A method and device for adaptive adjustment of PID controller parameters of a networked converter

Abstract

The application relates to the technical field of power systems, and discloses a PID controller parameter self-adaptive adjustment method and device of a grid-forming converter. Based on a small signal model of the grid-forming converter, an output error signal and a change rate of the output error signal of the small signal model are calculated, an error gradient is calculated by using the output error signal and the change rate, and the PID control parameters are dynamically updated based on the gradient descent method. When the PID control parameters are updated, whether the selection of the PID control parameters will lead to instability of the system where the grid-forming converter is located is checked. If yes, the error gradient calculation parameters are adjusted to recalculate the error gradient of the output error signal. If no, the updating of the PID controller parameters is stopped. By self-adaptively adjusting the PID control parameters, the stability of the grid-forming converter in the power grid is effectively ensured. The technical problem that the prior art lacks an effective technical means of self-adaptively adjusting the control parameters of the grid-forming converter to maintain stable operation of the power grid system is solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power systems, and in particular to a PID controller parameter adaptive adjustment method and device for a grid-forming inverter. BACKGROUND

[0002] As a device simulating the inertia of a synchronous machine, a grid-forming inverter (GFI) maintains the stability of a power grid by controlling voltage and frequency. In order to understand its dynamic behavior under disturbance, a small signal model is usually used for linear analysis of the system. The purpose of the small signal model is to study how the system responds under conditions such as power grid disturbance or load change. In general, in small signal analysis, small disturbances are assumed to occur near a certain stable operating point, and a set of transfer functions is obtained by linearizing the control system to describe the dynamic characteristics of the system. In grid-forming inverters, a proportion-integration-differentiation (PID) controller is often used to control key parameters such as voltage and current. Currently, how to adaptively adjust the parameters of the PID controller of the grid-forming inverter to ensure that the grid-forming inverter responds quickly and without oscillation in the power grid system and achieves stable operation of the power grid system is still a technical problem that needs to be solved by those skilled in the art. SUMMARY

[0003] The present application provides a PID controller parameter adaptive adjustment method and device for a grid-forming inverter, which solves the technical problem of the prior art that there is a lack of effective technical means for adaptively adjusting the control parameters of the grid-forming inverter to maintain stable operation of the power grid system.

[0004] Therefore, the first aspect of the present application provides a PID controller parameter adaptive adjustment method for a grid-forming inverter, comprising:

[0005] constructing a small signal model of the grid-forming inverter;

[0006] calculating an output error signal and a rate of change of the output error signal of the small signal model in real time;

[0007] calculating an error gradient of the output error signal based on the output error signal and the rate of change of the output error signal;

[0008] dynamically updating the PID controller parameters using the gradient descent method based on the error gradient;

[0009] based on the updated PID controller parameters, determining whether the system in which the grid-forming inverter is located will become unstable, if not, stopping updating the PID controller parameters, and if so, adjusting the error gradient calculation parameters to recalculate the error gradient of the output error signal.

[0010] Optionally, the formula for dynamically updating the PID controller parameters by using the gradient descent method is:

[0011]

[0012] wherein, is the proportional gain of the PID controller at t+1, is the proportional gain of the PID controller at t, is the learning rate, is the error function for controlling the adjustment direction of the PID controller parameters, is the integral gain of the PID controller at t+1, is the integral gain of the PID controller at t, is the differential gain of the PID controller at t+1, is the differential gain of the PID controller at t.

[0013] Optionally, the error function for controlling the adjustment direction of the PID controller parameters is:

[0014]

[0015] wherein, is the output error signal of the small signal model.

[0016] Optionally, the calculation formula of the error gradient of the output error signal is:

[0017]

[0018] wherein, is the error function for controlling the adjustment direction of the PID controller parameters, is the output error signal of the small signal model, is the proportional gain of the PID controller, is the integral gain of the PID controller, is the differential gain of the PID controller.

[0019] Optionally, adjusting the error gradient calculation parameter to recalculate the error gradient of the output error signal comprises:

[0020] decreasing the learning rate or adjusting the calculation formula parameter of the error gradient of the output error signal to recalculate the error gradient of the output error signal.

[0021] The second aspect of the present application provides a PID controller parameter adaptive adjustment device of a networked converter, comprising:

[0022] a modeling module for constructing a small signal model of the networked converter;

[0023] an error calculation module configured to calculate an output error signal of the small signal model and a change rate of the output error signal in real time;

[0024] a gradient calculation module configured to calculate an error gradient of the output error signal based on the output error signal and the change rate of the output error signal;

[0025] a parameter updating module configured to dynamically update parameters of the PID controller based on the error gradient by using a gradient descent method;

[0026] an adjustment module configured to determine whether the system in which the networked converter is located will be unstable based on the updated parameters of the PID controller, and if not, stop updating the parameters of the PID controller, and if so, adjust error gradient calculation parameters to recalculate the error gradient of the output error signal.

[0027] Optionally, the formula for dynamically updating the parameters of the PID controller by using the gradient descent method is:

[0028]

[0029] wherein, Kp(t+1) is a proportional gain of the PID controller at the time t+1, Kp(t) is a proportional gain of the PID controller at the time t, is a learning rate, is an error function for controlling the adjustment direction of the parameters of the PID controller, Ki(t+1) is an integral gain of the PID controller at the time t+1, Ki(t) is an integral gain of the PID controller at the time t, Kd(t+1) is a differential gain of the PID controller at the time t+1, Kd(t) is a differential gain of the PID controller at the time t.

[0030] Optionally, the error function for controlling the adjustment direction of the parameters of the PID controller is:

[0031]

[0032] wherein, e(t) is the output error signal of the small signal model.

[0033] Optionally, the calculation formula of the error gradient of the output error signal is:

[0034]

[0035] wherein, is an error function for controlling the adjustment direction of the parameters of the PID controller, e(t) is the output error signal of the small signal model, a proportional gain of the PID controller, an integral gain of the PID controller, a differential gain of the PID controller.

[0036] Optionally, the error gradient calculation parameter is adjusted to recalculate the error gradient of the output error signal, comprising:

[0037] The learning rate is reduced or the calculation formula parameter of the error gradient of the output error signal is adjusted to recalculate the error gradient of the output error signal.

[0038] From the above technical solutions, the PID controller parameter adaptive adjustment method of the networked converter provided by the present application has the following advantages:

[0039] The PID controller parameter adaptive adjustment method of the networked converter provided by the present application is based on a small signal model of the networked converter, calculates an output error signal and a change rate of the output error signal of the small signal model, calculates an error gradient by using the output error signal and the change rate thereof, and then dynamically updates PID control parameters based on the gradient descent method. When updating the PID control parameters, it is checked whether the selection of the PID control parameters will cause the system in which the networked converter is located to be unstable. If yes, the error gradient calculation parameter is adjusted to recalculate the error gradient of the output error signal. If no, the updating of the PID controller parameters is stopped. Through the adaptive adjustment of the PID control parameters, the stability of the networked converter in the power grid can be effectively ensured, the system can be quickly responded and no oscillation occurs, so that the stable operation of the system is realized, and the technical problem that the prior art lacks an effective technical means of adaptively adjusting the control parameters of the networked converter to maintain the stable operation of the power grid system is solved. BRIEF DESCRIPTION OF DRAWINGS

[0040] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or the prior art description will be briefly introduced. Obviously, the drawings in the following description only some embodiments of the present application, and for those skilled in the art, other related drawings can also be obtained without creative labor.

[0041] Figure 1 A flowchart of a PID controller parameter adaptive adjustment method of a networked converter provided in an embodiment of the present application;

[0042] Figure 2 A structural diagram of a PID controller parameter adaptive adjustment device of a networked converter provided in an embodiment of the present application. DETAILED DESCRIPTION

[0043] In order to make the person skilled in the art better understand the technical scheme of the present application, the technical scheme in the embodiments of the present application will be described clearly and completely below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by the person skilled in the art without creative labor shall fall within the protection scope of the present application.

[0044] For the convenience of understanding, please refer to Figure 1 The present application provides an embodiment of a grid-forming inverter control parameter adaptive adjustment method, comprising:

[0045] Step 101, constructing a small signal model of the grid-forming inverter.

[0046] It should be noted that when the grid-forming inverter (GFM) is connected to the power grid, its small signal model is used to analyze its dynamic response and stability. The small signal model system of the grid-forming inverter is composed of the interaction of the current control loop, the voltage control loop and the grid connection point. By combining the state space models of the current control loop, the voltage control loop and the grid connection point, the state space model of the entire system can be obtained. The state space model of the entire system is as follows:

[0047]

[0048] Among them, is the state vector of the power grid system, including the current variation, the voltage variation and the power variation, is the first derivative of , is the input vector, including the input current and the input voltage of the grid-forming inverter, is the output vector, A is the state coefficient matrix, B is the input coefficient matrix, C is the output coefficient matrix, and D is the transfer coefficient matrix. The PID controller parameters include proportional gain

[0049] , integral gain , and derivative gain . The proportional gain is adjusted according to the instantaneous value of the error. A large proportional gain can accelerate the response, but may cause oscillation, so it needs to be adjusted dynamically according to the error. The integral gain is adjusted according to the cumulative error, and a larger integral gain helps to eliminate steady-state error, but too large may lead to system instability. The derivative gain is adjusted according to the error rate, which helps to reduce overshoot and oscillation, and ensures that the system response is more stable.

[0050] ​By linearizing the small signal model, the poles of the power system and the controller parameters 、 、 are related. When the controller parameters are too large, the poles of the power system can move to the right half plane, resulting in system instability. In order to avoid this situation, the parameters of the PID controller must be adjusted in real time.

[0051] Step 102, calculate the output error signal and the rate of change of the output error signal of the small signal model in real time.

[0052] It should be noted that the design goal is to minimize the output error of the power system, and according to the feedback of the output error, the parameters of the PID controller are automatically adjusted 、 、 . The output error signal calculation formula of the small signal model is:

[0053]

[0054] wherein, is the output error signal of the small signal model, is the reference signal.

[0055] Then, according to the output error signal, the rate of change of the output error signal is calculated.

[0056] Step 103, calculate the error gradient of the output error signal based on the output error signal and the rate of change of the output error signal.

[0057] It should be noted that the error gradient of the output error signal is calculated according to the output error signal and the rate of change of the output error signal. The calculation formula of the error gradient of the output error signal is:

[0058]

[0059] wherein, is the error function for adjusting the direction of the PID controller parameters, is the output error signal of the small signal model, is the proportional gain of the PID controller, is the integral gain of the PID controller, is the differential gain of the PID controller.

[0060] The partial derivative can be seen as two parts, the numerator e(t) is the derivative with respect to time t, that is , and the denominator is the derivative with respect to time, that is , so . and By analogy.

[0061] The error gradient expression reflects the relationship between the output error and the PID controller parameters. By calculating the sensitivity of the error to the PID controller parameters (i.e. the gradient), the controller gain can be adjusted so as to reduce the error of the system.

[0062] Step 104, based on the error gradient, dynamically updating the PID controller parameters by using the gradient descent method.

[0063] It should be noted that a suitable error index is defined for the error function for controlling the adjustment direction of the PID controller parameters:

[0064]

[0065] wherein, is the output error signal of the small signal model.

[0066] The parameters of the PID controller are updated by using the gradient descent-based adaptive algorithm, and the formula for dynamically updating the PID controller parameters is:

[0067]

[0068] wherein, is the proportional gain of the PID controller at t+1, is the proportional gain of the PID controller at t, is the learning rate, which determines the step size of the parameter update, is the error function for controlling the adjustment direction of the PID controller parameters, is the integral gain of the PID controller at t+1, is the integral gain of the PID controller at t, is the differential gain of the PID controller at t+1, is the differential gain of the PID controller at t.

[0069] Step 105, based on the updated PID controller parameters, determining whether the system where the grid-connected converter is located will be unstable, if not, stopping updating the PID controller parameters, if yes, adjusting the error gradient calculation parameters to recalculate the error gradient of the output error signal.

[0070] It should be noted that after each parameter adjustment, the poles and zeros of the power grid system are checked to ensure that the selection of the PID controller parameters will not cause the power grid system to be unstable. When there are poles and / or zeros in the right half plane of the zero-pole diagram, the power grid system is unstable. If it will be unstable, the error gradient calculation parameters are adjusted to recalculate the error gradient of the output error signal. Specifically, the learning rate is reduced or adjust the error gradient calculation formula parameter of the output error signal, recalculate the error gradient of the output error signal. If instability does not occur, stop updating the PID controller parameters.

[0071] The following provides a specific calculation example:

[0072] Suppose at a certain time, the output error = 0.05, and the error rate of change = 0.01, .

[0073] Adjust the PID controller parameters by gradient descent method. Set the learning rate = 0.1, and suppose the initial PID controller parameters are = 10, = 5, = 2.

[0074] Calculate the output signal error gradient:

[0075]

[0076] Then update the PID controller parameters:

[0077]

[0078] By dynamically adjusting the parameters of the PID controller through the adaptive algorithm, the stability of the grid-connected converter in the power grid can be effectively guaranteed. Adaptive gain adjustment adjusts the controller gain by real-time calculation of system state and disturbance, ensures fast response and no oscillation of the system, and thus realizes stable operation of the system.

[0079] The PID controller parameter adaptive adjustment method for the grid-connected converter provided by the application is based on a small signal model of the grid-connected converter, calculates the output error signal and the output error signal rate of change of the small signal model, calculates the error gradient using the output error signal and its rate of change, and then dynamically updates the PID control parameters based on the gradient descent method. When updating the PID control parameters, check whether the selection of the PID control parameters will cause the system where the grid-connected converter is located to be unstable. If so, adjust the error gradient calculation parameter to recalculate the error gradient of the output error signal. If not, stop updating the PID controller parameters. By adaptively adjusting the PID control parameters, the stability of the grid-connected converter in the power grid can be effectively guaranteed, the system can be ensured to respond quickly and without oscillation, and thus the stable operation of the system is realized. The technical problem of the prior art that there is a lack of effective technical means for adaptively adjusting the control parameters of the grid-connected converter to maintain stable operation of the power grid system is solved.

[0080] For ease of understanding, please refer to Figure 2The embodiment of the PID controller parameter self-adaptive adjustment device of the networked converter provided in the application comprises:

[0081] The small signal model construction module is configured to construct a small signal model of the networked converter.

[0082] The modeling module is configured to construct a small signal model of the networked converter.

[0083] The error calculation module is configured to calculate an output error signal and a change rate of the output error signal of the small signal model in real time.

[0084] The gradient calculation module is configured to calculate an error gradient of the output error signal based on the output error signal and the change rate of the output error signal.

[0085] The parameter updating module is configured to dynamically update the PID controller parameters by using the gradient descent method based on the error gradient.

[0086] The adjustment module is configured to determine whether the system in which the networked converter is located will be unstable based on the updated PID controller parameters, and if not, stop updating the PID controller parameters, and if yes, adjust the error gradient calculation parameters to recalculate the error gradient of the output error signal.

[0087] In one embodiment, the formula for dynamically updating the PID controller parameters by using the gradient descent method is as follows:

[0088]

[0089] wherein, Kp(t+1) is the proportional gain of the PID controller at the t+1 moment, Kp(t) is the proportional gain of the PID controller at the t moment, is the learning rate, is the error function for controlling the adjustment direction of the PID controller parameters, Ki(t+1) is the integral gain of the PID controller at the t+1 moment, Ki(t) is the integral gain of the PID controller at the t moment, Kd(t+1) is the differential gain of the PID controller at the t+1 moment, Kd(t) is the differential gain of the PID controller at the t moment.

[0090] In one embodiment, the error function for controlling the adjustment direction of the PID controller parameters is as follows:

[0091]

[0092] wherein, e(t) is the output error signal of the small signal model.

[0093] In one embodiment, the error gradient of the output error signal is recalculated by adjusting the error gradient calculation parameters.

[0094]

[0095] wherein, is an error function for controlling the adjustment direction of the PID controller parameters, is the output error signal of the small signal model, is the proportional gain of the PID controller, is the integral gain of the PID controller, is the differential gain of the PID controller.

[0096] In one embodiment, adjusting the error gradient calculation parameters recalculates the error gradient of the output error signal, comprising:

[0097] Decreasing the learning rate or adjusting the error gradient calculation parameters of the output error signal recalculates the error gradient of the output error signal.

[0098] The PID controller parameter adaptive adjustment device for the grid-forming converter provided in the present application is used to execute the PID controller parameter adaptive adjustment method for the grid-forming converter provided in the present application, and the technical effects have been described in the embodiments of the PID controller parameter adaptive adjustment method for the grid-forming converter provided in the present application, which will not be described here.

[0099] The above-described embodiments are only used to illustrate the technical solutions of the present application, rather than limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacements for some technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for adaptive adjustment of PID controller parameters of a networked converter, characterized in that, The method comprises the following steps: constructing a small signal model of the grid-forming converter; calculating an output error signal and a change rate of the output error signal of the small signal model in real time; calculating an error gradient of the output error signal based on the output error signal and the change rate of the output error signal; updating PID controller parameters dynamically by using a gradient descent method based on the error gradient; judging whether the system where the grid-forming converter is located will be unstable based on the updated PID controller parameters, and if not, stopping updating the PID controller parameters, and if yes, adjusting error gradient calculation parameters to recalculate the error gradient of the output error signal; a formula for updating the PID controller parameters dynamically by using the gradient descent method is as follows: ； wherein, Kp(t + 1) is a proportional gain of the PID controller at time t + 1, Kp(t) is a proportional gain of the PID controller at time t, is a learning rate, is an error function for controlling a direction of adjustment of the PID controller parameters, Ki(t + 1) is an integral gain of the PID controller at time t + 1, Ki(t) is an integral gain of the PID controller at time t, Kd(t + 1) is a derivative gain of the PID controller at time t + 1, Kd(t) is a derivative gain of the PID controller at time t; a calculation formula of the error gradient of the output error signal is as follows: ； wherein is an error function for controlling the adjustment direction of the PID controller parameters, is an output error signal of the small signal model, is a proportional gain of the PID controller, is an integral gain of the PID controller, is a derivative gain of the PID controller.

2. The method of claim 1, wherein the PID controller parameters of the networked converter are adaptively adjusted based on the following equation: ###0001### where Kp, Ki, and Kd are the PID controller parameters of the networked converter, and ΔP is the power error. an error function for controlling an adjustment direction of the PID controller parameters is as follows: ； wherein, is the output error signal for the small signal model.

3. The method of claim 1, wherein the PID controller parameters of the networked converter are adaptively adjusted based on the following equation: ###0001### where Kp, Ki, and Kd are the PID controller parameters of the networked converter, and ΔP is the power error. adjusting the error gradient calculation parameters to recalculate the error gradient of the output error signal comprises: decreasing a learning rate or adjusting a calculation formula parameter of the error gradient of the output error signal to recalculate the error gradient of the output error signal.

4. A device for self-adapting PID controller parameters of a networked converter, characterized in that, The method comprises the following steps: constructing a small signal model of the grid-forming converter by a modeling module; calculating an output error signal and a change rate of the output error signal of the small signal model in real time by an error calculation module; calculating an error gradient of the output error signal based on the output error signal and the change rate of the output error signal by a gradient calculation module; updating PID controller parameters dynamically by using a gradient descent method based on the error gradient by a parameter updating module; judging whether the system where the grid-forming converter is located will be unstable based on the updated PID controller parameters by an adjustment module, and if not, stopping updating the PID controller parameters, and if yes, adjusting error gradient calculation parameters to recalculate the error gradient of the output error signal; a formula for updating the PID controller parameters dynamically by using the gradient descent method is as follows: ； wherein, Kp(t + 1) is a proportional gain of the PID controller at time t + 1, Kp(t) is a proportional gain of the PID controller at time t, is a learning rate, is an error function for controlling a direction of adjustment of the PID controller parameters, Ki(t + 1) is an integral gain of the PID controller at time t + 1, Ki(t) is an integral gain of the PID controller at time t, Kd(t + 1) is a derivative gain of the PID controller at time t + 1, Kd(t) is a derivative gain of the PID controller at time t; a calculation formula of the error gradient of the output error signal is as follows: ； wherein is an error function for controlling the direction of adjustment of the PID controller parameters, is an output error signal of the small signal model, is a proportional gain of the PID controller, is an integral gain of the PID controller, is a derivative gain of the PID controller.

5. The PID controller parameter adaptive adjustment device of the networked converter according to claim 4, characterized in that, an error function for controlling an adjustment direction of the PID controller parameters is as follows: ； wherein, is the output error signal for the small signal model.

6. The PID controller parameter adaptive adjustment device of the networked converter according to claim 4, characterized in that, adjusting the error gradient calculation parameters to recalculate the error gradient of the output error signal comprises: decreasing a learning rate or adjusting a calculation formula parameter of the error gradient of the output error signal to recalculate the error gradient of the output error signal.

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