Method and device for determining performance of Brayton cycle system

Abstract

The invention provides a performance determination method and device for a Brayton cycle system, and belongs to the technical field of computer aided design and the technical field of Brayton cycle systems. The performance determination method of the Brayton cycle system comprises the following steps: constructing a mathematical model of the Brayton cycle system; acquiring input parameters of the mathematical model; the input parameters are input into the mathematical model for simulation calculation, output parameters are obtained, and the output parameters comprise parameters obtained after the input parameters are updated; comparing the input parameter with the output parameter, and taking the output parameter as a target parameter under the condition that an error between the input parameter and the output parameter meets a first preset condition; according to the target parameters, the performance of a mathematical model is determined, and the performance of the mathematical model represents the performance of the Brayton cycle system.

Description

Technical Field

[0001] The present disclosure relates to the technical fields of computer-aided design and Brayton cycle systems, and more particularly to a method and apparatus for determining the performance of a Brayton cycle system. Background Art

[0002] The supercritical carbon dioxide Brayton cycle is a new type of power cycle. Due to its advantages such as low compression power consumption, high cycle efficiency and compact structure, it has broad application prospects in solar thermal power generation, thermal power generation, nuclear power generation, waste heat utilization and other fields.

[0003] However, in the relevant technologies, the supercritical carbon dioxide Brayton cycle system is still in the demonstration stage. The performance of the supercritical carbon dioxide Brayton cycle system determined by theoretical calculations, simulations, etc. also has a large deviation from the operational test efficiency of the actual system built, and it is impossible to accurately evaluate the performance of the supercritical carbon dioxide Brayton cycle system. Summary of the Invention

[0004] In view of this, the present disclosure provides a method and apparatus for determining the performance of a Brayton cycle system.

[0005] One aspect of the present disclosure provides a method for determining the performance of a Brayton cycle system, comprising: constructing a mathematical model of the Brayton cycle system, the Brayton cycle system comprising a first loop, a second loop, at least one of a pipeline assembly, and a turbine component, the first loop being configured to reinject leakage gas generated during operation of the Brayton cycle system into the Brayton cycle system, the second loop being configured to inject turbine cooling gas into the turbine component for turbine cooling, the mathematical model comprising at least one of a first loop simulation module for characterizing physical properties of the first loop, a second loop simulation module for characterizing physical properties of the second loop, and a pipeline assembly simulation module for characterizing physical properties of the pipeline assembly; and obtaining input parameters of the mathematical model. , the input parameters include at least one of leakage gas parameters, cooling gas parameters, and pressure loss parameters in the pipeline; the above input parameters are input into the above mathematical model for simulation calculation to obtain output parameters, wherein the above leakage gas parameters are input into the above first loop simulation module, the above cooling gas parameters are input into the above second loop simulation module, and the above pressure loss parameters in the pipeline are input into the above pipeline component simulation module, and the above output parameters include parameters updated from the above input parameters; the above input parameters are compared with the above output parameters, and when the error between the above input parameters and the above output parameters meets the first preset condition, the above output parameters are used as the target parameters; according to the above target parameters, the performance of the above mathematical model is determined, and the performance of the above mathematical model represents the performance of the above Brayton cycle system.

[0006] According to an embodiment of the present disclosure, the mathematical model includes a second loop simulation module and a turbine component simulation module for characterizing physical properties of the turbine component.

[0007] According to an embodiment of the present disclosure, the input parameters include cooling gas parameters, and the cooling gas parameters include the flow rate of the cooling gas.

[0008] According to an embodiment of the present disclosure, the above-mentioned acquisition of the input parameters of the mathematical model includes: calling the cooling gas parameter calculation module to perform the following operations to obtain the cooling gas parameters: calculating the cold side temperature of the turbine component simulation module based on the hot side temperature of the turbine component simulation module and the flow rate of the cooling gas; when the cold side temperature of the turbine component simulation module meets the second preset condition, the flow rate of the cooling gas is used as the cooling gas parameter.

[0009] According to an embodiment of the present disclosure, the above-mentioned cooling gas parameter calculation module is also used to perform the following operations: when the cold side temperature of the above-mentioned turbine component simulation module does not meet the second preset condition, the flow rate of the above-mentioned cooling gas is changed, and the cold side temperature of the above-mentioned turbine component simulation module is recalculated until the cold side temperature of the above-mentioned turbine component simulation module meets the second preset condition.

[0010] According to an embodiment of the present disclosure, the mathematical model includes a first loop simulation module and a sealing component simulation module.

[0011] According to an embodiment of the present disclosure, the above-mentioned input parameters include leakage gas parameters.

[0012] According to an embodiment of the present disclosure, the above-mentioned leakage gas parameters are obtained by at least one of the following methods: obtaining the above-mentioned leakage gas parameters by simulating and calculating the above-mentioned first loop simulation module and the above-mentioned sealing component simulation module; obtaining the above-mentioned leakage gas parameters based on expert experience; setting the above-mentioned leakage gas parameters to preset values.

[0013] According to an embodiment of the present disclosure, constructing the mathematical model of the Brayton cycle system includes: constructing the mathematical model based on the physical principles, connection relationships and pipeline layout of each component in the Brayton cycle system.

[0014] According to an embodiment of the present disclosure, the performance determination method of the above-mentioned Brayton cycle system also includes: when the error between the above-mentioned input parameters and the above-mentioned output parameters does not meet the first preset condition, performing the following operations: re-acquiring the input parameters of the above-mentioned mathematical model to obtain updated input parameters; inputting the above-mentioned updated input parameters into the above-mentioned mathematical model for simulation calculation to obtain updated output parameters, until the error between the updated input parameters and the updated output parameters meets the first preset condition, and using the output parameters output by the above-mentioned mathematical model for the last time as the target system parameters.

[0015] According to an embodiment of the present disclosure, reacquiring the input parameters of the above-mentioned mathematical model to obtain updated input parameters includes: calculating weighted input parameters based on the above-mentioned system input parameters and the above-mentioned system output parameters; and obtaining updated input parameters based on the above-mentioned weighted input parameters.

[0016] According to an embodiment of the present disclosure, the above-mentioned input parameters also include at least one of the efficiency, inlet temperature, inlet pressure, outlet temperature, outlet pressure, and expansion ratio of the turbine component module.

[0017] According to an embodiment of the present disclosure, the method for determining the performance of the Brayton cycle system further includes: if the performance of the Brayton cycle system satisfies a third preset condition, using the Brayton cycle system as a target Brayton cycle system.

[0018] According to an embodiment of the present disclosure, when the performance of the above-mentioned Brayton cycle system does not meet the third preset condition, the following operations are performed: the structure of the above-mentioned mathematical model is changed to obtain an updated mathematical model; the performance of the above-mentioned updated mathematical model is determined until the performance of the updated mathematical model meets the third preset condition, and the Brayton cycle system corresponding to the mathematical model after the last update is used as the target Brayton cycle system.

[0019] Another aspect of the present disclosure provides a performance determination device for a Brayton cycle system, comprising: a construction module for constructing a mathematical model of the Brayton cycle system, wherein the Brayton cycle system comprises a first loop, a second loop, at least one of a pipeline assembly, and a turbine component, wherein the first loop is used to reinject leakage gas generated during operation of the Brayton cycle system into the Brayton cycle system, and the second loop is used to inject turbine cooling gas into the turbine component for turbine cooling, and the mathematical model comprises at least one of a first loop simulation module for characterizing physical properties of the first loop, a second loop simulation module for characterizing physical properties of the second loop, and a pipeline assembly simulation module for characterizing physical properties of the pipeline assembly; and an acquisition module for acquiring input parameters of the mathematical model, wherein the input parameters are input to the mathematical model. The parameters include at least one of leakage gas parameters, cooling gas parameters, and pressure loss parameters in the pipeline; a simulation calculation module is used to input the above input parameters into the above mathematical model for simulation calculation to obtain output parameters, wherein the above leakage gas parameters are input into the above first loop simulation module, the above cooling gas parameters are input into the above second loop simulation module, and the above pressure loss parameters in the pipeline are input into the above pipeline component simulation module, and the above output parameters include parameters updated from the above input parameters; a comparison module is used to compare the above input parameters with the above output parameters, and when the error between the above input parameters and the above output parameters meets the first preset condition, the above output parameters are used as the target parameters; a determination module is used to determine the performance of the above mathematical model according to the above target parameters, and the performance of the above mathematical model represents the performance of the above Brayton cycle system.

[0020] Another aspect of the present disclosure provides an electronic device, comprising:

[0021] one or more processors;

[0022] a memory for storing one or more programs,

[0023] When the one or more programs are executed by the one or more processors, the one or more processors implement the method as described above.

[0024] Another aspect of the present disclosure provides a computer-readable storage medium storing computer-executable instructions, which are used to implement the method described above when executed.

[0025] Another aspect of the present disclosure provides a computer program product comprising computer executable instructions, which are used to implement the method described above when the instructions are executed.

[0026] According to an embodiment of the present disclosure, by constructing a mathematical model including at least one of a first loop simulation module, a second loop simulation module, and a pipeline assembly simulation module, at least one of seal leakage, turbine cooling, and pipeline pressure loss present during the actual operation of the Brayton cycle system is fully considered; the input parameters and output parameters of the mathematical model are compared, the output parameters include parameters after the input parameters are updated, and when the error between the input parameters and the output parameters meets a first preset condition, the output parameters are used as target parameters for determining the performance of the mathematical model based on the target parameters, and the performance of the mathematical model represents the performance of the Brayton cycle system, thereby improving the accuracy of the performance calculation of the Brayton cycle system. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The above and other objects, features and advantages of the present disclosure will become more apparent through the following description of the embodiments of the present disclosure with reference to the accompanying drawings, in which:

[0028] Figure 1 A schematic diagram of a supercritical carbon dioxide Brayton cycle system without considering internal losses according to an embodiment of the present disclosure is shown;

[0029] Figure 2 Schematically illustrates an exemplary system architecture to which the method and apparatus for determining performance of a Brayton cycle system according to an embodiment of the present disclosure may be applied;

[0030] Figure 3 Schematically shows a flow chart of a method for determining performance of a Brayton cycle system according to an embodiment of the present disclosure;

[0031] Figure 4 A Brayton cycle system diagram is schematically shown with internal losses taken into account according to an embodiment of the present disclosure;

[0032] Figure 5 Schematically shows the distribution of one-dimensional calculation sites of a labyrinth seal according to an embodiment of the present application;

[0033] Figure 6 Schematically shows a flow chart of a method for determining performance of a Brayton cycle system according to another embodiment of the present disclosure;

[0034] Figure 7 A block diagram schematically illustrates a device for determining performance of a Brayton cycle system according to an embodiment of the present disclosure; and

[0035] Figure 8 The block diagram schematically shows an electronic device suitable for implementing a method for determining the performance of a Brayton cycle system according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0036] Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are merely exemplary and are not intended to limit the scope of the present disclosure. In the detailed description below, for ease of explanation, many specific details are set forth to provide a comprehensive understanding of the embodiments of the present disclosure. However, it is apparent that one or more embodiments may also be implemented without these specific details. In addition, in the following description, descriptions of well-known structures and technologies are omitted to avoid unnecessary confusion of the concepts of the present disclosure.

[0037] The terms used herein are only for describing specific embodiments and are not intended to limit the present disclosure. The terms "comprise," "include," etc. used herein indicate the presence of the features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0038] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art unless otherwise defined. It should be noted that the terms used herein should be interpreted as having a meaning consistent with the context of this specification and should not be interpreted in an idealized or overly rigid manner.

[0039] When expressions such as "at least one of A, B, and C, etc." are used, they should generally be interpreted in accordance with the meaning commonly understood by those skilled in the art (for example, "a system having at least one of A, B, and C" should include but is not limited to a system having A alone, B alone, C alone, A and B, A and C, B and C, and / or A, B, C, etc.).

[0040] In the embodiments of the present disclosure, the collection, updating, analysis, processing, use, transmission, provision, disclosure, storage, etc. of the data involved (for example, including but not limited to user personal information) all comply with the provisions of relevant laws and regulations, are used for legitimate purposes, and do not violate public order and good morals.

[0041] The Brayton cycle is an energy conversion system based on thermodynamic cycle principles, primarily used to convert thermal energy into mechanical or electrical energy. It is widely used in gas turbines, aircraft engines, heat pumps, and other fields. The supercritical carbon dioxide Brayton cycle is a thermodynamic cycle using supercritical carbon dioxide as the working fluid.

[0042] Among related technologies, the supercritical carbon dioxide Brayton cycle system is still in the demonstration stage. Although the theoretical calculation efficiency of the cycle is high, the operational test efficiency of the actual built units is low, and many problems and defects are gradually emerging. For example, the drastic changes in the carbon dioxide working fluid near the critical point pose challenges to the stable operation of the compressor, seal leakage has a significant impact on the efficiency of the expander, thermal inertia has a certain impact on the variable load process, and the existence of various losses in the system has a significant impact on system performance. However, many studies and system designs have made idealized assumptions about the system's internal losses, ignoring their impact on the system's operational performance, resulting in the system's actual operating efficiency being lower than the theoretical calculated efficiency.

[0043] In some embodiments of the present disclosure, research has been conducted on the modeling of a supercritical carbon dioxide Brayton cycle system and the system has been analyzed. However, many idealized assumptions were made during the system simulation calculations, and therefore the lack of accuracy of the model will result in large errors in the simulation results. Figure 1 The following schematically shows a supercritical carbon dioxide Brayton cycle system diagram without considering internal losses in an embodiment of the present disclosure. Figure 1 As shown in Figure 1, the main components of the supercritical carbon dioxide Brayton cycle system include compressor C001, regenerator H001, heater H002, expander TU001 and cooler H003. Figure 1 In the supercritical carbon dioxide Brayton cycle system, the cycle process can be, for example: CO2 is compressed by C001 and usually reaches a high-pressure state of about 80°C and 20MPa, absorbs heat provided by the hot side carbon dioxide in H001, and then continues to heat in H002. Thereafter, CO2 expands and does work through TU001, and then passes through H001 to dissipate heat to the cold side carbon dioxide, and finally passes through H003 for cooling, the temperature drops to about 35°C and the pressure is usually 8MPa, and returns to the C001 entrance to complete a cycle.

[0044] The above simulation calculation process does not take into account internal losses such as pipeline pressure loss, turbine cooling and leakage reinjection. Therefore, the system performance calculation will deviate significantly from the actual situation.

[0045] In the process of implementing the present disclosure, it was found that by fully considering the various internal losses existing in the actual system operation process, namely pipeline pressure loss, seal leakage, and turbine cooling, the accuracy of the simulation calculation can be improved, providing a more accurate reference for the optimization and operation of the system.

[0046] In view of this, an embodiment of the present disclosure provides a method for determining the performance of a Brayton cycle system, comprising: constructing a mathematical model of the Brayton cycle system, the Brayton cycle system comprising a first loop, a second loop, at least one of a pipe assembly, and a turbine component, the first loop being used to reinject leakage gas generated during operation of the Brayton cycle system into the Brayton cycle system, the second loop being used to inject turbine cooling gas into the turbine component for turbine cooling, the mathematical model comprising at least one of a first loop simulation module for characterizing physical properties of the first loop, a second loop simulation module for characterizing physical properties of the second loop, and a pipe assembly simulation module for characterizing physical properties of the pipe assembly; and obtaining Input parameters of the mathematical model, the input parameters include at least one of leakage gas parameters, cooling gas parameters, and pressure loss parameters in the pipeline; the input parameters are input into the mathematical model for simulation calculation to obtain output parameters, wherein the leakage gas parameters are input into the first loop simulation module, the cooling gas parameters are input into the second loop simulation module, and the pressure loss parameters in the pipeline are input into the pipeline component simulation module, and the output parameters include parameters after the input parameters are updated; the input parameters and the output parameters are compared, and when the error between the input parameters and the output parameters meets the first preset condition, the output parameters are used as the target parameters; based on the target parameters, the performance of the mathematical model is determined, and the performance of the mathematical model represents the performance of the Brayton cycle system.

[0047] Figure 2 The following schematically illustrates an exemplary system architecture 100 to which the Brayton cycle system performance determination method and apparatus according to the present disclosure can be applied. Figure 2 The examples shown are merely examples of system architectures to which the embodiments of the present disclosure may be applied, to help those skilled in the art understand the technical content of the present disclosure, but do not mean that the embodiments of the present disclosure may not be used in other devices, systems, environments or scenarios.

[0048] like Figure 2 As shown, the system architecture 100 according to this embodiment may include a first terminal device 101, a second terminal device 102, a third terminal device 103, a network 104, and a server 105. The network 104 is used as a medium for providing a communication link between the first terminal device 101, the second terminal device 102, the third terminal device 103, and the server 105. The network 104 may include various connection types, such as wired and / or wireless communication links, etc.

[0049] A user may use a first terminal device 101, a second terminal device 102, or a third terminal device 103 to interact with a server 105 via a network 104 to receive or send messages, etc. Various communication client applications may be installed on the first terminal device 101, the second terminal device 102, or the third terminal device 103, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients, and / or social platform software (for example only).

[0050] The first terminal device 101 , the second terminal device 102 , and the third terminal device 103 may be various electronic devices having display screens and supporting web browsing, including but not limited to smart phones, tablet computers, laptop computers, desktop computers, and the like.

[0051] The server 105 may be a server that provides various services, such as a background management server (for example only) that supports websites browsed by users using the first terminal device 101, the second terminal device 102, and the third terminal device 103. The background management server may analyze and process received data such as user requests, and feed back processing results (e.g., web pages, information, or data obtained or generated based on user requests) to the terminal devices.

[0052] It should be noted that the Brayton cycle system performance determination method provided in the embodiments of the present disclosure can generally be executed by the server 105. Accordingly, the Brayton cycle system performance determination device provided in the embodiments of the present disclosure can generally be set in the server 105. The Brayton cycle system performance determination method provided in the embodiments of the present disclosure can also be executed by a server or server cluster that is different from the server 105 and can communicate with the first terminal device 101, the second terminal device 102, the third terminal device 103 and / or the server 105. Accordingly, the Brayton cycle system performance determination device provided in the embodiments of the present disclosure can also be set in a server or server cluster that is different from the server 105 and can communicate with the first terminal device 101, the second terminal device 102, the third terminal device 103 and / or the server 105. Alternatively, the Brayton cycle system performance determination method provided in the embodiments of the present disclosure can also be executed by the first terminal device 101, the second terminal device 102, or the third terminal device 103, or by other terminal devices different from the first terminal device 101, the second terminal device 102, or the third terminal device 103. Accordingly, the performance determination device of the Brayton cycle system provided in the embodiment of the present disclosure can also be set in the first terminal device 101, the second terminal device 102 or the third terminal device 103, or in other terminal devices different from the first terminal device 101, the second terminal device 102 or the third terminal device 103.

[0053] It should be understood that Figure 2 The number of terminal devices, networks and servers in the embodiment is merely illustrative. Any number of terminal devices, networks and servers may be provided as required.

[0054] Figure 3 A flow chart of a method for determining performance of a Brayton cycle system according to an embodiment of the present disclosure is schematically shown.

[0055] like Figure 3 As shown, the method includes operations S310 to S350.

[0056] In operation S310, a mathematical model of a Brayton cycle system is constructed. The Brayton cycle system includes a first loop, a second loop, at least one of a piping assembly, and a turbine component. The first loop is used to reinject leakage gas generated during operation of the Brayton cycle system into the Brayton cycle system. The second loop is used to inject turbine cooling gas into the turbine component for turbine cooling. The mathematical model includes at least one of a first loop simulation module for characterizing physical properties of the first loop, a second loop simulation module for characterizing physical properties of the second loop, and a piping assembly simulation module for characterizing physical properties of the piping assembly.

[0057] In operation S320 , input parameters of the mathematical model are acquired, where the input parameters include at least one of a leakage gas parameter, a cooling gas parameter, and a pressure loss parameter in the pipeline.

[0058] In operation S330, the input parameters are input into the mathematical model for simulation calculation to obtain output parameters, wherein the leakage gas parameters are input into the first loop simulation module, the cooling gas parameters are input into the second loop simulation module, and the pressure loss parameters in the pipeline are input into the pipeline component simulation module. The output parameters include parameters after the input parameters are updated.

[0059] In operation S340 , the input parameter and the output parameter are compared, and if an error between the input parameter and the output parameter satisfies a first preset condition, the output parameter is used as a target parameter.

[0060] In operation S350 , performance of the mathematical model is determined according to the target parameters, where the performance of the mathematical model represents performance of the Brayton cycle system.

[0061] According to an embodiment of the present disclosure, by constructing a mathematical model including at least one of a first loop simulation module, a second loop simulation module, and a pipeline assembly simulation module, at least one of seal leakage, turbine cooling, and pipeline pressure loss present during the actual operation of the Brayton cycle system is fully considered; the input parameters and output parameters of the mathematical model are compared, the output parameters include parameters after the input parameters are updated, and when the error between the input parameters and the output parameters meets a first preset condition, the output parameters are used as target parameters for determining the performance of the mathematical model based on the target parameters, and the performance of the mathematical model represents the performance of the Brayton cycle system, thereby improving the accuracy of the performance calculation of the Brayton cycle system.

[0062] In some embodiments of the present disclosure, the Brayton cycle system may be a supercritical carbon dioxide Brayton cycle system, that is, a thermodynamic cycle system using supercritical carbon dioxide as a working fluid.

[0063] In some embodiments of the present disclosure, a turbine component (turbine) is a machine that converts energy contained in a fluid medium into mechanical energy. Specifically, a turbine component may be a compressor, steam turbine, turbine, flue gas turbine, or expander.

[0064] Reference below Figure 4 , combined with specific embodiments Figure 3 The method shown is further explained.

[0065] Figure 4 A Brayton cycle system diagram is schematically shown with internal losses taken into account according to an embodiment of the present disclosure.

[0066] like Figure 4 As shown in the figure, the main components of the Brayton cycle system are compressor C001, regenerator H001, heater H002, expander TU001, cooler H003, booster pump P001, throttle valve V001, electric heaters H004 and H005, and the pipes connecting the main components within the system. During operation, turbine cooling gas is drawn from the outlet of compressor C001, heated by electric heater H004 and throttled by throttle valve V001, and then injected into the main shaft of expander TU001 for turbine cooling to prevent damage to the dry gas seal due to high temperatures. Leakage gas from expander TU001 and compressor C001 is heated by electric heater H005 and pressurized by booster pump P001 before being injected back into the hot end inlet of regenerator H001, forming a closed loop.

[0067] It can be understood that the first loop in the embodiment of the present disclosure may refer to Figure 4The orange loop in the diagram is the leaked gas from the expander TU001 and the compressor C001, which is heated by the electric heater H005 and pressurized by the pressure pump P001 before being injected back into the hot end inlet of the regenerator H001, forming a closed loop of the system. Figure 4 The blue circuit in the figure, that is, the turbine cooling gas is extracted from the outlet of the compressor C001, heated by the electric heater H004 and throttled by the throttle valve V001, and then injected into the main shaft of the expander TU001 for turbine cooling to prevent the dry gas seal from being damaged due to high temperature.

[0068] It should be noted that turbine cooling air can also be extracted at the cold outlet of the regenerator. The specific calculations can be adjusted based on the Brayton cycle system layout. The order in which cooling air passes through H004 and V001 after extraction can be modified based on the Brayton cycle system layout. Similarly, the order in which leaked gas passes through H005 and P001 after collection can also be modified based on the Brayton cycle system layout. During cooling air extraction and leaked gas collection and reinjection, the effects of pipeline pressure losses can be ignored due to the low flow rates. However, if a more accurate model is required, relevant pipeline pressure losses can be considered during the calculation.

[0069] According to an embodiment of the present disclosure, in operation S310, a mathematical model of the Brayton cycle system can be used to describe its thermodynamic processes, energy conversion, and system characteristics using mathematical expressions or equations. The mathematical model can be established based on thermodynamic laws, fluid mechanics principles, and component characteristics. For example, constructing the mathematical model of the Brayton cycle system can include: constructing the mathematical model based on the physical principles, connection relationships, and piping layout of the various components in the Brayton cycle system.

[0070] For example, in the mathematical model of the Brayton cycle system, the thermal efficiency of the mathematical model can be set with reference to equations (1) and (2).

[0071] (1)

[0072] (2)

[0073] Where η is the thermal efficiency of the system, W net is the net power generation of the system, W G is the net output power of the system, W M is the power consumption of each auxiliary motor, W H is the power consumption of the auxiliary electric heater, and Q is the input heat of the heater.

[0074] The efficiency of the compressor components can be set according to formula (3).

[0075] (3)

[0076] Among them, η c is the efficiency of the compressor components, h outc,s is the enthalpy of the outlet working fluid when the compressor is assumed to be isentropic, h inc is the enthalpy of the working fluid at the compressor inlet, h outc It is the enthalpy value of the outlet working fluid during the actual operation of the compressor.

[0077] The efficiency of the expander component can be set according to formula (4).

[0078] (4)

[0079] Among them, η TU is the efficiency of the compressor components, h outtu,s is the enthalpy of the working fluid at the outlet when the expander is assumed to be isentropic, h intu is the enthalpy of the working fluid at the expander inlet, h outtu is the enthalpy of the outlet working fluid during the actual operation of the expander.

[0080] The efficiency of the generator components can be set according to equations (5) and (6).

[0081] (5)

[0082] (6)

[0083] Among them, η G is the efficiency of the compressor components, W out is the output power of the generator, W in is the power input to the generator, W TU is the output power of the expander, W C The power consumption of the compressor.

[0084] The input heat of the heater can be set according to formula (7).

[0085] (7)

[0086] Where Q is the input heat of the heater, m is the mass flow rate of the working fluid passing through the heater, h out is the enthalpy of the working fluid at the heater outlet, h in is the enthalpy of the working fluid at the heater inlet.

[0087] The regenerator can be set according to equations (8) and (9).

[0088] (8)

[0089] (9)

[0090] Where ΔT is the end difference of the regenerator, T h,out is the temperature of the working medium at the outlet of the hot side of the regenerator, T c,out is the temperature of the working medium at the outlet of the regenerator, m h is the mass flow rate of the working fluid on the hot side of the regenerator, m c is the mass flow rate of the regenerator cooling medium, h h,in is the enthalpy of the working medium at the hot side inlet of the regenerator, h h,out is the enthalpy of the working fluid at the outlet of the hot side of the regenerator, h c,in is the enthalpy of the working medium at the regenerator cold inlet, h c,out is the enthalpy value of the working fluid at the outlet of the regenerator.

[0091] The cooler can be set according to formula (10).

[0092] (10)

[0093] Among them, m CO2 is the mass flow rate of carbon dioxide, m W is the mass flow rate of cooling water, h CO2,in is the enthalpy of carbon dioxide working fluid at the inlet side, h CO2,out is the enthalpy of the carbon dioxide working fluid at the outlet side, h W,in is the enthalpy of cooling water at the inlet side, h W,out is the enthalpy of the outlet cooler.

[0094] According to an embodiment of the present disclosure, in operation S320, the pressure loss parameter of the pipeline may include the pressure loss of each pipeline, etc. The pressure loss of the pipeline may be set with reference to equations (11) and (12).

[0095] (11)

[0096] (12)

[0097] Where Δp is the pressure loss in the pipeline, f is the friction factor, L is the length of the pipeline, D is the hydraulic diameter of the pipeline, ρ is the density of the fluid, u is the velocity of the fluid, and Re is the Reynolds number calculated from the arithmetic mean of the inlet and outlet pressures. In the pipeline calculation process, the outlet pressure of the working fluid is calculated based on the pressure loss, and the temperature is calculated by assuming the flow process is isenthalpic.

[0098] It should be noted that in addition to straight pipes, there are also elbows and other components between the components of the Brayton cycle system. The elbows can be calculated as equivalent length and added to the calculation of pipeline pressure loss.

[0099] According to an embodiment of the present disclosure, the mathematical model includes a first circuit simulation module and a sealing assembly simulation module. In operation S320, the input parameters include leakage gas parameters. For example, the leakage gas parameters may include at least one of leakage volume and leakage gas state (temperature, pressure, etc.).

[0100] According to an embodiment of the present disclosure, the leakage gas parameters are obtained by at least one of the following methods: obtaining the leakage gas parameters by simulating and calculating the first loop simulation module and the sealing component simulation module; obtaining the leakage gas parameters based on expert experience; setting the leakage gas parameters to a preset value.

[0101] For example, for the first loop simulation module, if the system uses dry gas sealing, the leakage gas parameters can be obtained based on expert experience; or the leakage gas parameters can be set to preset values. For example, the leakage flow of a single-stage impeller machine after dry gas sealing can be 0.0108 kg / s, the leakage gas pressure can be 1 bar, and the temperature can be 80°C.

[0102] For example, for the first loop simulation module, when the compressor and expander use labyrinth seals, in order to facilitate calculation, the one-dimensional flow in the labyrinth seal can be discretized, and the point with the minimum axial velocity can be used as the calculation site of the sealing cavity, and the point with the maximum axial velocity can be used as the calculation site of the sealing tooth. Figure 5 The schematic diagram shows the distribution of one-dimensional computation sites of the labyrinth seal according to the embodiment of the present application. Figure 5 As shown, the sealing cavity calculation sites are represented by 0 to n, and the sealing tooth calculation sites are represented by 0.5 to n-0.5. The specific distribution diagram can be shown as follows Figure 6 shown. Figure 6 The diagram schematically shows the distribution of one-dimensional computing stations of a labyrinth seal according to an embodiment of the present application.

[0103] According to the continuity equation shown in formula (13):

[0104] (13)

[0105] According to the calculation assumptions, the sealing process can be a process of constant total enthalpy as shown in formula (14):

[0106] (14)

[0107] in:

[0108] (15)

[0109] h0 is the mainstream unit total enthalpy, h is the mainstream unit static enthalpy, k is the mainstream unit kinetic energy, and u is the mainstream flow velocity.

[0110] When calculating the mass flow at the sealing teeth, the throttling flow coefficient C involved can be estimated by giving a suitable formula based on the experimental or numerical simulation results of different sealing structures and sealing media. The throttling flow coefficient C can be defined as follows (16).

[0111] (16)

[0112] Among them, ū(n-0.5) is the average flow velocity, u t (n-0.5) is the theoretical expansion rate.

[0113] The control equations of the isentropic expansion process are shown in Equation (17).

[0114] (17)

[0115] The isentropic expansion process requires iterative calculation. The purpose of the iteration is to adjust the seal pressure difference so that the calculated seal leakage is equal to the expected leakage. The specific iterative process can be as follows:

[0116] ① Expected mass flow rate G calculated based on given labyrinth seal performance 00 ;

[0117] ② For calculation site n-0.5, P(n-1) has been obtained. Given the initial static pressure difference δP, P(n-0.5) is determined.

[0118] ③ From the governing equation s(n-0.5)=s(n-1), we get s(n-0.5). Using (P,s) to query the NIST real fluid physical property library, we can obtain the thermodynamic state at n-0.5;

[0119] ④ According to the total enthalpy conservation, calculate the unit kinetic energy k(n-0.5) at n-0.5, and then get the flow velocity at n-0.5, calculate the mass flow rate G(n-0.5), and compare it with the expected mass flow rate G 00 For comparison, if the calculated mass flow rate is too small, increase the static pressure difference δP; if it is too large, reduce the given static pressure difference δP;

[0120] ⑤ Iterate multiple times until the mass flow rate G(n-0.5) is equal to the expected mass flow rate G 00 If the error is within the given range, the iteration process ends and the calculation process from calculation site n-0.5 to n begins.

[0121] The control equations of the isobaric dissipation process are shown in Equation (18).

[0122] (18)

[0123] Numerical simulation or experimental data can be used to develop an estimation formula for the kinetic energy carrying coefficient θ, thereby calculating the static enthalpy h(n) in the sealed cavity. By using (P,h) to query the NIST real fluid physical property library, the thermodynamic state at point n in the sealed cavity can be obtained.

[0124] According to an embodiment of the present disclosure, the mathematical model may include a second loop simulation module and a turbine component simulation module for characterizing physical properties of the turbine components. In operation S320, the input parameters may include cooling gas parameters, including cooling gas conditions (temperature, pressure, flow rate, etc.).

[0125] According to an embodiment of the present disclosure, obtaining the input parameters of the mathematical model includes: calling the cooling gas parameter calculation module to perform the following operations to obtain the cooling gas parameters: calculating the cold side temperature of the turbine component simulation module based on the hot side temperature of the turbine component simulation module and the flow rate of the cooling gas; when the cold side temperature of the turbine component simulation module meets the second preset condition, the flow rate of the cooling gas is used as the cooling gas parameter.

[0126] In some embodiments of the present disclosure, the cold-side temperature of the turbine component simulation module can be calculated based on the hot-side temperature of the turbine component simulation module and the cooling gas flow rate, cooling gas temperature, and cooling gas pressure. The second preset condition can be that the cold-side temperature of the turbine component simulation module is stable within a preset range. For example, the second preset condition can be that the cold-side temperature of the turbine component simulation module is stable between 199.9°C and 200.1°C.

[0127] According to an embodiment of the present disclosure, the cooling gas parameter calculation module is also used to perform the following operations: when the cold side temperature of the turbine component simulation module does not meet the second preset condition, the flow rate of the cooling gas is changed and the cold side temperature of the turbine component simulation module is recalculated until the cold side temperature of the turbine component simulation module meets the second preset condition.

[0128] For example, in the second-loop simulation module, regarding the turbine cooling portion, the carbon dioxide extracted from the compressor outlet is heated and throttled before being introduced onto the surface of the expander shaft for rotational flow and heat exchange, thereby cooling the expander shaft. The calculations for the turbine cooling portion can be found in Equations (19) to (22).

[0129] (19)

[0130] (20)

[0131] (twenty one)

[0132] (twenty two)

[0133] Where Nu is the Nusselt number, v is the kinematic viscosity, α is the thermal diffusion coefficient, c p is the specific heat at constant pressure, μ is the dynamic viscosity, λ is the thermal conductivity, Re eff is the effective Reynolds number, Pr is the Prandtl number, Γ is the aspect ratio of the rotating axis, H is the radius ratio of the rotating axis, V a is the axial velocity, R1 is the inner radius of the annular gap, ω is the angular velocity, V eff is the effective speed.

[0134] In some embodiments of the present disclosure, in operation S340, the error between the input parameter and the output parameter may be an absolute error, relative error, mean square error, standard deviation, variance, etc., of the input parameter and the output parameter. The first preset condition may be that the error between the input parameter and the output parameter is less than or equal to a first preset threshold. For example, the first preset threshold may be 0.01%, 0.1%, 1%, etc.

[0135] According to an embodiment of the present disclosure, the method for determining the performance of the Brayton cycle system further includes: when the error between the input parameter and the output parameter does not satisfy the first preset condition, performing the following operations:

[0136] Re-obtaining input parameters of the mathematical model to obtain updated input parameters;

[0137] The updated input parameters are input into the mathematical model for simulation calculation to obtain updated output parameters, until the error between the updated input parameters and the updated output parameters meets the first preset condition, and the output parameters outputted by the mathematical model for the last time are used as the target system parameters.

[0138] According to an embodiment of the present disclosure, reacquiring the input parameters of the mathematical model to obtain updated input parameters includes: calculating weighted input parameters based on system input parameters and system output parameters. Exemplarily, the input parameters and output parameters can be recombined or corrected by a weighted algorithm, and the corrected weighted input parameters can be obtained by weighted summation or weighted averaging. According to the weighted input parameters, updated input parameters are obtained. According to the weighted input parameters, updated leakage gas parameters, updated cooling gas parameters, and updated pressure loss parameters in the pipeline can be obtained. Exemplarily, the updated pressure loss parameters in the pipeline can be calculated according to the above method and formulas (11) and (12). For labyrinth seals, updated leakage gas parameters can be calculated according to the above method and formulas (13) to (18). Updated cooling gas parameters can be calculated according to the above method and formulas (19) to (22).

[0139] According to an embodiment of the present disclosure, the input parameters may also include critical parameters of the working fluid, state parameters of each component, mass flow rate or volume flow rate of the working fluid, etc. The state parameters of each component may include the inlet temperature and outlet temperature of each component, and the inlet pressure and outlet pressure of each component. Exemplarily, the input parameters also include at least one of the efficiency, inlet temperature, inlet pressure, outlet temperature, outlet pressure, and expansion ratio of the turbine component module.

[0140] According to an embodiment of the present disclosure, the method for determining Brayton cycle system performance further includes: if the Brayton cycle system performance satisfies a third preset condition, selecting the Brayton cycle system as a target Brayton cycle system. For example, the Brayton cycle system performance satisfying the third preset condition may mean that the power generation efficiency of the Brayton cycle system is greater than or equal to a second preset threshold.

[0141] According to an embodiment of the present disclosure, the above-mentioned method for determining the performance of a Brayton cycle system further includes, when the performance of the Brayton cycle system does not satisfy a third preset condition, performing the following operations: changing the structure of the mathematical model to obtain an updated mathematical model; determining the performance of the updated mathematical model until the performance of the updated mathematical model satisfies the third preset condition, and using the Brayton cycle system corresponding to the last updated mathematical model as the target Brayton cycle system.

[0142] This can provide more precise guidance for the design and operation of the Brayton cycle system and provide a reference for optimizing the system layout and improving system efficiency.

[0143] Figure 6 A flow chart of a method for determining performance of a Brayton cycle system according to another embodiment of the present disclosure is schematically shown.

[0144] like Figure 6 As shown, the method includes operations S601 to S610.

[0145] In operation S601 , a mathematical model of a Brayton cycle system is constructed.

[0146] In operation S602, initial parameters of the Brayton cycle system are obtained, which may include critical parameters of the working fluid, state parameters of each component, mass flow rate or volume flow rate of the working fluid, and the like.

[0147] In operation S603 , the position of leaked gas reinjection and the parameters of the leaked gas are determined.

[0148] In operation S604, the shaft end temperature of the expander is determined. The shaft end temperature of the expander may include the hot end temperature of the expander, etc.

[0149] In operation S605 , cooling gas parameters are determined.

[0150] In operation S606 , calculation is performed based on turbine cooling to obtain a cold-side temperature.

[0151] In operation S607 , it is determined whether the cold-side temperature meets a second preset condition.

[0152] If the cold side temperature satisfies the second preset condition, operation S608 is performed. If the cold side temperature does not satisfy the second preset condition, operations S605 to S607 are performed again.

[0153] In operation S608 , the input parameters are input into a mathematical model for simulation calculation to obtain output parameters.

[0154] In operation S609 , it is determined whether the error between the input parameter and the output parameter satisfies a first preset condition.

[0155] If the error between the input parameter and the output parameter satisfies the first preset condition, operation S610 is performed. If the error between the input parameter and the output parameter does not satisfy the first preset condition, operations S602 to S609 are performed.

[0156] In operation S610 , performance of a mathematical model is determined, the performance of the mathematical model representing performance of a Brayton cycle system.

[0157] Based on the above-mentioned Brayton cycle system performance determination method, the present disclosure also provides a Brayton cycle system performance determination device. Figure 7 The device is described in detail.

[0158] Figure 7 A block diagram schematically shows a device for determining performance of a Brayton cycle system according to an embodiment of the present disclosure.

[0159] like Figure 7 As shown, the performance determination device 700 of the Brayton cycle system includes a construction module 710 , an acquisition module 720 , a simulation calculation module 730 , a comparison module 740 and a first determination module 750 .

[0160] Construction module 710 is configured to construct a mathematical model of a Brayton cycle system. The Brayton cycle system includes at least one of a first loop, a second loop, a piping assembly, and a turbine component. The first loop is configured to reinject leakage gas generated during operation of the Brayton cycle system back into the Brayton cycle system, and the second loop is configured to inject turbine cooling gas into the turbine component for turbine cooling. The mathematical model includes at least one of a first loop simulation module for characterizing the physical properties of the first loop, a second loop simulation module for characterizing the physical properties of the second loop, and a piping assembly simulation module for characterizing the physical properties of the piping assembly. In one embodiment, construction module 710 can be configured to execute operation S310 described above, which will not be further described herein.

[0161] The acquisition module 720 is used to obtain input parameters of the mathematical model, including at least one of a leakage gas parameter, a cooling gas parameter, and a pressure loss parameter in the pipeline. In one embodiment, the acquisition module 720 can be used to perform the operation S320 described above, which will not be repeated here.

[0162] Simulation calculation module 730 is configured to input input parameters into a mathematical model for simulation calculation, thereby generating output parameters. The leakage gas parameters are input into the first loop simulation module, the cooling gas parameters are input into the second loop simulation module, and the pressure loss parameters within the pipeline are input into the pipeline assembly simulation module. The output parameters include updated parameters of the input parameters. In one embodiment, simulation calculation module 730 can be used to perform operation S330 described above and will not be further described here.

[0163] The comparison module 740 is configured to compare the input parameter and the output parameter, and when the error between the input parameter and the output parameter satisfies a first preset condition, the output parameter is used as the target parameter. In one embodiment, the comparison module 740 may be configured to execute the operation S340 described above, which will not be described in detail here.

[0164] The first determination module 750 is configured to determine the performance of the mathematical model according to the target parameters, where the performance of the mathematical model represents the performance of the Brayton cycle system. In one embodiment, the first determination module 750 may be configured to perform the operation S350 described above, which will not be described in detail herein.

[0165] According to an embodiment of the present disclosure, the mathematical model includes a second loop simulation module and a turbine component simulation module for characterizing physical properties of the turbine component. The input parameters include cooling gas parameters, which include cooling gas temperature.

[0166] The acquisition module 720 may include a first acquisition submodule, which is used to call the cooling gas parameter calculation module to perform the following operations to obtain the cooling gas parameters: based on the hot side temperature of the turbine component simulation module and the temperature of the cooling gas, calculate the cold side temperature of the turbine component simulation module; when the cold side temperature of the turbine component simulation module meets the second preset condition, use the temperature of the cooling gas as the cooling gas parameter.

[0167] According to an embodiment of the present disclosure, the cooling gas parameter calculation module is also used to perform the following operations: when the cold side temperature of the turbine component simulation module does not meet the second preset condition, change the temperature of the cooling gas and recalculate the cold side temperature of the turbine component simulation module until the cold side temperature of the turbine component simulation module meets the second preset condition.

[0168] According to an embodiment of the present disclosure, the mathematical model includes a first circuit simulation module and a sealing assembly simulation module. Input parameters include a leakage gas parameter. The leakage gas parameter is obtained by at least one of the following methods: obtaining the leakage gas parameter by simulating the first circuit simulation module and the sealing assembly simulation module; obtaining the leakage gas parameter based on expert experience; or setting the leakage gas parameter to a preset value.

[0169] According to an embodiment of the present disclosure, the construction module 710 may be used to construct a mathematical model based on the physical principles, connection relationships, and pipeline layout of various components in the Brayton cycle system.

[0170] The performance determination device 700 of the Brayton cycle system also includes an updating module, which is used to perform the following operations when the error between the input parameters and the output parameters does not meet the first preset condition: re-acquire the input parameters of the mathematical model to obtain updated input parameters; input the updated input parameters into the mathematical model for simulation calculation to obtain updated output parameters, until the error between the updated input parameters and the updated output parameters meets the first preset condition, and use the output parameters output by the mathematical model for the last time as the target system parameters.

[0171] According to an embodiment of the present disclosure, reacquiring input parameters of the mathematical model to obtain updated input parameters includes: calculating weighted input parameters based on system input parameters and system output parameters; and obtaining updated input parameters based on the weighted input parameters.

[0172] According to an embodiment of the present disclosure, the Brayton cycle system performance determination device 700 further includes a second determination module, which is configured to use the Brayton cycle system as a target Brayton cycle system when the performance of the Brayton cycle system meets a third preset condition.

[0173] According to an embodiment of the present disclosure, the apparatus 700 for determining the performance of a Brayton cycle system further includes a second updating module. The second updating module is configured to, when the performance of the Brayton cycle system does not satisfy a third preset condition, perform the following operations: modify the structure of the mathematical model to obtain an updated mathematical model; determine the performance of the updated mathematical model until the performance of the updated mathematical model satisfies the third preset condition, and use the Brayton cycle system corresponding to the last updated mathematical model as the target Brayton cycle system.

[0174] According to the embodiments of the present invention, any number of modules, sub-modules, units, and sub-units, or at least part of the functions of any number of them, can be implemented in one module. According to the embodiments of the present invention, any one or more of the modules, sub-modules, units, and sub-units can be split into multiple modules for implementation. According to the embodiments of the present invention, any one or more of the modules, sub-modules, units, and sub-units can be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on a chip, a system on a substrate, a system on a package, an application-specific integrated circuit (ASIC), or can be implemented by hardware or firmware in any other reasonable way of integrating or packaging the circuit, or can be implemented in any one of the three implementation methods of software, hardware, and firmware, or in any appropriate combination of any of them. Alternatively, according to the embodiments of the present invention, one or more of the modules, sub-modules, units, and sub-units can be at least partially implemented as a computer program module, which can perform the corresponding functions when the computer program module is executed.

[0175] For example, any number of the construction module 710, acquisition module 720, simulation calculation module 730, comparison module 740, and first determination module 750 can be combined into a single module / unit / sub-unit, or any one of these modules / units / sub-units can be split into multiple modules / units / sub-units. Alternatively, at least part of the functionality of one or more of these modules / units / sub-units can be combined with at least part of the functionality of other modules / units / sub-units and implemented in a single module / unit / sub-unit. According to an embodiment of the present disclosure, at least one of the construction module 710, acquisition module 720, simulation calculation module 730, comparison module 740, and first determination module 750 can be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on a chip, a system on a substrate, a system on a package, an application specific integrated circuit (ASIC), or can be implemented in hardware or firmware by any other reasonable means of integrating or packaging circuits, or can be implemented in any one of the three implementation methods of software, hardware, and firmware, or any appropriate combination of any of these. Alternatively, at least one of the construction module 710 , the acquisition module 720 , the simulation calculation module 730 , the comparison module 740 and the first determination module 750 may be at least partially implemented as a computer program module, which may perform corresponding functions when executed.

[0176] It should be noted that the data processing system part in the embodiments of the present disclosure corresponds to the data processing method part in the embodiments of the present disclosure. The description of the data processing system part specifically refers to the data processing method part and will not be repeated here.

[0177] Figure 8 A block diagram of an electronic device suitable for implementing the above-described method according to an embodiment of the present disclosure is schematically shown. Figure 8 The electronic device shown is only an example and should not limit the functions and scope of use of the embodiments of the present disclosure.

[0178] like Figure 8As shown, the electronic device 800 according to an embodiment of the present disclosure includes a processor 801, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 802 or a program loaded from a storage unit 808 into a random access memory (RAM) 803. The processor 801 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or a related chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 801 may also include onboard memory for caching purposes. The processor 801 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present disclosure.

[0179] Various programs and data required for the operation of the electronic device 800 are stored in the RAM 803. The processor 801, ROM 802, and RAM 803 are connected to each other via a bus 804. The processor 801 executes the various operations of the method flow according to the embodiment of the present disclosure by executing the programs in the ROM 802 and / or RAM 803. It should be noted that the programs may also be stored in one or more memories other than the ROM 802 and RAM 803. The processor 801 may also execute the various operations of the method flow according to the embodiment of the present disclosure by executing the programs stored in the one or more memories.

[0180] According to an embodiment of the present disclosure, electronic device 800 may further include an input / output (I / O) interface 805, which is also connected to bus 804. Electronic device 800 may also include one or more of the following components connected to I / O interface 805: an input section 806 including a keyboard, mouse, etc.; an output section 807 including devices such as a cathode ray tube (CRT), liquid crystal display (LCD), and speakers; a storage section 808 including a hard disk; and a communication section 809 including a network interface card such as a LAN card or modem. Communication section 809 performs communication processing via a network such as the Internet. A drive 810 is also connected to I / O interface 805 as needed. Removable media 811, such as a magnetic disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed in drive 810 as needed, so that computer programs read from the removable media can be installed into storage section 808 as needed.

[0181] According to an embodiment of the present disclosure, the method flow according to an embodiment of the present disclosure can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a computer-readable storage medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 809, and / or installed from the removable medium 811. When the computer program is executed by the processor 801, the above-mentioned functions defined in the system of the embodiment of the present disclosure are executed. According to an embodiment of the present disclosure, the system, device, apparatus, module, unit, etc. described above can be implemented by a computer program module.

[0182] The present disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments, or may exist independently and not be incorporated into the device / apparatus / system. The computer-readable storage medium carries one or more programs, and when executed, implements the method according to the embodiments of the present disclosure.

[0183] According to embodiments of the present disclosure, a computer-readable storage medium may be a non-volatile computer-readable storage medium. Examples include, but are not limited to, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0184] For example, according to an embodiment of the present disclosure, the computer-readable storage medium may include the ROM 802 and / or the RAM 803 described above and / or one or more memories other than the ROM 802 and the RAM 803 .

[0185] An embodiment of the present disclosure also includes a computer program product, which includes a computer program containing program code for executing the method provided by the embodiment of the present disclosure. When the computer program product is run on an electronic device, the program code is used to enable the electronic device to implement the performance determination method of the Brayton cycle system provided by the embodiment of the present disclosure.

[0186] When the computer program is executed by the processor 801, the above functions defined in the system / device of the embodiment of the present disclosure are performed. According to the embodiment of the present disclosure, the system, device, module, unit, etc. described above can be implemented by a computer program module.

[0187] In one embodiment, the computer program may be stored on a tangible storage medium such as an optical storage device or a magnetic storage device. In another embodiment, the computer program may be transmitted and distributed in the form of a signal on a network medium, downloaded and installed via the communication portion 809, and / or installed from a removable medium 811. The program code contained in the computer program may be transmitted using any appropriate network medium, including but not limited to wireless, wired, or any suitable combination thereof.

[0188] According to an embodiment of the present disclosure, the program code for executing the computer program provided by the embodiment of the present disclosure can be written in any combination of one or more programming languages. Specifically, these computer programs can be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, languages ​​such as Java, C++, Python, "C" or similar programming languages. The program code can be executed entirely on the user computing device, partially on the user device, partially on a remote computing device, or entirely on a remote computing device or server. In cases involving a remote computing device, the remote computing device can be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (for example, using an Internet service provider to connect via the Internet).

[0189] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of the systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each box in the flowchart or block diagram can represent a module, program segment, or part of the code, which contains one or more executable instructions for implementing the specified logical functions. It should also be noted that in some alternative implementations, the functions marked in the boxes can also occur in an order different from that marked in the accompanying drawings. For example, two boxes shown in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, as well as the combination of boxes in the block diagram or flowchart, can be implemented using a dedicated hardware-based system that performs the specified functions or operations, or can be implemented using a combination of dedicated hardware and computer instructions. It will be understood by those skilled in the art that the features described in the various embodiments of the present disclosure can be combined and / or combined in various ways, even if such combinations or combinations are not explicitly described in the present disclosure. In particular, without departing from the spirit and teachings of the present disclosure, the features described in the various embodiments of the present disclosure may be combined and / or coupled in various ways, and all of these combinations and / or couplings fall within the scope of the present disclosure.

[0190] The above describes the embodiments of the present disclosure. However, these embodiments are for illustrative purposes only and are not intended to limit the scope of the present disclosure. Although each embodiment has been described separately above, this does not mean that the measures in each embodiment cannot be advantageously used in combination. Without departing from the scope of the present disclosure, those skilled in the art may make various substitutions and modifications, which should all fall within the scope of the present disclosure.

Claims

1. A method for determining the performance of a Brayton cycle system, comprising: Constructing a mathematical model of a Brayton cycle system, the Brayton cycle system comprising at least one of a first loop, a second loop, a piping assembly, and a turbine component, wherein the first loop is configured to reinject leakage gas generated during operation of the Brayton cycle system into the Brayton cycle system, and the second loop is configured to inject turbine cooling gas into the turbine component for turbine cooling, the mathematical model comprising at least one of a first loop simulation module for characterizing physical properties of the first loop, a second loop simulation module for characterizing physical properties of the second loop, and a piping assembly simulation module for characterizing physical properties of the piping assembly; Obtaining input parameters of the mathematical model, the input parameters including at least one of a leakage gas parameter, a cooling gas parameter, and a pressure loss parameter in the pipeline; Inputting the input parameters into the mathematical model for simulation calculation to obtain output parameters, wherein the leakage gas parameter is input into the first loop simulation module, the cooling gas parameter is input into the second loop simulation module, and the pressure loss parameter in the pipeline is input into the pipeline component simulation module, and the output parameters include parameters after updating the input parameters; comparing the input parameter and the output parameter, and taking the output parameter as a target parameter if an error between the input parameter and the output parameter satisfies a first preset condition; The performance of the mathematical model is determined according to the target parameter, and the performance of the mathematical model represents the performance of the Brayton cycle system.

2. The method for determining the performance of a Brayton cycle system according to claim 1, wherein: The mathematical model includes a second loop simulation module and a turbine component simulation module for characterizing physical properties of the turbine component; The input parameters include cooling gas parameters, and the cooling gas parameters include the flow rate of cooling gas; The obtaining of the input parameters of the mathematical model includes: calling a cooling air parameter calculation module to perform the following operations to obtain the cooling air parameters: Calculating the cold side temperature of the turbine component simulation module according to the hot side temperature of the turbine component simulation module and the flow rate of the cooling gas; When the cold side temperature of the turbine component simulation module meets a second preset condition, the flow rate of the cooling gas is used as a cooling gas parameter.

3. The method for determining the performance of a Brayton cycle system according to claim 2, wherein: The cooling air parameter calculation module is further configured to perform the following operations: When the cold side temperature of the turbine component simulation module does not meet the second preset condition, the flow rate of the cooling gas is changed and the cold side temperature of the turbine component simulation module is recalculated until the cold side temperature of the turbine component simulation module meets the second preset condition.

4. The method for determining the performance of a Brayton cycle system according to claim 1, wherein: The mathematical model includes a first circuit simulation module and a sealing component simulation module; The input parameters include leakage gas parameters; The leakage gas parameters are obtained by at least one of the following methods: The leakage gas parameters are obtained by performing simulation calculations on the first loop simulation module and the sealing component simulation module; Obtaining the leakage gas parameters according to expert experience; The leakage gas parameter is set to a preset value.

5. The method for determining the performance of a Brayton cycle system according to claim 1 , wherein: The mathematical model for constructing the Brayton cycle system includes: The mathematical model is constructed based on the physical principles, connection relationships and pipeline layout of each component in the Brayton cycle system.

6. The method for determining the performance of a Brayton cycle system according to claim 1 , further comprising: When the error between the input parameter and the output parameter does not satisfy the first preset condition, perform the following operations: Re-acquiring the input parameters of the mathematical model to obtain updated input parameters; The updated input parameters are input into the mathematical model for simulation calculation to obtain updated output parameters, until the error between the updated input parameters and the updated output parameters meets the first preset condition, and the output parameters outputted by the mathematical model for the last time are used as the target system parameters.

7. The method for determining the performance of a Brayton cycle system according to claim 6, wherein: Re-acquiring the input parameters of the mathematical model, and obtaining updated input parameters includes: Calculating a weighted input parameter according to the system input parameter and the system output parameter; According to the weighted input parameters, updated input parameters are obtained.

8. The method for determining the performance of a Brayton cycle system according to claim 1, wherein: The input parameters further include at least one of the efficiency, inlet temperature, inlet pressure, outlet temperature, outlet pressure, and expansion ratio of the turbine component module.

9. The method for determining the performance of a Brayton cycle system according to claim 1 , further comprising: When the performance of the Brayton cycle system satisfies a third preset condition, taking the Brayton cycle system as a target Brayton cycle system; When the performance of the Brayton cycle system does not meet the third preset condition, the following operations are performed: changing the structure of the mathematical model to obtain an updated mathematical model; The performance of the updated mathematical model is determined until the performance of the updated mathematical model meets a third preset condition, and the Brayton cycle system corresponding to the mathematical model after the last update is used as the target Brayton cycle system.

10. A device for determining performance of a Brayton cycle system, comprising: a construction module configured to construct a mathematical model of a Brayton cycle system, the Brayton cycle system comprising at least one of a first loop, a second loop, a piping assembly, and a turbine component, the first loop being configured to reinject leakage gas generated during operation of the Brayton cycle system into the Brayton cycle system, the second loop being configured to inject turbine cooling gas into the turbine component for turbine cooling, the mathematical model comprising at least one of a first loop simulation module configured to characterize physical properties of the first loop, a second loop simulation module configured to characterize physical properties of the second loop, and a piping assembly simulation module configured to characterize physical properties of the piping assembly; an acquisition module, configured to acquire input parameters of the mathematical model, the input parameters including at least one of a leakage gas parameter, a cooling gas parameter, and a pressure loss parameter in the pipeline; a simulation calculation module, configured to input the input parameters into the mathematical model for simulation calculation to obtain output parameters, wherein the leakage gas parameter is input into the first loop simulation module, the cooling gas parameter is input into the second loop simulation module, and the pressure loss parameter in the pipeline is input into the pipeline component simulation module, and the output parameters include parameters updated from the input parameters; a comparison module, configured to compare the input parameter with the output parameter, and use the output parameter as a target parameter if an error between the input parameter and the output parameter satisfies a first preset condition; A determination module is used to determine the performance of the mathematical model according to the target parameter, where the performance of the mathematical model represents the performance of the Brayton cycle system.

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