CN117847537A - Combustion and smoke emission integrated control method and system for waste incineration power plant - Google Patents
Combustion and smoke emission integrated control method and system for waste incineration power plant Download PDFInfo
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Abstract
The invention discloses a method and a system for integrally controlling combustion and smoke emission of a waste incineration power plant, wherein the method comprises the following steps: the main control unit ACC calculates a difference value according to the current garbage combustion working condition and the pollutant emission concentration by utilizing signals of the LSTM intelligent control model and the historical database to generate a prediction signal, and transmits the prediction signal to the main control unit AFC; the main control unit AFC receives the prediction signal and generates a control signal after analysis, and the control signal is transmitted to related equipment, including equipment such as a garbage feeding vehicle, a primary fan, a secondary fan, a smoke circulating fan, a bag-type dust remover, a lime slurry reactor, a dry reactor, an SNCR reaction tower, a boiler, a deaerator, a steam turbine and the like, so that the actual value is close to the prediction value, and the whole-process control from ignition to furnace shutdown is realized. The invention solves the problems of response delay and parameter fluctuation of combustion working conditions or pollutant concentration, and the like, and effectively improves the running level of the unit.
Description
Technical Field
The application relates to the field of automatic control of waste incineration power plants, in particular to a combustion and smoke emission integrated control method of a waste incineration power plant.
Background
The garbage incineration power generation is one of the main modes for treating the household garbage at present, realizes the reduction, harmless and recycling of the garbage, has smaller carbon emission compared with fossil fuel power generation on one hand, avoids methane generated in the landfill process of the household garbage on the other hand, and realizes the double carbon reduction functions of reducing methane generation and replacing fossil fuel power generation. By the end of 2021, the national waste incineration power plant realizes 1.2 tons of carbon reduction by replacing landfill to produce methane, and simultaneously realizes 0.5 hundred million tons of carbon reduction by replacing coal-fired power generation, so that the rapid development of the waste incineration power plant can effectively assist in realizing the 'double carbon' target.
The existing garbage incineration power plant is also developed towards the direction of intellectualization, refinement, innovation and high efficiency, intelligent recognition and signal guidance are adopted in the aspect of garbage collection and storage, the high-efficiency collection and storage of garbage are realized, one-key start-stop, decentralized control and other control technologies are introduced in the aspect of combustion power generation, the running efficiency is improved while the running stability of a unit is ensured, the boiler water supply is heated by a power plant incineration and flue gas emission system, superheated steam is generated to drive a steam turbine to generate electricity, garbage is required to be incinerated, pollutants are eliminated, and the garbage incineration power plant has a vital effect on treating household garbage, building ecological civilization and assisting to realize a double-carbon target, so that the incineration efficiency and the technology for fine pollution treatment are further improved. In the incineration and flue gas emission system, the working condition of the fire grate for incinerating garbage directly influences the working condition of flue gas treatment, and the time required for starting and stopping the system and adjusting the working condition can be greatly reduced by mutually coupling and controlling all equipment in the fire grate incineration and flue gas purification system, so that unnecessary energy consumption is avoided. At present, visualization and centralized control of the whole power generation process of some novel garbage incineration power plants are realized, and under the background that intelligent control technology tends to be mature, a neural network intelligent control model is introduced into operation management of the garbage incineration power plants, so that on one hand, faults caused by manual misoperation can be greatly reduced, and on the other hand, the system running efficiency and the level of fault elimination can be effectively improved. At present, however, the intelligent control scheme of the garbage incinerator for combustion in the furnace and pollutants in the furnace is mainly based on the principles of fuzzy control, PID and the like, mainly aims at the conventional operation working conditions, and the combustion working conditions and the severe fluctuation of the concentration of the pollutants in the flue gas can be caused due to the change of garbage types, so that the conventional control scheme is difficult to realize advanced regulation and economic injection control of the combustion working conditions or the pollutants, and the control precision of the combustion working conditions and the concentration of the pollutants is lower. A high-precision intelligent control scheme is therefore required.
Disclosure of Invention
The invention aims to: the invention provides a method and a system for integrally controlling combustion and smoke emission of a waste incineration power plant, which realize the purposes of accurate, efficient, intelligent and stable operation of the system for incinerating and treating smoke of the waste incineration power plant.
The technical scheme is as follows: in a first aspect, a method for integrally controlling combustion and smoke emission in a waste incineration power plant includes:
the automatic combustion control main control unit ACC calculates a difference value by utilizing signals of the LSTM intelligent control model and the history database according to the current garbage combustion working condition and pollutant emission concentration to generate a prediction signal, and transmits the prediction signal to the automatic smoke control main control unit AFC;
the main control unit AFC judges whether the change rate of the thickness change rate of the garbage material layer represented by the prediction signal meets the specified condition, if so, the intelligent control model of the combustion working condition is utilized to intelligently adjust the primary air blower and the secondary air blower, otherwise, a control signal is sent to increase the valve opening of the primary air blower and the secondary air blower or a load reducing signal is sent to the main control unit ACC;
main control unit AFC judges flue gas NOx and SO represented by predicted signal 2 If the HCl emission concentration change rate meets the specified conditions, the intelligent control model for pollutant treatment is used for intelligently adjusting the lime slurry reactor, the dry reactor and the SNCR reactor, otherwise, a control signal is sent to increase the opening of a valve of a recirculation fan and reduce the opening of a valve of a primary air blower;
the main control unit AFC judges whether the change rate of the concentration of the CO in the flue gas represented by the predicted signal meets the specified condition, if so, the intelligent control model for pollutant treatment is utilized to intelligently adjust the primary air blower and the secondary air blower, otherwise, a control signal is sent to increase the valve opening of the primary air blower and the secondary air blower or a load reducing signal is sent to the main control unit ACC;
the main control unit ACC controls the pusher and the material layer thickness controller based on the load-reducing signal of the main control unit AFC to reduce the garbage feeding reference speed and the fire grate action frequency until the garbage material layer thickness reaches the standard and/or the CO concentration in the discharged flue gas reaches the standard.
Further, for the thickness of the garbage material layer, the main control unit AFC judges whether the change rate of the thickness of the garbage material layer represented by the prediction signal is in the range of a historical normal value, if so, the primary air blower and the secondary air blower are intelligently adjusted by using the intelligent combustion condition control model, and the combustion conditions such as the thickness of the garbage material layer are recorded and input into a historical database for archiving; if not, sending control signals to the primary air blower and the secondary air blower, increasing the opening of the valves of the primary air blower and the secondary air blower, and judging whether the thickness of the garbage material layer at the current moment is smaller than a system set value or not again; if so, the intelligent control model of the combustion working condition is utilized to intelligently adjust the primary air blower and the secondary air blower, if not, a load reduction signal is sent to the main control unit ACC, the main control unit ACC controls the pusher and the material layer thickness controller to reduce the garbage feeding reference speed and the fire grate action frequency until the garbage material layer thickness reaches the standard.
Further, for NOx, SO in the flue gas 2 The concentration of HCl and CO, and the main control unit AFC judges the NOx and SO of the discharged smoke represented by the predicted signal 2 If the HCl concentration change rate is in the range of the historical normal value, the intelligent control model for pollutant treatment is utilized to intelligently adjust the valve opening of the lime slurry reactor, the dry reactor and the SNCR reactor, and the pollutant emission concentration and the time of the outlet are recorded and input into the pollutant emission historical database for archiving; if not, a control signal is sent to the equipment, the valve opening of the lime slurry reactor, the dry method reactor and the SNCR reactor is increased, and the NOx and SO of the purified flue gas at the current moment are judged again 2 Whether the HCl concentration is smaller than the system set value; if yes, the intelligent control model for pollutant treatment is utilized to intelligently adjust the valve opening of the lime slurry reactor, the dry method reactor and the SNCR reactor, and the pollutant discharge concentration and the time of the outlet are recorded and input into the pollutant discharge history database for archiving; if not, sending a load-reducing signal to increase the valve opening of the recirculation fan and reduce the valve opening of the primary air blower until the NOx and SO in the flue gas are discharged 2 The HCl concentration reaches the standard.
Further, for the CO concentration in the flue gas, the main control unit AFC judges whether the CO concentration change rate of the discharged flue gas represented by the prediction signal is in the range of a historical normal value, if so, the intelligent control model for pollutant treatment is utilized to intelligently adjust the primary air blower and the secondary air blower, and the outlet pollutant discharge concentration and time are recorded and input into a pollutant discharge historical database for archiving; if not, sending control signals to the primary air blower and the secondary air blower, increasing the opening of the valves of the primary air blower and the secondary air blower, and judging whether the CO concentration of the purified flue gas at the current moment is smaller than the set value of the system again; if yes, the intelligent control model for pollutant treatment is utilized to intelligently adjust the primary air blower and the secondary air blower, and the pollutant emission concentration and the time of the outlet are recorded and input into the pollutant emission historical database for archiving; if not, a load reduction signal is sent to the main control unit ACC, the garbage feeding reference speed is reduced, the fire grate action frequency is reduced, and the concentration of CO in the discharged flue gas reaches the standard.
Further, the LSTM intelligent control model of the main control unit ACC comprises an input door, a forgetting door and an output door, and the parameters of the input LSTM intelligent control model comprise exhaust gas NOx and SO 2 The input gate receives actual value signals, the output gate transmits signals which accord with the set value range to the historical database, the forgetting gate outputs signals which do not accord with the set value range, the difference value is calculated with the signals of the historical database, and then a prediction signal is generated and transmitted to the main control unit AFC.
Further, the LSTM intelligent control model is trained by a back propagation algorithm to obtain relevant parameters of the LSTM, wherein the training information comprises primary air quantity, secondary air quantity, recirculation air quantity, primary air temperature, garbage thickness, fire grate oxygen content and SO 2 And HCl, NOx, CO gas concentration.
Further, the intelligent control model for combustion working conditions and the intelligent control model for pollutant treatment are based on BP neural network, training is carried out by utilizing a historical database, fan or pollutant treatment power and valve opening are calculated based on the difference value between the actual combustion working conditions or the actual pollutant emission concentration and the combustion working conditions or the pollutant system set values, the calculated values are converted into control signals and output to corresponding PID controllers, and intelligent adjustment is carried out on the fan or the pollutant treatment power and the valve opening.
Further, the intelligent control model for combustion conditions and the intelligent control model for pollutant treatment take dynamic parameters as input parameters, fan or pollutant treatment power as output parameters, data of a historical database as training data, and a 3-layer neural network structure is adopted, wherein the dynamic parameters and the pollutant treatment power are used as training dataThe number of the input layer nodes is 10, the number of the hidden layer nodes is 13, and the number of the output layer nodes is 1; the training data comprises primary air quantity, secondary air quantity, recirculation air quantity, primary air temperature, garbage thickness, fire grate oxygen content and SO 2 HCl, NOx, CO gas concentration, temperature, flow, parameter signals corresponding to the power of the contaminant processor.
Further, the main control unit ACC and the main control unit AFC monitor the working condition of the system in real time through working signals fed back by each device of the waste incineration power plant, when faults occur, the fault devices send corresponding fault signals to a historical fault database and store the fault signals, the main control unit ACC and the main control unit AFC analyze the fault signals through a fuzzy comprehensive evaluation method, a fault source is locked, and an optimization suggestion is provided for a device maintenance plan by combining fault historical data.
In a second aspect, a combustion and smoke emission integrated control system for a waste incineration power plant is configured to implement the combustion and smoke emission integrated control method for a waste incineration power plant according to the first aspect, where the integrated control system includes:
the distributed control system DCS comprises a distributed processing station, a man-machine interface device and a communication system, wherein the distributed processing station comprises a garbage feeding vehicle, a primary fan, a secondary fan, a smoke circulating fan, a bag-type dust remover, a lime slurry reactor, a dry method reactor, an SNCR reaction tower, a boiler, a deaerator, a steam turbine, primary/secondary/reheat attemperator equipment, the man-machine interface device provides garbage type selection through a control panel, a user can input the mixing proportion of garbage or waste of a certain type or any different type, and the communication system uses a PROFIBUS bus to connect an auxiliary machine and each sub-service subsystem in series so that control signals can be transmitted to combustion control and smoke treatment equipment;
the ACC main control unit is internally provided with an LSTM intelligent control model and is used for performing automatic combustion control on garbage incineration;
and the AFC main control unit is internally provided with a combustion working condition intelligent control model and a pollutant treatment intelligent control model and is used for automatically controlling the discharged smoke.
The beneficial effects are that:
(1) The invention provides aIntegrated control method for seed refuse incineration, which uses ACC and AFC as main control unit module to discharge NOx and SO in flue gas 2 The actual values of the HCl concentration, the CO concentration and the garbage layer thickness are transmitted to a main control unit ACC through a sensor, the signals are processed into prediction signals through an LSTM intelligent control model, and the prediction signals are transmitted to the main control unit AFC to carry out related parameters of flue gas NOx and SO 2 And (3) adjusting the concentration of HCl and CO and the thickness of the garbage layer. The main control unit AFC receives the prediction signal from the main control unit ACC and judges the NOx and SO of the exhaust gas represented by the prediction signal 2 And (3) whether the concentration change rate of HCl and CO is in the range of a historical normal value or not, and adjusting related parameters through a combustion working condition, an intelligent control strategy for pollutant treatment and a judgment model.
(2) According to the invention, the actual combustion working condition or the actual outlet pollutant emission concentration is monitored, compared with the combustion working condition or the outlet pollutant system set value, the difference value is calculated, the predicted signal is transmitted to the combustion working condition and pollutant treatment intelligent control model, the fan or pollutant treatment power and the valve opening are calculated, the calculated value is converted into the control signal and output to the corresponding PID controller, and the fan or pollutant treatment power and the valve opening are intelligently regulated, so that the problems of advanced regulation and economic injection control of the combustion working condition or the pollutant are realized, and the problems of delay of the combustion working condition or the pollutant emission concentration, severe parameter fluctuation and the like are avoided.
(3) The invention provides an integrated control system for garbage incineration, which combines the working principles and component arrangement of the existing garbage incineration power generation, steam-water circulation, decentralized control system and intelligent algorithm, and can effectively promote the accurate control in the garbage incineration power generation process, thereby promoting the power generation efficiency, controlling the pollution emission, effectively avoiding the abnormal conditions possibly generated during the incineration of different garbage types, realizing the efficient and stable working state of the incineration and flue gas purification system under less human intervention, and promoting the utilization efficiency of garbage resources.
Drawings
FIG. 1 is a flow chart of the combined control of the garbage combustion working condition by the main control unit ACC and the AFC provided by the embodiment of the invention;
FIG. 2 is the presentThe main control unit ACC and the AFC provided by the embodiment of the invention jointly control the NOx and SO of the acid gas 2 A flow chart of HCl concentration;
FIG. 3 is a flow chart of the combined control of the acid gas CO concentration by the main control unit ACC and the AFC provided by the embodiment of the invention;
FIG. 4 is a schematic diagram of a LSTM intelligent control model process according to an embodiment of the present invention;
FIG. 5 is a flow chart of a combustion condition and pollutant treatment intelligent control strategy provided by an embodiment of the invention;
FIG. 6 is a flowchart of a combined operation of the Master control Unit ACC and AFC provided by an embodiment of the present invention;
FIG. 7 is a flow chart of the whole process of system incineration and flue gas purification according to the embodiment of the invention.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
The invention provides a combustion and smoke emission integrated control method of a garbage incineration power plant, which utilizes two main control units of ACC (Auto Combustion Control, automatic combustion control) and AFC (Automatic Flow Control, automatic smoke control) to cooperate with a DCS system (Distributed Control System, decentralized control system) of the garbage incineration power plant to realize integrated intelligent control of combustion working conditions and pollutant emission of the garbage incineration power plant.
The main control unit ACC receives information input from a control panel, mainly including garbage type and power generation constraint, and also receives status signals from terminal equipment, receives parameters of actual values of signals by using an LSTM (Long-Short-Term-Memory) intelligent control model, calculates differences with data in a history database to generate predicted signals, and directly or indirectly transmits corresponding predicted signals to equipment such as garbage feeding vehicles, primary fans, secondary fans, flue gas circulating fans, bag dust collectors, lime slurry controllers, dry processes, SNCR (selective reduction and denitration) reaction towers, boilers, deaerators, steam turbines, primary/secondary/reheat attemperators and the like to control the equipment.
The main control unit AFC adopts different control modes for different controlled quality according to the characteristics of the flue gas purification system such as the action, hysteresis, priority and the like of different controlled quantities. The closed-loop control mode is adopted to control the wind speed and flow rate of a flue system, the pressure drop of a bed layer in an absorption tower, the liquid level of a process water tank and SO 2 Emission concentration, NOx emission concentration are controlled. In order to improve the control requirements of parameters such as flow, pressure and the like, a proportional-integral control rule is adopted to adapt to the conditions of small control channel time constant and stable system load. To solve SO 2 Differential control is added to such parameters due to hysteresis problems in the system chemistry, NOx concentration emissions. In addition to analog quantity control, starting and stopping of other devices in the system, such as a motor, a fan, a valve and other devices, and control of a device function control group are controlled in a sequential control mode, and finally, a high-automation and stable flue gas purification system is established.
According to the embodiment of the invention, the intelligent control of the incineration and flue gas purification system mainly relates to 3 different processes, which respectively comprise NOx and SO 2 HCl treatment, CO treatment, combustion control and garbage layer thickness control.
Referring to fig. 1, 2 and 3, the exhaust fumes NOx, SO 2 The actual values of the HCl concentration, the CO concentration and the garbage layer thickness are transmitted to the main control unit ACC through the sensor and are input into the LSTM intelligent control model, the LSTM intelligent control model comprises an input door, a forgetting door and an output door, and the input parameters comprise discharged flue gas NOx and SO 2 HCl, CO concentration, and garbage layer thickness. The input gate receives the actual value signal, the output gate transmits the signal which accords with the set value range to the historical database, the forgetting gate outputs the signal which does not accord with the set value range, the difference value is calculated with the signal of the historical database, and then a prediction signal is generated and transmitted to the main control unit AFC.
For the thickness of the garbage material layer, the main control unit AFC receives a prediction signal from the main control unit ACC, judges whether the change rate of the thickness of the garbage material layer represented by the prediction signal is in a history normal value range, if so, intelligently adjusts the primary fan and the secondary fan by utilizing an intelligent control strategy (intelligent combustion working condition control strategy), records the combustion working conditions such as the thickness of the garbage material layer and the like, and inputs the combustion working conditions into a history database for archiving; if not, sending control signals to the primary air blower and the secondary air blower, increasing the opening of the valves of the primary air blower and the secondary air blower, and judging whether the thickness of the garbage material layer at the moment is smaller than a system set value or not again; if so, the intelligent control strategy is utilized to intelligently adjust the primary air blower and the secondary air blower, if not, a load reduction signal is sent to the main control unit ACC, and the main control unit ACC controls the pusher and the material layer thickness controller to reduce the garbage feeding reference speed and the fire grate action frequency until the garbage material layer thickness reaches the standard.
For NOx, SO 2 HCl concentration, a main control unit AFC receives a prediction signal from a main control unit ACC, and judges NOx and SO of discharged smoke represented by the prediction signal 2 If the HCl concentration change rate is in the range of the historical normal value, the intelligent control strategy (the pollutant treatment intelligent control strategy) is utilized to intelligently adjust the valve opening of the lime slurry reactor, the dry reactor and the SNCR reactor, and the outlet pollutant emission concentration and the time are recorded and input into a pollutant emission historical database for archiving; if not, a control signal is sent to the equipment, the valve opening of the lime slurry reactor, the dry method reactor and the SNCR reactor is increased, and the purification of the NOx and SO of the flue gas at the moment is judged again 2 Whether the HCl concentration is smaller than the system set value; if yes, the opening of valves of the lime slurry reactor, the dry reactor and the SNCR reactor are intelligently adjusted by utilizing an intelligent control strategy, and the pollutant emission concentration and the time of an outlet are recorded and input into a pollutant emission historical database for archiving; if not, sending a load-reducing signal to increase the valve opening of the recirculation fan and reduce the valve opening of the primary air blower until the NOx and SO in the flue gas are discharged 2 The HCl concentration reaches the standard.
For the CO concentration, the main control unit AFC receives a prediction signal from the main control unit ACC, judges whether the CO concentration change rate of the discharged flue gas represented by the prediction signal is in a history normal value range, if so, intelligently adjusts the primary fan and the secondary fan by utilizing an intelligent control strategy (a pollutant treatment intelligent control strategy), records the discharge concentration of the outlet pollutant and inputs the time into a pollutant discharge history database for archiving; if not, sending control signals to the primary air blower and the secondary air blower, increasing the opening of the valves of the primary air blower and the secondary air blower, and judging whether the CO concentration of the purified flue gas at the moment is smaller than the set value of the system again; if yes, the intelligent control strategy is utilized to intelligently adjust the primary air blower and the secondary air blower, and the pollutant emission concentration and the time of the outlet are recorded and input into a pollutant emission historical database for archiving; if not, a load reduction signal is sent to the main control unit ACC, the garbage feeding reference speed is reduced, the fire grate action frequency is reduced, and the concentration of CO in the discharged flue gas reaches the standard.
The historical database comprises pollutant emission concentration historical data, garbage incinerator working condition historical data, garbage types and the like.
Referring to fig. 4, the lstm intelligent control model includes an input gate, an output gate, and a forget gate, which control the input and output of data and the cell states of cells within the model, respectively. The LSTM network model may employ a time back propagation algorithm to train the LSTM network to determine relevant parameters of the LSTM. The training information comprises primary air quantity, secondary air quantity, recirculation air quantity, primary air temperature, garbage thickness, fire grate oxygen content and SO 2 And HCl, NOx, CO, etc. If the predicted result is abnormal, outputting the predicted abnormal working condition data from a forgetting gate of the LSTM intelligent control model. The trained model can be used for prediction, prediction signals are generated by combining the difference values of the historical data and are transmitted to each device, and the combustion process of the incinerator and the waste heat boiler is automatically controlled.
The forgetting gate is used for controlling the persistence of information in the cell state, the calculation method is shown as a formula (1),
F t ＝σ(w F ·[h t-1 ，X t ]+b F ) (1)
the input gate is used for updating the information in the cell state, the calculation method is shown in the formula (2) and the formula (3),
A t ＝σ(w A ·[h t-1 ，X t ]+b A ) (2)
B t ＝σ(w B ·[h t-1 ，X t ]+b B ) (3)
the output gate is used for controlling output information, the calculation method is shown in the formulas (4) and (5),
O t ＝σ(w O ·[h t-1 ，X t ]+b o ) (4)
h t ＝O t ×tanh(C t ) (5)
wherein: w (w) F ，w A ，w B ，w O Respectively weighing; b F ，b A ，b B ，b O Respectively offset; h is a t-1 The output of the basic unit at the time t-1; x is X t Is the input of the current moment; c (C) t Is the updated cell state; f (F) t Is the output of the forget gate; a is that t And B is connected with t The product of (2) is the output of the input gate; h is a t Outputting a value for a t time unit; sigma represents a Sigmoid function, and tanh represents a hyperbolic tangent function, as shown in the formulas (6) and (7). X is X t Comprises primary air quantity, secondary air quantity, recirculation air quantity, primary air temperature, garbage thickness, fire grate oxygen content and SO 2 Parameter signals of acid gas concentration such as HCl and NOx. h is a t The method comprises the steps of controlling a primary fan, a secondary fan, a recirculation fan, an air preheater, a pusher, an SNCR reaction tower, a lime bin, an active carbon bin and other equipment to obtain a prediction signal precursor.
FIG. 5 shows an intelligent control strategy for combustion conditions and pollutant treatment, wherein a prediction signal is obtained by comparing a calculated difference value with a set value of a combustion condition or an outlet pollutant system by monitoring an actual combustion condition or an actual outlet pollutant emission concentration, then the prediction signal is transmitted to an intelligent control model of a combustion condition and pollutant treatment device (namely an intelligent control model of a fan or a pollutant treatment device in the figure), fan or pollutant treatment power and valve opening are calculated, and the calculated value is converted into a control signal to be output to a corresponding PID controller, so that the fan or pollutant treatment power and valve opening are intelligently regulated, thereby realizing advanced regulation and economic injection control of the combustion condition or the pollutant, and avoiding the problems of delay of the combustion condition or the pollutant emission concentration, severe parameter fluctuation and the like.
The valve opening of the fan and the pollutant treatment device comprises a valve opening deviation value O RD The control signal converted from the prediction signal of the combustion condition and the difference signal of the emission concentration of the outlet pollutant are processed by function calculation, the difference value between the actual concentration of the pollutant and the set concentration and the difference value between the actual temperature and the set temperature of different region conditions (SNCR, desulfurizing tower and combustion chamber) are converted into an opening difference value signal O P1 、O p2 ……O Pn And O T Giving weights a and b to the opening difference signals to calculate a valve opening deviation value O RD The calculation formula is as follows:
O RD ＝a 1 O P1 +a 2 O P2 +…a n O Pn +bO T (8)
wherein, the intelligent control model for the blower or the pollutant treatment adopts BP neural network, takes dynamic parameters as input parameters and blower or pollutant treatment power as output parameters, wherein, the blower power comprises the air volume power corresponding to a primary blower, a secondary blower and a recirculation blower, and the pollutant treatment power comprises SO 2 And HCl, NOx, CO, etc. Using the data of the historical database as training data, adopting a 3-layer neural network structure, whereinThe number of the input layer nodes is 10, the number of the hidden layer nodes is 13, and the number of the output layer nodes is 1; the training data comprises primary air quantity, secondary air quantity, recirculation air quantity, primary air temperature, garbage thickness, fire grate oxygen content and SO 2 Acid gas concentrations, HCl, NOx, CO, etc., and corresponding contaminant handling power.
The training steps of the intelligent control model of the fan or the pollutant processor based on the BP neural network are as follows:
s1, inputting primary air quantity, secondary air quantity, recirculation air quantity, primary air temperature, garbage thickness, fire grate oxygen content and SO 2 Acid gas concentration, temperature, flow and corresponding pollutant processor power data such as HCl, NOx and the like are used as input vectors;
s2, initializing the collected data in a characteristic standardization manner;
s3, dividing the initialized data set into a training set and a testing set, wherein the training set accounts for most of the data set, 80% of the data set is used for training a model, and 20% of the testing set is used for verifying the generalization capability of the model;
s4, preliminarily designing a BP neural network structure, wherein the BP neural network structure comprises an input layer, a hidden layer and an output layer, determining the node number of each layer, and obtaining a node number interval of the hidden layer according to an empirical formula of the node of the hidden layer;
s5, initializing weights and offsets, and generally adopting a random initialization method;
s6, training a BP neural network model, optimizing model parameters by adopting an error Back Propagation algorithm (BP), and calculating weight and bias adjustment quantity through multiple rounds of iteration, so that a prediction result of the neural network is continuously approximate to an actual value;
s7, evaluating the trained model by using a test set, and calculating prediction error indexes such as Root Mean Square Error (RMSE), mean Absolute Error (MAE) and the like;
and S8, if the model is not good in performance, parameters of the neural network can be further adjusted, and finally, the trained BP neural network model is determined to be used for predicting the fan or pollutant treatment power.
Further, when the equipment fails, the failure equipment sends corresponding failure signals to a historical failure database and stores the failure signals, an ACC main control unit and an AFC main control unit analyze the failure signals by using a fuzzy comprehensive evaluation method, a factor set and an evaluation grade of a target to be evaluated are determined, weight values of all factors in the whole evaluation system are further confirmed, and weights of all factors are determined; then quantitatively evaluating the target layer according to the evaluation grade, carrying the evaluation value into a membership function, and solving a fuzzy relation matrix; and finally, performing fuzzy synthesis operation on the fuzzy evaluation matrix and the weight to obtain a comprehensive evaluation result. The method comprises the following specific steps:
(1) Establishing a factor set U of an object to be evaluated: u= { U 1 ,u 2 ,u 3 …u n }；
(2) Determining an evaluation set V of an object to be evaluated: v= { V 1 ,v 2 ,v 3 …v n }；
(3) Determining the weight of the evaluation factors;
(4) According to the setting of the evaluation grade, fuzzy quantitative evaluation is carried out on each single factor, at the moment, professional personnel can evaluate each factor, the evaluation values are averaged, and a single factor evaluation matrix R= (R) is obtained ij ) m×n ；
(5) Synthesizing a fuzzy comprehensive evaluation result matrix: and (5) ranking the factor sets by using a weighted average membership grade solving method to obtain a sum evaluation result vector S of each factor.
Referring to fig. 6 and 7, a DCS, ACC, AFC integrated garbage incineration control system based on a PROFIBUS comprises a garbage feeding vehicle, a primary fan, a secondary fan, a flue gas circulating fan, a bag-type dust remover, a lime slurry reactor, a dry reactor, an SNCR reaction tower, a boiler, a deaerator, a steam turbine, a primary/secondary/reheat attemperator and other devices, wherein the control layer comprises an ACC main control unit and an AFC main control unit.
The garbage type represents the type of the incinerated garbage, specifically industrial garbage, household garbage, agricultural garbage, medical garbage, stale garbage, kitchen garbage and other types, and other cooperatively treated wastes such as sludge are added, and the mixing proportion of one type or any different type of garbage or waste can be input into the control panel, wherein the household garbage is taken as the main material in the normal case, and other types of garbage or waste are mixed;
the garbage feeding vehicle is used for conveying garbage required for combustion into the incinerator so as to provide heat energy for the boiler. The thickness and the oxygen amount of the garbage layer can influence the combustion working condition, and the feeding amount of the garbage feeding vehicle needs to be adjusted according to the requirements of the combustion working condition;
the primary air blower is used for providing primary air for the fire grate to promote the combustion of the garbage completely and inhibit the generation of pollutants such as nitrogen oxides, and the primary air quantity is mainly used for controlling the combustion efficiency so as to control the load, or enhancing/reducing the oxidation reaction so as to reduce the generation of the pollutants, and the primary air temperature mainly plays a role in drying the garbage, promotes the combustion of the garbage and ensures that the combustion temperature is in a reasonable interval;
the secondary air blower is used for providing secondary air for the fire grate, supplementing oxygen required by garbage combustion, promoting the garbage combustion to be sufficient so as to control the combustion working condition, diluting the concentration of pollutants such as CO and the like, and enabling the pollutant emission of the power plant to meet the requirements;
the smoke circulating fan is used for providing recirculated smoke for the fire grate, before the recirculated smoke enters the fire grate, the recirculated smoke needs to pass through a bag dust collector, a lime slurry controller, a smoke purifying device such as dry desulfurization, SNCR and the like, and the recirculated smoke is sent into the fire grate by the recirculated fan after being purified, so that the recirculated smoke has low oxygen content and can be used for inhibiting oxidation reaction in fire grate combustion, and can control the generation of pollutants such as NOx and the like under specific conditions;
the main function of the main control unit ACC is realized through an LSTM (long-short-term memory) intelligent control model, the LSTM intelligent control model carries out deep learning and training on the property parameters of mediums such as garbage feeding quantity, primary air, secondary air, smoke, boiler water supply, main steam and the like in a historical database in order to control the combustion working condition of the garbage incinerator, and if the prediction result is abnormal, the predicted abnormal working condition data is output from a forgetting door of the LSTM intelligent control model. The trained model can predict, the ACC sends actual data signals to an LSTM intelligent control model, the actual data signals are compared and analyzed with corresponding parameters of a historical database to generate predicted signals, the predicted signals are generated after being analyzed by a main control unit AFC, the control signals are transmitted to related equipment, and the predicted signals are sent to equipment such as a garbage feeding vehicle, a primary fan, a secondary fan, a smoke circulating fan, a bag-type dust remover, a lime slurry reactor, a dry reactor, an SNCR reaction tower, a boiler, a deaerator, a steam turbine, a primary/secondary/reheat attemperator and the like to enable the actual values to be close to the predicted values, so that the whole-course control from ignition to furnace shutdown is realized. The main control unit AFC builds a garbage factory boiler and a smoke purification control model based on the system, and the main control unit AFC is mainly applied to receive a prediction signal of the LSTM intelligent control model of the main control unit ACC combined with historical data and adjust smoke emission purification of the garbage incineration power plant, and the main control unit AFC relates to regulation and control of parameters of primary air, secondary air, primary air temperature and a recirculating fan.
The communication scheme of the DCS system adopts a PROFIBUS bus as a digital communication network system with serial, bidirectional transmission and multi-branch structure, and the serial power plant comprises an auxiliary machine, a smoke treatment system, a combustion system, a steam-water system and the like, so that the ACC and the AFC can send control signals to combustion control and smoke treatment equipment, and the combustion control and smoke treatment equipment can send feedback signals to the ACC and the AFC. The data transmission on the PROFIBUS bus is realized based on digital signals completely, so that the anti-interference capability in the signal transmission process is improved greatly. The PROFIBUS is connected with the intelligent equipment, so that links of A/D conversion are reduced, the acquisition precision of an automatic system is improved, and a guarantee is provided for accurate control.
Claims (10)
1. The integrated control method for the combustion and the smoke emission of the waste incineration power plant is characterized by comprising the following steps:
the automatic combustion control main control unit ACC calculates a difference value by utilizing signals of the LSTM intelligent control model and the history database according to the current garbage combustion working condition and pollutant emission concentration to generate a prediction signal, and transmits the prediction signal to the automatic smoke control main control unit AFC;
the main control unit AFC judges whether the change rate of the thickness change rate of the garbage material layer represented by the prediction signal meets the specified condition, if so, the intelligent control model of the combustion working condition is utilized to intelligently adjust the primary air blower and the secondary air blower, otherwise, a control signal is sent to increase the valve opening of the primary air blower and the secondary air blower or a load reducing signal is sent to the main control unit ACC;
main control unit AFC judges flue gas NOx and SO represented by predicted signal 2 If the HCl emission concentration change rate meets the specified conditions, the intelligent control model for pollutant treatment is used for intelligently adjusting the lime slurry reactor, the dry reactor and the SNCR reactor, otherwise, a control signal is sent to increase the opening of a valve of a recirculation fan and reduce the opening of a valve of a primary air blower;
the main control unit AFC judges whether the change rate of the concentration of the CO in the flue gas represented by the predicted signal meets the specified condition, if so, the intelligent control model for pollutant treatment is utilized to intelligently adjust the primary air blower and the secondary air blower, otherwise, a control signal is sent to increase the valve opening of the primary air blower and the secondary air blower or a load reducing signal is sent to the main control unit ACC;
the main control unit ACC controls the pusher and the material layer thickness controller based on the load-reducing signal of the main control unit AFC to reduce the garbage feeding reference speed and the fire grate action frequency until the garbage material layer thickness reaches the standard and/or the CO concentration in the discharged flue gas reaches the standard.
2. The method of claim 1, wherein for the thickness of the garbage material layer, the main control unit AFC judges whether the change rate of the thickness of the garbage material layer represented by the prediction signal is in a range of a historical normal value, if so, the primary fan and the secondary fan are intelligently adjusted by using the intelligent control model of the combustion working condition, and the combustion working conditions such as the thickness of the garbage material layer are recorded and input into the historical database for archiving; if not, sending control signals to the primary air blower and the secondary air blower, increasing the opening of the valves of the primary air blower and the secondary air blower, and judging whether the thickness of the garbage material layer at the current moment is smaller than a system set value or not again; if so, the intelligent control model of the combustion working condition is utilized to intelligently adjust the primary air blower and the secondary air blower, if not, a load reduction signal is sent to the main control unit ACC, the main control unit ACC controls the pusher and the material layer thickness controller to reduce the garbage feeding reference speed and the fire grate action frequency until the garbage material layer thickness reaches the standard.
3. The method according to claim 1, characterized in that for NOx, SO in flue gas 2 The concentration of HCl and CO, and the main control unit AFC judges the NOx and SO of the discharged smoke represented by the predicted signal 2 If the HCl concentration change rate is in the range of the historical normal value, the intelligent control model for pollutant treatment is utilized to intelligently adjust the valve opening of the lime slurry reactor, the dry reactor and the SNCR reactor, and the pollutant emission concentration and the time of the outlet are recorded and input into the pollutant emission historical database for archiving; if not, a control signal is sent to the equipment, the valve opening of the lime slurry reactor, the dry method reactor and the SNCR reactor is increased, and the NOx and SO of the purified flue gas at the current moment are judged again 2 Whether the HCl concentration is smaller than the system set value; if yes, the intelligent control model for pollutant treatment is utilized to intelligently adjust the valve opening of the lime slurry reactor, the dry method reactor and the SNCR reactor, and the pollutant discharge concentration and the time of the outlet are recorded and input into the pollutant discharge history database for archiving; if not, sending a load-reducing signal to increase the valve opening of the recirculation fan and reduce the valve opening of the primary air blower until the NOx and SO in the flue gas are discharged 2 The HCl concentration reaches the standard.
4. The method according to claim 1, wherein for the concentration of CO in the flue gas, the main control unit AFC judges whether the change rate of the concentration of CO in the discharged flue gas represented by the prediction signal is in a range of historical normal values, if so, the primary fan and the secondary fan are intelligently adjusted by using the intelligent control model for pollutant treatment, and the outlet pollutant discharge concentration and time are recorded and input into the pollutant discharge historical database for archiving; if not, sending control signals to the primary air blower and the secondary air blower, increasing the opening of the valves of the primary air blower and the secondary air blower, and judging whether the CO concentration of the purified flue gas at the current moment is smaller than the set value of the system again; if yes, the intelligent control model for pollutant treatment is utilized to intelligently adjust the primary air blower and the secondary air blower, and the pollutant emission concentration and the time of the outlet are recorded and input into the pollutant emission historical database for archiving; if not, a load reduction signal is sent to the main control unit ACC, the garbage feeding reference speed is reduced, the fire grate action frequency is reduced, and the concentration of CO in the discharged flue gas reaches the standard.
5. The method according to claim 1, wherein the LSTM intelligent control model of the main control unit ACC comprises an input gate, a forget gate, an output gate, and the parameters of the input LSTM intelligent control model comprise exhaust fumes NOx, SO 2 The input gate receives actual value signals, the output gate transmits signals which accord with the set value range to the historical database, the forgetting gate outputs signals which do not accord with the set value range, the difference value is calculated with the signals of the historical database, and then a prediction signal is generated and transmitted to the main control unit AFC.
6. The method of claim 5, wherein the LSTM intelligent control model is trained by a back propagation algorithm to obtain relevant parameters of the LSTM, and the training information comprises primary air quantity, secondary air quantity, recirculation air quantity, primary air temperature, garbage thickness, fire grate oxygen content and SO 2 And HCl, NOx, CO gas concentration.
7. The method according to claim 1, wherein the intelligent control model for combustion conditions and the intelligent control model for pollutant treatment are based on a BP neural network, trained by using a historical database, calculated to obtain fan or pollutant treatment power and valve opening based on the difference between the actual combustion conditions or actual outlet pollutant emission concentration and the combustion conditions or outlet pollutant system set values, and converted into control signals to be output to corresponding PID controllers, and the fan or pollutant treatment power and valve opening are intelligently adjusted.
8. The method of claim 7, wherein the intelligent control model for combustion conditions and the intelligent control model for pollutant treatment take dynamic parameters as input parameters, take fan or pollutant treatment power as output parameters, take data of a historical database as training data, and adopt a 3-layer neural network structure, wherein the number of nodes of an input layer is 10, the number of nodes of an hidden layer is 13, and the number of nodes of an output layer is 1; the training data comprises primary air quantity, secondary air quantity, recirculation air quantity, primary air temperature, garbage thickness, fire grate oxygen content and SO 2 HCl, NOx, CO gas concentration, temperature, flow, parameter signals corresponding to the power of the contaminant processor.
9. The method according to claim 1, wherein the main control unit ACC and the main control unit AFC monitor the system working conditions in real time by working signals fed back to each device of the waste incineration power plant, when a fault occurs, the fault device sends corresponding fault signals to a historical fault database and stores the fault signals, the main control unit ACC and the main control unit AFC analyze the fault signals through a fuzzy comprehensive evaluation method, lock fault sources, and provide optimization suggestions for a device maintenance plan in combination with fault historical data.
10. A waste incineration power plant combustion and smoke emission integrated control system for implementing the waste incineration power plant combustion and smoke emission integrated control method according to any one of claims 1-9, characterized in that the system comprises:
the distributed control system DCS comprises a distributed processing station, a man-machine interface device and a communication system, wherein the distributed processing station comprises a garbage feeding vehicle, a primary fan, a secondary fan, a smoke circulating fan, a bag-type dust remover, a lime slurry reactor, a dry method reactor, an SNCR reaction tower, a boiler, a deaerator, a steam turbine, primary/secondary/reheat attemperator equipment, the man-machine interface device provides garbage type selection through a control panel, a user can input the mixing proportion of garbage or waste of a certain type or any different type, and the communication system uses a PROFIBUS bus to connect an auxiliary machine and each sub-service subsystem in series so that control signals can be transmitted to combustion control and smoke treatment equipment;
the ACC main control unit is internally provided with an LSTM intelligent control model and is used for performing automatic combustion control on garbage incineration;
and the AFC main control unit is internally provided with a combustion working condition intelligent control model and a pollutant treatment intelligent control model and is used for automatically controlling the discharged smoke.
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