Turbine equipment simulation model calibration method based on mechanism model

Abstract

The invention belongs to the technical field of digital twin simulation, and particularly relates to a turbine equipment simulation model calibration method based on a mechanism model. Comprising the following steps: selecting calibration parameters and target parameters of a gas compressor or a turbine; reading unit operation data, and preprocessing the operation data to obtain a calibration data set and a test data set; based on the calibration data set, obtaining calibration coefficient groups of a gas compressor or a turbine of the rotating equipment under different inlet temperatures, pressures and flows; automatically fitting a pressure ratio correction coefficient relational expression and an efficiency correction coefficient relational expression; changing a pressure ratio and an efficiency correction coefficient in the gas compressor or turbine model from a fixed value into the obtained regression polynomial, and completing calibration of the gas compressor and turbine simulation model; and the calibrated gas compressor and turbine simulation model is used for twin operation. The method has the beneficial effects that the problems that a gas compressor and turbine simulation model is high in simulation precision only under the rated working condition and is not ideal in simulation precision under other rotating speed working conditions can be solved.

Description

Technical Field

[0001] The present invention belongs to the technical field of digital twin simulation, and in particular relates to a turbine equipment simulation model calibration method based on a mechanism model. Background Art

[0002] Turbine equipment such as compressors and turbines are widely used in various fields of gas Brayton cycle power generation or power. They are key core equipment of power generation or power systems, and their operating characteristics are directly related to system performance.

[0003] In the initial operation of turbine equipment such as compressors and turbines after initial installation, it is necessary to calibrate the digital twin simulation model of the equipment. Under the premise that the operating data is not sufficient, the characteristic curve of the mechanism model is corrected to ensure that the simulation model can simulate the flow characteristics of the turbine equipment with high precision under the full range of working conditions, and support the high-precision twin operation of the turbine equipment with virtual and real synchronization. Conventional correction coefficients are generally set with fixed parameters, or set with fixed parameters at a certain speed. They meet better conditions under some working conditions and worse conditions under other conditions. The method proposed in the present invention can solve this problem well.

[0004] Conventional compressor or turbine simulation models are developed based on equipment characteristic curves. The characteristic curves are generally obtained through theoretical calculations and may not completely match the actual situation. Therefore, there is often a certain deviation between the simulation results of the compressor or turbine simulation model and the measured data, such as ±30%.

[0005] Digital twin simulation modeling requires that the simulated characteristics of the compressor or turbine are highly consistent with the measured characteristics. In order for the compressor or turbine simulation model to accurately simulate the characteristics of the physical equipment and meet the high precision requirements of the digital twin simulation model, such as ±3%, it is necessary to calibrate the compressor or turbine simulation model with measured data. The calibration is achieved by correcting the compressor or turbine characteristic curve so that the flow characteristics of the compressor or turbine simulation are consistent with the measured data.

[0006] The conventional calibration method is to correct the pressure ratio and efficiency of the rated operating point of the compressor or turbine characteristic curve based on the rated operating data, and use this correction coefficient to correct the characteristic curve of the compressor or turbine at other speeds. The correction coefficient is generally a fixed value, which will cause the simulation accuracy of the corrected model to meet the requirements under the rated operating conditions, but the simulation accuracy under other conditions is often not as ideal as the rated operating conditions. In view of this situation, the present invention proposes a global correction method for the compressor or turbine characteristic curve, that is, different correction coefficients are used at different speeds, and the correction coefficient is a function of the specific speed. This method can achieve that the deviation between the compressor or turbine simulation model and the measured data meets the high-precision simulation requirements under any operating condition. Summary of the invention

[0007] The purpose of the present invention is to provide a turbine equipment simulation model calibration method based on a mechanism model, which improves the traditional full-speed constant correction method based on the characteristic curve pressure ratio and efficiency of the rated point to a polynomial correction related to the speed, so as to achieve high-precision requirements for the deviation between the compressor and turbine simulation models and the actual measured data in the entire operating range.

[0008] The technical solution of the present invention is as follows: A turbine equipment simulation model calibration method based on a mechanism model comprises the following steps:

[0009] Step 1: Select the calibration parameters and target parameters of the compressor or turbine;

[0010] Step 2: Read the unit operation data and pre-process the operation data to obtain the calibration data set and the test data set;

[0011] Step 3: Based on the calibration data set, a calibration coefficient group of the compressor or turbine of the rotating equipment at different inlet temperatures, pressures, and flow rates is obtained;

[0012] Step 4: Based on the polynomial regression algorithm, automatically fit the pressure ratio correction coefficient relationship and the efficiency correction coefficient relationship;

[0013] Step 5: Change the pressure ratio and efficiency correction coefficient in the compressor or turbine model from a fixed value to the regression polynomial obtained in step 4 to complete the calibration of the compressor and turbine simulation model;

[0014] Step 6: Use the calibrated compressor and turbine simulation models for twin operation, that is, transfer the measured compressor and turbine inlet fluid boundary parameters to the simulation model in real time, and the compressor and turbine model and the physical equipment run synchronously, and display the deviation between the simulation value and the measured value of the compressor and turbine outlet parameters in real time. If the model prediction accuracy meets the standard, the twin calibration is completed; if the model accuracy does not meet the standard, re-update the fitting relationship of the correction coefficient.

[0015] The calibration parameters in step 1 include a pressure ratio correction factor and an efficiency correction factor, and the target parameters include an outlet temperature and an outlet pressure.

[0016] In step 2, the calibration data set and the test data set have the same parameter types, but different operating conditions. The calibration data set is used to calibrate the correction coefficient, and the test data set is used to verify the correction effect of the correction coefficient on the compressor or turbine simulation model.

[0017] The calibration data set and the test data set in step 2 include operating parameters and result parameters; the boundary parameters include the inlet temperature, pressure, flow rate and speed of the compressor or turbine, and the result parameters include the outlet temperature, outlet pressure and power of the compressor or turbine.

[0018] The calculation method of the pressure ratio correction coefficient in step 3 is: π =(π mear -1) / (π calc -1);

[0019] The calculation method of efficiency correction factor is: k η =(η mear ) / (η calc )

[0020] Where k is the correction factor, the simulated and measured values ​​of the outlet pressure and outlet temperature of the compressor or turbine are consistent, or the deviation is within the allowable subscript π represents the pressure ratio, the subscript η represents the efficiency, the subscript mear represents the measured value, and the subscript calc represents the calculated value of the simulation model based on the theoretical characteristic curve;

[0021] The calibration logic is: adjust the pressure ratio correction coefficient so that the calculated value of the compressor or turbine outlet pressure is equal to the measured value; adjust the efficiency correction coefficient so that the calculated value of the compressor or turbine outlet temperature is equal to the measured value; through step 3, a set of pressure ratio correction coefficients and efficiency correction coefficients under different speed and flow operating parameters are obtained;

[0022] The deviation between the simulated value and the actual value is calculated as follows:

[0023] Outlet pressure deviation: Err(Pout)=abs(P out,calc- P out,mear ) / P out,calc

[0024] Outlet temperature deviation: Err(Tout)=abs(T out,calc-Tout,mear ) / T out,calc

[0025] Wherein, T represents temperature, °C; P represents pressure, MPa; ΔP represents pressure difference, kPa; subscript out represents outlet, calc represents simulation value, and mear represents measured value.

[0026] The pressure ratio correction coefficient K in step 4 is π =f(n)=a0+a1n+a2n 2 +a3n 3 +...

[0027] Efficiency correction factor:

[0028] The power of the polynomial fitting is selected according to the set accuracy, where n is the dimensionless speed, which is the ratio of the actual speed to the rated speed, the subscript π represents the pressure ratio, and the subscript η represents the efficiency.

[0029] In the step 5, the correction coefficient is replaced by the fitting relationship of the previous step 4, and the updated compressor and turbine models are tested and verified using the test set. If the deviation is within the allowable range, the calibration is successful. If the deviation exceeds the allowable range, the equipment operation data of more operating conditions with a longer operating cycle is selected, and the above process is repeated to refit the relationship until the deviation is met.

[0030] The beneficial effect of the present invention is that the present invention can solve the problem that the simulation accuracy of the compressor and turbine simulation models is high only under rated conditions, and the simulation accuracy is not ideal under other speed conditions, and can achieve high-precision simulation of the flow characteristics of the compressor and turbine under the full speed range of operating conditions, and support the high-precision twin operation of the power generation or power system where the compressor and turbine are located with virtual and real synchronization. By applying the present invention, it can be ensured that the model establishes a high-precision simulation benchmark under the full range of operating conditions, and achieves the simulation accuracy of the twin operation of the physical equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 The present invention provides a flow chart of a turbine equipment simulation model calibration method based on a mechanism model.

[0032] Figure 2 This is an example of a compressor simulation model. DETAILED DESCRIPTION

[0033] In order to have a clearer understanding of the technical features, purposes and effects of the present invention, the basic implementation principle of the present invention is described below in conjunction with the accompanying drawings. The specific implementation principle described herein is only used to explain the present invention and is not intended to limit the present invention. In the following description, many specific details are set forth in order to fully understand the present invention, but the present invention can also be implemented in other ways different from those within the scope of this description, and therefore, the protection scope of the present invention is not limited by the specific embodiments disclosed below. Based on the implementation principle of the present invention, all other implementation cases obtained by those skilled in the art without making creative work belong to the scope of protection of the present invention. In the absence of conflict, the embodiments of the present application and the features in the embodiments, as well as the steps in all disclosed methods or processes, except for mutually exclusive features or steps, can be combined, expanded and replaced in any way.

[0034] Digital twin modeling requires that the simulation characteristics of the compressor and turbine are highly consistent with the actual performance. Therefore, twin modeling needs to calibrate the compressor and turbine simulation models according to the measured data to ensure that the simulation data and the measured data meet the high-precision requirements of twin operation at all operating speeds of the compressor and turbine. The traditional calibration method based on the correction of the pressure ratio and efficiency constants of the rated point data cannot achieve high-precision simulation of the full speed operating range. In order to achieve the above purpose, the present invention provides a supercritical carbon dioxide compressor and turbine simulation model calibration method based on a mechanism model, which can simulate the flow characteristics of the compressor and turbine at all speeds with high precision to meet the requirements of digital twin modeling.

[0035] like Figure 1 As shown, a turbine equipment simulation model calibration method based on a mechanism model includes the following steps:

[0036] Step 1: Select calibration parameters and target parameters of turbine equipment such as compressor or turbine. The calibration parameters include pressure ratio correction factor and efficiency correction factor. The target parameters include outlet temperature and outlet pressure.

[0037] Step 2: Read the unit operation data and preprocess the operation data to obtain the calibration data set and the test data set.

[0038] The calibration data set and the test data set have the same parameters, including operating parameters (also called boundary parameters) and result parameters; boundary parameters include compressor or turbine inlet temperature, pressure, flow rate and speed, and result parameters include compressor or turbine outlet temperature, outlet pressure and power. The calibration data set and the test data set have different operating conditions. The former is used to calibrate the correction coefficient, and the latter is used to verify the correction effect of the correction coefficient on the heat exchanger simulation model.

[0039] Preprocessing of unit operation data, including noise filtering, missing value filling, outlier removal, etc., ensures that the data is accurate and available.

[0040] Step 3: Based on the calibration data set, obtain the calibration coefficient group of the rotating equipment compressor or turbine at different inlet temperatures, pressures, and flow rates.

[0041] The calibration logic is: adjust the pressure ratio correction coefficient so that the calculated value of the compressor or turbine outlet pressure is equal to the measured value; adjust the efficiency correction coefficient so that the calculated value of the compressor or turbine outlet temperature is equal to the measured value; through step 3, a set of pressure ratio correction coefficients and efficiency correction coefficients under different speed and flow operating parameters are obtained.

[0042] Specifically, in the NUMAP system simulation software, a simulation model of the compressor or turbine is constructed, and the inlet flow boundary and the outlet pressure boundary are set. The inlet flow boundary is input with the actual measured values ​​of the inlet parameter flow and temperature in the calibration data table, and the outlet pressure boundary is input with the actual measured value of the pressure in the calibration data table, and then the simulation is performed. During the simulation process, the pressure ratio correction factor and the efficiency correction factor are adjusted according to the above calibration logic through online parameter adjustment until the equipment outlet temperature and pressure are consistent with the actual measured values, that is, a set of correction factors under specific operating parameters are determined.

[0043] The calculation method of pressure ratio correction coefficient is: k π =(π mear -1) / (π calc -1);

[0044] π′=π·k π

[0045] The calculation method of efficiency correction factor is: k η =(η mear ) / (η calc )

[0046] η′=η·k η

[0047] Where k is the correction factor, the simulated and measured values ​​of the outlet pressure and outlet temperature of the compressor or turbine are consistent, or the deviation is within the allowable range. The subscript π represents the pressure ratio, the subscript η represents the efficiency, the subscript mear represents the measured value, and the subscript calc represents the calculated value of the simulation model based on the theoretical characteristic curve. π′ is the corrected pressure ratio, π is the design pressure ratio before correction, and k π is the pressure ratio correction coefficient; η′ is the efficiency after correction, η is the efficiency before correction, k η is the efficiency correction factor.

[0048] The deviation between the simulated value and the actual value is calculated as follows:

[0049] Outlet pressure deviation: Err(Pout)=abs(P out,calc- P out,mear ) / P out,calc

[0050] Outlet temperature deviation: Err(Tout)=abs(T out,calc-Tout,mear ) / T out,calc

[0051] Wherein, T represents temperature, °C; P represents pressure, MPa; ΔP represents pressure difference, kPa; subscript out represents outlet, calc represents simulation value, and mear represents measured value.

[0052] Step 4: Based on the polynomial regression algorithm, the correction coefficients under different working conditions obtained in the previous step are subjected to polynomial fitting to obtain the relationship between the pressure ratio correction coefficient and the efficiency correction coefficient;

[0053] Pressure ratio correction factor K π =f(n)=a0+a1n+a2n 2 +a3n 3 +...

[0054] Efficiency correction factor:

[0055] The power of the polynomial fitting is intelligently selected according to the set accuracy. Among them, n is the dimensionless speed, which is the ratio of the actual speed to the rated speed, K is the correction coefficient, the subscript π represents the pressure ratio, and the subscript η represents the efficiency.

[0056] Step 5: Change the pressure ratio and efficiency correction coefficient in the compressor or turbine model from a fixed value to the regression polynomial obtained in step 4 to complete the calibration of the compressor and turbine simulation model.

[0057] By modifying the correction coefficient in the compressor or turbine simulation model, the previous fixed value correction is changed to a correction based on a polynomial, that is, the correction coefficient is replaced with the fitting relationship in the previous step 4, and the updated compressor or turbine model is tested and verified using a test set. If the deviation is within the allowable range, the calibration is successful. If the deviation exceeds the allowable range, the relationship is refitted, that is, the coefficients of each polynomial in step 4 are refitted to improve the fitting accuracy of the polynomial until the calibration deviation requirements of this step are met.

[0058] Step 6: Use the calibrated compressor and turbine simulation models for twin operation, that is, transfer the measured compressor and turbine inlet fluid boundary parameters to the simulation model in real time, and the compressor and turbine model will run in virtual and real synchronization with the physical equipment, and display the deviation between the simulation value and the measured value of the compressor and turbine outlet parameters in real time. If the model prediction accuracy meets the standard, the twin calibration is completed; if the model accuracy does not meet the standard, re-update the fitting relationship of the correction coefficient. The model accuracy is given by humans.

[0059] Example:

[0060] A turbine equipment simulation model calibration method based on a mechanism model comprises the following steps:

[0061] Step 1: Select calibration parameters and target parameters of turbine equipment such as compressor or turbine. The calibration parameters include pressure ratio correction coefficient s_pi and efficiency correction coefficient s_eta. The target parameters include outlet temperature Tout and outlet pressure Pout.

[0062] Step 2: Read the unit operation data according to the set data table, including boundary parameters, result parameters and target parameters; boundary parameters include the compressor or turbine inlet temperature of 32°C, pressure of 8.2MPa, and variable operating flow and speed data; result parameters include outlet temperature and pressure; target parameters are the measured data table of speed ratio, flow ratio, pressure ratio and efficiency calculated based on boundary data and result data;

[0063] Step 3: In the calibration mode, based on the measured data and theoretical data of the unit, calculate the pressure ratio correction factor and efficiency correction factor under different speed ratios and flow ratios;

[0064] The calculation method of the pressure ratio correction coefficient is: pressure ratio correction coefficient = (actual pressure ratio - 1) / (theoretical pressure ratio - 1);

[0065] The calculation method of efficiency correction factor is: efficiency correction factor = actual efficiency / theoretical efficiency;

[0066] Step 4: According to the polynomial regression algorithm, the relationship between the pressure ratio correction coefficient and the efficiency correction coefficient under different speed ratios and flow ratios is automatically fitted. The pressure ratio correction coefficient = f (flow ratio, speed ratio), the specific formula is s_pi = pi_a + pi_b*(1-n_cor) + pi_c*(1-n_cor)**2, the efficiency correction coefficient = f (flow ratio, speed ratio), the specific formula is s_eta = eta_a + eta_b*(1-n_cor) + eta_c*(1-n_cor)**2; wherein, n_cor = n_in*np.sqrt(t_in_0) / (n_0*np.sqrt(t_in)), n_in, n_0 are the inlet speeds and the design value 8100rpm, t_in, t_in_0 are the inlet temperatures and the design value 32°C;

[0067] The calculation method of efficiency simulation accuracy is: (actual efficiency - theoretical efficiency) / actual efficiency, and the calculation result is (0.164918-0.169347) / 0.164918 = -0.02686;

[0068] The calculation method of the pressure ratio simulation accuracy is: (actual pressure ratio-theoretical pressure ratio) / actual pressure ratio, and the calculation result is (3.707957-3.727289) / 3.707957=-0.005214;

[0069] Step 5: Update the correction coefficient in the model to a regression polynomial, which becomes part of the simulation model, and perform parameter simulation calculations. At this time, the flow characteristics of turbine equipment such as compressors and turbines under different speed ratios and flow ratios are calculated as follows. When the speed ratio is 1.1 (rated speed 8100rpm) and the flow rate is 266.667kg / s:

[0070] Calculated pressure ratio = pressure ratio correction value * (theoretical pressure ratio - 1) + 1, the simulation result is 3.707957;

[0071] Calculation efficiency = efficiency correction value * theoretical efficiency, the simulation calculation result is 0.164918;

[0072] The theoretical pressure ratio and theoretical efficiency are obtained by differentiating the theoretical flow ratio-pressure ratio curve and the flow ratio-efficiency curve.

[0073] Step 6: In the operation mode, carry out virtual-real synchronous twin operation simulation of the turbine equipment. If the model prediction accuracy reaches the set value, the calibration is completed; if the model accuracy does not reach the set value, re-perform the polynomial regression fitting of the correction coefficient until the set simulation accuracy is reached.

Claims

1. A turbine equipment simulation model calibration method based on a mechanism model, characterized in that: The following steps are involved: Step 1: Select the calibration parameters and target parameters of the compressor or turbine; Step 2: Read the unit operation data and pre-process the operation data to obtain the calibration data set and the test data set; Step 3: Based on the calibration data set, a calibration coefficient group of the compressor or turbine of the rotating equipment at different inlet temperatures, pressures, and flow rates is obtained; Step 4: Based on the polynomial regression algorithm, automatically fit the pressure ratio correction coefficient relationship and the efficiency correction coefficient relationship; Step 5: Change the pressure ratio and efficiency correction coefficient in the compressor or turbine model from a fixed value to the regression polynomial obtained in step 4 to complete the calibration of the compressor and turbine simulation model; Step 6: Use the calibrated compressor and turbine simulation models for twin operation, that is, transfer the measured compressor and turbine inlet fluid boundary parameters to the simulation model in real time, and the compressor and turbine model and the physical equipment run synchronously, and display the deviation between the simulation value and the measured value of the compressor and turbine outlet parameters in real time. If the model prediction accuracy meets the standard, the twin calibration is completed; if the model accuracy does not meet the standard, re-update the fitting relationship of the correction coefficient.

2. A turbine equipment simulation model calibration method based on a mechanism model as claimed in claim 1, characterized in that: The calibration parameters in step 1 include a pressure ratio correction factor and an efficiency correction factor, and the target parameters include an outlet temperature and an outlet pressure.

3. The method for calibrating a turbine equipment simulation model based on a mechanism model according to claim 1, characterized in that: In step 2, the calibration data set and the test data set have the same parameter types, but different operating conditions. The calibration data set is used to calibrate the correction coefficient, and the test data set is used to verify the correction effect of the correction coefficient on the compressor or turbine simulation model.

4. A turbine equipment simulation model calibration method based on a mechanism model as claimed in claim 3, characterized in that: The calibration data set and the test data set in step 2 include operating parameters and result parameters; the boundary parameters include the inlet temperature, pressure, flow rate and speed of the compressor or turbine, and the result parameters include the outlet temperature, outlet pressure and power of the compressor or turbine.

5. The method for calibrating a turbine equipment simulation model based on a mechanism model according to claim 1, characterized in that: The calculation method of the pressure ratio correction coefficient in step 3 is: π =(π mear -1) / (π calc -1); The calculation method of efficiency correction factor is: k η =(η mear ) / (η calc ) Where k is the correction factor, the simulated and measured values ​​of the outlet pressure and outlet temperature of the compressor or turbine are consistent, or the deviation is within the allowable subscript π represents the pressure ratio, the subscript η represents the efficiency, the subscript mear represents the measured value, and the subscript calc represents the calculated value of the simulation model based on the theoretical characteristic curve; The calibration logic is: adjust the pressure ratio correction factor so that the calculated value of the compressor or turbine outlet pressure is equal to the measured value; adjust the efficiency correction factor so that the calculated value of the compressor or turbine outlet temperature is equal to the measured value; Through step 3, a set of pressure ratio correction coefficients and efficiency correction coefficients under different speed and flow rate operating parameters are obtained; The deviation between the simulated value and the actual value is calculated as follows: Outlet pressure deviation: Err(Pout)=abs(P out,calc- P out,mear ) / P out,calc Outlet temperature deviation: Err(Tout)=abs(T out,calc-Tout,mear ) / T out,calc Wherein, T represents temperature, °C; P represents pressure, MPa; ΔP represents the pressure difference, kPa; the subscript out represents the outlet, calc represents the simulation value, and mear represents the measured value.

6. The method for calibrating a turbine equipment simulation model based on a mechanism model according to claim 1, characterized in that: The pressure ratio correction coefficient K in step 4 is π =f(n)=a0+a1n+a2n 2 +a3n 3 +... Efficiency correction factor: The power of the polynomial fitting is selected according to the set accuracy, where n is the dimensionless speed, which is the ratio of the actual speed to the rated speed, the subscript π represents the pressure ratio, and the subscript η represents the efficiency.

7. The method for calibrating a turbine equipment simulation model based on a mechanism model according to claim 1, characterized in that: In the step 5, the correction coefficient is replaced by the fitting relationship of the previous step 4, and the updated compressor and turbine models are tested and verified using the test set. If the deviation is within the allowable range, the calibration is successful. If the deviation exceeds the allowable range, the equipment operation data of more operating conditions with a longer operating cycle is selected, and the above process is repeated to refit the relationship until the deviation is met.

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