Carbon neutralization energy optimization emission monitoring device

Abstract

The invention discloses a carbon neutralization energy optimization emission monitoring device, which is used in the technical field of carbon emission monitoring, and comprises a monitoring box; an intake pipe; an air outlet pipe; the control end is arranged at one end of the monitoring box; the fan is inserted into the top end of the monitoring box; the first partition plate is arranged at the inner top of the monitoring box; the second partition plate is arranged at the inner bottom of the monitoring box; the plurality of non-dispersive infrared sensors are respectively arranged at the top end and the bottom end of the inner side wall of the monitoring box; the cylinders are arranged at the top ends of the first partition plates; the filter screen bag is inserted between the first partition plate and the second partition plate; the sweeping mechanism is arranged at the bottom ends of the air cylinders; the reaction box is arranged at the top end of the inner bottom of the monitoring box; the ultrasonic sensor is arranged on the inner side wall of the reaction box. Dust gathered on the filter screen bag is cleaned in time, and the monitoring efficiency of the monitoring device is improved; and meanwhile, a complete carbon neutralization optimization chain of real-time monitoring, accurate kernel, notch prediction and dynamic regulation is formed.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of carbon emission monitoring, in particular, to a carbon neutral energy optimized emission monitoring device. BACKGROUND

[0002] Carbon neutral refers to the total amount of carbon dioxide emitted by an entity within a certain period of time being equal to the total amount of carbon dioxide removed or offset by various means such as afforestation, carbon capture technology, etc., so as to achieve net zero carbon emissions. Carbon neutral is an important strategy to combat climate change, aiming to reduce greenhouse gas emissions and slow down the trend of global warming.

[0003] Carbon neutral requires monitoring devices to accurately quantify carbon emissions, track emission reduction progress, and ensure compliance with environmental regulations. However, existing monitoring devices have the disadvantage of insufficient accuracy. Dust or harmful particulate matter is mixed in the gas to be measured, which cannot guarantee the accuracy of the environmental quality record monitoring device, resulting in insufficient gas density during monitoring, leading to inaccurate monitoring results or even no monitoring results.

[0004] The existing monitoring device has the disadvantage of being unable to form a complete carbon neutral optimization chain of real-time monitoring → accurate calculation → gap prediction → dynamic regulation.

[0005] At present, there is no effective solution to the problems in the related art. SUMMARY

[0006] In view of the problems in the related art, the present application aims to propose a carbon neutral energy optimized emission monitoring device to overcome the above technical problems existing in the prior art.

[0007] To this end, the specific technical scheme adopted by the present application is as follows:

[0008] A carbon neutral energy optimized emission monitoring device, comprising: a monitoring box; an air inlet pipe arranged at one side of the top end of the monitoring box; an air outlet pipe arranged at the other side of the bottom end of the monitoring box; a control end arranged at one end of the monitoring box; a fan arranged at the top end of the monitoring box; a first partition plate arranged at the inner top of the monitoring box; a second partition plate arranged at the inner bottom of the monitoring box; a plurality of non-dispersive infrared sensors arranged at the inner side wall top end and the inner side wall bottom end of the monitoring box, respectively; a plurality of air cylinders arranged at the top end of the first partition plate; a filter bag arranged between the first partition plate and the second partition plate and cooperating with the fan; a cleaning mechanism arranged at the bottom end of the plurality of air cylinders for cleaning the filter bag; a reaction box arranged at the inner bottom top end of the monitoring box; and an ultrasonic sensor arranged at the inner side wall of the reaction box.

[0009] Further, a liquid inlet pipe is arranged at the bottom end of one side of the monitoring box, and a liquid outlet pipe is arranged at the bottom end of the other side of the monitoring box; the liquid inlet pipe and the liquid outlet pipe both penetrate the reaction box and extend into the interior of the reaction box, and the outer sides of the liquid inlet pipe, the liquid outlet pipe, the gas inlet pipe and the gas outlet pipe are all provided with electromagnetic valves.

[0010] Further, the cleaning mechanism comprises a support plate arranged at the bottom end of the output end of the plurality of cylinders, a motor is arranged at the bottom end of the support plate, a first pulley is arranged at the output end of the motor and penetrates the support plate, two groups of first belts are sequentially arranged at the outer side of the first pulley, a second pulley is arranged at the other end of the first belts, and a third pulley is arranged at the outer side of the second pulley through a second belt; a clamping rotating wheel is arranged at one side of the second pulley and the third pulley and penetrates the support plate, a rotating ring is arranged in the clamping rotating wheel, a plurality of cleaning wheels are arranged at one side of the rotating ring, and the plurality of cleaning wheels are matched with the filter screen bag.

[0011] Further, the control end is embedded with a data acquisition module, a carbon emission calculation module, a carbon neutralization calculation module, a carbon neutralization prediction module and a closed-loop optimization control module.

[0012] The data acquisition module is used to acquire carbon emission data and carbon neutralization data.

[0013] The carbon emission calculation module is used to calculate the actual carbon emission amount by using a temperature dynamic compensation algorithm and combining the carbon emission data.

[0014] The carbon neutralization calculation module is used to calculate the actual carbon neutralization amount according to a temperature dynamic compensation algorithm and combining the carbon neutralization data.

[0015] The carbon neutralization prediction module is used to construct and train an autoregressive integrated moving average model based on the data acquisition module to obtain a carbon neutralization prediction model; and the carbon neutralization prediction model is used to obtain the required carbon neutralization amount in combination with the actual carbon emission amount obtained by the carbon emission calculation module.

[0016] The closed-loop optimization control module is used to compare the actual carbon neutralization amount with the required carbon neutralization amount, and control and optimize the monitoring box according to the comparison result.

[0017] Further, the data acquisition module comprises a gas flow acquisition sub-module, a carbon concentration acquisition sub-module and an absorbent state acquisition sub-module.

[0018] The gas flow acquisition sub-module is used to acquire gas flow data of the fan.

[0019] The carbon concentration acquisition sub-module is used to acquire inlet carbon concentration data and outlet carbon concentration data by using a plurality of non-dispersive infrared sensors.

[0020] The absorbent state acquisition sub-module is used to acquire absorbent precipitation state data in the reaction box based on an ultrasonic sensor.

[0021] The carbon emission data includes gas flow data, inlet carbon concentration data, and indirect emission data of the equipment, and the carbon neutralization data includes inlet carbon concentration data, outlet carbon concentration data, absorbent precipitation state data, and indirect carbon offset data.

[0022] Further, the actual carbon emission amount is calculated by using a temperature dynamic compensation algorithm and combining the carbon emission data, including:

[0023] The inlet carbon concentration data in the carbon neutralization data is optimized by using the temperature dynamic compensation algorithm;

[0024] The gas flow data and the optimized inlet carbon concentration data are standardized;

[0025] Based on the density conversion coefficient and the carbon conversion coefficient, and combining the standardized carbon emission data, the direct carbon emission amount is calculated;

[0026] Based on the motor energy consumption and the grid carbon intensity in the indirect emission data of the equipment, the indirect carbon emission amount is calculated;

[0027] The actual carbon emission amount is obtained by integrating the direct carbon emission amount and the indirect carbon emission amount.

[0028] Further, the actual carbon neutralization amount is calculated according to the temperature dynamic compensation algorithm and combining the carbon neutralization data, including:

[0029] The inlet carbon concentration data and the outlet carbon concentration data in the carbon neutralization data are optimized by using the temperature dynamic compensation algorithm;

[0030] The carbon absorption amount is calculated based on the optimized inlet carbon concentration data and the outlet carbon concentration data;

[0031] The carbon absorption real-time efficiency is calculated according to the absorbent precipitation state data in the carbon neutralization data;

[0032] The direct carbon neutralization amount is calculated by using the carbon absorption amount and the carbon absorption real-time efficiency;

[0033] The indirect carbon neutralization amount is obtained based on the carbon credit of the carbon neutralization data and combining the time ratio;

[0034] The actual carbon neutralization amount is obtained by integrating the direct carbon neutralization amount and the indirect carbon neutralization amount.

[0035] Further, based on the data acquisition module, an autoregressive integrated moving average model is constructed and trained to obtain a carbon neutralization prediction model; the demand carbon neutralization amount is obtained by using the carbon neutralization prediction model and combining the actual carbon emission amount obtained by the carbon emission calculation module, including:

[0036] Based on the data acquisition module, historical carbon emission data and carbon neutralization data are obtained;

[0037] The autoregressive integrated moving average model is constructed and trained by using historical carbon emission data and carbon neutralization data to obtain a carbon neutralization prediction model.

[0038] According to the actual carbon emission amount obtained by the carbon emission calculation module, and in combination with the carbon neutralization prediction model, the required carbon neutralization amount is obtained.

[0039] Further, the autoregressive integrated moving average model is constructed and trained by using historical carbon emission data and carbon neutralization data to obtain a carbon neutralization prediction model, which includes:

[0040] The time series of the historical carbon emission data and the carbon neutralization data are subjected to stationarity test by using a statistical test method, and the time series of the historical carbon emission data and the carbon neutralization data are optimized by using difference processing;

[0041] According to the autocorrelation function graph and the partial autocorrelation function graph, and in combination with the information criterion, the optimal parameters are determined to construct the autoregressive integrated moving average model;

[0042] Based on the optimized historical carbon emission data and the carbon neutralization data, the autoregressive integrated moving average model is trained, and the trained autoregressive integrated moving average model is subjected to cross-validation to obtain the carbon neutralization prediction model.

[0043] Compared with the prior art, the present application has the following beneficial effects:

[0044] 1、The carbon neutralization energy optimization emission monitoring device in the application can ensure that the dust accumulated on the filter bag is cleaned in time under the action of the cleaning mechanism, prevent the dust from affecting the monitoring efficiency of the carbon neutralization energy optimization emission monitoring device, and also prevent the dust from affecting the filtering effect of the filter bag.

[0045] 2、The carbon neutralization energy optimization emission monitoring device in the application integrates five core modules, i.e., a data acquisition module, a carbon emission calculation module, a carbon neutralization calculation module, a carbon neutralization prediction module, and a closed-loop optimization control module, under the action of the control end, to finally form a complete carbon neutralization optimization chain of real-time monitoring→accurate calculation→gap prediction→dynamic regulation. BRIEF DESCRIPTION OF DRAWINGS

[0046] The above characteristics, features and advantages of the present application and the implementation methods and means thereof will become more apparent and understandable in combination with the following description of the embodiments, which are described in detail in conjunction with the drawings. Herein, the following are schematically shown:

[0047] Figure 1 is a structural schematic view of a carbon neutralization energy optimization emission monitoring device according to an embodiment of the present application;

[0048] Figure 2 is a sectional schematic view of a carbon neutralization energy optimization emission monitoring device according to an embodiment of the present application;

[0049] Figure 3 is a structural schematic view of a cleaning structure in a carbon neutral energy optimization emission monitoring device according to an embodiment of the application;

[0050] Figure 4 is a structural schematic view of a cleaning structure in a carbon neutral energy optimization emission monitoring device according to an embodiment of the application;

[0051] Figure 5 is a principle block diagram of a control end in a carbon neutral energy optimization emission monitoring device according to an embodiment of the application.

[0052] In the figure:

[0053] 1, monitoring box; 2, air inlet pipe; 3, air outlet pipe; 4, control end; 5, fan; 6, first partition; 7, second partition; 8, non-dispersive infrared sensor; 9, air cylinder; 10, filter bag; 11, cleaning mechanism; 1101, support plate; 1102, motor; 1103, first belt pulley; 1104, first belt; 1105, second belt pulley; 1106, second belt; 1107, third belt pulley; 1108, clamping rotating wheel; 1109, rotating ring; 1110, cleaning wheel; 12, reaction box; 13, ultrasonic sensor; 14, liquid inlet pipe; 15, liquid outlet pipe; 16, electromagnetic valve; 17, data acquisition module; 18, carbon emission calculation module; 19, carbon neutralization calculation module; 20, carbon neutralization prediction module; 21, closed-loop optimization control module. DETAILED DESCRIPTION

[0054] In order to enable persons skilled in the art to better understand the schemes of the present application, the technical schemes in the embodiments of the present application will be clearly and completely described below in combination with the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by persons skilled in the art without creative labor fall within the scope of protection of the present application.

[0055] According to an embodiment of the present application, a carbon neutral energy optimization emission monitoring device is provided.

[0056] The present application will be further described in combination with the drawings and specific embodiments. Figures 1-5As shown, the carbon neutral energy optimization emission monitoring device according to the embodiment of the application comprises: a monitoring box 1; an air inlet pipe 2 arranged at one side of the top end of the monitoring box 1; an air outlet pipe 3 arranged at the other side of the bottom end of the monitoring box 1; a control end 4 arranged at one end of the monitoring box 1; a fan 5 arranged at the top end of the monitoring box 1; a first partition plate 6 arranged at the inner top of the monitoring box 1; a second partition plate 7 arranged at the inner bottom of the monitoring box 1; a plurality of non-dispersive infrared sensors 8 arranged at the inner side wall top end and the inner side wall bottom end of the monitoring box 1 respectively; a plurality of air cylinders 9 arranged at the top end of the first partition plate 6; a filter bag 10 arranged between the first partition plate 6 and the second partition plate 7 and matched with the fan 5; a cleaning mechanism 11 arranged at the bottom end of the plurality of air cylinders 9 and used for cleaning the filter bag 10; a reaction box 12 arranged at the inner bottom top end of the monitoring box 1; and an ultrasonic sensor 13 arranged at the inner side wall of the reaction box 12.

[0057] It needs to be explained that, under the action of the cleaning mechanism 11, the carbon neutral energy optimization emission monitoring device can ensure that the dust accumulated on the filter bag 10 is cleaned in time, so as to prevent the dust accumulation from affecting the monitoring efficiency of the carbon neutral energy optimization emission monitoring device and also prevent the dust accumulation from affecting the filtering effect of the filter bag 10.

[0058] In the optional embodiment, a liquid inlet pipe 14 is arranged at one side of the bottom end of the monitoring box 1, and a liquid outlet pipe 15 is arranged at the other side of the bottom end of the monitoring box 1; the liquid inlet pipe 14 and the liquid outlet pipe 15 both penetrate the reaction box 12 and extend into the interior of the reaction box 12, and the outer sides of the liquid inlet pipe 14, the liquid outlet pipe 15, the air inlet pipe 2 and the air outlet pipe 3 are all provided with electromagnetic valves 16.

[0059] It needs to be explained that, the electromagnetic valve 16 is usually composed of an electromagnetic coil, a valve body, a valve core, a spring, a sealing element and a port; the electromagnetic coil is the core component of the electromagnetic valve, generates a magnetic field after being electrified, and attracts or releases the valve core; the electromagnetic coil is the power source for controlling the opening and closing of the electromagnetic valve; the valve body is the shell of the electromagnetic valve, usually made of metal or plastic material, and contains a fluid channel and a valve seat in the interior; the valve core is the moving part in the interior of the electromagnetic valve, responsible for opening or closing the fluid channel; the spring is used for keeping the valve core in the default position in the unenergized state, usually the closed position, and the valve core is attracted after the electromagnetic coil is electrified, overcomes the force of the spring, and opens the fluid channel; the sealing element includes an O-ring, a gasket and the like, ensures the sealing between the valve body and the valve core, and prevents fluid leakage; the port is used for connecting the pipeline and controlling the inlet and outlet of the fluid; the electromagnetic valve 16 is electrically connected between the control end 4, and the working principle and structure of the electromagnetic valve 16 are prior art, which will not be described in detail here.

[0060] The reaction box 12 can optionally introduce calcium hydroxide suspension (Ca(OH)2) through the liquid inlet pipe 14, and the calcium hydroxide suspension reacts with carbon dioxide (CO2) to generate calcium carbonate (CaCO3) precipitate with high density (2.7 g / cm3).3 ), which is monitored by the ultrasonic sensor 13.

[0061] In this optional embodiment, the cleaning mechanism 11 comprises a support plate 1101 arranged at the bottom end of the output end of the plurality of cylinders 9, and the bottom end of the support plate 1101 is provided with a motor 1102. The output end of the motor 1102 is provided with a first pulley 1103 penetrating through the support plate 1101. The outer side of the first pulley 1103 is sequentially provided with two groups of first belts 1104. The other end of the first belts 1104 is provided with a second pulley 1105. The outer side of the second pulley 1105 is provided with a third pulley 1107 through a second belt 1106. The second pulley 1105 and one side of the third pulley 1107 are provided with a clamping rotating wheel 1108 penetrating through the support plate 1101. The inside of the clamping rotating wheel 1108 is provided with a rotating ring 1109. One side of the rotating ring 1109 is provided with a plurality of cleaning wheels 1110, which are matched with the filter bag 10, so as to ensure the timely cleaning of the dust accumulated on the filter bag 10, prevent the dust accumulation from affecting the monitoring efficiency of the carbon neutralization energy optimization emission monitoring device, and also prevent the influence on the filtering effect of the filter bag 10.

[0062] It should be explained that the working principle of the cleaning mechanism 11 is as follows: under the action of the control end 4, the motor 1102 is controlled and started. Under the action of the output shaft of the motor 1102, the first pulley 1103 is driven to rotate. Under the action of the first belt 1104, the two groups of second pulleys 1105 are driven to rotate in the process of the first pulley 1103. Under the action of the second belt 1106, the third pulley 1107 is driven to rotate in the process of the two groups of second pulleys 1105, and four groups of clamping rotating wheels 1108 are driven to rotate. The rotating ring 1109 is driven to rotate in the process of the four groups of clamping rotating wheels 1108. The cleaning wheel 1110 is driven to rotate in the process of the rotating ring 1109. The cleaning wheel 1110 is attached to the filter bag 10 and rotates to clean the filter bag 10. The dust falls on the second partition plate 7. The operator can open the door of the monitoring box 1 regularly to clean and collect the dust on the second partition plate 7.

[0063] In this optional embodiment, the control end 4 is embedded with a data acquisition module 17, a carbon emission calculation module 18, a carbon neutralization calculation module 19, a carbon neutralization prediction module 20, and a closed-loop optimization control module 21.

[0064] The data acquisition module 17 is used to acquire carbon emission data and carbon neutralization data.

[0065] The carbon emission calculation module 18 is used to calculate the actual carbon emission amount by using a temperature dynamic compensation algorithm and combining the carbon emission data.

[0066] The carbon neutralization calculation module 19 is configured to calculate the actual carbon neutralization amount according to a temperature dynamic compensation algorithm and in combination with carbon neutralization data.

[0067] The carbon neutralization prediction module 20 is configured to construct and train an autoregressive integrated moving average model based on the data acquisition module 17 to obtain a carbon neutralization prediction model, and obtain the required carbon neutralization amount by using the carbon neutralization prediction model and in combination with the actual carbon emission amount obtained by the carbon emission calculation module 18.

[0068] The closed-loop optimization control module 21 is configured to compare the actual carbon neutralization amount and the required carbon neutralization amount, and control and optimize the monitoring box 1 according to the comparison result.

[0069] It should be explained that, under the action of the control end 4, the five core modules of the data acquisition module, the carbon emission calculation module, the carbon neutralization calculation module, the carbon neutralization prediction module and the closed-loop optimization control module are integrated to finally form a complete carbon neutralization optimization chain of real-time monitoring→accurate calculation→gap prediction→dynamic regulation.

[0070] The comparison of the actual carbon neutralization amount and the required carbon neutralization amount and the control and optimization of the monitoring box 1 according to the comparison result include the following cases.

[0071] When the actual carbon neutralization amount is greater than the required carbon neutralization amount, the control end 4 controls and reduces the rotating speed of the fan 5; when the actual carbon neutralization amount is greater than the required carbon neutralization amount, the control end 4 controls and starts the electromagnetic valve 16 of the liquid inlet pipe 14 to make the liquid inlet pipe 14 inject the absorbent under pressure; when the absorption efficiency continues to decrease, the control end 4 controls and starts the cleaning mechanism 11 to clean the filter bag 10.

[0072] In this optional embodiment, the data acquisition module 17 includes a gas flow acquisition sub-module, a carbon concentration acquisition sub-module and an absorbent state acquisition sub-module.

[0073] The gas flow acquisition sub-module is configured to acquire the gas flow data of the fan 5.

[0074] It should be explained that the sensors on the fan 5 are not shown in the figure.

[0075] The carbon concentration acquisition sub-module is configured to acquire the inlet carbon concentration data and the outlet carbon concentration data by using a plurality of non-dispersive infrared sensors 8.

[0076] The absorbent state acquisition sub-module is configured to acquire the absorbent precipitation state data in the reaction box 12 based on an ultrasonic sensor 13.

[0077] The carbon emission data includes the gas flow data, the inlet carbon concentration data and the indirect emission data of the equipment, and the carbon neutralization data includes the inlet carbon concentration data, the outlet carbon concentration data, the absorbent precipitation state data and the indirect carbon offset data.

[0078] In this optional embodiment, the actual carbon emission amount is calculated by using a temperature dynamic compensation algorithm and combining carbon emission data, which includes:

[0079] The inlet carbon concentration data in the carbon neutralization data is optimized by using the temperature dynamic compensation algorithm;

[0080] The gas flow data and the optimized inlet carbon concentration data are standardized;

[0081] Based on the density conversion coefficient and the carbon conversion coefficient, and combining the standardized carbon emission data, the direct carbon emission amount is calculated;

[0082] Based on the motor energy consumption and the power grid carbon intensity in the indirect emission data of the equipment, the indirect carbon emission amount is calculated;

[0083] The actual carbon emission amount is obtained by integrating the direct carbon emission amount and the indirect carbon emission amount.

[0084] It needs to be explained that the carbon emission calculation module 18 integrates double data sources of direct emission monitoring and indirect energy consumption. Based on the internal temperature T chamber of the monitoring box 1, the inlet carbon concentration data in the carbon neutralization data is optimized, and the optimization process is expressed by the formula:

[0085]

[0086] In the formula, T chamber represents the internal temperature of the monitoring box 1; represents the inlet carbon concentration data; 0.003 represents the typical infrared sensor temperature coefficient (% / ℃); C 入corrected represents the optimized inlet carbon concentration data.

[0087] The gas flow data and the optimized inlet carbon concentration data are standardized, the measured flow is converted into dry basis flow under standard conditions (0℃, 101.325kPa), the influence of temperature and pressure fluctuations is eliminated, and the CO2 concentration unit is standardized and converted.

[0088] Based on the density conversion coefficient and the carbon conversion coefficient, and combining the standardized carbon emission data, the direct carbon emission amount is calculated, and the process calculation formula is:

[0089]

[0090] In the formula, represents the density conversion coefficient, the CO2 density under standard conditions = 1.977 kg / m 3 (constant); C represents the density conversion coefficient, the carbon conversion coefficient, the mass proportion of carbon in CO2(12gC / 44gCO2); Δt represents the time interval(unit: hour); E direct represents the direct carbon emission; C 入corrected(％) represents the normalized inlet carbon concentration data; Q std represents the normalized gas flow data.

[0091] The marginal carbon intensity of the power grid is obtained(e.g., the East China power grid in 2023, EF=0.581 kgCO2e / kWh), and the indirect carbon emission is calculated based on the motor energy consumption in the indirect emission data and the carbon intensity of the power grid; the actual carbon emission is obtained by integrating the direct carbon emission and the indirect carbon emission.

[0092] In this optional embodiment, the actual carbon neutralization amount is calculated according to the temperature dynamic compensation algorithm and combined with the carbon neutralization data, which includes:

[0093] The inlet carbon concentration data and the outlet carbon concentration data in the carbon neutralization data are optimized by using the temperature dynamic compensation algorithm;

[0094] The carbon absorption amount is calculated based on the optimized inlet carbon concentration data and the outlet carbon concentration data;

[0095] The carbon absorption real-time efficiency is calculated according to the absorbent precipitation state data in the carbon neutralization data;

[0096] The direct carbon neutralization amount is calculated by using the carbon absorption amount and the carbon absorption real-time efficiency;

[0097] The indirect carbon neutralization amount is obtained based on the carbon credit of the carbon neutralization data and combined with the time proportion;

[0098] The actual carbon neutralization amount is obtained by integrating the direct carbon neutralization amount and the indirect carbon neutralization amount.

[0099] It needs to be explained that the carbon neutralization calculation module 19 performs carbon neutralization by quantifying the amount of CO2 absorbed by the device itself(direct offset) and the amount of external carbon credit(indirect offset). The inlet carbon concentration data and the outlet carbon concentration data in the carbon neutralization data are optimized by using the temperature dynamic compensation algorithm, and the carbon absorption amount is calculated based on the optimized inlet carbon concentration data and the outlet carbon concentration data. The calculation formula of the carbon absorption amount is:

[0100]

[0101] In the formula, C in , C out respectively represent the optimized inlet / outlet CO2 concentration(ppm); represents the density conversion coefficient, the density of CO2 under standard conditions=1.977 kg / m 3 (constant); Mabsortheoryl represents the carbon absorption amount; and Δt represents the time interval (unit: hour).

[0102] Based on the thickness h of the precipitate monitored by the ultrasonic sensor 13 sludge and the type of the absorbent, the real-time efficiency of carbon absorption is calculated, and the direct carbon neutralization amount is calculated using the carbon absorption amount and the real-time efficiency of carbon absorption, with the calculation formula being:

[0103] M absorbreal = M absorbtheory × η abs ;

[0104] In the formula, M absorbreal represents the direct carbon neutralization amount; M absortheoryl represents the carbon absorption amount; and η abs represents the real-time efficiency of carbon absorption.

[0105] The indirect carbon neutralization amount is obtained by unifying different sources of carbon credits into CO2 equivalents and proportionally distributing the periodically input credit amount according to time; and the actual carbon neutralization amount is obtained by integrating the direct carbon neutralization amount and the indirect carbon neutralization amount.

[0106] In this optional embodiment, based on the data acquisition module 17, an autoregressive integrated moving average model is constructed and trained to obtain a carbon neutralization prediction model; and the demand carbon neutralization amount is obtained using the carbon neutralization prediction model and the actual carbon emission amount obtained by the carbon emission calculation module 18, including:

[0107] Based on the data acquisition module 17, historical carbon emission data and carbon neutralization data are obtained;

[0108] Using the historical carbon emission data and carbon neutralization data, an autoregressive integrated moving average model is constructed and trained to obtain a carbon neutralization prediction model;

[0109] According to the actual carbon emission amount obtained by the carbon emission calculation module 18 and in combination with the carbon neutralization prediction model, the demand carbon neutralization amount is obtained.

[0110] In this optional embodiment, using the historical carbon emission data and carbon neutralization data, an autoregressive integrated moving average model is constructed and trained to obtain a carbon neutralization prediction model, including:

[0111] Using statistical test methods, the time series of the historical carbon emission data and carbon neutralization data are tested for stationarity, and the time series of the historical carbon emission data and carbon neutralization data are optimized using difference processing;

[0112] According to the autocorrelation function graph and the partial autocorrelation function graph and in combination with information criteria, the optimal parameters are determined to construct an autoregressive integrated moving average model;

[0113] Based on the optimized historical carbon emission data and carbon neutralization data, an autoregressive integrated moving average model is trained, and the trained autoregressive integrated moving average model is cross-validated to obtain a carbon neutralization prediction model.

[0114] It should be explained that the carbon neutralization prediction module predicts the emission and offset curve in the next one hour based on the ARIMA model (i.e., autoregressive integrated moving average model), and the specific steps are as follows:

[0115] 1. Data collection and preprocessing.

[0116] The historical carbon emission data and carbon neutralization data are obtained from the data acquisition module 17. These data usually include time series information and need to be cleaned to remove outliers and fill in missing data.

[0117] 2. Stationarity test.

[0118] Use statistical test methods (such as ADF test) to determine whether the time series data is stationary. If the data is not stationary, make it stationary through difference processing.

[0119] 3. Determine model parameters.

[0120] The ARIMA model consists of three parameters: p (number of autoregressive terms), d (number of differences) and q (number of moving average terms). By observing the autocorrelation function (ACF) and partial autocorrelation function (PACF) graphs, combined with information criteria, select appropriate parameters.

[0121] 4. Train the model.

[0122] Use the determined p, d, q parameters to build an ARIMA model. Train the model with historical data and adjust the model parameters to minimize errors.

[0123] 5. Model validation.

[0124] Use the hold-out dataset to validate the predictive ability of the model. Evaluate the model performance by calculating the prediction error (such as mean square error), and adjust the parameters if necessary.

[0125] 6. Future prediction.

[0126] Based on the fitted ARIMA model, the carbon emissions and carbon neutralization in the next one hour are predicted. Generate a prediction curve to provide future trend analysis.

[0127] In order to facilitate the understanding of the above technical solutions of the present application, the working principle or operation mode of the present application in the actual process will be described in detail.

[0128] In actual application, the operator places the monitoring device at the position to be monitored, and the exhaust gas enters the inside of the monitoring box 1 from the air inlet pipe 2. Under the action of the control end 4, the fan 5 is controlled and started to blow the exhaust gas to the filter bag 10. Through the action of the filter bag 10, the filtered exhaust gas is guided to the reaction box 12. The reaction box 12 can selectively introduce calcium hydroxide suspension (Ca(OH)2) through the liquid inlet pipe 14. The calcium hydroxide suspension reacts with carbon dioxide (CO2) in the exhaust gas to generate calcium carbonate (CaCO3) precipitate, realizing carbon neutralization. At the same time, the data acquisition module 17 collects carbon emission data and carbon neutralization data during the monitoring process. The carbon emission calculation module 18 calculates the actual carbon emission amount, the carbon neutralization calculation module 19 calculates the actual carbon neutralization amount, the carbon neutralization prediction module 20 predicts the required carbon neutralization amount, and based on the comparison result of the actual carbon neutralization amount and the required carbon neutralization amount, the closed-loop optimization control module 21 controls and optimizes the monitoring box 1.

[0129] In summary, with the above technical solutions of the present application, under the action of the cleaning mechanism, the dust accumulated on the filter bag is cleaned in time to prevent the dust accumulation from affecting the monitoring efficiency of the carbon neutralization energy optimization emission monitoring device and affecting the filtering effect of the filter bag. Under the action of the control end, the five core modules of the data acquisition module, the carbon emission calculation module, the carbon neutralization calculation module, the carbon neutralization prediction module and the closed-loop optimization control module are integrated to finally form a complete carbon neutralization optimization chain of real-time monitoring→ accurate calculation→ gap prediction→ dynamic regulation.

[0130] Although the present application has been disclosed as above with preferred embodiments, the embodiments are only for illustration and do not limit the present application. Those skilled in the art can make some changes and modifications without departing from the spirit and scope of the present application. The protection scope of the present application should be subject to the description of the claims.

Claims

1. A carbon-neutral energy optimization emission monitoring device, characterized in that, include: Monitoring box (1); An air inlet pipe (2) is located at the top of one side of the monitoring box (1); An exhaust pipe (3) is located at the bottom of the other side of the monitoring box (1); The control terminal (4) is located at one end of the monitoring box (1); A fan (5) is interspersed at the top of the monitoring box (1); The first partition (6) is located at the top inside the monitoring box (1); The second partition (7) is located at the bottom inside the monitoring box (1); Several non-dispersive infrared sensors (8) are respectively installed at the top and bottom of the inner sidewall of the monitoring box (1); Several cylinders (9) are disposed at the top of the first partition (6); A filter bag (10) is interspersed between the first partition (6) and the second partition (7) and cooperates with the fan (5); A cleaning mechanism (11) is provided at the bottom of several cylinders (9) for cleaning the filter bag (10); The reaction box (12) is located at the top of the bottom of the monitoring box (1); An ultrasonic sensor (13) is disposed on the inner sidewall of the reaction box (12).

2. The carbon-neutral energy optimization emission monitoring device according to claim 1, characterized in that, A liquid inlet pipe (14) is provided at one bottom side of the monitoring box (1), and a liquid outlet pipe (15) is provided at the other bottom side of the monitoring box (1); Both the liquid inlet pipe (14) and the liquid outlet pipe (15) penetrate the reaction box (12) and extend into the interior of the reaction box (12). Solenoid valves (16) are provided on the outside of the liquid inlet pipe (14), the liquid outlet pipe (15), the air inlet pipe (2) and the air outlet pipe (3).

3. The carbon-neutral energy optimization emission monitoring device according to claim 1, characterized in that, The cleaning mechanism (11) includes a support plate (1101) disposed at the bottom of the output end of a plurality of cylinders (9). A motor (1102) is disposed at the bottom of the support plate (1101). A first pulley (1103) is disposed through the output end of the motor (1102) through the support plate (1101). Two sets of first belts (1104) are disposed sequentially on the outer side of the first pulley (1103). A second pulley (1105) is disposed at the other end of the first belts (1104). A third pulley (1107) is disposed on the outer side of the second pulley (1105) through the second belt (1106).

4. The carbon-neutral energy optimization emission monitoring device according to claim 3, characterized in that, A snap-fit ​​wheel (1108) is provided on one side of the second pulley (1105) and the third pulley (1107) through the support plate (1101). A rotating ring (1109) is provided inside the snap-fit ​​wheel (1108). A plurality of cleaning wheels (1110) are provided on one side of the rotating ring (1109), and the plurality of cleaning wheels (1110) cooperate with the filter bag (10).

5. The carbon-neutral energy optimization emission monitoring device according to claim 1, characterized in that, The control terminal (4) is equipped with a data acquisition module (17), a carbon emission calculation module (18), a carbon neutrality calculation module (19), a carbon neutrality prediction module (20), and a closed-loop optimization control module (21). The data acquisition module (17) is used to collect carbon emission data and carbon neutrality data; The carbon emission calculation module (18) is used to calculate the actual carbon emissions by using a temperature dynamic compensation algorithm and combining carbon emission data. The carbon neutrality calculation module (19) is used to calculate the actual amount of carbon neutralized based on the temperature dynamic compensation algorithm and combined with the carbon neutrality data. The carbon neutrality prediction module (20) is used to construct and train an autoregressive integral moving average model based on the data acquisition module (17) to obtain a carbon neutrality prediction model; and to obtain the required carbon neutrality amount by using the carbon neutrality prediction model and combining it with the actual carbon emissions obtained by the carbon emission calculation module (18). The closed-loop optimization control module (21) is used to compare the actual carbon neutralization amount with the required carbon neutralization amount, and to optimize the control of the monitoring box (1) based on the comparison results.

6. The carbon-neutral energy optimization emission monitoring device according to claim 5, characterized in that, The data acquisition module (17) includes a gas flow acquisition submodule, a carbon concentration acquisition submodule, and an absorbent state acquisition submodule; The gas flow acquisition submodule is used to acquire the gas flow data of the fan (5); The carbon concentration acquisition submodule is used to acquire inlet carbon concentration data and outlet carbon concentration data using several of the non-dispersive infrared sensors (8); The absorbent state acquisition submodule is used to acquire absorbent precipitation state data in the reaction box (12) based on the ultrasonic sensor (13); The carbon emission data includes gas flow rate data, inlet carbon concentration data, and equipment indirect emission data. The carbon neutrality data includes inlet carbon concentration data, outlet carbon concentration data, absorbent precipitation state data, and indirect carbon offset data.

7. The carbon-neutral energy optimization emission monitoring device according to claim 6, characterized in that, The calculation of actual carbon emissions using a dynamic temperature compensation algorithm combined with carbon emission data includes: The temperature dynamic compensation algorithm is used to optimize the inlet carbon concentration data in the carbon neutrality data; Standardize the gas flow rate data and the optimized inlet carbon concentration data; Based on the density conversion factor and carbon conversion factor, and combined with standardized carbon emission data, the direct carbon emissions were calculated. Indirect carbon emissions are calculated based on motor energy consumption and grid carbon intensity in the equipment indirect emission data. By integrating direct and indirect carbon emissions, we can obtain the actual carbon emissions.

8. The carbon-neutral energy optimization emission monitoring device according to claim 6, characterized in that, The calculation of the actual carbon neutrality based on the temperature dynamic compensation algorithm and combined with carbon neutrality data includes: A temperature dynamic compensation algorithm is used to optimize the inlet and outlet carbon concentration data in the carbon neutrality data. The carbon absorption was calculated based on the optimized inlet and outlet carbon concentration data. Calculate the real-time carbon absorption efficiency based on the absorbent precipitation state data in the carbon neutralization data; The amount of direct carbon neutralization is calculated using the amount of carbon absorbed and the real-time efficiency of carbon absorption. Carbon credits based on carbon neutrality data, combined with time proportions, yield indirect carbon neutrality. By integrating direct and indirect carbon neutralization, the actual carbon neutralization is obtained.

9. The carbon-neutral energy optimization emission monitoring device according to claim 6, characterized in that, The data acquisition module (17) is used to construct and train an autoregressive integral moving average model to obtain a carbon neutrality prediction model. Using the carbon neutrality prediction model and the actual carbon emissions obtained by the carbon emission calculation module (18), the required carbon neutrality amount is obtained, including: Based on the data acquisition module (17), historical carbon emission data and carbon neutrality data are acquired; Using historical carbon emission data and carbon neutrality data, an autoregressive integral moving average model was constructed and trained to obtain a carbon neutrality prediction model. Based on the actual carbon emissions obtained from the carbon emission calculation module (18) and combined with the carbon neutrality prediction model, the required carbon neutrality is obtained.

10. A carbon-neutral energy optimization emission monitoring device according to claim 9, characterized in that, The process of constructing and training an autoregressive integral moving average model using historical carbon emission data and carbon neutrality data to obtain a carbon neutrality prediction model includes: Statistical testing methods were used to test the stationarity of the time series of historical carbon emission data and carbon neutrality data, and the time series of historical carbon emission data and carbon neutrality data were optimized by difference processing. Based on the autocorrelation function graph and the partial autocorrelation function graph, and combined with the information criterion, the optimal parameters are determined, and an autoregressive integral moving average model is constructed. Based on optimized historical carbon emission data and carbon neutrality data, an autoregressive integral moving average model is trained, and a carbon neutrality prediction model is obtained by cross-validating the trained autoregressive integral moving average model.

Images