Carbon sequestration coupled supercritical carbon dioxide energy storage method and system

Abstract

The invention relates to the technical field of carbon dioxide energy storage, in particular to a carbon sequestration coupled supercritical carbon dioxide energy storage method and system, which comprises the following steps of: installing a sensor network on carbon sequestration equipment, collecting key data of supercritical carbon dioxide, sending the key data to a central processing unit in real time, and performing data synchronization and preliminary analysis; and generating initial monitoring data. In the invention, by introducing hydrodynamic force simulation and multi-stage hydrodynamic force control, the energy storage efficiency and stability in the energy storage process of supercritical carbon dioxide are greatly improved, the pressure and temperature are dynamically adjusted to provide flexibility for the energy storage process, and higher energy density and conversion efficiency are realized; the system has remarkable advantages in the aspects of peak valley adjustment and power grid stability enhancement, the performance of the thermoelectric conversion material is optimized in real time, the energy recovery efficiency is effectively improved, energy can be efficiently stored in the carbon sequestration process, captured carbon dioxide is converted into a useful energy form, and environmental benefits and energy recovery are optimized.

Description

Technical Field

[0001] The present invention relates to the field of carbon dioxide energy storage technology, and in particular to a carbon sequestration coupled supercritical carbon dioxide energy storage method and system. Background Art

[0002] The field of carbon dioxide energy storage technology mainly involves the use of changes in the physical state of carbon dioxide to store and release energy. Supercritical carbon dioxide has unique thermodynamic properties that make it denser than liquid or gas at a specific pressure and temperature. It is usually used in thermal energy storage systems, where supercritical carbon dioxide is used as a working fluid to store and release energy through compression and expansion. In addition, the supercritical state of carbon dioxide helps to improve the energy density and conversion efficiency of the system, making it particularly advantageous in large-scale energy storage, and plays an important role in renewable energy integration, improving energy efficiency, and realizing the space-time transfer of energy.

[0003] Among them, the method of carbon sequestration coupled with supercritical carbon dioxide energy storage is not only used for energy storage, but also combines carbon capture and storage technology to effectively reduce the concentration of carbon dioxide in the environment. By converting the captured carbon dioxide into a supercritical state and storing it, efficient energy storage and carbon emissions reduction are achieved. The main uses include providing peak and valley regulation for the power grid, enhancing the stability of the power grid, and providing carbon reduction solutions for industrial emissions, especially in the power industry and heavy industry. In addition, by coupling carbon sequestration and energy recovery, it is expected to become an effective means to address climate change.

[0004] The limitations of existing supercritical carbon dioxide energy storage technology in actual operation are mainly reflected in the maximization of energy storage and release capacity, especially the lack of temperature and pressure regulation mechanisms, which leads to the low efficiency of existing systems in applications in high-energy consumption industries and the power industry. In addition, existing technologies fail to achieve efficient energy recovery in the integrated application of carbon sequestration and energy conversion. In particular, the inefficiency of existing systems directly affects the economic benefits and environmental responsibilities of enterprises when dealing with carbon emissions and energy recovery. For example, in industrial applications with large fluctuations in energy demand, existing technologies fail to provide sufficient support to optimize energy use and reduce carbon emissions, resulting in waste of resources and environmental burden. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose a carbon sequestration coupled supercritical carbon dioxide energy storage method and system.

[0006] In order to achieve the above object, the present invention adopts the following technical solution: a carbon sequestration coupled supercritical carbon dioxide energy storage method, comprising the following steps: S1: Install a sensor network at the carbon storage equipment to collect key data of supercritical carbon dioxide and send it to the central processor in real time for data synchronization and preliminary analysis to generate initial monitoring data; S2: using the initial monitoring data, performing fluid dynamic simulation to simulate the behavior of supercritical carbon dioxide during storage, dynamically adjusting pressure and temperature, and integrating to generate simulation adjustment data; S3: Using the simulation adjustment data, perform multi-stage fluid dynamic control, adjust the flow rate and pressure of supercritical carbon dioxide, optimize the energy storage and storage process, and generate flow state control results; S4: Analyze the stability of supercritical carbon dioxide through the flow control results, evaluate the performance of supercritical carbon dioxide in carbon sequestration and energy conversion processes, adjust operating parameters according to the evaluation results, and generate energy efficiency optimization results; S5: Based on the energy efficiency optimization result, executing the energy recovery unit, calculating the thermoelectric conversion efficiency of the supercritical carbon dioxide, optimizing the performance of the thermoelectric conversion material in real time through dynamic adjustment, and generating thermoelectric optimization data; S6: Based on the thermoelectric optimization data, the carbon storage and energy feedback data are integrated, the stored supercritical carbon dioxide is converted into electrical energy by adjusting the carbon storage coupling equipment, and the system performance is simultaneously monitored to generate a supercritical carbon dioxide comprehensive energy storage solution.

[0007] As a further solution of the present invention, the initial monitoring data includes ambient temperature, storage pressure and fluid rate, the simulation adjustment data includes simulated pressure value, simulated temperature value and flow pattern, the flow state control result includes controlled flow rate, adjusted pressure and flow state balance record, the energy efficiency optimization result includes energy conversion rate, stability level and optimized operation settings, the thermoelectric optimization data includes conversion efficiency, material performance indicators and recovered energy data, and the supercritical carbon dioxide comprehensive energy storage solution includes power output details, monitoring system indicators and carbon recovery ratio.

[0008] As a further solution of the present invention, a sensor network is installed in the carbon sequestration equipment to collect key data of supercritical carbon dioxide and send it to the central processor in real time for data synchronization and preliminary analysis. The specific steps for generating initial monitoring data are as follows: S101: Install the sensor network, collect data in the key monitoring area, adjust the spacing of sensors according to the signal coverage test, and generate a data collection point distribution map; S102: adjusting the data synchronization frequency based on the data collection point distribution map, transmitting the data to the central processor through encrypted transmission, dynamically optimizing the data transmission path, and generating a real-time data synchronization solution; S103: Utilizing the real-time data synchronization solution, data analysis is performed, and the central processing unit performs integrity check on the received data to generate initial monitoring data.

[0009] As a further solution of the present invention, the initial monitoring data is used to perform fluid dynamic simulation, simulate the behavior of supercritical carbon dioxide during storage, dynamically adjust the pressure and temperature, and integrate and generate the simulation adjustment data in the following specific steps: S201: using the initial monitoring data, configuring the initial simulation conditions, inputting the density and viscosity parameters of the supercritical carbon dioxide, setting the geological structure characteristics and permeability data, confirming that the simulation environment basic data matches the actual storage environment, and generating simulation environment setting data; S202: Based on the simulation environment setting data, start the fluid dynamic simulation, monitor the pressure and temperature readings in the simulation, adjust the dynamic parameters in the model according to the real-time feedback, and generate the dynamic simulation results; S203: Analyze based on the dynamic simulation results, evaluate the flow characteristics and diffusion path of supercritical carbon dioxide, integrate and optimize the adjustment model, reflect the actual behavior during the storage process, and generate simulation adjustment data.

[0010] As a further solution of the present invention, the simulation adjustment data is used to perform multi-stage fluid dynamic control, adjust the flow rate and pressure of supercritical carbon dioxide, optimize the energy storage and storage process, and generate the flow state control result in the following specific steps: S301: using the simulation adjustment data, setting initial control parameters of flow rate and pressure, adjusting input values ​​according to the physical properties of supercritical carbon dioxide, simulating actual fluid behavior, and generating flow rate and pressure reference data; S302: Based on the flow rate and pressure reference data, the pressure and flow rate are adjusted in real time through closed-loop control, data changes are monitored, simulation accuracy and reaction speed are tested, and dynamically adjusted flow pattern data is generated; S303: Integrate the dynamically adjusted flow pattern data, evaluate and optimize the dynamic behavior of the fluid, analyze and determine the behavior of the fluid in the actual storage environment, and generate a flow pattern control result.

[0011] As a further solution of the present invention, the specific steps of analyzing the stability of supercritical carbon dioxide through the flow control results, evaluating the performance of supercritical carbon dioxide in carbon sequestration and energy conversion processes, adjusting operating parameters according to the evaluation results, and generating energy efficiency optimization results are as follows: S401: using the flow state control result, capturing the real-time data of temperature, pressure and flow rate of supercritical carbon dioxide in the storage environment, analyzing the stability in the differential storage stage, and generating stability analysis data; S402: Based on the stability analysis data, perform an in-depth evaluation of supercritical carbon dioxide in energy conversion, identify factors affecting key operating parameters, and generate energy efficiency evaluation data; S403: According to the energy efficiency evaluation data, the pressure and temperature control strategies are adjusted, the operating parameters are optimized to optimize the storage efficiency and energy utilization, and an energy efficiency optimization result is generated.

[0012] As a further solution of the present invention, based on the energy efficiency optimization result, the energy recovery unit is executed to calculate the thermoelectric conversion efficiency of supercritical carbon dioxide, and the performance of the thermoelectric conversion material is optimized in real time through dynamic adjustment to generate thermoelectric optimization data. The specific steps are: S501: Based on the energy efficiency optimization result, setting the operating parameters of the energy recovery unit, including the pressure and temperature of the input supercritical carbon dioxide, calculating the energy conversion efficiency in the initial stage, and generating initial thermoelectric efficiency data; S502: using the initial thermoelectric efficiency data, adjusting the temperature gradient and conductivity of the thermoelectric conversion material in real time, refining the material performance adjustment through feedback control, and generating adjusted thermoelectric efficiency data; S503: Based on the adjusted thermoelectric efficiency data, the thermoelectric conversion system configuration is optimized, the operating temperature and contact area of ​​the thermoelectric material are adjusted, and thermoelectric optimization data is generated.

[0013] As a further solution of the present invention, the energy conversion efficiency is according to the formula:

[0014] Calculate, where represents the energy conversion efficiency, is the inlet pressure of supercritical carbon dioxide, is the inlet temperature, It's traffic. It's entropy change.

[0015] As a further solution of the present invention, based on the thermoelectric optimization data, the carbon storage and energy feedback data are integrated, the stored supercritical carbon dioxide is converted into electrical energy by adjusting the carbon storage coupling device, and the system performance is simultaneously monitored to generate the supercritical carbon dioxide comprehensive energy storage solution. The specific steps are: S601: Based on the thermoelectric optimization data, adjusting the working parameters of the carbon sequestration coupling device, setting the pressure and temperature adaptation values ​​of the supercritical carbon dioxide, calibrating the device matching parameters, and generating coupling device calibration data; S602: Using the coupling device calibration data, start energy recovery, perform energy conversion of supercritical carbon dioxide, monitor and record conversion efficiency and system performance, and generate real-time energy conversion monitoring data; S603: Based on the real-time energy conversion monitoring data and combined with the energy feedback data, the carbon sequestration strategy is optimized, the system is continuously optimized, and a supercritical carbon dioxide comprehensive energy storage solution is generated.

[0016] A carbon sequestration coupled supercritical carbon dioxide energy storage system, comprising: The sensor deployment module installs the sensor network, collects data in key monitoring areas, transmits the data to the central processor, performs integrity checks on the received data, and generates initial monitoring data; The simulation configuration module uses the initial monitoring data to configure the initial simulation conditions, confirms that the basic data of the simulation environment matches the actual storage environment, starts the fluid dynamic simulation, monitors the pressure and temperature readings in the simulation, and generates dynamic simulation results; The fluid analysis module evaluates the flow characteristics and diffusion path of the supercritical carbon dioxide based on the dynamic simulation results, reflects the actual behavior during the storage process, simulates the actual fluid behavior, and generates flow rate and pressure benchmark data; The flow state regulation module adjusts the pressure and flow rate in real time through closed-loop control based on the flow rate and pressure reference data, monitors data changes, evaluates and optimizes the dynamic behavior of the fluid, analyzes and determines the behavior of the fluid in the actual storage environment, and generates flow state control results; The stability analysis module uses the flow state control results to capture real-time data of supercritical carbon dioxide in the storage environment, analyzes the stability in the differential storage stage, identifies the influencing factors of key operating parameters, adjusts the pressure and temperature control strategies, and generates energy efficiency optimization results; The thermoelectric optimization module sets the operating parameters of the energy recovery unit based on the energy efficiency optimization result, calculates the energy conversion efficiency in the initial stage, adjusts the temperature gradient and conductivity of the thermoelectric conversion material in real time, optimizes the thermoelectric conversion system configuration, and generates thermoelectric optimization data; Based on the thermoelectric optimization data, the comprehensive energy storage module adjusts the working parameters of the carbon storage coupling device, calibrates the equipment matching parameters, performs energy conversion of supercritical carbon dioxide, combines the energy feedback data, optimizes the carbon storage strategy, and generates a supercritical carbon dioxide comprehensive energy storage solution.

[0017] Compared with the prior art, the advantages and positive effects of the present invention are: In the present invention, by introducing fluid dynamics simulation and multi-stage fluid dynamics control, the energy storage efficiency and stability in the supercritical carbon dioxide energy storage process are greatly improved, and the dynamic adjustment of pressure and temperature provides flexibility for the energy storage process, achieving higher energy density and conversion efficiency, so that the system has significant advantages in peak-valley regulation and grid stability enhancement. The real-time optimization of thermoelectric conversion material performance effectively improves energy recovery efficiency, so that the carbon sequestration process can not only efficiently store energy, but also convert the captured carbon dioxide into useful energy forms, thereby optimizing environmental benefits and energy recovery. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is a schematic diagram of the steps of the present invention; Figure 2 is a flow chart of the steps of S1 of the present invention; Figure 3 is a flow chart of the steps of S2 of the present invention; Figure 4 is a flow chart of the steps of S3 of the present invention; Figure 5 is a flow chart of the steps of S4 of the present invention; Figure 6 is a flow chart of the steps of S5 of the present invention; Figure 7 is a flow chart of the steps of S6 of the present invention; Figure 8 It is a system module diagram of the present invention. DETAILED DESCRIPTION

[0019] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0020] In the description of the present invention, it should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, in the description of the present invention, "multiple" means two or more, unless otherwise clearly and specifically defined.

[0021] See also Figure 1 , a carbon sequestration coupled supercritical carbon dioxide energy storage method, comprising the following steps: S1: Install a sensor network at the carbon storage equipment to collect key data of supercritical carbon dioxide and send it to the central processor in real time for data synchronization and preliminary analysis to generate initial monitoring data; S2: Using the initial monitoring data, perform fluid dynamic simulation to simulate the behavior of supercritical carbon dioxide during storage, dynamically adjust the pressure and temperature, and integrate to generate simulation adjustment data; S3: Use simulation adjustment data to perform multi-stage fluid dynamic control, adjust the flow rate and pressure of supercritical carbon dioxide, optimize the energy storage and storage process, and generate flow control results; S4: Analyze the stability of supercritical carbon dioxide through flow control results, evaluate the performance of supercritical carbon dioxide in carbon sequestration and energy conversion processes, adjust operating parameters according to the evaluation results, and generate energy efficiency optimization results; S5: Based on the energy efficiency optimization results, the energy recovery unit is executed to calculate the thermoelectric conversion efficiency of supercritical carbon dioxide, and the performance of thermoelectric conversion materials is optimized in real time through dynamic adjustment to generate thermoelectric optimization data; S6: Based on the thermoelectric optimization data, the carbon storage and energy feedback data are integrated, the stored supercritical carbon dioxide is converted into electrical energy by adjusting the carbon storage coupling equipment, and the system performance is simultaneously monitored to generate a comprehensive supercritical carbon dioxide energy storage solution.

[0022] The initial monitoring data include ambient temperature, storage pressure and fluid rate, the simulation adjustment data include simulated pressure value, simulated temperature value and flow pattern, the flow control results include the flow rate after control, the pressure after adjustment and the flow balance record, the energy efficiency optimization results include the energy conversion rate, stability level and optimized operation settings, the thermoelectric optimization data include conversion efficiency, material performance indicators and recovered energy data, and the supercritical carbon dioxide comprehensive energy storage solution includes power output details, monitoring system indicators and carbon recovery ratio.

[0023] See also Figure 2 , the specific steps of S1 are: S101: Install the sensor network, collect data in the key monitoring area, adjust the spacing of sensors according to the signal coverage test, and generate a data collection point distribution map; In the process of establishing a sensor network, we first need to select a suitable monitoring area and design the sensor layout according to the environmental characteristics and monitoring objectives of the area. Considering the signal coverage between sensors and the stability of the network, we need to determine the appropriate sensor spacing through signal coverage testing. This test includes measuring the signal strength and coverage range of each sensor, as well as the signal attenuation in different environments. By comparing the coverage and stability of different layout schemes, the optimal scheme is selected for implementation. The data collection point distribution map reflects the final selected layout scheme, in which each data point is marked with the corresponding sensor position and its monitoring range.

[0024] S102: adjusting the data synchronization frequency based on the data collection point distribution map, transmitting the data to the central processor through encrypted transmission, dynamically optimizing the data transmission path, and generating a real-time data synchronization solution; According to the established data collection point distribution map, the data synchronization frequency is adjusted to optimize the data transmission efficiency of the sensor network and reduce energy consumption. By analyzing the data transmission requirements and transmission frequency of each collection point and combining the processing power of the central processor, the frequency and transmission path of data synchronization are dynamically adjusted. Encrypted transmission is used to ensure data security. The transmission efficiency and network load of different data synchronization schemes are simulated through network simulation tools. The final real-time data synchronization scheme can effectively guide actual network operations and data management.

[0025] S103: using the real-time data synchronization solution, executing data analysis, the central processor performs integrity check on the received data and generates initial monitoring data; Using the generated real-time data synchronization solution, the central processor first performs an integrity check on the received data. This process includes checking the integrity of the data packet and the data format to ensure that the received data has not been tampered with or damaged during transmission. Then, data analysis is performed, including data preprocessing, classification, and feature extraction. Through statistical analysis and pattern recognition technology, useful information and trends are extracted from large amounts of data to provide a scientific basis for subsequent decision-making. The generated initial monitoring data provides basic data for subsequent more in-depth analysis and reporting.

[0026] See also Figure 3 , the specific steps of S2 are: S201: using initial monitoring data, configuring initial simulation conditions, inputting density and viscosity parameters of supercritical carbon dioxide, setting geological structure characteristics and permeability data, confirming that the basic data of the simulation environment matches the actual storage environment, and generating simulation environment setting data; Using initial monitoring data as the basis for simulation, configuring the initial simulation conditions is a key step to ensure that the simulation environment is consistent with the actual geological structure characteristics and permeability data. The input parameters include the density and viscosity of supercritical carbon dioxide. The parameters are measured in the laboratory or obtained from the literature to provide the necessary physical property input for the simulation. The simulation environment is set through data to ensure that it has a good match with the actual storage environment. The simulation environment setting data finally generated will directly affect the accuracy and reliability of the simulation.

[0027] S202: Based on the simulation environment setting data, start the fluid dynamic simulation, monitor the pressure and temperature readings in the simulation, adjust the dynamic parameters in the model according to the real-time feedback, and generate the dynamic simulation results; During the start of the fluid dynamics simulation, monitor the pressure and temperature readings in the simulation and calculate the value according to the formula Make adjustments, where Indicates the pressure reading, represents the control volume, represents the number of moles of a substance, is the ideal gas constant, Indicates the temperature reading. Formula explanation and formula calculation derivation process: Consider a closed system where the pressure ,volume and temperature The relationship between describe, and is a constant. In the simulation process, by adjusting To adapt to changes in pressure and temperature, so as to achieve precise control of the system state. For example, assuming the initial temperature K, pressure kPa, volume m³, mol, J / (mol·K). The adjusted state is K, pressure Need to recalculate:

[0028] The result shows that the pressure increases from 100 kPa to 116.396 kPa when the temperature increases from 300 K to 350 K, thus verifying the effectiveness of the model adjustment.

[0029] S203: Analyze based on the dynamic simulation results, evaluate the flow characteristics and diffusion path of the supercritical carbon dioxide, integrate and optimize the adjustment model to reflect the actual behavior during the storage process, and generate simulation adjustment data; Based on the dynamic simulation results, evaluating the flow characteristics and diffusion path of supercritical carbon dioxide is a direct test of the simulation quality. Integrating and optimizing the adjustment model includes calibration and verification of the fluid flow equations to reflect the actual behavior during the storage process. The generated simulation adjustment data provides an evaluation basis for storage safety. This data is adjusted by comparing actual monitoring data and simulation data to ensure that the simulation results are highly close to the actual situation, providing scientific decision-making support for the long-term storage of carbon dioxide.

[0030] See also Figure 4 , the specific steps of S3 are: S301: using simulation adjustment data, setting initial control parameters of flow rate and pressure, adjusting input values ​​according to the physical properties of supercritical carbon dioxide, simulating actual fluid behavior, and generating flow rate and pressure reference data; Using the simulation adjustment data obtained from the previous stage, the initial control parameters of flow rate and pressure are precisely set according to the known physical properties of supercritical carbon dioxide. The parameters include the density and viscosity of the fluid. The characteristics are accurately measured by professional equipment in a laboratory environment to ensure high accuracy and reliability, which is the key to simulating actual fluid behavior. The process of setting parameters requires delicate operations, including calibration of input devices, continuous monitoring of parameters, and dynamic response to changes in environmental conditions, ensuring the accuracy and practicality of the generated flow rate and pressure benchmark data, providing a solid foundation for the next step of flow state control.

[0031] S302: Based on the flow rate and pressure reference data, the pressure and flow rate are adjusted in real time through closed-loop control, data changes are monitored, simulation accuracy and response speed are tested, and dynamic adjustment flow pattern data is generated; Based on the precisely set flow rate and pressure reference data, the closed-loop control system adjusts the flow rate and pressure in real time. During the process, sensors are used to monitor the changes in flow rate and pressure in real time. The system analyzes the data to ensure the accuracy of the feedback mechanism. Real-time adjustment is based on a continuous data stream and can automatically identify and respond to any abnormal changes in the data, thereby making necessary adjustments to ensure the stability of the simulation environment. This process not only verifies the accuracy of the simulation, but also tests the reaction speed of the system. It is an indispensable part of the simulation process and provides a guarantee to ensure that the simulation results can accurately reflect the actual fluid behavior.

[0032] S303: Integrate and dynamically adjust flow pattern data, evaluate and optimize the dynamic behavior of the fluid, analyze and determine the behavior of the fluid in the actual storage environment, and generate flow pattern control results; The process of integrating the dynamic adjustment flow pattern data involves in-depth analysis of multiple fluid dynamic parameters, based on real-time updated data streams, including every measurement of flow rate and pressure. These data are evaluated by advanced data processing algorithms, and the model is optimized to ensure that the fluid behavior perfectly matches the actual storage conditions. The core of this process is to dynamically adjust and optimize the simulation model, and continuously optimize the flow pattern model by comparing the predicted results with the actual observed values. In addition, the output data of this stage is the flow pattern control result, which provides a comprehensive analysis of the behavior of the fluid in the actual environment, enabling decision makers to manage and adjust scientifically based on these data to ensure the long-term stability and safety of the storage environment.

[0033] See also Figure 5 , the specific steps of S4 are: S401: Using the flow control results, capture the real-time data of temperature, pressure and flow rate of supercritical carbon dioxide in the storage environment, analyze the stability in the differential storage stage, and generate stability analysis data; After adopting the flow control results, the real-time data of temperature, pressure and flow rate of supercritical carbon dioxide in the storage environment are captured. These data are continuously recorded by high-precision sensors and then uploaded to the central monitoring system through the data interface for real-time analysis. The analysis focuses on any fluctuations or anomalies in the data, especially the stability changes in different storage stages, to ensure the balance and safety of the storage environment throughout the cycle. The stability analysis data obtained from the analysis is crucial for predicting potential risks in the system, and can adjust operating parameters in a timely manner to avoid possible environmental impacts or equipment failures, thereby ensuring the long-term stability and safety of the storage project.

[0034] S402: Based on the stability analysis data, conduct an in-depth assessment of supercritical carbon dioxide in energy conversion, identify the factors affecting key operating parameters, and generate energy efficiency assessment data; Based on the stability analysis data, in-depth evaluation of the energy conversion efficiency of supercritical carbon dioxide is a complex technical task, which requires precise identification of key operating parameters and analysis of influencing factors. Through data processing software and simulation programs, the expert team analyzes how these parameters affect the energy efficiency of the entire storage system, especially the performance during the energy conversion process. Using statistical and machine learning techniques, real-time and historical data are compared and analyzed to identify the main reasons for energy efficiency fluctuations. The results are summarized to generate energy efficiency evaluation data to help decision makers and engineers optimize system design, improve energy efficiency, and reduce operating costs.

[0035] S403: According to the energy efficiency evaluation data, the pressure and temperature control strategies are adjusted, the operation parameters are optimized, the storage efficiency and energy utilization are optimized, and the energy efficiency optimization results are generated; Based on the energy efficiency assessment data, the work of adjusting the pressure and temperature control strategies involves optimization at multiple technical levels. First, the efficiency of the current control strategy is evaluated, and comparative analysis is used to determine which parameter adjustments can significantly improve storage efficiency and energy utilization. Through real-time monitoring of system feedback, operating parameters are adjusted to achieve the best energy output-to-consumption ratio. In addition, dynamic simulation tools are used to test different control strategies to ensure that each adjustment is optimized in a data-driven manner to improve the energy efficiency of the entire storage system. The generated energy efficiency optimization results not only improve system performance, but also ensure reduced operating costs and minimized environmental impacts, bringing long-term economic and environmental benefits to the storage project.

[0036] See also Figure 6 , the specific steps of S5 are: S501: Based on the energy efficiency optimization result, the operating parameters of the energy recovery unit are set, including the pressure and temperature of the input supercritical carbon dioxide, the energy conversion efficiency in the initial stage is calculated, and the initial thermoelectric efficiency data is generated; Energy conversion efficiency, according to the formula:

[0037] Calculate, where represents the energy conversion efficiency, is the inlet pressure of supercritical carbon dioxide, is the inlet temperature, It's traffic. It's entropy change.

[0038] pressure :According to the latest industrial standards, the pressure of supercritical carbon dioxide is usually set at 20MPa. This value is based on the design specifications of the energy recovery system and is within the operational safety range.

[0039] temperature :The temperature of supercritical carbon dioxide is usually set at 330K, which meets the thermodynamic efficiency optimization criteria in the supercritical state.

[0040] flow :The design flow rate of the system is usually 0.5kg / s, which reflects the energy transmission capacity of the system under typical operating conditions.

[0041] Entropy change : In this example, the entropy change is set to 10 J / K, which is based on the entropy change measurement of the actual energy conversion system under the design state.

[0042] Given the above parameters, calculate the energy conversion efficiency:

[0043] Calculate the square root of temperature:

[0044] Compute the product:

[0045] Calculate the denominator:

[0046] Calculate the energy conversion efficiency:

[0047] The results show that under given pressure, temperature, flow rate and entropy change conditions, the energy conversion efficiency of the system is 72.66%, reflecting the energy efficiency performance of the system under operating parameters. This efficiency value is a key performance indicator used to evaluate the design and operation of the energy recovery unit and to further optimize the system configuration. S502: using the initial thermoelectric efficiency data, adjusting the temperature gradient and conductivity of the thermoelectric conversion material in real time, refining the material performance adjustment through feedback control, and generating adjusted thermoelectric efficiency data; Using the initial thermoelectric efficiency data, the temperature gradient and conductivity of the thermoelectric conversion material are adjusted in real time. The material performance is monitored in real time through feedback control, and the thermoelectric properties of the material, such as conductivity and temperature gradient, are adjusted according to the operating data. The process involves sophisticated material science knowledge and thermoelectric effect theory, and the performance of the material needs to be optimized through an algorithm model to ensure that the thermoelectric unit can maintain optimal efficiency under different operating conditions. The generated adjusted thermoelectric efficiency data provides an experimental basis for the continuous optimization of the system, helping the R&D team to further improve the overall energy efficiency of the system.

[0048] S503: comprehensively analyzing the adjusted thermoelectric efficiency data, optimizing the thermoelectric conversion system configuration, adjusting the operating temperature and contact area of ​​the thermoelectric material, and generating thermoelectric optimization data; The adjusted thermoelectric efficiency data is used to optimize the configuration of the thermoelectric conversion system. Calculate the heat flow, where is the heat flow, is the thermal conductivity, is the contact area of ​​the material, is the temperature difference, is the material thickness. According to the thermoelectric efficiency data, the operating temperature and contact area of ​​the thermoelectric material are adjusted to optimize the thermoelectric conversion efficiency. Consider an example of a thermoelectric material, assuming that the thermal conductivity 1.5W / mK, contact area 0.1m², temperature difference At 50°C, material thickness is 0.01m, then the heat flow It can be calculated as:

[0049] It means that under given conditions, the heat flow is 750 watts. This result shows that by optimizing the parameters, the thermoelectric conversion efficiency can be significantly improved, thereby improving the energy efficiency performance of the entire system.

[0050] See also Figure 7 , the specific steps of S6 are: S601: Based on the thermoelectric optimization data, adjust the working parameters of the carbon sequestration coupling device, set the pressure and temperature adaptation values ​​of the supercritical carbon dioxide, calibrate the device matching parameters, and generate coupling device calibration data; Adjusting the operating parameters of the carbon sequestration coupling device based on the thermoelectric optimization data is a complex and precise process. First, the pressure and temperature parameters of the supercritical carbon dioxide are set according to the results of the thermoelectric optimization to ensure that these parameters can best match the current working state of the device. With professional calibration equipment, each parameter is carefully adjusted and tested to ensure the coordinated work of the entire system and the most efficient energy conversion. The process involves not only the adjustment of physical parameters, but also the update of the control system software so that the new operating parameters can be accurately implemented. The generated coupling device calibration data is a guarantee of the final performance of the equipment, ensuring that all settings meet the predetermined working efficiency standards.

[0051] S602: Using the coupling device calibration data, start energy recovery, perform energy conversion of supercritical carbon dioxide, monitor and record conversion efficiency and system performance, and generate real-time energy conversion monitoring data; Using the coupled equipment calibration data, the energy recovery system is started to directly test the efficiency of supercritical carbon dioxide energy conversion. During this stage, the system monitors and records the conversion efficiency and related system performance indicators. During the process, the temperature gradient and conductivity of the thermoelectric conversion material are refined and adjusted to adapt to the changing operating conditions through the real-time data monitoring system. The generation of real-time energy conversion monitoring data is achieved through high-precision sensors and high-speed data processing systems, ensuring the optimization of the energy recovery process and the continuous improvement of system performance.

[0052] S603: Based on the real-time energy conversion monitoring data and combined with the energy feedback data, the carbon sequestration strategy is optimized, the system is continuously optimized, and a supercritical carbon dioxide comprehensive energy storage solution is generated; According to the real-time energy conversion monitoring data, combined with the energy feedback data, the key to optimizing the carbon sequestration strategy is the adjustment of the operating temperature and contact area of ​​the thermoelectric material. Calculate the heat conversion, where Represents heat, It's quality. is the specific heat capacity, is the temperature change. This calculation helps determine the optimum operating temperature of the material and adjust the contact area to maximize energy efficiency. Assuming the mass of the material 0.5kg, specific heat capacity is 0.9J / g°C, temperature changes is 30°C, the heat It can be calculated as:

[0053] This means that the system can transfer 13,500 joules of heat for a temperature change of 30°C, a result that helps optimize system configuration and improve overall thermoelectric conversion efficiency.

[0054] See also Figure 8 , a carbon sequestration coupled supercritical carbon dioxide energy storage system, comprising: The sensor deployment module installs the sensor network, collects data in key monitoring areas, transmits the data to the central processor, performs integrity checks on the received data, and generates initial monitoring data; The simulation configuration module uses the initial monitoring data, configures the initial simulation conditions, confirms that the basic data of the simulation environment matches the actual storage environment, starts the fluid dynamic simulation, monitors the pressure and temperature readings in the simulation, and generates dynamic simulation results; The fluid analysis module evaluates the flow characteristics and diffusion path of supercritical carbon dioxide based on dynamic simulation results, reflects the actual behavior during storage, simulates actual fluid behavior, and generates flow rate and pressure benchmark data; The flow regulation module adjusts the pressure and flow rate in real time through closed-loop control based on the flow rate and pressure reference data, monitors data changes, evaluates and optimizes the dynamic behavior of the fluid, analyzes and determines the behavior of the fluid in the actual storage environment, and generates flow control results; The stability analysis module uses flow control results to capture real-time data of supercritical carbon dioxide in the storage environment, analyzes stability during differential storage stages, identifies factors affecting key operating parameters, adjusts pressure and temperature control strategies, and generates energy efficiency optimization results; Based on the energy efficiency optimization results, the thermoelectric optimization module sets the operating parameters of the energy recovery unit, calculates the energy conversion efficiency at the initial stage, adjusts the temperature gradient and conductivity of the thermoelectric conversion material in real time, optimizes the thermoelectric conversion system configuration, and generates thermoelectric optimization data; Based on the thermoelectric optimization data, the integrated energy storage module adjusts the working parameters of the carbon storage coupling equipment, calibrates the equipment matching parameters, performs the energy conversion of supercritical carbon dioxide, combines the energy feedback data, optimizes the carbon storage strategy, and generates a supercritical carbon dioxide integrated energy storage solution.

[0055] The above are only preferred embodiments of the present invention and are not intended to limit the present invention in other forms. Any technician familiar with the profession may use the technical contents disclosed above to change or modify them into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. A carbon sequestration coupled supercritical carbon dioxide energy storage method, characterized in that: The following steps are involved: Install a sensor network at the carbon storage equipment to collect key data of supercritical carbon dioxide and send it to the central processor in real time for data synchronization and preliminary analysis to generate initial monitoring data; Using the initial monitoring data, a fluid dynamics simulation is performed to simulate the behavior of the supercritical carbon dioxide during storage, the pressure and temperature are dynamically adjusted, and the simulation adjustment data is integrated to generate; Using the simulation adjustment data, multi-stage fluid dynamic control is performed to adjust the flow rate and pressure of supercritical carbon dioxide, optimize the energy storage and storage process, and generate flow state control results; By using the flow control results, the stability of supercritical carbon dioxide is analyzed, the performance of supercritical carbon dioxide in carbon sequestration and energy conversion processes is evaluated, and the operating parameters are adjusted according to the evaluation results to generate energy efficiency optimization results; Based on the energy efficiency optimization result, an energy recovery unit is executed to calculate the thermoelectric conversion efficiency of supercritical carbon dioxide, and the performance of thermoelectric conversion materials is optimized in real time through dynamic adjustment to generate thermoelectric optimization data; Based on the thermoelectric optimization data, the carbon storage and energy feedback data are integrated, the stored supercritical carbon dioxide is converted into electrical energy by adjusting the carbon storage coupling equipment, and the system performance is simultaneously monitored to generate a supercritical carbon dioxide comprehensive energy storage solution.

2. The carbon sequestration coupled supercritical carbon dioxide energy storage method according to claim 1, characterized in that: The initial monitoring data includes ambient temperature, storage pressure and fluid rate, the simulation adjustment data includes simulated pressure value, simulated temperature value and flow pattern, the flow control results include controlled flow rate, adjusted pressure and flow balance records, the energy efficiency optimization results include energy conversion rate, stability level and optimized operating settings, the thermoelectric optimization data includes conversion efficiency, material performance indicators and recovered energy data, and the supercritical carbon dioxide comprehensive energy storage solution includes power output details, monitoring system indicators and carbon recovery ratio.

3. The carbon sequestration coupled supercritical carbon dioxide energy storage method according to claim 1, characterized in that: Install a sensor network at the carbon storage equipment to collect key data of supercritical carbon dioxide and send it to the central processor in real time for data synchronization and preliminary analysis. The specific steps to generate initial monitoring data are as follows: Install a sensor network to collect data in key monitoring areas, adjust the spacing of sensors based on signal coverage tests, and generate a distribution map of data collection points; Adjust the data synchronization frequency based on the data collection point distribution map, transmit the data to the central processor through encrypted transmission, dynamically optimize the data transmission path, and generate a real-time data synchronization solution; Using the real-time data synchronization solution, data analysis is performed, and the central processing unit performs integrity checks on the received data to generate initial monitoring data.

4. The carbon sequestration coupled supercritical carbon dioxide energy storage method according to claim 1, characterized in that: The specific steps of using the initial monitoring data to perform fluid dynamic simulation, simulate the behavior of supercritical carbon dioxide during storage, dynamically adjust the pressure and temperature, and integrate and generate simulation adjustment data are as follows: Using the initial monitoring data, configuring the initial simulation conditions, inputting the density and viscosity parameters of the supercritical carbon dioxide, setting the geological structure characteristics and permeability data, confirming that the basic data of the simulation environment matches the actual storage environment, and generating the simulation environment setting data; Based on the simulation environment setting data, start the fluid dynamic simulation, monitor the pressure and temperature readings in the simulation, adjust the dynamic parameters in the model according to the real-time feedback, and generate dynamic simulation results; Based on the dynamic simulation results, analysis is performed to evaluate the flow characteristics and diffusion path of supercritical carbon dioxide, integrate and optimize the adjustment model to reflect the actual behavior during the storage process, and generate simulation adjustment data.

5. The carbon sequestration coupled supercritical carbon dioxide energy storage method according to claim 1, characterized in that: The specific steps of using the simulation adjustment data to perform multi-stage fluid dynamic control, adjust the flow rate and pressure of supercritical carbon dioxide, optimize the energy storage and storage process, and generate the flow state control results are as follows: Using the simulation adjustment data, setting the initial control parameters of flow rate and pressure, adjusting the input value according to the physical properties of supercritical carbon dioxide, simulating the actual fluid behavior, and generating flow rate and pressure reference data; Based on the flow rate and pressure reference data, the pressure and flow rate are adjusted in real time through closed-loop control, data changes are monitored, simulation accuracy and reaction speed are tested, and dynamically adjusted flow state data is generated; The dynamically adjusted flow pattern data is integrated to evaluate and optimize the dynamic behavior of the fluid, analyze and determine the behavior of the fluid in the actual storage environment, and generate a flow pattern control result.

6. The carbon sequestration coupled supercritical carbon dioxide energy storage method according to claim 1, characterized in that: The specific steps of analyzing the stability of supercritical carbon dioxide through the flow control results, evaluating the performance of supercritical carbon dioxide in carbon sequestration and energy conversion processes, adjusting the operating parameters according to the evaluation results, and generating energy efficiency optimization results are as follows: Using the flow state control results, real-time data of temperature, pressure and flow rate of supercritical carbon dioxide in the storage environment are captured, the stability in the differential storage stage is analyzed, and stability analysis data is generated; Based on the stability analysis data, an in-depth evaluation of supercritical carbon dioxide in energy conversion is conducted to identify factors affecting key operating parameters and generate energy efficiency evaluation data; According to the energy efficiency evaluation data, the pressure and temperature control strategies are adjusted, the operating parameters are optimized to optimize the storage efficiency and energy utilization, and the energy efficiency optimization results are generated.

7. The carbon sequestration coupled supercritical carbon dioxide energy storage method according to claim 1, characterized in that: Based on the energy efficiency optimization results, the energy recovery unit is executed to calculate the thermoelectric conversion efficiency of supercritical carbon dioxide, and the performance of the thermoelectric conversion material is optimized in real time through dynamic adjustment to generate thermoelectric optimization data. The specific steps are: Based on the energy efficiency optimization result, setting the operating parameters of the energy recovery unit, including the pressure and temperature of the input supercritical carbon dioxide, calculating the energy conversion efficiency in the initial stage, and generating initial thermoelectric efficiency data; Using the initial thermoelectric efficiency data, adjusting the temperature gradient and conductivity of the thermoelectric conversion material in real time, refining the material performance adjustment through feedback control, and generating adjusted thermoelectric efficiency data; The adjusted thermoelectric efficiency data is integrated to optimize the configuration of the thermoelectric conversion system, adjust the operating temperature and contact area of ​​the thermoelectric material, and generate thermoelectric optimization data.

8. The carbon sequestration coupled supercritical carbon dioxide energy storage method according to claim 7, characterized in that: The energy conversion efficiency is according to the formula: Calculate, where represents the energy conversion efficiency, is the inlet pressure of supercritical carbon dioxide, is the inlet temperature, It's traffic. It's entropy change.

9. The carbon sequestration coupled supercritical carbon dioxide energy storage method according to claim 1, characterized in that: Based on the thermoelectric optimization data, the carbon storage and energy feedback data are integrated, the stored supercritical carbon dioxide is converted into electrical energy by adjusting the carbon storage coupling equipment, and the system performance is simultaneously monitored to generate the specific steps of the supercritical carbon dioxide comprehensive energy storage solution: Based on the thermoelectric optimization data, adjusting the working parameters of the carbon sequestration coupling device, setting the pressure and temperature adaptation values ​​of the supercritical carbon dioxide, calibrating the device matching parameters, and generating coupling device calibration data; Using the coupling device calibration data, start energy recovery, perform energy conversion of supercritical carbon dioxide, monitor and record conversion efficiency and system performance, and generate real-time energy conversion monitoring data; Based on the real-time energy conversion monitoring data, combined with the energy feedback data, the carbon sequestration strategy is optimized, the system is continuously optimized, and a supercritical carbon dioxide comprehensive energy storage solution is generated.

10. A carbon sequestration coupled supercritical carbon dioxide energy storage system, characterized in that: According to a carbon sequestration coupled supercritical carbon dioxide energy storage method according to any one of claims 1 to 9, the system comprises: The sensor deployment module installs the sensor network, collects data in key monitoring areas, transmits the data to the central processor, performs integrity checks on the received data, and generates initial monitoring data; The simulation configuration module uses the initial monitoring data to configure the initial simulation conditions, confirms that the basic data of the simulation environment matches the actual storage environment, starts the fluid dynamic simulation, monitors the pressure and temperature readings in the simulation, and generates dynamic simulation results; The fluid analysis module evaluates the flow characteristics and diffusion path of the supercritical carbon dioxide based on the dynamic simulation results, reflects the actual behavior during the storage process, simulates the actual fluid behavior, and generates flow rate and pressure benchmark data; The flow state regulation module adjusts the pressure and flow rate in real time through closed-loop control based on the flow rate and pressure reference data, monitors data changes, evaluates and optimizes the dynamic behavior of the fluid, analyzes and determines the behavior of the fluid in the actual storage environment, and generates flow state control results; The stability analysis module uses the flow state control results to capture real-time data of supercritical carbon dioxide in the storage environment, analyzes the stability in the differential storage stage, identifies the influencing factors of key operating parameters, adjusts the pressure and temperature control strategies, and generates energy efficiency optimization results; The thermoelectric optimization module sets the operating parameters of the energy recovery unit based on the energy efficiency optimization result, calculates the energy conversion efficiency in the initial stage, adjusts the temperature gradient and conductivity of the thermoelectric conversion material in real time, optimizes the thermoelectric conversion system configuration, and generates thermoelectric optimization data; Based on the thermoelectric optimization data, the comprehensive energy storage module adjusts the working parameters of the carbon storage coupling device, calibrates the equipment matching parameters, performs energy conversion of supercritical carbon dioxide, combines the energy feedback data, optimizes the carbon storage strategy, and generates a supercritical carbon dioxide comprehensive energy storage solution.

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