WO2019047561A1

WO2019047561A1 - Distributed coordination and control system for thermoelectric generating set based on multi-parameter dynamic matrix control

Info

Publication number: WO2019047561A1
Application number: PCT/CN2018/088140
Authority: WO
Inventors: 吕剑虹; 蔡戎彧; 于吉; 高峥; 葛浩
Original assignee: 东南大学
Priority date: 2017-09-06
Filing date: 2018-05-24
Publication date: 2019-03-14
Also published as: CN107515598A

Abstract

A distributed coordination and control system for a thermoelectric generating set based on multi-parameter dynamic matrix prediction and control. The control system consists of a load control loop, a main steam pressure control loop and a separator temperature control loop; deviations of a load, a main steam pressure and a separator temperature from set values are sent to a prediction controller based on a dynamic matrix control algorithm; and calculations are made to obtain an optimized value of the openness of a steam turbine governing valve, of a coal feed quantity and of a feed water flux, thereby ensuring the tracking performance of the set for a load instruction and the security performance of the operation of the set. By means of dynamic matrix control, the optimization problem of a multi-variable system can be conveniently processed; and the calculation process is clear and simple, and upon application of the program, the programming implementation is convenient. Since a corresponding control quantity is regulated in a timely manner by predicting a future output deviation, a real power can rapidly follow a load instruction, and the stability of a main steam pressure and a separator temperature can also be ensured. The set has a good reliability, and the control effect is better than traditional PID control.

Description

Distributed coordinated control system for thermal power units based on multi-parameter dynamic matrix control

Technical field

The invention relates to the field of thermal power engineering and automatic control, in particular to a distributed coordinated control system for a thermal power unit based on multi-parameter dynamic matrix control.

Background technique

As the unit parameters continue to increase, the complexity and control requirements of the controlled objects are improved, and many problems arise. In the super-supercritical unit coordinated control system, the disturbance of the feed water flow has a great influence on the actual power and main steam pressure of the unit. Therefore, in addition to the coal volume, the turbine opening degree as the control quantity of the coordinated control system, the main steam pressure and the actual power as the controlled quantity of the coordinated control system, the feed water flow should be used as the control amount in the coordinated system, and the intermediate point temperature As the controlled quantity; the ultra-supercritical unit adopts the DC furnace, and the steam-water circulation system has a high circulation speed, requiring the control system to move faster. If traditional PID control is still used, the effect will not be ideal, which requires us to explore other control solutions.

Predictive control can still maintain good robustness under the influence of system uncertainty factors, with good control effect and easy control on line. The widely used dynamic matrix control in predictive control has been successfully applied in the control of refining and chemical industries since the 1970s. Aiming at the characteristics of many super-supercritical unit variables and complex structure, the present invention proposes a coordinated control method for thermal power units based on dynamic matrix control of multivariable systems.

Summary of the invention

In order to solve the above problems, the present invention is directed to the coordinated control of an ultra-supercritical unit, and it is difficult to obtain an ideal control quality using a simple PID control scheme. The present invention proposes a feature of a large delay in the ultra-supercritical coordinated control process. The distributed coordinated control system of thermal power unit based on multi-parameter dynamic matrix predictive control can effectively improve the control quality. To achieve the purpose, the present invention provides a distributed coordinated control system for a thermal power unit based on multi-parameter dynamic matrix control, The dynamic matrix control system consists of load control loop, main steam pressure control loop and separator temperature control loop. The system input quantity is fuel quantity, turbine door opening degree, feed water flow rate, system output quantity is load, main steam pressure, separator temperature There is a coupling between the input and output, and the dynamic matrix controller is used for control.

According to a further development of the invention, the dynamic matrix controller comprises the following modules:

A. an output prediction module for predicting the output of each sampling moment in the future;

B. an optimization performance index calculation module, configured to calculate an optimal control increment within the control range according to the set performance index;

C. A control implementation module for applying the calculated optimal control law to the system.

According to a further improvement of the invention, the prediction model of the dynamic matrix controller is based on the step response of the object, that is, the load y ₁ , the main steam pressure y ₂ , and the separator temperature y ₃ respectively for the fuel amount u ₁ and the turbine opening degree u ₂ The unit step response α _ij (y _i vs. u _j ) of the feed water flow u ₃ :

α _ij =[α _ij (1), α _ij (2) Λα _ij (N)] ^T , i=1, Λ3, j=1, Λ3;

Where N is the truncation step size.

According to a further improvement of the invention, the prediction model of the dynamic matrix controller is:

among them,

For the time k, u _j has M incremental changes Δu _j (k), 输出Δu _j (k+M-1)

For the k- _{th order} , the output prediction value when u _j has the increment Δu _j (k)

P is the prediction time domain and M is the control time domain.

According to a further improvement of the invention, the optimization performance index of the dynamic matrix controller is:

Where ω(k)=[ω ₁ (k) ω ₂ (k) ω ₃ (k)] ^T is the set value, ω _i (k)=[ω _i (k+1) Λ ω _i (k+ P)] ^T , Q is the error weight matrix, and R is the control weight matrix;

The optimal control increment of the dynamic matrix controller is:

According to a further improvement of the invention, the dynamic matrix controller takes a control increment of the current time k in the calculated optimal control increment sequence to act on the system:

u _j (k)=u _j (k-1)+Δu _j (k), j=1, 2, 3

Then take the k+1 time as the base point and carry out the optimal control incremental sequence calculation at the next moment to realize the rolling optimization.

According to a further improvement of the invention, the dependent object model of the dynamic matrix controller is obtained by fitting experimental data, and the specific method is: establishing a linear transfer function at each load point by performing a step response test at a plurality of load points. The model, the model of the intermediate load is calculated by interpolation method through the linear transfer function model on the established adjacent load points.

Compared with the prior art, the present invention proposes a distributed coordinated control system for a thermal power unit based on multi-parameter dynamic matrix predictive control. The calculation process of the algorithm of the dynamic matrix controller is clear and simple, and the programming is very convenient when applied in engineering. Regardless of whether the controlled process is a linear model or a nonlinear model, the dynamic matrix control algorithm can be easily implemented regardless of whether the controlled object has large inertia or large delay; it can ensure that the actual power quickly follows the change of the load command, which is consistent with The situation in the actual problem; the coordinated control system based on the dynamic matrix control algorithm can optimize the fuel quantity, the turbine door opening degree and the feed water flow within a certain range, so that the actual power of the unit is effectively reduced while following the load command. The fluctuation of the main steam pressure and the separator temperature is economical and safe.

DRAWINGS

FIG. 1 is a schematic diagram of a control system according to an embodiment of the present invention.

Detailed ways

The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

The invention is directed to the coordinated control of the ultra-supercritical unit, and it is difficult to obtain the ideal control quality by using a simple PID control scheme. The present invention proposes a multi-parameter dynamic matrix prediction for the characteristics of the large super-supercritical coordinated control process with large delay. The distributed thermal power unit distributed coordinated control system can effectively improve the control quality.

FIG. 1 is a schematic diagram of a distributed coordinated control system for a thermal power unit based on multi-parameter dynamic matrix predictive control. The dynamic matrix control system is composed of a load control loop, a main steam pressure control loop, and a separator temperature control loop. The input quantity is the fuel quantity, the turbine door opening degree, the water supply flow rate, the output quantity is the load, the main steam pressure, the separator temperature, and the controller adopts a dynamic matrix controller.

According to the transfer function of the object, that is, the transfer function of the fuel amount u ₁ , the turbine opening degree u ₂ , and the feed water flow rate u ₃ to the load y ₁ , the main steam pressure y ₂ , and the separator temperature y ₃ , the respective output pairs are determined. The unit step response α _ij (y _i versus u _j ) for each input.

α _ij =[α _ij (1), α _ij (2) Λα _ij (N)] ^T , i=1, Λ3, j=1, Λ3;

Where N is the truncation step size.

Based on the unit step response α _ij , the output prediction module of the controller predicts the output of each sampling instant in the future. The prediction model is:

among them,

For the time k, u _j has M incremental changes Δu _j (k), 输出Δu _j (k+M-1)

P is the prediction time domain and M is the control time domain.

Determining the optimal performance index calculation module of the controller, and calculating an optimal control increment within the control range according to the set performance index. The optimization performance indicators are:

Where ω(k)=[ω ₁ (k) ω ₂ (k) ω ₃ (k)] ^T is the set value, ω _i (k)=[ω _i (k+1) Λ ω _i (k+ P)] ^T , Q is the error weight matrix, and R is the control weight matrix. The magnitude of the error weight determines the degree of emphasis on the output, and the size of the control determines the magnitude of the fluctuation range of the control amount.

Calculating the optimal control increment of the dynamic matrix controller is:

A control implementation module for applying the calculated optimal control law to the system. The controller takes the control increment of the current time k in the calculated optimal control increment sequence to act on the system:

u _j (k)=u _j (k-1)+Δu _j (k), j=1, 2, 3;

The object transfer function based on the step response of the measured object is obtained by fitting the experimental data. By performing a step response test at multiple load points, a linear transfer function model at each load point is established, and the intermediate load model is established. The linear transfer function model at adjacent load points is calculated by interpolation.

In the following, the 660 MW ultra-supercritical secondary reheat unit of a power plant adopts the optimized control system of the present invention as an example to describe the content of the present invention in detail. The sampling period is taken as 5s, the step response of the measurement object is determined, the truncation step length N is 5000, the prediction time domain P is taken as 2000, the control time domain M is taken as 100, and the error weight matrix is taken as Q=diag(1,1,Λ1) _{3× P} , the control weight matrix takes R = diag (R ₁ , R ₂ , R ₃ ) _{3 × M} , where R ₁ = diag (0.01, 0.01, Λ 0.01) _M , R ₂ = diag (0.05, 0.05, Λ 0. 05) _M , R ₃ = diag (0.03, 0.03, Λ 0.03) _M . The optimized control system of the invention has been successfully applied in a 660 MW ultra-supercritical unit of a certain plant. The lifting load test was carried out at a load of 600 MW at a load rate of 12 MW/min. The results show that the load command is reduced from 620 MW to 560 MW at a rate of 12 MW/min, and then restored to 620 MW at the same rate. The actual power quickly follows the load command, and the deviation between the main steam pressure and the pressure set value is within 0.15 MPa, and the maximum dynamic deviation Only 0.5 MPa, the maximum dynamic deviation of the superheated steam temperature and the reheated steam temperature is less than 1 °C due to the effective control of the separator temperature. The above example shows that the distributed coordinated control system of thermal power unit based on multi-parameter dynamic matrix predictive control can effectively improve the running performance of the coordinated control system. The real power can quickly follow the load command, while the main steam pressure and separator temperature deviation and fluctuation Very small, the unit economy and safety are guaranteed.

The above is only the preferred embodiment of the present invention, and is not intended to limit the scope of the present invention. Any modification or equivalent change made according to the technical essence of the present invention still falls within the scope of the claimed invention. .

Claims

A distributed coordination control system for a thermal power unit based on multi-parameter dynamic matrix control is characterized in that the dynamic matrix control system is composed of a load control loop, a main steam pressure control loop and a separator temperature control loop, and the system input amount is a fuel amount, The steam turbine adjusts the opening degree and the water supply flow rate. The system output is the load, the main steam pressure, the separator temperature, and there is coupling between the input and output, and the dynamic matrix controller is used for control.
The thermal power unit distributed coordinated control system based on multi-parameter dynamic matrix control according to claim 1, wherein the dynamic matrix controller comprises the following modules:

A. an output prediction module for predicting the output of each sampling moment in the future;

B. an optimization performance index calculation module, configured to calculate an optimal control increment within the control range according to the set performance index;

C. A control implementation module for applying the calculated optimal control law to the system.
The thermal power unit distributed coordinated control system based on multi-parameter dynamic matrix control according to claim 2, wherein the prediction model of the dynamic matrix controller is based on an object's step response, that is, load y 1 , main steam pressure y 2 , separator temperature y 3 for the fuel amount u 1 , the turbine opening degree u 2 , the feed water flow u 3 unit step response α ij (y i to u j ):

α ij =[α ij (1), α ij (2) Λα ij (N)] T , i=1, Λ3, j=1, Λ3;

Where N is the truncation step size.
The distributed coordinated control system for a thermal power unit based on multi-parameter dynamic matrix control according to claim 2, wherein the prediction model of the dynamic matrix controller is:

among them,

For the time k, u j has M incremental changes Δu j (k), 输出Δu j (k+M-1)
For the k- th order , the output prediction value when u j has the increment Δu j (k)
P is the prediction time domain and M is the control time domain.
The distributed coordinated control system for a thermal power unit based on multi-parameter dynamic matrix control according to claim 2, wherein the optimization performance index of the dynamic matrix controller is:

Where ω(k)=[ω 1 (k) ω 2 (k) ω 3 (k)] T is the set value, ω i (k)=[ω i (k+1) Λ ω i (k+ P)] T , Q is the error weight matrix, and R is the control weight matrix;

The optimal control increment of the dynamic matrix controller is:
The multi-parameter dynamic matrix control based thermal power unit distributed coordinated control system according to claim 2, wherein the dynamic matrix controller takes the control increment of the current time k in the calculated optimal control increment sequence. Act on the system:

u j (k)=u j (k-1)+Δu j (k), j=1, 2, 3;

Then take the k+1 time as the base point and carry out the optimal control incremental sequence calculation at the next moment to realize the rolling optimization.
The distributed coordinated control system for a thermal power unit based on multi-parameter dynamic matrix control according to claim 3, wherein the dependent object model of the dynamic matrix controller is obtained by fitting experimental data, and the specific method is: The linear transfer function model at each load point is established by performing step response tests at multiple load points. The intermediate load model is calculated by interpolation method through the linear transfer function model on the established adjacent load points.