model after calibrating the Manning coefficient, setting a fixed upstream flow rate for different working conditions, and adjusting the output to maintain the stable state of the downstream water level to obtain the stable operation state under different working conditions.

[0020] Optionally, when the one-dimensional hydrodynamic model of the river channel is in a stable operation state, a flow step is applied to the stable hydrodynamic model for parameter identification to obtain key parameters under different working conditions, specifically including:

[0021] Under the stable operation state, a flow step is applied to the stable hydrodynamic model, the water level change downstream is calculated by using the one-dimensional hydrodynamic model of the river channel, and characteristic parameter identification is carried out according to the simulation result of the water level change to obtain key parameters under different working conditions;

[0022] Among them, the simulation result of the water level change includes the backwater area; the calculation of the backwater area is: setting the lag time high-frequency response and , and calculating the backwater area according to the formula ; the lag time is the time interval between the moment of the downstream water level change and the moment of the upstream flow pulse disturbance, and the high-frequency response and are the high-frequency responses brought by dealing with instantaneous mutations, which are constants under different working conditions given by the stable hydrodynamic model;

[0023] The calculation formula of the backwater area is:

[0024] ,

[0025] where is the water level change amount after applying the upstream flow step, m³ / s; is the change duration, s; is the water level change slope, m / s; is the flow step amount, m 3 / s.

[0026] Optionally, the parameter setting in the stable operation state includes: giving a 5% step to the upstream fixedly, keeping the downstream output unchanged, and setting the output result step size to 1 min.

[0027] Optionally, the time-domain expression of the introduced integral time-delay zero-point model is specifically:

[0028] ,

[0029] where: is the model output quantity, which is the deviation of the downstream water depth value relative to the steady-state value, m; is the change amount of the upstream inflow discharge of the river channel relative to the steady-state value, m³ / s; is the change in the downstream discharge of the river channel relative to the steady-state value, m³ / s; is the backwater area, m 2 ; is the time delay, s; and constant coefficients.

[0030] According to the specific embodiments provided by the present invention, the following technical effects are disclosed:

[0031] The present invention discloses a method for identifying the parameters of an integral time-delay zero-point model and rolling simulation of water levels. The method includes constructing a one-dimensional hydrodynamic model of the river channel based on the Saint-Venant equations; wherein, the one-dimensional hydrodynamic model of the river channel is used for calibrating the Manning coefficient, designing working conditions, and obtaining the stable operating state of the working conditions; when the one-dimensional hydrodynamic model of the river channel is in a stable operating state, a flow step is applied to the stable hydrodynamic model for parameter identification to obtain the key parameters under different working conditions; the multivariate fitting method is used to fit each key parameter to determine the parameter functional relationship; based on the parameter functional relationship, the time-domain expression of the integral time-delay zero-point model is introduced to calculate the water level difference between adjacent moments; the rolling simulation of the river channel water level is carried out according to the set upstream and downstream discharges, the initial water level of the river channel, and the water level difference between adjacent moments. The present invention can improve the efficiency and accuracy of real-time dispatching of power stations. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0033] Figure 1 is the flowchart of the method for identifying the parameters of the integral time-delay zero-point model and rolling simulation of water levels of the present invention;

[0034] Figure 2 is the water level rolling prediction diagram of the integral time-delay zero-point model parameters considering adaptability in this embodiment;

[0035] Figure 3 is the module schematic diagram of applying the method in this embodiment. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0036] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0037] The object of the present invention is to provide a method for identifying the parameters of an integral time-delay zero model and rolling simulation of water level, which can improve the efficiency and accuracy of real-time scheduling of power stations.

[0038] In order to make the above objects, features, and advantages of the present invention more obvious and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0039] As Figure 1 shown, the present invention provides a method for identifying the parameters of an integral time-delay zero model and rolling simulation of water level, including:

[0040] Step 100: Construct a one-dimensional hydrodynamic model of the river based on the Saint-Venant equations; the one-dimensional hydrodynamic model of the river is used for Manning coefficient calibration, working condition design, and obtaining the stable operation state of the working condition. Among them, the designed working conditions should be based on a comprehensive analysis of historical flow and water level data, and the interval range of historical operation should be extracted. On this basis, the designed working conditions should cover the flow and water level changes from the lowest to the highest to ensure the safety and reliability of the project operation under various possible conditions. And, under the model after automatic calibration of the Manning coefficient, set a fixed upstream flow for different designed working conditions, and ensure the stability of the downstream water level by adjusting the output, so as to achieve the steady operation of the project.

[0041] Step 200: When the one-dimensional hydrodynamic model of the river is in a stable operation state, apply a flow step to the stable hydrodynamic model for parameter identification to obtain the key parameters under different working conditions.

[0042] Step 300: Use the multivariable fitting method to fit each of the key parameters to determine the parameter function relationship, which is convenient for quickly calling the parameters under different working conditions.

[0043] Step 400: Based on the parameter function relationship, introduce the time-domain expression of the integral time-delay zero model and calculate the water level difference between adjacent moments.

[0044] Step 500: Perform rolling simulation of the river channel water level based on the set upstream and downstream flows, the initial water level of the river channel, and the water level difference at adjacent moments. By using the measured flow and initial water level values to perform time series simulation of the water level, the model can gradually achieve dynamic update. Specifically, after each step, the model updates relevant parameters according to the operation results to ensure that the new input can better reflect the current water level state. Subsequently, the updated parameters are used to continue the water level simulation for the next step and gradually advance. The whole process loops continuously until the entire simulation is completed.

[0045] Based on the above technical solution, the following specific implementation manners are provided for each step.

[0046] Step 110, construct a one-dimensional hydrodynamic model of the river channel.

[0047] Among them, the construction of the one-dimensional hydrodynamic model of the river channel includes the calibration of the Manning coefficient of the model, the design of working conditions, and obtaining the stable operation state of the working conditions. Specifically, the construction of the one-dimensional hydrodynamic model of the river channel is based on the Saint-Venant equations and solved by the method of chasing.

[0048] In terms of water level simulation, since the one-dimensional hydrodynamic model needs to adjust relevant parameters to minimize the deviation between the simulated water level and flow and the actual values. For the one-dimensional hydrodynamic model of the river channel, only the Manning coefficient can be adjusted. When the Manning coefficient increases, the simulated water level rises; when the Manning coefficient decreases, the simulated water level drops. Within the range of the Manning coefficient of the river channel, the particle swarm algorithm is used for automatic calibration of the Manning coefficient of the river channel.

[0049] During the process of designing working conditions, since parameter identification needs to be carried out with the help of the hydrodynamic model, the wider the coverage of the working conditions, the more comprehensive the obtained parameter distribution; the finer the setting of the working conditions, the richer the collected parameter data. This has a decisive impact on the subsequent parameter fitting accuracy.

[0050] In terms of stable working conditions, it is necessary to set a fixed upstream flow under the given working conditions and ensure the stability of the downstream water level by adjusting the output to avoid the influence of the downstream water level on parameter identification.

[0051] Preferably, the equations of the one-dimensional hydrodynamic model of the river channel are:

[0052] ,

[0053] Among them, B is the surface width of the cross-section of the water flow, with the unit of m; Z is the water level, with the unit of m; t is the time, with the unit of s; Q is the flow rate, with the unit of m³ / s; x is the longitudinal distance of the channel along the main flow direction, with the unit of m; α is the momentum correction coefficient; Ais the cross-sectional area of flow, with the unit of m²; g is the acceleration due to gravity, with the unit of m / s²; S f is the friction slope.

[0054] The basic idea of the chase method is to gradually solve for the unknown water levels and discharges starting from the known initial conditions through a step-by-step advancing formula. First, convert the matrix A into an upper triangular matrix U while updating the vector Y to maintain the equivalence of the equations. The formulas are as follows:

[0055] ,

[0056] where: i = 2, 3, ……, n. The elements in A and Y are all known values.

[0057] Next, solve for X by back substitution. The formulas are as follows:

[0058] ,

[0059] where: i = n - 1, n - 2, ……, 0. The elements in X are the quantities to be solved, namely the water levels and discharges at each control section.

[0060] Preferably, the one-dimensional hydrodynamic model of the river channel needs to be calibrated. Since the Manning coefficient is the only controllable parameter, the particle swarm optimization algorithm is used to automatically calibrate the Manning coefficient. The objective function is set to minimize the error between the model simulation results and the observed data, and the error is expressed as the squared error. The specific objective function is:

[0061] ,

[0062] where, the error is minimized; N represents the number of observed data; is the model simulation result; is the observed data.

[0063] Preferably, the design conditions should be based on a comprehensive analysis of historical flow and water level data to extract the range of historical operation. On this basis, the designed conditions should cover the flow and water level changes from the lowest to the highest to ensure the safety and reliability of the project operation under various possible conditions.

[0064] Preferably, under the model after automatic calibration of the Manning coefficient, set a fixed upstream flow for different design conditions, and ensure the stability of the downstream water level by adjusting the output, so as to achieve the steady operation of the project and avoid the influence of the downstream water level on parameter identification.

[0065] The following takes the Shenxigou Hydropower Station as an example. First, a one-dimensional hydrodynamic model of the Shenxigou River channel is constructed based on the Saint-Venant equations, and the Manning coefficient n of the river channel is calibrated, with the Manning coefficient being 0.065. For the design conditions of the water level and flow rate that occurred in 23 years, the flow rate is 550 - 3550 m³ / s, with an interval of 1000 m³ / s; the water level is 655 - 660 m, with an interval of 1 - 2 m. The upstream flow rates are given as 550 m³ / s, 1550 m³ / s, 2550 m³ / s, and 3550 m³ / s, and the outflow is controlled so that the downstream water level is stabilized at 655 m, 657 m, 659 m, and 660 m.

[0066] Step 120, identification of the characteristic parameters of the integrator time-delay zero model.

[0067] Among them, the identification of the characteristic parameters of the integrator time-delay zero model is to perform identification based on a step given by a steady-state hydrodynamic model.

[0068] Specifically, considering the order of magnitude of the flow rate, the step percentage is considered. For example, a large order of magnitude and a large step will cause the hydrodynamic simulation to diverge and have no results. For a large flow rate and a small step, for a project with a large storage capacity, the water level rises slowly, and the simulation duration needs to be increased; for the output step size, it cannot be too large to avoid covering the time-delay duration.

[0069] Preferably, a step of 5% of the fixed upstream flow rate is given under the condition of stable operation, and the downstream output remains unchanged. The change in the downstream water level is calculated through the river channel hydraulics model.

[0070] Preferably, according to the simulation results of the downstream water level, the characteristic parameters are identified. In the simulation water level results, the time interval between the moment of the change in the downstream water level and the moment of the upstream flow rate pulse disturbance is the lag time ; 、 To handle the high-frequency response brought about by instantaneous mutations, constants under different working conditions are given by the hydrodynamic model; the backwater area can be calculated through the following formula:

[0071] ,

[0072] Among them, the change in water level after applying the upstream flow rate step, m³ / s; is the duration of the change, s; is the slope of the water level change, m / s.

[0073] Preferably, the output step size of the model is set to 1 min to avoid the time-delay time being less than the output step size, resulting in time-delay time errors and affecting the parameter accuracy.

[0074] The following takes the Shenxigou Power Station as an example. Under the stable condition of S110, a 5% flow step is given to the upstream initial flow rates, namely 577.5 m³ / s, 1627.5 m³ / s, 2782.5 m³ / s, and 3832.5 m³ / s. The detailed parameter identification is shown in Tables 1 to 4 as follows:

[0075] Table 1 Parameter results (㎡)

[0076] ,

[0077] Table 2 τ Parameter results (min)

[0078] ,

[0079] Table 3 Parameter results

[0080] ,

[0081] Table 4 Parameter results

[0082] ,

[0083] Step 130, fitting the integral time-delay model parameter adaptive function relationship.

[0084] Among them, fitting the integral time-delay model parameter adaptive function relationship means fitting the detailed parameter identification results.

[0085] Specifically, multivariate fitting is performed on the detailed parameter identification results.

[0086] Preferably, the relationship between the parameters of the integral time-delay zero-point model under different working conditions is fitted with two variables (stable water level, initial flow rate).

[0087] The following takes the Shenxigou Power Station as an example to perform bivariate fitting on Tables 1 to 4 in S120. The fitting function relationships are as follows:

[0088] Relationship 1: ,

[0089] Relationship 2: ,

[0090] Relationship 3: ,

[0091] Relationship 4: ,

[0092] Where: x is the downstream stable water level, m; y is the initial flow rate, m³ / s.

[0093] Step 140, introducing the time-domain function of the integral time-delay zero-point model.

[0094] Among them, introducing the time-domain function of the integral time-delay zero-point model means introducing a formula to calculate the water level.

[0095] Specifically, the time-domain expression of the integral time-delay zero-point model can calculate the water level difference and can perform iterative calculations of the water level.

[0096] Preferably, introduce the time-domain expression of the integral time-delay zero-point model:

[0097] ,

[0098] Where: is the model output, which is the deviation of the downstream water depth value from the steady-state value, m; is the change in the upstream inflow discharge of the river channel relative to the steady-state value, m³ / s; is the change in the downstream outflow discharge of the river channel relative to the steady-state value, m³ / s; is the backwater area, m 2 ; is the time delay, s; and are constant coefficients.

[0099] Through the four characteristic parameters, the water level difference between adjacent moments can be calculated, but the characteristic parameters at the next moment will change, and the initial characteristic parameters have a narrow applicability to the working conditions.

[0100] The following takes the Shenxigou Power Station as an example. Subtract the outflow discharge from the upstream time-delay discharge at a certain moment, perform interpolation calculations on the current upstream discharge and the water level at the initial moment for the four characteristic parameters, substitute the characteristic parameters into the time-domain expression to calculate the water level difference, and add the water level difference to the water level at the previous moment, which is the water level at the current moment.

[0101] Step 150, adaptive rolling prediction of the river channel water level

[0102] Preferably, use the measured discharge and the initial water level value to perform time series simulation on the water level and gradually achieve dynamic update. Specifically, after each step ends, the model will update the relevant parameters according to the operation results to ensure that the new input can better reflect the current water level state. Subsequently, use the updated parameters to continue the water level simulation for the next step and gradually advance. The whole process loops continuously until the entire simulation is completed.

[0103] The following takes the Shenxigou Power Station as an example. Use the upstream outflow, the outflow discharge of this power station, and the initial water level of this power station for a certain ten days (14,400 minutes) in February 2023 of the Shenxigou Power Station, gradually advance, and dynamically loop until the simulation ends. The results are as followsFigure 2 As shown, taking the Nash-Sutcliffe Efficiency (NSE), Root Mean Square Error (RMSE), and Mean Absolute Error (MAE) as evaluation indicators, the simulation accuracy is relatively high, and the specific results are shown in Table 5 as follows:

[0104] Table 5 Results of Evaluation Indicators

[0105] ,

[0106] Figure 3 is a schematic diagram of a module of an adaptive integral time-delay zero-point model parameter identification and water level rolling simulation method shown according to some embodiments of this specification. The adaptive integral time-delay zero-point model parameter identification and water level rolling simulation may include a model establishment module, a parameter identification module, a function fitting module, a time domain introduction module, and a dynamic simulation module.

[0107] The model establishment module is used to construct a one-dimensional river hydrodynamic model based on the Saint-Venant equations. Among them, the one-dimensional river hydrodynamic model includes the calibration of the Manning coefficient of the model, the design of working conditions, and the stable operation state of working conditions;

[0108] The parameter identification module is used to apply a flow step in the stable hydrodynamic model and perform parameter identification through this step change to obtain key parameters with high precision;

[0109] The function fitting module is used to perform multivariable fitting on parameters under different working conditions to generate a functional relationship between parameters;

[0110] The time domain introduction module is used to introduce the time domain expression of the integral time-delay zero-point model and calculate the water level difference between adjacent moments;

[0111] The dynamic simulation module is used to perform rolling simulation of the river water level by using the upstream and downstream flows and the initial water level of the river.

[0112] The river and river-type reservoirs can be used to execute an adaptive integral time-delay zero-point model parameter identification and water level rolling simulation method. For more descriptions of the rolling update simulation of the water level, reference can be made to the relevant descriptions of an adaptive integral time-delay zero-point model parameter identification and water level rolling simulation method, which will not be elaborated here.

[0113] Compared with the prior art, this embodiment has at least the following beneficial effects:

[0114] 1. This method conducts parameter identification through a hydrodynamic model, ensuring high parameter accuracy and being able to accurately reflect the hydraulic characteristics of the river channel. 2. This method introduces an integral time-delay zero-point model, overcoming the limitation that the integral time-delay model can only handle the low-frequency response of the river channel, possessing the ability to handle high-frequency responses caused by instantaneous mutations, significantly improving the simulation accuracy, and being closer to the actual engineering requirements. 3. This method realizes the rapid generation of parameters under different working conditions through the fitting of multivariable functional relationships, greatly facilitating the real-time invocation and application by front-line dispatchers, and improving the dispatching efficiency and operation convenience.

[0115] The various embodiments in this specification are described in a progressive manner. Each embodiment focuses on the differences from other embodiments. For the same and similar parts among the various embodiments, reference can be made to each other.

[0116] Specific examples are used in this article to elaborate on the principles and implementation methods of the present invention. The descriptions of the above embodiments are only used to help understand the core idea of the present invention; at the same time, for those of ordinary skill in the art, based on the idea of the present invention, there will be changes in the specific implementation methods and application scopes. In summary, the content of this specification should not be construed as a limitation to the present invention.

Claims

1. A method for parameter identification of integral time-delay zero-point model and water level rolling simulation, characterized in that: include: Construct a one-dimensional hydrodynamic model of the river channel based on Saint-Venant equations; The one-dimensional hydrodynamic model of the river channel is used for calibration of the Manning coefficient of the model, design of working conditions and acquisition of stable operating state of working conditions; When the one-dimensional hydrodynamic model of the river channel is in a stable operating state, a flow step is applied to the stable operating hydrodynamic model to perform parameter identification, and key parameters under different working conditions are obtained; Using a multivariate fitting method to fit each of the key parameters to determine the parameter function relationship; Based on the parameter function relationship, the time domain expression of the integral time-delay zero point model is introduced to calculate the water level difference at adjacent moments; Perform rolling simulation of the river water level according to the set upstream and downstream flow, the initial water level of the river and the water level difference at adjacent moments; For multivariable fitting methods, it includes: adaptive functional relationship fitting of integral time-lag model parameters; The adaptive function relationship fitting of the integral time-delay model parameters is to fit the detailed parameter identification results, specifically: to fit the detailed parameter identification results to perform multivariate fitting; The parameters of the integral time-lag zero-point model under different working conditions are fitted with a dual variable relationship; the dual variables include the stable water level and the initial flow; the fitting function relationship is as follows: Relation 1: ; Relation 2: ; Relation 3: ; Relation 4: ; Where: x is the downstream stable water level, m; y is the initial flow, m³ / s; The time domain functions for the integral delay zero point model are introduced, including: The water level difference is calculated using the time domain expression of the integral time-delay zero-point model, and the water level is calculated iteratively; The time domain expression of the integrated time-delay zero point model is introduced: ， in, is the model output, which is the deviation of the downstream water depth value relative to the steady-state value, m; is the change in the upstream inflow flow relative to the steady-state value, m³ / s; is the change in the downstream outflow flow of the river relative to the steady-state value, m³ / s; is the area of ​​the backwater zone, m2; is the lag time, s; and constant coefficient; Through the four characteristic parameters, the water level difference at adjacent moments is calculated. The upstream time-delay flow at a certain moment is subtracted from the outflow flow. The current upstream flow and the water level at the initial moment are interpolated to calculate the four characteristic parameters. The characteristic parameters are brought into the time domain expression, the water level difference is calculated, and the water level at the previous moment is added to the water level difference to obtain the water level at the current moment.

2. The integral time-delay zero point model parameter identification and water level rolling simulation method according to claim 1 is characterized in that: The expression of the one-dimensional hydrodynamic model of the river channel is: ， in, B is the surface width of the water-passing section, in m; Z is the water level, in m; t is time, unit is s; Q is the flow rate, in m³ / s; x is the longitudinal distance of the channel along the main flow direction, in meters; α is the momentum correction factor; A is the water flow area, in m²; g is the acceleration due to gravity, in m / s²; S f is the friction ratio; q is the lateral water volume per unit length of the river channel. Positive values ​​indicate inflow, negative values ​​indicate outflow, and zero indicates no lateral exchange. The unit is m 2 / s.

3. The integral time-delay zero point model parameter identification and water level rolling simulation method according to claim 1 is characterized in that: The process of calibrating the model Manning coefficient includes: automatically calibrating the model Manning coefficient using a particle swarm optimization algorithm, and iterating with the minimum error between the model simulation result and the observed data as the objective function; the objective function is specifically: ， in: is the objective function with the goal of minimizing the error; N represents the number of observations; is the model simulation result; is the observation data; i Indicates i data.

4. The integral time-delay zero point model parameter identification and water level rolling simulation method according to claim 1 is characterized in that: The process of the operating condition design includes: performing parameter analysis based on historical flow and water level data, determining the range of historical operation, and setting different operating conditions in sequence from low to high according to the range of historical operation.

5. The integral time-delay zero point model parameter identification and water level rolling simulation method according to claim 1 is characterized in that: The process of obtaining the stable operating state of the working condition includes: setting a fixed upstream flow for different working conditions based on the model calibrated by the Manning coefficient, maintaining the stable state of the downstream water level by adjusting the output, and obtaining the stable operating state under different working conditions.

6. The integral time-delay zero point model parameter identification and water level rolling simulation method according to claim 1 is characterized in that: When the one-dimensional hydrodynamic model of the river channel is in a stable operating state, a flow step is applied to the stable operating hydrodynamic model for parameter identification to obtain key parameters under different working conditions, including: Under a stable operation state, a flow step is applied to the stable operation hydrodynamic model, the water level change in the downstream is calculated using the one-dimensional hydrodynamic model of the river channel, and characteristic parameters are identified based on the simulation results of the water level change to obtain key parameters under different working conditions; The simulation result of the water level change includes the backwater area; the backwater area is calculated as follows: , high frequency response and , and according to the formula Calculate the backwater area; the lag time is the time interval between the moment when the downstream water level changes and the moment when the upstream flow pulse disturbance occurs. and In order to deal with the high-frequency response caused by transient mutations, the constants under different working conditions are given by the stable hydrodynamic model; The calculation formula of the backwater area is: ， in, is the water level change after applying the upstream flow step, m³ / s; is the duration of change, s; is the slope of water level change, m / s; is the flow step amount, m 3 / s.

7. The integral time-delay zero point model parameter identification and water level rolling simulation method according to claim 6 is characterized in that: The parameter setting under the stable operation state includes: giving a fixed 5% step to the upstream, keeping the downstream output unchanged, and setting the output result step size to 1 minute.

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