Compressed air energy storage system modeling simulation method based on Modelica language
By using the Modelica language to build compressed air energy storage system models, the problem of causal modeling difficulties is solved, efficient system design and operation guidance is achieved, the readability of the models and simulation efficiency are improved, and optimization throughout the entire life cycle is supported.
Patent Information
- Application Number
- CN202511368821.5
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-09-24
- Publication Date
- 2025-11-18
AI Technical Summary
In existing technologies, the modeling methods for compressed air energy storage systems suffer from difficulties in causal modeling, complex model adjustment, low reusability and versatility, and difficulty in achieving unified modeling across disciplines. This leads to large deviations in system efficiency prediction, extended development cycles, and fragmented toolchains that cause collaborative breakdowns and obstacles to solving algebraic loops.
A compressed air energy storage system model is constructed using the Modelica language. By decomposing the system components, and based on the energy conservation and mass conservation equations, combined with the medium model, the calculations at the component and system levels are realized, a high-fidelity model is established, supporting deep coupling of multiphysics fields, connecting the components to build a simulation model and solve the equations.
It enables efficient design and operation guidance for compressed air energy storage systems, improves model readability and maintainability, reduces computational complexity, supports simulation optimization throughout the entire lifecycle, and enhances system efficiency and innovation speed.
Smart Images
Figure CN120974768A_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The present application relates to the technical field of computer modeling and simulation, and particularly relates to a compressed air energy storage system modeling and simulation method based on a Modelica language. BACKGROUND
[0002] Building a new power system mainly based on new energy is a key measure to reduce carbon emissions. However, the intermittency and instability of renewable energy such as solar and wind energy bring challenges to the stability of the power system. Long-time energy storage technology becomes the key to balance supply and demand, and is expected to alleviate the peak shaving problem of the power grid. At present, only pumped storage and compressed air energy storage can meet the demand of long-time energy storage, and become the main energy storage form combined with power grid peak shaving, but pumped storage is limited by geography and environment. Compared with battery energy storage (limited in scale and high in cost) and pumped storage (strong dependence on geography), compressed air energy storage has large-scale (hundred megawatt level), long-time (hours to days) energy storage capacity and low cost, and has characteristics such as large capacity, long service life, intrinsic safety and providing rotational inertia, and becomes one of the key technical options to support the new power system.
[0003] The compressed air energy storage system includes an energy storage process and an energy release process, and involves main components such as compressors, turbines, heat exchangers and generators. The efficiency of the system depends largely on the control and operation of the energy storage process and the energy release process. Since the unit is often in variable operating conditions, studying and optimizing the variable operating characteristics of compressed air energy storage is the key to improving the safety and economy of the unit.
[0004] For the compressed air energy storage system, the traditional modeling method is a solid process model developed based on the causal modeling method of equations, and the solver is difficult to construct, has low extensibility, the model is complex to adjust, and has low reusability, universality and expandability. At the same time, in the dynamic system analysis model, it is difficult to realize unified modeling of cross-disciplinary models. Multi-field physical fields (thermodynamics, fluid, machinery and control) are independently modeled in different tools (such as CFD+MATLAB+Simulink), and data is transmitted through manual interface, which causes serious distortion of key coupling effects (such as dynamic interaction of compression heat-storage pressure-turbine efficiency). The causal modeling paradigm forces to preset the signal flow direction, so that the same physical component (such as a turbine) needs to be rebuilt when the charging / discharging mode is switched, which sacrifices the flexibility of the system. At the same time, in order to simplify the solution, empirical formulas (such as ideal gas instead of real state equation) and steady-state approximation are used, which cannot capture transient nonlinear behavior (such as valve start-stop pressure jump), and the collaborative fault caused by tool chain fragmentation and algebraic loop solving obstacles, eventually leading to a system efficiency prediction deviation of more than 10% and a development cycle extension of more than 30%, which significantly restricts the design accuracy and innovation speed of compressed air energy storage.
[0005] The Modelica language is a powerful language tool for the design, analysis and optimization of complex engineering systems due to its unity (multi-domain), physical nature (equation-based), flexibility (non-causal), efficiency (component reuse), robustness (handling complex problems) and openness (standard and open source ecosystem), which improves the universality and scalability of the model. The Modelica language is centered on classes to organize and encapsulate data, and connectors define flow variables and potential variables to ensure the directionality of flow and support the connection between components through connectors to build the transmission of physical quantities between components.
[0006] Therefore, it is of great significance to construct a precise compressed air energy storage system model using a convenient and applicable multi-platform modeling language to provide a solution for long-time energy storage, exert technical advantages, and provide a reliable solution for the development of new energy bases in deserts, gobi and deserts, and support the construction of new power systems. SUMMARY
[0007] In view of the problems in the prior art, the present application provides a compressed air energy storage system modeling and simulation method based on Modelica language, which uses Modelica language to construct a compressed air energy storage system, which can effectively avoid the causal modeling difficulty in traditional modeling methods, and at the same time realize the calculation at the component and system levels, and provide guidance for the design and efficient operation of the compressed air system.
[0008] To achieve this purpose, the present application adopts the following technical solutions:
[0009] The present application provides a compressed air energy storage system modeling and simulation method based on Modelica language, which comprises the following steps:
[0010] (1) determining the composition of the compressed air energy storage system to be modeled and simulated;
[0011] (2) splitting the compressed air energy storage system to be modeled and simulated in step (1) into each component to obtain a model library architecture;
[0012] (3) building a medium model based on Modelica language;
[0013] (4) modeling each component in step (2) based on Modelica language and energy conservation equation, mass conservation equation, and combining the medium model in step (3);
[0014] (5) connecting the models of each component modeling in step (4) based on Modelica language to establish a compressed air energy storage system simulation model;
[0015] (6) solving the equations in the compressed air energy storage system simulation model described in step (5) to obtain the parameter values of the inlets and outlets of each component.
[0016] The compressed air energy storage system modeling and simulation method based on the Modelica language provided by the application first splits the compressed air energy storage system to be modeled and simulated into components, then builds a medium model based on the Modelica language, and then encapsulates the medium model into each component model for modeling based on the Modelica language and the energy conservation equation and the mass conservation equation, so as to deeply couple multiple physical fields by coupling the thermodynamic principles of compressors, fluid transient of gas storage chambers and mechanical dynamics of turbines, and establish a high-fidelity model based on mass, energy and flow balance. Finally, the models of each component after modeling are connected based on the Modelica language to establish a compressed air energy storage system simulation model, equations in the compressed air energy storage system simulation model are solved to obtain the parameter values of the inlets and outlets of each component, the calculation of the component machine and the system coupling model can be realized, the system components are provided with reference for adjustment and design, and efficient operation of the system under different working conditions is realized. The compressed air energy storage system simulation model described in the application covers system-level verification with a single model from component design (optimization of compressor efficiency curve) to grid-level scheduling (verification of charge and discharge strategy), avoids data discontinuity of multiple tool chains, and can realize simulation optimization in the whole life cycle.
[0017] In step (1), the components of the compressed air energy storage system to be modeled and simulated are determined, which means that the number of compressors, turbines, heat exchangers, valves, heat storage medium storage devices, gas storage chambers, heat storage medium conveying devices, generators and motors in the compressed air energy storage system to be modeled and simulated and the connection relationship therebetween are determined.
[0018] Preferably, the components in step (2) include compressors, turbines, heat exchangers, valves, heat storage medium storage devices, gas storage chambers, heat storage medium conveying devices, generators and motors.
[0019] Preferably, the medium in step (3) includes air and heat storage medium.
[0020] Preferably, the heat storage medium includes any one of water, heat-conducting oil or molten salt.
[0021] Preferably, step (5) connects the models of each component after modeling in step (4) in a drag mode or a modular mode.
[0022] Preferably, the parameter values in step (6) include temperature, pressure, enthalpy and flow rate.
[0023] Preferably, the parameter values in step (6) are used for simulation analysis of the energy storage process and the energy release process of the compressed air energy storage system.
[0024] Preferably, the parameter values in step (6) are used for simulation analysis of the compressed air energy storage system in steady state and transient state.
[0025] Preferably, the transient state includes start-stop, load change and load shedding of the compressed air energy storage system.
[0026] Preferably, steps (3), (4) and (5) are based on Modelica language modeling on the Mworks platform.
[0027] The present application can realize component-based modeling by modeling based on Modelica language on the Mworks platform, greatly improve the readability and maintainability of the compressed air energy storage system simulation model by encapsulating and reusing components, and get rid of the complex causal-based modeling of traditional modeling. In addition, the Modelica model has good scalability and portability, can be easily integrated with other tools and platforms, supports multiple solvers and simulation environments, and has strong symbolic processing capability to automatically optimize model equations, reduce computational complexity and improve simulation efficiency.
[0028] As a preferred technical solution of the present application, the compressed air energy storage system modeling and simulation method comprises the following steps:
[0029] (1) determining the composition of the compressed air energy storage system to be modeled and simulated;
[0030] (2) splitting the compressed air energy storage system to be modeled and simulated in step (1) into components to obtain a model library architecture; the components include compressors, turbines, heat exchangers, valves, heat storage medium storage devices, air reservoirs, heat storage medium conveying devices, generators and motors;
[0031] (3) building a medium model based on Modelica language on the Mworks platform; the medium includes air and heat storage medium; the heat storage medium includes any one of water, heat conducting oil or molten salt;
[0032] (4) modeling each component in step (2) based on Modelica language and energy conservation equation, mass conservation equation, and combining the medium model in step (3) on the Mworks platform;
[0033] (5) connecting the models of each component modeling in step (4) based on Modelica language on the Mworks platform in a dragging or modular manner to establish a compressed air energy storage system simulation model;
[0034] (6) solving the equations in the compressed air energy storage system simulation model in step (5) to obtain parameter values of inlets and outlets of each component; the parameter values include temperature, pressure, enthalpy and flow rate;
[0035] The parameter values are used for simulation analysis of the energy storage process and the energy release process of the compressed air energy storage system; the parameter values are used for simulation analysis of the steady state condition and the transient condition of the compressed air energy storage system; the transient condition includes start and stop of the compressed air energy storage system, load increase and decrease, and load shedding.
[0036] Compared with the prior art, the present application has at least the following beneficial effects:
[0037] The compressed air energy storage system modeling and simulation method based on the Modelica language provided by the present application can effectively avoid the causality modeling difficulty in the traditional modeling method, and at the same time realize the calculation of the compressed air energy storage system and each component, thereby providing guidance for the design and efficient operation of the compressed air system. BRIEF DESCRIPTION OF DRAWINGS
[0038] Figure 1 is a flowchart of the compressed air energy storage system modeling and simulation method based on the Modelica language in the specific embodiment of the present application.
[0039] Figure 2 is a composition diagram of the compressed air energy storage system to be modeled and simulated in the specific embodiment of the present application.
[0040] In the figure: 1-Compressor 1#; 2-Class heat exchanger 1#; 3-Water cooler 1#; 4-Compressor 2#; 5-Class heat exchanger 2#; 6-Water cooler 2#; 7-Compressor 3#; 8-Class heat exchanger 3#; 9-Water cooler 3#; 10-Compressor 4#; 11-Class valve 1#; 12-Water cooler 4#; 13-Class valve 2#; 14-Gas storage; 15-Class valve 3#; 16-Three-class heat exchanger 1#; 17-Two-class valve; 18-Turbine 1# before air supplement; 19-Turbine 1# after air supplement; 20-Three-class heat exchanger 2#; 21-Turbine 2#; 22-Three-class heat exchanger 3#; 23-Turbine 3#; 24-Three-class valve 1#; 25-Three-class valve 2#; 26-First liquid storage tank; 27-Second liquid storage tank; 28-First water pump; 29-Second water pump. DETAILED DESCRIPTION
[0041] The technical solutions of the present application will be further described below in combination with the drawings and through specific embodiments.
[0042] The present application will be further described below. However, the following examples are only simple examples of the present application and do not represent or limit the protection scope of the present application, and the protection scope of the present application is subject to the claims.
[0043] As a specific embodiment of the present application, a compressed air energy storage system modeling and simulation method based on Modelica language is provided, and a flowchart thereof is shown in Figure 1 .
[0044] The compressed air energy storage system modeling and simulation method comprises the following steps:
[0045] (1) determining the composition of the compressed air energy storage system to be modeled and simulated, and a schematic diagram thereof is shown in Figure 2 . In the diagram, the red solid line represents air, the blue dotted line represents cold water, and the orange dotted line represents hot water.
[0046] The compressed air energy storage system to be modeled and simulated comprises, in sequence, a compressor 1#1, a first heat exchanger 1#2, a water cooler 1#3, a compressor 2#4, a second heat exchanger 2#5, a water cooler 2#6, a compressor 3#7, a third heat exchanger 3#8, a water cooler 3#9, a compressor 4#10, a first valve 1#11, a water cooler 4#12, a second valve 2#13, a gas storage 14, a third valve 3#15, a first third heat exchanger 1#16, a second valve 17, a turbine 1#air before supplementing 18, a turbine 1#air after supplementing 19, a second third heat exchanger 2#20, a turbine 2#21, a third third heat exchanger 3#22, and a turbine 3#23; the first third heat exchanger 1#16 is further connected to the turbine 1#air after supplementing 19 through a third valve 1#24; and the first third heat exchanger 1#16 is further connected to the turbine 2#21 through a third valve 2#25.
[0047] The compressor 1#1, the compressor 2#4, the compressor 3#7, and the compressor 4#10 are coaxially connected to a motor. The turbine 1#air before supplementing 18, the turbine 1#air after supplementing 19, the turbine 2#21, and the turbine 3#23 are all connected to a generator.
[0048] The compressed air energy storage system to be modeled and simulated further comprises a first liquid storage tank 26, a second liquid storage tank 27, a first water pump 28, and a second water pump 29. The first liquid storage tank 26 is connected to the first water pump 28, which is further connected to the first third heat exchanger 3#8, the second third heat exchanger 2#8, and the first third heat exchanger 1#2, respectively; the first third heat exchanger 3#8, the second third heat exchanger 2#5, and the first third heat exchanger 1#2 are all connected to the second liquid storage tank 27; the second liquid storage tank 27 is connected to the second water pump 29, which is further connected to the third third heat exchanger 3#22, the second third heat exchanger 2#20, and the first third heat exchanger 1#16, respectively; and the third third heat exchanger 3#22, the second third heat exchanger 2#20, and the first third heat exchanger 1#16 are all connected to the first liquid storage tank 26.
[0049] The heat storage medium in the specific embodiment is water, so the heat storage medium storage device is a liquid storage tank, and the heat storage medium conveying device is a water pump.
[0050] (2) decompose the compressed air energy storage system to be modeled in step (1) into components to obtain a model library architecture; the components include a compressor, a turbine, a heat exchanger, a valve, a heat storage medium storage device, an air reservoir, a heat storage medium conveying device, a generator, and a motor;
[0051] (3) build a medium model on an Mworks platform based on a Modelica language; the medium includes air and water;
[0052] (4) model each component in step (2) on an Mworks platform based on a Modelica language and energy conservation equations and mass conservation equations, in combination with the medium model in step (3);
[0053] (5) connect the models of the components in step (4) in a dragging or modular manner on an Mworks platform based on a Modelica language to establish a compressed air energy storage system simulation model;
[0054] (6) solve equations in the compressed air energy storage system simulation model in step (5) to obtain parameter values of inlets and outlets of the components; the parameter values include temperature, pressure, enthalpy, and flow rate;
[0055] The parameter values are used for simulation analysis of energy storage and energy release processes of the compressed air energy storage system, and are used for simulation analysis of steady-state conditions and transient conditions of the compressed air energy storage system; the transient conditions include start and stop of the compressed air energy storage system, load increase and decrease, and load shedding.
[0056] In the specific embodiment, the motor, the compressor 1#1, the heat exchanger 1#2, the water cooler 1#3, the compressor 2#4, the heat exchanger 2#5, the water cooler 2#6, the compressor 3#7, the heat exchanger 3#8, the water cooler 3#9, the compressor 4#10, the valve 1#11, the water cooler 4#12, the valve 2#13, the air reservoir 14, the first liquid storage tank 26, the second liquid storage tank 27, and the first water pump 28 perform the energy storage process of the compressed air energy storage system; the compressor mainly compresses air to a high-pressure state, the air reservoir is used for storing high-pressure air, the motor is used for driving the compressor, and the heat exchanger is used for recovering compression heat.
[0057] In the specific embodiment, the heat exchanger 1#16, the valve 17, the turbine 1#18, the turbine 1#19, the heat exchanger 2#20, the turbine 2#21, the heat exchanger 3#22, the turbine 3#23, the valve 1#24, the valve 2#25, the first liquid storage tank 26, the second liquid storage tank 27, the second water pump 29, and the generator perform the energy release process of the compressed air energy storage system; the turbine expands high-pressure gas to do work, the generator converts mechanical energy of the turbine into electrical energy, and the heat exchanger is used for heat exchange.
[0058] In the energy storage process, when the grid has surplus power, the motor drives the compressor to compress the normal pressure air into high pressure air, and the temperature of the air will rise due to compression. In order to improve the energy storage efficiency, the heat generated during the compression process is collected and stored in the second liquid tank 27. The high pressure air is stored in the air storage 14, waiting for the subsequent energy release process. The specific process is that the air is boosted by the compressor 1#1, the compressor 2#4, the compressor 3#7, and the compressor 4#10, and finally enters the air storage 14. During the compression process, the air is cooled by the first water pump 28, which drives the cold water in the first liquid tank 26 to enter the first heat exchanger 3#8, the second heat exchanger 2#5, and the first heat exchanger 1#2 to absorb the compression heat during the compression process, and then stored in the second liquid tank 27.
[0059] In the energy release process, the high pressure air in the air storage 14 expands to do work and is discharged to the atmosphere through the second valve 17, the turbine 1# before air supplement 18, the turbine 1# after air supplement 19, the turbine 2#21 and the turbine 3#23, and drives the generator to generate electricity, converts the compressed air energy stored in the second liquid tank 27 into electrical energy and outputs to the grid.
[0060] In this specific embodiment, intermediate air supplement is provided for the turbine 1#. After the pressure of the air storage 14 drops to the rated pressure, the third valve 1#24 and the third valve 2#25 are opened in turn as the pressure of the air storage 14 continues to drop. The hot water stored during the energy storage process is released from the second liquid tank 27 to the third heat exchanger 3#22, the third heat exchanger 2#20 and the third heat exchanger 1#16 by the second water pump 29 to heat the air and improve the work capacity of the turbine 2#21 and the turbine 3#23. The hot water in the second liquid tank 27 is discharged into the first liquid tank 26 after heat release.
[0061] In this specific embodiment, the compressed air energy storage system is modeled and simulated to have high efficiency. In the energy storage stage, the pressure and air charging flow are controlled, and the compression heat in the compression process is recycled. In the energy release stage, the discharge power is maintained by the operation mode of "throttling + air supplement", and the opening degree of the second valve 17, the third valve 1#24 and the third valve 2#25 can be controlled. At the same time, the heat exchange between the air storage 14 and the environment during the operation process can be considered, so that the efficiency of the compressed air energy storage system is above 65%.
[0062] The compressed air energy storage system constructed based on the Modelica language in the embodiment uses two media of compressed air and water, the water absorbs and utilizes the compression heat in the compression process, has the advantage of long-time energy storage, can store a large amount of electric energy, is suitable for used in power grid peak shaving, renewable energy consumption and the like, and effectively solves the problem of imbalance between power supply and demand. The air as the energy storage medium is free of chemical pollution, is environmentally friendly, is suitable for applied in the area where energy resources are rich but the flexibility of the power grid is insufficient, can effectively improve the stability and flexibility of the power grid, and promotes the large-scale development of renewable energy.
[0063] In conclusion, the modeling and simulation method of the compressed air energy storage system based on the Modelica language provided by the embodiment is object-oriented modeling, realizes componentized modeling, greatly improves the readability and maintainability of the model by encapsulating and reusing components, gets rid of the complexity of traditional modeling based on causality, and moreover, the Modelica model has good scalability and portability, can be conveniently integrated with other tools and platforms, supports multiple solvers and simulation environments, can automatically optimize model equations, reduces the calculation complexity, improves the simulation efficiency, and has large-scale popularization and application prospect.
[0064] The applicant declares that the above is only a specific embodiment of the present application, but the protection scope of the present application is not limited thereto, and those skilled in the art should understand that any changes or replacements within the technical scope disclosed by the present application can be easily thought by any person skilled in the art, and all fall within the protection scope and disclosure scope of the present application.
Claims
1. A modeling and simulation method for compressed air energy storage systems based on the Modelica language, characterized in that, The modeling and simulation method for the compressed air energy storage system includes the following steps: (1) Determine the composition of the compressed air energy storage system to be modeled and simulated; (2) The compressed air energy storage system to be modeled and simulated in step (1) is broken down into various components to obtain the model library architecture; (3) A media model was built based on the Modelica language; (4) Based on the Modelica language and the energy conservation equation and mass conservation equation, and combined with the medium model described in step (3), model each component in step (2) respectively; (5) Based on the Modelica language, connect the models of each component after modeling in step (4) to establish a simulation model of the compressed air energy storage system; (6) Solve the equations in the simulation model of the compressed air energy storage system described in step (5) to obtain the parameter values of the inlet and outlet of each component.
2. The compressed air energy storage system modeling and simulation method according to claim 1, characterized in that, The components in step (2) include a compressor, turbine, heat exchanger, valve, heat storage medium storage device, gas storage tank, heat storage medium conveying device, generator and motor.
3. The modeling and simulation method for compressed air energy storage systems according to claim 1 or 2, characterized in that, The medium in step (3) includes air and a heat storage medium.
4. The compressed air energy storage system modeling and simulation method according to claim 3, characterized in that, The heat storage medium includes any one of water, heat transfer oil, or molten salt.
5. The modeling and simulation method for compressed air energy storage systems according to any one of claims 1 to 4, characterized in that, Step (5) connect the models after modeling each component in step (4) using a drag-and-drop or modular approach.
6. The modeling and simulation method for compressed air energy storage systems according to any one of claims 1 to 5, characterized in that, The parameter values mentioned in step (6) include temperature, pressure, enthalpy, and flow rate.
7. The modeling and simulation method for compressed air energy storage system according to any one of claims 1 to 6, characterized in that, The parameter values described in step (6) are used for simulation analysis of the energy storage and release processes of the compressed air energy storage system.
8. The modeling and simulation method for compressed air energy storage system according to any one of claims 1 to 7, characterized in that, The parameter values described in step (6) are used for simulation analysis of steady-state and transient conditions of the compressed air energy storage system; Preferably, the transient operating conditions include starting and stopping the compressed air energy storage system, increasing or decreasing load, and shedding load.
9. The modeling and simulation method for compressed air energy storage system according to any one of claims 1 to 8, characterized in that, In steps (3), (4), and (5), modeling is performed on the Mworks platform using the Modelica language.
10. The modeling and simulation method for a compressed air energy storage system according to any one of claims 1 to 9, characterized in that, The modeling and simulation method for the compressed air energy storage system includes the following steps: (1) Determine the composition of the compressed air energy storage system to be modeled and simulated; (2) The compressed air energy storage system to be modeled and simulated in step (1) is divided into various components to obtain the model library architecture; the components include compressor, turbine, heat exchanger, valve, heat storage medium storage device, air storage tank, heat storage medium conveying device, generator and motor; (3) A medium model is built on the Mworks platform based on the Modelica language; the medium includes air and heat storage medium; the heat storage medium includes any one of water, heat transfer oil or molten salt; (4) Based on the Modelica language and the energy conservation equation and mass conservation equation, and combined with the medium model described in step (3), model each component in step (2) on the Mworks platform; (5) Based on the Modelica language on the Mworks platform, connect the models of each component modeled in step (4) in a drag-and-drop or modular manner to establish a simulation model of the compressed air energy storage system. (6) Solve the equations in the simulation model of the compressed air energy storage system described in step (5) to obtain the parameter values of the inlet and outlet of each component; the parameter values include temperature, pressure, enthalpy and flow rate; The parameter values are used for simulation analysis of the energy storage and release processes of the compressed air energy storage system; the parameter values are used for simulation analysis of the steady-state and transient operating conditions of the compressed air energy storage system; the transient operating conditions include the start-up and shutdown of the compressed air energy storage system, load increase / decrease, and load shedding.