A steam pipe network simulation system optimization scheduling method based on digital twinning

Abstract

The present application relates to a kind of steam pipe network simulation system optimization scheduling method based on digital twinning, comprising the following steps: S1, the real-time dynamic data information of entity steam pipe network system is obtained;S2, the real-time dynamic data information obtained is input into digital twinning steam pipe network simulation system, and digital twinning steam pipe network simulation system carries out virtual synchronous iteration with entity steam pipe network system according to real-time dynamic data information, and outputs scheduling scheme;S3, decision maker decides whether to execute according to experience and actual production condition;S4, after scheduling scheme is executed, the data of entity steam pipe network system is collected by real-time monitoring system, and the real-time dynamic data information collected is transmitted to digital twinning steam pipe network simulation system, to update and improve digital twinning steam pipe network simulation system.The regulation and control method provided by the present application can realize the synchronization and interaction of physical entity and virtual model, and give steam optimization scheduling scheme from the point of view of operating cost.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of energy optimal scheduling, and particularly relates to a steam pipe network simulation system and an optimal scheduling method based on digital twinning. BACKGROUND

[0002] Steam is one of the necessary energies in the production process of a steel enterprise, and many process production flows need to use steam. The steam pipe network system is an important component of the energy system in a steel enterprise. The steam pipe network system is divided into three subsystems, a steam production subsystem, a conveying subsystem, and a steam consumption subsystem. The steam production equipment mainly includes steam power equipment and waste heat recovery equipment. The conveying equipment includes steam pipe networks and accumulators. The steam consumption equipment includes production and living users.

[0003] The steam system of a steel enterprise includes steam generation, conveying, use, distribution, and recovery links, which are interrelated and interdependent. The steam pipe network system of a steel enterprise has the following characteristics: the steam production equipment is diverse, including steam boilers and waste heat boilers of each process in the steel production process; the steam pipe network structure is complex, the pipe network contains multiple pressure levels and has many loops, and the operation state of the pipe network directly affects the steam quality and the energy utilization rate of the system; there are multiple steam generation sources, multiple steam users of each process, different demands for steam quality, and large fluctuations in steam consumption. These characteristics determine the complexity of the steam system of a steel enterprise. Therefore, to study the optimal scheduling problem of the steam system, a suitable and targeted research method should be selected.

[0004] The steam pipe network system of a steel enterprise has the following problems in actual production operation: the steam consumption fluctuates greatly with the steel production plan, and if the steam production cannot keep up with the fluctuation of steam consumption, it will cause the steam to be unable to meet the needs of steel production or to be released; the steam system does not fully realize cascade utilization and energy use according to quality, the demands of users for steam quality are not completely the same, and users usually use steam after reducing the temperature and pressure to meet production needs, resulting in serious devaluation of high-grade steam; the steam pipe network structure is complex, and there are problems such as steam leakage, aging of the insulation layer, and condensate water. SUMMARY

[0005] (I) Technical problems to be solved

[0006] In order to solve the above problems of the prior art, the present application provides a steam pipe network simulation system and an optimal scheduling method based on digital twinning, which solves the problems of steam high-quality low-use and steam release in industrial enterprises such as steel enterprises, and realizes energy saving and emission reduction of the steam system.

[0007] (II) Technical solutions

[0008] In order to achieve the above purpose, the main technical solutions adopted by the present application include:

[0009] A digital-twin-based steam pipe network simulation system optimization scheduling method, comprising the following steps:

[0010] S1, obtaining real-time dynamic data information of an entity steam pipe network system;

[0011] S2, inputting the obtained real-time dynamic data information into a digital-twin-based steam pipe network simulation system, and performing virtual synchronous iteration of the digital-twin-based steam pipe network simulation system according to the real-time dynamic data information and the entity steam pipe network system, and outputting a scheduling scheme;

[0012] S3, determining whether to execute according to experience and actual production conditions;

[0013] If execution is performed, the entity steam pipe network system is executed by the executor to execute the scheduling scheme;

[0014] If execution is not performed, the scheduling scheme is modified and input into the digital-twin-based steam pipe network simulation system for simulation verification;

[0015] S4, after the scheduling scheme is executed, the real-time monitoring system collects data of the entity steam pipe network system, and transmits the collected real-time dynamic data information to the digital-twin-based steam pipe network simulation system for updating and improving the digital-twin-based steam pipe network simulation system.

[0016] Preferably, the S1 further comprises: establishing a digital-twin-based steam pipe network simulation system;

[0017] Comprising the following steps:

[0018] A1, obtaining steel enterprise steam production and consumption historical data, steam pipe network information, steam power boiler and waste heat boiler related parameters, determining production plan and maintenance plan in a scheduling period;

[0019] A2, training and identifying the working condition classification model, and pre-processing the steel enterprise steam production and consumption historical data in A1 by wavelet filtering, data repair, normalization, standardization and other methods;

[0020] A3, virtually modeling the entity steam pipe network system of the steel enterprise, corresponding to the physical entity, and establishing corresponding virtual models of the steam system from the steam supply side, the conveying side and the demand side;

[0021] A4, on the basis of establishing the digital-twin-based steam pipe network simulation model, performing simulation, optimization, decision-making and other operations according to related theories and methods, establishing steam optimization, taking the minimum economic operation cost as the target to calculate the optimal steam distribution scheme and save it to the database.

[0022] Preferably, the A1 further comprises: obtaining enterprise steam production and consumption history data, steam pipe network information, steam power boiler and waste heat boiler related parameters, production plan and maintenance plan through the enterprise comprehensive data integration platform server;

[0023] The steam production and consumption history data includes: steam production of power boilers and waste heat boilers, steam consumption of generator units, and steam consumption of production and life in the steel enterprise;

[0024] The steam pipe network information includes: topological information, pipe length, pipe diameter, pipe section flow, pipe section drainage flow, valves, pipe section import and export pressure and temperature, pipe fittings number, resistance coefficient, insulation layer material, and thickness.

[0025] Preferably, the A2 further comprises the following steps:

[0026] A201, reconfiguring data by using a vector space reconstruction method, recording each data according to different production conditions to match a condition label, taking the reconfigured data as input data and the data label as output data to form a training data set;

[0027] A202, classifying the data set by using a training neural network technology, and obtaining model parameters by using an error back propagation algorithm;

[0028] A203, collecting real-time data, taking the data after data preprocessing and vector space reconstruction as model input data, and obtaining an output data label as a current production condition;

[0029] A204, determining steam production and consumption in a future scheduling period in combination with the current production condition and the production plan and maintenance plan in the A1.

[0030] Preferably, the A3 further comprises: establishing a steam generating equipment model, and the steam generating equipment includes steam power boilers and waste heat boilers of each process;

[0031] including the following steps:

[0032] (1) Steam production of a steam boiler:

[0033]

[0034] wherein, G b is the steam production of the boiler per unit time, t / h; η b is the thermal efficiency of the steam boiler, %; k is the fuel type; B i is the consumption of the i-th fuel, t / h; b i is the standard coal coefficient of the i-th fuel, kgce / t; h s is the steam enthalpy value generated by the steam boiler, kJ / t; h wFor steam boiler feed water enthalpy, kJ / t;

[0035] (2) The waste heat boiler includes dry quenching waste heat boiler, sintering waste heat boiler, sintering waste heat boiler, converter waste heat boiler, and rolling steel waste heat boiler. The steam generation amount of the waste heat boiler is related to the boiler thermal efficiency, feed water parameters, steam parameters, heat exchange medium and other factors. The steam generation amount of the converter waste heat boiler is:

[0036]

[0037] Among them, is the steam generation amount of the converter waste heat boiler per unit time, t / h; t1 is the temperature of the flue gas entering the waste heat boiler, ℃; t2 is the temperature of the flue gas leaving the waste heat boiler, ℃; c p1 is the specific heat capacity of flue gas at t1, kJ / (m 3 ·℃); c p2 is the specific heat capacity of flue gas at t2, kJ / (m 3 ·℃); is the total amount of furnace gas generated by the oxidation of carbon in the carbon-containing material in the molten iron, m 3 / t; R is the combustion heat value of CO, kJ / m 3 ; is the thermal efficiency of the converter waste heat boiler, %; α is the distribution ratio of carbonization products CO and CO2, %; λ k is the air suction coefficient, the ratio of actual air suction amount to theoretical air for complete combustion of converter flue gas, %; is the specific enthalpy of steam generation, kJ / t; is the specific enthalpy of feed water, kJ / t.

[0038] Preferably, the A3 further comprises: establishing a steam consumption system model;

[0039] Obtain the process requirement information of steam of all production users in the entire steel enterprise, including pressure, temperature, summer steam consumption, winter steam consumption, average steam consumption, maximum steam consumption, use system, and record and process through a database.

[0040] Preferably, the A3 further comprises: establishing a steam delivery model;

[0041] Including the following steps:

[0042] Obtain the enterprise steam pipe network topology structure and related historical data records;

[0043] A basic information database of the pipe network is established to store specific parameters of the pipe network, such as the topological structure, pipe length, pipe diameter, flow of each pipe section, drainage amount of each pipe section, number of valves, number of pipe fittings, resistance coefficient, thermal insulation material, thickness of thermal insulation layer, pressure and temperature of each node, dynamic viscosity, correction coefficient, absolute roughness of each pipe section, steam density, and thermal conductivity.

[0044] The steam pipe network is simplified as a directed graph composed of pipe sections and nodes, the topological structure of the pipe network is obtained, and the topological relationship of the pipe network is described by using a pipe section-node association matrix, the steam source point, internal nodes, and user nodes are divided into reference nodes, calculation nodes, and independent nodes.

[0045] When the pipe section is too long, a large error is introduced in the calculation, and for the long pipe section, a method of adding a virtual node is needed to segment the long pipe section.

[0046] The actual pipe network is converted into a mathematical model, and based on the node flow conservation equation, pressure drop calculation formula, temperature drop calculation formula, and IAPWS-IF97 formula, a steam pipe network hydraulic and thermal coupling calculation model is established in combination with the dynamic viscosity, flow velocity, and Reynolds number calculation formula in fluid mechanics, wherein the hydraulic and thermal calculation of a single pipe section is as follows:

[0047] First, the pressure and temperature of the steam at the outlet of the pipe section are assumed, and the steam density is calculated by using the IAPWS-IF97 formula:

[0048]

[0049] In the formula, is the partial derivative of the ideal gas part of the specific Gibbs energy with respect to the specific pressure in a dimensionless form, is the partial derivative of the excess part of the specific Gibbs energy with respect to the specific pressure in a dimensionless form;

[0050] Then, the intermediate parameters of the steam flow velocity, dynamic viscosity, and Reynolds number are obtained:

[0051]

[0052] In the formula, v is the steam flow velocity, m / s; d is the equivalent diameter of the pipe section, m; and G is the flow of the pipe section, m 3 / s;

[0053]

[0054]

[0055] In the formula, μ is the dynamic viscosity, 10 -6 ·m 2 ·s -1 ; n i , I i , J iwherein, η is the correction factor; t is the steam temperature at the inlet of the pipe section, ℃; t is the steam temperature at the outlet of the pipe section, ℃; t is the ambient temperature, ℃; h1 is the inner side convective heat transfer coefficient; h2 is the outer side convective heat transfer coefficient; d2 is the outer diameter of the insulation layer, m; d1 is the steam pipe inner diameter, m; l is the pipe length, m; λ is the thermal conductivity of the insulation layer, W / (m·℃);

[0056]

[0057] wherein, R is the Reynolds number; ρ is the steam density, kg / m e ; v is the steam flow rate, m / s; μ is the steam dynamic viscosity, 10 3 -3m2 / s; d is the pipe diameter, m; l is the pipe length, m; l -6 is the equivalent length of the pipe fittings such as valves and bends, m; G is the pipe flow, kg / s; k is the pipe equivalent roughness, m; R 2 is the Reynolds number; -1 ;

[0058] The pipe section pressure drop and temperature drop are then calculated, and the pipe section pressure drop calculation formula is:

[0059]

[0060] wherein, Δp is the pressure drop of the pipe section, Pa; d is the inner diameter of the pipe section, m; β is the local pressure drop correction coefficient of the pipe section; l is the length of the pipe section, m; l e is the equivalent length of the pipe fittings such as valves and bends, m; G is the pipe flow, kg / s; k is the pipe equivalent roughness, m; R e is the Reynolds number;

[0061] The temperature drop calculation formula is:

[0062]

[0063] wherein, Δt is the temperature drop of the pipe section, ℃; η h is the correction factor; t in is the steam temperature at the inlet of the pipe section, ℃; t out is the steam temperature at the outlet of the pipe section, ℃; t f is the ambient temperature, ℃; h1 is the inner side convective heat transfer coefficient; h2 is the outer side convective heat transfer coefficient; d2 is the outer diameter of the insulation layer, m; d1 is the steam pipe inner diameter, m; l is the pipe length, m; λ is the thermal conductivity of the insulation layer, W / (m·℃);

[0064] The outlet pressure is obtained according to the pipe section pressure drop, and the assumed steam pressure and the obtained calculation result are compared, when the error is less than 5%, the iteration calculation is stopped, otherwise, the obtained steam pressure and temperature value are used for iteration calculation;

[0065] According to the hydraulic and thermal coupling calculation, the pressure and temperature of each node of the entire pipe network are calculated;

[0066] The node temperature and pressure are known, and the pipe section generated condensate amount is calculated:

[0067] h in = h out + Q sr + Q ln

[0068] Q ln = m ln · r qh

[0069] wherein h in is the enthalpy of the inlet steam, kJ / kg; h out is the enthalpy of the outlet steam, kJ / kg; Q ln is the heat loss of the condensate, kJ; Q sr is the heat dissipation of the pipe section, kJ; m ln is the mass of the condensate, kg; r qh is the latent heat of vaporization, kJ / kg;

[0070] The results obtained by the pipe network coupling calculation model are stored in a database.

[0071] Preferably, the A4 further comprises: establishing a steam conversion distribution calculation model, the steam conversion distribution calculation including high-pressure steam, medium-pressure steam and low-pressure steam distribution calculation. The conditions of the steam conversion distribution calculation are known steam user demand, pipe network topological relationship, waste heat source recovery amount and steam power equipment steam production capacity, and the three steam distribution calculation processes are consistent, wherein the high-pressure steam distribution calculation is as follows:

[0072] Steam supply model of the jth high-pressure steam target device:

[0073] U h,j =∑a i,j S h,i b i,j

[0074] wherein U h,j is the steam demand of the jth high-pressure steam target device; a i,j is whether the jth high-pressure steam target device is connected with the ith high-pressure steam source device, a i,j = 1 indicates that steam can be supplied, a i,j = 0 indicates that steam cannot be supplied; S h,i is the maximum high-pressure steam supply amount of the ith high-pressure steam source device; and b i,j is the proportion of the high-pressure steam amount provided by the ith high-pressure steam source device for the jth high-pressure steam target device to the maximum supply capacity of the ith high-pressure steam source device.

[0075] According to the demand of the high-pressure steam user, a high-pressure steam demand vector is constructed:

[0076] U h = [U h,1 , U h,2 , …, U h,n ] T

[0077] wherein n is the number of users of high-pressure steam.

[0078] Preferably, the high-pressure steam distribution calculation further comprises:

[0079] According to the high-pressure steam recovery amount of process waste heat, a high-pressure steam recovery vector R is constructed h = [R h,1 , R h,2 , …, R h,m ] T , m is the number of devices that can recover process waste heat steam; R h,i is the high-pressure steam recovery amount of the i-th waste heat steam recovery device;

[0080] According to the high-pressure steam pipe network topological relationship, a high-pressure steam accessibility matrix A is constructed h = (a i,j ) m×n ; a high-pressure steam distribution matrix C is constructed h = (a i,j *b i,j ) n×m ;

[0081] A linear equation U h = C h ×R h is solved;

[0082] A group of feasible solutions B h = (b i,j ) n×m is obtained, and it is determined whether the recoverable amount of high-pressure steam is greater than the total demand amount of steam. If then the excess high-pressure steam is converted into medium-pressure steam through a temperature-reducing and pressure-reducing device, and the conversion distribution ends. If the equation has no solution, it indicates that the high-pressure steam recovery amount of the process does not meet the demand of the steam target user, and at this time, a standby steam source needs to be connected. If all standby steam sources have been started, it indicates that the steam user demand exceeds the steam generation capacity of the entire steel plant, and external steam needs to be purchased or the production plan needs to be adjusted. If not all standby steam sources have been started, the standby steam sources need to be started according to the priority, that is, the number of steam source devices is m+1, and R h is an (m+1)×1 order vector R' h = [R h,1 , R h,2 , …, R h,m , R h,m+1 ] T , C h is an n×(m+1) order matrix C' h = (a i,j *b i,j ) n×(m+1) , and the linear equation Uh =C h x R h ;

[0083] The high-pressure steam distribution calculation ends.

[0084] Preferably, the A4 further comprises: sequentially calculating the distribution scheme of the medium-pressure steam and the low-pressure steam, and calculating the steam quantity for low-quality use;

[0085] A steam scheduling optimization model is established according to steam conversion, and a target function is the sum of actual cost of steam production, cost of enterprise self-power generation, cost of purchased electricity, cost of purchased water, and cost of energy level mismatch;

[0086]

[0087] Wherein, l is steam type, divided into high-pressure steam, medium-pressure steam and low-pressure steam; s is steam source; u is steam user; C s is actual cost of steam production of the steam source, yuan / t; Q s,l is steam production quantity of the steam source, t / h; is self-power generation cost of the steam turbine, yuan / (kW·h); is self-power generation quantity, kW; is purchased electricity cost, yuan / (kW·h); is purchased electricity quantity, kW; is purchased water cost, yuan / t; is purchased water demand, t / h; C Δ is unit energy level difference penalty, yuan / t; Omega u,l is energy level difference; R u,l is converted steam quantity of the user, t / h;

[0088] Constraint conditions include constraints of production equipment, working ranges of boiler, steam turbine, seawater desalination and other equipment are set upper and lower limits according to actual conditions; pipe network constraints, total steam quantity of each steam pipe network is guaranteed to balance in and out of the pipe network; production constraints of each production process of the steel enterprise, in different production stages, steam, electricity, water and other secondary energy demands are met to guarantee normal operation of each process; steam turbine extraction and power generation constraints; constraints of medium replacement relationship;

[0089] A Python software programming solver CONOPT is used for solving, a steam distribution scheme with the lowest economic operation cost is obtained, a scheduling scheme corresponding to the steam distribution scheme is displayed in the form of a chart, and a comparison and analysis of results before and after optimization are carried out, and the scheduling scheme is saved to a database.

[0090] (Three) beneficial effects

[0091] Beneficial effects of the present application are:

[0092] The scheme provided by the application can improve the efficient use of steam.

[0093] Specifically, the digital twin technology is applied to the steam system of a steel enterprise, combined with the physical entity and data information of the steam system, to realize holographic mapping of the physical entity of the steam system to a virtual object, compare the actual optimization result with the theoretical optimization result, perform error analysis, and realize the synchronization and interaction of the physical entity and the virtual model through continuous iteration of the virtual model.

[0094] A steam distribution conversion calculation model for different qualities is established to evaluate the high-quality and low-use of steam in the steel enterprise and provide a basis for the optimal scheduling of steam distribution.

[0095] For the mathematical programming model, a solver CONOPT is called to solve by using Python software programming, so as to obtain the optimal deployment scheme of the running cost and provide necessary technical support for the digital transformation of the steel enterprise.

[0096] The application comprehensively considers the problems existing in the running process of the steam system of the steel enterprise and the efficient use and optimal scheduling of steam, combines the digital twin technology, and proposes a steam pipe network system simulation and optimal scheduling technology based on digital twin.

[0097] The steam pipe network system simulation and optimal scheduling technology based on digital twin proposed by the application can realize the synchronization and interaction of the physical entity and the virtual model through continuous iteration of the virtual model, effectively evaluate the use of steam in the steel enterprise, and simultaneously give a steam optimal scheduling scheme from the running cost point of view. BRIEF DESCRIPTION OF DRAWINGS

[0098] Figure 1 A flowchart of the steam pipe network simulation system optimal scheduling method based on digital twin provided by the application is shown in the figure;

[0099] Figure 2 The structure diagram of the steam optimal scheduling system based on digital twin in the embodiment of the steam pipe network simulation system optimal scheduling method based on digital twin provided by the application is shown in the figure;

[0100] Figure 3 The schematic diagram of the interaction of the physical entity and the virtual model of the steam pipe network system in the embodiment of the steam pipe network simulation system optimal scheduling method based on digital twin provided by the application is shown in the figure;

[0101] Figure 4 The high-pressure steam conversion distribution calculation process in the embodiment of the steam pipe network simulation system optimal scheduling method based on digital twin provided by the application is shown in the figure. DETAILED DESCRIPTION

[0102] In order to better explain the present application, so as to be understood, the present application is described in detail below by specific embodiments in combination with the drawings.

[0103] As Figures 1-4 shown: a steam pipe network simulation system optimization scheduling method based on digital twinning is disclosed in this embodiment, including the following steps:

[0104] S1, obtaining real-time dynamic data information of the entity steam pipe network system;

[0105] S2, inputting the obtained real-time dynamic data information into the digital twinning steam pipe network simulation system, and the digital twinning steam pipe network simulation system performs virtual synchronous iteration with the entity steam pipe network system according to the real-time dynamic data information, and outputs a scheduling scheme;

[0106] S3, the decision maker decides whether to execute according to experience and actual production conditions;

[0107] If executed, the entity steam pipe network system is executed by the executor to execute the scheduling scheme;

[0108] If not executed, the scheduling scheme is modified and input into the digital twinning steam pipe network simulation system for simulation verification;

[0109] S4, after the execution of the scheduling scheme, the real-time monitoring system collects data of the entity steam pipe network system, and transmits the collected real-time dynamic data information to the digital twinning steam pipe network simulation system for updating and improving the digital twinning steam pipe network simulation system.

[0110] The method in this embodiment applies digital twinning technology to the steam pipe network system of a steel enterprise, combines with the physical entity and data information of the steam system, realizes holographic mapping of the physical entity of the steam pipe network system to a virtual object, completes calculation of the steam pipe network related parameters, calculates the transformation and distribution of steam, at the same time, establishes a steam supply and demand optimization scheduling model of the steel enterprise, realizes quality-based distribution and efficient use of steam, solves the problems of high-quality low-use and steam dissipation of the steam of the steel enterprise and other industrial enterprises, and realizes energy saving and emission reduction of the steam system.

[0111] The S1 in this embodiment further includes: establishing a digital twinning steam pipe network simulation system;

[0112] including the following steps:

[0113] A1, obtaining steam production and consumption historical data, steam pipe network information, steam power boiler and related parameters of waste heat boiler of a steel enterprise, determining production plan and maintenance plan in a scheduling period;

[0114] A2, training and condition recognition of the working condition classification model, and preprocessing the historical data of steam production and consumption of the steel enterprise in A1 through wavelet filtering, data repair, normalization, standardization and other methods;

[0115] A3, virtually modeling the entity steam pipe network system of the steel enterprise, corresponding to the physical entity, establishing corresponding virtual models of the steam system from the supply side, the transportation side and the demand side of the steam;

[0116] A4, on the basis of the steam pipe network simulation model of digital twinning, simulating, optimizing, decision-making and other operations according to related theories and methods, establishing steam optimization, calculating the optimal steam distribution scheme with the lowest economic operation cost as the target and saving it to the database.

[0117] In the embodiment, A1 further includes: obtaining the historical data of steam production and consumption, steam pipe network information, related parameters of steam power boilers and waste heat boilers, production plans and maintenance plans of the enterprise through the enterprise comprehensive data integration platform server;

[0118] The historical data of steam production and consumption includes: steam production of power boilers and waste heat boilers, steam consumption of generator units, and steam consumption of production and life of the steel enterprise;

[0119] The steam pipe network information includes: topological information, pipe length, pipe diameter, pipe section flow, pipe section drainage flow, valves, pipe section import and export pressure and temperature, pipe fittings, resistance coefficient, insulation layer material and thickness.

[0120] The embodiment A2 further includes the following steps:

[0121] A201, reconfiguring data by using vector space reconstruction method, matching working condition labels for each data according to different production working condition records, taking the reconfigured data as input data and the data labels as output data to form a training data set;

[0122] A202, classifying the data set by using training neural network technology, and obtaining model parameters by using error back propagation algorithm;

[0123] A203, collecting real-time data, taking the data after data preprocessing and vector space reconstruction as model input data, and obtaining the output data label as the current production working condition;

[0124] A204, combining the current production working condition and the production plan and maintenance plan in A1 to determine the steam production and consumption in the future scheduling period.

[0125] The embodiment A3 further includes: establishing a steam generating equipment model, the steam generating equipment including steam power boilers and waste heat boilers of each process;

[0126] comprising the following steps:

[0127] (1) Steam boiler steam generation capacity:

[0128]

[0129] wherein, G b is the steam generation capacity of the boiler per unit of time, t / h; η b is the thermal efficiency of the steam boiler, %; k is the fuel type; B i is the consumption of the i-th fuel, t / h; b i is the i-th fuel's reduced coal coefficient, kgce / t; h s is the steam enthalpy value generated by the steam boiler, kJ / t; h w is the steam boiler feedwater enthalpy value, kJ / t;

[0130] (2) Waste heat boiler including dry quenching waste heat boiler, sintering waste heat boiler, sintering waste heat boiler, converter waste heat boiler, steel rolling waste heat boiler, the steam generation capacity of the waste heat boiler is related to the boiler thermal efficiency, feedwater parameters, steam parameters, heat transfer medium and other factors, and the steam generation capacity of the converter waste heat boiler is:

[0131]

[0132] wherein, is the steam generation capacity of the converter waste heat boiler per unit of time, t / h; t1 is the temperature of the flue gas entering the waste heat boiler, ℃; t2 is the temperature of the flue gas leaving the waste heat boiler, ℃; c p1 is the specific heat capacity of the flue gas at t1, kJ / (m 3 ·℃); c p2 is the specific heat capacity of the flue gas at t2, kJ / (m 3 ·℃); is the sum of the flue gas generated by the carbon oxidation of the carbon-containing materials in the molten iron, m 3 / t; R is the combustion heat value of CO, kJ / m 3 ; is the thermal efficiency of the converter waste heat boiler, %; α is the distribution ratio of CO and CO2 produced by carbonization, %; λ k is the air suction coefficient, the ratio of the actual air suction amount to the theoretical air required for complete combustion of the converter flue gas, %; is the specific enthalpy of steam generation, kJ / t; is the specific enthalpy of feedwater, kJ / t.

[0133] The A3 in the embodiment further comprises: establishing a steam consumption system model;

[0134] Obtain the process requirement information of steam of all production users in the whole steel enterprise, including pressure, temperature, summer steam consumption, winter steam consumption, average steam consumption, maximum steam consumption, and use system, and record and process through a database.

[0135] The A3 in the embodiment further includes establishing a steam delivery model.

[0136] The method includes the following steps:

[0137] Obtain the topological structure of the steam pipe network of the enterprise and related historical data records;

[0138] Establish a pipe network basic information database, and store specific parameters such as the topological structure, pipe length, pipe diameter, flow of each pipe section, pipe section drainage, number of valves, number of pipe fittings, resistance coefficient, thermal insulation material, thickness of thermal insulation layer, pressure and temperature of each node, dynamic viscosity, correction coefficient, absolute roughness of pipe section, steam density, and thermal conductivity of each node;

[0139] Simplify the steam pipe network into a directed graph composed of pipe sections and nodes, obtain the topological structure of the pipe network, and describe the topological relationship of the pipe network by using an association matrix of pipe sections and nodes, divide the steam source point, internal nodes, and user nodes into reference nodes, calculation nodes, and independent nodes;

[0140] When a pipe section is too long, the calculation will introduce a large error, and for a long pipe section, a method of adding a virtual node is needed to segment the long pipe section;

[0141] Convert the actual pipe network into a mathematical model, and based on the node flow conservation equation, pressure drop calculation formula, temperature drop calculation formula, and IAPWS-IF97 formula, combine the dynamic viscosity, flow velocity, and Reynolds number calculation formula in fluid mechanics to establish a steam pipe network hydraulic and thermal coupling calculation model, wherein the hydraulic and thermal calculation of a single pipe section is as follows:

[0142] First, assume the pressure and temperature of steam at the outlet of the pipe section, and calculate the steam density by using the IAPWS-IF97 formula:

[0143]

[0144] In the formula, is the partial derivative of the ideal gas part of the specific Gibbs energy with respect to the specific pressure in a dimensionless form, is the partial derivative of the excess part of the specific Gibbs energy with respect to the specific pressure in a dimensionless form;

[0145] Then, the intermediate parameters steam flow velocity, dynamic viscosity, and Reynolds number are obtained:

[0146]

[0147] Where, v is the steam flow rate, m / s; d is the equivalent diameter of the pipe section, m; G is the flow rate of the pipe section, m 3 / s;

[0148]

[0149]

[0150] Where, μ is the dynamic viscosity, 10 -6 ·m 2 ·s -1 ; n i , I i , J i is the dynamic viscosity coefficient; T is the steam temperature, K;

[0151]

[0152] Where, R e is the Reynolds number, ρ is the steam density, kg / m 3 ; v is the steam flow rate, m / s; μ is the steam dynamic viscosity, 10 -6 ·m 2 ·s -1 ;

[0153] The pipe section pressure drop and temperature drop are then calculated, and the pipe section pressure drop calculation formula is:

[0154]

[0155] Where, Δp is the pressure drop of the pipe section, Pa; d is the inner diameter of the pipe section, m; β is the local pressure drop correction coefficient of the pipe section; l is the length of the pipe section, m; l e is the equivalent length of the valves, bends and other pipe fittings contained in the pipe section, m; G is the flow rate of the pipe section, kg / s; k is the equivalent roughness of the pipe section, m; R e is the Reynolds number;

[0156] The temperature drop calculation formula is:

[0157]

[0158] Where, Δt is the temperature drop of the pipe section, ℃; η h is the correction factor; t in is the steam temperature at the inlet of the pipe section, ℃; t out is the steam temperature at the outlet of the pipe section, ℃; t f is the ambient temperature, ℃; h1 is the inner side convective heat transfer coefficient; h2 is the outer side convective heat transfer coefficient; d2 is the outer diameter of the insulation layer, m; d1 is the inner diameter of the steam pipe, m; l is the pipe length, m; λ is the thermal conductivity of the insulation layer, W / (m·℃);

[0159] According to the pressure drop of the pipe section, the outlet pressure is obtained, the assumed steam pressure is compared with the obtained calculation result, when the error is less than 5%, the iteration calculation is stopped, otherwise, the iteration calculation is continued with the obtained steam pressure and temperature value;

[0160] According to the hydraulic and thermal coupling calculation, the pressure and temperature of each node of the whole pipe network are calculated;

[0161] The temperature and pressure of each node are known, the condensed water amount generated by the pipe section is calculated:

[0162] h in =h out +Q sr +Q ln

[0163] Q ln =m ln ·r qh

[0164] In the formula, h in is the inlet steam enthalpy value, kJ / kg; h out is the outlet steam enthalpy value, kJ / kg; Q ln is the condensed water heat loss amount, kJ; Q sr is the pipe section heat dissipation amount, kJ; m ln is the condensed water mass, kg; r qh is the vaporization latent heat, kJ / kg;

[0165] The result obtained by the pipe network coupling calculation model is stored in the database.

[0166] The A4 in the embodiment further includes: establishing a steam conversion distribution calculation model, the steam conversion distribution calculation includes high-pressure steam, medium-pressure steam and low-pressure steam distribution calculation. The condition of the steam conversion distribution calculation is that the steam user demand amount, the pipe network topological relation, the waste heat source recovery amount and the steam power equipment steam production capacity are known, the three steam distribution calculation processes are consistent, wherein, the high-pressure steam distribution calculation is as follows:

[0167] Steam supply model of the jth high-pressure steam target device:

[0168] U h,j =Σa i,j S h,i b i,j

[0169] In the formula, U h,j is the steam demand amount of the jth high-pressure steam target device; a i,j is whether the jth high-pressure steam target device and the ith high-pressure steam source device are communicated, a i,j = 1 indicates that steam can be supplied, a i,j = 0 indicates that steam cannot be supplied; Sh,i Let b represent the maximum high-pressure steam supply of the i-th high-pressure steam source device; i,j The proportion of high-pressure steam provided by the i-th high-pressure steam source device to the j-th high-pressure steam target device relative to its own maximum supply capacity;

[0170] Based on the demand from high-pressure steam users, construct a high-pressure steam demand vector:

[0171] U h =[U h,1 U h,2 …U h,n ] T

[0172] Where n is the number of users of high-pressure steam.

[0173] The high-pressure steam distribution calculation described in this embodiment also includes:

[0174] Based on the amount of high-pressure steam recovered from waste heat in the process, construct a high-pressure steam recovery vector R. h =[R h,1 ,R h,2 …R h,m ] T m represents the number of devices capable of recovering waste heat steam from the process; R h,i Let be the high-pressure steam recovery rate of the i-th waste heat steam recovery device;

[0175] Based on the topology of the high-pressure steam pipeline network, construct a high-pressure steam accessibility matrix, A. h =(a i,j ) m×n Construct the high-pressure steam distribution matrix C h =(a i,j *b i,j ) n×m ;

[0176] Solve the linear equation U h =C h ×R h ;

[0177] Find a feasible solution B h =(b i,j ) n×m Determine whether the recoverable amount of high-pressure steam is greater than the total steam demand. If the equation has a solution, the surplus high-pressure steam is converted into medium-pressure steam through a temperature and pressure reducing device, and the conversion distribution ends; if the equation has no solution, it indicates that the high-pressure steam recovery amount of the process cannot meet the demand of the steam target user, at which time a standby steam source needs to be connected, and it is determined whether the standby steam source in the steel plant is started. If all the standby steam sources have been started, it indicates that the steam user demand exceeds the steam production capacity of the entire steel enterprise, and steam needs to be purchased from outside or the production plan needs to be adjusted; if not all the standby steam sources have been started, the standby steam sources need to be started according to the priority of the standby steam sources, that is, the number of steam source devices is m+1, and R h is an (m+1)×1 order vector h h,1 h,2 h,m h,m+1 T is an n×(m+1) order matrix h h i,j i,j n×(m+1) , and jump to solve the linear equation h =C h ×R h .

[0178] The high-pressure steam distribution calculation ends.

[0179] The A4 in the embodiment further includes: sequentially calculating the distribution schemes of the medium-pressure steam and the low-pressure steam, and calculating the steam amount of high quality and low use;

[0180] According to the steam conversion, a steam dispatching optimization model is established, and the objective function is the sum of the actual cost of steam production, the cost of enterprise self-power generation, the cost of purchased power, the cost of purchased water, and the cost of energy level mismatch;

[0181]

[0182] wherein, l is the steam type, which is divided into high-pressure steam, medium-pressure steam and low-pressure steam; s is the steam source; u is the steam user; C s is the actual cost of steam production of the steam source, yuan / t; Q s,l is the steam production amount of the steam source, t / h; is the self-power generation cost of the steam turbine, yuan / (kW·h); is the self-power generation amount, kW; is the purchased power cost, yuan / (kW·h); is the purchased power amount, kW; is the purchased water cost, yuan / t; is the purchased water demand, t / h; C Δ is the unit energy level difference penalty, yuan / t; Ω u,l is the energy level difference; and R​​​​​​​​​u,l The converted steam amount t / h is used for the user;

[0183] The constraints include production equipment constraints, working ranges of boiler, steam turbine, seawater desalination and other equipment are set with upper and lower limits according to actual conditions; pipe network constraints, the total amount of steam entering and leaving the steam pipe network of each stage is balanced; production constraints of each production process of the steel enterprise, the demand for secondary energy such as steam, electricity and water is met in different production stages to ensure the normal operation of each process; steam turbine extraction and power generation constraints; medium replacement relationship constraints;

[0184] A Python software programming solver CONOPT is used for solving, a steam distribution scheme with the lowest economic operation cost is obtained, a corresponding scheduling scheme is displayed in the form of a chart, and a comparison and analysis of results before and after optimization is performed, and the scheduling scheme is saved to a database.

[0185] In the embodiment, a steam pipe network system simulation optimization scheduling method based on digital twinning is disclosed, by using the method, the synchronization and interaction of the physical entity and the virtual model can be realized by continuously iterating the virtual model; the use of steam in the steel enterprise is effectively evaluated, and a steam optimization scheduling scheme is given from the perspective of operation cost.

[0186] The technical principles of the present application are described above in combination with specific embodiments, and these descriptions are only for explaining the principles of the present application and cannot be interpreted in any way as a limitation on the scope of protection of the present application. Based on the explanations herein, those skilled in the art can think of other specific embodiments of the present application without creative labor, and these embodiments will fall within the scope of protection of the present application.

Claims

1. A method for optimizing the scheduling of a steam pipeline network simulation system based on digital twins, characterized in that, Includes the following steps: S1. Obtain real-time dynamic data information of the physical steam pipeline network system; S2. Input the obtained real-time dynamic data information into the digital twin steam pipeline network simulation system. The digital twin steam pipeline network simulation system performs virtual synchronous iteration with the physical steam pipeline network system based on the real-time dynamic data information and outputs a scheduling scheme. S3. Decision-makers decide whether to implement the plan based on their experience and actual production conditions. S4. After the scheduling plan is executed, the real-time monitoring system collects data from the physical steam pipeline network system and transmits the collected real-time dynamic data information to the digital twin steam pipeline network simulation system to update and improve the digital twin steam pipeline network simulation system. The preceding step, S1, also includes: establishing a digital twin simulation system for the steam pipeline network; Includes the following steps: A1. Obtain historical data on steam production and consumption of steel enterprises, steam pipeline network information, relevant parameters of steam power boilers and waste heat boilers, and determine the production plan and maintenance plan within the scheduling cycle. A2. Preprocess the historical steam production and consumption data of steel enterprises in A1; A3. To create a virtual model of the physical steam pipeline network system of steel enterprises, corresponding to the physical entity, and to establish corresponding virtual models of the steam system from the supply side, transmission side and demand side of steam. A4. Based on the establishment of a digital twin steam pipeline network simulation model, simulation, optimization, and decision-making operations are carried out according to relevant theories and methods. Steam optimization is established, and the optimal steam allocation scheme is calculated with the goal of minimizing economic operating costs and saved to the database. The A4 also includes: establishing a steam conversion and distribution calculation model, which includes high-pressure steam, medium-pressure steam, and low-pressure steam distribution calculation; the conditions for steam conversion and distribution calculation are known steam user demand, pipeline topology, waste heat recovery amount, and steam power equipment steam production capacity, and the calculation process for the three types of steam distribution is consistent; The high-pressure steam distribution calculation is as follows: No. Steam supply model for a high-pressure steam target device: ； in, For the first Steam demand of a high-pressure steam target device; For the first The high-pressure steam target equipment and the first Are the high-pressure steam source devices connected? This indicates that gasoline is available. This indicates that steam is not available. To indicate the first The maximum high steam supply capacity of each high-pressure steam source device; For the first The first high-pressure steam source device is the... The proportion of high-pressure steam provided by a target high-pressure steam device to its maximum supply capacity; Based on the demand from high-pressure steam users, construct a high-pressure steam demand vector: ； in, The number of users of high-pressure steam; The high-pressure steam distribution calculation also includes: Based on the amount of high-pressure steam recovered from waste heat in the process, a high-pressure steam recovery vector is constructed. , The number of devices capable of recovering waste heat steam from the process; For the first High-pressure steam recovery capacity of each waste heat steam recovery device; Based on the topology of the high-pressure steam pipeline network, a high-pressure steam accessibility matrix is ​​constructed. Construct a high-pressure steam distribution matrix ; Solve linear equations ; Find a feasible solution Determine whether the recoverable amount of high-pressure steam is greater than the total steam demand. If the excess high-pressure steam is converted into medium-pressure steam via a desuperheating and pressure-reducing device, the conversion and distribution process is complete. If the equation has no solution, it indicates that the high-pressure steam recovery rate of the process does not meet the demand of the target steam user. In this case, a backup steam source needs to be connected. It is necessary to determine whether the backup steam sources in the steel plant have been activated. If all backup steam sources have been activated, it indicates that the steam user demand exceeds the steam generation capacity of the entire steel enterprise, and steam needs to be purchased externally or the production plan needs to be adjusted. If not all backup steam sources have been activated, the backup steam sources need to be activated according to their priority, i.e., the number of steam source devices is [number missing]. , for rank vector , for 1-th order matrix Jump to solving the linear equation ; High-pressure steam distribution calculation complete; The A4 also includes: calculating the distribution schemes of medium-pressure steam and low-pressure steam in sequence, and calculating the amount of high-quality, low-use steam; A steam dispatch optimization model is established based on steam conversion. The objective function is the sum of the actual cost of steam production, the cost of self-generated electricity, the cost of purchased electricity, the cost of purchased water, and the cost caused by energy level mismatch. The costs arising from the energy level mismatch include: the unit energy level difference penalty, the energy level difference, and the product of the amount of steam converted by the user.

2. The method according to claim 1, characterized in that, A1 also includes: obtaining historical data on enterprise steam production and consumption, steam pipeline network information, relevant parameters of steam power boilers and waste heat boilers, production plans and maintenance plans through the enterprise integrated data integration platform server; Historical data on steam production and consumption include: steam generation from power boilers and waste heat boilers, steam consumption from generator sets, and steam consumption for production and daily life in steel enterprises. Steam pipeline information includes: topology information, pipe length, pipe diameter, pipe segment flow rate, pipe segment drainage flow rate, valves, inlet and outlet pressure and temperature of pipe segments, number of pipe fittings, resistance coefficient, insulation material, and thickness.

3. The method according to claim 2, characterized in that, A2 further includes the following steps: A201. Reconstruct the data using the vector space reconstruction method. Match the working condition label to each data according to different production working condition records. Use the reconstructed data as input data and the data label as output data to form a training dataset. A202. Use training neural network technology to classify the dataset, and use the backpropagation algorithm to obtain the model parameters; A203. Collect real-time data, and after data preprocessing and vector space reconstruction, use it as model input data. The resulting output data label is the current production condition. A204. Based on the current production conditions and the production and maintenance plans in A1, determine the steam production and consumption during the future scheduling cycle.

4. The method according to claim 3, characterized in that, The A3 also includes: establishing a model of steam generating equipment, which includes steam-powered boilers and waste heat boilers for each process.

5. The method according to claim 4, characterized in that, A3 also includes: establishing a steam consumption system model; Obtain information on the process requirements of all production users in the entire steel enterprise for steam, including pressure, temperature, summer steam consumption, winter steam consumption, average steam consumption, maximum steam consumption, and usage system, and process this information through a database.

6. The method according to claim 5, characterized in that, A3 also includes: establishing a steam transport model; Includes the following steps: Obtain the enterprise's steam pipeline network topology and related historical data records; Establish a pipeline network information database to store specific parameters such as pipeline topology, pipe length, pipe diameter, flow rate of each pipe segment, drainage capacity of each pipe segment, number of valves, number of pipe fittings, resistance coefficient, insulation material, insulation layer thickness, pressure, temperature, dynamic viscosity, correction factor, absolute roughness of pipe segment, steam density, and thermal conductivity. The steam pipeline network is simplified into a directed graph consisting of pipe segments and nodes to obtain the network topology. The pipe segment-node correlation matrix is ​​used to describe the network topology. The steam source point, internal nodes and user nodes are set as reference nodes, calculation nodes and independent nodes respectively. When the pipe segment is too long, the calculation will introduce a large error. For long pipe segments, it is necessary to use the method of adding virtual nodes to divide the long pipe segment into segments. The actual pipeline network is transformed into a mathematical model. Based on the nodal flow conservation equation, pressure drop calculation formula, temperature drop calculation formula and IAPWS-IF97 formula, combined with the dynamic viscosity, flow velocity and Reynolds number calculation formula in fluid mechanics, a hydraulic and thermodynamic coupling calculation model of steam pipeline network is established. The results obtained from the pipeline network coupling calculation model are stored in the database.

7. The method according to claim 1, characterized in that, The constraints include those related to production equipment, such as setting upper and lower limits for the operating range of boilers, steam turbines, and seawater desalination equipment based on actual conditions; pipeline network constraints, ensuring a balance of total steam volume in and out of each level of the steam pipeline network; production constraints for each production process in the steel enterprise, ensuring that the demand for secondary energy sources such as steam, electricity, and water is met at different production stages to guarantee the normal operation of each process; constraints related to steam extraction and power generation from steam turbines; and constraints related to medium substitution relationships. The solution is obtained using the CONOPT software program in Python, which yields the steam distribution scheme with the lowest economic operating cost. The corresponding scheduling scheme is displayed in the form of a chart, and a comparative analysis of the results before and after optimization is performed. The scheduling scheme is then saved to the database.

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