Scene-based old cavity salt cavern compressed air energy storage stability evaluation method

Abstract

The invention relates to the technical field of compressed air energy storage, in particular to an old cavity salt cavern compressed air energy storage stability evaluation method based on scenes. The technical problems that in the prior art, an old cavity salt cavern stability evaluation method is single, test complexity is high, and combination with engineering practice is insufficient are solved, key scenes are optimized through orthogonal design, numerical simulation modeling is combined, and influences of geological conditions, cavity structures and operation working conditions on old cavity salt cavern stability are comprehensively analyzed. The method specifically comprises the steps of scene optimization design, numerical simulation modeling, FLAC3D software calculation and stability evaluation. According to the method, the problems that an existing method is single and the test complexity is high are solved, the evaluation cost is remarkably reduced, the precision and efficiency are improved, and the method is suitable for old cavity salt cavern safety evaluation and optimization design under the complex geological condition.

Description

Technical Field

[0001] The present invention relates to the technical field of compressed air energy storage, and particularly relates to a method for evaluating the stability of compressed air energy storage in old cavity salt caverns based on scenarios. Background Art

[0002] Compressed Air Energy Storage (CAES) is a large-scale and long-term physical energy storage technology, which can effectively address the volatility and intermittency problems of renewable energy power generation and shows great potential in balancing the power grid load and improving energy utilization efficiency. Using old cavity salt caverns as gas storage facilities for compressed air energy storage has the advantages of significantly reducing construction costs and shortening the construction period, and has become an important gas storage method for compressed air energy storage technology.

[0003] The stability of old cavity salt caverns is the key to ensuring the long-term stable operation of the CAES system. However, due to the long mining history of old cavity salt caverns, their internal structures are complex, stress distributions are uneven, and the interaction with the surrounding strata is significant. These factors lead to great uncertainties in their stability, posing challenges to the stable operation of the CAES system.

[0004] Currently, the evaluation methods for the stability of salt cavern compressed air energy storage at home and abroad mostly focus on new cavity salt caverns, while there are few evaluation methods for the stability of old cavity salt caverns. Moreover, when evaluating stability, only the influence of a single factor is often considered, lacking a systematic, scientific, comprehensive method that can accurately quantify and analyze and evaluate the stability of old cavity salt caverns. Summary of the Invention

[0005] The problem to be solved by the present invention is to propose a method for evaluating the stability of compressed air energy storage in old cavity salt caverns by combining scenario analysis and numerical simulation, so as to solve the technical problems of single evaluation method for the stability of old cavity salt caverns, high test complexity, and insufficient combination with engineering practice in the prior art.

[0006] In view of the deficiencies of the prior art, the technical solution adopted by the present invention to solve its technical problems is: a method for evaluating the stability of compressed air energy storage in old cavity salt caverns based on scenarios, including the following steps,

[0007] Step 1, Scenario optimization design: Determine three types of factors and their levels that affect the stability of old cavity salt caverns, namely geological conditions, cavity structure, and operating conditions; use the orthogonal design method to select key scenarios from all possible scenarios;

[0008] Step 2, Numerical simulation modeling: Based on the parameters of the selected scenarios, construct a numerical simulation model of compressed air energy storage in old cavity salt caverns;

[0009] Step 3. Stability numerical simulation: Using the FLAC3D software and combining with the salt rock creep constitutive model, calculate the creep displacement around the cavity and the volume shrinkage rate under different scenarios;

[0010] Step 4. Stability evaluation: Analyze and evaluate the stability of the old cavity salt cavern according to the creep displacement and volume shrinkage rate indicators.

[0011] Preferably, the geological conditions include formation lithology, interlayer thickness and quantity, the cavity structure includes mining technology, solution cavity volume and burial depth, and the operating conditions include working pressure.

[0012] Preferably, the salt rock creep constitutive model is the improved Norton Power-Law model, and its mathematical expression is:

[0013]

[0014] Where: is the creep rate; A is the material property constant; n is the stress index constant; is the deviatoric part of σ ij

[0015] Preferably, the indicators for stability evaluation in Step 4 include the maximum creep displacement around the cavity and the volume shrinkage rate, and post-processing analysis of the simulation results is carried out through a visualization tool.

[0016] Preferably, the steps for stability simulation calculation using the FLAC3D software are as follows,

[0017] Import of the numerical simulation model of the old cavity salt cavern:

[0018] FLAC3D initial condition setting;

[0019] Time discretization and time step calculation;

[0020] Time integration update;

[0021] Stress state update;

[0022] Check the equilibrium condition and convergence;

[0023] Output and post-processing of the scenario simulation results.

[0024] Preferably, when using the FLAC3D software for numerical simulation, the time step satisfies the CFL condition where l is the minimum size of the element and c is the wave speed in the material.

[0025] ​Preferably, the time integration update uses an explicit central difference scheme to perform time integration on the motion equations, and gradually updates the velocities and displacements of the nodes. Let the time step be Δt, and the update formula for the node velocity is where is the velocity at the next time step, and a n is the acceleration at the current moment; the update formula for the node displacement is where u n+1 is the displacement at the next moment, and u n is the current displacement.

[0026] Preferably, the stress state update formula is σ n+1 = σ n + C:Δε, where C is the stiffness matrix of the material, and Δε is the incremental strain, ensuring that the stress change is consistent with the material properties and deformation characteristics.

[0027] Preferably, the FLAC3D initial condition settings include the initial stress state, boundary conditions, and material properties.

[0028] Preferably, the setting of the boundary conditions includes the following contents

[0029] 1) Calculate the equivalent load according to the depth from the upper surface of the model to the ground surface and the rock density, and simplify it to a vertical uniformly distributed load acting on the upper surface of the model;

[0030] 2) Simplify the gas pressure in the salt cavern cavity to a uniformly distributed load acting vertically on the inner surface of the cavity;

[0031] 3) Assume that the geological bodies around the model are rigid bodies, and apply vertical simply supported constraints to the boundaries around and at the bottom of the model to restrict the normal displacement;

[0032] 4) Set the vertical stress gradient according to the unit weight of each rock layer to simulate the actual stress distribution state of the formation.

[0033] The beneficial effects of the present invention are as follows: By combining the methods of scenario analysis and numerical simulation, the present invention comprehensively considers the complex geological conditions, cavity structure, and operating conditions of the old cavity salt cavern, and proposes a scientific and efficient stability evaluation method for the compressed air energy storage in the old cavity salt cavern. This method systematically identifies the complex characteristics and stability uncertainties of the old cavity salt cavern, optimizes the key scenarios through orthogonal scenario design, significantly reduces the test complexity, and at the same time combines numerical simulation technology to accurately quantify and evaluate the stability under different scenarios. This method is easy to operate, the evaluation process is efficient and accurate, applicable to the stability evaluation of old cavity salt caverns under complex geological conditions, and has important engineering application value and promotion potential. Description of the Drawings

[0034] Figure 1 is a schematic diagram of the scenario optimization design of the present invention;

[0035] Figure 2 It is a schematic cross-sectional view of the numerical simulation model of the old cavity salt cavern of the present invention;

[0036] Figure 3 It is a flow chart of the method of the present invention;

[0037] Figure 4 It is a broken line graph of the maximum creep displacement around the cavity under different interlayer thickness conditions;

[0038] Figure 5 Contour map of the cavity displacement distribution under different mining process conditions;

[0039] Figure 6 Broken line graph of the maximum creep displacement around the cavity under different working pressure range conditions. Detailed implementation manners

[0040] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific implementation manners. The embodiments of the present invention are given for the purpose of illustration and description, and are not exhaustive or limited to the disclosed form. Many modifications and variations are obvious to those of ordinary skill in the art. The embodiments are selected and described to better illustrate the principles and practical applications of the present invention, and enable those of ordinary skill in the art to understand the present invention and thus design various embodiments with various modifications suitable for specific purposes.

[0041] The present invention identifies the complex characteristics of the old cavity salt cavern and various operating conditions of compressed air energy storage through a scenario analysis system, optimizes the key scenarios affecting the stability of the old cavity salt cavern by using the orthogonal design method, and combines numerical simulation technology to analyze and evaluate the stability of the old cavity salt cavern under different scenarios. This method can scientifically quantify the stability of the old cavity salt cavern, provide a scientific basis for its safety assessment, operation optimization and engineering design, and significantly improve the long-term stability and economy of the compressed air energy storage system. The specific steps are as follows:

[0042] 1. Scenario optimization design

[0043] The main factors affecting the stability of the old cavity salt cavern can be summarized into three aspects: geological condition parameters, cavity structure parameters and operating condition parameters. Among them, the geological condition parameters include formation lithology, interlayer thickness and quantity; the cavity structure parameters involve mining technology, cavity volume and burial depth; the operating condition parameters are mainly reflected in the working pressure. These influencing factors and their levels are summarized in Table 1.

[0044] By combining various stability influencing factors and their levels in Table 1, all possible scenarios of compressed air energy storage in the old cavity salt cavern are constructed. Then, using the orthogonal design method, combined with the geological conditions, cavity structure and operating conditions of compressed air energy storage in the old cavity salt cavern, the key scenarios that meet the actual engineering requirements and have a significant impact on the stability of the old cavity salt cavern are optimized. Through scenario optimization design, the test complexity can be significantly reduced on the premise of ensuring the accuracy of the results, providing a scientific basis and an efficient experimental scheme for subsequent stability analysis. The schematic diagram of scenario optimization design is as shown in Figure 1 shown.

[0045] Table 1 Influence Scenario Factors and Levels of Compressed Air Energy Storage Stability in the Old Cavity Salt Cavern

[0046]

[0047]

[0048] 2. Scenario Parameter Input

[0049] According to the geological conditions, cavity structure and operating conditions of the optimized scenario, a numerical simulation model of compressed air energy storage in the salt cavern is constructed, and the corresponding scenario parameters are input to ensure that the model can accurately reflect the scenario characteristics and be highly consistent with the actual operating conditions.

[0050] 3. Numerical Simulation Modeling of the Stability of Compressed Air Energy Storage in the Old Cavity Salt Cavern Based on Scenarios

[0051] 3.1 Selection of Salt Rock Creep Constitutive Model

[0052] Before constructing the numerical simulation model of the stability of compressed air energy storage in the salt cavern, it is necessary to first determine the creep constitutive model of salt rock. This model is used to describe the long-term deformation behavior of salt rock under different stress states and loading paths, and is the basis for accurately simulating the stability of the salt cavern. The currently widely used model is the Norton Power model (also known as the power-law model) proposed by Norton. The Norton Power-Law model developed on this basis further combines the Mohr-Coulomb criterion and integrates the advantages of viscoelasticity and plasticity theories, and can more accurately describe the creep behavior of salt rock. The mathematical expression of this model is as follows:

[0053]

[0054] In the formula: is the creep rate; A is the material characteristic constant; n is the stress exponent constant; is the deviatoric part of σ ij , and σ ij is the stress tensor.

[0055] Creep rate It can be divided into two components according to different stress states:

[0056]

[0057] In the formula:

[0058]

[0059] The exponential model reflecting the steady-state creep rate of salt rock is expressed as follows:

[0060]

[0061] In the formula: K and m are creep experiment constants; ΔQ is the activation energy; T is the absolute temperature (K); Δσ is the deviator stress; σ * is the unit stress; R is the universal gas constant.

[0062] 3.2 Establishment of the numerical simulation model of the old cavity salt cavern

[0063] According to the geological conditions, cavity structure and operation conditions of the studied old cavity salt cavern, a geological model of the basic case and the corresponding numerical simulation model were constructed. The schematic cross-section is as Figure 2 shown. The basic case assumes the use of a single-well convection mining process. The dissolution cavity is ellipsoidal, with a cavity height of 120 m, a diameter of 80 m, and a height-to-diameter ratio of 1.5. Considering that when the boundary size of the geological model reaches more than 5 times the diameter of the salt cavern, the influence of the boundary effect on the deformation of the rock around the cavity can be ignored. Therefore, a cube with a size of 800 m × 800 m × 800 m was selected as the salt cavern geological model, and the top of the model was set at a position 1200 m from the ground. In this model, the salt cavern cavity exists in the salt rock formation and contains two mudstone interlayers, each 2 m thick.

[0064] 3.3 Calculation and solution of FLAC3D

[0065] FLAC3D is a three-dimensional finite difference software developed by the American ITASCA Group. This software uses an explicit Lagrangian algorithm and a mixed-discrete zoning technique, which can accurately simulate plastic failure and plastic flow in three-dimensional space, and can more accurately reflect the creep characteristics of salt rock. It has significant advantages in simulation accuracy and rationality. Therefore, FLAC3D software was used as the tool for simulating and calculating the stability of the old cavity salt cavern. The specific steps for simulating and calculating the stability are as follows:

[0066] 1) Import of the numerical simulation model of the old cavity salt cavern: Import the constructed numerical simulation model of the old cavity salt cavern into FLAC3D software.

[0067] 2) Initial conditions setting in FLAC3D: Define the initial conditions, including the initial stress state, boundary conditions, etc., and at the same time set the material properties, such as elastic modulus, Poisson's ratio, etc.

[0068] 3) Time discretization and time step calculation: FLAC3D adopts an explicit time integration method and usually uses the central difference format to update the system state. The time step needs to satisfy the CFL condition (Courant - Friedrichs - Lewy condition) to ensure the stability of the calculation: where l is the minimum size of the element and c is the wave speed in the material.

[0069] 4) Time integration update: Use the explicit central difference format to perform time integration on the motion equation and gradually update the velocity and displacement of the nodes. Let the time step be Δt, and the update formula for the node velocity is where is the velocity at the next time step, and a n is the acceleration at the current moment. The update formula for the node displacement is where u n+1 is the displacement at the next moment, and u n is the current displacement.

[0070] 5) Stress state update: According to the selected constitutive model, calculate the stress state at the new time step. The stress state update formula is σ n+1 = σ n + C:Δε, where C is the stiffness matrix of the material and Δε is the incremental strain, ensuring that the stress change is consistent with the material properties and deformation characteristics.

[0071] 6) Check the equilibrium condition and convergence: Calculate the residual force (the difference between the internal force and the external force) to judge whether the system reaches the equilibrium state. If it does not reach the equilibrium, continue to iterate into the next time step until the convergence condition is satisfied.

[0072] 7) Output and post - processing of the scenario simulation results: Record the key output data (such as the creep displacement around the salt cavern and the volume shrinkage rate, etc.) under different scenarios, and process and display the results through visualization means to provide a basis for the stability analysis.

[0073] 4. Stability analysis and evaluation of old - cavity salt caverns under various scenarios

[0074] For various scenarios of compressed air energy storage in old - cavity salt caverns, based on the simulation results of key stability indicators such as the maximum creep displacement around the cavity and the volume shrinkage rate, analyze and evaluate the stability of old - cavity salt caverns under different scenarios, reveal the key influencing factors and their action mechanisms, and provide a scientific basis for the safety assessment and optimal design of old - cavity salt caverns.

[0075] Through orthogonal scenario design, a multi-factor combined scenario is systematically constructed from a global perspective, and key scenarios that meet the actual requirements are optimized. Numerical simulation can quantitatively analyze the key stability indicators in a specific scenario, providing a scientific basis for stability assessment. Combining scenario analysis with numerical simulation can more comprehensively address the uncertainties in the stability of old cavity salt caverns.

[0076] The present invention provides a method for evaluating the stability of compressed air energy storage in old cavity salt caverns based on scenario analysis and numerical simulation. By orthogonal design, key scenarios are optimized from multi-factor combinations. Combining with an improved Norton Power-Law creep constitutive model and FLAC3D software, key indicators such as creep displacement around the cavity and volume shrinkage rate are quantitatively analyzed, realizing a scientific evaluation of the stability of old cavity salt caverns. This method has high systematicness and strong operability, can significantly reduce the test complexity, provides a reliable basis for the safe operation of old cavity salt caverns and the optimization of energy storage systems, and has important engineering application value.

[0077] The scenario optimization method adopted in this study is based on orthogonal design. By combining various stability influencing factors and their levels in Table 1, a total of 432 compressed air energy storage scenarios can be obtained. The huge number of scenarios poses challenges to the research work. Orthogonal design is an efficient experimental design method. By reasonably allocating experimental schemes, it can comprehensively understand the system performance with fewer experimental times in the case of multiple factors and multiple levels. Its core idea is to use the principle of "uniform dispersion" to distribute the level combinations of all factors as evenly as possible in the experimental scheme, so as to reduce the number of experiments while ensuring the representativeness and reliability of the results.

[0078] This study uses the orthogonal design method and combines the geological conditions, cavity structure and operating conditions of compressed air energy storage in old cavity salt caverns to optimize the designed scenarios. In terms of geological conditions, the stratigraphic lithology varies significantly in different regions. For example, in engineering areas dominated by impurity-containing salt rock, when optimizing scenarios, the consideration of scenarios related to pure salt rock cavities can be appropriately weakened, and the focus can be on the factor combinations of impurity-containing salt cavities. In terms of cavity structure, considering that the single-well convection mining technology is relatively mature, while the horizontal docking mining technology is more complex and difficult, in the process of optimizing the designed scenarios, the factor combinations related to single-well convection mining can be given more emphasis. In terms of operating conditions, according to the in-situ stress characteristics of the formation where the case old cavity salt cavern is located, the factor combinations matching the actual working pressure conditions are optimized. By screening and weighing in combination with engineering practice, the orthogonal design method can not only effectively reflect the influence of various factors, but also optimize scenarios that meet the actual requirements, significantly reducing the test complexity while ensuring accuracy, providing a scientific basis for the design and implementation of compressed air energy storage systems.

[0079] During the model calculation process, the boundary conditions are set as follows:

[0080] 1) Calculate the equivalent load as 26.7 MPa according to the depth from the upper surface of the model to the ground surface and the rock density, and simplify it to a vertical uniformly distributed load acting on the upper surface of the model.

[0081] 2) Simplify the gas pressure in the salt cavern cavity to a uniformly distributed load acting vertically on the inner surface of the cavity. Referring to the operation data of the already-operated power stations such as Huntorf, McIntosh and Jintan Power Station, the injection-production pressure difference is controlled within 3 MPa. In this study, the injection-production cycle of the compressed air energy storage system is set to 24 hours, including 8 hours of gas injection, 12 hours of high-pressure gas storage and 4 hours of gas production. The difference between the maximum and minimum working pressures is 3 MPa, and the specific pressure values are determined according to different working conditions.

[0082] 3) Assume that the geological bodies around the model are rigid bodies, and apply vertical simply supported constraints to the boundaries around and at the bottom of the model to restrict the normal displacement.

[0083] 4) Set the vertical stress gradient according to the unit weight of each rock layer to simulate the actual stress distribution state of the strata.

[0084] In this study, the Norton Power-Law creep model is used to characterize the creep characteristics of salt rock, and the creep parameters are obtained by referring to relevant literature and experimental data. In the numerical simulation model of salt cavern stability, the mechanical parameters used in the calculation of three lithologies, namely mudstone, mudstone interlayer and salt rock, are shown in Table 2. Note: The data source in Table 2 is the reference: Fu Xing. Numerical Simulation Study on the Stability of Compressed Air Energy Storage Cavity [D]. Beijing: China University of Petroleum (Beijing), 2018.

[0085] Table 2 Rock mechanical parameters used in numerical calculation

[0086]

[0087] Traditional test or numerical simulation methods can only evaluate the stability of the salt cavern compressed air energy storage cavity under the action of a single factor, while the numerical simulation method based on scenario design in this patent can evaluate the stability of the salt cavern compressed air energy storage cavity under the combined action of multiple factors such as geological conditions, cavity structure and operation conditions, which not only has higher accuracy but also a wider applicable range.

[0088] Constructed the scenario combinations of various factors and their levels that affect the stability of the old cavity salt cavern compressed air energy storage, and then combined with the geological conditions, cavity structure and operation conditions of the case salt cavern, and selected the key scenarios that meet the actual conditions from them, including a basic case and multiple scenarios with different factor combinations. The specific scenarios and parameter settings are shown in Table 3.

[0089] In terms of geological conditions, the scenario design selects the interlayer thickness and the number of interlayers that have a greater impact on the stability of the salt cavern cavity for analysis. The stability of the salt cavern cavity is studied under the conditions of interlayer thicknesses of 2m, 3m, and 4m, and the number of interlayers of 1, 2, and 3 respectively. In terms of the cavity structure, the scenario design focuses on the single-well convection extraction method, while also taking into account the horizontal docking extraction method, and studies the stability of the salt cavern cavity under the conditions of solution cavity depths of 1600m and 2000m respectively. In terms of operating conditions, the working pressure scenarios are designed according to the depth of the formation where the case salt cavern is located. The stability of the salt cavern cavity is studied under the conditions of working pressure ranges of 16 - 19MPa, 19 - 22MPa, and 22 - 25MPa respectively.

[0090] The basic case selects the most representative combination of salt cavern factors in the case area as the scenario for evaluating the stability of the old cavity salt cavern compressed air energy storage under standard conditions. The scenario analysis cases, on the other hand, simulate the changes in different geological conditions, cavity structures, and operating conditions by adjusting key parameters to comprehensively evaluate the influence of these factors on the stability of the old cavity salt cavern.

[0091] Table 3 Scenario Design and Parameter Settings

[0092]

[0093] Figure 4 It shows the simulation results of the maximum creep displacement around the cavity of the old cavity salt cavern after 30 years of compressed air energy storage operation under different interlayer thickness conditions. From Figure 4 it can be seen that under the same interlayer thickness condition, the maximum creep displacement around the cavity of the old cavity salt cavern increases year by year with the increase of the operation time, indicating that the salt cavern cavity will undergo slow creep deformation under the action of the cyclic injection and production pressure of the compressed air energy storage system, and long-term accumulation may pose a risk to the cavity stability. In addition, under the same operation duration, the larger the interlayer thickness of the salt cavern cavity, the smaller the maximum creep displacement generated, however, this difference is not significant, indicating that the interlayer can inhibit the deformation of the salt cavern cavity to a certain extent, thereby improving its stability.

[0094] Figure 5 It shows the contour map of the cavity displacement distribution of the old cavity salt cavern after 30 years of compressed air energy storage operation under different extraction process conditions. From Figure 5It can be seen that, whether it is a salt cavern formed by single-well convection mining or horizontal docking mining, slow creep displacement has occurred under the long-term cyclic injection-production pressure. Specifically, a downward creep displacement appears at the top of the salt cavern cavity, while an upward creep displacement occurs at the bottom, showing an overall shrinking trend. Horizontally, the shrinkage of the cavity is mainly concentrated in the middle of the cavity side, and the interlayer restricts the shrinkage of the cavity to a certain extent. In addition, after 30 years of compressed air energy storage operation, the overall horizontal and vertical displacements of the salt cavern formed by horizontal docking mining are greater than those of the salt cavern formed by single-well convection mining, indicating that the overall stability of the salt cavern formed by horizontal docking mining is lower than that of the salt cavern formed by single-well convection mining. It should be noted that the vertical displacement accumulation of the double-cavity connection part of the salt cavern formed by horizontal docking mining is relatively significant under the long-term cyclic injection-production pressure. Therefore, when conducting stability evaluation, the stability of this part should be focused on.

[0095] Figure 6 Figure 4 shows the simulation results of the maximum creep displacement around the cavity of the old salt cavern after 30 years of compressed air energy storage operation under different working pressure ranges. From Figure 6 it can be seen that, under the same working pressure range, the maximum creep displacement around the cavity of the old salt cavern gradually increases with the increase of the operation time; under the same operation duration, the higher the working pressure range in the cavity, the smaller the maximum creep displacement around the cavity of the old salt cavern. The results show that increasing the working pressure range of the compressed air energy storage system can effectively inhibit the deformation of the surrounding rock, thereby improving the overall stability of the salt cavern.

[0096] Table 4 shows the simulation results of the volume shrinkage rate of the old salt cavern after 30 years of compressed air energy storage operation under different scenarios and factor levels. It can be seen from Table 4 that, under the same interlayer thickness condition, the old salt cavern will experience volume shrinkage under long-term cyclic loading, which affects its stability. Under the same operation time, the greater the interlayer thickness, the lower the volume shrinkage rate of the solution cavity, indicating that some hard interlayers have an inhibitory effect on the deformation of the salt cavern cavity, which helps to reduce volume shrinkage and enhance the cavity stability. In addition, under the same number of interlayers condition, the volume shrinkage rate of the old salt cavern shows a gradually increasing trend with the increase of the operation time; under the same operation duration, the more the number of interlayers, the smaller the volume shrinkage rate of the solution cavity, further verifying the inhibitory effect of the hard interlayer on the cavity deformation, playing a role similar to that of reinforcement, thereby effectively improving the overall stability of the salt cavern cavity.

[0097] Scenario 3 in Table 4 shows the simulation results of the volume shrinkage rate of the old cavity salt cavern after 30 years of compressed air energy storage operation under different cavity depths. It can be seen from the table that under the same cavity depth condition, the volume shrinkage rate of the old cavity salt cavern gradually increases with the increase of the operation time; under the same operation duration, the deeper the cavity depth, the greater the volume shrinkage rate of the salt cavern. This is mainly because under the same burial depth condition, the working pressure in the cavity is lower than the formation stress, and with the increase of the cavity depth, the difference between the working pressure in the cavity and the external ground stress gradually expands, resulting in an increase in the uneven stress on the salt rock, and the salt layer continuously moves into the cavity, ultimately leading to an increase in the volume shrinkage rate.

[0098] Scenario 4 in Table 4 shows the simulation results of the volume shrinkage rate of the old cavity salt cavern after 30 years of compressed air energy storage operation under different working pressure ranges. It can be seen from the table that under the same working pressure range condition, the volume shrinkage rate of the old cavity salt cavern gradually increases with the increase of the operation time; under the same operation duration, with the increase of the working pressure range, the volume shrinkage rate of the old cavity salt cavern gradually decreases, indicating that increasing the working pressure range of the compressed air energy storage system can, to a certain extent, inhibit the creep displacement of the salt cavern cavity, thereby improving the overall stability of the salt cavern. It should be noted that a higher working pressure range will cause the compressed air to consume more energy, and too high a pressure may lead to an increase in the permeability of the surrounding rock, thereby increasing the risk of leakage of the gas storage. Therefore, when determining the most suitable working pressure range, the stability, tightness and cost - effectiveness of the cavity should be comprehensively considered.

[0099] Table 4 Simulation results of volume shrinkage rate under different scenarios and factor levels

[0100]

[0101]

[0102] During the model calculation process, the boundary conditions are set as follows:

[0103] 1) Calculate the equivalent load as 26.7 MPa according to the depth from the upper surface of the model to the ground surface and the rock density, and simplify it to a vertical uniformly distributed load acting on the upper surface of the model.

[0104] 2) Simplify the gas pressure in the salt cavern cavity to a uniformly distributed load acting vertically on the inner surface of the cavity. Referring to the operation data of the already - put - into - operation power stations such as Huntorf, McIntosh and Jintan Power Station, the injection - production pressure difference is controlled within 3 MPa. In this study, the injection - production cycle of the compressed air energy storage system is set to 24 hours, including 8 hours of gas injection, 12 hours of high - pressure gas storage and 4 hours of gas production. The difference between the maximum and minimum working pressures is 3 MPa, and the specific pressure values are determined according to different working conditions.

[0105] 3) Assume that the geological bodies around the model are rigid bodies, and vertical simply supported constraints are applied to the boundaries around and at the bottom of the model to restrict the normal displacement.

[0106] 4) Set the vertical stress gradient according to the unit weight of each rock stratum to simulate the actual stress distribution state of the stratum.

[0107] The present invention optimizes key scenarios through orthogonal design, combines numerical simulation technology, and comprehensively analyzes the influence of geological conditions, cavity structures, and operating conditions on the stability of old cavity salt caverns. Specifically, it includes steps such as scenario optimization design, numerical simulation modeling, FLAC3D software calculation, and stability evaluation. The present invention solves the problems of single existing methods and high test complexity, significantly reduces the evaluation cost, improves the accuracy and efficiency, and is applicable to the safety assessment and optimization design of old cavity salt caverns under complex geological conditions.

Claims

1. A scenario-based stability evaluation method for compressed air energy storage in old cavity salt mines, characterized by: It includes the following steps: Step 1, Scenario optimization design: Determine three types of factors and their levels that affect the stability of the old cavity salt cavern, namely geological conditions, cavity structure, and operating conditions; Using the orthogonal design method, select the key scenarios from all possible scenarios; Step 2, Numerical simulation modeling: Based on the parameters of the selected scenarios, construct a numerical simulation model for compressed air energy storage in the old cavity salt cavern; Step 3, Stability numerical simulation: Use the FLAC3D software, combined with the salt rock creep constitutive model, to calculate the creep displacement around the cavity and the volume shrinkage rate under different scenarios; Step 4, Stability evaluation: Analyze and evaluate the stability of the old cavity salt cavern according to the creep displacement and volume shrinkage rate indicators.

2. The method for evaluating the stability of the scenario-based compressed air energy storage in old cavity salt according to claim 1, characterized in that: The geological conditions include formation lithology, interlayer thickness and quantity, the cavity structure includes mining technology, solution cavity volume and burial depth, and the operating conditions include working pressure.

3. The method for evaluating the stability of the scenario-based compressed air energy storage in old cavity salt caves according to claim 1, wherein: The salt rock creep constitutive model is an improved Norton Power-Law model, and its mathematical expression is: Wherein: is the creep rate; A is the material characteristic constant; n is the stress exponent constant; is the deviatoric part of σ ij .

4. The method for evaluating the stability of the scenario-based compressed air energy storage in old cavity according to claim 1, wherein: The indicators for stability evaluation in Step 4 include the maximum creep displacement around the cavity and the volume shrinkage rate, and the simulation results are post-processed and analyzed through visualization tools.

5. The method for evaluating the stability of the scenario-based compressed air energy storage in old cavity salt caves according to claim 1, wherein: The steps for stability simulation calculation using the FLAC3D software are as follows: Import of the numerical simulation model of the old cavity salt cavern; FLAC3D initial condition setting; Time discretization and time step calculation; Time integration update; Stress state update; Check the equilibrium condition and convergence; Output and post-processing of the scenario simulation results.

6. The scenario-based stability evaluation method for compressed air energy storage in old cavity according to claim 5, wherein: When using the FLAC3D software for numerical simulation, the time step satisfies the CFL condition where l is the minimum size of the element and c is the wave speed in the material.

7. The scenario-based stability evaluation method for compressed air energy storage in old cavity salt according to claim 5, wherein: The time integration update uses an explicit central difference scheme to perform time integration on the motion equations and gradually update the velocities and displacements of the nodes. Assuming the time step is Δt, the update formula for the node velocity is where is the velocity at the next time step, and a n is the acceleration at the current moment; The formula for updating the nodal displacement is where u n+1 is the displacement at the next moment, and u n is the current displacement.

8. The method for evaluating the stability of scenario-based compressed air energy storage in old cavity salt caves according to claim 5, characterized in that: The stress state update formula is σ n+1 = σ n + C:Δε, where C is the stiffness matrix of the material and Δε is the incremental strain, ensuring that the stress change is consistent with the material properties and deformation characteristics.

9. The method for evaluating the stability of the scenario-based compressed air energy storage in old cavity salt caverns according to claim 5, wherein: The FLAC3D initial condition setting includes the initial stress state, boundary conditions, and material properties.

10. The method for evaluating the stability of the scenario-based compressed air energy storage in old cavity salt according to claim 9, characterized in that: The setting of the boundary conditions includes the following contents: 1) Calculate the equivalent load according to the depth from the upper surface of the model to the ground surface and the rock density, and simplify it into a vertical uniformly distributed load acting on the upper surface of the model; 2) Simplify the gas pressure in the salt cavern cavity into a uniformly distributed load acting vertically on the inner surface of the solution cavity; 3) Assume that the geological bodies around the model are rigid bodies, and apply vertical simply supported constraints to the boundaries around and at the bottom of the model to limit the normal displacement; 4) Set the vertical stress gradient according to the unit weight of each rock layer to simulate the actual stress distribution state of the strata.

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