A Variable Proportional Factor Fuzzy PID Excitation System and Its Application

Abstract

The present invention discloses a variable proportional factor fuzzy PID excitation system and its application. The excitation system first obtains the voltage deviation and voltage deviation change rate at the machine end, and uses them as input signals. Fuzzy reasoning is performed according to fuzzy rules. The fuzzy output is then integrated with the proportional factor after real-time adjustment. The fuzzy output is added to the PID initial parameter to form a new control parameter, which is linearly combined and finally converted into an accurate excitation voltage output. The present invention introduces a proportional factor adjustment link on the basis of fuzzy PID control to form a variable proportional factor fuzzy PID (V-FPID) excitation system. Its principle is simple and intuitive, and it only contains two constant parameters. The adjustment method is easy to implement, which greatly improves the parameter adjustment efficiency of the fuzzy control system. It has been verified that compared with traditional PID and FPID systems, the excitation system has significantly improved the robustness, stability, response speed and steady-state accuracy of the synchronous generator terminal voltage.

Description

Technical Field

[0001] The present invention belongs to the technical field of synchronous generator voltage regulation, and in particular relates to a variable proportional factor fuzzy PID (V-FPID) excitation system and an application thereof. Background Art

[0002] The excitation regulation system for synchronous generators is a crucial component of the power generation process, and its control performance directly impacts the stability and security of the power grid. PID regulation is one of the primary excitation control methods for synchronous generators, offering advantages such as a simple structure and low steady-state error. However, its drawbacks are also significant: PID parameters remain fixed during system operation, making it inflexible in responding to fault disturbances encountered by the power system. Consequently, generators controlled by a simple PID excitation system exhibit poor stability and robustness, potentially becoming unstable in the event of a fault, thus impacting the dynamic performance of the entire power system.

[0003] Fuzzy PID (FPID) combines traditional PID with a fuzzy control mechanism. It retains the advantages of PID control principles, simplicity, and reliability, while also offering the advantages of fuzzy control's independence from precise models and strong adaptability. Consequently, it has attracted considerable attention in recent years. However, its quantization and proportional factors are fixed, resulting in less than ideal adjustment range and control accuracy in practical applications. To overcome these shortcomings, variable-domain fuzzy PID controllers have emerged. These controllers are essentially fuzzy PID controllers that adjust the input and output domains based on system error, thereby improving system adaptability. However, they contain a large number of constant parameters (approximately 10), and there is no reliable method for selecting these constant parameters. This requires extensive debugging and is difficult to achieve optimal values, limiting their efficiency.

[0004] In view of this, the inventors propose a variable proportional factor fuzzy PID excitation system and its application to solve the above technical problems. Summary of the Invention

[0005] The purpose of the present invention is to overcome the shortcomings of the above-mentioned prior art and provide a variable proportional factor fuzzy PID excitation system and its application. The excitation system only contains two constant parameters and can adjust the proportional factor in real time according to the fuzzy input quantity, thereby improving the adaptability of the excitation system and thus improving the excitation performance; and it has been verified that the stability, robustness, response speed and steady-state accuracy of the terminal voltage of the synchronous generator are significantly improved.

[0006] The purpose of the present invention is to solve the problem through the following technical solutions:

[0007] A variable proportional factor fuzzy PID excitation system, the excitation system first obtains the voltage deviation ΔU at the machine end t and voltage deviation change rate ΔUc And take it as the input signal, perform fuzzy reasoning through fuzzy rules, and then integrate the fuzzy output through the proportional factor adjusted in real time, and add it to the PID initial parameter to form a new control parameter K P , K I , K D , as shown in formula (1), and then linearly combined and finally converted into the excitation voltage output U fd ;

[0008]

[0009] In formula (1): K P , K I , K D is the changed PID parameter; K PO , K IO , K DO is the initial PID parameter; k u is the scale factor; K FP , K FI , K FD is the fuzzy output; U fd is the excitation voltage output.

[0010] Furthermore, the excitation system includes:

[0011] The voltage sampling and calculation module obtains the actual voltage at the generator end through the voltage sensor, and compares the actual voltage with the rated voltage to obtain the voltage deviation ΔU t And the voltage deviation change rate ΔU c , as the input signal of the excitation system;

[0012] The fuzzy reasoning module is used to obtain the membership degree and corresponding fuzzy language of the input quantity, and then perform fuzzy reasoning on it using the fuzzy rule table to obtain the fuzzy output quantity;

[0013] A quantization factor module is used to map the input signal to the domain of the fuzzy inference rule in the fuzzy inference module;

[0014] The variable proportional factor module is used to adjust the output value inferred by the fuzzy reasoning module in real time.

[0015] Furthermore, the fuzzy inference module sets the input voltage deviation ΔU before formulating the fuzzy rule: t and voltage deviation change rate ΔU c And the output fuzzy output K FP , K FI , K FDIt is divided into seven levels, namely "positive large", "positive medium", "positive small", "zero", "negative small", "negative medium", and "negative large", and the corresponding fuzzy language is: PB, PM, PS, ZO, NS, NM, NB.

[0016] Furthermore, the fuzzy reasoning module sets the domain of input and output to {-6, -4, -2, 0, 2, 4, 6}, and uses the triangular membership function on the fuzzy subset to obtain the membership degree of the input and output.

[0017] Furthermore, the fuzzy rules in the fuzzy reasoning module are as follows:

[0018] (1) When the terminal voltage deviation ΔU t Corresponding to positive large, negative large, positive middle, negative middle, regardless of the voltage deviation change rate ΔU c The size of ΔK P , ΔK I should be positive, and ΔK D The negative value should be large to speed up the response of the terminal voltage;

[0019] (2) When ΔU t Corresponding to small positive and small negative, and ΔU t With ΔU c When the signs are the same, it indicates that the system has encountered a fault that causes voltage fluctuations. To improve the stability of the system, ΔK P , ΔK I The value should be positive and large, and ΔK D The value should be positive;

[0020] (3) When ΔU t Corresponding to small positive and small negative, and ΔU t With ΔU c When the sign is opposite, it indicates that the terminal voltage is transitioning to a steady-state value. To avoid excessive overshoot, ΔK D , ΔK I The value should be small or zero, but in order to take into account the response speed, ΔK P The value should be positive or neutral;

[0021] By analyzing and debugging the above control rules, the fuzzy control rules are shown in the following table:

[0022]

[0023] Furthermore, the quantization factor module needs to determine the initial parameters of PID adjustment before tuning, and determine its voltage deviation △U by observing the adjustment process of the system by PID containing only the initial parameters. t and voltage deviation change rate ΔU cThe actual domain of , according to formula (2), that is, the mapping relationship between the domain of the input variable and its actual domain, the quantization factor is obtained:

[0024]

[0025] In formula (2): k e is the quantization factor of voltage deviation; k ec is the quantization factor of the voltage deviation change rate; z e is the domain of voltage deviation; z ec is the domain of voltage deviation change rate; x e is the actual domain of voltage deviation; x ec is the actual domain of the voltage deviation change rate.

[0026] Furthermore, the principle of adjusting the variable scale factor module is as follows:

[0027] (1) In the OM segment (i.e. ΔU t When the corresponding fuzzy language is PB or PM, the variable proportional factor module amplifies its output result by α times (α>1). Combining the fuzzy rule table and formula (1), it can be seen that its response speed is significantly better than that of PID control.

[0028] (2) In the FI segment (i.e. ΔU t When the corresponding fuzzy language is ZO), the variable scale factor module amplifies its output result by β times (β>α), making the system more robust and having smaller steady-state error during operation.

[0029] (3) In the MZ segment and TF segment (i.e. ΔU t When the corresponding fuzzy language is PS and NS), the variable scale factor module amplifies its output result by γ times (γ>β). Combined with the fuzzy rule table, it can be seen that this can ensure that the system has a smaller overshoot and a faster stabilization time;

[0030] Furthermore, the variable proportional factor module obtains a proportional factor variation curve according to the setting principle, and performs data fitting on the curve to obtain a functional relationship between the proportional factor and the terminal voltage deviation, as shown in formula (3):

[0031]

[0032] In formula (3): 0<T1<1, 0<T2<1; k u is the scale factor; U F is the mapping value of the voltage deviation on the input domain; T1 is the final value factor, which determines the maximum value of the proportional factor and is strongly related to the robustness of the excitation system; T2 is the initial value factor, which determines the initial value and smaller value of the proportional factor and is strongly related to the response speed of the excitation system.

[0033] Furthermore, the variable scale factor module adjusts T1 and T2 in the scale factor according to the critical gain method. The specific process is as follows:

[0034] (1) First adjust T1, then set T2 = 1. The size of T1 is inversely proportional to the maximum value of the proportional factor. Combined with the above fuzzy control rules, it can be seen that the size of T1 is inversely proportional to the positive damping of the terminal voltage. Adjust T1 so that the generator voltage deviation change rate is |ΔU c |≤0.05pu, voltage deviation is |ΔU t |≤0.05pu;

[0035] (2) Adjust T2 again. The size of T2 is inversely proportional to the smaller and middle values ​​of the proportional factor. Combined with the above fuzzy control rules, the size of T2 is inversely proportional to the response speed of the generator. Adjust T2 so that the voltage deviation change rate of the generator terminal voltage is |ΔU c |≤0.05pu, voltage deviation is |ΔU t |≤0.02pu.

[0036] A synchronous generator adopts the above-mentioned excitation system based on variable proportional factor fuzzy PID control to improve the stability, robustness, response speed and steady-state accuracy of the synchronous generator terminal voltage.

[0037] Compared with the prior art, the present invention has the following beneficial effects:

[0038] The present invention provides a variable proportional factor fuzzy PID excitation system. The variable proportional factor fuzzy PID (V-FPID) excitation system uses the system error to adjust the value of the proportional factor in real time. The principle is simple and intuitive, and only two constant parameters are included. The adjustment method is easy to implement, which greatly improves the parameter adjustment efficiency of the fuzzy control system. In addition, a simulation comparison of three groups of generator excitation systems, PID, FPID, and V-FPID, is carried out in MATLAB / Simulink based on a single-machine-infinite system. The results show that compared with traditional PID and fuzzy PID (FPID) excitation systems, the variable proportional factor fuzzy PID (V-FPID) excitation system of the present invention has significantly improved the robustness, stability, response speed and steady-state accuracy of the synchronous generator terminal voltage. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] The accompanying drawings are incorporated in and constitute a part of this specification and, together with the description, serve to explain the principles of the invention.

[0040] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0041] Figure 1 This is a schematic diagram of the principle structure of the variable proportional factor fuzzy PID excitation system of the present invention;

[0042] Figure 2 The figure is a membership function diagram of input and output in the variable proportional factor fuzzy PID excitation system of the present invention;

[0043] Figure 3 It is a response curve diagram of the PID control system in the variable proportional factor fuzzy PID excitation system of the present invention;

[0044] Figure 4 The changing trend of the proportional factor in the variable proportional factor fuzzy PID excitation system of the present invention;

[0045] Figure 5 This is a curve diagram showing the change of proportional factor with T1 in the variable proportional factor fuzzy PID excitation system of the present invention;

[0046] Figure 6 This is a curve diagram showing the change of proportional factor with T2 in the variable proportional factor fuzzy PID excitation system of the present invention;

[0047] Figure 7 This is an excitation simulation model diagram based on a single-machine infinite system of the present invention;

[0048] Figure 8 This is a terminal voltage response curve diagram when the generator of the present invention starts, encounters a sudden increase in the reference voltage, and encounters a sudden decrease in the reference voltage;

[0049] Figure 9 This is a response curve diagram of the terminal voltage when the present invention encounters single-phase or three-phase short circuit, sudden increase or decrease of heavy load, sudden increase or decrease of mechanical power;

[0050] Figure 10 This is an analysis diagram of the terminal voltage simulation results when the present invention encounters fault interference; wherein P m The mechanical power input to the synchronous generator. DETAILED DESCRIPTION

[0051] Exemplary embodiments will be described in detail herein, examples of which are illustrated in the accompanying drawings. In the following description, when referring to the drawings, identical numerals in different figures represent identical or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all possible embodiments consistent with the present invention. Rather, they are merely examples of arrangements consistent with certain aspects of the present invention as detailed in the appended claims.

[0052] In order to enable those skilled in the art to better understand the technical solutions of the present invention, the present invention is described in further detail below with reference to the accompanying drawings and embodiments.

[0053] The present invention provides a variable proportional factor fuzzy PID excitation system, the principle of which is as follows: Figure 1 As shown in FIG, fuzzy PID (FPID) is formed by introducing fuzzy reasoning on the basis of conventional PID control, and the variable proportional factor fuzzy PID (V-FPID) control principle of the present invention is to introduce a proportional factor setting link on the fuzzy PID (FPID). Its working principle is as follows: the excitation system first obtains the voltage deviation △U at the machine end t and voltage deviation change rate ΔU c , and use it as the input signal, perform fuzzy reasoning through fuzzy rules, and then integrate the fuzzy output ΔK through the proportional factor adjusted in real time. p , ΔK i , ΔK d , added to the initial PID parameters to form a new control parameter K P , K I , K D , as shown in formula (1), and linearly combine them and finally convert them into the accurate excitation voltage output U fd ;

[0054]

[0055] In formula (1): K p , K I , K D is the changed PID parameter; K PO , K IO , K DO is the initial PID parameter; k u is the scale factor; K FP , K FI , K FD is the fuzzy output; U fd is the excitation voltage output.

[0056] The excitation system includes the following four modules:

[0057] 1. Voltage sampling and calculation module, which obtains the actual voltage at the generator end through the voltage sensor and compares the actual voltage with the rated voltage to obtain the voltage deviation △U t And the voltage deviation change rate △U c , as the input signal of the excitation system.

[0058] Second, the fuzzy reasoning module is used to obtain the membership degree of the input quantity and the corresponding fuzzy language, and then use the fuzzy rule table to perform fuzzy reasoning to obtain the fuzzy output quantity:

[0059] Specifically, in the excitation system, the input voltage deviation ΔU t and voltage deviation change rate ΔU c And the output fuzzy output K FP , K FI , K FD It is divided into seven levels, namely "positive large", "positive medium", "positive small", "zero", "negative small", "negative medium", and "negative large", and the corresponding fuzzy languages ​​are: PB, PM, PS, ZO, NS, NM, NB; and the domain of input and output is set to {-6, -4, -2, 0, 2, 4, 6}, and the above fuzzy subsets are selected as follows Figure 2 The triangular membership functions are shown.

[0060] After obtaining the input's membership and corresponding fuzzy language, a fuzzy rule table is used to perform fuzzy reasoning to obtain the fuzzy output. Because the proportional factor is adjusted in real time with voltage deviation and has high adaptability, the fuzzy control rules do not need to be very detailed; they only need to follow the general trend. This makes the control rules simpler and saves a lot of debugging work. The control rules are as follows:

[0061] Furthermore, the fuzzy rules in the fuzzy reasoning module are as follows:

[0062] (1) When the terminal voltage deviation ΔU t Corresponding to positive large, negative large, positive middle, negative middle, regardless of the voltage deviation change rate ΔU c The size of ΔK P , ΔK I should be positive, and ΔK D The negative value should be large to speed up the response of the terminal voltage;

[0063] (2) When ΔU t Corresponding to small positive and small negative, and ΔU t With ΔU c When the signs are the same, it indicates that the system has encountered a fault that causes voltage fluctuations. To improve the stability of the system, ΔK P , ΔK I The value should be positive and large, and ΔKD The value should be positive;

[0064] (3) When ΔU t Corresponding to small positive and small negative, and ΔU t With ΔU c When the sign is opposite, it indicates that the terminal voltage is transitioning to a steady-state value. To avoid excessive overshoot, ΔK D , ΔK I The value should be small or zero, but in order to take into account the response speed, ΔK P The value should be positive or neutral;

[0065] By analyzing and debugging the above control rules, the fuzzy control rules are shown in the following table:

[0066]

[0067] 3. Quantization factor module, used to map the input signal to the domain of fuzzy inference rules in the fuzzy inference module (the domain of input variables):

[0068] Specifically, its tuning requires first determining the initial parameters of the PID adjustment. By observing the adjustment process of the system using the PID with only the initial parameters, the voltage deviation ΔU can be determined. t and its rate of change ΔU c The actual domain of , according to formula (2), that is, the mapping relationship between the domain of the input variable and its actual domain, the quantization factor is obtained:

[0069]

[0070] In formula (2): k e is the quantization factor of voltage deviation; k ec is the quantization factor of the voltage deviation change rate; z e is the domain of voltage deviation; z ec is the domain of voltage deviation change rate; x e is the actual domain of voltage deviation; x ec is the actual domain of the voltage deviation change rate.

[0071] In this embodiment, the initial parameter K of PID is PO =181.0221, K IO =67.9,K DO =6.8; observing the control process, we can get the absolute value of the input voltage deviation |ΔU t The maximum value of | is 1, so its actual domain is [-1 1], and the absolute value of the deviation change rate |ΔU cThe maximum value of | is 25, so its actual domain is [-25 25]. Combined with the input domain set as {-6, -4, -2, 0, 2, 4, 6} in this paper, its quantization factor K can be obtained according to formula (2): e =6,K ec =0.24.

[0072] 4. Variable proportional factor module, used to adjust the output of the fuzzy reasoning module in real time:

[0073] Specifically, the response curve of the PID control system is as follows: Figure 3 As shown in the figure, the impact of the proportional factor on the system is mainly reflected in its scaling of the output of fuzzy reasoning, so the principles of the designed V-FPID proportional factor tuning method are as follows:

[0074] (1) In the OM segment (i.e. ΔU t When the corresponding fuzzy language is PB or PM, the variable proportional factor module amplifies its output result by α times (α>1). Combining the fuzzy rule table and formula (1), it can be seen that its response speed is significantly better than that of PID control.

[0075] (2) In the FI segment (i.e. ΔU t When the corresponding fuzzy language is ZO), the variable scale factor module amplifies its output result by β times (β>α), making the system more robust and having smaller steady-state error during operation.

[0076] (3) In the MZ segment and TF segment (i.e. ΔU t When the corresponding fuzzy language is PS and NS), the variable scale factor module amplifies its output result by γ times (γ>β). Combined with the fuzzy rule table, it can be seen that this can ensure that the system has a smaller overshoot and a faster stabilization time;

[0077] According to the above setting principles, the following can be drawn: Figure 4 The curve of the proportional factor change is shown in Figure 2. By fitting the data to this curve, the functional relationship between the proportional factor and the terminal voltage deviation can be obtained, as shown in formula (3):

[0078]

[0079] In formula (3): 0<T1<1, 0<T2<1; k u is the scale factor; U F is the mapping value of the voltage deviation on the input domain; T1 is the final value factor, which determines the maximum value of the proportional factor and is strongly related to the robustness of the excitation system; T2 is the initial value factor, which determines the initial value and smaller value of the proportional factor and is strongly related to the response speed of the excitation system.

[0080] Use the critical gain method to adjust T1 and T2 in the proportional factor:

[0081] (1) Adjust T1 first, then set T2 = 1, such as Figure 5 As shown, the size of T1 is inversely proportional to the maximum value of the proportional factor. Combined with the above fuzzy control rules, it can be seen that the size of T1 is inversely proportional to the positive damping of the terminal voltage. Adjust T1 to make the generator voltage deviation change rate a smaller value (generally |ΔU c |≤0.05pu), the voltage deviation is also maintained in a small range (|ΔU t |≤0.05pu);

[0082] (2) Adjust T2 again, such as Figure 6 As shown, the size of T2 is inversely proportional to the smaller and middle values ​​of the proportional factor. Combined with the above fuzzy control rules, the size of T2 is inversely proportional to the response speed of the generator. By adjusting T2, the voltage deviation change rate of the generator terminal voltage can be made into a smaller value (generally |ΔU c |<=0.05pu), the voltage deviation is also maintained in a small range (|ΔU t |<=0.02pu); After debugging by the above method, this embodiment takes T1=0.009 and T2=0.58.

[0083] In order to verify the effectiveness of the above variable proportional factor fuzzy PID excitation system, a simulation verification is carried out, as shown below:

[0084] When studying the simulation model of the excitation system, a single-machine-infinite system is generally used for simulation. The system consists of a generator, a transformer, a double-circuit line, a plant power load, and an infinite system; the transmission line is a 230kV line, and the infinite system is composed of a 10000MVA power supply and a 10MVA load. The V-FPID excitation system simulation model established based on the single-machine-infinite system is as follows: Figure 7 shown.

[0085] Construction of a single-machine infinite system: The standard per-unit synchronous generator (Synchronous Machine pu Standard) is selected for simulation in the Simulink library of MATLAB R2018a. It consists of a relatively accurate mathematical model of 12 electromagnetic equations and motion equations. The input is the mechanical power P m and excitation voltage V fThe output is three-phase AC power and the measurement terminal. The generator parameters are shown in Table 2. The auxiliary power load is a three-phase parallel RLC load with a parameter of 5 MW, which is a resistive load. The three-phase transformer is a three-phase transformer with parameters of 210 MVA 13.8 kV / 230 kV. The transmission line is a three-phase series RLC branch with a resistance of 0.1 Ω and an inductance of 0.01 H. The three-phase source module (parameters of 10000 MVA 230 kV) and the three-phase parallel RLC load module (parameters of 10 MW) are used as an infinite system.

[0086] To simulate power grid faults, the system incorporates additional fault configuration. A three-phase fault function module is set up in the line to simulate single-phase and three-phase short circuits. A 5000MW load with a three-phase breaker module is added to the line to simulate sudden load increases and load shedding. Mutation devices are added to the reference voltage input and the generator's mechanical power input to simulate sudden increases and decreases in reference voltage and mechanical power. Solver options are variable-step and ode23tb; the relative tolerance is 1e-3; all other parameters remain default.

[0087] Table 2 Generator parameters

[0088]

[0089] After building the simulation model and setting the parameters of each module, the excitation system with three control modes, PID, FPID and V-FPID, was simulated.

[0090] Simulation and analysis of generator terminal voltage under different conditions: During the simulation process, the focus is on simulating the operating characteristics of transient processes such as the startup of the synchronous generator, sudden increase and decrease of reference voltage, single-phase short circuit, three-phase short circuit, sudden increase and decrease of load, sudden increase and decrease of mechanical power, etc.

[0091] The operation process is as follows: start the generator, wait for the system to stabilize, then the reference voltage suddenly increases by 40% in the 2nd second of system operation, and suddenly decreases to the initial value after 4 seconds; a single-phase short circuit occurs in the system at 10 seconds, and the fault is cleared after 0.1 seconds; a three-phase short circuit occurs in the system at 12 seconds, and the fault is cleared after 0.1 seconds; the system suddenly increases the load at 15 seconds, and the system sheds the load after 3 seconds; the generator input mechanical power suddenly increases by 50% at 22 seconds, and the mechanical power suddenly decreases to the initial value after 4 seconds, and the system ends operation at 30 seconds.

[0092] The terminal voltage response curve when the generator starts, encounters a sudden increase or decrease in reference voltage is as follows: Figure 8 As shown, calculation and analysis are performed, and Table 3 can be obtained:

[0093] Table 3 Analysis of simulation results when the generator starts, encounters a sudden increase in reference voltage, and a sudden decrease in reference voltage

[0094]

[0095] In the table: σ is the overshoot, t s To adjust the time.

[0096] from Figure 8 As can be seen from Table 3, when the generator starts and encounters a sudden increase or decrease in the reference voltage, the response speed of the generator terminal voltage controlled by the V-FPID excitation system is significantly improved compared with the PID and FPID excitation modes, with almost no overshoot and faster adjustment time. Observing the terminal voltage after the transition, it can be seen that the steady-state accuracy of the generator terminal voltage controlled by the V-FPID excitation mode is higher than that of the other two modes.

[0097] The response curve of the terminal voltage when the generator encounters single-phase short circuit, three-phase short circuit, sudden increase in load, sudden decrease in load, sudden increase in mechanical power, sudden decrease in mechanical power, etc. is as follows Figure 9 As shown in Figure 2, the V-FPID excitation system significantly improves the performance of the generator terminal voltage. Due to space limitations, we will not list individual indicators here. Instead, we will use the comprehensive indicators shown in Equation (4)—Integral Absolute Error (IAE) and settling time—to comprehensively reflect the quality of the three excitation systems in generator operation control.

[0098]

[0099] Where: J is the objective function value, e is the dynamic deviation.

[0100] right Figure 9 The comprehensive indicators obtained by analyzing and calculating the simulation results of the generator terminal voltage are as follows Figure 10 As shown, from Figure 9 and Figure 10 Data analysis shows that when the generator encounters single-phase short circuit, three-phase short circuit, sudden load increase, sudden load reduction, sudden increase in mechanical power, sudden decrease in mechanical power, etc., compared with the PID and FPID excitation methods, the robustness and stability of the generator terminal voltage controlled by the V-FPID excitation system are significantly improved; similarly, after the transition is completed, the steady-state accuracy is also significantly higher.

[0101] In summary, the principles of the variable proportional factor fuzzy PID (V-FPID) excitation system and the tuning methods for its parameters are demonstrated in this paper. Simulations comparing three generator excitation systems, PID, FPID, and V-FPID, were conducted based on a single-machine-infinite system. The simulations focused on the operating characteristics of synchronous generators under various conditions, including startup, sudden increase and decrease in reference voltage, single-phase and three-phase short circuits, sudden increase and decrease in load, sudden increase and decrease in mechanical power, and the following key conclusions:

[0102] (1) Compared with the traditional FPID excitation system, the proportional factor of the V-FPID of the present invention is proportional to the voltage deviation ΔU t It can be flexibly adjusted according to the changes in the excitation process, and has a wider adaptability range and better control accuracy during the excitation process; the adjustment principle is simple and intuitive, and there are fewer constant parameters to be adjusted, so it is more feasible and easier to implement.

[0103] (2) Compared with the traditional FPID excitation system, the V-FPID excitation system of the present invention has more superior excitation control performance on the generator terminal voltage, which greatly improves its stability, robustness, response speed and steady-state accuracy.

[0104] The foregoing description is intended only to provide specific embodiments of the present invention, which will enable those skilled in the art to understand and implement the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention.

[0105] It should be understood that the present invention is not limited to the above description and that various modifications and changes may be made without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

Claims

1. A variable proportional factor fuzzy PID excitation system, characterized in that: The excitation system first obtains the voltage deviation at the machine end and voltage deviation change rate , and use it as input signal, perform fuzzy reasoning through fuzzy rules, and then integrate the fuzzy output through the proportional factor adjusted in real time , added to the PID initial parameters to form new control parameters , as shown in formula (1), and linearly combine them and finally convert them into accurate excitation voltage output ; （1） In formula (1): is the changed PID parameter; is the PID initial parameter; is the scale factor; is the fuzzy output; is the excitation voltage output; The excitation system comprises: The voltage sampling and calculation module obtains the actual voltage at the generator end through the voltage sensor and compares the actual voltage with the rated voltage to obtain the voltage deviation and voltage deviation change rate , as the input signal of the excitation system; The fuzzy reasoning module is used to obtain the membership degree and corresponding fuzzy language of the input quantity, and then perform fuzzy reasoning on it using the fuzzy rule table to obtain the fuzzy output quantity; A quantization factor module is used to map the input signal to the domain of the fuzzy inference rule in the fuzzy inference module; The variable proportional factor module is used to adjust the output value inferred by the fuzzy reasoning module in real time; The fuzzy reasoning module is set before formulating the fuzzy rules: the input voltage deviation and voltage deviation change rate And the output fuzzy output It is divided into seven levels, namely "positive large", "positive medium", "positive small", "zero", "negative small", "negative medium", and "negative large", and the corresponding fuzzy language is: PB, PM, PS, ZO, NS, NM, NB; The fuzzy reasoning module sets the domain of input and output to {-6, -4, -2, 0, 2, 4, 6}, and uses the triangular membership function on the fuzzy subset to obtain the membership degree of the input and output; The fuzzy rules in the fuzzy reasoning module are as follows: (1) When the terminal voltage is biased Corresponding to positive large, negative large, positive middle, negative middle, regardless of the voltage deviation change rate The size of All should be upright and The negative value should be large to speed up the response of the terminal voltage; (2) When Corresponding to small positive and small negative, and and When the same sign is shown, it indicates that the system has encountered a fault that causes voltage fluctuation. To improve the stability of the system, I The value should be positive, and The value should be positive; (3) When Corresponding to small positive and small negative, and Δ U t With Δ U c When the sign is different, it indicates that the terminal voltage is transitioning to a steady-state value. To avoid excessive overshoot, The value should be small or zero, but in order to take into account the response speed, The value should be positive or neutral; By analyzing and debugging the above control rules, the fuzzy control rules are shown in the following table: The principles for adjusting the variable scale factor module are as follows: (1) In the OM segment (i.e. When the corresponding fuzzy language is PB or PM), the variable scale factor module amplifies its output result. α times ( α >1), combined with the fuzzy rule table and formula (1), it can be seen that its response speed is significantly better than that of PID control; (2) In the FI segment (i.e. When the corresponding fuzzy language is ZO), the variable scale factor module amplifies its output result β times ( β > α ), which makes the system more robust and have smaller steady-state error during operation; (3) In the MZ segment and TF segment (i.e. When the corresponding fuzzy language is PS and NS), the variable scale factor module amplifies its output result γ times ( γ > β ), combined with the fuzzy rule table, it can be seen that at this time the system can be guaranteed to have a smaller overshoot and a faster stabilization time.

2. A variable scale factor fuzzy PID excitation system according to claim 1, characterized in that: The quantization factor module needs to determine the initial parameters of PID adjustment before tuning, and determine its voltage deviation by observing the adjustment process of the system with only the initial parameters. and voltage deviation change rate The actual domain of , according to formula (2), that is, the mapping relationship between the domain of the input variable and its actual domain, the quantization factor is obtained: （2） In formula (2): k e is the quantization factor of voltage deviation; k ec is the quantization factor of the voltage deviation change rate; z e is the domain of voltage deviation; z ec is the domain of voltage deviation change rate; x e is the actual domain of voltage deviation; x ec is the actual domain of the voltage deviation change rate.

3. The variable scale factor fuzzy PID excitation system according to claim 1, characterized in that: The variable proportional factor module obtains the proportional factor variation curve according to the setting principle. By performing data fitting on the curve, the functional relationship between the proportional factor and the terminal voltage deviation can be obtained, as shown in formula (3): （3） In formula (3): 0 < T 1<1、0< T 2<1; is the scale factor; is the mapping value of voltage deviation on the input domain; T 1 is the final value factor, which determines the maximum value of the proportional factor and is strongly related to the robustness of the excitation system; T 2 is the initial value factor, which determines the initial value and smaller value of the proportional factor and is strongly related to the response speed of the excitation system.

4. The variable scale factor fuzzy PID excitation system according to claim 3, characterized in that: The variable scale factor module adjusts the scale factor according to the critical gain method. T 1 and T 2. The specific process is as follows: (1) Adjust first T 1. This season T 2=1, T The size of 1 is inversely proportional to the maximum value of the proportional factor. Combined with the above fuzzy control rules, we can see that T The size of 1 is inversely proportional to the positive damping of the terminal voltage; adjust T 1, so that the generator voltage deviation change rate is | |≤0.05pu, voltage deviation is| |≤0.05pu; (2) Readjustment T 2, T The size of 2 is inversely proportional to the smaller and middle values ​​of the proportional factor. Combined with the above fuzzy control rules, at this time T The size of 2 is inversely proportional to the response speed of the generator; adjust T 2. Make the voltage deviation change rate of the generator terminal voltage be | |≤0.05pu, voltage deviation is| |≤0.02pu.

5. A synchronous generator, characterized in that: The synchronous generator adopts the excitation system based on variable proportional factor fuzzy PID control according to any one of claims 1 to 4 to improve the stability, robustness, response speed and steady-state accuracy of the synchronous generator terminal voltage.

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