An energy storage method and system using water-laden compressed air

Abstract

The application relates to the technical field of compressed air energy storage, and discloses an energy storage method and system for compressed air in an aquifer, which can select the most suitable aquifer for storing the excess power of a compressed air storage power plant according to the actual state of the aquifer when the excess power needs to be converted into compressed air and stored in the aquifer, ensures that the energy storage efficiency is relatively high, reduces energy loss, and reduces the cost; in addition, the suitable energy storage mode can be selected according to the actual aquifer state of the final energy storage aquifer, the energy conversion efficiency coefficient is ensured to be low, the operation cost is reduced, and the overall energy utilization efficiency is ensured.

Description

Technical Field

[0001] This invention relates to the field of compressed air energy storage technology, and in particular to a method and system for storing compressed air in aquifers. Background Technology

[0002] Aquifer compressed air energy storage (U-CAES) is a renewable energy storage technology that utilizes underground aquifers to store compressed air. This technology converts excess electricity, especially from wind power plants or other renewable energy sources, into compressed air and stores it in one or more underground aquifers surrounding the wind power plant or other renewable energy source. When electricity demand increases or renewable energy production is insufficient, the compressed air is released and used to generate electricity through turbines, thus providing a balanced and stable power output to the grid. U-CAES systems use underground aquifers as natural gas storage containers, avoiding reliance on expensive artificial gas storage containers and reducing construction and maintenance costs. Furthermore, underground aquifers typically possess relatively stable geological conditions and can withstand high gas storage pressures, further improving energy storage efficiency. This technology not only effectively regulates grid load and improves the utilization rate of renewable energy but also plays a significant role in reducing carbon emissions and optimizing the energy structure.

[0003] However, when excess electricity needs to be converted into compressed air and stored in aquifers, improper selection of the aquifer can lead to reduced energy storage efficiency, further resulting in energy loss and increased costs. For different aquifers, failure to select a suitable energy storage method based on the actual aquifer conditions can lead to low energy conversion efficiency coefficients, thereby increasing operating costs and reducing overall energy utilization efficiency. Therefore, existing aquifer compressed air energy storage methods suffer from low energy storage efficiency and low energy conversion efficiency coefficients. Summary of the Invention

[0004] This invention provides a method and system for storing compressed air in aquifers to solve the problems of low energy storage efficiency and low energy conversion efficiency coefficient in the prior art.

[0005] To achieve the above objectives, the present invention employs the following technical solution:

[0006] In a first aspect, the present invention provides a method for storing compressed air in an aquifer, comprising:

[0007] S1: Each aquifer around the power plant that has undergone energy storage is designated as the first aquifer. The state data corresponding to each first aquifer is obtained, and the state coefficient of the corresponding first aquifer is calculated.

[0008] S2: Compare the state coefficient with the preset state coefficient threshold, and record the first aquifer with a state coefficient not less than the preset state coefficient threshold as the first aquifer that can store energy, and replace each first aquifer that can store energy as the second aquifer.

[0009] S3: Obtain the priority selection data corresponding to each second aquifer and calculate the priority selection coefficient of each second aquifer;

[0010] S4: Select the second aquifer with the highest priority selection coefficient as the final aquifer for energy storage, compare the priority selection coefficient corresponding to the final aquifer with the preset priority selection coefficient threshold, and determine the energy storage method of the final aquifer based on the comparison result.

[0011] In a second aspect, this application provides an energy storage system for compressed air in an aquifer, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the method described in the first aspect above.

[0012] Beneficial effects:

[0013] The present invention provides a method for storing compressed air in aquifers. The method involves acquiring state data corresponding to a first aquifer and calculating its state coefficient. The state coefficient is compared with a preset state coefficient threshold. First aquifers with state coefficients greater than or equal to the preset threshold are designated as energy-storable aquifers, and each energy-storable first aquifer is designated as a second aquifer. Priority selection data for the second aquifer is acquired, and a priority selection coefficient is calculated. The second aquifer with the highest priority selection coefficient is selected as the final energy-storage aquifer. Its corresponding priority selection coefficient is compared with a preset priority selection coefficient threshold, and the energy storage method for the final energy-storage aquifer is determined based on the comparison results. Thus, when excess electricity needs to be converted into compressed air and stored in an aquifer, the most suitable aquifer can be selected based on its actual state to store the excess electricity from the power plant, ensuring high energy storage efficiency, reducing energy loss, and lowering costs. Furthermore, the method can select a suitable energy storage method based on the actual aquifer state of the final energy-storage aquifer, ensuring a low energy conversion efficiency coefficient, reducing operating costs, and ensuring overall energy utilization efficiency. Attached Figure Description

[0014] Figure 1 This is a flowchart of a preferred embodiment of the present invention for a method of storing energy in compressed air in an aquifer. Detailed Implementation

[0015] The technical solution of the present invention will be clearly and completely described below. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0016] Unless otherwise defined, the technical or scientific terms used in this invention shall have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "first," "second," and similar terms used in this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Similarly, the terms "an" or "a" and similar terms do not indicate a quantity limitation, but rather indicate the presence of at least one. The terms "connected" or "linked" and similar terms are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. "Up," "down," "left," "right," etc., are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship also changes accordingly.

[0017] It should be understood that when excess electricity needs to be converted into compressed air and stored in an aquifer, improper selection of the aquifer may lead to reduced energy storage efficiency, resulting in energy loss and increased costs. Furthermore, failing to select an appropriate energy storage method based on the actual aquifer conditions may result in low energy conversion efficiency coefficients, thereby increasing operating costs and reducing overall energy utilization efficiency. Therefore, this application provides a method for storing compressed air in an aquifer to address the problems of low energy storage efficiency and low energy conversion efficiency coefficients in existing technologies.

[0018] Please see Figure 1 This application provides a method for storing compressed air in an aquifer, comprising:

[0019] S1: Each aquifer around the power plant that has undergone energy storage is designated as the first aquifer. The state data corresponding to each first aquifer is obtained, and the state coefficient of the corresponding first aquifer is calculated.

[0020] S2: Compare the state coefficient with the preset state coefficient threshold, and record the first aquifer with a state coefficient greater than or equal to the preset state coefficient threshold as the first aquifer that can store energy, and replace each first aquifer that can store energy as the second aquifer.

[0021] S3: Obtain the priority selection data corresponding to each second aquifer and calculate the priority selection coefficient of each second aquifer;

[0022] S4: Select the second aquifer with the highest priority selection coefficient as the final aquifer for energy storage, compare the priority selection coefficient corresponding to the final aquifer with the preset priority selection coefficient threshold, and determine the energy storage method of the final aquifer based on the comparison result.

[0023] The aforementioned aquifer compressed air energy storage method, through the above-mentioned approach, allows for the selection of the most suitable aquifer for storing excess power when surplus electricity needs to be converted into compressed air and stored in the aquifer. This ensures high energy storage efficiency, reduces energy loss, and lowers costs. Furthermore, it allows for the selection of an appropriate energy storage method based on the actual aquifer state at the final energy storage location, ensuring a low energy conversion efficiency coefficient, reducing operating costs, and ensuring overall energy utilization efficiency.

[0024] In one example, the state coefficients include transmission coefficients, energy storage capacity coefficients, and equipment utilization coefficients.

[0025] Specifically, the calculation steps for the transmission coefficient are as follows:

[0026] For each first aquifer, obtain the shortest distance from the inlet of its energy storage pipeline to the power plant, the total length of the energy storage pipeline, and the average diameter of the energy storage pipeline, and calculate the transmission coefficient using the following formula:

[0027]

[0028] In the formula, HK represents the transmission coefficient, L represents the total length of the first aquifer energy storage pipeline, and D represents the total length of the pipeline. f d represents the shortest distance from the energy storage pipeline inlet to the power plant, d represents the average diameter of the energy storage pipeline, and k is a preset adjustment constant used to adjust the dimensions and scale in the formula. It is usually chosen as a small value to suit actual needs, typically k = 10. -9 .

[0029] It should be noted that the total length of the energy storage pipeline in the first aquifer can be measured using Geographic Information System (GIS) data or engineering design drawings, and is usually set during project planning; the shortest distance from the pipeline inlet to the power plant can be accurately calculated using GPS positioning technology or GIS data to ensure accurate measurement of the shortest path from the power plant to the pipeline inlet; the average diameter of the pipeline is usually provided by the pipeline design drawings, and this data is determined by the design and construction teams during the engineering implementation phase; the adjustment constant k is preset according to actual needs, and is generally taken as k = 10. -9 It can be other data, which is generally adjusted by professionals based on experience and specific application scenarios. No specific limitations or elaborations are made.

[0030] Furthermore, it's worth noting that the higher the transmission coefficient of the first aquifer, the less suitable it is for compressed air energy storage. This is because a higher transmission coefficient means that compressed air experiences greater energy loss during transport. Longer transport pipes, smaller pipe diameters, and longer transport distances all increase friction and resistance in airflow, leading to gradual energy loss from the compressed air. Therefore, although the energy storage capacity may meet the demand, a high transmission coefficient indicates low transmission efficiency, requiring more energy to overcome pipe resistance and resulting in unnecessary energy waste. In this case, the overall efficiency of the energy storage system will be significantly reduced, failing to fully utilize surplus electrical resources, increasing operating costs, and potentially leading to instability and energy waste. Therefore, aquifers with high transmission coefficients should be prioritized for exclusion in energy storage selection to ensure efficient operation of the energy storage system and minimize energy loss.

[0031] In this embodiment, the advantage of analyzing the transmission coefficient in determining whether an aquifer is suitable for compressed air energy storage is that it can quantify the potential energy loss during transmission and provide an objective standard based on distance, pipe size, and transmission efficiency, thereby helping to optimize the selection of the energy storage system. When the transmission coefficient is low, it means that compressed air can be efficiently delivered to the target aquifer, reducing energy loss and improving energy storage efficiency. Conversely, a high transmission coefficient indicates that the energy loss during transmission is greater, and more energy may be needed to overcome the resistance of the pipe, which will lead to a decrease in system efficiency and an increase in operating costs. Therefore, in this application, by evaluating the transmission coefficient, suitable aquifers for compressed air energy storage can be screened more accurately, avoiding excessive energy waste during transmission.

[0032] In one embodiment, the calculation steps for the energy storage capacity factor are as follows:

[0033] For each first aquifer, obtain the horizontal area A, aquifer thickness h, and aquifer porosity Φ of the corresponding aquifer, and calculate the energy storage space volume V. The calculation formula is: V=A×h×Φ.

[0034] Obtain the maximum pressure P during gas storage in each first aquifer. max And combined with the energy storage space volume V and atmospheric pressure P atm The formula for calculating the energy storage capacity factor is as follows:

[0035]

[0036] In the formula, CF is the energy storage capacity coefficient.

[0037] It should be noted that the horizontal area, thickness, and porosity of an aquifer can be obtained from existing topographic data, which is usually derived from geological exploration and measurement conducted during previous energy storage processes. Through geological exploration, relevant professional institutions or teams will use drilling, seismic surveys, and other technical means to obtain basic parameters such as the horizontal area, thickness, and porosity of the aquifer. The maximum gas storage pressure refers to the highest gas pressure value that the aquifer can withstand when storing gas, which is usually estimated and determined by professional personnel based on the geological characteristics and physical properties of the aquifer. Atmospheric pressure is generally obtained using meteorological data, usually from meteorological stations or weather forecast data, and the standard atmospheric pressure is approximately 101325 Pa.

[0038] In addition, data such as the horizontal area, thickness, porosity, and maximum gas storage pressure of the aquifer are collected to accurately calculate its energy storage capacity coefficient. The horizontal area and thickness determine the overall volume of the storage space, while porosity directly affects the effective volume of air that can be stored within these spaces. Porosity reflects the proportion of voids or fractures in the aquifer; these voids are the spaces for gas storage, making them a key factor affecting energy storage capacity. The maximum gas storage pressure is used to calculate the gas pressure that the aquifer can withstand, determining how much air it can store under high-pressure conditions. Atmospheric pressure serves as the benchmark pressure, used to calculate the effective gas volume in the storage space under different storage pressures. Therefore, collecting this data allows for a comprehensive assessment of the aquifer's gas storage capacity and efficiency.

[0039] It should be noted that the larger the energy storage capacity coefficient of the first aquifer, the more suitable the aquifer is for compressed air energy storage. This is because a larger energy storage capacity coefficient indicates that the aquifer has a larger gas storage space and a higher gas storage capacity, capable of storing more compressed air. This means it can accommodate more excess electricity during periods of power surplus and release more compressed air during peak electricity demand periods, thereby achieving effective power balance and energy storage. A larger energy storage capacity coefficient also indicates that the aquifer can withstand higher gas storage pressure, meaning that compressed air can be stored more efficiently during the gas storage process. In general, a larger energy storage capacity coefficient indicates that the aquifer has stronger energy storage capacity, higher gas storage efficiency, and greater gas storage potential, making it more suitable for compressed air energy storage. Therefore, a larger energy storage capacity coefficient means that the aquifer can effectively support large-scale, long-term compressed air energy storage operations, making it suitable for grid load regulation and renewable energy storage, thereby improving the reliability and efficiency of the entire energy storage system.

[0040] In this embodiment, by calculating the energy storage capacity coefficient, it can be clearly determined whether an aquifer has enough space to accommodate compressed air and whether it can operate stably under different gas storage pressures. A larger energy storage capacity coefficient means that the aquifer can effectively support higher gas storage pressures and larger gas storage volumes, thereby providing more energy release during peak electricity demand. Therefore, the energy storage capacity coefficient can provide a quantitative basis for selecting a suitable energy storage aquifer and reduce the risk of unstable power regulation caused by insufficient gas storage or low energy storage efficiency.

[0041] It is worth explaining that the first aquifer and the equipment have a one-to-many relationship, that is, the first aquifer corresponds to multiple pieces of equipment. In this application, the calculations are performed on multiple pieces of equipment to obtain the equipment utilization coefficient of the first aquifer.

[0042] In one embodiment, the steps for calculating the equipment utilization factor are as follows:

[0043] For each first aquifer, the actual time of use of each piece of equipment in the first aquifer and the preset usable time of the equipment are obtained. The actual time of use is divided by the preset usable time to obtain the service life progress of the corresponding equipment. The average service life progress of all equipment is calculated to obtain the overall service life coefficient of the equipment in the first aquifer.

[0044] Obtain the number of failures and the repair time for each equipment in the first aquifer, and calculate the average repair time for the corresponding equipment based on the repair time for each failure; take the average repair time of all equipment as the repair time for the corresponding equipment in the first aquifer.

[0045] The average time interval between failures and the time interval between the current time and the last failure are obtained for each device in the first aquifer. The average time interval is subtracted from the time interval between the current time and the last failure to obtain the corresponding failure time interval value. The failure time interval values ​​of all devices are used as the maintenance interval coefficients for the corresponding devices in the first aquifer.

[0046] The equipment utilization coefficient is obtained by normalizing the overall service life coefficient, maintenance cost time, and maintenance interval coefficient.

[0047] It should be noted that the equipment utilization coefficient WE is obtained by normalizing the overall service life coefficient, maintenance time, and maintenance interval coefficient. Specifically, WE = a1 × vc + a2 × vb + a3 × vn, where vc, vb, and vn are the normalized overall service life coefficient, maintenance time, and maintenance interval coefficient, respectively. a1, a2, and a3 represent the preset proportional coefficients of vc, vb, and vn, respectively, and a1, a2, and a3 are all greater than 0. a1, a2, and a3 are set according to the actual situation. Generally, the sum of a1, a2, and a3 is 1. For example, the values ​​of a1, a2, and a3 can be 0.3, 0.3, and 0.4, or other values, depending on the actual situation. No restrictions or elaborations are made.

[0048] It should be noted that before calculating the equipment usage coefficient, the overall service life coefficient, maintenance cost time and maintenance interval coefficient need to be normalized after removing the units. Commonly used normalization methods include Min-Max normalization, Z-Score normalization, etc., depending on the actual situation, and will not be limited or elaborated.

[0049] It should be noted that the actual time of equipment's commissioning and its preset usable time can usually be obtained from information such as equipment purchase records, installation dates, and usage logs; while data such as the number of equipment failures, repair times, and intervals between failures typically come from equipment failure reports, maintenance records, and maintenance logs. This data is usually recorded and tracked by equipment maintenance personnel, automated monitoring systems, or equipment management software. Through these detailed records, the equipment's lifespan, mean time to repair, and failure intervals can be accurately calculated, thus providing the necessary basis for ultimately determining the equipment's utilization factor.

[0050] It should be noted that the higher the equipment utilization factor of the first aquifer, the less suitable the aquifer is for compressed air energy storage. This is because the utilization factor reflects the overall condition and maintenance needs of the equipment. A higher utilization factor means that the equipment's lifespan is nearing or has exceeded its expected service life, resulting in a higher failure rate and increased maintenance requirements, potentially leading to decreased reliability. Furthermore, increased maintenance frequency and time mean more downtime during energy storage, impacting the system's operational efficiency. Frequent equipment failures can also cause gas leaks or instability during storage, reducing safety and efficiency. Therefore, aquifers with higher utilization factors may face greater maintenance costs and a higher risk of system failure, making them unsuitable for compressed air energy storage.

[0051] In this application, the advantages of analyzing the equipment utilization factor in determining whether an aquifer is suitable for compressed air energy storage are as follows: it provides a comprehensive assessment of the equipment's health status, helping to identify potential risks and deficiencies; a low equipment utilization factor indicates that the equipment is in good working condition, with a low failure rate, fewer maintenance requirements, and higher system reliability, making it suitable for long-term operation; the equipment utilization factor effectively reflects the equipment's working efficiency and maintenance costs, ensuring stable and efficient operation of the equipment during compressed air energy storage, reducing system interruptions caused by downtime and maintenance; by screening based on the equipment utilization factor, it is possible to avoid selecting aquifers with aging equipment and frequent failures, thereby improving the success rate and economic efficiency of energy storage projects.

[0052] Optionally, the state coefficient corresponding to the first aquifer is calculated, including:

[0053] The transmission coefficient, energy storage capacity coefficient, and equipment utilization coefficient are normalized, and the state coefficient of the first aquifer is calculated based on the normalized transmission coefficient, energy storage capacity coefficient, and equipment utilization coefficient. The calculation formula is as follows:

[0054]

[0055] In the formula, TF is the state coefficient, mjn, mnj and mjv are the normalized transmission coefficient, energy storage capacity coefficient and equipment utilization coefficient, respectively, and b1, b2 and b3 represent the preset proportional coefficients of mjn, mnj and mjv, respectively. b1, b2 and b3 are all greater than 0.

[0056] It should be noted that b1, b2, and b3 are set according to the actual situation. Generally, the sum of b1, b2, and b3 is 1. For example, the values ​​of b1, b2, and b3 can be 0.4, 0.35, and 0.25, or other values, depending on the specific circumstances. No further limitations or elaborations are provided. Before calculating the state coefficients, the overall service life coefficient, maintenance cost time, and maintenance interval coefficient need to be normalized after removing the units. Commonly used normalization methods include Min-Max normalization and Z-Score standardization, etc., depending on the specific circumstances. No further limitations or elaborations are provided.

[0057] In one embodiment, the state coefficient is compared with a preset state coefficient threshold. If the state coefficient is greater than or equal to the preset state coefficient threshold, the corresponding first aquifer is recorded as an energy-storing aquifer, and each energy-storing first aquifer is recorded as a second aquifer.

[0058] It should be noted that the preset state coefficient threshold is set by professionals based on the actual situation, and no specific limitations or details are provided.

[0059] It's worth explaining that the aforementioned second aquifer signifies superior performance in terms of transmission efficiency, gas storage capacity, and equipment reliability. This screening process effectively prevents unsuitable aquifers from being included in the energy storage system. This not only improves the overall operating efficiency of the energy storage system and reduces potential energy losses but also effectively lowers equipment failure and maintenance costs. The second aquifer meets certain standards in terms of gas storage capacity and equipment performance, ensuring the stability and safety of the energy storage process while also improving the system's economy and sustainability. This screening method helps optimize the allocation of energy storage resources, ensuring that compressed air energy storage systems can achieve efficient energy storage and release under optimal operating conditions, further enhancing the utilization rate of renewable energy.

[0060] In other words, the selected second aquifers generally possess good energy storage conditions. To ensure optimal energy storage performance, their priority selection coefficients need further evaluation. By obtaining the energy storage efficiency coefficient and energy storage pressure fluctuation coefficient of each second aquifer, its corresponding priority selection coefficient can be calculated. These coefficients reflect the efficiency and stability of the aquifer during the energy storage process, especially its performance during gas filling and releasing, as well as its pressure fluctuation control capability. Selecting second aquifers with higher priority selection coefficients ensures that the energy storage process proceeds under efficient and stable conditions. Aquifers with high priority selection coefficients indicate superior performance in gas storage efficiency and pressure control, maximizing energy storage benefits and reducing energy waste and equipment wear. Therefore, selecting the second aquifer with the highest priority selection coefficient as the final energy storage aquifer is a crucial step in ensuring the efficient and safe operation of the compressed air energy storage system.

[0061] Specifically, the steps for screening aquifers for final energy storage are as follows:

[0062] In one embodiment, for each second aquifer, the corresponding priority selection data is obtained to calculate the priority selection coefficient of the corresponding second aquifer; wherein, the priority selection data includes the energy storage efficiency coefficient and the energy storage pressure fluctuation coefficient.

[0063] The calculation steps for the energy storage efficiency coefficient are as follows:

[0064] The stored energy and released energy of each second aquifer are obtained from historical records for each energy storage event. The absolute difference between the stored energy and released energy for each energy storage event is calculated, and the absolute difference is divided by the stored energy to obtain the energy loss ratio for each energy storage event.

[0065] The gas filling and venting times for each energy storage operation in the second aquifer are obtained, and the sum of these times is calculated to obtain the total time spent on each energy storage operation. It's important to clarify that the energy storage time refers to the sum of the filling and venting times for each operation; these times are in a one-to-one correspondence. Generally, multiple venting operations after a single energy storage operation are avoided, as this would result in significant energy loss and pose geological safety risks. Therefore, energy storage systems typically employ a "one-time filling, one-time venting" method, releasing compressed air all at once when electrical energy needs to be released. Thus, the filling and venting times for each energy storage process are paired and correspond one-to-one.

[0066] The energy loss ratio and storage time for each energy storage event are weighted and summed after removing the units to obtain the corresponding energy storage efficiency value. The reciprocal of the mean of the energy storage efficiency values ​​for each energy storage event is taken as the energy storage efficiency coefficient of the corresponding second aquifer.

[0067] It should be noted that the number of energy storage operations in the second aquifer, the corresponding stored and released energy during each operation, and the time for gas filling and venting during each operation are typically obtained through historical energy storage records and real-time monitoring systems. Specifically, the number of energy storage operations can be automatically calculated from the energy storage system's operation logs or monitoring platform. The stored and released energy during each operation can be directly recorded by the energy metering equipment of the energy storage device (such as electricity meters, gas pressure sensors, etc.). The filling and venting times are obtained through the control system's time stamp or timing function. These data are usually automatically recorded and uploaded to the data platform during energy storage operations. By accumulating this real-time and historical data, key parameters such as energy loss and time costs during each energy storage process can be accurately calculated, thereby evaluating the energy storage efficiency coefficient.

[0068] It should be noted that the energy storage efficiency value is obtained by weighted summation after removing the units from the energy loss ratio and energy storage time for each energy storage operation. The formula is as follows: After removing the units from the energy loss ratio and energy storage time for each energy storage operation, normalize them, and then obtain the energy storage efficiency value based on the normalized energy loss ratio and energy storage time. The formula is: Ku = c1 × rf + C2 × rg; where Ku is the energy storage efficiency value, rf and rg are the normalized energy loss ratio and energy storage time, respectively, and c1 and c2 represent the preset proportional coefficients of rf and rg, respectively, and both c1 and c2 are greater than 0.

[0069] It should be noted that c1 and c2 are set according to the actual situation. Generally, the sum of c1 and c2 is 1. For example, the values ​​of c1 and c2 can be 0.5 and 0.5, or other values, depending on the actual situation. There are no restrictions or elaborations. Commonly used normalization methods include Min-Max normalization, Z-Score normalization, etc. The specific method depends on the actual situation. There are no restrictions or elaborations.

[0070] It should be noted that the higher the energy storage efficiency coefficient of the second aquifer, the greater its priority as the final energy storage layer for storing surplus power from the power plant. This is because a higher energy storage efficiency coefficient means that the aquifer can store and release energy more efficiently during the energy storage process, with less energy loss and a shorter storage time. This indicates that the aquifer has high gas filling and releasing efficiency and low energy loss, maximizing the overall efficiency and economy of the energy storage system. Therefore, when the energy storage efficiency coefficient of the aquifer is high, it can store power more quickly and stably, effectively meeting the power demand fluctuations of the power plant during peak loads or other periods, and reducing the waste of surplus power. For power plants, choosing an aquifer with a high energy storage efficiency coefficient for power storage not only improves the operating efficiency of the power system but also reduces maintenance and operating costs while ensuring energy storage stability. Therefore, such aquifers have a higher priority when storing surplus power.

[0071] In this application, the advantage of analyzing the energy storage efficiency coefficient in determining whether a second aquifer is the final energy storage layer for storing surplus power from a power plant is that it quantifies energy loss and time required during storage, thus providing a more accurate basis for selecting the energy storage aquifer. A higher energy storage efficiency coefficient means that the aquifer can store and release energy efficiently in a shorter time, reducing waste caused by energy loss and time delay during storage. This not only improves the economic benefits of power storage but also enhances the stability and sustainability of the energy storage system. By optimizing energy storage efficiency, power plants can more flexibly adjust the storage and release of surplus power, improving the reliability of the power system while reducing equipment failures and maintenance costs. Selecting an aquifer with a high energy storage efficiency coefficient maximizes the utilization of surplus power from the power plant, improves the overall operating efficiency of the energy storage system, and ensures timely power support during peak power demand periods.

[0072] In one embodiment, the calculation steps for the energy storage pressure fluctuation coefficient are as follows:

[0073] The energy storage pressures of each secondary aquifer during the most recent energy storage process are obtained from historical records to obtain a time-series energy storage pressure sequence; the energy storage pressures in the energy storage pressure sequence are denoted as A. sLet s represent the order number of the energy storage pressure in the energy storage pressure sequence, s∈[1,e], e is the total number of energy storage pressures in the energy storage pressure sequence, and e is a positive integer;

[0074] Calculate the mean of the energy storage pressure series The calculation formula is:

[0075] The formula for calculating the energy storage pressure fluctuation coefficient is as follows:

[0076]

[0077] Wherein, GH is the energy storage pressure fluctuation coefficient.

[0078] It should be noted that the energy storage pressure of each second aquifer during the most recent energy storage process can be obtained by monitoring and recording the data from pressure sensors during the energy storage process. During the energy storage process, pressure sensors installed in the gas well or aquifer will collect energy storage pressure data in real time. This data will be recorded by the system and stored in the historical database. By accessing these historical records, the energy storage pressure sequence of each second aquifer during the most recent energy storage process can be obtained, which can then be used for subsequent calculations and analysis.

[0079] It should be noted that the smaller the energy storage pressure fluctuation coefficient of the second aquifer, the greater its priority as the final energy storage layer for storing surplus power from the power plant. This is because a smaller energy storage pressure fluctuation coefficient means that the aquifer can maintain a more stable energy storage pressure during the energy storage process. This stability helps avoid a decrease in gas storage efficiency or frequent start-ups and shutdowns of equipment due to excessive pressure fluctuations, thereby improving the smoothness and reliability of the energy storage process. Aquifers with smaller pressure fluctuations can store and release electricity more effectively, reducing energy loss and equipment wear caused by pressure fluctuations, thus possessing higher economic efficiency and reliability in long-term operation. Therefore, second aquifers with smaller energy storage pressure fluctuation coefficients can provide more efficient and sustainable energy storage capacity and are preferentially selected for storing surplus power from power plants to ensure the efficiency and stability of energy storage and release.

[0080] In this application, the advantages of analyzing the energy storage pressure fluctuation coefficient for determining whether a second aquifer is the final energy storage layer for storing the remaining power from the power plant are as follows: It effectively assesses the stability of the energy storage process, especially under high-pressure conditions; a smaller pressure fluctuation coefficient means smoother pressure changes during storage, which helps reduce the operational burden on equipment and lower the failure rate, thereby extending equipment lifespan. Furthermore, stable energy storage pressure improves the storage efficiency of compressed air, preventing energy loss due to excessive pressure fluctuations; monitoring and analyzing the energy storage pressure fluctuation coefficient ensures that the selected energy storage aquifer has higher reliability and economic efficiency, thereby optimizing the efficiency of power storage and release, improving the overall operational performance of the energy storage system, and providing more robust power dispatch support for the power plant.

[0081] In one embodiment, the calculation steps for the preference selection coefficient are as follows:

[0082] The priority selection coefficient for each second aquifer is calculated based on its energy storage efficiency coefficient and energy storage pressure fluctuation coefficient. The formula for calculation is as follows:

[0083]

[0084] In the formula, Dax is the priority selection coefficient, Ku and GH are the energy storage efficiency coefficient and energy storage pressure fluctuation coefficient, respectively, and α and β represent the preset proportional coefficients of Ku and GH, respectively, and both α and β are greater than 0.

[0085] It should be noted that α and β are set according to the actual situation. Generally, the sum of α and β is 1. For example, the values ​​of α and β can be 0.6 and 0.4, or other values, depending on the actual situation. No restrictions or elaborations are made. Before calculating the priority selection coefficient, the energy storage efficiency coefficient and energy storage pressure fluctuation coefficient need to be removed from the units and normalized. Commonly used normalization methods include Min-Max normalization, Z-Score standardization, etc., depending on the actual situation. No restrictions or elaborations are made.

[0086] In this application, the second aquifer with the highest energy storage coefficient is preferentially selected as the final energy storage aquifer. This implies that the aquifer exhibits high energy utilization efficiency and minimal pressure fluctuations during the energy storage process, providing more stable and efficient energy storage capacity. This not only helps reduce potential energy losses during storage but also lowers the risk of equipment maintenance and failure, improving the long-term operational stability of the system. Furthermore, selecting an aquifer with higher energy storage efficiency and smaller pressure fluctuations as the final energy storage aquifer effectively enhances the power plant's capacity to store surplus electricity, ensuring a balanced and sustainable power supply, guaranteeing high energy storage efficiency, reducing energy losses, and lowering costs.

[0087] In one embodiment, the second aquifer with the highest priority selection coefficient is selected as the final aquifer for energy storage. Its corresponding priority selection coefficient is compared with a preset priority selection coefficient threshold, and the energy storage method of the final aquifer is determined based on the comparison result, including:

[0088] The priority selection coefficient of the aquifer for final energy storage is compared with the preset priority selection coefficient threshold. If the priority selection coefficient is less than or equal to the preset priority selection coefficient threshold, the corresponding method for storing the remaining power of the power plant in the aquifer is low-voltage energy storage and phased energy storage.

[0089] If the priority selection coefficient is greater than the preset priority selection coefficient threshold, the corresponding method for storing the remaining power of the power plant in the aquifer is pressurized energy storage.

[0090] It should be noted that the preset priority selection coefficient threshold is set by professionals based on the actual situation, and no specific limitations or details are provided.

[0091] It should be noted that low-pressure energy storage refers to maintaining a low gas pressure during the filling process, thereby reducing the pressure impact on the aquifer. This method is typically suitable for aquifers with unstable storage pressure or low filling efficiency. Low-pressure energy storage avoids potential risks caused by excessively high pressure by controlling the gas pressure within a low range. Staged energy storage involves dividing the gas storage process into multiple stages, with each stage gradually filling the aquifer to avoid storing too much air at once. This method is suitable for aquifers with low filling efficiency or unstable gas pressure, gradually building up the energy storage capacity through a staged filling process. This avoids excessive pressure fluctuations caused by storing gas all at once, effectively reducing the pressure impact on the aquifer and reducing the probability of failure. Pressurized energy storage increases storage capacity by increasing the gas pressure, and is suitable for aquifers with stable gas pressure that can withstand high pressure. In pressurized energy storage, compressed air is stored in a high-pressure environment, and power is generated through the expansion of the high-pressure gas upon release.

[0092] After the aquifer for final energy storage is determined and the energy storage method is selected, staff can dynamically optimize and adjust different energy storage methods. For example, for low-pressure energy storage and staged energy storage, more attention should be paid to pressure management and gas filling rate adjustment to ensure that the energy storage process does not damage the aquifer. At the same time, for pressurized energy storage, priority should be given to ensuring the stable operation of the compressor and related equipment to ensure safety and efficiency in a high-pressure gas storage environment. Specific operations depend on the actual situation and are not limited or elaborated.

[0093] Furthermore, by selecting an appropriate energy storage method based on the actual aquifer state of the final energy storage layer, the energy conversion efficiency coefficient is ensured to be low, operating costs are reduced, and overall energy utilization efficiency is ensured.

[0094] This application also provides an energy storage system for compressed air from an aquifer, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the above-described method. This compressed air energy storage system for an aquifer can implement various embodiments of the above-described method and achieve the same beneficial effects; further details are omitted here.

[0095] The preferred embodiments of the present invention have been described in detail above. It should be understood that those skilled in the art can make numerous modifications and variations based on the concept of the present invention without creative effort. Therefore, all technical solutions that can be obtained by those skilled in the art based on the concept of the present invention through logical analysis, reasoning, or limited experimentation on the basis of existing technology should be within the scope of protection defined by the claims.

Claims

1. A method for storing compressed air in an aquifer, characterized in that, include: S1: Each aquifer around the power plant that has undergone energy storage is designated as the first aquifer. The state data corresponding to each first aquifer is obtained, and the state coefficient of the corresponding first aquifer is calculated. S2: Compare the state coefficient with the preset state coefficient threshold, and record the first aquifer with a state coefficient greater than or equal to the preset state coefficient threshold as the first aquifer that can store energy, and replace each first aquifer that can store energy as the second aquifer. S3: Obtain the priority selection data corresponding to each second aquifer and calculate the priority selection coefficient of each second aquifer; S4: Select the second aquifer with the highest priority selection coefficient as the final aquifer for energy storage, compare the priority selection coefficient corresponding to the final aquifer with the preset priority selection coefficient threshold, and determine the energy storage method of the final aquifer based on the comparison results. The state coefficients include the transmission coefficient, energy storage capacity coefficient, and equipment utilization coefficient; The transmission coefficient is related to the shortest distance from the inlet of the energy storage pipeline of the first aquifer to the power plant, the total length of the energy storage pipeline, and the average diameter of the energy storage pipeline. The energy storage capacity coefficient is related to the maximum pressure and energy storage space volume when the first aquifer stores gas. The equipment utilization factor is related to the overall service life factor, maintenance cost time, and maintenance interval factor. The preferred data include the energy storage efficiency coefficient and the energy storage pressure fluctuation coefficient. The energy storage efficiency coefficient is related to the energy loss ratio of each energy storage operation and the time spent on each energy storage operation.

2. The method for storing compressed air in an aquifer according to claim 1, characterized in that, The calculation of the state coefficient corresponding to the first aquifer includes: The transmission coefficient, energy storage capacity coefficient, and equipment utilization coefficient are normalized, and the state coefficient of the first aquifer is calculated based on the normalized transmission coefficient, energy storage capacity coefficient, and equipment utilization coefficient, satisfying the following relationship: ； In the formula, For state coefficients, , and These are the normalized transmission coefficient, energy storage capacity coefficient, and equipment utilization coefficient, respectively. They represent and The preset proportional coefficient, and All are greater than 0.

3. The method for storing compressed air in an aquifer according to claim 2, characterized in that, The calculation steps for the transmission coefficient are as follows: Obtain the shortest distance from the energy storage pipeline inlet to the power plant for each first aquifer. Total length of energy storage pipeline and the average diameter of the energy storage pipeline The transmission coefficients are calculated and satisfy the following relationship: ； In the formula, Indicates the transmission coefficient. This is a preset adjustment constant.

4. The method for storing compressed air in an aquifer according to claim 2, characterized in that, The calculation steps for the energy storage capacity coefficient are as follows: Obtain the horizontal area of ​​each first aquifer Aquifer thickness and the pores of the aquifer Calculate the volume of energy storage space It satisfies the following relationship: ； Obtain the maximum pressure during gas storage in each of the first aquifers. And combined with the volume of energy storage space and atmospheric pressure The energy storage capacity factor is calculated to satisfy the following relationship: ； In the formula, This represents the energy storage capacity coefficient.

5. The energy storage method for compressed air in an aquifer according to claim 2, characterized in that, The calculation steps for the equipment utilization factor are as follows: Obtain the actual usage time and the preset usable time of each device corresponding to each first aquifer, and divide the actual usage time by the preset usable time to obtain the service life progress of the corresponding device. Calculate the average service life progress of all devices to obtain the overall service life coefficient of the corresponding device in the first aquifer. Obtain the number of failures and the repair time for each failure of the equipment corresponding to each first aquifer, and calculate the average repair time of the corresponding equipment based on the repair time for each failure; take the average repair time of all equipment as the repair time of the corresponding equipment in the first aquifer. The average time interval of failures of the equipment corresponding to each first aquifer and the time interval between the current failure and the previous failure are obtained. The average time interval is subtracted from the time interval between the current failure and the previous failure to obtain the corresponding failure time interval value. The failure time interval values ​​of all equipment are used as the maintenance interval coefficient of the equipment corresponding to the first aquifer. The overall service life coefficient, maintenance cost time, and maintenance interval coefficient are normalized to obtain the equipment utilization coefficient, which satisfies the following relationship: ； In the formula, WE is the equipment utilization factor. , and These are the normalized overall service life coefficient, maintenance cost time, and maintenance interval coefficient, respectively. They represent , and The preset ratio coefficient.

6. The method for storing compressed air in an aquifer according to claim 1, characterized in that, The calculation of the priority selection coefficient for each second aquifer includes: The priority selection coefficient is calculated based on the energy storage efficiency coefficient and energy storage pressure fluctuation coefficient of each second aquifer, satisfying the following relationship: ； In the formula, As a priority selection factor, and These are the energy storage efficiency coefficient and the energy storage pressure fluctuation coefficient, respectively. They represent and The preset proportional coefficient, and All are greater than 0.

7. The method for storing compressed air in an aquifer according to claim 6, characterized in that, The steps for calculating the energy storage efficiency coefficient are as follows: The stored energy and released energy of each second aquifer are obtained from historical records. The absolute difference between the stored energy and released energy for each energy storage is calculated, and the absolute difference is divided by the stored energy to obtain the energy loss ratio for each energy storage. Obtain the inflation and deflation times for each of the second aquifers during each energy storage operation, and calculate the sum of the inflation and deflation times to obtain the time spent on each energy storage operation. The energy loss ratio and the time spent on each energy storage session are weighted and summed after removing the units to obtain the corresponding energy storage efficiency value, which satisfies the following relationship: ； In the formula, This represents the energy storage efficiency value. and These represent the normalized energy loss ratio and the time spent storing energy, respectively. They represent and The preset proportional coefficient; The reciprocal of the average energy storage efficiency value of each energy storage is taken as the energy storage efficiency coefficient of the corresponding second aquifer.

8. The method for storing compressed air in an aquifer according to claim 6, characterized in that, The calculation steps for the energy storage pressure fluctuation coefficient are as follows: The energy storage pressure of each secondary aquifer during its most recent energy storage process was obtained from historical records, resulting in a time-series-based energy storage pressure sequence. The energy storage pressures in this sequence were then calibrated as follows: ,use This indicates the sequence number of the energy storage pressures in the energy storage pressure sequence. , Let be the total number of energy storage pressures in the energy storage pressure sequence, and It is a positive integer; Calculate the mean of the energy storage pressure series , And calculate the energy storage pressure fluctuation coefficient, which satisfies the following relationship: ； in, This is the energy storage pressure fluctuation coefficient.

9. The method for storing compressed air in an aquifer according to claim 1, characterized in that, The process of determining the final energy storage method for the aquifer based on the comparison results includes: The priority selection coefficient of the aquifer for final energy storage is compared with the preset priority selection coefficient threshold. If the priority selection coefficient is less than or equal to the preset priority selection coefficient threshold, the method of storing the remaining power of the power plant in the corresponding aquifer is set as low-voltage energy storage and phased energy storage. If the priority selection coefficient is greater than the preset priority selection coefficient threshold, the method for storing the remaining power of the corresponding aquifer power plant is set to boosted energy storage.

10. An energy storage system for compressed air in an aquifer, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 9.

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