Compressed air energy storage compression side extended stability power tracking control method and device

Abstract

The invention relates to the technical field of novel energy, in particular to a compressed air energy storage compression side spread stability power tracking control method and device, and the method comprises the steps: building a variable pressure ratio dynamic model of a compressed air energy storage compression side; based on the variable-pressure-ratio dynamic model and the fuzzy PID control theory, a compressed air energy storage compression side power tracking model containing anti-surge valve control is established; establishing a PID data set of the compressed air energy storage compression side power tracking model containing anti-surge valve control so as to train a pre-constructed control neural network to obtain a stability extension performance neural network model; and inputting a real-time state variable of the compressed air energy storage compression side to the stability extension performance neural network model to obtain PID control parameters to perform parameter updating on the compressed air energy storage compression side power tracking model containing anti-surge valve control. Therefore, the problem that the efficiency of an electric power system is reduced and the like due to the fact that an anti-surge valve is designed in an existing method for restraining the surge working condition in the gas storage is solved.

Description

Technical Field

[0001] The present invention relates to the field of new energy technologies, and in particular to a method and device for tracking and controlling compression-side stabilization power of compressed air energy storage. Background Art

[0002] At present, the rapid development of the power system and the large-scale access of new energy to the power grid have led to a larger peak-to-valley difference, which has put forward higher requirements for energy storage technology. Among the many energy storage technologies, pumped storage and compressed air energy storage technologies have the characteristics and potential of large-capacity and long-term energy storage, which can absorb new energy electricity on a large scale and ensure the safe and stable operation of the power grid. However, pumped storage has high requirements for site selection. The construction cost is too high in areas lacking mountainous terrain, and the construction period of pumped storage is relatively long. Compressed air energy storage is relatively flexible in site selection and has a short construction period. It is expected to become the next generation of large-scale energy storage technology. However, the interface between the compression side of compressed air energy storage and the power grid is currently a compressor. Due to adverse working conditions such as surge, the operating range of the compressor is narrow, which cannot adapt well to the characteristics of large volatility of new energy and cannot absorb wind and solar power well. Although an anti-surge valve can be designed in the gas storage reservoir and opened when there is a risk of surge, the surge condition can be well suppressed, but this will cause a significant decrease in the efficiency of the system.

[0003] Therefore, there is an urgent need for a control method that can expand the safe and stable operating range of the compressor while still ensuring efficiency. Summary of the invention

[0004] The present invention provides a method and device for tracking and controlling the compression-side stabilization power of compressed air energy storage, so as to solve the problem that the existing method of suppressing surge conditions by designing an anti-surge valve in the gas storage reservoir leads to a decrease in the efficiency of the power system.

[0005] The first aspect of the present invention provides a method for tracking and controlling a compression side expansion stabilization power of a compressed air energy storage system, comprising the following steps:

[0006] Establish a dynamic model of the pressure ratio of the compressed air energy storage compression side;

[0007] Based on the transformation ratio dynamic model and fuzzy proportional integral differential PID control theory, a compressed air energy storage compression side power tracking model including anti-surge valve control is established;

[0008] Establishing a PID data set of the compressed air energy storage compression side power tracking model including the anti-surge valve control, and using the PID data set to train a pre-built control neural network to obtain a stabilization performance neural network model;

[0009] The real-time state variables of the compressed air energy storage compression side are input into the stabilization performance neural network model to obtain PID control parameters, and the PID control parameters are used to update the parameters of the compressed air energy storage compression side power tracking model including anti-surge valve control.

[0010] Optionally, the compressed air energy storage compression side includes an electric motor, a multi-stage compressor, an air storage reservoir, an anti-surge valve and a heat exchanger.

[0011] Optionally, the input quantities of the compressed air energy storage compression side power tracking model including anti-surge valve control are air mass flow, compressor speed, and air pressure, and the output quantities of the compressed air energy storage compression side power tracking model including anti-surge valve control are anti-surge valve opening and motor torque.

[0012] Optionally, the PID data set includes a parameter set that can be expanded and stabilized and power tracked and a parameter set that cannot achieve the target.

[0013] The second embodiment of the present invention provides a compressed air energy storage compression side expansion stabilization power tracking control device, comprising:

[0014] The first building block is used to establish a dynamic model of the pressure ratio of the compressed air energy storage compression side;

[0015] The second building module is used to establish a compressed air energy storage compression side power tracking model including anti-surge valve control based on the transformation ratio dynamic model and fuzzy proportional integral differential PID control theory;

[0016] A training module, for establishing a PID data set of the compressed air energy storage compression side power tracking model including the anti-surge valve control, and using the PID data set to train a pre-built control neural network to obtain a stabilization performance neural network model;

[0017] An updating module is used to input the real-time state variables of the compressed air energy storage compression side into the stabilization performance neural network model to obtain PID control parameters, and use the PID control parameters to update the parameters of the compressed air energy storage compression side power tracking model including anti-surge valve control.

[0018] Optionally, the compressed air energy storage compression side includes an electric motor, a multi-stage compressor, an air storage reservoir, an anti-surge valve and a heat exchanger.

[0019] Optionally, the input quantities of the compressed air energy storage compression side power tracking model including anti-surge valve control are air mass flow, compressor speed, and air pressure, and the output quantities of the compressed air energy storage compression side power tracking model including anti-surge valve control are anti-surge valve opening and motor torque.

[0020] Optionally, the PID data set includes a parameter set that can be expanded and stabilized and power tracked and a parameter set that cannot achieve the target.

[0021] An embodiment of the third aspect of the present invention provides 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 compressed air energy storage compression side stabilization power tracking control method as described in the above embodiment.

[0022] A fourth aspect of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, which, when executed by a processor, implements the above-mentioned compressed air energy storage compression side stabilization power tracking control method.

[0023] The compressed air energy storage compression side stabilization power tracking control method and device proposed in the embodiment of the present invention adopt fuzzy PID control theory to establish a compressed air energy storage compression side power tracking model including anti-surge valve control, and adopt a neural network to train on a PID parameter set capable of stabilizing operation, so that it can output PID control parameters when the state variables are known, and then update the parameters of the compressed air energy storage compression side power tracking model. Therefore, when there is a surge risk, even if the anti-surge valve is opened to suppress the surge condition, the safe and stable operation range of the compressor will not be reduced, thereby ensuring that the efficiency of the power system is not affected.

[0024] 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

[0025] 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:

[0026] Figure 1 A flow chart of a method for tracking and controlling the compression side expansion stabilization power of compressed air energy storage provided by an embodiment of the present invention;

[0027] Figure 2 A schematic diagram of a compression side model of a compressed air energy storage provided by an embodiment of the present invention;

[0028] Figure 3 A block diagram of a compressed air energy storage compression side stabilization power tracking control device provided by an embodiment of the present invention;

[0029] Figure 4 The present invention is a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0030] 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.

[0031] The following describes a method and device for controlling the compression-side stabilization power tracking of compressed air energy storage according to an embodiment of the present invention with reference to the accompanying drawings.

[0032] Figure 1 A flow chart of a method for tracking and controlling the compression-side stabilization power of compressed air energy storage provided in an embodiment of the present invention.

[0033] like Figure 1 As shown, the compressed air energy storage compression side expansion stabilization power tracking control method includes the following steps:

[0034] In step S101, a dynamic model of the transformation ratio of the compressed air energy storage compression side is established.

[0035] In the actual implementation process, Figure 2 As shown in the figure, the compression side of the compressed air energy storage includes a motor, a multi-stage compressor, a gas storage reservoir, an anti-surge valve and a heat exchanger. When the compressed air energy storage is compressed, the motor drives the multi-stage compressor, and the high-temperature and high-pressure air passing through the compressor flows through the heat exchanger to heat the heat transfer oil and then flows into the next compressor or gas storage reservoir. The heat transfer oil is heated and flows into the heat storage reservoir. There is an anti-surge valve in the gas storage reservoir, which has a great influence on the dynamic performance of the compression side of the compressed air energy storage and cannot be ignored in dynamic modeling.

[0036] Therefore, the embodiment of the present invention constructs the following dynamic model of the pressure ratio of the compressed air energy storage compression side:

[0037] The temperature of the air after passing through the compressor is:

[0038]

[0039] in, are the air temperatures flowing out and in the j-th compressor, is the per unit value of the air mass flow rate flowing through the compressor, is the mass flow rate of the jth compressor The pressure ratio under the condition can be calculated by the air pressure before and after the compressor. γ is the specific heat ratio, that is, the ratio of the specific heat capacity at constant pressure to the specific heat capacity at constant volume. η c,j is the isentropic efficiency of the j-th compressor, which can be calculated by the following formula:

[0040]

[0041] in, are the outlet enthalpy values ​​of the ideal isentropic process and the actual isentropic process of the j-th compressor, respectively; is the inlet enthalpy of the j-th compressor.

[0042] The power consumed by the compressor is:

[0043]

[0044] in, P cj0 are the per unit value and rated reference value of the power consumption of the j-th compressor, respectively, c p is the constant pressure specific heat capacity of air, It is the rated reference value of air mass flow rate.

[0045] The mass flow rate of the anti-surge valve can be calculated by the following formula:

[0046]

[0047] in, is the air mass flow rate flowing through the anti-surge valve, δ b is the valve opening coefficient, b is the anti-surge valve coefficient, They are the pressures upstream and downstream of the anti-surge valve respectively.

[0048] In step S102, based on the transformation ratio dynamic model and fuzzy proportional integral differential PID control theory, a compressed air energy storage compression side power tracking model including anti-surge valve control is established.

[0049] In some embodiments, the input quantities of the compressed air energy storage compression side power tracking model including anti-surge valve control are air mass flow, compressor speed, and air pressure, and the output quantities of the compressed air energy storage compression side power tracking model including anti-surge valve control are anti-surge valve opening and motor torque.

[0050] In the actual implementation process, a control model with inputs of air mass flow, compressor speed, and air pressure, and outputs of anti-surge valve opening and motor torque is constructed based on the transformation ratio dynamic model. In order to better adapt to real-time working conditions, the fuzzy proportional integral differential PID control theory is adopted to adjust the PID parameters in real time to make the optimal choice, thereby constructing a compressed air energy storage compression side power tracking model including anti-surge valve control.

[0051] Among them, the construction power index is as follows:

[0052] minΔP=|P c -P ref |

[0053] Among them, P refis the compression side power signal transmitted from the power grid to the compressed air energy storage, P c is the actual power consumed by the multi-stage compressor, which can be calculated by the following formula:

[0054]

[0055] Among them, N c is the number of compressor stages.

[0056] In step S103, a PID data set of a compressed air energy storage compression side power tracking model including anti-surge valve control is established, and the pre-built control neural network is trained using the PID data set to obtain a stabilization performance neural network model.

[0057] In step S104, the real-time state variables of the compressed air energy storage compression side are input into the stabilization performance neural network model to obtain PID control parameters, and the PID control parameters are used to update the parameters of the compressed air energy storage compression side power tracking model including the anti-surge valve control.

[0058] In the actual implementation process, a PID data set that can achieve the optimal stabilization performance is established based on the above-mentioned compressed air energy storage compression side power tracking model. The PID data set includes a set of parameter sets that can be stabilized and power tracked and a set of parameter sets that cannot achieve the goal, and is divided into a training set and a test set. The training set is used to train the pre-built control neural network, so that after the control neural network training is completed (i.e., the stabilization performance neural network model), it can output a set of PID parameters when the current air mass flow, compressor speed, air pressure, anti-surge valve opening, motor torque and other system states are input.

[0059] The real-time state variables of the compression side of the compressed air energy storage are obtained, and the real-time state variables are input into the stability expansion performance neural network model to obtain PID control parameters. The PID control parameters are used to update the parameters of the power tracking model of the compression side of the compressed air energy storage including the anti-surge valve control, so that the compression side of the compressed air energy storage can expand the safe and stable operation range of the compressor while ensuring a certain efficiency.

[0060] According to the compressed air energy storage compression side stabilization power tracking control method proposed in an embodiment of the present invention, fuzzy PID control theory is used to establish a compressed air energy storage compression side power tracking model including anti-surge valve control, and a neural network is used to train on a PID parameter set that can stabilize operation, so that it can output PID control parameters when the state variables are known, and then the parameters of the compressed air energy storage compression side power tracking model are updated. Therefore, when there is a surge risk, even if the anti-surge valve is opened to suppress the surge condition, the safe and stable operation range of the compressor will not be reduced, thereby ensuring that the efficiency of the power system is not affected.

[0061] Next, the compressed air energy storage compression side stabilization power tracking control device proposed in accordance with an embodiment of the present invention is described with reference to the accompanying drawings.

[0062] Figure 3 It is a block diagram of a compressed air energy storage compression side stabilization power tracking control device according to an embodiment of the present invention.

[0063] like Figure 3 As shown, the compressed air energy storage compression side stabilization power tracking control device 30 includes: a first construction module 301, a second construction module 302, a training module 303 and an update module 304.

[0064] Among them, the first construction module 301 is used to establish a dynamic model of the transformation ratio of the compression side of the compressed air energy storage; the second construction module 302 is used to establish a power tracking model of the compression side of the compressed air energy storage including anti-surge valve control based on the transformation ratio dynamic model and fuzzy proportional integral differential PID control theory. The training module 303 is used to establish a PID data set of the power tracking model of the compression side of the compressed air energy storage including anti-surge valve control, and use the PID data set to train the pre-built control neural network to obtain a neural network model of expansion stability performance. The update module 304 is used to input the real-time state variables of the compression side of the compressed air energy storage into the neural network model of expansion stability performance to obtain PID control parameters, and use the PID control parameters to update the parameters of the power tracking model of the compression side of the compressed air energy storage including anti-surge valve control.

[0065] In some embodiments, the compression side of the compressed air energy storage includes an electric motor, a multi-stage compressor, an air storage reservoir, an anti-surge valve and a heat exchanger.

[0066] In some embodiments, the input quantities of the compressed air energy storage compression side power tracking model including anti-surge valve control are air mass flow, compressor speed, and air pressure, and the output quantities of the compressed air energy storage compression side power tracking model including anti-surge valve control are anti-surge valve opening and motor torque.

[0067] In some embodiments, the PID data set includes a parameter set that can be expanded and power tracked and a parameter set that cannot achieve the target.

[0068] It should be noted that the aforementioned explanation of the embodiment of the compressed air energy storage compression side stabilization power tracking control method is also applicable to the compressed air energy storage compression side stabilization power tracking control device of this embodiment, and will not be repeated here.

[0069] According to the compressed air energy storage compression side stabilization power tracking control device proposed in the embodiment of the present invention, fuzzy PID control theory is used to establish a compressed air energy storage compression side power tracking model including anti-surge valve control, and a neural network is used to train on a PID parameter set that can stabilize operation, so that it can output PID control parameters when the state variables are known, and then the parameters of the compressed air energy storage compression side power tracking model are updated. Therefore, when there is a surge risk, even if the anti-surge valve is opened to suppress the surge condition, the safe and stable operation range of the compressor will not be reduced, thereby ensuring that the efficiency of the power system is not affected.

[0070] Figure 4 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. The electronic device may include:

[0071] Memory 401 , processor 402 , and a computer program stored in the memory 401 and executable on the processor 402 .

[0072] When the processor 402 executes the program, the compressed air energy storage compression side stabilization power tracking control method provided in the above embodiment is implemented.

[0073] Furthermore, the electronic device further comprises:

[0074] The communication interface 403 is used for communication between the memory 401 and the processor 402 .

[0075] The memory 401 is used to store computer programs that can be executed on the processor 402 .

[0076] The memory 401 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0077] If the memory 401, the processor 402 and the communication interface 403 are implemented independently, the communication interface 403, the memory 401 and the processor 402 can be connected to each other through a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 4 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.

[0078] Optionally, in a specific implementation, if the memory 401, the processor 402 and the communication interface 403 are integrated on a chip, the memory 401, the processor 402 and the communication interface 403 can communicate with each other through an internal interface.

[0079] The processor 402 may be a central processing unit (CPU), or an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present invention.

[0080] An embodiment of the present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-mentioned compressed air energy storage compression side stabilization power tracking control method.

[0081] 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 do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or N 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.

[0082] 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 "N" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0083] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or N executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present invention includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present invention belong.

[0084] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purpose of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or N wirings (electronic devices), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways as necessary and then storing it in a computer memory.

[0085] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above embodiment, the N steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. If implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0086] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0087] In addition, each functional unit in each embodiment of the present invention may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0088] The storage medium mentioned above may be a read-only memory, a magnetic disk or an optical disk, etc. Although the embodiments of the present invention have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limiting the present invention. A person of ordinary skill in the art may change, modify, replace and modify the above embodiments within the scope of the present invention.

Claims

1. A method for tracking and controlling the compression side expansion power of compressed air energy storage, characterized in that: The following steps are involved: Establish a dynamic model of the pressure ratio of the compressed air energy storage compression side; Based on the transformation ratio dynamic model and fuzzy proportional integral differential PID control theory, a compressed air energy storage compression side power tracking model including anti-surge valve control is established; Establishing a PID data set of the compressed air energy storage compression side power tracking model including the anti-surge valve control, and using the PID data set to train a pre-built control neural network to obtain a stabilization performance neural network model; The real-time state variables of the compressed air energy storage compression side are input into the stabilization performance neural network model to obtain PID control parameters, and the PID control parameters are used to update the parameters of the compressed air energy storage compression side power tracking model including anti-surge valve control.

2. The compressed air energy storage compression side expansion stabilization power tracking control method according to claim 1 is characterized in that: The compressed air energy storage compression side includes an electric motor, a multi-stage compressor, an air storage reservoir, an anti-surge valve and a heat exchanger.

3. The compressed air energy storage compression side expansion stabilization power tracking control method according to claim 1 is characterized in that: The input quantities of the compressed air energy storage compression side power tracking model including anti-surge valve control are air mass flow, compressor speed, and air pressure, and the output quantities of the compressed air energy storage compression side power tracking model including anti-surge valve control are anti-surge valve opening and motor torque.

4. The compressed air energy storage compression side expansion stabilization power tracking control method according to claim 1 is characterized in that: The PID data set includes a parameter set that can be expanded and stabilized and power tracked and a parameter set that cannot achieve the target.

5. A compressed air energy storage compression side expansion stabilization power tracking control device, characterized in that: include: The first building block is used to establish a dynamic model of the pressure ratio of the compressed air energy storage compression side; The second building module is used to establish a compressed air energy storage compression side power tracking model including anti-surge valve control based on the transformation ratio dynamic model and fuzzy proportional integral differential PID control theory; A training module, for establishing a PID data set of the compressed air energy storage compression side power tracking model including the anti-surge valve control, and using the PID data set to train a pre-built control neural network to obtain a stabilization performance neural network model; An updating module is used to input the real-time state variables of the compressed air energy storage compression side into the stabilization performance neural network model to obtain PID control parameters, and use the PID control parameters to update the parameters of the compressed air energy storage compression side power tracking model including anti-surge valve control.

6. The compressed air energy storage compression side stabilization power tracking control device according to claim 5 is characterized in that: The compressed air energy storage compression side includes an electric motor, a multi-stage compressor, an air storage reservoir, an anti-surge valve and a heat exchanger.

7. The compressed air energy storage compression side stabilization power tracking control device according to claim 5 is characterized in that: The input quantities of the compressed air energy storage compression side power tracking model including anti-surge valve control are air mass flow, compressor speed, and air pressure, and the output quantities of the compressed air energy storage compression side power tracking model including anti-surge valve control are anti-surge valve opening and motor torque.

8. The compressed air energy storage compression side stabilization power tracking control device according to claim 5 is characterized in that: The PID data set includes a parameter set that can be expanded and stabilized and power tracked and a parameter set that cannot achieve the target.

9. 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 compressed air energy storage compression side stabilization power tracking control method as described in any one of claims 1 to 4.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: The program is executed by a processor to implement the compressed air energy storage compression side stabilization power tracking control method as described in any one of claims 1 to 4.

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