Method for optimizing operation pressure and storage capacity of compressed air energy storage salt-cavern gas storage

Abstract

The invention belongs to the technical field of compressed air energy storage. The invention provides a compressed air energy storage salt cavern gas storage operating pressure and storage capacity optimization method. Comprising seven steps of determining electric energy requirements, evaluating salt cavern geological conditions, initially setting geometric and pressure boundaries, calculating reservoir mass flow, determining adaptive maximum and minimum working pressures of the reservoir, estimating reservoir capacity, and implementing maximum and minimum working pressure-reservoir capacity coupling optimization. By establishing the multi-parameter coupling optimization model, geological conditions, equipment performance and safety specifications are comprehensively considered, the optimal balance of energy storage density, economy and safety is achieved, and the method is suitable for design of the salt cavern type compressed air energy storage system and has the advantages of being high in system collaboration, high in engineering applicability and the like.

Description

Technical Field

[0001] This invention relates to the field of compressed air energy storage technology, specifically to a method for optimizing the operating pressure and storage capacity of a compressed air energy storage salt cavern gas storage facility. Background Technology

[0002] The statements in this section are merely background information related to the present invention and do not necessarily constitute prior art.

[0003] Compressed-air energy storage (CAES) is a large-scale, long-term energy storage technology, and the design of its underground gas storage facility is a key factor affecting the system's efficiency, safety, and economy. Salt cavern gas storage facilities have become the preferred gas storage medium for CAES systems due to their advantages such as low permeability, good sealing performance, and high flexibility.

[0004] However, the existing technology has the following problems: (1) Traditional design methods often consider the operating pressure range and storage capacity separately, ignoring the coupling relationship between the two, resulting in non-optimal design results; (2) When determining the pressure range, the mutual balance between geological conditions, equipment performance and operational safety is not fully considered; (3) When calculating the storage capacity, the two working conditions of variable and constant storage pressure are not distinguished, resulting in insufficient accuracy of the calculation results; and there is a lack of systematic optimization models, making it difficult to achieve the best balance between energy storage density, economy and safety. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a method for optimizing the operating pressure and storage capacity of compressed air energy storage salt cavern gas storage facilities. By establishing a multi-parameter coupled optimization model, and comprehensively considering geological conditions, equipment performance, and safety standards, the optimal balance between energy storage density, economy, and safety is achieved.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: In a first aspect, the present invention provides a method for optimizing the operating pressure and storage capacity of a compressed air energy storage salt cavern gas storage facility.

[0007] A method for optimizing the operating pressure and storage capacity of a compressed air energy storage salt cavern gas storage facility includes the following steps: Based on the grid's peak-shaving demand, determine the power generation capacity and continuous power generation time that the energy storage system needs to provide, and calculate the total amount of electrical energy that needs to be stored; combined with the efficiency of the energy storage system, convert the total amount of electrical energy into the thermodynamic energy of compressed air that needs to be stored. Obtain key geological parameters, including: net thickness of salt layer, stress of overlying strata, brine density, depth of the last stage casing shoe, salt layer temperature, and elastic modulus, Poisson's ratio, tensile strength and compressive strength of salt rock; Based on the net thickness of the salt layer, the maximum allowable height of a single cavity is estimated. Combined with the peak-shaving requirements of the power grid and the elastic modulus, Poisson's ratio, tensile strength and compressive strength of the salt rock, the initial pressure range of the storage tank is set. Calculate the mass flow rate of the compressor based on its input power, inlet temperature, inlet and outlet pressures, and specific heat capacity. Calculate the mass flow rate of the turbine based on its output power, mechanical efficiency, generator efficiency, inlet and outlet temperatures, and specific heat capacity. Based on the stress of the overlying strata, the density of the brine, and the depth of the last stage casing shoe, the upper limit of the maximum pressure and the lower limit of the minimum pressure of the reservoir under geological constraints are determined. Based on the upper limit of the maximum pressure and the lower limit of the minimum pressure of the reservoir, the minimum working pressure and the maximum working pressure of the reservoir are determined. Based on the gas law, and combined with the thermodynamic energy of compressed air, turbine mass flow rate, minimum working pressure of the storage tank, and maximum working pressure of the storage tank, the storage capacity is calculated for both variable and constant pressure conditions. A state-space model is introduced, in which the air mass and pressure inside the salt cavern change over time and are directly related to the compressor mass flow rate and turbine mass flow rate. The current effective storage capacity is then calculated by back-calculating the real-time changes in the air mass and pressure inside the salt cavern.

[0008] Secondly, the present invention provides a system for optimizing the operating pressure and storage capacity of a compressed air energy storage salt cavern gas storage facility.

[0009] A compressed air energy storage salt cavern gas storage facility operating pressure and storage capacity optimization system includes: The compressed air thermodynamic energy calculation unit is configured to: determine the power generation capacity and continuous power generation time required by the energy storage system based on the grid peak shaving demand, and calculate the total amount of electrical energy to be stored; and convert the total amount of electrical energy into the compressed air thermodynamic energy to be stored, taking into account the efficiency of the energy storage system. The geological key parameter acquisition unit is configured to acquire geological key parameters, including: net thickness of salt layer, stress of overlying strata, brine density, depth of the last stage casing shoe, salt layer temperature, and elastic modulus, Poisson's ratio, tensile strength and compressive strength of salt rock. The initial pressure range setting unit is configured to: estimate the maximum allowable height of a single cavity based on the net thickness of the salt layer, and set the initial pressure range of the storage tank in combination with the peak shaving requirements of the power grid and the elastic modulus, Poisson's ratio, tensile strength and compressive strength of the salt rock; The mass flow calculation unit is configured to: calculate the mass flow of the compressor based on the compressor's input power, inlet temperature, inlet and outlet pressures, and specific heat capacity; and calculate the mass flow of the turbine based on the turbine's output power, mechanical efficiency, generator efficiency, inlet and outlet temperatures, and specific heat capacity. The working pressure range determination unit is configured to: determine the upper limit of the maximum pressure of the reservoir and the lower limit of the minimum pressure of the reservoir under geological constraints based on the stress of the overlying strata, the density of the brine, and the depth of the last stage casing shoe; and determine the minimum working pressure and the maximum working pressure of the reservoir based on the upper limit of the maximum pressure and the lower limit of the minimum pressure of the reservoir. The storage capacity prediction unit is configured to calculate the storage capacity under variable pressure and constant pressure conditions based on the gas state equation, combined with the thermodynamic energy of compressed air, the mass flow rate of the turbine, the minimum working pressure of the storage tank, and the maximum working pressure of the storage tank. The dynamic optimization unit is configured to: introduce a state-space model, where the air quality and pressure inside the salt cavern change over time and are directly related to the compressor mass flow rate and turbine mass flow rate, and back-calculate the current effective storage capacity based on the real-time changes in the air quality and pressure inside the salt cavern.

[0010] Thirdly, the present invention provides a computer device, comprising: a processor and a computer-readable storage medium; A processor, adapted to execute computer programs; A computer-readable storage medium storing a computer program, which, when executed by a processor, implements the method for optimizing the operating pressure and storage capacity of a compressed air energy storage salt cavern gas storage facility according to the first aspect of this invention.

[0011] Fourthly, the present invention provides a computer-readable storage medium storing a computer program adapted to be loaded by a processor and executed by the method for optimizing the operating pressure and storage capacity of a compressed air energy storage salt cavern gas storage facility according to the first aspect of the present invention.

[0012] Compared with the prior art, the beneficial effects of the present invention are: This invention integrates geological evaluation, equipment parameters, and storage capacity calculation into a unified optimization framework through systematic coupling optimization, achieving bidirectional feedback design of pressure range and storage capacity, thus avoiding the one-way estimation bias of traditional empirical methods. It has good dynamic adaptability, adapting to different power grid peak-shaving needs through dual-mode storage capacity calculation of variable pressure and constant pressure. While meeting geological safety constraints, it optimizes equipment selection and reduces overall investment costs. It adopts a standardized parameter acquisition and calculation process, which is convenient for practical engineering applications and can be extended to the design of salt cavern gas storage facilities under different geological conditions.

[0013] This invention starts from the peak-shaving demand of the power grid and integrates a closed-loop process of power demand calculation, acquisition of key geological parameters, initial setting of geometric and pressure boundaries, mass flow calculation, determination of pressure under dual constraints of geology and equipment, estimation of storage capacity under different operating conditions, and dynamic iteration of the state-space model. Furthermore, by taking the extreme values ​​of the corresponding pressures in the geological and equipment constraints to determine the final working pressure, it solves the problems of traditional storage design that considers pressure and storage capacity separately, with isolated parameters and a lack of dynamic feedback. It overcomes the shortcomings of traditional unidirectional design that ignores the grid demand, geological conditions, and equipment performance coordination and adaptation, improves the systematicness and accuracy of storage design, and ensures that pressure and storage capacity meet the peak-shaving demand of the power grid while adapting to geological carrying capacity and equipment operating efficiency. It avoids situations where the storage is not safe enough, economically inefficient, or cannot match the actual peak-shaving scenario due to parameter disconnect.

[0014] This invention employs a storage capacity calculation formula that integrates compressed air thermodynamic energy, turbine mass flow rate, storage pressure range, pipeline friction loss, and gas state equation under variable pressure conditions. The formula explicitly links key parameters (such as universal gas constant, specific heat ratio, and storage temperature), solving the problem of low capacity estimation accuracy in variable pressure scenarios caused by traditional storage capacity calculations failing to differentiate between pressure conditions and ignoring pipeline losses. It overcomes the shortcomings of traditional methods, such as poor adaptability to dynamic pressure changes and inability to reflect actual capacity fluctuations with pressure, thus improving the accuracy of storage capacity estimation under variable pressure scenarios. This provides a precise basis for storage capacity configuration during dynamic peak shaving of the power grid (such as rapid load fluctuations), avoiding situations where inaccurate capacity estimation leads to insufficient energy storage to meet peak shaving needs or excessive energy storage resulting in resource waste.

[0015] This invention employs a storage capacity calculation formula that combines compressed air thermodynamic energy, equipment parameters (specific heat ratio, atmospheric pressure, etc.), and the gas state equation under constant pressure conditions. Focusing on parameter integration for the specific operating scenario of constant pressure, it solves the problem of traditional design methods that provide coarse estimations under constant pressure conditions and fail to systematically integrate key parameters, leading to a disconnect between capacity calculations and actual stable operation requirements. It overcomes the shortcomings of traditional methods that cannot accurately adapt to constant pressure scenarios (such as continuous stable power generation). By clarifying parameter correlations, it improves calculation reliability and increases the accuracy of storage capacity estimation under constant pressure scenarios. This provides accurate data support for the design and equipment selection under stable storage operation modes, avoiding situations where subsequent power generation is unstable or equipment operates under long-term overload due to capacity estimation deviations under constant pressure.

[0016] This invention employs explicit formulas for calculating α and β coefficients, integrating key parameters such as turbine mechanical efficiency, generator efficiency, compressor and turbine mass flow rates, specific heat capacity, and temperature under different conditions. It establishes a direct correlation between these coefficients and equipment performance and thermodynamic state, resolving the problems of ambiguous coefficient definitions and unclear parameter relationships in traditional storage capacity calculations, which lead to logical gaps or coefficient values ​​deviating from reality. It overcomes the shortcomings of arbitrary coefficient values ​​and disconnection from equipment operating conditions, providing clear physical and equipment parameter support for coefficient calculations. This improves the accuracy and transparency of coefficients in storage capacity calculations, thereby enhancing the credibility of overall capacity estimation. It provides a precise data foundation for pressure and capacity optimization, avoiding the accumulation of calculation errors caused by ambiguous coefficients and the deviation of subsequent optimization schemes from actual equipment performance and operating requirements.

[0017] This invention employs a discrete state-space model and corresponding matrix equations to dynamically correlate the air quality and pressure within the salt cavern with the compressor / turbine mass flow rate. Through iterative calculations, it reflects the changes in the salt cavern state at different times, solving the problem that traditional static analysis of the salt cavern state cannot reflect the dynamic changes of parameters during charging and discharging in real time. It overcomes the shortcomings of traditional static methods, such as their inability to adapt to the dynamic operation of the storage facility and the lack of real-time feedback, accurately capturing the changing patterns of air quality and pressure over time. This improves the dynamic monitoring and prediction capabilities of the salt cavern storage facility's operating status, providing dynamic data support for real-time adjustment of charging and discharging strategies and optimization of pressure and capacity matching. It avoids situations where the inability to monitor the salt cavern state in real time leads to pressure exceeding safe limits, insufficient capacity utilization, or failure to respond promptly to grid peak-shaving demands.

[0018] Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0019] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0020] Figure 1 A flowchart illustrating a method for optimizing the operating pressure and storage capacity of a compressed air energy storage salt cavern gas storage facility, provided as an exemplary embodiment of the present invention. Figure 2 A structural diagram of a compressed air energy storage system based on a salt cavern gas storage facility is provided as an exemplary embodiment of the present invention. Figure 3 A dynamic operation diagram of optimized operating pressure and storage capacity of a compressed air energy storage salt cavern gas storage facility, provided as an exemplary embodiment of the present invention; Figure 4A flowchart illustrating the operating pressure and storage capacity optimization system for a compressed air energy storage salt cavern gas storage facility, provided as an exemplary embodiment of the present invention. Figure 5 A schematic diagram of a computer device provided for an exemplary embodiment of the present invention. Detailed Implementation

[0021] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0022] It should be noted that the following detailed descriptions are exemplary and intended to provide further illustration of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0023] The structural diagram of the compressed air energy storage system involved in this invention is shown below. Figure 1 As shown, this is a compressed air energy storage system based on underground salt caverns: During periods of low electricity demand, an electric motor drives a compressor to compress air into a high-pressure state, and recovers the heat of compression through a heat exchanger. The high-pressure air at room temperature is then injected into the underground salt cavern for storage. When electricity is needed, the high-pressure air in the salt cavern is released, and the previously recovered heat energy is used to preheat and pressurize it. This allows the air to expand and do work through high-pressure and low-pressure turbines in sequence, driving a generator to generate electricity and transmitting the electrical energy to the power grid, thus achieving efficient energy storage and release.

[0024] More specifically, Figure 1 The system is divided into three parts: charging, gas storage, and power generation. During the charging process at off-peak hours, the power grid provides power P and time t, which is then processed by the energy storage system E=Pt and the charging efficiency η. p Through the electric motor (power P) c Efficiency η m ) drives the compressor (inlet pressure P1, outlet pressure P2, inlet temperature T) in Efficiency η compressor airflow High-temperature, high-pressure air is generated, cooled / recovered by a heat recovery system (heat recovery efficiency) to become ambient-temperature, high-pressure air, injected into the salt cavern, and pressure controlled. The underground salt cavern gas storage system is determined by the salt layer (last stage casing shoe depth HLCCS, overburden stress of the overlying strata, pore pressure P). pore ) and the main body of the salt cavern (burial depth Hnet, pressure range P) min ~P max Composed of volume (Vs), temperature (Ts), it stores high-pressure air at room temperature and then releases high-pressure air; during peak electricity generation, the released high-pressure air (outlet flow rate) (Release control) After passing through the preheating booster (preheating temperature T1 / T2, boosting efficiency), the air is transformed into high-temperature and high-pressure air, which then enters the high-pressure / low-pressure turbine (inlet pressure P1' / outlet pressure P2', mechanical efficiency ηM, power generation P) G The mechanical energy output drives the generator, and the final generated power is fed into the power grid.

[0025] like Figure 2 and Figure 3 As shown, a method for optimizing the operating pressure and storage capacity of compressed air energy storage salt cavern gas storage is proposed, specifically including the following process: S1: Determine the electricity demand.

[0026] Based on the grid's peak-shaving demand, determine the power generation capacity and continuous power generation time required by the energy storage system, and calculate the total amount of electrical energy that needs to be stored. (MWh) and compressed air thermodynamic energy .

[0027] The scale of energy storage is determined by the peak-shaving demand of the power grid and must meet the continuous discharge time under rated power. Therefore, the application scenarios need to be determined first: daily peak shaving, charging and discharging once a day to shave peaks and fill valleys; weekly / seasonal peak shaving to cope with long-cycle fluctuations of new energy sources or seasonal differences in load; emergency backup. Key parameters to obtain: the peak-shaving power P (MW) and the continuous discharge time t (h) required by the energy storage system. By analyzing the load curve of the target area's power grid (especially the difference between peak and off-peak loads), the peak-shaving discharge power and continuous discharge time required to meet the maximum peak-shaving gap of the regional power grid are determined. The two are then multiplied to estimate the total amount of electrical energy E (MWh) that the system needs to store.

[0028] CAES systems are energy conversion systems and therefore suffer from efficiency losses. (Typically between 0.6 and 0.75), mainly including losses from the compressor, expander, and heat storage system, then the compressed air thermodynamic energy that needs to be stored. =E / Unit: Megawatt-hour (MWh).

[0029] S2: Obtain and evaluate key geological parameters.

[0030] Obtaining information such as depth, formation pressure and pore pressure, caprock structural features, key mechanical parameters, and thermodynamic parameters is essential for estimating the operating pressure and storage capacity of underground gas storage facilities, which are fundamentally dependent on the physical and mechanical properties of the reservoir. Before conducting estimations, the following information needs to be obtained and evaluated: Depth and formation pressure: Determine the burial depth of the top and bottom of the reservoir; Structural characteristics of the caprock: confirm the continuity and thickness of the caprock (such as mudstone and salt rock); Initial formation pressure, minimum wellhead pressure required by the surface pipeline network, and formation pore pressure near the salt layer; Rock mechanics parameters: The elastic modulus, Poisson's ratio, compressive strength, tensile strength, and average density of overlying strata of the caprock and reservoir are obtained through well logging and core experiments. These parameters can be obtained through triaxial testing. The test specimens for triaxial testing should meet the technical requirements of height / diameter ratio ≥2 and roughness ≤0.2mm. Estimate the magnitude and direction of the field stress (maximum and minimum horizontal principal stress and vertical stress).

[0031] S3: Initial setting of geometric and pressure boundaries.

[0032] Estimate the approximate range of the maximum permissible height and working pressure for a single chamber, specifically including: According to the salt layer thickness grading design standard (generally, salt layers are divided into three grades according to thickness and purity): Grade 1 is a high-quality salt layer with a large thickness, few interlayers, and weak creep. The cavity can take the upper limit of the high thickness ratio and width-to-height ratio, and allow for a large pressure difference; Grade 2 is a medium-quality salt layer with a moderate thickness and many interlayers. The high thickness ratio needs to be reduced and the impact of interlayers needs to be evaluated. The design tends to be conservative; Grade 3 is a poor salt layer with thin layers, dense interlayers, or strong creep. The height of a single cavity is limited. If it is still selected, the high thickness ratio and operating pressure range must be strictly controlled, and the size of a single cavity must be reduced. Based on the above standards, and using previously obtained data on salt layer burial depth, effective salt layer thickness, and minimum continuous thickness of the caprock, the maximum allowable height of a single cavity is estimated: Based on the salt layer classification design standard, the maximum height of a single cavity ( The salt layer thickness should be controlled within the specified range. Within a specific ratio range, it is generally required ≤ .

[0033] S4: Calculate mass flow rate.

[0034] Based on the compressor / turbine parameters, calculate the compressor's mass flow rate and the turbine's mass flow rate using formulas. Typically, compressors are purchased based on their mass flow rate and outlet pressure. The following formula can be used to correlate the machine's power consumption with the outlet pressure: (1); in, The mass flow rate of the compressor (kg / s) This refers to the compressor's input power (kW). For constant pressure specific heat capacity, and For compressor outlet and inlet pressures (kPa); The compressor inlet temperature (K) It is the ratio of the specific heat capacity at constant pressure to the specific heat capacity at constant volume.

[0035] Calculate the turbine mass flow rate using the following formula. : (2); in, The turbine mass flow rate is (kg / s). Mass flow rate of fuel entering the turbine (kg / s); Power generated by the turbine (kPa); , , These represent the high-pressure turbine, low-pressure turbine, and atmospheric pressure (kPa), respectively. The mechanical efficiency of a turbine; It refers to the generator's efficiency; yes and The ratio; It is the specific heat capacity at constant volume. The temperature at the inlet of the low-pressure turbine (K); It is the temperature at the inlet of the high-pressure turbine.

[0036] In this step, the safety margin of brine static pressure For a pressure of 1-2 MPa, the turbine inlet pressure matching error should be controlled within ±5%. S5: Determine the maximum and minimum working pressure of the appropriate storage facility.

[0037] The maximum and minimum pressures of the storage facility need to match the geological evaluation conditions, as well as the design pressure ranges of the compressor and expander, while also considering equipment efficiency: according to the gas law, higher pressure means higher density and greater mass per unit volume, thus increasing the maximum operating pressure. The higher the setting, the higher the energy storage density, and the larger the total energy storage capacity of the system; maximum operating pressure The lower the setting, the more air is extracted from the salt cavern, resulting in higher energy density and energy utilization. But higher settings... and lower This also places higher demands on the geological conditions of the storage facility and the performance of the compressor. Therefore, the maximum and minimum working pressures of the storage facility need to match the geological evaluation conditions, as well as the design pressure ranges of the compressor and expander, while also considering equipment efficiency. The specific process is as follows: S501: The maximum and minimum working pressures are matched with the geological evaluation conditions.

[0038] Maximum working pressure Due to the stress constraints of the overlying strata, a safety factor is assigned, typically 0.8, as shown in the following formula: (3); in: The safety factor is (0.8-0.85). The stress of the overlying rock strata is expressed in MPa.

[0039] Minimum working pressure The depth of the final sleeve shoe (LCCS) must be considered, along with the pressure safety margin, which can be estimated using the following formula: (4); in: The density of the brine is (kg / m³). The depth (m) of the last stage of the sleeve shoe; For pressure safety margin (usually 1-2 MPa); The acceleration due to gravity (m / ).

[0040] Simultaneously, to prevent excessive convergence of the salt rock leading to cavity deformation, the minimum working pressure must meet the following requirements. In summary, The estimation formula requires that, Take the maximum value.

[0041] S502: The maximum and minimum operating pressures must match the design pressure ranges of the compressor and expander, while also considering equipment efficiency: CAES operates through a "compression-storage-expansion power generation" cycle. During the compression phase, air must be pressurized to the upper limit of the gas storage tank's operating pressure. During the expansion phase, the pressure drops from the upper limit to the lower limit. The operating pressure range of the gas storage tank must fully cover and optimize the most efficient and economical operating pressure ranges for the compressor and turbine. Therefore, the maximum operating pressure of the gas storage tank must match the compressor outlet pressure, and the minimum operating pressure must match the turbine inlet pressure. If the gas storage tank pressure exceeds the pressure the compressor can provide, air cannot be injected and may even flow back, causing compressor failure. Considering equipment operating efficiency, the compressor and turbine have different efficiencies at different pressures. Based on the "pressure-efficiency" curve, the most efficient pressure operating range is selected.

[0042] S503: Considering the above factors, including matching with geological evaluation conditions, matching with the design pressure range of the compressor and expander, and taking equipment efficiency into account, the smallest value is selected. and the largest This represents the maximum and minimum operating pressure of the storage facility.

[0043] S6: Estimate the storage capacity.

[0044] Based on the gas law and system parameters, the storage capacity is calculated under both variable and constant pressure conditions. Through steps S1-S5 above, the following parameters have been determined: Electricity demand (MWh); The mechanical efficiency of the turbine; It refers to the generator's efficiency; The mass flow rate of the storage tank is (kg / s). The mass flow rate of fuel entering the turbine (kg / s); is the universal gas constant (kJ / mol K); The molar mass of air (kg / mol); coefficient , , These are atmospheric pressure, maximum working pressure, and minimum working pressure (kPa); For constant pressure Specific heat capacity under certain conditions; For constant pressure Specific heat capacity under certain conditions; Storage temperature (K) under maximum working pressure; , , These represent the specific heat capacity ratios under storage, high-pressure turbine, and low-pressure turbine conditions, respectively. Assumed pipe friction loss; and The average temperature (K) of the high-pressure turbine and the low-pressure turbine.

[0045] (5); (6); During actual system operation, the pressure at the turbine inlet and the pressure inside the salt cavern gas storage tank are variable and not constant. The pressure gradually decreases as air flows out of the storage tank and energy is released.

[0046] When the turbine inlet pressure is variable, i.e., when the reservoir pressure is variable, the reservoir's available capacity (mass flow rate) can be estimated based on the following operation. (m³): (7); A theoretically simplified model or ideal operating condition is used to simplify calculations or perform analyses under specific conditions. During system operation, the pressure at the turbine inlet and the reservoir pressure are assumed to be constant, allowing for an idealized estimation of the reservoir capacity.

[0047] When the turbine inlet pressure is constant, i.e., when the storage pressure is constant, the storage capacity (mass flow rate) can be estimated using the following formula. (m³): (8).

[0048] S7: Implement dynamic optimization of maximum and minimum workload and storage capacity.

[0049] Introducing a state-space model, this model treats the salt cave as a dynamic system, whose state (air mass inside the salt cave) is... and pressure ) varies over time and is correlated with the input (compressor mass flow rate) ) and output (turbine mass flow rate) Directly related: (9); This model can be transformed into a discrete state-space form that is easy to solve iteratively by computer: (10); (11).

[0050] Initialization: Input initial salt cavern pressure Temperature inside the salt cave And the geometric volume V of the salt cavern; Using minutes or hours as the time step Δt, based on the current required charging power or discharge power The air mass inside the salt cave at the next moment is calculated using the above model iteratively. and pressure ; Real-time storage capacity estimation: Storage capacity is no longer a fixed value, but a function of the current state. It can be estimated using the gas law based on real-time pressure. and quality The current effective storage capacity is obtained by reverse calculation. .

[0051] The above model considers geological constraints, equipment constraints, operational constraints, safety margins, and geometric constraints: The constraints are: (12); In the aforementioned steps, the storage capacity The estimation depends on the operating pressure range ( , The determination of the operating pressure range is subject to multiple constraints, including geological conditions, equipment performance, and safety regulations. However, the relationship between storage capacity and operating pressure is not unidirectional but involves significant interaction and feedback mechanisms. Coupled optimization is required during the engineering design phase to achieve the best balance between system energy storage density, economy, and safety.

[0052] According to the gas law, air density and pressure have a non-linear positive correlation. At a fixed temperature, the air mass *m* inside the gas storage tank is proportional to *PV*. Therefore: increasing... It is possible to do without adding Under the premise of significantly improving gas storage quality, thereby increasing energy storage density; reducing This can release more usable air and improve reservoir capacity utilization; however, both are limited by geological strength, brine intrusion risk, and turbine inlet pressure requirements. In actual engineering, if the pressure range allowed by geological conditions cannot match the target reservoir capacity requirements, a two-way feedback design mechanism must be activated. When capacity is insufficient: try to increase capacity first. However, the tensile strength of the salt rock and the integrity of the caprock need to be re-examined; if the geological limit has been reached, consider increasing the volume of the salt cavern (such as increasing the dissolution height or diameter), but the impact of creep convergence on long-term sealing needs to be assessed; or relax the limits. However, it must be ensured that it is still higher than the brine static pressure plus safety margin, and that the turbine can operate efficiently at lower pressures.

[0053] When there is excess capacity: it can be reduced To reduce compressor power consumption and equipment grade, thereby improving system economy; or to increase This reduces pressure fluctuations, inhibits the creep rate of salt rock, and extends the life of the storage facility.

[0054] This invention systematically proposes a method and optimization process for estimating the operating pressure and storage capacity of compressed air energy storage (CAES) salt cavern gas storage facilities, providing a clear and operable technical path for engineering design and practical applications. Through progressive analysis of seven key steps, it covers the entire process from power demand analysis, geological condition evaluation, initial design of geometric and pressure boundaries, equipment matching to capacity estimation and multi-objective optimization, forming a complete and logically rigorous design framework. Its comprehensiveness and integration: It not only considers the geological and physical constraints of the gas storage facility itself, but also incorporates the performance parameters and operating efficiency of key equipment such as compressors and turbines into the analysis system, realizing the coordinated design among "equipment-geology-operation". The established optimization model aims to minimize the total cost, and significantly improves the economy and reliability of the system while meeting safety regulations and technical requirements, providing a scientific basis for the early planning and preliminary design of CAES projects; Figure 4 A compressed air energy storage salt cavern gas storage facility operating pressure and storage capacity optimization system is shown, comprising: The compressed air thermodynamic energy calculation unit 401 is configured to: determine the power generation capacity and continuous power generation time required by the energy storage system based on the grid peak shaving demand, calculate the total amount of electrical energy to be stored; and convert the total amount of electrical energy into the compressed air thermodynamic energy to be stored, taking into account the efficiency of the energy storage system. The geological key parameter acquisition unit 402 is configured to acquire geological key parameters, including: net thickness of salt layer, stress of overlying strata, brine density, depth of the last stage casing shoe, salt layer temperature, and elastic modulus, Poisson's ratio, tensile strength and compressive strength of salt rock. The initial pressure range setting unit 403 is configured to: estimate the maximum allowable height of a single cavity based on the net thickness of the salt layer, and set the initial pressure range of the storage tank in combination with the peak shaving requirements of the power grid and the elastic modulus, Poisson's ratio, tensile strength and compressive strength of the salt rock; The mass flow calculation unit 404 is configured to: calculate the mass flow of the compressor based on the compressor's input power, inlet temperature, inlet and outlet pressures and specific heat capacity; and calculate the mass flow of the turbine based on the turbine's output power, mechanical efficiency, generator efficiency, inlet and outlet temperatures and specific heat capacity. The working pressure range determination unit 405 is configured to: determine the upper limit of the maximum pressure of the reservoir and the lower limit of the minimum pressure of the reservoir under geological constraints based on the stress of the overlying strata, the density of the brine, and the depth of the last stage casing shoe; and determine the minimum working pressure and the maximum working pressure of the reservoir based on the upper limit of the maximum pressure and the lower limit of the minimum pressure of the reservoir. The storage capacity prediction unit 406 is configured to: calculate the storage capacity under variable pressure and constant pressure conditions based on the gas state equation, combined with the thermodynamic energy of compressed air, the mass flow rate of the turbine, the minimum working pressure of the storage tank and the maximum working pressure of the storage tank. The dynamic optimization unit 407 is configured to: introduce a state-space model, where the air quality and pressure inside the salt cavern change over time and are directly related to the compressor mass flow rate and turbine mass flow rate, and back-calculate the current effective storage capacity based on the real-time changes in the air quality and pressure inside the salt cavern.

[0055] It is understood that the aforementioned units can be individually or entirely merged into one or more other units, or some of the units can be further divided into multiple functionally smaller units. This achieves the same operation without affecting the technical effects of the embodiments of the present invention. The aforementioned units are based on logical functional division. In practical applications, the function of one unit can be implemented by multiple units, or the function of multiple units can be implemented by one unit. In other embodiments of the present invention, the system may also include other units. In practical applications, these functions can also be implemented with the assistance of other units, and can be implemented collaboratively by multiple units.

[0056] According to another embodiment of the present invention, the system of this embodiment can be constructed by running a computer program (including program code) capable of performing the steps involved in the corresponding method of the present invention on a general-purpose computing device, such as a computer, which includes processing elements and storage elements such as a central processing unit (CPU), random access memory (RAM), and read-only memory (ROM). The computer program can be recorded on, for example, a computer-readable recording medium, loaded into the aforementioned computing device through the computer-readable recording medium, and run therein.

[0057] Figure 5 A computer device is shown, which includes a processor 501, a communication interface 502, and a computer-readable storage medium 503. The processor 501, communication interface 502, and computer-readable storage medium 503 can be connected via a bus or other means.

[0058] The communication interface 502 is used to receive and send data. The computer-readable storage medium 503 can be stored in the memory of the electronic device. The computer-readable storage medium 503 is used to store computer programs, which include program instructions. The processor 501 is used to execute the program instructions stored in the computer-readable storage medium 503.

[0059] The processor 501 is the computing and control core of the electronic device. It is suitable for implementing one or more instructions, specifically for loading and executing one or more instructions to achieve the corresponding method flow or corresponding function.

[0060] Processor 501 is configured to perform the following procedure: Based on the grid's peak-shaving demand, determine the power generation capacity and continuous power generation time that the energy storage system needs to provide, and calculate the total amount of electrical energy that needs to be stored; combined with the efficiency of the energy storage system, convert the total amount of electrical energy into the thermodynamic energy of compressed air that needs to be stored. Obtain key geological parameters, including: net thickness of salt layer, stress of overlying strata, brine density, depth of the last stage casing shoe, salt layer temperature, and elastic modulus, Poisson's ratio, tensile strength and compressive strength of salt rock; Based on the net thickness of the salt layer, the maximum allowable height of a single cavity is estimated. Combined with the peak-shaving requirements of the power grid and the elastic modulus, Poisson's ratio, tensile strength and compressive strength of the salt rock, the initial pressure range of the storage tank is set. Calculate the mass flow rate of the compressor based on its input power, inlet temperature, inlet and outlet pressures, and specific heat capacity. Calculate the mass flow rate of the turbine based on its output power, mechanical efficiency, generator efficiency, inlet and outlet temperatures, and specific heat capacity. Based on the stress of the overlying strata, the density of the brine, and the depth of the last stage casing shoe, the upper limit of the maximum pressure and the lower limit of the minimum pressure of the reservoir under geological constraints are determined. Based on the upper limit of the maximum pressure and the lower limit of the minimum pressure of the reservoir, the minimum working pressure and the maximum working pressure of the reservoir are determined. Based on the gas law, and combined with the thermodynamic energy of compressed air, turbine mass flow rate, minimum working pressure of the storage tank, and maximum working pressure of the storage tank, the storage capacity is calculated for both variable and constant pressure conditions. A state-space model is introduced, in which the air mass and pressure inside the salt cavern change over time and are directly related to the compressor mass flow rate and turbine mass flow rate. The current effective storage capacity is then calculated by back-calculating the real-time changes in the air mass and pressure inside the salt cavern.

[0061] This invention also provides a computer-readable storage medium, which is a memory device in an electronic device for storing programs and data. It is understood that the computer-readable storage medium here may include both built-in storage media in the electronic device and extended storage media supported by the electronic device. The computer-readable storage medium provides storage space for storing the processing system of the electronic device.

[0062] Furthermore, this storage space also contains one or more instructions suitable for loading and execution by the processor. These instructions can be one or more computer programs (including program code). It should be noted that the computer-readable storage medium here can be a high-speed RAM memory; alternatively, it can also be at least one computer-readable storage medium located remotely from the aforementioned processor.

[0063] In one embodiment, the computer-readable storage medium stores one or more instructions; the processor loads and executes the one or more instructions stored in the computer-readable storage medium to perform the following process: Based on the grid's peak-shaving demand, determine the power generation capacity and continuous power generation time that the energy storage system needs to provide, and calculate the total amount of electrical energy that needs to be stored; combined with the efficiency of the energy storage system, convert the total amount of electrical energy into the thermodynamic energy of compressed air that needs to be stored. Obtain key geological parameters, including: net thickness of salt layer, stress of overlying strata, brine density, depth of the last stage casing shoe, salt layer temperature, and elastic modulus, Poisson's ratio, tensile strength and compressive strength of salt rock; Based on the net thickness of the salt layer, the maximum allowable height of a single cavity is estimated. Combined with the peak-shaving requirements of the power grid and the elastic modulus, Poisson's ratio, tensile strength and compressive strength of the salt rock, the initial pressure range of the storage tank is set. Calculate the mass flow rate of the compressor based on its input power, inlet temperature, inlet and outlet pressures, and specific heat capacity. Calculate the mass flow rate of the turbine based on its output power, mechanical efficiency, generator efficiency, inlet and outlet temperatures, and specific heat capacity. Based on the stress of the overlying strata, the density of the brine, and the depth of the last stage casing shoe, the upper limit of the maximum pressure and the lower limit of the minimum pressure of the reservoir under geological constraints are determined. Based on the upper limit of the maximum pressure and the lower limit of the minimum pressure of the reservoir, the minimum working pressure and the maximum working pressure of the reservoir are determined. Based on the gas law, and combined with the thermodynamic energy of compressed air, the mass flow rate of the turbine, the minimum working pressure of the storage tank, and the maximum working pressure of the storage tank, the storage capacity is calculated under the conditions of variable pressure and constant pressure. A state-space model is introduced, in which the air mass and pressure inside the salt cavern change over time and are directly related to the compressor mass flow rate and turbine mass flow rate. The current effective storage capacity is then calculated by back-calculating the real-time changes in the air mass and pressure inside the salt cavern.

[0064] The present invention also provides a computer program product or computer program comprising computer instructions stored in a computer-readable storage medium. A processor of an electronic device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the electronic device to perform the following process: Based on the grid's peak-shaving demand, determine the power generation capacity and continuous power generation time that the energy storage system needs to provide, and calculate the total amount of electrical energy that needs to be stored; combined with the efficiency of the energy storage system, convert the total amount of electrical energy into the thermodynamic energy of compressed air that needs to be stored. Obtain key geological parameters, including: net thickness of salt layer, stress of overlying strata, brine density, depth of the last stage casing shoe, salt layer temperature, and elastic modulus, Poisson's ratio, tensile strength and compressive strength of salt rock; Based on the net thickness of the salt layer, the maximum allowable height of a single cavity is estimated. Combined with the peak-shaving requirements of the power grid and the elastic modulus, Poisson's ratio, tensile strength and compressive strength of the salt rock, the initial pressure range of the storage tank is set. Calculate the mass flow rate of the compressor based on its input power, inlet temperature, inlet and outlet pressures, and specific heat capacity. Calculate the mass flow rate of the turbine based on its output power, mechanical efficiency, generator efficiency, inlet and outlet temperatures, and specific heat capacity. Based on the stress of the overlying strata, the density of the brine, and the depth of the last stage casing shoe, the upper limit of the maximum pressure and the lower limit of the minimum pressure of the reservoir under geological constraints are determined. Based on the upper limit of the maximum pressure and the lower limit of the minimum pressure of the reservoir, the minimum working pressure and the maximum working pressure of the reservoir are determined. Based on the gas law, and combined with the thermodynamic energy of compressed air, the mass flow rate of the turbine, the minimum working pressure of the storage tank, and the maximum working pressure of the storage tank, the storage capacity is calculated under the conditions of variable pressure and constant pressure. A state-space model is introduced, in which the air mass and pressure inside the salt cavern change over time and are directly related to the compressor mass flow rate and turbine mass flow rate. The current effective storage capacity is then calculated by back-calculating the real-time changes in the air mass and pressure inside the salt cavern.

[0065] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed in this invention can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can implement the described functions using different methods for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0066] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product. A computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the flow or function according to the embodiments of the present invention is generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in or transmitted through a computer-readable storage medium. The computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic cable, digital cable) or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that a computer can access or a data processing device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid-state drive), etc.

[0067] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for optimizing the operating pressure and storage capacity of a compressed air energy storage salt cavern gas storage facility, characterized in that, Includes the following processes: Based on the grid's peak-shaving demand, determine the power generation capacity and continuous power generation time that the energy storage system needs to provide, and calculate the total amount of electrical energy that needs to be stored; Based on the efficiency of the energy storage system, the total electrical energy is converted into the thermodynamic energy of compressed air that needs to be stored; Obtain key geological parameters, including: net thickness of salt layer, stress of overlying strata, brine density, depth of the last stage casing shoe, salt layer temperature, and elastic modulus, Poisson's ratio, tensile strength and compressive strength of salt rock; Based on the net thickness of the salt layer, the maximum allowable height of a single cavity is estimated. Combined with the peak-shaving requirements of the power grid and the elastic modulus, Poisson's ratio, tensile strength and compressive strength of the salt rock, the initial pressure range of the storage tank is set. Calculate the mass flow rate of the compressor based on its input power, inlet temperature, inlet and outlet pressures, and specific heat capacity. Calculate the mass flow rate of the turbine based on its output power, mechanical efficiency, generator efficiency, inlet and outlet temperatures, and specific heat capacity. Based on the stress of the overlying strata, the density of the brine, and the depth of the last stage casing shoe, the upper limit of the maximum pressure and the lower limit of the minimum pressure of the reservoir under geological constraints are determined. Based on the upper limit of the maximum pressure and the lower limit of the minimum pressure of the reservoir, the minimum working pressure and the maximum working pressure of the reservoir are determined. Based on the gas law, and combined with the thermodynamic energy of compressed air, the mass flow rate of the turbine, the minimum working pressure of the storage tank, and the maximum working pressure of the storage tank, the storage capacity is calculated under the conditions of variable pressure and constant pressure. A state-space model is introduced, in which the air mass and pressure inside the salt cavern change over time and are directly related to the compressor mass flow rate and turbine mass flow rate. The current effective storage capacity is then calculated by back-calculating the real-time changes in the air mass and pressure inside the salt cavern.

2. The method for optimizing the operating pressure and storage capacity of a compressed air energy storage salt cavern gas storage facility as described in claim 1, characterized in that, The efficiency of the energy storage system ranges from 0.6 to 0.75; the compressed air thermodynamic energy is calculated by dividing the total electrical energy to be stored by the efficiency of the energy storage system to obtain the compressed air thermodynamic energy to be stored.

3. The method for optimizing the operating pressure and storage capacity of a compressed air energy storage salt cavern gas storage facility as described in claim 1, characterized in that, The minimum and maximum operating pressures of the storage facility are determined based on the maximum pressure upper limit and the minimum pressure lower limit, including: Based on the compressor outlet pressure, turbine inlet pressure and equipment efficiency range corresponding to mass flow rate, candidate values ​​for maximum and minimum storage pressure under equipment constraints are determined. The smaller value between the upper limit of the maximum pressure of the storage under geological constraints and the candidate value of the maximum pressure of the storage under equipment constraints is taken as the maximum working pressure of the storage; the larger value between the lower limit of the minimum pressure of the storage under geological constraints and the candidate value of the minimum pressure of the storage under equipment constraints is taken as the minimum working pressure of the storage.

4. The method for optimizing the operating pressure and storage capacity of a compressed air energy storage salt cavern gas storage facility as described in claim 1, characterized in that, Storage capacity under variable storage pressure for: ； in, For electricity demand; The mechanical efficiency of a turbine; It refers to the generator's efficiency; Mass flow rate of fuel entering the turbine; Represents the universal gas constant; Molar mass of air; For coefficients, , These represent the power outputs of the high-pressure turbine and the low-pressure turbine, respectively. , , These are atmospheric pressure, maximum working pressure, and minimum working pressure, respectively. Storage temperature under maximum working pressure; , The specific heat ratios are respectively expressed in the storage state and the low-pressure turbine state; This represents the assumed pipe friction loss.

5. The method for optimizing the operating pressure and storage capacity of a compressed air energy storage salt cavern gas storage facility as described in claim 1, characterized in that, Storage capacity under constant pressure for: ； in, For electricity demand; Represents the universal gas constant; Molar mass of air; For coefficients, Indicates the power of the high and low pressure turbines. , , These are atmospheric pressure, maximum working pressure, and minimum working pressure, respectively. Storage temperature under maximum working pressure; , The specific heat ratios are respectively expressed in the storage state and the low-pressure turbine state; This represents the assumed pipe friction loss.

6. The method for optimizing the operating pressure and storage capacity of a compressed air energy storage salt cavern gas storage facility as described in claim 4 or 5, characterized in that, ； ； in, The mechanical efficiency of a turbine; It refers to the generator's efficiency; Mass flow rate of the storage facility; Mass flow rate of fuel entering the turbine; Specific heat capacity under constant pressure; Specific heat capacity under constant pressure; This indicates the specific heat ratio under high-pressure turbine conditions; and This represents the average temperature of the high-pressure turbine and the low-pressure turbine.

7. The method for optimizing the operating pressure and storage capacity of a compressed air energy storage salt cavern gas storage facility as described in claim 1, characterized in that, The air mass and pressure within the salt cavern change over time and are directly related to the compressor mass flow rate and turbine mass flow rate, including: in, represent The air quality inside the salt cave at any given time. represent Pressure within the salt cavern at any given moment represent compressor mass flow rate at any given time represent Constant turbine mass flow rate Represents the universal gas constant. Represents the compressor inlet temperature. Represents the temperature of the salt layer. This represents the geometric volume of the salt cavern.

8. A system for optimizing the operating pressure and storage capacity of a compressed air energy storage salt cavern gas storage facility, characterized in that, include: The compressed air thermodynamic energy calculation unit is configured to: determine the power generation capacity and continuous power generation time required by the energy storage system based on the grid peak shaving demand, and calculate the total amount of electrical energy to be stored; and convert the total amount of electrical energy into the compressed air thermodynamic energy to be stored, taking into account the efficiency of the energy storage system. The geological key parameter acquisition unit is configured to acquire geological key parameters, including: net thickness of salt layer, stress of overlying strata, brine density, depth of the last stage casing shoe, salt layer temperature, and elastic modulus, Poisson's ratio, tensile strength and compressive strength of salt rock. The initial pressure range setting unit is configured to: estimate the maximum allowable height of a single cavity based on the net thickness of the salt layer, and set the initial pressure range of the storage tank in combination with the peak shaving requirements of the power grid and the elastic modulus, Poisson's ratio, tensile strength and compressive strength of the salt rock; The mass flow calculation unit is configured to: calculate the mass flow of the compressor based on the compressor's input power, inlet temperature, inlet and outlet pressures, and specific heat capacity; and calculate the mass flow of the turbine based on the turbine's output power, mechanical efficiency, generator efficiency, inlet and outlet temperatures, and specific heat capacity. The working pressure range determination unit is configured to: determine the upper limit of the maximum pressure of the reservoir and the lower limit of the minimum pressure of the reservoir under geological constraints based on the stress of the overlying strata, the density of the brine, and the depth of the last stage casing shoe; and determine the minimum working pressure and the maximum working pressure of the reservoir based on the upper limit of the maximum pressure and the lower limit of the minimum pressure of the reservoir. The storage capacity prediction unit is configured to calculate the storage capacity under variable pressure and constant pressure conditions based on the gas state equation, combined with the thermodynamic energy of compressed air, the mass flow rate of the turbine, the minimum working pressure of the storage tank, and the maximum working pressure of the storage tank. The dynamic optimization unit is configured to: introduce a state-space model, where the air quality and pressure inside the salt cavern change over time and are directly related to the compressor mass flow rate and turbine mass flow rate, and back-calculate the current effective storage capacity based on the real-time changes in the air quality and pressure inside the salt cavern.

9. A computer device, characterized in that, include: Processor and computer-readable storage media; A processor, adapted to execute computer programs; A computer-readable storage medium storing a computer program, which, when executed by the processor, implements the method for optimizing the operating pressure and storage capacity of a compressed air energy storage salt cavern gas storage facility as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program adapted to be loaded by a processor and executed as described in any one of claims 1 to 7, which is the method for optimizing the operating pressure and storage capacity of a compressed air energy storage salt cavern gas storage facility.

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