Nuclear power conventional island thermodynamic system data correction method

Abstract

The invention belongs to the technical field of nuclear power operation management, and particularly relates to a nuclear power conventional island thermodynamic system data correction method. The method includes the following steps that a nuclear power unit conventional island principle thermodynamic system diagram is used for disassembling the nuclear power unit conventional island principle thermodynamic system diagram; establishing constraint equations for the disassembled subsystems one by one; through topology analysis, physical quantities representing the same meaning in the disassembled system are combined; establishing a Jacobian matrix for column-by-column scanning analysis; constructing an optimization problem of a complete thermodynamic cycle system; and correction values of various parameters of the complete thermodynamic cycle system are obtained. The method has the beneficial effects that the conventional island thermodynamic system is disassembled into a plurality of subsystems, the correction value of the thermodynamic parameter of each subsystem can be stably obtained by utilizing the characteristic that the number of optimization variables of the subsystems is small, and the correction value is used as an iteration initial value for solving the complete thermodynamic cycle system optimization algorithm, so that the solving stability is effectively improved.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of nuclear power operation management, and particularly relates to a nuclear power conventional island thermal system data correction method. BACKGROUND

[0002] In the operation process of the nuclear power plant conventional island thermal system, a large amount of measurement data will be collected, but due to instrument errors, environmental factors, long operation time and the like, these data often have inconsistency, resulting in inaccurate model calculation results based on these data, and affecting the performance evaluation of the system. The traditional data correction method has many problems in processing complex thermal systems, such as low calculation accuracy, long calculation time, poor processing capacity for nonlinear problems, and numerical instability caused by a large number of boundary constraints. SUMMARY

[0003] The purpose of the present application is to provide a nuclear power conventional island thermal system data correction method, which is based on an interior point algorithm and combined with a variety of optimization strategies, and realizes efficient coordination of the thermal system data, and improves the accuracy and stability of the data correction model solution.

[0004] The technical scheme of the present application is as follows: a nuclear power conventional island thermal system data correction method, comprising the following steps:

[0005] Step 1: using the principle thermal system diagram of the nuclear power unit conventional island, the system is disassembled;

[0006] Step 2: constraint equations are established for each of the disassembled subsystems in step 1;

[0007] f i (x)=0,i=1,2,3……m,x∈R n

[0008] In the formula, x is a vector with a length of n, and each element in the vector represents a physical parameter in the thermal system, including temperature, pressure, flow, dryness, efficiency, power, and pressure drop; f i (x) represents the i-th constraint, indicating the balance relationship in the thermal system;

[0009] Step 3: through topological analysis, the physical quantities representing the same meaning in the disassembled system are merged to reduce the parameter dimension, and the physical quantities representing the same meaning represent the physical quantities on the same pipe in the thermal system;

[0010] Step 4: the dimension of x is reduced from n to n1, and the dimension of the constraint f(x) is reduced from m to m1;

[0011] Step 5: the Jacobian matrix of the constraint f(x) after dimension reduction in step 4 is calculated as follows, the Jacobian matrix has m1 rows and n1 columns;

[0012]

[0013] Step 6: Column by column scanning analysis of the Jacobian matrix in step 5;

[0014] Step 7: Defining the n1-dimensional vector formed in step 5 as a total variable m1-dimensional constraint f(x) as a total equation Defining the p-dimensional vector formed as a non-isolated variable x p , and the q-dimensional constraint f(x) as a non-isolated equation f q (x p ), the deleted n1-p as a vector is an isolated variable, and the m1-q dimensional constraint is an isolated equation;

[0015] Step 8: Using the defined non-isolated variables and non-isolated equations to construct an optimization problem for the correction of thermal parameters;

[0016] Step 9: Using an interior point optimization algorithm to solve the optimization problem constructed in step 8 to obtain the correction value of the non-isolated variable;

[0017] Step 10: Each of the subsystems disassembled in step 1 is subjected to steps 2-9 to obtain the correction value of the isolated variable in each subsystem;

[0018] Step 11: The twelve subsystems disassembled in step 1 are combined into a complete thermal cycle system, and an optimization problem for the complete thermal cycle system is constructed according to the above steps;

[0019] Step 12: The calculated correction values of all isolated variables are used as initial values for the iterative solution of the optimization problem of the complete thermal cycle system;

[0020] Step 13: Using an interior point optimization algorithm, the results of step 12 are used as initial values for the iterative solution of the optimization problem constructed in step 12 to obtain the correction values of the parameters of the complete thermal cycle system.

[0021] The twelve subsystems disassembled in step 1 include a main steam system, a high-pressure steam turbine system, a steam-water separation and reheating system, a low-pressure steam turbine system, a condenser system, a low-pressure heater system, a feedwater pump system, a high-pressure heater system, a blowdown cooling system, a shaft seal overflow system, a circulating water system, and an electric power output system.

[0022] In step 4, the physical parameters are initialized according to the state of the working medium in the thermal system.

[0023] In step 4, if the state of the working medium is unsaturated water or superheated steam, other physical parameters are initialized through temperature and pressure; if the state of the working medium is wet steam, saturated water or saturated steam, other physical parameters are initialized through pressure and dryness or temperature and dryness.

[0024] In step 6, if there is only one element in the column that is not 0, the row and the column where the element is located are deleted, and the Jacobian matrix is changed to the following p-row and q-column form after processing, indicating that the dimension of x is reduced to p and the constraint f(x) is reduced to q after the above steps, a ij is any element in the following Jacobian matrix, which means that the i-th constraint f i (x) is the partial derivative of the i-th constraint f j (x) with respect to the j-th physical parameter x

[0025]

[0026] In step 8,

[0027]

[0028] where x p is a non-isolated variable, also known as a variable to be corrected; is the corresponding measurement data, f q (x p ) represents the equality constraint relationship satisfied between non-isolated variables, lb and ub are the lower and upper boundary vectors of the isolated variable x p , respectively, and X c -1 is a diagonal matrix composed of the variances of the measurement data, which has the following form, where the diagonal elements are the inverses of the variances of the corresponding non-isolated variable measurement data,

[0029]

[0030] The present application has the beneficial effects that the conventional island thermal system is disassembled into multiple subsystems, the number of optimization variables of the subsystems is small, the correction values of the thermal parameters of each subsystem can be stably obtained, and the correction values are used as the initial values of the iteration of the optimization algorithm of the complete thermal cycle system, thereby effectively improving the stability of the solution. The spatial dimension reduction technology and the variable segmentation technology are used to effectively reduce the number of optimization variables and the number of constraints in the data correction optimization algorithm, thereby improving the stability and robustness of the solution algorithm. BRIEF DESCRIPTION OF DRAWINGS

[0031] Figure 1 is a flow chart of a nuclear power plant conventional island thermal system data correction method provided by the present application. DETAILED DESCRIPTION

[0032] The present application will be further described in detail below in combination with the drawings and specific embodiments.

[0033] The nuclear power conventional island heat system data correction method provided by the application divides the heat system into multiple subsystems, respectively establishes data correction models, then performs modeling, debugging and fusion of each system, and finally solves the whole system. The data of each subsystem and the complete heat circulation system are calculated by the interior point optimization algorithm to obtain the coordinated values that meet the thermodynamic balance model and the measurement data.

[0034] A nuclear power conventional island heat system data correction method, comprising the following contents:

[0035] 1. According to the composition of the conventional island heat system, the complete heat system is disassembled into multiple subsystems.

[0036] 2. The spatial dimension reduction technology is used to perform equivalent processing on the variable properties of the directly connected spatial ports through topological analysis before calculation, so as to reduce the variable dimension and equation dimension of system calculation.

[0037] 3. According to the working medium state in the heat system, the heat system parameters are initialized to reduce the constraint violation degree at the beginning of data correction model optimization solution.

[0038] 4. The full variable, full equation, isolated variable, isolated equation, non-isolated variable, non-isolated equation and empty variable are defined, the whole variables and equations of the heat system are segmented, only the non-isolated variables and equations participate in iterative solution, and the calculation efficiency is improved.

[0039] 5. The interior point algorithm is used to solve each subsystem one by one to obtain the heat parameter correction value of each subsystem.

[0040] 6. The complete heat circulation system is composed of each subsystem, the heat parameter correction value of each subsystem is used as the initial value of the iteration of the complete heat system data correction optimization algorithm, and the interior point method is used for solution.

[0041] As shown in Figure 1 A nuclear power conventional island heat system data correction method, comprising the following steps:

[0042] Step 1: The principle heat system diagram of the nuclear power unit conventional island is used to analyze the system composition and disassemble it;

[0043] The disassembly is specifically twelve subsystems, including the main steam system, the high-pressure steam turbine system, the steam-water separation and reheating system, the low-pressure steam turbine system, the condenser system, the low-pressure heater system, the feedwater pump system, the high-pressure heater system, the blowdown cooling system, the shaft seal overflow system, the circulating water system and the electric power output system.

[0044] Step 2: According to the operation mechanism of the heat system, the constraint equations of the above twelve subsystems are established one by one;

[0045] xi (x)=0,i=1,2,3...m,x∈R n

[0046] In the formula, x is a vector of length n, and each element in the vector represents a physical parameter in the thermodynamic system, including temperature, pressure, flow rate, dryness fraction, efficiency, power, pressure drop, etc. i (x) represents the i-th constraint, indicating the equilibrium relationship in the thermodynamic system, such as mass balance, energy balance, and pressure balance.

[0047] Step 3: Through topology analysis, merge physical quantities that represent the same meaning in the disassembled system to reduce the parameter dimensionality. Specifically, physical quantities that represent the same meaning are physical quantities on the same pipe in the thermal system, such as the outlet pipe of the previous stage heater and the inlet pipe of the next stage heater being the same pipe.

[0048] Step 4: Reduce the dimension of x from n to n1, and reduce the dimension of constraint f(x) from m to m1;

[0049] Furthermore, physical parameters are initialized based on the working fluid state in the thermal system. Specifically, if the working fluid state is unsaturated water or superheated steam, other physical parameters are initialized using temperature and pressure; if the working fluid state is wet steam, saturated water, or saturated steam, other physical parameters are initialized using pressure and dryness fraction or temperature and dryness fraction.

[0050] Step 5: Calculate the Jacobian matrix of the constraint f(x) after dimensionality reduction in step 4 as follows: Jacobian matrix has m1 rows and n1 columns.

[0051]

[0052] Step 6: Perform a column-by-column scan analysis on the Jacobian matrix from Step 5;

[0053] If there is exactly one non-zero element in this column, delete the row and column containing that element. After processing, the Jacobian matrix becomes p rows and q columns, indicating that after the above steps, the dimension of x is reduced to p, and the constraint f(x) is reduced to q. ij Let f be any element in the Jacobian matrix below, and let f represent the i-th constraint f. i (x) for the j-th physical parameter x j The partial differential of .

[0054]

[0055] Step 7: Define the n1-dimensional vector formed in Step 5 as a total variable. m1-dimensional constraint f(x) is the total equation The resulting p-dimensional vector is defined as a non-isolated variable x. pThe q-dimensional constraint f(x) is a non-isolated equation f q (x p The deleted n1-p is a vector and an isolated variable, and the m1-q dimensional constraint is an isolated equation.

[0056] Step 8: Construct the following optimization problem using the defined non-isolated variables and non-isolated equations for the correction of thermodynamic parameters.

[0057]

[0058] stf q (x p ) = 0

[0059] lb≤x p ≤ub

[0060] In the formula, x p These are non-isolated variables, also known as variables to be corrected; For the corresponding measured data, f q (x p ) represents the equality constraint relationship satisfied between non-isolated variables, where lb and ub are the isolation variables x and y respectively. p The lower and upper boundary vectors, X c -1 The diagonal matrix formed by the variances of the measurement data is as follows, where the diagonal elements are the reciprocals of the variances of the corresponding non-isolated variable measurement data.

[0061]

[0062] Step 9: Use the interior point optimization algorithm to solve the optimization problem constructed in step 8 and obtain the correction values ​​of the non-isolated variables.

[0063] Step 10: For each of the twelve subsystems decomposed in Step 1, go through Steps 2 to 9 one by one to obtain the correction value of the isolated variable in each subsystem.

[0064] Step 11: Combine the twelve subsystems disassembled in Step 1 into a complete thermodynamic cycle system, and construct the optimization problem of the complete thermodynamic cycle system according to the above steps.

[0065] Step 12: Use the calculated correction values ​​of all isolated variables as initial values ​​for iteratively solving the optimization problem of the complete thermodynamic cycle system.

[0066] Step 13: Using the interior point optimization algorithm, with the calculation results in Step 12 as the initial values ​​for iteration, solve the optimization problem constructed in Step 12 to obtain the correction values ​​of various parameters of the complete thermodynamic cycle system.

Claims

1. A method for correcting data of the thermal system of a conventional island in a nuclear power plant, characterized in that, Includes the following steps: Step 1: Using the principle thermal system diagram of the conventional island of the nuclear power unit, disassemble it; Step 2: Establish constraint equations for each of the subsystems decomposed in Step 1; f i (x)=0,i=1,2,3……m,x∈R n In the formula, x is a vector of length n, and each element in the vector represents a physical parameter in the thermodynamic system, including temperature, pressure, flow rate, dryness fraction, efficiency, power, and pressure drop. i (x) represents the i-th constraint, indicating the equilibrium relationship in the thermodynamic system; Step 3: Through topology analysis, merge physical quantities that represent the same meaning in the disassembled system to reduce the parameter dimensionality. Physical quantities with the same meaning represent physical quantities on the same pipe in the thermal system. Step 4: Reduce the dimension of x from n to n1, and reduce the dimension of constraint f(x) from m to m1; Step 5: Calculate the Jacobian matrix of the constraint f(x) after dimensionality reduction in Step 4 as follows: Jacobian matrix has m1 rows and n1 columns; Step 6: Perform a column-by-column scan analysis on the Jacobian matrix from Step 5; Step 7: Define the n1-dimensional vector formed in Step 5 as a total variable. m1-dimensional constraint f(x) is the total equation The resulting p-dimensional vector is defined as a non-isolated variable x. p The q-dimensional constraint f(x) is a non-isolated equation f q (x p The deleted n1-p is a vector and an isolated variable, and the m1-q dimensional constraint is an isolated equation; Step 8: Construct an optimization problem using the defined non-isolated variables and non-isolated equations for the correction of thermodynamic parameters; Step 9: Solve the optimization problem constructed in Step 8 using the interior point optimization algorithm to obtain the correction values ​​of the non-isolated variables; Step 10: For each of the subsystems decomposed in Step 1, go through Steps 2 to 9 one by one to obtain the correction value of the isolated variable in each subsystem; Step 11: Combine the twelve subsystems disassembled in Step 1 into a complete thermodynamic cycle system, and construct the optimization problem of the complete thermodynamic cycle system according to the above steps; Step 12: Use the calculated correction values ​​of all isolated variables as initial values ​​for iteratively solving the optimization problem of the complete thermodynamic cycle system; Step 13: Using the interior point optimization algorithm, with the calculation results in Step 12 as the initial values ​​for iteration, solve the optimization problem constructed in Step 12 to obtain the correction values ​​of various parameters of the complete thermodynamic cycle system.

2. The data correction method for the conventional island thermal system of a nuclear power plant as described in claim 1, characterized in that: Step 1 is broken down into twelve subsystems, including the main steam system, high-pressure steam turbine system, steam-water separation and reheat system, low-pressure steam turbine system, condenser system, low-pressure heater system, feedwater pump system, high-pressure heater system, blowdown cooling system, shaft seal overflow system, circulating water system, and electric power output system.

3. The data correction method for the conventional island thermal system of a nuclear power plant as described in claim 1, characterized in that: In step 4, physical parameters are initialized based on the state of the working fluid in the thermodynamic system.

4. The data correction method for the conventional island thermal system of a nuclear power plant as described in claim 3, characterized in that: In step 4, if the working fluid is unsaturated water or superheated steam, other physical parameters are initialized by temperature and pressure; if the working fluid is wet steam, saturated water or saturated steam, other physical parameters are initialized by pressure and dryness or temperature and dryness.

5. The data correction method for the conventional island thermal system of a nuclear power plant as described in claim 1, characterized in that: In step 6, if there is exactly one non-zero element in this column, then delete the row and column containing that element. After processing, the Jacobian matrix becomes a p-row, q-column matrix, indicating that after the above steps, the dimension of x is reduced to p, and the constraint f(x) is reduced to q. ij Let f be any element in the Jacobian matrix below, and let f represent the i-th constraint f. i (x) for the j-th physical parameter x j partial differential 6. The data correction method for the conventional island thermal system of a nuclear power plant as described in claim 1, characterized in that: In step 8, 7. The data correction method for the conventional island thermal system of a nuclear power plant as described in claim 6, characterized in that: In step 8, x p These are non-isolated variables, also known as variables to be corrected; For the corresponding measured data, f q (x p ) represents the equality constraint relationship satisfied between non-isolated variables, where lb and ub are the isolation variables x and y respectively. p The lower and upper boundary vectors, X c -1 The diagonal matrix representing the variances of the measurement data is as follows, where the diagonal elements are the reciprocals of the variances of the corresponding non-isolated variable measurement data.

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