CN109062053B - Denitration ammonia injection control method based on multivariate correction - Google Patents
Denitration ammonia injection control method based on multivariate correction Download PDFInfo
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Abstract
The invention relates to a denitration ammonia injection control method based on multivariate correction, belongs to the technical field of ammonia injection control of a denitration system of a thermal generator set, and solves the problem of severe fluctuation of NOx at an outlet of an SCR system in the prior art. The method comprises the following steps: acquiring measurement data and working condition information of a denitration system instrument in real time; constructing a prediction model of the NOx content at the inlet of the SCR denitration system, and predicting the NOx content at the inlet of the SCR denitration system at the current moment; based on the predicted NOx content and the measured data of the SCR system inlet, performing ammonia injection amount feedforward control and prediction correction, generating an ammonia injection amount control instruction at the current moment, controlling an ammonia injection adjusting valve and adjusting the ammonia injection amount. According to the invention, on the premise of ensuring that the emission of the NOx in the flue gas meets the environmental protection index, the fluctuation and the spatial deviation of the NOx at the outlet of the SCR denitration system are greatly reduced through the accurate prediction model of the NOx content of the SCR inlet denitration system and the intelligent feedforward control method, so that the average value of the NOx at the outlet is improved, the ammonia injection amount is reduced, the ammonia escape level is reduced, and the denitration cost is reduced.
Description
Technical Field
The invention relates to the technical field of ammonia injection control of a denitration system of a thermal generator set, in particular to a denitration ammonia injection control method based on multivariate correction.
Background
Research on an SCR (Selective Catalytic Reduction) denitration system mainly focuses on the physical principle, equipment structure and operation mode, research on an automatic denitration control strategy is not carried out, and the automatic control quality of the denitration system is closely related to the long-term operation cost of a power plant. Due to denitration controlled object (NH) 3 Flow-chimney inlet NOx concentration) is close to 3min, the whole response process is as long as ten minutes and several minutes, which is a typical large-lag controlled object, and the SCR denitration process itself is a complex nonlinear chemical reaction process, and as the catalyst is continuously consumed, the dynamic characteristics of the controlled process of denitration can change greatly. Therefore, a simple PID control (proportional-integral-derivative control) is adoptedMachine) solution has difficulty achieving the desired quality of control.
Currently, research on the control of ammonia injection systems also focuses primarily on optimizing existing control systems. Such as: 1. load feedforward is introduced, timeliness of the control system is enhanced when the load is changed, and proportional-integral control parameters in the controller are set, so that concentration of outlet nitrogen oxides is changed along with change of the load, and stability of the control system is enhanced when the load is changed. However, the method only adds the load as an influence factor into the control process, and other influence factors are not considered yet; 2. the ammonia spraying process is optimized by establishing a strict mathematical model and applying a modern control theory, and the method is not suitable for practical engineering application; 3. the method is characterized in that the ammonia injection amount in an ammonia injection system is controlled by applying a mixed structure radial basis function neural network method, the structure has certain dynamic adjustment capability by establishing an ammonia-nitrogen ratio and a generalized mathematical model of inlet and outlet NOx (nitrogen oxide), but the number of neurons of a hidden layer is selected as a fixed value, and the number of the selected hidden layer cannot be guaranteed to be an optimal value; 4. the ammonia spraying amount of the ammonia spraying system is predicted and controlled based on a model, but the model is established by adopting data on a plurality of fixed load points, and the model has larger deviation with the actual operation condition of the control system.
Disclosure of Invention
In view of the above analysis, the present invention aims to provide a method for controlling denitration ammonia injection based on multivariate correction, so as to solve the problem in the prior art that the NOx measurement delay at the inlet and outlet of the SCR system is huge, so that the ammonia injection control loop cannot adapt to the characteristics of nonlinearity, large delay and fast time variation in the denitration process, which causes severe outlet NOx fluctuation.
The purpose of the invention is mainly realized by the following technical scheme:
the method for controlling denitration ammonia injection based on multivariate correction comprises the following steps:
acquiring measurement data of an SCR denitration system instrument and working condition information of a generator set in real time;
constructing a prediction model of the NOx content at the inlet of the SCR denitration system, and predicting the current state according to the working condition information of the generator setNO at inlet of SCR denitration system at any moment X Content (c);
NO at inlet of SCR denitration system at current moment based on prediction X Carrying out feedforward control and prediction correction on the ammonia injection amount according to the content and measurement data of an SCR denitration system instrument, and generating an ammonia injection amount control instruction at the current moment;
and controlling an ammonia injection regulating valve according to the ammonia injection amount control instruction to regulate the ammonia injection amount.
The invention has the following beneficial effects:
according to the invention, the problems caused by large hysteresis, complexity and nonlinearity of a denitration process can be well solved through an intelligent feedforward control method of an SCR inlet NOx accurate prediction model and an ultra-relaxation model, and on the premise of ensuring that the emission of flue gas NOx meets the environmental protection index, the fluctuation and the spatial deviation of the outlet NOx are greatly reduced, the outlet NOx average value is improved, the ammonia injection amount is reduced, the ammonia escape level is reduced, and the denitration cost is reduced.
On the basis of the scheme, the invention is also improved as follows:
further, the performing ammonia injection amount feedforward control includes:
and carrying out ammonia injection amount feedforward control through an outlet NOx content set value of the SCR denitration system, an inlet NOx content prediction model of the SCR denitration system and an inlet NOx content actual value of the SCR denitration system.
Further, the method also comprises the following steps: and correcting the NOx content set value at the outlet of the SCR denitration system according to the ammonia escape rate at the outlet of the SCR denitration system obtained in real time.
Further, the performing ammonia injection amount prediction correction includes:
deviation calculation is carried out on a set value of the NOx content at the outlet of the SCR denitration system and a feedback value of the NOx content at the outlet of the SCR denitration system, and then ammonia injection amount prediction correction is carried out;
carrying out ammonia spraying amount disturbance test under different unit loads to obtain NO at the outlet of the SCR denitration system X Dynamic characteristic of content, according to the dynamic characteristic, obtaining NO at the outlet of SCR denitration system in real time X The fluctuation trend of the content feedback value corrects the ammonia injection amount prediction.
The beneficial effect of adopting the further scheme is that: according to the invention, the ammonia injection control process is optimized based on SCR outlet ammonia escape closed-loop correction, namely, the ammonia escape rate of the denitration outlet is added into the ammonia injection amount correction link, so that the outlet ammonia escape rate and the ammonia injection amount can be effectively reduced. The optimization can reduce the escape rate of ammonia by more than 3ppm compared with the prior optimization.
Further, the performing ammonia injection amount prediction correction further includes:
by analyzing NO and NO in flue gas at the outlet of the SCR denitration system under different loads of the unit 2 The reasonable ammonia nitrogen molar ratio under different load working conditions is determined, the ammonia spraying amount is adjusted, and the phenomenon of yellow smoke is prevented.
Further, a unit load, air volume and coal volume are used as input parameters to construct a prediction model of the NOx content at the inlet of the SCR denitration system.
Further, constructing a prediction model of the NOx content at the inlet of the SCR denitration system, and predicting NO at the inlet of the SCR denitration system at the current moment according to the working condition information of the generator set X The content comprises the following steps:
screening and processing working condition information data of the generator set through the SPSS, and extracting main components;
searching for optimal parameters by combining a particle swarm optimization algorithm to obtain an optimal parameter combination;
and predicting the NOx content at the inlet of the SCR denitration system at the current moment through an SVM prediction model.
Further, the correcting the set value of the NOx content at the outlet of the SCR denitration system according to the ammonia slip rate at the outlet of the SCR denitration system obtained in real time includes:
measuring the ammonia escape rate and the denitration efficiency of flues at two sides of the SCR denitration system in real time;
and comparing the ammonia escape rate and the denitration efficiency of the flues at the two sides, and correcting the set value of the outlet NOx of the flue at the side with higher ammonia escape rate.
Further, still include: and correcting the prediction model of the NOx content at the inlet of the SCR denitration system by using the actual value of the NOx content at the inlet of the SCR denitration system.
In the invention, the technical schemes can be combined with each other to realize more preferable combination schemes. Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
Drawings
The drawings, in which like reference numerals refer to like parts throughout, are for the purpose of illustrating particular embodiments only and are not to be considered limiting of the invention.
FIG. 1 is a flow chart of a control method for denitration ammonia injection based on multivariate calibration according to an embodiment of the present invention;
FIG. 2 is a flowchart illustrating the calibration of the set point for the NOx content at the outlet of the SCR denitration system in accordance with an embodiment of the present invention;
FIG. 3 is a diagram of NO at the inlet of the mixed SPSS-PSO-SVMSCR denitration system in an embodiment of the present invention X Content prediction flow chart.
Detailed Description
The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate preferred embodiments of the invention and together with the description, serve to explain the principles of the invention and not to limit the scope of the invention.
One embodiment of the present invention discloses a method for controlling denitration ammonia injection based on multivariate correction, as shown in fig. 2, comprising the following steps:
s1, acquiring measurement data of an SCR denitration system instrument and working condition information of a generator set in real time;
s2, constructing a NOx content prediction model at the inlet of the SCR denitration system, and predicting NO at the inlet of the SCR denitration system at the current moment according to the working condition information of the generator set X The content;
step S3, predicting NO at inlet of SCR denitration system at current time based on prediction X The measurement data of the instrument of the content and SCR denitration system is used for carrying out feedforward control and prediction correction on the ammonia injection amount to generate the ammonia injection amount control at the current momentMaking an instruction;
and S4, controlling an ammonia injection regulating valve according to the ammonia injection amount control instruction, and regulating the ammonia injection amount.
Compared with the prior art, the denitration ammonia injection control method based on multivariate correction provided by the embodiment can well solve the problems caused by large hysteresis, complexity and nonlinearity of the denitration process through the SCR inlet NOx accurate prediction model and the intelligent feedforward control method, greatly reduce fluctuation and spatial deviation of outlet NOx, improve the average value of the outlet NOx, reduce ammonia injection amount, reduce ammonia escape level and reduce denitration cost on the premise of ensuring that the emission of the flue gas NOx meets environmental protection indexes. Based on theoretical calculation and numerical simulation results, the method can reduce the fluctuation of NOx at the denitration outlet by more than 20% relative to that before optimization, and reduce the total ammonia injection amount by more than 4% relative to that before optimization.
Specifically, in step S1, measuring data of an SCR denitration system instrument and working condition information of a generator set are obtained in real time;
wherein, the measurement data of the SCR denitration system instrument (NO at the inlet of the SCR denitration system) X Actual content value, ammonia escape rate at outlet of SCR denitration system, and NO at outlet of SCR denitration system X Content feedback value, etc.) and the working condition information (unit load, air quantity, coal quantity, etc.) of the generator set are directly uploaded to the DCS, and the relevant data in the DCS can be read through the communication between the OPC or MODBUS and the DCS of the power plant.
In step S2, a NOx content prediction model of an inlet of the SCR denitration system is constructed, and NO of the inlet of the SCR denitration system at the current moment is predicted according to the working condition information of the generator set X The content;
in view of the large delay characteristic of the SCR denitration system, the control strategy in the embodiment adopts a prediction control method with an estimation function to realize the stable operation of the NOx at the outlet of the SCR.
The method has the advantages that the NOx content at the inlet of the SCR denitration system is predicted through the NOx content prediction model at the inlet of the SCR denitration system, and the prediction model is used as an important parameter of ammonia injection feedforward and participates in the closed-loop control of the total ammonia injection amount, so that the problem of delay in the measurement of the NOx content at the inlet of the SCR denitration system is solved. In particular, the deviceAn inlet NOx accurate prediction model is established according to combustion working conditions such as air quantity, coal quantity and load of the generator set, and NO at the inlet of the SCR denitration system at the current moment is obtained through the real-time obtained working condition information prediction X And (4) content.
A prediction model of the inlet NOx content of the SCR denitration system is constructed, as shown in fig. 3, data is screened and processed through SPSS (Statistical Product and Service Solutions), an SVM is used as the prediction model, and an optimal parameter is found by combining a Particle Swarm Optimization algorithm (PSO), so as to obtain an inlet NOx accurate prediction model with good prediction accuracy. The method specifically comprises the following steps:
step S201, SPSS principal component analysis is carried out to eliminate the correlation among the variables and remove the variables with smaller influence so as to avoid causing deviation of the conclusion.
The principal components are small comprehensive variables converted from a plurality of single variables under the premise of less information loss, each group component is obtained by linear combination of original variables, and the principal components have no correlation. Assuming that the original variable matrix X is composed of p vectors, and is denoted by X = (X1, X2., xp), the principal component matrix Y is composed of the following vectors, which satisfy the following equation:
Y i ＝b i1 X 1 +b i2 X 2 +…+b ip X p
in the formula, b i1 …b ip Respectively, the coefficients of the ith vector.
Through linear transformation of the formula, the statistical properties of the obtained principal components are not unique, reasonable principal component extraction needs to meet three conditions, and the square sum of the coefficient corresponding to each principal component is 1; the different principal components are linearly independent; the variance of the principal component extracted first is always larger than that of the principal component extracted later.
The extraction coefficient of the principal component cannot be directly obtained by SPSS, but a factor load matrix ξ = (ξ) based on principal component analysis can be obtained i1 ,ξ i2 ,…ξ ip ) (p is the number of vectors), q common factors are extracted, and the extracted factor model can be expressed as follows:
ZX i ＝ξ i1 f 1 +ξ i2 f 2 +…+ξ iq f q +ε i
wherein i = (1, 2 \8230p), q is number of common factors, epsilon i Is a special factor.
Wherein the relation between the factor load coefficient and the principal component coefficient is
The variance corresponding to the jth principal component.
The principal component can be expressed as:
wherein λ is j The variance corresponding to the jth principal component; p is the number of vectors; ZX is the extracted factor model; xi shape pj Is a factor load matrix vector.
Step S202, obtaining an optimal parameter combination through a Particle Swarm Optimization (PSO) algorithm to achieve optimal prediction precision;
the particle swarm Z is in a D-dimensional search space, and each particle (working condition information such as air volume, coal volume, load, boiler body oxygen volume, secondary air volume and the like of a generator set) is represented by a D-dimensional vector, and the speed and the position of the particle swarm Z are updated according to the following formula.
In the formula: v id Is the velocity of the ith particle; z is a linear or branched member id Is the position of the ith particle; p id Is a population individual extremum; p gd Is a global extremum; k is the kth iteration; c. C 1 And c 2 Learning factors which are non-negative constants in value are considered as cognitive and social parameters respectively; r1 and r2 are two random functions with a value range of [0,1 ]]For increasing search randomness; w reflects the degree to which the particle inherits the previous velocity in velocity, i.e., the inertial weight; α is a constraint factor that limits the speed weight.
And comparing the adaptive value of the historical best position of each particle with the adaptive value of the global best position, determining a global optimal value until a condition is met, and terminating the PSO operation.
And S203, matlab simulation of a Support Vector Machine (SVM) is carried out, the NOx content at the boiler outlet at the current moment is predicted, and the ammonia injection amount is formulated.
According to the principle of minimizing the structural risk, the SVM transformation research process is to solve an optimization problem, and finally a solving function is to maximize a quadratic programming equation through the mutual transformation of dual problems.
And solving the optimal classification hyperplane by adopting a Lagrange operator, wherein a decision function is shown as the following formula:
where x is the sample in the training set, a i * (ii) a solution to the ith final dual optimization problem; b is a mixture of * ＝1-w 0 x i ，y i =1 or b * ＝-1-w 0 x i ,y i ＝-1，
The transfer functions of the SCR reactors under different loads are obtained through tests, and then the advanced control model is implemented in a targeted manner. The data obtained by the test are gradually accumulated, automatic learning is achieved, rapid judgment and adjustment in combination with a burner and during fuel change are gradually achieved, (the problems of blockage, abrasion failure and the like of the SCR device can be found in time according to the data change trend, the operation mode can be adjusted in time), the frequency of real-time test is gradually reduced, and finally intelligent and fine control of the SCR system is achieved.
In order to further improve the accuracy of the prediction model, the constructed model is continuously calibrated through the measured actual NOx content at the inlet of the SCR denitration system.
Step S3, predicting NO at the inlet of the SCR denitration system at the current moment based on the prediction X Carrying out feedforward control and prediction correction on the ammonia spraying amount according to the content and measurement data of an SCR denitration system instrument, and generating an ammonia spraying amount control instruction at the current moment;
after the system is put into operation with the ammonia escape instrument, the ammonia escape rate of the denitration outlet is added into a correction link by combining the real-time ammonia escape measurement data and the NOx content of the flue gas at the SCR outlet, the ammonia injection amount control process of the SCR denitration system is optimized, the ammonia escape rate and the ammonia injection amount at the outlet can be effectively reduced, and therefore the ammonia escape rate can be reduced by more than 3ppm compared with the ammonia escape rate before optimization.
And S301, performing ammonia injection amount feedforward control by using the set value of the NOx content at the outlet of the SCR denitration system, the prediction model of the NOx content at the inlet of the SCR denitration system and the actual value of the NOx content at the inlet of the SCR denitration system.
Correcting the NOx content set value at the outlet of the SCR denitration system according to the ammonia escape rate at the outlet of the SCR denitration system measured in real time by an accurate ammonia escape measurement technology and the denitration efficiency of the flues at two sides, as shown in FIG. 2;
specifically, the ammonia escape rate and the denitration efficiency of the flues on the two sides A and B are compared, an influence factor (namely a function of the difference value between the ammonia escape rate and the denitration efficiency of the flues on the two sides A and B) is generated, and the side with the higher ammonia escape rate is corrected. Generally, the higher the denitration efficiency, the higher the ammonia slip. Therefore, when the ammonia slip on one side is high (the influence factor is in accordance with the normal condition), the ammonia injection amount on the side is considered to be too high, and then the ammonia injection amount is adjusted by correcting the NOx set value at the outlet of the SCR denitration system on the corresponding side, so that the purpose of balancing the ammonia slip on the two sides is achieved.
In addition, in order to further reasonably control the predicted ammonia spraying amount, NO and NO in the smoke are analyzed under different loads of the unit 2 The reasonable ammonia nitrogen molar ratio under different load working conditions is determined, and the phenomenon of yellow smoke is prevented.
It is emphasized that in order to ensure the accuracy and timeliness of ammonia spraying amount in the dynamic process of the unit, the measurement of flue gas flow is consideredThe inaccuracy and the hysteresis of NOx measurement adopt a soft measurement method to dynamically correct the measurement parameters in the control; the soft measurement is indirectly obtained through a large amount of measured data, and NO is overcome X The slow reaction of sampling and measuring of the measuring instrument.
And S302, predicting and correcting the ammonia injection amount by the NOx content of the smoke at the SCR outlet.
In order to increase the stability of ammonia injection control in variable load, in this embodiment, an ammonia injection amount disturbance test is performed under three different unit load conditions (preferably, 660MW (100% load), 495MW (75% load), and 330MW (50% load)), so as to obtain the dynamic characteristic of the SCR outlet, and the dynamic characteristic is used as a design basis of a closed-loop control strategy; NO at outlet of SCR denitration system X The fluctuation trend of the content feedback value corrects the ammonia injection amount prediction.
In order to further improve the accuracy of the ammonia injection amount prediction, the deviation between the outlet NOx set value and the outlet NOx feedback value of the SCR denitration system is calculated, and the ammonia injection amount prediction correction is performed as part of a prediction control system of the ammonia injection main circuit.
And S4, controlling an ammonia spraying adjusting valve according to the ammonia spraying amount control instruction, and adjusting the ammonia spraying amount.
And generating an optimization instruction through the control processing of the steps. And transmitting the optimization instruction after analysis processing to a DCS, adjusting an ammonia spraying adjusting valve through the DCS, realizing the control of ammonia spraying amount, and adjusting and updating the ammonia spraying amount in real time.
Those skilled in the art will appreciate that all or part of the flow of the method implementing the above embodiments may be implemented by hardware associated with computer program instructions, and the program may be stored in a computer readable storage medium. The computer readable storage medium is a magnetic disk, an optical disk, a read-only memory or a random access memory, etc.
While the invention has been described with reference to specific preferred embodiments, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the invention as defined in the following claims.
Claims (2)
1. A denitration ammonia injection control method based on multivariate correction is characterized by comprising the following steps:
the method comprises the steps of obtaining measurement data of an SCR denitration system instrument and working condition information of a generator set in real time, wherein the measurement data of the SCR denitration system instrument comprises the following steps: NO at inlet of SCR denitration system X Actual content value, ammonia escape rate at outlet of SCR denitration system, and NO at outlet of SCR denitration system X A content feedback value; the working condition information of the generator set comprises unit load, air volume and coal volume;
constructing a prediction model of the NOx content at the inlet of the SCR denitration system, and predicting the NOx content at the inlet of the SCR denitration system at the current moment through the real-time acquired working condition information, wherein the prediction model comprises the following steps:
the working condition information data of the generator set is screened and processed through the SPSS, main components are extracted, correlation among variables is eliminated, and meanwhile, the variables with smaller influence are removed;
searching for optimal parameters by combining a particle swarm optimization algorithm to obtain an optimal parameter combination;
predicting the NOx content at the inlet of the SCR denitration system at the current moment through an SVM prediction model;
correcting the prediction model of the NOx content at the inlet of the SCR denitration system by using the actual value of the NOx content at the inlet of the SCR denitration system;
NO at inlet of SCR denitration system at current moment based on prediction X Carrying out feedforward control and prediction correction on the ammonia injection amount according to the content and measurement data of an SCR denitration system instrument, and generating an ammonia injection amount control instruction at the current moment;
the performing ammonia injection amount feedforward control includes: carrying out ammonia injection amount feedforward control on the NOx content at the inlet of the SCR denitration system and the actual value of the NOx content at the inlet of the SCR denitration system at the current moment, which are obtained through the set value of the NOx content at the outlet of the SCR denitration system and the prediction model of the NOx content at the inlet of the SCR denitration system;
correcting the NOx content set value at the outlet of the SCR denitration system according to the ammonia slip rate at the outlet of the SCR denitration system obtained in real time, wherein the correction comprises the following steps:
measuring the ammonia escape rate and the denitration efficiency of the flues at two sides of the SCR denitration system in real time;
comparing the ammonia escape rate and the denitration efficiency of the flues at the two sides, and correcting the set value of the outlet NOx of the flue at the side with higher ammonia escape rate;
the performing ammonia injection amount prediction correction comprises: deviation calculation is carried out on a set value of the NOx content at the outlet of the SCR denitration system and a feedback value of the NOx content at the outlet of the SCR denitration system, and then ammonia injection amount prediction correction is carried out; carrying out ammonia spraying amount disturbance test under different unit loads to obtain NO at the outlet of the SCR denitration system X Dynamic characteristic of content, according to the dynamic characteristic, obtaining NO at the outlet of SCR denitration system in real time X The fluctuation trend of the content feedback value is used for predicting and correcting the ammonia spraying amount;
and controlling an ammonia injection regulating valve according to the ammonia injection amount control instruction to regulate the ammonia injection amount.
2. The method of claim 1, wherein said performing ammonia injection prediction correction further comprises:
by analyzing NO and NO in flue gas at outlet of SCR denitration system under different loads of unit 2 The reasonable ammonia nitrogen molar ratio under different load working conditions is determined, the ammonia spraying amount is adjusted, and the phenomenon of yellow smoke is prevented.
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