CN113932215A - Cascade main steam temperature control system and method based on prediction algorithm - Google Patents

Cascade main steam temperature control system and method based on prediction algorithm Download PDF

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CN113932215A
CN113932215A CN202111178312.8A CN202111178312A CN113932215A CN 113932215 A CN113932215 A CN 113932215A CN 202111178312 A CN202111178312 A CN 202111178312A CN 113932215 A CN113932215 A CN 113932215A
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steam temperature
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leading
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main steam
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栾丛超
吴涛
杜保华
吴智群
张建刚
柴胜凯
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Xian Thermal Power Research Institute Co Ltd
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    • FMECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F22STEAM GENERATION
    • F22GSUPERHEATING OF STEAM
    • F22G5/00Controlling superheat temperature
    • FMECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F22STEAM GENERATION
    • F22GSUPERHEATING OF STEAM
    • F22G5/00Controlling superheat temperature
    • F22G5/12Controlling superheat temperature by attemperating the superheated steam, e.g. by injected water sprays

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Abstract

The invention provides a cascade main steam temperature control system and a method thereof based on a prediction algorithm, which utilize the quick response characteristic of the steam temperature of a foreward region to control in advance through an auxiliary control loop, the main steam temperature is finely adjusted through a main control loop, and the main control loop and the auxiliary control loop both adopt a state space model prediction algorithm to improve the accuracy and the rapidity of the steam temperature control.

Description

Cascade main steam temperature control system and method based on prediction algorithm
Technical Field
The invention relates to the field of main steam temperature control of thermal generator sets, belongs to the design of a main steam temperature control system, and particularly relates to a cascade main steam temperature control system and a cascade main steam temperature control method based on a prediction algorithm.
Background
A large amount of heating surface metal exists in boiler equipment of the thermal generator set, and the temperature of main steam needs to be strictly controlled during operation of the thermal generator set in consideration of the upper limit of the bearing temperature of metal materials. However, due to the fact that delay and inertia of a heat exchange process are large, the temperature of main steam is adjusted very slowly, reaction is insensitive, the temperature of the main steam is difficult to control, and difficulty is brought to safe operation of boiler equipment of a thermal generator set.
At present, a single-loop PID feedback control system is mostly adopted for controlling the temperature of main steam of a thermal generator set, but due to the delay and inertia of a heat exchange process, the control effect of the single-loop PID feedback control system is poor, the temperature fluctuation of the main steam is large, and the phenomenon of overtemperature often occurs. In addition, some researchers propose a cascade PID control system to control the temperature of the main steam, and although the control system improves the dynamic characteristic of the temperature of the main steam to a certain extent, the limit of a PID controller causes the temperature of the main steam to still have certain fluctuation, thus endangering the safe operation of the boiler of the thermal generator set. In conclusion, it is very meaningful for the thermal generator set to design a control system which quickly tracks the set value of the main steam temperature and reduces the fluctuation of the main steam temperature.
Disclosure of Invention
The invention provides a cascade main steam temperature control system and a method thereof based on a prediction algorithm, aiming at the problems of delay and inertia of steam temperature control of a power plant in the prior art, wherein the system utilizes the quick response characteristic of leading steam temperature to control in advance through a secondary control loop, the main steam temperature is finely adjusted through a main control loop, the main control loop and the secondary control loop both adopt a state space model prediction algorithm to improve the accuracy and rapidity of the steam temperature control, and the control system can improve the dynamic characteristic of the main steam temperature control of the power plant and reduce the influence of desuperheating water disturbance on main steam.
The invention is realized by the following technical scheme:
a cascade primary steam temperature control system based on a prediction algorithm comprises a primary prediction controller, a secondary prediction controller and a controlled object, wherein the controlled object comprises a conductive area and an inert area;
the input end of the main prediction controller is connected with the main steam temperature instruction receiving module and the main steam temperature measuring module, the input end of the auxiliary prediction controller is respectively connected with the output end of the main prediction controller and the leading steam temperature measuring module, the output end of the auxiliary prediction controller is connected with the leading area, the output end of the leading area is respectively connected with the input ends of the inert zone and the leading steam temperature measuring module and is connected to the auxiliary prediction controller through the leading steam temperature measuring module to form an auxiliary prediction controller loop, and the output end of the inert zone is connected to the main prediction controller through the main steam temperature measuring module to form a main prediction controller loop;
after the main prediction controller receives the signal instruction of the main steam temperature instruction receiving module and the measurement data output by the main steam temperature measurement module, the main prediction controller outputs a leading steam temperature operating variable to the auxiliary prediction controller based on a state space model prediction algorithm;
and after receiving the leading steam temperature operating variable output by the main predictive controller and the measurement data output by the leading steam temperature measurement module, the auxiliary predictive controller outputs a water spray temperature reduction execution value to the leading area based on a state space model prediction algorithm.
Preferably, the instruction signal received by the main steam temperature instruction receiving module is a main steam temperature set value, and the measurement data output by the main steam temperature measurement module is a main steam temperature measurement value.
Preferably, the measurement data output by the leading steam temperature measurement module is a leading steam temperature measurement value.
Preferably, the prediction algorithm based on the state space model in the main prediction controller and the sub-prediction controller specifically includes the following steps:
predicting a state space model;
and (4) optimizing rolling.
Further, the state space model prediction is to predict the output value of the controlled object at the next moment on the basis of linearization and non-dimensionalization, and the prediction model after linearization and non-dimensionalization should have the state space form of the following linear discrete time system:
x(k+1)=Ax(k)+Bu(k);
y(k)=Cx(k);
wherein x (k) is a state variable; u (k) is a control input variable; y (k) is the controlled variable output; a is a system matrix; b is an input matrix; c is an output matrix;
taking a dimensionless factor adopted by input and output dimensionless as 1;
the prediction models of the main prediction controller and the auxiliary prediction controller are designed in the following leading region and inactive region models:
Figure BDA0003296241710000031
Figure BDA0003296241710000032
wherein G is1(s) is a transfer function of the leading steam temperature of the controlled object; g1(s) is a transfer function of the temperature of the main steam of the controlled object; s is the complex frequency.
Further, the scrolling is optimized as follows:
under cascade predictive control, the objective function of the main controller is as follows:
Figure BDA0003296241710000033
wherein J is an objective function; gamma-shapedθy1,iA weighting factor for the predicted main steam temperature control deviation at the ith moment; gamma-shapedθu1,iA weighting factor for predicting a control increment for an ith moment; thetac1(k + i | k) is a predicted value of the main steam temperature; k + i | k is the prediction of k + i moment at k moment; thetar1(k + i) is the given value of the main steam temperature at the moment of k + i; delta theta2(k + i-1) is the variable quantity of the leading steam temperature given value at the moment of k + i-1;
the objective function of the secondary controller is:
Figure BDA0003296241710000034
wherein J is an objective function; gamma-shapedθy2,iWeighting factors of leading steam temperature control deviation predicted at the ith moment; gamma-shapedθu2,iA weighting factor for predicting a control increment for an ith moment; thetac2(k + i | k) is a predicted value of the leading steam temperature; k + i | k is the prediction of k + i moment at k moment; theta2(k + i) is a leading steam temperature set value at the moment of k + i, namely, is determined by the output of the main controller; Δ Wb(k + i-1) is the amount of change in the temperature-reduced water at the time k + i-1.
A cascade main steam temperature control method based on a prediction algorithm is based on the cascade main steam temperature control system based on the prediction algorithm, and comprises the following specific steps:
step 1, after a main steam temperature prediction model and a lead steam temperature prediction model are initialized, a main prediction controller receives a signal instruction and measurement data output by a main steam temperature measurement module through a main steam temperature instruction receiving module, and then performs state estimation by using a state space model to predict a main steam temperature value at the next moment; the output of the main steam temperature is restrained by utilizing an objective function, and the main steam temperature control process is optimized so as to realize the fastest tracking of the main steam temperature; solving the output of a main steam temperature target function to obtain a leading steam temperature operating variable, namely a leading steam temperature set value;
step 2, after the auxiliary predictive controller receives the operation variable of the leading steam temperature output by the main predictive controller and the measurement data output by the leading steam temperature measurement module, the output of the leading steam temperature is restrained by utilizing an objective function, and the control process of the leading steam temperature is optimized so as to realize the fastest tracking of the leading steam temperature; solving a water spraying temperature reduction execution value obtained by a leading steam temperature objective function, namely the temperature reduction water quantity; and only acting the next moment value in the obtained temperature reduction water quantity control sequence on the leading area, outputting a leading steam temperature measured value to the auxiliary prediction controller through the leading steam temperature measuring module on one side of the leading steam temperature output by the leading area to form an auxiliary control loop, inputting a main steam temperature measured value to the main prediction controller through the main steam temperature measuring module on the other side of the leading steam temperature output by the leading area to form a main control loop.
Preferably, when the main steam temperature prediction model is disturbed by the desuperheating water amount, the leading steam temperature quickly shows obvious deviation after the water spraying desuperheating execution value output by the auxiliary prediction controller or the opening of the desuperheating water valve is disturbed, the auxiliary control loop utilizes the model prediction control to quickly adjust the desuperheating water amount so as to eliminate the leading steam temperature deviation, greatly reduce the influence of disturbance and realize the rough regulation of the main steam temperature; the temperature of the main steam changes slowly, after the main control loop measures the temperature deviation of the main steam, the model prediction controller in the main control loop is used for realizing the no-difference adjustment of the deviation of the main steam and realizing the fine adjustment of the temperature of the main steam; after the whole process of coarse adjustment and fine adjustment, the main steam temperature is kept at the set value.
Compared with the prior art, the invention has the following beneficial technical effects:
the invention provides a cascade main steam temperature control system and a method thereof based on a prediction algorithm, which utilize the quick response characteristic of the steam temperature of a foreward region to control in advance through an auxiliary control loop, the main steam temperature is finely adjusted through a main control loop, and the main control loop and the auxiliary control loop both adopt a state space model prediction algorithm to improve the accuracy and the rapidity of the steam temperature control.
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FIG. 1 is a diagram of a cascade primary steam temperature control system based on a predictive algorithm in accordance with the present invention;
FIG. 2 illustrates the control steps of the main steam temperature setpoint tracking process of the present invention;
FIG. 3 is a control step of the main steam temperature tracking process under the disturbance of the amount of desuperheated water in the present invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
The invention is described in further detail below with reference to the accompanying drawings:
referring to fig. 1, in an embodiment of the present invention, a cascade main steam temperature control system based on a prediction algorithm is provided, in the system, a rapid response characteristic of a leading steam temperature is utilized to control in advance through an auxiliary control loop, a main steam temperature is finely adjusted through a main control loop, and the main control loop and the auxiliary control loop both adopt a state space model prediction algorithm to improve accuracy and rapidity of steam temperature control.
Specifically, the cascade-stage main steam temperature control system based on the prediction algorithm comprises a main prediction controller, a secondary prediction controller and a controlled object, wherein the controlled object comprises a leading area and an inert area;
the input end of the main prediction controller is connected with the main steam temperature instruction receiving module and the main steam temperature measuring module, the input end of the auxiliary prediction controller is respectively connected with the output end of the main prediction controller and the leading steam temperature measuring module, the output end of the auxiliary prediction controller is connected with the leading area, the output end of the leading area is respectively connected with the input ends of the inert zone and the leading steam temperature measuring module and is connected to the auxiliary prediction controller through the leading steam temperature measuring module to form an auxiliary prediction controller loop, and the output end of the inert zone is connected to the main prediction controller through the main steam temperature measuring module to form a main prediction controller loop;
after the main prediction controller receives the signal instruction of the main steam temperature instruction receiving module and the measurement data output by the main steam temperature measurement module, the main prediction controller outputs the leading steam temperature optimal operating variable to the auxiliary prediction controller based on a state space model prediction algorithm;
and after receiving the optimal operation variable of the leading steam temperature output by the main prediction controller and the measurement data output by the leading steam temperature measurement module, the auxiliary prediction controller outputs the optimal execution value of water spraying temperature reduction to the leading area based on a state space model prediction algorithm.
The main control loop is a closed loop formed by feeding back a main steam temperature measured value, and the auxiliary control loop is a closed loop formed by feeding back a leading steam temperature measured value.
Specifically, the instruction signal received by the main steam temperature instruction receiving module is a main steam temperature given value, and the measurement data output by the main steam temperature measurement module is a main steam temperature measurement value.
Specifically, the measurement data output by the leading steam temperature measurement module is a leading steam temperature measurement value.
Specifically, the state space model-based prediction algorithm in the main prediction controller and the auxiliary prediction controller specifically comprises the following steps:
predicting a state space model;
and (4) optimizing rolling.
The state space model prediction is used for predicting an output value of a controlled object at the next moment on the basis of linearization and non-dimensionalization, and the linearized and non-dimensionalized prediction model has a state space form of a linear discrete time system as follows:
x(k+1)=Ax(k)+Bu(k);
y(k)=Cx(k);
wherein x (k) is a state variable; u (k) is a control input variable; y (k) is the controlled variable output, A is the system matrix; b is an input matrix; c is an output matrix;
taking a dimensionless factor adopted by input and output dimensionless as 1;
the prediction models of the main prediction controller and the auxiliary prediction controller are designed in the following leading region and inactive region models:
Figure BDA0003296241710000071
Figure BDA0003296241710000072
wherein G is1(s) is a transfer function of the leading steam temperature of the controlled object; g1(s) is a transfer function of the temperature of the main steam of the controlled object; s is the complex frequency.
The prediction model of the main prediction controller is as follows:
Figure BDA0003296241710000081
Figure BDA0003296241710000082
C=[0 0 0 0.003769 0 0 0];
the prediction model of the secondary predictive controller is:
Figure BDA0003296241710000083
Figure BDA0003296241710000084
C=[0 -0.002515]。
preferably, the scrolling is optimized as:
under cascade predictive control, the objective function of the main controller is as follows:
Figure BDA0003296241710000085
wherein J is an objective function; gamma-shapedθy1,iA weighting factor for the predicted main steam temperature control deviation at the ith moment; gamma-shapedθu1,iA weighting factor for predicting a control increment for an ith moment; thetac1(k + i | k) is a predicted value of the main steam temperature; k + i | k is the prediction of k + i moment at k moment; thetar1(k + i) is the given value of the main steam temperature at the moment of k + i; delta theta2(k + i-1) is the variable quantity of the leading steam temperature given value at the moment of k + i-1;
the objective function of the secondary controller is:
Figure BDA0003296241710000091
wherein J is an objective function; gamma-shapedθy2,iWeighting factors of leading steam temperature control deviation predicted at the ith moment; gamma-shapedθu2,iA weighting factor for predicting a control increment for an ith moment; thetac2(k + i | k) is a predicted value of the leading steam temperature; k + i | k is the prediction of k + i moment at k moment; theta2(k + i) is a leading steam temperature set value at the moment of k + i, namely, is determined by the output of the main controller; Δ Wb(k + i-1) is the amount of change in the temperature-reduced water at the time k + i-1.
The invention discloses a cascade main steam temperature control method based on a prediction algorithm, and a cascade main steam temperature control system based on the prediction algorithm, which comprises the following specific steps as shown in figure 2:
step 1, after a main steam temperature prediction model and a lead steam temperature prediction model are initialized, a main prediction controller receives a signal instruction and measurement data output by a main steam temperature measurement module through a main steam temperature instruction receiving module, and then performs state estimation by using a state space model to predict a main steam temperature value at the next moment; the output of the main steam temperature is restrained by utilizing an objective function, and the main steam temperature control process is optimized so as to realize the fastest tracking of the main steam temperature; solving the output of a main steam temperature target function to obtain a leading steam temperature operating variable, namely a leading steam temperature set value;
step 2, after the auxiliary predictive controller receives the operation variable of the leading steam temperature output by the main predictive controller and the measurement data output by the leading steam temperature measurement module, the output of the leading steam temperature is restrained by utilizing an objective function, and the control process of the leading steam temperature is optimized so as to realize the fastest tracking of the leading steam temperature; solving a water spraying temperature reduction execution value obtained by a leading steam temperature objective function, namely the temperature reduction water quantity; and only acting the next moment value in the obtained temperature reduction water quantity control sequence on the leading area, outputting a leading steam temperature measured value to the auxiliary prediction controller through the leading steam temperature measuring module on one side of the leading steam temperature output by the leading area to form an auxiliary control loop, inputting a main steam temperature measured value to the main prediction controller through the main steam temperature measuring module on the other side of the leading steam temperature output by the leading area to form a main control loop.
Specifically, as shown in fig. 3, when the main steam temperature prediction model is disturbed by the amount of desuperheating water, when the water spraying desuperheating execution value output by the auxiliary prediction controller or the opening of the desuperheating water valve is disturbed, the leading steam temperature rapidly shows an obvious deviation, the auxiliary control loop rapidly adjusts the amount of desuperheating water by using model prediction control to eliminate the leading steam temperature deviation, greatly reduces the influence of disturbance, and realizes the coarse adjustment of the main steam temperature; the temperature of the main steam changes slowly, after the main control loop measures the temperature deviation of the main steam, the model prediction controller in the main control loop is used for realizing the no-difference adjustment of the deviation of the main steam and realizing the fine adjustment of the temperature of the main steam; after the whole process of coarse adjustment and fine adjustment, the main steam temperature is kept at the set value.
In summary, the main predictive controller in the invention is based on a state space model prediction algorithm, the input signal of the main predictive controller comprises a main steam temperature given value and a main steam temperature measured value, and the output signal of the main predictive controller is the optimal operating variable of the leading steam temperature.
The auxiliary predictive controller is based on a state space model prediction algorithm, the input signal of the auxiliary predictive controller comprises a leading steam temperature set value, namely, the optimal operating variable and a leading steam temperature measured value of the leading steam temperature are calculated by the output of the main predictive controller, and the output signal of the auxiliary predictive controller is the optimal operating variable for water spraying temperature reduction.
The controlled object is divided into a front guide area and an inert area, the output of the front guide area is the front guide steam temperature, namely the steam temperature at the outlet of the desuperheater, and the outlet of the inert area is the main steam temperature.
The leading temperature is the temperature behind the mixing area of the desuperheating water and the main steam, and the leading steam temperature can respond quickly due to the fact that the leading area has smaller delay and inertia, and therefore the desuperheating water is adopted to control the leading steam temperature to have a quick control effect.
The main steam temperature and the temperature-reducing water are separated from the front conducting area and the inert area, and the inert area has larger delay and inertia, so the effect of controlling the main steam temperature by the temperature-reducing water is poor.
The cascade control fully utilizes the characteristic of quick response of the leading steam temperature, the auxiliary control loop quickly eliminates the leading steam temperature deviation to finish the rough adjustment of the main steam temperature, and the main control loop finely adjusts the main steam temperature.
The dynamic characteristic of the temperature control of the main steam of the power plant is improved, namely the fluctuation range of the temperature of the main steam is reduced, and the recovery time of the temperature of the main steam under disturbance is shorter.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting the same, and although the present invention is described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: modifications and equivalents may be made to the embodiments of the invention without departing from the spirit and scope of the invention, which is to be covered by the claims.

Claims (8)

1. The cascade primary steam temperature control system based on the prediction algorithm is characterized by comprising a primary prediction controller, a secondary prediction controller and a controlled object, wherein the controlled object comprises a leading area and an inert area;
the input end of the main prediction controller is connected with the main steam temperature instruction receiving module and the main steam temperature measuring module, the input end of the auxiliary prediction controller is respectively connected with the output end of the main prediction controller and the leading steam temperature measuring module, the output end of the auxiliary prediction controller is connected with the leading area, the output end of the leading area is respectively connected with the input ends of the inert zone and the leading steam temperature measuring module and is connected to the auxiliary prediction controller through the leading steam temperature measuring module to form an auxiliary prediction controller loop, and the output end of the inert zone is connected to the main prediction controller through the main steam temperature measuring module to form a main prediction controller loop;
after the main prediction controller receives the signal instruction of the main steam temperature instruction receiving module and the measurement data output by the main steam temperature measurement module, the main prediction controller outputs a leading steam temperature operating variable to the auxiliary prediction controller based on a state space model prediction algorithm;
and after receiving the leading steam temperature operating variable output by the main predictive controller and the measurement data output by the leading steam temperature measurement module, the auxiliary predictive controller outputs a water spray temperature reduction execution value to the leading area based on a state space model prediction algorithm.
2. The cascade primary steam temperature control system based on the prediction algorithm as claimed in claim 1, wherein the command signal received by the primary steam temperature command receiving module is a primary steam temperature set value, and the measurement data output by the primary steam temperature measurement module is a primary steam temperature measurement value.
3. The cascade primary steam temperature control system based on a predictive algorithm as claimed in claim 1, wherein the measurement data output by the lead steam temperature measurement module is a lead steam temperature measurement value.
4. The cascade main steam temperature control system based on the prediction algorithm as claimed in claim 1, wherein the prediction algorithm based on the state space model in the main prediction controller and the auxiliary prediction controller specifically comprises the following steps:
predicting a state space model;
and (4) optimizing rolling.
5. The cascade main steam temperature control system based on prediction algorithm according to claim 4, wherein the state space model prediction is performed on the basis of the linearization and non-dimensionalization of the controlled object for the next time output value, and the linearized and non-dimensionalized prediction model has the following state space form of linear discrete time system:
x(k+1)=Ax(k)+Bu(k);
y(k)=Cx(k);
wherein x (k) is a state variable; u (k) is a control input variable; y (k) is the controlled variable output; a is a system matrix; b is an input matrix; c is an output matrix;
taking a dimensionless factor adopted by input and output dimensionless as 1;
the prediction models of the main prediction controller and the auxiliary prediction controller are designed in the following leading region and inactive region models:
Figure FDA0003296241700000021
Figure FDA0003296241700000022
wherein G is1(s) is a transfer function of the leading steam temperature of the controlled object; g1(s) is a transfer function of the temperature of the main steam of the controlled object; s is the complex frequency.
6. The cascade primary steam temperature control system based on a predictive algorithm of claim 4, wherein the roll optimization is:
under cascade predictive control, the objective function of the main controller is as follows:
Figure FDA0003296241700000023
wherein J is an objective function; gamma-shapedθy1,iA weighting factor for the predicted main steam temperature control deviation at the ith moment; gamma-shapedθu1,iA weighting factor for predicting a control increment for an ith moment; thetac1(k + i | k) is a predicted value of the main steam temperature; k + i | k is the prediction of k + i moment at k moment; thetar1(k + i) is the given value of the main steam temperature at the moment of k + i; delta theta2(k + i-1) is the variable quantity of the leading steam temperature given value at the moment of k + i-1;
the objective function of the secondary controller is:
Figure FDA0003296241700000031
wherein J is an objective function; gamma-shapedθy2,iWeighting factors of leading steam temperature control deviation predicted at the ith moment; gamma-shapedθu2,iA weighting factor for predicting a control increment for an ith moment; thetac2(k + i | k) is a predicted value of the leading steam temperature; k + i | k is the prediction of k + i moment at k moment; theta2(k + i) is a leading steam temperature set value at the moment of k + i, namely, is determined by the output of the main controller; Δ Wb(k + i-1) is the amount of change in the temperature-reduced water at the time k + i-1.
7. A cascade main steam temperature control method based on a prediction algorithm is based on the cascade main steam temperature control system based on the prediction algorithm of any one of claims 1 to 6, and is characterized by comprising the following specific steps:
step 1, after a main steam temperature prediction model and a lead steam temperature prediction model are initialized, a main prediction controller receives a signal instruction and measurement data output by a main steam temperature measurement module through a main steam temperature instruction receiving module, and then performs state estimation by using a state space model to predict a main steam temperature value at the next moment; the output of the main steam temperature is restrained by utilizing an objective function, and the main steam temperature control process is optimized so as to realize the fastest tracking of the main steam temperature; solving the output of a main steam temperature target function to obtain a leading steam temperature operating variable, namely a leading steam temperature set value;
step 2, after the auxiliary predictive controller receives the operation variable of the leading steam temperature output by the main predictive controller and the measurement data output by the leading steam temperature measurement module, the output of the leading steam temperature is restrained by utilizing an objective function, and the control process of the leading steam temperature is optimized so as to realize the fastest tracking of the leading steam temperature; solving a water spraying temperature reduction execution value obtained by a leading steam temperature objective function, namely the temperature reduction water quantity; and only acting the next moment value in the obtained temperature reduction water quantity control sequence on the leading area, outputting a leading steam temperature measured value to the auxiliary prediction controller through the leading steam temperature measuring module on one side of the leading steam temperature output by the leading area to form an auxiliary control loop, inputting a main steam temperature measured value to the main prediction controller through the main steam temperature measuring module on the other side of the leading steam temperature output by the leading area to form a main control loop.
8. The cascade main steam temperature control method based on the prediction algorithm as claimed in claim 7, wherein when the main steam temperature prediction model is disturbed by the amount of desuperheating water, when the water spraying desuperheating execution value output by the auxiliary prediction controller or the opening of the desuperheating water valve is disturbed, the lead steam temperature rapidly shows obvious deviation, the auxiliary control loop rapidly adjusts the amount of desuperheating water by using the model prediction control to eliminate the lead steam temperature deviation, greatly reduces the influence of disturbance, and realizes the rough adjustment of the main steam temperature; the temperature of the main steam changes slowly, after the main control loop measures the temperature deviation of the main steam, the model prediction controller in the main control loop is used for realizing the no-difference adjustment of the deviation of the main steam and realizing the fine adjustment of the temperature of the main steam; after the whole process of coarse adjustment and fine adjustment, the main steam temperature is kept at the set value.
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