A method and system for flexible operation of a carbon capture power plant coupled with solar-membrane absorption

Abstract

This invention discloses a flexible operation method and system for a carbon capture power plant coupled with solar energy and membrane absorption. This invention relates to the field of energy optimization technology and includes the following steps: obtaining the initial liquid level values ​​of the rich solvent and lean solvent storage tanks, and collecting predicted data on electricity prices and solar irradiance during the control period; calculating the heat supplied to the reboiler by the solar thermal collector based on the solar irradiance; automatically introducing steam extracted from the turbine to supplement the heat load if the heat supply is insufficient; constructing an optimization decision model with the goal of maximizing overall operating benefits, where the decision variables are the rich solvent mass flow rate and absorbent concentration entering the reboiler at each time period; outputting the optimal rich solvent mass flow rate and corresponding absorbent concentration; and controlling the rich solvent flow rate entering the reboiler by adjusting the conveying equipment to achieve optimized operation. This invention improves the safety and stability of resource utilization and further optimizes the overall efficiency of carbon capture.

Description

Technical Field

[0001] This invention relates to the field of energy optimization technology, specifically to a flexible operation method and system for a carbon capture power plant coupled with solar energy and membrane absorption. Background Technology

[0002] With the increasing global demand for renewable energy and emission reduction technologies, carbon capture, utilization and storage (CCUS) technology is playing an increasingly important role in reducing greenhouse gas emissions. Therefore, carbon capture power plants that couple solar energy and membrane absorption technologies have emerged as a new solution that can improve energy efficiency while reducing carbon emissions.

[0003] Existing technologies typically rely on traditional fossil fuel power plants for carbon capture. These plants regenerate absorbents under high temperature and pressure, often requiring large amounts of fossil fuels or electricity to meet their heat load requirements. In this process, the utilization of solar energy is often overlooked, resulting in the underutilization of the potential of renewable energy. At the same time, existing technologies often cannot respond in real time to fluctuations in electricity prices and changes in solar irradiance when adjusting the operation mode of power plants, lacking flexible control mechanisms. This makes it difficult for power plants to maximize their overall benefits when facing volatile market conditions. Meanwhile, in optimizing the operation of carbon capture systems, existing technologies often treat the capacity limit of the storage tank as a static constraint, simply ensuring that the liquid level in the solvent storage tank does not exceed the rated capacity or is not lower than a certain safe level. However, in actual operation, the absorption and regeneration process of the solvent is dynamic. Especially under the influence of solar energy input and electricity price fluctuations, the flow rate and concentration of the solvent are constantly changing. Existing technologies have failed to effectively model and optimize these dynamic changes, resulting in low capacity utilization of the storage tank and slow response to solvent level regulation, which cannot meet the needs of flexible system operation.

[0004] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0005] The purpose of this invention is to provide a flexible operation method and system for carbon capture power plants coupled with solar energy and membrane absorption, so as to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: A flexible operation method for a carbon capture power plant coupled with solar energy and membrane absorption includes the following steps: At the start of the control period, obtain the initial liquid level values ​​of the absorbent solvent in the rich solvent storage tank and the lean solvent storage tank of the power plant to be controlled, and obtain the electricity price data and the predicted value of solar irradiance during the control period. Based on solar irradiance data, the heat load supplied to the reboiler by the solar thermal collector and storage device during the control cycle is calculated. When the heat load is insufficient to meet the heat load of solvent regeneration during the control cycle, steam is automatically introduced from the turbine for supplementation. Based on electricity price data and the heat load supplemented by steam turbine extraction, with the goal of maximizing the comprehensive operating benefits of the power plant to be regulated within the regulation cycle, and with the rich solvent mass flow rate and absorbent concentration entering the reboiler at each time period within the regulation cycle as decision variables, an optimization decision model is constructed that includes a benefit objective function and operating constraints. Based on the optimization decision model, the optimal rich solvent mass flow rate and corresponding absorbent concentration for each time period within the entire control cycle are output. According to the output optimal rich solvent mass flow rate, the conveying equipment from the outlet of the rich solvent storage tank to the inlet of the reboiler is adjusted in each time period of the control cycle to control the flow rate of rich solvent entering the reboiler to reach the optimal rich solvent mass flow rate.

[0007] Furthermore, the logic underlying the calculation of heating load based on solar irradiance data is as follows: Based on the optical efficiency of direct normal and diffuse irradiance, combined with solar radiation, the heat energy collected per unit area of ​​the solar thermal collector and storage device is calculated. Based on the heat energy collected per unit area of ​​the solar thermal collector and storage device, the heating load supplied to the reboiler by the solar thermal collector and storage device during the control cycle is calculated. The specific formula used to calculate the heat energy collected per unit area of ​​the solar thermal collector and storage device is as follows: In the formula, To determine the amount of heat energy collected per unit area by the solar thermal collector and storage device at time t within the control period. Optical efficiency for direct normal irradiance. Optical efficiency for diffuse irradiance. This is the correction coefficient for the incident angle at time t within the control period. This refers to the direct solar radiation at time t within the regulation period. To adjust the diffuse irradiance at time t within the control period, The first total heat loss coefficient, The second total heat loss coefficient, To determine the average temperature of the solar thermal collector and storage device at time t within the control period, The ambient temperature at time t within the control period is the temperature of the solar thermal collector and storage device, where t is the time variable within the control period. The incident angle correction factor is calculated based on the solar incident angle of the solar thermal collector and storage device, and the specific formula used is as follows: In the formula, To correct the proportionality constant, To determine the solar incidence angle of the solar thermal collector and storage device at time t within the control period; The formula used to calculate the specific heating load supplied to the reboiler by the solar thermal collector and storage device during the control cycle is as follows: In the formula, To regulate the heating load supplied to the reboiler by the solar thermal collector and storage device during the regulation cycle. The area of ​​the solar collector within the solar thermal storage device. To regulate the mass flow rate of carbon dioxide flowing through the reboiler during the cycle .

[0008] Furthermore, the heat load for absorbent solvent regeneration specifically refers to the power consumption of the reboiler, calculated using the heat consumption of purge steam and the heat consumption of raising the absorbent-rich solution to the regeneration temperature. The heat consumption of purge steam is specifically expressed as the product of the latent heat of vaporization of water and the mass flow rate of the purge steam. The formula used for the specific calculation is as follows: In the formula, To purge steam heat consumption, To regulate the mass flow rate of purge steam within the cycle, The latent heat of vaporization of water; The heat consumption of the absorbent solution rising to the regeneration temperature is calculated by using the mass flow rate of the absorbent flowing through the reboiler and the specific heat capacity of the absorbent at constant pressure. The specific formula used for the calculation is as follows: In the formula, The heat consumption required to raise the absorbent-rich solution to the regeneration temperature. To regulate the mass flow rate of the absorbent flowing through the reboiler during the cycle, The specific heat capacity at constant pressure of the absorbent. and These are the absorbent temperatures entering and exiting the reboiler, respectively. The specific formula used to calculate the heat load for solvent regeneration is as follows: In the formula, To absorb the heat load of solvent regeneration.

[0009] Furthermore, the logic underlying the construction of the revenue objective function is as follows: Based on electricity price data and combined with power generation calculations, the total revenue of the power plant to be regulated during the regulation period is obtained by subtracting the electricity loss cost, carbon trading cost, cost of solar thermal energy storage device, carbon capture cost, and device operating cost from the total revenue. The formula underlying the construction of the revenue objective function is as follows: In the formula, To maximize operational benefits, The average electricity price during the regulation period. This refers to the rated power generation of the power plant to be regulated during the regulation cycle. To control the amount of power loss during the regulation period, In order to regulate carbon trading costs during the cycle, To control carbon capture costs during the control cycle, In order to control the cost of solar thermal collectors and storage devices during the control period, To control the operating costs of the equipment during the control period; The power loss during the control period specifically consists of equivalent power loss and vacuum pump power consumption. The vacuum pump power consumption specifically refers to the power consumption required to maintain the negative pressure state for solvent regeneration. The formula used to calculate the power loss during the control period is as follows: In the formula, To control the vacuum pump power at time t within the control period, For equivalent power loss, This marks the beginning of the regulatory cycle. This marks the end of the regulatory cycle.

[0010] Furthermore, the equivalent power loss is calculated based on the power consumption of the reboiler, specifically based on the Carnot cycle principle, and calculated through the steam loss energy consumption of the steam cycle during carbon capture. The formula used to calculate the equivalent power loss is as follows: In the formula, For the Carnot efficiency of the steam cycle, This refers to the energy consumption due to steam loss during steam extraction per unit mass flow rate. The density of the absorbent, This represents the carbon dioxide loading concentration in the absorbent. The heat load supplied to the reboiler by the steam extracted from the turbine is specifically expressed as follows: The Carnot efficiency of a steam cycle is specifically expressed as: In the formula, The extraction temperature during the steam cycle; The formula used to calculate the steam power loss caused by steam extraction is as follows: In the formula, This represents the temperature of the main condenser during the steam cycle.

[0011] Furthermore, carbon trading costs are specifically calculated based on carbon trading prices, using the following formula: In the formula, For carbon trading prices, This represents the actual carbon emissions of the power plant to be regulated during the regulation period. The initial carbon emission allowance for the power plant to be regulated during the regulation cycle; The cost of a solar thermal collector and storage device is specifically expressed as follows: In the formula, The cost per unit area of ​​solar collectors during the regulation period. For the lifespan of solar collectors This refers to the thermal storage capacity of the solar thermal storage unit in the solar thermal collector and storage device during the regulation period. The price of energy storage materials for solar thermal storage devices, For the lifespan of solar thermal storage devices The density of the energy storage material; The operating cost of carbon capture is calculated based on the duration of carbon capture, using the following formula: In the formula, This represents the total capacity of the absorbent solvent to be regenerated. This represents the runtime cost coefficient.

[0012] Furthermore, the operational constraints specifically include the output power constraint of the power plant to be regulated and the solvent storage tank constraint. Specifically, the output power constraint of the power plant to be regulated means that the actual output power of the power plant to be regulated at each moment of the regulation cycle is not less than the minimum output power set by the power plant to be regulated, and not greater than the maximum output power set by the power plant to be regulated, as expressed in: In the formula, The minimum output power set for the power plant to be regulated. The actual output power of the power plant to be regulated at time t within the regulation period. The maximum output power set for the power plant to be regulated; The constraints on the solvent storage tank are specifically expressed as follows: In the formula, To determine the liquid storage capacity of the solvent-rich storage tank at time t within the control period, To determine the liquid storage capacity of the lean solvent storage tank at time t within the control period, Within the regulation cycle At this moment, the liquid storage capacity of the rich solvent storage tank, To control the net flow rate into the solvent-rich storage tank at time t within the control period, To control the net flow rate into the lean solvent storage tank at time t within the control period, Within the regulation cycle At any given time, the liquid storage capacity of the lean solvent storage tank, To determine the maximum liquid storage capacity of the solvent-rich storage tank at time t within the control period. To determine the maximum liquid storage capacity of the lean solvent storage tank at time t within the control period. This refers to the unit of time; it is generally set to 2-10 minutes.

[0013] The maximum storage capacity of the rich solvent storage tank and the lean solvent storage tank is dynamically adjusted based on the monitoring characteristic data of the absorbent liquid. This monitoring characteristic data includes the actual pressure drop of the solvent storage tank and the concentration of thermally stable degradation products in the solvent. A quality degradation coefficient of the absorbent liquid is calculated based on this monitoring characteristic data. The rated maximum storage capacity of the rich solvent storage tank and the lean solvent storage tank is then corrected based on this quality degradation coefficient to obtain the maximum storage capacity of the two tanks. The specific formula used to calculate the quality degradation coefficient is as follows: In the formula, Let be the mass deterioration coefficient of the absorbent liquid in the solvent storage tank at time t. Let t be the half-life of the foam in the solvent storage tank at time t. The preset maximum foam half-life, Let be the concentration of thermally stable degradation products in the solvent at time t. The preset maximum concentration, and These are weighting coefficients, and ; The foam half-life in the solvent storage tank at time t is calculated based on the actual pressure drop in the solvent storage tank, and the specific formula used for the calculation is as follows: In the formula, Let t be the actual pressure drop of the solvent storage tank at time t. For the design pressure drop of the solvent storage tank, The decay rate constant is denoted by . Based on the quality deterioration coefficient of the absorbent, the formula used to determine the maximum storage capacity of rich solvent storage tanks and lean solvent storage tanks is as follows: In the formula, and These are the rated maximum storage capacities of the rich solvent storage tank and the lean solvent storage tank at time t, respectively. and , respectively, are the capacity decay coefficients for rich solvent storage tanks and lean solvent storage tanks, where .

[0014] Furthermore, the logic underlying the output of the optimal solvent-rich mass flow rate and corresponding absorbent concentration throughout the entire control cycle is as follows: Using the rich solvent mass flow rate and absorbent concentration entering the reboiler at various times within the control cycle as decision variables, a genetic algorithm is used to determine the optimal rich solvent mass flow rate and corresponding absorbent concentration. The rich solvent mass flow rate and absorbent concentration are used as genes, and within their preset value range, several data combinations containing rich solvent mass flow rate and absorbent concentration are generated, which are individuals. The fitness function is used as the profit objective function, and the individual with the largest fitness function value is determined as the optimal combination of rich solvent mass flow rate and corresponding absorbent concentration.

[0015] This invention also provides a flexible operation system for a carbon capture power plant coupled with solar energy and membrane absorption. This flexible operation system is used to execute the aforementioned flexible operation method for a carbon capture power plant coupled with solar energy and membrane absorption, comprising: The data monitoring module is used to obtain the initial liquid level of the solvent in the rich solvent storage tank and the lean solvent storage tank of the power plant to be regulated at the start of the regulation cycle, and to obtain the electricity price data and the predicted value of solar irradiance during the regulation cycle. The heat load compensation module is used to calculate the heat load supplied to the reboiler by the solar thermal collector and storage device within the control cycle based on solar irradiance data. When the heat load is insufficient to meet the heat load of solvent regeneration within the control cycle, steam is automatically introduced from the turbine for supplementation. The decision optimization module is used to construct an optimization decision model that includes a profit objective function and operating constraints, based on electricity price data and the heat load of steam turbine extraction supplementation, with the goal of maximizing the comprehensive operating benefits of the power plant to be regulated within the regulation cycle, and with the rich solvent mass flow rate and absorbent concentration entering the reboiler at each time period within the regulation cycle as decision variables. The optimal decision analysis module is used to output the optimal rich solvent mass flow rate and corresponding absorbent concentration for each time period within the entire control cycle based on the optimization decision model. According to the output optimal rich solvent mass flow rate, the conveying equipment from the outlet of the rich solvent storage tank to the inlet of the reboiler is adjusted in each time period of the control cycle to control the flow rate of rich solvent entering the reboiler to reach the optimal rich solvent mass flow rate.

[0016] Compared with the prior art, the beneficial effects of the present invention are: This solution maximizes the overall operating benefits of the power plant by automatically adjusting the flow rate of the rich solvent and the concentration of the absorbent during the control cycle by real-time monitoring of electricity prices and solar irradiance. Dynamic control not only reduces operating costs but also improves the system's adaptability to market fluctuations, thereby enhancing overall economic efficiency. Furthermore, the real-time response capability of the control equipment ensures that the regeneration process of the rich solvent remains stable under varying solar input and electricity demand, thus reducing energy waste and optimizing resource allocation.

[0017] Secondly, this scheme also introduces the concept of dynamic constraints on solvent storage tanks. By monitoring the actual pressure drop and the concentration of thermally stable degradation products in the solvent storage tank, the quality deterioration coefficient of the absorbent is calculated, thereby dynamically adjusting the maximum storage capacity of rich and lean solvents. This effectively overcomes the limitation of existing technologies that only use the rated capacity of the solvent storage tank as a constraint, ensuring that the carbon capture process can more flexibly respond to changes in different operating conditions in actual operation, effectively avoiding unsafe situations such as tank overflow or insufficient liquid level, improving the safety and stability of resource utilization, and further optimizing the overall efficiency of carbon capture. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of the overall method flow of the present invention; Figure 2 A statistical chart showing the impact of solar heating load on CO2 capture rate; Figure 3 A chart showing the predicted on-grid electricity price for power plants and the trend of carbon trading prices; Figure 4 This is a schematic diagram of the overall system structure of the present invention. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments.

[0020] It should be noted that, unless otherwise defined, the technical or scientific terms used in this invention should 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. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed following the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0021] Example: Please see Figures 1-3 The present invention provides a technical solution: A flexible operation method for a carbon capture power plant coupled with solar energy and membrane absorption includes the following steps: Step 1: Obtain the initial liquid level values ​​of the solvent in the rich solvent storage tank and the lean solvent storage tank of the power plant to be regulated at the start of the regulation cycle, and obtain the electricity price data and the predicted value of solar irradiance during the regulation cycle.

[0022] This embodiment describes the operation and control of a solvent storage solar-powered carbon capture (CCC) system in a power plant under control. Specifically, the pre-treated flue gas from the power plant is fed into the bottom of the absorption unit of a hollow fiber membrane contactor via a blower. The flue gas is absorbed by the rich solvent inside the absorption unit. The rich solvent then enters a rich solvent storage tank, and the outflow rate is regulated by a pump. After the rich solvent is regenerated, the lean absorbent is extracted from the bottom of the hollow fiber membrane contactor and flows into the lean solvent storage tank or the absorption unit of the hollow fiber membrane contactor to continue absorbing carbon dioxide from the flue gas. Solvent regeneration is specifically achieved using an integrated solar collector and storage device. Energy consumption during solvent regeneration is primarily achieved through desorption using heat released from the solar collector and storage device; any shortfall is supplied by steam extraction from a low-pressure turbine.

[0023] Specifically, the pre-treated flue gas from the power plant enters the bottom of the hollow fiber membrane contactor absorber (HFMCAbsorber) via a blower. At a temperature of 40 to 60°C, it reacts counter-currently with an amine solvent. The CO2-rich amine solvent, having absorbed CO2, flows into the hollow fiber membrane contactor stripper (HFMC Stripper). The CO2-rich solvent flows downwards along the tube side of the membrane contactor, contacting counter-currently with purge steam from the bottom of the shell side. After solvent regeneration, the CO2-lean absorbent is extracted from the bottom of the membrane contactor and flows back into the hollow fiber membrane contactor absorber to continue the CO2 absorption cycle. CO2 gas is released from the top of the hollow fiber membrane contactor stripper and compressed for storage.

[0024] The total membrane area of ​​the hollow fiber membrane contactor is determined based on the carbon dioxide flux and the mass flow rates flowing into and out of the contactor. The formula used to calculate the total membrane area is as follows: In the formula, This refers to the total membrane area of ​​the hollow fiber membrane contactor. The design value for the mass flow rate into the hollow fiber membrane contactor. The mass flow rate exiting the hollow fiber membrane contactor, Here is the molar mass of carbon dioxide. This represents the carbon dioxide flux, which is determined based on the concentration of the absorbent.

[0025] The specific method for obtaining electricity price data within the regulation cycle includes: electricity price data within the regulation cycle can be predicted using a deep learning network, specifically based on an LSTM model. An activation function and optimization algorithm are selected, with the Tanh function chosen as the activation function and Adam chosen as the optimization algorithm for the LSTM model. Simultaneously, the hyperparameters of the LSTM model are set, including: number of network layers, number of iterations, learning rate, batch size, number of training iterations, batch size, and number of hidden layer neurons. The network is set to a 4-layer structure, the number of iterations is set to 200, the learning rate is set to 0.001, the batch size is set to 32, the number of training iterations is set to 100, the number of batches is set to 256, and the number of hidden layer neurons is set to 32. The specific training process includes: acquiring several previous electricity price time series data, using the last electricity price data of each time series data as the label, and using the remaining electricity price data in that time series data as the output to train the LSTM model. The input of the trained LSTM model is several electricity price time series data, and the output is the electricity price time series data of subsequent times.

[0026] Predictions of solar irradiance can be obtained from historical, real-time, and future weather data through weather stations, satellite remote sensing, or weather APIs such as OpenWeatherMap and Meteomatics.

[0027] Step 2: Calculate the heating load supplied to the reboiler by the solar thermal collector and storage device within the control cycle based on solar irradiance data. When the heating load is insufficient to meet the heat load of solvent regeneration within the control cycle, steam is automatically introduced from the turbine for supplementary heating.

[0028] The logic behind calculating the heating load based on solar irradiance data is as follows: Based on the optical efficiency of direct normal and diffuse irradiance, combined with solar radiation, the heat energy collected per unit area of ​​the solar thermal collector and storage device is calculated. Based on the heat energy collected per unit area of ​​the solar thermal collector and storage device, the heating load supplied to the reboiler by the solar thermal collector and storage device during the control cycle is calculated. The specific formula used to calculate the heat energy collected per unit area of ​​the solar thermal collector and storage device is as follows: In the formula, To determine the amount of heat energy collected per unit area by the solar thermal collector and storage device at time t within the control period. Optical efficiency for direct normal irradiance. Optical efficiency for diffuse irradiance. This is the correction coefficient for the incident angle at time t within the control period. This refers to the direct solar radiation at time t within the regulation period. To adjust the diffuse irradiance at time t within the control period, The first total heat loss coefficient, The second total heat loss coefficient, To determine the average temperature of the solar thermal collector and storage device at time t within the control period, The ambient temperature at time t within the control period is the temperature of the solar thermal collector and storage device, where t is the time variable within the control period. It should be noted that, This indicates a specific moment within the control cycle. The effective heat energy that a solar thermal collector can collect per unit area reflects the actual heat energy output of the collector under specific environmental conditions and solar radiation intensity. Among them, the optical efficiency of solar collectors and This is used to quantify the ability of a solar collector to capture and convert sunlight into heat energy. The optical efficiency of direct and diffuse radiation varies depending on the materials and design; in this embodiment, the optical efficiency of direct normal irradiance is used. Specifically, the optical efficiency of diffuse irradiance is taken as 0.75. Specifically, the value is 0.08. The direct solar radiation and diffuse irradiance at time t within the control period are specifically targeted at the solar radiation and diffuse irradiance at the solar thermal collector and storage device. In the formula This is the heat loss term, used to evaluate the heat loss of the solar collector during operation. Heat loss is related to the temperature difference and is usually described using a linear and squared relationship, conforming to the physical laws of heat conduction. The specific value is 0.5. The specific value is between 0.1 and 0.5.

[0029] The incident angle correction factor is calculated based on the solar incident angle of the solar thermal collector and storage device, and the specific formula used is as follows: In the formula, To correct the proportionality constant, To determine the solar incidence angle of the solar thermal collector and storage device at time t within the control period; It should be noted that when sunlight shines on the solar thermal collector and storage device, the angle of solar incidence... This directly affects the effectiveness of the solar collector in receiving solar radiation. The larger the angle of incidence, the more the light deviates from the normal to the collector surface, resulting in a decrease in the intensity of the collected solar radiation. According to the geometric properties of light, the effective intensity of solar radiation is related to the cosine of the angle of incidence. When (That is, when sunlight shines perpendicularly), the solar collector receives the most energy. For larger incident angles, the cosine value decreases, leading to a reduction in the actual received radiation intensity. This indicates the attenuation ratio relative to the vertical incidence.

[0030] The formula used to calculate the specific heating load supplied to the reboiler by the solar thermal collector and storage device during the control cycle is as follows: In the formula, To regulate the heating load supplied to the reboiler by the solar thermal collector and storage device during the regulation cycle. The area of ​​the solar collector within the solar thermal storage device. To regulate the mass flow rate of carbon dioxide passing through the reboiler during the cycle.

[0031] It should be noted that, Indicates the time of a solar collector per unit area. The collected heating load is compared with the area of ​​the collector. Multiplying these values ​​yields the total heating load of the entire solar collector at that moment. This value reflects the working efficiency and collection capacity of the solar collector under specific environmental conditions. The mass flow rate of carbon dioxide flowing through the reboiler directly affects the heat transfer efficiency. The larger the mass flow rate, the more heat the fluid transfers and absorbs in the reboiler. Using the mass flow rate as the denominator reflects the relationship between heat and fluid flow. The total heating load within the control cycle is divided by the carbon dioxide mass flow rate to match the heat load of the absorbed solvent regeneration.

[0032] The regeneration heat load of the absorbent solvent is specifically the power consumption of the reboiler, calculated by the heat consumption of the purge steam and the heat consumption of raising the absorbent-rich solution to the regeneration temperature. The heat consumption of the purge steam is specifically expressed as the product of the latent heat of vaporization of water and the mass flow rate of the purge steam. The specific formula used for the calculation is as follows: In the formula, To purge steam heat consumption, To regulate the mass flow rate of purge steam within the cycle, The latent heat of vaporization of water; The heat consumption of the absorbent solution rising to the regeneration temperature is calculated by using the mass flow rate of the absorbent flowing through the reboiler and the specific heat capacity of the absorbent at constant pressure. The specific formula used for the calculation is as follows: In the formula, The heat consumption required to raise the absorbent-rich solution to the regeneration temperature. To regulate the mass flow rate of the absorbent flowing through the reboiler during the cycle, The specific heat capacity at constant pressure of the absorbent. and These are the absorbent temperatures entering and exiting the reboiler, respectively. The specific formula used to calculate the heat load for solvent regeneration is as follows: In the formula, To absorb the heat load of solvent regeneration.

[0033] Step 3: Based on electricity price data and the heat load of steam extraction from the turbine, with the goal of maximizing the comprehensive operating benefits of the power plant to be regulated within the regulation cycle, and with the rich solvent mass flow rate and absorbent concentration entering the reboiler at each time period within the regulation cycle as decision variables, an optimization decision model is constructed that includes a benefit objective function and operating constraints.

[0034] The logic behind constructing the revenue objective function is as follows: Based on electricity price data and combined with power generation calculations, the total revenue of the power plant to be regulated during the regulation period is obtained by subtracting the costs of electricity loss, carbon trading, solar thermal energy storage, carbon capture, and equipment operation from the total revenue. The specific formula for constructing the revenue objective function is as follows: In the formula, To maximize operational benefits, The average electricity price during the regulation period. This refers to the rated power generation of the power plant to be regulated during the regulation cycle. To control the amount of power loss during the regulation period, In order to regulate carbon trading costs during the cycle, To control carbon capture costs during the control cycle, In order to control the cost of solar thermal collectors and storage devices during the control period, To control the operating costs of the equipment during the control period; The carbon capture cost during the regulation cycle The specific calculation method is as follows: In the formula, The depreciation cost of carbon capture equipment; This represents the solvent loss cost during the operation of the carbon capture equipment at time t within the control period. The coal consumption cost at time t within the control period; The unit solvent cost for the storage tank; This refers to the volume of the storage tank. The service life of the storage tank; The equipment cost, excluding storage tanks, includes the cost of pumps, blowers, compressors, and HFMC equipment. The service life of equipment excluding storage tanks; Cost of the absorbent; The mass of solvent lost for every 1 t of CO2 captured; For coal costs; The power loss during the control period specifically consists of equivalent power loss and vacuum pump power consumption. The vacuum pump power consumption specifically refers to the power consumption required to maintain the negative pressure state for solvent regeneration. The formula used to calculate the power loss during the control period is as follows: In the formula, To control the vacuum pump power at time t within the control period, For equivalent power loss, This marks the beginning of the regulatory cycle. This marks the end of the regulatory cycle.

[0035] The specific method for obtaining the vacuum pump power at time t within the control period is as follows: Calculate the adiabatic index of the regenerated gas, calculate the vacuum pump efficiency based on the adiabatic index of the regenerated gas, and then calculate the vacuum pump power. The specific steps include: The adiabatic index is an important parameter characterizing the thermodynamic properties of a gas. The adiabatic index of the regenerated gas can be calculated by weighted averaging the adiabatic indices and mole fractions of each component in the gas mixture. Specifically, it is necessary to know the mole fractions of carbon dioxide and water vapor in the gas, as well as their respective adiabatic indices. After combining the data, the adiabatic index of the gas mixture can be calculated. The efficiency of the vacuum pump depends on the pressure ratio between the gas inlet pressure and the outlet pressure. By dividing the inlet pressure by the outlet pressure, the pressure ratio is obtained. Then, the efficiency of the vacuum pump is calculated using empirical formulas. Finally, the power consumption of the vacuum pump needs to be calculated by combining information such as the gas molar velocity, gas constant, regeneration temperature, adiabatic index, vacuum pump efficiency, number of compression stages, inlet pressure, and outlet pressure, taking into account the adiabatic compression formula in thermodynamics and the working efficiency of the vacuum pump. The specific calculation formulas are conventional techniques and will not be elaborated here.

[0036] The equivalent power loss is calculated based on the power consumption of the reboiler, specifically based on the Carnot cycle principle, and calculated through the steam loss energy consumption of the steam cycle during carbon capture. The formula used to calculate the equivalent power loss is as follows: In the formula, For the Carnot efficiency of the steam cycle, This refers to the energy consumption due to steam loss during steam extraction per unit mass flow rate. The density of the absorbent, This represents the carbon dioxide loading concentration in the absorbent. The heat load supplied to the reboiler by the steam extracted from the turbine is specifically expressed as follows: The Carnot efficiency of a steam cycle is specifically expressed as: In the formula, The extraction temperature during the steam cycle; The formula used to calculate the steam power loss caused by steam extraction is as follows: In the formula, This represents the temperature of the main condenser during the steam cycle.

[0037] During the operation of a steam cycle system, the extraction steam temperature is typically monitored and recorded in real time by the system's sensors or thermometers. This temperature can be obtained through monitoring equipment connected to the control system; temperature sensors installed at the outlet or cooling water inlet of the main condenser can monitor the condenser temperature in real time.

[0038] It should be noted that the formula is based on thermodynamic principles, especially the concepts of Carnot cycle and energy conservation. It can effectively assess the power loss caused by steam loss in actual operation. Carnot efficiency is an important concept in thermodynamics, which provides the highest efficiency of an ideal heat engine between a given high and low temperature heat source. By multiplying the efficiency of the actual steam cycle by the Carnot efficiency, the energy loss under actual operating conditions can be estimated. The energy loss caused by steam extraction is described by the mass flow rate, density and carbon dioxide concentration of the absorbent per unit mass flow rate, which reflects the energy consumed by the absorbent in the carbon capture process.

[0039] The heat load supplied to the reboiler by turbine extraction steam is specifically as follows: when the reboiler's heat load is insufficient to meet the heat load for solvent regeneration during the control cycle, turbine extraction steam is automatically introduced to make up the difference. Therefore, it is expressed as follows: ,when When the value is negative, it indicates that the heat load of the solar thermal collector and storage device is sufficient to meet the operation of the reboiler. At this time, the heat load supplied to the reboiler by the steam extracted from the turbine is 0.

[0040] For power generation companies, their participation in the carbon trading market will be determined based on their allocated carbon emission allowances and actual carbon emissions. The resulting additional transaction costs or benefits constitute the company's carbon trading costs. Based on the operating principles of the carbon trading management platform, carbon trading costs are specifically calculated based on carbon trading prices, using the following formula: In the formula, For carbon trading prices, This represents the actual carbon emissions of the power plant to be regulated during the regulation period. The initial carbon emission allowance for the power plant to be regulated during the regulation period is set at 10% of the plant's rated emissions during the regulation period. The cost of a solar thermal collector and storage device is specifically expressed as follows: In the formula, The cost per unit area of ​​solar collectors during the regulation period, specifically expressed as monthly cost. For the lifespan of solar collectors This refers to the thermal storage capacity of the solar thermal storage unit in the solar thermal collector and storage device during the regulation period. The price of energy storage materials for solar thermal storage devices, For the lifespan of solar thermal storage devices The density of the energy storage material; It's important to note that multiplying the cost per unit area by the total area yields the initial investment for the entire solar collector. This is directly related to energy capture capacity; a larger collector area typically means a higher initial cost, but may also result in more energy collection. Combining storage capacity with the cost and density of storage materials allows for an assessment of the total cost of the storage system. Larger storage capacity often requires more storage material, thus increasing the system's total cost. Lifespan is a crucial factor for investment recovery. By amortizing costs over lifespan, the average annual or monthly cost can be calculated. Dividing by 12 may convert the annual cost to a monthly cost, making cost comparisons and financial analysis more feasible and facilitating cash flow management.

[0041] The operating cost of carbon capture is calculated based on the duration of carbon capture, using the following formula: In the formula, This represents the total capacity of the absorbent solvent to be regenerated. This represents the runtime cost coefficient.

[0042] It should be noted that carbon capture operation costs specifically refer to the time cost of carrying out carbon capture, through... This represents the time required to complete carbon capture under different rich solvent mass flow rates within the control period. This time is converted into cost for comparison using an operating time cost coefficient, which is specifically set based on industry standards, empirical data, and expert experience.

[0043] The operational constraints specifically include the output power constraint of the power plant to be regulated and the solvent storage tank constraint. Specifically, the output power constraint of the power plant to be regulated means that the actual output power of the power plant to be regulated at any time during the regulation period is not less than the minimum output power set by the power plant to be regulated, and not greater than the maximum output power set by the power plant to be regulated. This is specifically expressed as follows: In the formula, The minimum output power set for the power plant to be regulated. The actual output power of the power plant to be regulated at time t within the regulation period. The maximum output power set for the power plant to be regulated; The constraints on the solvent storage tank are specifically expressed as follows: In the formula, To determine the liquid storage capacity of the solvent-rich storage tank at time t within the control period, To determine the liquid storage capacity of the lean solvent storage tank at time t within the control period, Within the regulation cycle At this moment, the liquid storage capacity of the rich solvent storage tank, To control the net flow rate into the solvent-rich storage tank at time t within the control period, To control the net flow rate into the lean solvent storage tank at time t within the control period, Within the regulation cycle At any given time, the liquid storage capacity of the lean solvent storage tank, To determine the maximum liquid storage capacity of the solvent-rich storage tank at time t within the control period. To determine the maximum liquid storage capacity of the lean solvent storage tank at time t within the control period. The unit time length is specifically set to 1 second. The maximum storage capacity of the rich solvent storage tank and the lean solvent storage tank is dynamically adjusted based on the monitoring characteristic data of the absorbent liquid. This monitoring characteristic data includes the actual pressure drop of the solvent storage tank and the concentration of thermally stable degradation products in the solvent. A quality degradation coefficient of the absorbent liquid is calculated based on this monitoring characteristic data. The rated maximum storage capacity of the rich solvent storage tank and the lean solvent storage tank is then corrected based on this quality degradation coefficient to obtain the maximum storage capacity of the two tanks. The specific formula used to calculate the quality degradation coefficient is as follows: In the formula, Let be the mass deterioration coefficient of the absorbent liquid in the solvent storage tank at time t. Let t be the half-life of the foam in the solvent storage tank at time t. The preset maximum foam half-life, Let be the concentration of thermally stable degradation products in the solvent at time t. The preset maximum concentration, and These are weighting coefficients, and ; It should be noted that the foam half-life directly affects the stability of the solvent and the performance of the storage solution. Excessive foam or an excessively long half-life may cause a surge in pressure within the solvent storage tank, preventing the absorbent from flowing normally, affecting mass transfer efficiency, and potentially even causing solvent loss or tank overflow. Therefore, the foam half-life has a more significant impact on the performance of the absorbent, hence the setting of a foam half-life. ,and For weighting coefficients The typical value range is between 0.5 and 0.6.

[0044] The foam half-life in the solvent storage tank at time t is calculated based on the actual pressure drop in the solvent storage tank, and the specific formula used for the calculation is as follows: In the formula, Let t be the actual pressure drop of the solvent storage tank at time t. For the design pressure drop of the solvent storage tank, The decay rate constant is denoted by . It should be noted that the quality degradation coefficient It is a comprehensive indicator that reflects the quality changes of the absorbent during use. As foam stability decreases and the concentration of thermally stable degradation products increases, the quality deterioration coefficient increases, indicating a decline in the quality and performance of the solvent. Bubble half-life This reflects the stability of the foam in the solvent. Poor foam stability usually means a decline in the physical properties of the solvent, which may lead to faster quality deterioration. Therefore, comparing the foam half-life with the preset maximum foam half-life helps to evaluate the current performance of the solvent. Concentration of thermally stable degradation products It is one of the important indicators of solvent quality. The higher its concentration, the more serious the degradation of the solvent, which affects its trapping ability. Therefore, comparing the current concentration with the maximum concentration can effectively reflect the degree of solvent quality deterioration. Changes in foam half-life and degradation product concentration are closely related to chemical reaction kinetics. Monitoring reaction rate and reaction products can effectively assess the quality of absorbent.

[0045] The half-life of foam can be obtained through laboratory testing or field monitoring. Generally, it is determined by observing the time required for foam to disappear from its formation. Real-time monitoring can be performed using devices such as flow meters and pressure sensors. Specifically, the flow meter and pressure sensor are connected to a real-time monitoring system or data acquisition system to ensure that the equipment can continuously acquire fluid flow and pressure data. An appropriate sampling frequency is set to ensure that the dynamic changes of foam can be captured. The collected flow and pressure data are then processed and analyzed using data analysis software such as MATLAB and Python. By analyzing pressure and flow changes, the formation and disappearance process of foam can be identified. By monitoring the time required for bubbles to disappear after formation and combining it with flow data, the exchange rate between gas and liquid can be estimated, thereby more accurately calculating the foam half-life.

[0046] This concentration is usually obtained through sampling analysis. In the laboratory, it is quantitatively determined using analytical methods such as gas chromatography (GC) and high-performance liquid chromatography (HPLC). For real-time monitoring systems, it can also be directly measured using online analytical instruments such as infrared spectrometers.

[0047] Exponential function in the formula This indicates the sensitivity of the foam half-life to changes in pressure drop. As the actual pressure drop increases, the foam half-life decays exponentially, highlighting the impact of pressure drop on system stability and effectively reflecting the foam's performance under different pressure states. The exponential function form effectively represents this time dependence, especially when the system experiences changes in monitored pressure drop. The relationship between the rate of change of foam stability and pressure can be described by exponential decay, which is relevant to designing the pressure drop. This provides a benchmark, allowing the impact of the current actual pressure drop to be quantified relatively. Normalizing to the design pressure drop eliminates differences between different tank designs, facilitating comparisons. Based on the quality deterioration coefficient of the absorbent, the formula used to determine the maximum storage capacity of rich solvent storage tanks and lean solvent storage tanks is as follows: In the formula, and These are the rated maximum storage capacities of the rich solvent storage tank and the lean solvent storage tank at time t, respectively. and , respectively, are the capacity decay coefficients for rich solvent storage tanks and lean solvent storage tanks, where .

[0048] It should be noted that the rated maximum liquid storage capacity of the solvent storage tank varies with the mass deterioration coefficient. As the concentration increases, the storage capacity decreases. Specifically, the amount of capacity decay is proportional to the product of the quality degradation coefficient and the capacity decay coefficient, allowing for dynamic adjustment of the maximum storage capacity when the quality deteriorates, in order to ensure the safety and performance of the system. The capacity decay coefficients of rich solvent and lean solvent storage tanks are different. For the capacity decay coefficient of rich solvents The value is typically set between 0.03 and 0.15; this is the capacity decay coefficient for lean solvent storage tanks. It is generally set between 0.01 and 0.1; this indicates that the capacity reduction of the rich solvent storage tank is greater when the quality deteriorates, because solvent regeneration and carbon dioxide absorption in the rich solvent make it more susceptible to degradation or other adverse reactions.

[0049] Step 4: Based on the optimization decision model, output the optimal rich solvent mass flow rate and corresponding absorbent concentration for each time period within the entire control cycle. According to the output optimal rich solvent mass flow rate, adjust the conveying equipment from the outlet of the rich solvent storage tank to the inlet of the reboiler in each time period of the control cycle to control the flow rate of rich solvent entering the reboiler to reach the optimal rich solvent mass flow rate.

[0050] The logic underlying the output of the optimal solvent-rich mass flow rate and corresponding absorbent concentration throughout the entire control cycle is as follows: Using the rich solvent mass flow rate and absorbent concentration entering the reboiler at various times within the control cycle as decision variables, the optimal rich solvent mass flow rate and corresponding absorbent concentration are determined by a genetic algorithm. The rich solvent mass flow rate and absorbent concentration are used as genes, and within their preset value range, several data combinations containing the rich solvent mass flow rate and absorbent concentration are generated as individuals. Several individuals form an initial population, and the initial population is iteratively optimized, specifically including iterative operations of selection, crossover, and mutation of individuals in the initial population. Using the objective function of profit as the fitness function, an iterative optimization termination condition is set, which can be set as the maximum number of iterations. After the iteration optimization terminates, the individual with the largest fitness function value is determined, which is the optimal combination of solvent-rich mass flow rate and corresponding absorbent concentration. The genetic algorithm is a conventional technique and will not be elaborated upon here.

[0051] Please see Figure 4 The present invention also provides a flexible operation system for a carbon capture power plant coupled with solar energy and membrane absorption. This flexible operation system is used to execute the aforementioned flexible operation method for a carbon capture power plant coupled with solar energy and membrane absorption, comprising: The data monitoring module is used to obtain the initial liquid level of the solvent in the rich solvent storage tank and the lean solvent storage tank of the power plant to be regulated at the start of the regulation cycle, and to obtain the electricity price data and the predicted value of solar irradiance during the regulation cycle. The heat load compensation module is used to calculate the heat load supplied to the reboiler by the solar thermal collector and storage device within the control cycle based on solar irradiance data. When the heat load is insufficient to meet the heat load of solvent regeneration within the control cycle, steam is automatically introduced from the turbine for supplementation. The decision optimization module is used to construct an optimization decision model that includes a profit objective function and operating constraints, based on electricity price data and the heat load of steam turbine extraction supplementation, with the goal of maximizing the comprehensive operating benefits of the power plant to be regulated within the regulation cycle, and with the rich solvent mass flow rate and absorbent concentration entering the reboiler at each time period within the regulation cycle as decision variables. The optimal decision analysis module is used to output the optimal rich solvent mass flow rate and corresponding absorbent concentration for each time period within the entire control cycle based on the optimization decision model. According to the output optimal rich solvent mass flow rate, the conveying equipment from the outlet of the rich solvent storage tank to the inlet of the reboiler is adjusted in each time period of the control cycle to control the flow rate of rich solvent entering the reboiler to reach the optimal rich solvent mass flow rate.

[0052] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0053] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented in software, the above embodiments can be implemented, in whole or in part, as a computer program product. Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution.

[0054] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0055] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. A flexible operation method for a carbon capture power plant coupled with solar energy and membrane absorption, characterized in that, The specific steps include: At the start of the control period, obtain the initial liquid level values ​​of the absorbent solvent in the rich solvent storage tank and the lean solvent storage tank of the power plant to be controlled, and obtain the electricity price data and the predicted value of solar irradiance during the control period. Based on solar irradiance data, the heat load supplied to the reboiler by the solar thermal collector and storage device during the control cycle is calculated. When the heat load is insufficient to meet the heat load of solvent regeneration during the control cycle, steam is automatically introduced from the turbine for supplementation. Based on electricity price data and the heat load supplemented by steam turbine extraction, with the goal of maximizing the comprehensive operating benefits of the power plant to be regulated within the regulation cycle, and with the rich solvent mass flow rate and absorbent concentration entering the reboiler at each time period within the regulation cycle as decision variables, an optimization decision model is constructed that includes a benefit objective function and operating constraints. Based on the optimization decision model, the optimal rich solvent mass flow rate and corresponding absorbent concentration for each time period within the entire control cycle are output. According to the output optimal rich solvent mass flow rate, the conveying equipment from the outlet of the rich solvent storage tank to the inlet of the reboiler is adjusted in each time period of the control cycle to control the flow rate of rich solvent entering the reboiler to reach the optimal rich solvent mass flow rate.

2. The flexible operation method of a carbon capture power plant coupled with solar energy and membrane absorption according to claim 1, characterized in that: The logic behind calculating the heating load based on solar irradiance data is as follows: Based on the optical efficiency of direct normal and diffuse irradiance, combined with solar radiation, the heat energy collected per unit area of ​​the solar thermal collector and storage device is calculated. Based on the heat energy collected per unit area of ​​the solar thermal collector and storage device, the heating load supplied to the reboiler by the solar thermal collector and storage device during the control cycle is calculated. The specific formula used to calculate the heat energy collected per unit area of ​​the solar thermal collector and storage device is as follows: In the formula, To determine the amount of heat energy collected per unit area by the solar thermal collector and storage device at time t within the control period. Optical efficiency for direct normal irradiance. Optical efficiency for diffuse irradiance. This is the correction coefficient for the incident angle at time t within the control period. This refers to the direct solar radiation at time t within the regulation period. To adjust the diffuse irradiance at time t within the control period, The first total heat loss coefficient, The second total heat loss coefficient, To determine the average temperature of the solar thermal collector and storage device at time t within the control period, The ambient temperature at time t within the control period is the temperature of the solar thermal collector and storage device, where t is the time variable within the control period. The incident angle correction factor is calculated based on the solar incident angle of the solar thermal collector and storage device, and the specific formula used is as follows: In the formula, To correct the proportionality constant, To determine the solar incidence angle of the solar thermal collector and storage device at time t within the control period; The formula used to calculate the specific heating load supplied to the reboiler by the solar thermal collector and storage device during the control cycle is as follows: In the formula, To regulate the heating load supplied to the reboiler by the solar thermal collector and storage device during the regulation cycle. The area of ​​the solar collector within the solar thermal storage device. To regulate the mass flow rate of carbon dioxide passing through the reboiler during the cycle.

3. A flexible operation method for a carbon capture power plant coupled with solar energy and membrane absorption as described in claim 2, characterized in that: The regeneration heat load of the absorbent solvent is specifically the power consumption of the reboiler, calculated by the heat consumption of the purge steam and the heat consumption of raising the absorbent-rich solution to the regeneration temperature. The heat consumption of the purge steam is specifically expressed as the product of the latent heat of vaporization of water and the mass flow rate of the purge steam. The specific formula used for the calculation is as follows: In the formula, To purge steam heat consumption, To regulate the mass flow rate of purge steam within the cycle, The latent heat of vaporization of water; The heat consumption of the absorbent solution rising to the regeneration temperature is calculated by using the mass flow rate of the absorbent flowing through the reboiler and the specific heat capacity of the absorbent at constant pressure. The specific formula used for the calculation is as follows: In the formula, The heat consumption required to raise the absorbent-rich solution to the regeneration temperature. To regulate the mass flow rate of the absorbent flowing through the reboiler during the cycle, The specific heat capacity at constant pressure of the absorbent. and These are the absorbent temperatures entering and exiting the reboiler, respectively. The specific formula used to calculate the heat load for solvent regeneration is as follows: In the formula, To absorb the heat load of solvent regeneration.

4. A flexible operation method for a carbon capture power plant coupled with solar energy and membrane absorption according to claim 3, characterized in that, The logic behind constructing the revenue objective function is as follows: Based on electricity price data and combined with power generation calculations, the total revenue of the power plant to be regulated during the regulation period is obtained by subtracting the costs of electricity loss, carbon trading, solar thermal energy storage, carbon capture, and equipment operation from the total revenue. The specific formula for constructing the revenue objective function is as follows: In the formula, To maximize operational benefits, The average electricity price during the regulation period. This refers to the rated power generation of the power plant to be regulated during the regulation cycle. To control the amount of power loss during the regulation period, In order to regulate carbon trading costs during the cycle, To control carbon capture costs during the control cycle, In order to control the cost of solar thermal collectors and storage devices during the control period, To control the operating costs of the equipment during the control period; The power loss during the control period specifically consists of equivalent power loss and vacuum pump power consumption. The vacuum pump power consumption specifically refers to the power consumption required to maintain the negative pressure state for solvent regeneration. The formula used to calculate the power loss during the control period is as follows: In the formula, To control the vacuum pump power at time t within the control period, For equivalent power loss, This marks the beginning of the regulatory cycle. This marks the end of the regulatory cycle.

5. A flexible operation method for a carbon capture power plant coupled with solar energy and membrane absorption according to claim 4, characterized in that: The equivalent power loss is calculated based on the power consumption of the reboiler, specifically based on the Carnot cycle principle, and calculated through the steam loss energy consumption of the steam cycle during carbon capture. The formula used to calculate the equivalent power loss is as follows: In the formula, For the Carnot efficiency of the steam cycle, This refers to the energy consumption due to steam loss during steam extraction per unit mass flow rate. The density of the absorbent, This represents the carbon dioxide loading concentration in the absorbent. The heat load supplied to the reboiler by the steam extracted from the turbine is specifically expressed as follows: The Carnot efficiency of a steam cycle is specifically expressed as: In the formula, The extraction temperature during the steam cycle; The formula used to calculate the steam power loss caused by steam extraction is as follows: In the formula, This represents the temperature of the main condenser during the steam cycle.

6. A flexible operation method for a carbon capture power plant coupled with solar energy and membrane absorption according to claim 5, characterized in that: Carbon trading costs are calculated based on carbon trading prices, using the following formula: In the formula, For carbon trading prices, This represents the actual carbon emissions of the power plant to be regulated during the regulation period. The initial carbon emission allowance for the power plant to be regulated during the regulation cycle; The cost of a solar thermal collector and storage device is specifically expressed as follows: In the formula, The cost per unit area of ​​solar collectors during the regulation period. For the lifespan of solar collectors This refers to the thermal storage capacity of the solar thermal storage unit in the solar thermal collector and storage device during the regulation period. The price of energy storage materials for solar thermal storage devices, For the lifespan of solar thermal storage devices The density of the energy storage material; The operating cost of carbon capture is calculated based on the duration of carbon capture, using the following formula: In the formula, This represents the total capacity of the solvent to be absorbed during regeneration. This represents the runtime cost coefficient.

7. A flexible operation method for a carbon capture power plant coupled with solar energy and membrane absorption as described in claim 6, characterized in that: The operational constraints specifically include the output power constraint of the power plant to be regulated and the solvent storage tank constraint. Specifically, the output power constraint of the power plant to be regulated means that the actual output power of the power plant to be regulated at any time during the regulation period is not less than the minimum output power set by the power plant to be regulated, and not greater than the maximum output power set by the power plant to be regulated. This is specifically expressed as follows: In the formula, The minimum output power set for the power plant to be regulated. The actual output power of the power plant to be regulated at time t within the regulation period. The maximum output power set for the power plant to be regulated; The constraints on the solvent storage tank are specifically expressed as follows: In the formula, To determine the liquid storage capacity of the solvent-rich storage tank at time t within the control period, To determine the liquid storage capacity of the lean solvent storage tank at time t within the control period, Within the regulation cycle At this moment, the liquid storage capacity of the rich solvent storage tank, To control the net flow rate into the solvent-rich storage tank at time t within the control period, To control the net flow rate into the lean solvent storage tank at time t within the control period, Within the regulation cycle At any given time, the liquid storage capacity of the lean solvent storage tank, To determine the maximum liquid storage capacity of the solvent-rich storage tank at time t within the control period. To determine the maximum liquid storage capacity of the lean solvent storage tank at time t within the control period. The unit of time length; The maximum storage capacity of the rich solvent storage tank and the lean solvent storage tank is dynamically adjusted based on the monitoring characteristic data of the absorbent liquid. This monitoring characteristic data includes the actual pressure drop of the solvent storage tank and the concentration of thermally stable degradation products in the solvent. A quality degradation coefficient of the absorbent liquid is calculated based on this monitoring characteristic data. The rated maximum storage capacity of the rich solvent storage tank and the lean solvent storage tank is then corrected based on this quality degradation coefficient to obtain the maximum storage capacity of the two tanks. The specific formula used to calculate the quality degradation coefficient is as follows: In the formula, Let be the mass deterioration coefficient of the absorbent liquid in the solvent storage tank at time t. Let t be the half-life of the foam in the solvent storage tank at time t. The preset maximum foam half-life, Let be the concentration of thermally stable degradation products in the solvent at time t. The preset maximum concentration, and These are weighting coefficients, and ; The foam half-life in the solvent storage tank at time t is calculated based on the actual pressure drop in the solvent storage tank, and the specific formula used for the calculation is as follows: In the formula, Let t be the actual pressure drop of the solvent storage tank at time t. For the design pressure drop of the solvent storage tank, The decay rate constant is denoted by . The formula used to determine the maximum storage capacity of rich solvent storage tanks and lean solvent storage tanks based on the quality deterioration coefficient of the absorbent is as follows: In the formula, and These are the rated maximum storage capacities of the rich solvent storage tank and the lean solvent storage tank at time t, respectively. and , respectively, are the capacity decay coefficients for rich solvent storage tanks and lean solvent storage tanks, where .

8. A flexible operation method for a carbon capture power plant coupled with solar energy and membrane absorption according to claim 7, characterized in that: The logic underlying the output of the optimal solvent-rich mass flow rate and corresponding absorbent concentration throughout the entire control cycle is as follows: Using the rich solvent mass flow rate and absorbent concentration entering the reboiler at various times within the control cycle as decision variables, a genetic algorithm is used to determine the optimal rich solvent mass flow rate and corresponding absorbent concentration. The rich solvent mass flow rate and absorbent concentration are used as genes, and within their preset value range, several data combinations containing rich solvent mass flow rate and absorbent concentration are generated, which are individuals. The fitness function is used as the profit objective function, and the individual with the largest fitness function value is determined as the optimal combination of rich solvent mass flow rate and corresponding absorbent concentration.

9. A flexible operation system for a carbon capture power plant coupled with solar energy and membrane absorption, characterized in that: The aforementioned flexible operation system for a carbon capture power plant coupled with solar energy and membrane absorption is used to execute the flexible operation method for a carbon capture power plant coupled with solar energy and membrane absorption as described in any one of claims 1-8, comprising: The data monitoring module is used to obtain the initial liquid level of the solvent in the rich solvent storage tank and the lean solvent storage tank of the power plant to be regulated at the start of the regulation cycle, and to obtain the electricity price data and the predicted value of solar irradiance during the regulation cycle. The heat load compensation module is used to calculate the heat load supplied to the reboiler by the solar thermal collector and storage device within the control cycle based on solar irradiance data. When the heat load is insufficient to meet the heat load of solvent regeneration within the control cycle, steam is automatically introduced from the turbine for supplementation. The decision optimization module is used to construct an optimization decision model that includes a profit objective function and operating constraints, based on electricity price data and the heat load of steam turbine extraction supplementation, with the goal of maximizing the comprehensive operating benefits of the power plant to be regulated within the regulation cycle, and with the rich solvent mass flow rate and absorbent concentration entering the reboiler at each time period within the regulation cycle as decision variables. The optimal decision analysis module is used to output the optimal rich solvent mass flow rate and corresponding absorbent concentration for each time period within the entire control cycle based on the optimization decision model. According to the output optimal rich solvent mass flow rate, the conveying equipment from the outlet of the rich solvent storage tank to the inlet of the reboiler is adjusted in each time period of the control cycle to control the flow rate of rich solvent entering the reboiler to reach the optimal rich solvent mass flow rate.

Images