CN111884217A - Single-machine infinite electric power system optimization control method based on T-S model - Google Patents

Abstract

The present invention provides an optimal control method for a single-machine infinite power system based on a T-S model, comprising the following steps: S1, establishing a single-machine infinite power system model; S2, performing local linearization on the single-machine infinite power system model to obtain a single-machine infinite power system model. Fuzzy state model of the infinite power system; S3. Convert the fuzzy state model of the single-machine infinite power system into a global fuzzy state model of the single-machine infinite power system according to fuzzy rules; S4. Construct a fuzzy event trigger controller and define a trigger Form and condition; S5, establish the optimal performance index under the zero initial state, adopt the fuzzy event trigger controller to carry out the optimal control of the single-machine infinite power system.

Description

An Optimal Control Method for Single-machine Infinite Power System Based on T-S Model

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 technique

During the more than 40 years of China's reform and opening up, my country's consumption of coal, oil and other energy sources has been unprecedented. The consumption and release of a large amount of coal and oil have caused serious energy shortages and environmental pollution problems. Distributed clean energy at the end or electric vehicles at the power end are closely based on the theme of clean and green. It is also because of this characteristic of electric energy that the country vigorously develops the power grid so that electric energy can be transmitted to thousands of households.

In southern China, due to the large-scale use of air conditioners, fans and other household appliances by residential users in the hot summer, electricity consumption has increased sharply; in addition, the electric vehicle industry has developed rapidly. In 2019 alone, the sales of new energy vehicles in my country reached 1.2 million, of which new energy vehicles The sales volume of vehicles was 1.060 million units, a year-on-year increase of 0.7%; the sales of pure electric passenger vehicles was 788,000 units, a year-on-year increase of 5.9%. Electric vehicle charging is highly uncertain. The amount of electricity will rise sharply, which will have an impact on the stability of the power system. If it is not handled properly, the sudden increase of electricity load may cause the instability of the power grid and cause large-scale power outages. Therefore, ensuring the stability of the power grid is very important for both the national economy and people's lives. Because the single-machine infinite power system model is a simplified power system model, it is helpful for the study of power system stability and avoids considering unnecessary influencing factors. Therefore, the single-machine infinite power system is used for the study of this patent. This patent is mainly aimed at single-machine infinite power. System stability research and research on the integration of single-machine infinite power system and event trigger technology, so as to achieve the effect of improving the stability and intelligence of the power system.

SUMMARY OF THE INVENTION

The purpose of the present invention is to provide a single-machine infinite power system optimization control method based on the T-S model, so as to solve the modeling and controller design problems of the single-machine infinite power system, realize the high-performance event-triggered control target of the single-machine infinite power system, and satisfy the single-machine infinite power system. Reliable and stable operation of infinite power system.

The present invention is achieved through the following technical solutions: a single-machine infinite power system optimization control method based on the T-S model, comprising the following steps:

S1. Establish a single-machine infinite power system model;

S2, performing local linearization processing on the single-machine infinite power system model to obtain a fuzzy state model of the single-machine infinite power system;

S3. Convert the fuzzy state model of the single-machine infinite power system into a global fuzzy state model of the single-machine infinite power system according to the fuzzy rules;

S4, build a fuzzy event trigger controller, and define the trigger form and conditions;

S5. Based on the optimal performance index in the zero initial state, the fuzzy event trigger controller is used to perform the optimal control of the single-machine infinite power system.

Preferably, in the step S1, the established single-machine infinite power system model with uncertainty is:

In the formula, δ is the operating angle of the generator rotor; ω is the relative rotational speed of the generator; E′ _q is the q-axis transient potential of the generator; ω ₀ is the initial angular velocity of the generator; H is the moment of inertia of the generator rotor; P _m is The mechanical power output by the prime mover; V _s is the infinite bus voltage; x′ _dz is the sum of the transient reactance of the generator; D is the damping coefficient of the generator; T′ _do is the time constant of the excitation winding when the stator winding is closed; x′ _d is the generator shaft transient reactance; T _do is the time constant of the excitation winding when the excitation winding is closed; V _f is the excitation winding voltage, which is set as the control variable, w ₁ (t), w ₂ (t) are the disturbance quantities, x _d is the equivalent reactance of the generator shaft.

Preferably, the step S2 includes using the sector method to locally linearize the single-machine infinite power system model, and the linearized fuzzy state model of the single-machine infinite power system is:

a₁、a₂分别为z₁(t)的最大值和最小值，表达式为：

Wherein, x 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 and a ₂ are the maximum and minimum values of z ₁ (t), respectively, and the expressions are:

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, wherein the first rule is: when z ₁ (t) , when z ₂ (t) is 1, the first fuzzy state equation is obtained:

The second rule is: when z ₁ (t) and z ₂ (t) are -1, the second fuzzy state equation is obtained:

隶属度函数：in

Membership function:

Preferably, in the step S3, a global fuzzy state model is obtained according to the first fuzzy state equation and the second fuzzy state equation:

其中K_h为对应模糊规则的1*3维控制静态增益反馈矩阵，t_k表示触发时刻，F₁、F₂为隶属度函数。Preferably, in step S4, the fuzzy event-triggered controller is designed using parallel distributed compensation technology, and the following control rules are set: if x ₁ (t) is F ₁ and x _g (t) is F ₂ , then

Among them, K _h is the 1*3-dimensional control static gain feedback matrix corresponding to the fuzzy rules, t _k is the trigger time, and F ₁ and F ₂ are membership functions.

Preferably, the triggering form of the fuzzy event triggering controller is:

e(t)=x(t _k )-x(t)

where e(t) is the event-triggered driving of the system, _k is the number of times the event is triggered, and tk is the triggering moment.

Preferably, the triggering condition of the fuzzy event triggering the controller is:

Among them, ρ is the set dimensionless number, which _{is used to adjust the trigger condition, and He and H x are} the pre-set matrices.

Preferably, the optimized performance indicators in the zero initial state include:

Among them, γ is a constant, which is the reference value of the suppression index of external interference.

Preferably, in step S5, the controller is triggered according to the fuzzy event to perform real-time control of the single-machine infinite power system, so that the closed-loop system is asymptotically stabilized, and a set of positive definite symmetric matrix solutions P are obtained, so that the following linear matrix inequality is established:

where Q=P ^-1 , H _h =K _h Q, l=1,2, h=1,2, K ₁ , K ₂ are 1*3-dimensional control gain matrices corresponding to the corresponding fuzzy rules, and P is 3*3 dimensional symmetric positive definite matrix.

Compared with the prior art, the beneficial effects achieved by the present invention are as follows:

The invention provides an optimal control method for a single-machine infinite power system based on a T-S model, which is designed from the fuzzy modeling and controller design of a single-machine infinite power system, and can realize high-function event triggering of a single-machine infinite power system. Optimize the control objective, meet the high functionality and reliability of the power system during operation, and have strong feasibility, fully meet the high functional requirements of the real-time event-triggered control of the single-machine infinite power system, and improve the robustness and reliability of the single-machine infinite power system. High functionality.

Description of drawings

In order to illustrate the technical solutions in the embodiments of the present invention more clearly, the following briefly introduces the accompanying drawings used in the description of the embodiments. Obviously, the accompanying drawings in the following description are only preferred embodiments of the present invention. For those of ordinary skill in the art, other drawings can also be obtained from these drawings without creative labor.

Fig. 1 is a flow chart of a T-S model-based optimal control method for a single-machine infinite power system provided by the present invention;

Fig. 2 is the sector diagram of cos(x1(t)) of the present invention;

Fig. 3 is the state response of the stand-alone infinite power system of the present invention;

Fig. 4 is the control input of the stand-alone infinite power system of the present invention;

Fig. 5 is the optimized output response of the single-machine infinite power system of the present invention;

FIG. 6 is an event trigger signal of the single-machine infinite power system of the present invention.

Detailed ways

In order to better understand the technical content of the present invention, specific embodiments are provided below, and the present invention is further described with reference to the accompanying drawings.

Referring to FIG. 1, a T-S model-based optimal control method for a single-machine infinite power system in this embodiment is applied to the control of a single-machine infinite power system. Now the event triggering technology has developed into a relatively mature technology and has been widely used in many fields. , the use of event-triggered technology makes the application system have obvious effects in improving work efficiency and reducing workload. Therefore, in this embodiment, a single-machine infinite power system is established by linearizing the mathematical model of the single-machine infinite power system. The fuzzy event-triggered controller is constructed based on the global fuzzy state model of the system. By defining the event-triggering form and triggering conditions and establishing the optimal performance index under the zero initial state, the event-triggered optimal control of the single-machine infinite power system can be carried out. , can achieve the high-function event-triggered control target of the single-machine infinite power system, meet the high security and high reliability of the power system during operation, improve the control method of the control method in terms of information sampling technology, and greatly reduce the unnecessary acquisition of the system. The number of times of information can effectively relieve the pressure of the system information transmission channel and improve the robustness and high functionality of the single-machine infinite power system. An optimal control method for the single-machine infinite power system based on the T-S model includes the following steps:

S1. Establish a single-machine infinite power system model, and the established single-machine infinite power system model with uncertainty is:

In the formula, δ is the operating angle of the generator rotor; ω is the relative rotational speed of the generator; E′ _q is the q-axis transient potential of the generator; ω ₀ is the initial angular velocity of the generator; H is the moment of inertia of the generator rotor; P _m is The mechanical power output by the prime mover; V _s is the infinite bus voltage; x′ _dz is the sum of the transient reactance of the generator; D is the damping coefficient of the generator; T′ _do is the time constant of the excitation winding when the stator winding is closed; x′ _d is the generator shaft transient reactance; T _do is the time constant of the excitation winding when the excitation winding is closed; V _f is the excitation winding voltage, which is set as the control variable, w ₁ (t), w ₂ (t) are the disturbance quantities, x _d is the equivalent reactance of the generator shaft.

S2, using the sector method to locally linearize the single-machine infinite power system model, the linearized fuzzy state model of the single-machine infinite power system is:

Wherein, x 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 ,

a₁、a₂分别为z₁(t)的最大值和最小值。表达式为：

a ₁ and a ₂ are the maximum and minimum values of z ₁ (t), respectively. The expression is:

最终通过扇区法可将cos(x₁(t))线性化。As can be seen from Figure 2, the sector [b ₁ , b ₂ ] consists of two lines b ₁ x ₁ and b ₂ x ₁ , with slopes of

Finally, cos(x ₁ (t)) can be linearized by the sector method.

S3. Convert the fuzzy state model of the single-machine infinite power system into a global fuzzy state model of the single-machine infinite power system according to the fuzzy rules, wherein the fuzzy rules include If-Then modeling rules, and the If-Then modeling The rules include a first rule and a second rule, wherein the first rule is: when z ₁ (t) and z ₂ (t) are 1, the first fuzzy state equation is obtained:

The second rule is: when z ₁ (t) and z ₂ (t) are -1, the second fuzzy state equation is obtained:

隶属度函数：in

Membership function:

A global fuzzy state model is obtained according to the first fuzzy state equation and the second fuzzy state equation:

其中K_h为对应模糊规则的1*3维控制静态增益反馈矩阵，t_k表示触发时刻，F₁、F₂为隶属度函数，并定义所述模糊事件触发控制器的触发形式为：S4. Design a fuzzy event-triggered controller using parallel distributed compensation technology, and set the following control rules: if x ₁ (t) is F ₁ and x _g (t) is F ₂ , then

Wherein K _h is the 1*3-dimensional control static gain feedback matrix corresponding to the fuzzy rule, t _k represents the trigger time, F ₁ and F ₂ are membership functions, and the trigger form of the fuzzy event-triggered controller is defined as:

e(t)=x(t _k )-x(t)

where e(t) is the event-triggered driving of the system, _k is the number of times the event is triggered, and tk is the triggering moment.

Define the trigger condition for the fuzzy event to trigger the controller as:

Among them, ρ is the set dimensionless number, which _{is used to adjust the trigger condition, and He and H x are} the pre-set matrices.

S5. The optimized performance index established in the zero initial state:

According to the fuzzy event trigger controller, the real-time control of the single-machine infinite power system is performed, the closed-loop system is asymptotically stabilized, and a set of positive definite symmetric matrix solutions P are obtained, so that the following linear matrix inequality is established:

where Q=P ^-1 , H _h =K _h Q, l=1,2, h=1,2, K ₁ , K ₂ are 1*3-dimensional control gain matrices corresponding to the corresponding fuzzy rules, and P is 3*3 dimensional symmetric positive definite matrix.

The following experiments are carried out with a single-machine infinite power system. The main technical performance indicators and equipment parameters selected are: 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 rules in the fuzzy time-triggered controller:

K ₁ = [-28.0562 -127.2194 -77.7566]

K ₂ = [-28.6512 -126.5596 -77.3654]

The positive definite symmetric matrix obtained from the above parameters and data:

The initial condition of the single _- machine infinite power system is set as x _{0 =} [0.21 0.62 0.33] ^T . t) and x ₃ (t) are respectively the operating angle of the generator rotor, the relative rotational speed of the generator, and the q-axis transient potential of the generator. It can be seen from Figure 3 that after the system is disturbed, x ₂ (t), x ₃ ( t) After the system runs for 1s, it basically tends to be stable and has a relatively fast recovery ability, and there is no obvious increase in x ₁ (t), indicating that it has a certain anti-interference ability; Figure 4 shows the stable operation of a single-machine infinite power system in a closed-loop system It can be seen from Figure 4 that the control input is completely balanced at about 1s, which can prove that the system has strong robustness; Figure 5 is the optimized output response of the single-machine infinite power system. It can be seen that the output response of the system drops sharply after 1s, and basically returns to normal after 2-3s; Figure 6 is the state curve of the single-machine infinite system under the event trigger control, and it can be seen from Figure 6 that when the actual value exceeds the preset value. , the system will automatically adjust for effective control.

In summary, the data and graphs can prove that the method of the present invention improves the control capability of the single-machine infinite power system in terms of information sampling technology, greatly reduces the number of times the system collects unnecessary information, effectively relieves the pressure on the system information transmission channel, and improves the efficiency of the system. Robustness and high functionality of a single-machine infinite power system.

The above descriptions are only preferred embodiments of the present invention, and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included in the present invention. within the scope of protection.

Claims (10)

1. A single machine infinite electric 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;

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 fuzzy rules;

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 as claimed in claim 1, wherein in step S1, the established model of the single infinite electric power system with uncertainty is:

in the formula, the running angle of the generator rotor is shown; omega is the relative rotating speed of the generator; e'_qIs a generator q-axis transient potential; omega₀Is the initial angular velocity of the generator; h is the rotational inertia of the generator rotor; p_mMechanical power output by the prime mover; v_sInfinite bus voltage; x'_dzIs the sum of transient reactances of the generators; d is a damping coefficient of the generator; t'_doThe time constant of the excitation winding when the stator winding is closed; x'_dIs a generator shaft transient reactance; t is_doIs the time constant of the exciting winding when the exciting winding is closed; v_fTo the field winding voltage, w₁(t)、w₂(t) is the amount of interference, x_dEqual reactance for the generator shaft.

3. The method as claimed in claim 2, wherein the step S2 includes performing local linearization on the model of the single infinite electric power system by using a sector method, where the fuzzy state model of the linearized single infinite electric power system is:

wherein x is₁(t)＝，x₂(t)＝ω，x₃(t)＝E′_q，u(t)＝V_f，x(t)＝[x₁(t) x₂(t) x₃(t)]^T，w(t)＝[0 w₁(t) w₂(t)]^T，

a₁、a₂Are each z₁(t) maximum and minimum values, expressed as:

4. the method as claimed in claim 3, wherein 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 is₁(t)、z₂(t) is 1, obtaining a first fuzzy state equation:

the second rule is: when z is₁(t)、z₂(t) is-1, obtaining a second fuzzy state equation:

wherein

Membership function:

5. the method as claimed in claim 4, wherein in step S3, a global fuzzy state model is obtained according to the first fuzzy state equation and the second fuzzy state equation:

6. the method as claimed in claim 5, wherein in step S4, the fuzzy event-triggered controller is designed by using a parallel distribution compensation technique, and the following control rules are set: if x₁(t) is F₁And x is_g(t) is F₂Then, then

Wherein K_hFor controlling the static gain feedback matrix in 1 x 3 dimensions corresponding to the fuzzy rule, t_kIndicating the moment of triggering, F₁、F₂Is a function of membership.

7. The method for optimizing and controlling the stand-alone infinite electric power system based on the T-S model as claimed in claim 6, 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 travel of the system, k represents the number of event triggers, t_kIndicating the moment of trigger.

8. The method as claimed in claim 7, wherein 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_eAnd H_xIs a preset matrix.

9. The method as claimed in claim 8, wherein the optimization performance index in the zero initial state includes:

∫₀ ^∞[z^T(t)z(t)-γ²w^T(t)w(t)]dt<0

where γ is a constant and is a suppression index reference value of the external disturbance.

10. The method as claimed in claim 9, wherein in step S5, the fuzzy event trigger controller is used 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 symmetry matrix solutions P, so that the following linear matrix inequalities hold:

wherein Q ═ P^-1，H_h＝K_hQ，l＝1,2，h＝1,2，K₁、K₂P is a 3-dimensional symmetric positive definite matrix corresponding to the 1-dimensional 3-dimensional control gain matrix of the corresponding fuzzy rule.

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