A Parameter Optimization Method for a Liquid-Liquid Carbon Dioxide Energy Storage System

Abstract

The present invention discloses a method for optimizing parameters of a liquid-liquid carbon dioxide energy storage system, which relates to the technical field of energy storage. The method includes: based on the system architecture of the target energy storage system, combining the energy storage and energy release processes, extracting an intermediate process set, which includes a plurality of energy storage and energy release intermediate processes. Analyze the intermediate process set to obtain the physical property program set of the energy storage and energy release intermediate processes. According to the physical property program set, the system architecture and the intermediate process set, construct a physical property numerical model of the energy storage system. Obtain the design condition information, define the reference constants and reference variables, and generate a parameter constraint set and a target set. Input the parameter constraint set into the physical property numerical model for initialization, optimize based on the target set, and optimize the reference variables by the control variable method to obtain an optimized energy storage parameter set. Furthermore, the technical effects of improving the parameter setting effect, enhancing the energy storage efficiency and economy are achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of energy storage, and particularly relates to a method for optimizing parameters of 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 energy release processes, and can effectively achieve high energy density and relatively high energy efficiency conversion. It can not only store electrical energy efficiently, but also achieve relatively stable energy release.

[0003] Currently, 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 parameter values of each state point that maximize the efficiency of the entire energy storage system after determining the high and low pressure states has not been clearly explored. Therefore, to a great extent, the efficiency of the energy storage system is greatly reduced. There are technical problems such as the difficulty in setting state point parameters, which affect the energy storage efficiency and economy. Summary of the Invention

[0004] The present invention provides a method for optimizing parameters of a liquid-liquid carbon dioxide energy storage system to solve the technical problems in the prior art of the difficulty in setting state point parameters, which affect the energy storage efficiency and economy, and to achieve the technical effects of improving the parameter setting effect, enhancing the energy storage efficiency and economy.

[0005] A method for optimizing parameters of a liquid-liquid carbon dioxide energy storage system provided by the present invention includes:

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

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

[0008] 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.

[0009] Obtain the design condition information of the target energy storage system, define reference quantities and reference variables according to the design condition information, and correspondingly generate a parameter constraint set and a parameter target set.

[0010] Input the parameter constraint set into the physical property numerical model for model initialization, and use the parameter target set as the optimization target. Through the control variable method, traverse the parameter target set to optimize the parameters of multiple reference variables, and obtain an optimized energy storage parameter set.

[0011] In a feasible implementation, the system architecture of the target energy storage system combines the energy storage process and the energy release process to extract the intermediate process set. Among them, multiple energy storage intermediate processes include low-pressure preheating gasification, primary compression, inter-stage cooling, and secondary compression, and multiple energy release intermediate processes include high-pressure preheating gasification, primary turbine, inter-stage heating, and secondary turbine.

[0012] In a feasible implementation, 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. Among them, 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, obtain the design condition information of the target energy storage system, define the reference quantities and reference variables according to the design condition information, and correspondingly generate a parameter constraint set and a parameter target set, including:

[0014] Analyze the design condition information and extract the fluid parameter set and the equipment parameter set.

[0015] According to the fluid parameter set, extract the low-pressure pressure, low-pressure temperature, high-pressure pressure, and high-pressure temperature, define them as the reference quantities, and store them in the parameter constraint set.

[0016] According to the equipment parameter set, extract the isentropic efficiency and compression ratio of the compressor, and extract the isentropic efficiency and turbine ratio of the turbine, define them as the reference quantities, and store them in the parameter constraint set.

[0017] According to the equipment parameter set, extract the operating condition limits of the compressor and the turbine and store them in the parameter constraint set.

[0018] In a feasible implementation, obtain the design condition information of the target energy storage system, define the reference quantities and reference variables according to the design condition information, and correspondingly generate a parameter constraint set and a parameter target set, further including:

[0019] According to the fluid parameter set, extract the preheating temperature difference, inter-stage cooling temperature difference, low-pressure gasification preheating temperature difference, and high-pressure gasification preheating temperature difference, and define them as the reference variables.

[0020] Based on the process time sequence relationship of the intermediate process set, serialize multiple reference variables, and output the serialization result as the parameter target set.

[0021] In a feasible implementation, input the parameter constraint set into the physical property numerical model for model initialization, including:

[0022] Establish the mapping relationship between the parameter constraint set and multiple physical property programs in the physical property numerical model.

[0023] Define fixed values of corresponding variables of multiple physical property programs based on the mapping relationship and the parameter constraint set.

[0024] Define the value spaces of multiple parameter variables in multiple physical property programs based on the operating condition limitations.

[0025] In a feasible implementation, taking the parameter target set as the optimization objective, traverse the parameter target set by the control variable method to optimize the parameters of multiple parameter variables, and obtain an optimized energy storage parameter set, including:

[0026] Sequentially extract the parameter target set, determine the first variable, and define temporary fixed values of multiple parameter variables except the first variable.

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

[0028] Iteratively and sequentially extract the parameter target set, 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 the second optimized value of the second variable.

[0029] Traverse the parameter target set for iterative optimization until the optimized values of multiple parameter variables are obtained, and output them as the optimized energy storage parameter set.

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

[0031] E ffi = ET / EC.

[0032] Where, 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 method for optimizing parameters of a liquid-liquid carbon dioxide energy storage system, including: based on the system architecture of the target energy storage system, combining the energy storage and energy release processes, extracting an intermediate process set, which includes a plurality of energy storage intermediate processes and a plurality of energy release intermediate processes. Analyze the intermediate process set to obtain the physical property program sets of the energy storage intermediate processes and the energy release intermediate processes. According to the physical property program sets, the system architecture, and the intermediate process set, construct a physical property numerical model of the target energy storage system. Obtain the design condition information of the target energy storage system, define the reference quantities and reference variables according to the design conditions, and generate the corresponding parameter constraint set and parameter target set. Input the parameter constraint set into the physical property numerical model for model initialization; taking the parameter target set as the optimization target, traverse the parameter target set by the control variable method, optimize the parameters of multiple reference variables, and obtain the optimized energy storage parameter set. The method for optimizing parameters of a liquid-liquid carbon dioxide energy storage system disclosed by the present invention solves the technical problems of difficult state point parameter setting and affecting energy storage efficiency and economy, and realizes the technical effects of improving the parameter setting effect, enhancing energy storage efficiency and economy. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 It is a schematic flow chart of the method for optimizing parameters of a liquid-liquid carbon dioxide energy storage system of the present invention;

[0035] Figure 2 It is a schematic flow chart of generating a parameter constraint set and a parameter target set in the method for optimizing parameters of a liquid-liquid carbon dioxide energy storage system of the present invention;

[0036] Figure 3 It is a schematic diagram of a liquid-liquid carbon dioxide energy storage system in the method for optimizing parameters of a liquid-liquid carbon dioxide energy storage system of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0037] In the embodiments of the present invention, the overall idea adopted for solving the technical problems of difficult state point parameter setting and affecting energy storage efficiency and economy existing in the prior art is as follows:

[0038] First, based on the system architecture of the target energy storage system, combining the energy storage process and the energy release process, an intermediate process set is extracted, where the intermediate process set includes multiple energy storage intermediate processes and multiple energy release intermediate processes; then, the intermediate process set is parsed to obtain the physical property program sets of the multiple energy storage intermediate processes and the multiple energy release intermediate processes; then, according to the physical property program sets, the system architecture, and the intermediate process set, a physical property numerical model of the target energy storage system is constructed; next, the design condition information of the target energy storage system is obtained, and the reference constants and reference variables are defined according to the design condition information, and a parameter constraint set and a parameter target set are correspondingly generated; furthermore, the parameter constraint set is input into the physical property numerical model for model initialization, and with the parameter target set as the optimization target, the parameter optimization of multiple reference variables is performed by traversing the parameter target set through the method of controlling variables to obtain an optimized energy storage parameter set.

[0039] The above technical solutions will be described in detail below in conjunction with the accompanying drawings of the specification and specific embodiments to better understand the above technical solutions. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments of the present invention. It should be understood that the present invention is not limited to the exemplary embodiments for explaining the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention. In addition, it should be noted that, for the sake of description, only the parts related to the present invention are shown in the drawings rather than all.

[0040] Embodiment 1

[0041] Figure 1 It is a schematic flowchart of a parameter optimization method for a liquid-liquid carbon dioxide energy storage system of the present invention, where the method includes:

[0042] Based on the system architecture of the target energy storage system, combining the energy storage process and the energy release process, an intermediate process set is extracted, where 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 architecture 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, while the intermediate process set refers to multiple intermediate states or steps that may exist during the energy storage and energy release processes, involving multiple state conversion 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 processes of liquid carbon dioxide. Exemplarily, its system architecture includes the following main parts: an energy storage unit, i.e., a liquid carbon dioxide storage device, which is used to store carbon dioxide converted into a liquid state. The energy storage unit consists of a high-pressure container and a cooling device. Among them, liquefied carbon dioxide needs to be stored under low temperature and high-pressure environments, so a high-pressure container is used. At the same time, to maintain the liquid state of carbon dioxide, a cooling device is required to reduce the temperature; an energy conversion device, including a compressor and a turbine for liquid carbon dioxide. Among them, 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, which is responsible for managing the energy flow during energy storage and release processes to ensure efficient energy utilization, including controlling the temperature, pressure, and flow rate of carbon dioxide; a heat exchange device, which is used to adjust the temperature change caused by the expansion of liquid carbon dioxide during the energy release process to further optimize the energy release process.

[0045] In some embodiments, for the system architecture of the target energy storage system, by combining the energy storage process and the energy release process, an intermediate process set is extracted. Among them, multiple energy storage intermediate processes include low-pressure preheating and gasification, primary compression, inter-stage cooling, and secondary compression, and multiple energy release intermediate processes include high-pressure preheating and gasification, primary turbine, inter-stage heating, and secondary turbine.

[0046] Specifically, as Figure 3 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 energy storage intermediate processes include low-pressure preheating and gasification, primary compression, inter-stage cooling, and secondary compression. Among them, low-pressure preheating and gasification means that during the energy storage process, through a waste heat recovery system or an external heat source, a heat exchanger is used to preheat the gas. After the gas passes through the preheating stage, it enters the compression process under appropriate temperature conditions. By preheating the gas, the working load of the compressor can be reduced, the energy required for gas compression can be decreased, and thus the energy storage efficiency can be improved; primary compression is the first-stage compression operation in the gas energy storage process to achieve the preliminary compression of the gas; before the compressed gas enters the next-stage compressor, it needs to be cooled to reduce the temperature of the gas and improve the efficiency of the subsequent compression process, which is inter-stage cooling; secondary compression is used to further increase the gas pressure after primary compression to reach the final state required for energy storage.

[0048] Specifically, the intermediate energy release process includes high-pressure preheating and gasification, a first-stage turbine, inter-stage heating, and a second-stage turbine. Among them, high-pressure preheating and gasification is used to preheat and gasify liquid carbon dioxide before the start of the energy release process to increase its temperature and ensure smooth entry into the turbine system. Through high-pressure preheating and gasification, the expansion efficiency of the gas can be improved, energy loss during the energy release process can be reduced, and the energy release capacity of the system can be enhanced; the first-stage turbine is the energy release process, and the carbon dioxide gas expands through the expander or turbine of the first-stage turbine, converting its pressure energy into rotational mechanical energy during gas flow and can be further converted into electrical energy; during the turbine expansion process, the temperature of the gas will decrease, so it is necessary to heat the gas to ensure the continued efficient operation of the turbine system, that is, inter-stage heating; the second-stage turbine is used to further expand the gas after the first-stage turbine and inter-stage heating, converting the remaining expansion energy and improving the energy conversion efficiency during the energy release process.

[0049] Combined with the system framework of the liquid-liquid carbon dioxide energy storage system, each link of the energy storage process and the energy release process, and the extracted intermediate process set, the technical details of energy storage and energy release, the energy flow and conversion pathways can be clarified, providing a basis for the use of subsequent physical property programs.

[0050] Analyze the intermediate process set to obtain the physical property program sets of multiple energy storage intermediate processes and multiple energy release intermediate processes.

[0051] Specifically, the energy storage and energy release processes mainly involve steps such as compression and gasification. During this process, the physical state, pressure, temperature and other characteristics of the gas will change significantly. Therefore, from the perspective of physical properties, key parameters in each intermediate process, such as temperature, pressure, flow rate, and substance state, need to be analyzed, and a detailed physical property analysis is carried out for each process to obtain the physical property program sets of multiple energy storage intermediate processes and multiple energy release intermediate processes.

[0052] Specifically, the physical property program set includes multiple physical property programs, and the multiple physical property programs are used to express the call relationships of various physical properties (such as the 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, it stipulates how to calculate the physical property changes of multiple intermediate processes.

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

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

[0055] Construct a physical property numerical model of the target energy storage system according to the physical property assembly, the system framework, 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 for system performance optimization and simulation analysis. Among them, through the physical property assembly, system framework, and intermediate process set, the physical property change process of each component in the system can be clearly defined, a corresponding physical property program can be assigned to each intermediate process and component, and the association relationship between the physical property programs of multiple components and multiple intermediate processes can be established.

[0057] Specifically, the physical property numerical model of the target energy storage system constructed through the physical property assembly, system framework, and intermediate process set can calculate the physical property changes of carbon dioxide gas and liquid in different energy storage and energy release processes, evaluate the energy efficiency performance of the system, and then optimize the energy storage and release processes to improve 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 according to the physical property assembly, the system framework, and the intermediate process set, where 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 physical property program is used to describe the physical property changes of carbon dioxide in different stages, and the circulating water physical property program is used to describe the physical property changes of the 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 as needed in the system and calculate the mass flow rate change of the fluid during the diversion process; the mixer is used to mix the fluids flowing in different paths and calculate the temperature, pressure, and flow rate after mixing.

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

[0061] Obtain the design condition information of the target energy storage system, define the reference quantities and variables according to the design condition information, and correspondingly generate a parameter constraint set and a parameter target set.

[0062] Specifically, before optimizing the system parameters, first determine the parameter target set to be optimized and the parameter constraint set that is known and given as unchanged. Among them, by way of example, the parameter constraint set includes defining the fluid, the high and low pressure values and the 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 state point parameters of the energy storage process and the energy release process.

[0063] Specifically, the design condition refers to the working state and performance requirements of the target energy storage system under specific operating conditions, which are determined by the system's requirements, the capabilities of the equipment, and the operating environment. By way of example, it includes the working fluid state (temperature, pressure, flow rate, phase state, etc.), the performance of the heat exchanger, the performance of the circulating water system, etc.

[0064] By defining the reference quantities and variables, and establishing a parameter constraint set and a parameter target set, it provides a systematic framework for the 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 operating conditions.

[0065] In some embodiments, as Figure 2 shown, the obtaining of the design condition information of the target energy storage system, defining the reference quantities and variables according to the design condition information, and correspondingly generating a parameter constraint set and a parameter target set includes:

[0066] Analyze the design condition information, and extract the fluid parameter set and the equipment parameter set; according to the fluid parameter set, extract the low pressure, low pressure temperature, high pressure and high pressure temperature, define them as the reference quantities and store them in the parameter constraint set; according to the equipment parameter set, extract the isentropic efficiency and compression ratio of the compressor, extract the isentropic efficiency and turbine ratio of the turbine, define them as the reference quantities and store them in the parameter constraint set; according to the equipment parameter set, extract the operating condition limits of the compressor and turbine and store them in the parameter constraint set.

[0067] Specifically, the fluid parameter set includes parameters describing 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 pressure, the pressure on the low-pressure side 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 temperature on the low-pressure side, which is used to describe the initial thermal state of the carbon dioxide working medium before compression; high-pressure pressure, the pressure on the high-pressure side during the energy storage process, which is used to define the final high-pressure state of the carbon dioxide working medium after energy storage; high-pressure temperature, the temperature on the high-pressure side, which is used to describe the state of the compressed carbon dioxide working medium.

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

[0069] Specifically, the operating condition limits 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 reference quantity is a fixed parameter in the system design, directly obtained from the design condition information and will not change during the optimization process. In other words, the reference quantity defines the basic physical conditions of the system under different operating conditions.

[0071] In some embodiments, the method of obtaining the design condition information of the target energy storage system, defining the reference quantity and reference variables according to the design 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, inter-stage cooling temperature difference, low-pressure gasification preheating temperature difference, and high-pressure gasification preheating temperature difference are extracted and defined as the reference variables; based on the process time sequence relationship of the intermediate process set, multiple reference variables are serialized, and the serialized result is output as the parameter target set. Specifically, the reference variable is a parameter that can be adjusted during the design or operation process to optimize the performance of the system. Multiple reference variables are related to the working conditions of the equipment, the load of the system, and environmental conditions. The reference variables include the preheating temperature difference, inter-stage 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, during the process of heating the carbon dioxide gas after depressurizing the carbon dioxide working fluid in the low-pressure liquid storage tank to an appropriate temperature by the system, the difference between the initial temperature and the final preheating temperature of the gas; the inter-stage cooling temperature difference refers to the temperature change of the gas after each stage of compression in the multi-stage compression process. By controlling this 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 during the preheating stage of the gas 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 high-pressure side gasification process.

[0074] Specifically, the parameter target set defines the target objects for system optimization, including multiple parameter variables. By analyzing the design condition information, extracting the fluid and equipment parameter sets, defining the constant parameters and parameter variables, and generating the parameter constraint set and parameter target set, 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 the links from gas compression to expansion and energy release processes, and there are temporal and operational sequence relationships between different processes. The parameters of each process are 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 time sequence relationship, the parameter variables are serialized in time order. The serialization of parameter variables facilitates the subsequent reasonable transfer and optimization of multiple parameter variables in sequence according to the actual sequence of system operation.

[0077] Input the parameter constraint set into the physical property numerical model for model initialization, and use the parameter target set as the optimization target. Through the method of controlling variables, traverse the parameter target set to optimize the parameters of multiple parameter variables, and obtain the optimized energy storage parameter set.

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

[0079] Specifically, after the model initialization is completed, the parameter variables of the system are adjusted through an optimization algorithm to find the optimal energy storage parameter set. Among them, it involves traversing the parameter target set by the method of controlling variables, that is, optimizing different system parameters respectively, gradually adjusting each parameter, and calculating its impact on the 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 for model initialization includes:

[0081] Establish a mapping relationship between the parameter constraint set and multiple physical property programs in the physical property numerical model; define fixed values of corresponding variables of multiple physical property programs based on the mapping relationship and the parameter constraint set; define the value range of multiple parameter variables in multiple physical property programs based on the operating condition limitations.

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

[0083] Specifically, define the value range of multiple parameter variables in the physical property program according to the operating condition limitations of the system to ensure that the parameter changes during the optimization process do not violate physical and equipment limitations. Among them, the operating condition limitations include equipment pressure limitations and equipment temperature limitations.

[0084] Specifically, the above constraint conditions and value range provide boundaries for subsequent optimization calculations, ensuring that the parameter variables are not adjusted beyond the design and physical capabilities of the equipment or system.

[0085] In some embodiments, taking the parameter target set as the optimization target, traverse the parameter target set by the method of controlling variables to optimize the parameters of multiple parameter variables, and obtain an optimized energy storage parameter set, including:

[0086] Sequentially extract the parameter target set, determine the first variable, and define temporary fixed values of multiple parameter variables except the first variable; based on the optimization algorithm, take the value range as the optimization space and the system efficiency function as the objective function, perform iterative optimization of the first variable, and obtain the first optimized value of the first variable; perform iterative sequential extraction of the parameter target set, 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 the second optimized value of the second variable; traverse the parameter target set for iterative optimization until the optimized values of multiple parameter variables are obtained, and output as the optimized energy storage parameter set.

[0087] Specifically, traverse the parameter target set by the method of controlling variables to gradually optimize multiple parameter variables. Among them, the core idea of the method of controlling variables is "optimize one by one" - that is, fix a part of the parameter variables in each round of optimization, adjust one variable iteratively, find the optimal solution and then optimize the next variable, and finally obtain a set of optimal energy storage parameter sets.

[0088] Specifically, first, select a variable from the parameter target set as the "first variable", and use the other variables as temporary fixed values, that is, do not optimize all variables simultaneously, but optimize step by step to avoid unnecessary computational complexity caused by the changes of multiple variables; then, perform iterative optimization on the "first variable" through an optimization algorithm, that is, try different values of the first variable, calculate the value of the objective function (i.e., the system efficiency function), and then select the value of the first variable that maximizes (or minimizes) the objective function; next, based on the previous optimization, update the temporary fixed value of the first variable using the first optimized value (i.e., the preheating temperature difference that has been optimized), and continue to optimize the second variable using the control variable method. This optimization process is similar to that of the first variable. Explore the value range of the second variable through the optimization algorithm and gradually adjust it until the best second optimized value is found.

[0089] Further, sequential optimization is performed on each parameter variable according to the steps of the control variable method. In each round of optimization, fix the optimized variables and optimize the current variable. When the optimization process of all parameter variables is completed, the optimal solutions of all variables are obtained and output as the optimized energy storage parameter set. Optionally, a termination condition can be set for this optimization process, such as reaching the maximum number of iterations or the value of the objective function reaching a predetermined value.

[0090] Through the above steps, the control variable method is used to gradually optimize multiple parameter variables of the energy storage system, and 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, and optimizing operating costs.

[0091] In some implementation manners, with the system efficiency function as the objective function, the system efficiency function is expressed as:

[0092] E ffi = ET / EC;

[0093] where, 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). Among them, 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 turbine for the expanded gas.

[0095] In summary, the parameter optimization method for 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, which includes a plurality of energy storage intermediate processes and a plurality of energy release intermediate processes. Analyze the intermediate process set to obtain the physical property program sets of the energy storage intermediate processes and the energy release intermediate processes. According to the physical property program sets, the system architecture, and the intermediate process set, construct a physical property numerical model of the target energy storage system. Obtain the design condition information of the target energy storage system, define the reference quantities and reference variables according to the design conditions, and generate the corresponding parameter constraint set and parameter target set. Input the parameter constraint set into the physical property numerical model for model initialization; take the parameter target set as the optimization objective, traverse the parameter target set by the control variable method, optimize the multiple reference variables, and obtain the optimized energy storage parameter set, so as to achieve the technical effects of improving the parameter setting effect, enhancing the energy storage efficiency and economy.

[0097] It should be understood that the disclosed embodiments of the present invention and the above descriptions enable those skilled in the art to implement the present invention using the present invention. At the same time, the present invention is not limited to the above-mentioned part of the embodiments. It should be understood that ordinary skilled in the art can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; 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 all 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: Parsing the design operating condition information, extracting a fluid parameter set and an 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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