Compressor type selection method and device for four-section type compressed air energy storage system

Abstract

The invention relates to the technical field of compressed air energy storage, discloses a compressor type selection method and device of a four-section type compressed air energy storage system, and aims at solving the problem that an existing compressor type selection method is poor in accuracy. Calculating the target power of the compressed air energy storage system; determining inlet and outlet temperatures of each section of compressor; respectively determining a first compression ratio of the first-section compressor and a second compression ratio of the second-section compressor based on a genetic algorithm; determining inlet and outlet pressure of each section of compressor according to the first compression ratio and the second compression ratio; the specific volume of each section of compressor is calculated according to the inlet and outlet temperature and inlet and outlet pressure of each section of compressor, and the air volume flow of an inlet of each section of compressor is calculated; and determining the model of each section of compressor according to the inlet-outlet temperature, the inlet-outlet pressure and the air volume flow. The compressor model selection accuracy is improved, and the method is particularly suitable for a large-scale compressed air energy storage system.

Description

Technical Field

[0001] The present application relates to the technical field of compressed air energy storage, and in particular to a compressor selection method and device for a four-stage compressed air energy storage system. Background Art

[0002] As the installed capacity of new energy continues to expand, the timing of the construction of power transmission channels and power supply points does not match, resulting in the frequent occurrence of "wind abandonment" and "light abandonment", which seriously affects the economic efficiency of new energy power generation projects and causes unnecessary waste of resources. Energy storage technology can play a great advantage in the consumption of new energy. By absorbing redundant power from new energy, compressing and storing air and releasing it during peak power consumption, it can not only smooth out the instability and volatility of new energy power generation, but also solve the problems of wind abandonment and light abandonment. Compressed air energy storage power stations, which have the advantages of being green and pollution-free, large-scale, long-term energy storage, and flexible construction, have great development potential at the moment when new energy is vigorously developing.

[0003] The compressed air energy storage power station mainly includes a four-stage compressed air energy storage system, an expansion power generation system, a heat storage system, a heat exchange system, a gas storage system and a process water system. Among them, the four-stage compressed air energy storage system is one of the most critical systems in the compressed air energy storage power station system. It uses electrical energy to compress air during the low load period of the power grid, and seals the air at high pressure in specific gas storage facilities, such as abandoned mines, sunken submarine gas tanks, caves, expired oil and gas wells or newly built gas storage wells. During the peak load period of the power grid, the compressed air is released to drive the steam turbine to generate electricity, thereby realizing the storage and transfer of electrical energy. At the same time, as the core equipment in the entire four-stage compressed air energy storage system, the selection of the compressor is very critical in engineering applications, which directly affects whether the entire system can operate normally and the economy of operation.

[0004] Air compressors are commonly used in chemical processes, gas separation / transportation and other fields. They are also widely used as power sources, but their process parameter requirements are much lower than those of compressed air energy storage systems. Large-scale compressed air energy storage systems put forward new process requirements for air compressors. The existing method of determining the required compressor size by determining the gas flow rate that needs to be compressed cannot fully meet the process requirements of large-scale compressed air energy storage power stations. Secondly, the compressors selected for the general compression system are of the same type of equipment. Therefore, the design principle of maximum power at the same pressure ratio at each stage is adopted. However, the current large-scale compressed air energy storage system is composed of a variety of high-power equipment (axial flow compressors, centrifugal compressors), and the original design principles are not fully applicable, resulting in poor accuracy in compressor selection. Summary of the invention

[0005] The present application aims to solve the problem of poor accuracy in the existing compressor selection method of compressed air energy storage system, and proposes a compressor selection method and device for a four-stage compressed air energy storage system.

[0006] The technical solution adopted by this application to solve the above technical problems is:

[0007] In a first aspect, the present application provides a compressor selection method for a four-stage compressed air energy storage system, the method comprising:

[0008] Step 1: Determine the project boundary conditions, which at least include atmospheric pressure, ambient temperature, gas storage reservoir operating pressure range, pressure loss of each compressor section, and heat storage temperature of the storage tank;

[0009] Step 2: Calculate the target power of the compressed air energy storage system according to the required compression time, discharge time, turbine output power and preliminary system efficiency;

[0010] Step 3, determining the inlet and outlet temperatures of each compressor section according to the ambient temperature and the heat storage temperature;

[0011] Step 4, determining a first compression ratio of the first compressor and a second compression ratio of the second compressor respectively according to the target power and the inlet and outlet temperatures and based on a genetic algorithm;

[0012] Step 5, determining the inlet and outlet pressures of each compressor section according to the atmospheric pressure, the operating pressure range of the gas storage reservoir, the pressure loss of each compressor section, the first compression ratio and the second compression ratio;

[0013] Step 6, calculating the specific volume of each compressor section according to the inlet and outlet temperatures and inlet and outlet pressures of each compressor section, and calculating the air volume flow rate at the inlet of each compressor section according to the specific volume;

[0014] Step 7: Determine the model of each compressor section according to the inlet and outlet temperatures, inlet and outlet pressures and air volume flow rate.

[0015] Furthermore, the target power of the compressed air energy storage system is calculated as follows:

[0016] W C1 =W T ·t sn / t cn / η z ;

[0017] Among them, W C1 Indicates the target power, W T represents turbine output power, t sn Indicates the discharge time, t cn Indicates the compression duration, η zRepresents the preliminary system efficiency.

[0018] Further, the inlet and outlet temperatures of each compressor section are determined according to the ambient temperature and the heat storage temperature, specifically including:

[0019] The inlet temperature of the first compressor is the ambient temperature, the inlet temperatures of the second, third and fourth compressors are preset fixed temperatures, and the outlet temperature of each compressor is calculated based on the heat storage temperature of the storage tank and the corresponding terminal difference.

[0020] Furthermore, the step 4 specifically includes:

[0021] Step 41: Encode the first compression ratio and the second compression ratio, determine a fitness function and create constraint conditions according to the target power;

[0022] Step 42, randomly generate an initial population of the first compression ratio and the second compression ratio, and use the initial population as the parent population;

[0023] Step 43, calculating the fitness of each group compression ratio in the parent population according to the fitness function, and taking the maximum fitness as the optimal fitness;

[0024] Step 44: Perform genetic operations to generate new subpopulations. The genetic operations include selection, crossover and mutation.

[0025] Step 45, replacing the original parent population with the new child population, and repeating steps 43 to 44 until the number of cycles reaches a preset genetic generation;

[0026] Step 46: Determine the first compression ratio and the second compression ratio corresponding to the optimal fitness finally obtained.

[0027] Furthermore, the constraints are as follows:

[0028]

[0029]

[0030] Among them, W c Indicates actual power, m c represents the air mass flow rate, η mec represents the mechanical efficiency, η m Indicates the motor efficiency, h c,out represents the designed outlet fluid enthalpy, h c,in represents the design inlet fluid enthalpy value, m represents the compression time of the compressed air energy storage system t cn The air quality required.

[0031] Furthermore, the fitness function is as follows:

[0032]

[0033] Among them, η c represents fitness, W T represents turbine output power, t sn Indicates the discharge time, t cn Indicates the compression time, T i represents the inlet temperature of the compressor in the i-th section, k represents the insulation coefficient, m c represents the air mass flow rate, R g represents the gas constant, η represents the compressor adiabatic efficiency, π i Represents the compression ratio of the i-th compressor.

[0034] Furthermore, the step 5 specifically includes:

[0035] Step 51, the inlet pressure of the first stage compressor is atmospheric pressure, and the outlet pressure of the first stage compressor is calculated according to the inlet pressure of the first stage compressor, the pressure loss of the first stage compressor and the first compression ratio, and the calculation formula is as follows:

[0036]

[0037] in, represents the outlet pressure of the first compressor, π1 represents the first compression ratio, Δp1 represents the pressure loss of the first compressor, and P0 represents the atmospheric pressure;

[0038] Step 52: The inlet pressure of the second-stage compressor is the outlet pressure of the first-stage compressor. The outlet pressure of the second-stage compressor is calculated according to the inlet pressure of the second-stage compressor, the pressure loss of the second-stage compressor and the second compression ratio. The calculation formula is as follows:

[0039]

[0040] in, represents the outlet pressure of the second compressor, π2 represents the second compression ratio, and Δp2 represents the pressure loss of the second compressor;

[0041] Step 53, assuming that the operating pressure range of the gas storage is [a, b], the outlet pressure of the fourth stage compressor is b, and the inlet pressure of the fourth stage compressor is a+Δp4, where Δp4 represents the pressure loss of the fourth stage compressor;

[0042] Step 54: the inlet pressure of the third-stage compressor is the outlet pressure of the second-stage compressor, and the outlet pressure of the third-stage compressor is the inlet pressure of the fourth-stage compressor.

[0043] Furthermore, the specific volume of each compressor stage is calculated by calling Volume() function using the working fluid property calculation software REFPROP.

[0044] Furthermore, the calculation formula of the air volume flow rate at the inlet of each compressor section is as follows:

[0045] V i =v i ·m c ;

[0046] Among them, V i represents the air volume flow rate at the inlet of the i-th compressor, v i represents the specific volume of the i-th compressor, m c Indicates the air mass flow rate.

[0047] In a second aspect, the present application provides a compressor selection device for a four-stage compressed air energy storage system, wherein the device is used to implement the steps of the compressor selection method for a four-stage compressed air energy storage system as described in the first aspect.

[0048] The beneficial effects of the present application are as follows: the compressor selection method and device of the four-stage compressed air energy storage system provided by the present application, in combination with the engineering design operation plan, determines the inlet and outlet pressures of the fourth-stage compressor and the inlet and outlet temperatures of each stage compressor, and takes the target efficiency of the compressor system as the goal, optimizes the compression ratio of the first-stage compressor and the second-stage compressor based on the genetic algorithm, thereby obtaining the inlet and outlet pressures of each stage compressor, and then calculates the air volume flow rate at the inlet of each stage compressor according to the temperature and pressure parameters, and finally determines the selection scheme of each stage compressor according to the inlet and outlet temperature and pressure and the air volume flow rate. Compared with the prior art, the present application can avoid the problem of the original design principles being inapplicable caused by the compressed air energy storage system being composed of a variety of high-power equipment (axial flow compressors, centrifugal compressors) by considering the engineering design operation plan, improves the accuracy of compressor selection, and allocates the compression ratio of the first-stage compressor and the second-stage compressor based on the genetic algorithm, further improving the accuracy of compressor selection. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 A schematic flow chart of a compressor selection method for a four-stage compressed air energy storage system provided in an embodiment of the present application;

[0050] Figure 2 A flowchart of a genetic algorithm provided in an embodiment of the present application. DETAILED DESCRIPTION

[0051] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application.

[0052] The technical solution of the embodiment of the present application is applicable to application scenarios where it is necessary to determine the compressor model in a four-stage compressed air energy storage system, especially a large-scale compressed air energy storage system. Since the current method of determining the required compressor size by determining the gas flow rate that needs to be compressed cannot fully meet the process requirements of large-scale compressed air energy storage power stations, and the compressors selected for general compression systems are the same type of equipment, the design principle of maximum power at the same pressure ratio of each stage is adopted. However, the current large-scale compressed air energy storage system is composed of a variety of high-power equipment (axial flow compressors, centrifugal compressors), and the original design principles are not fully applicable, resulting in poor accuracy in compressor selection.

[0053] Based on this, the technical solution of the present application is proposed. In the embodiment of the present application, the project boundary conditions are determined, and the project boundary conditions at least include atmospheric pressure, ambient temperature, gas storage reservoir operating pressure range, pressure loss of each section compressor and heat storage temperature of the storage tank; the target power of the compressed air energy storage system is calculated according to the required compression time, discharge time, turbine output power and initial system efficiency; the inlet and outlet temperatures of each section compressor are determined according to the ambient temperature and heat storage temperature; the first compression ratio of the first section compressor and the second compression ratio of the second section compressor are determined based on the target power and inlet and outlet temperatures and based on a genetic algorithm; the inlet and outlet pressures of each section compressor are determined according to the atmospheric pressure, gas storage reservoir operating pressure range, pressure loss of each section compressor, the first compression ratio and the second compression ratio; the specific volume of each section compressor is calculated according to the inlet and outlet temperatures and inlet and outlet pressures of each section compressor, and the air volume flow rate at the inlet of each section compressor is calculated according to the specific volume; the model of each section compressor is determined according to the inlet and outlet temperatures, inlet and outlet pressures and air volume flow rate.

[0054] Specifically, this application comprehensively considers factors such as the power generation demand of the energy storage power station, the compression side process flow, and the energy storage scale of the power station to determine the boundary conditions of the project. Since the efficiency of the compression system will affect the efficiency of the entire energy storage power station to the greatest extent, and the compression system efficiency is related to the compression ratio of each section, the boundary conditions are used in combination with the requirements of the compressed air energy storage process system to analyze the inlet and outlet temperatures and inlet and outlet pressures of each compressor section by section. At the same time, under the condition of meeting the design temperature and pressure requirements, a genetic algorithm is used to simulate and iterate the calculation of the first compression ratio of the first compressor and the compression ratio of the second compressor with the compressor system efficiency as the target, and then the inlet and outlet temperatures and inlet and outlet pressures of each compressor section are calculated, and then the air volume flow rate at the inlet of each compressor section is calculated according to the temperature and pressure parameters. Finally, the selection scheme of each compressor section is determined according to the inlet and outlet temperatures and pressures and the air volume flow rate, so as to achieve the purpose of improving the accuracy of compressor selection.

[0055] The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments.

[0056] See also Figure 1 The compressor selection method of the four-stage compressed air energy storage system provided in the embodiment of the present application is characterized in that the method comprises:

[0057] S1. Determine the project boundary conditions, which at least include atmospheric pressure, ambient temperature, gas storage reservoir operating pressure range, pressure loss of each compressor section, and heat storage temperature of the storage tank.

[0058] In practical applications, the atmospheric pressure P0 can be determined according to the geographical location of the project, the ambient temperature C0 of the equipment can be determined according to the multi-year average temperature of the project site, and the operating pressure range of the gas storage reservoir can be determined according to the operating parameters of the turbine side [a, b] MPa. The pressure loss Δp of each compressor is generally taken between 1.5 and 20 KPa according to the empirical value. The heat storage medium of the storage tank is water, and the heat storage temperature is C c .

[0059] S2. Calculate the target power of the compressed air energy storage system based on the required compression time, discharge time, turbine output power and preliminary system efficiency.

[0060] Specifically, the shaft power demand of the compressed air energy storage system is preliminarily calculated with the output power as the target, that is, the target power of the compressed air energy storage system is calculated, and the calculation formula is as follows:

[0061] W C1 =W T ·t sn / t cn / η z ;

[0062] Among them, W C1 Indicates the target power, W T represents turbine output power, t sn Indicates the discharge time, t cn Indicates the compression duration, η z Represents the preliminary system efficiency.

[0063] S3. Determine the inlet and outlet temperatures of each compressor section according to the ambient temperature and the heat storage temperature.

[0064] Specifically, the inlet temperature of the first-stage compressor is the ambient temperature C0, the inlet temperatures of the second-stage compressor, the third-stage compressor and the fourth-stage compressor are preset fixed temperatures, generally 40°C, and the outlet temperature of each stage compressor is calculated based on the sum of the heat storage temperature of the storage tank and the corresponding end difference.

[0065] S4. Determine the first compression ratio of the first compressor and the second compression ratio of the second compressor according to the target power and the inlet and outlet temperatures based on a genetic algorithm.

[0066] In the embodiment of the present application, the calculation of the first compression ratio of the first compressor and the second compression ratio of the second compressor is optimized and solved by genetic algorithm. Genetic algorithm (GA) is a random global search and optimization method proposed by Professor John Holland of the University of Michigan in the 1970s. It obtains the optimal solution by simulating the natural selection and natural genetics mechanism in Darwin's theory of biological genetic evolution. The basic solution idea of ​​genetic algorithm is: starting from any initial population, genetic operations (selection, crossover and mutation) are repeatedly performed, and according to the evolutionary principle of survival of the fittest, a group of individuals that are more adapted to the environment are generated. In this way, they continue to multiply and evolve, and finally converge to a group of individuals that are most adapted to the environment, thereby obtaining the optimal solution to the problem.

[0067] In practical applications, the first compression ratio and the second compression ratio are set to π1 and π2 respectively, and the value range of the parameters π1 and π2 to be solved is represented as a binary space. The binary representation of each set of π1 and π2 data constitutes a chromosome; and a set of several chromosomes constitutes a population.

[0068] See also Figure 2 In the embodiment of the present application, the specific steps of iterative calculation of the genetic algorithm include:

[0069] S41, encoding the first compression ratio π1 and the second compression ratio π2, determining a fitness function and creating constraint conditions according to the target power;

[0070] S42, randomly generate an initial population with a first compression ratio π1 and a second compression ratio π2, and use the initial population as a parent population;

[0071] S43, calculating the fitness of each group compression ratio in the parent population according to the fitness function, and taking the maximum fitness as the optimal fitness;

[0072] The fitness function is an indicator used to judge the quality of individuals in a group. It is set according to the objective function of the problem being solved. The principle is that the greater the fitness, the better the result. The fitness function iteratively calculated in the embodiment of the present application is as follows:

[0073]

[0074] Among them, η c represents fitness, W T represents turbine output power, t sn Indicates the discharge time, t cn Indicates the compression time, T i represents the inlet temperature of the compressor in the i-th section, k represents the insulation coefficient, m c represents the air mass flow rate, R g represents the gas constant, η represents the compressor adiabatic efficiency, π i Represents the compression ratio of the i-th compressor.

[0075] The constraints in the embodiments of the present application are:

[0076]

[0077] Among them, W c Indicates actual power, m c represents the air mass flow rate, η mec represents the mechanical efficiency, η m Indicates the motor efficiency, h c,out represents the designed outlet fluid enthalpy, h c,in represents the design inlet fluid enthalpy value, m represents the compression time of the compressed air energy storage system t cn The air quality required.

[0078] S44, perform genetic operations to generate new sub-populations, the genetic operations include selection, crossover and mutation;

[0079] S45, replacing the original parent population with the new child population, and repeating S43 to S44 until the number of cycles reaches a preset genetic generation;

[0080] S46, determining the first compression ratio π1 and the second compression ratio π2 corresponding to the optimal fitness finally obtained, and outputting π1 and π2 corresponding to the optimal fitness as the optimal solution.

[0081] S5. Determine the inlet and outlet pressures of each compressor section according to the atmospheric pressure, the operating pressure range of the gas storage reservoir, the pressure loss of each compressor section, the first compression ratio and the second compression ratio.

[0082] It can be understood that according to the operating characteristics of the compressor, in the compressed air energy storage system, the inlet pressure of the first compressor is the atmospheric pressure P0. Assuming that the operating pressure range of the gas storage reservoir is [a, b], the outlet pressure of the fourth compressor is b, and the outlet pressure of the fourth compressor is a+Δp4, where Δp4 represents the pressure loss of the fourth compressor. Since the first compressor, the second compressor, the third compressor and the fourth compressor are connected in series in sequence, the outlet pressure of the first compressor is equal to the inlet pressure of the second compressor, the outlet pressure of the second compressor is equal to the inlet pressure of the third compressor, and the outlet pressure of the third compressor is equal to the inlet pressure of the fourth compressor.

[0083] Based on this, in the embodiment of the present application, the step of determining the inlet and outlet pressures of each compressor section specifically includes:

[0084] S51. The inlet pressure of the first compressor is atmospheric pressure. The outlet pressure of the first compressor is calculated according to the inlet pressure of the first compressor, the pressure loss of the first compressor and the first compression ratio. The calculation formula is as follows:

[0085]

[0086] in, represents the outlet pressure of the first compressor, π1 represents the first compression ratio, Δp1 represents the pressure loss of the first compressor, and P0 represents the atmospheric pressure;

[0087] S52, the inlet pressure of the second stage compressor is the outlet pressure of the first stage compressor, and the outlet pressure of the second stage compressor is calculated according to the inlet pressure of the second stage compressor, the pressure loss of the second stage compressor and the second compression ratio, and the calculation formula is as follows:

[0088]

[0089] in, represents the outlet pressure of the second compressor, π2 represents the second compression ratio, and Δp2 represents the pressure loss of the second compressor;

[0090] S53, assuming that the operating pressure range of the gas storage is [a, b], then the outlet pressure of the fourth stage compressor is b, and the inlet pressure of the fourth stage compressor is a+Δp4, where Δp4 represents the pressure loss of the fourth stage compressor;

[0091] S54: The inlet pressure of the third-stage compressor is the outlet pressure of the second-stage compressor, and the outlet pressure of the third-stage compressor is the inlet pressure of the fourth-stage compressor.

[0092] S6. Calculate the specific volume of each compressor section according to the inlet and outlet temperatures and inlet and outlet pressures of each compressor section, and calculate the air volume flow rate at the inlet of each compressor section according to the specific volume.

[0093] After obtaining the inlet and outlet temperatures and pressures of each compressor section, the specific volume v of each compressor section can be calculated using the working fluid property calculation software REFPROP. i Specifically, the function is called in the calculation table: Volume("AIR", "TP", "SI WITH C", parameter 1, parameter 2), where parameter 1 and parameter 2 represent the inlet temperature and inlet pressure of the corresponding compressor respectively. Then calculate the air volume flow rate at the inlet of each compressor section, and the calculation formula is as follows:

[0094] V i =v i ·m c ;

[0095] Among them, V i represents the air volume flow rate at the inlet of the i-th compressor, v i represents the specific volume of the i-th compressor, m c Indicates the air mass flow rate.

[0096] S7. Determine the model of each compressor section according to the inlet and outlet temperatures, inlet and outlet pressures and air volume flow rate.

[0097] After determining the inlet and outlet temperatures, inlet and outlet pressures and air volume flow of each compressor section, the model of each compressor section can be determined based on these parameters, thus completing the compressor selection.

[0098] In practical applications, considering that the pressure of the gas storage reservoir of the compression system gradually increases with the operation of the compression system until it reaches the design pressure value during operation, a compression operation scheme of compression and startup in stages is adopted during the compression process. That is, the first two compressors are started first to compress the air from the ambient atmospheric pressure to a certain pressure, and then directly enter the gas storage reservoir through the third and fourth compressors, until the internal pressure of the gas storage reservoir reaches the pressure of the first two compression systems, the third compressor is started, and the fourth compressor is started until the outlet pressure of the third compressor is consistent with the gas storage reservoir pressure until the gas storage reservoir pressure reaches the design pressure value. This operation scheme makes the pressure difference between the compression pressure and the gas storage reservoir pressure as small as possible, reducing pressure loss. In addition, the pressure change of the fourth compressor during the compression process is large. In order to better achieve the real-time consistency between the motor power change and the compressor power demand, the embodiment of the present application can adopt a variable frequency design in the fourth compressor, that is, add a frequency converter, so that the compressor power consumption increases with the pressure during the fourth compression operation and matches the motor power consumption in real time, thereby reducing power consumption.

[0099] In summary, the compressor selection method for the four-stage compressed air energy storage system provided in the embodiment of the present application combines the engineering design operation plan to determine the inlet and outlet pressures of the fourth-stage compressor and the inlet and outlet temperatures of each stage compressor, and takes the target efficiency of the compressor system as the goal, optimizes the compression ratio of the first-stage compressor and the second-stage compressor based on the genetic algorithm, thereby obtaining the inlet and outlet pressures of each compressor, and then calculates the air volume flow rate at the inlet of each compressor according to the temperature and pressure parameters, and finally determines the selection plan for each compressor according to the inlet and outlet temperature and pressure and the air volume flow rate. Compared with the prior art, the present application can avoid the problem of the original design principles being inapplicable due to the compressed air energy storage system being composed of a variety of high-power equipment (axial flow compressors, centrifugal compressors) by considering the engineering design operation plan, thereby improving the accuracy of compressor selection, and allocating the compression ratio of the first-stage compressor and the second-stage compressor based on the genetic algorithm, further improving the accuracy of compressor selection.

[0100] Based on the above technical solution, this embodiment also proposes a compressor selection device for a four-stage compressed air energy storage system, which is used to implement the steps of the compressor selection method for a four-stage compressed air energy storage system as described in the embodiment of the present application.

[0101] It can be understood that since the compressor selection device for the four-stage compressed air energy storage system described in the embodiment of the present application is a device for implementing the compressor selection method for the four-stage compressed air energy storage system described in the embodiment, for the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple. For relevant matters, please refer to the partial description of the method, which will not be repeated here.

Claims

1. A compressor selection method for a four-stage compressed air energy storage system, characterized in that: The method comprises: Step 1: Determine the project boundary conditions, which at least include atmospheric pressure, ambient temperature, gas storage reservoir operating pressure range, pressure loss of each compressor section, and heat storage temperature of the storage tank; Step 2: Calculate the target power of the compressed air energy storage system according to the required compression time, discharge time, turbine output power and preliminary system efficiency; Step 3, determining the inlet and outlet temperatures of each compressor section according to the ambient temperature and the heat storage temperature; Step 4, determining a first compression ratio of the first compressor and a second compression ratio of the second compressor respectively according to the target power and the inlet and outlet temperatures and based on a genetic algorithm; Step 5, determining the inlet and outlet pressures of each compressor section according to the atmospheric pressure, the operating pressure range of the gas storage reservoir, the pressure loss of each compressor section, the first compression ratio and the second compression ratio; Step 6, calculating the specific volume of each compressor section according to the inlet and outlet temperatures and inlet and outlet pressures of each compressor section, and calculating the air volume flow rate at the inlet of each compressor section according to the specific volume; Step 7: Determine the model of each compressor section according to the inlet and outlet temperatures, inlet and outlet pressures and air volume flow rate.

2. The compressor selection method of the four-stage compressed air energy storage system according to claim 1 is characterized in that: The target power calculation formula of the compressed air energy storage system is as follows: W C1 =W T ·t sn / t cn / η z ; Among them, W C1 Indicates the target power, W T represents turbine output power, t sn Indicates the discharge time, t cn Indicates the compression duration, η z Represents the preliminary system efficiency.

3. The compressor selection method of the four-stage compressed air energy storage system according to claim 1 is characterized in that: The inlet and outlet temperatures of each compressor section are determined according to the ambient temperature and the heat storage temperature, specifically including: The inlet temperature of the first-stage compressor is the ambient temperature, the inlet temperatures of the second-stage compressor, the third-stage compressor and the fourth-stage compressor are preset fixed temperatures, and the outlet temperature of each stage compressor is calculated based on the heat storage temperature of the storage tank and the corresponding terminal difference.

4. The compressor selection method of the four-stage compressed air energy storage system according to claim 1 is characterized in that: The step 4 specifically includes: Step 41: Encode the first compression ratio and the second compression ratio, determine a fitness function and create constraint conditions according to the target power; Step 42, randomly generate an initial population of the first compression ratio and the second compression ratio, and use the initial population as the parent population; Step 43, calculating the fitness of each group compression ratio in the parent population according to the fitness function, and taking the maximum fitness as the optimal fitness; Step 44: Perform genetic operations to generate new subpopulations. The genetic operations include selection, crossover and mutation. Step 45, replacing the original parent population with the new child population, and repeating steps 43 to 44 until the number of cycles reaches a preset genetic generation; Step 46: Determine the first compression ratio and the second compression ratio corresponding to the optimal fitness finally obtained.

5. The compressor selection method of the four-stage compressed air energy storage system according to claim 4 is characterized in that: The constraints are as follows: Among them, W c Indicates actual power, m c represents the air mass flow rate, η mec represents the mechanical efficiency, η m Indicates the motor efficiency, h c,out represents the designed outlet fluid enthalpy, h c,in represents the design inlet fluid enthalpy value, m represents the compression time of the compressed air energy storage system t cn The air quality required.

6. The compressor selection method of the four-stage compressed air energy storage system according to claim 5 is characterized in that: The fitness function is as follows: Among them, η c represents fitness, W T represents turbine output power, t sn Indicates the discharge time, t cn Indicates the compression time, T i represents the inlet temperature of the compressor in the i-th section, k represents the insulation coefficient, m c represents the air mass flow rate, R g represents the gas constant, η represents the compressor adiabatic efficiency, π i Represents the compression ratio of the i-th compressor.

7. The compressor selection method of the four-stage compressed air energy storage system according to claim 1 is characterized in that: The step 5 specifically includes: Step 51, the inlet pressure of the first stage compressor is atmospheric pressure, and the outlet pressure of the first stage compressor is calculated according to the inlet pressure of the first stage compressor, the pressure loss of the first stage compressor and the first compression ratio, and the calculation formula is as follows: in, represents the outlet pressure of the first compressor, π1 represents the first compression ratio, Δp1 represents the pressure loss of the first compressor, and P0 represents the atmospheric pressure; Step 52: The inlet pressure of the second-stage compressor is the outlet pressure of the first-stage compressor. The outlet pressure of the second-stage compressor is calculated according to the inlet pressure of the second-stage compressor, the pressure loss of the second-stage compressor and the second compression ratio. The calculation formula is as follows: in, represents the outlet pressure of the second compressor, π2 represents the second compression ratio, and Δp2 represents the pressure loss of the second compressor; Step 53, assuming that the operating pressure range of the gas storage is [a, b], the outlet pressure of the fourth stage compressor is b, and the inlet pressure of the fourth stage compressor is a+Δp4, where Δp4 represents the pressure loss of the fourth stage compressor; Step 54: the inlet pressure of the third-stage compressor is the outlet pressure of the second-stage compressor, and the outlet pressure of the third-stage compressor is the inlet pressure of the fourth-stage compressor.

8. The compressor selection method of the four-stage compressed air energy storage system according to claim 1, characterized in that: The specific volume of each compressor section is calculated by calling Volume() function using the working fluid property calculation software REFPROP.

9. The compressor selection method of the four-stage compressed air energy storage system according to claim 1, characterized in that: The calculation formula of the air volume flow rate at the inlet of each compressor section is as follows: In i =in i ·m c ; Among them, V i represents the air volume flow rate at the inlet of the i-th compressor, v i represents the specific volume of the i-th compressor, m c Indicates the air mass flow rate.

10. A compressor selection device for a four-stage compressed air energy storage system, characterized in that: The device is used to implement the steps of the compressor selection method for a four-stage compressed air energy storage system as described in any one of claims 1 to 9.

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