Dynamic modeling method, device and equipment for compressed air energy storage system and medium

Abstract

The invention relates to a dynamic modeling method, device and equipment for a compressed air energy storage system and a medium, and the method comprises the steps: obtaining a plurality of parameters of a compressor, and carrying out the fitting according to the plurality of parameters and derivative calculation results thereof to obtain a compressor dynamic model; a plurality of parameters of the turbine are obtained, and a turbine dynamic model is obtained through fitting according to the parameters and derivative calculation results of the parameters; based on the compressor dynamic model and the turbine dynamic model, establishing a pipeline volume inertia model by utilizing a preset lumped parameter strategy, and approximating a plurality of dynamic characteristics to obtain a compressor subsystem and a turbine subsystem; and based on preset safe operation constraint conditions, the compressed air energy storage system is constructed according to the compressor subsystem and the turbine subsystem. Therefore, based on various variable working condition factors of the compressed air energy storage system, the all-working-condition thermodynamic dynamic simulation model is established, the dynamic characteristics of the compressed air energy storage system are fully reflected, and the practical value is extremely high.

Description

Technical Field

[0001] The present invention relates to the field of new energy technologies, and in particular to a dynamic modeling method, device, equipment and medium for a compressed air energy storage system. Background Art

[0002] Compressed Air Energy Storage (CAES) is a technology that stores energy by compressing air. As a clean physical energy storage technology, Advanced Adiabatic Compressed Air Energy Storage (AA-CAES) technology eliminates the reburning link in traditional CAES technology, and heats the air between turbine stages by collecting the compression heat generated by the system during the compression energy storage process, achieving zero carbon emissions in the entire process. It has the advantages of large capacity, low cost, and long life, and is the most important and most promising technical route in compressed air energy storage technology.

[0003] In related technologies, a mechanism and data fusion method is usually used to establish a simulation model of a compressed air energy storage system, which is used in the design, operation, maintenance or troubleshooting of the compressed air energy storage system.

[0004] However, the above-mentioned technical means only build models based on system mechanisms and operating data. But in the actual operation of the system, internal components often need to operate under non-design conditions to respond to frequent changes in electric and thermal loads. There is a lack of dynamic simulation of the entire system operating conditions, making it difficult to meet the actual operating requirements of the compressed air energy storage system. Summary of the invention

[0005] The present invention provides a dynamic modeling method, device, equipment and medium for a compressed air energy storage system to solve the problem that the related technology lacks dynamic simulation of the full working conditions of the compressed air energy storage system and is difficult to meet the actual operation requirements of the compressed air energy storage system. Based on the various variable working condition factors of the compressed air energy storage system, a full-working condition thermodynamic dynamic simulation model is established to fully reflect the dynamic characteristics of the compressed air energy storage system, which has extremely high practical value.

[0006] To achieve the above object, a first embodiment of the present invention provides a dynamic modeling method for a compressed air energy storage system, comprising the following steps:

[0007] Obtaining the intake temperature, intake pressure, pressure ratio and isentropic efficiency of the compressor, and calculating the outlet temperature, outlet pressure and total power consumption of the compressor during the compression process, and obtaining a dynamic model of the compressor by fitting the pressure ratio and the isentropic efficiency;

[0008] Acquiring the inlet temperature, inlet pressure, expansion ratio and isentropic efficiency of the turbine, calculating the outlet temperature, outlet pressure and actual power generation of the turbine, and obtaining a dynamic model of the turbine by fitting according to the expansion ratio and the isentropic efficiency;

[0009] Based on the compressor dynamic model and the turbine dynamic model, a pipeline volume inertia model is established by using a preset lumped parameter strategy, and the dynamic characteristics of the pipeline volume inertia effect, the throttle valve, the inlet guide vane and the oil pump are approximated according to a preset first-order inertia link formula to obtain a compressor subsystem and a turbine subsystem;

[0010] Based on the preset safe operation constraints of the compression subsystem and the preset safe operation constraints of the turbine subsystem, the compressed air energy storage system is constructed according to the compressor subsystem and the turbine subsystem.

[0011] According to an embodiment of the present invention, it is characterized in that the pressure ratio is:

[0012]

[0013] in, The mass flow rate of air through the compressor, is the compressor speed;

[0014] The isentropic efficiency is:

[0015]

[0016] in, The mass flow rate of air through the compressor, is the compressor speed.

[0017] According to one embodiment of the present invention, when the turbine dynamic model is obtained by fitting the expansion ratio and the isentropic efficiency, the method further includes:

[0018] Based on a preset turbine performance curve, a turbine dynamic model is obtained by fitting according to the expansion ratio and the isentropic efficiency, wherein the preset turbine performance curve is:

[0019]

[0020] Among them, m e is the air mass flow rate, is the dimensionless reduced speed of the turbine, β e is the expansion ratio, is the intake air temperature.

[0021] According to an embodiment of the present invention, the preset lumped parameter strategy is:

[0022]

[0023] in, is the outlet pressure, is the outlet temperature, is the volumetric inlet air flow rate, is the volumetric outlet air flow rate, R g is the gas constant, M a is the molar mass of air, and V is the volume of the connected body.

[0024] According to one embodiment of the present invention, the preset compression subsystem safe operation constraint conditions include compressor outlet temperature constraint conditions and compressor surge and blocking margin constraint conditions;

[0025] The preset safe operation constraint conditions of the turbine subsystem include turbine exhaust temperature constraint conditions, turbine intake pressure constraint conditions and control amount upper and lower limit constraint conditions.

[0026] According to the dynamic modeling method of the compressed air energy storage system proposed in the embodiment of the present invention, the multiple operating parameters of the compressor and the turbine are analyzed based on the thermodynamic dynamic characteristics to obtain their dynamic characteristics, and the compressor dynamic model and the turbine dynamic model are obtained according to the dynamic characteristics fitting, and the volume inertia model of the connecting pipe is established by using the preset lumped parameter strategy, and its dynamic characteristics are approximated to obtain the compressor subsystem and the turbine subsystem, and the compressor subsystem and the turbine subsystem are constrained based on the preset safe operation constraints, and finally the compressed air energy storage system is constructed. Therefore, by establishing a full-condition thermodynamic dynamic simulation model based on various variable operating conditions of the compressed air energy storage system, the dynamic characteristics of the compressed air energy storage system are fully reflected, which has extremely high practical value.

[0027] To achieve the above-mentioned purpose, a second embodiment of the present invention provides a dynamic modeling device for a compressed air energy storage system, comprising:

[0028] A compressor dynamic modeling module is used to obtain the intake temperature, intake pressure, pressure ratio and isentropic efficiency of the compressor, and calculate the outlet temperature, outlet pressure and total power consumption of the compressor during the compression process, and obtain the compressor dynamic model according to the pressure ratio and the isentropic efficiency;

[0029] A turbine dynamic modeling module is used to obtain the inlet temperature, inlet pressure, expansion ratio and isentropic efficiency of the turbine, calculate the outlet temperature, outlet pressure and actual power generation of the turbine, and obtain the turbine dynamic model by fitting the expansion ratio and the isentropic efficiency;

[0030] An approximation module is used to establish a pipeline volume inertia model based on the compressor dynamic model and the turbine dynamic model using a preset lumped parameter strategy, and approximate the dynamic characteristics of the pipeline volume inertia effect, the throttle valve, the inlet guide vane and the oil pump according to a preset first-order inertia link formula to obtain a compressor subsystem and a turbine subsystem;

[0031] A construction module is used to construct the compressed air energy storage system according to the compressor subsystem and the turbine subsystem based on the preset compression subsystem safety operation constraints and the preset turbine subsystem safety operation constraints.

[0032] According to one embodiment of the present invention, the pressure ratio is:

[0033]

[0034] in, The mass flow rate of air through the compressor, is the compressor speed;

[0035] The isentropic efficiency is:

[0036]

[0037] in, The mass flow rate of air through the compressor, is the compressor speed.

[0038] According to one embodiment of the present invention, when the turbine dynamic model is obtained by fitting the expansion ratio and the isentropic efficiency, the turbine dynamic modeling module is further used to:

[0039] Based on a preset turbine performance curve, a turbine dynamic model is obtained by fitting according to the expansion ratio and the isentropic efficiency, wherein the preset turbine performance curve is:

[0040]

[0041] Among them, m e is the air mass flow rate, is the dimensionless reduced speed of the turbine, β e is the expansion ratio, is the intake air temperature.

[0042] According to an embodiment of the present invention, the preset lumped parameter strategy is:

[0043]

[0044] in, is the outlet pressure, is the outlet temperature, is the volumetric inlet air flow rate, is the volumetric outlet air flow rate, R g is the gas constant, M a is the molar mass of air, and V is the volume of the connected body.

[0045] According to one embodiment of the present invention, the preset compression subsystem safe operation constraint conditions include compressor outlet temperature constraint conditions and compressor surge and blocking margin constraint conditions;

[0046] The preset safe operation constraint conditions of the turbine subsystem include turbine exhaust temperature constraint conditions, turbine intake pressure constraint conditions and control amount upper and lower limit constraint conditions.

[0047] According to the dynamic modeling device of the compressed air energy storage system proposed in the embodiment of the present invention, the dynamic characteristics of the compressor and the turbine are obtained by analyzing the multiple operating parameters of the compressor and the turbine based on the thermodynamic dynamic characteristics, and the dynamic model of the compressor and the turbine are obtained according to the dynamic characteristics. The volume inertia model of the connecting pipe is established by using the preset lumped parameter strategy, and the dynamic characteristics are approximated to obtain the compressor subsystem and the turbine subsystem. The compressor subsystem and the turbine subsystem are constrained based on the preset safe operation constraints, and finally the compressed air energy storage system is constructed. Therefore, by establishing a full-operating-condition thermodynamic dynamic simulation model based on a variety of variable operating conditions of the compressed air energy storage system, the dynamic characteristics of the compressed air energy storage system are fully reflected, which has a very high practical value.

[0048] To achieve the above-mentioned objectives, the third aspect of the present invention proposes an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the dynamic modeling method of the compressed air energy storage system as described in the above-mentioned embodiment.

[0049] To achieve the above objectives, a fourth aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, which is executed by a processor to implement the dynamic modeling method of a compressed air energy storage system as described in the above embodiments.

[0050] To achieve the above objectives, a fifth aspect of the present invention provides a computer program product, including a computer program, which, when executed by a processor, is used to implement the dynamic modeling method of the compressed air energy storage system as described in the above embodiments.

[0051] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] The above and / or additional aspects and advantages of the present invention will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0053] Figure 1A flowchart of a dynamic modeling method for a compressed air energy storage system provided by one embodiment of the present invention;

[0054] Figure 2 A schematic diagram of a model of a compressor subsystem provided according to a specific embodiment of the present invention;

[0055] Figure 3 A schematic diagram of a model of a turbine subsystem provided according to a specific embodiment of the present invention;

[0056] Figure 4 A block diagram of a dynamic modeling device for a compressed air energy storage system according to an embodiment of the present invention;

[0057] Figure 5 It is a schematic diagram of the structure of an electronic device provided according to an embodiment of the present invention.

[0058] Reference numerals:

[0059] Among them, 10-dynamic modeling device of compressed air energy storage system, 100-compressor dynamic modeling module, 200-turbine dynamic modeling module, 300-approximation module, 400-construction module, 501-memory, 502-processor, 503-communication interface. DETAILED DESCRIPTION

[0060] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present invention, and should not be construed as limiting the present invention.

[0061] The following describes a dynamic modeling method, device, equipment and medium for a compressed air energy storage system according to an embodiment of the present invention with reference to the accompanying drawings.

[0062] Before introducing the dynamic modeling method of the compressed air energy storage system according to the embodiment of the present application, the working principle of the compressed air energy storage system is briefly introduced.

[0063] Specifically, the working principle of the Advanced Adiabatic Compressed Air Energy Storage (AA-CAES) system is to use excess electricity to drive the compressor to compress air when electricity demand is low, and store the compressed air in an underground gas storage reservoir, while storing the heat generated during the compression process in a thermal storage system. When electricity demand peaks, the stored compressed air and heat are used to drive the turbine expander to generate electricity, thereby releasing energy.

[0064] Therefore, according to the above working principle, the embodiment of the present invention divides the dynamic modeling steps of the AA-CAES system into two parts: establishing a model of the compressor subsystem and establishing a model of the turbine subsystem, wherein the compressor subsystem and the turbine subsystem mainly include: key equipment such as a compressor, a turbine, a heat exchanger, an air storage chamber and a heat storage tank.

[0065] Specifically, Figure 1 It is a flow chart of a dynamic modeling method of a compressed air energy storage system provided by an embodiment of the present invention.

[0066] like Figure 1 As shown, the dynamic modeling method of the compressed air energy storage system includes the following steps:

[0067] In step S101, the intake temperature, intake pressure, pressure ratio and isentropic efficiency of the compressor are obtained, and the outlet temperature, outlet pressure and total power consumption of the compressor during compression are calculated, and the dynamic model of the compressor is obtained by fitting the pressure ratio and isentropic efficiency.

[0068] Specifically, the embodiment of the present invention can obtain the intake air temperature of the i-th stage compressor by setting a temperature sensor and a pressure sensor at the compressor inlet. and intake pressure As well as the pressure ratio and isentropic efficiency of the compressor, and according to the inlet temperature and intake pressure Calculate the compressor outlet temperature Outlet pressure And the total power consumption of the compression process P c , where the compressor outlet temperature can be calculated as:

[0069]

[0070] in, is the outlet temperature, is the isentropic efficiency, is the intake air temperature, is the pressure ratio and k is the adiabatic index.

[0071] The compressor outlet pressure can be calculated as:

[0072]

[0073] in, is the outlet pressure, is the pressure ratio, is the intake pressure.

[0074] The total power consumption during compression can be calculated as:

[0075]

[0076] Among them, P c is the total power consumption of the compression process, η M is the mechanical efficiency of the compressor system, is the constant pressure specific heat capacity of air, is the air mass flow rate flowing through the compressor, is the outlet temperature, is the intake air temperature.

[0077] It should be noted that, according to the system operating status, the embodiment of the present invention regards the compression process inside each level of compressor of the compressed air energy storage system as an isentropic compression process, that is, the process of gas compression is regarded as a situation without heat loss.

[0078] In order to reflect the dynamic characteristics of the compressor, it is also necessary to accurately describe the performance of the compressor through the compressor performance curve, and not only accurately describe the curve equation at a given speed, but also be able to describe the curve equation at all speeds within a certain range. Therefore, a preset polynomial fitting strategy is used to describe the compressor performance curve, and the compressor pressure ratio and isentropic efficiency are fitted into a polynomial function of the compressor speed and air mass flow rate using the actual compressor data.

[0079] As a possible implementation method, in some embodiments, the pressure ratio is:

[0080]

[0081] in, The mass flow rate of air through the compressor, is the compressor speed;

[0082] The isentropic efficiency is:

[0083]

[0084] in, The mass flow rate of air through the compressor, is the compressor speed.

[0085] Therefore, the outlet temperature, outlet pressure and total power consumption of the compressor during the compression process can be calculated according to the intake temperature, intake pressure, pressure ratio and isentropic efficiency of the compressor, and the pressure ratio and isentropic efficiency of the compressor can be fitted using the polynomial fitting method to obtain the dynamic model of the compressor.

[0086] In step S102, the intake temperature, intake pressure, expansion ratio and isentropic efficiency of the turbine are obtained, and the outlet temperature, outlet pressure and actual power generation of the turbine are calculated. The dynamic model of the turbine is obtained by fitting the expansion ratio and isentropic efficiency.

[0087] Specifically, similar to the fitting method of the compressor dynamic model, the embodiment of the present invention can obtain the intake temperature of the i-th stage turbine by setting a temperature sensor and a pressure sensor at the turbine inlet. and intake pressure As well as the expansion ratio and isentropic efficiency of the turbine, and according to the inlet temperature and intake pressure Calculate the turbine outlet temperature Outlet pressure and the actual generating power P e , where the turbine outlet temperature can be calculated as:

[0088]

[0089] in, is the turbine outlet temperature, η e is the isentropic efficiency, is the intake air temperature, is the expansion ratio and k is the adiabatic index.

[0090] The turbine outlet pressure can be calculated as:

[0091]

[0092] in, is the outlet pressure, is the intake pressure, is the expansion ratio.

[0093] The actual power generation of the unit can be calculated as:

[0094]

[0095] Among them, P e is the actual generating power of the unit, η G is the mechanical efficiency of the turbine subsystem, is the constant pressure specific heat capacity of air, is the air mass flow rate through the turbine, is the intake air temperature, is the outlet temperature.

[0096] During the dynamic operation of the compressed air energy storage system, the turbine is in a wide operating condition. Therefore, the embodiment of the present invention can fit the expansion ratio and isentropic efficiency by using a preset turbine performance curve to obtain a turbine dynamic model.

[0097] As a possible implementation method, when the turbine dynamic model is obtained by fitting the expansion ratio and the isentropic efficiency, the following is also included:

[0098] Based on the preset turbine performance curve, the turbine dynamic model is obtained by fitting according to the expansion ratio and isentropic efficiency, wherein the preset turbine performance curve is:

[0099]

[0100] Among them, m e is the air mass flow rate through the turbine, is the dimensionless reduced speed of the turbine, β e is the expansion ratio, is the intake air temperature.

[0101] Among them, the ratio of the isentropic efficiency of the turbine under partial load operation to the design value is satisfy:

[0102]

[0103] Where b0 is the fitting coefficient, is the dimensionless reduced speed of the turbine, is the dimensionless reduced flow rate of the turbine.

[0104] The calculation method of the dimensionless reduced flow of the turbine is:

[0105]

[0106] Among them, m e is the air mass flow rate, is the intake air temperature, is the inlet pressure.

[0107] The dimensionless reduced speed of the turbine is calculated as:

[0108]

[0109] in, is the intake air temperature, is the outlet temperature.

[0110] Therefore, the outlet temperature, outlet pressure and actual power generation of the turbine can be calculated according to the intake temperature, intake pressure, pressure ratio and isentropic efficiency of the turbine. The expansion ratio and isentropic efficiency are fitted according to the turbine performance curve to obtain the dynamic model of the turbine.

[0111] In step S103, based on the compressor dynamic model and the turbine dynamic model, a pipeline volume inertia model is established using a preset lumped parameter strategy, and the dynamic characteristics of the pipeline volume inertia effect, the throttle valve, the inlet guide vane and the oil pump are approximated according to the preset first-order inertia link formula to obtain the compressor subsystem and the turbine subsystem.

[0112] Specifically, considering the pressure change caused by the difference in the inflow and outflow flow rates of the compressor and the turbine, the embodiment of the present invention also simulates the pressure change caused by the inflow and outflow flow rates of the air by establishing a pipeline volume inertia model. The embodiment of the present invention assumes that the pressure loss is concentrated at the pipeline outlet and uses a preset lumped parameter method to establish the pipeline volume inertia model.

[0113] As a possible implementation method, the preset lumped parameter strategy is:

[0114]

[0115] in, is the outlet pressure, is the outlet temperature, is the volumetric inlet air flow rate, is the volumetric outlet air flow rate, R g is the gas constant, M a is the molar mass of air, and V is the volume of the connected body.

[0116] In addition, the embodiment of the present invention also approximates the pipeline volume inertia effect through a first-order inertia link to simulate the inertial change of the gas in the pipeline due to its own volume and mass. The transfer function of the approximate pipeline volume inertia effect can be expressed as:

[0117]

[0118] in, is the volumetric outlet air flow rate, is the volumetric inlet air flow rate, T V is the time constant and s is the Laplace operator.

[0119] Based on the same principle, the embodiment of the present invention also approximates the dynamic characteristics of the throttle valve, inlet guide vane and oil pump of the compressed air energy storage system through the first-order inertia link. The transfer function of the approximated throttle valve can be expressed as:

[0120]

[0121] Among them, T TV is the time constant of the throttle valve.

[0122] The approximate transfer function of the inlet guide vane can be expressed as:

[0123]

[0124] Among them, T IGV is the time constant of the inlet guide vane.

[0125] The approximate transfer function of the oil pump can be expressed as:

[0126]

[0127] Among them, T OP is the time constant of the oil pump.

[0128] Therefore, by establishing a pipeline volume inertia model to simulate the pressure changes caused by the air inflow and outflow, the corresponding compressor subsystem and turbine subsystem can be obtained.

[0129] In addition, a throttle valve is usually installed at the final compression outlet or the first turbine inlet. By adjusting the valve opening to change the pipeline resistance, the pressure difference and flow rate on both sides of the throttle valve can reach the preset value. According to the Bernoulli equation and the fluid continuity equation, the throttle valve flow equation is obtained as follows:

[0130]

[0131] Among them, m TV A is the valve flow rate; TV Represents the flow area, which is a design parameter; is the throttle valve inlet pressure, which is equal to the final stage compression outlet pressure; is the throttle valve outlet pressure, which is equal to the inlet pressure of the gas pipeline connecting the gas storage and the compression subsystem. When the pipeline pressure drop is ignored, it can be regarded as the gas storage pressure; ρ is the air density; the resistance coefficient ξ is related to the flow area and the valve opening.

[0132] In step S104, based on the preset safe operation constraints of the compression subsystem and the preset safe operation constraints of the turbine subsystem, a compressed air energy storage system is constructed according to the compressor subsystem and the turbine subsystem.

[0133] Specifically, in order to ensure the safety of system operation, the embodiment of the present invention also fully considers the safe operation constraints of the compression subsystem and the turbine subsystem. Based on the preset safe operation conditions, the compressor subsystem and the turbine subsystem are constrained, and finally the compressed air energy storage system is constructed to complete the dynamic modeling of the compressed air energy storage system.

[0134] Optionally, in some embodiments, the preset compression subsystem safe operation constraints include compressor outlet temperature constraints and compressor surge and blockage margin constraints;

[0135] The preset safe operation constraints of the turbine subsystem include turbine exhaust temperature constraints, turbine inlet pressure constraints and upper and lower limit constraints of the control quantity.

[0136] Specifically, the preset safe operation constraints of the compression subsystem include:

[0137] (1) Compressor outlet temperature constraints

[0138] Considering the impeller material manufacturing process and equipment life requirements, the compressor outlet exhaust temperature must be strictly limited to not exceed the specified value:

[0139]

[0140] in, is the upper limit of the outlet temperature of the i-th stage compressor.

[0141] (2) Compressor surge and choke margin constraints

[0142] Among them, the stable working area of ​​the compressor is located between the surge condition area and the blocking condition area. At a given speed, when the flow rate drops to a certain critical value, the compressor surges, accompanied by periodic low-frequency, large-amplitude airflow oscillations and mechanical vibrations; due to the sonic shock effect, when the air flow rate approaches the blocking line in the positive direction, the pressure rise slows down. When the flow rate increases to a certain extent, the work done by the blades is completely converted into energy, and blocking occurs, corresponding to the maximum flow condition at a given speed. Ignoring the non-steady-state process of the airflow, the surge and blocking margin constraints can be converted into constraints on the upper and lower limits of the compressed air flow:

[0143]

[0144] Among them, λ sg is the surge margin, λ ck is the blocking margin, m sg is the air mass flow rate at the surge point, m ck To block traffic.

[0145] (3) Turbine exhaust temperature constraints

[0146] The expansion process is accompanied by the consumption of air heat and a drop in temperature. To prevent the humid air from freezing and impacting the rotor blades at high speed, it is necessary to ensure that the turbine exhaust temperature is not lower than the freezing point:

[0147]

[0148] Among them, T f The freezing point of air.

[0149] (4) Turbine inlet pressure limit conditions

[0150] The change of gas storage pressure requires the turbine to operate under a wide range of pressure conditions. However, the turbine's ability to operate efficiently under a wide range of conditions is limited. It is necessary to limit the size of the intake pressure, considering the following constraints:

[0151]

[0152] in, is the lower limit of the inlet pressure of the i-th stage turbine, is the upper limit of the inlet pressure of the i-th stage turbine.

[0153] (5) Upper and lower limit constraints of control quantity

[0154] The control system has limited adjustment capability, and the adjustment range of the control quantity needs to be limited. Specifically, the throttle valve opening constraint needs to be considered:

[0155]

[0156] Air flow upper and lower limit constraints:

[0157]

[0158] in, is the minimum throttle valve opening, is the maximum throttle valve opening, m i is the minimum air flow rate, is the maximum air flow rate, and the subscript i represents the number of compression or turbine stages.

[0159] In addition, the dynamic modeling of the air compression energy storage system also includes: heat exchanger modeling, air storage chamber modeling and heat storage tank modeling.

[0160] Among them, the heat exchanger can be modeled by the thermal efficiency-heat transfer unit number method (i.e., the ε-NTU method), the gas storage chamber adopts the classic isochoric adiabatic gas storage chamber model, and the heat storage tank adopts the classic heat recovery double-tank liquid heat storage tank model. The dynamic modeling method of the above equipment will not be repeated here.

[0161] In order to enable those skilled in the art to further understand the dynamic modeling method of the compressed air energy storage system in the embodiment of the present invention, it is described in detail below in conjunction with specific embodiments.

[0162] Specifically, Figure 2 As shown, Figure 2 A schematic diagram of a model of a compressor subsystem provided according to a specific embodiment of the present invention.

[0163] Among them, the actual power of the compressor P c With reference power P ref After the deviation is adjusted by PID, the air mass flow rate at the compressor inlet can be obtained. By adjusting the air mass flow rate at the compressor inlet, the compressor power can be adjusted. Among them, T LT is the outlet temperature of the low temperature hot tank. Considering that the mass flow rate of the heat storage medium is proportional to the mass flow rate of the air, the proportionality coefficient is set to M re , the outlet temperature corresponding to the dynamic model of the heat exchanger is i is the series number.

[0164] In addition, if Figure 3 As shown, Figure 3 A schematic diagram of a model of a turbine subsystem provided according to a specific embodiment of the present invention.

[0165] Among them, the input of power control is power deviation, actual turbine power P e With reference power P ref The deviation is adjusted by PID and the output is the throttle valve opening. Through the throttle valve model established previously, the throttle valve opening can be converted into the inlet control mass flow of the turbine, thereby realizing the adjustment of the turbine power. The air flow and the heat storage medium flow are used as the input parameters of the turbine power generation system. AS and T HT are the outlet temperatures of the gas storage and high-temperature heat storage tank, respectively.

[0166] According to the dynamic modeling method of the compressed air energy storage system proposed in the embodiment of the present invention, the multiple operating parameters of the compressor and the turbine are analyzed based on the thermodynamic dynamic characteristics to obtain their dynamic characteristics, and the compressor dynamic model and the turbine dynamic model are obtained according to the dynamic characteristics fitting, and the volume inertia model of the connecting pipe is established by using the preset lumped parameter strategy, and its dynamic characteristics are approximated to obtain the compressor subsystem and the turbine subsystem, and the compressor subsystem and the turbine subsystem are constrained based on the preset safe operation constraints, and finally the compressed air energy storage system is constructed. Therefore, by establishing a full-condition thermodynamic dynamic simulation model based on various variable operating conditions of the compressed air energy storage system, the dynamic characteristics of the compressed air energy storage system are fully reflected, which has extremely high practical value.

[0167] Next, the dynamic modeling device of the compressed air energy storage system proposed in accordance with an embodiment of the present invention will be described with reference to the accompanying drawings.

[0168] Figure 4 Detailed description of the invention The figure is a block diagram of a dynamic modeling device for a compressed air energy storage system according to an embodiment of the present invention.

[0169] like Figure 4 As shown, the dynamic modeling device 10 of the compressed air energy storage system includes: a compressor dynamic modeling module 100, a turbine dynamic modeling module 200, an approximation module 300 and a construction module 400.

[0170] The compressor dynamic modeling module 100 is used to obtain the intake temperature, intake pressure, pressure ratio and isentropic efficiency of the compressor, and calculate the outlet temperature, outlet pressure and total power consumption of the compressor during the compression process, and obtain the compressor dynamic model according to the pressure ratio and isentropic efficiency.

[0171] The turbine dynamic modeling module 200 is used to obtain the inlet temperature, inlet pressure, expansion ratio and isentropic efficiency of the turbine, calculate the outlet temperature, outlet pressure and actual power generation of the turbine, and obtain the turbine dynamic model according to the expansion ratio and isentropic efficiency.

[0172] The approximation module 300 is used to establish a pipeline volume inertia model based on the compressor dynamic model and the turbine dynamic model using a preset lumped parameter strategy, and approximate the dynamic characteristics of the pipeline volume inertia effect, the throttle valve, the inlet guide vane and the oil pump according to a preset first-order inertia link formula to obtain a compressor subsystem and a turbine subsystem;

[0173] The construction module 400 is used to construct a compressed air energy storage system according to the compressor subsystem and the turbine subsystem based on the preset compression subsystem safety operation constraints and the preset turbine subsystem safety operation constraints.

[0174] According to one embodiment of the present invention, the pressure ratio is:

[0175]

[0176] in, The mass flow rate of air through the compressor, is the compressor speed;

[0177] The isentropic efficiency is:

[0178]

[0179] in, The mass flow rate of air through the compressor, is the compressor speed.

[0180] According to one embodiment of the present invention, when the turbine dynamic model is obtained by fitting the expansion ratio and the isentropic efficiency, the turbine dynamic modeling module 200 is further used to:

[0181] Based on the preset turbine performance curve, the turbine dynamic model is obtained by fitting according to the expansion ratio and isentropic efficiency, wherein the preset turbine performance curve is:

[0182]

[0183] Among them, m e is the air mass flow rate, is the dimensionless reduced speed of the turbine, β e is the expansion ratio, is the intake air temperature.

[0184] According to one embodiment of the present invention, the preset lumped parameter strategy is:

[0185]

[0186] in, is the outlet pressure, is the outlet temperature, is the volumetric inlet air flow rate, is the volumetric outlet air flow rate, R g is the gas constant, M a is the molar mass of air, and V is the volume of the connected body.

[0187] According to one embodiment of the present invention, the preset compression subsystem safe operation constraint conditions include compressor outlet temperature constraint conditions and compressor surge and blocking margin constraint conditions;

[0188] The preset safe operation constraints of the turbine subsystem include turbine exhaust temperature constraints, turbine inlet pressure constraints and upper and lower limit constraints of the control quantity.

[0189] According to the dynamic modeling device of the compressed air energy storage system proposed in the embodiment of the present invention, the dynamic characteristics of the compressor and the turbine are obtained by analyzing the multiple operating parameters of the compressor and the turbine based on the thermodynamic dynamic characteristics, and the dynamic model of the compressor and the turbine are obtained according to the dynamic characteristics. The volume inertia model of the connecting pipe is established by using the preset lumped parameter strategy, and the dynamic characteristics are approximated to obtain the compressor subsystem and the turbine subsystem. The compressor subsystem and the turbine subsystem are constrained based on the preset safe operation constraints, and finally the compressed air energy storage system is constructed. Therefore, by establishing a full-operating-condition thermodynamic dynamic simulation model based on a variety of variable operating conditions of the compressed air energy storage system, the dynamic characteristics of the compressed air energy storage system are fully reflected, which has a very high practical value.

[0190] Figure 5 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. The electronic device may include:

[0191] A memory 501 , a processor 502 , and a computer program stored in the memory 501 and executable on the processor 502 .

[0192] When the processor 502 executes the program, the dynamic modeling method of the compressed air energy storage system provided in the above embodiment is implemented.

[0193] Furthermore, the electronic device further comprises:

[0194] The communication interface 503 is used for communication between the memory 501 and the processor 502 .

[0195] The memory 501 is used to store computer programs that can be executed on the processor 502 .

[0196] The memory 501 may include a high-speed RAM (Random Access Memory) memory, and may also include a non-volatile memory, such as at least one disk memory.

[0197] If the memory 501, the processor 502 and the communication interface 503 are implemented independently, the communication interface 503, the memory 501 and the processor 502 can be connected to each other through a bus and communicate with each other. The bus can be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 5 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0198] Optionally, in a specific implementation, if the memory 501, the processor 502 and the communication interface 503 are integrated on a chip, the memory 501, the processor 502 and the communication interface 503 can communicate with each other through an internal interface.

[0199] The processor 502 may be a CPU (Central Processing Unit), or an ASIC (Application Specific Integrated Circuit), or one or more integrated circuits configured to implement the embodiments of the present invention.

[0200] An embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-mentioned dynamic modeling method for a compressed air energy storage system.

[0201] An embodiment of the present invention further provides a computer program product, including a computer program, which, when executed by a processor, implements the above-mentioned dynamic modeling method for a compressed air energy storage system.

[0202] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of the present invention, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0203] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example" or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms are not necessarily directed to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0204] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present invention.

Claims

1. A dynamic modeling method for a compressed air energy storage system, characterized in that: The following steps are involved: Obtaining the intake temperature, intake pressure, pressure ratio and isentropic efficiency of the compressor, and calculating the outlet temperature, outlet pressure and total power consumption of the compressor during the compression process, and obtaining a dynamic model of the compressor by fitting the pressure ratio and the isentropic efficiency; Acquiring the inlet temperature, inlet pressure, expansion ratio and isentropic efficiency of the turbine, calculating the outlet temperature, outlet pressure and actual power generation of the turbine, and obtaining a dynamic model of the turbine by fitting according to the expansion ratio and the isentropic efficiency; Based on the compressor dynamic model and the turbine dynamic model, a pipeline volume inertia model is established by using a preset lumped parameter strategy, and the dynamic characteristics of the pipeline volume inertia effect, the throttle valve, the inlet guide vane and the oil pump are approximated according to a preset first-order inertia link formula to obtain a compressor subsystem and a turbine subsystem; Based on the preset safe operation constraints of the compression subsystem and the preset safe operation constraints of the turbine subsystem, the compressed air energy storage system is constructed according to the compressor subsystem and the turbine subsystem.

2. The method according to claim 1, characterized in that The pressure ratio is: in, The mass flow rate of air through the compressor, is the compressor speed; The isentropic efficiency is: in, The mass flow rate of air through the compressor, is the compressor speed.

3. The method according to claim 1, characterized in that When the turbine dynamic model is obtained by fitting the expansion ratio and the isentropic efficiency, the method further includes: Based on a preset turbine performance curve, a turbine dynamic model is obtained by fitting according to the expansion ratio and the isentropic efficiency, wherein the preset turbine performance curve is: Among them, m e is the air mass flow rate, is the dimensionless reduced speed of the turbine, β e is the expansion ratio, is the intake air temperature.

4. The method according to claim 1, characterized in that: The preset lumped parameter strategy is: in, is the outlet pressure, is the outlet temperature, is the volumetric inlet air flow rate, is the volumetric outlet air flow rate, R g is the gas constant, M a is the molar mass of air, and V is the volume of the connected body.

5. The method according to claim 1, characterized in that The preset compression subsystem safe operation constraint conditions include compressor outlet temperature constraint conditions and compressor surge and blocking margin constraint conditions; The preset safe operation constraint conditions of the turbine subsystem include turbine exhaust temperature constraint conditions, turbine intake pressure constraint conditions and control amount upper and lower limit constraint conditions.

6. A dynamic modeling device for a compressed air energy storage system, characterized in that: include: A compressor dynamic modeling module is used to obtain the intake temperature, intake pressure, pressure ratio and isentropic efficiency of the compressor, and calculate the outlet temperature, outlet pressure and total power consumption of the compressor during the compression process, and obtain the compressor dynamic model according to the pressure ratio and the isentropic efficiency; A turbine dynamic modeling module is used to obtain the inlet temperature, inlet pressure, expansion ratio and isentropic efficiency of the turbine, calculate the outlet temperature, outlet pressure and actual power generation of the turbine, and obtain the turbine dynamic model by fitting the expansion ratio and the isentropic efficiency; An approximation module is used to establish a pipeline volume inertia model based on the compressor dynamic model and the turbine dynamic model using a preset lumped parameter strategy, and approximate the dynamic characteristics of the pipeline volume inertia effect, the throttle valve, the inlet guide vane and the oil pump according to a preset first-order inertia link formula to obtain a compressor subsystem and a turbine subsystem; A construction module is used to construct the compressed air energy storage system according to the compressor subsystem and the turbine subsystem based on the preset compression subsystem safety operation constraints and the preset turbine subsystem safety operation constraints.

7. The device according to claim 6, characterized in that The pressure ratio is: in, The mass flow rate of air through the compressor, is the compressor speed; The isentropic efficiency is: in, The mass flow rate of air through the compressor, is the compressor speed.

8. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the dynamic modeling method for a compressed air energy storage system as described in any one of claims 1 to 7.

9. A computer storage medium having a computer program stored thereon, characterized in that: The program is executed by a processor to implement the dynamic modeling method of the compressed air energy storage system as described in any one of claims 1 to 7.

10. A computer program product, characterized in that It includes a computer program, which, when executed by a processor, is used to implement the dynamic modeling method of the compressed air energy storage system according to any one of claims 1 to 7.

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