Method for energy consumption optimization of variable load flue gas carbon capture based on model predictive control

Abstract

This invention discloses a variable-load flue gas carbon capture energy consumption optimization method based on model predictive control, belonging to the field of flue gas carbon capture energy consumption optimization technology. It addresses the problem of high overall energy consumption due to long dwell times in inefficient operating areas. By selecting multiple sets of different input power to input to the flue gas capture system, setting a detection time, and detecting the corresponding flue gas flow rate and carbon dioxide concentration, candidate capture power is obtained after screening. An input power range is set based on the candidate power, and capture power is randomly set, marked, and input into the system within the range. The corresponding equipment vibration frequency is detected, the capture power is sorted, and the change in vibration frequency between adjacent power values ​​is calculated. Multiple target capture powers are comprehensively screened, and heat information is detected in real time, and the target power input is selected accordingly, thereby achieving energy saving and efficiency improvement optimization in variable-load flue gas carbon capture.

Description

Technical Field

[0001] This invention relates to the field of flue gas carbon capture energy consumption optimization technology, and more specifically, to a variable load flue gas carbon capture energy consumption optimization method based on model predictive control. Background Technology

[0002] With the continuous acceleration of industrialization, a large number of industrial emission sources, mainly based on fossil fuels, emit high concentrations of carbon dioxide, becoming a major contributor to the greenhouse effect. Carbon capture and storage (CCS) technology, as an important means of mitigating carbon emissions, has been widely studied and applied. In existing carbon capture technologies, flue gas carbon capture systems generally adopt absorption and separation methods under constant load, ignoring the dynamic response of the system caused by load fluctuations during industrial operation. This leads to problems such as low energy efficiency, uneven equipment load, and poor operational stability of carbon capture equipment under variable load operation.

[0003] The existing technology has the following shortcomings:

[0004] Currently, carbon capture systems typically operate with a fixed input power during flue gas capture, failing to dynamically sense and adapt to real-time changes in capture conditions. They also lack comprehensive modeling and optimized control of flue gas flow rate, carbon dioxide concentration, and equipment response parameters, resulting in prolonged periods of inefficient operation and high overall energy consumption. Therefore, a variable load flue gas carbon capture energy consumption optimization method based on model predictive control is proposed.

[0005] 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

[0006] To overcome the aforementioned deficiencies of the prior art, embodiments of the present invention provide a variable load flue gas carbon capture energy consumption optimization method based on model predictive control. This method solves the problems mentioned in the background art by employing a model predictive control mechanism that combines multiple sets of input power experimental analysis, flue gas carbon content ratio calculation, dynamic screening of capture power, and target power prediction and regulation.

[0007] To achieve the above objectives, the present invention provides the following technical solution: a method for optimizing the energy consumption of flue gas carbon capture under variable load based on model predictive control, comprising the following steps:

[0008] Step S1: Select multiple sets of different input power to input the flue gas capture system, set the detection time, and detect the flue gas flow rate and carbon dioxide concentration absorbed by the flue gas capture system under each set of input power within the detection time.

[0009] Step S2: Calculate the carbon content of flue gas under each group of input power based on carbon dioxide concentration, generate flue gas flow coefficient under each group of input power after standard processing of flue gas flow rate, and screen each group of input power to obtain candidate capture power based on the carbon content of flue gas.

[0010] Step S3: Set the input power range according to the candidate capture power, randomly set the capture power in each input power range, mark it, and input it to the flue gas capture system, and detect the vibration frequency of the capture equipment under each capture power.

[0011] Step S4: After sorting the capture power, calculate the power change of adjacent capture power and the vibration frequency change of the capture equipment. Combine the power change and the vibration frequency change of the capture equipment to select multiple target capture powers. Real-time detection of the heat information of the capture equipment, and select the target capture power based on the heat information.

[0012] In a preferred embodiment, in step S1, the input power range of the flue gas capture system in the historical database is called, multiple input powers are randomly set within the input power range and grouped, a period of time is selected as the detection time, and each group of input power is used as the input of the flue gas capture system in each detection time. The flow rate of the flue gas absorbed by the flue gas capture system under each group of input power is detected by the flow meter during the detection time.

[0013] A carbon dioxide sensor is used to detect the concentration of carbon dioxide absorbed by the flue gas capture system under each input power group. For each flue gas capture system under each input power group, the carbon dioxide concentration in the test environment where the flue gas capture system is located is detected before the detection time, and the carbon dioxide concentration in the test environment where the flue gas capture system is located is detected a second time after the detection time. The difference between the two detection results is taken as the concentration of carbon dioxide absorbed by the flue gas capture system under the corresponding input power group.

[0014] In a preferred embodiment, in step S2, in the test environment, the total concentration of gas in the test environment is detected by a gas composition analyzer, and the ratio of carbon dioxide concentration to total gas concentration is calculated to obtain the carbon content of flue gas under each group of input power.

[0015] By calling the historical flue gas flow database, the maximum and minimum historical flue gas flow values ​​are determined to construct a standardized reference range. The flue gas flow is then standardized to obtain the flue gas flow coefficient.

[0016] In a preferred embodiment, in step S2, the flue gas flow coefficient and the carbon content of the flue gas are substituted into the logistic regression calculation to obtain the input power screening score.

[0017] The input power screening score is compared with the preset screening threshold. If the input power screening score exceeds the screening threshold, the current input power group is marked as a candidate capture power.

[0018] If the input power screening score is lower than the screening threshold, the current input power group will be screened out.

[0019] In a preferred embodiment, in step S3, the candidate capture power values ​​are sorted in ascending order from smallest to largest to obtain the candidate capture power in ascending order. An interval between adjacent power values ​​is constructed based on the ascending order to form the input power interval corresponding to the candidate capture power.

[0020] In each input power range, the capture power is randomly set according to the segmented uniform random sampling rule, and the capture power is marked.

[0021] The capture power is input to the flue gas capture system as the capture power of the corresponding input power range.

[0022] In a preferred embodiment, in step S3, after the capture power is input to the flue gas capture system, the vibration frequency of the capture equipment under each capture power is detected.

[0023] The vibration frequency of the collection device is obtained by calculating the ratio of the number of mechanical vibrations collected by vibration sensors installed on the main body of the collection device within a set unit time to the unit time length.

[0024] In a preferred embodiment, in step S4, the capture power is sorted in ascending order of numerical value, and the difference between adjacent capture power values ​​is calculated and the absolute value is processed to obtain the power change of adjacent capture power.

[0025] The difference between the vibration frequencies of the capture equipment corresponding to adjacent capture powers is calculated and the absolute value is processed to obtain the change in the vibration frequency of the capture equipment for adjacent capture powers.

[0026] The power change and the vibration frequency change of the capture equipment are standardized.

[0027] The target power score is obtained by calculating the ratio between the standardized power change and the vibration frequency change of the capture equipment.

[0028] In a preferred embodiment, in step S4, the target power score is compared with a preset target threshold.

[0029] If the target power score exceeds the target threshold, the current capture power is marked as the target capture power;

[0030] If the target power score is lower than the target threshold, the current capture power will be filtered out.

[0031] In a preferred embodiment, in step S4, the surface temperature of the trapping device is detected in real time by a temperature sensor as the device's heat information.

[0032] The target capture power values ​​are sorted from largest to smallest and input into the flue gas capture system in that order. The maximum target capture power value is input first, and the surface temperature of the capture equipment is monitored in real time and compared with a preset heat threshold.

[0033] In a preferred embodiment, in step S4, if the surface temperature of the capture device exceeds the heat threshold, the capture device is waited to fall below the heat threshold before the next target capture power is input to the flue gas capture system.

[0034] If the surface temperature of the capture device at the next target capture power is lower than the heat threshold, then the current target capture power will be selected for operation.

[0035] If the surface temperature of the capture device at the next target capture power still exceeds the heat threshold, the target capture power will continue to be replaced until the minimum target capture power is reached.

[0036] If the surface temperature of the capture device with the minimum target capture power still exceeds the heat threshold, a message with an alarm message will be generated and sent to the visualization port.

[0037] The technical effects and advantages of this invention are as follows:

[0038] This invention optimizes flue gas carbon capture by selecting multiple sets of different input power to input into the flue gas capture system, setting a detection time, and detecting the flue gas flow rate and carbon dioxide concentration absorbed by the system under each set of input power within the detection time. After screening each set of input power, candidate capture power is obtained. Input power ranges are set according to the candidate capture power, and capture power is randomly set and marked within each input power range and input into the flue gas capture system. The vibration frequency of the capture equipment under each capture power is detected. After sorting the capture power, the power change of adjacent capture power and the vibration frequency change of the capture equipment are calculated. Multiple target capture power are selected by combining the power change and the vibration change of the capture equipment. The heat information of the capture equipment is detected in real time, and the target capture power is selected and input based on the heat information. This optimizes variable load flue gas carbon capture from the aspects of energy saving and efficiency improvement, realizing intelligent adjustment and dynamic optimal control of energy consumption in the carbon capture process. Attached Figure Description

[0039] Figure 1 This is a flowchart illustrating the implementation of the variable load flue gas carbon capture energy consumption optimization method based on model predictive control according to the present invention.

[0040] Figure 2 This is a schematic diagram illustrating the steps of the variable load flue gas carbon capture energy consumption optimization method based on model predictive control according to the present invention. Detailed Implementation

[0041] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0042] This invention optimizes variable-load flue gas carbon capture by selecting multiple sets of different input power to input into the flue gas capture system, setting a detection time, and detecting the flue gas flow rate and carbon dioxide concentration absorbed by the system under each set of input power within the detection time. After screening each set of input power, candidate capture power is obtained. Input power ranges are set according to the candidate capture power, and capture power is randomly set and marked within each input power range and input into the flue gas capture system. The vibration frequency of the capture equipment under each capture power is detected. After sorting the capture power, the power change of adjacent capture power and the vibration frequency change of the capture equipment are calculated. Multiple target capture power are selected by combining the power change and the vibration change of the capture equipment. The heat information of the capture equipment is detected in real time, and the target capture power is selected and input based on the heat information. This optimizes variable-load flue gas carbon capture from the aspects of energy saving and efficiency improvement.

[0043] Example 1

[0044] Please see Figures 1 to 2 The specific operation process of the variable load flue gas carbon capture energy consumption optimization method based on model predictive control is as follows:

[0045] Step S1: Select multiple sets of different input power to input the flue gas capture system, set the detection time, and detect the flue gas flow rate and carbon dioxide concentration absorbed by the flue gas capture system under each set of input power within the detection time.

[0046] Step S2: Calculate the carbon content of flue gas under each group of input power based on carbon dioxide concentration, generate flue gas flow coefficient under each group of input power after standard processing of flue gas flow rate, and screen each group of input power to obtain candidate capture power based on the carbon content of flue gas.

[0047] Step S3: Set the input power range according to the candidate capture power, randomly set the capture power in each input power range, mark it, and input it to the flue gas capture system, and detect the vibration frequency of the capture equipment under each capture power.

[0048] Step S4: After sorting the capture power, calculate the power change of adjacent capture power and the vibration frequency change of the capture equipment. Combine the power change and the vibration frequency change of the capture equipment to select multiple target capture powers. Real-time detection of the heat information of the capture equipment, and select the target capture power based on the heat information.

[0049] The specific implementation is as follows:

[0050] In step S1, the flue gas capture system is a system used to capture carbon dioxide from industrial emissions or combustion processes and prevent it from being released into the atmosphere. It operates after being powered on by a set input power to achieve the effect of capturing carbon dioxide.

[0051] Different input power levels affect the carbon capture efficiency and energy consumption of a flue gas capture system. Optimizing the input power can balance the carbon capture efficiency and energy consumption.

[0052] The input power range of the flue gas capture system is called from the historical database. Multiple input powers are randomly set within the input power range and grouped. A period of time is selected as the detection time. Each group of input power is used as the input of the flue gas capture system in each detection time. The flow rate of the flue gas absorbed by the flue gas capture system under each group of input power is detected by the flow meter during the detection time.

[0053] The flue gas flow rate is the amount of flue gas absorbed by the flue gas capture system within the detection time after it is started. The larger the amount of flue gas absorbed by the flue gas capture system within the detection time, the better its capture effect and the higher its capture efficiency.

[0054] A carbon dioxide sensor is used to detect the concentration of carbon dioxide absorbed by the flue gas capture system under each input power group. For each flue gas capture system under each input power group, the carbon dioxide concentration in the test environment where the flue gas capture system is located is detected before the detection time, and the carbon dioxide concentration in the test environment where the flue gas capture system is located is detected a second time after the detection time. The difference between the two detection results is taken as the concentration of carbon dioxide absorbed by the flue gas capture system under the corresponding input power group.

[0055] It should be explained that when using the above method to detect the carbon dioxide concentration in the test environment, the gas absorbed and treated by the flue gas capture system needs to be discharged from the test environment. This can be done by connecting a pipe to discharge the gas from the test environment, thus preventing the treated gas from still containing a small amount of carbon dioxide from returning to the test environment, thereby improving the accuracy of carbon dioxide concentration detection in the test environment.

[0056] The higher the concentration of carbon dioxide absorbed by the flue gas capture system within the detection time, the better its flue gas carbon capture effect and the higher its flue gas carbon capture efficiency.

[0057] It should be noted that a historical database refers to a database that stores and manages historical data. In this example, the historical database is the historical database of the flue gas capture system. The input power used by the flue gas capture system during a historical period is retrieved through the historical database, and the range between the maximum and minimum input power used during that period is used as the input power range. A flow meter is an instrument for measuring fluid flow rate and is used to detect the flue gas flow rate in the test environment. A carbon dioxide sensor is a device used to detect and measure the carbon dioxide concentration in the environment. In this example, it is used to detect the carbon dioxide concentration in the test environment before and after the detection time.

[0058] In step S2, in the test environment, the total concentration of gas in the test environment is detected by a gas composition analyzer, and the ratio of carbon dioxide concentration to total gas concentration is calculated to obtain the carbon content of flue gas under each input power.

[0059] Among them, a gas composition analyzer is a device used to detect the concentration of multiple gas components in a specific environment. It can collect and analyze the volume fraction of gases including but not limited to carbon dioxide, oxygen, nitrogen, carbon monoxide, sulfur dioxide, and methane in the test environment in real time. It uses devices such as infrared gas analyzers, mass spectrometers, or multi-channel gas detection modules. The specific equipment selection is determined by the experimenters based on the specific test environment scenario, and will not be elaborated here.

[0060] Furthermore, by calling the historical flue gas flow database, the maximum and minimum historical flue gas flow values ​​are determined to construct a standardized reference range and standardize the flue gas flow.

[0061] Specifically, the standardization process is based on a linear normalization method, which converts the flue gas flow rate into a dimensionless flue gas flow coefficient. The linear normalization method is as follows, and the specific formula is expressed below:

[0062] ;

[0063] In the formula, The flue gas flow rate is the input power. The flue gas flow coefficient is the value corresponding to the input power. This is the highest historical flue gas flow rate. This represents the historical minimum flue gas flow rate.

[0064] It should be noted that the flue gas flow history database refers to the database used to record, store, and retrieve flue gas flow data collected by the flue gas capture system under different operating cycles or different operating conditions, which will not be elaborated here;

[0065] Substituting the flue gas flow rate coefficient and the carbon content of the flue gas into the logistic regression calculation, the input power screening score is obtained. The specific formula is expressed as follows:

[0066] ;

[0067] In the formula, L is the result of logistic regression calculation, i.e., the input power screening score, e is the natural base, and y is the linear combination term of the logistic regression model, specifically set as follows:

[0068] ;

[0069] In the formula, For bias terms, The flue gas flow rate coefficient, The percentage of carbon in flue gas. as well as These are the regression coefficients for the flue gas flow rate coefficient and the carbon content of the flue gas, respectively.

[0070] It should be noted that when the flue gas flow rate coefficient and the carbon content of the flue gas are larger, it indicates that the flue gas capture system absorbs a higher total amount of flue gas and a higher proportion of carbon dioxide concentration within the detection time at the corresponding input power. In other words, the carbon capture effect corresponding to the input power is better. Therefore, the flue gas flow rate coefficient and the carbon content of the flue gas can be used as positive weighted indicators for fusion calculation. The larger the input power screening score, the stronger the comprehensive capture capability of the input power, and the more likely it is to be selected as a candidate capture power.

[0071] The input power screening score is compared with the preset screening threshold. If the input power screening score exceeds the screening threshold, the current input power group is marked as a candidate capture power.

[0072] If the input power screening score is lower than the screening threshold, the current input power group will be screened out.

[0073] It should be noted that the preset screening threshold was set by the researchers based on the statistical analysis results of historical capture efficiency distribution and the energy consumption control of the actual carbon capture system, and will not be elaborated here.

[0074] In step S3, the candidate capture power values ​​are sorted in ascending order from smallest to largest to obtain the candidate capture power in ascending order. Based on the ascending order, the interval between adjacent power values ​​is constructed to form the input power interval corresponding to the candidate capture power.

[0075] Specifically, the ascending sort format is denoted as:

[0076] ;

[0077] In the formula, Sort in ascending order, where n is the total number of candidate capture powers;

[0078] Furthermore, the input power range corresponding to the candidate capture power is denoted as follows:

[0079] ;

[0080] In the formula, For the k-th input power interval, For the k-th candidate capture power, The power of the (k+1)th candidate capture;

[0081] In each input power range, the capture power is randomly set according to the segmented uniform random sampling rule, and the capture power is marked.

[0082] Within each input power range, the capture power is generated according to a piecewise uniform random sampling rule. The specific calculation formula is as follows:

[0083] ;

[0084] In the formula, For capture power, The random coefficients are located in the input power range and are uniformly distributed in the interval 0-1.

[0085] The capture power is input to the flue gas capture system as the capture power of the corresponding input power range;

[0086] It should be noted that the piecewise uniform random sampling rule is a sampling method that randomly selects a representative value from a numerical interval based on a uniform probability distribution function. For the input power interval, the randomly selected sampling point is used as the capture power.

[0087] Furthermore, the capture power refers to the system operating power determined based on the input power and system load characteristics. It is the electrical power actually input into the flue gas capture system to drive the carbon capture reaction process. As can be understood by those skilled in the art, although power is a basic physical quantity, the capture power described in this embodiment needs to be clarified in conjunction with the characteristics of the electric drive system to avoid ambiguity in the terminology.

[0088] Furthermore, the input power range refers to the closed or half-open range constructed based on the power values ​​of adjacent candidate collections, which is used to limit the random sampling range. The specific selection of the closed or half-open range is determined by those in the field based on the number of sets and their corresponding power ranges. The researchers in this experiment need to understand that it is a real continuous range, not a discrete set, to avoid misunderstanding.

[0089] It should be noted that, in order to avoid confusion in power units and ambiguity in technical understanding, all power-related parameters (including input power, capture power, rated power, etc.) involved in this article are measured in a unified unit set by the researchers. This unit can be set to kilowatt or watt. The uniformity of the unit of measurement ensures that the power comparison, grouping, sorting and control operations in each step are carried out under a consistent measurement system.

[0090] After the capture power is input to the flue gas capture system, the vibration frequency of the capture equipment under each capture power is detected;

[0091] The vibration frequency of the capture device refers to the number of mechanical vibrations that occur in the structural components of the capture device within a set unit time under the condition of capture power drive. The acquisition logic is to calculate the vibration frequency of the capture device by comparing the number of mechanical vibrations collected by the vibration sensors installed on the capture device body within a set unit time with the unit time length.

[0092] It should be noted that structural components in the collection device refer to components that directly participate in the gas or liquid flow path during the collection process and generate a mechanical response due to the collection power. The specific components are selected by the researchers based on the physical properties of the collection medium, and will not be elaborated here.

[0093] Specifically, the unit time was determined by the researchers based on the data sampling rate and the system response characteristics, and will not be elaborated here.

[0094] Among them, the vibration sensor is a high-sensitivity miniature piezoelectric accelerometer that can accurately sense and record minute vibration changes of structural components. Its sensing signal is processed by the analog-to-digital conversion module and then input to the host computer for frequency calculation and state analysis.

[0095] In step S4, the capture power is sorted in ascending order of numerical value, and the difference between adjacent capture power values ​​is calculated and the absolute value is processed to obtain the power change of adjacent capture power.

[0096] Similarly, the difference between the vibration frequencies of the capture equipment corresponding to adjacent capture powers is calculated and the absolute value is processed to obtain the change in the vibration frequency of the capture equipment for adjacent capture powers.

[0097] The power change and the vibration frequency change of the capture equipment are standardized to keep them under the same dimension.

[0098] It should be noted that the standardization methods include, but are not limited to, standard linear transformation based on interval scaling, statistical Z-Score standardization method, or normalization method based on nonlinear mapping function. The application methods of standardization will not be elaborated here.

[0099] The target power score is obtained by calculating the ratio of the standardized power change to the vibration frequency change of the capture equipment.

[0100] The target power score is compared with the preset target threshold.

[0101] If the target power score exceeds the target threshold, the current capture power is marked as the target capture power;

[0102] If the target power score is lower than the target threshold, the current capture power will be filtered out.

[0103] It should be noted that the target threshold was set by the researchers based on the structural characteristics of the collection equipment and the stability requirements of the vibration frequency, and will not be elaborated here.

[0104] For example, five capture powers are set and ordered from largest to smallest, namely A capture power > B capture power > C capture power > D capture power > E capture power;

[0105] Then the power change of adjacent capture power is |A capture power - B capture power|, |B capture power - C capture power|, |C capture power - D capture power|, |D capture power - E capture power|. Similarly, the vibration frequency change of the capture equipment for adjacent capture power can be obtained.

[0106] The target power score is obtained by the power change of adjacent capture power and the vibration frequency change of the capture equipment of adjacent capture power. If the target power score corresponding to the capture power of A and B exceeds the target threshold, then the capture power of A and the capture power of B are marked as the target capture power. Similarly, if the target power score corresponding to the capture power of B and C exceeds the target threshold, then the capture power of C is added and marked as the target capture power.

[0107] The surface temperature of the capture device is detected in real time by a temperature sensor to obtain the device's heat information.

[0108] It should be noted that the temperature sensor is a high-response contact thermocouple sensor or infrared temperature sensor, which can meet the high-precision heat acquisition requirements under different working conditions. The specific temperature sensor was selected by the researchers based on the surface area of ​​the collection equipment and the temperature rise trend, and will not be elaborated here.

[0109] The target capture power values ​​are sorted from largest to smallest and input into the flue gas capture system in the order of sorting. The maximum value of the target capture power is input first, and the surface temperature of the capture equipment is detected in real time and compared with the preset heat threshold.

[0110] If the surface temperature of the capture device exceeds the heat threshold, wait for the capture device to fall below the heat threshold before inputting the next target capture power into the flue gas capture system.

[0111] If the surface temperature of the capture device at the next target capture power is lower than the heat threshold, then the current target capture power will be selected for operation.

[0112] If the surface temperature of the capture device at the next target capture power still exceeds the heat threshold, the target capture power will continue to be replaced until the minimum target capture power is reached.

[0113] If the surface temperature of the capture device with the minimum target capture power still exceeds the heat threshold, a message with an alarm message will be generated and sent to the visualization port.

[0114] The preset heat threshold was set by the researchers based on the heat capacity characteristics of the collection equipment and the critical temperature rise conditions required for long-term stable operation of the equipment, and will not be elaborated here.

[0115] It should be noted that the alarm information is displayed on the visual terminal interface in the form of warning text, graphics or a combination thereof, through highlighting, color change or icon flashing. The content includes words such as "over-temperature alarm" and "abnormal equipment capture power", which are used to remind the operator to pay attention to the current operating status of the capture equipment that has exceeded the set heat threshold range.

[0116] Finally, it should be noted that in this paper, relational terms such as first and second are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations.

[0117] Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0118] In this document, the singular forms “a,” “an,” and “the” may also include the plural forms unless the context clearly indicates otherwise. It should also be understood that terms such as “comprising / including” or “having” specify the presence of the stated features, integrals, steps, operations, components, parts, or combinations thereof, but do not preclude the possibility of the presence or addition of one or more other features, integrals, steps, operations, components, parts, or combinations thereof. Meanwhile, the term “and / or” as used in this specification includes any and all combinations of the associated listed items.

[0119] The various embodiments in this specification are described in a progressive manner. Each embodiment focuses on the differences from other embodiments. The various embodiments can be combined as needed, and the same or similar parts can be referred to each other.

[0120] The above description of the disclosed embodiments will enable those skilled in the art to make or use various modifications to these embodiments. It will be readily apparent to those skilled in the art that the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for optimizing the energy consumption of flue gas carbon capture under varying loads based on model predictive control, characterized in that: Includes the following steps: Step S1: Select multiple sets of different input power to input the flue gas capture system, set the detection time, and detect the flue gas flow rate and carbon dioxide concentration absorbed by the flue gas capture system under each set of input power within the detection time. Step S2: Calculate the carbon content of flue gas under each group of input power based on carbon dioxide concentration, generate flue gas flow coefficient under each group of input power after standard processing of flue gas flow rate, and screen each group of input power to obtain candidate capture power based on the carbon content of flue gas. In step S2, in the test environment, the total concentration of gas in the test environment is detected by a gas composition analyzer, and the ratio of carbon dioxide concentration to total gas concentration is calculated to obtain the carbon content of flue gas under each input power. By calling the historical flue gas flow database, the maximum and minimum historical flue gas flow values ​​are determined to construct a standardized reference range. The flue gas flow is then standardized to obtain the flue gas flow coefficient. Substitute the flue gas flow coefficient and the carbon content of the flue gas into the logistic regression calculation to obtain the input power screening score; The input power screening score is compared with the preset screening threshold. If the input power screening score exceeds the screening threshold, the current input power group is marked as a candidate capture power. If the input power screening score is lower than the screening threshold, the current input power group will be screened out. Step S3: Set the input power range according to the candidate capture power, randomly set the capture power in each input power range, mark it, and input it to the flue gas capture system, and detect the vibration frequency of the capture equipment under each capture power. Step S4: After sorting the capture power, calculate the power change of adjacent capture power and the vibration frequency change of the capture equipment. Combine the power change and the vibration frequency change of the capture equipment to filter out multiple target capture powers. Real-time detection of the heat information of the capture equipment, and select the target capture power based on the heat information. In step S4, the capture power is sorted in ascending order of numerical value, and the difference between adjacent capture power values ​​is calculated and the absolute value is processed to obtain the power change of adjacent capture power. The difference between the vibration frequencies of the capture equipment corresponding to adjacent capture powers is calculated and the absolute value is processed to obtain the change in the vibration frequency of the capture equipment for adjacent capture powers. The power change and the vibration frequency change of the capture equipment are standardized. The target power score is obtained by calculating the ratio between the standardized power change and the vibration frequency change of the capture equipment.

2. The method for optimizing the energy consumption of flue gas carbon capture based on model predictive control according to claim 1, characterized in that: In step S1, the input power range of the flue gas capture system in the historical database is called, multiple input powers are randomly set within the input power range and grouped, a period of time is selected as the detection time, and each group of input power is used as the input of the flue gas capture system in each detection time. The flow meter detects the flue gas flow rate absorbed by the flue gas capture system under each group of input power in the detection time. A carbon dioxide sensor is used to detect the concentration of carbon dioxide absorbed by the flue gas capture system under each input power group. For each flue gas capture system under each input power group, the carbon dioxide concentration in the test environment where the flue gas capture system is located is detected before the detection time, and the carbon dioxide concentration in the test environment where the flue gas capture system is located is detected a second time after the detection time. The difference between the two detection results is taken as the concentration of carbon dioxide absorbed by the flue gas capture system under the corresponding input power group.

3. The method for optimizing the energy consumption of flue gas carbon capture based on model predictive control according to claim 1, characterized in that: In step S3, the candidate capture power values ​​are sorted in ascending order from smallest to largest to obtain the candidate capture power in ascending order. Based on the ascending order, the interval between adjacent power values ​​is constructed to form the input power interval corresponding to the candidate capture power. In each input power range, the capture power is randomly set according to the segmented uniform random sampling rule, and the capture power is marked. The capture power is input to the flue gas capture system as the capture power of the corresponding input power range.

4. The method for optimizing the energy consumption of flue gas carbon capture based on model predictive control according to claim 3, characterized in that: In step S3, after the capture power is input to the flue gas capture system, the vibration frequency of the capture equipment under each capture power is detected. The vibration frequency of the collection device is obtained by calculating the ratio of the number of mechanical vibrations collected by vibration sensors installed on the main body of the collection device within a set unit time to the unit time length.

5. The method for optimizing the energy consumption of flue gas carbon capture based on model predictive control according to claim 1, characterized in that: In step S4, the target power score is compared with a preset target threshold. If the target power score exceeds the target threshold, the current capture power is marked as the target capture power; If the target power score is lower than the target threshold, the current capture power will be filtered out.

6. The method for optimizing the energy consumption of flue gas carbon capture based on model predictive control according to claim 1, characterized in that: In step S4, the surface temperature of the capture device is detected in real time by a temperature sensor as the heat information of the device; The target capture power values ​​are sorted from largest to smallest and input into the flue gas capture system in that order. The maximum target capture power value is input first, and the surface temperature of the capture equipment is monitored in real time and compared with a preset heat threshold.

7. The method for optimizing the energy consumption of flue gas carbon capture based on model predictive control according to claim 6, characterized in that: In step S4, if the surface temperature of the capture device exceeds the heat threshold, wait for the capture device to fall below the heat threshold before inputting the next target capture power to the flue gas capture system. If the surface temperature of the capture device at the next target capture power is lower than the heat threshold, then the current target capture power will be selected for operation. If the surface temperature of the capture device at the next target capture power still exceeds the heat threshold, the target capture power will continue to be replaced until the minimum target capture power is reached. If the surface temperature of the capture device with the minimum target capture power still exceeds the heat threshold, a message with an alarm message will be generated and sent to the visualization port.

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