CN108281972A - AGC methods based on forecasting type PID controller - Google Patents
AGC methods based on forecasting type PID controller Download PDFInfo
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- CN108281972A CN108281972A CN201711439764.0A CN201711439764A CN108281972A CN 108281972 A CN108281972 A CN 108281972A CN 201711439764 A CN201711439764 A CN 201711439764A CN 108281972 A CN108281972 A CN 108281972A
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/24—Arrangements for preventing or reducing oscillations of power in networks
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
Abstract
The invention discloses a kind of AGC methods based on forecasting type PID controller.This method includes：The frequency departure of electric system is obtained, the frequency departure of the electric system comes from sensor；Sliding-model control is carried out to power system frequency deviation；It is multiplied by the expectation as ACE after feedback factor, is input in forecasting type PID controller；According to PID control feature, the output sequence of the PID control effect of each sampling instant of calculated for subsequent, as predicted value；Design object function carries out global optimizing to object function, finds out the optimal solution that object function is zero to input local derviation；The adjusted value of the PID controller input terminal after optimization is calculated according to optimal solution；Input terminal desired value after optimization is input in PID control, calculates the output of PID controller, and export to AGC system.The control method has robustness good, can be with dynamic optimization the characteristics of.
Description
Technical field
The present invention relates to AGC (Automatic Generation Control, Automatic Generation Control) control fields, specifically
It is related to a kind of AGC methods based on forecasting type PID controller.
Background technology
In recent years, as the continuous expansion of interconnected network scale, load variations form become increasingly complex, how to optimize AGC
System control method also becomes a project for being worth research.There are different control methods for this problem at present：Based on something lost
It passes the AGC control systems research of fuzzy, the interconnected network AGC based on MFA control algorithm, be based on Time-Delay model
The networking AGC researchs of predictive control algorithm.AGC control systems based on Genetic-fuzzy PID can overcome traditional fuzzy control to need
The drawbacks of degree of membership is manually set and is unable to dynamically-adjusting parameter；Interconnected network AGC based on MFA control algorithm
System has stronger robustness, non-linear adaptive and CPS indexs；Networking based on Time-Delay model predictive control algorithm
AGC control systems ensure robustness and adaptability of the networking AGC to communication delay.
Although the above-mentioned stability and dynamic property enumerated control method and be capable of Guarantee control system, generally existing control
Precision is limited, the problem of control algolithm complexity, and the problem of only considered controller Optimization about control parameter, and actually controls process
In, other than the optimization of controller control parameter, it is also contemplated that optimized to the input of controller.Therefore, for PID
The prediction optimization method of controller input has more practical significance.
Invention content
In order to solve the problems, such as that above-mentioned background technology exists, the object of the present invention is to provide one kind based on forecasting type PID controls
The AGC methods of device processed.
In order to achieve the above object, the technical solution adopted in the present invention is：The side AGC based on forecasting type PID controller
Method, which is characterized in that described method includes following steps：
Step 1：The frequency departure of electric system is obtained, the frequency departure of the electric system comes from sensor；
Step 2：Sliding-model control is carried out to power system frequency deviation；It is multiplied by after feedback factor as ACE (area
Control error, ACE) expectation, be input in forecasting type PID controller；
Step 3：According to PID control feature, the output sequence of the PID control effect of each sampling instant of calculated for subsequent will
It is as predicted value；
Step 4：Design object function carries out global optimizing to object function, and it is zero to input local derviation to find out object function
Optimal solution；
Step 5：The adjusted value of the PID controller input terminal after optimization is calculated according to optimal solution；
Step 6：Input terminal desired value after optimization is input in PID control, calculates the output of PID controller, and defeated
Go out to AGC system.
Further, in step 4, specific implementation process includes：
Assuming that as follows with the research object number sequence model that discrete form describes：
X (k+1)=Ax (k)+Bu (k)+Fw (k)
Y=Cx (k)
Wherein, x is state variable, and u is input state variable, and w is state of disturbance variable, and y is output state variable, and A is
Coefficient matrix, B are input matrix, and C is output matrix, and F is perturbation matrix, and k is sampling instant；Object function is defined as：
J=| | E (k) | |2Q+||△uM(k)||2R
||△uM(k)||≤△umax
Wherein, E (k) indicates the tracking error matrix that the difference of prediction output quantity and the following tracking target reference is formed, Q, R
For diagonal weight coefficient matrix, △ umaxIndicate generator power maximum permissible value, wherein
E (k)=yS(k)-yPM(k)
yS(k) indicate output quantity in the desired output sequence at k moment, yPM(k) it is the tracking target reference at k moment；
Its control process shows as the optimization for object function, and one can be all calculated most in each sampling instant system
Excellent list entries：
U*=[u*(k)u*(k+1)…u*(k+Nc-1)]T
Wherein NcFor the control domain of system；
According to the state variable x (k) at this moment and disturbance variable w (k) at this moment, subsequent time is calculated
State variable x (k+1), and calculate the output variable y (k+1) at k+1 moment；
It repeats the above steps and calculates u (k) all in entire control domain, x (k), y (k).
Further, forecasting type PID controller calculates the defeated of control system according to the optimal output sequence
Go out, formula is as follows：
G (s)=U (s)/E (s)=KP[1+1/(KI*s)+TD*s]
Here U (s) is the output of forecasting type PID controller, and E (s) is the optimal output sequence y (k) of prediction of system.
Further, when the experiment porch of selection is two regional internet power grid AGC systems, mathematical model is：
Y (t)=CX (t)
In formula, X ∈ Rn, U ∈ Rm, W ∈ Rk, Y ∈ RrRespectively represent system state variables, control variable, disturbance variable and defeated
Go out variable, A, B, F, C are respectively the parameter matrix of corresponding dimension；Wherein：
X=[△ f1 △Pt1 △Pr1 △Xg1 △Pt12 △f2 △Pt2 △Pr2 △Xg2]T
Y=[ACE1 ACE2 △f1 △f2 △Pt12]T
U=[△ Pc1 △Pc2]T
W=[△ PL1 △PL2]T
According to above-mentioned mathematical model two regional internet power grids are constructed using the module in Simulink in MATLAB
The model of AGC system, by ACE1And ACE2Input of the desired value as forecasting type PID controller, each sampling instant control system
System can all calculate an optimal output sequence of AGC system, and the prediction optimization of control sequence is exported by predictive controller
It adjusts to PID controller input.
Compared with prior art, the beneficial effects of the invention are as follows：The present invention uses forecasting type PID controller, solves well
Conventional PID controllers of having determined robustness is insufficient, can not dynamically realize the problems such as system optimization, be obviously improved the control of system
Effect processed.The control method overshoot is small, regulating time is short, robustness is good.
Description of the drawings
It in order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, below will be to institute in embodiment
Attached drawing to be used is needed to be briefly described, it should be apparent that, the accompanying drawings in the following description is only some implementations of the present invention
Example, for those of ordinary skill in the art, without having to pay creative labor, can also be according to these attached drawings
Obtain other attached drawings.
Fig. 1；The two regional internet power grid AGC system dynamic model figures of forecasting type PID.
Fig. 2；The flow chart of the AGC methods based on forecasting type PID controller of the present invention.
Fig. 3；Control variables choice schematic diagram.
Fig. 4；ACE1 response curves under the step signal of prediction optimization PID controller.
Fig. 5；ACE2 response curves under the step signal of prediction optimization PID controller.
Fig. 6；△ f1 response curves under the step signal of prediction optimization PID controller.
Fig. 7；△ f2 response curves under the step signal of prediction optimization PID controller.
Fig. 8；ACE1 response curves under the step signal of conventional PID controllers.
Fig. 9；ACE2 response curves under the step signal of conventional PID controllers.
Figure 10；△ f1 response curves under the step signal of conventional PID controllers.
Figure 11；△ f2 response curves under the step signal of conventional PID controllers.
Specific implementation mode
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation describes, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.It is based on
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts every other
Embodiment shall fall within the protection scope of the present invention.
The object of the present invention is to provide a kind of AGC methods based on forecasting type PID, which has robustness good,
Can be with dynamic optimization the characteristics of.This method includes：Power system frequency parameter is obtained, the power system frequency parameter comes from
In sensor；The power system frequency parameter is compared with the power system frequency of national standard, seeks difference；By institute
The differential transmission for the power system frequency stated is to AGC system, and the AGC system master controller is made of PID, by PID
Control output selects and generates optimum control signal to be practiced in the prediction of a domain internal control effect；Frequency-modulated station
Obtain control signal；The electricity that frequency-modulated station should be sent out is determined according to the control signal, should be sent out according to described
The electricity gone out compensates electric system；It is zero to make power system frequency difference, and power system frequency is restored to country
Standard value.
In order to make the foregoing objectives, features and advantages of the present invention clearer and more comprehensible, below in conjunction with the accompanying drawings and specific real
Applying mode, the present invention is described in further detail.
Fig. 1 is that two regional internet power grid AGC systems of AGC method of the present invention implementation based on forecasting type PID controller are dynamic
States model figure.
As shown in Fig. 2, steps are as follows for control method provided by the invention：
Step 1：The frequency departure of electric system is obtained, the frequency departure of the electric system comes from sensor；
Step 2：Sliding-model control is carried out to power system frequency deviation；It is multiplied by the expectation as ACE after feedback factor,
It is input in forecasting type PID controller；
Step 3：According to PID control feature, the output sequence of the PID control effect of each sampling instant of calculated for subsequent will
It is as predicted value；
Step 4：Design object function carries out global optimizing to object function, and it is zero to input local derviation to find out object function
Optimal solution；
Step 5：The adjusted value of the PID controller input terminal after optimization is calculated according to optimal solution；
Step 6：Input terminal desired value after optimization is input in PID control, calculates the output of PID controller, and defeated
Go out to AGC system.
Specific implementation process is as follows：
1, assume that the research object number sequence model described with discrete form is as follows：
X (k+1)=Ax (k)+Bu (k)+Fw (k)
Y=Cx (k)
Wherein, x is state variable, and u is input state variable, and w is state of disturbance variable, and y is output state variable, and A is
Coefficient matrix, B are input matrix, and C is output matrix, and F is perturbation matrix, and k is sampling instant；
2, in step 4, object function is defined as：
J=| | E (k) | |2Q+||△uM(k)||2R
||△uM(k)||≤△umax
Wherein, E (k) indicates the tracking error matrix that the difference of prediction output quantity and the following tracking target reference is formed, Q, R
For diagonal weight coefficient matrix, △ umaxIndicate generator power maximum permissible value, wherein
E (k)=yS(k)-yPM(k)
yS(k) desired output sequence of the expression output quantity at the k moment.yPM(k) it is the tracking target reference at k moment.
Its control process shows as the optimization for object function, and one can be all calculated most in each sampling instant system
Excellent list entries：
U*=[u*(k)u*(k+1)…u*(k+Nc-1)]T
Wherein NcFor the control domain of system.
According to the state variable x (k) at this moment and disturbance variable w (k) at this moment, subsequent time is calculated
State variable x (k+1), and calculate the output variable y (k+1) at k+1 moment.
It repeats the above steps and calculates u (k) all in entire control domain, x (k), y (k).
3, forecasting type PID controller calculates the output of control system, formula is such as according to the optimal output sequence
Under：
G (s)=U (s)/E (s)=KP[1+1/(KI*s)+TD*s]
Here U (s) is the output of forecasting type PID controller, and E (s) is the optimal output sequence y (k) of prediction of system.
4, when the experiment porch of selection is two regional internet power grid AGC systems, mathematical model is：
Y (t)=CX (t)
In formula, X ∈ Rn, U ∈ Rm, W ∈ Rk, Y ∈ RrRespectively represent system state variables, control variable, disturbance variable and defeated
Go out variable.A, B, F, C are respectively the parameter matrix of corresponding dimension；Wherein：
X=[△ f1 △Pt1 △Pr1 △Xg1 △Pt12 △f2 △Pt2 △Pr2 △Xg2]T
Y=[ACE1 ACE2 △f1 △f2 △Pt12]T
U=[△ Pc1 △Pc2]T
W=[△ PL1 △PL2]T
Given two regional internet AGC system dynamic model simulation parameters, as shown in table 1.Setting prediction time domain NP=10, control
Time domain N processedc=4, weight matrix R=I.It is as shown in table 1 that systematic parameter is set.
1 systematic parameter of table
T in tablegiFor governor time constant；TtiFor generator time constant；KriFor steam turbine reheat factor；TriReheating
Time constant；RiFor unit difference coefficient；BiFor system difference coefficient；MiFor turbine generator inertia；DiFor load damped coefficient；
T12For dominant eigenvalues synchronization factor.
According to mathematical model and setup parameter above, PID controller in MATLAB and S-function modules, structure are utilized
The model of two region AGC systems is built out, as shown in Figure 1, in Fig. 1, by ACE1、ACE2Desired value as the defeated of prediction module
Enter, by the ACE after adjustment1、ACE2Input of the desired value as PID controller.
In the case of studying various disturbances, the dynamic property of the AGC system controlled using institute's extracting method of the present invention and
Stability, the disturbance load Δ P of given area 1L1For 0.04pu, the disturbance load Δ P in region 2L2For 0.06pu, test disturbance
Each output response of AGC system when input is step signal, as shown in figures 5-8；
As can be seen that being optimized to PID controller list entries and not to PID control from Fig. 3~6 and Fig. 7~10
Device list entries is shorter compared to regulating time, overshoot smaller, and system has better stability.
Each embodiment is described by the way of progressive in this specification, the highlights of each of the examples are with other
The difference of embodiment, just to refer each other for identical similar portion between each embodiment.For system disclosed in embodiment
For, since it is corresponded to the methods disclosed in the examples, so description is fairly simple, related place is said referring to method part
It is bright.
Principle and implementation of the present invention are described for specific case used herein, and above example is said
The bright method and its core concept for being merely used to help understand the present invention；Meanwhile for those of ordinary skill in the art, foundation
The thought of the present invention, there will be changes in the specific implementation manner and application range.In conclusion the content of the present specification is not
It is interpreted as limitation of the present invention.
Claims (4)
1. the AGC methods based on forecasting type PID controller, which is characterized in that described method includes following steps：
Step 1：The frequency departure of electric system is obtained, the frequency departure of the electric system comes from sensor；
Step 2：Sliding-model control is carried out to power system frequency deviation；It is multiplied by the expectation as ACE after feedback factor, input
Into forecasting type PID controller；
Step 3：According to PID control feature, the output sequence of the PID control effect of each sampling instant of calculated for subsequent is made
For predicted value；
Step 4：Design object function carries out global optimizing to object function, and it is zero most to input local derviation to find out object function
Excellent solution；
Step 5：The adjusted value of the PID controller input terminal after optimization is calculated according to optimal solution；
Step 6：Input terminal desired value after optimization is input in PID control, calculates the output of PID controller, and export and give
AGC system.
2. the AGC methods according to claim 1 based on forecasting type PID controller, which is characterized in that in step 4, specifically
Realization process includes：
Assuming that as follows with the research object number sequence model that discrete form describes：
X (k+1)=Ax (k)+Bu (k)+Fw (k)
Y=Cx (k)
Wherein, x is state variable, and u is input state variable, and w is state of disturbance variable, and y is output state variable, and A is coefficient
Matrix, B are input matrix, and C is output matrix, and F is perturbation matrix, and k is sampling instant；Object function is defined as：
J=| | E (k) | |2Q+||△uM(k)||2R
||△uM(k)||≤△umax
Wherein, E (k) indicates the tracking error matrix that the difference of prediction output quantity and the following tracking target reference is formed, and Q, R are pair
Angle weight coefficient matrix, △ umaxIndicate generator power maximum permissible value, wherein
E (k)=yS(k)-yPM(k)
yS(k) indicate output quantity in the desired output sequence at k moment, yPM(k) it is the tracking target reference at k moment；
Its control process shows as the optimization for object function, each sampling instant system can all calculate one it is optimal
List entries：
U*=[u*(k)u*(k+1)…u*(k+Nc-1)]T
Wherein NcFor the control domain of system；
According to the state variable x (k) at this moment and disturbance variable w (k) at this moment, the state of subsequent time is calculated
Variable x (k+1), and calculate the output variable y (k+1) at k+1 moment；
It repeats the above steps and calculates u (k) all in entire control domain, x (k), y (k).
3. the AGC methods according to claim 1 based on forecasting type PID controller, which is characterized in that forecasting type PID controls
Device processed calculates the output of control system according to the optimal output sequence, and formula is as follows：
G (s)=U (s)/E (s)=KP[1+1/(KI*s)+TD*s]
Here U (s) is the output of forecasting type PID controller, and E (s) is the optimal output sequence y (k) of prediction of system.
4. the AGC methods according to claim 1 based on forecasting type PID controller, which is characterized in that when the experiment of selection
Platform is two regional internet power grid AGC systems, and mathematical model is：
Y (t)=CX (t)
In formula, X ∈ Rn, U ∈ Rm, W ∈ Rk, Y ∈ RrSystem state variables, control variable, disturbance variable and output is respectively represented to become
Amount, A, B, F, C are respectively the parameter matrix of corresponding dimension；Wherein：
X=[△ f1 △Pt1 △Pr1 △Xg1 △Pt12 △f2 △Pt2 △Pr2 △Xg2]T
Y=[ACE1 ACE2 △f1 △f2 △Pt12]T
U=[△ Pc1 △Pc2]T
W=[△ PL1 △PL2]T
According to above-mentioned mathematical model two regional internet power grid AGC systems are constructed using the module in Simulink in MATLAB
The model of system, by ACE1And ACE2Input of the desired value as forecasting type PID controller, each sampling instant control system is all
An optimal output sequence of AGC system can be calculated, and the prediction optimization of control sequence is exported to PID by predictive controller
Controller input adjusts.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109062040A (en) * | 2018-07-27 | 2018-12-21 | 湖北工业大学 | Predictive PID method based on the optimization of system nesting |
| CN110233486A (en) * | 2018-12-17 | 2019-09-13 | 万克能源科技有限公司 | Energy storage based on active predicting SOC assists fuzzy PID control method |
-
2017
- 2017-12-27 CN CN201711439764.0A patent/CN108281972A/en active Pending
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109062040A (en) * | 2018-07-27 | 2018-12-21 | 湖北工业大学 | Predictive PID method based on the optimization of system nesting |
| CN109062040B (en) * | 2018-07-27 | 2021-12-10 | 湖北工业大学 | PID (proportion integration differentiation) predicting method based on system nesting optimization |
| CN110233486A (en) * | 2018-12-17 | 2019-09-13 | 万克能源科技有限公司 | Energy storage based on active predicting SOC assists fuzzy PID control method |
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