Boiler tail gas multi-pollutant cooperative control system based on linkage of PLC and frequency converter

Abstract

The invention relates to the technical field of boiler tail gas treatment, in particular to a boiler tail gas multi-pollutant cooperative control system based on linkage of a PLC and a frequency converter. The system comprises a data acquisition module, a PLC control module and a collaborative optimization module. Concentration data of pollutants in boiler tail gas are collected in real time through the data collection module, the boiler tail gas is introduced into the desulfurization and denitrification tower through the inlet induced draft fan, the PLC control module sets driving rules of the inlet induced draft fan through a logic controller of a PLC, the operation frequency of the inlet induced draft fan is dynamically adjusted according to the content of the pollutants in the boiler tail gas, and the desulfurization and denitrification effect of the boiler tail gas is improved. And the collaborative optimization module returns the tail gas which does not reach the standard to a boiler for secondary desulfurization and denitrification, the tail gas which reaches the standard is introduced into a dust removal tower through an outlet induced draft fan, the electric dust removal voltage is adjusted according to the content of ammonia gas in the tail gas, and linkage control over desulfurization, denitrification and dust removal is achieved by taking the minimum operation cost as the target and adopting a genetic algorithm.

Description

Technical Field

[0001] The present invention relates to the technical field of boiler tail gas treatment, and in particular to a boiler tail gas multi-pollutant collaborative control system based on PLC and inverter linkage. Background Art

[0002] Industrial boiler exhaust gas treatment has become a critical component in reducing air pollution. Traditional technologies for treating pollutants such as particulate matter (PM), sulfur oxides (SOx), and nitrogen oxides (NOx) in boiler exhaust have evolved from single-stage purification to coordinated multi-pollutant treatment. However, existing technologies lack a high degree of automation, leading to energy waste and unstable treatment results, making it difficult to meet increasingly stringent environmental protection requirements.

[0003] Currently, electrostatic precipitators are used to purify boiler exhaust gas. Flue gas passes through a high-voltage electric field, and the charged particulate matter is adsorbed by the dust collecting electrode. The particulate matter is then vibrated and cleaned into the ash hopper. However, the voltage of the high-voltage electric field is fixed and cannot be dynamically adjusted according to the dust load, resulting in excessive PM emissions and reduced cleaning efficiency. Wet desulfurization is used, and flue gas enters the desulfurization tower and comes into countercurrent contact with the sprayed limestone slurry. SO2 is absorbed to form calcium sulfite, which is further oxidized to gypsum. However, the slurry pump has a fixed operating frequency, and pH adjustment relies on manual intervention, resulting in excessive slurry circulation when the equipment is under low load. SCR denitrification is used, and flue gas passes through the catalyst layer. At a temperature of 280-400°C, the injected ammonia reacts with NOx to produce N2 and H2O. However, the amount of ammonia sprayed is controlled by a fixed ratio and is not linked to the flue gas flow rate. This results in unstable NOx removal rates and high ammonia escape rates, affecting the overall denitrification effect.

[0004] In order to be able to control the frequency of the induced draft fan using the PLC controller according to the flue gas flow, pollutant concentration, and equipment status data obtained by the sensor in real time, adjust the slurry pump frequency in conjunction with the SO2 concentration, and dynamically adjust the operating parameters of the ammonia injection device according to the NOx concentration and flue gas flow, so as to timely adjust the operating parameters of the equipment according to the real-time concentration changes of exhaust pollutants, improve the treatment efficiency, and ensure the stability and compliance rate of exhaust emissions, we propose a boiler exhaust multi-pollutant collaborative control system based on the linkage of PLC and frequency converter. Summary of the Invention

[0005] The purpose of the present invention is to solve the problem that when an enterprise treats boiler exhaust gas, the control logic of the exhaust gas treatment system is simple, relies on threshold alarms or fixed parameters, cannot adapt to complex working conditions, each processing unit is controlled independently, and lacks global optimization. In order to be able to achieve precise regulation of the boiler exhaust gas treatment equipment through the linkage control of PLC and frequency converter, the operating parameters of the equipment can be adjusted in time according to the real-time concentration changes of exhaust gas pollutants, thereby improving the treatment efficiency and ensuring the stability and compliance rate of exhaust gas emissions.

[0006] To achieve the above objectives, the present invention provides a data acquisition module, a PLC control module and a collaborative optimization module;

[0007] The data acquisition module collects the concentration data of pollutants in the boiler tail gas, flue gas flow and equipment status data in real time, and uses the inlet induced draft fan to introduce the boiler tail gas into the desulfurization and denitrification tower;

[0008] The PLC control module uses a PLC logic controller to set the driving rules of the inlet induced draft fan, dynamically adjusts the operating frequency of the inlet induced draft fan according to the content of pollutants in the boiler exhaust gas, takes the error value between the concentration of sulfur dioxide and nitrogen oxides in the boiler exhaust gas and the target concentration as input, uses a PID control algorithm to output the operating parameters of the slurry circulation pump and the ammonia injection pump, and uses a frequency converter to dynamically adjust the operating frequency of the slurry circulation pump and the ammonia injection pump to remove sulfur and denitrify the boiler exhaust gas;

[0009] The collaborative optimization module detects the content of sulfur dioxide and nitrogen oxides in the exhaust gas after desulfurization and denitrification. The PLC logic controller determines the desulfurization and denitrification of the exhaust gas, and returns the exhaust gas that does not meet the standards to the boiler for secondary desulfurization and denitrification. The exhaust gas that meets the standards is introduced into the dust removal tower through the outlet induced draft fan. The electrostatic precipitator voltage is adjusted according to the ammonia content in the exhaust gas. With the goal of minimizing operating costs, a genetic algorithm is used to coordinate the linkage control of desulfurization, denitrification and dust removal.

[0010] Compared with the prior art, the present invention has the following beneficial effects:

[0011] 1. This boiler exhaust multi-pollutant collaborative control system based on the linkage of PLC and frequency converter collects the concentration data of pollutants in the boiler exhaust, flue gas flow and equipment status data in real time through the data acquisition module, and uses the inlet induced draft fan to introduce the boiler exhaust into the desulfurization and denitrification tower. The PLC control module uses the PLC logic controller to set the driving rules of the inlet induced draft fan. According to the content of pollutants in the boiler exhaust gas, the operating frequency of the inlet induced draft fan is dynamically adjusted. The error value between the concentration of sulfur dioxide and nitrogen oxides in the boiler exhaust gas and the target concentration is used as input. The PID control algorithm is used to output the operating parameters of the slurry circulation pump and the ammonia injection pump. The frequency converter is used to dynamically adjust the operating frequency of the slurry circulation pump and the ammonia injection pump to remove sulfur and denitrify the boiler exhaust. According to the real-time concentration data of pollutants in the boiler exhaust gas, the flue gas flow in the desulfurization and denitrification tower and the operating frequency of the slurry circulation pump and the ammonia injection pump are controlled, thereby improving the stability and compliance rate of boiler exhaust gas treatment.

[0012] 2. The collaborative optimization module detects the content of sulfur dioxide and nitrogen oxides in the exhaust gas after desulfurization and denitrification. The PLC logic controller determines the desulfurization and denitrification of the exhaust gas, and returns the exhaust gas that does not meet the standards to the boiler for secondary desulfurization and denitrification. The exhaust gas that meets the standards is introduced into the dust removal tower through the outlet induced draft fan. According to the ammonia content in the exhaust gas, the electrostatic precipitator voltage is adjusted to improve the purification rate of pollutants in the boiler exhaust gas, ensure the emission quality of the exhaust gas, and with the goal of minimizing operating costs, adopt a genetic algorithm to coordinate the linkage control of desulfurization, denitrification and dust removal to purify the pollutants in the exhaust gas, while reducing energy consumption and saving resources.

[0013] As a further improvement of the present technical solution, the PLC control module sets the reference value of boiler exhaust pollutants according to environmental protection requirements and the parameters of the desulfurization and denitrification tower. When the pollutant concentration or flue gas flow deviates from the reference value, the PLC logic controller adjusts the operating frequency of the induced draft fan proportionally according to the size of the deviation.

[0014] As a further improvement of the present technical solution, the PLC control module includes a parameter control unit and a variable frequency drive unit;

[0015] The parameter control unit defines a fuzzy set based on the error value and error change rate between the collected sulfur dioxide and nitrogen oxide concentration data and flue gas flow and the target concentration value in the environmental protection emission standard, as well as the output parameter adjustment amount of the PID controller. The fuzzy set is: negative large NB, negative medium NM, negative small NS, zero ZO, positive small PS, positive medium PM, and positive large PB;

[0016] The variable frequency drive unit adjusts the proportional coefficient, differential coefficient and integral coefficient of the PID controller according to the parameter adjustment amount of the output PID controller, and uses the PID control algorithm to calculate the operating parameters of the fan, slurry circulation pump and ammonia injection pump.

[0017] The beneficial effect of adopting the above further improvement is that the definition of fuzzy sets provides a basis for the formulation of fuzzy control rules. According to the fuzzy sets of error values and error change rates and the corresponding fuzzy rules, the system can realize intelligent decision-making and automatically adjust the parameters of the PID controller according to different situations.

[0018] By adjusting the parameters of the PID controller online, fuzzy adaptive PID control can be optimized according to the real-time status of the system to improve control accuracy. Compared with traditional fixed-parameter PID control, fuzzy adaptive PID control can better track the target concentration value, reduce errors, and make exhaust emissions closer to environmental emission standards.

[0019] As a further improvement of this technical solution, the parameter control unit establishes a fuzzy rule base in the following form:

[0020] IF e is Ai AND Δe is B j THEN ΔK p is C ij ;

[0021] Among them, e is the error value, Δe is the error change rate, A i is the fuzzy set of error value e, B j is the fuzzy set of error change rate Δe, ΔK p is the parameter adjustment of the PID controller, C ij is the PID controller parameter adjustment value ΔK p fuzzy set.

[0022] The beneficial effect of adopting the above further improvements is that the fuzzy rule base can formulate rules according to different working conditions, allowing the system to automatically adjust the control strategy to ensure that exhaust emissions can be effectively controlled under various working conditions. With the help of the fuzzy rule base, the PID controller parameters can be adjusted in real time according to the error and the error change rate. The system can dynamically adjust the proportional, integral, and differential coefficients of the PID based on the error and error change rate between the exhaust pollutant concentration and the target value, thereby enhancing the control effect and ensuring that the exhaust emissions meet the standards.

[0023] As a further improvement of the present technical solution, the variable frequency drive unit adopts a discrete PID control algorithm to calculate the operating parameters of the corresponding equipment based on the collected concentration data of sulfur dioxide and nitrogen oxides and the error value of the flue gas flow rate. The formula is:

[0024]

[0025] Among them, μ(t) is the equipment operating parameter, K p is the proportionality coefficient, K i is the differential coefficient, K d is the integral coefficient, e(t) is the error value at time t, and e(t-1) is the error value at time t-1.

[0026] The beneficial effect of these further improvements is that the PID control algorithm can precisely adjust the control variable based on the error between the system output and the set target value through the combined effects of proportional, integral, and differential functions. In boiler exhaust gas treatment systems, the concentration of pollutants such as sulfur dioxide and nitrogen oxides in the exhaust gas, as well as the flue gas flow rate, can be steadily maintained close to the target values specified by environmental emission standards, achieving high-precision steady-state control.

[0027] As a further improvement of this technical solution, the collaborative optimization module includes a detection and determination unit and a genetic optimization unit;

[0028] The detection and judgment unit collects the content data of these two pollutants in the exhaust gas in real time through the sulfur dioxide and nitrogen oxide sensors installed on the exhaust gas pipeline after desulfurization and denitrification, and uses the PLC logic controller to compare the received sulfur dioxide and nitrogen oxide content data with the set threshold values to determine the desulfurization and denitrification of the exhaust gas;

[0029] The genetic optimization unit takes minimizing the desulfurizer cost, denitrifier cost and equipment energy consumption cost as the objective function, uses real number coding to encode the decision variables, and selects the decision variable combination corresponding to the optimal individual through selection, inheritance and mutation operations.

[0030] As a further improvement of the present technical solution, the detection and judgment unit adopts a graded threshold setting method to set the sulfur dioxide and nitrogen oxide content thresholds in the PLC logic controller, which are divided into normal area, warning area, first-level exceeding standard area and second-level exceeding standard area, and a graded response strategy is set.

[0031] As a further improvement of the present technical solution, the detection and determination unit sets corresponding response delays for different threshold intervals, and sets upper and lower limits for corresponding device adjustment.

[0032] The beneficial effect of adopting the above further improvements is that traditional single-threshold control easily leads to "black-or-white" decisions, while graded thresholds can dynamically adjust the response intensity according to the pollution level to achieve precise control. The graded response can reduce the number of unnecessary equipment starts and stops (such as backup pumps), reducing equipment losses. By setting the first and second level exceeding the standard zone, safety redundancy is formed. When the first level measures are ineffective, the more stringent control logic is automatically triggered.

[0033] During exhaust gas testing, sensors may experience momentary fluctuations or errors for various reasons. For example, brief airflow changes or minor instrument failures can cause momentary anomalies in the test data. Without a response delay, the system might immediately make adjustments based on these momentary anomalies, causing unnecessary and frequent device actions. With a response delay, the system continuously monitors data over a period of time. Only when the data remains within the corresponding threshold range within that period will the corresponding action be triggered, effectively avoiding false actions caused by momentary data fluctuations.

[0034] As a further improvement of the present technical solution, when the genetic optimization unit uses a genetic algorithm to find the optimal combination of decision variables, it determines that pollutant emissions meet standards and equipment parameters operate within a normal range as constraints.

[0035] The beneficial effect of adopting the above-mentioned further improvements is that setting the pollutant emission standards as constraints can ensure that the concentrations of pollutants such as sulfur dioxide, nitrogen oxides, particulate matter, etc. in the boiler exhaust gas are always controlled within the range specified by environmental protection standards. This is the basic requirement and primary goal of system operation, and is of vital importance for reducing environmental pollution, protecting the ecological environment and human health. By using genetic algorithms to find the optimal combination of decision variables while meeting this constraint, precise control of the exhaust gas treatment process can be achieved, ensuring that the system can stably and efficiently control pollutant emissions at a compliance level under various operating conditions.

[0036] As a further improvement of this technical solution, the genetic optimization unit runs the genetic algorithm multiple times, observes the change of fitness value with the number of iterations, analyzes the convergence speed of the algorithm, selects the convergence threshold of the fitness value, and determines the termination condition of the genetic algorithm.

[0037] The beneficial effect of adopting the above further improvement is that the genetic algorithm is an iterative search algorithm. If a reasonable termination condition is not set, a large number of unnecessary iterations may be performed, wasting computing resources and time. By observing the changes in the fitness value and analyzing the convergence speed, it is possible to determine when the algorithm is close to the optimal solution. By selecting a suitable convergence threshold as the termination condition, the iteration can be stopped in time after the algorithm reaches a certain degree of optimization, avoiding excessive calculation and improving the algorithm's operating efficiency.

[0038] In addition to the above-described objects, features and advantages, the present invention has other objects, features and advantages. The present invention will be further described in detail below with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 It is a schematic diagram of the overall process of the present invention;

[0040] Figure 2 It is a schematic diagram of the overall details of the present invention;

[0041] Figure 3 It is a schematic diagram of the overall structure of the present invention.

[0042] The meaning of each number in the figure is:

[0043] 100, data acquisition module; 200, PLC control module; 210, parameter control unit; 220, variable frequency drive unit; 300, collaborative optimization module; 310, detection and judgment unit; 320, genetic optimization unit. DETAILED DESCRIPTION

[0044] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0045] At present, when enterprises treat boiler exhaust gas, the control logic of the exhaust gas treatment system is simple, relying on threshold alarms or fixed parameters, and cannot adapt to complex working conditions. Each treatment unit is controlled independently and lacks global optimization. In order to achieve precise regulation of boiler exhaust gas treatment equipment through the linkage control of PLC and inverter, the operating parameters of the equipment can be adjusted in time according to the real-time concentration changes of exhaust gas pollutants, thereby improving treatment efficiency and ensuring the stability and compliance rate of exhaust gas emissions.

[0046] Therefore, the present invention proposes to collect the concentration data, flue gas flow rate and equipment status data of pollutants in the boiler exhaust gas in real time through the data acquisition module, and use the inlet induced draft fan to introduce the boiler exhaust gas into the desulfurization and denitrification tower, the PLC control module uses the PLC logic controller to set the driving rules of the inlet induced draft fan, and dynamically adjusts the operating frequency of the inlet induced draft fan according to the content of pollutants in the boiler exhaust gas, the collaborative optimization module detects the content of sulfur dioxide and nitrogen oxides in the exhaust gas after desulfurization and denitrification, and the PLC logic controller determines the desulfurization and denitrification of the exhaust gas, and returns the exhaust gas that does not meet the standards to the boiler for secondary desulfurization and denitrification. The exhaust gas that meets the standards is introduced into the dust removal tower through the outlet induced draft fan, and the electrostatic precipitator voltage is adjusted according to the ammonia content in the exhaust gas. With the goal of minimizing operating costs, a genetic algorithm is used to coordinate the linkage control of desulfurization, denitrification and dust removal.

[0047] The details are as follows:

[0048] See also Figure 1 As shown, the present invention provides a boiler exhaust gas multi-pollutant collaborative control system based on PLC and inverter linkage, including a data acquisition module 100, a PLC control module 200 and a collaborative optimization module 300;

[0049] The data acquisition module 100 collects the concentration data of pollutants in the boiler exhaust, flue gas flow and equipment status data in real time, and uses the inlet induced draft fan to introduce the boiler exhaust into the desulfurization and denitrification tower.

[0050] Laser PM sensors, infrared SO2 / SOx analyzers, and temperature / pressure transmitters are used to collect concentration data of sulfur dioxide and nitrogen oxide pollutants in boiler exhaust gas and flue gas flow, and frequency converters are used to control the speed and frequency of equipment such as the induced draft fan, slurry circulation pump, and ammonia injection pump.

[0051] In addition, the PLC control module 200 uses the PLC logic controller to set the driving rules of the inlet draft fan, dynamically adjusts the operating frequency of the inlet draft fan according to the content of pollutants in the boiler exhaust gas, takes the error value between the concentration of sulfur dioxide and nitrogen oxides in the boiler exhaust gas and the target concentration as input, uses the PID control algorithm to output the operating parameters of the slurry circulation pump and the ammonia injection pump, and uses the frequency converter to dynamically adjust the operating frequency of the slurry circulation pump and the ammonia injection pump to desulfurize and denitrify the boiler exhaust gas.

[0052] In order to better set the driving rules of the inlet induced draft fan, the PLC control module 200 sets the reference value of the boiler exhaust pollutants according to environmental protection requirements and the parameters of the desulfurization and denitrification tower. When the pollutant concentration or flue gas flow rate deviates from the reference value, the PLC logic controller adjusts the operating frequency of the induced draft fan in proportion to the deviation.

[0053] When pollutant concentrations or flue gas flow rates deviate from reference values, the PLC adjusts the induced draft fan frequency proportionally based on the magnitude of the deviation. For example, if sulfur dioxide concentrations are higher than the reference value and flue gas flow rates are low, the PLC will increase the induced draft fan frequency proportionally, increasing the flue gas flow rate and allowing more exhaust gas to enter the desulfurization and denitrification towers for treatment, thereby reducing sulfur dioxide concentrations.

[0054] Reduced frequency of the induced draft fan means a reduction in the amount of flue gas entering the desulfurization system. To maintain the residence time of the flue gas in the desulfurization tower, automatically shortening the spray layer interval is an effective adjustment method. By shortening the spray layer interval, the flue gas can pass through more spray layers within the spray area, increasing the number and duration of contact between the flue gas and the spray slurry. This ensures that the desulfurization reaction proceeds fully even when the flue gas volume is reduced, maintaining a good desulfurization effect.

[0055] By adjusting the parameters of the PID controller (proportional coefficient, integral time constant, differential time constant), the frequency adjustment of the induced draft fan can respond quickly and stably to changes in pollutant concentration, while ensuring that the system will not experience excessive oscillation or overshoot.

[0056] like Figure 2 As shown, the PLC control module 200 includes a parameter control unit 210 and a variable frequency drive unit 220;

[0057] The parameter control unit 210 defines fuzzy sets based on the error values and error change rates between the collected sulfur dioxide and nitrogen oxide concentration data and flue gas flow and the target concentration values in the environmental emission standards, as well as the output parameter adjustment values of the PID controller. The fuzzy sets are: negative large NB, negative medium NM, negative small NS, zero ZO, positive small PS, positive medium PM, and positive large PB.

[0058] The variable frequency drive unit 220 adjusts the proportional coefficient, differential coefficient and integral coefficient of the PID controller according to the parameter adjustment amount of the output PID controller, and uses the PID control algorithm to calculate the operating parameters of the fan, slurry circulation pump and ammonia injection pump;

[0059] Fuzzy rules can reasonably adjust the parameters of the PID controller according to different errors and error change rates, so that the system can achieve better control effects under various working conditions. By continuously applying these rules to adjust the PID parameters according to real-time errors and error change rates, the system can more accurately track the target concentration and improve control accuracy and stability.

[0060] Fuzzy reasoning process:

[0061] First, the membership of the input variable is calculated, and then the "smaller" operation is used to obtain the precondition membership of the rule. According to the precondition membership, the conclusion fuzzy set is "truncated" to obtain the conclusion membership of the rule. The conclusion membership of all rules is operated with a "larger" operation to obtain the fuzzy membership of the final output variable. The center of gravity method is used to convert the fuzzy membership of the output variable obtained by fuzzy reasoning into an accurate adjustment amount.

[0062] In order to better establish a fuzzy rule base, the parameter control unit 210 establishes a fuzzy rule base in the following form:

[0063] IF e is A i AND Δe is B j THEN ΔK p is C ij ;

[0064] Among them, e is the error value, Δe is the error change rate, A i is the fuzzy set of error value e, B j is the fuzzy set of error change rate Δe, ΔK p is the parameter adjustment of the PID controller, C ij ΔK is the PID controller parameter adjustment p fuzzy set.

[0065] The collected sulfur dioxide and nitrogen oxide concentration data and flue gas flow are compared with the target concentration values in the environmental emission standards. The error value and error change rate between the actual collected concentration data and the target concentration are used as input to establish a fuzzy rule base, part of which is shown below:

[0066] Error / rate of change NB NM NS ZO NB PB,NB,PB PB,NB,PM PM,NM,PM PM,NM,PS NM PB,NB,PB PB,NB,PM PM,NM,PM PM,NS,PS NS PM,NM,PB PM,NM,PM PM,NS,PM PS,NS,PS ZO PM,NM,PM PM,NS,PM PS,NS,PS ZO, ZO, ZO

[0067] Take the rule "PB, NB, PB" in the first row and first column as an example:

[0068] Precondition: When the error e is "negatively large" (NB) and the error change rate Δe is "negatively large" (NB);

[0069] Conclusion: The proportional coefficient adjustment ΔKp is "positive and large" (PB), the integral coefficient adjustment ΔKi is "negative and large" (NB), and the differential coefficient adjustment ΔKd is "positive and large" (PB);

[0070] Explanation: When the error between the actual collected concentration data value and the target concentration is a large negative value, and the error change rate is also a large negative value, in order to make the system respond quickly and reduce the error, it is necessary to significantly increase the proportional coefficient Kp (ΔKp is "positive and large"), and at the same time significantly reduce the integral coefficient Ki (ΔKi is "negative and large", and excessive integral effect may cause slow system response or overshoot, so Ki is reduced), and significantly increase the differential coefficient Kd (ΔKd is "positive and large", which enhances the dynamic performance of the system and speeds up the response).

[0071] In order to better calculate the operating parameters of the corresponding equipment, the variable frequency drive unit 220 adopts a discrete PID control algorithm to calculate the operating parameters of the corresponding equipment based on the collected sulfur dioxide and nitrogen oxide concentration data and the error value of the flue gas flow rate. The formula is:

[0072]

[0073] Among them, μ(t) is the equipment operating parameter, K p is the proportionality coefficient, K i is the differential coefficient, K d is the integral coefficient, e(t) is the error value at time t, and e(t-1) is the error value at time t-1.

[0074] Through the above formula, the concentration data of sulfur dioxide and nitrogen oxides and the error value of flue gas flow rate are respectively substituted, and the operating parameters of the slurry circulation pump, ammonia injection pump and induced draft fan are calculated in turn. The operating frequencies of the slurry circulation pump, ammonia injection pump and induced draft fan are dynamically adjusted through the frequency converter to improve the efficiency of exhaust gas treatment.

[0075] Specific control targets are determined for different equipment. For example, the induced draft fan mainly controls the flue gas flow or furnace negative pressure; the slurry circulation pump controls the slurry circulation volume in the desulfurization tower to ensure desulfurization efficiency; and the ammonia injection pump controls the ammonia injection volume to ensure that nitrogen oxide emissions meet standards during the denitrification process.

[0076] According to process requirements and environmental protection standards, set reasonable set values for each control target. For example, determine the set value of flue gas flow rate based on boiler load and environmental protection requirements, determine the set value of slurry circulation volume based on desulfurization efficiency and emission standards, and determine the set value of ammonia injection volume based on denitrification efficiency and nitrogen oxide emission standards;

[0077] The error between the set value and the actual measured value of the control target is calculated in real time, the calculated error is substituted into the discrete PID formula, the control output at the kth moment is calculated, the control output after the limiting processing is converted into the control signal of the frequency converter, and the operating frequency of the induced draft fan, slurry circulation pump and ammonia injection pump is dynamically adjusted through the frequency converter.

[0078] In addition, the collaborative optimization module 300 detects the content of sulfur dioxide and nitrogen oxides in the exhaust gas after desulfurization and denitrification. The PLC logic controller determines the desulfurization and denitrification of the exhaust gas, and returns the exhaust gas that does not meet the standards to the boiler for secondary desulfurization and denitrification. The exhaust gas that meets the standards is introduced into the dust removal tower through the outlet induced draft fan. The electrostatic precipitator voltage is adjusted according to the ammonia content in the exhaust gas. With the goal of minimizing operating costs, a genetic algorithm is used to coordinate the linkage control of desulfurization, denitrification and dust removal.

[0079] The collaborative optimization module 300 includes a detection and determination unit 310 and a genetic optimization unit 320;

[0080] The detection and judgment unit 310 collects real-time data on the content of these two pollutants in the exhaust gas through the sulfur dioxide and nitrogen oxide sensors installed on the exhaust gas pipeline after desulfurization and denitrification. The received sulfur dioxide and nitrogen oxide content data are compared with the set threshold values by the PLC logic controller to determine the desulfurization and denitrification of the exhaust gas.

[0081] The genetic optimization unit 320 takes minimizing the desulfurization agent cost, the denitrification agent cost and the equipment energy consumption cost as the objective function, uses real number coding to encode the decision variables, and selects the decision variable combination corresponding to the optimal individual through selection, inheritance and mutation operations;

[0082] Assume that the amount of desulfurizer added is x1, the amount of denitrifier added is x2, the fan speed is x3, the water pump speed is x4, and the ammonia injection frequency of the ammonia injection device is x5. Then the decision variable vector can be expressed as X = (x1, x2, x3, x4, x5);

[0083] Using real number encoding, the decision variable vector X is directly used as a chromosome. Each chromosome represents a possible combination of decision variables. N chromosomes are randomly generated to form the initial population P. The decision variable x in each chromosome randomly takes a value within its feasible range. The fitness function F is used to evaluate the performance of each chromosome. Since the goal is to minimize operating costs, the fitness function can be defined as the inverse of the objective function. A roulette wheel selection method is used to calculate the probability of each chromosome being selected, and crossover and mutation operations are performed. After the algorithm terminates, the decision variable combination corresponding to the optimal chromosome is the solution that minimizes operating costs. Applying these decision variable values to actual systems can achieve optimized control of the desulfurization and denitrification processes.

[0084] In order to better set the sulfur dioxide and nitrogen oxide content thresholds, the detection and judgment unit 310 adopts a hierarchical threshold setting method, sets the sulfur dioxide and nitrogen oxide content thresholds in the PLC logic controller, divides them into normal zone, warning zone, first-level exceeding zone and second-level exceeding zone, and sets a hierarchical response strategy;

[0085] Set emission standards (SO2≤35mg / m 3 ), the parameter range is divided into normal area, warning area, first level exceeding standard area, and second level exceeding standard area as follows:

[0086] Normal zone: 0-30 (green);

[0087] Warning zone: 30-35 (yellow);

[0088] Level 1: 35-45 (orange);

[0089] Level 2: >45 (red);

[0090] Hierarchical control strategy based on SO2 concentration:

[0091]

[0092] The hierarchical output control strategy forms a closed-loop system through threshold classification → step response → safety protection → adaptive optimization, which can not only ensure process stability but also avoid resource waste.

[0093] In order to prevent malfunctions caused by instantaneous data fluctuations, the detection and determination unit 310 sets corresponding response delays for different threshold intervals and sets upper and lower limits for corresponding device adjustments;

[0094] Set different response delays at different levels to avoid false triggering due to instantaneous fluctuations:

[0095] Warning area: Delay 30 seconds before confirmation and adjustment;

[0096] Level 1 exceeding the limit: 10 seconds delay;

[0097] Level 2 exceeding the standard: immediately;

[0098] The desulfurization and denitrification system is a complex, dynamic system, requiring time for equipment adjustments to reach a stable state. A short response delay can cause the system to be overly sensitive to small changes, requiring frequent adjustments and leaving the system in an unstable, fluctuating state. By setting different response delays, the system can adjust at different paces based on different threshold intervals. For relatively minor changes, such as those in the early warning zone, appropriately extending the response delay allows the system more time to confirm the trend of change, avoiding over-adjustment and achieving smoother system adjustments, which helps maintain system stability and reliability.

[0099] In order to better determine the termination conditions, when the genetic optimization unit 320 uses the genetic algorithm to find the optimal decision variable combination, it is determined that the pollutant emissions meet the standards and the equipment parameters operate within the normal range as constraints;

[0100] Keeping equipment parameters operating within normal ranges is a prerequisite for safe and stable operation. Equipment such as fans, pumps, and agitators in boiler exhaust treatment systems have specific operating parameter ranges, such as motor speed, pressure, and temperature. Limiting these parameters to normal ranges as constraints prevents equipment damage from abnormal conditions such as overload, overheating, and overpressure, extending equipment life and reducing equipment repair and replacement costs.

[0101] Stable equipment operation is crucial to the reliability of the entire boiler exhaust gas treatment system. When equipment parameters exceed their normal range, system performance may decline, treatment results may become unstable, and even system failure may occur. By using genetic algorithms to find the optimal combination of decision variables within the normal range of equipment parameters, we can ensure coordinated operation among system components, improve overall system reliability and stability, and reduce the risk of production interruptions and environmental pollution caused by equipment failures.

[0102] In order to better determine the convergence threshold of the fitness value, the genetic optimization unit 320 runs the genetic algorithm multiple times, observes the change of the fitness value with the number of iterations, analyzes the convergence speed of the algorithm, selects the convergence threshold of the fitness value, and determines the termination condition of the genetic algorithm;

[0103] After multiple tests, it was found that the change in the algorithm's fitness value within 50 iterations was less than 10-3, so the convergence threshold can be set to 10-3. On the contrary, if the algorithm converges slowly and the fitness value still fluctuates greatly over a long period of time, a larger convergence threshold needs to be set to avoid excessive iteration of the algorithm and resulting in low efficiency;

[0104] During the algorithm's execution, monitor the diversity of the population. If population diversity decreases rapidly, the algorithm may converge to a local optimum prematurely. In this case, the convergence threshold can be appropriately increased to allow the algorithm more opportunities to search in different areas and maintain population diversity. Population diversity can be assessed by calculating the similarity between individuals in the population. When the similarity exceeds a certain ratio, increase the convergence threshold.

[0105] like Figure 3 As shown, boiler 1 and boiler 2 generate exhaust gas. By detecting the content of pollutants in boiler 1 and boiler 2, the operating frequency of the inlet induced draft fan is dynamically adjusted to introduce the boiler exhaust gas into the desulfurization and denitrification tower. The PLC control module 200 is used to output the operating parameters of the slurry circulation pump and the ammonia injection pump according to the error value between the concentration of sulfur dioxide and nitrogen oxides in the boiler exhaust gas and the target concentration. The operating frequency of the slurry circulation pump and the ammonia injection pump is dynamically adjusted using the frequency converter to desulfurize and denitrify the exhaust gas. The results of the desulfurization and denitrification are tested. For the boiler exhaust gas that does not meet the standards, it is guided to boiler 1 and boiler 2 through the outlet induced draft fan 1 for secondary desulfurization and denitrification until it meets the exhaust gas emission standards. For the exhaust gas that meets the standards, the exhaust gas is guided to the dust removal tower through the outlet induced draft fan 2 and the outlet induced draft fan 3 for electrostatic dust removal. The impurities in the desulfurization and denitrification tower and the dust adsorbed by the dust removal tower are collected and processed in the ash bin below. The boiler exhaust gas that has undergone dust removal is discharged from the top of the dust removal tower.

[0106] In summary, the working principle of this solution is as follows:

[0107] This boiler exhaust multi-pollutant collaborative control system based on PLC and inverter linkage collects pollutant concentration data, flue gas flow rate and equipment status data in the boiler exhaust in real time through the data acquisition module 100. By detecting the content of pollutants in the boiler, the frequency of the inlet induced draft fan is dynamically adjusted. When the pollutant content is high, the frequency converter is used to increase the operating frequency of the inlet induced draft fan. Conversely, the operating frequency of the inlet induced draft fan is reduced. This achieves dynamic adjustment of the boiler exhaust processing rate based on real-time pollutant concentration data.

[0108] The PLC control module 200 uses a PLC logic controller to calculate the operating parameters of the slurry circulation pump and the ammonia injection pump based on the error value between the concentration of sulfur dioxide and nitrogen oxides in the boiler exhaust gas and the target concentration, and uses a PID control algorithm to dynamically adjust the operating frequency of the slurry circulation pump and the ammonia injection pump using a frequency converter. When the SO2 concentration is higher than the target value, it means that the desulfurization effect needs to be enhanced. The PLC control module 200 increases the operating frequency of the slurry pump, increases the circulation volume of the slurry in the desulfurization tower, and increases the contact area and reaction time between the slurry and SO2 in the flue gas, thereby improving the desulfurization efficiency. Conversely, when the SO2 concentration is lower than the target value, the slurry pump frequency can be appropriately reduced, reducing the slurry circulation volume, while ensuring the desulfurization effect, reducing energy consumption and equipment wear;

[0109] The collaborative optimization module 300 uses the PLC logic controller to determine the desulfurization and denitrification of the exhaust gas, and returns the exhaust gas that does not meet the standards to the boiler for secondary desulfurization and denitrification. The exhaust gas that meets the standards is introduced into the dust removal tower through the outlet induced draft fan. According to the ammonia content in the exhaust gas, the electrostatic precipitator voltage is adjusted to improve the purification rate of pollutants in the boiler exhaust gas, ensure the emission quality of the exhaust gas, and with the goal of minimizing operating costs, adopt a genetic algorithm to coordinate the linkage control of desulfurization, denitrification and dust removal to achieve purification of pollutants in the exhaust gas, while reducing energy consumption and saving resources.

[0110] The above shows and describes the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions are merely preferred examples of the present invention and are not intended to limit the present invention. Various changes and improvements may be made to the present invention without departing from the spirit and scope of the present invention. Such changes and improvements fall within the scope of the present invention. The scope of protection claimed in the present invention is defined by the appended claims and their equivalents.

Claims

1. A collaborative control system for multiple pollutants in boiler tail gas based on the linkage of PLC and frequency converter, characterized by: It includes a data acquisition module (100), a PLC control module (200) and a collaborative optimization module (300); The data acquisition module (100) collects the concentration data of pollutants in the boiler tail gas, the flue gas flow rate and the equipment status data in real time, and introduces the boiler tail gas into the desulfurization and denitrification tower by using the inlet induced draft fan; The PLC control module (200) uses a PLC logic controller to set a driving rule for the inlet induced draft fan, dynamically adjusts the operating frequency of the inlet induced draft fan according to the content of pollutants in the boiler tail gas, takes the error value between the concentration of sulfur dioxide and nitrogen oxides in the boiler tail gas and the target concentration as input, uses a PID control algorithm to output the operating parameters of the slurry circulation pump and the ammonia injection pump, and uses a frequency converter to dynamically adjust the operating frequency of the slurry circulation pump and the ammonia injection pump to remove sulfur and denitrify the boiler tail gas; The collaborative optimization module (300) detects the content of sulfur dioxide and nitrogen oxides in the tail gas after desulfurization and denitrification, and the PLC logic controller determines the desulfurization and denitrification of the tail gas. The tail gas that does not meet the standards is returned to the boiler for secondary desulfurization and denitrification. The tail gas that meets the standards is introduced into the dust removal tower through the outlet induced draft fan. The electric dust removal voltage is adjusted according to the ammonia content in the tail gas. With the goal of minimizing operating costs, a genetic algorithm is used to coordinate the linkage control of desulfurization, denitrification and dust removal.

2. The boiler exhaust gas multi-pollutant coordinated control system based on PLC and inverter linkage according to claim 1 is characterized by: The PLC control module (200) sets reference values of boiler tail gas pollutants according to environmental protection requirements and parameters of the desulfurization and denitrification tower. When the pollutant concentration or flue gas flow rate deviates from the reference value, the PLC logic controller proportionally adjusts the operating frequency of the induced draft fan according to the size of the deviation.

3. The boiler exhaust gas multi-pollutant coordinated control system based on PLC and inverter linkage according to claim 1 is characterized by: The PLC control module (200) includes a parameter control unit (210) and a variable frequency drive unit (220); The parameter control unit (210) defines a fuzzy set for the error value and error change rate between the collected sulfur dioxide and nitrogen oxide concentration data and the flue gas flow rate and the target concentration value in the environmental emission standard, as well as the output parameter adjustment amount of the PID controller, wherein the fuzzy set is: negative large NB, negative medium NM, negative small NS, zero ZO, positive small PS, positive medium PM, and positive large PB; The variable frequency drive unit (220) adjusts the proportional coefficient, differential coefficient and integral coefficient of the PID controller according to the parameter adjustment amount of the output PID controller, and uses the PID control algorithm to calculate the operating parameters of the fan, slurry circulation pump and ammonia injection pump.

4. The boiler tail gas multi-pollutant coordinated control system based on PLC and inverter linkage according to claim 3 is characterized by: The parameter control unit (210) establishes a fuzzy rule base in the following form: IFe is A i ANDΔe is B j THENΔK p is C ij ; Among them, e is the error value, Δe is the error change rate, A i is the fuzzy set of error value e, B j is the fuzzy set of error change rate Δe, ΔK p is the parameter adjustment of the PID controller, C ij is the PID controller parameter adjustment value ΔK p fuzzy set.

5. The boiler tail gas multi-pollutant coordinated control system based on PLC and inverter linkage according to claim 3 is characterized by: The variable frequency drive unit (220) adopts a discrete PID control algorithm to calculate the operating parameters of the corresponding equipment based on the collected concentration data of sulfur dioxide and nitrogen oxides and the error value of the flue gas flow rate. The formula is: Among them, μ(t) is the equipment operating parameter, K p is the proportionality coefficient, K i is the differential coefficient, K d is the integral coefficient, e(t) is the error value at time t, and e(t-1) is the error value at time t-1.

6. The boiler tail gas multi-pollutant coordinated control system based on PLC and inverter linkage according to claim 1 is characterized by: The collaborative optimization module (300) includes a detection and determination unit (310) and a genetic optimization unit (320); The detection and judgment unit (310) collects data on the content of the two pollutants in the exhaust gas in real time through the sulfur dioxide and nitrogen oxide sensors installed on the exhaust gas pipeline after desulfurization and denitrification, and compares the received sulfur dioxide and nitrogen oxide content data with the set threshold values using the PLC logic controller to judge the desulfurization and denitrification of the exhaust gas; The genetic optimization unit (320) takes minimizing the desulfurization agent cost, the denitrification agent cost and the equipment energy consumption cost as the objective function, uses real number coding to encode the decision variables, and selects the decision variable combination corresponding to the optimal individual through selection, inheritance and mutation operations.

7. The boiler exhaust gas multi-pollutant coordinated control system based on PLC and inverter linkage according to claim 6 is characterized by: The detection and judgment unit (310) adopts a hierarchical threshold setting method to set the sulfur dioxide and nitrogen oxide content thresholds in the PLC logic controller, divide them into a normal area, a warning area, a first-level exceeding standard area and a second-level exceeding standard area, and set a hierarchical response strategy.

8. The boiler exhaust gas multi-pollutant coordinated control system based on PLC and inverter linkage according to claim 7 is characterized by: The detection and determination unit (310) sets corresponding response delays for different threshold intervals, and sets upper and lower limits for corresponding device adjustments.

9. The boiler exhaust gas multi-pollutant coordinated control system based on PLC and inverter linkage according to claim 6 is characterized by: When the genetic optimization unit (320) uses the genetic algorithm to find the optimal decision variable combination, it is determined that pollutant emissions meet standards and equipment parameters operate within normal ranges as constraint conditions.

10. The boiler tail gas multi-pollutant coordinated control system based on PLC and inverter linkage according to claim 9 is characterized in that: The genetic optimization unit (320) runs the genetic algorithm multiple times, observes the change of the fitness value with the number of iterations, analyzes the convergence speed of the algorithm, selects the convergence threshold of the fitness value, and determines the termination condition of the genetic algorithm.

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