CN114388162A - Helium-xenon cooling reactor control method and device and electronic equipment - Google Patents
Helium-xenon cooling reactor control method and device and electronic equipment Download PDFInfo
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Abstract
The invention provides a control method and a device for a helium-xenon cooled reactor and electronic equipment, and relates to the technical field of nuclear reactors, wherein the control method for the helium-xenon cooled reactor comprises the following steps: monitoring the operation state information of the helium-xenon cooled reactor in the operation process of the helium-xenon cooled reactor, and acquiring a pre-constructed mathematical model of the helium-xenon cooled reactor; performing numerical simulation on the mathematical model based on the current running state information to obtain a numerical simulation result; and adjusting various control parameters of the helium-xenon cooled reactor based on the numerical simulation result so as to enable the power generation power of the helium-xenon cooled reactor to reach the preset power generation power. The invention can adaptively control each control parameter of the reactor according to the running state of the reactor, and improves the control reliability of the helium-xenon cooling reactor.
Description
Technical Field
The invention relates to the technical field of nuclear reactors, in particular to a helium-xenon cooled reactor control method and device and electronic equipment.
Background
At present, in order to enable a helium xenon cooled reactor to stably operate for a long time on the basis of meeting load requirements, control parameters of the nuclear reactor need to be rapidly adjusted in real time according to load changes (such as power generation changes), so that the power generation power of the reactor can follow the set power generation power. Because the mathematical model of the reactor has the characteristics of dynamic uncertainty, nonlinearity, strong coupling among main parameters and the like, how to realize the self-adaptive reliable control of the helium-xenon cooled reactor becomes a problem to be solved urgently.
Disclosure of Invention
In view of the above, an object of the present invention is to provide a method and an apparatus for controlling a he-xe cooled reactor, and an electronic device, which can adaptively control each control parameter of the reactor according to an operating state of the reactor, thereby improving the reliability of controlling the he-xe cooled reactor.
In order to achieve the above purpose, the embodiment of the present invention adopts the following technical solutions:
in a first aspect, an embodiment of the present invention provides a method for controlling a helium-xenon cooled reactor, including:
monitoring the operation state information of the helium-xenon cooled reactor in the operation process of the helium-xenon cooled reactor, and acquiring a pre-constructed mathematical model of the helium-xenon cooled reactor; the operation state information comprises main loop flow, precooler side flow and reactor core reflector drawing distance; performing numerical simulation on the mathematical model based on the current running state information to obtain a numerical simulation result; and adjusting each control parameter of the helium-xenon cooling reactor based on the numerical simulation result so as to enable the power generation power of the helium-xenon cooling reactor to reach the preset power generation power.
Further, embodiments of the present invention provide a first possible implementation manner of the first aspect, wherein,
the step of performing numerical simulation on the mathematical model based on the current operating state information to obtain a numerical simulation result includes: performing thermodynamic cycle calculation on the helium-xenon cooled reactor based on the current operating state information to obtain the reactor core inlet temperature and the reactor core outlet temperature; performing thermal calculation on the core region based on the core inlet temperature and the core outlet temperature to obtain the temperature of each part in the core; performing neutron physical calculation on the reactor core region based on the temperature of each part inside the reactor core to obtain the current power generation power of the helium-xenon cooled reactor in the current operation state.
Further, an embodiment of the present invention provides a second possible implementation manner of the first aspect, where the numerical simulation result includes a current generated power, and the step of adjusting each control parameter of the helium xenon cooled reactor based on the numerical simulation result so that the generated power of the helium xenon cooled reactor reaches a preset generated power includes: calculating each control parameter of the helium-xenon cooled reactor at the next moment based on the current power generation power and the preset power generation power, and controlling each device of the helium-xenon cooled reactor to operate based on the control parameters so as to enable the power generation power of the helium-xenon cooled reactor to reach the preset power generation power; the control parameters comprise main loop flow, precooler side flow and reactor core reflector drawing distance.
Further, an embodiment of the present invention provides a third possible implementation manner of the first aspect, wherein the step of calculating each control parameter of the helium-xenon cooled reactor at a next time based on the current generated power and the preset generated power includes: and carrying out sensitivity analysis on the mathematical model based on the current generating power and the preset generating power, and determining a control parameter of the helium-xenon cooling reactor at the next moment.
Further, an embodiment of the present invention provides a fourth possible implementation manner of the first aspect, where the method for controlling a he-xenon cooled reactor further includes: performing state prediction on the helium-xenon cooling reactor based on a neural network and the running state information to obtain a state prediction result; and judging whether the state prediction result exceeds a preset physical thermal constraint, and if so, controlling the helium-xenon cooling reactor to execute an accident control step.
Further, an embodiment of the present invention provides a fifth possible implementation manner of the first aspect, where the method for controlling a he-xenon cooled reactor further includes: and if the state prediction result does not exceed the preset physical thermal constraints, returning to the step of executing the numerical simulation of the mathematical model based on the current operating state information to obtain a numerical simulation result.
Further, an embodiment of the present invention provides a sixth possible implementation manner of the first aspect, wherein the step of performing state prediction on the he-xe-cooled reactor based on a neural network and the operating state information to obtain a state prediction result includes: and inputting the generated power in the running state information into a neural network model, training the neural network model on line based on the generated power, and performing single-step prediction on the helium-xenon cooled reactor based on the neural network model to obtain a state prediction result.
In a second aspect, an embodiment of the present invention further provides a helium-xenon cooled reactor control apparatus, including: the monitoring module is used for monitoring the operation state information of the helium-xenon cooled reactor in the operation process of the helium-xenon cooled reactor and acquiring a pre-constructed mathematical model of the helium-xenon cooled reactor; the operation state information comprises main loop flow, precooler side flow and reactor core reflector drawing distance; the simulation module is used for carrying out numerical simulation on the mathematical model based on the current running state information to obtain a numerical simulation result; and the control module is used for adjusting each control parameter of the helium-xenon cooling reactor based on the numerical simulation result so as to enable the power generation power of the helium-xenon cooling reactor to reach the preset power generation power.
In a third aspect, an embodiment of the present invention provides an electronic device, including: a processor and a storage device; the storage means has stored thereon a computer program which, when executed by the processor, performs the method of any of the first aspects.
In a fourth aspect, the present invention provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, performs the steps of the method according to any one of the above first aspects.
The embodiment of the invention provides a control method, a device and electronic equipment for a helium-xenon cooled reactor, wherein the control method for the helium-xenon cooled reactor comprises the following steps: monitoring the operation state information of the helium-xenon cooled reactor in the operation process of the helium-xenon cooled reactor, and acquiring a pre-constructed mathematical model of the helium-xenon cooled reactor; the operation state information comprises main loop flow, precooler side flow and reactor core reflector drawing distance; performing numerical simulation on the mathematical model based on the current running state information to obtain a numerical simulation result; and adjusting various control parameters of the helium-xenon cooled reactor based on the numerical simulation result so as to enable the power generation power of the helium-xenon cooled reactor to reach the preset power generation power. According to the control method of the helium-xenon cooled reactor, the operation state information of the reactor is monitored in the operation process of the helium-xenon cooled reactor, numerical simulation is carried out according to the current operation state information of the reactor, and the control parameters of the reactor are adjusted according to the numerical simulation result, so that the power generation power of the reactor follows the preset power generation power, the self-adaptive control of each control parameter of the reactor according to the operation state of the reactor is realized, the load requirement is met, and the operation stability of the reactor is improved.
Additional features and advantages of embodiments of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of embodiments of the invention as set forth above.
In order to make the aforementioned and other objects, features and advantages of the present invention comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
FIG. 1 is a flow chart illustrating a control method for a helium-xenon cooled reactor according to an embodiment of the present invention;
FIG. 2 illustrates a schematic diagram of a Brayton cycle provided by an embodiment of the present invention;
FIG. 3 is a schematic diagram illustrating an Elman neural network structure provided by an embodiment of the present invention;
FIG. 4 illustrates an intelligent control flow diagram provided by an embodiment of the present invention;
FIG. 5 is a schematic diagram of a control apparatus for a HEXe-cooled reactor according to an embodiment of the present invention;
fig. 6 shows a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Reference numerals:
201-reactor; 202-turbine; 203-a regenerator; 204-precooler; 205-a compressor; 206-generator.
Detailed Description
To make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some, not all, embodiments of the present invention.
At present, in order to enable a nuclear reactor to operate in an expected mode or automatically operate according to certain criteria, many scholars research on reactor control, but few scholars relate to a small-sized helium-xenon cooled reactor, and the helium-xenon cooled small-sized reactor has the requirement of long-term unmanned operation, so that the requirement on control reliability is high. The embodiment of the invention provides a control method and device for a helium-xenon cooled reactor and electronic equipment, and the technology can be applied to improving the control reliability of the helium-xenon cooled reactor. The following describes embodiments of the present invention in detail.
The present embodiment provides a method for controlling a he-xe cooled reactor, which can be applied to electronic devices such as computers, and refer to a flowchart of the he-xe cooled reactor control method shown in fig. 1, the method mainly includes the following steps S102 to S106:
and S102, monitoring the operation state information of the helium-xenon cooled reactor in the operation process of the helium-xenon cooled reactor, and acquiring a pre-constructed mathematical model of the helium-xenon cooled reactor.
The operation state information comprises the main loop flow, the precooler side flow and the reactor core reflector drawing distance, and the main loop flow, the precooler side flow and the reactor core reflector drawing distance of the helium xenon cooled reactor are detected in real time or at preset time intervals.
The components of the reactor for control include: the turbine valve, the precooler cold side valve and the reactor core drawing type reflecting layer respectively control the main loop flow, the precooler side flow and the reactor core reflecting layer drawing distance correspondingly. And respectively detecting the current opening of a turbine valve and the current opening of a cold side valve of the precooler during the operation process of the helium-xenon cooled reactor to obtain the flow of the main loop and the side flow of the precooler.
The mathematical model of the helium-xenon cooled reactor is constructed based on the geometric parameters, the environmental heat dissipation coefficient, the wall friction factor and other parameters of the helium-xenon cooled reactor, that is, the geometric parameters, the environmental heat dissipation coefficient, the wall friction factor and other parameters of the helium-xenon cooled reactor are input into preset modeling software (such as Computational Fluid Dynamics (CFD) modeling software) for model construction, so as to obtain the mathematical model of the helium-xenon cooled reactor.
And step S104, carrying out numerical simulation on the mathematical model based on the current running state information to obtain a numerical simulation result.
And inputting the detected main loop flow, the front cooler side flow and the reactor core reflector drawing distance as input data into a mathematical model of the helium-xenon cooled reactor, and controlling the mathematical model of the helium-xenon cooled reactor to perform synchronous power generation simulation calculation so that the mathematical model of the helium-xenon cooled reactor simulates and calculates the reactor core thermal power in the operating state according to the current operating state information.
And S106, adjusting each control parameter of the helium-xenon cooled reactor based on the numerical simulation result so as to enable the power generation power of the helium-xenon cooled reactor to reach the preset power generation power.
In order to enable the reactor to stably operate for a long time and meet the load requirement, various control parameters of the helium-xenon cooling reactor are rapidly adjusted in real time according to the thermal power of the reactor core of the helium-xenon cooling reactor in the current operating state, so that the power generation power of the helium-xenon cooling reactor can follow the preset power generation power, namely the helium-xenon cooling reactor is controlled to be close to the power generation power set by a user.
The control parameters are parameters of controllable equipment in the reactor, and the control parameters comprise control parameters of a turbine valve, a precooler cold-side valve and a reactor core drawing type reflecting layer in the helium-xenon cooled reactor, namely the control parameters comprise main loop flow, precooler side flow and reactor core reflecting layer drawing distance. The above steps S104 to S106 are repeatedly executed to enable the generated power of the reactor to follow the generated power curve set by the user.
According to the control method for the helium-xenon cooled reactor, the operation state information of the reactor is monitored in the operation process of the helium-xenon cooled reactor, numerical simulation is carried out according to the current operation state information of the reactor, and the control parameters of the reactor are adjusted according to the numerical simulation result, so that the power generation power of the reactor follows the preset power generation power, the self-adaptive control of each control parameter of the reactor according to the operation state of the reactor is realized, the load requirement is met, and the operation stability of the reactor is improved.
In order to calculate and obtain the current generated power of the he-xe cooled reactor, this embodiment provides an implementation manner of performing numerical simulation on a mathematical model based on the current operating state information to obtain a numerical simulation result, which may be specifically executed with reference to the following steps (1) to (3):
step (1): and performing thermodynamic cycle calculation on the helium-xenon cooled reactor based on the current operating state information to obtain the inlet temperature and the outlet temperature of the reactor core.
Referring to the schematic of the brayton cycle shown in fig. 2, the he-xe cooled reactor includes a reactor 201, a turbine 202, a regenerator 203, a precooler 204, a compressor 205, and a generator 206. Based on the thermodynamic cycle relationship among the devices in the Brayton cycle schematic diagram and the working principle of each device, the thermodynamic cycle calculation is carried out on the helium-xenon cooled reactor by using the thermodynamic relationship formula to obtain the inlet and outlet temperatures of the reactor core.
Calculating the actual power consumption of the compressor based on the flow of the main loop, wherein the working principle of the compressor is as follows:
for adiabatic processes, the compressor inlet and outlet temperature relationship can be represented by the following equation:
wherein phi is4-5Is the mean adiabatic coefficient, T, of the compressor thermodynamic process4The actual inlet working medium temperature (also the outlet temperature of the precooler) P of the gas compressor4Is the actual inlet working medium pressure, P, of the compressor5For the actual outlet working-medium pressure of the compressor, i.e. P5The highest pressure of the whole circuit (the circulation circuit of 1-2-3-4-5-6-1 in FIG. 2), T5sThe temperature of the outlet working medium of the compressor in the heat insulation process.
The isentropic efficiency of the compressor is:
wherein H5sSpecific enthalpy of outlet working medium H in heat insulation process5Specific enthalpy, H, of outlet working medium of compressor in actual process4The specific enthalpy of the inlet working medium of the compressor in the actual process,
is the isobaric specific heat capacity of the compressor in the adiabatic process,
is the isobaric specific heat capacity, T, of the compressor in the actual process5The temperature of the outlet working medium of the compressor in the actual process is also the temperature of the inlet working medium at the cold side of the heat regenerator.The relation between the specific enthalpy and specific heat capacity of the working medium and the temperature and pressure can be found by a helium xenon gas property table. Obtaining a mechanical efficiency η of a compressorC,MThen actual power consumption W of the compressorCComprises the following steps:
wherein G is the mass flow of the working medium flowing through the compressor (namely the flow G of the main loop), and the mass flow in the thermodynamic cycle is consistent everywhere.
A heat regenerator:
conservation of energy in heat exchange between cold and hot side fluids of the regenerator:
wherein the content of the first and second substances,
is the average constant pressure specific heat capacity of the thermodynamic process 2-3 (the hot side of the regenerator) in figure 2,
the average constant pressure specific heat capacity of the thermodynamic process 5-6 (the cold side of the regenerator) in fig. 2, the specific heat capacity of the working medium can be obtained by inquiring a helium xenon gas property table. T is2The temperature of working medium at the inlet of the hot side of the heat regenerator is also the temperature of working medium at the outlet of the turbine; t is3The temperature of the working medium at the outlet of the hot side of the heat regenerator is also the temperature of the working medium at the inlet of the precooler; t is5The temperature of a working medium at the inlet of the cold side of the heat regenerator is also the temperature of a working medium at the outlet of the gas compressor; t is6The temperature of the working medium at the outlet of the cold side of the heat regenerator is also the temperature of the working medium at the inlet of the reactor core.
Heat regeneration degree alpha of heat regeneratorrDefined as the ratio of the actual heat return quantity of the cycle to the maximum heat return quantity which can be reached, the calculation formula of the heat return degree is as follows:
wherein H5Is the specific enthalpy of the working medium at the outlet of the gas compressor (also the specific enthalpy of the working medium at the inlet of the cold side of the heat regenerator), H6Is the specific enthalpy of the working medium at the outlet of the cold side of the heat regenerator (also the specific enthalpy of the working medium at the inlet of the reactor core), H2Is the specific enthalpy of the working medium at the outlet of the turbine (the specific enthalpy of the working medium at the inlet of the hot side of the heat regenerator), Cp,2Constant pressure specific heat capacity of working medium at hot side inlet of heat regenerator, Cp,5The constant pressure specific heat capacity of the working medium at the cold side inlet of the heat regenerator.
Turbine:
for turbines, their isentropic efficiency ηT,sThe constant entropy efficiency is defined as the ratio of the actual expansion work and the ideal expansion work of the working medium in the turbine, the larger the constant entropy efficiency is, the larger the actual work of the turbine is, the higher the thermal efficiency of the whole cycle is, and the calculation formula of the constant entropy efficiency is as follows:
wherein H2sSpecific enthalpy of outlet working medium H of turbine in heat insulation process2Is the specific enthalpy, H, of the outlet working medium of the turbine in the actual process1Is the specific enthalpy of the working medium at the inlet of the turbine,
for the isobaric specific heat capacity in the turbine adiabatic process,
is the isobaric specific heat capacity, T, of the turbine in practice2sFor the outlet working medium temperature, T, of the turbine in an adiabatic process2Outlet working medium temperature, T, of turbine in actual process1Is the inlet working medium temperature of the turbine.
Output power W of the turbineTThe calculation formula of (a) is as follows:
wherein eta isT,MThe mechanical efficiency of the turbine.
A precooler:
when the precooler is in a stable state, the heat exchange quantity of the hot side is equal to that of the cold side, and the working medium of the cold side is water.
Wherein the content of the first and second substances,
is the average constant pressure specific heat capacity of the thermodynamic process of the hot side of the precooler,
is the average constant pressure specific heat capacity, T, of the thermodynamic process of the cold side of the precooler22Outlet temperature of working medium water at cold side, T21The inlet temperature of working medium water at the cold side, G is the mass flow (namely the flow of the main loop) of the helium xenon working medium flowing through the hot side of the front cooler, GcIs the mass flow rate of water passing through the cold side of the precooler (i.e., the precooler side flow rate).
Based on the input main loop flow, the precooler side flow and the reactor core reflector drawing distance, the reactor core inlet and outlet temperature of the reactor can be calculated by the simultaneous upper formula.
Step (2): and performing thermal calculation on the core region based on the core inlet temperature and the core outlet temperature to obtain the temperature of each part in the core.
The core region includes three portions of a substrate, fuel elements, coolant channels, and cladding. The coolant channels and the cladding and fuel elements are regularly arranged in a matrix, the material of which is graphite. The most basic unit of the arrangement repetition is a regular hexagon structure, the fuel element adopts uranium carbide and has the radius of 7mm, the distance P between the center of the fuel element and the center of the coolant channel is 17mm, the radius of the coolant channel is 3mm, the thickness of the cladding is 1mm, and the material is Molybdenum alloy (Molybdenum-TZM, Ti-0.5, Zr-0.1 and C-0.03).
The fuel element is made of uranium carbide alloy, the matrix material is graphite, and the coolant channel cladding material is molybdenum alloy. Of the three above, the worst temperature tolerance is a molybdenum alloy, so in the preliminary thermodynamic cycle design, only the highest temperature of the coolant channel clad in the core is considered to be not more than 1400K.
Adopt single channel procedure to carry out thermotechnical calculation, the main relational expression who relates to includes:
1. the heat transfer relation of helium and xenon is that under the condition of same pipeline and same molar mass flow rate, the heat transfer coefficient h of mixed working medium and the heat transfer coefficient h of pure helium working mediumHeThe ratio is defined as relative heat transfer coefficient, which can be expressed by basic physical property parameters of the mixed working medium:
wherein mu is the viscosity of the mixed working medium, MmixIs the average molar mass of the working mixture, CpThe constant-pressure specific heat capacity of the mixed working medium is shown, lambda is the heat conductivity of the mixed working medium, and the calculation formula of the average molar mass of the mixed working medium is as follows:
Mmix＝αMHe+(1-α)MXe
where α is the volume fraction of helium, MHeThe molar mass of helium is 4g/mol, MXeThe molar mass of xenon is 131.29 g/mol.
Pure helium working medium heat transfer coefficient hHeThe calculation of (c) is based on an empirical relationship proposed by Taylor, which has a deviation from the experimental values within 10% for low heat flux heating and within 20% for high heat flux heating.
Wherein, c is 0.57- [1.59/(z/D)]Z is the distance from the inlet, D is the internal diameter of the pipe, Nub、Reb、PrbThe Knudsen number, Reynolds number and Prandtl number of the main stream are three dimensionless numbers, hHeIncluding in dimensionless numberingIn meaning, T can be solved from the empirical relationshipsAnd TbWall and mainstream temperatures, respectively.
2. The pressure drop relation of helium and xenon, the ratio of the heat transfer pressure drop of the mixed working medium to the pressure drop of the pure helium working medium under the condition of the same temperature, pressure and pipeline geometry and the same molar mass flow is defined as the relative pressure loss coefficient
The calculation formula of the relative pressure loss coefficient is as follows:
wherein mu is the viscosity of the mixed working medium, MmixIs the average molar mass of the mixed working medium, and Z is the compression coefficient of the mixed working medium. And for pure helium working fluid, when the Reynolds number is more than 3000, the pressure drop friction coefficient f in the pipeline can be calculated by the following formula:
wherein, ResIs the Reynolds number at the wall surface, the pressure drop delta p of the pure helium working mediumHeThe pressure drop friction coefficient f of the pure helium working medium can be used for obtaining in a single-channel program, and then the pressure drop of each part in the reactor core under the actual mixed working medium can be obtained.
The pressure loss mainly comprises four parts of the cold end pressure loss of the heat regenerator, the reactor core pressure loss, the hot end pressure loss of the heat regenerator and the pressure loss of the front cooler. The pressure loss ratio is defined as the pressure loss of each part and the highest pressure (p) of the cycle5I.e. the highest pressure, p, of the whole circuit 1-2-3-4-5-6-14The lowest pressure). Pressure loss for a component refers to the decrease in outlet pressure relative to inlet pressure for a helium xenon working fluid flowing through the component. The compressor is not shown in the table below, since the pressure of the working fluid flowing through the component increases, and the relationship between the inlet and outlet pressures is determined by the pressure ratio. For pure helium working fluids, the pressure drop Δ p isHeSpecific values (i.e., pressure loss ratios) can be found in the following table one:
table-pure helium working medium pressure loss ratio of each portion
| Region(s) | Pressure loss ratio |
| Regenerator cold end | 0.6％ |
| Reactor core | 0.7％ |
| Hot end of heat regenerator | 0.4％ |
| Front cooler | 0.5％ |
| Mixing box | 0.2％ |
As for the helium-xenon mixed working medium, the viscosity of the mixed working medium is increased due to the introduction of xenon, so that the pressure loss of the mixed working medium is larger than that of a pure helium working medium. Defining the relative pressure loss coefficient
The ratio of the pressure loss of the helium-xenon mixed working medium to the pressure loss of the pure helium working medium under the same conditions (the temperature, the pressure and the pipeline geometry are the same), therefore, the pressure drop proportion delta p of the helium-xenon mixed working medium in each part can be multiplied by the pressure loss proportion (shown in table one) of the pure helium working medium in each part by the relative pressure loss coefficient
And (4) obtaining. Thus, pressure values at various locations can be determined over the loop 1-2-3-4-5-6-1. The pressure ratio at the turbine is calculated from the pressure ratio of the compressor and the pressure loss of the circuit.
And (3): and performing neutron physical calculation on the core region based on the temperature of each part inside the core to obtain the current power generation power of the helium-xenon cooled reactor in the current operation state.
Obtaining the material information of the reactor, referring to the material table of each part of the reactor shown in the first table and the core material density table shown in the second table:
table-reactor each part material table
Meter-two core material density meter
The Monte Carlo program is adopted for calculation, the geometric shape of a calculation domain, the physical properties of each region and the like are specified, then grids are divided, a neutron transport equation and the like are discretized, and solution is carried out, so that the reactivity k and the reactor core thermal power Q can be obtained, and the control variable 'reaction layer drawing distance X' is calculated here as one of boundary conditions. The calculation formula of the thermal power of the reactor core is as follows:
wherein H1Is the specific enthalpy of the working medium at the outlet of the reactor core (also the specific enthalpy of the working medium at the inlet of the turbine),
is the average constant pressure specific heat capacity of the 6-1 thermodynamic process (core heating).
Shaft work input by the generatorMost of the heat energy is converted into electric power output, the rest is dissipated in the form of heat energy, and the generating efficiency (obtained based on the thermal power of the reactor core) of the generator is set as etaGThe generated power W of the generatorGComprises the following steps:
WG＝ηG(WT-WC)
in a specific embodiment, each control parameter at the next moment of the helium-xenon cooled reactor is calculated based on the current generated power and the preset generated power, and each device of the helium-xenon cooled reactor is controlled to operate based on the control parameters, so that the generated power of the helium-xenon cooled reactor reaches the preset generated power; the control parameters comprise main loop flow, precooler side flow and reactor core reflector drawing distance.
The reactor has three parts for control, namely a turbine valve, a precooler cold side valve and a reactor core drawing type reflecting layer. The respectively corresponding control variables are: main loop flow M1(kg/s), precooler cold side flow M2(kg/s), and reflector pull distance X (cm). (i.e., main circuit flow G, precooler cold side flow G in the mathematical model equation abovecAnd a reflective layer pull distance X).
Because the compressor, the turbine and the generator are connected through one shaft, the rotating speeds of the compressor, the turbine and the generator are consistent in a steady state. When the system is in steady-state operation, the rotor moment is balanced, and the rotating speed of the turbine is kept constant; when the rotating speed of the steam turbine is unequal to the power consumption of the air compressor, the rotor is accelerated or decelerated under the action of torque. The rotational speed of the turbine is mainly adjusted by the intake air amount M1.
When the flow of the helium xenon gas is changed in the closed cycle, the cooling capacity of the precooler is changed, and the cooling water flow M2 on the cold side of the precooler is adjusted to realize the purpose. The reactor core is controlled to control the reactor core reactivity by changing the drawing distance X of the reflecting layer to adjust the neutron leakage of the reactor core, and the reactor is closed or the power level of the reactor is adjusted.
In order to improve the reliability of the reactor control, the embodiment provides a specific implementation manner for calculating each control parameter of the helium-xenon cooled reactor at the next moment based on the current generated power and the preset generated power: and carrying out sensitivity analysis on the mathematical model based on the current generating power and the preset generating power, and determining a control parameter of the helium-xenon cooled reactor at the next moment.
The preset generated power may be obtained from a preset generated power curve pre-stored in a computer, and the preset generated power of the reactor may be obtained at preset time intervals in order to track the actual generated power of the reactor in order to allow the generated power of the reactor to operate according to the preset generated power curve.
Taking the current time step t as the time k as an example, the current preset generated power (i.e. the generated power set point) is yset(ii) a The measured value of the generated power at the time step of t-k is defined as
The power difference between the two is recorded as:
for the above mathematical model of a helium xenon cooled reactor, a method of on-line sensitivity analysis is used to derive a sensitivity matrix between the generated power and the control variables. Theta key parameters (main loop flow, precooler side flow and reactor core reflector drawing distance) selected from the mathematical model
Making a small variation Δ pc,jFor example, when the control parameter is changed by 5% in a lifting process, the other two control parameters are kept unchanged, since there are 3 control parameters, that is, the model is calculated 3 times, the current power calculation value of (M1, M2, X) in the current state is set to be y, and the power y + Δ y1 for (M1+ Δ M1, M2, X), (the power y + Δ y2 for M1, M2+ Δ M2, X) and the power y + Δ y3 for (M1, M2, X + Δ X) are calculated respectively.
Sequentially using the mathematical model of the reactor to obtain the calculated value y of the generated power after the parameter changek(pj+Δpc,j) Relative to the measured value of the power generation power before the parameter change
Change of (e)kAnd calculating partial derivatives of the generated power relative to each control parameter to obtain a sensitivity matrix (after normalization):
wherein j is 1L theta, ykIs a calculated value of the generated power at time step t-k (i.e. the generated power W of the generator calculated at time step t-kG) Considering equal time steps thus ignores possible effects of different time steps.
And solving a new control variable value according to a deviation value between the preset generating power of the current time step and the actual generating power of the reactor (the calculated current generating power).
The adjustment amount of the control parameter is calculated based on the following equation:
Δpk＝S+·Rk
wherein S is+Representing the pseudo-inverse of the sensitivity matrix S, for N reference physical quantities (total number of model and control quantities), M parameters to be adjusted (i.e. model or control quantities), S+The calculation method is as follows:
for the power generation control of the small helium xenon stack, N is 1, and M is 3. To avoid that the parameters are corrected beyond their physical meaning and to allow for faster convergence, a gain factor a may be set. Then the control parameters of the model at this time should be adjusted to:
Pk+1＝Pk+a*ΔPk
i.e. obtaining the control parameter P of the next time stepk+1And the power generation power regulation is applied to the reactor in the next time step.
The sensitivity analysis algorithm is to change each control parameter in a mathematical model of the helium-xenon cooled reactor, calculate the sensitivity of the power generation of the reactor relative to the control parameters, and calculate the control parameters of the mathematical model at the next moment according to the difference between the acquired power generation of the reactor and the preset power generation. After calculating the control parameters of the mathematical model, the computer applies the control parameters at the next moment to the devices of the reactor, such as increasing or decreasing the main loop flow, the precooler side flow and the core reflector pull distance.
In a specific embodiment, before the step S104, the method further includes the following steps a to c:
step a: and performing state prediction on the helium-xenon cooling reactor based on the neural network and the running state information to obtain a state prediction result.
And inputting the current running state information detected by the reactor from the sensor into a neural network for future state prediction, and judging whether the running state of the reactor at a certain future time exceeds the physical thermal constraint.
In a specific implementation mode, the generated power in the running state information is input into a neural network model, the neural network model is trained on line based on the generated power, and the helium-xenon cooled reactor is subjected to single-step prediction based on the neural network model to obtain a state prediction result. The neural network model may be an Elman neural network, a forward neural network, or a recurrent neural network (such as a recurrent neural network or a long-short term memory network, etc.).
When the neural network model is an Elman neural network, see the schematic diagram of the Elman neural network structure shown in fig. 3, the neural network model includes an input layer, a hidden layer and an output layer. Acquiring time sequence data y of generated powerk+1＝f(yk,yk-1,L,yk-s+1) Time series data is a series of data points arranged in time sequence, in the time series data, time is usually independent variable, therefore, for the time series data with equal time intervals, time items are often omitted, and only the data series is reserved. Number of passage through s historical time stepsThe next step of the method is determined (where t ═ k is the current time step), and the method can be regarded as an input-output system determined by a nonlinear mechanism, where the relation f can be obtained by fitting or the like.
The single-step prediction of the neural network refers to the prediction of the generated power of the future step by using s historical data of the generated power, and the nonlinear state space expression of the Elman neural network is as follows:
y(k)＝g(w3x(k))
x(k)＝f(w1xc(k)+w2u(k-1))
the accepting layer delays the hidden layer output to feed back to the hidden layer input by one step, then:
xc(k)＝x(k-1)
the activation functions of the hidden layer and the output layer in the above formula are respectively:
g(x)＝purelin(x)＝x
training of the neural network adjusts the weights w by a gradient descent learning algorithm to minimize the loss function (loss function), which is the mean square error.
When the future operation state information of the reactor is predicted on line based on the neural network, the neural network is trained on line and predicts the future operation state information of the reactor on line, the number of historical data during the neural network training is set to be s, the number of nodes of an implicit layer of the neural network model is set to be a, and the structure of the network, namely the number of nodes of three layers, is respectively recorded as s-a-1. L is the number of samples required for each step of single-step prediction, taking the kth time step as an example, the flow of online single-step prediction of the neural network is as follows:
according to each step of training sample L set in advance, experimental data y at the current time stepkWindow forward continuously selects L training samples, where ykThe actual generated power of the reactor obtained at the time k, i.e., the 1 st training sample is { (y)k-s,yk-s+1,L,yk-2,yk-1),ykIs (y) of the 2 ndk-s-1,yk-s,L,yk-3,yk-2),yk-1And sequentially recursion until L samples are selected as a training set to train the neural network model, namely:
wherein, the first L columns in the above formula are L training samples. The last column is used for single-step prediction after training is completed, the first s rows are all input of the neural network, and the last row is output of the neural network. Element yk+1Initially set to null, representing a single step prediction to be performed
The termination condition of the neural network model training is that the set training upper limit time T is reachedmaxThis time is limited by both the actual time step and the program computation time.
Obtaining the adjusted weight W after the training of the current step is completedkOne-step prediction is carried out by using the current neural network, and the latest s experimental data Y (Y) are input into the networkk-s+1,yk-s+2,L,yk-1,yk) The output of the neural network model is the result of the single step prediction:
by repeatedly executing the prediction steps, the multi-step prediction of the operating state of the reactor can be realized.
Step b: and judging whether the state prediction result exceeds a preset physical thermal constraint, and if so, controlling the helium-xenon cooling reactor to execute an accident control step.
The accident control step includes: and performing temperature reduction and pressure reduction control on the helium-xenon cooled reactor so as to ensure that the helium-xenon cooled reactor operates stably. Referring to an intelligent control flow chart shown in fig. 4, a key physical quantity, namely the highest temperature of a reactor core flow channel cladding is predicted, early warning is carried out, if a temperature overrun accident is predicted to occur, high temperature early warning is sent out, accident response operation is carried out, namely, the in-reactor cooling and depressurization operation is carried out immediately.
Step c: if the state prediction result does not exceed the preset physical thermal constraint, step S104 is executed.
The physical and thermal constraints include: 1. neutron physical restraint, which is expressed as critical when the reactor normally operates, and the effective multiplication coefficient is more than 1; 2. the thermal hydraulic constraint is characterized in that the central temperature of the fuel and the highest temperature of a corresponding sensitive area do not exceed the tolerance temperature of the material and a certain safety margin is reserved.
As shown in fig. 4, if the prediction result indicates that no temperature overrun accident occurs, the specific embodiment of adjusting each control parameter of the he-xe cooled reactor based on the numerical simulation result is performed to make the power generation of the he-xe cooled reactor reach the preset power generation is performed, that is, the relationship between the objective function and the control variable at the current time step is obtained, the value of the new control variable is obtained according to the deviation value between the actual power generation at the current time step and the preset power generation, the new control variable is applied to the reactor to control the power generation, the current time step is increased by 1, and the above-mentioned he-xe cooled reactor control method is repeatedly performed to realize the adaptive control of the he-xe cooled reactor.
The control method for the helium-xenon cooled reactor provided by the embodiment can realize the self-adaptive control of the reactor, so that the reactor can stably run, and the control stability of the helium-xenon cooled reactor is improved.
On the basis of the foregoing embodiments, this embodiment provides an example of intelligently controlling a small-sized he-xe-cooled solid reactor by using the foregoing he-xe-cooled reactor control method, which can be specifically executed by referring to the following steps 1 to 4:
step 1: and establishing a mathematical model of reactor thermodynamic cycle and reactor core neutron physics.
Analyzing the flow law of the coolant in the helium-xenon cooled reactor, establishing a mathematical model by combining reactor core neutron physics, and selecting initial parameters to carry out physical thermal numerical simulation calculation according to the existing reliable data so as to verify the reliability and accuracy of numerical calculation.
The helium xenon cooling reactor has strong coupling performance, and the neutron physics and the thermal hydraulic power of the reactor core of the helium xenon cooling reactor can carry out a numerical method to simulate the internal heat transfer process in the power generation process of the reactor; the equipment such as the air compressor, the precooler, the heat regenerator, the turbine, the reactor, the generator and the like can adopt a thermodynamic empirical relation to carry out analog calculation.
The mathematical simulation of a reactor can be divided into three parts: 1. the thermodynamic cycle part (outside the core part) using thermodynamic relations; 2. thermal calculation of the core region (including the flow channel and the solid region) by using a single-channel program; 3. neutron physics calculations for the core region use the monte carlo program.
Step 2: and obtaining a sensitivity matrix between the generated power and the control variable based on a mathematical model and an online sensitivity analysis method.
And for the current time step, acquiring the relation between the target function and the control variable. In order to control the reactor, i.e., obtain specific values of the current controlled variables, it is necessary to first determine the relationships between the controlled variables and the objective function, i.e., the generated power, i.e., Δ Y/Δ M1, Δ Y/Δ M2, and Δ Y/Δ X. The step is obtained by respectively changing three control parameters (when one of the three control parameters is changed, the other two control parameters are kept unchanged), and calculating the corresponding generated power change through a mathematical model (namely, the formula and the program iterative solution in the simultaneous section I are converged), so as to obtain the step (namely, the online sensitivity analysis).
And step 3: and solving the control variable based on the sensitivity matrix and the deviation value of the current generating power and the set point.
And solving a new control variable value according to the deviation value between the generated power set point of the current time step and the actual generated power of the stack.
And 4, step 4: the future short-term prediction of the key physical quantity (highest temperature of the cladding) is realized through online prediction of a neural network so as to carry out accident early warning.
And predicting the key physical quantity, namely the highest temperature of the reactor core flow channel cladding, and early warning. If the temperature overrun accident is expected to occur, the in-pile temperature reduction and pressure reduction operation is immediately carried out. A neural network is used for future short-term prediction of highest cladding temperature.
In addition to the above mentioned Elman neural network, other kinds of neural network implementations can be used in the neural network prediction, such as a forward neural network, or a recurrent neural network RNN, LSTM, etc.
Corresponding to the control method for the helium-xenon cooled reactor provided in the above embodiment, an embodiment of the present invention provides a control apparatus for a helium-xenon cooled reactor, and referring to a schematic structural diagram of the control apparatus for a helium-xenon cooled reactor shown in fig. 5, the apparatus includes the following modules:
the monitoring module 51 is used for monitoring the operation state information of the helium-xenon cooled reactor in the operation process of the helium-xenon cooled reactor and acquiring a pre-constructed mathematical model of the helium-xenon cooled reactor; the operating state information includes a primary loop flow rate, a precooler side flow rate and a core reflector pull distance.
And the simulation module 52 is configured to perform numerical simulation on the mathematical model based on the current operating state information to obtain a numerical simulation result.
And the control module 53 is used for adjusting each control parameter of the helium-xenon cooled reactor based on the numerical simulation result so as to enable the power generation power of the helium-xenon cooled reactor to reach the preset power generation power.
According to the helium xenon cooling reactor control device provided by the embodiment, the operation state information of the reactor is monitored in the operation process of the helium xenon cooling reactor, the numerical simulation is carried out according to the current operation state information of the reactor, and the control parameters of the reactor are adjusted according to the numerical simulation result, so that the power generation power of the reactor follows the preset power generation power, the self-adaptive control of each control parameter of the reactor according to the operation state of the reactor is realized, the load requirement is met, and the operation stability of the reactor is improved.
In one embodiment, the simulation module 52 is further configured to perform a thermodynamic cycle calculation on the helium-xenon cooled reactor based on the current operating state information to obtain a core inlet temperature and a core outlet temperature; performing thermal calculation on the core region based on the core inlet temperature and the core outlet temperature to obtain the temperature of each part in the core; and performing neutron physical calculation on the core region based on the temperature of each part inside the core to obtain the current power generation power of the helium-xenon cooled reactor in the current operation state.
In an embodiment, the control module 53 is further configured to calculate control parameters at a next moment of the helium-xenon cooled reactor based on the current generated power and a preset generated power, and control operations of devices of the helium-xenon cooled reactor based on the control parameters so that the generated power of the helium-xenon cooled reactor reaches the preset generated power; the control parameters comprise main loop flow, precooler side flow and reactor core reflector drawing distance.
In an embodiment, the control module 53 is further configured to perform a sensitivity analysis on the mathematical model based on the current generated power and the preset generated power, and determine a control parameter at a next moment when the he-xe-cooled reactor is started.
In one embodiment, the above apparatus further comprises:
the prediction module is used for predicting the state of the helium-xenon cooling reactor based on the neural network and the running state information to obtain a state prediction result; and judging whether the state prediction result exceeds a preset physical thermal constraint, and if so, controlling the helium-xenon cooling reactor to execute an accident control step.
And the prediction module is further used for triggering the simulation module to operate when the state prediction result does not exceed the preset physical thermal constraints.
And the prediction module is further used for inputting the generated power in the running state information into the neural network model, training the neural network model on line based on the generated power, and performing single-step prediction on the helium-xenon cooling reactor based on the neural network model to obtain a state prediction result.
The helium xenon cooling reactor control device provided by the embodiment can realize the self-adaptive control of the reactor, so that the reactor can stably run, and the control stability of the helium xenon cooling reactor is improved.
The device provided by the embodiment has the same implementation principle and technical effect as the foregoing embodiment, and for the sake of brief description, reference may be made to the corresponding contents in the foregoing method embodiment for the portion of the embodiment of the device that is not mentioned.
An embodiment of the present invention provides an electronic device, as shown in a schematic structural diagram of the electronic device shown in fig. 6, where the electronic device includes a processor 61 and a memory 62, where a computer program operable on the processor is stored in the memory, and when the processor executes the computer program, the steps of the method provided in the foregoing embodiment are implemented.
Referring to fig. 6, the electronic device further includes: a bus 64 and a communication interface 63, and the processor 61, the communication interface 63 and the memory 62 are connected by the bus 64. The processor 61 is for executing executable modules, such as computer programs, stored in the memory 62.
The Memory 62 may include a high-speed Random Access Memory (RAM) and may also include a non-volatile Memory (non-volatile Memory), such as at least one disk Memory. The communication connection between the network element of the system and at least one other network element is realized through at least one communication interface 63 (which may be wired or wireless), and the internet, a wide area network, a local network, a metropolitan area network, and the like can be used.
The bus 64 may be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, an EISA (Extended Industry Standard Architecture) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one double-headed arrow is shown in FIG. 6, but that does not indicate only one bus or one type of bus.
The memory 62 is configured to store a program, and the processor 61 executes the program after receiving an execution instruction, and the method executed by the apparatus defined by the flow process disclosed in any of the foregoing embodiments of the present invention may be applied to the processor 61, or implemented by the processor 61.
The processor 61 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware or instructions in the form of software in the processor 61. The Processor 61 may be a general-purpose Processor, and includes a Central Processing Unit (CPU), a Network Processor (NP), and the like. The device can also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components. The various methods, steps and logic blocks disclosed in the embodiments of the present invention may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present invention may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The storage medium is located in the memory 62, and the processor 61 reads the information in the memory 62, and completes the steps of the method in combination with the hardware thereof.
Embodiments of the present invention provide a computer-readable medium, wherein the computer-readable medium stores computer-executable instructions, which, when invoked and executed by a processor, cause the processor to implement the method of the above-mentioned embodiments.
It can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working process of the system described above may refer to the corresponding process in the foregoing embodiments, and is not described herein again.
The helium-xenon cooled reactor control method, the helium-xenon cooled reactor control device, and the computer program product of the electronic device provided by the embodiments of the present invention include a computer readable storage medium storing program codes, instructions included in the program codes may be used to execute the methods described in the foregoing method embodiments, and specific implementation may refer to the method embodiments, and will not be described herein again.
In addition, in the description of the embodiments of the present invention, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, e.g., as meaning either a fixed connection, a removable connection, or an integral connection; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, and are only for convenience of description and simplicity of description, but do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, should not be construed as limiting the present invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
Finally, it should be noted that: the above-mentioned embodiments are only specific embodiments of the present invention, which are used for illustrating the technical solutions of the present invention and not for limiting the same, and the protection scope of the present invention is not limited thereto, although the present invention is described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: any person skilled in the art can modify or easily conceive the technical solutions described in the foregoing embodiments or equivalent substitutes for some technical features within the technical scope of the present disclosure; such modifications, changes or substitutions do not depart from the spirit and scope of the embodiments of the present invention, and they should be construed as being included therein. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.
Claims (10)
1. A helium xenon cooled reactor control method, comprising:
monitoring the operation state information of the helium-xenon cooled reactor in the operation process of the helium-xenon cooled reactor, and acquiring a pre-constructed mathematical model of the helium-xenon cooled reactor; the operation state information comprises main loop flow, precooler side flow and reactor core reflector drawing distance;
performing numerical simulation on the mathematical model based on the current running state information to obtain a numerical simulation result;
and adjusting each control parameter of the helium-xenon cooling reactor based on the numerical simulation result so as to enable the power generation power of the helium-xenon cooling reactor to reach the preset power generation power.
2. The method of claim 1, wherein the step of numerically simulating the mathematical model based on the current operating state information to obtain a numerical simulation result comprises:
performing thermodynamic cycle calculation on the helium-xenon cooled reactor based on the current operating state information to obtain the reactor core inlet temperature and the reactor core outlet temperature;
performing thermal calculation on the core region based on the core inlet temperature and the core outlet temperature to obtain the temperature of each part in the core;
performing neutron physical calculation on the reactor core region based on the temperature of each part inside the reactor core to obtain the current power generation power of the helium-xenon cooled reactor in the current operation state.
3. The method of claim 1, wherein the numerical simulation result comprises a current power generation power, and the step of adjusting each control parameter of the he-xe-cooled reactor based on the numerical simulation result to make the power generation power of the he-xe-cooled reactor reach a preset power generation power comprises:
calculating each control parameter of the helium-xenon cooled reactor at the next moment based on the current power generation power and the preset power generation power, and controlling each device of the helium-xenon cooled reactor to operate based on the control parameters so as to enable the power generation power of the helium-xenon cooled reactor to reach the preset power generation power; the control parameters comprise main loop flow, precooler side flow and reactor core reflector drawing distance.
4. The method of claim 3, wherein the step of calculating the control parameters for the next time when the HEXe cools the reactor based on the current generated power and the preset generated power comprises:
and carrying out sensitivity analysis on the mathematical model based on the current generating power and the preset generating power, and determining a control parameter of the helium-xenon cooling reactor at the next moment.
5. The method of claim 1, further comprising:
performing state prediction on the helium-xenon cooling reactor based on a neural network and the running state information to obtain a state prediction result;
and judging whether the state prediction result exceeds a preset physical thermal constraint, and if so, controlling the helium-xenon cooling reactor to execute an accident control step.
6. The method of claim 5, further comprising:
and if the state prediction result does not exceed the preset physical thermal constraints, returning to the step of executing the numerical simulation of the mathematical model based on the current operating state information to obtain a numerical simulation result.
7. The method of claim 5, wherein the step of performing a state prediction for the HEXe cooled reactor based on the neural network and the operating state information to obtain a state prediction result comprises:
and inputting the generated power in the running state information into a neural network model, training the neural network model on line based on the generated power, and performing single-step prediction on the helium-xenon cooled reactor based on the neural network model to obtain a state prediction result.
8. A helium xenon cooled reactor control apparatus, comprising:
the monitoring module is used for monitoring the operation state information of the helium-xenon cooled reactor in the operation process of the helium-xenon cooled reactor and acquiring a pre-constructed mathematical model of the helium-xenon cooled reactor; the operation state information comprises main loop flow, precooler side flow and reactor core reflector drawing distance;
the simulation module is used for carrying out numerical simulation on the mathematical model based on the current running state information to obtain a numerical simulation result;
and the control module is used for adjusting each control parameter of the helium-xenon cooling reactor based on the numerical simulation result so as to enable the power generation power of the helium-xenon cooling reactor to reach the preset power generation power.
9. An electronic device, comprising: a processor and a storage device;
the storage device has stored thereon a computer program which, when executed by the processor, performs the method of any one of claims 1 to 7.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method according to any one of the claims 1 to 7.
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| CN116994787B (en) * | 2023-07-28 | 2024-05-24 | 华能核能技术研究院有限公司 | Method and system for controlling nuclear power of high-temperature gas cooled reactor nuclear power plant |
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