Total pollutant emission tracking system and method for wet desulphurization system

Abstract

The invention relates to a total pollutant emission tracking system and method for a wet desulphurization system in the technical field of wet desulphurization, and the system comprises a spraying system, a data visualization module, an emission prediction module, a frequency conversion PID control module and a DCS system, and the spraying system, the data visualization module, the emission prediction module and the frequency conversion PID control module are connected with the DCS system. The DCS system is connected with the environmental protection private network; the method comprises the following steps of S1, environmental protection data access and emission visualization, S2, emission prediction modeling and S3, frequency conversion PID control. According to the invention, intelligent tracking and accurate control of pollutant emission are realized through a closed-loop logic of data access-quantitative calculation-prediction modeling-frequency conversion PID control in combination with a spraying system in the prior art.

Description

Technical Field

[0001] This invention belongs to the field of wet desulfurization technology, specifically providing a system and method for tracking total pollution emissions from wet desulfurization systems. Background Technology

[0002] Wet desulfurization systems primarily control the sulfur dioxide concentration at enterprise emission outlets. Current technologies control emissions by regulating the number of spray layers in operation, typically 1-4 layers, thus limiting concentration control to a maximum of four levels. However, local environmental protection bureaus impose stringent requirements on enterprise pollution emissions, periodically demanding emission reductions. Furthermore, local environmental protection departments dynamically adjust emission reduction targets (reductions of 10%-50%) based on weather conditions. Relying solely on controlling the number of spray layers is insufficient for accurately controlling total emissions and meeting environmental requirements. Therefore, a comprehensive pollution emission tracking system and method for wet desulfurization systems are urgently needed to address these issues. Summary of the Invention

[0003] In response to the above situation, the present invention provides a total pollutant emission tracking system and method for wet desulfurization systems, aiming to solve the problems of the inability to accurately control the total amount of pollutant emissions, hourly emissions, and hourly concentrations in existing wet desulfurization systems, making it difficult to achieve the emission reduction targets required by environmental protection requirements.

[0004] To achieve the above objectives, the present invention adopts the following technical solution:

[0005] The total pollution emission tracking system for wet desulfurization systems includes a spray system, a data visualization module, an emission prediction module, a variable frequency PID control module, and a DCS system. The spray system, data visualization module, emission prediction module, and variable frequency PID control module are connected to the DCS system, and the DCS system is connected to the environmental protection network. The data visualization module displays real-time emission data, the DCS system performs time-accumulated calculation of emissions, the emission prediction module predicts emissions, and the variable frequency PID control module controls emissions.

[0006] Preferably, the variable frequency PID control module includes a circulating pump and a standby pump, the circulating pump is connected to a frequency converter, and the circulating pump and the standby pump are connected to the spray system to control the spraying.

[0007] The present invention also includes a method for tracking the total amount of pollutant emissions from a wet desulfurization system, which employs the aforementioned system for tracking the total amount of pollutant emissions from a wet desulfurization system.

[0008] The method includes the following steps: S1. Environmental data access and emission visualization The environmental protection network is connected to the DCS system to obtain real-time emission data. Based on the formula "emissions = air volume × concentration", the DCS programming is used to calculate the cumulative emission over time, obtain the cumulative emission value and the cumulative time value, and display them in real time. S2, Emission Prediction Modeling Obtain the instantaneous cumulative emission value and the current cumulative emission value in step S1, call historical emission data, use the moving average algorithm to predict the daily emission, and output the predicted value (predicted emission) in real time for regulation reference; S3: Variable frequency PID control, Configure PID parameters: Based on historical emission data, set the proportional band to 50, integral time to 1, and derivative time to 0.5. Use proportional-integral-derivative adjustment to counteract interference. Set the predicted emission value as the PV (process value) in the PID controller and the emission limit as the SP (setpoint). Link the PID control output value to the variable frequency drive (VFD) speed control of the circulating pump. After adjusting the proportional band, integral time, derivative time, and upper and lower limits, automatic control of pollutant emissions can be achieved.

[0009] Hybrid control logic: When the predicted emission is close to the limit, the speed of the circulating pump is adjusted by the frequency converter (instead of starting and stopping) to achieve dynamic constant control of the emission. When the emission exceeds the limit, the standby pump is started to assist in emission control.

[0010] Preferably, the real-time emission data includes real-time air volume, SO2 concentration, and dust concentration. The cumulative emission value includes hourly and daily cumulative values. A calculation program is written in the DCS system to calculate the hourly and daily cumulative values ​​by minute-level integration based on the formula "cumulative emission = ∫(real-time air volume × real-time SO2 concentration) dt". The calculation program has built-in data verification logic, which automatically calibrates when the error with the platform data of the environmental protection network exceeds 1%.

[0011] Preferably, the calculation logic for the cumulative hourly emission value is as follows: starting at each hour, the SO2 concentration value is automatically accumulated every second as the numerator, and the time is automatically accumulated as the denominator. The program divides the two values ​​and outputs the average value. The calculation is automatically cleared and recalculated at the hour.

[0012] Current pollutant emission calculation logic: Starting at 0:00 each day, (SO2 concentration + dust concentration) is calculated. The air volume is automatically accumulated per second as the numerator, and the time is automatically accumulated as the denominator. The program divides the result and outputs the pollutant emission value. The system automatically clears and recalculates at the top of the hour.

[0013] Preferably, the historical emission data includes inlet sulfur content, air volume fluctuations, pH value changes, and data related to other interfering factors.

[0014] Preferably, the moving average algorithm includes SEQ sequence storage and cumulative averaging. The daily emission prediction adopts the moving average algorithm. Through a large amount of instantaneous cumulative emission data stored in the SEQ sequence, the average instantaneous emission is calculated according to the formula "ZQ=ΣSEQ[i](i=1 to INS) / INS". Combined with the current running time and the total duration of the day, the predicted value for the whole day is obtained. Here, INS is the size of the moving window. The value of INS is not less than 300 sets to ensure the prediction accuracy is ≥95%.

[0015] Average predicted total emissions logic: Current pollutant emissions / Accumulated time for the day (how many seconds have passed since 0:00). The average predicted total emissions for the day can be calculated by adding the remaining time of the day (how many seconds are left until midnight) to the current pollutant emissions.

[0016] Instantaneous emission prediction logic: Write the emissions from the previous period (period time adjustable) to the storage group, and retrieve the emissions from the previous period. The instantaneous periodic predicted emissions can be obtained by adding the remaining time of the day to the current pollutant emissions.

[0017] This invention achieves intelligent tracking and precise control of pollutant emissions by combining a closed-loop logic of "data access - quantitative calculation - predictive modeling - variable frequency PID control" with existing spray systems.

[0018] The beneficial effects of this invention are as follows: 1. Precise emission control: Real-time visualization and all-day prediction of emissions are achieved, daily emissions are stably close to the limit, and hourly emission fluctuations are significantly reduced, meeting environmental protection requirements for emission stability; 2. Convenient and efficient operation: Monitoring personnel can directly view emissions, predicted values ​​and control status through the DCS interface, without the need for manual calculation and manual start-up and shutdown of equipment, reducing operational intensity. PID automatic control of emissions improves the degree of automation in emissions control and enhances emission control efficiency. 3. High adaptability: It can be flexibly adapted to the emission reduction targets (10%~50%) that are dynamically adjusted according to environmental protection, and is compatible with emission control requirements under different working conditions, with a wide range of applications. Detailed Implementation

[0019] The present invention will now be clearly described with reference to specific embodiments. Any modifications, equivalent substitutions, improvements, etc., made by those skilled in the art based on the embodiments of the present invention without inventive effort to obtain all other embodiments should be included within the scope of protection of the present invention.

[0020] Example 1 This invention proposes a total pollution emission tracking system for wet desulfurization systems, including a data visualization module, an emission prediction module, a variable frequency PID control module, and a DCS system. The data visualization module, emission prediction module, and variable frequency PID control module are connected to the DCS system, and the DCS system is connected to an environmental protection network. The data visualization module displays real-time emission data, the DCS system performs time-accumulated calculation of emissions, the emission prediction module predicts emissions, and the variable frequency PID control module controls emissions.

[0021] The variable frequency PID control module includes a circulating pump and a standby pump, and the circulating pump is connected to a frequency converter.

[0022] The spray system in this embodiment adopts the existing spray system, and its specific structure will not be described in detail here.

[0023] Example 2 This implementation includes a method for tracking the total pollution emissions of a wet desulfurization system, which uses the total pollution emissions tracking system for a wet desulfurization system in Example 1.

[0024] The method includes the following steps: S1. Environmental data access and emission visualization The environmental protection network is integrated with the DCS system to obtain real-time emission data. Based on the formula "Emissions = Air Volume × Concentration", the DCS program calculates the cumulative emissions over time, obtaining and displaying the cumulative emission and time values ​​in real time. The real-time emission data includes real-time air volume, SO2 concentration, and dust concentration. The cumulative emission values ​​include hourly and daily values. A calculation program is written in the DCS system, based on the formula "Cumulative Emissions = ∫(Real-time Air Volume × Real-time SO2 Concentration) dt", to calculate the hourly and daily cumulative values ​​by minute-level integration. The calculation program has built-in data verification logic, automatically calibrating when the error with the environmental protection network platform data exceeds 1%. The calculation logic for the hourly cumulative emission value is as follows: starting at the top of each hour, the SO2 concentration value is automatically accumulated per second as the numerator, and the time is automatically accumulated as the denominator. The program divides the values ​​and outputs the average value. The calculation is automatically cleared and restarted at the top of each hour. S2, Emission Prediction Modeling Obtain the instantaneous cumulative emission value and the current cumulative value from step S1, call historical emission data, and use a moving average algorithm to predict the daily emission volume, and output the predicted value (predicted emission volume) in real time for regulatory reference; the current pollutant emission calculation logic is as follows: at 0:00 every day, start calculating (SO2 concentration + dust concentration). The air volume is automatically accumulated per second as the numerator, and the time is automatically accumulated as the denominator. The program divides the result and outputs the pollutant emission value. The system automatically clears and recalculates at the top of the hour.

[0025] The moving average algorithm includes SEQ sequence storage and cumulative averaging. The daily emission prediction adopts the moving average algorithm. It calculates the average instantaneous emission using the nearly 600 sets of instantaneous cumulative emission data stored in the SEQ sequence according to the formula "ZQ=ΣSEQ[i](i=1 to INS) / INS". Combined with the current running time and the total duration of the day, the predicted value for the whole day is obtained. Here, INS is the size of the moving window. The value of INS is not less than 300 sets to ensure the prediction accuracy is ≥95%.

[0026] S3: Variable frequency PID control, Configure PID parameters: Based on historical emission data, set the proportional band to 50, integral time to 1, and derivative time to 0.5. Use proportional-integral-derivative adjustment to counteract interference. Set the predicted emission value as the PV (process value) in the PID controller and the emission limit as the SP (setpoint). Link the PID control output value to the variable frequency drive (VFD) speed control of the circulating pump. After adjusting the proportional band, integral time, derivative time, and upper and lower limits, automatic control of pollutant emissions can be achieved. The historical emission data includes data related to interference factors such as inlet sulfur content, airflow fluctuations, and pH changes. In this embodiment, the average predicted total emissions logic is: current pollutant emissions / accumulated time for the day (how many seconds have passed since 0:00). The average predicted total emissions for the day can be calculated by adding the remaining time of the day (how many seconds are left until midnight) to the current pollutant emissions.

[0027] Instantaneous emission prediction logic: Write the emissions from the previous period (period time adjustable) to the storage group, and retrieve the emissions from the previous period. The instantaneous cycle emission forecast can be obtained by adding the remaining time of the day to the current pollutant emission amount. For example, if the cycle is set to 1 hour, the current time is 2 PM, the emission amount for the cycle from 1 PM to 2 PM is 50 kg, and 600 kg of pollutants have been emitted by 2 PM, then the instantaneous cycle emission forecast total = (24 - 14). 50 + 600 = 1100KG.

[0028] In this embodiment, if the total emissions for today are ≤1200KG and the concentration limit is greater than the hourly average and ≤30mg, then... Selection of PV (Process Value) and SP (Setup Value): When the total forecast value for the day is ≥1200, move the total forecast value for the day to PV and move the total limit for today, 1200, to SP.

[0029] When the hourly value is ≥30mg, move the predicted hourly value to PV and move 30mg to SP.

[0030] The system automatically increases the frequency regardless of whether the concentration or the total amount exceeds the standard, thus preventing data from exceeding the standard.

[0031] The PID control output value is linked to the frequency converter speed control of the circulating pump.

[0032] Hybrid control logic: When the predicted emission is close to the limit, the speed of the circulating pump is adjusted by the frequency converter (instead of starting and stopping), and the spray adjustment of the spray system is used to achieve dynamic constant control of the emission. When the emission exceeds the limit and an early warning is issued, the standby pump is started to assist in emission control.

[0033] In this embodiment, the specific adjustments to the PID module are as follows: Output lower limit setting: Based on the proportional relationship between the circulating pump's speed and the square of its head, the minimum speed of the spray system can be calculated and determined using the circulating pump's head and spray height. This minimum speed is set as the PID output lower limit (to prevent the system from not performing work at excessively low speeds).

[0034] P is the adjustment of the proportion: it should not be set too small in the early stage, because the emission value, whether it is the total emission or the hourly value, is a slow process. The slow change is not sensitive to deviation. If the P value is too small, it will lead to sluggish adjustment and serious lag. The P value needs to be increased to 80% to 90% of the "system close to the critical oscillation". When the system oscillation is very small and there is a relatively "fixed deviation" between the process value and the target value, the P value is gradually reduced to reduce the "fixed deviation" and the critical value with small oscillation.

[0035] I represents the adjustment of the integration time: it should not be set too small initially. Once P is adjusted, gradually reduce the value of I. The "fixed deviation" will gradually decrease. When this fixed deviation decreases and the process value and target value overlap, the integration time will no longer need to be adjusted.

[0036] D is the adjustment of the derivative: if there is still a slight overshoot, increase Td slightly (e.g., Td = 0.1~0.3 × Ti), each adjustment not exceeding 20% ​​of the current value, and the overshoot will disappear.

[0037] The above are merely preferred embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A total emission tracking system for wet desulfurization systems, including a spray system, characterized in that, It also includes a data visualization module, an emission prediction module, a variable frequency PID control module, and a DCS system. The data visualization module, emission prediction module, variable frequency PID control module, and spray system are connected to the DCS system, and the DCS system is connected to the environmental protection network. The data visualization module displays real-time emission data, the DCS system performs time-accumulated calculation of emissions, the emission prediction module predicts emissions, and the variable frequency PID control module controls emissions.

2. The total pollution emission tracking system for wet desulfurization systems according to claim 1, characterized in that, The variable frequency PID control module includes a circulating pump and a standby pump. The circulating pump is connected to a frequency converter, and the circulating pump and the standby pump are connected to the spray system to control the spraying.

3. A method for tracking total pollutant emissions from wet desulfurization systems, characterized in that, The total pollution emission tracking system of the wet desulfurization system described in any one of claims 1-2 is adopted.

4. The method for tracking total pollutant emissions from a wet desulfurization system according to claim 3, characterized in that, Includes the following steps: S1. Environmental data access and emission visualization The environmental protection network is connected to the DCS system to obtain real-time emission data. Based on the formula "emissions = air volume × concentration", the DCS programming is used to calculate the cumulative emission over time, obtain the cumulative emission value and the cumulative time value, and display them in real time. S2, Emission Prediction Modeling Obtain the instantaneous cumulative emission value and the current time cumulative value in step S1, call historical emission data, use the moving average algorithm to predict the daily emission, and output the predicted value in real time for regulation reference; S3: Variable frequency PID control, Configure PID parameters: Based on historical emission data, set the parameters for proportional band, integral time, and derivative time, and use proportional-integral-derivative adjustment to counteract interference; Hybrid control logic: When the predicted emission is close to the limit, the speed of the circulating pump is adjusted by the frequency converter to achieve dynamic constant control of the emission. When the emission exceeds the limit, the standby pump is started to assist in emission control.

5. The method for tracking total pollutant emissions from a wet desulfurization system according to claim 4, characterized in that, The real-time emission data includes real-time air volume, SO2 concentration, and dust concentration. The cumulative emission value includes hourly and daily cumulative values. A calculation program is written in the DCS system to calculate the hourly and daily cumulative values ​​based on the formula "cumulative emission = ∫(real-time air volume × real-time SO2 concentration) dt". The calculation program has built-in data verification logic, which automatically calibrates when the error with the platform data of the environmental protection network exceeds 1%.

6. The method for tracking total pollutant emissions from a wet desulfurization system according to claim 5, characterized in that, The calculation logic for the cumulative hourly emission value is as follows: starting at the top of each hour, the SO2 concentration value is automatically accumulated every second as the numerator, and the time is automatically accumulated as the denominator. The program divides the two values ​​and outputs the average value. The calculation is automatically cleared and recalculated at the top of each hour.

7. The method for tracking total pollutant emissions from a wet desulfurization system according to claim 4, characterized in that, The historical emission data includes inlet sulfur content, air volume fluctuations, pH changes, and data related to other interfering factors.

8. The method for tracking total pollutant emissions from a wet desulfurization system according to claim 4, characterized in that, The moving average algorithm includes SEQ sequence storage and cumulative averaging. The daily emission prediction adopts the moving average algorithm. Through a large amount of instantaneous cumulative emission data stored in the SEQ sequence, the average instantaneous emission is calculated according to the formula "ZQ=ΣSEQ [i] (i=1 to INS) / INS". Combined with the current running time and the total duration of the day, the daily prediction value is obtained, where INS is the size of the sliding window and the number of INS values ​​is not less than 300.