CN111884217B - Single-machine infinite electric power system optimization control method based on T-S model - Google Patents
Single-machine infinite electric power system optimization control method based on T-S model Download PDFInfo
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- CN111884217B CN111884217B CN202010751817.8A CN202010751817A CN111884217B CN 111884217 B CN111884217 B CN 111884217B CN 202010751817 A CN202010751817 A CN 202010751817A CN 111884217 B CN111884217 B CN 111884217B
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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
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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
- H02J2203/10—Power transmission or distribution systems management focussing at grid-level, e.g. load flow analysis, node profile computation, meshed network optimisation, active network management or spinning reserve management
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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 provides a single-machine infinite electric power system optimization control method based on a T-S model, which comprises the following steps: s1, establishing a single-machine infinite electric power system model; s2, carrying out local linearization processing on the single-machine infinite electric power system model to obtain a fuzzy state model of the single-machine infinite electric power system; s3, converting the fuzzy state model of the single-machine infinite electric power system into a global fuzzy state model of the single-machine infinite electric power system according to a fuzzy rule; s4, constructing a fuzzy event trigger controller, and defining a trigger form and conditions; and S5, establishing an optimized performance index in a zero initial state, and performing single-machine infinite electric power system optimized control by adopting a fuzzy event trigger controller.
Description
Technical Field
The invention relates to the technical field of power system stability control, in particular to a single-machine infinite power system optimization control method based on a T-S model.
Background
During the period of more than 40 years of Chinese reform, the consumption of energy sources such as coal, petroleum and the like in China is unprecedentedly huge, and the consumption and the release of a large amount of coal and petroleum cause the problems of serious energy shortage and environmental pollution, so that the trend of energy development at present depends on the subjects of cleanness and greenness whether distributed clean energy sources at the power generation end or electric vehicles at the power utilization end. Also because of this characteristic of electrical energy, the nation has vigorously developed electrical grids that enable the delivery of electrical energy to thousands of households.
In south China, due to the fact that residents use household appliances such as air conditioners and electric fans in a large scale in summer, the power consumption is increased rapidly; in addition, the electric automobile industry develops rapidly and the sales volume of new energy automobiles in China is up to 120 thousands of automobiles in 2019, wherein the sales volume of new energy passenger automobiles is 106.0 thousands of automobiles, and the sales volume is increased by 0.7% on year-by-year basis; the sales volume of the pure electric passenger vehicle is 78.8 thousands, the sales volume is increased by 5.9 percent on a same scale, the charging of the electric vehicle has strong uncertainty, and if the pure electric passenger vehicle happens to be charged in a large-scale centralized manner, the power consumption of a load end is increased rapidly, so that the stability of an electric power system is influenced. If the treatment is not good, the suddenly increased electric load can cause the grid to be unstable and cause large-scale power failure. Therefore, the stability of the power grid is guaranteed to be very important for national economy and people's life. Because of the stand-alone infinity electric power system model for the electric power system model after simplifying helps the research of electric power system stability, avoided considering unnecessary influence factor, consequently adopt stand-alone infinity electric power system to carry out this patent research, this patent is mainly to the research that stand-alone infinity electric power system stability research and stand-alone infinity electric power system and event trigger technique fuse mutually to reach the effect that makes electric power system's stability and intelligent improvement.
Disclosure of Invention
The invention aims to provide a T-S model-based single infinite electric power system optimization control method, which aims to solve the problems of modeling and controller design of a single infinite electric power system, realize a high-performance event trigger control target of the single infinite electric power system and meet the reliable and stable operation of the single infinite electric power system.
The invention is realized by the following technical scheme: a single machine infinite electric power system optimization control method based on a T-S model comprises the following steps:
s1, establishing a single-machine infinite electric power system model;
s2, carrying out local linearization processing on the single-machine infinite electric power system model to obtain a fuzzy state model of the single-machine infinite electric power system;
s3, converting the fuzzy state model of the single-machine infinite electric power system into a global fuzzy state model of the single-machine infinite electric power system according to a fuzzy rule;
s4, constructing a fuzzy event trigger controller, and defining a trigger form and conditions;
and S5, establishing an optimized performance index in a zero initial state, and performing single-machine infinite power system optimized control by adopting a fuzzy event trigger controller.
Preferably, in step S1, the established model of the single infinite electric power system with uncertainty is:
in the formula, delta is a generator rotor running angle; omega is the relative rotating speed of the generator; e' q Is a generator q-axis transient potential; omega 0 An initial angular velocity of the generator; h is the rotational inertia of the generator rotor; p m Mechanical power output by the prime mover; v s Infinite bus voltage; x' dz Is the sum of transient reactances of the generators; d is a damping coefficient of the generator; t' do The time constant of the excitation winding when the stator winding is closed; x' d Is a generator shaft transient reactance; t is do The time constant of the excitation winding when the excitation winding is closed; v f For the field winding voltage, defined as a control variable, w 1 (t)、w 2 (t) is the amount of interference, x d Equal reactance for the generator shaft.
Preferably, the step S2 includes performing local linearization on the single infinite electric power system model by using a sector method, where a linearized fuzzy state model of the single infinite electric power system is:
wherein x is 1 (t)＝δ，x 2 (t)＝ω，x 3 (t)＝E′ q ，u(t)＝V f ，x(t)＝[x 1 (t) x 2 (t) x 3 (t)] T ，w(t)＝[0 w 1 (t) w 2 (t)] T ，
a 1 、a 2 Are each z 1 (t) maximum and minimum values, expressed as:
preferably, in the step S3, the fuzzy rule includes an If-Then modeling rule, and the If-Then modeling rule includes a first rule and a second rule, where the first rule is: when z is 1 (t)、z 2 (t) is 1, obtaining a first fuzzy state equation:
the second rule is: when z is 1 (t)、z 2 (t) is-1, obtaining a second fuzzy state equation:
wherein
Membership function:
preferably, in step S3, a global fuzzy state model is obtained according to the first fuzzy state equation and the second fuzzy state equation:
preferably, in step S4, the fuzzy event trigger controller is designed by using a parallel distribution compensation techniqueAnd setting the following control rules: if x 1 (t) is F 1 And x is g (t) is F 2 Then, then
Wherein K h Control the static gain feedback matrix for the 1*3 dimension corresponding to the fuzzy rule, t k Indicating the moment of triggering, F 1 、F 2 Is a function of membership.
Preferably, the fuzzy event trigger controller is triggered in the form of:
e(t)＝x(t k )-x(t)
where e (t) is the event-triggered travel of the system, k represents the number of event triggers, t k Indicating the moment of trigger.
Preferably, the trigger conditions of the fuzzy event trigger controller are as follows:
where p is a set dimensionless number for adjusting the trigger condition, H e And H x Is a preset matrix.
Preferably, the optimized performance index in the zero initial state includes:
where γ is a constant and is a suppression index reference value of the external disturbance.
Preferably, in step S5, the controller is triggered according to the fuzzy event to perform real-time control on the single infinite power system, so as to gradually stabilize the closed-loop system, and a set of positive definite symmetric matrix solutions P is obtained, so that the following linear matrix inequality is established:
wherein Q = P -1 ，H h ＝K h Q，l＝1,2，h＝1,2，K 1 、K 2 For a 1*3 dimensional steering gain matrix corresponding to the corresponding fuzzy rule, P is a 3*3 dimensional symmetric positive definite matrix.
Compared with the prior art, the invention has the following beneficial effects:
the single infinite power system optimization control method based on the T-S model provided by the invention starts from two aspects of fuzzy modeling and controller design of the single infinite power system to carry out overall design, can realize the high-function event trigger optimization control target of the single infinite power system, meets the high functionality and high reliability of the power system in operation, has strong feasibility, completely meets the high functional requirement of real-time event trigger control of the single infinite power system, and realizes the improvement of the robustness and high functionality of the single infinite power system.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only preferred embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without inventive exercise.
FIG. 1 is a flow chart of a method for optimizing and controlling a single infinite power system based on a T-S model according to the present invention;
FIG. 2 is a sector diagram of cos (x 1 (t)) of the present invention;
FIG. 3 is a state response of the stand-alone infinity power system of the present invention;
FIG. 4 is a control input for the stand-alone infinity power system of the present invention;
FIG. 5 is an optimized output response of the stand-alone infinite power system of the present invention;
fig. 6 is an event trigger signal of the stand-alone infinite power system of the present invention.
Detailed Description
For a better understanding of the technical content of the present invention, the following detailed description is provided in conjunction with the accompanying drawings for further explanation of the present invention.
Referring to fig. 1, the present embodiment of a method for optimally controlling a stand-alone infinite power system based on a T-S model, which is applied to control the stand-alone infinite power system, where an event triggering technology has been developed into a mature technology and is widely applied in many fields, and the use of the event triggering technology makes the application system have an obvious effect in improving work efficiency and reducing work task load, so that the present embodiment establishes a global fuzzy state model of the stand-alone infinite power system by linearizing a mathematical model of the stand-alone infinite power system, and thus constructs a fuzzy event trigger controller, and after defining an event triggering form and triggering conditions and establishing an optimized performance index in a zero initial state, can perform event triggering optimal control on the stand-alone infinite power system, thereby achieving a high-function event triggering control target of the stand-alone infinite power system, satisfying high safety and high reliability of the power system during operation, improving control capability of the control method in the information sampling technology, greatly reducing the number of unnecessary information acquisition of the system, effectively relieving pressure of a system information transmission channel, improving robustness of the stand-alone infinite power system, and the stand-alone infinite power system based on the T-alone infinite function optimization method, and the stand-alone infinite power system, and the method comprising a robustness optimization step:
s1, establishing a single-machine infinite electric power system model, wherein the established single-machine infinite electric power system model containing uncertainty is as follows:
in the formula, delta is a generator rotor running angle; omega is the relative rotating speed of the generator; e' q Is a generator q-axis transient potential; omega 0 Is the initial angular velocity of the generator; h is the rotational inertia of the generator rotor; p m Mechanical power output by the prime mover; v s Infinite bus voltage; x' dz For generator transient state electricityThe sum of the resistance; d is a damping coefficient of the generator; t' do The time constant of the excitation winding when the stator winding is closed; x' d Is a generator shaft transient reactance; t is do Is the time constant of the exciting winding when the exciting winding is closed; v f For the field winding voltage, defined as a control variable, w 1 (t)、w 2 (t) is the amount of interference, x d Equal reactance for the generator shaft.
S2, local linearization processing is carried out on the single-machine infinite electric power system model by adopting a sector method, and a linearized fuzzy state model of the single-machine infinite electric power system is as follows:
wherein x is 1 (t)＝δ，x 2 (t)＝ω，x 3 (t)＝E′ q ，u(t)＝V f ，x(t)＝[x 1 (t) x 2 (t) x 3 (t)] T ，w(t)＝[0 w 1 (t) w 2 (t)] T ，
as can be seen from FIG. 2, sector b 1 ,b 2 ]Is formed by two lines b 1 x 1 And b 2 x 1 Composition, slope respectively
Finally, cos (x) can be converted by the sector method 1 (t)) linearizing.
S3, converting the fuzzy state model of the single infinite electric power system into a global fuzzy state model of the single infinite electric power system according to fuzzy rules, wherein the fuzzy rules comprise If-Then modeling rules, the If-Then modeling rules comprise a first rule and a second rule, and the first rule is as follows: when z is 1 (t)、z 2 (t) is 1, obtaining a first fuzzy state equation:
the second rule is: when z is 1 (t)、z 2 (t) is-1, obtaining a second fuzzy state equation:
wherein
Membership function:
obtaining a global fuzzy state model according to the first fuzzy state equation and the second fuzzy state equation:
s4, designing a fuzzy event trigger controller by adopting a parallel distribution compensation technology, and setting the following control rules: if x 1 (t) is F 1 And x is g (t) is F 2 Then, then
Wherein K h Control the static gain feedback matrix for the 1*3 dimension corresponding to the fuzzy rule, t k Indicating the moment of triggering, F 1 、F 2 Is a membership function, and defines the triggering form of the fuzzy event triggering controller as follows:
e(t)＝x(t k )-x(t)
where e (t) is the event-triggered travel of the system, k represents the number of event triggers, t k Indicating the moment of trigger.
Defining the trigger condition of the fuzzy event trigger controller as follows:
where p is a set dimensionless number for adjusting the trigger condition, H e And H x Is a preset matrix.
S5, establishing an optimized performance index in a zero initial state:
triggering a controller according to the fuzzy event, carrying out real-time control on a single infinite power system, enabling a closed-loop system to be gradually stabilized, solving a group of positive definite symmetric matrix solutions P, and enabling the following linear matrix inequality to be established:
wherein Q = P -1 ，H h ＝K h Q，l＝1,2，h＝1,2，K 1 、K 2 For a 1*3 dimensional steering gain matrix corresponding to the corresponding fuzzy rule, P is a 3*3 dimensional symmetric positive definite matrix.
The following experiments were conducted with a single machine infinite power system, where the main technical performance indicators and equipment parameters were selected as follows: d =0.15,h =12.9,v s ＝1，T d0 ＝6.45，T′ d0 ＝1.2，x d ＝0.83，x′ d ＝0.105，x′ d∑ ＝0.16，ω 0 =314.154, the corresponding parameters in step S2 are:
the 1*3 dimensional control static gain feedback matrix corresponding to the fuzzy rule in the fuzzy time trigger controller:
K 1 ＝[-28.0562 -127.2194 -77.7566]
K 2 ＝[-28.6512 -126.5596 -77.3654]
a positive definite symmetric matrix obtained according to the parameters and the data:
setting the initial condition of a single-machine infinite power system as x 0 ＝[0.21 0.62 0.33] T FIG. 3 is a system state response graph of a stand-alone infinity power system operating with a stable closed loop system, where x 1 (t)、x 2 (t)、x 3 (t) are respectively the generator rotor running angle, the generator relative rotating speed and the generator q-axis transient potential, and x is shown in figure 3 after the system is interfered 2 (t)、x 3 (t) substantially stabilizes after 1s of system operation with a faster recovery capability and x 1 (t) no obvious hiking phenomenon indicates that the anti-interference performance is certain; FIG. 4 is a control input curve diagram of a single infinite power system during stable operation of a closed loop system, and it can be seen from FIG. 4 that the control input completely approaches to about 1sIn balance, the system can be proved to have stronger robustness; FIG. 5 is the optimized output response of the single infinite power system, and it can be seen from FIG. 5 that the output response of the system is greatly reduced after 1s, and then the system is basically recovered to normal after 2-3 s; fig. 6 is a state curve of a single infinite system under event trigger control, and it can be seen from fig. 6 that when an actual value exceeds a preset value, the system automatically adjusts to perform effective control.
The data and the curve chart prove that the method improves the control capability of the single infinite electric power system in the aspect of the information sampling technology, greatly reduces the times of acquiring unnecessary information by the system, effectively relieves the pressure of a system information transmission channel, and improves the robustness and the high functionality of the single infinite electric power system.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (9)
1. A single infinite power system optimization control method based on a T-S model is characterized by comprising the following steps:
s1, establishing a single-machine infinite electric power system model;
s2, carrying out local linearization processing on the single-machine infinite electric power system model to obtain a fuzzy state model of the single-machine infinite electric power system, carrying out local linearization on the single-machine infinite electric power system model by adopting a sector method, wherein the linearized fuzzy state model of the single-machine infinite electric power system is as follows:
wherein x is 1 (t)＝δ，x 2 (t)＝ω，x 3 (t)＝E′ q ，u(t)＝V f ，x(t)＝[x 1 (t) x 2 (t) x 3 (t)] T ，w(t)＝[0 w 1 (t) w 2 (t)] T ，
a 1 、a 2 Are each z 1 (t) a maximum and a minimum, expressed as:
s3, converting the fuzzy state model of the single-machine infinite electric power system into a global fuzzy state model of the single-machine infinite electric power system according to a fuzzy rule;
s4, constructing a fuzzy event trigger controller, and defining a trigger form and conditions;
and S5, establishing an optimized performance index in a zero initial state, and performing single-machine infinite electric power system optimized control by adopting a fuzzy event trigger controller.
2. The method according to claim 1, wherein in step S1, the model of the standalone infinite electric power system is:
in the formula, delta is a generator rotor running angle; omega is the relative rotating speed of the generator; e' q Is a generator q-axis transient potential; omega 0 Is the initial angular velocity of the generator; h is the rotational inertia of the generator rotor; p m Mechanical power output by the prime mover; v s Infinite bus voltage; x' dz Is the sum of transient reactances of the generators; d is hairA motor damping coefficient; t' do The time constant of the excitation winding when the stator winding is closed; x' d Is a generator shaft transient reactance; t is do Is the time constant of the exciting winding when the exciting winding is closed; v f To the field winding voltage, w 1 (t)、w 2 (t) is the amount of interference, x d Equal reactance for the generator shaft.
3. The method according to claim 2, wherein in step S3, the fuzzy rule includes an If-Then modeling rule, and the If-Then modeling rule includes a first rule and a second rule, where the first rule is: when z is 1 (t)、z 2 (t) is 1, obtaining a first fuzzy state equation:
the second rule is: when z is 1 (t)、z 2 (t) is-1, obtaining a second fuzzy state equation:
wherein
Membership function:
4. the method as claimed in claim 3, wherein in step S3, a global fuzzy state model is obtained according to the first fuzzy state equation and the second fuzzy state equation:
5. the method as claimed in claim 4, wherein in step S4, the fuzzy event trigger controller is designed by using a parallel distribution compensation technique, and the following control rules are set: if x 1 (t) is F 1 And x is g (t) is F 2 Then, then
Wherein K is h Control the static gain feedback matrix for the 1*3 dimension corresponding to the fuzzy rule, t k Indicating the moment of triggering, F 1 、F 2 Is a function of membership.
6. The method for optimizing and controlling the stand-alone infinite electric power system based on the T-S model as claimed in claim 5, wherein the fuzzy event trigger controller is triggered in the form of:
e(t)＝x(t k )-x(t)
where e (t) is the event-triggered form of the system, k represents the number of event triggers, t k Indicating the moment of trigger.
7. The method as claimed in claim 6, wherein the trigger conditions of the fuzzy event trigger controller are as follows:
where ρ isFor setting dimensionless numbers for adjusting the trigger conditions, H e And H x Is a preset matrix.
8. The method as claimed in claim 7, wherein the optimized performance index in the zero initial state includes:
where γ is a constant and is a suppression index reference value of the external disturbance.
9. The method as claimed in claim 8, wherein in step S5, the controller is triggered according to the fuzzy event to perform real-time control of the single infinite power system, so as to gradually stabilize the closed-loop system, and obtain a set of positive symmetric matrix solutions, so that the following linear matrix inequality holds:
wherein Q = P -1 ，H h ＝K h Q，l＝1,2，h＝1,2，K 1 、K 2 For a 1*3 dimensional steering gain matrix corresponding to the corresponding fuzzy rule, P is a 3*3 dimensional symmetric positive definite matrix.
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