Low-pressure cylinder efficiency improving method based on data coordination technology

Abstract

The invention belongs to the technical field of nuclear turbine parameter calculation, and particularly relates to a low-pressure cylinder efficiency improving method based on a data coordination technology. Comprising the following steps: step 1, constructing a low-pressure cylinder system heat balance model; 2, calculating the efficiency of the low-pressure cylinder under the design working condition; 3, establishing a low-pressure cylinder model equation for each stage of low-pressure cylinder; 4, constructing a mean value and covariance matrix according to power plant measuring instrument information; 5, solving the heat balance model and the low-pressure cylinder model to obtain unknown variable data of the system; step 6, establishing a redundancy balance equation, and constructing a Jacobian matrix of the residual relative to the known parameters; 7, calculating a known parameter correction amount; and step 8, calculating the corrected measuring point value and the low-pressure cylinder efficiency parameter. The method has the beneficial effects that the efficiency of each stage of the low-pressure cylinder is corrected by using data redundancy of a plurality of measurement points in an actual nuclear power unit and by means of a data coordination technology from design working conditions.

Description

Technical Field

[0001] The present invention belongs to the technical field of nuclear power steam turbine parameter calculation, and particularly relates to a method for improving the efficiency of a low-pressure cylinder based on data reconciliation technology. Background Art

[0002] As a key component of the thermal system of a nuclear power plant, the operating state of a nuclear power steam turbine is crucial for ensuring the safety and efficiency of the entire power plant. In order to enable operators to monitor the working state of the nuclear power steam turbine in real time, a series of measuring instruments are installed near the nuclear power steam turbine to record parameters such as temperature, pressure, and flow rate. However, in actual operation, due to reasons such as environmental conditions, equipment aging, or calibration deviation, these measured values may deviate from the standard values, thereby affecting the assessment of the equipment operating conditions by the operators.

[0003] In particular, the cylinder efficiency of a steam turbine is an important performance indicator, which is directly related to the energy conversion efficiency and economic benefits of the generator set. In a nuclear power plant, especially in the low-pressure cylinder part, the exhausted steam is usually wet steam (i.e., steam containing liquid water droplets). In this case, the efficiency of the low-pressure cylinder is not only affected by the inlet and exhaust steam pressures and temperatures, but also significantly affected by the steam humidity. Although existing technologies can accurately measure temperature, pressure, and steam flow rate, there is still a lack of accurate and effective measurement methods for the water content (i.e., humidity) in the steam. This limitation makes it very difficult to accurately calculate the efficiency of the low-pressure cylinder, and considering the errors existing in the measuring equipment itself, this problem becomes even more complicated.

[0004] In order to ensure the accurate calculation of the efficiency of the low-pressure cylinder of a nuclear power steam turbine, a method that can not only adapt to actual complex working conditions but also estimate the efficiency of the low-pressure cylinder according to the component characteristics and operating state needs to be developed. According to the industry standard performance test procedure, when considering the exhaust loss, the calculation of the low-pressure cylinder efficiency usually requires a complex iterative process to finally make the enthalpy value at the end of the low-pressure cylinder expansion line reach a stable state. This method requires strict isolation of the system to accurately control and measure each variable.

[0005] It should be particularly noted that in the last-stage blade area of the low-pressure cylinder, the steam is in a wet saturated state, which makes the determination of the extraction steam enthalpy value also require an iterative calculation method to approximate the actual value. This complex calculation process not only has a huge calculation amount but also has cumbersome steps. In the real nuclear power plant environment, the actual conditions are often more complex and changeable, which further increases the difficulty of implementing this method and limits its practicality in daily operation and maintenance. Therefore, it is particularly important to find a more efficient and adaptable calculation scheme. Summary of the Invention

[0006] The object of the present invention is to provide a method for improving the low-pressure cylinder efficiency based on data reconciliation technology, which is used to improve the evaluation accuracy of the low-pressure cylinder efficiency of nuclear power steam turbines. This method analyzes the change of the working fluid enthalpy value and combines data reconciliation technology to correct the calculation result of the low-pressure cylinder efficiency, thereby improving the accuracy of the low-pressure cylinder efficiency and the calculation of other unknown parameters. The present invention makes full use of the measurement data redundancy at each extraction steam point, enhances the stability and reliability of the calculation process, and is applicable to the wide calculation requirements of the low-pressure cylinder system of nuclear power steam turbines.

[0007] The technical solution of the present invention is as follows: A method for improving the low-pressure cylinder efficiency based on data reconciliation technology includes the following steps:

[0008] Step 1: Construct a heat balance model of the low-pressure cylinder system;

[0009] Step 2: Calculate the low-pressure cylinder efficiency under the design condition;

[0010] Step 3: Establish a low-pressure cylinder model equation for each low-pressure cylinder;

[0011] Step 4: Construct a mean and covariance matrix according to the power plant measurement instrument information;

[0012] Step 5: Solve the heat balance model and the low-pressure cylinder model to obtain the system unknown variable data;

[0013] Step 6: Establish a redundancy balance equation and construct a Jacobian matrix of the residual with respect to the known parameters;

[0014] Step 7: Calculate the known parameter correction amount;

[0015] Step 8: Calculate the corrected measured point value and the low-pressure cylinder efficiency parameter.

[0016] The said Step 1 includes:

[0017] Establish the following relationship using the measurement information in the power station:

[0018] y = f(x) (1)

[0019] In the formula, x represents the known parameters in the low-pressure cylinder system of the power station, and y represents the unknown physical property parameters obtained by combining the measured values with the physical property relationship of the working fluid

[0020] For a specific component with a label i in the low-pressure cylinder system, its mass balance equation can be expressed as:

[0021] f m,i = q out,i - q in,i = 0 (2)

[0022] In the formula, f m,iDenote the residual of the mass balance equation for component \(i\) (the subscript \(m\) represents the mass balance equation, to be distinguished from the energy balance equation in the following text), \(q\) in,i Denote the total mass flow rate of the working fluid input to component \(i\), \(q\) out,i Denote component i The total mass flow rate of the working fluid flowing out. The flow rates are all calculated using absolute values. For a certain component, there is the following energy balance equation:

[0023] \(f\) e,i \(=h\) out,i \(-h\) in,i \(=0\ (3)\)

[0024] In the formula, \(f\) e,i Denote the residual of the energy balance equation for a certain component \(i\), \(h\) in,i Denote a certain component i The total input energy, \(h\) out,i Denote the total output energy of a certain component \(i\). The residual vector of the overall system balance equation is:

[0025] \(R = n(y)\ (4)\)

[0026] In the formula, \(R\) denotes the current residual vector of the system balance equation, and \(n\) is a function symbol representing the residual of the entire system.

[0027] The said step 2 includes:

[0028] For the isentropic efficiency \(\eta\) of each stage of nuclear power steam turbine i The definition is as follows:

[0029]

[0030] In the formula, \(h\) in,i Denote the enthalpy value of the working fluid at the inlet of the i th stage of the nuclear power steam turbine; \(h\) out,i Denote the enthalpy value of the working fluid at the outlet of the i th stage of the nuclear power steam turbine; \(h\) out,is Denote the adiabatic enthalpy value of the working fluid at the outlet of the \(i\)th stage of the nuclear power steam turbine;

[0031] For the design condition, the enthalpy values of the working fluid at the inlet and outlet of the \(i\)th stage of the low-pressure cylinder of the nuclear power steam turbine are obtained from the design drawing. The adiabatic enthalpy value of the working fluid at the outlet of the \(i\)th stage of the nuclear power steam turbine is queried using the enthalpy-entropy diagram. Substituting it into Equation (5) gives the efficiency \(\eta\) of the low-pressure cylinder at the \(i\)th stage under the design condition i .

[0032] The said step 3 includes:

[0033] For the nuclear power steam turbine, there is the following relationship between mass and energy balance:

[0034] \(m\) in,i \(=m\)out,i (6)

[0035] m in,i h in,i = m out,i h out,i + W i,out (7)

[0036] In the formula, m in,i represents the working fluid flow rate at the inlet of the i-th stage nuclear power steam turbine; m out,i represents the working fluid flow rate at the outlet of the i-th stage nuclear power steam turbine; W i,out represents the output shaft work of the i-th stage nuclear power steam turbine. The model of each low-pressure cylinder also includes the extraction part, and there are the following balance relations:

[0037] m out,i = m out,1,i + m in,i+1 (8)

[0038] m out,i h out,i = m out,1,i h out,1,i + m in,i+1 h in,i+1 (9)

[0039] In the formula, m out,1,i represents the extraction steam flow rate at the outlet of the i-th stage nuclear power steam turbine; m in,i+1 represents the working fluid flow rate at the outlet of the (i + 1)-th stage nuclear power steam turbine; h out,1,i represents the extraction steam enthalpy value at the outlet of the i-th stage nuclear power steam turbine; h in,i+1 represents the working fluid enthalpy value at the outlet of the i+ 1st stage nuclear power steam turbine.

[0040] Step 4 mentioned above includes: After completing the modeling work for the equilibrium relationship of certain system parameters of the nuclear power plant, the modeling input data used comes from the measurement results of each monitoring point in the actual power plant. For the operating parameter A of a certain component of the system i a total of n measurement results are selected, and a series of measurement values are obtained: A i,1 , A i,2 , …, A i,n , then the mean value of the measurement values at this measuring point is:

[0041]

[0042] In the formula, is the mean value estimation at this measuring point. The instrument uncertainty is used to measure the randomness of the fluctuation of the measuring point measurement values over a period of time, and the covariance matrix X c of the measuring point measurement values is obtained. Its elements are calculated as follows:

[0043]

[0044] Wherein, x ij is an element in the covariance matrix; is the variance of the measurement value at the i-th measurement point, is the variance of the measurement value at the j-th measurement point; r ij is the correlation coefficient between the measurement points.

[0045] The said step 5 includes:

[0046] According to the mass, energy balance and the low-pressure cylinder model, the following system of equations is obtained:

[0047]

[0048] Solve by using the Newton-Raphson iteration method. Denote this non-linear system of equations as F(x)=0, then the Jacobian matrix of this system of equations is defined as:

[0049]

[0050] After obtaining its Jacobian matrix, construct the following iteration format:

[0051] x (m+1) =x (m) -J -1 (x (m) )F(x (m) ) (14)

[0052] Wherein, m is the number of iterations, x (m) represents the solution x of the system of equations at the m-th iteration; J-1(x(m)) represents the inverse matrix of the Jacobian matrix of x (m) ; starting from m =0, and setting the iteration solution accuracy ε, the following linear system of equations should be solved during the iteration process:

[0053] J(x (m) )d=-F(x (m) ) (15)

[0054] Solve d from the above formula. When |d|<ε, it means that this iteration converges and meets the accuracy requirements, and the iteration process terminates; otherwise, make x (m+1) =x (m) +d (m) , and continue the iterative solution.

[0055] The said step 6 includes:

[0056] Calculate two sub-matrices respectively: J y,x is the Jacobian matrix of the unknown parameters of the power station with respect to the known parameters; J R,yis the Jacobian matrix of the redundancy balance equation with respect to the unknown parameters of the power station. Using the chain rule, these two sub-matrices are combined to calculate the required total Jacobian matrix J R,x :

[0057] J R,x = J R,y J y,x (16).

[0058] According to the calculated Jacobian matrix and combined with the mean and covariance matrix of the known parameters, calculate the residuals of the system redundancy balance equation, further calculate the correction amounts of all known parameters in the system. According to the mean of the known parameters in the system, calculate the mean values of the unknown parameters and the residuals of the system balance equation. The formula is as follows:

[0059]

[0060] In the formula, are the mean vectors of the unknown parameters and known parameters in the system respectively; are the residuals in the system respectively. From this, the covariance matrix X of the residual vector of the system balance equation is calculated R :

[0061]

[0062] For the known parameter correction amount c, there is the following constrained optimization problem:

[0063]

[0064] The goal of this constrained optimization problem is to minimize the optimization function ξ(c), that is, to ensure that the parameter correction amount is as small as possible while satisfying the constraint condition that the residual of the system balance equation is zero. Apply the Lagrange multiplier method to the above constrained optimization problem to convert it into an unconstrained optimization problem. Finally, the correction amount is obtained as:

[0065]

[0066] Under the condition of ensuring that the optimization objective function reaches the minimum value, solve the correction amounts of each known parameter and at the same time minimize the residuals of the system redundancy balance equation.

[0067] After completing the above calculations, the obtained correction amount c is added to the mean vector of the original known parameters as the final correction vector to complete the correction of these known parameters. The mean vector of the corrected known parameters is the updated result, and there is:

[0068]

[0069] For the low-pressure cylinder efficiency, there is:

[0070]

[0071] Wherein, is the corrected low-pressure cylinder efficiency, is the low-pressure cylinder efficiency under the design condition, is the correction amount of the low-pressure cylinder efficiency.

[0072] The beneficial effects of the present invention are as follows: starting from the design condition, the present invention utilizes the data redundancy of multiple measurement points in the actual nuclear power unit and corrects the efficiency of each stage of the low-pressure cylinder by means of data reconciliation technology. In addition, this method can further correct other related parameters, thereby simplifying the calculation process and improving the overall calculation accuracy and practicability. By evaluating the efficiency of the low-pressure cylinder of the nuclear power steam turbine based on the design condition, this method can directly calculate the enthalpy value and steam humidity at the outlet of each stage of the low-pressure cylinder, thus effectively ensuring the accuracy of the efficiency calculation of the nuclear power steam turbine. This method also follows the principles of mass and energy conservation of each stage of the steam turbine, makes full use of the multiple measurement data in the extraction steam link, and realizes the data reconciliation within the low-pressure cylinder system. This not only maximally ensures the calculation accuracy of the entire system, but also improves the reliability of the low-pressure cylinder efficiency evaluation. Description of the Drawings

[0073] Figure 1 is the solution flow chart of the correction process of the low-pressure cylinder efficiency of the nuclear power steam turbine based on data reconciliation;

[0074] Figure 2 is the measuring point and connection relationship diagram of the low-pressure cylinder system of a nuclear power plant. Detailed Embodiment

[0075] In order to enable those skilled in the art to better understand the technical solutions in the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention.

[0076] A method for improving the low-pressure cylinder efficiency based on data reconciliation technology provided by the present invention includes the following steps:

[0077] Step 1: Construct a thermal balance model of the low-pressure cylinder system

[0078] Specifically, the following relational expressions are established by using the measurement information in the power station:

[0079] y = f(x) (1)

[0080] In the formula, x represents known parameters in the low-pressure cylinder system of the power station, including the measurement value vectors of various actually arranged measuring points and known component characteristic parameters. y represents unknown physical property parameters obtained by combining measurement values with the physical property relationships of the working fluid, such as the enthalpy value or entropy value of the working fluid in a certain section of the pipeline in the system, or other unknown parameters in the power station system. These unknown parameters may be physical quantities calculated based on known measurement values, such as power or heat transfer, or may be the transfer or transformation of measurement values in the system, such as the change in mass flow rate during the convergence or divergence of pipeline working fluids.

[0081] The thermal balance model of the low-pressure cylinder system is established based on the principles of mass and energy conservation. For a specific component (labeled i) in the low-pressure cylinder system, its mass balance equation can be expressed as:

[0082] f m,i =q out,i -q in,i =0 (2)

[0083] In the formula, f m,i represents the residual of the mass balance equation of component i, q in,i represents the total flow rate of the working fluid input to component i, q out,i represents the total flow rate of the working fluid flowing out of component i. The flow rates are all calculated using absolute values and do not require the use of positive or negative signs to represent the direction relationship. m represents the mass flow rate. For a certain component, there is the following energy balance equation:

[0084] f e,i =h out,i -h in,i =0 (3)

[0085] In the formula, f e,i represents the residual of the energy balance equation of a certain component i, h in,i represents the total energy input to a certain component i, h out,i represents the total energy flowing out of a certain component i. By combining the balance equations of each component, the residual vector of the overall system balance equation can be obtained as:

[0086] R=n(y) (4)

[0087] In the formula, R represents the current residual vector of the system balance equation. The meaning of n is that n represents the system balance equation vector arranged by the balance equations of the aforementioned various components (f m,i 、f e,i etc.). It is the number of equations in the entire system and represents the entire system.

[0088] Step 2: Calculate the low-pressure cylinder efficiency under the design conditions.

[0089] In this method, for the isentropic efficiency η of each stage of nuclear power steam turbine iis defined as follows:

[0090]

[0091] In the formula, h in,i represents the enthalpy value of the working fluid at the inlet of the i-th stage nuclear power steam turbine; h out,i represents the enthalpy value of the working fluid at the outlet of the i-th stage nuclear power steam turbine; h out,is represents the adiabatic enthalpy value of the working fluid at the outlet of the i-th stage nuclear power steam turbine.

[0092] For the design condition, the enthalpy values of the working fluid at the inlet and outlet of the i-th stage of the low-pressure cylinder in the design drawing of the nuclear power steam turbine are both easily obtained, and the adiabatic enthalpy value of the working fluid at the outlet of the i-th stage nuclear power steam turbine can also be queried using the enthalpy-entropy diagram. Substituting it into Equation (5), the efficiency η of the low-pressure cylinder under the i-th stage design condition can be obtained i .

[0093] Step 3: Establish the low-pressure cylinder model equation for each stage of the low-pressure cylinder

[0094] For the nuclear power steam turbine, there are the following relationships for mass and energy balance:

[0095] m in,i = m out,i (6)

[0096] m in,i h in,i = m out,i h out,i + W i,out (7)

[0097] In the formula, m in,i represents the working fluid flow rate at the inlet of the i-th stage nuclear power steam turbine; m out,i represents the working fluid flow rate at the outlet of the i-th stage nuclear power steam turbine; W i,out represents the output shaft work of the i-th stage nuclear power steam turbine. Since there is a flow rate extracted from the outlet of each stage of the low-pressure cylinder and flowing towards the regenerative system in the actual power plant system, and the temperature, pressure, and flow rate of this flow rate are all known. Therefore, the low-pressure cylinder model for each stage also includes the extraction steam part, and there are the following balance relationships:

[0098] m out,i = m out,1,i + m in,i+1 (8)

[0099] m out,i h out,i = m out,1,i h out,1,i + m in,i+1 h in ,i+1 (9)

[0100] In the formula, m out,1,iIt represents the extraction steam flow rate at the outlet of the i-th stage nuclear power steam turbine; m in,i+1 It represents the working fluid flow rate at the outlet of the (i + 1)-th stage nuclear power steam turbine; h out,1,i It represents the extraction steam enthalpy value at the outlet of the i-th stage nuclear power steam turbine; h in,i+1 It represents the working fluid enthalpy value at the outlet of the (i + 1)-th stage nuclear power steam turbine. Thus, the calculation relationship of the measured values of the model measuring points of each low-pressure cylinder can be constructed.

[0101] Step 4: Construct the mean and covariance matrix according to the power plant measurement instrument information

[0102] After completing the modeling work for the equilibrium relationship of some system parameters of the nuclear power plant, the modeling input data used comes from the measurement results of each monitoring point in the actual power plant. Although the overall operation of the power plant is usually relatively stable, there will still be some fluctuations in the state and random errors caused by short-term instrument measurements. Therefore, when inputting data into the model, the measured values at a certain moment during the operation of the power plant should not be used, but the average values of the measured values of each monitoring point within a certain period of time should be adopted to accurately reflect the actual operation status of the system. For the operating parameter A of a certain component of the system within a period of time i A total of n measurement results are selected to obtain a series of measured values: A i,1 , A i,2 , …, A i,n , then the mean value of the measured values at this measuring point is:

[0103]

[0104] In the formula, is the mean value estimation at this measuring point. In addition to the mean value of the measured values, the instrument uncertainty is also needed to measure the randomness of the fluctuations of the measured values at the measuring point within a period of time. The covariance matrix X of the measured values at the measuring point can be obtained c , and its elements are calculated as follows:

[0105]

[0106] In the formula, x ij is the element in the covariance matrix; is the variance of the measured value at the i-th measuring point; r ij is the correlation coefficient between the measuring points, and this coefficient is determined according to the historical operation data of the actual power plant and combined with engineering experience.

[0107] is the variance of the measured value at the j-th measuring point.

[0108] Step 5: Solve the heat balance model and the low-pressure cylinder model to obtain the system unknown variable data According to the aforementioned mass, energy balance and low-pressure cylinder model, the following equations can be obtained:

[0109]

[0110] This system of equations is a system of multivariate nonlinear equations, and the Newton-Raphson iteration method can be used to solve it. Denote the above nonlinear system of equations as F(x) = 0, then the Jacobian matrix of this system of equations is defined as:

[0111]

[0112] After obtaining its Jacobian matrix, construct the following iteration format:

[0113] x (m+1) = x (m) - J -1 (x (m) )F(x (m) ) (14)

[0114] In the formula, m is the number of iterations, and x (m) represents the solution x of the system of equations in the m-th iteration; J-1(x(m)) represents the inverse matrix of the Jacobian matrix of x (m) ; starting from m = 0, and setting the iteration solution accuracy ε, the following linear system of equations should be solved in the iteration process:

[0115] J(x (m) )d = -F(x (m) ) (15)

[0116] Solve d from the above formula. When |d| < ε, it means that this iteration converges and meets the accuracy requirements, and the iteration process terminates; otherwise, make x (m+1) = x (m) + d (m) , and continue the iterative solution.

[0117] Step 9: Establish a redundant balance equation and construct the Jacobian matrix of the residual with respect to the known parameters.

[0118] To evaluate the overall error level of the system under the current operating state, the system residual can be calculated by using the redundant part in the above balance equation. Furthermore, the Jacobian matrix of the redundant balance equation with respect to the known parameters can be calculated. To obtain this Jacobian matrix, two sub-matrices need to be calculated separately: J y,x is the Jacobian matrix of the unknown parameters of the power station with respect to the known parameters; J R,y is the Jacobian matrix of the redundant balance equation with respect to the unknown parameters of the power station. Using the chain rule, these two sub-matrices can be combined to calculate the required total Jacobian matrix J R,x :

[0119] J R,x = J R,y Jy,x (16)

[0120] In other words, by analyzing the redundant data and calculating the system residuals, we can further obtain the Jacobian matrix of the known and unknown parameters, so as to better understand the mutual relationship and influence among the system parameters.

[0121] Step 7: Calculate the correction amount of known parameters

[0122] Based on the previously calculated Jacobian matrix and combined with the mean and covariance matrix of the known parameters, the residuals of the system redundancy balance equation can be calculated. Based on these conditions, the correction amounts of all the known parameters in the system can be further calculated. Specifically, according to the mean of the known parameters of the system, the means of the unknown parameters and the residuals of the system balance equation in the system can be calculated. The formula is as follows:

[0123]

[0124] In the formula, are the mean vectors of the unknown parameters and the known parameters in the system respectively; are the residuals in the system respectively. From this, the covariance matrix X of the residual vector of the system balance equation can be calculated R :

[0125]

[0126] In short, by using the Jacobian matrix and combining the statistical characteristics (such as mean and covariance) of the known parameters, the mean of the unknown parameters in the system and the mean of the system residuals can be calculated. Furthermore, the covariance matrix of the system residual vector can be obtained, which is of great significance for subsequent system state estimation and parameter correction.

[0127] For the correction amount c of the known parameters, there is the following constrained optimization problem:

[0128]

[0129] The goal of this constrained optimization problem is to minimize the optimization function ξ(c), that is, to ensure that the parameter correction amount is as small as possible while satisfying the constraint condition that the residuals of the system balance equation are zero. Applying the Lagrange multiplier method to the above constrained optimization problem is transformed into an unconstrained optimization problem, and finally the correction amount is obtained as:

[0130]

[0131] Through the above process, under the condition of ensuring that the optimization objective function reaches the minimum value, the correction amounts of each known parameter can be solved, and at the same time, the residuals of the system redundancy balance equation can be minimized.

[0132] Step 8: Calculate the corrected measured point values and the low-pressure cylinder efficiency parameters

[0133] After completing the above calculations, the obtained correction amount c can be added as the final correction vector to the mean vector of the original known parameters to complete the correction of these known parameters. The mean vector of the corrected known parameters is the updated result, and we have:

[0134]

[0135] Specifically, for the low-pressure cylinder efficiency, we have:

[0136]

[0137] In the formula, is the corrected low-pressure cylinder efficiency, is the low-pressure cylinder efficiency under the design condition, is the low-pressure cylinder efficiency correction amount.

[0138] Example:

[0139] According to the layout of the actual power plant system and measuring instruments, for the measuring points in the low-pressure cylinder system, they can be sorted and arranged in the following order: inlet flow rate (IN-M), inlet pressure (IN-P), inlet temperature (IN-T), exhaust flow rate (EX-M), exhaust pressure (EX-P), exhaust temperature (EX-T).

[0140] As Figure 2 shown, combining the characteristic parameters of the components and the known boundary conditions, a known parameter vector x can be formed, which has the following form:

[0141] x = (x 1 , x 2 , …, x 8 ) (24)

[0142] In addition to the above six measuring points, the known parameter vector x also includes component characteristic parameters, the pressure ratio of the nuclear power steam turbine, and the isentropic efficiency of the nuclear power steam turbine design. The corresponding relationships of the above parameters are shown in the following table:

[0143]

[0144] According to the known data, the unknown physical property parameter vector y can be queried, which has the following form:

[0145] y = (y 1 , y 2 ,..., y 11 ) (25)

[0146] Each component of the unknown physical property parameter vector y represents the inlet enthalpy value of the nuclear power steam turbine, the outlet enthalpy value of the nuclear power steam turbine, etc. The above parameter correspondence is shown in the following table:

[0147]

[0148] The following balance relationships exist for the above components according to mass and energy balance:

[0149]

[0150] In addition to the known parameters used in the above basic solution, the remaining part can be used to establish redundant balance equations to obtain the residual vector R=(R 1 ,R 2 ), and the calculation methods of its components are as follows:

[0151]

[0152] Calculate the efficiency of the low-pressure cylinder under the design conditions.

[0153] Query the enthalpy values of the working fluid at the inlet and outlet of the low-pressure cylinder of the nuclear power steam turbine in the design drawing, and query the adiabatic enthalpy value of the working fluid at the outlet of the nuclear power steam turbine through the enthalpy-entropy diagram. Substitute it into Equation (5) to obtain the efficiency η of the low-pressure cylinder under the design conditions, that is, x 8 .

[0154] Establish a low-pressure cylinder model equation for the low-pressure cylinder of the nuclear power steam turbine and its extraction steam.

[0155] For the low-pressure cylinder of the nuclear power steam turbine, the following relationship can be obtained by establishing a low-pressure cylinder model:

[0156] x 8 (y 1 -y 3 ) = y 1 -y 2 (28)

[0157] For the extraction steam part of the low-pressure cylinder of the nuclear power steam turbine, the following balance relationship related to the low-pressure cylinder can be obtained by using mass and energy balance:

[0158]

[0159] Construct the mean and covariance matrix according to the power plant measurement instrument information. By selecting the measured values of the measuring points within a certain period of time in the power station and calculating the mean value of the measured values of each measuring point according to Equation (10) At the same time, estimate the variance according to the uncertainty of the instrument Then, use Equation (11) to further calculate the uncertainty relationship between the known parameters, so as to construct the covariance matrix X between these known parameters c. In this process, the correlation coefficient is determined based on the historical operation data of the power station and combined with engineering experience.

[0160] The above covariance matrix reflects the statistical characteristics of the current operating condition of the system, can describe the statistical distribution of the measured values of the measuring points, and is an important basis for subsequent correction of the measured values.

[0161] Solve the thermal balance model and the low-pressure cylinder model to obtain the data of the unknown variables of the system.

[0162]

[0163] For the above system of multivariate nonlinear equations, the Newton-Raphson iteration method is used for solution. Let the system of multivariate nonlinear equations be F(y)=0. First, calculate the Jacobian matrix J(y) of the system of equations according to formula (13). Then, construct the iteration format shown in formula (14), and continue to iterate until the predetermined accuracy requirement is met, so as to obtain the numerical solutions of all unknown parameters in the system of equations. Simply put, through the Newton-Raphson method, first obtain the Jacobian matrix of the system of nonlinear equations, then construct the iteration formula based on this matrix, and continuously iterate until the accuracy of the solution meets the requirements, and finally obtain the approximate solutions of all unknown parameters.

[0164] Establish a redundant balance equation and construct the Jacobian matrix of the residual with respect to the known parameters. In order to evaluate the overall error level of the system under the current operating state, the system residual can be calculated by using the redundant part in the above balance equation. Furthermore, the Jacobian matrix of the redundant balance equation with respect to the known parameters can be calculated. To obtain this Jacobian matrix, two sub-matrices need to be calculated separately: J y,x is the Jacobian matrix of the unknown parameters of the power station with respect to the known parameters; J R,y is the Jacobian matrix of the redundant balance equation with respect to the unknown parameters of the power station. Using the chain rule, these two sub-matrices can be combined to calculate the required total Jacobian matrix J R,x .

[0165] Calculate the correction amount of the known parameter variables. According to the previously calculated Jacobian matrix J R,x , combined with the mean value and covariance matrix of the measured values of the measuring points, the residual of the redundant balance equation of the system can be calculated. Based on these conditions, the correction amount c of all known parameters in the system can be further calculated. According to the mean value of the known parameters of the system, the mean values of the unknown parameters in the system and the mean value of the residual of the system balance equation According to formula (19), the covariance matrix X R of the residual vector of the system balance equation can be calculated. For the correction amount c of the known parameters, there is the following constrained optimization problem:

[0166]

[0167] Apply the Lagrange multiplier method to the above constrained optimization problem to transform it into an unconstrained optimization problem, and finally obtain the correction amount as:

[0168]

[0169] Calculate the measured point values and parameters such as the low-pressure cylinder efficiency after correction. After completing the above calculations, the obtained correction amount c can be added as the final correction vector to the mean vector of the original known parameters, thereby completing the correction of these known parameters. The corrected mean vector of the known parameters is the updated result, and there is:

[0170]

[0171] In particular, for the low-pressure cylinder efficiency, there is:

[0172] η * = η + c η (34)

[0173] In the formula, η * is the corrected low-pressure cylinder efficiency, η is the low-pressure cylinder efficiency under the design condition, and c η is the low-pressure cylinder efficiency correction amount.

Claims

1. A method for improving the efficiency of a low-pressure cylinder based on data coordination technology, characterized in that: The steps include: Step 1: Construct a thermal balance model of the low-pressure cylinder system; Step 2: Calculate the low-pressure cylinder efficiency under design conditions; Step 3: Establish low-pressure cylinder model equations for each level of low-pressure cylinders; Step 4: Construct the mean and covariance matrix based on the power plant measurement instrument information; Step 5: Solve the thermal balance model and the low-pressure cylinder model to obtain the unknown variable data of the system; Step 6: Establish redundant equilibrium equations and construct the Jacobian matrix of the residual with respect to known parameters; Step 7: Calculate the correction amount of known parameters; Step 8: Calculate the corrected measuring point values ​​and low-pressure cylinder efficiency parameters.

2. A method for improving the efficiency of a low-pressure cylinder based on data coordination technology as claimed in claim 1, characterized in that: The step 1 comprises: The following relationship is established using the measurement information in the power station: y=f(x) (1) In the formula, x represents the known parameters in the low-pressure cylinder system of the power station, and y represents the unknown physical property parameters obtained by combining the measured values ​​with the physical property relationship of the working fluid. For a specific component numbered i in the low-pressure cylinder system, its mass balance equation can be expressed as: f m,i =q out,i -q in,i =0 (2) In the formula, f m,i represents the residual of the mass balance equation for component i, q in,i represents the total flow rate of the input fluid of component i, q out,i It represents the total flow rate of the working fluid flowing out of component i. The flow rate is calculated using absolute values. For a certain component, there is the following energy balance equation: f e,i =h out,i -h in,i =0 (3) In the formula, f e,i represents the residual of the energy balance equation for a component i, h in,i represents the total input energy of a component i, h out,i Represents the total energy flowing out of a component i, and the residual vector of the overall balance equation of the system is: R=n(y) (4) Where R represents the residual vector of the current equilibrium equation of the system.

3. A method for improving the efficiency of a low-pressure cylinder based on data coordination technology as claimed in claim 1, characterized in that: The step 2 comprises: For each level of nuclear power steam turbine isentropic efficiency η i is defined as follows: In the formula, h in,i represents the enthalpy of the working medium at the inlet of the i-th nuclear power steam turbine; h out,i represents the enthalpy of the working fluid at the outlet of the i-th nuclear power steam turbine; h out,is It represents the adiabatic enthalpy of the working fluid at the outlet of the i-th nuclear power steam turbine; For the design condition, the enthalpy values ​​of the working fluid at the inlet and outlet of the i-th nuclear power steam turbine of the low-pressure cylinder are obtained from the design drawing. The adiabatic enthalpy value of the working fluid at the outlet of the i-th nuclear power steam turbine is queried using the enthalpy entropy diagram. Substituting it into formula (5) can obtain the low-pressure cylinder efficiency η under the i-th design condition: i .

4. A method for improving the efficiency of a low-pressure cylinder based on data coordination technology as claimed in claim 1, characterized in that: The step 3 comprises: The mass and energy balance for nuclear power steam turbines has the following relationship: m in,i =m out,i (6) m in,i h in,i =m out,i h out,i +W i,out (7) In the formula, m in,i represents the working fluid flow rate at the inlet of the i-th nuclear power steam turbine; m out,i represents the working fluid flow rate at the outlet of the i-th nuclear power steam turbine; W i,out It represents the output shaft work of the i-th nuclear power steam turbine. The low-pressure cylinder model of each stage also includes the steam extraction part, and there is the following balance relationship: m out,i =m out,1,i +m in,i+1 (8) m out,i h out,i =m out,1,i h out,1,i +m in,i+1 h in,i+1 (9) In the formula, m out,1,i represents the steam extraction flow rate at the outlet of the i-th nuclear power steam turbine; m in,i+1 represents the working fluid flow rate at the outlet of the i+1th nuclear power steam turbine; h out,1,i represents the extraction enthalpy at the outlet of the i-th nuclear power steam turbine; h in,i+1 It represents the enthalpy of the working fluid at the outlet of the i+1th stage nuclear power steam turbine.

5. The method for improving the efficiency of a low-pressure cylinder based on data coordination technology according to claim 1, characterized in that: The step 4 includes: after completing the modeling work for the equilibrium relationship of certain system parameters of the nuclear power plant, the modeling input data used is derived from the measurement results of each monitoring point in the actual power plant, and the operating parameter A of a certain component of the system over a period of time is i A total of n measurement results are selected to obtain a series of measurement values: A i,1 ,A i,2 ,…,A i,n , then the mean value of the measured value at this measuring point is: In the formula, is the estimated value of the mean at the measuring point. The instrument uncertainty is used to measure the randomness of the fluctuation of the measured value of the measuring point over a period of time, and the covariance matrix X between the measured values ​​of the measuring points is obtained. c , whose elements are calculated as follows: In the formula, x ij are the elements in the covariance matrix; is the variance of the measured value at the measuring point; r ij is the correlation coefficient between the measurement points.

6. A method for improving the efficiency of a low-pressure cylinder based on data coordination technology as claimed in claim 1, characterized in that: The step 5 comprises: According to the mass, energy balance and low-pressure cylinder model, the following equations are obtained: The Newton-Raphson iteration method is used to solve the nonlinear equations. Let F(x) = 0, then the Jacobian matrix of the equations is defined as: After obtaining its Jacobian matrix, construct the following iterative format: In the formula, m is the number of iterations, x is (m) represents the solution x of the mth iteration system of equations; J-1(x(m)) express x (m) The inverse matrix of the Jacobian matrix; initially from m = 0, and set the iterative solution precision ε. The iterative process should solve the following linear equations: J(x (m) )d=-F(x (m) ) (15) Solve d from the above formula. When |d| < ε, it means that the iteration converges and meets the accuracy requirement, and the iteration process terminates; otherwise, let x (m+1) =x (m) +d (m) , and continue to iterate and solve.

7. A method for improving the efficiency of a low-pressure cylinder based on data coordination technology as claimed in claim 1, characterized in that: The step 6 comprises: Calculate two sub-matrices separately: J y,x is the Jacobian matrix of the unknown parameters of the power plant relative to the known parameters; J R,y is the Jacobian matrix of the redundant balance equations relative to the unknown parameters of the power plant. Using the chain rule, these two sub-matrices are combined to calculate the required total Jacobian matrix J R,x : I R,x =J R,y I y,x (16) 8. The method for improving the efficiency of a low-pressure cylinder based on data coordination technology according to claim 1, characterized in that: The step 7 includes: calculating the residual of the system redundant balance equation according to the calculated Jacobian matrix and combining the mean and covariance matrix of the known parameters, further calculating the correction amount of all known parameters in the system, and calculating the mean of the residual of the unknown parameters and the system balance equation according to the mean of the known parameters of the system, the formula is as follows: In the formula, are the mean vectors of unknown and known parameters in the system respectively; are the residuals in the system respectively, and the covariance matrix X of the residual vector of the system equilibrium equation is calculated R : For a known parameter correction c, there is the following constrained optimization problem: The goal of this constrained optimization problem is to minimize the optimization function ξ(c), that is, to ensure that the parameter correction is as small as possible while satisfying the constraint that the residual of the system equilibrium equation is zero. The above constrained optimization problem is converted into an unconstrained optimization problem by applying the Lagrange multiplier method, and the final correction is: Under the condition of ensuring that the optimization objective function reaches the minimum value, the correction amount of each known parameter is solved and the residual of the system redundant balance equation is minimized at the same time.

9. The method for improving the efficiency of a low-pressure cylinder based on data coordination technology according to claim 1, characterized in that: The step 8 comprises: after completing the above calculation, the obtained correction amount c is added as the final correction vector to the mean vector of the original known parameters The correction of these known parameters is completed, and the corrected known parameter mean vector Then the updated results are: For the low pressure cylinder efficiency: In the formula, is the corrected low-pressure cylinder efficiency, is the efficiency of the low-pressure cylinder under design conditions, It is the correction value of low-pressure cylinder efficiency.

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