Parameter optimization method of liquid-liquid carbon dioxide energy storage system

Abstract

The invention discloses a parameter optimization method for a liquid-liquid carbon dioxide energy storage system, and relates to the technical field of energy storage, and the method comprises the steps: based on a system architecture of a target energy storage system, combining energy storage and energy release processes, and extracting an intermediate process set which comprises a plurality of energy storage and energy release intermediate processes. And analyzing the intermediate process set to obtain a physical property program set of the energy storage and release intermediate process. And constructing a physical property numerical model of the energy storage system according to the physical property program set, the system architecture and the intermediate process set. Obtaining design working condition information, defining a parameter quantity and a parameter variable, and generating a parameter constraint set and a target set; and inputting the parameter constraint set to the physical property numerical model for initialization, optimizing the parameters through a control variable method based on target set optimization, and obtaining an optimized energy storage parameter set. Therefore, the technical effects of improving the parameter setting effect and improving the energy storage efficiency and economical efficiency are achieved.

Description

Technical Field

[0001] The present invention relates to the field of energy storage technology, and in particular to a parameter optimization method for a liquid-liquid carbon dioxide energy storage system. Background Art

[0002] As a new type of energy storage method, the liquid-liquid carbon dioxide energy storage system utilizes the phase change characteristics of liquid carbon dioxide during the energy storage and release process, which can effectively achieve high energy density and high energy efficiency conversion. It can not only store electrical energy efficiently, but also achieve relatively stable energy release.

[0003] At present, the forms of liquid-liquid carbon dioxide energy storage systems are basically the same, and the difference lies in the parameter settings of different state points. How to obtain the parameters of each state point that maximizes the efficiency of the entire energy storage system after determining the high and low pressure states has never been clearly explored. Therefore, the efficiency of the energy storage system is greatly reduced to a large extent. There are technical problems such as difficulty in setting state point parameters and affecting energy storage efficiency and economy. Summary of the invention

[0004] The present invention provides a parameter optimization method for a liquid-liquid carbon dioxide energy storage system to solve the technical problems in the prior art that the state point parameter setting is difficult and affects the energy storage efficiency and economy, thereby achieving the technical effects of improving the parameter setting effect and enhancing the energy storage efficiency and economy.

[0005] The present invention provides a parameter optimization method for a liquid-liquid carbon dioxide energy storage system, comprising:

[0006] Based on the system architecture of the target energy storage system, an intermediate process set is extracted by combining the energy storage process and the energy release process, wherein the intermediate process set includes multiple energy storage intermediate processes and multiple energy release intermediate processes.

[0007] The intermediate process set is parsed to obtain a physical property program set of a plurality of the energy storage intermediate processes and a plurality of the energy release intermediate processes.

[0008] A physical property numerical model of a target energy storage system is constructed according to the physical property program set, the system architecture and the intermediate process set.

[0009] The design operating condition information of the target energy storage system is obtained, and parameter quantities and parameter variables are defined according to the design operating condition information, and a parameter constraint set and a parameter target set are correspondingly generated.

[0010] The parameter constraint set is input into the physical property numerical model to initialize the model, and the parameter target set is used as the optimization target. The parameter target set is traversed through the control variable method to perform parameter optimization of multiple parameters to obtain an optimized energy storage parameter set.

[0011] In a feasible implementation, the system architecture based on the target energy storage system combines the energy storage process and the energy release process to extract a set of intermediate processes, wherein multiple energy storage intermediate processes include low-pressure preheating gasification, first-stage compression, interstage cooling, and second-stage compression; multiple energy release intermediate processes include high-pressure preheating gasification, first-stage turbine, interstage heating, and second-stage turbine.

[0012] In a feasible implementation, a physical property numerical model of the target energy storage system is constructed based on the physical property program set, the system architecture and the intermediate process set, wherein the physical property numerical model at least includes a carbon dioxide physical property program, a circulating water physical property program, a heat exchanger, a diverter and a mixer.

[0013] In a feasible implementation, the obtaining of design operating condition information of the target energy storage system, defining parameter quantities and parameter variables according to the design operating condition information, and correspondingly generating a parameter constraint set and a parameter target set include:

[0014] The design operating condition information is parsed to extract the fluid parameter set and the equipment parameter set.

[0015] According to the fluid parameter set, low pressure, low pressure temperature, high pressure and high pressure temperature are extracted, defined as the parameter quantities and stored in the parameter constraint set.

[0016] According to the equipment parameter set, the isentropic efficiency and compression ratio of the compressor are extracted, and the isentropic efficiency and turbine ratio of the turbine are extracted, which are defined as the parameter quantities and stored in the parameter constraint set.

[0017] Based on the equipment parameter set, operating condition constraints of the compressor and turbine are extracted and stored in the parameter constraint set.

[0018] In a feasible implementation, the step of obtaining design operating condition information of the target energy storage system, defining parameter quantities and parameter variables according to the design operating condition information, and correspondingly generating a parameter constraint set and a parameter target set also includes:

[0019] According to the fluid parameter set, the preheating temperature difference, the inter-stage cooling temperature difference, the low-pressure gasification preheating temperature difference and the high-pressure gasification preheating temperature difference are extracted and defined as the parameter variables.

[0020] Based on the process timing relationship of the intermediate process set, the plurality of parameter variables are serialized, and the serialization result is output as the parameter target set.

[0021] In a feasible implementation, inputting the parameter constraint set into the physical property numerical model to initialize the model includes:

[0022] A mapping relationship between the parameter constraint set and a plurality of physical property programs in the physical property numerical model is established.

[0023] Based on the mapping relationship and the parameter constraint set, fixed values ​​of corresponding variables of a plurality of the physical property programs are defined.

[0024] Based on the operating condition restrictions, the value spaces of the multiple parameters in the multiple physical property programs are defined.

[0025] In a feasible implementation, the parameter target set is used as the optimization target, and the parameter target set is traversed by the control variable method to perform parameter optimization of multiple parameters to obtain the optimized energy storage parameter set, including:

[0026] The parameter target set is sequentially extracted to determine a first variable, and temporary fixed values ​​of a plurality of parameter variables except the first variable are defined.

[0027] Based on the optimization algorithm, taking the value space as the optimization space and the system efficiency function as the objective function, the first variable is iteratively optimized to obtain a first optimized value of the first variable.

[0028] The parameter target set is extracted in an iterative sequence, the next variable of the first variable is obtained as the second variable, and the temporary fixed value of the first variable is updated with the first optimized value, and the second variable is iteratively optimized to obtain the second optimized value of the second variable.

[0029] The parameter target set is traversed to perform iterative optimization until the optimized values ​​of the plurality of parameter variables are obtained, and the optimized energy storage parameter set is output.

[0030] In a feasible implementation, the system efficiency function is used as the objective function, and the system efficiency function is expressed as:

[0031] E ffi =ET / EC.

[0032] Among them, E ffi Characterizes the system efficiency of the target energy storage system. ET characterizes the power consumed by the compressor. EC characterizes the power consumed by the turbine.

[0033] The present invention discloses a parameter optimization method for a liquid-liquid carbon dioxide energy storage system, comprising: extracting an intermediate process set based on a system architecture of a target energy storage system, combining energy storage and energy release processes, including a plurality of energy storage intermediate processes and a plurality of energy release intermediate processes. Parsing the intermediate process set, obtaining a physical property program set of the energy storage intermediate process and the energy release intermediate process. Constructing a physical property numerical model of the target energy storage system according to the physical property program set, the system architecture and the intermediate process set. Obtaining the design operating condition information of the target energy storage system, defining parameter quantities and parameter variables according to the design operating conditions, and generating a corresponding parameter constraint set and parameter target set. Inputting the parameter constraint set into the physical property numerical model to initialize the model; taking the parameter target set as the optimization target, traversing the parameter target set by a control variable method, optimizing parameters of a plurality of parameter variables, and obtaining an optimized energy storage parameter set. The parameter optimization method for a liquid-liquid carbon dioxide energy storage system disclosed by the present invention solves the technical problems that the state point parameter setting is difficult and affects the energy storage efficiency and economy, and achieves the technical effects of improving the parameter setting effect and improving the energy storage efficiency and economy. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 It is a flow chart of a parameter optimization method of a liquid-liquid carbon dioxide energy storage system of the present invention;

[0035] Figure 2 A schematic diagram of a process for generating a parameter constraint set and a parameter target set in a parameter optimization method for a liquid-liquid carbon dioxide energy storage system according to the present invention;

[0036] Figure 3 It is a schematic diagram of a liquid-liquid carbon dioxide energy storage system in a parameter optimization method of a liquid-liquid carbon dioxide energy storage system of the present invention. DETAILED DESCRIPTION

[0037] The technical solution provided in the embodiments of the present invention is to solve the technical problems existing in the prior art that the state point parameter setting is difficult and affects the energy storage efficiency and economy. The overall idea adopted is as follows:

[0038] Firstly, based on the system architecture of the target energy storage system, in combination with the energy storage process and the energy release process, an intermediate process set is extracted, wherein the intermediate process set includes a plurality of energy storage intermediate processes and a plurality of energy release intermediate processes; then, the intermediate process set is parsed to obtain a physical property program set of the plurality of energy storage intermediate processes and the plurality of energy release intermediate processes; then, a physical property numerical model of the target energy storage system is constructed according to the physical property program set, the system architecture and the intermediate process set; then, the design operating condition information of the target energy storage system is obtained, and parameter quantities and parameter variables are defined according to the design operating condition information, and a parameter constraint set and a parameter target set are generated correspondingly; then, the parameter constraint set is input into the physical property numerical model to initialize the model, and the parameter target set is used as the optimization target, and the parameter target set is traversed through the control variable method to perform parameter optimization of a plurality of parameter variables to obtain an optimized energy storage parameter set.

[0039] The above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods of the specification to better understand the above technical solution. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments of the present invention. It should be understood that the present invention is not limited to the example embodiments used only to explain the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention. In addition, it should be noted that, for the convenience of description, only the parts related to the present invention are shown in the drawings, rather than all of them.

[0040] Embodiment 1

[0041] Figure 1 The present invention is a flow chart of a parameter optimization method for a liquid-liquid carbon dioxide energy storage system, wherein the method comprises:

[0042] Based on the system architecture of the target energy storage system, an intermediate process set is extracted by combining the energy storage process and the energy release process, wherein the intermediate process set includes multiple energy storage intermediate processes and multiple energy release intermediate processes.

[0043] Specifically, the architecture of the target energy storage system refers to the architectural design of the entire energy storage device, including hardware, software and their interacting components, involving energy storage units, control systems, energy management systems and interfaces with other systems. The intermediate process set refers to multiple intermediate states or steps that may exist in the energy storage and release process, involving multiple state transition processes of carbon dioxide materials, including phase transitions and changes in temperature and pressure.

[0044] Specifically, the liquid-liquid carbon dioxide energy storage system realizes energy storage and release through the storage and energy release process of liquid carbon dioxide. Exemplarily, its system architecture includes the following main parts: an energy storage unit, that is, a liquid carbon dioxide storage device, used to store carbon dioxide converted into liquid, the energy storage unit consists of a high-pressure container and a cooling device, wherein liquefied carbon dioxide needs to be stored under a relatively low temperature and high pressure environment, so a high-pressure container is used, and at the same time, in order to maintain the liquid state of carbon dioxide, a cooling device is required to lower the temperature; an energy conversion device, including a compressor and a turbine for liquid carbon dioxide, wherein the compressor is used for the transportation and compression of liquid carbon dioxide, and the turbine is used for energy conversion during the energy release process; an energy management system, responsible for managing the energy flow during the energy storage and release process to ensure efficient energy utilization, including controlling the temperature, pressure and flow rate of carbon dioxide; a heat exchange device, used to adjust the temperature change caused by the expansion of liquid carbon dioxide during the energy release process, and further optimize the energy release process.

[0045] In some embodiments, the system architecture based on the target energy storage system combines the energy storage process and the energy release process to extract a set of intermediate processes, wherein multiple energy storage intermediate processes include low-pressure preheating gasification, first-stage compression, interstage cooling, and second-stage compression; multiple energy release intermediate processes include high-pressure preheating gasification, first-stage turbine, interstage heating, and second-stage turbine.

[0046] Specifically, Figure 3 As shown, in the liquid-liquid carbon dioxide energy storage system, energy is stored and released through compression and expansion operations, and the energy storage process and the energy release process are gradually realized through multiple intermediate processes.

[0047] Specifically, the intermediate process of energy storage includes low-pressure preheating gasification, primary compression, interstage cooling, and secondary compression. Among them, low-pressure preheating gasification refers to the use of a heat exchanger to preheat the gas through a waste heat recovery system or an external heating source during the energy storage process. The gas passes through the preheating stage and enters the compression process at an appropriate temperature condition. By preheating the gas, the workload of the compressor can be reduced and the energy required for gas compression can be reduced, thereby improving the energy storage efficiency; primary compression is the first stage compression operation in the gas energy storage process to achieve initial compression of the gas; the compressed gas needs to be cooled before entering the next stage compressor to reduce the temperature of the gas and improve the efficiency of the subsequent compression process, which is interstage cooling; secondary compression is used to further increase the gas pressure after the first stage compression to achieve the final state required for energy storage.

[0048] Specifically, the intermediate process of energy release includes high-pressure preheating gasification, a first-stage turbine, interstage heating, and a second-stage turbine. Among them, the high-pressure preheating gasification is used to preheat and gasify the liquid carbon dioxide before the energy release process begins, so as to increase its temperature and ensure that it enters the turbine system smoothly. Through high-pressure preheating gasification, the expansion efficiency of the gas can be improved, the energy loss in the energy release process can be reduced, and the energy release capacity of the system can be improved; the first-stage turbine is the energy release process, and the carbon dioxide gas is expanded through the expander or turbine of the first-stage turbine, and its pressure energy is converted into rotational mechanical energy during the gas flow, and can be further converted into electrical energy; during the turbine expansion process, the temperature of the gas will decrease, so the gas needs to be heated to ensure that the turbine system continues to operate efficiently, that is, interstage heating; the second-stage turbine is used to further expand the gas after the first-stage turbine and interstage heating, convert the remaining expansion energy, and improve the energy conversion efficiency in the energy release process.

[0049] Combining the system architecture of the liquid-liquid carbon dioxide energy storage system, each link of the energy storage process and the energy release process, as well as the extracted intermediate process set, can clarify the technical details of energy storage and release, energy flow and conversion pathways, and provide a basis for the use of subsequent physical property programs.

[0050] The intermediate process set is parsed to obtain a physical property program set of a plurality of the energy storage intermediate processes and a plurality of the energy release intermediate processes.

[0051] Specifically, the energy storage and release process mainly involves steps such as compression and gasification. In this process, the physical state, pressure, temperature and other characteristics of the gas will change significantly. Therefore, it is necessary to analyze the key parameters in each intermediate process from the perspective of physical properties, such as temperature, pressure, flow, material state, etc., and conduct detailed physical property analysis for each process to obtain a set of physical property programs for multiple energy storage intermediate processes and multiple energy release intermediate processes.

[0052] Specifically, the physical property program set includes multiple physical property programs, which are used to express the calling relationship between various physical properties (such as temperature, pressure, enthalpy, entropy, etc. of carbon dioxide gas and liquid) in multiple energy storage intermediate processes and multiple energy release intermediate processes, that is, they specify how to calculate the physical property changes of multiple intermediate processes.

[0053] In other words, the physical property program set refers to a set of programs used to describe and calculate the physical property changes of carbon dioxide (CO2) gas and liquid in multiple energy storage and release intermediate processes. The physical property program includes multiple calculation methods, which are used to calculate and describe the relationship and change process of physical properties such as temperature, pressure, enthalpy, entropy, etc. of gas and liquid in the energy storage and release process. The change of physical property parameters is the key to optimizing energy storage and release efficiency, and has an important impact on system performance.

[0054] Optionally, the physical property program set involves the ideal gas state equation, van der Waals equation and RK equation, etc., wherein, for carbon dioxide gas, the ideal gas state equation or the modified state equation (such as van der Waals equation) is used to calculate the temperature, pressure, enthalpy, entropy and other physical properties of the gas; for the calculation of liquid carbon dioxide, the state equation (such as Redlich-Kwong equation) is used to describe the changes in the physical properties of the liquid, and thermodynamic relationships are used to solve the enthalpy, entropy and other physical property parameters of the liquid.

[0055] A physical property numerical model of a target energy storage system is constructed according to the physical property program set, the system architecture and the intermediate process set.

[0056] Specifically, the goal of the physical property numerical model is to simulate the thermodynamic behavior of different components and intermediate processes in the energy storage system in order to optimize system performance and perform simulation analysis. The physical property program set, system architecture and intermediate process set can clearly define the physical property change process of each component in the system, assign corresponding physical property programs to each intermediate process and component, and establish an association relationship between the physical property programs of multiple components and multiple intermediate processes.

[0057] Specifically, through the physical property numerical model of the target energy storage system constructed by the physical property program set, system architecture and intermediate process set, it is possible to calculate the changes in the physical properties of carbon dioxide gas and liquid during different energy storage and release processes, evaluate the system energy efficiency performance, and then optimize the energy storage and release process, thereby improving the overall energy conversion efficiency and economic benefits of the system.

[0058] In some embodiments, a physical property numerical model of the target energy storage system is constructed based on the physical property program set, the system architecture and the intermediate process set, wherein the physical property numerical model at least includes a carbon dioxide physical property program, a circulating water physical property program, a heat exchanger, a diverter, and a mixer.

[0059] Specifically, the carbon dioxide property program is used to describe the changes in the physical properties of carbon dioxide in different stages, and the circulating water property program is used to describe the changes in the physical properties of water used for heat exchange in the system, mainly involving parameters such as temperature, pressure and heat capacity; the heat exchanger is used to calculate the heat exchange process between carbon dioxide and circulating water, involving heat transfer, temperature change, etc.; the diverter is used to distribute the fluid to different paths in the system as needed, and calculate the change in mass flow rate of the fluid during the diversion process; the mixer is used to mix fluids flowing in different paths and calculate the temperature, pressure and flow after mixing.

[0060] The above-mentioned physical property numerical model provides a complete thermodynamic and fluid dynamics calculation framework for the target energy storage system. Through this model, the physical property changes in the system can be accurately calculated and optimized, which helps to improve the overall efficiency and economy of the system.

[0061] The design operating condition information of the target energy storage system is obtained, and parameter quantities and parameter variables are defined according to the design operating condition information, and a parameter constraint set and a parameter target set are correspondingly generated.

[0062] Specifically, before performing system parameter optimization, first determine the parameter target set to be optimized and the known given constant parameter constraint set, where, exemplarily, the parameter constraint set includes defining the fluid, high and low pressure values ​​and corresponding temperature parameters, as well as the isentropic efficiency, compression ratio and turbine pressure ratio of the compressor and turbine; the parameter target set includes the parameters of each state point of the energy storage process and the energy release process.

[0063] Specifically, the design operating conditions refer to the working state and performance requirements of the target energy storage system under specific operating conditions, which are determined by the system requirements, equipment capabilities and operating environment. Exemplary conditions include the working fluid state (temperature, pressure, flow rate, phase state, etc.), heat exchanger performance, circulating water system performance, etc.

[0064] By defining parameter quantities and variable parameters and establishing parameter constraint sets and parameter target sets, a systematic framework is provided for parameter optimization of the target energy storage system, which not only helps to optimize the energy efficiency, economy and environmental impact of the system, but also ensures the stable operation of the system under different working conditions.

[0065] In some embodiments, Figure 2 As shown, the design operating condition information of the target energy storage system is obtained, and parameter quantities and parameter variables are defined according to the design operating condition information, and a parameter constraint set and a parameter target set are correspondingly generated, including:

[0066] The design operating condition information is parsed to extract a fluid parameter set and an equipment parameter set; based on the fluid parameter set, low pressure, low pressure temperature, high pressure and high pressure temperature are extracted, defined as the parameter quantities and stored in the parameter constraint set; based on the equipment parameter set, the isentropic efficiency and compression ratio of the compressor are extracted, and the isentropic efficiency and turbine ratio of the turbine are extracted, defined as the parameter quantities and stored in the parameter constraint set; based on the equipment parameter set, the operating condition restrictions of the compressor and the turbine are extracted and stored in the parameter constraint set.

[0067] Specifically, the fluid parameter set includes parameters that describe the characteristics of carbon dioxide gas or liquid, such as temperature, pressure, flow rate, etc. For the target energy storage system, the fluid parameter set mainly involves: low pressure, the low-pressure side pressure during the energy storage process, which is used to define the initial compression pressure of carbon dioxide during the energy storage process; low pressure temperature, that is, the low-pressure side temperature, which is used to describe the initial thermal state of the carbon dioxide working fluid before compression; high pressure pressure, the high-pressure side pressure during the energy storage process, which is used to define the final high-pressure state of the carbon dioxide working fluid after energy storage; high pressure temperature, the high-pressure side temperature, which is used to describe the state of the carbon dioxide working fluid after compression.

[0068] Specifically, the equipment parameter set includes parameters about the performance and operating conditions of various key equipment in the system (such as compressors and turbines), such as the isentropic efficiency and compression ratio of the compressor, the isentropic efficiency and turbine ratio of the turbine. The parameters of the equipment parameter set directly affect the design of the equipment, the operating efficiency and the overall performance of the system.

[0069] Specifically, the operating condition limitations of the equipment include the range of operating parameters that the equipment must comply with during operation, which is used to ensure the safe and efficient operation of the equipment and prevent damage caused by exceeding the design capacity of the equipment.

[0070] Specifically, the parameters are fixed parameters in the system design, which are directly derived from the design operating conditions information and will not change during the optimization process. In other words, the parameters define the basic physical conditions of the system under different operating conditions.

[0071] In some embodiments, the step of acquiring design operating condition information of the target energy storage system, defining parameter quantities and parameter variables according to the design operating condition information, and correspondingly generating a parameter constraint set and a parameter target set further includes:

[0072] According to the fluid parameter set, the preheating temperature difference, interstage cooling temperature difference, low-pressure gasification preheating temperature difference and high-pressure gasification preheating temperature difference are extracted and defined as the parameter variables; based on the process timing relationship of the intermediate process set, multiple parameter variables are serialized, and the serialization results are output as the parameter target set. Specifically, the parameter variables are parameters that can be adjusted during the design or operation process to optimize the performance of the system. Multiple parameter variables are related to the working conditions of the equipment, the load of the system, and the environmental conditions. The parameter variables include preheating temperature difference, interstage cooling temperature difference, low-pressure gasification preheating temperature difference and high-pressure gasification preheating temperature difference.

[0073] Among them, the preheating temperature difference refers to the temperature difference when the carbon dioxide working fluid passes through the preheating device, that is, the difference between the initial temperature of the gas and the final preheating temperature in the process of the system heating the carbon dioxide gas after the pressure of the carbon dioxide working fluid in the low-pressure liquid storage tank is released to an appropriate temperature; the interstage cooling temperature difference refers to the temperature change of the gas after each stage of compression in the multi-stage compression process. By controlling the temperature difference through intermediate cooling, the system efficiency can be improved and overheating can be avoided; the low-pressure gasification preheating temperature difference is the temperature change of the gas in the preheating stage during the low-pressure gasification process; the high-pressure gasification preheating temperature difference is similar to the low-pressure gasification preheating temperature difference, but this temperature difference is the preheating temperature difference during the gasification process on the high-pressure side.

[0074] Specifically, the parameter target set defines the target object of system optimization, including multiple parameter variables. By parsing the design operating condition information, extracting the fluid and equipment parameter sets, defining parameter quantities and parameter variables, and generating parameter constraint sets and parameter target sets, a systematic and quantitative framework can be provided for the design of the target energy storage system.

[0075] Specifically, the intermediate process set of the target energy storage system defines all links from gas compression to expansion and energy release, and there is a time sequence and operation sequence relationship between different processes. The parameters of each process will be affected by the previous process. For example, the preheating temperature difference of the low-pressure gas directly affects the efficiency of the first-stage compression, and the inter-stage cooling temperature difference affects the efficiency of the second-stage compression.

[0076] Specifically, based on the process timing relationship, the parameter variables are serialized in time order. The serialization of the parameter variables facilitates the subsequent reasonable transfer and optimization of multiple parameter variables in sequence according to the actual order of system operation.

[0077] The parameter constraint set is input into the physical property numerical model to initialize the model, and the parameter target set is used as the optimization target. The parameter target set is traversed through the control variable method to perform parameter optimization of multiple parameters to obtain an optimized energy storage parameter set.

[0078] Specifically, the parameter constraint set is input into the physical property numerical model to initialize the model, that is, the initial state of the system is determined according to the input parameters to ensure that the model can correctly simulate the starting conditions of each process.

[0079] Specifically, after the model is initialized, the system parameters are adjusted through the optimization algorithm to find the optimal energy storage parameter set, which involves traversing the parameter target set through the control variable method, that is, optimizing different system parameters separately, gradually adjusting each parameter, and calculating its impact on system performance, and finally optimizing the performance of the energy storage system.

[0080] In some embodiments, inputting the parameter constraint set into the physical property numerical model to initialize the model includes:

[0081] A mapping relationship between the parameter constraint set and a plurality of physical property programs in the physical property numerical model is established; based on the mapping relationship and the parameter constraint set, fixed values ​​of corresponding variables of a plurality of the physical property programs are defined; based on the operating condition restrictions, the value space of a plurality of the parameter variables in the plurality of the physical property programs is defined.

[0082] Specifically, the parameter constraint set is mapped to each physical property program in the physical property numerical model to ensure that each physical property program can be initialized according to the constraints and physical limitations in the design. Through the above mapping, the physical property numerical model can obtain the state and constraints that are consistent with the design conditions during initialization, ensuring that subsequent optimization and simulation calculations have a reasonable basis.

[0083] Specifically, according to the operating condition restrictions of the system, the value space of multiple parameters in the physical property program is defined to ensure that parameter changes during the optimization process will not violate physical and equipment restrictions. The operating condition restrictions include equipment pressure restrictions and equipment temperature restrictions.

[0084] Specifically, the above constraints and value spaces provide boundaries for subsequent optimization calculations, ensuring that the design and physical capabilities of the device or system are not exceeded when adjusting the parameters.

[0085] In some embodiments, taking the parameter target set as the optimization target, traversing the parameter target set by a control variable method to perform parameter optimization of multiple parameters, and obtaining an optimized energy storage parameter set, includes:

[0086] The parameter target set is sequentially extracted to determine the first variable, and temporary fixed values ​​of multiple parameter variables except the first variable are defined; based on the optimization algorithm, the value space is used as the optimization space, and the system efficiency function is used as the objective function to iteratively optimize the first variable and obtain a first optimized value of the first variable; the parameter target set is iteratively extracted to obtain the next variable of the first variable as the second variable, and the temporary fixed value of the first variable is updated with the first optimized value, and the second variable is iteratively optimized to obtain a second optimized value of the second variable; the parameter target set is traversed to iteratively optimize until the optimized values ​​of multiple parameter variables are obtained, and the output is the optimized energy storage parameter set.

[0087] Specifically, the parameter target set is traversed through the control variable method, and multiple parameter variables are gradually optimized. The core idea of ​​the control variable method is "optimization one by one" - that is, a part of the parameter variables is fixed in each round of optimization, and one of the variables is iteratively adjusted to find the optimal solution before optimizing the next variable, and finally a set of optimal energy storage parameter sets is obtained.

[0088] Specifically, first, a variable is selected from the parameter target set as the "first variable", and other variables are used as temporary fixed values, that is, not all variables are optimized at the same time, but optimized in steps to avoid unnecessary computational complexity caused by changes in multiple variables; then, the "first variable" is iteratively optimized through the optimization algorithm, that is, different values ​​of the first variable are tried, the value of the objective function (that is, the system efficiency function) is calculated, and then the value of the first variable that maximizes (or minimizes) the objective function is selected; then, based on the previous optimization, the first optimization value (that is, the optimized preheating temperature difference) is used to update the temporary fixed value of the first variable, and the control variable method is used to continue to optimize the second variable. The optimization process is similar to the optimization process of the first variable. The value space of the second variable is explored through the optimization algorithm and gradually adjusted until the best second optimization value is found.

[0089] Furthermore, each parameter is optimized sequentially according to the steps of the control variable method. In each round of optimization, the optimized variables are fixed and the current variables are optimized. When the optimization process of all parameter variables is completed, the optimal solution of all variables is obtained and output as the optimized energy storage parameter set. Optionally, the optimization process can set termination conditions, such as reaching the maximum number of iterations or the objective function value reaching a predetermined value.

[0090] Through the above steps, the control variable method is used to gradually optimize multiple parameters of the energy storage system. The output optimized energy storage parameter set can help improve the performance of the energy storage system, including improving energy conversion efficiency, reducing energy loss, optimizing operating costs, etc.

[0091] In some implementations, the system efficiency function is used as the objective function, and the system efficiency function is expressed as:

[0092] E ffi =ET / EC;

[0093] Among them, E ffi Characterizes the system efficiency of the target energy storage system; ET characterizes the power consumed by the compressor; EC characterizes the power consumed by the turbine.

[0094] Specifically, the system efficiency function is used to measure the overall operating efficiency of the energy storage system. The system efficiency function is defined as the ratio of the power consumed by the compressor (ET) to the power consumed by the turbine (EC), wherein the power consumption of the compressor is related to the pressure increment, flow rate and isentropic efficiency required to compress the gas, and the power consumption of the turbine (EC) is related to the pressure, flow rate and efficiency of the expanding gas.

[0095] In summary, the parameter optimization method of a liquid-liquid carbon dioxide energy storage system provided by the present invention has the following technical effects:

[0096] By combining the energy storage and energy release processes with the system architecture of the target energy storage system, an intermediate process set is extracted, including multiple energy storage intermediate processes and multiple energy release intermediate processes. The intermediate process set is parsed to obtain the physical property program set of the energy storage intermediate process and the energy release intermediate process. According to the physical property program set, the system architecture and the intermediate process set, a physical property numerical model of the target energy storage system is constructed. The design operating condition information of the target energy storage system is obtained, and the parameter quantity and parameter variable are defined according to the design operating condition to generate the corresponding parameter constraint set and parameter target set. The parameter constraint set is input into the physical property numerical model to initialize the model; with the parameter target set as the optimization target, the parameter target set is traversed through the control variable method, and multiple parameter variables are optimized to obtain the optimized energy storage parameter set, thereby achieving the technical effect of improving the parameter setting effect and improving the energy storage efficiency and economy.

[0097] It should be understood that the embodiments disclosed in the present invention and the above description can enable those skilled in the art to use the present invention to implement the present invention. At the same time, the present invention is not limited to the above-mentioned embodiments. It should be understood that those skilled in the art can still modify the technical solutions recorded in the above-mentioned embodiments, or replace some of the technical features therein by equivalents; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the protection scope of the present invention.

Claims

1. A parameter optimization method for a liquid-liquid carbon dioxide energy storage system, characterized in that: The method comprises: Based on the system architecture of the target energy storage system, combining the energy storage process and the energy release process, extracting an intermediate process set, wherein the intermediate process set includes multiple energy storage intermediate processes and multiple energy release intermediate processes; Parsing the intermediate process set to obtain a physical property program set of a plurality of the energy storage intermediate processes and a plurality of the energy release intermediate processes; Constructing a physical property numerical model of a target energy storage system according to the physical property program set, the system architecture and the intermediate process set; Acquire design operating condition information of the target energy storage system, and define parameter quantities and parameter variables according to the design operating condition information, and correspondingly generate a parameter constraint set and a parameter target set; The parameter constraint set is input into the physical property numerical model to initialize the model, and the parameter target set is used as the optimization target. The parameter target set is traversed through the control variable method to perform parameter optimization of multiple parameters to obtain an optimized energy storage parameter set.

2. A parameter optimization method for a liquid-liquid carbon dioxide energy storage system according to claim 1, characterized in that: The system architecture based on the target energy storage system combines the energy storage process and the energy release process to extract the intermediate process set, wherein multiple energy storage intermediate processes include low-pressure preheating gasification, first-stage compression, interstage cooling, and second-stage compression; multiple energy release intermediate processes include high-pressure preheating gasification, first-stage turbine, interstage heating, and second-stage turbine.

3. A parameter optimization method for a liquid-liquid carbon dioxide energy storage system according to claim 2, characterized in that: According to the physical property program set, the system architecture and the intermediate process set, a physical property numerical model of the target energy storage system is constructed, wherein the physical property numerical model at least includes a carbon dioxide physical property program, a circulating water physical property program, a heat exchanger, a splitter and a mixer.

4. A parameter optimization method for a liquid-liquid carbon dioxide energy storage system according to claim 3, characterized in that: The step of obtaining design operating condition information of the target energy storage system, defining parameter quantities and parameter variables according to the design operating condition information, and correspondingly generating a parameter constraint set and a parameter target set includes: Analyze the design operating condition information and extract the fluid parameter set and the equipment parameter set; According to the fluid parameter set, extracting low pressure, low pressure temperature, high pressure and high pressure temperature, defining them as the parameter quantities and storing them in the parameter constraint set; According to the equipment parameter set, extracting the isentropic efficiency and compression ratio of the compressor, extracting the isentropic efficiency and turbine ratio of the turbine, defining them as the parameter quantities and storing them in the parameter constraint set; Based on the equipment parameter set, operating condition constraints of the compressor and turbine are extracted and stored in the parameter constraint set.

5. A parameter optimization method for a liquid-liquid carbon dioxide energy storage system according to claim 4, characterized in that: The step of obtaining design operating condition information of the target energy storage system, defining parameter quantities and parameter variables according to the design operating condition information, and correspondingly generating a parameter constraint set and a parameter target set, further includes: According to the fluid parameter set, extract the preheating temperature difference, the inter-stage cooling temperature difference, the low-pressure gasification preheating temperature difference and the high-pressure gasification preheating temperature difference, and define them as the parameter variables; Based on the process timing relationship of the intermediate process set, the plurality of parameter variables are serialized, and the serialization result is output as the parameter target set.

6. A parameter optimization method for a liquid-liquid carbon dioxide energy storage system according to claim 5, characterized in that: Inputting the parameter constraint set into the physical property numerical model to initialize the model includes: Establishing a mapping relationship between the parameter constraint set and a plurality of physical property programs in the physical property numerical model; Based on the mapping relationship and the parameter constraint set, defining fixed values ​​of corresponding variables of a plurality of the physical property programs; Based on the operating condition restrictions, the value spaces of the multiple parameters in the multiple physical property programs are defined.

7. A parameter optimization method for a liquid-liquid carbon dioxide energy storage system according to claim 6, characterized in that: Taking the parameter target set as the optimization target, traversing the parameter target set by the control variable method to optimize the parameters of multiple parameters, and obtaining the optimized energy storage parameter set, including: Sequentially extracting the parameter target set, determining a first variable, and defining temporary fixed values ​​of a plurality of parameter variables except the first variable; Based on the optimization algorithm, taking the value space as the optimization space and the system efficiency function as the objective function, performing iterative optimization of the first variable to obtain a first optimized value of the first variable; Iteratively extract the parameter target set in sequence, obtain the next variable of the first variable as the second variable, update the temporary fixed value of the first variable with the first optimized value, perform iterative optimization of the second variable, and obtain a second optimized value of the second variable; The parameter target set is traversed to perform iterative optimization until the optimized values ​​of the plurality of parameter variables are obtained, and the optimized energy storage parameter set is output.

8. A parameter optimization method for a liquid-liquid carbon dioxide energy storage system according to claim 7, characterized in that: The system efficiency function is taken as the objective function, and the system efficiency function is expressed as: From ffi =ET / EC; Among them, E ffi Characterizes the system efficiency of the target energy storage system; ET characterizes the power consumed by the compressor; EC characterizes the power consumed by the turbine.

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